A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

PubMed

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-07

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy

NASA Astrophysics Data System (ADS)

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A New Approach to Integrate GPU-based Monte Carlo Simulation into Inverse Treatment Plan Optimization for Proton Therapy

PubMed Central

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2016-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6±15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size. PMID:27991456

A backward Monte Carlo method for efficient computation of runaway probabilities in runaway electron simulation

NASA Astrophysics Data System (ADS)

Zhang, Guannan; Del-Castillo-Negrete, Diego

2017-10-01

Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.

Monte Carlo based electron treatment planning and cutout output factor calculations

NASA Astrophysics Data System (ADS)

Mitrou, Ellis

Electron radiotherapy (RT) offers a number of advantages over photons. The high surface dose, combined with a rapid dose fall-off beyond the target volume presents a net increase in tumor control probability and decreases the normal tissue complication for superficial tumors. Electron treatments are normally delivered clinically without previously calculated dose distributions due to the complexity of the electron transport involved and greater error in planning accuracy. This research uses Monte Carlo (MC) methods to model clinical electron beams in order to accurately calculate electron beam dose distributions in patients as well as calculate cutout output factors, reducing the need for a clinical measurement. The present work is incorporated into a research MC calculation system: McGill Monte Carlo Treatment Planning (MMCTP) system. Measurements of PDDs, profiles and output factors in addition to 2D GAFCHROMICRTM EBT2 film measurements in heterogeneous phantoms were obtained to commission the electron beam model. The use of MC for electron TP will provide more accurate treatments and yield greater knowledge of the electron dose distribution within the patient. The calculation of output factors could invoke a clinical time saving of up to 1 hour per patient.

Dosimetric quality control of Eclipse treatment planning system using pelvic digital test object

NASA Astrophysics Data System (ADS)

Benhdech, Yassine; Beaumont, Stéphane; Guédon, Jeanpierre; Crespin, Sylvain

2011-03-01

Last year, we demonstrated the feasibility of a new method to perform dosimetric quality control of Treatment Planning Systems in radiotherapy, this method is based on Monte-Carlo simulations and uses anatomical Digital Test Objects (DTOs). The pelvic DTO was used in order to assess this new method on an ECLIPSE VARIAN Treatment Planning System. Large dose variations were observed particularly in air and bone equivalent material. In this current work, we discuss the results of the previous paper and provide an explanation for observed dose differences, the VARIAN Eclipse (Anisotropic Analytical) algorithm was investigated. Monte Carlo simulations (MC) were performed with a PENELOPE code version 2003. To increase efficiency of MC simulations, we have used our parallelized version based on the standard MPI (Message Passing Interface). The parallel code has been run on a 32- processor SGI cluster. The study was carried out using pelvic DTOs and was performed for low- and high-energy photon beams (6 and 18MV) on 2100CD VARIAN linear accelerator. A square field (10x10 cm2) was used. Assuming the MC data as reference, χ index analyze was carried out. For this study, a distance to agreement (DTA) was set to 7mm while the dose difference was set to 5% as recommended in the TRS-430 and TG-53 (on the beam axis in 3-D inhomogeneities). When using Monte Carlo PENELOPE, the absorbed dose is computed to the medium, however the TPS computes dose to water. We have used the method described by Siebers et al. based on Bragg-Gray cavity theory to convert MC simulated dose to medium to dose to water. Results show a strong consistency between ECLIPSE and MC calculations on the beam axis.

Safe bunker designing for the 18 MV Varian 2100 Clinac: a comparison between Monte Carlo simulation based upon data and new protocol recommendations.

PubMed

Beigi, Manije; Afarande, Fatemeh; Ghiasi, Hosein

2016-01-01

The aim of this study was to compare two bunkers designed by only protocols recommendations and Monte Carlo (MC) based upon data derived for an 18 MV Varian 2100Clinac accelerator. High energy radiation therapy is associated with fast and thermal photoneutrons. Adequate shielding against the contaminant neutron has been recommended by IAEA and NCRP new protocols. The latest protocols released by the IAEA (safety report No. 47) and NCRP report No. 151 were used for the bunker designing calculations. MC method based upon data was also derived. Two bunkers using protocols and MC upon data were designed and discussed. From designed door's thickness, the door designed by the MC simulation and Wu-McGinley analytical method was closer in both BPE and lead thickness. In the case of the primary and secondary barriers, MC simulation resulted in 440.11 mm for the ordinary concrete, total concrete thickness of 1709 mm was required. Calculating the same parameters value with the recommended analytical methods resulted in 1762 mm for the required thickness using 445 mm as recommended by TVL for the concrete. Additionally, for the secondary barrier the thickness of 752.05 mm was obtained. Our results showed MC simulation and the followed protocols recommendations in dose calculation are in good agreement in the radiation contamination dose calculation. Difference between the two analytical and MC simulation methods revealed that the application of only one method for the bunker design may lead to underestimation or overestimation in dose and shielding calculations.

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system.

PubMed

Ma, Jiasen; Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G

2014-12-01

Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. For relatively large and complex three-field head and neck cases, i.e., >100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

Monte Carlo modeling of a conventional X-ray computed tomography scanner for gel dosimetry purposes.

PubMed

Hayati, Homa; Mesbahi, Asghar; Nazarpoor, Mahmood

2016-01-01

Our purpose in the current study was to model an X-ray CT scanner with the Monte Carlo (MC) method for gel dosimetry. In this study, a conventional CT scanner with one array detector was modeled with use of the MCNPX MC code. The MC calculated photon fluence in detector arrays was used for image reconstruction of a simple water phantom as well as polyacrylamide polymer gel (PAG) used for radiation therapy. Image reconstruction was performed with the filtered back-projection method with a Hann filter and the Spline interpolation method. Using MC results, we obtained the dose-response curve for images of irradiated gel at different absorbed doses. A spatial resolution of about 2 mm was found for our simulated MC model. The MC-based CT images of the PAG gel showed a reliable increase in the CT number with increasing absorbed dose for the studied gel. Also, our results showed that the current MC model of a CT scanner can be used for further studies on the parameters that influence the usability and reliability of results, such as the photon energy spectra and exposure techniques in X-ray CT gel dosimetry.

A technique for generating phase-space-based Monte Carlo beamlets in radiotherapy applications.

PubMed

Bush, K; Popescu, I A; Zavgorodni, S

2008-09-21

As radiotherapy treatment planning moves toward Monte Carlo (MC) based dose calculation methods, the MC beamlet is becoming an increasingly common optimization entity. At present, methods used to produce MC beamlets have utilized a particle source model (PSM) approach. In this work we outline the implementation of a phase-space-based approach to MC beamlet generation that is expected to provide greater accuracy in beamlet dose distributions. In this approach a standard BEAMnrc phase space is sorted and divided into beamlets with particles labeled using the inheritable particle history variable. This is achieved with the use of an efficient sorting algorithm, capable of sorting a phase space of any size into the required number of beamlets in only two passes. Sorting a phase space of five million particles can be achieved in less than 8 s on a single-core 2.2 GHz CPU. The beamlets can then be transported separately into a patient CT dataset, producing separate dose distributions (doselets). Methods for doselet normalization and conversion of dose to absolute units of Gy for use in intensity modulated radiation therapy (IMRT) plan optimization are also described.

Thermodynamics and simulation of hard-sphere fluid and solid: Kinetic Monte Carlo method versus standard Metropolis scheme

NASA Astrophysics Data System (ADS)

Ustinov, E. A.

2017-01-01

The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.

A calibrated Monte Carlo approach to quantify the impacts of misorientation and different driving forces on texture development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liangzhe Zhang; Anthony D. Rollett; Timothy Bartel

2012-02-01

A calibrated Monte Carlo (cMC) approach, which quantifies grain boundary kinetics within a generic setting, is presented. The influence of misorientation is captured by adding a scaling coefficient in the spin flipping probability equation, while the contribution of different driving forces is weighted using a partition function. The calibration process relies on the established parametric links between Monte Carlo (MC) and sharp-interface models. The cMC algorithm quantifies microstructural evolution under complex thermomechanical environments and remedies some of the difficulties associated with conventional MC models. After validation, the cMC approach is applied to quantify the texture development of polycrystalline materials withmore » influences of misorientation and inhomogeneous bulk energy across grain boundaries. The results are in good agreement with theory and experiments.« less

Towards real-time photon Monte Carlo dose calculation in the cloud

NASA Astrophysics Data System (ADS)

Ziegenhein, Peter; Kozin, Igor N.; Kamerling, Cornelis Ph; Oelfke, Uwe

2017-06-01

Near real-time application of Monte Carlo (MC) dose calculation in clinic and research is hindered by the long computational runtimes of established software. Currently, fast MC software solutions are available utilising accelerators such as graphical processing units (GPUs) or clusters based on central processing units (CPUs). Both platforms are expensive in terms of purchase costs and maintenance and, in case of the GPU, provide only limited scalability. In this work we propose a cloud-based MC solution, which offers high scalability of accurate photon dose calculations. The MC simulations run on a private virtual supercomputer that is formed in the cloud. Computational resources can be provisioned dynamically at low cost without upfront investment in expensive hardware. A client-server software solution has been developed which controls the simulations and transports data to and from the cloud efficiently and securely. The client application integrates seamlessly into a treatment planning system. It runs the MC simulation workflow automatically and securely exchanges simulation data with the server side application that controls the virtual supercomputer. Advanced encryption standards were used to add an additional security layer, which encrypts and decrypts patient data on-the-fly at the processor register level. We could show that our cloud-based MC framework enables near real-time dose computation. It delivers excellent linear scaling for high-resolution datasets with absolute runtimes of 1.1 seconds to 10.9 seconds for simulating a clinical prostate and liver case up to 1% statistical uncertainty. The computation runtimes include the transportation of data to and from the cloud as well as process scheduling and synchronisation overhead. Cloud-based MC simulations offer a fast, affordable and easily accessible alternative for near real-time accurate dose calculations to currently used GPU or cluster solutions.

Towards real-time photon Monte Carlo dose calculation in the cloud.

PubMed

Ziegenhein, Peter; Kozin, Igor N; Kamerling, Cornelis Ph; Oelfke, Uwe

2017-06-07

Near real-time application of Monte Carlo (MC) dose calculation in clinic and research is hindered by the long computational runtimes of established software. Currently, fast MC software solutions are available utilising accelerators such as graphical processing units (GPUs) or clusters based on central processing units (CPUs). Both platforms are expensive in terms of purchase costs and maintenance and, in case of the GPU, provide only limited scalability. In this work we propose a cloud-based MC solution, which offers high scalability of accurate photon dose calculations. The MC simulations run on a private virtual supercomputer that is formed in the cloud. Computational resources can be provisioned dynamically at low cost without upfront investment in expensive hardware. A client-server software solution has been developed which controls the simulations and transports data to and from the cloud efficiently and securely. The client application integrates seamlessly into a treatment planning system. It runs the MC simulation workflow automatically and securely exchanges simulation data with the server side application that controls the virtual supercomputer. Advanced encryption standards were used to add an additional security layer, which encrypts and decrypts patient data on-the-fly at the processor register level. We could show that our cloud-based MC framework enables near real-time dose computation. It delivers excellent linear scaling for high-resolution datasets with absolute runtimes of 1.1 seconds to 10.9 seconds for simulating a clinical prostate and liver case up to 1% statistical uncertainty. The computation runtimes include the transportation of data to and from the cloud as well as process scheduling and synchronisation overhead. Cloud-based MC simulations offer a fast, affordable and easily accessible alternative for near real-time accurate dose calculations to currently used GPU or cluster solutions.

Safe bunker designing for the 18 MV Varian 2100 Clinac: a comparison between Monte Carlo simulation based upon data and new protocol recommendations

PubMed Central

Beigi, Manije; Afarande, Fatemeh; Ghiasi, Hosein

2016-01-01

Aim The aim of this study was to compare two bunkers designed by only protocols recommendations and Monte Carlo (MC) based upon data derived for an 18 MV Varian 2100Clinac accelerator. Background High energy radiation therapy is associated with fast and thermal photoneutrons. Adequate shielding against the contaminant neutron has been recommended by IAEA and NCRP new protocols. Materials and methods The latest protocols released by the IAEA (safety report No. 47) and NCRP report No. 151 were used for the bunker designing calculations. MC method based upon data was also derived. Two bunkers using protocols and MC upon data were designed and discussed. Results From designed door's thickness, the door designed by the MC simulation and Wu–McGinley analytical method was closer in both BPE and lead thickness. In the case of the primary and secondary barriers, MC simulation resulted in 440.11 mm for the ordinary concrete, total concrete thickness of 1709 mm was required. Calculating the same parameters value with the recommended analytical methods resulted in 1762 mm for the required thickness using 445 mm as recommended by TVL for the concrete. Additionally, for the secondary barrier the thickness of 752.05 mm was obtained. Conclusion Our results showed MC simulation and the followed protocols recommendations in dose calculation are in good agreement in the radiation contamination dose calculation. Difference between the two analytical and MC simulation methods revealed that the application of only one method for the bunker design may lead to underestimation or overestimation in dose and shielding calculations. PMID:26900357

Data decomposition of Monte Carlo particle transport simulations via tally servers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithmmore » in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.« less

Accelerated event-by-event Monte Carlo microdosimetric calculations of electrons and protons tracks on a multi-core CPU and a CUDA-enabled GPU.

PubMed

Kalantzis, Georgios; Tachibana, Hidenobu

2014-01-01

For microdosimetric calculations event-by-event Monte Carlo (MC) methods are considered the most accurate. The main shortcoming of those methods is the extensive requirement for computational time. In this work we present an event-by-event MC code of low projectile energy electron and proton tracks for accelerated microdosimetric MC simulations on a graphic processing unit (GPU). Additionally, a hybrid implementation scheme was realized by employing OpenMP and CUDA in such a way that both GPU and multi-core CPU were utilized simultaneously. The two implementation schemes have been tested and compared with the sequential single threaded MC code on the CPU. Performance comparison was established on the speed-up for a set of benchmarking cases of electron and proton tracks. A maximum speedup of 67.2 was achieved for the GPU-based MC code, while a further improvement of the speedup up to 20% was achieved for the hybrid approach. The results indicate the capability of our CPU-GPU implementation for accelerated MC microdosimetric calculations of both electron and proton tracks without loss of accuracy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

SU-E-T-397: Evaluation of Planned Dose Distributions by Monte Carlo (0.5%) and Ray Tracing Algorithm for the Spinal Tumors with CyberKnife

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, H; Brindle, J; Hepel, J

2015-06-15

Purpose: To analyze and evaluate dose distribution between Ray Tracing (RT) and Monte Carlo (MC) algorithms of 0.5% uncertainty on a critical structure of spinal cord and gross target volume and planning target volume. Methods: Twenty four spinal tumor patients were treated with stereotactic body radiotherapy (SBRT) by CyberKnife in 2013 and 2014. The MC algorithm with 0.5% of uncertainty is used to recalculate the dose distribution for the treatment plan of the patients using the same beams, beam directions, and monitor units (MUs). Results: The prescription doses are uniformly larger for MC plans than RT except one case. Upmore » to a factor of 1.19 for 0.25cc threshold volume and 1.14 for 1.2cc threshold volume of dose differences are observed for the spinal cord. Conclusion: The MC recalculated dose distributions are larger than the original MC calculations for the spinal tumor cases. Based on the accuracy of the MC calculations, more radiation dose might be delivered to the tumor targets and spinal cords with the increase prescription dose.« less

McStas 1.1: a tool for building neutron Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Lefmann, K.; Nielsen, K.; Tennant, A.; Lake, B.

2000-03-01

McStas is a project to develop general tools for the creation of simulations of neutron scattering experiments. In this paper, we briefly introduce McStas and describe a particular application of the program: the Monte Carlo calculation of the resolution function of a standard triple-axis neutron scattering instrument. The method compares well with the analytical calculations of Popovici.

Study on method to simulate light propagation on tissue with characteristics of radial-beam LED based on Monte-Carlo method.

PubMed

Song, Sangha; Elgezua, Inko; Kobayashi, Yo; Fujie, Masakatsu G

2013-01-01

In biomedical, Monte-carlo simulation is commonly used for simulation of light diffusion in tissue. But, most of previous studies did not consider a radial beam LED as light source. Therefore, we considered characteristics of a radial beam LED and applied them on MC simulation as light source. In this paper, we consider 3 characteristics of radial beam LED. The first is an initial launch area of photons. The second is an incident angle of a photon at an initial photon launching area. The third is the refraction effect according to contact area between LED and a turbid medium. For the verification of the MC simulation, we compared simulation and experimental results. The average of the correlation coefficient between simulation and experimental results is 0.9954. Through this study, we show an effective method to simulate light diffusion on tissue with characteristics for radial beam LED based on MC simulation.

Monte Carlo simulations on atropisomerism of thienotriazolodiazepines applicable to slow transition phenomena using potential energy surfaces by ab initio molecular orbital calculations.

PubMed

Morikami, Kenji; Itezono, Yoshiko; Nishimoto, Masahiro; Ohta, Masateru

2014-01-01

Compounds with a medium-sized flexible ring often show atropisomerism that is caused by the high-energy barriers between long-lived conformers that can be isolated and often have different biological properties to each other. In this study, the frequency of the transition between the two stable conformers, aS and aR, of thienotriazolodiazepine compounds with flexible 7-membered rings was estimated computationally by Monte Carlo (MC) simulations and validated experimentally by NMR experiments. To estimate the energy barriers for transitions as precisely as possible, the potential energy (PE) surfaces used in the MC simulations were calculated by molecular orbital (MO) methods. To accomplish the MC simulations with the MO-based PE surfaces in a practical central processing unit (CPU) time, the MO-based PE of each conformer was pre-calculated and stored before the MC simulations, and then only referred to during the MC simulations. The activation energies for transitions calculated by the MC simulations agreed well with the experimental ΔG determined by the NMR experiments. The analysis of the transition trajectories of the MC simulations revealed that the transition occurred not only through the transition states, but also through many different transition paths. Our computational methods gave us quantitative estimates of atropisomerism of the thienotriazolodiazepine compounds in a practical period of time, and the method could be applicable for other slow-dynamics phenomena that cannot be investigated by other atomistic simulations.

A GPU OpenCL based cross-platform Monte Carlo dose calculation engine (goMC)

NASA Astrophysics Data System (ADS)

Tian, Zhen; Shi, Feng; Folkerts, Michael; Qin, Nan; Jiang, Steve B.; Jia, Xun

2015-09-01

Monte Carlo (MC) simulation has been recognized as the most accurate dose calculation method for radiotherapy. However, the extremely long computation time impedes its clinical application. Recently, a lot of effort has been made to realize fast MC dose calculation on graphic processing units (GPUs). However, most of the GPU-based MC dose engines have been developed under NVidia’s CUDA environment. This limits the code portability to other platforms, hindering the introduction of GPU-based MC simulations to clinical practice. The objective of this paper is to develop a GPU OpenCL based cross-platform MC dose engine named goMC with coupled photon-electron simulation for external photon and electron radiotherapy in the MeV energy range. Compared to our previously developed GPU-based MC code named gDPM (Jia et al 2012 Phys. Med. Biol. 57 7783-97), goMC has two major differences. First, it was developed under the OpenCL environment for high code portability and hence could be run not only on different GPU cards but also on CPU platforms. Second, we adopted the electron transport model used in EGSnrc MC package and PENELOPE’s random hinge method in our new dose engine, instead of the dose planning method employed in gDPM. Dose distributions were calculated for a 15 MeV electron beam and a 6 MV photon beam in a homogenous water phantom, a water-bone-lung-water slab phantom and a half-slab phantom. Satisfactory agreement between the two MC dose engines goMC and gDPM was observed in all cases. The average dose differences in the regions that received a dose higher than 10% of the maximum dose were 0.48-0.53% for the electron beam cases and 0.15-0.17% for the photon beam cases. In terms of efficiency, goMC was ~4-16% slower than gDPM when running on the same NVidia TITAN card for all the cases we tested, due to both the different electron transport models and the different development environments. The code portability of our new dose engine goMC was validated by successfully running it on a variety of different computing devices including an NVidia GPU card, two AMD GPU cards and an Intel CPU processor. Computational efficiency among these platforms was compared.

A GPU OpenCL based cross-platform Monte Carlo dose calculation engine (goMC).

PubMed

Tian, Zhen; Shi, Feng; Folkerts, Michael; Qin, Nan; Jiang, Steve B; Jia, Xun

2015-10-07

Monte Carlo (MC) simulation has been recognized as the most accurate dose calculation method for radiotherapy. However, the extremely long computation time impedes its clinical application. Recently, a lot of effort has been made to realize fast MC dose calculation on graphic processing units (GPUs). However, most of the GPU-based MC dose engines have been developed under NVidia's CUDA environment. This limits the code portability to other platforms, hindering the introduction of GPU-based MC simulations to clinical practice. The objective of this paper is to develop a GPU OpenCL based cross-platform MC dose engine named goMC with coupled photon-electron simulation for external photon and electron radiotherapy in the MeV energy range. Compared to our previously developed GPU-based MC code named gDPM (Jia et al 2012 Phys. Med. Biol. 57 7783-97), goMC has two major differences. First, it was developed under the OpenCL environment for high code portability and hence could be run not only on different GPU cards but also on CPU platforms. Second, we adopted the electron transport model used in EGSnrc MC package and PENELOPE's random hinge method in our new dose engine, instead of the dose planning method employed in gDPM. Dose distributions were calculated for a 15 MeV electron beam and a 6 MV photon beam in a homogenous water phantom, a water-bone-lung-water slab phantom and a half-slab phantom. Satisfactory agreement between the two MC dose engines goMC and gDPM was observed in all cases. The average dose differences in the regions that received a dose higher than 10% of the maximum dose were 0.48-0.53% for the electron beam cases and 0.15-0.17% for the photon beam cases. In terms of efficiency, goMC was ~4-16% slower than gDPM when running on the same NVidia TITAN card for all the cases we tested, due to both the different electron transport models and the different development environments. The code portability of our new dose engine goMC was validated by successfully running it on a variety of different computing devices including an NVidia GPU card, two AMD GPU cards and an Intel CPU processor. Computational efficiency among these platforms was compared.

SU-E-T-175: Clinical Evaluations of Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chi, Y; Li, Y; Tian, Z

2015-06-15

Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine wasmore » used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.« less

Monte Carlo simulations within avalanche rescue

NASA Astrophysics Data System (ADS)

Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg

2016-04-01

Refining concepts for avalanche rescue involves calculating suitable settings for rescue strategies such as an adequate probing depth for probe line searches or an optimal time for performing resuscitation for a recovered avalanche victim in case of additional burials. In the latter case, treatment decisions have to be made in the context of triage. However, given the low number of incidents it is rarely possible to derive quantitative criteria based on historical statistics in the context of evidence-based medicine. For these rare, but complex rescue scenarios, most of the associated concepts, theories, and processes involve a number of unknown "random" parameters which have to be estimated in order to calculate anything quantitatively. An obvious approach for incorporating a number of random variables and their distributions into a calculation is to perform a Monte Carlo (MC) simulation. We here present Monte Carlo simulations for calculating the most suitable probing depth for probe line searches depending on search area and an optimal resuscitation time in case of multiple avalanche burials. The MC approach reveals, e.g., new optimized values for the duration of resuscitation that differ from previous, mainly case-based assumptions.

Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study

NASA Astrophysics Data System (ADS)

Bieda, Bogusław; Grzesik, Katarzyna

2017-11-01

The study proposes an stochastic approach based on Monte Carlo (MC) simulation for life cycle assessment (LCA) method limited to life cycle inventory (LCI) study for rare earth elements (REEs) recovery from the secondary materials processes production applied to the New Krankberg Mine in Sweden. The MC method is recognizes as an important tool in science and can be considered the most effective quantification approach for uncertainties. The use of stochastic approach helps to characterize the uncertainties better than deterministic method. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation or variance). The data used in this study are obtained from: (i) site-specific measured or calculated data, (ii) values based on literature, (iii) the ecoinvent process "rare earth concentrate, 70% REO, from bastnäsite, at beneficiation". Environmental emissions (e.g, particulates, uranium-238, thorium-232), energy and REE (La, Ce, Nd, Pr, Sm, Dy, Eu, Tb, Y, Sc, Yb, Lu, Tm, Y, Gd) have been inventoried. The study is based on a reference case for the year 2016. The combination of MC analysis with sensitivity analysis is the best solution for quantified the uncertainty in the LCI/LCA. The reliability of LCA results may be uncertain, to a certain degree, but this uncertainty can be noticed with the help of MC method.

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer.

PubMed

Maes, Dominic; Saini, Jatinder; Zeng, Jing; Rengan, Ramesh; Wong, Tony; Bowen, Stephen R

2018-04-01

Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung V RX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10 -5 ). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10 -3 ). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., V RX ). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10 -3 ). MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer

PubMed Central

Maes, Dominic; Saini, Jatinder; Zeng, Jing; Rengan, Ramesh; Wong, Tony

2018-01-01

Background Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. Methods With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. Results In this ten-patient sample, CTV V95 decreased significantly from 99–100% for PBopt to 77–94% for MCrecalc and recovered to 99–100% for MCopt (P<10−5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10−3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =−1%) compared to MCrecalc (ΔD95 =−6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10−3). Conclusions MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy. PMID:29876310

Technical Note: Defining cyclotron-based clinical scanning proton machines in a FLUKA Monte Carlo system.

PubMed

Fiorini, Francesca; Schreuder, Niek; Van den Heuvel, Frank

2018-02-01

Cyclotron-based pencil beam scanning (PBS) proton machines represent nowadays the majority and most affordable choice for proton therapy facilities, however, their representation in Monte Carlo (MC) codes is more complex than passively scattered proton system- or synchrotron-based PBS machines. This is because degraders are used to decrease the energy from the cyclotron maximum energy to the desired energy, resulting in a unique spot size, divergence, and energy spread depending on the amount of degradation. This manuscript outlines a generalized methodology to characterize a cyclotron-based PBS machine in a general-purpose MC code. The code can then be used to generate clinically relevant plans starting from commercial TPS plans. The described beam is produced at the Provision Proton Therapy Center (Knoxville, TN, USA) using a cyclotron-based IBA Proteus Plus equipment. We characterized the Provision beam in the MC FLUKA using the experimental commissioning data. The code was then validated using experimental data in water phantoms for single pencil beams and larger irregular fields. Comparisons with RayStation TPS plans are also presented. Comparisons of experimental, simulated, and planned dose depositions in water plans show that same doses are calculated by both programs inside the target areas, while penumbrae differences are found at the field edges. These differences are lower for the MC, with a γ(3%-3 mm) index never below 95%. Extensive explanations on how MC codes can be adapted to simulate cyclotron-based scanning proton machines are given with the aim of using the MC as a TPS verification tool to check and improve clinical plans. For all the tested cases, we showed that dose differences with experimental data are lower for the MC than TPS, implying that the created FLUKA beam model is better able to describe the experimental beam. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

McSnow: A Monte-Carlo Particle Model for Riming and Aggregation of Ice Particles in a Multidimensional Microphysical Phase Space

NASA Astrophysics Data System (ADS)

Brdar, S.; Seifert, A.

2018-01-01

We present a novel Monte-Carlo ice microphysics model, McSnow, to simulate the evolution of ice particles due to deposition, aggregation, riming, and sedimentation. The model is an application and extension of the super-droplet method of Shima et al. (2009) to the more complex problem of rimed ice particles and aggregates. For each individual super-particle, the ice mass, rime mass, rime volume, and the number of monomers are predicted establishing a four-dimensional particle-size distribution. The sensitivity of the model to various assumptions is discussed based on box model and one-dimensional simulations. We show that the Monte-Carlo method provides a feasible approach to tackle this high-dimensional problem. The largest uncertainty seems to be related to the treatment of the riming processes. This calls for additional field and laboratory measurements of partially rimed snowflakes.

The specific purpose Monte Carlo code McENL for simulating the response of epithermal neutron lifetime well logging tools

NASA Astrophysics Data System (ADS)

Prettyman, T. H.; Gardner, R. P.; Verghese, K.

1993-08-01

A new specific purpose Monte Carlo code called McENL for modeling the time response of epithermal neutron lifetime tools is described. The weight windows technique, employing splitting and Russian roulette, is used with an automated importance function based on the solution of an adjoint diffusion model to improve the code efficiency. Complete composition and density correlated sampling is also included in the code, and can be used to study the effect on tool response of small variations in the formation, borehole, or logging tool composition and density. An illustration of the latter application is given for the density of a thermal neutron filter. McENL was benchmarked against test-pit data for the Mobil pulsed neutron porosity tool and was found to be very accurate. Results of the experimental validation and details of code performance are presented.

Analysis of dense-medium light scattering with applications to corneal tissue: experiments and Monte Carlo simulations.

PubMed

Kim, K B; Shanyfelt, L M; Hahn, D W

2006-01-01

Dense-medium scattering is explored in the context of providing a quantitative measurement of turbidity, with specific application to corneal haze. A multiple-wavelength scattering technique is proposed to make use of two-color scattering response ratios, thereby providing a means for data normalization. A combination of measurements and simulations are reported to assess this technique, including light-scattering experiments for a range of polystyrene suspensions. Monte Carlo (MC) simulations were performed using a multiple-scattering algorithm based on full Mie scattering theory. The simulations were in excellent agreement with the polystyrene suspension experiments, thereby validating the MC model. The MC model was then used to simulate multiwavelength scattering in a corneal tissue model. Overall, the proposed multiwavelength scattering technique appears to be a feasible approach to quantify dense-medium scattering such as the manifestation of corneal haze, although more complex modeling of keratocyte scattering, and animal studies, are necessary.

MUFFSgenMC: An Open Source MUon Flexible Framework for Spectral GENeration for Monte Carlo Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatzidakis, Stylianos; Greulich, Christopher

A cosmic ray Muon Flexible Framework for Spectral GENeration for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon tomographic applications. The flexible framework allows for easy and fast creation of source terms for popular Monte Carlo applications like GEANT4 and MCNP. This code framework simplifies the process of simulations used for cosmic ray muon tomography.

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

NASA Astrophysics Data System (ADS)

El Naqa, Issam; Pater, Piotr; Seuntjens, Jan

2012-06-01

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.

Development and reproducibility evaluation of a Monte Carlo-based standard LINAC model for quality assurance of multi-institutional clinical trials.

PubMed

Usmani, Muhammad Nauman; Takegawa, Hideki; Takashina, Masaaki; Numasaki, Hodaka; Suga, Masaki; Anetai, Yusuke; Kurosu, Keita; Koizumi, Masahiko; Teshima, Teruki

2014-11-01

Technical developments in radiotherapy (RT) have created a need for systematic quality assurance (QA) to ensure that clinical institutions deliver prescribed radiation doses consistent with the requirements of clinical protocols. For QA, an ideal dose verification system should be independent of the treatment-planning system (TPS). This paper describes the development and reproducibility evaluation of a Monte Carlo (MC)-based standard LINAC model as a preliminary requirement for independent verification of dose distributions. The BEAMnrc MC code is used for characterization of the 6-, 10- and 15-MV photon beams for a wide range of field sizes. The modeling of the LINAC head components is based on the specifications provided by the manufacturer. MC dose distributions are tuned to match Varian Golden Beam Data (GBD). For reproducibility evaluation, calculated beam data is compared with beam data measured at individual institutions. For all energies and field sizes, the MC and GBD agreed to within 1.0% for percentage depth doses (PDDs), 1.5% for beam profiles and 1.2% for total scatter factors (Scps.). Reproducibility evaluation showed that the maximum average local differences were 1.3% and 2.5% for PDDs and beam profiles, respectively. MC and institutions' mean Scps agreed to within 2.0%. An MC-based standard LINAC model developed to independently verify dose distributions for QA of multi-institutional clinical trials and routine clinical practice has proven to be highly accurate and reproducible and can thus help ensure that prescribed doses delivered are consistent with the requirements of clinical protocols. © The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Patient-specific Monte Carlo-based dose-kernel approach for inverse planning in afterloading brachytherapy.

PubMed

D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc

2011-12-01

Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source. Copyright © 2011 Elsevier Inc. All rights reserved.

SU-E-T-29: A Web Application for GPU-Based Monte Carlo IMRT/VMAT QA with Delivered Dose Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Folkerts, M; University of California, San Diego, La Jolla, CA; Graves, Y

Purpose: To enable an existing web application for GPU-based Monte Carlo (MC) 3D dosimetry quality assurance (QA) to compute “delivered dose” from linac logfile data. Methods: We added significant features to an IMRT/VMAT QA web application which is based on existing technologies (HTML5, Python, and Django). This tool interfaces with python, c-code libraries, and command line-based GPU applications to perform a MC-based IMRT/VMAT QA. The web app automates many complicated aspects of interfacing clinical DICOM and logfile data with cutting-edge GPU software to run a MC dose calculation. The resultant web app is powerful, easy to use, and is ablemore » to re-compute both plan dose (from DICOM data) and delivered dose (from logfile data). Both dynalog and trajectorylog file formats are supported. Users upload zipped DICOM RP, CT, and RD data and set the expected statistic uncertainty for the MC dose calculation. A 3D gamma index map, 3D dose distribution, gamma histogram, dosimetric statistics, and DVH curves are displayed to the user. Additional the user may upload the delivery logfile data from the linac to compute a 'delivered dose' calculation and corresponding gamma tests. A comprehensive PDF QA report summarizing the results can also be downloaded. Results: We successfully improved a web app for a GPU-based QA tool that consists of logfile parcing, fluence map generation, CT image processing, GPU based MC dose calculation, gamma index calculation, and DVH calculation. The result is an IMRT and VMAT QA tool that conducts an independent dose calculation for a given treatment plan and delivery log file. The system takes both DICOM data and logfile data to compute plan dose and delivered dose respectively. Conclusion: We sucessfully improved a GPU-based MC QA tool to allow for logfile dose calculation. The high efficiency and accessibility will greatly facilitate IMRT and VMAT QA.« less

Effect of inhomogeneity in a patient's body on the accuracy of the pencil beam algorithm in comparison to Monte Carlo

NASA Astrophysics Data System (ADS)

Yamashita, T.; Akagi, T.; Aso, T.; Kimura, A.; Sasaki, T.

2012-11-01

The pencil beam algorithm (PBA) is reasonably accurate and fast. It is, therefore, the primary method used in routine clinical treatment planning for proton radiotherapy; still, it needs to be validated for use in highly inhomogeneous regions. In our investigation of the effect of patient inhomogeneity, PBA was compared with Monte Carlo (MC). A software framework was developed for the MC simulation of radiotherapy based on Geant4. Anatomical sites selected for the comparison were the head/neck, liver, lung and pelvis region. The dose distributions calculated by the two methods in selected examples were compared, as well as a dose volume histogram (DVH) derived from the dose distributions. The comparison of the off-center ratio (OCR) at the iso-center showed good agreement between the PBA and MC, while discrepancies were seen around the distal fall-off regions. While MC showed a fine structure on the OCR in the distal fall-off region, the PBA showed smoother distribution. The fine structures in MC calculation appeared downstream of very low-density regions. Comparison of DVHs showed that most of the target volumes were similarly covered, while some OARs located around the distal region received a higher dose when calculated by MC than the PBA.

Peer-to-peer Monte Carlo simulation of photon migration in topical applications of biomedical optics

NASA Astrophysics Data System (ADS)

Doronin, Alexander; Meglinski, Igor

2012-09-01

In the framework of further development of the unified approach of photon migration in complex turbid media, such as biological tissues we present a peer-to-peer (P2P) Monte Carlo (MC) code. The object-oriented programming is used for generalization of MC model for multipurpose use in various applications of biomedical optics. The online user interface providing multiuser access is developed using modern web technologies, such as Microsoft Silverlight, ASP.NET. The emerging P2P network utilizing computers with different types of compute unified device architecture-capable graphics processing units (GPUs) is applied for acceleration and to overcome the limitations, imposed by multiuser access in the online MC computational tool. The developed P2P MC was validated by comparing the results of simulation of diffuse reflectance and fluence rate distribution for semi-infinite scattering medium with known analytical results, results of adding-doubling method, and with other GPU-based MC techniques developed in the past. The best speedup of processing multiuser requests in a range of 4 to 35 s was achieved using single-precision computing, and the double-precision computing for floating-point arithmetic operations provides higher accuracy.

Peer-to-peer Monte Carlo simulation of photon migration in topical applications of biomedical optics.

PubMed

Doronin, Alexander; Meglinski, Igor

2012-09-01

In the framework of further development of the unified approach of photon migration in complex turbid media, such as biological tissues we present a peer-to-peer (P2P) Monte Carlo (MC) code. The object-oriented programming is used for generalization of MC model for multipurpose use in various applications of biomedical optics. The online user interface providing multiuser access is developed using modern web technologies, such as Microsoft Silverlight, ASP.NET. The emerging P2P network utilizing computers with different types of compute unified device architecture-capable graphics processing units (GPUs) is applied for acceleration and to overcome the limitations, imposed by multiuser access in the online MC computational tool. The developed P2P MC was validated by comparing the results of simulation of diffuse reflectance and fluence rate distribution for semi-infinite scattering medium with known analytical results, results of adding-doubling method, and with other GPU-based MC techniques developed in the past. The best speedup of processing multiuser requests in a range of 4 to 35 s was achieved using single-precision computing, and the double-precision computing for floating-point arithmetic operations provides higher accuracy.

Newly developed photon-cell interactive Monte Carlo (pciMC) simulation for non-invasive and continuous diagnosis of blood during extracorporeal circulation support

NASA Astrophysics Data System (ADS)

Sakota, Daisuke; Takatani, Setsuo

2011-07-01

We have sought for non-invasive diagnosis of blood during the extracorporeal circulation support. To achieve the goal, we have newly developed a photon-cell interactive Monte Carlo (pciMC) model for optical propagation through blood. The pciMC actually describes the interaction of photons with 3-dimentional biconcave RBCs. The scattering is described by micro-scopical RBC boundary condition based on geometric optics. By using pciMC, we modeled the RBCs inside the extracorporeal circuit will be oriented by the blood flow. The RBCs' orientation was defined as their long axis being directed to the center of the circulation tube. Simultaneously the RBCs were allowed to randomly rotate about the long axis direction. As a result, as flow rate increased, the orientation rate increased and converged to approximately 22% at 0.5 L/min flow rate and above. And finally, by using this model, the pciMC non-invasively and absolutely predicted Hct and hemoglobin with the accuracies of 0.84+/-0.82 [HCT%] and 0.42+/-0.28 [g/dL] respectively against measurements by a blood gas analyzer.

A preliminary study of in-house Monte Carlo simulations: an integrated Monte Carlo verification system.

PubMed

Mukumoto, Nobutaka; Tsujii, Katsutomo; Saito, Susumu; Yasunaga, Masayoshi; Takegawa, Hideki; Yamamoto, Tokihiro; Numasaki, Hodaka; Teshima, Teruki

2009-10-01

To develop an infrastructure for the integrated Monte Carlo verification system (MCVS) to verify the accuracy of conventional dose calculations, which often fail to accurately predict dose distributions, mainly due to inhomogeneities in the patient's anatomy, for example, in lung and bone. The MCVS consists of the graphical user interface (GUI) based on a computational environment for radiotherapy research (CERR) with MATLAB language. The MCVS GUI acts as an interface between the MCVS and a commercial treatment planning system to import the treatment plan, create MC input files, and analyze MC output dose files. The MCVS consists of the EGSnrc MC codes, which include EGSnrc/BEAMnrc to simulate the treatment head and EGSnrc/DOSXYZnrc to calculate the dose distributions in the patient/phantom. In order to improve computation time without approximations, an in-house cluster system was constructed. The phase-space data of a 6-MV photon beam from a Varian Clinac unit was developed and used to establish several benchmarks under homogeneous conditions. The MC results agreed with the ionization chamber measurements to within 1%. The MCVS GUI could import and display the radiotherapy treatment plan created by the MC method and various treatment planning systems, such as RTOG and DICOM-RT formats. Dose distributions could be analyzed by using dose profiles and dose volume histograms and compared on the same platform. With the cluster system, calculation time was improved in line with the increase in the number of central processing units (CPUs) at a computation efficiency of more than 98%. Development of the MCVS was successful for performing MC simulations and analyzing dose distributions.

EDITORIAL: Special section: Selected papers from the Third European Workshop on Monte Carlo Treatment Planning (MCTP2012) Special section: Selected papers from the Third European Workshop on Monte Carlo Treatment Planning (MCTP2012)

NASA Astrophysics Data System (ADS)

Spezi, Emiliano; Leal, Antonio

2013-04-01

The Third European Workshop on Monte Carlo Treatment Planning (MCTP2012) was held from 15-18 May, 2012 in Seville, Spain. The event was organized by the Universidad de Sevilla with the support of the European Workgroup on Monte Carlo Treatment Planning (EWG-MCTP). MCTP2012 followed two successful meetings, one held in Ghent (Belgium) in 2006 (Reynaert 2007) and one in Cardiff (UK) in 2009 (Spezi 2010). The recurrence of these workshops together with successful events held in parallel by McGill University in Montreal (Seuntjens et al 2012), show consolidated interest from the scientific community in Monte Carlo (MC) treatment planning. The workshop was attended by a total of 90 participants, mainly coming from a medical physics background. A total of 48 oral presentations and 15 posters were delivered in specific scientific sessions including dosimetry, code development, imaging, modelling of photon and electron radiation transport, external beam radiation therapy, nuclear medicine, brachitherapy and hadrontherapy. A copy of the programme is available on the workshop's website (www.mctp2012.com). In this special section of Physics in Medicine and Biology we report six papers that were selected following the journal's rigorous peer review procedure. These papers actually provide a good cross section of the areas of application of MC in treatment planning that were discussed at MCTP2012. Czarnecki and Zink (2013) and Wagner et al (2013) present the results of their work in small field dosimetry. Czarnecki and Zink (2013) studied field size and detector dependent correction factors for diodes and ion chambers within a clinical 6MV photon beam generated by a Siemens linear accelerator. Their modelling work based on the BEAMnrc/EGSnrc codes and experimental measurements revealed that unshielded diodes were the best choice for small field dosimetry because of their independence from the electron beam spot size and correction factor close to unity. Wagner et al (2013) investigated the recombination effect on liquid ionization chambers for stereotactic radiotherapy, a field of increasing importance in external beam radiotherapy. They modelled both radiation source (Cyberknife unit) and detector with the BEAMnrc/EGSnrc codes and quantified the dependence of the response of this type of detectors on factors such as the volume effect and the electrode. They also recommended that these dependences be accounted for in measurements involving small fields. In the field of external beam radiotherapy, Chakarova et al (2013) showed how total body irradiation (TBI) could be improved by simulating patient treatments with MC. In particular, BEAMnrc/EGSnrc based simulations highlighted the importance of optimizing individual compensators for TBI treatments. In the same area of application, Mairani et al (2013) reported on a new tool for treatment planning in proton therapy based on the FLUKA MC code. The software, used to model both proton therapy beam and patient anatomy, supports single-field and multiple-field optimization and can be used to optimize physical and relative biological effectiveness (RBE)-weighted dose distribution, using both constant and variable RBE models. In the field of nuclear medicine Marcatili et al (2013) presented RAYDOSE, a Geant4-based code specifically developed for applications in molecular radiotherapy (MRT). RAYDOSE has been designed to work in MRT trials using sequential positron emission tomography (PET) or single-photon emission tomography (SPECT) imaging to model patient specific time-dependent metabolic uptake and to calculate the total 3D dose distribution. The code was validated through experimental measurements in homogeneous and heterogeneous phantoms. Finally, in the field of code development Miras et al (2013) reported on CloudMC, a Windows Azure-based application for the parallelization of MC calculations in a dynamic cluster environment. Although the performance of CloudMC has been tested with the PENELOPE MC code, the authors report that software has been designed in a way that it should be independent of the type of MC code, provided that simulation meets a number of operational criteria. We wish to thank Elekta/CMS Inc., the University of Seville, the Junta of Andalusia and the European Regional Development Fund for their financial support. We would like also to acknowledge the members of EWG-MCTP for their help in peer-reviewing all the abstracts, and all the invited speakers who kindly agreed to deliver keynote presentations in their area of expertise. A final word of thanks to our colleagues who worked on the reviewing process of the papers selected for this special section and to the IOP Publishing staff who made it possible. MCTP2012 was accredited by the European Federation of Organisations for Medical Physics as a CPD event for medical physicists. Emiliano Spezi and Antonio Leal Guest Editors References Chakarova R, Müntzing K, Krantz M, E Hedin E and Hertzman S 2013 Monte Carlo optimization of total body irradiation in a phantom and patient geometry Phys. Med. Biol. 58 2461-69 Czarnecki D and Zink K 2013 Monte Carlo calculated correction factors for diodes and ion chambers in small photon fields Phys. Med. Biol. 58 2431-44 Mairani A, Böhlen T T, Schiavi A, Tessonnier T, Molinelli S, Brons S, Battistoni G, Parodi K and Patera V 2013 A Monte Carlo-based treatment planning tool for proton therapy Phys. Med. Biol. 58 2471-90 Marcatili S, Pettinato C, Daniels S, Lewis G, Edwards P, Fanti S and Spezi E 2013 Development and validation of RAYDOSE: a Geant4 based application for molecular radiotherapy Phys. Med. Biol. 58 2491-508 Miras H, Jiménez R, Miras C and Gomà C 2013 CloudMC: A cloud computing application for Monte Carlo simulation Phys. Med. Biol. 58 N125-33 Reynaert N 2007 First European Workshop on Monte Carlo Treatment Planning J. Phys.: Conf. Ser. 74 011001 Seuntjens J, Beaulieu L, El Naqa I and Després P 2012 Special section: Selected papers from the Fourth International Workshop on Recent Advances in Monte Carlo Techniques for Radiation Therapy Phys. Med. Biol. 57 (11) E01 Spezi E 2010 Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) Phys. Med. Biol. 55 (16) E01 Wagner A, Crop F, Lacornerie T, Vandevelde F and Reynaert N 2013 Use of a liquid ionization chamber for stereotactic radiotherapy dosimetry Phys. Med. Biol. 58 2445-59

SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moskvin, V; Pirlepesov, F; Tsiamas, P

Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to themore » dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometry simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.« less

Monte Carlo based, patient-specific RapidArc QA using Linac log files.

PubMed

Teke, Tony; Bergman, Alanah M; Kwa, William; Gill, Bradford; Duzenli, Cheryl; Popescu, I Antoniu

2010-01-01

A Monte Carlo (MC) based QA process to validate the dynamic beam delivery accuracy for Varian RapidArc (Varian Medical Systems, Palo Alto, CA) using Linac delivery log files (DynaLog) is presented. Using DynaLog file analysis and MC simulations, the goal of this article is to (a) confirm that adequate sampling is used in the RapidArc optimization algorithm (177 static gantry angles) and (b) to assess the physical machine performance [gantry angle and monitor unit (MU) delivery accuracy]. Ten clinically acceptable RapidArc treatment plans were generated for various tumor sites and delivered to a water-equivalent cylindrical phantom on the treatment unit. Three Monte Carlo simulations were performed to calculate dose to the CT phantom image set: (a) One using a series of static gantry angles defined by 177 control points with treatment planning system (TPS) MLC control files (planning files), (b) one using continuous gantry rotation with TPS generated MLC control files, and (c) one using continuous gantry rotation with actual Linac delivery log files. Monte Carlo simulated dose distributions are compared to both ionization chamber point measurements and with RapidArc TPS calculated doses. The 3D dose distributions were compared using a 3D gamma-factor analysis, employing a 3%/3 mm distance-to-agreement criterion. The dose difference between MC simulations, TPS, and ionization chamber point measurements was less than 2.1%. For all plans, the MC calculated 3D dose distributions agreed well with the TPS calculated doses (gamma-factor values were less than 1 for more than 95% of the points considered). Machine performance QA was supplemented with an extensive DynaLog file analysis. A DynaLog file analysis showed that leaf position errors were less than 1 mm for 94% of the time and there were no leaf errors greater than 2.5 mm. The mean standard deviation in MU and gantry angle were 0.052 MU and 0.355 degrees, respectively, for the ten cases analyzed. The accuracy and flexibility of the Monte Carlo based RapidArc QA system were demonstrated. Good machine performance and accurate dose distribution delivery of RapidArc plans were observed. The sampling used in the TPS optimization algorithm was found to be adequate.

Surface tension and phase coexistence properties of the lattice fluid from a virtual site removal Monte Carlo strategy

NASA Astrophysics Data System (ADS)

Provata, Astero; Prassas, Vassilis D.; Theodorou, Doros N.

1997-10-01

A thin liquid film of lattice fluid in equilibrium with its vapor is studied in 2 and 3 dimensions with canonical Monte Carlo simulation (MC) and Self-Consistent Field Theory (SCF) in the temperature range 0.45Tc to Tc, where Tc the liquid-gas critical temperature. Extending the approach of Oates et al. [Philos. Mag. B 61, 337 (1990)] to anisotropic systems, we develop a method for the MC computation of the transverse and normal pressure profiles, hence of the surface tension, based on virtual removals of individual sites or blocks of sites from the system. Results from implementation of this new method, obtained at very modest computational cost, are in reasonable agreement with exact values and other MC estimates of the surface tension of the 2-d and 3-d model systems, respectively. SCF estimates of the interfacial density profiles, the surface tension, the vapor pressure curve and the binodal curve compare well with MC results away from Tc, but show the expected deviations at high temperatures.

Concurrent Monte Carlo transport and fluence optimization with fluence adjusting scalable transport Monte Carlo

PubMed Central

Svatos, M.; Zankowski, C.; Bednarz, B.

2016-01-01

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship within a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead. PMID:27277051

Monte Carlo-based fluorescence molecular tomography reconstruction method accelerated by a cluster of graphic processing units.

PubMed

Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming

2011-02-01

High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.

Electron dose distributions caused by the contact-type metallic eye shield: Studies using Monte Carlo and pencil beam algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Sei-Kwon; Yoon, Jai-Woong; Hwang, Taejin

A metallic contact eye shield has sometimes been used for eyelid treatment, but dose distribution has never been reported for a patient case. This study aimed to show the shield-incorporated CT-based dose distribution using the Pinnacle system and Monte Carlo (MC) calculation for 3 patient cases. For the artifact-free CT scan, an acrylic shield machined as the same size as that of the tungsten shield was used. For the MC calculation, BEAMnrc and DOSXYZnrc were used for the 6-MeV electron beam of the Varian 21EX, in which information for the tungsten, stainless steel, and aluminum material for the eye shieldmore » was used. The same plan was generated on the Pinnacle system and both were compared. The use of the acrylic shield produced clear CT images, enabling delineation of the regions of interest, and yielded CT-based dose calculation for the metallic shield. Both the MC and the Pinnacle systems showed a similar dose distribution downstream of the eye shield, reflecting the blocking effect of the metallic eye shield. The major difference between the MC and the Pinnacle results was the target eyelid dose upstream of the shield such that the Pinnacle system underestimated the dose by 19 to 28% and 11 to 18% for the maximum and the mean doses, respectively. The pattern of dose difference between the MC and the Pinnacle systems was similar to that in the previous phantom study. In conclusion, the metallic eye shield was successfully incorporated into the CT-based planning, and the accurate dose calculation requires MC simulation.« less

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning.

PubMed

Chetty, Indrin J; Curran, Bruce; Cygler, Joanna E; DeMarco, John J; Ezzell, Gary; Faddegon, Bruce A; Kawrakow, Iwan; Keall, Paul J; Liu, Helen; Ma, C M Charlie; Rogers, D W O; Seuntjens, Jan; Sheikh-Bagheri, Daryoush; Siebers, Jeffrey V

2007-12-01

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

SU-E-T-769: T-Test Based Prior Error Estimate and Stopping Criterion for Monte Carlo Dose Calculation in Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, X; Gao, H; Schuemann, J

2015-06-15

Purpose: The Monte Carlo (MC) method is a gold standard for dose calculation in radiotherapy. However, it is not a priori clear how many particles need to be simulated to achieve a given dose accuracy. Prior error estimate and stopping criterion are not well established for MC. This work aims to fill this gap. Methods: Due to the statistical nature of MC, our approach is based on one-sample t-test. We design the prior error estimate method based on the t-test, and then use this t-test based error estimate for developing a simulation stopping criterion. The three major components are asmore » follows.First, the source particles are randomized in energy, space and angle, so that the dose deposition from a particle to the voxel is independent and identically distributed (i.i.d.).Second, a sample under consideration in the t-test is the mean value of dose deposition to the voxel by sufficiently large number of source particles. Then according to central limit theorem, the sample as the mean value of i.i.d. variables is normally distributed with the expectation equal to the true deposited dose.Third, the t-test is performed with the null hypothesis that the difference between sample expectation (the same as true deposited dose) and on-the-fly calculated mean sample dose from MC is larger than a given error threshold, in addition to which users have the freedom to specify confidence probability and region of interest in the t-test based stopping criterion. Results: The method is validated for proton dose calculation. The difference between the MC Result based on the t-test prior error estimate and the statistical Result by repeating numerous MC simulations is within 1%. Conclusion: The t-test based prior error estimate and stopping criterion are developed for MC and validated for proton dose calculation. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Commissioning and Validation of the First Monte Carlo Based Dose Calculation Algorithm Commercial Treatment Planning System in Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larraga-Gutierrez, J. M.; Garcia-Garduno, O. A.; Hernandez-Bojorquez, M.

2010-12-07

This work presents the beam data commissioning and dose calculation validation of the first Monte Carlo (MC) based treatment planning system (TPS) installed in Mexico. According to the manufacturer specifications, the beam data commissioning needed for this model includes: several in-air and water profiles, depth dose curves, head-scatter factors and output factors (6x6, 12x12, 18x18, 24x24, 42x42, 60x60, 80x80 and 100x100 mm{sup 2}). Radiographic and radiochromic films, diode and ionization chambers were used for data acquisition. MC dose calculations in a water phantom were used to validate the MC simulations using comparisons with measured data. Gamma index criteria 2%/2 mmmore » were used to evaluate the accuracy of MC calculations. MC calculated data show an excellent agreement for field sizes from 18x18 to 100x100 mm{sup 2}. Gamma analysis shows that in average, 95% and 100% of the data passes the gamma index criteria for these fields, respectively. For smaller fields (12x12 and 6x6 mm{sup 2}) only 92% of the data meet the criteria. Total scatter factors show a good agreement (<2.6%) between MC calculated and measured data, except for the smaller fields (12x12 and 6x6 mm{sup 2}) that show a error of 4.7%. MC dose calculations are accurate and precise for clinical treatment planning up to a field size of 18x18 mm{sup 2}. Special care must be taken for smaller fields.« less

SU-G-TeP4-04: An Automated Monte Carlo Based QA Framework for Pencil Beam Scanning Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shin, J; Jee, K; Clasie, B

2016-06-15

Purpose: Prior to treating new PBS field, multiple (three) patient-field-specific QA measurements are performed: two 2D dose distributions at shallow depth (M1) and at the tumor depth (M2) with treatment hardware at zero gantry angle; one 2D dose distribution at iso-center (M3) without patient specific devices at the planned gantry angle. This patient-specific QA could be simplified by the use of MC model. The results of MC model commissioning for a spot-scanning system and the fully automated TOPAS/MC-based QA framework will be presented. Methods: We have developed in-house MC interface to access a TPS (Astroid) database from a computer clustermore » remotely. Once a plan is identified, the interface downloads information for the MC simulations, such as patient images, apertures points, and fluence maps and initiates calculations in both the patient and QA geometries. The resulting calculations are further analyzed to evaluate the TPS dose accuracy and the PBS delivery. Results: The Monte Carlo model of our system was validated within 2.0 % accuracy over the whole range of the dose distribution (proximal/shallow part, as well as target dose part) due to the location of the measurements. The averaged range difference after commissioning was 0.25 mm over entire treatment ranges, e.g., 6.5 cm to 31.6 cm. Conclusion: As M1 depths range typically from 1 cm to 4 cm from the phantom surface, The Monte Carlo model of our system was validated within +− 2.0 % in absolute dose level over a whole treatment range. The averaged range difference after commissioning was 0.25 mm over entire treatment ranges, e.g., 6.5 cm to 31.6 cm. This work was supported by NIH/NCI under CA U19 21239.« less

SU-F-BRD-07: Fast Monte Carlo-Based Biological Optimization of Proton Therapy Treatment Plans for Thyroid Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan Chan Tseung, H; Ma, J; Ma, D

2015-06-15

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) based biological planning for the treatment of thyroid tumors in spot-scanning proton therapy. Methods: Recently, we developed a fast and accurate GPU-based MC simulation of proton transport that was benchmarked against Geant4.9.6 and used as the dose calculation engine in a clinically-applicable GPU-accelerated IMPT optimizer. Besides dose, it can simultaneously score the dose-averaged LET (LETd), which makes fast biological dose (BD) estimates possible. To convert from LETd to BD, we used a linear relation based on cellular irradiation data. Given a thyroid patient with a 93cc tumor volume, we createdmore » a 2-field IMPT plan in Eclipse (Varian Medical Systems). This plan was re-calculated with our MC to obtain the BD distribution. A second 5-field plan was made with our in-house optimizer, using pre-generated MC dose and LETd maps. Constraints were placed to maintain the target dose to within 25% of the prescription, while maximizing the BD. The plan optimization and calculation of dose and LETd maps were performed on a GPU cluster. The conventional IMPT and biologically-optimized plans were compared. Results: The mean target physical and biological doses from our biologically-optimized plan were, respectively, 5% and 14% higher than those from the MC re-calculation of the IMPT plan. Dose sparing to critical structures in our plan was also improved. The biological optimization, including the initial dose and LETd map calculations, can be completed in a clinically viable time (∼30 minutes) on a cluster of 25 GPUs. Conclusion: Taking advantage of GPU acceleration, we created a MC-based, biologically optimized treatment plan for a thyroid patient. Compared to a standard IMPT plan, a 5% increase in the target’s physical dose resulted in ∼3 times as much increase in the BD. Biological planning was thus effective in escalating the target BD.« less

Subtle Monte Carlo Updates in Dense Molecular Systems.

PubMed

Bottaro, Sandro; Boomsma, Wouter; E Johansson, Kristoffer; Andreetta, Christian; Hamelryck, Thomas; Ferkinghoff-Borg, Jesper

2012-02-14

Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.

Monte Carlo simulation of prompt γ-ray emission in proton therapy using a specific track length estimator

NASA Astrophysics Data System (ADS)

El Kanawati, W.; Létang, J. M.; Dauvergne, D.; Pinto, M.; Sarrut, D.; Testa, É.; Freud, N.

2015-10-01

A Monte Carlo (MC) variance reduction technique is developed for prompt-γ emitters calculations in proton therapy. Prompt-γ emitted through nuclear fragmentation reactions and exiting the patient during proton therapy could play an important role to help monitoring the treatment. However, the estimation of the number and the energy of emitted prompt-γ per primary proton with MC simulations is a slow process. In order to estimate the local distribution of prompt-γ emission in a volume of interest for a given proton beam of the treatment plan, a MC variance reduction technique based on a specific track length estimator (TLE) has been developed. First an elemental database of prompt-γ emission spectra is established in the clinical energy range of incident protons for all elements in the composition of human tissues. This database of the prompt-γ spectra is built offline with high statistics. Regarding the implementation of the prompt-γ TLE MC tally, each proton deposits along its track the expectation of the prompt-γ spectra from the database according to the proton kinetic energy and the local material composition. A detailed statistical study shows that the relative efficiency mainly depends on the geometrical distribution of the track length. Benchmarking of the proposed prompt-γ TLE MC technique with respect to an analogous MC technique is carried out. A large relative efficiency gain is reported, ca. 105.

An efficient Bayesian data-worth analysis using a multilevel Monte Carlo method

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Evans, Katherine

2018-03-01

Improving the understanding of subsurface systems and thus reducing prediction uncertainty requires collection of data. As the collection of subsurface data is costly, it is important that the data collection scheme is cost-effective. Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface hydrological model simulations using standard Monte Carlo (MC) sampling or surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose an efficient Bayesian data-worth analysis using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce computational costs using multifidelity approximations. Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it for a highly heterogeneous two-phase subsurface flow simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the standard MC estimation. But compared to the standard MC, the MLMC greatly reduces the computational costs.

A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

PubMed

Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2015-04-07

Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation time including both MC dose calculations and plan optimizations was reduced by a factor of 4.4, from 494 to 113 s, using only one GPU card.

Monte Carlo calculations of positron emitter yields in proton radiotherapy.

PubMed

Seravalli, E; Robert, C; Bauer, J; Stichelbaut, F; Kurz, C; Smeets, J; Van Ngoc Ty, C; Schaart, D R; Buvat, I; Parodi, K; Verhaegen, F

2012-03-21

Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring. © 2012 Institute of Physics and Engineering in Medicine

Calibration of the Top-Quark Monte Carlo Mass.

PubMed

Kieseler, Jan; Lipka, Katerina; Moch, Sven-Olaf

2016-04-22

We present a method to establish, experimentally, the relation between the top-quark mass m_{t}^{MC} as implemented in Monte Carlo generators and the Lagrangian mass parameter m_{t} in a theoretically well-defined renormalization scheme. We propose a simultaneous fit of m_{t}^{MC} and an observable sensitive to m_{t}, which does not rely on any prior assumptions about the relation between m_{t} and m_{t}^{MC}. The measured observable is independent of m_{t}^{MC} and can be used subsequently for a determination of m_{t}. The analysis strategy is illustrated with examples for the extraction of m_{t} from inclusive and differential cross sections for hadroproduction of top quarks.

GPU-accelerated Monte Carlo convolution/superposition implementation for dose calculation.

PubMed

Zhou, Bo; Yu, Cedric X; Chen, Danny Z; Hu, X Sharon

2010-11-01

Dose calculation is a key component in radiation treatment planning systems. Its performance and accuracy are crucial to the quality of treatment plans as emerging advanced radiation therapy technologies are exerting ever tighter constraints on dose calculation. A common practice is to choose either a deterministic method such as the convolution/superposition (CS) method for speed or a Monte Carlo (MC) method for accuracy. The goal of this work is to boost the performance of a hybrid Monte Carlo convolution/superposition (MCCS) method by devising a graphics processing unit (GPU) implementation so as to make the method practical for day-to-day usage. Although the MCCS algorithm combines the merits of MC fluence generation and CS fluence transport, it is still not fast enough to be used as a day-to-day planning tool. To alleviate the speed issue of MC algorithms, the authors adopted MCCS as their target method and implemented a GPU-based version. In order to fully utilize the GPU computing power, the MCCS algorithm is modified to match the GPU hardware architecture. The performance of the authors' GPU-based implementation on an Nvidia GTX260 card is compared to a multithreaded software implementation on a quad-core system. A speedup in the range of 6.7-11.4x is observed for the clinical cases used. The less than 2% statistical fluctuation also indicates that the accuracy of the authors' GPU-based implementation is in good agreement with the results from the quad-core CPU implementation. This work shows that GPU is a feasible and cost-efficient solution compared to other alternatives such as using cluster machines or field-programmable gate arrays for satisfying the increasing demands on computation speed and accuracy of dose calculation. But there are also inherent limitations of using GPU for accelerating MC-type applications, which are also analyzed in detail in this article.

Combined Monte Carlo and path-integral method for simulated library of time-resolved reflectance curves from layered tissue models

NASA Astrophysics Data System (ADS)

Wilson, Robert H.; Vishwanath, Karthik; Mycek, Mary-Ann

2009-02-01

Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert factor to scale the time-resolved reflectance of the simulated zero-absorption tissue model. This method is a unique alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on the accuracy of the method will be discussed.

Validation of a track repeating algorithm for intensity modulated proton therapy: clinical cases study

NASA Astrophysics Data System (ADS)

Yepes, Pablo P.; Eley, John G.; Liu, Amy; Mirkovic, Dragan; Randeniya, Sharmalee; Titt, Uwe; Mohan, Radhe

2016-04-01

Monte Carlo (MC) methods are acknowledged as the most accurate technique to calculate dose distributions. However, due its lengthy calculation times, they are difficult to utilize in the clinic or for large retrospective studies. Track-repeating algorithms, based on MC-generated particle track data in water, accelerate dose calculations substantially, while essentially preserving the accuracy of MC. In this study, we present the validation of an efficient dose calculation algorithm for intensity modulated proton therapy, the fast dose calculator (FDC), based on a track-repeating technique. We validated the FDC algorithm for 23 patients, which included 7 brain, 6 head-and-neck, 5 lung, 1 spine, 1 pelvis and 3 prostate cases. For validation, we compared FDC-generated dose distributions with those from a full-fledged Monte Carlo based on GEANT4 (G4). We compared dose-volume-histograms, 3D-gamma-indices and analyzed a series of dosimetric indices. More than 99% of the voxels in the voxelized phantoms describing the patients have a gamma-index smaller than unity for the 2%/2 mm criteria. In addition the difference relative to the prescribed dose between the dosimetric indices calculated with FDC and G4 is less than 1%. FDC reduces the calculation times from 5 ms per proton to around 5 μs.

Acceleration of Monte Carlo SPECT simulation using convolution-based forced detection

NASA Astrophysics Data System (ADS)

de Jong, H. W. A. M.; Slijpen, E. T. P.; Beekman, F. J.

2001-02-01

Monte Carlo (MC) simulation is an established tool to calculate photon transport through tissue in Emission Computed Tomography (ECT). Since the first appearance of MC a large variety of variance reduction techniques (VRT) have been introduced to speed up these notoriously slow simulations. One example of a very effective and established VRT is known as forced detection (FD). In standard FD the path from the photon's scatter position to the camera is chosen stochastically from the appropriate probability density function (PDF), modeling the distance-dependent detector response. In order to speed up MC the authors propose a convolution-based FD (CFD) which involves replacing the sampling of the PDF by a convolution with a kernel which depends on the position of the scatter event. The authors validated CFD for parallel-hole Single Photon Emission Computed Tomography (SPECT) using a digital thorax phantom. Comparison of projections estimated with CFD and standard FD shows that both estimates converge to practically identical projections (maximum bias 0.9% of peak projection value), despite the slightly different photon paths used in CFD and standard FD. Projections generated with CFD converge, however, to a noise-free projection up to one or two orders of magnitude faster, which is extremely useful in many applications such as model-based image reconstruction.

Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Ritsch, E.; Atlas Collaboration

2014-06-01

The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during Run 1 relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for Run 2, and beyond. A number of fast detector simulation, digitization and reconstruction techniques are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

A virtual source model for Monte Carlo simulation of helical tomotherapy.

PubMed

Yuan, Jiankui; Rong, Yi; Chen, Quan

2015-01-08

The purpose of this study was to present a Monte Carlo (MC) simulation method based on a virtual source, jaw, and MLC model to calculate dose in patient for helical tomotherapy without the need of calculating phase-space files (PSFs). Current studies on the tomotherapy MC simulation adopt a full MC model, which includes extensive modeling of radiation source, primary and secondary jaws, and multileaf collimator (MLC). In the full MC model, PSFs need to be created at different scoring planes to facilitate the patient dose calculations. In the present work, the virtual source model (VSM) we established was based on the gold standard beam data of a tomotherapy unit, which can be exported from the treatment planning station (TPS). The TPS-generated sinograms were extracted from the archived patient XML (eXtensible Markup Language) files. The fluence map for the MC sampling was created by incorporating the percentage leaf open time (LOT) with leaf filter, jaw penumbra, and leaf latency contained from sinogram files. The VSM was validated for various geometry setups and clinical situations involving heterogeneous media and delivery quality assurance (DQA) cases. An agreement of < 1% was obtained between the measured and simulated results for percent depth doses (PDDs) and open beam profiles for all three jaw settings in the VSM commissioning. The accuracy of the VSM leaf filter model was verified in comparing the measured and simulated results for a Picket Fence pattern. An agreement of < 2% was achieved between the presented VSM and a published full MC model for heterogeneous phantoms. For complex clinical head and neck (HN) cases, the VSM-based MC simulation of DQA plans agreed with the film measurement with 98% of planar dose pixels passing on the 2%/2 mm gamma criteria. For patient treatment plans, results showed comparable dose-volume histograms (DVHs) for planning target volumes (PTVs) and organs at risk (OARs). Deviations observed in this study were consistent with literature. The VSM-based MC simulation approach can be feasibly built from the gold standard beam model of a tomotherapy unit. The accuracy of the VSM was validated against measurements in homogeneous media, as well as published full MC model in heterogeneous media.

A virtual source model for Monte Carlo simulation of helical tomotherapy

PubMed Central

Yuan, Jiankui; Rong, Yi

2015-01-01

The purpose of this study was to present a Monte Carlo (MC) simulation method based on a virtual source, jaw, and MLC model to calculate dose in patient for helical tomotherapy without the need of calculating phase‐space files (PSFs). Current studies on the tomotherapy MC simulation adopt a full MC model, which includes extensive modeling of radiation source, primary and secondary jaws, and multileaf collimator (MLC). In the full MC model, PSFs need to be created at different scoring planes to facilitate the patient dose calculations. In the present work, the virtual source model (VSM) we established was based on the gold standard beam data of a tomotherapy unit, which can be exported from the treatment planning station (TPS). The TPS‐generated sinograms were extracted from the archived patient XML (eXtensible Markup Language) files. The fluence map for the MC sampling was created by incorporating the percentage leaf open time (LOT) with leaf filter, jaw penumbra, and leaf latency contained from sinogram files. The VSM was validated for various geometry setups and clinical situations involving heterogeneous media and delivery quality assurance (DQA) cases. An agreement of <1% was obtained between the measured and simulated results for percent depth doses (PDDs) and open beam profiles for all three jaw settings in the VSM commissioning. The accuracy of the VSM leaf filter model was verified in comparing the measured and simulated results for a Picket Fence pattern. An agreement of <2% was achieved between the presented VSM and a published full MC model for heterogeneous phantoms. For complex clinical head and neck (HN) cases, the VSM‐based MC simulation of DQA plans agreed with the film measurement with 98% of planar dose pixels passing on the 2%/2 mm gamma criteria. For patient treatment plans, results showed comparable dose‐volume histograms (DVHs) for planning target volumes (PTVs) and organs at risk (OARs). Deviations observed in this study were consistent with literature. The VSM‐based MC simulation approach can be feasibly built from the gold standard beam model of a tomotherapy unit. The accuracy of the VSM was validated against measurements in homogeneous media, as well as published full MC model in heterogeneous media. PACS numbers: 87.53.‐j, 87.55.K‐ PMID:25679157

Efficient Data-Worth Analysis Using a Multilevel Monte Carlo Method Applied in Oil Reservoir Simulations

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Evans, K. J.

2017-12-01

Data-worth analysis plays an essential role in improving the understanding of the subsurface system, in developing and refining subsurface models, and in supporting rational water resources management. However, data-worth analysis is computationally expensive as it requires quantifying parameter uncertainty, prediction uncertainty, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface simulations using standard Monte Carlo (MC) sampling or advanced surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose efficient Bayesian analysis of data-worth using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce the computational cost with the use of multifidelity approximations. As the data-worth analysis involves a great deal of expectation estimations, the cost savings from MLMC in the assessment can be very outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it to a highly heterogeneous oil reservoir simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the estimation obtained from the standard MC. But compared to the standard MC, the MLMC greatly reduces the computational costs in the uncertainty reduction estimation, with up to 600 days cost savings when one processor is used.

Top Quark Mass Calibration for Monte Carlo Event Generators.

PubMed

Butenschoen, Mathias; Dehnadi, Bahman; Hoang, André H; Mateu, Vicent; Preisser, Moritz; Stewart, Iain W

2016-12-02

The most precise top quark mass measurements use kinematic reconstruction methods, determining the top mass parameter of a Monte Carlo event generator m_{t}^{MC}. Because of hadronization and parton-shower dynamics, relating m_{t}^{MC} to a field theory mass is difficult. We present a calibration procedure to determine this relation using hadron level QCD predictions for observables with kinematic mass sensitivity. Fitting e^{+}e^{-} 2-jettiness calculations at next-to-leading-logarithmic and next-to-next-to-leading-logarithmic order to pythia 8.205, m_{t}^{MC} differs from the pole mass by 900 and 600 MeV, respectively, and agrees with the MSR mass within uncertainties, m_{t}^{MC}≃m_{t,1  GeV}^{MSR}.

Crossover of cation partitioning in olivines: a combination of ab initio and Monte Carlo study

NASA Astrophysics Data System (ADS)

Chatterjee, Swastika; Bhattacharyya, Sirshendu; Sengupta, Surajit; Saha-Dasgupta, Tanusri

2011-04-01

We report studies based on a combination of ab initio electronic structure and Monte Carlo (MC) technique on the problem of cation partitioning among inequivalent octahedral sites, M1 and M2 in mixed olivines containing Mg2+ and Fe2+ ions. Our MC scheme uses interactions derived out of ab initio, density functional calculations carried out on measured crystal structure data. Our results show that there is no reversal of the preference of Fe for M1 over M2 as a function of temperature. Our findings do not agree with the experimental findings of Redfern et al. (Phys Chem Miner 27:630-637, 2000), but are in agreement with those of Heinemann et al. (Eur J Mineral 18:673-689, 2006) and Morozov et al. (Eur J Mineral 17:495-500, 2005).

Improved cache performance in Monte Carlo transport calculations using energy banding

NASA Astrophysics Data System (ADS)

Siegel, A.; Smith, K.; Felker, K.; Romano, P.; Forget, B.; Beckman, P.

2014-04-01

We present an energy banding algorithm for Monte Carlo (MC) neutral particle transport simulations which depend on large cross section lookup tables. In MC codes, read-only cross section data tables are accessed frequently, exhibit poor locality, and are typically too much large to fit in fast memory. Thus, performance is often limited by long latencies to RAM, or by off-node communication latencies when the data footprint is very large and must be decomposed on a distributed memory machine. The proposed energy banding algorithm allows maximal temporal reuse of data in band sizes that can flexibly accommodate different architectural features. The energy banding algorithm is general and has a number of benefits compared to the traditional approach. In the present analysis we explore its potential to achieve improvements in time-to-solution on modern cache-based architectures.

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures.

PubMed

Souris, Kevin; Lee, John Aldo; Sterpin, Edmond

2016-04-01

Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the gate/geant4 Monte Carlo application for homogeneous and heterogeneous geometries. Comparisons with gate/geant4 for various geometries show deviations within 2%-1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10(7) primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.

Comparison of film measurements and Monte Carlo simulations of dose delivered with very high-energy electron beams in a polystyrene phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bazalova-Carter, Magdalena; Liu, Michael; Palma, Bianey

2015-04-15

Purpose: To measure radiation dose in a water-equivalent medium from very high-energy electron (VHEE) beams and make comparisons to Monte Carlo (MC) simulation results. Methods: Dose in a polystyrene phantom delivered by an experimental VHEE beam line was measured with Gafchromic films for three 50 MeV and two 70 MeV Gaussian beams of 4.0–6.9 mm FWHM and compared to corresponding MC-simulated dose distributions. MC dose in the polystyrene phantom was calculated with the EGSnrc/BEAMnrc and DOSXYZnrc codes based on the experimental setup. Additionally, the effect of 2% beam energy measurement uncertainty and possible non-zero beam angular spread on MC dosemore » distributions was evaluated. Results: MC simulated percentage depth dose (PDD) curves agreed with measurements within 4% for all beam sizes at both 50 and 70 MeV VHEE beams. Central axis PDD at 8 cm depth ranged from 14% to 19% for the 5.4–6.9 mm 50 MeV beams and it ranged from 14% to 18% for the 4.0–4.5 mm 70 MeV beams. MC simulated relative beam profiles of regularly shaped Gaussian beams evaluated at depths of 0.64 to 7.46 cm agreed with measurements to within 5%. A 2% beam energy uncertainty and 0.286° beam angular spread corresponded to a maximum 3.0% and 3.8% difference in depth dose curves of the 50 and 70 MeV electron beams, respectively. Absolute dose differences between MC simulations and film measurements of regularly shaped Gaussian beams were between 10% and 42%. Conclusions: The authors demonstrate that relative dose distributions for VHEE beams of 50–70 MeV can be measured with Gafchromic films and modeled with Monte Carlo simulations to an accuracy of 5%. The reported absolute dose differences likely caused by imperfect beam steering and subsequent charge loss revealed the importance of accurate VHEE beam control and diagnostics.« less

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Efficient gradient-based Monte Carlo simulation of materials: Applications to amorphous Si and Fe and Ni clusters

NASA Astrophysics Data System (ADS)

Limbu, Dil; Biswas, Parthapratim

We present a simple and efficient Monte-Carlo (MC) simulation of Iron (Fe) and Nickel (Ni) clusters with N =5-100 and amorphous Silicon (a-Si) starting from a random configuration. Using Sutton-Chen and Finnis-Sinclair potentials for Ni (in fcc lattice) and Fe (in bcc lattice), and Stillinger-Weber potential for a-Si, respectively, the total energy of the system is optimized by employing MC moves that include both the stochastic nature of MC simulations and the gradient of the potential function. For both iron and nickel clusters, the energy of the configurations is found to be very close to the values listed in the Cambridge Cluster Database, whereas the maximum force on each cluster is found to be much lower than the corresponding value obtained from the optimized structural configurations reported in the database. An extension of the method to model the amorphous state of Si is presented and the results are compared with experimental data and those obtained from other simulation methods. The work is partially supported by the NSF under Grant Number DMR 1507166.

"First-principles" kinetic Monte Carlo simulations revisited: CO oxidation over RuO2 (110).

PubMed

Hess, Franziska; Farkas, Attila; Seitsonen, Ari P; Over, Herbert

2012-03-15

First principles-based kinetic Monte Carlo (kMC) simulations are performed for the CO oxidation on RuO(2) (110) under steady-state reaction conditions. The simulations include a set of elementary reaction steps with activation energies taken from three different ab initio density functional theory studies. Critical comparison of the simulation results reveals that already small variations in the activation energies lead to distinctly different reaction scenarios on the surface, even to the point where the dominating elementary reaction step is substituted by another one. For a critical assessment of the chosen energy parameters, it is not sufficient to compare kMC simulations only to experimental turnover frequency (TOF) as a function of the reactant feed ratio. More appropriate benchmarks for kMC simulations are the actual distribution of reactants on the catalyst's surface during steady-state reaction, as determined by in situ infrared spectroscopy and in situ scanning tunneling microscopy, and the temperature dependence of TOF in the from of Arrhenius plots. Copyright © 2012 Wiley Periodicals, Inc.

Development of Subspace-based Hybrid Monte Carlo-Deterministric Algorithms for Reactor Physics Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdel-Khalik, Hany S.; Zhang, Qiong

2014-05-20

The development of hybrid Monte-Carlo-Deterministic (MC-DT) approaches, taking place over the past few decades, have primarily focused on shielding and detection applications where the analysis requires a small number of responses, i.e. at the detector locations(s). This work further develops a recently introduced global variance reduction approach, denoted by the SUBSPACE approach is designed to allow the use of MC simulation, currently limited to benchmarking calculations, for routine engineering calculations. By way of demonstration, the SUBSPACE approach is applied to assembly level calculations used to generate the few-group homogenized cross-sections. These models are typically expensive and need to be executedmore » in the order of 10 3 - 10 5 times to properly characterize the few-group cross-sections for downstream core-wide calculations. Applicability to k-eigenvalue core-wide models is also demonstrated in this work. Given the favorable results obtained in this work, we believe the applicability of the MC method for reactor analysis calculations could be realized in the near future.« less

Methods for Monte Carlo simulations of biomacromolecules

PubMed Central

Vitalis, Andreas; Pappu, Rohit V.

2010-01-01

The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies. PMID:20428473

Monte Carlo simulations to replace film dosimetry in IMRT verification.

PubMed

Goetzfried, Thomas; Rickhey, Mark; Treutwein, Marius; Koelbl, Oliver; Bogner, Ludwig

2011-01-01

Patient-specific verification of intensity-modulated radiation therapy (IMRT) plans can be done by dosimetric measurements or by independent dose or monitor unit calculations. The aim of this study was the clinical evaluation of IMRT verification based on a fast Monte Carlo (MC) program with regard to possible benefits compared to commonly used film dosimetry. 25 head-and-neck IMRT plans were recalculated by a pencil beam based treatment planning system (TPS) using an appropriate quality assurance (QA) phantom. All plans were verified both by film and diode dosimetry and compared to MC simulations. The irradiated films, the results of diode measurements and the computed dose distributions were evaluated, and the data were compared on the basis of gamma maps and dose-difference histograms. Average deviations in the high-dose region between diode measurements and point dose calculations performed with the TPS and MC program were 0.7 ± 2.7% and 1.2 ± 3.1%, respectively. For film measurements, the mean gamma values with 3% dose difference and 3mm distance-to-agreement were 0.74 ± 0.28 (TPS as reference) with dose deviations up to 10%. Corresponding values were significantly reduced to 0.34 ± 0.09 for MC dose calculation. The total time needed for both verification procedures is comparable, however, by far less labor intensive in the case of MC simulations. The presented study showed that independent dose calculation verification of IMRT plans with a fast MC program has the potential to eclipse film dosimetry more and more in the near future. Thus, the linac-specific QA part will necessarily become more important. In combination with MC simulations and due to the simple set-up, point-dose measurements for dosimetric plausibility checks are recommended at least in the IMRT introduction phase. Copyright © 2010. Published by Elsevier GmbH.

A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of nonelastic interactions.

PubMed

Wan Chan Tseung, H; Ma, J; Beltran, C

2015-06-01

Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on graphics processing units (GPUs). However, these MCs usually use simplified models for nonelastic proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and nonelastic proton-nucleus collisions. Using the cuda framework, the authors implemented GPU kernels for the following tasks: (1) simulation of beam spots from our possible scanning nozzle configurations, (2) proton propagation through CT geometry, taking into account nuclear elastic scattering, multiple scattering, and energy loss straggling, (3) modeling of the intranuclear cascade stage of nonelastic interactions when they occur, (4) simulation of nuclear evaporation, and (5) statistical error estimates on the dose. To validate our MC, the authors performed (1) secondary particle yield calculations in proton collisions with therapeutically relevant nuclei, (2) dose calculations in homogeneous phantoms, (3) recalculations of complex head and neck treatment plans from a commercially available treatment planning system, and compared with (GEANT)4.9.6p2/TOPAS. Yields, energy, and angular distributions of secondaries from nonelastic collisions on various nuclei are in good agreement with the (GEANT)4.9.6p2 Bertini and Binary cascade models. The 3D-gamma pass rate at 2%-2 mm for treatment plan simulations is typically 98%. The net computational time on a NVIDIA GTX680 card, including all CPU-GPU data transfers, is ∼ 20 s for 1 × 10(7) proton histories. Our GPU-based MC is the first of its kind to include a detailed nuclear model to handle nonelastic interactions of protons with any nucleus. Dosimetric calculations are in very good agreement with (GEANT)4.9.6p2/TOPAS. Our MC is being integrated into a framework to perform fast routine clinical QA of pencil-beam based treatment plans, and is being used as the dose calculation engine in a clinically applicable MC-based IMPT treatment planning system. The detailed nuclear modeling will allow us to perform very fast linear energy transfer and neutron dose estimates on the GPU.

SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, K; Leung, R; Law, G

Background: Commercial treatment planning system Pinnacle3 (Philips, Fitchburg, WI, USA) employs a convolution-superposition algorithm for volumetric-modulated arc radiotherapy (VMAT) optimization and dose calculation. Study of Monte Carlo (MC) dose recalculation of VMAT plans for advanced-stage nasopharyngeal cancers (NPC) is currently limited. Methods: Twenty-nine VMAT prescribed 70Gy, 60Gy, and 54Gy to the planning target volumes (PTVs) were included. These clinical plans achieved with a CS dose engine on Pinnacle3 v9.0 were recalculated by the Monaco TPS v5.0 (Elekta, Maryland Heights, MO, USA) with a XVMC-based MC dose engine. The MC virtual source model was built using the same measurement beam datasetmore » as for the Pinnacle beam model. All MC recalculation were based on absorbed dose to medium in medium (Dm,m). Differences in dose constraint parameters per our institution protocol (Supplementary Table 1) were analyzed. Results: Only differences in maximum dose to left brachial plexus, left temporal lobe and PTV54Gy were found to be statistically insignificant (p> 0.05). Dosimetric differences of other tumor targets and normal organs are found in supplementary Table 1. Generally, doses outside the PTV in the normal organs are lower with MC than with CS. This is also true in the PTV54-70Gy doses but higher dose in the nasal cavity near the bone interfaces is consistently predicted by MC, possibly due to the increased backscattering of short-range scattered photons and the secondary electrons that is not properly modeled by the CS. The straight shoulders of the PTV dose volume histograms (DVH) initially resulted from the CS optimization are merely preserved after MC recalculation. Conclusion: Significant dosimetric differences in VMAT NPC plans were observed between CS and MC calculations. Adjustments of the planning dose constraints to incorporate the physics differences from conventional CS algorithm should be made when VMAT optimization is carried out directly with MC dose engine.« less

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

Monte Carlo simulations of neutron-scattering instruments using McStas

NASA Astrophysics Data System (ADS)

Nielsen, K.; Lefmann, K.

2000-06-01

Monte Carlo simulations have become an essential tool for improving the performance of neutron-scattering instruments, since the level of sophistication in the design of instruments is defeating purely analytical methods. The program McStas, being developed at Risø National Laboratory, includes an extension language that makes it easy to adapt it to the particular requirements of individual instruments, and thus provides a powerful and flexible tool for constructing such simulations. McStas has been successfully applied in such areas as neutron guide design, flux optimization, non-Gaussian resolution functions of triple-axis spectrometers, and time-focusing in time-of-flight instruments.

Hydrologic Process Parameterization of Electrical Resistivity Imaging of Solute Plumes Using POD McMC

NASA Astrophysics Data System (ADS)

Awatey, M. T.; Irving, J.; Oware, E. K.

2016-12-01

Markov chain Monte Carlo (McMC) inversion frameworks are becoming increasingly popular in geophysics due to their ability to recover multiple equally plausible geologic features that honor the limited noisy measurements. Standard McMC methods, however, become computationally intractable with increasing dimensionality of the problem, for example, when working with spatially distributed geophysical parameter fields. We present a McMC approach based on a sparse proper orthogonal decomposition (POD) model parameterization that implicitly incorporates the physics of the underlying process. First, we generate training images (TIs) via Monte Carlo simulations of the target process constrained to a conceptual model. We then apply POD to construct basis vectors from the TIs. A small number of basis vectors can represent most of the variability in the TIs, leading to dimensionality reduction. A projection of the starting model into the reduced basis space generates the starting POD coefficients. At each iteration, only coefficients within a specified sampling window are resimulated assuming a Gaussian prior. The sampling window grows at a specified rate as the number of iteration progresses starting from the coefficients corresponding to the highest ranked basis to those of the least informative basis. We found this gradual increment in the sampling window to be more stable compared to resampling all the coefficients right from the first iteration. We demonstrate the performance of the algorithm with both synthetic and lab-scale electrical resistivity imaging of saline tracer experiments, employing the same set of basis vectors for all inversions. We consider two scenarios of unimodal and bimodal plumes. The unimodal plume is consistent with the hypothesis underlying the generation of the TIs whereas bimodality in plume morphology was not theorized. We show that uncertainty quantification using McMC can proceed in the reduced dimensionality space while accounting for the physics of the underlying process.

Top Quark Mass Calibration for Monte Carlo Event Generators

DOE PAGES

Butenschoen, Mathias; Dehnadi, Bahman; Hoang, André H.; ...

2016-11-29

The most precise top quark mass measurements use kinematic reconstruction methods, determining the top mass parameter of a Monte Carlo event generator mmore » $$MC\\atop{t}$$. Because of hadronization and parton-shower dynamics, relating m$$MC\\atop{t}$$ to a field theory mass is difficult. Here, we present a calibration procedure to determine this relation using hadron level QCD predictions for observables with kinematic mass sensitivity. Fitting e +e −2-jettiness calculations at next-to-leading-logarithmic and next-to-next-to-leading-logarithmic order to PYTHIA 8.205, m$$MC\\atop{t}$$ differs from the pole mass by 900 and 600 MeV, respectively, and agrees with the MSR mass within uncertainties, m$$MC\\atop{t}$$ ≃ m$$MSR\\atop{t,1 GeV}$$.« less

NOTE: MMCTP: a radiotherapy research environment for Monte Carlo and patient-specific treatment planning

NASA Astrophysics Data System (ADS)

Alexander, A.; DeBlois, F.; Stroian, G.; Al-Yahya, K.; Heath, E.; Seuntjens, J.

2007-07-01

Radiotherapy research lacks a flexible computational research environment for Monte Carlo (MC) and patient-specific treatment planning. The purpose of this study was to develop a flexible software package on low-cost hardware with the aim of integrating new patient-specific treatment planning with MC dose calculations suitable for large-scale prospective and retrospective treatment planning studies. We designed the software package 'McGill Monte Carlo treatment planning' (MMCTP) for the research development of MC and patient-specific treatment planning. The MMCTP design consists of a graphical user interface (GUI), which runs on a simple workstation connected through standard secure-shell protocol to a cluster for lengthy MC calculations. Treatment planning information (e.g., images, structures, beam geometry properties and dose distributions) is converted into a convenient MMCTP local file storage format designated, the McGill RT format. MMCTP features include (a) DICOM_RT, RTOG and CADPlan CART format imports; (b) 2D and 3D visualization views for images, structure contours, and dose distributions; (c) contouring tools; (d) DVH analysis, and dose matrix comparison tools; (e) external beam editing; (f) MC transport calculation from beam source to patient geometry for photon and electron beams. The MC input files, which are prepared from the beam geometry properties and patient information (e.g., images and structure contours), are uploaded and run on a cluster using shell commands controlled from the MMCTP GUI. The visualization, dose matrix operation and DVH tools offer extensive options for plan analysis and comparison between MC plans and plans imported from commercial treatment planning systems. The MMCTP GUI provides a flexible research platform for the development of patient-specific MC treatment planning for photon and electron external beam radiation therapy. The impact of this tool lies in the fact that it allows for systematic, platform-independent, large-scale MC treatment planning for different treatment sites. Patient recalculations were performed to validate the software and ensure proper functionality.

Efficient Coupling of Fluid-Plasma and Monte-Carlo-Neutrals Models for Edge Plasma Transport

NASA Astrophysics Data System (ADS)

Dimits, A. M.; Cohen, B. I.; Friedman, A.; Joseph, I.; Lodestro, L. L.; Rensink, M. E.; Rognlien, T. D.; Sjogreen, B.; Stotler, D. P.; Umansky, M. V.

2017-10-01

UEDGE has been valuable for modeling transport in the tokamak edge and scrape-off layer due in part to its efficient fully implicit solution of coupled fluid neutrals and plasma models. We are developing an implicit coupling of the kinetic Monte-Carlo (MC) code DEGAS-2, as the neutrals model component, to the UEDGE plasma component, based on an extension of the Jacobian-free Newton-Krylov (JFNK) method to MC residuals. The coupling components build on the methods and coding already present in UEDGE. For the linear Krylov iterations, a procedure has been developed to ``extract'' a good preconditioner from that of UEDGE. This preconditioner may also be used to greatly accelerate the convergence rate of a relaxed fixed-point iteration, which may provide a useful ``intermediate'' algorithm. The JFNK method also requires calculation of Jacobian-vector products, for which any finite-difference procedure is inaccurate when a MC component is present. A semi-analytical procedure that retains the standard MC accuracy and fully kinetic neutrals physics is therefore being developed. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and LDRD project 15-ERD-059, by PPPL under Contract DE-AC02-09CH11466, and supported in part by the U.S. DOE, OFES.

The Ultimate Monte Carlo: Studying Cross-Sections With Cosmic Rays

NASA Technical Reports Server (NTRS)

Wilson, Thomas L.

2007-01-01

The high-energy physics community has been discussing for years the need to bring together the three principal disciplines that study hadron cross-section physics - ground-based accelerators, cosmic-ray experiments in space, and air shower research. Only recently have NASA investigators begun discussing the use of space-borne cosmic-ray payloads to bridge the gap between accelerator physics and air shower work using cosmic-ray measurements. The common tool used in these three realms of high-energy hadron physics is the Monte Carlo (MC). Yet the obvious has not been considered - using a single MC for simulating the entire relativistic energy range (GeV to EeV). The task is daunting due to large uncertainties in accelerator, space, and atmospheric cascade measurements. These include inclusive versus exclusive cross-section measurements, primary composition, interaction dynamics, and possible new physics beyond the standard model. However, the discussion of a common tool or ultimate MC might be the very thing that could begin to unify these independent groups into a common purpose. The Offline ALICE concept of a Virtual MC at CERN s Large Hadron Collider (LHC) will be discussed as a rudimentary beginning of this idea, and as a possible forum for carrying it forward in the future as LHC data emerges.

Assessment of Person Fit Using Resampling-Based Approaches

ERIC Educational Resources Information Center

Sinharay, Sandip

2016-01-01

De la Torre and Deng suggested a resampling-based approach for person-fit assessment (PFA). The approach involves the use of the [math equation unavailable] statistic, a corrected expected a posteriori estimate of the examinee ability, and the Monte Carlo (MC) resampling method. The Type I error rate of the approach was closer to the nominal level…

Monte Carlo grain growth modeling with local temperature gradients

NASA Astrophysics Data System (ADS)

Tan, Y.; Maniatty, A. M.; Zheng, C.; Wen, J. T.

2017-09-01

This work investigated the development of a Monte Carlo (MC) simulation approach to modeling grain growth in the presence of non-uniform temperature field that may vary with time. We first scale the MC model to physical growth processes by fitting experimental data. Based on the scaling relationship, we derive a grid site selection probability (SSP) function to consider the effect of a spatially varying temperature field. The SSP function is based on the differential MC step, which allows it to naturally consider time varying temperature fields too. We verify the model and compare the predictions to other existing formulations (Godfrey and Martin 1995 Phil. Mag. A 72 737-49 Radhakrishnan and Zacharia 1995 Metall. Mater. Trans. A 26 2123-30) in simple two-dimensional cases with only spatially varying temperature fields, where the predicted grain growth in regions of constant temperature are expected to be the same as for the isothermal case. We also test the model in a more realistic three-dimensional case with a temperature field varying in both space and time, modeling grain growth in the heat affected zone of a weld. We believe the newly proposed approach is promising for modeling grain growth in material manufacturing processes that involves time-dependent local temperature gradient.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y M; Bush, K; Han, B

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) methodmore » that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.« less

Validation of a GPU-based Monte Carlo code (gPMC) for proton radiation therapy: clinical cases study.

PubMed

Giantsoudi, Drosoula; Schuemann, Jan; Jia, Xun; Dowdell, Stephen; Jiang, Steve; Paganetti, Harald

2015-03-21

Monte Carlo (MC) methods are recognized as the gold-standard for dose calculation, however they have not replaced analytical methods up to now due to their lengthy calculation times. GPU-based applications allow MC dose calculations to be performed on time scales comparable to conventional analytical algorithms. This study focuses on validating our GPU-based MC code for proton dose calculation (gPMC) using an experimentally validated multi-purpose MC code (TOPAS) and compare their performance for clinical patient cases. Clinical cases from five treatment sites were selected covering the full range from very homogeneous patient geometries (liver) to patients with high geometrical complexity (air cavities and density heterogeneities in head-and-neck and lung patients) and from short beam range (breast) to large beam range (prostate). Both gPMC and TOPAS were used to calculate 3D dose distributions for all patients. Comparisons were performed based on target coverage indices (mean dose, V95, D98, D50, D02) and gamma index distributions. Dosimetric indices differed less than 2% between TOPAS and gPMC dose distributions for most cases. Gamma index analysis with 1%/1 mm criterion resulted in a passing rate of more than 94% of all patient voxels receiving more than 10% of the mean target dose, for all patients except for prostate cases. Although clinically insignificant, gPMC resulted in systematic underestimation of target dose for prostate cases by 1-2% compared to TOPAS. Correspondingly the gamma index analysis with 1%/1 mm criterion failed for most beams for this site, while for 2%/1 mm criterion passing rates of more than 94.6% of all patient voxels were observed. For the same initial number of simulated particles, calculation time for a single beam for a typical head and neck patient plan decreased from 4 CPU hours per million particles (2.8-2.9 GHz Intel X5600) for TOPAS to 2.4 s per million particles (NVIDIA TESLA C2075) for gPMC. Excellent agreement was demonstrated between our fast GPU-based MC code (gPMC) and a previously extensively validated multi-purpose MC code (TOPAS) for a comprehensive set of clinical patient cases. This shows that MC dose calculations in proton therapy can be performed on time scales comparable to analytical algorithms with accuracy comparable to state-of-the-art CPU-based MC codes.

Monte Carlo modeling of HD120 multileaf collimator on Varian TrueBeam linear accelerator for verification of 6X and 6X FFF VMAT SABR treatment plans

PubMed Central

Gete, Ermias; Duzenli, Cheryl; Teke, Tony

2014-01-01

A Monte Carlo (MC) validation of the vendor‐supplied Varian TrueBeam 6 MV flattened (6X) phase‐space file and the first implementation of the Siebers‐Keall MC MLC model as applied to the HD120 MLC (for 6X flat and 6X flattening filterfree (6X FFF) beams) are described. The MC model is validated in the context of VMAT patient‐specific quality assurance. The Monte Carlo commissioning process involves: 1) validating the calculated open‐field percentage depth doses (PDDs), profiles, and output factors (OF), 2) adapting the Siebers‐Keall MLC model to match the new HD120‐MLC geometry and material composition, 3) determining the absolute dose conversion factor for the MC calculation, and 4) validating this entire linac/MLC in the context of dose calculation verification for clinical VMAT plans. MC PDDs for the 6X beams agree with the measured data to within 2.0% for field sizes ranging from 2 × 2 to 40 × 40 cm2. Measured and MC profiles show agreement in the 50% field width and the 80%‐20% penumbra region to within 1.3 mm for all square field sizes. MC OFs for the 2 to 40 cm2 square fields agree with measurement to within 1.6%. Verification of VMAT SABR lung, liver, and vertebra plans demonstrate that measured and MC ion chamber doses agree within 0.6% for the 6X beam and within 2.0% for the 6X FFF beam. A 3D gamma factor analysis demonstrates that for the 6X beam, > 99% of voxels meet the pass criteria (3%/3 mm). For the 6X FFF beam, > 94% of voxels meet this criteria. The TrueBeam accelerator delivering 6X and 6X FFF beams with the HD120 MLC can be modeled in Monte Carlo to provide an independent 3D dose calculation for clinical VMAT plans. This quality assurance tool has been used clinically to verify over 140 6X and 16 6X FFF TrueBeam treatment plans. PACS number: 87.55.K‐ PMID:24892341

The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

PubMed

Siebers, Jeffrey V

2008-04-04

Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs <100 cGy (1.5% of the prescription dose) for MC-optimized IMRT treatment plans.Seven-field prostate IMRT treatment plans for 10 prostate patients are used in this study. Pre-optimization is performed for deliverable beams with a pencil-beam (PB) dose algorithm. Further deliverable-based optimization proceeds using: (1) MC-based optimization, where dose is recomputed with MC after each intensity update or (2) a once-corrected (OC) MC-hybrid optimization, where a MC dose computation defines beam-by-beam dose correction matrices that are used during a PB-based optimization. Optimizations are performed with nominal per beam MC statistical precisions of 2, 5, 8, 10, 15, and 20%. Following optimizer convergence, beams are re-computed with MC using 2% per beam nominal statistical precision and the 2 PTV and 10 OAR dose indices used in the optimization objective function are tallied. For both the MC-optimization and OC-optimization methods, statistical equivalence tests found that OCEs are less than 1.5% of the prescription dose for plans optimized with nominal statistical uncertainties of up to 10% per beam. The achieved statistical uncertainty in the patient for the 10% per beam simulations from the combination of the 7 beams is ~3% with respect to maximum dose for voxels with D>0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC computations.

Monte Carlo decision curve analysis using aggregate data.

PubMed

Hozo, Iztok; Tsalatsanis, Athanasios; Djulbegovic, Benjamin

2017-02-01

Decision curve analysis (DCA) is an increasingly used method for evaluating diagnostic tests and predictive models, but its application requires individual patient data. The Monte Carlo (MC) method can be used to simulate probabilities and outcomes of individual patients and offers an attractive option for application of DCA. We constructed a MC decision model to simulate individual probabilities of outcomes of interest. These probabilities were contrasted against the threshold probability at which a decision-maker is indifferent between key management strategies: treat all, treat none or use predictive model to guide treatment. We compared the results of DCA with MC simulated data against the results of DCA based on actual individual patient data for three decision models published in the literature: (i) statins for primary prevention of cardiovascular disease, (ii) hospice referral for terminally ill patients and (iii) prostate cancer surgery. The results of MC DCA and patient data DCA were identical. To the extent that patient data DCA were used to inform decisions about statin use, referral to hospice or prostate surgery, the results indicate that MC DCA could have also been used. As long as the aggregate parameters on distribution of the probability of outcomes and treatment effects are accurately described in the published reports, the MC DCA will generate indistinguishable results from individual patient data DCA. We provide a simple, easy-to-use model, which can facilitate wider use of DCA and better evaluation of diagnostic tests and predictive models that rely only on aggregate data reported in the literature. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.

MC 2 -3: Multigroup Cross Section Generation Code for Fast Reactor Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Changho; Yang, Won Sik

This paper presents the methods and performance of the MC2 -3 code, which is a multigroup cross-section generation code for fast reactor analysis, developed to improve the resonance self-shielding and spectrum calculation methods of MC2 -2 and to simplify the current multistep schemes generating region-dependent broad-group cross sections. Using the basic neutron data from ENDF/B data files, MC2 -3 solves the consistent P1 multigroup transport equation to determine the fundamental mode spectra for use in generating multigroup neutron cross sections. A homogeneous medium or a heterogeneous slab or cylindrical unit cell problem is solved in ultrafine (2082) or hyperfine (~400more » 000) group levels. In the resolved resonance range, pointwise cross sections are reconstructed with Doppler broadening at specified temperatures. The pointwise cross sections are directly used in the hyperfine group calculation, whereas for the ultrafine group calculation, self-shielded cross sections are prepared by numerical integration of the pointwise cross sections based upon the narrow resonance approximation. For both the hyperfine and ultrafine group calculations, unresolved resonances are self-shielded using the analytic resonance integral method. The ultrafine group calculation can also be performed for a two-dimensional whole-core problem to generate region-dependent broad-group cross sections. Verification tests have been performed using the benchmark problems for various fast critical experiments including Los Alamos National Laboratory critical assemblies; Zero-Power Reactor, Zero-Power Physics Reactor, and Bundesamt für Strahlenschutz experiments; Monju start-up core; and Advanced Burner Test Reactor. Verification and validation results with ENDF/B-VII.0 data indicated that eigenvalues from MC2 -3/DIF3D agreed well with Monte Carlo N-Particle5 MCNP5 or VIM Monte Carlo solutions within 200 pcm and regionwise one-group fluxes were in good agreement with Monte Carlo solutions.« less

Simulation of gas adsorption on a surface and in slit pores with grand canonical and canonical kinetic Monte Carlo methods.

PubMed

Ustinov, E A; Do, D D

2012-08-21

We present for the first time in the literature a new scheme of kinetic Monte Carlo method applied on a grand canonical ensemble, which we call hereafter GC-kMC. It was shown recently that the kinetic Monte Carlo (kMC) scheme is a very effective tool for the analysis of equilibrium systems. It had been applied in a canonical ensemble to describe vapor-liquid equilibrium of argon over a wide range of temperatures, gas adsorption on a graphite open surface and in graphitic slit pores. However, in spite of the conformity of canonical and grand canonical ensembles, the latter is more relevant in the correct description of open systems; for example, the hysteresis loop observed in adsorption of gases in pores under sub-critical conditions can only be described with a grand canonical ensemble. Therefore, the present paper is aimed at an extension of the kMC to open systems. The developed GC-kMC was proved to be consistent with the results obtained with the canonical kMC (C-kMC) for argon adsorption on a graphite surface at 77 K and in graphitic slit pores at 87.3 K. We showed that in slit micropores the hexagonal packing in the layers adjacent to the pore walls is observed at high loadings even at temperatures above the triple point of the bulk phase. The potential and applicability of the GC-kMC are further shown with the correct description of the heat of adsorption and the pressure tensor of the adsorbed phase.

Dosimetric verification and clinical evaluation of a new commercially available Monte Carlo-based dose algorithm for application in stereotactic body radiation therapy (SBRT) treatment planning

NASA Astrophysics Data System (ADS)

Fragoso, Margarida; Wen, Ning; Kumar, Sanath; Liu, Dezhi; Ryu, Samuel; Movsas, Benjamin; Munther, Ajlouni; Chetty, Indrin J.

2010-08-01

Modern cancer treatment techniques, such as intensity-modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT), have greatly increased the demand for more accurate treatment planning (structure definition, dose calculation, etc) and dose delivery. The ability to use fast and accurate Monte Carlo (MC)-based dose calculations within a commercial treatment planning system (TPS) in the clinical setting is now becoming more of a reality. This study describes the dosimetric verification and initial clinical evaluation of a new commercial MC-based photon beam dose calculation algorithm, within the iPlan v.4.1 TPS (BrainLAB AG, Feldkirchen, Germany). Experimental verification of the MC photon beam model was performed with film and ionization chambers in water phantoms and in heterogeneous solid-water slabs containing bone and lung-equivalent materials for a 6 MV photon beam from a Novalis (BrainLAB) linear accelerator (linac) with a micro-multileaf collimator (m3 MLC). The agreement between calculated and measured dose distributions in the water phantom verification tests was, on average, within 2%/1 mm (high dose/high gradient) and was within ±4%/2 mm in the heterogeneous slab geometries. Example treatment plans in the lung show significant differences between the MC and one-dimensional pencil beam (PB) algorithms within iPlan, especially for small lesions in the lung, where electronic disequilibrium effects are emphasized. Other user-specific features in the iPlan system, such as options to select dose to water or dose to medium, and the mean variance level, have been investigated. Timing results for typical lung treatment plans show the total computation time (including that for processing and I/O) to be less than 10 min for 1-2% mean variance (running on a single PC with 8 Intel Xeon X5355 CPUs, 2.66 GHz). Overall, the iPlan MC algorithm is demonstrated to be an accurate and efficient dose algorithm, incorporating robust tools for MC-based SBRT treatment planning in the routine clinical setting.

A Practical Cone-beam CT Scatter Correction Method with Optimized Monte Carlo Simulations for Image-Guided Radiation Therapy

PubMed Central

Xu, Yuan; Bai, Ti; Yan, Hao; Ouyang, Luo; Pompos, Arnold; Wang, Jing; Zhou, Linghong; Jiang, Steve B.; Jia, Xun

2015-01-01

Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 HU to 3 HU and from 78 HU to 9 HU in the full-fan and the half-fan cases, respectively. In both the phantom and the patient cases, image artifacts caused by scatter, such as ring artifacts around the bowtie area, were reduced. With all the techniques employed, we achieved computation time of less than 30 sec including the time for both the scatter estimation and CBCT reconstruction steps. The efficacy of our method and its high computational efficiency make our method attractive for clinical use. PMID:25860299

PyMC: Bayesian Stochastic Modelling in Python

PubMed Central

Patil, Anand; Huard, David; Fonnesbeck, Christopher J.

2010-01-01

This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques. PMID:21603108

Monte Carlo Simulations: Number of Iterations and Accuracy

DTIC Science & Technology

2015-07-01

iterations because of its added complexity compared to the WM . We recommend that the WM be used for a priori estimates of the number of MC ...inaccurate.15 Although the WM and the WSM have generally proven useful in estimating the number of MC iterations and addressing the accuracy of the MC ...Theorem 3 3. A Priori Estimate of Number of MC Iterations 7 4. MC Result Accuracy 11 5. Using Percentage Error of the Mean to Estimate Number of MC

A Comparison of Experimental EPMA Data and Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2004-01-01

Monte Carlo (MC) modeling shows excellent prospects for simulating electron scattering and x-ray emission from complex geometries, and can be compared to experimental measurements using electron-probe microanalysis (EPMA) and phi(rho z) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been used to develop phi(rho z) correction algorithms. The accuracy of MC calculations obtained using the NIST, WinCasino, WinXray, and Penelope MC packages will be evaluated relative to these experimental data. There is additional information contained in the extended abstract.

Coupled reactors analysis: New needs and advances using Monte Carlo methodology

DOE PAGES

Aufiero, M.; Palmiotti, G.; Salvatores, M.; ...

2016-08-20

Coupled reactors and the coupling features of large or heterogeneous core reactors can be investigated with the Avery theory that allows a physics understanding of the main features of these systems. However, the complex geometries that are often encountered in association with coupled reactors, require a detailed geometry description that can be easily provided by modern Monte Carlo (MC) codes. This implies a MC calculation of the coupling parameters defined by Avery and of the sensitivity coefficients that allow further detailed physics analysis. The results presented in this paper show that the MC code SERPENT has been successfully modifed tomore » meet the required capabilities.« less

Top Quark Mass Calibration for Monte Carlo Event Generators

NASA Astrophysics Data System (ADS)

Butenschoen, Mathias; Dehnadi, Bahman; Hoang, André H.; Mateu, Vicent; Preisser, Moritz; Stewart, Iain W.

2016-12-01

The most precise top quark mass measurements use kinematic reconstruction methods, determining the top mass parameter of a Monte Carlo event generator mtMC. Because of hadronization and parton-shower dynamics, relating mtMC to a field theory mass is difficult. We present a calibration procedure to determine this relation using hadron level QCD predictions for observables with kinematic mass sensitivity. Fitting e+e- 2-jettiness calculations at next-to-leading-logarithmic and next-to-next-to-leading-logarithmic order to pythia 8.205, mtMC differs from the pole mass by 900 and 600 MeV, respectively, and agrees with the MSR mass within uncertainties, mtMC≃mt,1 GeV MSR .

Kinetic Monte Carlo (kMC) simulation of carbon co-implant on pre-amorphization process.

PubMed

Park, Soonyeol; Cho, Bumgoo; Yang, Seungsu; Won, Taeyoung

2010-05-01

We report our kinetic Monte Carlo (kMC) study of the effect of carbon co-implant on the pre-amorphization implant (PAL) process. We employed BCA (Binary Collision Approximation) approach for the acquisition of the initial as-implant dopant profile and kMC method for the simulation of diffusion process during the annealing process. The simulation results implied that carbon co-implant suppresses the boron diffusion due to the recombination with interstitials. Also, we could compare the boron diffusion with carbon diffusion by calculating carbon reaction with interstitial. And we can find that boron diffusion is affected from the carbon co-implant energy by enhancing the trapping of interstitial between boron and interstitial.

Gas-surface interactions using accommodation coefficients for a dilute and a dense gas in a micro- or nanochannel: heat flux predictions using combined molecular dynamics and Monte Carlo techniques.

PubMed

Nedea, S V; van Steenhoven, A A; Markvoort, A J; Spijker, P; Giordano, D

2014-05-01

The influence of gas-surface interactions of a dilute gas confined between two parallel walls on the heat flux predictions is investigated using a combined Monte Carlo (MC) and molecular dynamics (MD) approach. The accommodation coefficients are computed from the temperature of incident and reflected molecules in molecular dynamics and used as effective coefficients in Maxwell-like boundary conditions in Monte Carlo simulations. Hydrophobic and hydrophilic wall interactions are studied, and the effect of the gas-surface interaction potential on the heat flux and other characteristic parameters like density and temperature is shown. The heat flux dependence on the accommodation coefficient is shown for different fluid-wall mass ratios. We find that the accommodation coefficient is increasing considerably when the mass ratio is decreased. An effective map of the heat flux depending on the accommodation coefficient is given and we show that MC heat flux predictions using Maxwell boundary conditions based on the accommodation coefficient give good results when compared to pure molecular dynamics heat predictions. The accommodation coefficients computed for a dilute gas for different gas-wall interaction parameters and mass ratios are transferred to compute the heat flux predictions for a dense gas. Comparison of the heat fluxes derived using explicit MD, MC with Maxwell-like boundary conditions based on the accommodation coefficients, and pure Maxwell boundary conditions are discussed. A map of the heat flux dependence on the accommodation coefficients for a dense gas, and the effective accommodation coefficients for different gas-wall interactions are given. In the end, this approach is applied to study the gas-surface interactions of argon and xenon molecules on a platinum surface. The derived accommodation coefficients are compared with values of experimental results.

Validation of total skin electron irradiation (TSEI) technique dosimetry data by Monte Carlo simulation

PubMed Central

Borzov, Egor; Daniel, Shahar; Bar‐Deroma, Raquel

2016-01-01

Total skin electron irradiation (TSEI) is a complex technique which requires many nonstandard measurements and dosimetric procedures. The purpose of this work was to validate measured dosimetry data by Monte Carlo (MC) simulations using EGSnrc‐based codes (BEAMnrc and DOSXYZnrc). Our MC simulations consisted of two major steps. In the first step, the incident electron beam parameters (energy spectrum, FWHM, mean angular spread) were adjusted to match the measured data (PDD and profile) at SSD=100 cm for an open field. In the second step, these parameters were used to calculate dose distributions at the treatment distance of 400 cm. MC simulations of dose distributions from single and dual fields at the treatment distance were performed in a water phantom. Dose distribution from the full treatment with six dual fields was simulated in a CT‐based anthropomorphic phantom. MC calculations were compared to the available set of measurements used in clinical practice. For one direct field, MC calculated PDDs agreed within 3%/1 mm with the measurements, and lateral profiles agreed within 3% with the measured data. For the OF, the measured and calculated results were within 2% agreement. The optimal angle of 17° was confirmed for the dual field setup. Dose distribution from the full treatment with six dual fields was simulated in a CT‐based anthropomorphic phantom. The MC‐calculated multiplication factor (B12‐factor), which relates the skin dose for the whole treatment to the dose from one calibration field, for setups with and without degrader was 2.9 and 2.8, respectively. The measured B12‐factor was 2.8 for both setups. The difference between calculated and measured values was within 3.5%. It was found that a degrader provides more homogeneous dose distribution. The measured X‐ray contamination for the full treatment was 0.4%; this is compared to the 0.5% X‐ray contamination obtained with the MC calculation. Feasibility of MC simulation in an anthropomorphic phantom for a full TSEI treatment was proved and is reported for the first time in the literature. The results of our MC calculations were found to be in general agreement with the measurements, providing a promising tool for further studies of dose distribution calculations in TSEI. PACS number(s): 87.10. Rt, 87.55.K, 87.55.ne PMID:27455502

Development of accelerated Raman and fluorescent Monte Carlo method

NASA Astrophysics Data System (ADS)

Dumont, Alexander P.; Patil, Chetan

2018-02-01

Monte Carlo (MC) modeling of photon propagation in turbid media is an essential tool for understanding optical interactions between light and tissue. Insight gathered from outputs of MC models assists in mapping between detected optical signals and bulk tissue optical properties, and as such, has proven useful for inverse calculations of tissue composition and optimization of the design of optical probes. MC models of Raman scattering have previously been implemented without consideration to background autofluorescence, despite its presence in raw measurements. Modeling both Raman and fluorescence profiles at high spectral resolution requires a significant increase in computation, but is more appropriate for investigating issues such as detection limits. We present a new Raman Fluorescence MC model developed atop an existing GPU parallelized MC framework that can run more than 300x times faster than CPU methods. The robust acceleration allows for the efficient production of both Raman and fluorescence outputs from the MC model. In addition, this model can handle arbitrary sample morphologies of excitation and collection geometries to more appropriately mimic experimental settings. We will present the model framework and initial results.

A model for the accurate computation of the lateral scattering of protons in water

NASA Astrophysics Data System (ADS)

Bellinzona, E. V.; Ciocca, M.; Embriaco, A.; Ferrari, A.; Fontana, A.; Mairani, A.; Parodi, K.; Rotondi, A.; Sala, P.; Tessonnier, T.

2016-02-01

A pencil beam model for the calculation of the lateral scattering in water of protons for any therapeutic energy and depth is presented. It is based on the full Molière theory, taking into account the energy loss and the effects of mixtures and compounds. Concerning the electromagnetic part, the model has no free parameters and is in very good agreement with the FLUKA Monte Carlo (MC) code. The effects of the nuclear interactions are parametrized with a two-parameter tail function, adjusted on MC data calculated with FLUKA. The model, after the convolution with the beam and the detector response, is in agreement with recent proton data in water from HIT. The model gives results with the same accuracy of the MC codes based on Molière theory, with a much shorter computing time.

A model for the accurate computation of the lateral scattering of protons in water.

PubMed

Bellinzona, E V; Ciocca, M; Embriaco, A; Ferrari, A; Fontana, A; Mairani, A; Parodi, K; Rotondi, A; Sala, P; Tessonnier, T

2016-02-21

A pencil beam model for the calculation of the lateral scattering in water of protons for any therapeutic energy and depth is presented. It is based on the full Molière theory, taking into account the energy loss and the effects of mixtures and compounds. Concerning the electromagnetic part, the model has no free parameters and is in very good agreement with the FLUKA Monte Carlo (MC) code. The effects of the nuclear interactions are parametrized with a two-parameter tail function, adjusted on MC data calculated with FLUKA. The model, after the convolution with the beam and the detector response, is in agreement with recent proton data in water from HIT. The model gives results with the same accuracy of the MC codes based on Molière theory, with a much shorter computing time.

Efficiency in nonequilibrium molecular dynamics Monte Carlo simulations

DOE PAGES

Radak, Brian K.; Roux, Benoît

2016-10-07

Hybrid algorithms combining nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) offer a powerful avenue for improving the sampling efficiency of computer simulations of complex systems. These neMD/MC algorithms are also increasingly finding use in applications where conventional approaches are impractical, such as constant-pH simulations with explicit solvent. However, selecting an optimal nonequilibrium protocol for maximum efficiency often represents a non-trivial challenge. This work evaluates the efficiency of a broad class of neMD/MC algorithms and protocols within the theoretical framework of linear response theory. The approximations are validated against constant pH-MD simulations and shown to provide accurate predictions of neMD/MC performance.more » An assessment of a large set of protocols confirms (both theoretically and empirically) that a linear work protocol gives the best neMD/MC performance. Lastly, a well-defined criterion for optimizing the time parameters of the protocol is proposed and demonstrated with an adaptive algorithm that improves the performance on-the-fly with minimal cost.« less

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Souris, Kevin, E-mail: kevin.souris@uclouvain.be; Lee, John Aldo; Sterpin, Edmond

2016-04-15

Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithmmore » of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.« less

SU-E-T-503: IMRT Optimization Using Monte Carlo Dose Engine: The Effect of Statistical Uncertainty.

PubMed

Tian, Z; Jia, X; Graves, Y; Uribe-Sanchez, A; Jiang, S

2012-06-01

With the development of ultra-fast GPU-based Monte Carlo (MC) dose engine, it becomes clinically realistic to compute the dose-deposition coefficients (DDC) for IMRT optimization using MC simulation. However, it is still time-consuming if we want to compute DDC with small statistical uncertainty. This work studies the effects of the statistical error in DDC matrix on IMRT optimization. The MC-computed DDC matrices are simulated here by adding statistical uncertainties at a desired level to the ones generated with a finite-size pencil beam algorithm. A statistical uncertainty model for MC dose calculation is employed. We adopt a penalty-based quadratic optimization model and gradient descent method to optimize fluence map and then recalculate the corresponding actual dose distribution using the noise-free DDC matrix. The impacts of DDC noise are assessed in terms of the deviation of the resulted dose distributions. We have also used a stochastic perturbation theory to theoretically estimate the statistical errors of dose distributions on a simplified optimization model. A head-and-neck case is used to investigate the perturbation to IMRT plan due to MC's statistical uncertainty. The relative errors of the final dose distributions of the optimized IMRT are found to be much smaller than those in the DDC matrix, which is consistent with our theoretical estimation. When history number is decreased from 108 to 106, the dose-volume-histograms are still very similar to the error-free DVHs while the error in DDC is about 3.8%. The results illustrate that the statistical errors in the DDC matrix have a relatively small effect on IMRT optimization in dose domain. This indicates we can use relatively small number of histories to obtain the DDC matrix with MC simulation within a reasonable amount of time, without considerably compromising the accuracy of the optimized treatment plan. This work is supported by Varian Medical Systems through a Master Research Agreement. © 2012 American Association of Physicists in Medicine.

TH-E-BRE-09: TrueBeam Monte Carlo Absolute Dose Calculations Using Monitor Chamber Backscatter Simulations and Linac-Logged Target Current

DOE Office of Scientific and Technical Information (OSTI.GOV)

A, Popescu I; Lobo, J; Sawkey, D

2014-06-15

Purpose: To simulate and measure radiation backscattered into the monitor chamber of a TrueBeam linac; establish a rigorous framework for absolute dose calculations for TrueBeam Monte Carlo (MC) simulations through a novel approach, taking into account the backscattered radiation and the actual machine output during beam delivery; improve agreement between measured and simulated relative output factors. Methods: The ‘monitor backscatter factor’ is an essential ingredient of a well-established MC absolute dose formalism (the MC equivalent of the TG-51 protocol). This quantity was determined for the 6 MV, 6X FFF, and 10X FFF beams by two independent Methods: (1) MC simulationsmore » in the monitor chamber of the TrueBeam linac; (2) linac-generated beam record data for target current, logged for each beam delivery. Upper head MC simulations used a freelyavailable manufacturer-provided interface to a cloud-based platform, allowing use of the same head model as that used to generate the publicly-available TrueBeam phase spaces, without revealing the upper head design. The MC absolute dose formalism was expanded to allow direct use of target current data. Results: The relation between backscatter, number of electrons incident on the target for one monitor unit, and MC absolute dose was analyzed for open fields, as well as a jaw-tracking VMAT plan. The agreement between the two methods was better than 0.15%. It was demonstrated that the agreement between measured and simulated relative output factors improves across all field sizes when backscatter is taken into account. Conclusion: For the first time, simulated monitor chamber dose and measured target current for an actual TrueBeam linac were incorporated in the MC absolute dose formalism. In conjunction with the use of MC inputs generated from post-delivery trajectory-log files, the present method allows accurate MC dose calculations, without resorting to any of the simplifying assumptions previously made in the TrueBeam MC literature. This work has been partially funded by Varian Medical Systems.« less

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

Dosimetric investigation of proton therapy on CT-based patient data using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Chongsan, T.; Liamsuwan, T.; Tangboonduangjit, P.

2016-03-01

The aim of radiotherapy is to deliver high radiation dose to the tumor with low radiation dose to healthy tissues. Protons have Bragg peaks that give high radiation dose to the tumor but low exit dose or dose tail. Therefore, proton therapy is promising for treating deep- seated tumors and tumors locating close to organs at risk. Moreover, the physical characteristic of protons is suitable for treating cancer in pediatric patients. This work developed a computational platform for calculating proton dose distribution using the Monte Carlo (MC) technique and patient's anatomical data. The studied case is a pediatric patient with a primary brain tumor. PHITS will be used for MC simulation. Therefore, patient-specific CT-DICOM files were converted to the PHITS input. A MATLAB optimization program was developed to create a beam delivery control file for this study. The optimization program requires the proton beam data. All these data were calculated in this work using analytical formulas and the calculation accuracy was tested, before the beam delivery control file is used for MC simulation. This study will be useful for researchers aiming to investigate proton dose distribution in patients but do not have access to proton therapy machines.

Proton therapy treatment monitoring with the DoPET system: activity range, positron emitters evaluation and comparison with Monte Carlo predictions

NASA Astrophysics Data System (ADS)

Muraro, S.; Battistoni, G.; Belcari, N.; Bisogni, M. G.; Camarlinghi, N.; Cristoforetti, L.; Del Guerra, A.; Ferrari, A.; Fracchiolla, F.; Morrocchi, M.; Righetto, R.; Sala, P.; Schwarz, M.; Sportelli, G.; Topi, A.; Rosso, V.

2017-12-01

Ion beam irradiations can deliver conformal dose distributions minimizing damage to healthy tissues thanks to their characteristic dose profiles. Nevertheless, the location of the Bragg peak can be affected by different sources of range uncertainties: a critical issue is the treatment verification. During the treatment delivery, nuclear interactions between the ions and the irradiated tissues generate β+ emitters: the detection of this activity signal can be used to perform the treatment monitoring if an expected activity distribution is available for comparison. Monte Carlo (MC) codes are widely used in the particle therapy community to evaluate the radiation transport and interaction with matter. In this work, FLUKA MC code was used to simulate the experimental conditions of irradiations performed at the Proton Therapy Center in Trento (IT). Several mono-energetic pencil beams were delivered on phantoms mimicking human tissues. The activity signals were acquired with a PET system (DoPET) based on two planar heads, and designed to be installed along the beam line to acquire data also during the irradiation. Different acquisitions are analyzed and compared with the MC predictions, with a special focus on validating the PET detectors response for activity range verification.

SU-E-T-493: Accelerated Monte Carlo Methods for Photon Dosimetry Using a Dual-GPU System and CUDA.

PubMed

Liu, T; Ding, A; Xu, X

2012-06-01

To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that accelerates dose calculations on a dual-GPU system. We simulated a clinical case of prostate cancer treatment. A voxelized abdomen phantom derived from 120 CT slices was used containing 218×126×60 voxels, and a GE LightSpeed 16-MDCT scanner was modeled. A CPU version of the MC code was first developed in C++ and tested on Intel Xeon X5660 2.8GHz CPU, then it was translated into GPU version using CUDA C 4.1 and run on a dual Tesla m 2 090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy- and material- dependent cross-sections. Double-precision floating point format was used for accuracy. Doses to the rectum, prostate, bladder and femoral heads were calculated. When running on a single GPU, the MC GPU code was found to be ×19 times faster than the CPU code and ×42 times faster than MCNPX. These speedup factors were doubled on the dual-GPU system. The dose Result was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. A GPU-based MC code was developed for dose calculations using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual-GPU system. © 2012 American Association of Physicists in Medicine.

Estimation of absorbed doses from paediatric cone-beam CT scans: MOSFET measurements and Monte Carlo simulations.

PubMed

Kim, Sangroh; Yoshizumi, Terry T; Toncheva, Greta; Frush, Donald P; Yin, Fang-Fang

2010-03-01

The purpose of this study was to establish a dose estimation tool with Monte Carlo (MC) simulations. A 5-y-old paediatric anthropomorphic phantom was computed tomography (CT) scanned to create a voxelised phantom and used as an input for the abdominal cone-beam CT in a BEAMnrc/EGSnrc MC system. An X-ray tube model of the Varian On-Board Imager((R)) was built in the MC system. To validate the model, the absorbed doses at each organ location for standard-dose and low-dose modes were measured in the physical phantom with MOSFET detectors; effective doses were also calculated. In the results, the MC simulations were comparable to the MOSFET measurements. This voxelised phantom approach could produce a more accurate dose estimation than the stylised phantom method. This model can be easily applied to multi-detector CT dosimetry.

Monte Carlo simulation of inverse geometry x-ray fluoroscopy using a modified MC-GPU framework

PubMed Central

Dunkerley, David A. P.; Tomkowiak, Michael T.; Slagowski, Jordan M.; McCabe, Bradley P.; Funk, Tobias; Speidel, Michael A.

2015-01-01

Scanning-Beam Digital X-ray (SBDX) is a technology for low-dose fluoroscopy that employs inverse geometry x-ray beam scanning. To assist with rapid modeling of inverse geometry x-ray systems, we have developed a Monte Carlo (MC) simulation tool based on the MC-GPU framework. MC-GPU version 1.3 was modified to implement a 2D array of focal spot positions on a plane, with individually adjustable x-ray outputs, each producing a narrow x-ray beam directed toward a stationary photon-counting detector array. Geometric accuracy and blurring behavior in tomosynthesis reconstructions were evaluated from simulated images of a 3D arrangement of spheres. The artifact spread function from simulation agreed with experiment to within 1.6% (rRMSD). Detected x-ray scatter fraction was simulated for two SBDX detector geometries and compared to experiments. For the current SBDX prototype (10.6 cm wide by 5.3 cm tall detector), x-ray scatter fraction measured 2.8–6.4% (18.6–31.5 cm acrylic, 100 kV), versus 2.1–4.5% in MC simulation. Experimental trends in scatter versus detector size and phantom thickness were observed in simulation. For dose evaluation, an anthropomorphic phantom was imaged using regular and regional adaptive exposure (RAE) scanning. The reduction in kerma-area-product resulting from RAE scanning was 45% in radiochromic film measurements, versus 46% in simulation. The integral kerma calculated from TLD measurement points within the phantom was 57% lower when using RAE, versus 61% lower in simulation. This MC tool may be used to estimate tomographic blur, detected scatter, and dose distributions when developing inverse geometry x-ray systems. PMID:26113765

Monte Carlo simulation of inverse geometry x-ray fluoroscopy using a modified MC-GPU framework.

PubMed

Dunkerley, David A P; Tomkowiak, Michael T; Slagowski, Jordan M; McCabe, Bradley P; Funk, Tobias; Speidel, Michael A

2015-02-21

Scanning-Beam Digital X-ray (SBDX) is a technology for low-dose fluoroscopy that employs inverse geometry x-ray beam scanning. To assist with rapid modeling of inverse geometry x-ray systems, we have developed a Monte Carlo (MC) simulation tool based on the MC-GPU framework. MC-GPU version 1.3 was modified to implement a 2D array of focal spot positions on a plane, with individually adjustable x-ray outputs, each producing a narrow x-ray beam directed toward a stationary photon-counting detector array. Geometric accuracy and blurring behavior in tomosynthesis reconstructions were evaluated from simulated images of a 3D arrangement of spheres. The artifact spread function from simulation agreed with experiment to within 1.6% (rRMSD). Detected x-ray scatter fraction was simulated for two SBDX detector geometries and compared to experiments. For the current SBDX prototype (10.6 cm wide by 5.3 cm tall detector), x-ray scatter fraction measured 2.8-6.4% (18.6-31.5 cm acrylic, 100 kV), versus 2.1-4.5% in MC simulation. Experimental trends in scatter versus detector size and phantom thickness were observed in simulation. For dose evaluation, an anthropomorphic phantom was imaged using regular and regional adaptive exposure (RAE) scanning. The reduction in kerma-area-product resulting from RAE scanning was 45% in radiochromic film measurements, versus 46% in simulation. The integral kerma calculated from TLD measurement points within the phantom was 57% lower when using RAE, versus 61% lower in simulation. This MC tool may be used to estimate tomographic blur, detected scatter, and dose distributions when developing inverse geometry x-ray systems.

Toward high-efficiency and detailed Monte Carlo simulation study of the granular flow spallation target

NASA Astrophysics Data System (ADS)

Cai, Han-Jie; Zhang, Zhi-Lei; Fu, Fen; Li, Jian-Yang; Zhang, Xun-Chao; Zhang, Ya-Ling; Yan, Xue-Song; Lin, Ping; Xv, Jian-Ya; Yang, Lei

2018-02-01

The dense granular flow spallation target is a new target concept chosen for the Accelerator-Driven Subcritical (ADS) project in China. For the R&D of this kind of target concept, a dedicated Monte Carlo (MC) program named GMT was developed to perform the simulation study of the beam-target interaction. Owing to the complexities of the target geometry, the computational cost of the MC simulation of particle tracks is highly expensive. Thus, improvement of computational efficiency will be essential for the detailed MC simulation studies of the dense granular target. Here we present the special design of the GMT program and its high efficiency performance. In addition, the speedup potential of the GPU-accelerated spallation models is discussed.

Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr

2015-12-31

The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problemmore » are presented.« less

McSKY: A hybrid Monte-Carlo lime-beam code for shielded gamma skyshine calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shultis, J.K.; Faw, R.E.; Stedry, M.H.

1994-07-01

McSKY evaluates skyshine dose from an isotropic, monoenergetic, point photon source collimated into either a vertical cone or a vertical structure with an N-sided polygon cross section. The code assumes an overhead shield of two materials, through the user can specify zero shield thickness for an unshielded calculation. The code uses a Monte-Carlo algorithm to evaluate transport through source shields and the integral line source to describe photon transport through the atmosphere. The source energy must be between 0.02 and 100 MeV. For heavily shielded sources with energies above 20 MeV, McSKY results must be used cautiously, especially at detectormore » locations near the source.« less

SU-E-T-491: Importance of Energy Dependent Protons Per MU Calibration Factors in IMPT Dose Calculations Using Monte Carlo Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Randeniya, S; Mirkovic, D; Titt, U

2014-06-01

Purpose: In intensity modulated proton therapy (IMPT), energy dependent, protons per monitor unit (MU) calibration factors are important parameters that determine absolute dose values from energy deposition data obtained from Monte Carlo (MC) simulations. Purpose of this study was to assess the sensitivity of MC-computed absolute dose distributions to the protons/MU calibration factors in IMPT. Methods: A “verification plan” (i.e., treatment beams applied individually to water phantom) of a head and neck patient plan was calculated using MC technique. The patient plan had three beams; one posterior-anterior (PA); two anterior oblique. Dose prescription was 66 Gy in 30 fractions. Ofmore » the total MUs, 58% was delivered in PA beam, 25% and 17% in other two. Energy deposition data obtained from the MC simulation were converted to Gy using energy dependent protons/MU calibrations factors obtained from two methods. First method is based on experimental measurements and MC simulations. Second is based on hand calculations, based on how many ion pairs were produced per proton in the dose monitor and how many ion pairs is equal to 1 MU (vendor recommended method). Dose distributions obtained from method one was compared with those from method two. Results: Average difference of 8% in protons/MU calibration factors between method one and two converted into 27 % difference in absolute dose values for PA beam; although dose distributions preserved the shape of 3D dose distribution qualitatively, they were different quantitatively. For two oblique beams, significant difference in absolute dose was not observed. Conclusion: Results demonstrate that protons/MU calibration factors can have a significant impact on absolute dose values in IMPT depending on the fraction of MUs delivered. When number of MUs increases the effect due to the calibration factors amplify. In determining protons/MU calibration factors, experimental method should be preferred in MC dose calculations. Research supported by National Cancer Institute grant P01CA021239.« less

SU-F-T-81: Treating Nose Skin Using Energy and Intensity Modulated Electron Beams with Monte Carlo Based Dose Calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, L; Fan, J; Eldib, A

Purpose: Treating nose skin with an electron beam is of a substantial challenge due to uneven nose surfaces and tissue heterogeneity, and consequently could have a great uncertainty of dose accuracy on the target. This work explored the method using Monte Carlo (MC)-based energy and intensity modulated electron radiotherapy (MERT), which would be delivered with a photon MLC in a standard medical linac (Artiste). Methods: The traditional treatment on the nose skin involves the usage of a bolus, often with a single energy electron beam. This work avoided using the bolus, and utilized mixed energies of electron beams. An in-housemore » developed Monte Carlo (MC)-based dose calculation/optimization planning system was employed for treatment planning. Phase space data (6, 9, 12 and 15 MeV) were used as an input source for MC dose calculations for the linac. To reduce the scatter-caused penumbra, a short SSD (61 cm) was used. A clinical case of the nose skin, which was previously treated with a single 9 MeV electron beam, was replanned with the MERT method. The resultant dose distributions were compared with the plan previously clinically used. The dose volume histogram of the MERT plan is calculated to examine the coverage of the planning target volume (PTV) and critical structure doses. Results: The target coverage and conformality in the MERT plan are improved as compared to the conventional plan. The MERT can provide more sufficient target coverage and less normal tissue dose underneath the nose skin. Conclusion: Compared to the conventional treatment technique, using MERT for the nose skin treatment has shown the dosimetric advantages in the PTV coverage and conformality. In addition, this technique eliminates the necessity of the cutout and bolus, which makes the treatment more efficient and accurate.« less

A comparison of Monte-Carlo simulations using RESTRAX and McSTAS with experiment on IN14

NASA Astrophysics Data System (ADS)

Wildes, A. R.; S̆aroun, J.; Farhi, E.; Anderson, I.; Høghøj, P.; Brochier, A.

2000-03-01

Monte-Carlo simulations of a focusing supermirror guide after the monochromator on the IN14 cold neutron three-axis spectrometer, I.L.L. were carried out using the instrument simulation programs RESTRAX and McSTAS. The simulations were compared to experiment to check their accuracy. Comparisons of the flux ratios over both a 100 and a 1600 mm 2 area at the sample position compare well, and there is a very close agreement between simulation and experiment for the energy spread of the incident beam.

Modeling the migration of platinum nanoparticles on surfaces using a kinetic Monte Carlo approach

DOE PAGES

Li, Lin; Plessow, Philipp N.; Rieger, Michael; ...

2017-02-15

We propose a kinetic Monte Carlo (kMC) model for simulating the movement of platinum particles on supports, based on atom-by-atom diffusion on the surface of the particle. The proposed model was able to reproduce equilibrium cluster shapes predicted using Wulff-construction. The diffusivity of platinum particles was simulated both purely based on random motion and assisted using an external field that causes a drift velocity. The overall particle diffusivity increases with temperature; however, the extracted activation barrier appears to be temperature independent. Additionally, this barrier was found to increase with particle size, as well as, with the adhesion between the particlemore » and the support.« less

OpenMC In Situ Source Convergence Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aldrich, Garrett Allen; Dutta, Soumya; Woodring, Jonathan Lee

2016-05-07

We designed and implemented an in situ version of particle source convergence for the OpenMC particle transport simulator. OpenMC is a Monte Carlo based-particle simulator for neutron criticality calculations. For the transport simulation to be accurate, source particles must converge on a spatial distribution. Typically, convergence is obtained by iterating the simulation by a user-settable, fixed number of steps, and it is assumed that convergence is achieved. We instead implement a method to detect convergence, using the stochastic oscillator for identifying convergence of source particles based on their accumulated Shannon Entropy. Using our in situ convergence detection, we are ablemore » to detect and begin tallying results for the full simulation once the proper source distribution has been confirmed. Our method ensures that the simulation is not started too early, by a user setting too optimistic parameters, or too late, by setting too conservative a parameter.« less

Quantitative analysis of optical properties of flowing blood using a photon-cell interactive Monte Carlo code: effects of red blood cells' orientation on light scattering.

PubMed

Sakota, Daisuke; Takatani, Setsuo

2012-05-01

Optical properties of flowing blood were analyzed using a photon-cell interactive Monte Carlo (pciMC) model with the physical properties of the flowing red blood cells (RBCs) such as cell size, shape, refractive index, distribution, and orientation as the parameters. The scattering of light by flowing blood at the He-Ne laser wavelength of 632.8 nm was significantly affected by the shear rate. The light was scattered more in the direction of flow as the flow rate increased. Therefore, the light intensity transmitted forward in the direction perpendicular to flow axis decreased. The pciMC model can duplicate the changes in the photon propagation due to moving RBCs with various orientations. The resulting RBC's orientation that best simulated the experimental results was with their long axis perpendicular to the direction of blood flow. Moreover, the scattering probability was dependent on the orientation of the RBCs. Finally, the pciMC code was used to predict the hematocrit of flowing blood with accuracy of approximately 1.0 HCT%. The photon-cell interactive Monte Carlo (pciMC) model can provide optical properties of flowing blood and will facilitate the development of the non-invasive monitoring of blood in extra corporeal circulatory systems.

NOTE: Monte Carlo evaluation of kerma in an HDR brachytherapy bunker

NASA Astrophysics Data System (ADS)

Pérez-Calatayud, J.; Granero, D.; Ballester, F.; Casal, E.; Crispin, V.; Puchades, V.; León, A.; Verdú, G.

2004-12-01

In recent years, the use of high dose rate (HDR) after-loader machines has greatly increased due to the shift from traditional Cs-137/Ir-192 low dose rate (LDR) to HDR brachytherapy. The method used to calculate the required concrete and, where appropriate, lead shielding in the door is based on analytical methods provided by documents published by the ICRP, the IAEA and the NCRP. The purpose of this study is to perform a more realistic kerma evaluation at the entrance maze door of an HDR bunker using the Monte Carlo code GEANT4. The Monte Carlo results were validated experimentally. The spectrum at the maze entrance door, obtained with Monte Carlo, has an average energy of about 110 keV, maintaining a similar value along the length of the maze. The comparison of results from the aforementioned values with the Monte Carlo ones shows that results obtained using the albedo coefficient from the ICRP document more closely match those given by the Monte Carlo method, although the maximum value given by MC calculations is 30% greater.

Validation of a Monte Carlo code system for grid evaluation with interference effect on Rayleigh scattering

NASA Astrophysics Data System (ADS)

Zhou, Abel; White, Graeme L.; Davidson, Rob

2018-02-01

Anti-scatter grids are commonly used in x-ray imaging systems to reduce scatter radiation reaching the image receptor. Anti-scatter grid performance and validation can be simulated through use of Monte Carlo (MC) methods. Our recently reported work has modified existing MC codes resulting in improved performance when simulating x-ray imaging. The aim of this work is to validate the transmission of x-ray photons in grids from the recently reported new MC codes against experimental results and results previously reported in other literature. The results of this work show that the scatter-to-primary ratio (SPR), the transmissions of primary (T p), scatter (T s), and total (T t) radiation determined using this new MC code system have strong agreement with the experimental results and the results reported in the literature. T p, T s, T t, and SPR determined in this new MC simulation code system are valid. These results also show that the interference effect on Rayleigh scattering should not be neglected in both mammographic and general grids’ evaluation. Our new MC simulation code system has been shown to be valid and can be used for analysing and evaluating the designs of grids.

Estimation of computed tomography dose index in cone beam computed tomography: MOSFET measurements and Monte Carlo simulations.

PubMed

Kim, Sangroh; Yoshizumi, Terry; Toncheva, Greta; Yoo, Sua; Yin, Fang-Fang; Frush, Donald

2010-05-01

To address the lack of accurate dose estimation method in cone beam computed tomography (CBCT), we performed point dose metal oxide semiconductor field-effect transistor (MOSFET) measurements and Monte Carlo (MC) simulations. A Varian On-Board Imager (OBI) was employed to measure point doses in the polymethyl methacrylate (PMMA) CT phantoms with MOSFETs for standard and low dose modes. A MC model of the OBI x-ray tube was developed using BEAMnrc/EGSnrc MC system and validated by the half value layer, x-ray spectrum and lateral and depth dose profiles. We compared the weighted computed tomography dose index (CTDIw) between MOSFET measurements and MC simulations. The CTDIw was found to be 8.39 cGy for the head scan and 4.58 cGy for the body scan from the MOSFET measurements in standard dose mode, and 1.89 cGy for the head and 1.11 cGy for the body in low dose mode, respectively. The CTDIw from MC compared well to the MOSFET measurements within 5% differences. In conclusion, a MC model for Varian CBCT has been established and this approach may be easily extended from the CBCT geometry to multi-detector CT geometry.

Applications of Monte Carlo method to nonlinear regression of rheological data

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

2018-02-01

In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

Monte Carlo-based QA for IMRT of head and neck cancers

NASA Astrophysics Data System (ADS)

Tang, F.; Sham, J.; Ma, C.-M.; Li, J.-S.

2007-06-01

It is well-known that the presence of large air cavity in a dense medium (or patient) introduces significant electronic disequilibrium when irradiated with megavoltage X-ray field. This condition may worsen by the possible use of tiny beamlets in intensity-modulated radiation therapy (IMRT). Commercial treatment planning systems (TPSs), in particular those based on the pencil-beam method, do not provide accurate dose computation for the lungs and other cavity-laden body sites such as the head and neck. In this paper we present the use of Monte Carlo (MC) technique for dose re-calculation of IMRT of head and neck cancers. In our clinic, a turn-key software system is set up for MC calculation and comparison with TPS-calculated treatment plans as part of the quality assurance (QA) programme for IMRT delivery. A set of 10 off-the-self PCs is employed as the MC calculation engine with treatment plan parameters imported from the TPS via a graphical user interface (GUI) which also provides a platform for launching remote MC simulation and subsequent dose comparison with the TPS. The TPS-segmented intensity maps are used as input for the simulation hence skipping the time-consuming simulation of the multi-leaf collimator (MLC). The primary objective of this approach is to assess the accuracy of the TPS calculations in the presence of air cavities in the head and neck whereas the accuracy of leaf segmentation is verified by fluence measurement using a fluoroscopic camera-based imaging device. This measurement can also validate the correct transfer of intensity maps to the record and verify system. Comparisons between TPS and MC calculations of 6 MV IMRT for typical head and neck treatments review regional consistency in dose distribution except at and around the sinuses where our pencil-beam-based TPS sometimes over-predicts the dose by up to 10%, depending on the size of the cavities. In addition, dose re-buildup of up to 4% is observed at the posterior nasopharyngeal mucosa for some treatments with heavily-weighted anterior fields.

ICF target 2D modeling using Monte Carlo SNB electron thermal transport in DRACO

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2016-10-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup diffusion electron thermal transport method is adapted into a Monte Carlo (MC) transport method to better model angular and long mean free path non-local effects. The MC model was first implemented in the 1D LILAC code to verify consistency with the iSNB model. Implementation of the MC SNB model in the 2D DRACO code enables higher fidelity non-local thermal transport modeling in 2D implosions such as polar drive experiments on NIF. The final step is to optimize the MC model by hybridizing it with a MC version of the iSNB diffusion method. The hybrid method will combine the efficiency of a diffusion method in intermediate mean free path regions with the accuracy of a transport method in long mean free path regions allowing for improved computational efficiency while maintaining accuracy. Work to date on the method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.

Monte Carlo simulations in radiotherapy dosimetry.

PubMed

Andreo, Pedro

2018-06-27

The use of the Monte Carlo (MC) method in radiotherapy dosimetry has increased almost exponentially in the last decades. Its widespread use in the field has converted this computer simulation technique in a common tool for reference and treatment planning dosimetry calculations. This work reviews the different MC calculations made on dosimetric quantities, like stopping-power ratios and perturbation correction factors required for reference ionization chamber dosimetry, as well as the fully realistic MC simulations currently available on clinical accelerators, detectors and patient treatment planning. Issues are raised that include the necessity for consistency in the data throughout the entire dosimetry chain in reference dosimetry, and how Bragg-Gray theory breaks down for small photon fields. Both aspects are less critical for MC treatment planning applications, but there are important constraints like tissue characterization and its patient-to-patient variability, which together with the conversion between dose-to-water and dose-to-tissue, are analysed in detail. Although these constraints are common to all methods and algorithms used in different types of treatment planning systems, they make uncertainties involved in MC treatment planning to still remain "uncertain".

Fermi gases with imaginary mass imbalance and the sign problem in Monte-Carlo calculations

NASA Astrophysics Data System (ADS)

Roscher, Dietrich; Braun, Jens; Chen, Jiunn-Wei; Drut, Joaquín E.

2014-05-01

Fermi gases in strongly coupled regimes are inherently challenging for many-body methods. Although progress has been made analytically, quantitative results require ab initio numerical approaches, such as Monte-Carlo (MC) calculations. However, mass-imbalanced and spin-imbalanced gases are not accessible to MC calculations due to the infamous sign problem. For finite spin imbalance, the problem can be circumvented using imaginary polarizations and analytic continuation, and large parts of the phase diagram then become accessible. We propose to apply this strategy to the mass-imbalanced case, which opens up the possibility to study the associated phase diagram with MC calculations. We perform a first mean-field analysis which suggests that zero-temperature studies, as well as detecting a potential (tri)critical point, are feasible.

Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

PubMed Central

Peter, Silvia; Modregger, Peter; Fix, Michael K.; Volken, Werner; Frei, Daniel; Manser, Peter; Stampanoni, Marco

2014-01-01

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging. PMID:24763652

Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy.

PubMed

Chi, Yujie; Tian, Zhen; Jia, Xun

2016-08-07

Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0.69-1.23 times for photon only transport.

Accelerated SPECT Monte Carlo Simulation Using Multiple Projection Sampling and Convolution-Based Forced Detection

NASA Astrophysics Data System (ADS)

Liu, Shaoying; King, Michael A.; Brill, Aaron B.; Stabin, Michael G.; Farncombe, Troy H.

2008-02-01

Monte Carlo (MC) is a well-utilized tool for simulating photon transport in single photon emission computed tomography (SPECT) due to its ability to accurately model physical processes of photon transport. As a consequence of this accuracy, it suffers from a relatively low detection efficiency and long computation time. One technique used to improve the speed of MC modeling is the effective and well-established variance reduction technique (VRT) known as forced detection (FD). With this method, photons are followed as they traverse the object under study but are then forced to travel in the direction of the detector surface, whereby they are detected at a single detector location. Another method, called convolution-based forced detection (CFD), is based on the fundamental idea of FD with the exception that detected photons are detected at multiple detector locations and determined with a distance-dependent blurring kernel. In order to further increase the speed of MC, a method named multiple projection convolution-based forced detection (MP-CFD) is presented. Rather than forcing photons to hit a single detector, the MP-CFD method follows the photon transport through the object but then, at each scatter site, forces the photon to interact with a number of detectors at a variety of angles surrounding the object. This way, it is possible to simulate all the projection images of a SPECT simulation in parallel, rather than as independent projections. The result of this is vastly improved simulation time as much of the computation load of simulating photon transport through the object is done only once for all projection angles. The results of the proposed MP-CFD method agrees well with the experimental data in measurements of point spread function (PSF), producing a correlation coefficient (r2) of 0.99 compared to experimental data. The speed of MP-CFD is shown to be about 60 times faster than a regular forced detection MC program with similar results.

Episcleral eye plaque dosimetry comparison for the Eye Physics EP917 using Plaque Simulator and Monte Carlo simulation

PubMed Central

Amoush, Ahmad; Wilkinson, Douglas A.

2015-01-01

This work is a comparative study of the dosimetry calculated by Plaque Simulator, a treatment planning system for eye plaque brachytherapy, to the dosimetry calculated using Monte Carlo simulation for an Eye Physics model EP917 eye plaque. Monte Carlo (MC) simulation using MCNPX 2.7 was used to calculate the central axis dose in water for an EP917 eye plaque fully loaded with 17 IsoAid Advantage  125I seeds. In addition, the dosimetry parameters Λ, gL(r), and F(r,θ) were calculated for the IsoAid Advantage model IAI‐125  125I seed and benchmarked against published data. Bebig Plaque Simulator (PS) v5.74 was used to calculate the central axis dose based on the AAPM Updated Task Group 43 (TG‐43U1) dose formalism. The calculated central axis dose from MC and PS was then compared. When the MC dosimetry parameters for the IsoAid Advantage  125I seed were compared with the consensus values, Λ agreed with the consensus value to within 2.3%. However, much larger differences were found between MC calculated gL(r) and F(r,θ) and the consensus values. The differences between MC‐calculated dosimetry parameters are much smaller when compared with recently published data. The differences between the calculated central axis absolute dose from MC and PS ranged from 5% to 10% for distances between 1 and 12 mm from the outer scleral surface. When the dosimetry parameters for the  125I seed from this study were used in PS, the calculated absolute central axis dose differences were reduced by 2.3% from depths of 4 to 12 mm from the outer scleral surface. We conclude that PS adequately models the central dose profile of this plaque using its defaults for the IsoAid model IAI‐125 at distances of 1 to 7 mm from the outer scleral surface. However, improved dose accuracy can be obtained by using updated dosimetry parameters for the IsoAid model IAI‐125  125I seed. PACS number: 87.55.K‐ PMID:26699577

Study on efficiency of time computation in x-ray imaging simulation base on Monte Carlo algorithm using graphics processing unit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Setiani, Tia Dwi, E-mail: tiadwisetiani@gmail.com; Suprijadi; Nuclear Physics and Biophysics Reaserch Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung Jalan Ganesha 10 Bandung, 40132

Monte Carlo (MC) is one of the powerful techniques for simulation in x-ray imaging. MC method can simulate the radiation transport within matter with high accuracy and provides a natural way to simulate radiation transport in complex systems. One of the codes based on MC algorithm that are widely used for radiographic images simulation is MC-GPU, a codes developed by Andrea Basal. This study was aimed to investigate the time computation of x-ray imaging simulation in GPU (Graphics Processing Unit) compared to a standard CPU (Central Processing Unit). Furthermore, the effect of physical parameters to the quality of radiographic imagesmore » and the comparison of image quality resulted from simulation in the GPU and CPU are evaluated in this paper. The simulations were run in CPU which was simulated in serial condition, and in two GPU with 384 cores and 2304 cores. In simulation using GPU, each cores calculates one photon, so, a large number of photon were calculated simultaneously. Results show that the time simulations on GPU were significantly accelerated compared to CPU. The simulations on the 2304 core of GPU were performed about 64 -114 times faster than on CPU, while the simulation on the 384 core of GPU were performed about 20 – 31 times faster than in a single core of CPU. Another result shows that optimum quality of images from the simulation was gained at the history start from 10{sup 8} and the energy from 60 Kev to 90 Kev. Analyzed by statistical approach, the quality of GPU and CPU images are relatively the same.« less

GATE Monte Carlo simulations for variations of an integrated PET/MR hybrid imaging system based on the Biograph mMR model

NASA Astrophysics Data System (ADS)

Aklan, B.; Jakoby, B. W.; Watson, C. C.; Braun, H.; Ritt, P.; Quick, H. H.

2015-06-01

A simulation toolkit, GATE (Geant4 Application for Tomographic Emission), was used to develop an accurate Monte Carlo (MC) simulation of a fully integrated 3T PET/MR hybrid imaging system (Siemens Biograph mMR). The PET/MR components of the Biograph mMR were simulated in order to allow a detailed study of variations of the system design on the PET performance, which are not easy to access and measure on a real PET/MR system. The 3T static magnetic field of the MR system was taken into account in all Monte Carlo simulations. The validation of the MC model was carried out against actual measurements performed on the PET/MR system by following the NEMA (National Electrical Manufacturers Association) NU 2-2007 standard. The comparison of simulated and experimental performance measurements included spatial resolution, sensitivity, scatter fraction, and count rate capability. The validated system model was then used for two different applications. The first application focused on investigating the effect of an extension of the PET field-of-view on the PET performance of the PET/MR system. The second application deals with simulating a modified system timing resolution and coincidence time window of the PET detector electronics in order to simulate time-of-flight (TOF) PET detection. A dedicated phantom was modeled to investigate the impact of TOF on overall PET image quality. Simulation results showed that the overall divergence between simulated and measured data was found to be less than 10%. Varying the detector geometry showed that the system sensitivity and noise equivalent count rate of the PET/MR system increased progressively with an increasing number of axial detector block rings, as to be expected. TOF-based PET reconstructions of the modeled phantom showed an improvement in signal-to-noise ratio and image contrast to the conventional non-TOF PET reconstructions. In conclusion, the validated MC simulation model of an integrated PET/MR system with an overall accuracy error of less than 10% can now be used for further MC simulation applications such as development of hardware components as well as for testing of new PET/MR software algorithms, such as assessment of point-spread function-based reconstruction algorithms.

A novel Monte Carlo algorithm for simulating crystals with McStas

NASA Astrophysics Data System (ADS)

Alianelli, L.; Sánchez del Río, M.; Felici, R.; Andersen, K. H.; Farhi, E.

2004-07-01

We developed an original Monte Carlo algorithm for the simulation of Bragg diffraction by mosaic, bent and gradient crystals. It has practical applications, as it can be used for simulating imperfect crystals (monochromators, analyzers and perhaps samples) in neutron ray-tracing packages, like McStas. The code we describe here provides a detailed description of the particle interaction with the microscopic homogeneous regions composing the crystal, therefore it can be used also for the calculation of quantities having a conceptual interest, as multiple scattering, or for the interpretation of experiments aiming at characterizing crystals, like diffraction topographs.

SimDoseCT: dose reporting software based on Monte Carlo simulation for a 320 detector-row cone-beam CT scanner and ICRP computational adult phantoms

NASA Astrophysics Data System (ADS)

Cros, Maria; Joemai, Raoul M. S.; Geleijns, Jacob; Molina, Diego; Salvadó, Marçal

2017-08-01

This study aims to develop and test software for assessing and reporting doses for standard patients undergoing computed tomography (CT) examinations in a 320 detector-row cone-beam scanner. The software, called SimDoseCT, is based on the Monte Carlo (MC) simulation code, which was developed to calculate organ doses and effective doses in ICRP anthropomorphic adult reference computational phantoms for acquisitions with the Aquilion ONE CT scanner (Toshiba). MC simulation was validated by comparing CTDI measurements within standard CT dose phantoms with results from simulation under the same conditions. SimDoseCT consists of a graphical user interface connected to a MySQL database, which contains the look-up-tables that were generated with MC simulations for volumetric acquisitions at different scan positions along the phantom using any tube voltage, bow tie filter, focal spot and nine different beam widths. Two different methods were developed to estimate organ doses and effective doses from acquisitions using other available beam widths in the scanner. A correction factor was used to estimate doses in helical acquisitions. Hence, the user can select any available protocol in the Aquilion ONE scanner for a standard adult male or female and obtain the dose results through the software interface. Agreement within 9% between CTDI measurements and simulations allowed the validation of the MC program. Additionally, the algorithm for dose reporting in SimDoseCT was validated by comparing dose results from this tool with those obtained from MC simulations for three volumetric acquisitions (head, thorax and abdomen). The comparison was repeated using eight different collimations and also for another collimation in a helical abdomen examination. The results showed differences of 0.1 mSv or less for absolute dose in most organs and also in the effective dose calculation. The software provides a suitable tool for dose assessment in standard adult patients undergoing CT examinations in a 320 detector-row cone-beam scanner.

SimDoseCT: dose reporting software based on Monte Carlo simulation for a 320 detector-row cone-beam CT scanner and ICRP computational adult phantoms.

PubMed

Cros, Maria; Joemai, Raoul M S; Geleijns, Jacob; Molina, Diego; Salvadó, Marçal

2017-07-17

This study aims to develop and test software for assessing and reporting doses for standard patients undergoing computed tomography (CT) examinations in a 320 detector-row cone-beam scanner. The software, called SimDoseCT, is based on the Monte Carlo (MC) simulation code, which was developed to calculate organ doses and effective doses in ICRP anthropomorphic adult reference computational phantoms for acquisitions with the Aquilion ONE CT scanner (Toshiba). MC simulation was validated by comparing CTDI measurements within standard CT dose phantoms with results from simulation under the same conditions. SimDoseCT consists of a graphical user interface connected to a MySQL database, which contains the look-up-tables that were generated with MC simulations for volumetric acquisitions at different scan positions along the phantom using any tube voltage, bow tie filter, focal spot and nine different beam widths. Two different methods were developed to estimate organ doses and effective doses from acquisitions using other available beam widths in the scanner. A correction factor was used to estimate doses in helical acquisitions. Hence, the user can select any available protocol in the Aquilion ONE scanner for a standard adult male or female and obtain the dose results through the software interface. Agreement within 9% between CTDI measurements and simulations allowed the validation of the MC program. Additionally, the algorithm for dose reporting in SimDoseCT was validated by comparing dose results from this tool with those obtained from MC simulations for three volumetric acquisitions (head, thorax and abdomen). The comparison was repeated using eight different collimations and also for another collimation in a helical abdomen examination. The results showed differences of 0.1 mSv or less for absolute dose in most organs and also in the effective dose calculation. The software provides a suitable tool for dose assessment in standard adult patients undergoing CT examinations in a 320 detector-row cone-beam scanner.

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

DOE PAGES

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

2017-12-22

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

A compression algorithm for the combination of PDF sets.

PubMed

Carrazza, Stefano; Latorre, José I; Rojo, Juan; Watt, Graeme

The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different groups, each of which comprises a relatively large number of either Hessian eigenvectors or Monte Carlo (MC) replicas. While many fixed-order and parton shower programs allow the evaluation of PDF uncertainties for a single PDF set at no additional CPU cost, this feature is not universal, and, moreover, the a posteriori combination of the predictions using at least three different PDF sets is still required. In this work, we present a strategy for the statistical combination of individual PDF sets, based on the MC representation of Hessian sets, followed by a compression algorithm for the reduction of the number of MC replicas. We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets. The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions. We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

Centrality measures highlight proton traps and access points to proton highways in kinetic Monte Carlo trajectories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krueger, Rachel A.; Haibach, Frederick G.; Fry, Dana L.

2015-04-21

A centrality measure based on the time of first returns rather than the number of steps is developed and applied to finding proton traps and access points to proton highways in the doped perovskite oxides: AZr{sub 0.875}D{sub 0.125}O{sub 3}, where A is Ba or Sr and the dopant D is Y or Al. The high centrality region near the dopant is wider in the SrZrO{sub 3} systems than the BaZrO{sub 3} systems. In the aluminum-doped systems, a region of intermediate centrality (secondary region) is found in a plane away from the dopant. Kinetic Monte Carlo (kMC) trajectories show that thismore » secondary region is an entry to fast conduction planes in the aluminum-doped systems in contrast to the highest centrality area near the dopant trap. The yttrium-doped systems do not show this secondary region because the fast conduction routes are in the same plane as the dopant and hence already in the high centrality trapped area. This centrality measure complements kMC by highlighting key areas in trajectories. The limiting activation barriers found via kMC are in very good agreement with experiments and related to the barriers to escape dopant traps.« less

Assessment of mean-field microkinetic models for CO methanation on stepped metal surfaces using accelerated kinetic Monte Carlo

NASA Astrophysics Data System (ADS)

Andersen, Mie; Plaisance, Craig P.; Reuter, Karsten

2017-10-01

First-principles screening studies aimed at predicting the catalytic activity of transition metal (TM) catalysts have traditionally been based on mean-field (MF) microkinetic models, which neglect the effect of spatial correlations in the adsorbate layer. Here we critically assess the accuracy of such models for the specific case of CO methanation over stepped metals by comparing to spatially resolved kinetic Monte Carlo (kMC) simulations. We find that the typical low diffusion barriers offered by metal surfaces can be significantly increased at step sites, which results in persisting correlations in the adsorbate layer. As a consequence, MF models may overestimate the catalytic activity of TM catalysts by several orders of magnitude. The potential higher accuracy of kMC models comes at a higher computational cost, which can be especially challenging for surface reactions on metals due to a large disparity in the time scales of different processes. In order to overcome this issue, we implement and test a recently developed algorithm for achieving temporal acceleration of kMC simulations. While the algorithm overall performs quite well, we identify some challenging cases which may lead to a breakdown of acceleration algorithms and discuss possible directions for future algorithm development.

Integration of OpenMC methods into MAMMOTH and Serpent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerby, Leslie; DeHart, Mark; Tumulak, Aaron

OpenMC, a Monte Carlo particle transport simulation code focused on neutron criticality calculations, contains several methods we wish to emulate in MAMMOTH and Serpent. First, research coupling OpenMC and the Multiphysics Object-Oriented Simulation Environment (MOOSE) has shown promising results. Second, the utilization of Functional Expansion Tallies (FETs) allows for a more efficient passing of multiphysics data between OpenMC and MOOSE. Both of these capabilities have been preliminarily implemented into Serpent. Results are discussed and future work recommended.

Optimization of GATE and PHITS Monte Carlo code parameters for uniform scanning proton beam based on simulation with FLUKA general-purpose code

NASA Astrophysics Data System (ADS)

Kurosu, Keita; Takashina, Masaaki; Koizumi, Masahiko; Das, Indra J.; Moskvin, Vadim P.

2014-10-01

Although three general-purpose Monte Carlo (MC) simulation tools: Geant4, FLUKA and PHITS have been used extensively, differences in calculation results have been reported. The major causes are the implementation of the physical model, preset value of the ionization potential or definition of the maximum step size. In order to achieve artifact free MC simulation, an optimized parameters list for each simulation system is required. Several authors have already proposed the optimized lists, but those studies were performed with a simple system such as only a water phantom. Since particle beams have a transport, interaction and electromagnetic processes during beam delivery, establishment of an optimized parameters-list for whole beam delivery system is therefore of major importance. The purpose of this study was to determine the optimized parameters list for GATE and PHITS using proton treatment nozzle computational model. The simulation was performed with the broad scanning proton beam. The influences of the customizing parameters on the percentage depth dose (PDD) profile and the proton range were investigated by comparison with the result of FLUKA, and then the optimal parameters were determined. The PDD profile and the proton range obtained from our optimized parameters list showed different characteristics from the results obtained with simple system. This led to the conclusion that the physical model, particle transport mechanics and different geometry-based descriptions need accurate customization in planning computational experiments for artifact-free MC simulation.

Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) to the steel process chain: case study.

PubMed

Bieda, Bogusław

2014-05-15

The purpose of the paper is to present the results of application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) data of Mittal Steel Poland (MSP) complex in Kraków, Poland. In order to assess the uncertainty, the software CrystalBall® (CB), which is associated with Microsoft® Excel spreadsheet model, is used. The framework of the study was originally carried out for 2005. The total production of steel, coke, pig iron, sinter, slabs from continuous steel casting (CSC), sheets from hot rolling mill (HRM) and blast furnace gas, collected in 2005 from MSP was analyzed and used for MC simulation of the LCI model. In order to describe random nature of all main products used in this study, normal distribution has been applied. The results of the simulation (10,000 trials) performed with the use of CB consist of frequency charts and statistical reports. The results of this study can be used as the first step in performing a full LCA analysis in the steel industry. Further, it is concluded that the stochastic approach is a powerful method for quantifying parameter uncertainty in LCA/LCI studies and it can be applied to any steel industry. The results obtained from this study can help practitioners and decision-makers in the steel production management. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiple Time-Step Dual-Hamiltonian Hybrid Molecular Dynamics — Monte Carlo Canonical Propagation Algorithm

PubMed Central

Weare, Jonathan; Dinner, Aaron R.; Roux, Benoît

2016-01-01

A multiple time-step integrator based on a dual Hamiltonian and a hybrid method combining molecular dynamics (MD) and Monte Carlo (MC) is proposed to sample systems in the canonical ensemble. The Dual Hamiltonian Multiple Time-Step (DHMTS) algorithm is based on two similar Hamiltonians: a computationally expensive one that serves as a reference and a computationally inexpensive one to which the workload is shifted. The central assumption is that the difference between the two Hamiltonians is slowly varying. Earlier work has shown that such dual Hamiltonian multiple time-step schemes effectively precondition nonlinear differential equations for dynamics by reformulating them into a recursive root finding problem that can be solved by propagating a correction term through an internal loop, analogous to RESPA. Of special interest in the present context, a hybrid MD-MC version of the DHMTS algorithm is introduced to enforce detailed balance via a Metropolis acceptance criterion and ensure consistency with the Boltzmann distribution. The Metropolis criterion suppresses the discretization errors normally associated with the propagation according to the computationally inexpensive Hamiltonian, treating the discretization error as an external work. Illustrative tests are carried out to demonstrate the effectiveness of the method. PMID:26918826

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

PubMed

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-07

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations

PubMed Central

Yang, Kecheng; Różycki, Bartosz; Cui, Fengchao; Shi, Ce; Chen, Wenduo; Li, Yunqi

2016-01-01

Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation. PMID:27227775

Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations.

PubMed

Yang, Kecheng; Różycki, Bartosz; Cui, Fengchao; Shi, Ce; Chen, Wenduo; Li, Yunqi

2016-01-01

Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.

SU-E-T-486: Effect of the Normalized Prescription Isodose Line On Target Dose Deficiency in Lung SBRT Based On Monte Carlo Calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, D; Zhang, Q; Zhou, S

Purpose: To investigate the impact of normalized prescription isodose line on target dose deficiency calculated with Monte Carlo (MC) vs. pencil Beam (PB) in lung SBRT. RTOG guidelines recommend prescription lines between 60% and 90% for lung SBRT. How this affects the magnitude of MC-calculated target dose deficiency has never been studied. Methods: Under an IRB-approved protocol, four lung SBRT patients were replanned following RTOG0813 by a single physicist. For each patient, four alternative plans were generated based on PB calculation prescribing to 60–90% isodose lines, respectively. Each plan consisted of 360o coplanar dynamic conformal arcs with beam apertures manuallymore » optimized to achieve similar dose coverage and conformity for all plans of the same patient. Dose distribution was calculated with MC and compared to that with PB. PTV dose-volume endpoints were compared, including Dmin, D5, Dmean, D95, and Dmax. PTV V100 coverage, conformity index (CI), and heterogeneity index (HI) were also evaluated. Results: For all 16 plans, median (range) PTV V100 and CI were 99.7% (97.5–100%) and 1.27 (1.20–1.41), respectively. As expected, lower prescription line resulted in higher target dose heterogeneity, yielding median (range) HI of 1.26 (1.05–1.51) for all plans. Comparing MC to PB, median (range) D95, Dmean, D5 PTV dose deficiency were 18.9% (11.2–23.2%), 15.6% (10.0–22.7%), and 9.4%(5.5–13.6%) of the prescription dose, respectively. The Dmean, D5, and Dmax deficiency was found to monotonically increase with decreasing prescription line from 90% to 60%, while the Dmin deficiency monotonically decreased. D95 deficiency exhibited more complex trend, reaching the largest deficiency at 80% for all patients. Conclusion: Dependence on prescription isodose line was found for MC-calculated PTV dose deficiency of lung SBRT. When comparing reported MC dose deficiency values from different institutions, their individual selections of prescription line should be considered in addition to other factors affecting the deficiency magnitude.« less

Computational model for simulation of sequences of helicity and angular momentum transfer in turbid tissue-like scattering medium (Conference Presentation)

NASA Astrophysics Data System (ADS)

Doronin, Alexander; Meglinski, Igor

2017-02-01

Current report considers development of a unified Monte Carlo (MC) -based computational model for simulation of propagation of Laguerre-Gaussian (LG) beams in turbid tissue-like scattering medium. With a primary goal to proof the concept of using complex light for tissue diagnosis we explore propagation of LG beams in comparison with Gaussian beams for both linear and circular polarization. MC simulations of radially and azimuthally polarized LG beams in turbid media have been performed, classic phenomena such as preservation of the orbital angular momentum, optical memory and helicity flip are observed, detailed comparison is presented and discussed.

MO-FG-CAMPUS-TeP3-03: Calculation of Proton Pencil Beam Properties with Full Beamline Model in TOPAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wulff, J; Abel, E

2016-06-15

Purpose: Introducing Monte Carlo based dose calculation algorithms into proton therapy planning systems (TPS) leads to improved accuracy. However accurate modelling of the proton pencil beam impinging the patient is necessary. Current approaches rely on measurement-driven reconstruction of phase-space and spectrum properties, typically constrained to analytical model functions. In this study a detailed Monte Carlo model of the complete cyclotron-based delivery system was created with the aim of providing more representative beam properties at treatment position. Methods: A model of the Varian Probeam proton system from the cyclotron exit to isocenter was constructed in the TOPAS Monte Carlo framework. Themore » beam evolution through apertures and magnetic elements was validated using Transport/Turtle calculations and additionally against measurements from the Probeam™ system at Scripps Proton Therapy Center (SPTC) in San Diego, CA. A voxelized water phantom at isocenter allowed for comparison of the dose-depth curve from the Probeam model with that of a corresponding Gaussian beam over the entire energy range (70–240 MeV). Measurements of relative beam fluence cross-profiles and depth-dose curves at and around isocenter were also compared to the MC results. Results: The simulated TOPAS beam envelope was found to agree with both the Transport/Turtle and measurements to within 5% for most of the beamline. The MC predicted energy spectrum at isocenter was found to deviate increasingly from Gaussian at energies below 160 MeV. The corresponding effects on the depth dose curve agreed well with measurements. Conclusion: Given the flexibility of TOPAS and available details of the delivery system, an accurate characterization of a proton pencil beam at isocenter is possible. Incorporation of the MC derived properties of the proton pencil beam can eliminate analytical approximations and ultimately increase treatment plan accuracy and quality. Both authors are employees of Varian Medical Systems.« less

Verification measurements and clinical evaluation of the iPlan RT Monte Carlo dose algorithm for 6 MV photon energy

NASA Astrophysics Data System (ADS)

Petoukhova, A. L.; van Wingerden, K.; Wiggenraad, R. G. J.; van de Vaart, P. J. M.; van Egmond, J.; Franken, E. M.; van Santvoort, J. P. C.

2010-08-01

This study presents data for verification of the iPlan RT Monte Carlo (MC) dose algorithm (BrainLAB, Feldkirchen, Germany). MC calculations were compared with pencil beam (PB) calculations and verification measurements in phantoms with lung-equivalent material, air cavities or bone-equivalent material to mimic head and neck and thorax and in an Alderson anthropomorphic phantom. Dosimetric accuracy of MC for the micro-multileaf collimator (MLC) simulation was tested in a homogeneous phantom. All measurements were performed using an ionization chamber and Kodak EDR2 films with Novalis 6 MV photon beams. Dose distributions measured with film and calculated with MC in the homogeneous phantom are in excellent agreement for oval, C and squiggle-shaped fields and for a clinical IMRT plan. For a field with completely closed MLC, MC is much closer to the experimental result than the PB calculations. For fields larger than the dimensions of the inhomogeneities the MC calculations show excellent agreement (within 3%/1 mm) with the experimental data. MC calculations in the anthropomorphic phantom show good agreement with measurements for conformal beam plans and reasonable agreement for dynamic conformal arc and IMRT plans. For 6 head and neck and 15 lung patients a comparison of the MC plan with the PB plan was performed. Our results demonstrate that MC is able to accurately predict the dose in the presence of inhomogeneities typical for head and neck and thorax regions with reasonable calculation times (5-20 min). Lateral electron transport was well reproduced in MC calculations. We are planning to implement MC calculations for head and neck and lung cancer patients.

TH-A-18C-04: Ultrafast Cone-Beam CT Scatter Correction with GPU-Based Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Y; Southern Medical University, Guangzhou; Bai, T

2014-06-15

Purpose: Scatter artifacts severely degrade image quality of cone-beam CT (CBCT). We present an ultrafast scatter correction framework by using GPU-based Monte Carlo (MC) simulation and prior patient CT image, aiming at automatically finish the whole process including both scatter correction and reconstructions within 30 seconds. Methods: The method consists of six steps: 1) FDK reconstruction using raw projection data; 2) Rigid Registration of planning CT to the FDK results; 3) MC scatter calculation at sparse view angles using the planning CT; 4) Interpolation of the calculated scatter signals to other angles; 5) Removal of scatter from the raw projections;more » 6) FDK reconstruction using the scatter-corrected projections. In addition to using GPU to accelerate MC photon simulations, we also use a small number of photons and a down-sampled CT image in simulation to further reduce computation time. A novel denoising algorithm is used to eliminate MC scatter noise caused by low photon numbers. The method is validated on head-and-neck cases with simulated and clinical data. Results: We have studied impacts of photo histories, volume down sampling factors on the accuracy of scatter estimation. The Fourier analysis was conducted to show that scatter images calculated at 31 angles are sufficient to restore those at all angles with <0.1% error. For the simulated case with a resolution of 512×512×100, we simulated 10M photons per angle. The total computation time is 23.77 seconds on a Nvidia GTX Titan GPU. The scatter-induced shading/cupping artifacts are substantially reduced, and the average HU error of a region-of-interest is reduced from 75.9 to 19.0 HU. Similar results were found for a real patient case. Conclusion: A practical ultrafast MC-based CBCT scatter correction scheme is developed. The whole process of scatter correction and reconstruction is accomplished within 30 seconds. This study is supported in part by NIH (1R01CA154747-01), The Core Technology Research in Strategic Emerging Industry, Guangdong, China (2011A081402003)« less

SU-G-IeP2-04: Dosimetric Accuracy of a Monte Carlo-Based Tool for Cone-Beam CT Organ Dose Calculation: Validation Against OSL and XRQA2 Film Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chesneau, H; Lazaro, D; Blideanu, V

Purpose: The intensive use of Cone-Beam Computed Tomography (CBCT) during radiotherapy treatments raise some questions about the dose to healthy tissues delivered during image acquisitions. We hence developed a Monte Carlo (MC)-based tool to predict doses to organs delivered by the Elekta XVI kV-CBCT. This work aims at assessing the dosimetric accuracy of the MC tool, in all tissue types. Methods: The kV-CBCT MC model was developed using the PENELOPE code. The beam properties were validated against measured lateral and depth dose profiles in water, and energy spectra measured with a CdTe detector. The CBCT simulator accuracy then required verificationmore » in clinical conditions. For this, we compared calculated and experimental dose values obtained with OSL nanoDots and XRQA2 films inserted in CIRS anthropomorphic phantoms (male, female, and 5-year old child). Measurements were performed at different locations, including bone and lung structures, and for several acquisition protocols: lung, head-and-neck, and pelvis. OSLs and film measurements were corrected when possible for energy dependence, by taking into account for spectral variations between calibration and measurement conditions. Results: Comparisons between measured and MC dose values are summarized in table 1. A mean difference of 8.6% was achieved for OSLs when the energy correction was applied, and 89.3% of the 84 dose points were within uncertainty intervals, including those in bones and lungs. Results with XRQA2 are not as good, because incomplete information about electronic equilibrium in film layers hampered the application of a simple energy correction procedure. Furthermore, measured and calculated doses (Fig.1) are in agreement with the literature. Conclusion: The MC-based tool developed was validated with an extensive set of measurements, and enables the organ dose calculation with accuracy. It can now be used to compute and report doses to organs for clinical cases, and also to drive strategies to optimize imaging protocols.« less

SU-F-T-364: Monte Carlo-Dose Verification of Volumetric Modulated Arc Therapy Plans Using AAPM TG-119 Test Patterns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Onizuka, R; Araki, F; Ohno, T

2016-06-15

Purpose: To investigate the Monte Carlo (MC)-based dose verification for VMAT plans by a treatment planning system (TPS). Methods: The AAPM TG-119 test structure set was used for VMAT plans by the Pinnacle3 (convolution/superposition), using a Synergy radiation head of a 6 MV beam with the Agility MLC. The Synergy was simulated with the EGSnrc/BEAMnrc code, and VMAT dose distributions were calculated with the EGSnrc/DOSXYZnrc code by the same irradiation conditions as TPS. VMAT dose distributions of TPS and MC were compared with those of EBT3 film, by 2-D gamma analysis of ±3%/3 mm criteria with a threshold of 30%more » of prescribed doses. VMAT dose distributions between TPS and MC were also compared by DVHs and 3-D gamma analysis of ±3%/3 mm criteria with a threshold of 10%, and 3-D passing rates for PTVs and OARs were analyzed. Results: TPS dose distributions differed from those of film, especially for Head & neck. The dose difference between TPS and film results from calculation accuracy for complex motion of MLCs like tongue and groove effect. In contrast, MC dose distributions were in good agreement with those of film. This is because MC can model fully the MLC configuration and accurately reproduce the MLC motion between control points in VMAT plans. D95 of PTV for Prostate, Head & neck, C-shaped, and Multi Target was 97.2%, 98.1%, 101.6%, and 99.7% for TPS and 95.7%, 96.0%, 100.6%, and 99.1% for MC, respectively. Similarly, 3-D gamma passing rates of each PTV for TPS vs. MC were 100%, 89.5%, 99.7%, and 100%, respectively. 3-D passing rates of TPS reduced for complex VMAT fields like Head & neck because MLCs are not modeled completely for TPS. Conclusion: MC-calculated VMAT dose distributions is useful for the 3-D dose verification of VMAT plans by TPS.« less

TU-H-CAMPUS-IeP1-04: Combined Organ Dose for Digital Subtraction Angiography and Computed Tomography Using Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakabe, D; Ohno, T; Araki, F

Purpose: The purpose of this study was to evaluate the combined organ dose of digital subtraction angiography (DSA) and computed tomography (CT) using a Monte Carlo (MC) simulation on the abdominal intervention. Methods: The organ doses for DSA and CT were obtained with MC simulation and actual measurements using fluorescent-glass dosimeters at 7 abdominal portions in an Alderson-Rando phantom. DSA was performed from three directions: posterior anterior (PA), right anterior oblique (RAO), and left anterior oblique (LAO). The organ dose with MC simulation was compared with actual radiation dose measurements. Calculations for the MC simulation were carried out with themore » GMctdospp (IMPS, Germany) software based on the EGSnrc MC code. Finally, the combined organ dose for DSA and CT was calculated from the MC simulation using the X-ray conditions of a patient with a diagnosis of hepatocellular carcinoma. Results: For DSA from the PA direction, the organ doses for the actual measurements and MC simulation were 2.2 and 2.4 mGy/100 mAs at the liver, respectively, and 3.0 and 3.1 mGy/100 mAs at the spinal cord, while for CT, the organ doses were 15.2 and 15.1 mGy/100 mAs at the liver, and 14.6 and 13.5 mGy/100 mAs at the spinal cord. The maximum difference in organ dose between the actual measurements and the MC simulation was 11.0% of the spleen at PA, 8.2% of the spinal cord at RAO, and 6.1% of left kidney at LAO with DSA and 9.3% of the stomach with CT. The combined organ dose (4 DSAs and 6 CT scans) with the use of actual patient conditions was found to be 197.4 mGy for the liver and 205.1 mGy for the spinal cord. Conclusion: Our method makes it possible to accurately assess the organ dose to patients for abdominal intervention with combined DSA and CT.« less

SU-E-T-314: The Application of Cloud Computing in Pencil Beam Scanning Proton Therapy Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Z; Gao, M

Purpose: Monte Carlo simulation plays an important role for proton Pencil Beam Scanning (PBS) technique. However, MC simulation demands high computing power and is limited to few large proton centers that can afford a computer cluster. We study the feasibility of utilizing cloud computing in the MC simulation of PBS beams. Methods: A GATE/GEANT4 based MC simulation software was installed on a commercial cloud computing virtual machine (Linux 64-bits, Amazon EC2). Single spot Integral Depth Dose (IDD) curves and in-air transverse profiles were used to tune the source parameters to simulate an IBA machine. With the use of StarCluster softwaremore » developed at MIT, a Linux cluster with 2–100 nodes can be conveniently launched in the cloud. A proton PBS plan was then exported to the cloud where the MC simulation was run. Results: The simulated PBS plan has a field size of 10×10cm{sup 2}, 20cm range, 10cm modulation, and contains over 10,000 beam spots. EC2 instance type m1.medium was selected considering the CPU/memory requirement and 40 instances were used to form a Linux cluster. To minimize cost, master node was created with on-demand instance and worker nodes were created with spot-instance. The hourly cost for the 40-node cluster was $0.63 and the projected cost for a 100-node cluster was $1.41. Ten million events were simulated to plot PDD and profile, with each job containing 500k events. The simulation completed within 1 hour and an overall statistical uncertainty of < 2% was achieved. Good agreement between MC simulation and measurement was observed. Conclusion: Cloud computing is a cost-effective and easy to maintain platform to run proton PBS MC simulation. When proton MC packages such as GATE and TOPAS are combined with cloud computing, it will greatly facilitate the pursuing of PBS MC studies, especially for newly established proton centers or individual researchers.« less

Applying Monte-Carlo simulations to optimize an inelastic neutron scattering system for soil carbon analysis

USDA-ARS?s Scientific Manuscript database

Computer Monte-Carlo (MC) simulations (Geant4) of neutron propagation and acquisition of gamma response from soil samples was applied to evaluate INS system performance characteristic [sensitivity, minimal detectable level (MDL)] for soil carbon measurement. The INS system model with best performanc...

GATE Monte Carlo simulation in a cloud computing environment

NASA Astrophysics Data System (ADS)

Rowedder, Blake Austin

The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications, e.g. PET, SPECT, CT, radiotherapy, and hadron therapy. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time. By accessing the powerful computational resources of a cloud computing environment, GATE's runtime can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulations using a commercial cloud computing services. Amazon's Elastic Compute Cloud was used to launch several nodes equipped with GATE. Job data was initially broken up on the local computer, then uploaded to the worker nodes on the cloud. The results were automatically downloaded and aggregated on the local computer for display and analysis. Five simulations were repeated for every cluster size between 1 and 20 nodes. Ultimately, increasing cluster size resulted in a decrease in calculation time that could be expressed with an inverse power model. Comparing the benchmark results to the published values and error margins indicated that the simulation results were not affected by the cluster size and thus that integrity of a calculation is preserved in a cloud computing environment. The runtime of a 53 minute long simulation was decreased to 3.11 minutes when run on a 20-node cluster. The ability to improve the speed of simulation suggests that fast MC simulations are viable for imaging and radiotherapy applications. With high power computing continuing to lower in price and accessibility, implementing Monte Carlo techniques with cloud computing for clinical applications will continue to become more attractive.

Atomistic Monte Carlo Simulation of Lipid Membranes

PubMed Central

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol. PMID:24469314

A Detailed FLUKA-2005 Monte Carlo Simulation for the ATIC Detector

NASA Technical Reports Server (NTRS)

Gunasingha, R. M.; Fazely, A. R.; Adams, J. H.; Ahn, H. S.; Bashindzhagyan, G. L.; Batkov, K. E.; Chang, J.; Christl, M.; Ganel, O.; Guzik, T. G.

2006-01-01

We have performed a detailed Monte Carlo (MC) calculation for the Advanced thin Ionization Calorimeter (ATIC) detector using the MC code FLUKA-2005 which is capable of simulating particles up to 10 PeV. The ATIC detector has completed two successful balloon flights from McMurdo, Antarctica lasting a total of more than 35 days. ATIC is designed as a multiple, long duration balloon Bight, investigation of the cosmic ray spectra from below 50 GeV to near 100 TeV total energy; using a fully active Bismuth Germanate @GO) calorimeter. It is equipped with a large mosaic of silicon detector pixels capable of charge identification and as a particle tracking system, three projective layers of x-y scintillator hodoscopes were employed, above, in the middle and below a 0.75 nuclear interaction length graphite target. Our calculations are part of an analysis package of both A- and energy-dependences of different nuclei interacting with the ATIC detector. The MC simulates the responses of different components of the detector such as the Simatrix, the scintillator hodoscopes and the BGO calorimeter to various nuclei. We also show comparisons of the FLUKA-2005 MC calculations with a GEANT calculation and data for protons, He and CNO.

A medical image-based graphical platform -- features, applications and relevance for brachytherapy.

PubMed

Fonseca, Gabriel P; Reniers, Brigitte; Landry, Guillaume; White, Shane; Bellezzo, Murillo; Antunes, Paula C G; de Sales, Camila P; Welteman, Eduardo; Yoriyaz, Hélio; Verhaegen, Frank

2014-01-01

Brachytherapy dose calculation is commonly performed using the Task Group-No 43 Report-Updated protocol (TG-43U1) formalism. Recently, a more accurate approach has been proposed that can handle tissue composition, tissue density, body shape, applicator geometry, and dose reporting either in media or water. Some model-based dose calculation algorithms are based on Monte Carlo (MC) simulations. This work presents a software platform capable of processing medical images and treatment plans, and preparing the required input data for MC simulations. The A Medical Image-based Graphical platfOrm-Brachytherapy module (AMIGOBrachy) is a user interface, coupled to the MCNP6 MC code, for absorbed dose calculations. The AMIGOBrachy was first validated in water for a high-dose-rate (192)Ir source. Next, dose distributions were validated in uniform phantoms consisting of different materials. Finally, dose distributions were obtained in patient geometries. Results were compared against a treatment planning system including a linear Boltzmann transport equation (LBTE) solver capable of handling nonwater heterogeneities. The TG-43U1 source parameters are in good agreement with literature with more than 90% of anisotropy values within 1%. No significant dependence on the tissue composition was observed comparing MC results against an LBTE solver. Clinical cases showed differences up to 25%, when comparing MC results against TG-43U1. About 92% of the voxels exhibited dose differences lower than 2% when comparing MC results against an LBTE solver. The AMIGOBrachy can improve the accuracy of the TG-43U1 dose calculation by using a more accurate MC dose calculation algorithm. The AMIGOBrachy can be incorporated in clinical practice via a user-friendly graphical interface. Copyright © 2014 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Acceleration of Monte Carlo simulation of photon migration in complex heterogeneous media using Intel many-integrated core architecture.

PubMed

Gorshkov, Anton V; Kirillin, Mikhail Yu

2015-08-01

Over two decades, the Monte Carlo technique has become a gold standard in simulation of light propagation in turbid media, including biotissues. Technological solutions provide further advances of this technique. The Intel Xeon Phi coprocessor is a new type of accelerator for highly parallel general purpose computing, which allows execution of a wide range of applications without substantial code modification. We present a technical approach of porting our previously developed Monte Carlo (MC) code for simulation of light transport in tissues to the Intel Xeon Phi coprocessor. We show that employing the accelerator allows reducing computational time of MC simulation and obtaining simulation speed-up comparable to GPU. We demonstrate the performance of the developed code for simulation of light transport in the human head and determination of the measurement volume in near-infrared spectroscopy brain sensing.

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisenbach, Markus; Li, Ying Wai

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage ofmore » avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.« less

Performance of two commercial electron beam algorithms over regions close to the lung-mediastinum interface, against Monte Carlo simulation and point dosimetry in virtual and anthropomorphic phantoms.

PubMed

Ojala, J; Hyödynmaa, S; Barańczyk, R; Góra, E; Waligórski, M P R

2014-03-01

Electron radiotherapy is applied to treat the chest wall close to the mediastinum. The performance of the GGPB and eMC algorithms implemented in the Varian Eclipse treatment planning system (TPS) was studied in this region for 9 and 16 MeV beams, against Monte Carlo (MC) simulations, point dosimetry in a water phantom and dose distributions calculated in virtual phantoms. For the 16 MeV beam, the accuracy of these algorithms was also compared over the lung-mediastinum interface region of an anthropomorphic phantom, against MC calculations and thermoluminescence dosimetry (TLD). In the phantom with a lung-equivalent slab the results were generally congruent, the eMC results for the 9 MeV beam slightly overestimating the lung dose, and the GGPB results for the 16 MeV beam underestimating the lung dose. Over the lung-mediastinum interface, for 9 and 16 MeV beams, the GGPB code underestimated the lung dose and overestimated the dose in water close to the lung, compared to the congruent eMC and MC results. In the anthropomorphic phantom, results of TLD measurements and MC and eMC calculations agreed, while the GGPB code underestimated the lung dose. Good agreement between TLD measurements and MC calculations attests to the accuracy of "full" MC simulations as a reference for benchmarking TPS codes. Application of the GGPB code in chest wall radiotherapy may result in significant underestimation of the lung dose and overestimation of dose to the mediastinum, affecting plan optimization over volumes close to the lung-mediastinum interface, such as the lung or heart. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Deviation from equilibrium conditions in molecular dynamic simulations of homogeneous nucleation.

PubMed

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-28

We present a comparison between Monte Carlo (MC) results for homogeneous vapour-liquid nucleation of Lennard-Jones clusters and previously published values from molecular dynamics (MD) simulations. Both the MC and MD methods sample real cluster configuration distributions. In the MD simulations, the extent of the temperature fluctuation is usually controlled with an artificial thermostat rather than with more realistic carrier gas. In this study, not only a primarily velocity scaling thermostat is considered, but also Nosé-Hoover, Berendsen, and stochastic Langevin thermostat methods are covered. The nucleation rates based on a kinetic scheme and the canonical MC calculation serve as a point of reference since they by definition describe an equilibrated system. The studied temperature range is from T = 0.3 to 0.65 ϵ/k. The kinetic scheme reproduces well the isothermal nucleation rates obtained by Wedekind et al. [J. Chem. Phys. 127, 064501 (2007)] using MD simulations with carrier gas. The nucleation rates obtained by artificially thermostatted MD simulations are consistently lower than the reference nucleation rates based on MC calculations. The discrepancy increases up to several orders of magnitude when the density of the nucleating vapour decreases. At low temperatures, the difference to the MC-based reference nucleation rates in some cases exceeds the maximal nonisothermal effect predicted by classical theory of Feder et al. [Adv. Phys. 15, 111 (1966)].

Deviation from equilibrium conditions in molecular dynamic simulations of homogeneous nucleation

NASA Astrophysics Data System (ADS)

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-01

We present a comparison between Monte Carlo (MC) results for homogeneous vapour-liquid nucleation of Lennard-Jones clusters and previously published values from molecular dynamics (MD) simulations. Both the MC and MD methods sample real cluster configuration distributions. In the MD simulations, the extent of the temperature fluctuation is usually controlled with an artificial thermostat rather than with more realistic carrier gas. In this study, not only a primarily velocity scaling thermostat is considered, but also Nosé-Hoover, Berendsen, and stochastic Langevin thermostat methods are covered. The nucleation rates based on a kinetic scheme and the canonical MC calculation serve as a point of reference since they by definition describe an equilibrated system. The studied temperature range is from T = 0.3 to 0.65 ɛ/k. The kinetic scheme reproduces well the isothermal nucleation rates obtained by Wedekind et al. [J. Chem. Phys. 127, 064501 (2007)] using MD simulations with carrier gas. The nucleation rates obtained by artificially thermostatted MD simulations are consistently lower than the reference nucleation rates based on MC calculations. The discrepancy increases up to several orders of magnitude when the density of the nucleating vapour decreases. At low temperatures, the difference to the MC-based reference nucleation rates in some cases exceeds the maximal nonisothermal effect predicted by classical theory of Feder et al. [Adv. Phys. 15, 111 (1966)].

SU-G-BRC-10: Feasibility of a Web-Based Monte Carlo Simulation Tool for Dynamic Electron Arc Radiotherapy (DEAR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodrigues, A; Wu, Q; Sawkey, D

Purpose: DEAR is a radiation therapy technique utilizing synchronized motion of gantry and couch during delivery to optimize dose distribution homogeneity and penumbra for treatment of superficial disease. Dose calculation for DEAR is not yet supported by commercial TPSs. The purpose of this study is to demonstrate the feasibility of using a web-based Monte Carlo (MC) simulation tool (VirtuaLinac) to calculate dose distributions for a DEAR delivery. Methods: MC simulations were run through VirtuaLinac, which is based on the GEANT4 platform. VirtuaLinac utilizes detailed linac head geometry and material models, validated phase space files, and a voxelized phantom. The inputmore » was expanded to include an XML file for simulation of varying mechanical axes as a function of MU. A DEAR XML plan was generated and used in the MC simulation and delivered on a TrueBeam in Developer Mode. Radiographic film wrapped on a cylindrical phantom (12.5 cm radius) measured dose at a depth of 1.5 cm and compared to the simulation results. Results: A DEAR plan was simulated using an energy of 6 MeV and a 3×10 cm{sup 2} cut-out in a 15×15 cm{sup 2} applicator for a delivery of a 90° arc. The resulting data were found to provide qualitative and quantitative evidence that the simulation platform could be used as the basis for DEAR dose calculations. The resulting unwrapped 2D dose distributions agreed well in the cross-plane direction along the arc, with field sizes of 18.4 and 18.2 cm and penumbrae of 1.9 and 2.0 cm for measurements and simulations, respectively. Conclusion: Preliminary feasibility of a DEAR delivery using a web-based MC simulation platform has been demonstrated. This tool will benefit treatment planning for DEAR as a benchmark for developing other model based algorithms, allowing efficient optimization of trajectories, and quality assurance of plans without the need for extensive measurements.« less

Multiscale modelling of precipitation in concentrated alloys: from atomistic Monte Carlo simulations to cluster dynamics I thermodynamics

NASA Astrophysics Data System (ADS)

Lépinoux, J.; Sigli, C.

2018-01-01

In a recent paper, the authors showed how the clusters free energies are constrained by the coagulation probability, and explained various anomalies observed during the precipitation kinetics in concentrated alloys. This coagulation probability appeared to be a too complex function to be accurately predicted knowing only the cluster distribution in Cluster Dynamics (CD). Using atomistic Monte Carlo (MC) simulations, it is shown that during a transformation at constant temperature, after a short transient regime, the transformation occurs at quasi-equilibrium. It is proposed to use MC simulations until the system quasi-equilibrates then to switch to CD which is mean field but not limited by a box size like MC. In this paper, we explain how to take into account the information available before the quasi-equilibrium state to establish guidelines to safely predict the cluster free energies.

Implementation and verification of nuclear interactions in a Monte-Carlo code for the Procom-ProGam proton therapy planning system

NASA Astrophysics Data System (ADS)

Kostyuchenko, V. I.; Makarova, A. S.; Ryazantsev, O. B.; Samarin, S. I.; Uglov, A. S.

2014-06-01

A great breakthrough in proton therapy has happened in the new century: several tens of dedicated centers are now operated throughout the world and their number increases every year. An important component of proton therapy is a treatment planning system. To make calculations faster, these systems usually use analytical methods whose reliability and accuracy do not allow the advantages of this method of treatment to implement to the full extent. Predictions by the Monte Carlo (MC) method are a "gold" standard for the verification of calculations with these systems. At the Institute of Experimental and Theoretical Physics (ITEP) which is one of the eldest proton therapy centers in the world, an MC code is an integral part of their treatment planning system. This code which is called IThMC was developed by scientists from RFNC-VNIITF (Snezhinsk) under ISTC Project 3563.

Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach

NASA Astrophysics Data System (ADS)

Leblanc, Benoit; Braunschweig, Bertrand; Toulhoat, Hervé; Lutton, Evelyne

We present a new approach in order to improve the convergence of Monte Carlo (MC) simulations of molecular systems belonging to complex energetic landscapes: the problem is redefined in terms of the dynamic allocation of MC move frequencies depending on their past efficiency, measured with respect to a relevant sampling criterion. We introduce various empirical criteria with the aim of accounting for the proper convergence in phase space sampling. The dynamic allocation is performed over parallel simulations by means of a new evolutionary algorithm involving 'immortal' individuals. The method is bench marked with respect to conventional procedures on a model for melt linear polyethylene. We record significant improvement in sampling efficiencies, thus in computational load, while the optimal sets of move frequencies are liable to allow interesting physical insights into the particular systems simulated. This last aspect should provide a new tool for designing more efficient new MC moves.

Risk Assessment and Prediction of Flyrock Distance by Combined Multiple Regression Analysis and Monte Carlo Simulation of Quarry Blasting

NASA Astrophysics Data System (ADS)

Armaghani, Danial Jahed; Mahdiyar, Amir; Hasanipanah, Mahdi; Faradonbeh, Roohollah Shirani; Khandelwal, Manoj; Amnieh, Hassan Bakhshandeh

2016-09-01

Flyrock is considered as one of the main causes of human injury, fatalities, and structural damage among all undesirable environmental impacts of blasting. Therefore, it seems that the proper prediction/simulation of flyrock is essential, especially in order to determine blast safety area. If proper control measures are taken, then the flyrock distance can be controlled, and, in return, the risk of damage can be reduced or eliminated. The first objective of this study was to develop a predictive model for flyrock estimation based on multiple regression (MR) analyses, and after that, using the developed MR model, flyrock phenomenon was simulated by the Monte Carlo (MC) approach. In order to achieve objectives of this study, 62 blasting operations were investigated in Ulu Tiram quarry, Malaysia, and some controllable and uncontrollable factors were carefully recorded/calculated. The obtained results of MC modeling indicated that this approach is capable of simulating flyrock ranges with a good level of accuracy. The mean of simulated flyrock by MC was obtained as 236.3 m, while this value was achieved as 238.6 m for the measured one. Furthermore, a sensitivity analysis was also conducted to investigate the effects of model inputs on the output of the system. The analysis demonstrated that powder factor is the most influential parameter on fly rock among all model inputs. It is noticeable that the proposed MR and MC models should be utilized only in the studied area and the direct use of them in the other conditions is not recommended.

Constant-pH Hybrid Nonequilibrium Molecular Dynamics–Monte Carlo Simulation Method

PubMed Central

2016-01-01

A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys.2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD–MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD–MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems. PMID:26300709

Sci-Sat AM: Brachy - 04: Neutron production around a radiation therapy linac bunker - monte carlo simulations and physical measurements.

PubMed

Khatchadourian, R; Davis, S; Evans, M; Licea, A; Seuntjens, J; Kildea, J

2012-07-01

Photoneutrons are a major component of the equivalent dose in the maze and near the door of linac bunkers. Physical measurements and Monte Carlo (MC) calculations of neutron dose are key for validating bunker design with respect to health regulations. We attempted to use bubble detectors and a 3 He neutron spectrometer to measure neutron equivalent dose and neutron spectra in the maze and near the door of one of our bunkers. We also ran MC simulations with MCNP5 to measure the neutron fluence in the same region. Using a point source of neutrons, a Clinac 1800 linac operating at 10 MV was simulated and the fluence measured at various locations of interest. We describe the challenges faced when measuring dose with bubble detectors in the maze and the complexity of photoneutron spectrometry with linacs operating in pulsed mode. Finally, we report on the development of a userfriendly GUI for shielding calculations based on the NCRP 151 formalism. © 2012 American Association of Physicists in Medicine.

Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.

PubMed Central

Mathiowetz, A. M.; Goddard, W. A.

1995-01-01

Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better. PMID:7549885

The dose distribution of low dose rate Cs-137 in intracavitary brachytherapy: comparison of Monte Carlo simulation, treatment planning calculation and polymer gel measurement

NASA Astrophysics Data System (ADS)

Fragoso, M.; Love, P. A.; Verhaegen, F.; Nalder, C.; Bidmead, A. M.; Leach, M.; Webb, S.

2004-12-01

In this study, the dose distribution delivered by low dose rate Cs-137 brachytherapy sources was investigated using Monte Carlo (MC) techniques and polymer gel dosimetry. The results obtained were compared with a commercial treatment planning system (TPS). The 20 mm and the 30 mm diameter Selectron vaginal applicator set (Nucletron) were used for this study. A homogeneous and a heterogeneous—with an air cavity—polymer gel phantom was used to measure the dose distribution from these sources. The same geometrical set-up was used for the MC calculations. Beyond the applicator tip, differences in dose as large as 20% were found between the MC and TPS. This is attributed to the presence of stainless steel in the applicator and source set, which are not considered by the TPS calculations. Beyond the air cavity, differences in dose of around 5% were noted, due to the TPS assuming a homogeneous water medium. The polymer gel results were in good agreement with the MC calculations for all the cases investigated.

Cellular dosimetry calculations for Strontium-90 using Monte Carlo code PENELOPE.

PubMed

Hocine, Nora; Farlay, Delphine; Boivin, Georges; Franck, Didier; Agarande, Michelle

2014-11-01

To improve risk assessments associated with chronic exposure to Strontium-90 (Sr-90), for both the environment and human health, it is necessary to know the energy distribution in specific cells or tissue. Monte Carlo (MC) simulation codes are extremely useful tools for calculating deposition energy. The present work was focused on the validation of the MC code PENetration and Energy LOss of Positrons and Electrons (PENELOPE) and the assessment of dose distribution to bone marrow cells from punctual Sr-90 source localized within the cortical bone part. S-values (absorbed dose per unit cumulated activity) calculations using Monte Carlo simulations were performed by using PENELOPE and Monte Carlo N-Particle eXtended (MCNPX). Cytoplasm, nucleus, cell surface, mouse femur bone and Sr-90 radiation source were simulated. Cells are assumed to be spherical with the radii of the cell and cell nucleus ranging from 2-10 μm. The Sr-90 source is assumed to be uniformly distributed in cell nucleus, cytoplasm and cell surface. The comparison of S-values calculated with PENELOPE to MCNPX results and the Medical Internal Radiation Dose (MIRD) values agreed very well since the relative deviations were less than 4.5%. The dose distribution to mouse bone marrow cells showed that the cells localized near the cortical part received the maximum dose. The MC code PENELOPE may prove useful for cellular dosimetry involving radiation transport through materials other than water, or for complex distributions of radionuclides and geometries.

Comparison of measured and Monte Carlo calculated dose distributions in inhomogeneous phantoms in clinical electron beams

NASA Astrophysics Data System (ADS)

Doucet, R.; Olivares, M.; DeBlois, F.; Podgorsak, E. B.; Kawrakow, I.; Seuntjens, J.

2003-08-01

Calculations of dose distributions in heterogeneous phantoms in clinical electron beams, carried out using the fast voxel Monte Carlo (MC) system XVMC and the conventional MC code EGSnrc, were compared with measurements. Irradiations were performed using the 9 MeV and 15 MeV beams from a Varian Clinac-18 accelerator with a 10 × 10 cm2 applicator and an SSD of 100 cm. Depth doses were measured with thermoluminescent dosimetry techniques (TLD 700) in phantoms consisting of slabs of Solid WaterTM (SW) and bone and slabs of SW and lung tissue-equivalent materials. Lateral profiles in water were measured using an electron diode at different depths behind one and two immersed aluminium rods. The accelerator was modelled using the EGS4/BEAM system and optimized phase-space files were used as input to the EGSnrc and the XVMC calculations. Also, for the XVMC, an experiment-based beam model was used. All measurements were corrected by the EGSnrc-calculated stopping power ratios. Overall, there is excellent agreement between the corrected experimental and the two MC dose distributions. Small remaining discrepancies may be due to the non-equivalence between physical and simulated tissue-equivalent materials and to detector fluence perturbation effect correction factors that were calculated for the 9 MeV beam at selected depths in the heterogeneous phantoms.

Comparison of measured and Monte Carlo calculated dose distributions in inhomogeneous phantoms in clinical electron beams.

PubMed

Doucet, R; Olivares, M; DeBlois, F; Podgorsak, E B; Kawrakow, I; Seuntjens, J

2003-08-07

Calculations of dose distributions in heterogeneous phantoms in clinical electron beams, carried out using the fast voxel Monte Carlo (MC) system XVMC and the conventional MC code EGSnrc, were compared with measurements. Irradiations were performed using the 9 MeV and 15 MeV beams from a Varian Clinac-18 accelerator with a 10 x 10 cm2 applicator and an SSD of 100 cm. Depth doses were measured with thermoluminescent dosimetry techniques (TLD 700) in phantoms consisting of slabs of Solid Water (SW) and bone and slabs of SW and lung tissue-equivalent materials. Lateral profiles in water were measured using an electron diode at different depths behind one and two immersed aluminium rods. The accelerator was modelled using the EGS4/BEAM system and optimized phase-space files were used as input to the EGSnrc and the XVMC calculations. Also, for the XVMC, an experiment-based beam model was used. All measurements were corrected by the EGSnrc-calculated stopping power ratios. Overall, there is excellent agreement between the corrected experimental and the two MC dose distributions. Small remaining discrepancies may be due to the non-equivalence between physical and simulated tissue-equivalent materials and to detector fluence perturbation effect correction factors that were calculated for the 9 MeV beam at selected depths in the heterogeneous phantoms.

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M; Rearden, Bradley T

2015-01-01

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Threemore » of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations.« less

MC-TESTER: a universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

NASA Astrophysics Data System (ADS)

Golonka, P.; Pierzchała, T.; Waş, Z.

2004-02-01

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be used for such tests of decays of intermediate states (particles or resonances) in a semi-automated way. Our test consists of two steps. Different Monte Carlo programs are run; events with decays of a chosen particle are searched, decay trees are analyzed and appropriate information is stored. Then, at the analysis step, a list of all found decay modes is defined and branching ratios are calculated for both runs. Histograms of all scalar Lorentz-invariant masses constructed from the decay products are plotted and compared for each decay mode found in both runs. For each plot a measure of the difference of the distributions is calculated and its maximal value over all histograms for each decay channel is printed in a summary table. As an example of MC-TESTER application, we include a test with the τ lepton decay Monte Carlo generators, TAUOLA and PYTHIA. The HEPEVT (or LUJETS) common block is used as exclusive source of information on the generated events. Program summaryTitle of the program:MC-TESTER, version 1.1 Catalogue identifier: ADSM Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSM Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer: PC, two Intel Xeon 2.0 GHz processors, 512MB RAM Operating system: Linux Red Hat 6.1, 7.2, and also 8.0 Programming language used:C++, FORTRAN77: gcc 2.96 or 2.95.2 (also 3.2) compiler suite with g++ and g77 Size of the package: 7.3 MB directory including example programs (2 MB compressed distribution archive), without ROOT libraries (additional 43 MB). No. of bytes in distributed program, including test data, etc.: 2 024 425 Distribution format: tar gzip file Additional disk space required: Depends on the analyzed particle: 40 MB in the case of τ lepton decays (30 decay channels, 594 histograms, 82-pages booklet). Keywords: particle physics, decay simulation, Monte Carlo methods, invariant mass distributions, programs comparison Nature of the physical problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast, semi-automatic way of comparing results from different programs is often desirable, for the development of new programs, to check correctness of the installations or for discussion of uncertainties. Method of solution: A typical HEP Monte Carlo program stores the generated events in the event records such as HEPEVT or PYJETS. MC-TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table. Restrictions on the complexity of the problem: For a list of limitations see Section 6. Typical running time: Varies substantially with the analyzed decay particle. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100 000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; ? processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multi-processor machines. Accessibility: web page: http://cern.ch/Piotr.Golonka/MC/MC-TESTER e-mails: Piotr.Golonka@CERN.CH, T.Pierzchala@friend.phys.us.edu.pl, Zbigniew.Was@CERN.CH.

TH-A-18C-09: Ultra-Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sisniega, A; Zbijewski, W; Stayman, J

Purpose: Application of cone-beam CT (CBCT) to low-contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high-quality CBCT imaging of acute brain injury. Methods: The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC-GPU), with baseline simulation speed of ~1e7 photons/sec. MC-GPU is accelerated by a novel, GPU-optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced formore » additional speed-up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source-detector distance 700 mm, source-axis distance 480 mm). Results: For a fixed run-time of ~1 sec/projection, GPU-optimized VR reduces the noise in MC-GPU scatter estimates by a factor of 4. For scatter correction, MC-GPU with VR is executed with 4-fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run-time per scan, and de-noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast-tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction. Conclusion: Acceleration of MC-GPU achieved through GPU-optimized variance reduction and kernel smoothing yields an efficient (<5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications. Research grant from Carestream Health. JY is an employee of Carestream Health.« less

Calculated X-ray Intensities Using Monte Carlo Algorithms: A Comparison to Experimental EPMA Data

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2005-01-01

Monte Carlo (MC) modeling has been used extensively to simulate electron scattering and x-ray emission from complex geometries. Here are presented comparisons between MC results and experimental electron-probe microanalysis (EPMA) measurements as well as phi(rhoz) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been widely used to develop phi(rhoz) correction algorithms. X-ray intensity data produced by MC simulations represents an independent test of both experimental and phi(rhoz) correction algorithms. The alpha-factor method has previously been used to evaluate systematic errors in the analysis of semiconductor and silicate minerals, and is used here to compare the accuracy of experimental and MC-calculated x-ray data. X-ray intensities calculated by MC are used to generate a-factors using the certificated compositions in the CuAu binary relative to pure Cu and Au standards. MC simulations are obtained using the NIST, WinCasino, and WinXray algorithms; derived x-ray intensities have a built-in atomic number correction, and are further corrected for absorption and characteristic fluorescence using the PAP phi(rhoz) correction algorithm. The Penelope code additionally simulates both characteristic and continuum x-ray fluorescence and thus requires no further correction for use in calculating alpha-factors.

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation.

PubMed

Zhao, Yanqun; Qi, Guohai; Yin, Gang; Wang, Xianliang; Wang, Pei; Li, Jian; Xiao, Mingyong; Li, Jie; Kang, Shengwei; Liao, Xiongfei

2014-12-16

The accuracy of dose calculation is crucial to the quality of treatment planning and, consequently, to the dose delivered to patients undergoing radiation therapy. Current general calculation algorithms such as Pencil Beam Convolution (PBC) and Collapsed Cone Convolution (CCC) have shortcomings in regard to severe inhomogeneities, particularly in those regions where charged particle equilibrium does not hold. The aim of this study was to evaluate the accuracy of the PBC and CCC algorithms in lung cancer radiotherapy using Monte Carlo (MC) technology. Four treatment plans were designed using Oncentra Masterplan TPS for each patient. Two intensity-modulated radiation therapy (IMRT) plans were developed using the PBC and CCC algorithms, and two three-dimensional conformal therapy (3DCRT) plans were developed using the PBC and CCC algorithms. The DICOM-RT files of the treatment plans were exported to the Monte Carlo system to recalculate. The dose distributions of GTV, PTV and ipsilateral lung calculated by the TPS and MC were compared. For 3DCRT and IMRT plans, the mean dose differences for GTV between the CCC and MC increased with decreasing of the GTV volume. For IMRT, the mean dose differences were found to be higher than that of 3DCRT. The CCC algorithm overestimated the GTV mean dose by approximately 3% for IMRT. For 3DCRT plans, when the volume of the GTV was greater than 100 cm(3), the mean doses calculated by CCC and MC almost have no difference. PBC shows large deviations from the MC algorithm. For the dose to the ipsilateral lung, the CCC algorithm overestimated the dose to the entire lung, and the PBC algorithm overestimated V20 but underestimated V5; the difference in V10 was not statistically significant. PBC substantially overestimates the dose to the tumour, but the CCC is similar to the MC simulation. It is recommended that the treatment plans for lung cancer be developed using an advanced dose calculation algorithm other than PBC. MC can accurately calculate the dose distribution in lung cancer and can provide a notably effective tool for benchmarking the performance of other dose calculation algorithms within patients.

Postimplant dosimetry using a Monte Carlo dose calculation engine: a new clinical standard.

PubMed

Carrier, Jean-François; D'Amours, Michel; Verhaegen, Frank; Reniers, Brigitte; Martin, André-Guy; Vigneault, Eric; Beaulieu, Luc

2007-07-15

To use the Monte Carlo (MC) method as a dose calculation engine for postimplant dosimetry. To compare the results with clinically approved data for a sample of 28 patients. Two effects not taken into account by the clinical calculation, interseed attenuation and tissue composition, are being specifically investigated. An automated MC program was developed. The dose distributions were calculated for the target volume and organs at risk (OAR) for 28 patients. Additional MC techniques were developed to focus specifically on the interseed attenuation and tissue effects. For the clinical target volume (CTV) D(90) parameter, the mean difference between the clinical technique and the complete MC method is 10.7 Gy, with cases reaching up to 17 Gy. For all cases, the clinical technique overestimates the deposited dose in the CTV. This overestimation is mainly from a combination of two effects: the interseed attenuation (average, 6.8 Gy) and tissue composition (average, 4.1 Gy). The deposited dose in the OARs is also overestimated in the clinical calculation. The clinical technique systematically overestimates the deposited dose in the prostate and in the OARs. To reduce this systematic inaccuracy, the MC method should be considered in establishing a new standard for clinical postimplant dosimetry and dose-outcome studies in a near future.

Comparison of Fluka-2006 Monte Carlo Simulation and Flight Data for the ATIC Detector

NASA Technical Reports Server (NTRS)

Gunasingha, R.M.; Fazely, A.R.; Adams, J.H.; Ahn, H.S.; Bashindzhagyan, G.L.; Chang, J.; Christl, M.; Ganel, O.; Guzik, T.G.; Isbert, J.;

A Monte Carlo simulation study of associated liquid crystals

NASA Astrophysics Data System (ADS)

Berardi, R.; Fehervari, M.; Zannoni, C.

We have performed a Monte Carlo simulation study of a system of ellipsoidal particles with donor-acceptor sites modelling complementary hydrogen-bonding groups in real molecules. We have considered elongated Gay-Berne particles with terminal interaction sites allowing particles to associate and form dimers. The changes in the phase transitions and in the molecular organization and the interplay between orientational ordering and dimer formation are discussed. Particle flip and dimer moves have been used to increase the convergency rate of the Monte Carlo (MC) Markov chain.

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Don S.; Anderson, Kevin K.; White, Amanda M.

Background: A microarray of enzyme-linked immunosorbent assays, or ELISA microarray, predicts simultaneously the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Making sound biological inferences as well as improving the ELISA microarray process require require both concentration predictions and creditable estimates of their errors. Methods: We present a statistical method based on monotonic spline statistical models, penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict concentrations and estimate prediction errors in ELISA microarray. PCLS restrains the flexible spline to a fit of assay intensitymore » that is a monotone function of protein concentration. With MC, both modeling and measurement errors are combined to estimate prediction error. The spline/PCLS/MC method is compared to a common method using simulated and real ELISA microarray data sets. Results: In contrast to the rigid logistic model, the flexible spline model gave credible fits in almost all test cases including troublesome cases with left and/or right censoring, or other asymmetries. For the real data sets, 61% of the spline predictions were more accurate than their comparable logistic predictions; especially the spline predictions at the extremes of the prediction curve. The relative errors of 50% of comparable spline and logistic predictions differed by less than 20%. Monte Carlo simulation rendered acceptable asymmetric prediction intervals for both spline and logistic models while propagation of error produced symmetric intervals that diverged unrealistically as the standard curves approached horizontal asymptotes. Conclusions: The spline/PCLS/MC method is a flexible, robust alternative to a logistic/NLS/propagation-of-error method to reliably predict protein concentrations and estimate their errors. The spline method simplifies model selection and fitting, and reliably estimates believable prediction errors. For the 50% of the real data sets fit well by both methods, spline and logistic predictions are practically indistinguishable, varying in accuracy by less than 15%. The spline method may be useful when automated prediction across simultaneous assays of numerous proteins must be applied routinely with minimal user intervention.« less

The Simulation of the Recharging Method Based on Solar Radiation for an Implantable Biosensor.

PubMed

Li, Yun; Song, Yong; Kong, Xianyue; Li, Maoyuan; Zhao, Yufei; Hao, Qun; Gao, Tianxin

2016-09-10

A method of recharging implantable biosensors based on solar radiation is proposed. Firstly, the models of the proposed method are developed. Secondly, the recharging processes based on solar radiation are simulated using Monte Carlo (MC) method and the energy distributions of sunlight within the different layers of human skin have been achieved and discussed. Finally, the simulation results are verified experimentally, which indicates that the proposed method will contribute to achieve a low-cost, convenient and safe method for recharging implantable biosensors.

The Simulation of the Recharging Method Based on Solar Radiation for an Implantable Biosensor

PubMed Central

Li, Yun; Song, Yong; Kong, Xianyue; Li, Maoyuan; Zhao, Yufei; Hao, Qun; Gao, Tianxin

2016-01-01

A method of recharging implantable biosensors based on solar radiation is proposed. Firstly, the models of the proposed method are developed. Secondly, the recharging processes based on solar radiation are simulated using Monte Carlo (MC) method and the energy distributions of sunlight within the different layers of human skin have been achieved and discussed. Finally, the simulation results are verified experimentally, which indicates that the proposed method will contribute to achieve a low-cost, convenient and safe method for recharging implantable biosensors. PMID:27626422

SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Y; Southern Medical University, Guangzhou; Tian, Z

Purpose: Monte Carlo (MC) simulation is an important tool to solve radiotherapy and medical imaging problems. Low computational efficiency hinders its wide applications. Conventionally, MC is performed in a particle-by -particle fashion. The lack of control on particle trajectory is a main cause of low efficiency in some applications. Take cone beam CT (CBCT) projection simulation as an example, significant amount of computations were wasted on transporting photons that do not reach the detector. To solve this problem, we propose an innovative MC simulation scheme with a path-by-path sampling method. Methods: Consider a photon path starting at the x-ray source.more » After going through a set of interactions, it ends at the detector. In the proposed scheme, we sampled an entire photon path each time. Metropolis-Hasting algorithm was employed to accept/reject a sampled path based on a calculated acceptance probability, in order to maintain correct relative probabilities among different paths, which are governed by photon transport physics. We developed a package gMMC on GPU with this new scheme implemented. The performance of gMMC was tested in a sample problem of CBCT projection simulation for a homogeneous object. The results were compared to those obtained using gMCDRR, a GPU-based MC tool with the conventional particle-by-particle simulation scheme. Results: Calculated scattered photon signals in gMMC agreed with those from gMCDRR with a relative difference of 3%. It took 3.1 hr. for gMCDRR to simulate 7.8e11 photons and 246.5 sec for gMMC to simulate 1.4e10 paths. Under this setting, both results attained the same ∼2% statistical uncertainty. Hence, a speed-up factor of ∼45.3 was achieved by this new path-by-path simulation scheme, where all the computations were spent on those photons contributing to the detector signal. Conclusion: We innovatively proposed a novel path-by-path simulation scheme that enabled a significant efficiency enhancement for MC particle transport simulations.« less

SU-E-T-558: Monte Carlo Photon Transport Simulations On GPU with Quadric Geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chi, Y; Tian, Z; Jiang, S

Purpose: Monte Carlo simulation on GPU has experienced rapid advancements over the past a few years and tremendous accelerations have been achieved. Yet existing packages were developed only in voxelized geometry. In some applications, e.g. radioactive seed modeling, simulations in more complicated geometry are needed. This abstract reports our initial efforts towards developing a quadric geometry module aiming at expanding the application scope of GPU-based MC simulations. Methods: We defined the simulation geometry consisting of a number of homogeneous bodies, each specified by its material composition and limiting surfaces characterized by quadric functions. A tree data structure was utilized tomore » define geometric relationship between different bodies. We modified our GPU-based photon MC transport package to incorporate this geometry. Specifically, geometry parameters were loaded into GPU’s shared memory for fast access. Geometry functions were rewritten to enable the identification of the body that contains the current particle location via a fast searching algorithm based on the tree data structure. Results: We tested our package in an example problem of HDR-brachytherapy dose calculation for shielded cylinder. The dose under the quadric geometry and that under the voxelized geometry agreed in 94.2% of total voxels within 20% isodose line based on a statistical t-test (95% confidence level), where the reference dose was defined to be the one at 0.5cm away from the cylinder surface. It took 243sec to transport 100million source photons under this quadric geometry on an NVidia Titan GPU card. Compared with simulation time of 99.6sec in the voxelized geometry, including quadric geometry reduced efficiency due to the complicated geometry-related computations. Conclusion: Our GPU-based MC package has been extended to support photon transport simulation in quadric geometry. Satisfactory accuracy was observed with a reduced efficiency. Developments for charged particle transport in this geometry are currently in progress.« less

Monte Carlo MP2 on Many Graphical Processing Units.

PubMed

Doran, Alexander E; Hirata, So

2016-10-11

In the Monte Carlo second-order many-body perturbation (MC-MP2) method, the long sum-of-product matrix expression of the MP2 energy, whose literal evaluation may be poorly scalable, is recast into a single high-dimensional integral of functions of electron pair coordinates, which is evaluated by the scalable method of Monte Carlo integration. The sampling efficiency is further accelerated by the redundant-walker algorithm, which allows a maximal reuse of electron pairs. Here, a multitude of graphical processing units (GPUs) offers a uniquely ideal platform to expose multilevel parallelism: fine-grain data-parallelism for the redundant-walker algorithm in which millions of threads compute and share orbital amplitudes on each GPU; coarse-grain instruction-parallelism for near-independent Monte Carlo integrations on many GPUs with few and infrequent interprocessor communications. While the efficiency boost by the redundant-walker algorithm on central processing units (CPUs) grows linearly with the number of electron pairs and tends to saturate when the latter exceeds the number of orbitals, on a GPU it grows quadratically before it increases linearly and then eventually saturates at a much larger number of pairs. This is because the orbital constructions are nearly perfectly parallelized on a GPU and thus completed in a near-constant time regardless of the number of pairs. In consequence, an MC-MP2/cc-pVDZ calculation of a benzene dimer is 2700 times faster on 256 GPUs (using 2048 electron pairs) than on two CPUs, each with 8 cores (which can use only up to 256 pairs effectively). We also numerically determine that the cost to achieve a given relative statistical uncertainty in an MC-MP2 energy increases as O(n 3 ) or better with system size n, which may be compared with the O(n 5 ) scaling of the conventional implementation of deterministic MP2. We thus establish the scalability of MC-MP2 with both system and computer sizes.

Head-and-neck IMRT treatments assessed with a Monte Carlo dose calculation engine.

PubMed

Seco, J; Adams, E; Bidmead, M; Partridge, M; Verhaegen, F

2005-03-07

IMRT is frequently used in the head-and-neck region, which contains materials of widely differing densities (soft tissue, bone, air-cavities). Conventional methods of dose computation for these complex, inhomogeneous IMRT cases involve significant approximations. In the present work, a methodology for the development, commissioning and implementation of a Monte Carlo (MC) dose calculation engine for intensity modulated radiotherapy (MC-IMRT) is proposed which can be used by radiotherapy centres interested in developing MC-IMRT capabilities for research or clinical evaluations. The method proposes three levels for developing, commissioning and maintaining a MC-IMRT dose calculation engine: (a) development of a MC model of the linear accelerator, (b) validation of MC model for IMRT and (c) periodic quality assurance (QA) of the MC-IMRT system. The first step, level (a), in developing an MC-IMRT system is to build a model of the linac that correctly predicts standard open field measurements for percentage depth-dose and off-axis ratios. Validation of MC-IMRT, level (b), can be performed in a rando phantom and in a homogeneous water equivalent phantom. Ultimately, periodic quality assurance of the MC-IMRT system is needed to verify the MC-IMRT dose calculation system, level (c). Once the MC-IMRT dose calculation system is commissioned it can be applied to more complex clinical IMRT treatments. The MC-IMRT system implemented at the Royal Marsden Hospital was used for IMRT calculations for a patient undergoing treatment for primary disease with nodal involvement in the head-and-neck region (primary treated to 65 Gy and nodes to 54 Gy), while sparing the spinal cord, brain stem and parotid glands. Preliminary MC results predict a decrease of approximately 1-2 Gy in the median dose of both the primary tumour and nodal volumes (compared with both pencil beam and collapsed cone). This is possibly due to the large air-cavity (the larynx of the patient) situated in the centre of the primary PTV and the approximations present in the dose calculation.

Fred: a GPU-accelerated fast-Monte Carlo code for rapid treatment plan recalculation in ion beam therapy

NASA Astrophysics Data System (ADS)

Schiavi, A.; Senzacqua, M.; Pioli, S.; Mairani, A.; Magro, G.; Molinelli, S.; Ciocca, M.; Battistoni, G.; Patera, V.

2017-09-01

Ion beam therapy is a rapidly growing technique for tumor radiation therapy. Ions allow for a high dose deposition in the tumor region, while sparing the surrounding healthy tissue. For this reason, the highest possible accuracy in the calculation of dose and its spatial distribution is required in treatment planning. On one hand, commonly used treatment planning software solutions adopt a simplified beam-body interaction model by remapping pre-calculated dose distributions into a 3D water-equivalent representation of the patient morphology. On the other hand, Monte Carlo (MC) simulations, which explicitly take into account all the details in the interaction of particles with human tissues, are considered to be the most reliable tool to address the complexity of mixed field irradiation in a heterogeneous environment. However, full MC calculations are not routinely used in clinical practice because they typically demand substantial computational resources. Therefore MC simulations are usually only used to check treatment plans for a restricted number of difficult cases. The advent of general-purpose programming GPU cards prompted the development of trimmed-down MC-based dose engines which can significantly reduce the time needed to recalculate a treatment plan with respect to standard MC codes in CPU hardware. In this work, we report on the development of fred, a new MC simulation platform for treatment planning in ion beam therapy. The code can transport particles through a 3D voxel grid using a class II MC algorithm. Both primary and secondary particles are tracked and their energy deposition is scored along the trajectory. Effective models for particle-medium interaction have been implemented, balancing accuracy in dose deposition with computational cost. Currently, the most refined module is the transport of proton beams in water: single pencil beam dose-depth distributions obtained with fred agree with those produced by standard MC codes within 1-2% of the Bragg peak in the therapeutic energy range. A comparison with measurements taken at the CNAO treatment center shows that the lateral dose tails are reproduced within 2% in the field size factor test up to 20 cm. The tracing kernel can run on GPU hardware, achieving 10 million primary s-1 on a single card. This performance allows one to recalculate a proton treatment plan at 1% of the total particles in just a few minutes.

Application of the MCNPX-McStas interface for shielding calculations and guide design at ESS

NASA Astrophysics Data System (ADS)

Klinkby, E. B.; Knudsen, E. B.; Willendrup, P. K.; Lauritzen, B.; Nonbøl, E.; Bentley, P.; Filges, U.

2014-07-01

Recently, an interface between the Monte Carlo code MCNPX and the neutron ray-tracing code MCNPX was developed [1, 2]. Based on the expected neutronic performance and guide geometries relevant for the ESS, the combined MCNPX-McStas code is used to calculate dose rates along neutron beam guides. The generation and moderation of neutrons is simulated using a full scale MCNPX model of the ESS target monolith. Upon entering the neutron beam extraction region, the individual neutron states are handed to McStas via the MCNPX-McStas interface. McStas transports the neutrons through the beam guide, and by using newly developed event logging capability, the neutron state parameters corresponding to un-reflected neutrons are recorded at each scattering. This information is handed back to MCNPX where it serves as neutron source input for a second MCNPX simulation. This simulation enables calculation of dose rates in the vicinity of the guide. In addition the logging mechanism is employed to record the scatterings along the guides which is exploited to simulate the supermirror quality requirements (i.e. m-values) needed at different positions along the beam guide to transport neutrons in the same guide/source setup.

Poster - Thurs Eve-23: Effect of lung density and geometry variation on inhomogeneity correction algorithms: A Monte Carlo dosimetry evaluation.

PubMed

Chow, J; Leung, M; Van Dyk, J

2008-07-01

This study provides new information on the evaluation of the lung dose calculation algorithms as a function of the relative electron density of lung, ρ e,lung . Doses calculated using the collapsed cone convolution (CCC) and adaptive convolution (AC) algorithm in lung with the Pinnacle 3 system were compared to those calculated using the Monte Carlo (MC) simulation (EGSnrc-based code). Three groups of lung phantoms, namely, "Slab", "Column" and "Cube" with different ρ e,lung (0.05-0.7), positions, volumes and shapes of lung in water were used. 6 and 18MV photon beams with 4×4 and 10×10cm 2 field sizes produced by a Varian 21EX Linac were used in the MC dose calculations. Results show that the CCC algorithm agrees well with AC to within ±1% for doses calculated in the lung phantoms, indicating that the AC, with 3-4 times less computing time required than CCC, is a good substitute for the CCC method. Comparing the CCC and AC with MC, dose deviations are found when ρ e,lung are ⩽0.1-0.3. The degree of deviation depends on the photon beam energy and field size, and is relatively large when high-energy photon beams with small field are used. For the penumbra widths (20%-80%), the CCC and AC agree well with MC for the "Slab" and "Cube" phantoms with the lung volumes at the central beam axis (CAX). However, deviations >2mm occur in the "Column" phantoms, with two lung volumes separated by a water column along the CAX, using the 18MV (4×4cm 2 ) photon beams with ρ e,lung ⩽0.1. © 2008 American Association of Physicists in Medicine.

Maier-Saupe model of polymer nematics: Comparing free energies calculated with Self Consistent Field theory and Monte Carlo simulations.

PubMed

Greco, Cristina; Jiang, Ying; Chen, Jeff Z Y; Kremer, Kurt; Daoulas, Kostas Ch

2016-11-14

Self Consistent Field (SCF) theory serves as an efficient tool for studying mesoscale structure and thermodynamics of polymeric liquid crystals (LC). We investigate how some of the intrinsic approximations of SCF affect the description of the thermodynamics of polymeric LC, using a coarse-grained model. Polymer nematics are represented as discrete worm-like chains (WLC) where non-bonded interactions are defined combining an isotropic repulsive and an anisotropic attractive Maier-Saupe (MS) potential. The range of the potentials, σ, controls the strength of correlations due to non-bonded interactions. Increasing σ (which can be seen as an increase of coarse-graining) while preserving the integrated strength of the potentials reduces correlations. The model is studied with particle-based Monte Carlo (MC) simulations and SCF theory which uses partial enumeration to describe discrete WLC. In MC simulations the Helmholtz free energy is calculated as a function of strength of MS interactions to obtain reference thermodynamic data. To calculate the free energy of the nematic branch with respect to the disordered melt, we employ a special thermodynamic integration (TI) scheme invoking an external field to bypass the first-order isotropic-nematic transition. Methodological aspects which have not been discussed in earlier implementations of the TI to LC are considered. Special attention is given to the rotational Goldstone mode. The free-energy landscape in MC and SCF is directly compared. For moderate σ the differences highlight the importance of local non-bonded orientation correlations between segments, which SCF neglects. Simple renormalization of parameters in SCF cannot compensate the missing correlations. Increasing σ reduces correlations and SCF reproduces well the free energy in MC simulations.

Monte Carlo simulations of a low energy proton beamline for radiobiological experiments.

PubMed

Dahle, Tordis J; Rykkelid, Anne Marit; Stokkevåg, Camilla H; Mairani, Andrea; Görgen, Andreas; Edin, Nina J; Rørvik, Eivind; Fjæra, Lars Fredrik; Malinen, Eirik; Ytre-Hauge, Kristian S

2017-06-01

In order to determine the relative biological effectiveness (RBE) of protons with high accuracy, radiobiological experiments with detailed knowledge of the linear energy transfer (LET) are needed. Cell survival data from high LET protons are sparse and experiments with low energy protons to achieve high LET values are therefore required. The aim of this study was to quantify LET distributions from a low energy proton beam by using Monte Carlo (MC) simulations, and to further compare to a proton beam representing a typical minimum energy available at clinical facilities. A Markus ionization chamber and Gafchromic films were employed in dose measurements in the proton beam at Oslo Cyclotron Laboratory. Dose profiles were also calculated using the FLUKA MC code, with the MC beam parameters optimized based on comparisons with the measurements. LET spectra and dose-averaged LET (LET d ) were then estimated in FLUKA, and compared with LET calculated from an 80 MeV proton beam. The initial proton energy was determined to be 15.5 MeV, with a Gaussian energy distribution of 0.2% full width at half maximum (FWHM) and a Gaussian lateral spread of 2 mm FWHM. The LET d increased with depth, from approximately 5 keV/μm in the entrance to approximately 40 keV/μm in the distal dose fall-off. The LET d values were considerably higher and the LET spectra were much narrower than the corresponding spectra from the 80 MeV beam. MC simulations accurately modeled the dose distribution from the proton beam and could be used to estimate the LET at any position in the setup. The setup can be used to study the RBE for protons at high LET d , which is not achievable in clinical proton therapy facilities.

Absolute dose calculations for Monte Carlo simulations of radiotherapy beams.

PubMed

Popescu, I A; Shaw, C P; Zavgorodni, S F; Beckham, W A

2005-07-21

Monte Carlo (MC) simulations have traditionally been used for single field relative comparisons with experimental data or commercial treatment planning systems (TPS). However, clinical treatment plans commonly involve more than one field. Since the contribution of each field must be accurately quantified, multiple field MC simulations are only possible by employing absolute dosimetry. Therefore, we have developed a rigorous calibration method that allows the incorporation of monitor units (MU) in MC simulations. This absolute dosimetry formalism can be easily implemented by any BEAMnrc/DOSXYZnrc user, and applies to any configuration of open and blocked fields, including intensity-modulated radiation therapy (IMRT) plans. Our approach involves the relationship between the dose scored in the monitor ionization chamber of a radiotherapy linear accelerator (linac), the number of initial particles incident on the target, and the field size. We found that for a 10 x 10 cm2 field of a 6 MV photon beam, 1 MU corresponds, in our model, to 8.129 x 10(13) +/- 1.0% electrons incident on the target and a total dose of 20.87 cGy +/- 1.0% in the monitor chambers of the virtual linac. We present an extensive experimental verification of our MC results for open and intensity-modulated fields, including a dynamic 7-field IMRT plan simulated on the CT data sets of a cylindrical phantom and of a Rando anthropomorphic phantom, which were validated by measurements using ionization chambers and thermoluminescent dosimeters (TLD). Our simulation results are in excellent agreement with experiment, with percentage differences of less than 2%, in general, demonstrating the accuracy of our Monte Carlo absolute dose calculations.

ACCELERATING FUSION REACTOR NEUTRONICS MODELING BY AUTOMATIC COUPLING OF HYBRID MONTE CARLO/DETERMINISTIC TRANSPORT ON CAD GEOMETRY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biondo, Elliott D; Ibrahim, Ahmad M; Mosher, Scott W

2015-01-01

Detailed radiation transport calculations are necessary for many aspects of the design of fusion energy systems (FES) such as ensuring occupational safety, assessing the activation of system components for waste disposal, and maintaining cryogenic temperatures within superconducting magnets. Hybrid Monte Carlo (MC)/deterministic techniques are necessary for this analysis because FES are large, heavily shielded, and contain streaming paths that can only be resolved with MC. The tremendous complexity of FES necessitates the use of CAD geometry for design and analysis. Previous ITER analysis has required the translation of CAD geometry to MCNP5 form in order to use the AutomateD VAriaNcemore » reducTion Generator (ADVANTG) for hybrid MC/deterministic transport. In this work, ADVANTG was modified to support CAD geometry, allowing hybrid (MC)/deterministic transport to be done automatically and eliminating the need for this translation step. This was done by adding a new ray tracing routine to ADVANTG for CAD geometries using the Direct Accelerated Geometry Monte Carlo (DAGMC) software library. This new capability is demonstrated with a prompt dose rate calculation for an ITER computational benchmark problem using both the Consistent Adjoint Driven Importance Sampling (CADIS) method an the Forward Weighted (FW)-CADIS method. The variance reduction parameters produced by ADVANTG are shown to be the same using CAD geometry and standard MCNP5 geometry. Significant speedups were observed for both neutrons (as high as a factor of 7.1) and photons (as high as a factor of 59.6).« less

Raman Monte Carlo simulation for light propagation for tissue with embedded objects

NASA Astrophysics Data System (ADS)

Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

2018-02-01

Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

A hybrid (Monte Carlo/deterministic) approach for multi-dimensional radiation transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bal, Guillaume, E-mail: gb2030@columbia.edu; Davis, Anthony B., E-mail: Anthony.B.Davis@jpl.nasa.gov; Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106-4030

2011-08-20

Highlights: {yields} We introduce a variance reduction scheme for Monte Carlo (MC) transport. {yields} The primary application is atmospheric remote sensing. {yields} The technique first solves the adjoint problem using a deterministic solver. {yields} Next, the adjoint solution is used as an importance function for the MC solver. {yields} The adjoint problem is solved quickly since it ignores the volume. - Abstract: A novel hybrid Monte Carlo transport scheme is demonstrated in a scene with solar illumination, scattering and absorbing 2D atmosphere, a textured reflecting mountain, and a small detector located in the sky (mounted on a satellite or amore » airplane). It uses a deterministic approximation of an adjoint transport solution to reduce variance, computed quickly by ignoring atmospheric interactions. This allows significant variance and computational cost reductions when the atmospheric scattering and absorption coefficient are small. When combined with an atmospheric photon-redirection scheme, significant variance reduction (equivalently acceleration) is achieved in the presence of atmospheric interactions.« less

Split exponential track length estimator for Monte-Carlo simulations of small-animal radiation therapy

NASA Astrophysics Data System (ADS)

Smekens, F.; Létang, J. M.; Noblet, C.; Chiavassa, S.; Delpon, G.; Freud, N.; Rit, S.; Sarrut, D.

2014-12-01

We propose the split exponential track length estimator (seTLE), a new kerma-based method combining the exponential variant of the TLE and a splitting strategy to speed up Monte Carlo (MC) dose computation for low energy photon beams. The splitting strategy is applied to both the primary and the secondary emitted photons, triggered by either the MC events generator for primaries or the photon interactions generator for secondaries. Split photons are replaced by virtual particles for fast dose calculation using the exponential TLE. Virtual particles are propagated by ray-tracing in voxelized volumes and by conventional MC navigation elsewhere. Hence, the contribution of volumes such as collimators, treatment couch and holding devices can be taken into account in the dose calculation. We evaluated and analysed the seTLE method for two realistic small animal radiotherapy treatment plans. The effect of the kerma approximation, i.e. the complete deactivation of electron transport, was investigated. The efficiency of seTLE against splitting multiplicities was also studied. A benchmark with analog MC and TLE was carried out in terms of dose convergence and efficiency. The results showed that the deactivation of electrons impacts the dose at the water/bone interface in high dose regions. The maximum and mean dose differences normalized to the dose at the isocenter were, respectively of 14% and 2% . Optimal splitting multiplicities were found to be around 300. In all situations, discrepancies in integral dose were below 0.5% and 99.8% of the voxels fulfilled a 1%/0.3 mm gamma index criterion. Efficiency gains of seTLE varied from 3.2 × 105 to 7.7 × 105 compared to analog MC and from 13 to 15 compared to conventional TLE. In conclusion, seTLE provides results similar to the TLE while increasing the efficiency by a factor between 13 and 15, which makes it particularly well-suited to typical small animal radiation therapy applications.

Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

NASA Astrophysics Data System (ADS)

Guerra, Pedro; Udías, José M.; Herranz, Elena; Santos-Miranda, Juan Antonio; Herraiz, Joaquín L.; Valdivieso, Manlio F.; Rodríguez, Raúl; Calama, Juan A.; Pascau, Javier; Calvo, Felipe A.; Illana, Carlos; Ledesma-Carbayo, María J.; Santos, Andrés

2014-12-01

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation.

SU-F-J-14: Kilovoltage Cone-Beam CT Dose Estimation of Varian On-Board Imager Using GMctdospp Monte Carlo Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, S; Rangaraj, D

2016-06-15

Purpose: Although cone-beam CT (CBCT) imaging became popular in radiation oncology, its imaging dose estimation is still challenging. The goal of this study is to assess the kilovoltage CBCT doses using GMctdospp - an EGSnrc based Monte Carlo (MC) framework. Methods: Two Varian OBI x-ray tube models were implemented in the GMctpdospp framework of EGSnrc MC System. The x-ray spectrum of 125 kVp CBCT beam was acquired from an EGSnrc/BEAMnrc simulation and validated with IPEM report 78. Then, the spectrum was utilized as an input spectrum in GMctdospp dose calculations. Both full and half bowtie pre-filters of the OBI systemmore » were created by using egs-prism module. The x-ray tube MC models were verified by comparing calculated dosimetric profiles (lateral and depth) to ion chamber measurements for a static x-ray beam irradiation to a cuboid water phantom. An abdominal CBCT imaging doses was simulated in GMctdospp framework using a 5-year-old anthropomorphic phantom. The organ doses and effective dose (ED) from the framework were assessed and compared to the MOSFET measurements and convolution/superposition dose calculations. Results: The lateral and depth dose profiles in the water cuboid phantom were well matched within 6% except a few areas - left shoulder of the half bowtie lateral profile and surface of water phantom. The organ doses and ED from the MC framework were found to be closer to MOSFET measurements and CS calculations within 2 cGy and 5 mSv respectively. Conclusion: This study implemented and validated the Varian OBI x-ray tube models in the GMctdospp MC framework using a cuboid water phantom and CBCT imaging doses were also evaluated in a 5-year-old anthropomorphic phantom. In future study, various CBCT imaging protocols will be implemented and validated and consequently patient CT images will be used to estimate the CBCT imaging doses in patients.« less

SU-F-T-54: Determination of the AAPM TG-43 Brachytherapy Dosimetry Parameters for A New Titanium-Encapsulated Yb-169 Source by Monte Carlo Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reynoso, F; Washington University School of Medicine, St. Louis, MO; Munro, J

2016-06-15

Purpose: To determine the AAPM TG-43 brachytherapy dosimetry parameters of a new titanium-encapsulated Yb-169 source designed to maximize the dose enhancement during gold nanoparticle-aided radiation therapy (GNRT). Methods: An existing Monte Carlo (MC) model of the titanium-encapsulated Yb-169 source, which was described in the current investigators’ published MC optimization study, was modified based on the source manufacturer’s detailed specifications, resulting in an accurate model of the titanium-encapsulated Yb-169 source that was actually manufactured. MC calculations were then performed using the MCNP5 code system and the modified source model, in order to obtain a complete set of the AAPM TG-43 parametersmore » for the new Yb-169 source. Results: The MC-calculated dose rate constant for the new titanium-encapsulated Yb-169 source was 1.05 ± 0.03 cGy per hr U, indicating about 10% decrease from the values reported for the conventional stainless steel-encapsulated Yb-169 sources. The source anisotropy and radial dose function for the new source were found similar to those reported for the conventional Yb-169 sources. Conclusion: In this study, the AAPM TG-43 brachytherapy dosimetry parameters of a new titanium-encapsulated Yb-169 source were determined by MC calculations. The current results suggested that the use of titanium, instead of stainless steel, to encapsulate the Yb-169 core would not lead to any major change in the dosimetric characteristics of the Yb-169 source, while it would allow more low energy photons being transmitted through the source filter thereby leading to an increased dose enhancement during GNRT. Supported by DOD/PCRP grant W81XWH-12-1-0198 This investigation was supported by DOD/PCRP grant W81XWH-12-1- 0198.« less

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

NASA Astrophysics Data System (ADS)

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-01

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed. This work was presented in part at the 2010 Annual Meeting of the American Association of Physicists in Medicine (AAPM), Philadelphia, PA.

Lens implementation on the GATE Monte Carlo toolkit for optical imaging simulation

NASA Astrophysics Data System (ADS)

Kang, Han Gyu; Song, Seong Hyun; Han, Young Been; Kim, Kyeong Min; Hong, Seong Jong

2018-02-01

Optical imaging techniques are widely used for in vivo preclinical studies, and it is well known that the Geant4 Application for Emission Tomography (GATE) can be employed for the Monte Carlo (MC) modeling of light transport inside heterogeneous tissues. However, the GATE MC toolkit is limited in that it does not yet include optical lens implementation, even though this is required for a more realistic optical imaging simulation. We describe our implementation of a biconvex lens into the GATE MC toolkit to improve both the sensitivity and spatial resolution for optical imaging simulation. The lens implemented into the GATE was validated against the ZEMAX optical simulation using an US air force 1951 resolution target. The ray diagrams and the charge-coupled device images of the GATE optical simulation agreed with the ZEMAX optical simulation results. In conclusion, the use of a lens on the GATE optical simulation could improve the image quality of bioluminescence and fluorescence significantly as compared with pinhole optics.

Numerical simulation studies for optical properties of biomaterials

NASA Astrophysics Data System (ADS)

Krasnikov, I.; Seteikin, A.

2016-11-01

Biophotonics involves understanding how light interacts with biological matter, from molecules and cells, to tissues and even whole organisms. Light can be used to probe biomolecular events, such as gene expression and protein-protein interaction, with impressively high sensitivity and specificity. The spatial and temporal distribution of biochemical constituents can also be visualized with light and, thus, the corresponding physiological dynamics in living cells, tissues, and organisms in real time. Computer-based Monte Carlo (MC) models of light transport in turbid media take a different approach. In this paper, the optical and structural properties of biomaterials discussed. We explain the numerical simulationmethod used for studying the optical properties of biomaterials. Applications of the Monte-Carlo method in photodynamic therapy, skin tissue optics, and bioimaging described.

Space Object Collision Probability via Monte Carlo on the Graphics Processing Unit

NASA Astrophysics Data System (ADS)

Vittaldev, Vivek; Russell, Ryan P.

2017-09-01

Fast and accurate collision probability computations are essential for protecting space assets. Monte Carlo (MC) simulation is the most accurate but computationally intensive method. A Graphics Processing Unit (GPU) is used to parallelize the computation and reduce the overall runtime. Using MC techniques to compute the collision probability is common in literature as the benchmark. An optimized implementation on the GPU, however, is a challenging problem and is the main focus of the current work. The MC simulation takes samples from the uncertainty distributions of the Resident Space Objects (RSOs) at any time during a time window of interest and outputs the separations at closest approach. Therefore, any uncertainty propagation method may be used and the collision probability is automatically computed as a function of RSO collision radii. Integration using a fixed time step and a quartic interpolation after every Runge Kutta step ensures that no close approaches are missed. Two orders of magnitude speedups over a serial CPU implementation are shown, and speedups improve moderately with higher fidelity dynamics. The tool makes the MC approach tractable on a single workstation, and can be used as a final product, or for verifying surrogate and analytical collision probability methods.

Evaluation and optimization of sampling errors for the Monte Carlo Independent Column Approximation

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Barker, W. Howard

2004-07-01

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average broadband radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. McICA's sampling errors are evaluated here using a global climate model (GCM) dataset and a correlated-k distribution (CKD) radiation scheme. Two approaches to reduce McICA's sampling variance are discussed. The first is to simply restrict all of McICA's samples to cloudy regions. This avoids wasting precious few samples on essentially homogeneous clear skies. Clear-sky fluxes need to be computed separately for this approach, but this is usually done in GCMs for diagnostic purposes anyway. Second, accuracy can be improved by repeated sampling, and averaging those CKD terms with large cloud radiative effects. Although this naturally increases computational costs over the standard CKD model, random errors for fluxes and heating rates are reduced by typically 50% to 60%, for the present radiation code, when the total number of samples is increased by 50%. When both variance reduction techniques are applied simultaneously, globally averaged flux and heating rate random errors are reduced by a factor of #3.

Assessing the convergence of LHS Monte Carlo simulations of wastewater treatment models.

PubMed

Benedetti, Lorenzo; Claeys, Filip; Nopens, Ingmar; Vanrolleghem, Peter A

2011-01-01

Monte Carlo (MC) simulation appears to be the only currently adopted tool to estimate global sensitivities and uncertainties in wastewater treatment modelling. Such models are highly complex, dynamic and non-linear, requiring long computation times, especially in the scope of MC simulation, due to the large number of simulations usually required. However, no stopping rule to decide on the number of simulations required to achieve a given confidence in the MC simulation results has been adopted so far in the field. In this work, a pragmatic method is proposed to minimize the computation time by using a combination of several criteria. It makes no use of prior knowledge about the model, is very simple, intuitive and can be automated: all convenient features in engineering applications. A case study is used to show an application of the method, and the results indicate that the required number of simulations strongly depends on the model output(s) selected, and on the type and desired accuracy of the analysis conducted. Hence, no prior indication is available regarding the necessary number of MC simulations, but the proposed method is capable of dealing with these variations and stopping the calculations after convergence is reached.

MO-E-18C-02: Hands-On Monte Carlo Project Assignment as a Method to Teach Radiation Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pater, P; Vallieres, M; Seuntjens, J

2014-06-15

Purpose: To present a hands-on project on Monte Carlo methods (MC) recently added to the curriculum and to discuss the students' appreciation. Methods: Since 2012, a 1.5 hour lecture dedicated to MC fundamentals follows the detailed presentation of photon and electron interactions. Students also program all sampling steps (interaction length and type, scattering angle, energy deposit) of a MC photon transport code. A handout structured in a step-by-step fashion guides student in conducting consistency checks. For extra points, students can code a fully working MC simulation, that simulates a dose distribution for 50 keV photons. A kerma approximation to dosemore » deposition is assumed. A survey was conducted to which 10 out of the 14 attending students responded. It compared MC knowledge prior to and after the project, questioned the usefulness of radiation physics teaching through MC and surveyed possible project improvements. Results: According to the survey, 76% of students had no or a basic knowledge of MC methods before the class and 65% estimate to have a good to very good understanding of MC methods after attending the class. 80% of students feel that the MC project helped them significantly to understand simulations of dose distributions. On average, students dedicated 12.5 hours to the project and appreciated the balance between hand-holding and questions/implications. Conclusion: A lecture on MC methods with a hands-on MC programming project requiring about 14 hours was added to the graduate study curriculum since 2012. MC methods produce “gold standard” dose distributions and slowly enter routine clinical work and a fundamental understanding of MC methods should be a requirement for future students. Overall, the lecture and project helped students relate crosssections to dose depositions and presented numerical sampling methods behind the simulation of these dose distributions. Research funding from governments of Canada and Quebec. PP acknowledges partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290)« less

On the definition of a Monte Carlo model for binary crystal growth.

PubMed

Los, J H; van Enckevort, W J P; Meekes, H; Vlieg, E

2007-02-01

We show that consistency of the transition probabilities in a lattice Monte Carlo (MC) model for binary crystal growth with the thermodynamic properties of a system does not guarantee the MC simulations near equilibrium to be in agreement with the thermodynamic equilibrium phase diagram for that system. The deviations remain small for systems with small bond energies, but they can increase significantly for systems with large melting entropy, typical for molecular systems. These deviations are attributed to the surface kinetics, which is responsible for a metastable zone below the liquidus line where no growth occurs, even in the absence of a 2D nucleation barrier. Here we propose an extension of the MC model that introduces a freedom of choice in the transition probabilities while staying within the thermodynamic constraints. This freedom can be used to eliminate the discrepancy between the MC simulations and the thermodynamic equilibrium phase diagram. Agreement is achieved for that choice of the transition probabilities yielding the fastest decrease of the free energy (i.e., largest growth rate) of the system at a temperature slightly below the equilibrium temperature. An analytical model is developed, which reproduces quite well the MC results, enabling a straightforward determination of the optimal set of transition probabilities. Application of both the MC and analytical model to conditions well away from equilibrium, giving rise to kinetic phase diagrams, shows that the effect of kinetics on segregation is even stronger than that predicted by previous models.

Twomey Effect in Subtropical Stratocumulus Clouds from UV Depolarization LIDAR

NASA Astrophysics Data System (ADS)

de Graaf, Martin; Brown, Jessica; Donovan, David

2018-04-01

Marine stratocumulus clouds are important climate regulators, reflecting sunlight over a dark ocean background. A UV-depolarization lidar on Ascension, a small remote island in the south Atlantic, measured cloud droplet sizes and number concentration using an inversion method based on Monte Carlo (MC) modelling of multiple scattering in idealised semiadiabatic clouds. The droplet size and number concentration weremodulated due to smoke from the African continent, measured by the same instrument.

Monte-Carlo simulation of a stochastic differential equation

NASA Astrophysics Data System (ADS)

Arif, ULLAH; Majid, KHAN; M, KAMRAN; R, KHAN; Zhengmao, SHENG

2017-12-01

For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient, Monte Carlo (MC) techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem. Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

Adatom lifetime in film growth at solid surfaces in the framework of the Johnson Mehl Avrami Kolmogorov model

NASA Astrophysics Data System (ADS)

Tomellini, M.; Fanfoni, M.

1999-10-01

On the basis of the quasi-static approximation and for simultaneous nucleation the adatom lifetime, τ, during film growth at solid surfaces has been computed by Monte Carlo (MC) simulation. The quantity DN0τ, N0 and D being respectively the cluster density and the adatom diffusion coefficient, is found to depend upon the portion of surface covered by clusters and, very weakly, on N0. Moreover, a stochastic approach based on the Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory has been developed to obtain the analytical expression of the MC curve. The collision factor of the mean island has been calculated and compared with those previously obtained from the uniform depletion approximation and the lattice approximation.

On Fitting a Multivariate Two-Part Latent Growth Model

PubMed Central

Xu, Shu; Blozis, Shelley A.; Vandewater, Elizabeth A.

2017-01-01

A 2-part latent growth model can be used to analyze semicontinuous data to simultaneously study change in the probability that an individual engages in a behavior, and if engaged, change in the behavior. This article uses a Monte Carlo (MC) integration algorithm to study the interrelationships between the growth factors of 2 variables measured longitudinally where each variable can follow a 2-part latent growth model. A SAS macro implementing Mplus is developed to estimate the model to take into account the sampling uncertainty of this simulation-based computational approach. A sample of time-use data is used to show how maximum likelihood estimates can be obtained using a rectangular numerical integration method and an MC integration method. PMID:29333054

InAs wetting layer and quantum dots on GaAs(001) surface studied by in situ STM placed inside MBE growth chamber and kMC simulations based on first-principles calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsukamoto, S.; Arakawa, Y.; Bell, G. R.

2007-04-10

Dynamic images of InAs quantum dots (QDs) formation are obtained using a unique scanning tunneling microscope (STM) placed within the growth chamber. These images are interpreted with the aid of kinetic Monte Carlo (kMC) simulations of the QD nucleation process. Alloy fluctuations in the InGaAs wetting layer prior to QD formation assist in the nucleation of stable InAs islands containing tens of atoms which grow extremely rapidly to form QDs. Furthermore, not all deposited In is initially incorporated into the lattice, providing a large supply of material to rapidly form QDs at the critical thickness.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y. M., E-mail: ymingy@gmail.com; Bednarz, B.; Svatos, M.

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship withinmore » a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead.« less

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taleei, R; Qin, N; Jiang, S

2016-06-15

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relativemore » Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.« less

MCViNE- An object oriented Monte Carlo neutron ray tracing simulation package

DOE PAGES

Lin, J. Y. Y.; Smith, Hillary L.; Granroth, Garrett E.; ...

2015-11-28

MCViNE (Monte-Carlo VIrtual Neutron Experiment) is an open-source Monte Carlo (MC) neutron ray-tracing software for performing computer modeling and simulations that mirror real neutron scattering experiments. We exploited the close similarity between how instrument components are designed and operated and how such components can be modeled in software. For example we used object oriented programming concepts for representing neutron scatterers and detector systems, and recursive algorithms for implementing multiple scattering. Combining these features together in MCViNE allows one to handle sophisticated neutron scattering problems in modern instruments, including, for example, neutron detection by complex detector systems, and single and multiplemore » scattering events in a variety of samples and sample environments. In addition, MCViNE can use simulation components from linear-chain-based MC ray tracing packages which facilitates porting instrument models from those codes. Furthermore it allows for components written solely in Python, which expedites prototyping of new components. These developments have enabled detailed simulations of neutron scattering experiments, with non-trivial samples, for time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. As a result, with simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.« less

SU-E-T-632: Preliminary Study On Treating Nose Skin Using Energy and Intensity Modulated Electron Beams with Monte Carlo Based Dose Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, L; Eldib, A; Li, J

Purpose: Uneven nose surfaces and air cavities underneath and the use of bolus present complexity and dose uncertainty when using a single electron energy beam to plan treatments of nose skin with a pencil beam-based planning system. This work demonstrates more accurate dose calculation and more optimal planning using energy and intensity modulated electron radiotherapy (MERT) delivered with a pMLC. Methods: An in-house developed Monte Carlo (MC)-based dose calculation/optimization planning system was employed for treatment planning. Phase space data (6, 9, 12 and 15 MeV) were used as an input source for MC dose calculations for the linac. To reducemore » the scatter-caused penumbra, a short SSD (61 cm) was used. Our previous work demonstrates good agreement in percentage depth dose and off-axis dose between calculations and film measurement for various field sizes. A MERT plan was generated for treating the nose skin using a patient geometry and a dose volume histogram (DVH) was obtained. The work also shows the comparison of 2D dose distributions between a clinically used conventional single electron energy plan and the MERT plan. Results: The MERT plan resulted in improved target dose coverage as compared to the conventional plan, which demonstrated a target dose deficit at the field edge. The conventional plan showed higher dose normal tissue irradiation underneath the nose skin while the MERT plan resulted in improved conformity and thus reduces normal tissue dose. Conclusion: This preliminary work illustrates that MC-based MERT planning is a promising technique in treating nose skin, not only providing more accurate dose calculation, but also offering an improved target dose coverage and conformity. In addition, this technique may eliminate the necessity of bolus, which often produces dose delivery uncertainty due to the air gaps that may exist between the bolus and skin.« less

Recommendations for dose calculations of lung cancer treatment plans treated with stereotactic ablative body radiotherapy (SABR)

NASA Astrophysics Data System (ADS)

Devpura, S.; Siddiqui, M. S.; Chen, D.; Liu, D.; Li, H.; Kumar, S.; Gordon, J.; Ajlouni, M.; Movsas, B.; Chetty, I. J.

2014-03-01

The purpose of this study was to systematically evaluate dose distributions computed with 5 different dose algorithms for patients with lung cancers treated using stereotactic ablative body radiotherapy (SABR). Treatment plans for 133 lung cancer patients, initially computed with a 1D-pencil beam (equivalent-path-length, EPL-1D) algorithm, were recalculated with 4 other algorithms commissioned for treatment planning, including 3-D pencil-beam (EPL-3D), anisotropic analytical algorithm (AAA), collapsed cone convolution superposition (CCC), and Monte Carlo (MC). The plan prescription dose was 48 Gy in 4 fractions normalized to the 95% isodose line. Tumors were classified according to location: peripheral tumors surrounded by lung (lung-island, N=39), peripheral tumors attached to the rib-cage or chest wall (lung-wall, N=44), and centrally-located tumors (lung-central, N=50). Relative to the EPL-1D algorithm, PTV D95 and mean dose values computed with the other 4 algorithms were lowest for "lung-island" tumors with smallest field sizes (3-5 cm). On the other hand, the smallest differences were noted for lung-central tumors treated with largest field widths (7-10 cm). Amongst all locations, dose distribution differences were most strongly correlated with tumor size for lung-island tumors. For most cases, convolution/superposition and MC algorithms were in good agreement. Mean lung dose (MLD) values computed with the EPL-1D algorithm were highly correlated with that of the other algorithms (correlation coefficient =0.99). The MLD values were found to be ~10% lower for small lung-island tumors with the model-based (conv/superposition and MC) vs. the correction-based (pencil-beam) algorithms with the model-based algorithms predicting greater low dose spread within the lungs. This study suggests that pencil beam algorithms should be avoided for lung SABR planning. For the most challenging cases, small tumors surrounded entirely by lung tissue (lung-island type), a Monte-Carlo-based algorithm may be warranted.

Independent Monte-Carlo dose calculation for MLC based CyberKnife radiotherapy

NASA Astrophysics Data System (ADS)

Mackeprang, P.-H.; Vuong, D.; Volken, W.; Henzen, D.; Schmidhalter, D.; Malthaner, M.; Mueller, S.; Frei, D.; Stampanoni, M. F. M.; Dal Pra, A.; Aebersold, D. M.; Fix, M. K.; Manser, P.

2018-01-01

This work aims to develop, implement and validate a Monte Carlo (MC)-based independent dose calculation (IDC) framework to perform patient-specific quality assurance (QA) for multi-leaf collimator (MLC)-based CyberKnife® (Accuray Inc., Sunnyvale, CA) treatment plans. The IDC framework uses an XML-format treatment plan as exported from the treatment planning system (TPS) and DICOM format patient CT data, an MC beam model using phase spaces, CyberKnife MLC beam modifier transport using the EGS++ class library, a beam sampling and coordinate transformation engine and dose scoring using DOSXYZnrc. The framework is validated against dose profiles and depth dose curves of single beams with varying field sizes in a water tank in units of cGy/Monitor Unit and against a 2D dose distribution of a full prostate treatment plan measured with Gafchromic EBT3 (Ashland Advanced Materials, Bridgewater, NJ) film in a homogeneous water-equivalent slab phantom. The film measurement is compared to IDC results by gamma analysis using 2% (global)/2 mm criteria. Further, the dose distribution of the clinical treatment plan in the patient CT is compared to TPS calculation by gamma analysis using the same criteria. Dose profiles from IDC calculation in a homogeneous water phantom agree within 2.3% of the global max dose or 1 mm distance to agreement to measurements for all except the smallest field size. Comparing the film measurement to calculated dose, 99.9% of all voxels pass gamma analysis, comparing dose calculated by the IDC framework to TPS calculated dose for the clinical prostate plan shows 99.0% passing rate. IDC calculated dose is found to be up to 5.6% lower than dose calculated by the TPS in this case near metal fiducial markers. An MC-based modular IDC framework was successfully developed, implemented and validated against measurements and is now available to perform patient-specific QA by IDC.

Monte Carlo replica-exchange based ensemble docking of protein conformations.

PubMed

Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin

2017-05-01

A replica-exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein-protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1-2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924-937. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

EDITORIAL: International Workshop on Current Topics in Monte Carlo Treatment Planning

NASA Astrophysics Data System (ADS)

Verhaegen, Frank; Seuntjens, Jan

2005-03-01

The use of Monte Carlo particle transport simulations in radiotherapy was pioneered in the early nineteen-seventies, but it was not until the eighties that they gained recognition as an essential research tool for radiation dosimetry, health physics and later on for radiation therapy treatment planning. Since the mid-nineties, there has been a boom in the number of workers using MC techniques in radiotherapy, and the quantity of papers published on the subject. Research and applications of MC techniques in radiotherapy span a very wide range from fundamental studies of cross sections and development of particle transport algorithms, to clinical evaluation of treatment plans for a variety of radiotherapy modalities. The International Workshop on Current Topics in Monte Carlo Treatment Planning took place at Montreal General Hospital, which is part of McGill University, halfway up Mount Royal on Montreal Island. It was held from 3-5 May, 2004, right after the freezing winter has lost its grip on Canada. About 120 workers attended the Workshop, representing 18 countries. Most of the pioneers in the field were present but also a large group of young scientists. In a very full programme, 41 long papers were presented (of which 12 were invited) and 20 posters were on display during the whole meeting. The topics covered included the latest developments in MC algorithms, statistical issues, source modelling and MC treatment planning for photon, electron and proton treatments. The final day was entirely devoted to clinical implementation issues. Monte Carlo radiotherapy treatment planning has only now made a slow entrée in the clinical environment, taking considerably longer than envisaged ten years ago. Of the twenty-five papers in this dedicated special issue, about a quarter deal with this topic, with probably many more studies to follow in the near future. If anything, we hope the Workshop served as an accelerator for more clinical evaluation of MC applications. The remainder of the papers in this issue demonstrate that there is still plenty of work to be undertaken on other topics such as source modelling, calculation speed, data analysis, and development of user-friendly applications. We acknowledge the financial support of the National Cancer Institute of Canada, the Institute of Cancer Research of the Canadian Institutes of Health Research, the Research Grants Office and the Post Graduate Student Society of McGill University, and the Institute of Physics Publishing (IOPP). A final word of thanks goes out to all of those who contributed to the successful Workshop: our local medical physics students and staff, the many colleagues who acted as guest associate editors for the reviewing process, the IOPP staff, and the authors who generated new and exciting work.

CT-based MCNPX dose calculations for gynecology brachytherapy employing a Henschke applicator

NASA Astrophysics Data System (ADS)

Yu, Pei-Chieh; Nien, Hsin-Hua; Tung, Chuan-Jong; Lee, Hsing-Yi; Lee, Chung-Chi; Wu, Ching-Jung; Chao, Tsi-Chian

2017-11-01

The purpose of this study is to investigate the dose perturbation caused by the metal ovoid structures of a Henschke applicator using Monte Carlo simulation in a realistic phantom. The Henschke applicator has been widely used for gynecologic patients treated by brachytherapy in Taiwan. However, the commercial brachytherapy planning system (BPS) did not properly evaluate the dose perturbation caused by its metal ovoid structures. In this study, Monte Carlo N-Particle Transport Code eXtended (MCNPX) was used to evaluate the brachytherapy dose distribution of a Henschke applicator embedded in a Plastic water phantom and a heterogeneous patient computed tomography (CT) phantom. The dose comparison between the MC simulations and film measurements for a Plastic water phantom with Henschke applicator were in good agreement. However, MC dose with the Henschke applicator showed significant deviation (-80.6%±7.5%) from those without Henschke applicator. Furthermore, the dose discrepancy in the heterogeneous patient CT phantom and Plastic water phantom CT geometries with Henschke applicator showed 0 to -26.7% dose discrepancy (-8.9%±13.8%). This study demonstrates that the metal ovoid structures of Henschke applicator cannot be disregard in brachytherapy dose calculation.

3D quantitative photoacoustic image reconstruction using Monte Carlo method and linearization

NASA Astrophysics Data System (ADS)

Okawa, Shinpei; Hirasawa, Takeshi; Tsujita, Kazuhiro; Kushibiki, Toshihiro; Ishihara, Miya

2018-02-01

To quantify the functional and structural information of peripheral blood vessels for diagnoses of diseases which affects peripheral blood vessels such as diabetes and peripheral vascular disease, a 3D quantitative photoacoustic tomography (QPAT) reconstructing the optical properties such as the absorption coefficient reflecting microvascular structures and hemoglobin concentration and oxygenation saturation is studied. QPAT image reconstruction algorithms based on radiative transfer equation (RTE) and photon diffusion equation (PDE) have been proposed. However, it is not easy to use RTE in the clinical practice because of the huge computational load and long calculation time. On the other hand, it is always considered problematic to use PDE, because it does not approximate RTE well near the illuminating position. In this study, we developed the 3D QPAT image reconstruction using Monte Carlo (MC) method which approximates RTE better than PDE to reconstruct the optical properties in the region near the illuminating surface. To reduce the calculation time, we applied linearization. The QPAT image reconstruction algorithm with MC method and linearization was examined in numerical simulations and phantom experiment by use of a scanning system with a single probe consisting of P(VDF-TrFE) piezo electric film and optical fiber.

Statistical thermodynamics of aligned rigid rods with attractive lateral interactions: Theory and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

dos Santos, G. J.; Linares, D. H.; Ramirez-Pastor, A. J.

2018-04-01

The phase behaviour of aligned rigid rods of length k (k-mers) adsorbed on two-dimensional square lattices has been studied by Monte Carlo (MC) simulations and histogram reweighting technique. The k-mers, containing k identical units (each one occupying a lattice site) were deposited along one of the directions of the lattice. In addition, attractive lateral interactions were considered. The methodology was applied, particularly, to the study of the critical point of the condensation transition occurring in the system. The process was monitored by following the fourth order Binder cumulant as a function of temperature for different lattice sizes. The results, obtained for k ranging from 2 to 7, show that: (i) the transition coverage exhibits a decreasing behaviour when it is plotted as a function of the k-mer size and (ii) the transition temperature, Tc, exhibits a power law dependence on k, Tc ∼k 0 , 4, shifting to higher values as k increases. Comparisons with an analytical model based on a generalization of the Bragg-Williams approximation (BWA) were performed in order to support the simulation technique. A significant qualitative agreement was obtained between BWA and MC results.

SU-F-T-157: Physics Considerations Regarding Dosimetric Accuracy of Analytical Dose Calculations for Small Field Proton Therapy: A Monte Carlo Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geng, C; Nanjing University of Aeronautics and Astronautics, Nanjing; Daartz, J

Purpose: To evaluate the accuracy of dose calculations by analytical dose calculation methods (ADC) for small field proton therapy in a gantry based passive scattering facility. Methods: 50 patients with intra-cranial disease were evaluated in the study. Treatment plans followed standard prescription and optimization procedures of proton stereotactic radiosurgery. Dose distributions calculated with the Monte Carlo (MC) toolkit TOPAS were used to represent delivered treatments. The MC dose was first adjusted using the output factor (OF) applied clinically. This factor is determined from the field size and the prescribed range. We then introduced a normalization factor to measure the differencemore » in mean dose between the delivered dose (MC dose with OF) and the dose calculated by ADC for each beam. The normalization was determined by the mean dose of the center voxels of the target area. We compared delivered dose distributions and those calculated by ADC in terms of dose volume histogram parameters and beam range distributions. Results: The mean target dose for a whole treatment is generally within 5% comparing delivered dose (MC dose with OF) and ADC dose. However, the differences can be as great as 11% for shallow and small target treated with a thick range compensator. Applying the normalization factor to the MC dose with OF can reduce the mean dose difference to less than 3%. Considering range uncertainties, the generally applied margins (3.5% of the prescribed range + 1mm) to cover uncertainties in range might not be sufficient to guarantee tumor coverage. The range difference for R90 (90% distal dose falloff) is affected by multiple factors, such as the heterogeneity index. Conclusion: This study indicates insufficient accuracy calculating proton doses using ADC. Our results suggest that uncertainties of target doses are reduced using MC techniques, improving the dosimetric accuracy for proton stereotactic radiosurgery. The work was supported by NIH/NCI under CA U19 021239. CG was partially supported by the Chinese Scholarship Council (CSC) and the National Natural Science Foundation of China (Grant No. 11475087).« less

TU-AB-BRC-09: Fast Dose-Averaged LET and Biological Dose Calculations for Proton Therapy Using Graphics Cards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan, H; Tseung, Chan; Beltran, C

Purpose: To demonstrate fast and accurate Monte Carlo (MC) calculations of proton dose-averaged linear energy transfer (LETd) and biological dose (BD) on a Graphics Processing Unit (GPU) card. Methods: A previously validated GPU-based MC simulation of proton transport was used to rapidly generate LETd distributions for proton treatment plans. Since this MC handles proton-nuclei interactions on an event-by-event using a Bertini intranuclear cascade-evaporation model, secondary protons were taken into account. The smaller contributions of secondary neutrons and recoil nuclei were ignored. Recent work has shown that LETd values are sensitive to the scoring method. The GPU-based LETd calculations were verifiedmore » by comparing with a TOPAS custom scorer that uses tabulated stopping powers, following recommendations by other authors. Comparisons were made for prostate and head-and-neck patients. A python script is used to convert the MC-generated LETd distributions to BD using a variety of published linear quadratic models, and to export the BD in DICOM format for subsequent evaluation. Results: Very good agreement is obtained between TOPAS and our GPU MC. Given a complex head-and-neck plan with 1 mm voxel spacing, the physical dose, LETd and BD calculations for 10{sup 8} proton histories can be completed in ∼5 minutes using a NVIDIA Titan X card. The rapid turnover means that MC feedback can be obtained on dosimetric plan accuracy as well as BD hotspot locations, particularly in regards to their proximity to critical structures. In our institution the GPU MC-generated dose, LETd and BD maps are used to assess plan quality for all patients undergoing treatment. Conclusion: Fast and accurate MC-based LETd calculations can be performed on the GPU. The resulting BD maps provide valuable feedback during treatment plan review. Partially funded by Varian Medical Systems.« less

Application of a Monte Carlo framework with bootstrapping for quantification of uncertainty in baseline map of carbon emissions from deforestation in Tropical Regions

Treesearch

William Salas; Steve Hagen

2013-01-01

This presentation will provide an overview of an approach for quantifying uncertainty in spatial estimates of carbon emission from land use change. We generate uncertainty bounds around our final emissions estimate using a randomized, Monte Carlo (MC)-style sampling technique. This approach allows us to combine uncertainty from different sources without making...

Daylighting Strategies for U. S. Air Force Office Facilities: Economic Analysis of Building Energy Performance and Life-Cycle Cost Modeling with Monte Carlo Method

DTIC Science & Technology

2009-03-26

annually ( McHugh , et al., 1998). USAF has used daylighting as an energy savings strategy in earlier studies (Holtz, 1990); and is pursuing it to meet...using renewable energy to generate electricity ( McHugh , et al., 1998). For example, traditional utility systems that are straining to meet peak...1998) found that lighting accounts for 40-50% of commercial energy consumption and McHugh , Burns, and Hittle (1998) stated that electric lighting and

Patient-specific CT dosimetry calculation: a feasibility study.

PubMed

Fearon, Thomas; Xie, Huchen; Cheng, Jason Y; Ning, Holly; Zhuge, Ying; Miller, Robert W

2011-11-15

Current estimation of radiation dose from computed tomography (CT) scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of "standard man". Radiation dose to both adult and pediatric patients from a CT scan has been a concern, as noted in recent reports. The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient-specific CT dosimetry. A radiation treatment planning system was modified to calculate patient-specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose-volumes (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. The RTPS calculation algorithm is based on a semi-empirical, measured correction-based algorithm, which has been well established in the radiotherapy community. Digital representations of the physical phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms (digital representation). Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The RTPS algorithm can be extended to calculate the organ dose by calculating a dose distribution point-by-point for a designated volume. Electron Gamma Shower (EGSnrc) codes for radiation transport calculations developed by National Research Council of Canada (NRCC) were utilized to perform the Monte Carlo (MC) simulation. In general, the RTPS and MC dose calculations are within 10% of the TLD measurements for the infant and child chest scans. With respect to the dose comparisons for the head, the RTPS dose calculations are slightly higher (10%-20%) than the TLD measurements, while the MC results were within 10% of the TLD measurements. The advantage of the algebraic dose calculation engine of the RTPS is a substantially reduced computation time (minutes vs. days) relative to Monte Carlo calculations, as well as providing patient-specific dose estimation. It also provides the basis for a more elaborate reporting of dosimetric results, such as patient specific organ dose volumes after image segmentation.

Model Comparisons For Space Solar Cell End-Of-Life Calculations

NASA Astrophysics Data System (ADS)

Messenger, Scott; Jackson, Eric; Warner, Jeffrey; Walters, Robert; Evans, Hugh; Heynderickx, Daniel

2011-10-01

Space solar cell end-of-life (EOL) calculations are performed over a wide range of space radiation environments for GaAs-based single and multijunction solar cell technologies. Two general semi-empirical approaches will used to generate these EOL calculation results: 1) the JPL equivalent fluence (EQFLUX) and 2) the NRL displacement damage dose (SCREAM). This paper also includes the first results using the Monte Carlo-based version of SCREAM, called MC- SCREAM, which is now freely available online as part of the SPENVIS suite of programs.

SU-E-T-489: Quantum versus Classical Trajectory Monte Carlo Simulations of Low Energy Electron Transport.

PubMed

Thomson, R; Kawrakow, I

2012-06-01

Widely-used classical trajectory Monte Carlo simulations of low energy electron transport neglect the quantum nature of electrons; however, at sub-1 keV energies quantum effects have the potential to become significant. This work compares quantum and classical simulations within a simplified model of electron transport in water. Electron transport is modeled in water droplets using quantum mechanical (QM) and classical trajectory Monte Carlo (MC) methods. Water droplets are modeled as collections of point scatterers representing water molecules from which electrons may be isotropically scattered. The role of inelastic scattering is investigated by introducing absorption. QM calculations involve numerically solving a system of coupled equations for the electron wavefield incident on each scatterer. A minimum distance between scatterers is introduced to approximate structured water. The average QM water droplet incoherent cross section is compared with the MC cross section; a relative error (RE) on the MC results is computed. RE varies with electron energy, average and minimum distances between scatterers, and scattering amplitude. The mean free path is generally the relevant length scale for estimating RE. The introduction of a minimum distance between scatterers increases RE substantially (factors of 5 to 10), suggesting that the structure of water must be modeled for accurate simulations. Inelastic scattering does not improve agreement between QM and MC simulations: for the same magnitude of elastic scattering, the introduction of inelastic scattering increases RE. Droplet cross sections are sensitive to droplet size and shape; considerable variations in RE are observed with changing droplet size and shape. At sub-1 keV energies, quantum effects may become non-negligible for electron transport in condensed media. Electron transport is strongly affected by the structure of the medium. Inelastic scatter does not improve agreement between QM and MC simulations of low energy electron transport in condensed media. © 2012 American Association of Physicists in Medicine.

Mean transverse momenta correlations in hadron-hadron collisions in MC toy model with repulsing strings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Altsybeev, Igor

2016-01-22

In the present work, Monte-Carlo toy model with repulsing quark-gluon strings in hadron-hadron collisions is described. String repulsion creates transverse boosts for the string decay products, giving modifications of observables. As an example, long-range correlations between mean transverse momenta of particles in two observation windows are studied in MC toy simulation of the heavy-ion collisions.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. Thesemore » lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.« less

CAST: a new program package for the accurate characterization of large and flexible molecular systems.

PubMed

Grebner, Christoph; Becker, Johannes; Weber, Daniel; Bellinger, Daniel; Tafipolski, Maxim; Brückner, Charlotte; Engels, Bernd

2014-09-15

The presented program package, Conformational Analysis and Search Tool (CAST) allows the accurate treatment of large and flexible (macro) molecular systems. For the determination of thermally accessible minima CAST offers the newly developed TabuSearch algorithm, but algorithms such as Monte Carlo (MC), MC with minimization, and molecular dynamics are implemented as well. For the determination of reaction paths, CAST provides the PathOpt, the Nudge Elastic band, and the umbrella sampling approach. Access to free energies is possible through the free energy perturbation approach. Along with a number of standard force fields, a newly developed symmetry-adapted perturbation theory-based force field is included. Semiempirical computations are possible through DFTB+ and MOPAC interfaces. For calculations based on density functional theory, a Message Passing Interface (MPI) interface to the Graphics Processing Unit (GPU)-accelerated TeraChem program is available. The program is available on request. Copyright © 2014 Wiley Periodicals, Inc.

SU-F-T-365: Clinical Commissioning of the Monaco Treatment Planning System for the Novalis Tx to Deliver VMAT, SRS and SBRT Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adnani, N

Purpose: To commission the Monaco Treatment Planning System for the Novalis Tx machine. Methods: The commissioning of Monte-Carlo (MC), Collapsed Cone (CC) and electron Monte-Carlo (eMC) beam models was performed through a series of measurements and calculations in medium and in water. In medium measurements relied Octavius 4D QA system with the 1000 SRS detector array for field sizes less than 4 cm × 4 cm and the 1500 detector array for larger field sizes. Heterogeneity corrections were validated using a custom built phantom. Prior to clinical implementation, an end to end testing of a Prostate and H&N VMAT plansmore » was performed. Results: Using a 0.5% uncertainty and 2 mm grid sizes, Tables I and II summarize the MC validation at 6 MV and 18 MV in both medium and water. Tables III and IV show similar comparisons for CC. Using the custom heterogeneity phantom setup of Figure 1 and IGRT guidance summarized in Figure 2, Table V lists the percent pass rate for a 2%, 2 mm gamma criteria at 6 and 18 MV for both MC and CC. The relationship between MC calculations settings of uncertainty and grid size and the gamma passing rate for a prostate and H&N case is shown in Table VI. Table VII lists the results of the eMC calculations compared to measured data for clinically available applicators and Table VIII for small field cutouts. Conclusion: MU calculations using MC are highly sensitive to uncertainty and grid size settings. The difference can be of the order of several per cents. MC is superior to CC for small fields and when using heterogeneity corrections, regardless of field size, making it more suitable for SRS, SBRT and VMAT deliveries. eMC showed good agreement with measurements down to 2 cm − 2 cm field size.« less

Dynamic 99mTc-MAG3 renography: images for quality control obtained by combining pharmacokinetic modelling, an anthropomorphic computer phantom and Monte Carlo simulated scintillation camera imaging

NASA Astrophysics Data System (ADS)

Brolin, Gustav; Sjögreen Gleisner, Katarina; Ljungberg, Michael

2013-05-01

In dynamic renal scintigraphy, the main interest is the radiopharmaceutical redistribution as a function of time. Quality control (QC) of renal procedures often relies on phantom experiments to compare image-based results with the measurement setup. A phantom with a realistic anatomy and time-varying activity distribution is therefore desirable. This work describes a pharmacokinetic (PK) compartment model for 99mTc-MAG3, used for defining a dynamic whole-body activity distribution within a digital phantom (XCAT) for accurate Monte Carlo (MC)-based images for QC. Each phantom structure is assigned a time-activity curve provided by the PK model, employing parameter values consistent with MAG3 pharmacokinetics. This approach ensures that the total amount of tracer in the phantom is preserved between time points, and it allows for modifications of the pharmacokinetics in a controlled fashion. By adjusting parameter values in the PK model, different clinically realistic scenarios can be mimicked, regarding, e.g., the relative renal uptake and renal transit time. Using the MC code SIMIND, a complete set of renography images including effects of photon attenuation, scattering, limited spatial resolution and noise, are simulated. The obtained image data can be used to evaluate quantitative techniques and computer software in clinical renography.

Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems

DOE PAGES

Brooks, Scott C.; Brandt, Craig C.; Griffiths, Natalie A.

2016-10-07

Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (S w-amb) and maximum areal uptake rates (U max) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCCmore » experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate S w-amb and U max, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way to estimate uncertainty, as the calculation of S w-amb and U max violates assumptions of OLS/NLS while the MC approach is free of these assumptions. The MC approach can be applied to other ecosystem metrics that are calculated from multiple parameters, providing a more robust estimate of these metrics and their associated uncertainties.« less

Estimating uncertainty in ambient and saturation nutrient uptake metrics from nutrient pulse releases in stream ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Scott C.; Brandt, Craig C.; Griffiths, Natalie A.

Nutrient spiraling is an important ecosystem process characterizing nutrient transport and uptake in streams. Various nutrient addition methods are used to estimate uptake metrics; however, uncertainty in the metrics is not often evaluated. A method was developed to quantify uncertainty in ambient and saturation nutrient uptake metrics estimated from saturating pulse nutrient additions (Tracer Additions for Spiraling Curve Characterization; TASCC). Using a Monte Carlo (MC) approach, the 95% confidence interval (CI) was estimated for ambient uptake lengths (S w-amb) and maximum areal uptake rates (U max) based on 100,000 datasets generated from each of four nitrogen and five phosphorous TASCCmore » experiments conducted seasonally in a forest stream in eastern Tennessee, U.S.A. Uncertainty estimates from the MC approach were compared to the CIs estimated from ordinary least squares (OLS) and non-linear least squares (NLS) models used to calculate S w-amb and U max, respectively, from the TASCC method. The CIs for Sw-amb and Umax were large, but were not consistently larger using the MC method. Despite the large CIs, significant differences (based on nonoverlapping CIs) in nutrient metrics among seasons were found with more significant differences using the OLS/NLS vs. the MC method. Lastly, we suggest that the MC approach is a robust way to estimate uncertainty, as the calculation of S w-amb and U max violates assumptions of OLS/NLS while the MC approach is free of these assumptions. The MC approach can be applied to other ecosystem metrics that are calculated from multiple parameters, providing a more robust estimate of these metrics and their associated uncertainties.« less

Efficient Application of Continuous Fractional Component Monte Carlo in the Reaction Ensemble

PubMed Central

2017-01-01

A new formulation of the Reaction Ensemble Monte Carlo technique (RxMC) combined with the Continuous Fractional Component Monte Carlo method is presented. This method is denoted by serial Rx/CFC. The key ingredient is that fractional molecules of either reactants or reaction products are present and that chemical reactions always involve fractional molecules. Serial Rx/CFC has the following advantages compared to other approaches: (1) One directly obtains chemical potentials of all reactants and reaction products. Obtained chemical potentials can be used directly as an independent check to ensure that chemical equilibrium is achieved. (2) Independent biasing is applied to the fractional molecules of reactants and reaction products. Therefore, the efficiency of the algorithm is significantly increased, compared to the other approaches. (3) Changes in the maximum scaling parameter of intermolecular interactions can be chosen differently for reactants and reaction products. (4) The number of fractional molecules is reduced. As a proof of principle, our method is tested for Lennard-Jones systems at various pressures and for various chemical reactions. Excellent agreement was found both for average densities and equilibrium mixture compositions computed using serial Rx/CFC, RxMC/CFCMC previously introduced by Rosch and Maginn (Journal of Chemical Theory and Computation, 2011, 7, 269–279), and the conventional RxMC approach. The serial Rx/CFC approach is also tested for the reaction of ammonia synthesis at various temperatures and pressures. Excellent agreement was found between results obtained from serial Rx/CFC, experimental results from literature, and thermodynamic modeling using the Peng–Robinson equation of state. The efficiency of reaction trial moves is improved by a factor of 2 to 3 (depending on the system) compared to the RxMC/CFCMC formulation by Rosch and Maginn. PMID:28737933

Absolute dose calculations for Monte Carlo simulations of radiotherapy beams

NASA Astrophysics Data System (ADS)

Popescu, I. A.; Shaw, C. P.; Zavgorodni, S. F.; Beckham, W. A.

2005-07-01

Monte Carlo (MC) simulations have traditionally been used for single field relative comparisons with experimental data or commercial treatment planning systems (TPS). However, clinical treatment plans commonly involve more than one field. Since the contribution of each field must be accurately quantified, multiple field MC simulations are only possible by employing absolute dosimetry. Therefore, we have developed a rigorous calibration method that allows the incorporation of monitor units (MU) in MC simulations. This absolute dosimetry formalism can be easily implemented by any BEAMnrc/DOSXYZnrc user, and applies to any configuration of open and blocked fields, including intensity-modulated radiation therapy (IMRT) plans. Our approach involves the relationship between the dose scored in the monitor ionization chamber of a radiotherapy linear accelerator (linac), the number of initial particles incident on the target, and the field size. We found that for a 10 × 10 cm2 field of a 6 MV photon beam, 1 MU corresponds, in our model, to 8.129 × 1013 ± 1.0% electrons incident on the target and a total dose of 20.87 cGy ± 1.0% in the monitor chambers of the virtual linac. We present an extensive experimental verification of our MC results for open and intensity-modulated fields, including a dynamic 7-field IMRT plan simulated on the CT data sets of a cylindrical phantom and of a Rando anthropomorphic phantom, which were validated by measurements using ionization chambers and thermoluminescent dosimeters (TLD). Our simulation results are in excellent agreement with experiment, with percentage differences of less than 2%, in general, demonstrating the accuracy of our Monte Carlo absolute dose calculations.

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin I.

2016-01-01

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

Accuracy and convergence of coupled finite-volume/Monte Carlo codes for plasma edge simulations of nuclear fusion reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghoos, K., E-mail: kristel.ghoos@kuleuven.be; Dekeyser, W.; Samaey, G.

2016-10-01

The plasma and neutral transport in the plasma edge of a nuclear fusion reactor is usually simulated using coupled finite volume (FV)/Monte Carlo (MC) codes. However, under conditions of future reactors like ITER and DEMO, convergence issues become apparent. This paper examines the convergence behaviour and the numerical error contributions with a simplified FV/MC model for three coupling techniques: Correlated Sampling, Random Noise and Robbins Monro. Also, practical procedures to estimate the errors in complex codes are proposed. Moreover, first results with more complex models show that an order of magnitude speedup can be achieved without any loss in accuracymore » by making use of averaging in the Random Noise coupling technique.« less

Combined FDTD-Monte Carlo analysis and a novel design for ZnO scintillator rods in polycarbonate membrane for X-ray imaging

NASA Astrophysics Data System (ADS)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar; Mohammadi, Mohammad

2017-05-01

A combination of Finite Difference Time Domain (FDTD) and Monte Carlo (MC) methods is proposed for simulation and analysis of ZnO microscintillators grown in polycarbonate membrane. A planar 10 keV X-ray source irradiating the detector is simulated by MC method, which provides the amount of absorbed X-ray energy in the assembly. The transport of generated UV scintillation light and its propagation in the detector was studied by the FDTD method. Detector responses to different probable scintillation sites and under different energies of X-ray source from 10 to 25 keV are reported. Finally, the tapered geometry for the scintillators is proposed, which shows enhanced spatial resolution in comparison to cylindrical geometry for imaging applications.

Production Management System for AMS Computing Centres

NASA Astrophysics Data System (ADS)

Choutko, V.; Demakov, O.; Egorov, A.; Eline, A.; Shan, B. S.; Shi, R.

2017-10-01

The Alpha Magnetic Spectrometer [1] (AMS) has collected over 95 billion cosmic ray events since it was installed on the International Space Station (ISS) on May 19, 2011. To cope with enormous flux of events, AMS uses 12 computing centers in Europe, Asia and North America, which have different hardware and software configurations. The centers are participating in data reconstruction, Monte-Carlo (MC) simulation [2]/Data and MC production/as well as in physics analysis. Data production management system has been developed to facilitate data and MC production tasks in AMS computing centers, including job acquiring, submitting, monitoring, transferring, and accounting. It was designed to be modularized, light-weighted, and easy-to-be-deployed. The system is based on Deterministic Finite Automaton [3] model, and implemented by script languages, Python and Perl, and the built-in sqlite3 database on Linux operating systems. Different batch management systems, file system storage, and transferring protocols are supported. The details of the integration with Open Science Grid are presented as well.

Solar Proton Transport within an ICRU Sphere Surrounded by a Complex Shield: Combinatorial Geometry

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

The 3DHZETRN code, with improved neutron and light ion (Z (is) less than 2) transport procedures, was recently developed and compared to Monte Carlo (MC) simulations using simplified spherical geometries. It was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in general combinatorial geometry. A more complex shielding structure with internal parts surrounding a tissue sphere is considered and compared against MC simulations. It is shown that even in the more complex geometry, 3DHZETRN agrees well with the MC codes and maintains a high degree of computational efficiency.

Monte Carlo dose calculations for high-dose-rate brachytherapy using GPU-accelerated processing.

PubMed

Tian, Z; Zhang, M; Hrycushko, B; Albuquerque, K; Jiang, S B; Jia, X

2016-01-01

Current clinical brachytherapy dose calculations are typically based on the Association of American Physicists in Medicine Task Group report 43 (TG-43) guidelines, which approximate patient geometry as an infinitely large water phantom. This ignores patient and applicator geometries and heterogeneities, causing dosimetric errors. Although Monte Carlo (MC) dose calculation is commonly recognized as the most accurate method, its associated long computational time is a major bottleneck for routine clinical applications. This article presents our recent developments of a fast MC dose calculation package for high-dose-rate (HDR) brachytherapy, gBMC, built on a graphics processing unit (GPU) platform. gBMC-simulated photon transport in voxelized geometry with physics in (192)Ir HDR brachytherapy energy range considered. A phase-space file was used as a source model. GPU-based parallel computation was used to simultaneously transport multiple photons, one on a GPU thread. We validated gBMC by comparing the dose calculation results in water with that computed TG-43. We also studied heterogeneous phantom cases and a patient case and compared gBMC results with Acuros BV results. Radial dose function in water calculated by gBMC showed <0.6% relative difference from that of the TG-43 data. Difference in anisotropy function was <1%. In two heterogeneous slab phantoms and one shielded cylinder applicator case, average dose discrepancy between gBMC and Acuros BV was <0.87%. For a tandem and ovoid patient case, good agreement between gBMC and Acruos BV results was observed in both isodose lines and dose-volume histograms. In terms of the efficiency, it took ∼47.5 seconds for gBMC to reach 0.15% statistical uncertainty within the 5% isodose line for the patient case. The accuracy and efficiency of a new GPU-based MC dose calculation package, gBMC, for HDR brachytherapy make it attractive for clinical applications. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

SU-C-BRC-06: OpenCL-Based Cross-Platform Monte Carlo Simulation Package for Carbon Ion Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qin, N; Tian, Z; Pompos, A

2016-06-15

Purpose: Monte Carlo (MC) simulation is considered to be the most accurate method for calculation of absorbed dose and fundamental physical quantities related to biological effects in carbon ion therapy. Its long computation time impedes clinical and research applications. We have developed an MC package, goCMC, on parallel processing platforms, aiming at achieving accurate and efficient simulations for carbon therapy. Methods: goCMC was developed under OpenCL framework. It supported transport simulation in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history algorithm was employed for charged particle transport with stopping power computed via Bethe-Bloch equation. Secondarymore » electrons were not transported with their energy locally deposited. Energy straggling and multiple scattering were modeled. Production of secondary charged particles from nuclear interactions was implemented based on cross section and yield data from Geant4. They were transported via the condensed history scheme. goCMC supported scoring various quantities of interest e.g. physical dose, particle fluence, spectrum, linear energy transfer, and positron emitting nuclei. Results: goCMC has been benchmarked against Geant4 with different phantoms and beam energies. For 100 MeV/u, 250 MeV/u and 400 MeV/u beams impinging to a water phantom, range difference was 0.03 mm, 0.20 mm and 0.53 mm, and mean dose difference was 0.47%, 0.72% and 0.79%, respectively. goCMC can run on various computing devices. Depending on the beam energy and voxel size, it took 20∼100 seconds to simulate 10{sup 7} carbons on an AMD Radeon GPU card. The corresponding CPU time for Geant4 with the same setup was 60∼100 hours. Conclusion: We have developed an OpenCL-based cross-platform carbon MC simulation package, goCMC. Its accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon therapy.« less

Non-line-of-sight single-scatter propagation model for noncoplanar geometries.

PubMed

Elshimy, Mohamed A; Hranilovic, Steve

2011-03-01

In this paper, a geometrical propagation model is developed that generalizes the classical single-scatter model under the assumption of first-order scattering and non-line-of-sight (NLOS) communication. The generalized model considers the case of a noncoplanar geometry, where it overcomes the restriction that the transmitter and the receiver cone axes lie in the same plane. To verify the model, a Monte Carlo (MC) radiative transfer model based on a photon transport algorithm is constructed. Numerical examples for a wavelength of 266 nm are illustrated, which corresponds to a solar-blind NLOS UV communication system. A comparison of the temporal responses of the generalized model and the MC simulation results shows close agreement. Path loss and delay spread are also shown for different pointing directions.

Technical Note: Dosimetric evaluation of Monte Carlo algorithm in iPlan for stereotactic ablative body radiotherapy (SABR) for lung cancer patients using RTOG 0813 parameters.

PubMed

Pokhrel, Damodar; Badkul, Rajeev; Jiang, Hongyu; Kumar, Pravesh; Wang, Fen

2015-01-08

For stereotactic ablative body radiotherapy (SABR) in lung cancer patients, Radiation Therapy Oncology Group (RTOG) protocols currently require radiation dose to be calculated using tissue heterogeneity corrections. Dosimetric criteria of RTOG 0813 were established based on the results obtained from non-Monte Carlo (MC) algorithms, such as superposition/convolutions. Clinically, MC-based algorithms are now routinely used for lung SABR dose calculations. It is essential to confirm that MC calculations in lung SABR meet RTOG guidelines. This report evaluates iPlan MC plans for SABR in lung cancer patients using dose-volume histogram normalization per current RTOG 0813 compliance criteria. Eighteen Stage I-II non-small cell lung cancer (NSCLC) patients with centrally located tumors, who underwent MC-based lung SABR with heterogeneity correction using X-ray Voxel Monte Carlo (XVMC) algorithm (BrainLAB iPlan version 4.1.2), were analyzed. Total dose of 60 Gy in 5 fractions was delivered to planning target volume (PTV) with at least V100% = 95%. Internal target volumes (ITVs) were delineated on maximum intensity projection (MIP) images of 4D CT scans. PTV (ITV + 5 mm margin) volumes ranged from 10.0 to 99.9 cc (mean = 36.8 ± 20.7 cc). Organs at risk (OARs) were delineated on average images of 4D CT scans. Optimal clinical MC SABR plans were generated using a combination of non-coplanar conformal arcs and beams for the Novalis-TX consisting of high definition multileaf collimators (MLCs) and 6 MV-SRS (1000 MU/min) mode. All plans were evaluated using the RTOG 0813 high and intermediate dose spillage criteria: conformity index (R100%), ratio of 50% isodose volume to the PTV (R50%), maximum dose 2 cm away from PTV in any direction (D2 cm), and percent of normal lung receiving 20 Gy (V20) or more. Other organs-at-risk (OARs) doses were tabulated, including the volume of normal lung receiving 5 Gy (V5), maximum cord dose, dose to < 15 cc of heart, and dose to <5 cc of esophagus. Only six out of 18 patients met all RTOG 0813 compliance criteria. Eight of 18 patients had minor deviations in R100%, four in R50%, and nine in D2 cm. However, only one patient had minor deviation in V20. All other OARs doses, such as maximum cord dose, dose to < 15 cc of heart, and dose to < 5 cc of esophagus, were satisfactory for RTOG criteria, except for one patient, for whom the dose to < 15 cc of heart was higher than RTOG guidelines. The preliminary results for our limited iPlan XVMC dose calculations indicate that the majority (i.e., 2/3) of our patients had minor deviations in the dosimetric guidelines set by RTOG 0813 protocol in one way or another. When using an exclusive highly sophisticated XVMC algorithm, the RTOG 0813 dosimetric compliance criteria such as R100% and D2 cm may need to be revisited. Based on our limited number of patient datasets, in general, about 6% for R100% and 9% for D2 cm corrections could be applied to pass the RTOG 0813 compliance criteria in most of those patients. More patient plans need to be evaluated to make recommendation for R50%. No adjustment is necessary for OAR dose tolerances, including normal lung V20. In order to establish new MC specific dose parameters, further investigation with a large cohort of patients including central, as well as peripheral lung tumors, is anticipated and strongly recommended.

Game of Life on the Equal Degree Random Lattice

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Chen, Tao

2010-12-01

An effective matrix method is performed to build the equal degree random (EDR) lattice, and then a cellular automaton game of life on the EDR lattice is studied by Monte Carlo (MC) simulation. The standard mean field approximation (MFA) is applied, and then the density of live cells is given ρ=0.37017 by MFA, which is consistent with the result ρ=0.37±0.003 by MC simulation.

Pinhole X-ray fluorescence imaging of gadolinium and gold nanoparticles using polychromatic X-rays: a Monte Carlo study

PubMed Central

Jung, Seongmoon; Sung, Wonmo; Ye, Sung-Joon

2017-01-01

This work aims to develop a Monte Carlo (MC) model for pinhole K-shell X-ray fluorescence (XRF) imaging of metal nanoparticles using polychromatic X-rays. The MC model consisted of two-dimensional (2D) position-sensitive detectors and fan-beam X-rays used to stimulate the emission of XRF photons from gadolinium (Gd) or gold (Au) nanoparticles. Four cylindrical columns containing different concentrations of nanoparticles ranging from 0.01% to 0.09% by weight (wt%) were placed in a 5 cm diameter cylindrical water phantom. The images of the columns had detectable contrast-to-noise ratios (CNRs) of 5.7 and 4.3 for 0.01 wt% Gd and for 0.03 wt% Au, respectively. Higher concentrations of nanoparticles yielded higher CNR. For 1×1011 incident particles, the radiation dose to the phantom was 19.9 mGy for 110 kVp X-rays (Gd imaging) and 26.1 mGy for 140 kVp X-rays (Au imaging). The MC model of a pinhole XRF can acquire direct 2D slice images of the object without image reconstruction. The MC model demonstrated that the pinhole XRF imaging system could be a potential bioimaging modality for nanomedicine. PMID:28860750

Theoretical study of the ammonia nitridation rate on an Fe (100) surface: a combined density functional theory and kinetic Monte Carlo study.

PubMed

Yeo, Sang Chul; Lo, Yu Chieh; Li, Ju; Lee, Hyuck Mo

2014-10-07

Ammonia (NH3) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (Eb) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (Eb) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH3 nitridation rate on the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH3 nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH3 nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH3 nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.

Study on photon transport problem based on the platform of molecular optical simulation environment.

PubMed

Peng, Kuan; Gao, Xinbo; Liang, Jimin; Qu, Xiaochao; Ren, Nunu; Chen, Xueli; Ma, Bin; Tian, Jie

2010-01-01

As an important molecular imaging modality, optical imaging has attracted increasing attention in the recent years. Since the physical experiment is usually complicated and expensive, research methods based on simulation platforms have obtained extensive attention. We developed a simulation platform named Molecular Optical Simulation Environment (MOSE) to simulate photon transport in both biological tissues and free space for optical imaging based on noncontact measurement. In this platform, Monte Carlo (MC) method and the hybrid radiosity-radiance theorem are used to simulate photon transport in biological tissues and free space, respectively, so both contact and noncontact measurement modes of optical imaging can be simulated properly. In addition, a parallelization strategy for MC method is employed to improve the computational efficiency. In this paper, we study the photon transport problems in both biological tissues and free space using MOSE. The results are compared with Tracepro, simplified spherical harmonics method (SP(n)), and physical measurement to verify the performance of our study method on both accuracy and efficiency.

Study on Photon Transport Problem Based on the Platform of Molecular Optical Simulation Environment

PubMed Central

Peng, Kuan; Gao, Xinbo; Liang, Jimin; Qu, Xiaochao; Ren, Nunu; Chen, Xueli; Ma, Bin; Tian, Jie

2010-01-01

As an important molecular imaging modality, optical imaging has attracted increasing attention in the recent years. Since the physical experiment is usually complicated and expensive, research methods based on simulation platforms have obtained extensive attention. We developed a simulation platform named Molecular Optical Simulation Environment (MOSE) to simulate photon transport in both biological tissues and free space for optical imaging based on noncontact measurement. In this platform, Monte Carlo (MC) method and the hybrid radiosity-radiance theorem are used to simulate photon transport in biological tissues and free space, respectively, so both contact and noncontact measurement modes of optical imaging can be simulated properly. In addition, a parallelization strategy for MC method is employed to improve the computational efficiency. In this paper, we study the photon transport problems in both biological tissues and free space using MOSE. The results are compared with Tracepro, simplified spherical harmonics method (S P n), and physical measurement to verify the performance of our study method on both accuracy and efficiency. PMID:20445737

SU-C-204-01: A Fast Analytical Approach for Prompt Gamma and PET Predictions in a TPS for Proton Range Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroniger, K; Herzog, M; Landry, G

2015-06-15

Purpose: We describe and demonstrate a fast analytical tool for prompt-gamma emission prediction based on filter functions applied on the depth dose profile. We present the implementation in a treatment planning system (TPS) of the same algorithm for positron emitter distributions. Methods: The prediction of the desired observable is based on the convolution of filter functions with the depth dose profile. For both prompt-gammas and positron emitters, the results of Monte Carlo simulations (MC) are compared with those of the analytical tool. For prompt-gamma emission from inelastic proton-induced reactions, homogeneous and inhomogeneous phantoms alongside with patient data are used asmore » irradiation targets of mono-energetic proton pencil beams. The accuracy of the tool is assessed in terms of the shape of the analytically calculated depth profiles and their absolute yields, compared to MC. For the positron emitters, the method is implemented in a research RayStation TPS and compared to MC predictions. Digital phantoms and patient data are used and positron emitter spatial density distributions are analyzed. Results: Calculated prompt-gamma profiles agree with MC within 3 % in terms of absolute yield and reproduce the correct shape. Based on an arbitrary reference material and by means of 6 filter functions (one per chemical element), profiles in any other material composed of those elements can be predicted. The TPS implemented algorithm is accurate enough to enable, via the analytically calculated positron emitters profiles, detection of range differences between the TPS and MC with errors of the order of 1–2 mm. Conclusion: The proposed analytical method predicts prompt-gamma and positron emitter profiles which generally agree with the distributions obtained by a full MC. The implementation of the tool in a TPS shows that reliable profiles can be obtained directly from the dose calculated by the TPS, without the need of full MC simulation.« less

Monte Carlo and discrete-ordinate simulations of spectral radiances in a coupled air-tissue system.

PubMed

Hestenes, Kjersti; Nielsen, Kristian P; Zhao, Lu; Stamnes, Jakob J; Stamnes, Knut

2007-04-20

We perform a detailed comparison study of Monte Carlo (MC) simulations and discrete-ordinate radiative-transfer (DISORT) calculations of spectral radiances in a 1D coupled air-tissue (CAT) system consisting of horizontal plane-parallel layers. The MC and DISORT models have the same physical basis, including coupling between the air and the tissue, and we use the same air and tissue input parameters for both codes. We find excellent agreement between radiances obtained with the two codes, both above and in the tissue. Our tests cover typical optical properties of skin tissue at the 280, 540, and 650 nm wavelengths. The normalized volume scattering function for internal structures in the skin is represented by the one-parameter Henyey-Greenstein function for large particles and the Rayleigh scattering function for small particles. The CAT-DISORT code is found to be approximately 1000 times faster than the CAT-MC code. We also show that the spectral radiance field is strongly dependent on the inherent optical properties of the skin tissue.

An interface for simulating radiative transfer in and around volcanic plumes with the Monte Carlo radiative transfer model McArtim

USGS Publications Warehouse

Kern, Christoph

2016-03-23

This report describes two software tools that, when used as front ends for the three-dimensional backward Monte Carlo atmospheric-radiative-transfer model (RTM) McArtim, facilitate the generation of lookup tables of volcanic-plume optical-transmittance characteristics in the ultraviolet/visible-spectral region. In particular, the differential optical depth and derivatives thereof (that is, weighting functions), with regard to a change in SO2 column density or aerosol optical thickness, can be simulated for a specific measurement geometry and a representative range of plume conditions. These tables are required for the retrieval of SO2 column density in volcanic plumes, using the simulated radiative-transfer/differential optical-absorption spectroscopic (SRT-DOAS) approach outlined by Kern and others (2012). This report, together with the software tools published online, is intended to make this sophisticated SRT-DOAS technique available to volcanologists and gas geochemists in an operational environment, without the need for an indepth treatment of the underlying principles or the low-level interface of the RTM McArtim.

Lens implementation on the GATE Monte Carlo toolkit for optical imaging simulation.

PubMed

Kang, Han Gyu; Song, Seong Hyun; Han, Young Been; Kim, Kyeong Min; Hong, Seong Jong

2018-02-01

Optical imaging techniques are widely used for in vivo preclinical studies, and it is well known that the Geant4 Application for Emission Tomography (GATE) can be employed for the Monte Carlo (MC) modeling of light transport inside heterogeneous tissues. However, the GATE MC toolkit is limited in that it does not yet include optical lens implementation, even though this is required for a more realistic optical imaging simulation. We describe our implementation of a biconvex lens into the GATE MC toolkit to improve both the sensitivity and spatial resolution for optical imaging simulation. The lens implemented into the GATE was validated against the ZEMAX optical simulation using an US air force 1951 resolution target. The ray diagrams and the charge-coupled device images of the GATE optical simulation agreed with the ZEMAX optical simulation results. In conclusion, the use of a lens on the GATE optical simulation could improve the image quality of bioluminescence and fluorescence significantly as compared with pinhole optics. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

The Monte Carlo simulation of the Borexino detector

NASA Astrophysics Data System (ADS)

Agostini, M.; Altenmüller, K.; Appel, S.; Atroshchenko, V.; Bagdasarian, Z.; Basilico, D.; Bellini, G.; Benziger, J.; Bick, D.; Bonfini, G.; Borodikhina, L.; Bravo, D.; Caccianiga, B.; Calaprice, F.; Caminata, A.; Canepa, M.; Caprioli, S.; Carlini, M.; Cavalcante, P.; Chepurnov, A.; Choi, K.; D'Angelo, D.; Davini, S.; Derbin, A.; Ding, X. F.; Di Noto, L.; Drachnev, I.; Fomenko, K.; Formozov, A.; Franco, D.; Froborg, F.; Gabriele, F.; Galbiati, C.; Ghiano, C.; Giammarchi, M.; Goeger-Neff, M.; Goretti, A.; Gromov, M.; Hagner, C.; Houdy, T.; Hungerford, E.; Ianni, Aldo; Ianni, Andrea; Jany, A.; Jeschke, D.; Kobychev, V.; Korablev, D.; Korga, G.; Kryn, D.; Laubenstein, M.; Litvinovich, E.; Lombardi, F.; Lombardi, P.; Ludhova, L.; Lukyanchenko, G.; Machulin, I.; Magnozzi, M.; Manuzio, G.; Marcocci, S.; Martyn, J.; Meroni, E.; Meyer, M.; Miramonti, L.; Misiaszek, M.; Muratova, V.; Neumair, B.; Oberauer, L.; Opitz, B.; Ortica, F.; Pallavicini, M.; Papp, L.; Pocar, A.; Ranucci, G.; Razeto, A.; Re, A.; Romani, A.; Roncin, R.; Rossi, N.; Schönert, S.; Semenov, D.; Shakina, P.; Skorokhvatov, M.; Smirnov, O.; Sotnikov, A.; Stokes, L. F. F.; Suvorov, Y.; Tartaglia, R.; Testera, G.; Thurn, J.; Toropova, M.; Unzhakov, E.; Vishneva, A.; Vogelaar, R. B.; von Feilitzsch, F.; Wang, H.; Weinz, S.; Wojcik, M.; Wurm, M.; Yokley, Z.; Zaimidoroga, O.; Zavatarelli, S.; Zuber, K.; Zuzel, G.

2018-01-01

We describe the Monte Carlo (MC) simulation of the Borexino detector and the agreement of its output with data. The Borexino MC "ab initio" simulates the energy loss of particles in all detector components and generates the resulting scintillation photons and their propagation within the liquid scintillator volume. The simulation accounts for absorption, reemission, and scattering of the optical photons and tracks them until they either are absorbed or reach the photocathode of one of the photomultiplier tubes. Photon detection is followed by a comprehensive simulation of the readout electronics response. The MC is tuned using data collected with radioactive calibration sources deployed inside and around the scintillator volume. The simulation reproduces the energy response of the detector, its uniformity within the fiducial scintillator volume relevant to neutrino physics, and the time distribution of detected photons to better than 1% between 100 keV and several MeV. The techniques developed to simulate the Borexino detector and their level of refinement are of possible interest to the neutrino community, especially for current and future large-volume liquid scintillator experiments such as Kamland-Zen, SNO+, and Juno.

Designing new guides and instruments using McStas

NASA Astrophysics Data System (ADS)

Farhi, E.; Hansen, T.; Wildes, A.; Ghosh, R.; Lefmann, K.

With the increasing complexity of modern neutron-scattering instruments, the need for powerful tools to optimize their geometry and physical performances (flux, resolution, divergence, etc.) has become essential. As the usual analytical methods reach their limit of validity in the description of fine effects, the use of Monte Carlo simulations, which can handle these latter, has become widespread. The McStas program was developed at Riso National Laboratory in order to provide neutron scattering instrument scientists with an efficient and flexible tool for building Monte Carlo simulations of guides, neutron optics and instruments [1]. To date, the McStas package has been extensively used at the Institut Laue-Langevin, Grenoble, France, for various studies including cold and thermal guides with ballistic geometry, diffractometers, triple-axis, backscattering and time-of-flight spectrometers [2]. In this paper, we present some simulation results concerning different guide geometries that may be used in the future at the Institut Laue-Langevin. Gain factors ranging from two to five may be obtained for the integrated intensities, depending on the exact geometry, the guide coatings and the source.

A method for photon beam Monte Carlo multileaf collimator particle transport

NASA Astrophysics Data System (ADS)

Siebers, Jeffrey V.; Keall, Paul J.; Kim, Jong Oh; Mohan, Radhe

2002-09-01

Monte Carlo (MC) algorithms are recognized as the most accurate methodology for patient dose assessment. For intensity-modulated radiation therapy (IMRT) delivered with dynamic multileaf collimators (DMLCs), accurate dose calculation, even with MC, is challenging. Accurate IMRT MC dose calculations require inclusion of the moving MLC in the MC simulation. Due to its complex geometry, full transport through the MLC can be time consuming. The aim of this work was to develop an MLC model for photon beam MC IMRT dose computations. The basis of the MC MLC model is that the complex MLC geometry can be separated into simple geometric regions, each of which readily lends itself to simplified radiation transport. For photons, only attenuation and first Compton scatter interactions are considered. The amount of attenuation material an individual particle encounters while traversing the entire MLC is determined by adding the individual amounts from each of the simplified geometric regions. Compton scatter is sampled based upon the total thickness traversed. Pair production and electron interactions (scattering and bremsstrahlung) within the MLC are ignored. The MLC model was tested for 6 MV and 18 MV photon beams by comparing it with measurements and MC simulations that incorporate the full physics and geometry for fields blocked by the MLC and with measurements for fields with the maximum possible tongue-and-groove and tongue-or-groove effects, for static test cases and for sliding windows of various widths. The MLC model predicts the field size dependence of the MLC leakage radiation within 0.1% of the open-field dose. The entrance dose and beam hardening behind a closed MLC are predicted within +/-1% or 1 mm. Dose undulations due to differences in inter- and intra-leaf leakage are also correctly predicted. The MC MLC model predicts leaf-edge tongue-and-groove dose effect within +/-1% or 1 mm for 95% of the points compared at 6 MV and 88% of the points compared at 18 MV. The dose through a static leaf tip is also predicted generally within +/-1% or 1 mm. Tests with sliding windows of various widths confirm the accuracy of the MLC model for dynamic delivery and indicate that accounting for a slight leaf position error (0.008 cm for our MLC) will improve the accuracy of the model. The MLC model developed is applicable to both dynamic MLC and segmental MLC IMRT beam delivery and will be useful for patient IMRT dose calculations, pre-treatment verification of IMRT delivery and IMRT portal dose transmission dosimetry.

SU-E-J-205: Monte Carlo Modeling of Ultrasound Probes for Real-Time Ultrasound Image-Guided Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hristov, D; Schlosser, J; Bazalova, M

2014-06-01

Purpose: To quantify the effect of ultrasound (US) probe beam attenuation for radiation therapy delivered under real-time US image guidance by means of Monte Carlo (MC) simulations. Methods: MC models of two Philips US probes, an X6-1 matrix-array transducer and a C5-2 curved-array transducer, were built based on their CT images in the EGSnrc BEAMnrc and DOSXYZnrc codes. Due to the metal parts, the probes were scanned in a Tomotherapy machine with a 3.5 MV beam. Mass densities in the probes were assigned based on an electron density calibration phantom consisting of cylinders with mass densities between 0.2–8.0 g/cm{sup 3}.more » Beam attenuation due to the probes was measured in a solid water phantom for a 6 MV and 15 MV 15x15 cm{sup 2} beam delivered on a Varian Trilogy linear accelerator. The dose was measured with the PTW-729 ionization chamber array at two depths and compared to MC simulations. The extreme case beam attenuation expected in robotic US image guided radiotherapy for probes in upright position was quantified by means of MC simulations. Results: The 3.5 MV CT number to mass density calibration curve was found to be linear with R{sup 2} > 0.99. The maximum mass densities were 4.6 and 4.2 g/cm{sup 3} in the C5-2 and X6-1 probe, respectively. Gamma analysis of the simulated and measured doses revealed that over 98% of measurement points passed the 3%/3mm criteria for both probes and measurement depths. The extreme attenuation for probes in upright position was found to be 25% and 31% for the C5-2 and X6-1 probe, respectively, for both 6 and 15 MV beams at 10 cm depth. Conclusion: MC models of two US probes used for real-time image guidance during radiotherapy have been built. As a Result, radiotherapy treatment planning with the imaging probes in place can now be performed. J Schlosser is an employee of SoniTrack Systems, Inc. D Hristov has financial interest in SoniTrack Systems, Inc.« less

Poster - Thur Eve - 45: Commissioning of the Varian ECLIPSE eMC algorithm for clinical electron treatment planning.

PubMed

Serban, M; Ruo, R; Sarfehnia, A; Parker, W; Evans, M

2012-07-01

Fast electron Monte Carlo systems have been developed commercially, and implemented for clinical practice in radiation therapy clinics. In this work the Varian eMC (electron Monte Carlo) algorithm was commissioned for clinical electron beams of energies between 6 MeV and 20 MeV. Beam outputs, PDDs and profiles were measured for 29 regular and irregular cutouts using the IC-10 (Wellhöfer) ionization chamber. Detailed percentage depth dose comparisons showed that the agreement between measurement and eMC for different characteristic points on the PDD are generally less than 1 mm and always less than 2 mm, with the eMC calculated values being lower than the measured values. Of the 145 measured output factors, 19 cases fail a ±2% agreement but only 8 cases fail a ±3% agreement between calculation and measurement. Comparison of central axis dose distributions for two electron energies (9, and 20 MeV) for a 10 × 10 cm 2 field, centrally shielded with Pb of width 0 cm (open), 1, 2 and 3 cm, shows agreement to within 3% except near the surface. Comparison of central axis dose distributions for 9 MeV in heterogeneous phantoms including bone and lung inserts showed agreement of 1 mm and 3 mm respectively with measured TLD data. The overall agreement between measurement and eMC calculation has enabled us to begin implementing this calculation model for clinical use. © 2012 American Association of Physicists in Medicine.

kmos: A lattice kinetic Monte Carlo framework

NASA Astrophysics Data System (ADS)

Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten

2014-07-01

Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abouelnasr, MKF; Smit, B

2012-01-01

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) Amore » new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective-diffusion behavior that was reproduced with kMC simulations.« less

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases.

PubMed

Abouelnasr, Mahmoud K F; Smit, Berend

2012-09-07

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) A new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective- diffusion behavior that was reproduced with kMC simulations.

Orthogonal Multi-Carrier DS-CDMA with Frequency-Domain Equalization

NASA Astrophysics Data System (ADS)

Tanaka, Ken; Tomeba, Hiromichi; Adachi, Fumiyuki

Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of orthogonal frequency division multiplexing (OFDM) and time-domain spreading, while multi-carrier code division multiple access (MC-CDMA) is a combination of OFDM and frequency-domain spreading. In MC-CDMA, a good bit error rate (BER) performance can be achieved by using frequency-domain equalization (FDE), since the frequency diversity gain is obtained. On the other hand, the conventional orthogonal MC DS-CDMA fails to achieve any frequency diversity gain. In this paper, we propose a new orthogonal MC DS-CDMA that can obtain the frequency diversity gain by applying FDE. The conditional BER analysis is presented. The theoretical average BER performance in a frequency-selective Rayleigh fading channel is evaluated by the Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation of the orthogonal MC DS-CDMA signal transmission.

SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dance, M; Wu, G; Gao, Y

2016-06-15

Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generatedmore » target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacent lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.« less

Validation of the Oncentra Brachy Advanced Collapsed cone Engine for a commercial (192)Ir source using heterogeneous geometries.

PubMed

Ma, Yunzhi; Lacroix, Fréderic; Lavallée, Marie-Claude; Beaulieu, Luc

2015-01-01

To validate the Advanced Collapsed cone Engine (ACE) dose calculation engine of Oncentra Brachy (OcB) treatment planning system using an (192)Ir source. Two levels of validation were performed, conformant to the model-based dose calculation algorithm commissioning guidelines of American Association of Physicists in Medicine TG-186 report. Level 1 uses all-water phantoms, and the validation is against TG-43 methodology. Level 2 uses real-patient cases, and the validation is against Monte Carlo (MC) simulations. For each case, the ACE and TG-43 calculations were performed in the OcB treatment planning system. ALGEBRA MC system was used to perform MC simulations. In Level 1, the ray effect depends on both accuracy mode and the number of dwell positions. The volume fraction with dose error ≥2% quickly reduces from 23% (13%) for a single dwell to 3% (2%) for eight dwell positions in the standard (high) accuracy mode. In Level 2, the 10% and higher isodose lines were observed overlapping between ACE (both standard and high-resolution modes) and MC. Major clinical indices (V100, V150, V200, D90, D50, and D2cc) were investigated and validated by MC. For example, among the Level 2 cases, the maximum deviation in V100 of ACE from MC is 2.75% but up to ~10% for TG-43. Similarly, the maximum deviation in D90 is 0.14 Gy between ACE and MC but up to 0.24 Gy for TG-43. ACE demonstrated good agreement with MC in most clinically relevant regions in the cases tested. Departure from MC is significant for specific situations but limited to low-dose (<10% isodose) regions. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment

NASA Astrophysics Data System (ADS)

Almeida, Isabel P.; Schyns, Lotte E. J. R.; Vaniqui, Ana; van der Heyden, Brent; Dedes, George; Resch, Andreas F.; Kamp, Florian; Zindler, Jaap D.; Parodi, Katia; Landry, Guillaume; Verhaegen, Frank

2018-06-01

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for GEANT4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with  >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in  ‑1.2  ±  1.2 mm (‑0.5%  ±  0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

Limitations of analytical dose calculations for small field proton radiosurgery.

PubMed

Geng, Changran; Daartz, Juliane; Lam-Tin-Cheung, Kimberley; Bussiere, Marc; Shih, Helen A; Paganetti, Harald; Schuemann, Jan

2017-01-07

The purpose of the work was to evaluate the dosimetric uncertainties of an analytical dose calculation engine and the impact on treatment plans using small fields in intracranial proton stereotactic radiosurgery (PSRS) for a gantry based double scattering system. 50 patients were evaluated including 10 patients for each of 5 diagnostic indications of: arteriovenous malformation (AVM), acoustic neuroma (AN), meningioma (MGM), metastasis (METS), and pituitary adenoma (PIT). Treatment plans followed standard prescription and optimization procedures for PSRS. We performed comparisons between delivered dose distributions, determined by Monte Carlo (MC) simulations, and those calculated with the analytical dose calculation algorithm (ADC) used in our current treatment planning system in terms of dose volume histogram parameters and beam range distributions. Results show that the difference in the dose to 95% of the target (D95) is within 6% when applying measured field size output corrections for AN, MGM, and PIT. However, for AVM and METS, the differences can be as great as 10% and 12%, respectively. Normalizing the MC dose to the ADC dose based on the dose of voxels in a central area of the target reduces the difference of the D95 to within 6% for all sites. The generally applied margin to cover uncertainties in range (3.5% of the prescribed range  +  1 mm) is not sufficient to cover the range uncertainty for ADC in all cases, especially for patients with high tissue heterogeneity. The root mean square of the R90 difference, the difference in the position of distal falloff to 90% of the prescribed dose, is affected by several factors, especially the patient geometry heterogeneity, modulation and field diameter. In conclusion, implementation of Monte Carlo dose calculation techniques into the clinic can reduce the uncertainty of the target dose for proton stereotactic radiosurgery. If MC is not available for treatment planning, using MC dose distributions to adjust the delivered doses level can also reduce uncertainties below 3% for mean target dose and 6% for the D95.

Development of a generalized perturbation theory method for sensitivity analysis using continuous-energy Monte Carlo methods

DOE PAGES

Perfetti, Christopher M.; Rearden, Bradley T.

2016-03-01

The sensitivity and uncertainty analysis tools of the ORNL SCALE nuclear modeling and simulation code system that have been developed over the last decade have proven indispensable for numerous application and design studies for nuclear criticality safety and reactor physics. SCALE contains tools for analyzing the uncertainty in the eigenvalue of critical systems, but cannot quantify uncertainty in important neutronic parameters such as multigroup cross sections, fuel fission rates, activation rates, and neutron fluence rates with realistic three-dimensional Monte Carlo simulations. A more complete understanding of the sources of uncertainty in these design-limiting parameters could lead to improvements in processmore » optimization, reactor safety, and help inform regulators when setting operational safety margins. A novel approach for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was recently explored as academic research and has been found to accurately and rapidly calculate sensitivity coefficients in criticality safety applications. The work presented here describes a new method, known as the GEAR-MC method, which extends the CLUTCH theory for calculating eigenvalue sensitivity coefficients to enable sensitivity coefficient calculations and uncertainty analysis for a generalized set of neutronic responses using high-fidelity continuous-energy Monte Carlo calculations. Here, several criticality safety systems were examined to demonstrate proof of principle for the GEAR-MC method, and GEAR-MC was seen to produce response sensitivity coefficients that agreed well with reference direct perturbation sensitivity coefficients.« less

Simulation tools for scattering corrections in spectrally resolved x-ray computed tomography using McXtrace

NASA Astrophysics Data System (ADS)

Busi, Matteo; Olsen, Ulrik L.; Knudsen, Erik B.; Frisvad, Jeppe R.; Kehres, Jan; Dreier, Erik S.; Khalil, Mohamad; Haldrup, Kristoffer

2018-03-01

Spectral computed tomography is an emerging imaging method that involves using recently developed energy discriminating photon-counting detectors (PCDs). This technique enables measurements at isolated high-energy ranges, in which the dominating undergoing interaction between the x-ray and the sample is the incoherent scattering. The scattered radiation causes a loss of contrast in the results, and its correction has proven to be a complex problem, due to its dependence on energy, material composition, and geometry. Monte Carlo simulations can utilize a physical model to estimate the scattering contribution to the signal, at the cost of high computational time. We present a fast Monte Carlo simulation tool, based on McXtrace, to predict the energy resolved radiation being scattered and absorbed by objects of complex shapes. We validate the tool through measurements using a CdTe single PCD (Multix ME-100) and use it for scattering correction in a simulation of a spectral CT. We found the correction to account for up to 7% relative amplification in the reconstructed linear attenuation. It is a useful tool for x-ray CT to obtain a more accurate material discrimination, especially in the high-energy range, where the incoherent scattering interactions become prevailing (>50 keV).

Evidence for using Monte Carlo calculated wall attenuation and scatter correction factors for three styles of graphite-walled ion chamber.

PubMed

McCaffrey, J P; Mainegra-Hing, E; Kawrakow, I; Shortt, K R; Rogers, D W O

2004-06-21

The basic equation for establishing a 60Co air-kerma standard based on a cavity ionization chamber includes a wall correction term that corrects for the attenuation and scatter of photons in the chamber wall. For over a decade, the validity of the wall correction terms determined by extrapolation methods (K(w)K(cep)) has been strongly challenged by Monte Carlo (MC) calculation methods (K(wall)). Using the linear extrapolation method with experimental data, K(w)K(cep) was determined in this study for three different styles of primary-standard-grade graphite ionization chamber: cylindrical, spherical and plane-parallel. For measurements taken with the same 60Co source, the air-kerma rates for these three chambers, determined using extrapolated K(w)K(cep) values, differed by up to 2%. The MC code 'EGSnrc' was used to calculate the values of K(wall) for these three chambers. Use of the calculated K(wall) values gave air-kerma rates that agreed within 0.3%. The accuracy of this code was affirmed by its reliability in modelling the complex structure of the response curve obtained by rotation of the non-rotationally symmetric plane-parallel chamber. These results demonstrate that the linear extrapolation technique leads to errors in the determination of air-kerma.

Analysis of light incident location and detector position in early diagnosis of knee osteoarthritis by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Chen, Yanping; Chen, Yisha; Yan, Huangping; Wang, Xiaoling

2017-01-01

Early detection of knee osteoarthritis (KOA) is meaningful to delay or prevent the onset of osteoarthritis. In consideration of structural complexity of knee joint, position of light incidence and detector appears to be extremely important in optical inspection. In this paper, the propagation of 780-nm near infrared photons in three-dimensional knee joint model is simulated by Monte Carlo (MC) method. Six light incident locations are chosen in total to analyze the influence of incident and detecting location on the number of detected signal photons and signal to noise ratio (SNR). Firstly, a three-dimensional photon propagation model of knee joint is reconstructed based on CT images. Then, MC simulation is performed to study the propagation of photons in three-dimensional knee joint model. Photons which finally migrate out of knee joint surface are numerically analyzed. By analyzing the number of signal photons and SNR from the six given incident locations, the optimal incident and detecting location is defined. Finally, a series of phantom experiments are conducted to verify the simulation results. According to the simulation and phantom experiments results, the best incident location is near the right side of meniscus at the rear end of left knee joint and the detector is supposed to be set near patella, correspondingly.

Stability of nanocrystalline Ni-based alloys: coupling Monte Carlo and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Waseda, O.; Goldenstein, H.; Silva, G. F. B. Lenz e.; Neiva, A.; Chantrenne, P.; Morthomas, J.; Perez, M.; Becquart, C. S.; Veiga, R. G. A.

2017-10-01

The thermal stability of nanocrystalline Ni due to small additions of Mo or W (up to 1 at%) was investigated in computer simulations by means of a combined Monte Carlo (MC)/molecular dynamics (MD) two-steps approach. In the first step, energy-biased on-lattice MC revealed segregation of the alloying elements to grain boundaries. However, the condition for the thermodynamic stability of these nanocrystalline Ni alloys (zero grain boundary energy) was not fulfilled. Subsequently, MD simulations were carried out for up to 0.5 μs at 1000 K. At this temperature, grain growth was hindered for minimum global concentrations of 0.5 at% W and 0.7 at% Mo, thus preserving most of the nanocrystalline structure. This is in clear contrast to a pure Ni model system, for which the transformation into a monocrystal was observed in MD simulations within 0.2 μs at the same temperature. These results suggest that grain boundary segregation of low-soluble alloying elements in low-alloyed systems can produce high-temperature metastable nanocrystalline materials. MD simulations carried out at 1200 K for 1 at% Mo/W showed significant grain boundary migration accompanied by some degree of solute diffusion, thus providing additional evidence that solute drag mostly contributed to the nanostructure stability observed at lower temperature.

Solar proton exposure of an ICRU sphere within a complex structure Part I: Combinatorial geometry.

PubMed

Wilson, John W; Slaba, Tony C; Badavi, Francis F; Reddell, Brandon D; Bahadori, Amir A

2016-06-01

The 3DHZETRN code, with improved neutron and light ion (Z≤2) transport procedures, was recently developed and compared to Monte Carlo (MC) simulations using simplified spherical geometries. It was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in general combinatorial geometry. A more complex shielding structure with internal parts surrounding a tissue sphere is considered and compared against MC simulations. It is shown that even in the more complex geometry, 3DHZETRN agrees well with the MC codes and maintains a high degree of computational efficiency. Published by Elsevier Ltd.

MC21 analysis of the MIT PWR benchmark: Hot zero power results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly Iii, D. J.; Aviles, B. N.; Herman, B. R.

2013-07-01

MC21 Monte Carlo results have been compared with hot zero power measurements from an operating pressurized water reactor (PWR), as specified in a new full core PWR performance benchmark from the MIT Computational Reactor Physics Group. Included in the comparisons are axially integrated full core detector measurements, axial detector profiles, control rod bank worths, and temperature coefficients. Power depressions from grid spacers are seen clearly in the MC21 results. Application of Coarse Mesh Finite Difference (CMFD) acceleration within MC21 has been accomplished, resulting in a significant reduction of inactive batches necessary to converge the fission source. CMFD acceleration has alsomore » been shown to work seamlessly with the Uniform Fission Site (UFS) variance reduction method. (authors)« less

Recent developments and comprehensive evaluations of a GPU-based Monte Carlo package for proton therapy

PubMed Central

Qin, Nan; Botas, Pablo; Giantsoudi, Drosoula; Schuemann, Jan; Tian, Zhen; Jiang, Steve B.; Paganetti, Harald; Jia, Xun

2016-01-01

Monte Carlo (MC) simulation is commonly considered as the most accurate dose calculation method for proton therapy. Aiming at achieving fast MC dose calculations for clinical applications, we have previously developed a GPU-based MC tool, gPMC. In this paper, we report our recent updates on gPMC in terms of its accuracy, portability, and functionality, as well as comprehensive tests on this tool. The new version, gPMC v2.0, was developed under the OpenCL environment to enable portability across different computational platforms. Physics models of nuclear interactions were refined to improve calculation accuracy. Scoring functions of gPMC were expanded to enable tallying particle fluence, dose deposited by different particle types, and dose-averaged linear energy transfer (LETd). A multiple counter approach was employed to improve efficiency by reducing frequency of memory writing conflict at scoring. For dose calculation, accuracy improvements over gPMC v1.0 were observed in both water phantom cases and a patient case. For a prostate cancer case planned using high-energy proton beams, dose discrepancies in beam entrance and target region seen in gPMC v1.0 with respect to the gold standard tool for proton Monte Carlo simulations (TOPAS) results were substantially reduced and gamma test passing rate (1%/1mm) was improved from 82.7% to 93.1%. Average relative difference in LETd between gPMC and TOPAS was 1.7%. Average relative differences in dose deposited by primary, secondary, and other heavier particles were within 2.3%, 0.4%, and 0.2%. Depending on source proton energy and phantom complexity, it took 8 to 17 seconds on an AMD Radeon R9 290x GPU to simulate 107 source protons, achieving less than 1% average statistical uncertainty. As beam size was reduced from 10×10 cm2 to 1×1 cm2, time on scoring was only increased by 4.8% with eight counters, in contrast to a 40% increase using only one counter. With the OpenCL environment, the portability of gPMC v2.0 was enhanced. It was successfully executed on different CPUs and GPUs and its performance on different devices varied depending on processing power and hardware structure. PMID:27694712

An experimental approach to improve the Monte Carlo modelling of offline PET/CT-imaging of positron emitters induced by scanned proton beams

NASA Astrophysics Data System (ADS)

Bauer, J.; Unholtz, D.; Kurz, C.; Parodi, K.

2013-08-01

We report on the experimental campaign carried out at the Heidelberg Ion-Beam Therapy Center (HIT) to optimize the Monte Carlo (MC) modelling of proton-induced positron-emitter production. The presented experimental strategy constitutes a pragmatic inverse approach to overcome the known uncertainties in the modelling of positron-emitter production due to the lack of reliable cross-section data for the relevant therapeutic energy range. This work is motivated by the clinical implementation of offline PET/CT-based treatment verification at our facility. Here, the irradiation induced tissue activation in the patient is monitored shortly after the treatment delivery by means of a commercial PET/CT scanner and compared to a MC simulated activity expectation, derived under the assumption of a correct treatment delivery. At HIT, the MC particle transport and interaction code FLUKA is used for the simulation of the expected positron-emitter yield. For this particular application, the code is coupled to externally provided cross-section data of several proton-induced reactions. Studying experimentally the positron-emitting radionuclide yield in homogeneous phantoms provides access to the fundamental production channels. Therefore, five different materials have been irradiated by monoenergetic proton pencil beams at various energies and the induced β+ activity subsequently acquired with a commercial full-ring PET/CT scanner. With the analysis of dynamically reconstructed PET images, we are able to determine separately the spatial distribution of different radionuclide concentrations at the starting time of the PET scan. The laterally integrated radionuclide yields in depth are used to tune the input cross-section data such that the impact of both the physical production and the imaging process on the various positron-emitter yields is reproduced. The resulting cross-section data sets allow to model the absolute level of measured β+ activity induced in the investigated targets within a few per cent. Moreover, the simulated distal activity fall-off positions, representing the central quantity for treatment monitoring in terms of beam range verification, are found to agree within 0.6 mm with the measurements at different initial beam energies in both homogeneous and heterogeneous targets. Based on work presented at the Third European Workshop on Monte Carlo Treatment Planning (Seville, 15-18 May 2012).

Build-up and surface dose measurements on phantoms using micro-MOSFET in 6 and 10 MV x-ray beams and comparisons with Monte Carlo calculations.

PubMed

Xiang, Hong F; Song, Jun S; Chin, David W H; Cormack, Robert A; Tishler, Roy B; Makrigiorgos, G Mike; Court, Laurence E; Chin, Lee M

2007-04-01

This work is intended to investigate the application and accuracy of micro-MOSFET for superficial dose measurement under clinically used MV x-ray beams. Dose response of micro-MOSFET in the build-up region and on surface under MV x-ray beams were measured and compared to Monte Carlo calculations. First, percentage-depth-doses were measured with micro-MOSFET under 6 and 10 MV beams of normal incidence onto a flat solid water phantom. Micro-MOSFET data were compared with the measurements from a parallel plate ionization chamber and Monte Carlo dose calculation in the build-up region. Then, percentage-depth-doses were measured for oblique beams at 0 degrees-80 degrees onto the flat solid water phantom with micro-MOSFET placed at depths of 2 cm, 1 cm, and 2 mm below the surface. Measurements were compared to Monte Carlo calculations under these settings. Finally, measurements were performed with micro-MOSFET embedded in the first 1 mm layer of bolus placed on a flat phantom and a curved phantom of semi-cylindrical shape. Results were compared to superficial dose calculated from Monte Carlo for a 2 mm thin layer that extends from the surface to a depth of 2 mm. Results were (1) Comparison of measurements with MC calculation in the build-up region showed that micro-MOSFET has a water-equivalence thickness (WET) of 0.87 mm for 6 MV beam and 0.99 mm for 10 MV beam from the flat side, and a WET of 0.72 mm for 6 MV beam and 0.76 mm for 10 MV beam from the epoxy side. (2) For normal beam incidences, percentage depth dose agree within 3%-5% among micro-MOSFET measurements, parallel-plate ionization chamber measurements, and MC calculations. (3) For oblique incidence on the flat phantom with micro-MOSFET placed at depths of 2 cm, 1 cm, and 2 mm, measurements were consistent with MC calculations within a typical uncertainty of 3%-5%. (4) For oblique incidence on the flat phantom and a curved-surface phantom, measurements with micro-MOSFET placed at 1.0 mm agrees with the MC calculation within 6%, including uncertainties of micro-MOSFET measurements of 2%-3% (1 standard deviation), MOSFET angular dependence of 3.0%-3.5%, and 1%-2% systematical error due to phantom setup geometry asymmetry. Micro-MOSFET can be used for skin dose measurements in 6 and 10 MV beams with an estimated accuracy of +/- 6%.

Modeling of Radiotherapy Linac Source Terms Using ARCHER Monte Carlo Code: Performance Comparison for GPU and MIC Parallel Computing Devices

NASA Astrophysics Data System (ADS)

Lin, Hui; Liu, Tianyu; Su, Lin; Bednarz, Bryan; Caracappa, Peter; Xu, X. George

2017-09-01

Monte Carlo (MC) simulation is well recognized as the most accurate method for radiation dose calculations. For radiotherapy applications, accurate modelling of the source term, i.e. the clinical linear accelerator is critical to the simulation. The purpose of this paper is to perform source modelling and examine the accuracy and performance of the models on Intel Many Integrated Core coprocessors (aka Xeon Phi) and Nvidia GPU using ARCHER and explore the potential optimization methods. Phase Space-based source modelling for has been implemented. Good agreements were found in a tomotherapy prostate patient case and a TrueBeam breast case. From the aspect of performance, the whole simulation for prostate plan and breast plan cost about 173s and 73s with 1% statistical error.

LCG MCDB—a knowledgebase of Monte-Carlo simulated events

NASA Astrophysics Data System (ADS)

Belov, S.; Dudko, L.; Galkin, E.; Gusev, A.; Pokorski, W.; Sherstnev, A.

2008-02-01

In this paper we report on LCG Monte-Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC Collaborations by experts. In many cases, the modern Monte-Carlo simulation of physical processes requires expert knowledge in Monte-Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly dedicated to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project. Program summaryProgram title: LCG Monte-Carlo Data Base Catalogue identifier: ADZX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 30 129 No. of bytes in distributed program, including test data, etc.: 216 943 Distribution format: tar.gz Programming language: Perl Computer: CPU: Intel Pentium 4, RAM: 1 Gb, HDD: 100 Gb Operating system: Scientific Linux CERN 3/4 RAM: 1 073 741 824 bytes (1 Gb) Classification: 9 External routines:perl >= 5.8.5; Perl modules DBD-mysql >= 2.9004, File::Basename, GD::SecurityImage, GD::SecurityImage::AC, Linux::Statistics, XML::LibXML > 1.6, XML::SAX, XML::NamespaceSupport; Apache HTTP Server >= 2.0.59; mod auth external >= 2.2.9; edg-utils-system RPM package; gd >= 2.0.28; rpm package CASTOR-client >= 2.1.2-4; arc-server (optional) Nature of problem: Often, different groups of experimentalists prepare similar samples of particle collision events or turn to the same group of authors of Monte-Carlo (MC) generators to prepare the events. For example, the same MC samples of Standard Model (SM) processes can be employed for the investigations either in the SM analyses (as a signal) or in searches for new phenomena in Beyond Standard Model analyses (as a background). If the samples are made available publicly and equipped with corresponding and comprehensive documentation, it can speed up cross checks of the samples themselves and physical models applied. Some event samples require a lot of computing resources for preparation. So, a central storage of the samples prevents possible waste of researcher time and computing resources, which can be used to prepare the same events many times. Solution method: Creation of a special knowledgebase (MCDB) designed to keep event samples for the LHC experimental and phenomenological community. The knowledgebase is realized as a separate web-server ( http://mcdb.cern.ch). All event samples are kept on types at CERN. Documentation describing the events is the main contents of MCDB. Users can browse the knowledgebase, read and comment articles (documentation), and download event samples. Authors can upload new event samples, create new articles, and edit own articles. Restrictions: The software is adopted to solve the problems, described in the article and there are no any additional restrictions. Unusual features: The software provides a framework to store and document large files with flexible authentication and authorization system. Different external storages with large capacity can be used to keep the files. The WEB Content Management System provides all of the necessary interfaces for the authors of the files, end-users and administrators. Running time: Real time operations. References: [1] The main LCG MCDB server, http://mcdb.cern.ch/. [2] P. Bartalini, L. Dudko, A. Kryukov, I.V. Selyuzhenkov, A. Sherstnev, A. Vologdin, LCG Monte-Carlo data base, hep-ph/0404241. [3] J.P. Baud, B. Couturier, C. Curran, J.D. Durand, E. Knezo, S. Occhetti, O. Barring, CASTOR: status and evolution, cs.oh/0305047.

Rotating and translating anthropomorphic head voxel models to establish an horizontal Frankfort plane for dental CBCT Monte Carlo simulations: a dose comparison study

NASA Astrophysics Data System (ADS)

Stratis, A.; Zhang, G.; Jacobs, R.; Bogaerts, R.; Bosmans, H.

2016-12-01

In order to carry out Monte Carlo (MC) dosimetry studies, voxel phantoms, modeling human anatomy, and organ-based segmentation of CT image data sets are applied to simulation frameworks. The resulting voxel phantoms preserve patient CT acquisition geometry; in the case of head voxel models built upon head CT images, the head support with which CT scanners are equipped introduces an inclination to the head, and hence to the head voxel model. In dental cone beam CT (CBCT) imaging, patients are always positioned in such a way that the Frankfort line is horizontal, implying that there is no head inclination. The orientation of the head is important, as it influences the distance of critical radiosensitive organs like the thyroid and the esophagus from the x-ray tube. This work aims to propose a procedure to adjust head voxel phantom orientation, and to investigate the impact of head inclination on organ doses in dental CBCT MC dosimetry studies. The female adult ICRP, and three in-house-built paediatric voxel phantoms were in this study. An EGSnrc MC framework was employed to simulate two commonly used protocols; a Morita Accuitomo 170 dental CBCT scanner (FOVs: 60  ×  60 mm2 and 80  ×  80 mm2, standard resolution), and a 3D Teeth protocol (FOV: 100  ×  90 mm2) in a Planmeca Promax 3D MAX scanner. Result analysis revealed large absorbed organ dose differences in radiosensitive organs between the original and the geometrically corrected voxel models of this study, ranging from  -45.6% to 39.3%. Therefore, accurate dental CBCT MC dose calculations require geometrical adjustments to be applied to head voxel models.

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator

NASA Astrophysics Data System (ADS)

Suh, Donghyuk; Radak, Brian K.; Chipot, Christophe; Roux, Benoît

2018-01-01

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator.

PubMed

Suh, Donghyuk; Radak, Brian K; Chipot, Christophe; Roux, Benoît

2018-01-07

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

Effect of Gold Nanoparticles on Prostate Dose Distribution under Ir-192 Internal and 18 MV External Radiotherapy Procedures Using Gel Dosimetry and Monte Carlo Method.

PubMed

Khosravi, H; Hashemi, B; Mahdavi, S R; Hejazi, P

2015-03-01

Gel polymers are considered as new dosimeters for determining radiotherapy dose distribution in three dimensions. The ability of a new formulation of MAGIC-f polymer gel was assessed by experimental measurement and Monte Carlo (MC) method for studying the effect of gold nanoparticles (GNPs) in prostate dose distributions under the internal Ir-192 and external 18MV radiotherapy practices. A Plexiglas phantom was made representing human pelvis. The GNP shaving 15 nm in diameter and 0.1 mM concentration were synthesized using chemical reduction method. Then, a new formulation of MAGIC-f gel was synthesized. The fabricated gel was poured in the tubes located at the prostate (with and without the GNPs) and bladder locations of the phantom. The phantom was irradiated to an Ir-192 source and 18 MV beam of a Varian linac separately based on common radiotherapy procedures used for prostate cancer. After 24 hours, the irradiated gels were read using a Siemens 1.5 Tesla MRI scanner. The absolute doses at the reference points and isodose curves resulted from the experimental measurement of the gels and MC simulations following the internal and external radiotherapy practices were compared. The mean absorbed doses measured with the gel in the presence of the GNPs in prostate were 15% and 8 % higher than the corresponding values without the GNPs under the internal and external radiation therapies, respectively. MC simulations also indicated a dose increase of 14 % and 7 % due to presence of the GNPs, for the same experimental internal and external radiotherapy practices, respectively. There was a good agreement between the dose enhancement factors (DEFs) estimated with MC simulations and experiment gel measurements due to the GNPs. The results indicated that the polymer gel dosimetry method as developed and used in this study, can be recommended as a reliable method for investigating the DEF of GNPs in internal and external radiotherapy practices.

Dosimetric response of variable-size cavities in photon-irradiated media and the behaviour of the Spencer-Attix cavity integral with increasing Δ.

PubMed

Kumar, Sudhir; Deshpande, Deepak D; Nahum, Alan E

2016-04-07

Cavity theory is fundamental to understanding and predicting dosimeter response. Conventional cavity theories have been shown to be consistent with one another by deriving the electron (+positron) and photon fluence spectra with the FLURZnrc user-code (EGSnrc Monte-Carlo system) in large volumes under quasi-CPE for photon beams of 1 MeV and 10 MeV in three materials (water, aluminium and copper) and then using these fluence spectra to evaluate and then inter-compare the Bragg-Gray, Spencer-Attix and 'large photon' 'cavity integrals'. The behaviour of the 'Spencer-Attix dose' (aka restricted cema), D S-A(▵), in a 1-MeV photon field in water has been investigated for a wide range of values of the cavity-size parameter ▵: D S-A(▵) decreases far below the Monte-Carlo dose (D MC) for ▵ greater than  ≈  30 keV due to secondary electrons with starting energies below ▵ not being 'counted'. We show that for a quasi-scatter-free geometry (D S-A(▵)/D MC) is closely equal to the proportion of energy transferred to Compton electrons with initial (kinetic) energies above ▵, derived from the Klein-Nishina (K-N) differential cross section. (D S-A(▵)/D MC) can be used to estimate the maximum size of a detector behaving as a Bragg-Gray cavity in a photon-irradiated medium as a function of photon-beam quality (under quasi CPE) e.g. a typical air-filled ion chamber is 'Bragg-Gray' at (monoenergetic) beam energies  ⩾260 keV. Finally, by varying the density of a silicon cavity (of 2.26 mm diameter and 2.0 mm thickness) in water, the response of different cavity 'sizes' was simulated; the Monte-Carlo-derived ratio D w/D Si for 6 MV and 15 MV photons varied from very close to the Spencer-Attix value at 'gas' densities, agreed well with Burlin cavity theory as ρ increased, and approached large photon behaviour for ρ  ≈  10 g cm(-3). The estimate of ▵ for the Si cavity was improved by incorporating a Monte-Carlo-derived correction for electron 'detours'. Excellent agreement was obtained between the Burlin 'd' factor for the Si cavity and D S-A(▵)/D MC at different (detour-corrected) ▵, thereby suggesting a further application for the D S-A(▵)/D MC ratio.

Improving x-ray fluorescence signal for benchtop polychromatic cone-beam x-ray fluorescence computed tomography by incident x-ray spectrum optimization: A Monte Carlo study

PubMed Central

Manohar, Nivedh; Jones, Bernard L.; Cho, Sang Hyun

2014-01-01

Purpose: To develop an accurate and comprehensive Monte Carlo (MC) model of an experimental benchtop polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) setup and apply this MC model to optimize incident x-ray spectrum for improving production/detection of x-ray fluorescence photons from gold nanoparticles (GNPs). Methods: A detailed MC model, based on an experimental XFCT system, was created using the Monte Carlo N-Particle (MCNP) transport code. The model was validated by comparing MC results including x-ray fluorescence (XRF) and scatter photon spectra with measured data obtained under identical conditions using 105 kVp cone-beam x-rays filtered by either 1 mm of lead (Pb) or 0.9 mm of tin (Sn). After validation, the model was used to investigate the effects of additional filtration of the incident beam with Pb and Sn. Supplementary incident x-ray spectra, representing heavier filtration (Pb: 2 and 3 mm; Sn: 1, 2, and 3 mm) were computationally generated and used with the model to obtain XRF/scatter spectra. Quasimonochromatic incident x-ray spectra (81, 85, 90, 95, and 100 keV with 10 keV full width at half maximum) were also investigated to determine the ideal energy for distinguishing gold XRF signal from the scatter background. Fluorescence signal-to-dose ratio (FSDR) and fluorescence-normalized scan time (FNST) were used as metrics to assess results. Results: Calculated XRF/scatter spectra for 1-mm Pb and 0.9-mm Sn filters matched (r ≥ 0.996) experimental measurements. Calculated spectra representing additional filtration for both filter materials showed that the spectral hardening improved the FSDR at the expense of requiring a much longer FNST. In general, using Sn instead of Pb, at a given filter thickness, allowed an increase of up to 20% in FSDR, more prominent gold XRF peaks, and up to an order of magnitude decrease in FNST. Simulations using quasimonochromatic spectra suggested that increasing source x-ray energy, in the investigated range of 81–100 keV, increased the FSDR up to a factor of 20, compared to 1 mm Pb, and further facilitated separation of gold XRF peaks from the scatter background. Conclusions: A detailed MC model of an experimental benchtop XFCT system has been developed and validated. In exemplary calculations to illustrate the usefulness of this model, it was shown that potential use of quasimonochromatic spectra or judicious choice of filter material/thickness to tailor the spectrum of a polychromatic x-ray source can significantly improve the performance of benchtop XFCT, while considering trade-offs between FSDR and FNST. As demonstrated, the current MC model is a reliable and powerful computational tool that can greatly expedite the further development of a benchtop XFCT system for routine preclinical molecular imaging with GNPs and other metal probes. PMID:25281958

Improving x-ray fluorescence signal for benchtop polychromatic cone-beam x-ray fluorescence computed tomography by incident x-ray spectrum optimization: a Monte Carlo study.

PubMed

Manohar, Nivedh; Jones, Bernard L; Cho, Sang Hyun

2014-10-01

To develop an accurate and comprehensive Monte Carlo (MC) model of an experimental benchtop polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) setup and apply this MC model to optimize incident x-ray spectrum for improving production/detection of x-ray fluorescence photons from gold nanoparticles (GNPs). A detailed MC model, based on an experimental XFCT system, was created using the Monte Carlo N-Particle (MCNP) transport code. The model was validated by comparing MC results including x-ray fluorescence (XRF) and scatter photon spectra with measured data obtained under identical conditions using 105 kVp cone-beam x-rays filtered by either 1 mm of lead (Pb) or 0.9 mm of tin (Sn). After validation, the model was used to investigate the effects of additional filtration of the incident beam with Pb and Sn. Supplementary incident x-ray spectra, representing heavier filtration (Pb: 2 and 3 mm; Sn: 1, 2, and 3 mm) were computationally generated and used with the model to obtain XRF/scatter spectra. Quasimonochromatic incident x-ray spectra (81, 85, 90, 95, and 100 keV with 10 keV full width at half maximum) were also investigated to determine the ideal energy for distinguishing gold XRF signal from the scatter background. Fluorescence signal-to-dose ratio (FSDR) and fluorescence-normalized scan time (FNST) were used as metrics to assess results. Calculated XRF/scatter spectra for 1-mm Pb and 0.9-mm Sn filters matched (r ≥ 0.996) experimental measurements. Calculated spectra representing additional filtration for both filter materials showed that the spectral hardening improved the FSDR at the expense of requiring a much longer FNST. In general, using Sn instead of Pb, at a given filter thickness, allowed an increase of up to 20% in FSDR, more prominent gold XRF peaks, and up to an order of magnitude decrease in FNST. Simulations using quasimonochromatic spectra suggested that increasing source x-ray energy, in the investigated range of 81-100 keV, increased the FSDR up to a factor of 20, compared to 1 mm Pb, and further facilitated separation of gold XRF peaks from the scatter background. A detailed MC model of an experimental benchtop XFCT system has been developed and validated. In exemplary calculations to illustrate the usefulness of this model, it was shown that potential use of quasimonochromatic spectra or judicious choice of filter material/thickness to tailor the spectrum of a polychromatic x-ray source can significantly improve the performance of benchtop XFCT, while considering trade-offs between FSDR and FNST. As demonstrated, the current MC model is a reliable and powerful computational tool that can greatly expedite the further development of a benchtop XFCT system for routine preclinical molecular imaging with GNPs and other metal probes.

Photon beam dosimetry with EBT3 film in heterogeneous regions: Application to the evaluation of dose-calculation algorithms

NASA Astrophysics Data System (ADS)

Jung, Hyunuk; Kum, Oyeon; Han, Youngyih; Park, Byungdo; Cheong, Kwang-Ho

2014-12-01

For a better understanding of the accuracy of state-of-the-art-radiation therapies, 2-dimensional dosimetry in a patient-like environment will be helpful. Therefore, the dosimetry of EBT3 films in non-water-equivalent tissues was investigated, and the accuracy of commercially-used dose-calculation algorithms was evaluated with EBT3 measurement. Dose distributions were measured with EBT3 films for an in-house-designed phantom that contained a lung or a bone substitute, i.e., an air cavity (3 × 3 × 3 cm3) or teflon (2 × 2 × 2 cm3 or 3 × 3 × 3 cm3), respectively. The phantom was irradiated with 6-MV X-rays with field sizes of 2 × 2, 3 × 3, and 5 × 5 cm2. The accuracy of EBT3 dosimetry was evaluated by comparing the measured dose with the dose obtained from Monte Carlo (MC) simulations. A dose-to-bone-equivalent material was obtained by multiplying the EBT3 measurements by the stopping power ratio (SPR). The EBT3 measurements were then compared with the predictions from four algorithms: Monte Carlo (MC) in iPlan, acuros XB (AXB), analytical anisotropic algorithm (AAA) in Eclipse, and superposition-convolution (SC) in Pinnacle. For the air cavity, the EBT3 measurements agreed with the MC calculation to within 2% on average. For teflon, the EBT3 measurements differed by 9.297% (±0.9229%) on average from the Monte Carlo calculation before dose conversion, and by 0.717% (±0.6546%) after applying the SPR. The doses calculated by using the MC, AXB, AAA, and SC algorithms for the air cavity differed from the EBT3 measurements on average by 2.174, 2.863, 18.01, and 8.391%, respectively; for teflon, the average differences were 3.447, 4.113, 7.589, and 5.102%. The EBT3 measurements corrected with the SPR agreed with 2% on average both within and beyond the heterogeneities with MC results, thereby indicating that EBT3 dosimetry can be used in heterogeneous media. The MC and the AXB dose calculation algorithms exhibited clinically-acceptable accuracy (<5%) in heterogeneities.

Verification of recursive probabilistic integration (RPI) method for fatigue life management using non-destructive inspections

NASA Astrophysics Data System (ADS)

Chen, Tzikang J.; Shiao, Michael

2016-04-01

This paper verified a generic and efficient assessment concept for probabilistic fatigue life management. The concept is developed based on an integration of damage tolerance methodology, simulations methods1, 2, and a probabilistic algorithm RPI (recursive probability integration)3-9 considering maintenance for damage tolerance and risk-based fatigue life management. RPI is an efficient semi-analytical probabilistic method for risk assessment subjected to various uncertainties such as the variability in material properties including crack growth rate, initial flaw size, repair quality, random process modeling of flight loads for failure analysis, and inspection reliability represented by probability of detection (POD). In addition, unlike traditional Monte Carlo simulations (MCS) which requires a rerun of MCS when maintenance plan is changed, RPI can repeatedly use a small set of baseline random crack growth histories excluding maintenance related parameters from a single MCS for various maintenance plans. In order to fully appreciate the RPI method, a verification procedure was performed. In this study, MC simulations in the orders of several hundred billions were conducted for various flight conditions, material properties, and inspection scheduling, POD and repair/replacement strategies. Since the MC simulations are time-consuming methods, the simulations were conducted parallelly on DoD High Performance Computers (HPC) using a specialized random number generator for parallel computing. The study has shown that RPI method is several orders of magnitude more efficient than traditional Monte Carlo simulations.

Neutron Angular Scatter Effects in 3DHZETRN: Quasi-Elastic

NASA Technical Reports Server (NTRS)

Wilson, John W.; Werneth, Charles M.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2017-01-01

The current 3DHZETRN code has a detailed three dimensional (3D) treatment of neutron transport based on a forward/isotropic assumption and has been compared to Monte Carlo (MC) simulation codes in various geometries. In most cases, it has been found that 3DHZETRN agrees with the MC codes to the extent they agree with each other. However, a recent study of neutron leakage from finite geometries revealed that further improvements to the 3DHZETRN formalism are needed. In the present report, angular scattering corrections to the neutron fluence are provided in an attempt to improve fluence estimates from a uniform sphere. It is found that further developments in the nuclear production models are required to fully evaluate the impact of transport model updates. A model for the quasi-elastic neutron production spectra is therefore developed and implemented into 3DHZETRN.

Instrumental resolution of the chopper spectrometer 4SEASONS evaluated by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Kajimoto, Ryoichi; Sato, Kentaro; Inamura, Yasuhiro; Fujita, Masaki

2018-05-01

We performed simulations of the resolution function of the 4SEASONS spectrometer at J-PARC by using the Monte Carlo simulation package McStas. The simulations showed reasonably good agreement with analytical calculations of energy and momentum resolutions by using a simplified description. We implemented new functionalities in Utsusemi, the standard data analysis tool used in 4SEASONS, to enable visualization of the simulated resolution function and predict its shape for specific experimental configurations.

A Probabilistic Collocation Based Iterative Kalman Filter for Landfill Data Assimilation

NASA Astrophysics Data System (ADS)

Qiang, Z.; Zeng, L.; Wu, L.

2016-12-01

Due to the strong spatial heterogeneity of landfill, uncertainty is ubiquitous in gas transport process in landfill. To accurately characterize the landfill properties, the ensemble Kalman filter (EnKF) has been employed to assimilate the measurements, e.g., the gas pressure. As a Monte Carlo (MC) based method, the EnKF usually requires a large ensemble size, which poses a high computational cost for large scale problems. In this work, we propose a probabilistic collocation based iterative Kalman filter (PCIKF) to estimate permeability in a liquid-gas coupling model. This method employs polynomial chaos expansion (PCE) to represent and propagate the uncertainties of model parameters and states, and an iterative form of Kalman filter to assimilate the current gas pressure data. To further reduce the computation cost, the functional ANOVA (analysis of variance) decomposition is conducted, and only the first order ANOVA components are remained for PCE. Illustrated with numerical case studies, this proposed method shows significant superiority in computation efficiency compared with the traditional MC based iterative EnKF. The developed method has promising potential in reliable prediction and management of landfill gas production.

MCMEG: Simulations of both PDD and TPR for 6 MV LINAC photon beam using different MC codes

NASA Astrophysics Data System (ADS)

Fonseca, T. C. F.; Mendes, B. M.; Lacerda, M. A. S.; Silva, L. A. C.; Paixão, L.; Bastos, F. M.; Ramirez, J. V.; Junior, J. P. R.

2017-11-01

The Monte Carlo Modelling Expert Group (MCMEG) is an expert network specializing in Monte Carlo radiation transport and the modelling and simulation applied to the radiation protection and dosimetry research field. For the first inter-comparison task the group launched an exercise to model and simulate a 6 MV LINAC photon beam using the Monte Carlo codes available within their laboratories and validate their simulated results by comparing them with experimental measurements carried out in the National Cancer Institute (INCA) in Rio de Janeiro, Brazil. The experimental measurements were performed using an ionization chamber with calibration traceable to a Secondary Standard Dosimetry Laboratory (SSDL). The detector was immersed in a water phantom at different depths and was irradiated with a radiation field size of 10×10 cm2. This exposure setup was used to determine the dosimetric parameters Percentage Depth Dose (PDD) and Tissue Phantom Ratio (TPR). The validation process compares the MC calculated results to the experimental measured PDD20,10 and TPR20,10. Simulations were performed reproducing the experimental TPR20,10 quality index which provides a satisfactory description of both the PDD curve and the transverse profiles at the two depths measured. This paper reports in detail the modelling process using MCNPx, MCNP6, EGSnrc and Penelope Monte Carlo codes, the source and tally descriptions, the validation processes and the results.

MC EMiNEM maps the interaction landscape of the Mediator.

PubMed

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C; Martin, Dietmar E; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.

Estimating the Standard Error of Robust Regression Estimates.

DTIC Science & Technology

1987-03-01

error is 0(n4/5). In another Monte Carlo study, McKean and Schrader (1984) found that the tests resulting from studentizing ; by _3d/1/2 with d =0(n4 /5...44 4 -:~~-~*v: -. *;~ ~ ~*t .~ # ~ 44 % * ~ .%j % % % * . ., ~ -%. -14- Sheather, S. J. and McKean, J. W. (1987). A comparison of testing and...Wiley, New York. Welsch, R. E. (1980). Regression Sensitivity Analysis and Bounded- Influence Estimation, in Evaluation of Econometric Models eds. J

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagaoka, Masataka; Core Research for Evolutional Science and Technology; ESICB, Kyoto University, Kyodai Katsura, Nishikyo-ku, Kyoto 615-8520

A new efficient hybrid Monte Carlo (MC)/molecular dynamics (MD) reaction method with a rare event-driving mechanism is introduced as a practical ‘atomistic’ molecular simulation of large-scale chemically reactive systems. Starting its demonstrative application to the racemization reaction of (R)-2-chlorobutane in N,N-dimethylformamide solution, several other applications are shown from the practical viewpoint of molecular controlling of complex chemical reactions, stereochemistry and aggregate structures. Finally, I would like to mention the future applications of the hybrid MC/MD reaction method.

Theoretical study of the ammonia nitridation rate on an Fe (100) surface: A combined density functional theory and kinetic Monte Carlo study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeo, Sang Chul; Lee, Hyuck Mo, E-mail: hmlee@kaist.ac.kr; Lo, Yu Chieh

2014-10-07

Ammonia (NH{sub 3}) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (E{sub b}) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (E{sub b}) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH{sub 3} nitridation rate onmore » the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH{sub 3} nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH{sub 3} nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH{sub 3} nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.« less

MC-TESTER v. 1.23: A universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

NASA Astrophysics Data System (ADS)

Davidson, N.; Golonka, P.; Przedziński, T.; Waş, Z.

2011-03-01

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be used for such tests of decays of intermediate states (particles or resonances) in a semi-automated way. Since 2002 new functionalities were introduced into the package. In particular, it now works with the HepMC event record, the standard for C++ programs. The complete set-up for benchmarking the interfaces, such as interface between τ-lepton production and decay, including QED bremsstrahlung effects is shown. The example is chosen to illustrate the new options introduced into the program. From the technical perspective, our paper documents software updates and supplements previous documentation. As in the past, our test consists of two steps. Distinct Monte Carlo programs are run separately; events with decays of a chosen particle are searched, and information is stored by MC-TESTER. Then, at the analysis step, information from a pair of runs may be compared and represented in the form of tables and plots. Updates introduced in the program up to version 1.24.4 are also documented. In particular, new configuration scripts or script to combine results from multitude of runs into single information file to be used in analysis step are explained. Program summaryProgram title: MC-TESTER, version 1.23 and version 1.24.4 Catalog identifier: ADSM_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSM_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 250 548 No. of bytes in distributed program, including test data, etc.: 4 290 610 Distribution format: tar.gz Programming language: C++, FORTRAN77 Tested and compiled with: gcc 3.4.6, 4.2.4 and 4.3.2 with g77/gfortran Computer: Tested on various platforms Operating system: Tested on operating systems: Linux SLC 4.6 and SLC 5, Fedora 8, Ubuntu 8.2 etc. Classification: 11.9 External routines: HepMC ( https://savannah.cern.ch/projects/hepmc/), PYTHIA8 ( http://home.thep.lu.se/~torbjorn/Pythia.html), LaTeX ( http://www.latex-project.org/) Catalog identifier of previous version: ADSM_v1_0 Journal reference of previous version: Comput. Phys. Comm. 157 (2004) 39 Does the new version supersede the previous version?: Yes Nature of problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast, semi-automatic way of comparing results from different programs is often desirable for the development of new programs, in order to check correctness of the installations or for discussion of uncertainties. Solution method: A typical HEP Monte Carlo program stores the generated events in event records such as HepMC, HEPEVT or PYJETS. MC-TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table. Reasons for new version: Interface for HepMC Event Record is introduced. Setup for benchmarking the interfaces, such as τ-lepton production and decay, including QED bremsstrahlung effects is introduced as well. This required significant changes in the algorithm. As a consequence, a new version of the code was introduced. Restrictions: Only the first 200 decay channels that were found will initialize histograms and if the multiplicity of decay products in a given channel was larger than 7, histograms will not be created for that channel. Additional comments: New features: HepMC interface, use of lists in definition of histograms and decay channels, filters for decay products or secondary decays to be omitted, bug fixing, extended flexibility in representation of program output, installation configuration scripts, merging multiple output files from separate generations. Running time: Varies substantially with the analyzed decay particle, but generally speed estimation of the old version remains valid. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100 000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; LATEX processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multiprocessor machines.

McStas-model of the delft SESANS

NASA Astrophysics Data System (ADS)

Knudsen, E.; Udby, L.; Willendrup, P. K.; Lefmann, K.; Bouwman, W. G.

2011-06-01

We present simulation results taking first virtual data from a model of the Spin-Echo Small Angle Scattering (SESANS) instrument situated in Delft, in the framework of the McStas Monte Carlo software package. The main focus has been on making a model of the Delft SESANS instrument, and we can now present the first virtual data from it, using a refracting prism-like sample model. In consequence, polarisation instrumentation is now included natively in the McStas kernel, including options for magnetic fields and a number of utility components. This development has brought us to a point where realistic models of polarisation-enabled instrumentation can be built.

Measurement and Monte Carlo simulation for energy- and intensity-modulated electron radiotherapy delivered by a computer-controlled electron multileaf collimator.

PubMed

Jin, Lihui; Eldib, Ahmed; Li, Jinsheng; Emam, Ismail; Fan, Jiajin; Wang, Lu; Ma, C-M

2014-01-06

The dosimetric advantage of modulated electron radiotherapy (MERT) has been explored by many investigators and is considered to be an advanced radiation therapy technique in the utilization of electrons. A computer-controlled electron multileaf collimator (MLC) prototype, newly designed to be added onto a Varian linac to deliver MERT, was investigated both experimentally and by Monte Carlo simulations. Four different electron energies, 6, 9, 12, and 15 MeV, were employed for this investigation. To ensure that this device was capable of delivering the electron beams properly, measurements were performed to examine the electron MLC (eMLC) leaf leakage and to determine the appropriate jaw positioning for an eMLC-shaped field in order to eliminate a secondary radiation peak that could otherwise appear outside of an intended radiation field in the case of inappropriate jaw positioning due to insufficient radiation blockage from the jaws. Phase space data were obtained by Monte Carlo (MC) simulation and recorded at the plane just above the jaws for each of the energies (6, 9, 12, and 15 MeV). As an input source, phase space data were used in MC dose calculations for various sizes of the eMLC shaped field (10 × 10 cm2, 3.4 × 3.4 cm2, and 2 × 2 cm2) with respect to a water phantom at source-to-surface distance (SSD) = 94 cm, while the jaws, eMLC leaves, and some accessories associated with the eMLC assembly as well were modeled as modifiers in the calculations. The calculated results were then compared with measurements from a water scanning system. The results showed that jaw settings with 5 mm margins beyond the field shaped by the eMLC were appropriate to eliminate the secondary radiation peak while not widening the beam penumbra; the eMLC leaf leakage measurements ranged from 0.3% to 1.8% for different energies based on in-phantom measurements, which should be quite acceptable for MERT. Comparisons between MC dose calculations and measurements showed agreement within 1%/1 mm based on percentage depth doses (PDDs) and off-axis dose profiles for a range of field sizes for each of the electron energies. Our current work has demonstrated that the eMLC and other relevant components in the linac were correctly modeled and simulated via our in-house MC codes, and the eMLC is capable of accurately delivering electron beams for various eMLC-shaped field sizes with appropriate jaw settings. In the next stage, patient-specific verification with a full MERT plan should be performed.

Measurement and Monte Carlo simulation for energy‐ and intensity‐modulated electron radiotherapy delivered by a computer‐controlled electron multileaf collimator

PubMed Central

Eldib, Ahmed; Li, Jinsheng; Emam, Ismail; Fan, Jiajin; Wang, Lu; Ma, C‐M

2014-01-01

The dosimetric advantage of modulated electron radiotherapy (MERT) has been explored by many investigators and is considered to be an advanced radiation therapy technique in the utilization of electrons. A computer‐controlled electron multileaf collimator (MLC) prototype, newly designed to be added onto a Varian linac to deliver MERT, was investigated both experimentally and by Monte Carlo simulations. Four different electron energies, 6, 9, 12, and 15 MeV, were employed for this investigation. To ensure that this device was capable of delivering the electron beams properly, measurements were performed to examine the electron MLC (eMLC) leaf leakage and to determine the appropriate jaw positioning for an eMLC‐shaped field in order to eliminate a secondary radiation peak that could otherwise appear outside of an intended radiation field in the case of inappropriate jaw positioning due to insufficient radiation blockage from the jaws. Phase space data were obtained by Monte Carlo (MC) simulation and recorded at the plane just above the jaws for each of the energies (6, 9, 12, and 15 MeV). As an input source, phase space data were used in MC dose calculations for various sizes of the eMLC shaped field (10×10 cm2, 3.4×3.4 cm2, and 2×2 cm2) with respect to a water phantom at source‐to‐surface distance (SSD)=94cm, while the jaws, eMLC leaves, and some accessories associated with the eMLC assembly as well were modeled as modifiers in the calculations. The calculated results were then compared with measurements from a water scanning system. The results showed that jaw settings with 5 mm margins beyond the field shaped by the eMLC were appropriate to eliminate the secondary radiation peak while not widening the beam penumbra; the eMLC leaf leakage measurements ranged from 0.3% to 1.8% for different energies based on in‐phantom measurements, which should be quite acceptable for MERT. Comparisons between MC dose calculations and measurements showed agreement within 1%/1mm based on percentage depth doses (PDDs) and off‐axis dose profiles for a range of field sizes for each of the electron energies. Our current work has demonstrated that the eMLC and other relevant components in the linac were correctly modeled and simulated via our in‐house MC codes, and the eMLC is capable of accurately delivering electron beams for various eMLC‐shaped field sizes with appropriate jaw settings. In the next stage, patient‐specific verification with a full MERT plan should be performed. PACS number: 87.55.ne PMID:24423848

Patient‐specific CT dosimetry calculation: a feasibility study

PubMed Central

Xie, Huchen; Cheng, Jason Y.; Ning, Holly; Zhuge, Ying; Miller, Robert W.

2011-01-01

Current estimation of radiation dose from computed tomography (CT) scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of “standard man”. Radiation dose to both adult and pediatric patients from a CT scan has been a concern, as noted in recent reports. The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient‐specific CT dosimetry. A radiation treatment planning system was modified to calculate patient‐specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose‐volumes (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. The RTPS calculation algorithm is based on a semi‐empirical, measured correction‐based algorithm, which has been well established in the radiotherapy community. Digital representations of the physical phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms (digital representation). Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The RTPS algorithm can be extended to calculate the organ dose by calculating a dose distribution point‐by‐point for a designated volume. Electron Gamma Shower (EGSnrc) codes for radiation transport calculations developed by National Research Council of Canada (NRCC) were utilized to perform the Monte Carlo (MC) simulation. In general, the RTPS and MC dose calculations are within 10% of the TLD measurements for the infant and child chest scans. With respect to the dose comparisons for the head, the RTPS dose calculations are slightly higher (10%–20%) than the TLD measurements, while the MC results were within 10% of the TLD measurements. The advantage of the algebraic dose calculation engine of the RTPS is a substantially reduced computation time (minutes vs. days) relative to Monte Carlo calculations, as well as providing patient‐specific dose estimation. It also provides the basis for a more elaborate reporting of dosimetric results, such as patient specific organ dose volumes after image segmentation. PACS numbers: 87.55.D‐, 87.57.Q‐, 87.53.Bn, 87.55.K‐ PMID:22089016

Competitive Adsorption and Ordered Packing of Counterions near Highly Charged Surfaces: From Mean-Field Theory to Monte Carlo Simulations

PubMed Central

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2013-01-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson’s equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both of the mean-field theory and MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling. PMID:22680474

Competitive adsorption and ordered packing of counterions near highly charged surfaces: From mean-field theory to Monte Carlo simulations.

PubMed

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2012-04-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect-included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson's equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both the mean-field theory and the MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling.

Efficient hybrid non-equilibrium molecular dynamics--Monte Carlo simulations with symmetric momentum reversal.

PubMed

Chen, Yunjie; Roux, Benoît

2014-09-21

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Efficient hybrid non-equilibrium molecular dynamics - Monte Carlo simulations with symmetric momentum reversal

NASA Astrophysics Data System (ADS)

Chen, Yunjie; Roux, Benoît

2014-09-01

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Mathematical modelling of scanner-specific bowtie filters for Monte Carlo CT dosimetry

NASA Astrophysics Data System (ADS)

Kramer, R.; Cassola, V. F.; Andrade, M. E. A.; de Araújo, M. W. C.; Brenner, D. J.; Khoury, H. J.

2017-02-01

The purpose of bowtie filters in CT scanners is to homogenize the x-ray intensity measured by the detectors in order to improve the image quality and at the same time to reduce the dose to the patient because of the preferential filtering near the periphery of the fan beam. For CT dosimetry, especially for Monte Carlo calculations of organ and tissue absorbed doses to patients, it is important to take the effect of bowtie filters into account. However, material composition and dimensions of these filters are proprietary. Consequently, a method for bowtie filter simulation independent of access to proprietary data and/or to a specific scanner would be of interest to many researchers involved in CT dosimetry. This study presents such a method based on the weighted computer tomography dose index, CTDIw, defined in two cylindrical PMMA phantoms of 16 cm and 32 cm diameter. With an EGSnrc-based Monte Carlo (MC) code, ratios CTDIw/CTDI100,a were calculated for a specific CT scanner using PMMA bowtie filter models based on sigmoid Boltzmann functions combined with a scanner filter factor (SFF) which is modified during calculations until the calculated MC CTDIw/CTDI100,a matches ratios CTDIw/CTDI100,a, determined by measurements or found in publications for that specific scanner. Once the scanner-specific value for an SFF has been found, the bowtie filter algorithm can be used in any MC code to perform CT dosimetry for that specific scanner. The bowtie filter model proposed here was validated for CTDIw/CTDI100,a considering 11 different CT scanners and for CTDI100,c, CTDI100,p and their ratio considering 4 different CT scanners. Additionally, comparisons were made for lateral dose profiles free in air and using computational anthropomorphic phantoms. CTDIw/CTDI100,a determined with this new method agreed on average within 0.89% (max. 3.4%) and 1.64% (max. 4.5%) with corresponding data published by CTDosimetry (www.impactscan.org) for the CTDI HEAD and BODY phantoms, respectively. Comparison with results calculated using proprietary data for the PHILIPS Brilliance 64 scanner showed agreement on average within 2.5% (max. 5.8%) and with data measured for that scanner within 2.1% (max. 3.7%). Ratios of CTDI100,c/CTDI100, p for this study and corresponding data published by CTDosimetry (www.impactscan.org) agree on average within about 11% (max. 28.6%). Lateral dose profiles calculated with the proposed bowtie filter and with proprietary data agreed within 2% (max. 5.9%), and both calculated data agreed within 5.4% (max. 11.2%) with measured results. Application of the proposed bowtie filter and of the exactly modelled filter to human phantom Monte Carlo calculations show agreement on the average within less than 5% (max. 7.9%) for organ and tissue absorbed doses.

Modified Monte Carlo method for study of electron transport in degenerate electron gas in the presence of electron-electron interactions, application to graphene

NASA Astrophysics Data System (ADS)

Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek

2017-07-01

Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron-electron (e-e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e-e interactions. This required adapting the treatment of e-e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.

Systematic discrepancies in Monte Carlo predictions of k-ratios emitted from thin films on substrates

NASA Astrophysics Data System (ADS)

Statham, P.; Llovet, X.; Duncumb, P.

2012-03-01

We have assessed the reliability of different Monte Carlo simulation programmes using the two available Bastin-Heijligers databases of thin-film measurements by EPMA. The MC simulation programmes tested include Curgenven-Duncumb MSMC, NISTMonte, Casino and PENELOPE. Plots of the ratio of calculated to measured k-ratios ("kcalc/kmeas") against various parameters reveal error trends that are not apparent in simple error histograms. The results indicate that the MC programmes perform quite differently on the same dataset. However, they appear to show a similar pronounced trend with a "hockey stick" shape in the "kcalc/kmeas versus kmeas" plots. The most sophisticated programme PENELOPE gives the closest correspondence with experiment but still shows a tendency to underestimate experimental k-ratios by 10 % for films that are thin compared to the electron range. We have investigated potential causes for this systematic behaviour and extended the study to data not collected by Bastin and Heijligers.

Kinetic Monte Carlo study of vinyl acetate synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100)

NASA Astrophysics Data System (ADS)

Huang, Yanping; Dong, Xiuqin; Yu, Yingzhe; Zhang, Minhua

2017-11-01

On the basis of the activation barriers and reaction energies from DFT calculations, kinetic Monte Carlo (kMC) simulations of vinyl acetate (VA) synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100) were carried out. Through kMC simulation, it was found that VA synthesis from ethylene acetoxylation proceeds via Moiseev mechanism on both Pd(100) and Pd/Au(100). The addition of Au into Pd can suppress ethylene dehydrogenation while it can promote acetic acid dehydrogenation, which can eventually facilitate VA synthesis as a whole. The addition of Au into Pd can further improve the conversion and selectivity of VA synthesis from ethylene acetoxylation. When the reaction network is analyzed, besides the energetics of each elementary reaction, the surface coverage of each species and the occupancy of the surface sites on the catalyst should also be taken into consideration.

Grid Block Design Based on Monte Carlo Simulated Dosimetry, the Linear Quadratic and Hug–Kellerer Radiobiological Models

PubMed Central

Gholami, Somayeh; Nedaie, Hassan Ali; Longo, Francesco; Ay, Mohammad Reza; Dini, Sharifeh A.; Meigooni, Ali S.

2017-01-01

Purpose: The clinical efficacy of Grid therapy has been examined by several investigators. In this project, the hole diameter and hole spacing in Grid blocks were examined to determine the optimum parameters that give a therapeutic advantage. Methods: The evaluations were performed using Monte Carlo (MC) simulation and commonly used radiobiological models. The Geant4 MC code was used to simulate the dose distributions for 25 different Grid blocks with different hole diameters and center-to-center spacing. The therapeutic parameters of these blocks, namely, the therapeutic ratio (TR) and geometrical sparing factor (GSF) were calculated using two different radiobiological models, including the linear quadratic and Hug–Kellerer models. In addition, the ratio of the open to blocked area (ROTBA) is also used as a geometrical parameter for each block design. Comparisons of the TR, GSF, and ROTBA for all of the blocks were used to derive the parameters for an optimum Grid block with the maximum TR, minimum GSF, and optimal ROTBA. A sample of the optimum Grid block was fabricated at our institution. Dosimetric characteristics of this Grid block were measured using an ionization chamber in water phantom, Gafchromic film, and thermoluminescent dosimeters in Solid Water™ phantom materials. Results: The results of these investigations indicated that Grid blocks with hole diameters between 1.00 and 1.25 cm and spacing of 1.7 or 1.8 cm have optimal therapeutic parameters (TR > 1.3 and GSF~0.90). The measured dosimetric characteristics of the optimum Grid blocks including dose profiles, percentage depth dose, dose output factor (cGy/MU), and valley-to-peak ratio were in good agreement (±5%) with the simulated data. Conclusion: In summary, using MC-based dosimetry, two radiobiological models, and previously published clinical data, we have introduced a method to design a Grid block with optimum therapeutic response. The simulated data were reproduced by experimental data. PMID:29296035

Canopy polarized BRDF simulation based on non-stationary Monte Carlo 3-D vector RT modeling

NASA Astrophysics Data System (ADS)

Kallel, Abdelaziz; Gastellu-Etchegorry, Jean Philippe

2017-03-01

Vector radiative transfer (VRT) has been largely used to simulate polarized reflectance of atmosphere and ocean. However it is still not properly used to describe vegetation cover polarized reflectance. In this study, we try to propose a 3-D VRT model based on a modified Monte Carlo (MC) forward ray tracing simulation to analyze vegetation canopy reflectance. Two kinds of leaf scattering are taken into account: (i) Lambertian diffuse reflectance and transmittance and (ii) specular reflection. A new method to estimate the condition on leaf orientation to produce reflection is proposed, and its probability to occur, Pl,max, is computed. It is then shown that Pl,max is low, but when reflection happens, the corresponding radiance Stokes vector, Io, is very high. Such a phenomenon dramatically increases the MC variance and yields to an irregular reflectance distribution function. For better regularization, we propose a non-stationary MC approach that simulates reflection for each sunny leaf assuming that its orientation is randomly chosen according to its angular distribution. It is shown in this case that the average canopy reflection is proportional to Pl,max ·Io which produces a smooth distribution. Two experiments are conducted: (i) assuming leaf light polarization is only due to the Fresnel reflection and (ii) the general polarization case. In the former experiment, our results confirm that in the forward direction, canopy polarizes horizontally light. In addition, they show that in inclined forward direction, diagonal polarization can be observed. In the latter experiment, polarization is produced in all orientations. It is particularly pointed out that specular polarization explains just a part of the forward polarization. Diffuse scattering polarizes light horizontally and vertically in forward and backward directions, respectively. Weak circular polarization signal is also observed near the backscattering direction. Finally, validation of the non-polarized reflectance using the ROMC tool is done, and our model shows good agreement with the ROMC reference.

Dose Reduction Study in Vaginal Balloon Packing Filled With Contrast for HDR Brachytherapy Treatment;HDR; Uterine cervix cancer; Vaginal balloon packing; Contrast; Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saini, Amarjit S.; Zhang, Geoffrey G., E-mail: geoffrey.zhang@moffitt.org; Finkelstein, Steven E.

2011-07-15

Purpose: Vaginal balloon packing is a means to displace organs at risk during high dose rate brachytherapy of the uterine cervix. We tested the hypothesis that contrast-filled vaginal balloon packing reduces radiation dose to organs at risk, such as the bladder and rectum, in comparison to water- or air-filled balloons. Methods and Materials: In a phantom study, semispherical vaginal packing balloons were filled with air, saline solution, and contrast agents. A high dose rate iridium-192 source was placed on the anterior surface of the balloon, and the diode detector was placed on the posterior surface. Dose ratios were taken withmore » each material in the balloon. Monte Carlo (MC) simulations, by use of the MC computer program DOSXYZnrc, were performed to study dose reduction vs. balloon size and contrast material, including commercially available iodine- and gadolinium-based contrast agents. Results: Measured dose ratios on the phantom with the balloon radius of 3.4 cm were 0.922 {+-} 0.002 for contrast/saline solution and 0.808 {+-} 0.001 for contrast/air. The corresponding ratios by MC simulations were 0.895 {+-} 0.010 and 0.781 {+-} 0.010. The iodine concentration in the contrast was 23.3% by weight. The dose reduction of contrast-filled balloon ranges from 6% to 15% compared with water-filled balloon and 11% to 26% compared with air-filled balloon, with a balloon size range between 1.4 and 3.8 cm, and iodine concentration in contrast of 24.9%. The dose reduction was proportional to the contrast agent concentration. The gadolinium-based contrast agents showed less dose reduction because of much lower concentrations in their solutions. Conclusions: The dose to the posterior wall of the bladder and the anterior wall of the rectum can be reduced if the vaginal balloon is filled with contrast agent in comparison to vaginal balloons filled with saline solution or air.« less

Self-Consistent Monte Carlo Study of the Coulomb Interaction under Nano-Scale Device Structures

NASA Astrophysics Data System (ADS)

Sano, Nobuyuki

2011-03-01

It has been pointed that the Coulomb interaction between the electrons is expected to be of crucial importance to predict reliable device characteristics. In particular, the device performance is greatly degraded due to the plasmon excitation represented by dynamical potential fluctuations in high-doped source and drain regions by the channel electrons. We employ the self-consistent 3D Monte Carlo (MC) simulations, which could reproduce both the correct mobility under various electron concentrations and the collective plasma waves, to study the physical impact of dynamical potential fluctuations on device performance under the Double-gate MOSFETs. The average force experienced by an electron due to the Coulomb interaction inside the device is evaluated by performing the self-consistent MC simulations and the fixed-potential MC simulations without the Coulomb interaction. Also, the band-tailing associated with the local potential fluctuations in high-doped source region is quantitatively evaluated and it is found that the band-tailing becomes strongly dependent of position in real space even inside the uniform source region. This work was partially supported by Grants-in-Aid for Scientific Research B (No. 2160160) from the Ministry of Education, Culture, Sports, Science and Technology in Japan.

Paracousti-UQ: A Stochastic 3-D Acoustic Wave Propagation Algorithm.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preston, Leiph

Acoustic full waveform algorithms, such as Paracousti, provide deterministic solutions in complex, 3-D variable environments. In reality, environmental and source characteristics are often only known in a statistical sense. Thus, to fully characterize the expected sound levels within an environment, this uncertainty in environmental and source factors should be incorporated into the acoustic simulations. Performing Monte Carlo (MC) simulations is one method of assessing this uncertainty, but it can quickly become computationally intractable for realistic problems. An alternative method, using the technique of stochastic partial differential equations (SPDE), allows computation of the statistical properties of output signals at a fractionmore » of the computational cost of MC. Paracousti-UQ solves the SPDE system of 3-D acoustic wave propagation equations and provides estimates of the uncertainty of the output simulated wave field (e.g., amplitudes, waveforms) based on estimated probability distributions of the input medium and source parameters. This report describes the derivation of the stochastic partial differential equations, their implementation, and comparison of Paracousti-UQ results with MC simulations using simple models.« less

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE PAGES

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk; ...

2017-11-07

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

General Monte Carlo reliability simulation code including common mode failures and HARP fault/error-handling

NASA Technical Reports Server (NTRS)

Platt, M. E.; Lewis, E. E.; Boehm, F.

1991-01-01

A Monte Carlo Fortran computer program was developed that uses two variance reduction techniques for computing system reliability applicable to solving very large highly reliable fault-tolerant systems. The program is consistent with the hybrid automated reliability predictor (HARP) code which employs behavioral decomposition and complex fault-error handling models. This new capability is called MC-HARP which efficiently solves reliability models with non-constant failures rates (Weibull). Common mode failure modeling is also a specialty.

Probability of misclassifying biological elements in surface waters.

PubMed

Loga, Małgorzata; Wierzchołowska-Dziedzic, Anna

2017-11-24

Measurement uncertainties are inherent to assessment of biological indices of water bodies. The effect of these uncertainties on the probability of misclassification of ecological status is the subject of this paper. Four Monte-Carlo (M-C) models were applied to simulate the occurrence of random errors in the measurements of metrics corresponding to four biological elements of surface waters: macrophytes, phytoplankton, phytobenthos, and benthic macroinvertebrates. Long series of error-prone measurement values of these metrics, generated by M-C models, were used to identify cases in which values of any of the four biological indices lay outside of the "true" water body class, i.e., outside the class assigned from the actual physical measurements. Fraction of such cases in the M-C generated series was used to estimate the probability of misclassification. The method is particularly useful for estimating the probability of misclassification of the ecological status of surface water bodies in the case of short sequences of measurements of biological indices. The results of the Monte-Carlo simulations show a relatively high sensitivity of this probability to measurement errors of the river macrophyte index (MIR) and high robustness to measurement errors of the benthic macroinvertebrate index (MMI). The proposed method of using Monte-Carlo models to estimate the probability of misclassification has significant potential for assessing the uncertainty of water body status reported to the EC by the EU member countries according to WFD. The method can be readily applied also in risk assessment of water management decisions before adopting the status dependent corrective actions.

Validation of a commercial TPS based on the VMC(++) Monte Carlo code for electron beams: commissioning and dosimetric comparison with EGSnrc in homogeneous and heterogeneous phantoms.

PubMed

Ferretti, A; Martignano, A; Simonato, F; Paiusco, M

2014-02-01

The aim of the present work was the validation of the VMC(++) Monte Carlo (MC) engine implemented in the Oncentra Masterplan (OMTPS) and used to calculate the dose distribution produced by the electron beams (energy 5-12 MeV) generated by the linear accelerator (linac) Primus (Siemens), shaped by a digital variable applicator (DEVA). The BEAMnrc/DOSXYZnrc (EGSnrc package) MC model of the linac head was used as a benchmark. Commissioning results for both MC codes were evaluated by means of 1D Gamma Analysis (2%, 2 mm), calculated with a home-made Matlab (The MathWorks) program, comparing the calculations with the measured profiles. The results of the commissioning of OMTPS were good [average gamma index (γ) > 97%]; some mismatches were found with large beams (size ≥ 15 cm). The optimization of the BEAMnrc model required to increase the beam exit window to match the calculated and measured profiles (final average γ > 98%). Then OMTPS dose distribution maps were compared with DOSXYZnrc with a 2D Gamma Analysis (3%, 3 mm), in 3 virtual water phantoms: (a) with an air step, (b) with an air insert, and (c) with a bone insert. The OMTPD and EGSnrc dose distributions with the air-water step phantom were in very high agreement (γ ∼ 99%), while for heterogeneous phantoms there were differences of about 9% in the air insert and of about 10-15% in the bone region. This is due to the Masterplan implementation of VMC(++) which reports the dose as "dose to water", instead of "dose to medium". Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Monte Carlo simulation tool for online treatment monitoring in hadrontherapy with in-beam PET: A patient study.

PubMed

Fiorina, E; Ferrero, V; Pennazio, F; Baroni, G; Battistoni, G; Belcari, N; Cerello, P; Camarlinghi, N; Ciocca, M; Del Guerra, A; Donetti, M; Ferrari, A; Giordanengo, S; Giraudo, G; Mairani, A; Morrocchi, M; Peroni, C; Rivetti, A; Da Rocha Rolo, M D; Rossi, S; Rosso, V; Sala, P; Sportelli, G; Tampellini, S; Valvo, F; Wheadon, R; Bisogni, M G

2018-05-07

Hadrontherapy is a method for treating cancer with very targeted dose distributions and enhanced radiobiological effects. To fully exploit these advantages, in vivo range monitoring systems are required. These devices measure, preferably during the treatment, the secondary radiation generated by the beam-tissue interactions. However, since correlation of the secondary radiation distribution with the dose is not straightforward, Monte Carlo (MC) simulations are very important for treatment quality assessment. The INSIDE project constructed an in-beam PET scanner to detect signals generated by the positron-emitting isotopes resulting from projectile-target fragmentation. In addition, a FLUKA-based simulation tool was developed to predict the corresponding reference PET images using a detailed scanner model. The INSIDE in-beam PET was used to monitor two consecutive proton treatment sessions on a patient at the Italian Center for Oncological Hadrontherapy (CNAO). The reconstructed PET images were updated every 10 s providing a near real-time quality assessment. By half-way through the treatment, the statistics of the measured PET images were already significant enough to be compared with the simulations with average differences in the activity range less than 2.5 mm along the beam direction. Without taking into account any preferential direction, differences within 1 mm were found. In this paper, the INSIDE MC simulation tool is described and the results of the first in vivo agreement evaluation are reported. These results have justified a clinical trial, in which the MC simulation tool will be used on a daily basis to study the compliance tolerances between the measured and simulated PET images. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations

NASA Astrophysics Data System (ADS)

Sempau, Josep; Wilderman, Scott J.; Bielajew, Alex F.

2000-08-01

A new Monte Carlo (MC) algorithm, the `dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high-accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 1283 voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a `mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The δ-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, M; Lee, V; Leung, R

Purpose: Investigating the relative sensitivity of Monte Carlo (MC) and Pencil Beam (PB) dose calculation algorithms to low-Z (titanium) metallic artifacts is important for accurate and consistent dose reporting in post¬operative spinal RS. Methods: Sensitivity analysis of MC and PB dose calculation algorithms on the Monaco v.3.3 treatment planning system (Elekta CMS, Maryland Heights, MO, USA) was performed using CT images reconstructed without (plain) and with Orthopedic Metal Artifact Reduction (OMAR; Philips Healthcare system, Cleveland, OH, USA). 6MV and 10MV volumetric-modulated arc (VMAT) RS plans were obtained for MC and PB on the plain and OMAR images (MC-plain/OMAR and PB-plain/OMAR).more » Results: Maximum differences in dose to 0.2cc (D0.2cc) of spinal cord and cord +2mm for 6MV and 10MV VMAT plans were 0.1Gy between MC-OMAR and MC-plain, and between PB-OMAR and PB-plain. Planning target volume (PTV) dose coverage changed by 0.1±0.7% and 0.2±0.3% for 6MV and 10MV from MC-OMAR to MC-plain, and by 0.1±0.1% for both 6MV and 10 MV from PB-OMAR to PB-plain, respectively. In no case for both MC and PB the D0.2cc to spinal cord was found to exceed the planned tolerance changing from OMAR to plain CT in dose calculations. Conclusion: Dosimetric impacts of metallic artifacts caused by low-Z metallic spinal hardware (mainly titanium alloy) are not clinically important in VMAT-based spine RS, without significant dependence on dose calculation methods (MC and PB) and photon energy ≥ 6MV. There is no need to use one algorithm instead of the other to reduce uncertainty for dose reporting. The dose calculation method that should be used in spine RS shall be consistent with the usual clinical practice.« less

Analytical, experimental, and Monte Carlo system response matrix for pinhole SPECT reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es; Pino, Francisco; Silva-Rodríguez, Jesús

2014-03-15

Purpose: To assess the performance of two approaches to the system response matrix (SRM) calculation in pinhole single photon emission computed tomography (SPECT) reconstruction. Methods: Evaluation was performed using experimental data from a low magnification pinhole SPECT system that consisted of a rotating flat detector with a monolithic scintillator crystal. The SRM was computed following two approaches, which were based on Monte Carlo simulations (MC-SRM) and analytical techniques in combination with an experimental characterization (AE-SRM). The spatial response of the system, obtained by using the two approaches, was compared with experimental data. The effect of the MC-SRM and AE-SRM approachesmore » on the reconstructed image was assessed in terms of image contrast, signal-to-noise ratio, image quality, and spatial resolution. To this end, acquisitions were carried out using a hot cylinder phantom (consisting of five fillable rods with diameters of 5, 4, 3, 2, and 1 mm and a uniform cylindrical chamber) and a custom-made Derenzo phantom, with center-to-center distances between adjacent rods of 1.5, 2.0, and 3.0 mm. Results: Good agreement was found for the spatial response of the system between measured data and results derived from MC-SRM and AE-SRM. Only minor differences for point sources at distances smaller than the radius of rotation and large incidence angles were found. Assessment of the effect on the reconstructed image showed a similar contrast for both approaches, with values higher than 0.9 for rod diameters greater than 1 mm and higher than 0.8 for rod diameter of 1 mm. The comparison in terms of image quality showed that all rods in the different sections of a custom-made Derenzo phantom could be distinguished. The spatial resolution (FWHM) was 0.7 mm at iteration 100 using both approaches. The SNR was lower for reconstructed images using MC-SRM than for those reconstructed using AE-SRM, indicating that AE-SRM deals better with the projection noise than MC-SRM. Conclusions: The authors' findings show that both approaches provide good solutions to the problem of calculating the SRM in pinhole SPECT reconstruction. The AE-SRM was faster to create and handle the projection noise better than MC-SRM. Nevertheless, the AE-SRM required a tedious experimental characterization of the intrinsic detector response. Creation of the MC-SRM required longer computation time and handled the projection noise worse than the AE-SRM. Nevertheless, the MC-SRM inherently incorporates extensive modeling of the system and therefore experimental characterization was not required.« less

Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations

NASA Astrophysics Data System (ADS)

Saini, Jatinder; Maes, Dominic; Egan, Alexander; Bowen, Stephen R.; St. James, Sara; Janson, Martin; Wong, Tony; Bloch, Charles

2017-10-01

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and  >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations.

PubMed

Saini, Jatinder; Maes, Dominic; Egan, Alexander; Bowen, Stephen R; St James, Sara; Janson, Martin; Wong, Tony; Bloch, Charles

2017-09-12

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and  >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

NMR diffusion simulation based on conditional random walk.

PubMed

Gudbjartsson, H; Patz, S

1995-01-01

The authors introduce here a new, very fast, simulation method for free diffusion in a linear magnetic field gradient, which is an extension of the conventional Monte Carlo (MC) method or the convolution method described by Wong et al. (in 12th SMRM, New York, 1993, p.10). In earlier NMR-diffusion simulation methods, such as the finite difference method (FD), the Monte Carlo method, and the deterministic convolution method, the outcome of the calculations depends on the simulation time step. In the authors' method, however, the results are independent of the time step, although, in the convolution method the step size has to be adequate for spins to diffuse to adjacent grid points. By always selecting the largest possible time step the computation time can therefore be reduced. Finally the authors point out that in simple geometric configurations their simulation algorithm can be used to reduce computation time in the simulation of restricted diffusion.

Monte Carlo modelling of Schottky diode for rectenna simulation

NASA Astrophysics Data System (ADS)

Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.

2017-09-01

Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.

GPU Accelerated DG-FDF Large Eddy Simulator

NASA Astrophysics Data System (ADS)

Inkarbekov, Medet; Aitzhan, Aidyn; Sammak, Shervin; Givi, Peyman; Kaltayev, Aidarkhan

2017-11-01

A GPU accelerated simulator is developed and implemented for large eddy simulation (LES) of turbulent flows. The filtered density function (FDF) is utilized for modeling of the subgrid scale quantities. The filtered transport equations are solved via a discontinuous Galerkin (DG) and the FDF is simulated via particle based Lagrangian Monte-Carlo (MC) method. It is demonstrated that the GPUs simulations are of the order of 100 times faster than the CPU-based calculations. This brings LES of turbulent flows to a new level, facilitating efficient simulation of more complex problems. The work at Al-Faraby Kazakh National University is sponsored by MoES of RK under Grant 3298/GF-4.

Simulating Silicon Photomultiplier Response to Scintillation Light

PubMed Central

Jha, Abhinav K.; van Dam, Herman T.; Kupinski, Matthew A.; Clarkson, Eric

2015-01-01

The response of a Silicon Photomultiplier (SiPM) to optical signals is affected by many factors including photon-detection efficiency, recovery time, gain, optical crosstalk, afterpulsing, dark count, and detector dead time. Many of these parameters vary with overvoltage and temperature. When used to detect scintillation light, there is a complicated non-linear relationship between the incident light and the response of the SiPM. In this paper, we propose a combined discrete-time discrete-event Monte Carlo (MC) model to simulate SiPM response to scintillation light pulses. Our MC model accounts for all relevant aspects of the SiPM response, some of which were not accounted for in the previous models. We also derive and validate analytic expressions for the single-photoelectron response of the SiPM and the voltage drop across the quenching resistance in the SiPM microcell. These analytic expressions consider the effect of all the circuit elements in the SiPM and accurately simulate the time-variation in overvoltage across the microcells of the SiPM. Consequently, our MC model is able to incorporate the variation of the different SiPM parameters with varying overvoltage. The MC model is compared with measurements on SiPM-based scintillation detectors and with some cases for which the response is known a priori. The model is also used to study the variation in SiPM behavior with SiPM-circuit parameter variations and to predict the response of a SiPM-based detector to various scintillators. PMID:26236040

The accuracy of the out-of-field dose calculations using a model based algorithm in a commercial treatment planning system

NASA Astrophysics Data System (ADS)

Wang, Lilie; Ding, George X.

2014-07-01

The out-of-field dose can be clinically important as it relates to the dose of the organ-at-risk, although the accuracy of its calculation in commercial radiotherapy treatment planning systems (TPSs) receives less attention. This study evaluates the uncertainties of out-of-field dose calculated with a model based dose calculation algorithm, anisotropic analytical algorithm (AAA), implemented in a commercial radiotherapy TPS, Varian Eclipse V10, by using Monte Carlo (MC) simulations, in which the entire accelerator head is modeled including the multi-leaf collimators. The MC calculated out-of-field doses were validated by experimental measurements. The dose calculations were performed in a water phantom as well as CT based patient geometries and both static and highly modulated intensity-modulated radiation therapy (IMRT) fields were evaluated. We compared the calculated out-of-field doses, defined as lower than 5% of the prescription dose, in four H&N cancer patients and two lung cancer patients treated with volumetric modulated arc therapy (VMAT) and IMRT techniques. The results show that the discrepancy of calculated out-of-field dose profiles between AAA and the MC depends on the depth and is generally less than 1% for in water phantom comparisons and in CT based patient dose calculations for static field and IMRT. In cases of VMAT plans, the difference between AAA and MC is <0.5%. The clinical impact resulting from the error on the calculated organ doses were analyzed by using dose-volume histograms. Although the AAA algorithm significantly underestimated the out-of-field doses, the clinical impact on the calculated organ doses in out-of-field regions may not be significant in practice due to very low out-of-field doses relative to the target dose.

Development and application of CATIA-GDML geometry builder

NASA Astrophysics Data System (ADS)

Belogurov, S.; Berchun, Yu; Chernogorov, A.; Malzacher, P.; Ovcharenko, E.; Schetinin, V.

2014-06-01

Due to conceptual difference between geometry descriptions in Computer-Aided Design (CAD) systems and particle transport Monte Carlo (MC) codes direct conversion of detector geometry in either direction is not feasible. The paper presents an update on functionality and application practice of the CATIA-GDML geometry builder first introduced at CHEP2010. This set of CATIAv5 tools has been developed for building a MC optimized GEANT4/ROOT compatible geometry based on the existing CAD model. The model can be exported via Geometry Description Markup Language (GDML). The builder allows also import and visualization of GEANT4/ROOT geometries in CATIA. The structure of a GDML file, including replicated volumes, volume assemblies and variables, is mapped into a part specification tree. A dedicated file template, a wide range of primitives, tools for measurement and implicit calculation of parameters, different types of multiple volume instantiation, mirroring, positioning and quality check have been implemented. Several use cases are discussed.

MO-G-17A-06: Kernel Based Dosimetry for 90Y Microsphere Liver Therapy Using 90Y Bremsstrahlung SPECT/CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mikell, J; Siman, W; Kappadath, S

2014-06-15

Purpose: 90Y microsphere therapy in liver presents a situation where beta transport is dominant and the tissue is relatively homogenous. We compare voxel-based absorbed doses from a 90Y kernel to Monte Carlo (MC) using quantitative 90Y bremsstrahlung SPECT/CT as source distribution. Methods: Liver, normal liver, and tumors were delineated by an interventional radiologist using contrast-enhanced CT registered with 90Y SPECT/CT scans for 14 therapies. Right lung was segmented via region growing. The kernel was generated with 1.04 g/cc soft tissue for 4.8 mm voxel matching the SPECT. MC simulation materials included air, lung, soft tissue, and bone with varying densities.more » We report percent difference between kernel and MC (%Δ(K,MC)) for mean absorbed dose, D70, and V20Gy in total liver, normal liver, tumors, and right lung. We also report %Δ(K,MC) for heterogeneity metrics: coefficient of variation (COV) and D10/D90. The impact of spatial resolution (0, 10, 20 mm FWHM) and lung shunt fraction (LSF) (1,5,10,20%) on the accuracy of MC and kernel doses near the liver-lung interface was modeled in 1D. We report the distance from the interface where errors become <10% of unblurred MC as d10(side of interface, dose calculation, FWHM blurring, LSF). Results: The %Δ(K,MC) for mean, D70, and V20Gy in tumor and liver was <7% while right lung differences varied from 60–90%. The %Δ(K,MC) for COV was <4.8% for tumor and liver and <54% for the right lung. The %Δ(K,MC) for D10/D90 was <5% for 22/23 tumors. d10(liver,MC,10,1–20) awere <9mm and d10(liver,MC,20,1–20) awere <15mm; both agreed within 3mm to the kernel. d10(lung,MC,10,20), d10(lung,MC,10,1), d10(lung,MC,20,20), and d10(lung,MC,20,1) awere 6, 25, 15, and 34mm, respectively. Kernel calculations on blurred distributions in lung had errors > 10%. Conclusions: Liver and tumor voxel doses with 90Y kernel and MC agree within 7%. Large differences exist between the two methods in right lung. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA138986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

Study of extracerebral contamination for three cerebral oximeters by Monte Carlo simulation using CT data

NASA Astrophysics Data System (ADS)

Tarasov, A. P.; Egorov, A. I.; Rogatkin, D. A.

2017-07-01

Using multidetector computed tomography, thicknesses of bone squame and soft tissues of human head were assessed. MC simulation revealed impropriety of source-detector separation distances for 3 oximeters, which can cause extracerebral contamination.

First observations of separated atmospheric νμ and ν¯μ events in the MINOS detector

NASA Astrophysics Data System (ADS)

Adamson, P.; Alexopoulos, T.; Allison, W. W. M.; Alner, G. J.; Anderson, K.; Andreopoulos, C.; Andrews, M.; Andrews, R.; Arroyo, C.; Avvakumov, S.; Ayres, D. S.; Baller, B.; Barish, B.; Barker, M. A.; Barnes, P. D., Jr.; Barr, G.; Barrett, W. L.; Beall, E.; Becker, B. R.; Belias, A.; Bergfeld, T.; Bernstein, R. H.; Bhattacharya, D.; Bishai, M.; Blake, A.; Bocean, V.; Bock, B.; Bock, G. J.; Boehm, J.; Boehnlein, D. J.; Bogert, D.; Border, P. M.; Bower, C.; Boyd, S.; Buckley-Geer, E.; Byon-Wagner, A.; Cabrera, A.; Chapman, J. D.; Chase, T. R.; Chernichenko, S. K.; Childress, S.; Choudhary, B. C.; Cobb, J. H.; Cossairt, J. D.; Courant, H.; Crane, D. A.; Culling, A. J.; Dawson, J. W.; Demuth, D. M.; de Santo, A.; Dierckxsens, M.; Diwan, M. V.; Dorman, M.; Drake, G.; Ducar, R.; Durkin, T.; Erwin, A. R.; Escobar, C. O.; Evans, J.; Fackler, O. D.; Harris, E. Falk; Feldman, G. J.; Felt, N.; Fields, T. H.; Ford, R.; Frohne, M. V.; Gallagher, H. R.; Gebhard, M.; Godley, A.; Gogos, J.; Goodman, M. C.; Gornushkin, Yu.; Gouffon, P.; Grashorn, E.; Grossman, N.; Grudzinski, J. J.; Grzelak, K.; Guarino, V.; Habig, A.; Halsall, R.; Hanson, J.; Harris, D.; Harris, P. G.; Hartnell, J.; Hartouni, E. P.; Hatcher, R.; Heller, K.; Hill, N.; Ho, Y.; Howcroft, C.; Hylen, J.; Ignatenko, M.; Indurthy, D.; Irwin, G. M.; James, C.; Jenner, L.; Jensen, D.; Joffe-Minor, T.; Kafka, T.; Kang, H. J.; Kasahara, S. M. S.; Kilmer, J.; Kim, H.; Koizumi, G.; Kopp, S.; Kordosky, M.; Koskinen, D. J.; Kostin, M.; Krakauer, D. A.; Kumaratunga, S.; Ladran, A. S.; Lang, K.; Laughton, C.; Lebedev, A.; Lee, R.; Lee, W. Y.; Libkind, M. A.; Liu, J.; Litchfield, P. J.; Litchfield, R. P.; Longley, N. P.; Lucas, P.; Luebke, W.; Madani, S.; Maher, E.; Makeev, V.; Mann, W. A.; Marchionni, A.; Marino, A. D.; Marshak, M. L.; Marshall, J. S.; McDonald, J.; McGowan, A.; Meier, J. R.; Merzon, G. I.; Messier, M. D.; Michael, D. G.; Milburn, R. H.; Miller, J. L.; Miller, W. H.; Mishra, S. R.; Miyagawa, P. S.; Moore, C.; Morfín, J.; Morse, R.; Mualem, L.; Mufson, S.; Murgia, S.; Murtagh, M. J.; Musser, J.; Naples, D.; Nelson, C.; Nelson, J. K.; Newman, H. B.; Nezrick, F.; Nichol, R. J.; Nicholls, T. C.; Ochoa-Ricoux, J. P.; Oliver, J.; Oliver, W. P.; Onuchin, V. A.; Osiecki, T.; Ospanov, R.; Paley, J.; Paolone, V.; Para, A.; Patzak, T.; Pavlovich, Z.; Pearce, G. F.; Pearson, N.; Peck, C. W.; Perry, C.; Peterson, E. A.; Petyt, D. A.; Ping, H.; Piteira, R.; Pla-Dalmau, A.; Plunkett, R. K.; Price, L. E.; Proga, M.; Pushka, D. R.; Rahman, D.; Rameika, R. A.; Raufer, T. M.; Read, A. L.; Rebel, B.; Reyna, D. E.; Rosenfeld, C.; Rubin, H. A.; Ruddick, K.; Ryabov, V. A.; Saakyan, R.; Sanchez, M. C.; Saoulidou, N.; Schneps, J.; Schoessow, P. V.; Schreiner, P.; Schwienhorst, R.; Semenov, V. K.; Seun, S.-M.; Shanahan, P.; Shield, P. D.; Smart, W.; Smirnitsky, V.; Smith, C.; Smith, P. N.; Sousa, A.; Speakman, B.; Stamoulis, P.; Stefanik, A.; Sullivan, P.; Swan, J. M.; Symes, P. A.; Tagg, N.; Talaga, R. L.; Tetteh-Lartey, E.; Thomas, J.; Thompson, J.; Thomson, M. A.; Thron, J. L.; Trendler, R.; Trevor, J.; Trostin, I.; Tsarev, V. A.; Tzanakos, G.; Urheim, J.; Vahle, P.; Vakili, M.; Vaziri, K.; Velissaris, C.; Verebryusov, V.; Viren, B.; Wai, L.; Ward, C. P.; Ward, D. R.; Watabe, M.; Weber, A.; Webb, R. C.; Wehmann, A.; West, N.; White, C.; White, R. F.; Wojcicki, S. G.; Wright, D. M.; Wu, Q. K.; Yan, W. G.; Yang, T.; Yumiceva, F. X.; Yun, J. C.; Zheng, H.; Zois, M.; Zwaska, R.

2006-04-01

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of νμ and ν¯μ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field νμ and ν¯μ interactions are separated. The ratio of ν¯μ to νμ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving Rν¯μ/νμdata/Rν¯μ/νμMC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for νμ and ν¯μ.

MO-FG-202-08: Real-Time Monte Carlo-Based Treatment Dose Reconstruction and Monitoring for Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Z; Shi, F; Gu, X

2016-06-15

Purpose: This proof-of-concept study is to develop a real-time Monte Carlo (MC) based treatment-dose reconstruction and monitoring system for radiotherapy, especially for the treatments with complicated delivery, to catch treatment delivery errors at the earliest possible opportunity and interrupt the treatment only when an unacceptable dosimetric deviation from our expectation occurs. Methods: First an offline scheme is launched to pre-calculate the expected dose from the treatment plan, used as ground truth for real-time monitoring later. Then an online scheme with three concurrent threads is launched while treatment delivering, to reconstruct and monitor the patient dose in a temporally resolved fashionmore » in real-time. Thread T1 acquires machine status every 20 ms to calculate and accumulate fluence map (FM). Once our accumulation threshold is reached, T1 transfers the FM to T2 for dose reconstruction ad starts to accumulate a new FM. A GPU-based MC dose calculation is performed on T2 when MC dose engine is ready and a new FM is available. The reconstructed instantaneous dose is directed to T3 for dose accumulation and real-time visualization. Multiple dose metrics (e.g. maximum and mean dose for targets and organs) are calculated from the current accumulated dose and compared with the pre-calculated expected values. Once the discrepancies go beyond our tolerance, an error message will be send to interrupt the treatment delivery. Results: A VMAT Head-and-neck patient case was used to test the performance of our system. Real-time machine status acquisition was simulated here. The differences between the actual dose metrics and the expected ones were 0.06%–0.36%, indicating an accurate delivery. ∼10Hz frequency of dose reconstruction and monitoring was achieved, with 287.94s online computation time compared to 287.84s treatment delivery time. Conclusion: Our study has demonstrated the feasibility of computing a dose distribution in a temporally resolved fashion in real-time and quantitatively and dosimetrically monitoring the treatment delivery.« less

Proton and helium ion radiotherapy for meningioma tumors: a Monte Carlo-based treatment planning comparison.

PubMed

Tessonnier, Thomas; Mairani, Andrea; Chen, Wenjing; Sala, Paola; Cerutti, Francesco; Ferrari, Alfredo; Haberer, Thomas; Debus, Jürgen; Parodi, Katia

2018-01-09

Due to their favorable physical and biological properties, helium ion beams are increasingly considered a promising alternative to proton beams for radiation therapy. Hence, this work aims at comparing in-silico the treatment of brain and ocular meningiomas with protons and helium ions, using for the first time a dedicated Monte Carlo (MC) based treatment planning engine (MCTP) thoroughly validated both in terms of physical and biological models. Starting from clinical treatment plans of four patients undergoing proton therapy with a fixed relative biological effectiveness (RBE) of 1.1 and a fraction dose of 1.8 Gy(RBE), new treatment plans were optimized with MCTP for both protons (with variable and fixed RBE) and helium ions (with variable RBE) under the same constraints derived from the initial clinical plans. The resulting dose distributions were dosimetrically compared in terms of dose volume histograms (DVH) parameters for the planning target volume (PTV) and the organs at risk (OARs), as well as dose difference maps. In most of the cases helium ion plans provided a similar PTV coverage as protons with a consistent trend of superior OAR sparing. The latter finding was attributed to the ability of helium ions to offer sharper distal and lateral dose fall-offs, as well as a more favorable differential RBE variation in target and normal tissue. Although more studies are needed to investigate the clinical potential of helium ions for different tumour entities, the results of this work based on an experimentally validated MC engine support the promise of this modality with state-of-the-art pencil beam scanning delivery, especially in case of tumours growing in close proximity of multiple OARs such as meningiomas.

MC EMiNEM Maps the Interaction Landscape of the Mediator

PubMed Central

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C.; Martin, Dietmar E.; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors. PMID:22737066

Coarse-grained stochastic processes and kinetic Monte Carlo simulators for the diffusion of interacting particles

NASA Astrophysics Data System (ADS)

Katsoulakis, Markos A.; Vlachos, Dionisios G.

2003-11-01

We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.

Multileaf collimator tongue-and-groove effect on depth and off-axis doses: A comparison of treatment planning data with measurements and Monte Carlo calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Hee Jung; Department of Biomedical Engineering, Seoul National University, Seoul; Department of Radiation Oncology, Soonchunhyang University Hospital, Seoul

2015-01-01

To investigate how accurately treatment planning systems (TPSs) account for the tongue-and-groove (TG) effect, Monte Carlo (MC) simulations and radiochromic film (RCF) measurements were performed for comparison with TPS results. Two commercial TPSs computed the TG effect for Varian Millennium 120 multileaf collimator (MLC). The TG effect on off-axis dose profile at 3 depths of solid water was estimated as the maximum depth and the full width at half maximum (FWHM) of the dose dip at an interleaf position. When compared with the off-axis dose of open field, the maximum depth of the dose dip for MC and RCF rangedmore » from 10.1% to 20.6%; the maximum depth of the dose dip gradually decreased by up to 8.7% with increasing depths of 1.5 to 10 cm and also by up to 4.1% with increasing off-axis distances of 0 to 13 cm. However, TPS results showed at most a 2.7% decrease for the same depth range and a negligible variation for the same off-axis distances. The FWHM of the dose dip was approximately 0.19 cm for MC and 0.17 cm for RCF, but 0.30 cm for Eclipse TPS and 0.45 cm for Pinnacle TPS. Accordingly, the integrated value of TG dose dip for TPS was larger than that for MC and RCF and almost invariant along the depths and off-axis distances. We concluded that the TG dependence on depth and off-axis doses shown in the MC and RCF results could not be appropriately modeled by the TPS versions in this study.« less

An improved Monte-Carlo model of the Varian EPID separating support arm and rear-housing backscatter

NASA Astrophysics Data System (ADS)

Monville, M. E.; Kuncic, Z.; Greer, P. B.

2014-03-01

Previous investigators of EPID dosimetric properties have ascribed the backscatter, that contaminates dosimetric EPID images, to its supporting arm. Accordingly, Monte-Carlo (MC) EPID models have approximated the backscatter signal from the layers under the detector and the robotic support arm using either uniform or non-uniform solid water slabs, or through convolutions with back-scatter kernels. The aim of this work is to improve the existent MC models by measuring and modelling the separate backscatter contributions of the robotic arm and the rear plastic housing of the EPID. The EPID plastic housing is non-uniform with a 11.9 cm wide indented section that runs across the cross-plane direction in the superior half of the EPID which is 1.75 cm closer to the EPID sensitive layer than the rest of the housing. The thickness of the plastic housing is 0.5 cm. Experiments were performed with and without the housing present by removing all components of the EPID from the housing. The robotic support arm was not present for these measurements. A MC model of the linear accelerator and the EPID was modified to include the rear-housing indentation and results compared to the measurement. The rear housing was found to contribute a maximum of 3% additional signal. The rear housing contribution to the image is non-uniform in the in-plane direction with 2% asymmetry across the central 20 cm of an image irradiating the entire detector. The MC model was able to reproduce this non-uniform contribution. The EPID rear housing contributes a non-uniform backscatter component to the EPID image, which has not been previously characterized. This has been incorporated into an improved MC model of the EPID.

A Study of Neutron Leakage in Finite Objects

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

A computationally efficient 3DHZETRN code capable of simulating High charge (Z) and Energy (HZE) and light ions (including neutrons) under space-like boundary conditions with enhanced neutron and light ion propagation was recently developed for simple shielded objects. Monte Carlo (MC) benchmarks were used to verify the 3DHZETRN methodology in slab and spherical geometry, and it was shown that 3DHZETRN agrees with MC codes to the degree that various MC codes agree among themselves. One limitation in the verification process is that all of the codes (3DHZETRN and three MC codes) utilize different nuclear models/databases. In the present report, the new algorithm, with well-defined convergence criteria, is used to quantify the neutron leakage from simple geometries to provide means of verifying 3D effects and to provide guidance for further code development.

Evaluation of General and Tailor Made Force Fields via X-ray Thermal Diffuse Scattering Using Molecular Dynamics and Monte Carlo Simulations of Crystalline Aspirin.

PubMed

Chan, Eric J; Neumann, Marcus A

2018-04-10

We have performed a comparison of the experimental thermal diffuse scattering (TDS) from crystalline Aspirin (form I) to that calculated from molecular dynamics (MD) simulations based on a variety of general force fields and a tailor-made force field (TMFF). A comparison is also made with Monte Carlo (MC) simulations which use a "harmonic network" approach to describe the intermolecular interactions. These comparisons were based on the hypothesis that TDS could be a useful experimental data in validation of such simulation parameter sets, especially when calculations of dynamical properties (e.g., thermodynamic free energies) from molecular crystals are concerned. Currently such a validation of force field parameters against experimental data is often limited to calculation of specific physical properties, e.g., absolute lattice energies usually at 0 K or heat capacity measurements. TDS harvested from in-house or synchrotron experiments comprises highly detailed structural information representative of the dynamical motions of the crystal lattice. Thus, TDS is a well-suited experimental data-driven means of cross validating theoretical approaches targeted at understanding dynamical properties of crystals. We found from the results of our investigation that the TMFF and COMPASS (from the commercial software "Materials Studio") parameter sets gave the best agreement with experiment. From our homologous MC simulation analysis we are able to show that force constants associated with the molecular torsion angles are likely to be a strong contributing factor for the apparent reason why these aforementioned force fields performed better.

SU-E-T-24: A Simple Correction-Based Method for Independent Monitor Unit (MU) Verification in Monte Carlo (MC) Lung SBRT Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pokhrel, D; Badkul, R; Jiang, H

2014-06-01

Purpose: Lung-SBRT uses hypo-fractionated dose in small non-IMRT fields with tissue-heterogeneity corrected plans. An independent MU verification is mandatory for safe and effective delivery of the treatment plan. This report compares planned MU obtained from iPlan-XVM-Calgorithm against spreadsheet-based hand-calculation using most commonly used simple TMR-based method. Methods: Treatment plans of 15 patients who underwent for MC-based lung-SBRT to 50Gy in 5 fractions for PTV V100%=95% were studied. ITV was delineated on MIP images based on 4D-CT scans. PTVs(ITV+5mm margins) ranged from 10.1- 106.5cc(average=48.6cc). MC-SBRT plans were generated using a combination of non-coplanar conformal arcs/beams using iPlan XVM-Calgorithm (BrainLAB iPlan ver.4.1.2)more » for Novalis-TX consisting of micro-MLCs and 6MV-SRS (1000MU/min) beam. These plans were re-computed using heterogeneity-corrected Pencil-Beam (PB-hete) algorithm without changing any beam parameters, such as MLCs/MUs. Dose-ratio: PB-hete/MC gave beam-by-beam inhomogeneity-correction-factors (ICFs):Individual Correction. For independent-2nd-check, MC-MUs were verified using TMR-based hand-calculation and obtained an average ICF:Average Correction, whereas TMR-based hand-calculation systematically underestimated MC-MUs by ∼5%. Also, first 10 MC-plans were verified with an ion-chamber measurement using homogenous phantom. Results: For both beams/arcs, mean PB-hete dose was systematically overestimated by 5.5±2.6% and mean hand-calculated MU systematic underestimated by 5.5±2.5% compared to XVMC. With individual correction, mean hand-calculated MUs matched with XVMC by - 0.3±1.4%/0.4±1.4 for beams/arcs, respectively. After average 5% correction, hand-calculated MUs matched with XVMC by 0.5±2.5%/0.6±2.0% for beams/arcs, respectively. Smaller dependence on tumor volume(TV)/field size(FS) was also observed. Ion-chamber measurement was within ±3.0%. Conclusion: PB-hete overestimates dose to lung tumor relative to XVMC. XVMC-algorithm is much more-complex and accurate with tissues-heterogeneities. Measurement at machine is time consuming and need extra resources; also direct measurement of dose for heterogeneous treatment plans is not clinically practiced, yet. This simple correction-based method was very helpful for independent-2nd-check of MC-lung-SBRT plans and routinely used in our clinic. A look-up table can be generated to include TV/FS dependence in ICFs.« less

SU-F-19A-05: Experimental and Monte Carlo Characterization of the 1 Cm CivaString 103Pd Brachytherapy Source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reed, J; Micka, J; Culberson, W

Purpose: To determine the in-air azimuthal anisotropy and in-water dose distribution for the 1 cm length of the CivaString {sup 103}Pd brachytherapy source through measurements and Monte Carlo (MC) simulations. American Association of Physicists in Medicine Task Group No. 43 (TG-43) dosimetry parameters were also determined for this source. Methods: The in-air azimuthal anisotropy of the source was measured with a NaI scintillation detector and simulated with the MCNP5 radiation transport code. Measured and simulated results were normalized to their respective mean values and compared. The TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function for this sourcemore » were determined from LiF:Mg,Ti thermoluminescent dosimeter (TLD) measurements and MC simulations. The impact of {sup 103}Pd well-loading variability on the in-water dose distribution was investigated using MC simulations by comparing the dose distribution for a source model with four wells of equal strength to that for a source model with strengths increased by 1% for two of the four wells. Results: NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy showed that ≥95% of the normalized data were within 1.2% of the mean value. TLD measurements and MC simulations of the TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function agreed to within the experimental TLD uncertainties (k=2). MC simulations showed that a 1% variability in {sup 103}Pd well-loading resulted in changes of <0.1%, <0.1%, and <0.3% in the TG-43 dose-rate constant, radial dose distribution, and polar dose distribution, respectively. Conclusion: The CivaString source has a high degree of azimuthal symmetry as indicated by the NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy. TG-43 dosimetry parameters for this source were determined from TLD measurements and MC simulations. {sup 103}Pd well-loading variability results in minimal variations in the in-water dose distribution according to MC simulations. This work was partially supported by CivaTech Oncology, Inc. through an educational grant for Joshua Reed, John Micka, Wesley Culberson, and Larry DeWerd and through research support for Mark Rivard.« less

SU-F-T-74: Experimental Validation of Monaco Electron Monte Carlo Dose Calculation for Small Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varadhan; Way, S; Arentsen, L

2016-06-15

Purpose: To verify experimentally the accuracy of Monaco (Elekta) electron Monte Carlo (eMC) algorithm to calculate small field size depth doses, monitor units and isodose distributions. Methods: Beam modeling of eMC algorithm was performed for electron energies of 6, 9, 12 15 and 18 Mev for a Elekta Infinity Linac and all available ( 6, 10, 14 20 and 25 cone) applicator sizes. Electron cutouts of incrementally smaller field sizes (20, 40, 60 and 80% blocked from open cone) were fabricated. Dose calculation was performed using a grid size smaller than one-tenth of the R{sub 80–20} electron distal falloff distancemore » and number of particle histories was set at 500,000 per cm{sup 2}. Percent depth dose scans and beam profiles at dmax, d{sub 90} and d{sub 80} depths were measured for each cutout and energy with Wellhoffer (IBA) Blue Phantom{sup 2} scanning system and compared against eMC calculated doses. Results: The measured dose and output factors of incrementally reduced cutout sizes (to 3cm diameter) agreed with eMC calculated doses within ± 2.5%. The profile comparisons at dmax, d{sub 90} and d{sub 80} depths and percent depth doses at reduced field sizes agreed within 2.5% or 2mm. Conclusion: Our results indicate that the Monaco eMC algorithm can accurately predict depth doses, isodose distributions, and monitor units in homogeneous water phantom for field sizes as small as 3.0 cm diameter for energies in the 6 to 18 MeV range at 100 cm SSD. Consequently, the old rule of thumb to approximate limiting cutout size for an electron field determined by the lateral scatter equilibrium (E (MeV)/2.5 in centimeters of water) does not apply to Monaco eMC algorithm.« less

Kinetic Monte Carlo Simulations of Rod Eutectics and the Surface Roughening Transition in Binary Alloys

NASA Technical Reports Server (NTRS)

Bentz, Daniel N.; Betush, William; Jackson, Kenneth A.

2003-01-01

In this paper we report on two related topics: Kinetic Monte Carlo simulations of the steady state growth of rod eutectics from the melt, and a study of the surface roughness of binary alloys. We have implemented a three dimensional kinetic Monte Carlo (kMC) simulation with diffusion by pair exchange only in the liquid phase. Entropies of fusion are first chosen to fit the surface roughness of the pure materials, and the bond energies are derived from the equilibrium phase diagram, by treating the solid and liquid as regular and ideal solutions respectively. A simple cubic lattice oriented in the {100} direction is used. Growth of the rods is initiated from columns of pure B material embedded in an A matrix, arranged in a close packed array with semi-periodic boundary conditions. The simulation cells typically have dimensions of 50 by 87 by 200 unit cells. Steady state growth is compliant with the Jackson-Hunt model. In the kMC simulations, using the spin-one Ising model, growth of each phase is faceted or nonfaceted phases depending on the entropy of fusion. There have been many studies of the surface roughening transition in single component systems, but none for binary alloy systems. The location of the surface roughening transition for the phases of a eutectic alloy determines whether the eutectic morphology will be regular or irregular. We have conducted a study of surface roughness on the spin-one Ising Model with diffusion using kMC. The surface roughness was found to scale with the melting temperature of the alloy as given by the liquidus line on the equilibrium phase diagram. The density of missing lateral bonds at the surface was used as a measure of surface roughness.

On the Monte Carlo simulation of electron transport in the sub-1 keV energy range.

PubMed

Thomson, Rowan M; Kawrakow, Iwan

2011-08-01

The validity of "classic" Monte Carlo (MC) simulations of electron and positron transport at sub-1 keV energies is investigated in the context of quantum theory. Quantum theory dictates that uncertainties on the position and energy-momentum four-vectors of radiation quanta obey Heisenberg's uncertainty relation; however, these uncertainties are neglected in "classical" MC simulations of radiation transport in which position and momentum are known precisely. Using the quantum uncertainty relation and electron mean free path, the magnitudes of uncertainties on electron position and momentum are calculated for different kinetic energies; a validity bound on the classical simulation of electron transport is derived. In order to satisfy the Heisenberg uncertainty principle, uncertainties of 5% must be assigned to position and momentum for 1 keV electrons in water; at 100 eV, these uncertainties are 17 to 20% and are even larger at lower energies. In gaseous media such as air, these uncertainties are much smaller (less than 1% for electrons with energy 20 eV or greater). The classical Monte Carlo transport treatment is questionable for sub-1 keV electrons in condensed water as uncertainties on position and momentum must be large (relative to electron momentum and mean free path) to satisfy the quantum uncertainty principle. Simulations which do not account for these uncertainties are not faithful representations of the physical processes, calling into question the results of MC track structure codes simulating sub-1 keV electron transport. Further, the large difference in the scale at which quantum effects are important in gaseous and condensed media suggests that track structure measurements in gases are not necessarily representative of track structure in condensed materials on a micrometer or a nanometer scale.

Parallel and Portable Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Lee, S. R.; Cummings, J. C.; Nolen, S. D.; Keen, N. D.

1997-08-01

We have developed a multi-group, Monte Carlo neutron transport code in C++ using object-oriented methods and the Parallel Object-Oriented Methods and Applications (POOMA) class library. This transport code, called MC++, currently computes k and α eigenvalues of the neutron transport equation on a rectilinear computational mesh. It is portable to and runs in parallel on a wide variety of platforms, including MPPs, clustered SMPs, and individual workstations. It contains appropriate classes and abstractions for particle transport and, through the use of POOMA, for portable parallelism. Current capabilities are discussed, along with physics and performance results for several test problems on a variety of hardware, including all three Accelerated Strategic Computing Initiative (ASCI) platforms. Current parallel performance indicates the ability to compute α-eigenvalues in seconds or minutes rather than days or weeks. Current and future work on the implementation of a general transport physics framework (TPF) is also described. This TPF employs modern C++ programming techniques to provide simplified user interfaces, generic STL-style programming, and compile-time performance optimization. Physics capabilities of the TPF will be extended to include continuous energy treatments, implicit Monte Carlo algorithms, and a variety of convergence acceleration techniques such as importance combing.

Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study

NASA Astrophysics Data System (ADS)

Lerendegui-Marco, J.; Cortés-Giraldo, M. A.; Guerrero, C.; Quesada, J. M.; Meo, S. Lo; Massimi, C.; Barbagallo, M.; Colonna, N.; Mancussi, D.; Mingrone, F.; Sabaté-Gilarte, M.; Vannini, G.; Vlachoudis, V.; Aberle, O.; Andrzejewski, J.; Audouin, L.; Bacak, M.; Balibrea, J.; Bečvář, F.; Berthoumieux, E.; Billowes, J.; Bosnar, D.; Brown, A.; Caamaño, M.; Calviño, F.; Calviani, M.; Cano-Ott, D.; Cardella, R.; Casanovas, A.; Cerutti, F.; Chen, Y. H.; Chiaveri, E.; Cortés, G.; Cosentino, L.; Damone, L. A.; Diakaki, M.; Domingo-Pardo, C.; Dressler, R.; Dupont, E.; Durán, I.; Fernández-Domínguez, B.; Ferrari, A.; Ferreira, P.; Finocchiaro, P.; Göbel, K.; Gómez-Hornillos, M. B.; García, A. R.; Gawlik, A.; Gilardoni, S.; Glodariu, T.; Gonçalves, I. F.; González, E.; Griesmayer, E.; Gunsing, F.; Harada, H.; Heinitz, S.; Heyse, J.; Jenkins, D. G.; Jericha, E.; Käppeler, F.; Kadi, Y.; Kalamara, A.; Kavrigin, P.; Kimura, A.; Kivel, N.; Kokkoris, M.; Krtička, M.; Kurtulgil, D.; Leal-Cidoncha, E.; Lederer, C.; Leeb, H.; Lonsdale, S. J.; Macina, D.; Marganiec, J.; Martínez, T.; Masi, A.; Mastinu, P.; Mastromarco, M.; Maugeri, E. A.; Mazzone, A.; Mendoza, E.; Mengoni, A.; Milazzo, P. M.; Musumarra, A.; Negret, A.; Nolte, R.; Oprea, A.; Patronis, N.; Pavlik, A.; Perkowski, J.; Porras, I.; Praena, J.; Radeck, D.; Rauscher, T.; Reifarth, R.; Rout, P. C.; Rubbia, C.; Ryan, J. A.; Saxena, A.; Schillebeeckx, P.; Schumann, D.; Smith, A. G.; Sosnin, N. V.; Stamatopoulos, A.; Tagliente, G.; Tain, J. L.; Tarifeño-Saldivia, A.; Tassan-Got, L.; Valenta, S.; Variale, V.; Vaz, P.; Ventura, A.; Vlastou, R.; Wallner, A.; Warren, S.; Woods, P. J.; Wright, T.; Žugec, P.

2017-09-01

Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field had been MCNPX and FLUKA. However, the Geant4 toolkit has also become a competitive code for the transport of neutrons after the development of the native Geant4 format for neutron data libraries, G4NDL. In this context, we present the Geant4 simulations of the neutron spallation target of the n_TOF facility at CERN, done with version 10.1.1 of the toolkit. The first goal was the validation of the intra-nuclear cascade models implemented in the code using, as benchmark, the characteristics of the neutron beam measured at the first experimental area (EAR1), especially the neutron flux and energy distribution, and the time distribution of neutrons of equal kinetic energy, the so-called Resolution Function. The second goal was the development of a Monte Carlo tool aimed to provide useful calculations for both the analysis and planning of the upcoming measurements at the new experimental area (EAR2) of the facility.

Neutron track length estimator for GATE Monte Carlo dose calculation in radiotherapy.

PubMed

Elazhar, H; Deschler, T; Létang, J M; Nourreddine, A; Arbor, N

2018-06-20

The out-of-field dose in radiation therapy is a growing concern in regards to the late side-effects and secondary cancer induction. In high-energy x-ray therapy, the secondary neutrons generated through photonuclear reactions in the accelerator are part of this secondary dose. The neutron dose is currently not estimated by the treatment planning system while it appears to be preponderant for distances greater than 50 cm from the isocenter. Monte Carlo simulation has become the gold standard for accurately calculating the neutron dose under specific treatment conditions but the method is also known for having a slow statistical convergence, which makes it difficult to be used on a clinical basis. The neutron track length estimator, a neutron variance reduction technique inspired by the track length estimator method has thus been developped for the first time in the Monte Carlo code GATE to allow a fast computation of the neutron dose in radiotherapy. The details of its implementation, as well as the comparison of its performances against the analog MC method, are presented here. A gain of time from 15 to 400 can be obtained by our method, with a mean difference in the dose calculation of about 1% in comparison with the analog MC method.

LMC: Logarithmantic Monte Carlo

NASA Astrophysics Data System (ADS)

Mantz, Adam B.

2017-06-01

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

The SM and NLO Multileg and SM MC Working Groups: Summary Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alcaraz Maestre, J.; et al.

2012-03-01

The 2011 Les Houches workshop was the first to confront LHC data. In the two years since the previous workshop there have been significant advances in both soft and hard QCD, particularly in the areas of multi-leg NLO calculations, the inclusion of those NLO calculations into parton shower Monte Carlos, and the tuning of the non-perturbative parameters of those Monte Carlos. These proceedings describe the theoretical advances that have taken place, the impact of the early LHC data, and the areas for future development.

KMCThinFilm: A C++ Framework for the Rapid Development of Lattice Kinetic Monte Carlo (kMC) Simulations of Thin Film Growth

DTIC Science & Technology

2015-09-01

direction, so if the simulation domain is set to be a certain size, then that presents a hard ceiling on the thickness of a film that may be grown in...FFA, Los J, Cuppen HM, Bennema P, Meekes H. MONTY:  Monte Carlo crystal growth on any crystal structure in any crystallographic orientation...mhoffman.github.io/kmos/. 23. Kiravittaya S, Schmidt OG. Quantum-dot crystal defects. Applied Physics Letters. 2008;93:173109. 24. Leetmaa M

Monitoring System for the GRID Monte Carlo Mass Production in the H1 Experiment at DESY

NASA Astrophysics Data System (ADS)

Bystritskaya, Elena; Fomenko, Alexander; Gogitidze, Nelly; Lobodzinski, Bogdan

2014-06-01

The H1 Virtual Organization (VO), as one of the small VOs, employs most components of the EMI or gLite Middleware. In this framework, a monitoring system is designed for the H1 Experiment to identify and recognize within the GRID the best suitable resources for execution of CPU-time consuming Monte Carlo (MC) simulation tasks (jobs). Monitored resources are Computer Elements (CEs), Storage Elements (SEs), WMS-servers (WMSs), CernVM File System (CVMFS) available to the VO HONE and local GRID User Interfaces (UIs). The general principle of monitoring GRID elements is based on the execution of short test jobs on different CE queues using submission through various WMSs and directly to the CREAM-CEs as well. Real H1 MC Production jobs with a small number of events are used to perform the tests. Test jobs are periodically submitted into GRID queues, the status of these jobs is checked, output files of completed jobs are retrieved, the result of each job is analyzed and the waiting time and run time are derived. Using this information, the status of the GRID elements is estimated and the most suitable ones are included in the automatically generated configuration files for use in the H1 MC production. The monitoring system allows for identification of problems in the GRID sites and promptly reacts on it (for example by sending GGUS (Global Grid User Support) trouble tickets). The system can easily be adapted to identify the optimal resources for tasks other than MC production, simply by changing to the relevant test jobs. The monitoring system is written mostly in Python and Perl with insertion of a few shell scripts. In addition to the test monitoring system we use information from real production jobs to monitor the availability and quality of the GRID resources. The monitoring tools register the number of job resubmissions, the percentage of failed and finished jobs relative to all jobs on the CEs and determine the average values of waiting and running time for the involved GRID queues. CEs which do not meet the set criteria can be removed from the production chain by including them in an exception table. All of these monitoring actions lead to a more reliable and faster execution of MC requests.

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation

NASA Astrophysics Data System (ADS)

Magro, G.; Molinelli, S.; Mairani, A.; Mirandola, A.; Panizza, D.; Russo, S.; Ferrari, A.; Valvo, F.; Fossati, P.; Ciocca, M.

2015-09-01

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo® TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus® chamber. An EBT3® film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation.

PubMed

Magro, G; Molinelli, S; Mairani, A; Mirandola, A; Panizza, D; Russo, S; Ferrari, A; Valvo, F; Fossati, P; Ciocca, M

2015-09-07

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo(®) TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus(®) chamber. An EBT3(®) film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

Development of an effective dose coefficient database using a computational human phantom and Monte Carlo simulations to evaluate exposure dose for the usage of NORM-added consumer products.

PubMed

Yoo, Do Hyeon; Shin, Wook-Geun; Lee, Jaekook; Yeom, Yeon Soo; Kim, Chan Hyeong; Chang, Byung-Uck; Min, Chul Hee

2017-11-01

After the Fukushima accident in Japan, the Korean Government implemented the "Act on Protective Action Guidelines Against Radiation in the Natural Environment" to regulate unnecessary radiation exposure to the public. However, despite the law which came into effect in July 2012, an appropriate method to evaluate the equivalent and effective doses from naturally occurring radioactive material (NORM) in consumer products is not available. The aim of the present study is to develop and validate an effective dose coefficient database enabling the simple and correct evaluation of the effective dose due to the usage of NORM-added consumer products. To construct the database, we used a skin source method with a computational human phantom and Monte Carlo (MC) simulation. For the validation, the effective dose was compared between the database using interpolation method and the original MC method. Our result showed a similar equivalent dose across the 26 organs and a corresponding average dose between the database and the MC calculations of < 5% difference. The differences in the effective doses were even less, and the result generally show that equivalent and effective doses can be quickly calculated with the database with sufficient accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of doses calculated by the Monte Carlo method and measured by LiF TLD in the buildup region for a 60Co photon beam.

PubMed

Budanec, M; Knezević, Z; Bokulić, T; Mrcela, I; Vrtar, M; Vekić, B; Kusić, Z

2008-12-01

This work studied the percent depth doses of (60)Co photon beams in the buildup region of a plastic phantom by LiF TLD measurements and by Monte Carlo calculations. An agreement within +/-1.5% was found between PDDs measured by TLD and calculated by the Monte Carlo method with the TLD in a plastic phantom. The dose in the plastic phantom was scored in voxels, with thickness scaled by physical and electron density. PDDs calculated by electron density scaling showed a better match with PDD(TLD)(MC); the difference is within +/-1.5% in the buildup region for square and rectangular field sizes.

Spin polarisation of tt¯γγ production at NLO+PS with GoSam interfaced to MadGraph5_aMC@NLO

DOE PAGES

van Deurzen, Hans; Frederix, Rikkert; Hirschi, Valentin; ...

2016-04-22

Here, we present an interface between the multipurpose Monte Carlo tool MadGraph5_aMC@NLO and the automated amplitude generator GoSam. As a first application of this novel framework, we compute the NLO corrections to pp→ tt¯H and pp→ tt¯γγ matched to a parton shower. In the phenomenological analyses of these processes, we focus our attention on observables which are sensitive to the polarisation of the top quarks.

Spin polarisation of tt¯γγ production at NLO+PS with GoSam interfaced to MadGraph5_aMC@NLO

DOE Office of Scientific and Technical Information (OSTI.GOV)

van Deurzen, Hans; Frederix, Rikkert; Hirschi, Valentin

Here, we present an interface between the multipurpose Monte Carlo tool MadGraph5_aMC@NLO and the automated amplitude generator GoSam. As a first application of this novel framework, we compute the NLO corrections to pp→ tt¯H and pp→ tt¯γγ matched to a parton shower. In the phenomenological analyses of these processes, we focus our attention on observables which are sensitive to the polarisation of the top quarks.

McStas 1.7 - a new version of the flexible Monte Carlo neutron scattering package

NASA Astrophysics Data System (ADS)

Willendrup, Peter; Farhi, Emmanuel; Lefmann, Kim

2004-07-01

Current neutron instrumentation is both complex and expensive, and accurate simulation has become essential both for building new instruments and for using them effectively. The McStas neutron ray-trace simulation package is a versatile tool for producing such simulations, developed in collaboration between Risø and ILL. The new version (1.7) has many improvements, among these added support for the popular Microsoft Windows platform. This presentation will demonstrate a selection of the new features through a simulation of the ILL IN6 beamline.

Interfacing MCNPX and McStas for simulation of neutron transport

NASA Astrophysics Data System (ADS)

Klinkby, Esben; Lauritzen, Bent; Nonbøl, Erik; Kjær Willendrup, Peter; Filges, Uwe; Wohlmuther, Michael; Gallmeier, Franz X.

2013-02-01

Simulations of target-moderator-reflector system at spallation sources are conventionally carried out using Monte Carlo codes such as MCNPX (Waters et al., 2007 [1]) or FLUKA (Battistoni et al., 2007; Ferrari et al., 2005 [2,3]) whereas simulations of neutron transport from the moderator and the instrument response are performed by neutron ray tracing codes such as McStas (Lefmann and Nielsen, 1999; Willendrup et al., 2004, 2011a,b [4-7]). The coupling between the two simulation suites typically consists of providing analytical fits of MCNPX neutron spectra to McStas. This method is generally successful but has limitations, as it e.g. does not allow for re-entry of neutrons into the MCNPX regime. Previous work to resolve such shortcomings includes the introduction of McStas inspired supermirrors in MCNPX. In the present paper different approaches to interface MCNPX and McStas are presented and applied to a simple test case. The direct coupling between MCNPX and McStas allows for more accurate simulations of e.g. complex moderator geometries, backgrounds, interference between beam-lines as well as shielding requirements along the neutron guides.

SU-F-19A-10: Recalculation and Reporting Clinical HDR 192-Ir Head and Neck Dose Distributions Using Model Based Dose Calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlsson Tedgren, A; Persson, M; Nilsson, J

Purpose: To retrospectively re-calculate dose distributions for selected head and neck cancer patients, earlier treated with HDR 192Ir brachytherapy, using Monte Carlo (MC) simulations and compare results to distributions from the planning system derived using TG43 formalism. To study differences between dose to medium (as obtained with the MC code) and dose to water in medium as obtained through (1) ratios of stopping powers and (2) ratios of mass energy absorption coefficients between water and medium. Methods: The MC code Algebra was used to calculate dose distributions according to earlier actual treatment plans using anonymized plan data and CT imagesmore » in DICOM format. Ratios of stopping power and mass energy absorption coefficients for water with various media obtained from 192-Ir spectra were used in toggling between dose to water and dose to media. Results: Differences between initial planned TG43 dose distributions and the doses to media calculated by MC are insignificant in the target volume. Differences are moderate (within 4–5 % at distances of 3–4 cm) but increase with distance and are most notable in bone and at the patient surface. Differences between dose to water and dose to medium are within 1-2% when using mass energy absorption coefficients to toggle between the two quantities but increase to above 10% for bone using stopping power ratios. Conclusion: MC predicts target doses for head and neck cancer patients in close agreement with TG43. MC yields improved dose estimations outside the target where a larger fraction of dose is from scattered photons. It is important with awareness and a clear reporting of absorbed dose values in using model based algorithms. Differences in bone media can exceed 10% depending on how dose to water in medium is defined.« less

Anode optimization for miniature electronic brachytherapy X-ray sources using Monte Carlo and computational fluid dynamic codes

PubMed Central

Khajeh, Masoud; Safigholi, Habib

2015-01-01

A miniature X-ray source has been optimized for electronic brachytherapy. The cooling fluid for this device is water. Unlike the radionuclide brachytherapy sources, this source is able to operate at variable voltages and currents to match the dose with the tumor depth. First, Monte Carlo (MC) optimization was performed on the tungsten target-buffer thickness layers versus energy such that the minimum X-ray attenuation occurred. Second optimization was done on the selection of the anode shape based on the Monte Carlo in water TG-43U1 anisotropy function. This optimization was carried out to get the dose anisotropy functions closer to unity at any angle from 0° to 170°. Three anode shapes including cylindrical, spherical, and conical were considered. Moreover, by Computational Fluid Dynamic (CFD) code the optimal target-buffer shape and different nozzle shapes for electronic brachytherapy were evaluated. The characterization criteria of the CFD were the minimum temperature on the anode shape, cooling water, and pressure loss from inlet to outlet. The optimal anode was conical in shape with a conical nozzle. Finally, the TG-43U1 parameters of the optimal source were compared with the literature. PMID:26966563

Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems

DOE PAGES

Biondo, Elliott D.; Davidson, Gregory G.; Pandya, Tara M.; ...

2018-04-30

The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SPNSPN or SNSN solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solutionmore » parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. Here it is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.« less

Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biondo, Elliott D.; Davidson, Gregory G.; Pandya, Tara M.

The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SPNSPN or SNSN solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solutionmore » parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. Here it is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.« less

SU-F-T-371: Development of a Linac Monte Carlo Model to Calculate Surface Dose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prajapati, S; Yan, Y; Gifford, K

2016-06-15

Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V4-2.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V4-2.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films weremore » placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and was 3.5% for MLC. For the 6 MV beam, the average root mean square(RMS) deviation for the central 80% of the beam profile for open fields was 1.5%, whereas it was 1.6% for MLC. For the 18 MV beam, the maximum RMS for open fields was 3%, and was 3.1% for MLC. Conclusion: The MC model of a linac agreed to within 4% of film measurements for depths ranging from the surface to dmax. Therefore, the MC linac model can predict surface dose for clinical applications. Future work will focus on adjusting the linac MC model to reduce RMS error and improve accuracy.« less

Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

NASA Astrophysics Data System (ADS)

Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.

2018-02-01

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan Chan Tseung, Hok Seum, E-mail: wanchantseung.hok@mayo.edu; Ma, Jiasen; Kreofsky, Cole R.

Purpose: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)–based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. Methods and Materials: Recently, a fast and accurate graphics processor unit (GPU)–based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LET{sub d}), which makes biological dose (BD) optimization possible. To convert from LET{sub d} to BD, a simple linear relation was assumed. By use of thismore » novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. Results: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. Conclusions: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small–tumor target patients. This optimizer will be used in an upcoming feasibility trial on LET{sub d} painting for radioresistant tumors.« less

ProMC: Input-output data format for HEP applications using varint encoding

NASA Astrophysics Data System (ADS)

Chekanov, S. V.; May, E.; Strand, K.; Van Gemmeren, P.

2014-10-01

A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach is implemented in the PROMC library which produces smaller file sizes for MC records compared to the existing input-output libraries used in high-energy physics (HEP). Other important features of the proposed format are a separation of abstract data layouts from concrete programming implementations, self-description and random access. Data stored in PROMC files can be written, read and manipulated in a number of programming languages, such C++, JAVA, FORTRAN and PYTHON.

Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.

2015-01-01

The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysismore » that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR.« less

SU-E-I-28: Evaluating the Organ Dose From Computed Tomography Using Monte Carlo Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ono, T; Araki, F

Purpose: To evaluate organ doses from computed tomography (CT) using Monte Carlo (MC) calculations. Methods: A Philips Brilliance CT scanner (64 slice) was simulated using the GMctdospp (IMPS, Germany) based on the EGSnrc user code. The X-ray spectra and a bowtie filter for MC simulations were determined to coincide with measurements of half-value layer (HVL) and off-center ratio (OCR) profile in air. The MC dose was calibrated from absorbed dose measurements using a Farmer chamber and a cylindrical water phantom. The dose distribution from CT was calculated using patient CT images and organ doses were evaluated from dose volume histograms.more » Results: The HVLs of Al at 80, 100, and 120 kV were 6.3, 7.7, and 8.7 mm, respectively. The calculated HVLs agreed with measurements within 0.3%. The calculated and measured OCR profiles agreed within 3%. For adult head scans (CTDIvol) =51.4 mGy), mean doses for brain stem, eye, and eye lens were 23.2, 34.2, and 37.6 mGy, respectively. For pediatric head scans (CTDIvol =35.6 mGy), mean doses for brain stem, eye, and eye lens were 19.3, 24.5, and 26.8 mGy, respectively. For adult chest scans (CTDIvol=19.0 mGy), mean doses for lung, heart, and spinal cord were 21.1, 22.0, and 15.5 mGy, respectively. For adult abdominal scans (CTDIvol=14.4 mGy), the mean doses for kidney, liver, pancreas, spleen, and spinal cord were 17.4, 16.5, 16.8, 16.8, and 13.1 mGy, respectively. For pediatric abdominal scans (CTDIvol=6.76 mGy), mean doses for kidney, liver, pancreas, spleen, and spinal cord were 8.24, 8.90, 8.17, 8.31, and 6.73 mGy, respectively. In head scan, organ doses were considerably different from CTDIvol values. Conclusion: MC dose distributions calculated by using patient CT images are useful to evaluate organ doses absorbed to individual patients.« less

MO-E-17A-03: Monte Carlo CT Dose Calculation: A Comparison Between Experiment and Simulation Using ARCHER-CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, T; Du, X; Su, L

2014-06-15

Purpose: To compare the CT doses derived from the experiments and GPU-based Monte Carlo (MC) simulations, using a human cadaver and ATOM phantom. Methods: The cadaver of an 88-year old male and the ATOM phantom were scanned by a GE LightSpeed Pro 16 MDCT. For the cadaver study, the Thimble chambers (Model 10×5−0.6CT and 10×6−0.6CT) were used to measure the absorbed dose in different deep and superficial organs. Whole-body scans were first performed to construct a complete image database for MC simulations. Abdomen/pelvis helical scans were then conducted using 120/100 kVps, 300 mAs and a pitch factor of 1.375:1. Formore » the ATOM phantom study, the OSL dosimeters were used and helical scans were performed using 120 kVp and x, y, z tube current modulation (TCM). For the MC simulations, sufficient particles were run in both cases such that the statistical errors of the results by ARCHER-CT were limited to 1%. Results: For the human cadaver scan, the doses to the stomach, liver, colon, left kidney, pancreas and urinary bladder were compared. The difference between experiments and simulations was within 19% for the 120 kVp and 25% for the 100 kVp. For the ATOM phantom scan, the doses to the lung, thyroid, esophagus, heart, stomach, liver, spleen, kidneys and thymus were compared. The difference was 39.2% for the esophagus, and within 16% for all other organs. Conclusion: In this study the experimental and simulated CT doses were compared. Their difference is primarily attributed to the systematic errors of the MC simulations, including the accuracy of the bowtie filter modeling, and the algorithm to generate voxelized phantom from DICOM images. The experimental error is considered small and may arise from the dosimeters. R01 grant (R01EB015478) from National Institute of Biomedical Imaging and Bioengineering.« less

WE-EF-207-05: Monte Carlo Dosimetry for a Dedicated Cone-Beam CT Head Scanner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sisniega, A; Zbijewski, W; Xu, J

Purpose: Cone-Beam CT (CBCT) is an attractive platform for point-of-care imaging of traumatic brain injury and intracranial hemorrhage. This work implements and evaluates a fast Monte-Carlo (MC) dose estimation engine for development of a dedicated head CBCT scanner, optimization of acquisition protocols, geometry, bowtie filter designs, and patient-specific dosimetry. Methods: Dose scoring with a GPU-based MC CBCT simulator was validated on an imaging bench using a modified 16 cm CTDI phantom with 7 ion chamber shafts along the central ray for 80–100 kVp (+2 mm Al, +0.2 mm Cu). Dose distributions were computed in a segmented CBCT reconstruction of anmore » anthropomorphic head phantom with 4×10{sup 5} tracked photons per scan (5 min runtime). Circular orbits with angular span ranging from short scan (180° + fan angle) to full rotation (360°) were considered for fixed total mAs per scan. Two aluminum filters were investigated: aggressive bowtie, and moderate bowtie (matched to 16 cm and 32 cm water cylinder, respectively). Results: MC dose estimates showed strong agreement with measurements (RMSE<0.001 mGy/mAs). A moderate (aggressive) bowtie reduced the dose, per total mAs, by 20% (30%) at the center of the head, by 40% (50%) at the eye lens, and by 70% (80%) at the posterior skin entrance. For the no bowtie configuration, a short scan reduced the eye lens dose by 62% (from 0.08 mGy/mAs to 0.03 mGy/mAs) compared to full scan, although the dose to spinal bone marrow increased by 40%. For both bowties, the short scan resulted in a similar 40% increase in bone marrow dose, but the reduction in the eye lens was more pronounced: 70% (90%) for the moderate (aggressive) bowtie. Conclusions: Dose maps obtained with validated MC simulation demonstrated dose reduction in sensitive structures (eye lens and bone marrow) through combination of short-scan trajectories and bowtie filters. Xiaohui Wang and David Foos are employees of Carestream Health.« less

Application of a Java-based, univel geometry, neutral particle Monte Carlo code to the searchlight problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Charles A. Wemple; Joshua J. Cogliati

2005-04-01

A univel geometry, neutral particle Monte Carlo transport code, written entirely in the Java programming language, is under development for medical radiotherapy applications. The code uses ENDF-VI based continuous energy cross section data in a flexible XML format. Full neutron-photon coupling, including detailed photon production and photonuclear reactions, is included. Charged particle equilibrium is assumed within the patient model so that detailed transport of electrons produced by photon interactions may be neglected. External beam and internal distributed source descriptions for mixed neutron-photon sources are allowed. Flux and dose tallies are performed on a univel basis. A four-tap, shift-register-sequence random numbermore » generator is used. Initial verification and validation testing of the basic neutron transport routines is underway. The searchlight problem was chosen as a suitable first application because of the simplicity of the physical model. Results show excellent agreement with analytic solutions. Computation times for similar numbers of histories are comparable to other neutron MC codes written in C and FORTRAN.« less

The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.

2015-12-01

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple becausemore » it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.« less

Computational Characterization of Type I collagen-based Extra-cellular Matrix

NASA Astrophysics Data System (ADS)

Liang, Long; Jones, Christopher Allen Rucksack; Lin, Daniel; Jiao, Yang; Sun, Bo

2015-03-01

A model of extracellular matrix (ECM) of collagen fibers has been built, in which cells could communicate with distant partners via fiber-mediated long-range-transmitted stress states. The ECM is modeled as a spring-like fiber network derived from skeletonized confocal microscopy data. Different local and global perturbations have been performed on the network, each followed by an optimized global Monte-Carlo (MC) energy minimization leading to the deformed network in response to the perturbations. In the optimization, a highly efficient local energy update procedure is employed and force-directed MC moves are used, which results in a convergence to the energy minimum state 20 times faster than the commonly used random displacement trial moves in MC. Further analysis and visualization of the distribution and correlation of the resulting force network reveal that local perturbations can give rise to global impacts: the force chains formed with a linear extent much further than the characteristic length scale associated with the perturbation sites and average fiber length. This behavior provides a strong evidence for our hypothesis of fiber-mediated long-range force transmission in ECM networks and the resulting long-range cell-cell mechanical signaling. ASU Seed Grant.

Transient in-plane thermal transport in nanofilms with internal heating

PubMed Central

Cao, Bing-Yang

2016-01-01

Wide applications of nanofilms in electronics necessitate an in-depth understanding of nanoscale thermal transport, which significantly deviates from Fourier's law. Great efforts have focused on the effective thermal conductivity under temperature difference, while it is still ambiguous whether the diffusion equation with an effective thermal conductivity can accurately characterize the nanoscale thermal transport with internal heating. In this work, transient in-plane thermal transport in nanofilms with internal heating is studied via Monte Carlo (MC) simulations in comparison to the heat diffusion model and mechanism analyses using Fourier transform. Phonon-boundary scattering leads to larger temperature rise and slower thermal response rate when compared with the heat diffusion model based on Fourier's law. The MC simulations are also compared with the diffusion model with effective thermal conductivity. In the first case of continuous internal heating, the diffusion model with effective thermal conductivity under-predicts the temperature rise by the MC simulations at the initial heating stage, while the deviation between them gradually decreases and vanishes with time. By contrast, for the one-pulse internal heating case, the diffusion model with effective thermal conductivity under-predicts both the peak temperature rise and the cooling rate, so the deviation can always exist. PMID:27118903

Mesoscale Thermodynamically motivated Statistical Mechanics based Kinetic Model for Sintering monoliths

NASA Astrophysics Data System (ADS)

Mohan, Nisha

Modeling the evolution of microstructure during sintering is a persistent challenge in ceramics science, although needed as the microstructure impacts properties of an engineered material. Bridging the gap between microscopic and continuum models, kinetic Monte Carlo (kMC) methods provide a stochastic approach towards sintering and microstructure evolution. These kMC models work at the mesoscale, with length and time-scales between those of atomistic and continuum approaches. We develop a sintering/compacting model for the two-phase sintering of boron nitride ceramics and allotropes alike. Our formulation includes mechanisms for phase transformation between h-BN and c-BN and takes into account thermodynamics of pressure and temperature on interaction energies and mechanism rates. In addition to replicating the micro-structure evolution observed in experiments, it also captures the phase diagram of Boron Nitride materials. Results have been analyzed in terms of phase diagrams and crystal growth. It also serves with insights to guide the choice of additives and conditions for the sintering process.While detailed time and spatial resolutions are lost in any MC, the progression of stochastic events still captures plausible local energy minima and long-time temporal developments. DARPA.

Transient in-plane thermal transport in nanofilms with internal heating.

PubMed

Hua, Yu-Chao; Cao, Bing-Yang

2016-02-01

Wide applications of nanofilms in electronics necessitate an in-depth understanding of nanoscale thermal transport, which significantly deviates from Fourier's law. Great efforts have focused on the effective thermal conductivity under temperature difference, while it is still ambiguous whether the diffusion equation with an effective thermal conductivity can accurately characterize the nanoscale thermal transport with internal heating. In this work, transient in-plane thermal transport in nanofilms with internal heating is studied via Monte Carlo (MC) simulations in comparison to the heat diffusion model and mechanism analyses using Fourier transform. Phonon-boundary scattering leads to larger temperature rise and slower thermal response rate when compared with the heat diffusion model based on Fourier's law. The MC simulations are also compared with the diffusion model with effective thermal conductivity. In the first case of continuous internal heating, the diffusion model with effective thermal conductivity under-predicts the temperature rise by the MC simulations at the initial heating stage, while the deviation between them gradually decreases and vanishes with time. By contrast, for the one-pulse internal heating case, the diffusion model with effective thermal conductivity under-predicts both the peak temperature rise and the cooling rate, so the deviation can always exist.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, M; Lloyd, S AM; Townson, R

2014-08-15

This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access tomore » underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.« less

Bayesian inversion using a geologically realistic and discrete model space

NASA Astrophysics Data System (ADS)

Jaeggli, C.; Julien, S.; Renard, P.

2017-12-01

Since the early days of groundwater modeling, inverse methods play a crucial role. Many research and engineering groups aim to infer extensive knowledge of aquifer parameters from a sparse set of observations. Despite decades of dedicated research on this topic, there are still several major issues to be solved. In the hydrogeological framework, one is often confronted with underground structures that present very sharp contrasts of geophysical properties. In particular, subsoil structures such as karst conduits, channels, faults, or lenses, strongly influence groundwater flow and transport behavior of the underground. For this reason it can be essential to identify their location and shape very precisely. Unfortunately, when inverse methods are specially trained to consider such complex features, their computation effort often becomes unaffordably high. The following work is an attempt to solve this dilemma. We present a new method that is, in some sense, a compromise between the ergodicity of Markov chain Monte Carlo (McMC) methods and the efficient handling of data by the ensemble based Kalmann filters. The realistic and complex random fields are generated by a Multiple-Point Statistics (MPS) tool. Nonetheless, it is applicable with any conditional geostatistical simulation tool. Furthermore, the algorithm is independent of any parametrization what becomes most important when two parametric systems are equivalent (permeability and resistivity, speed and slowness, etc.). When compared to two existing McMC schemes, the computational effort was divided by a factor of 12.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jiangjiang; Li, Weixuan; Lin, Guang

In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters.more » To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.« less

Hybrid computer optimization of systems with random parameters

NASA Technical Reports Server (NTRS)

White, R. C., Jr.

1972-01-01

A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

LRFD Resistance Factor Calibration for Axially Loaded Drilled Shafts in the Las Vegas Valley

DOT National Transportation Integrated Search

2016-07-19

Resistance factors for LRFD of axially loaded drilled shafts in the Las Vegas Valley are calibrated using data from 41 field load tests. In addition to the traditional implementation of Monte Carlo (MC) simulations for calibration, a more robust tech...

The effect of voxel size on dose distribution in Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Yani, Sitti; Dirgayussa, I. Gde E.; Rhani, Moh. Fadhillah; Haryanto, Freddy; Arif, Idam

2015-09-01

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. The MC code system (especially DOSXYZnrc) has been used to investigate the different voxel (volume elements) sizes effect on the accuracy of dose distributions. To investigate this effect on dosimetry parameters, calculations were made with three different voxel sizes. The effects were investigated with dose distribution calculations for seven voxel sizes: 1 × 1 × 0.1 cm3, 1 × 1 × 0.5 cm3, and 1 × 1 × 0.8 cm3. The 1 × 109 histories were simulated in order to get statistical uncertainties of 2%. This simulation takes about 9-10 hours to complete. Measurements are made with field sizes 10 × 10 cm2 for the 6 MV photon beams with Gaussian intensity distribution FWHM 0.1 cm and SSD 100.1 cm. MC simulated and measured dose distributions in a water phantom. The output of this simulation i.e. the percent depth dose and dose profile in dmax from the three sets of calculations are presented and comparisons are made with the experiment data from TTSH (Tan Tock Seng Hospital, Singapore) in 0-5 cm depth. Dose that scored in voxels is a volume averaged estimate of the dose at the center of a voxel. The results in this study show that the difference between Monte Carlo simulation and experiment data depend on the voxel size both for percent depth dose (PDD) and profile dose. PDD scan on Z axis (depth) of water phantom, the big difference obtain in the voxel size 1 × 1 × 0.8 cm3 about 17%. In this study, the profile dose focused on high gradient dose area. Profile dose scan on Y axis and the big difference get in the voxel size 1 × 1 × 0.1 cm3 about 12%. This study demonstrated that the arrange voxel in Monte Carlo simulation becomes important.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

NASA Astrophysics Data System (ADS)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods

DOE PAGES

Liu, Peigui; Elshall, Ahmed S.; Ye, Ming; ...

2016-02-05

Evaluating marginal likelihood is the most critical and computationally expensive task, when conducting Bayesian model averaging to quantify parametric and model uncertainties. The evaluation is commonly done by using Laplace approximations to evaluate semianalytical expressions of the marginal likelihood or by using Monte Carlo (MC) methods to evaluate arithmetic or harmonic mean of a joint likelihood function. This study introduces a new MC method, i.e., thermodynamic integration, which has not been attempted in environmental modeling. Instead of using samples only from prior parameter space (as in arithmetic mean evaluation) or posterior parameter space (as in harmonic mean evaluation), the thermodynamicmore » integration method uses samples generated gradually from the prior to posterior parameter space. This is done through a path sampling that conducts Markov chain Monte Carlo simulation with different power coefficient values applied to the joint likelihood function. The thermodynamic integration method is evaluated using three analytical functions by comparing the method with two variants of the Laplace approximation method and three MC methods, including the nested sampling method that is recently introduced into environmental modeling. The thermodynamic integration method outperforms the other methods in terms of their accuracy, convergence, and consistency. The thermodynamic integration method is also applied to a synthetic case of groundwater modeling with four alternative models. The application shows that model probabilities obtained using the thermodynamic integration method improves predictive performance of Bayesian model averaging. As a result, the thermodynamic integration method is mathematically rigorous, and its MC implementation is computationally general for a wide range of environmental problems.« less

Poster — Thur Eve — 47: Monte Carlo Simulation of Scp, Sc and Sp

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhan, Lixin; Jiang, Runqing; Osei, Ernest K.

The in-water output ratio (Scp), in-air output ratio (Sc), and phantom scattering factor (Sp) are important parameters for radiotherapy dose calculation. Experimentally, Scp is obtained by measuring the dose rate ratio in water phantom, and Sc the water Kerma rate ratio in air. There is no method that allows direct measurement of Sp. Monte Carlo (MC) method has been used to simulate Scp and Sc in literatures, similar to experimental setup, but no MC direct simulation of Sp available yet to the best of our knowledge. We propose in this report a method of performing direct MC simulation of Sp.more » Starting from the definition, we derived that Sp of a clinical photon beam can be approximated by the ratio of the dose rates contributed from the primary beam for a given field size to the reference field size. Since only the primary beam is used, any Linac head scattering should be excluded from the simulation, which can be realized by using the incident electron as a scoring parameter for MU. We performed MC simulations for Scp, Sc and Sp. Scp matches well with golden beam data. Sp obtained by the proposed method agrees well with what is obtained using the traditional method, Sp=Scp/Sc. Since the smaller the field size, the more the primary beam dominates, our Sp simulation method is accurate for small field. By analyzing the calculated data, we found that this method can be used with no problem for large fields. The difference it introduced is clinically insignificant.« less

Dosimetry applications in GATE Monte Carlo toolkit.

PubMed

Papadimitroulas, Panagiotis

2017-09-01

Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Shielding evaluation for solar particle events using MCNPX, PHITS and OLTARIS codes

NASA Astrophysics Data System (ADS)

Aghara, S. K.; Sriprisan, S. I.; Singleterry, R. C.; Sato, T.

2015-01-01

Detailed analyses of Solar Particle Events (SPE) were performed to calculate primary and secondary particle spectra behind aluminum, at various thicknesses in water. The simulations were based on Monte Carlo (MC) radiation transport codes, MCNPX 2.7.0 and PHITS 2.64, and the space radiation analysis website called OLTARIS (On-Line Tool for the Assessment of Radiation in Space) version 3.4 (uses deterministic code, HZETRN, for transport). The study is set to investigate the impact of SPEs spectra transporting through 10 or 20 g/cm2 Al shield followed by 30 g/cm2 of water slab. Four historical SPE events were selected and used as input source spectra particle differential spectra for protons, neutrons, and photons are presented. The total particle fluence as a function of depth is presented. In addition to particle flux, the dose and dose equivalent values are calculated and compared between the codes and with the other published results. Overall, the particle fluence spectra from all three codes show good agreement with the MC codes showing closer agreement compared to the OLTARIS results. The neutron particle fluence from OLTARIS is lower than the results from MC codes at lower energies (E < 100 MeV). Based on mean square difference analysis the results from MCNPX and PHITS agree better for fluence, dose and dose equivalent when compared to OLTARIS results.

Monte Carlo modeling of ultrasound probes for image guided radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bazalova-Carter, Magdalena, E-mail: bazalova@uvic.ca; Schlosser, Jeffrey; Chen, Josephine

2015-10-15

Purpose: To build Monte Carlo (MC) models of two ultrasound (US) probes and to quantify the effect of beam attenuation due to the US probes for radiation therapy delivered under real-time US image guidance. Methods: MC models of two Philips US probes, an X6-1 matrix-array transducer and a C5-2 curved-array transducer, were built based on their megavoltage (MV) CT images acquired in a Tomotherapy machine with a 3.5 MV beam in the EGSnrc, BEAMnrc, and DOSXYZnrc codes. Mass densities in the probes were assigned based on an electron density calibration phantom consisting of cylinders with mass densities between 0.2 andmore » 8.0 g/cm{sup 3}. Beam attenuation due to the US probes in horizontal (for both probes) and vertical (for the X6-1 probe) orientation was measured in a solid water phantom for 6 and 15 MV (15 × 15) cm{sup 2} beams with a 2D ionization chamber array and radiographic films at 5 cm depth. The MC models of the US probes were validated by comparison of the measured dose distributions and dose distributions predicted by MC. Attenuation of depth dose in the (15 × 15) cm{sup 2} beams and small circular beams due to the presence of the probes was assessed by means of MC simulations. Results: The 3.5 MV CT number to mass density calibration curve was found to be linear with R{sup 2} > 0.99. The maximum mass densities in the X6-1 and C5-2 probes were found to be 4.8 and 5.2 g/cm{sup 3}, respectively. Dose profile differences between MC simulations and measurements of less than 3% for US probes in horizontal orientation were found, with the exception of the penumbra region. The largest 6% dose difference was observed in dose profiles of the X6-1 probe placed in vertical orientation, which was attributed to inadequate modeling of the probe cable. Gamma analysis of the simulated and measured doses showed that over 96% of measurement points passed the 3%/3 mm criteria for both probes placed in horizontal orientation and for the X6-1 probe in vertical orientation. The X6-1 probe in vertical orientation caused the highest attenuation of the 6 and 15 MV beams, which at 10 cm depth accounted for 33% and 43% decrease compared to the respective (15 × 15) cm{sup 2} open fields. The C5-2 probe in horizontal orientation, on the other hand, caused a dose increase of 10% and 53% for the 6 and 15 MV beams, respectively, in the buildup region at 0.5 cm depth. For the X6-1 probe in vertical orientation, the dose at 5 cm depth for the 3-cm diameter 6 MV and 5-cm diameter 15 MV beams was attenuated compared to the corresponding open fields to a greater degree by 65% and 43%, respectively. Conclusions: MC models of two US probes used for real-time image guidance during radiotherapy have been built. Due to the high beam attenuation of the US probes, the authors generally recommend avoiding delivery of treatment beams that intersect the probe. However, the presented MC models can be effectively integrated into US-guided radiotherapy treatment planning in cases for which beam avoidance is not practical due to anatomy geometry.« less

Application of the Monte Carlo method to estimate doses due to neutron activation of different materials in a nuclear reactor

NASA Astrophysics Data System (ADS)

Ródenas, José

2017-11-01

All materials exposed to some neutron flux can be activated independently of the kind of the neutron source. In this study, a nuclear reactor has been considered as neutron source. In particular, the activation of control rods in a BWR is studied to obtain the doses produced around the storage pool for irradiated fuel of the plant when control rods are withdrawn from the reactor and installed into this pool. It is very important to calculate these doses because they can affect to plant workers in the area. The MCNP code based on the Monte Carlo method has been applied to simulate activation reactions produced in the control rods inserted into the reactor. Obtained activities are introduced as input into another MC model to estimate doses produced by them. The comparison of simulation results with experimental measurements allows the validation of developed models. The developed MC models have been also applied to simulate the activation of other materials, such as components of a stainless steel sample introduced into a training reactors. These models, once validated, can be applied to other situations and materials where a neutron flux can be found, not only nuclear reactors. For instance, activation analysis with an Am-Be source, neutrography techniques in both medical applications and non-destructive analysis of materials, civil engineering applications using a Troxler, analysis of materials in decommissioning of nuclear power plants, etc.

Ion channeling study of defects in compound crystals using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Turos, A.; Jozwik, P.; Nowicki, L.; Sathish, N.

2014-08-01

Ion channeling is a well-established technique for determination of structural properties of crystalline materials. Defect depth profiles have been usually determined basing on the two-beam model developed by Bøgh (1968) [1]. As long as the main research interest was focused on single element crystals it was considered as sufficiently accurate. New challenge emerged with growing technological importance of compound single crystals and epitaxial heterostructures. Overlap of partial spectra due to different sublattices and formation of complicated defect structures makes the two beam method hardly applicable. The solution is provided by Monte Carlo computer simulations. Our paper reviews principal aspects of this approach and the recent developments in the McChasy simulation code. The latter made it possible to distinguish between randomly displaced atoms (RDA) and extended defects (dislocations, loops, etc.). Hence, complex defect structures can be characterized by the relative content of these two components. The next refinement of the code consists of detailed parameterization of dislocations and dislocation loops. Defect profiles for variety of compound crystals (GaN, ZnO, SrTiO3) have been measured and evaluated using the McChasy code. Damage accumulation curves for RDA and extended defects revealed non monotonous defect buildup with some characteristic steps. Transition to each stage is governed by the different driving force. As shown by the complementary high resolution XRD measurements lattice strain plays here the crucial role and can be correlated with the concentration of extended defects.

Re-186 and Sm-153 dosimetry based on scintigraphic imaging data in skeletal metastasis palliative treatment and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Andreou, M.; Lagopati, N.; Lyra, M.

2011-09-01

Optimum treatment planning of patients suffering from painful skeletal metastases requires accurate calculations concerning absorbed dose in metastatic lesions and critical organs, such as red marrow. Delivering high doses to tumor cells while limiting radiation dose to normal tissue, is the key for successful palliation treatment. The aim of this study is to compare the dosimetric calculations, obtained by Monte Carlo (MC) simulation and the MIRDOSE model, in therapeutic schemes of skeleton metastatic lesions, with Rhenium-186 (Sn) -HEDP and Samarium-153 -EDTMP. A bolus injection of 1295 MBq (35mCi) Re-186- HEDP was infused in 11 patients with multiple skeletal metastases. The administered dose for the 8 patients who received Sm-153 was 1 mCi /kg. Planar scintigraphic images for the two groups of patients were obtained, 24 h, 48 h and 72 h post injection, by an Elscint Apex SPX gamma camera. The images were processed, utilizing ROI quantitative methods, to determine residence times and radionuclide uptakes. Dosimetric calculations were performed using the patient specific scintigraphic data by the MIRDOSE3 code of MIRD. Also, MCNPX was employed, simulating the distribution of the radioisotope in the ROI and calculating the absorbed doses in the metastatic lesion, and in critical organs. Summarizing, there is a good agreement between the results, derived from the two pathways, the patient specific and the mathematical, with a deviation of less than 9% for planar scintigraphic data compared to MC, for both radiopharmaceuticals.

Solution processed deposition of electron transport layers on perovskite crystal surface-A modeling based study

NASA Astrophysics Data System (ADS)

Mortuza, S. M.; Taufique, M. F. N.; Banerjee, Soumik

2017-02-01

The power conversion efficiency (PCE) of planar perovskite solar cells (PSCs) has reached up to ∼20%. However, structural and chemicals defects that lead to hysteresis in the perovskite based thin film pose challenges. Recent work has shown that thin films of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) deposited on the photo absorption layer, using solution processing techniques, minimize surface pin holes and defects thereby increasing the PCE. We developed and employed a multiscale model based on molecular dynamics (MD) and kinetic Monte Carlo (kMC) to establish a relationship between deposition rate and surface coverage on perovskite surface. The MD simulations of PCBMs dispersed in chlorobenzene, sandwiched between (110) perovskite substrates, indicate that PCBMs are deposited through anchoring of the oxygen atom of carbonyl group to the exposed lead (Pb) atom of (110) perovskite surface. Based on rates of distinct deposition events calculated from MD, kMC simulations were run to determine surface coverage at much larger time and length scales than accessible by MD alone. Based on the model, a generic relationship is established between deposition rate of PCBMs and surface coverage on perovskite crystal. The study also provides detailed insights into the morphology of the deposited film.

An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.

PubMed

Tian, Zhen; Li, Yongbao; Folkerts, Michael; Shi, Feng; Jiang, Steve B; Jia, Xun

2015-10-21

Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum dose difference within 1.7%. The maximum relative difference of output factors was within 0.5%. Over 98.5% passing rate was achieved in 3D gamma-index tests with 2%/2 mm criteria in both an IMRT prostate patient case and a head-and-neck case. These results demonstrated the efficacy of our model in terms of accurately representing a reference phase-space file. We have also tested the efficiency gain of our source model over our previously developed phase-space-let file source model. The overall efficiency of dose calculation was found to be improved by ~1.3-2.2 times in water and patient cases using our analytical model.

Two-dimensional molecular line transfer for a cometary coma

NASA Astrophysics Data System (ADS)

Szutowicz, S.

2017-09-01

In the proposed axisymmetric model of the cometary coma the gas density profile is described by an angular density function. Three methods for treating two-dimensional radiative transfer are compared: the Large Velocity Gradient (LVG) (the Sobolev method), Accelerated Lambda Iteration (ALI) and accelerated Monte Carlo (MC).

Microsolvation of Cl anion by water clusters: Pertubative Monte Carlo simulations using a hybrid HF/MM potential

NASA Astrophysics Data System (ADS)

Truong, Thanh N.; Stefanovich, Eugene V.

1997-05-01

We present a study of micro-solvation of Cl anion by water clusters of the size up to seven molecules using a perturbative Monte Carlo approach with a hybrid HF/MM potential. In this approach, a perturbation theory was used to avoid performing full SCF calculations at every Monte Carlo step. In this study, the anion is treated quantum mechanically at the HF/6-31G ∗ level of theory while interactions between solvent waters are presented by the TIP3P potential force field. Analysis on the solvent induced dipole moment of the ion indicates that the Cl anion resides most of the time on the surface of the clusters. Accuracy of the perturbative MC approach is also discussed.

EDITORIAL: International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification

NASA Astrophysics Data System (ADS)

Verhaegen, Frank; Seuntjens, Jan

2008-03-01

Monte Carlo particle transport techniques offer exciting tools for radiotherapy research, where they play an increasingly important role. Topics of research related to clinical applications range from treatment planning, motion and registration studies, brachytherapy, verification imaging and dosimetry. The International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification took place in a hotel in Montreal in French Canada, from 29 May-1 June 2007, and was the third workshop to be held on a related topic, which now seems to have become a tri-annual event. About one hundred workers from many different countries participated in the four-day meeting. Seventeen experts in the field were invited to review topics and present their latest work. About half of the audience was made up by young graduate students. In a very full program, 57 papers were presented and 10 posters were on display during most of the meeting. On the evening of the third day a boat trip around the island of Montreal allowed participants to enjoy the city views, and to sample the local cuisine. The topics covered at the workshop included the latest developments in the most popular Monte Carlo transport algorithms, fast Monte Carlo, statistical issues, source modeling, MC treatment planning, modeling of imaging devices for treatment verification, registration and deformation of images and a sizeable number of contributions on brachytherapy. In this volume you will find 27 short papers resulting from the workshop on a variety of topics, some of them on very new stuff such as graphics processing units for fast computing, PET modeling, dual-energy CT, calculations in dynamic phantoms, tomotherapy devices, . . . . We acknowledge the financial support of the National Cancer Institute of Canada, the Institute of Cancer Research of the Canadian Institutes of Health Research, the Association Québécoise des Physicien(ne)s Médicaux Clinique, the Institute of Physics, and MedicalPhysicsWeb. At McGill we thank the following departments for support: the Cancer Axis of the Research Institute of the McGill University Health Center, the Faculties of Medicine and Science, the Departments of Oncology and Physics and the Medical Physics Unit. The following companies are thanked: TomoTherapy and Standard Imaging. The American Association of Physicists in Medicine and the International Atomic Energy Agency are gratefully acknowledged for endorsing the meeting. A final word of thanks goes out to all of those who contributed to the successful Workshop: first of all our administrative assistant Ms Margery Knewstubb, the website developer Dr François DeBlois, the two heads of the logistics team, Ms Emily Poon and Ms Emily Heath, our local medical physics students and staff, the IOP staff and the authors who shared their new and exciting work with us. Editors: Frank Verhaegen and Jan Seuntjens (McGill University) Associate editors: Luc Beaulieu, Iwan Kawrakow, Tony Popescu and David Rogers

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Souris, K; Sterpin, E; Lee, J

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than onemore » minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)« less

Methods for calculating the absolute entropy and free energy of biological systems based on ideas from polymer physics.

PubMed

Meirovitch, Hagai

2010-01-01

The commonly used simulation techniques, Metropolis Monte Carlo (MC) and molecular dynamics (MD) are of a dynamical type which enables one to sample system configurations i correctly with the Boltzmann probability, P(i)(B), while the value of P(i)(B) is not provided directly; therefore, it is difficult to obtain the absolute entropy, S approximately -ln P(i)(B), and the Helmholtz free energy, F. With a different simulation approach developed in polymer physics, a chain is grown step-by-step with transition probabilities (TPs), and thus their product is the value of the construction probability; therefore, the entropy is known. Because all exact simulation methods are equivalent, i.e. they lead to the same averages and fluctuations of physical properties, one can treat an MC or MD sample as if its members have rather been generated step-by-step. Thus, each configuration i of the sample can be reconstructed (from nothing) by calculating the TPs with which it could have been constructed. This idea applies also to bulk systems such as fluids or magnets. This approach has led earlier to the "local states" (LS) and the "hypothetical scanning" (HS) methods, which are approximate in nature. A recent development is the hypothetical scanning Monte Carlo (HSMC) (or molecular dynamics, HSMD) method which is based on stochastic TPs where all interactions are taken into account. In this respect, HSMC(D) can be viewed as exact and the only approximation involved is due to insufficient MC(MD) sampling for calculating the TPs. The validity of HSMC has been established by applying it first to liquid argon, TIP3P water, self-avoiding walks (SAW), and polyglycine models, where the results for F were found to agree with those obtained by other methods. Subsequently, HSMD was applied to mobile loops of the enzymes porcine pancreatic alpha-amylase and acetylcholinesterase in explicit water, where the difference in F between the bound and free states of the loop was calculated. Currently, HSMD is being extended for calculating the absolute and relative free energies of ligand-enzyme binding. We describe the whole approach and discuss future directions. 2009 John Wiley & Sons, Ltd.

Methods for modeling non-equilibrium degenerate statistics and quantum-confined scattering in 3D ensemble Monte Carlo transport simulations

NASA Astrophysics Data System (ADS)

Crum, Dax M.; Valsaraj, Amithraj; David, John K.; Register, Leonard F.; Banerjee, Sanjay K.

2016-12-01

Particle-based ensemble semi-classical Monte Carlo (MC) methods employ quantum corrections (QCs) to address quantum confinement and degenerate carrier populations to model tomorrow's ultra-scaled metal-oxide-semiconductor-field-effect-transistors. Here, we present the most complete treatment of quantum confinement and carrier degeneracy effects in a three-dimensional (3D) MC device simulator to date, and illustrate their significance through simulation of n-channel Si and III-V FinFETs. Original contributions include our treatment of far-from-equilibrium degenerate statistics and QC-based modeling of surface-roughness scattering, as well as considering quantum-confined phonon and ionized-impurity scattering in 3D. Typical MC simulations approximate degenerate carrier populations as Fermi distributions to model the Pauli-blocking (PB) of scattering to occupied final states. To allow for increasingly far-from-equilibrium non-Fermi carrier distributions in ultra-scaled and III-V devices, we instead generate the final-state occupation probabilities used for PB by sampling the local carrier populations as function of energy and energy valley. This process is aided by the use of fractional carriers or sub-carriers, which minimizes classical carrier-carrier scattering intrinsically incompatible with degenerate statistics. Quantum-confinement effects are addressed through quantum-correction potentials (QCPs) generated from coupled Schrödinger-Poisson solvers, as commonly done. However, we use these valley- and orientation-dependent QCPs not just to redistribute carriers in real space, or even among energy valleys, but also to calculate confinement-dependent phonon, ionized-impurity, and surface-roughness scattering rates. FinFET simulations are used to illustrate the contributions of each of these QCs. Collectively, these quantum effects can substantially reduce and even eliminate otherwise expected benefits of considered In0.53Ga0.47 As FinFETs over otherwise identical Si FinFETs despite higher thermal velocities in In0.53Ga0.47 As. It also may be possible to extend these basic uses of QCPs, however calculated, to still more computationally efficient drift-diffusion and hydrodynamic simulations, and the basic concepts even to compact device modeling.

A Monte Carlo calculation model of electronic portal imaging device for transit dosimetry through heterogeneous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Jihyung; Jung, Jae Won, E-mail: jungj@ecu.edu; Kim, Jong Oh

2016-05-15

Purpose: To develop and evaluate a fast Monte Carlo (MC) dose calculation model of electronic portal imaging device (EPID) based on its effective atomic number modeling in the XVMC code. Methods: A previously developed EPID model, based on the XVMC code by density scaling of EPID structures, was modified by additionally considering effective atomic number (Z{sub eff}) of each structure and adopting a phase space file from the EGSnrc code. The model was tested under various homogeneous and heterogeneous phantoms and field sizes by comparing the calculations in the model with measurements in EPID. In order to better evaluate themore » model, the performance of the XVMC code was separately tested by comparing calculated dose to water with ion chamber (IC) array measurement in the plane of EPID. Results: In the EPID plane, calculated dose to water by the code showed agreement with IC measurements within 1.8%. The difference was averaged across the in-field regions of the acquired profiles for all field sizes and phantoms. The maximum point difference was 2.8%, affected by proximity of the maximum points to penumbra and MC noise. The EPID model showed agreement with measured EPID images within 1.3%. The maximum point difference was 1.9%. The difference dropped from the higher value of the code by employing the calibration that is dependent on field sizes and thicknesses for the conversion of calculated images to measured images. Thanks to the Z{sub eff} correction, the EPID model showed a linear trend of the calibration factors unlike those of the density-only-scaled model. The phase space file from the EGSnrc code sharpened penumbra profiles significantly, improving agreement of calculated profiles with measured profiles. Conclusions: Demonstrating high accuracy, the EPID model with the associated calibration system may be used for in vivo dosimetry of radiation therapy. Through this study, a MC model of EPID has been developed, and their performance has been rigorously investigated for transit dosimetry.« less

Monte Carlo simulation of MOSFET detectors for high-energy photon beams using the PENELOPE code

NASA Astrophysics Data System (ADS)

Panettieri, Vanessa; Amor Duch, Maria; Jornet, Núria; Ginjaume, Mercè; Carrasco, Pablo; Badal, Andreu; Ortega, Xavier; Ribas, Montserrat

2007-01-01

The aim of this work was the Monte Carlo (MC) simulation of the response of commercially available dosimeters based on metal oxide semiconductor field effect transistors (MOSFETs) for radiotherapeutic photon beams using the PENELOPE code. The studied Thomson&Nielsen TN-502-RD MOSFETs have a very small sensitive area of 0.04 mm2 and a thickness of 0.5 µm which is placed on a flat kapton base and covered by a rounded layer of black epoxy resin. The influence of different metallic and Plastic water™ build-up caps, together with the orientation of the detector have been investigated for the specific application of MOSFET detectors for entrance in vivo dosimetry. Additionally, the energy dependence of MOSFET detectors for different high-energy photon beams (with energy >1.25 MeV) has been calculated. Calculations were carried out for simulated 6 MV and 18 MV x-ray beams generated by a Varian Clinac 1800 linear accelerator, a Co-60 photon beam from a Theratron 780 unit, and monoenergetic photon beams ranging from 2 MeV to 10 MeV. The results of the validation of the simulated photon beams show that the average difference between MC results and reference data is negligible, within 0.3%. MC simulated results of the effect of the build-up caps on the MOSFET response are in good agreement with experimental measurements, within the uncertainties. In particular, for the 18 MV photon beam the response of the detectors under a tungsten cap is 48% higher than for a 2 cm Plastic water™ cap and approximately 26% higher when a brass cap is used. This effect is demonstrated to be caused by positron production in the build-up caps of higher atomic number. This work also shows that the MOSFET detectors produce a higher signal when their rounded side is facing the beam (up to 6%) and that there is a significant variation (up to 50%) in the response of the MOSFET for photon energies in the studied energy range. All the results have shown that the PENELOPE code system can successfully reproduce the response of a detector with such a small active area.

Monte Carlo simulation of MOSFET detectors for high-energy photon beams using the PENELOPE code.

PubMed

Panettieri, Vanessa; Duch, Maria Amor; Jornet, Núria; Ginjaume, Mercè; Carrasco, Pablo; Badal, Andreu; Ortega, Xavier; Ribas, Montserrat

2007-01-07

The aim of this work was the Monte Carlo (MC) simulation of the response of commercially available dosimeters based on metal oxide semiconductor field effect transistors (MOSFETs) for radiotherapeutic photon beams using the PENELOPE code. The studied Thomson&Nielsen TN-502-RD MOSFETs have a very small sensitive area of 0.04 mm(2) and a thickness of 0.5 microm which is placed on a flat kapton base and covered by a rounded layer of black epoxy resin. The influence of different metallic and Plastic water build-up caps, together with the orientation of the detector have been investigated for the specific application of MOSFET detectors for entrance in vivo dosimetry. Additionally, the energy dependence of MOSFET detectors for different high-energy photon beams (with energy >1.25 MeV) has been calculated. Calculations were carried out for simulated 6 MV and 18 MV x-ray beams generated by a Varian Clinac 1800 linear accelerator, a Co-60 photon beam from a Theratron 780 unit, and monoenergetic photon beams ranging from 2 MeV to 10 MeV. The results of the validation of the simulated photon beams show that the average difference between MC results and reference data is negligible, within 0.3%. MC simulated results of the effect of the build-up caps on the MOSFET response are in good agreement with experimental measurements, within the uncertainties. In particular, for the 18 MV photon beam the response of the detectors under a tungsten cap is 48% higher than for a 2 cm Plastic water cap and approximately 26% higher when a brass cap is used. This effect is demonstrated to be caused by positron production in the build-up caps of higher atomic number. This work also shows that the MOSFET detectors produce a higher signal when their rounded side is facing the beam (up to 6%) and that there is a significant variation (up to 50%) in the response of the MOSFET for photon energies in the studied energy range. All the results have shown that the PENELOPE code system can successfully reproduce the response of a detector with such a small active area.

Acceptance and commissioning of a treatment planning system based on Monte Carlo calculations.

PubMed

Lopez-Tarjuelo, J; Garcia-Molla, R; Juan-Senabre, X J; Quiros-Higueras, J D; Santos-Serra, A; de Marco-Blancas, N; Calzada-Feliu, S

2014-04-01

The Monaco Treatment Planning System (TPS), based on a virtual energy fluence model of the photon beam head components of the linac and a dose computation engine made with Monte Carlo (MC) algorithm X-Ray Voxel MC (XVMC), has been tested before being put into clinical use. An Elekta Synergy with 6 MV was characterized using routine equipment. After the machine's model was installed, a set of functionality, geometric, dosimetric and data transfer tests were performed. The dosimetric tests included dose calculations in water, heterogeneous phantoms and Intensity Modulated Radiation Therapy (IMRT) verifications. Data transfer tests were run for every imaging device, TPS and the electronic medical record linked to Monaco. Functionality and geometric tests were run properly. Dose calculations in water were in accordance with measurements so that, in 95% of cases, differences were up to 1.9%. Dose calculation in heterogeneous media showed expected results found in the literature. IMRT verification results with an ionization chamber led to dose differences lower than 2.5% for points inside a standard gradient. When an 2-D array was used, all the fields passed the g (3%, 3 mm) test with a percentage of succeeding points between 90% and 95%, of which the majority of the mentioned fields had a percentage of succeeding points between 95% and 100%. Data transfer caused problems that had to be solved by means of changing our workflow. In general, tests led to satisfactory results. Monaco performance complied with published international recommendations and scored highly in the dosimetric ambit. However, the problems detected when the TPS was put to work together with our current equipment showed that this kind of product must be completely commissioned, without neglecting data workflow, before treating the first patient.

Comprehensive evaluations of cone-beam CT dose in image-guided radiation therapy via GPU-based Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Montanari, Davide; Scolari, Enrica; Silvestri, Chiara; Jiang Graves, Yan; Yan, Hao; Cervino, Laura; Rice, Roger; Jiang, Steve B.; Jia, Xun

2014-03-01

Cone beam CT (CBCT) has been widely used for patient setup in image-guided radiation therapy (IGRT). Radiation dose from CBCT scans has become a clinical concern. The purposes of this study are (1) to commission a graphics processing unit (GPU)-based Monte Carlo (MC) dose calculation package gCTD for Varian On-Board Imaging (OBI) system and test the calculation accuracy, and (2) to quantitatively evaluate CBCT dose from the OBI system in typical IGRT scan protocols. We first conducted dose measurements in a water phantom. X-ray source model parameters used in gCTD are obtained through a commissioning process. gCTD accuracy is demonstrated by comparing calculations with measurements in water and in CTDI phantoms. Twenty-five brain cancer patients are used to study dose in a standard-dose head protocol, and 25 prostate cancer patients are used to study dose in pelvis protocol and pelvis spotlight protocol. Mean dose to each organ is calculated. Mean dose to 2% voxels that have the highest dose is also computed to quantify the maximum dose. It is found that the mean dose value to an organ varies largely among patients. Moreover, dose distribution is highly non-homogeneous inside an organ. The maximum dose is found to be 1-3 times higher than the mean dose depending on the organ, and is up to eight times higher for the entire body due to the very high dose region in bony structures. High computational efficiency has also been observed in our studies, such that MC dose calculation time is less than 5 min for a typical case.

Simultaneous 99mtc/111in spect reconstruction using accelerated convolution-based forced detection monte carlo

NASA Astrophysics Data System (ADS)

Karamat, Muhammad I.; Farncombe, Troy H.

2015-10-01

Simultaneous multi-isotope Single Photon Emission Computed Tomography (SPECT) imaging has a number of applications in cardiac, brain, and cancer imaging. The major concern however, is the significant crosstalk contamination due to photon scatter between the different isotopes. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc and 111In. We have developed an iterative image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. Our approach uses an accelerated Monte Carlo (MC) technique for the forward projection step in an iterative reconstruction algorithm. The MC estimated scatter contamination of a radionuclide contained in a given projection view is then used to compensate for the photon contamination in the acquisition window of other nuclide. We use a modified ordered subset-expectation maximization (OS-EM) algorithm named simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique was also evaluated by reconstruction of experimentally acquired phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of contrast recovery and uniformity of object background compared to alternative reconstruction methods implementing alternative scatter correction schemes (i.e., triple energy window or separately acquired projection data). In this study the evaluation is based on the quality of reconstructed images and activity estimated using Sim-OSEM. In order to quantitate the possible improvement in spatial resolution and signal to noise ratio (SNR) observed in this study, further simulation and experimental studies are required.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kieselmann, J; Bartzsch, S; Oelfke, U

Purpose: Microbeam Radiation Therapy is a preclinical method in radiation oncology that modulates radiation fields on a micrometre scale. Dose calculation is challenging due to arising dose gradients and therapeutically important dose ranges. Monte Carlo (MC) simulations, often used as gold standard, are computationally expensive and hence too slow for the optimisation of treatment parameters in future clinical applications. On the other hand, conventional kernel based dose calculation leads to inaccurate results close to material interfaces. The purpose of this work is to overcome these inaccuracies while keeping computation times low. Methods: A point kernel superposition algorithm is modified tomore » account for tissue inhomogeneities. Instead of conventional ray tracing approaches, methods from differential geometry are applied and the space around the primary photon interaction is locally warped. The performance of this approach is compared to MC simulations and a simple convolution algorithm (CA) for two different phantoms and photon spectra. Results: While peak doses of all dose calculation methods agreed within less than 4% deviations, the proposed approach surpassed a simple convolution algorithm in accuracy by a factor of up to 3 in the scatter dose. In a treatment geometry similar to possible future clinical situations differences between Monte Carlo and the differential geometry algorithm were less than 3%. At the same time the calculation time did not exceed 15 minutes. Conclusion: With the developed method it was possible to improve the dose calculation based on the CA method with respect to accuracy especially at sharp tissue boundaries. While the calculation is more extensive than for the CA method and depends on field size, the typical calculation time for a 20×20 mm{sup 2} field on a 3.4 GHz and 8 GByte RAM processor remained below 15 minutes. Parallelisation and optimisation of the algorithm could lead to further significant calculation time reductions.« less

Self-learning Monte Carlo with deep neural networks

NASA Astrophysics Data System (ADS)

Shen, Huitao; Liu, Junwei; Fu, Liang

2018-05-01

The self-learning Monte Carlo (SLMC) method is a general algorithm to speedup MC simulations. Its efficiency has been demonstrated in various systems by introducing an effective model to propose global moves in the configuration space. In this paper, we show that deep neural networks can be naturally incorporated into SLMC, and without any prior knowledge can learn the original model accurately and efficiently. Demonstrated in quantum impurity models, we reduce the complexity for a local update from O (β2) in Hirsch-Fye algorithm to O (β lnβ ) , which is a significant speedup especially for systems at low temperatures.

Monte Carlo simulation of particle-induced bit upsets

NASA Astrophysics Data System (ADS)

Wrobel, Frédéric; Touboul, Antoine; Vaillé, Jean-Roch; Boch, Jérôme; Saigné, Frédéric

2017-09-01

We investigate the issue of radiation-induced failures in electronic devices by developing a Monte Carlo tool called MC-Oracle. It is able to transport the particles in device, to calculate the energy deposited in the sensitive region of the device and to calculate the transient current induced by the primary particle and the secondary particles produced during nuclear reactions. We compare our simulation results with SRAM experiments irradiated with neutrons, protons and ions. The agreement is very good and shows that it is possible to predict the soft error rate (SER) for a given device in a given environment.

Evaluation of dosimetric properties of shielding disk used in intraoperative electron radiotherapy: A Monte Carlo study.

PubMed

Robatjazi, Mostafa; Baghani, Hamid Reza; Mahdavic, Seied Rabi; Felici, Giuseppe

2018-05-01

A shielding disk is used for IOERT procedures to absorb radiation behind the target and protect underlying healthy tissues. Setup variation of shielding disk can affect the corresponding in-vivo dose distribution. In this study, the changes of dosimetric parameters due to the disk setup variations is evaluated using EGSnrc Monte Carlo (MC) code. The results can help treatment team to decide about the level of accuracy in the setup procedure and delivered dose to the target volume during IOERT. Copyright © 2018 Elsevier Ltd. All rights reserved.

CosmoSIS: A system for MC parameter estimation

DOE PAGES

Bridle, S.; Dodelson, S.; Jennings, E.; ...

2015-12-23

CosmoSIS is a modular system for cosmological parameter estimation, based on Markov Chain Monte Carlo and related techniques. It provides a series of samplers, which drive the exploration of the parameter space, and a series of modules, which calculate the likelihood of the observed data for a given physical model, determined by the location of a sample in the parameter space. While CosmoSIS ships with a set of modules that calculate quantities of interest to cosmologists, there is nothing about the framework itself, nor in the Markov Chain Monte Carlo technique, that is specific to cosmology. Thus CosmoSIS could bemore » used for parameter estimation problems in other fields, including HEP. This paper describes the features of CosmoSIS and show an example of its use outside of cosmology. Furthermore, it also discusses how collaborative development strategies differ between two different communities: that of HEP physicists, accustomed to working in large collaborations, and that of cosmologists, who have traditionally not worked in large groups.« less

Contrast of Backscattered Electron SEM Images of Nanoparticles on Substrates with Complex Structure

PubMed Central

Müller, Erich; Fritsch-Decker, Susanne; Hettler, Simon; Störmer, Heike; Weiss, Carsten; Gerthsen, Dagmar

2017-01-01

This study is concerned with backscattered electron scanning electron microscopy (BSE SEM) contrast of complex nanoscaled samples which consist of SiO2 nanoparticles (NPs) deposited on indium-tin-oxide covered bulk SiO2 and glassy carbon substrates. BSE SEM contrast of NPs is studied as function of the primary electron energy and working distance. Contrast inversions are observed which prevent intuitive interpretation of NP contrast in terms of material contrast. Experimental data is quantitatively compared with Monte-Carlo- (MC-) simulations. Quantitative agreement between experimental data and MC-simulations is obtained if the transmission characteristics of the annular semiconductor detector are taken into account. MC-simulations facilitate the understanding of NP contrast inversions and are helpful to derive conditions for optimum material and topography contrast. PMID:29109816

Contrast of Backscattered Electron SEM Images of Nanoparticles on Substrates with Complex Structure.

PubMed

Kowoll, Thomas; Müller, Erich; Fritsch-Decker, Susanne; Hettler, Simon; Störmer, Heike; Weiss, Carsten; Gerthsen, Dagmar

2017-01-01

This study is concerned with backscattered electron scanning electron microscopy (BSE SEM) contrast of complex nanoscaled samples which consist of SiO 2 nanoparticles (NPs) deposited on indium-tin-oxide covered bulk SiO 2 and glassy carbon substrates. BSE SEM contrast of NPs is studied as function of the primary electron energy and working distance. Contrast inversions are observed which prevent intuitive interpretation of NP contrast in terms of material contrast. Experimental data is quantitatively compared with Monte-Carlo- (MC-) simulations. Quantitative agreement between experimental data and MC-simulations is obtained if the transmission characteristics of the annular semiconductor detector are taken into account. MC-simulations facilitate the understanding of NP contrast inversions and are helpful to derive conditions for optimum material and topography contrast.

Universal aspects of conformations and transverse fluctuations of a two-dimensional semi-flexible chain

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Huang, Aiqun; Bhattacharya, Aniket; Binder, Kurt

2015-03-01

In this talk we compare the results obtained from Monte Carlo (MC) and Brownian dynamics (BD) simulation for the universal properties of a semi-flexible chain. Specifically we compare MC results obtained using pruned-enriched Rosenbluth method (PERM) with those obtained from BD simulation. We find that the scaled plot of root-mean-square (RMS) end-to-end distance / 2 Llp and RMS transverse transverse fluctuations √{ } /lp as a function of L /lp (where L and lp are the contour length, and the persistence length respectively) are universal and independent of the definition of the persistence length used in MC and BD schemes. We further investigate to what extent these results agree for a semi-flexible polymer confined in a quasi one dimensional channel.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K.

2018-01-01

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems.

PubMed

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K

2017-12-19

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martinez-Rovira, I.; Sempau, J.; Prezado, Y.

Purpose: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-{mu}m-wide microbeams spaced by 200-400 {mu}m) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct featuresmore » of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. Methods: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Results: Good agreement between MC simulations and experimental results was achieved, even at the interfaces between two different media. Optimization of the simulation parameters and the use of VR techniques saved a significant amount of computation time. Finally, parallelization of the simulations improved even further the calculation time, which reached 1 day for a typical irradiation case envisaged in the forthcoming clinical trials in MRT. An example of MRT treatment in a dog's head is presented, showing the performance of the calculation engine. Conclusions: The development of the first MC-based calculation engine for the future TPS devoted to MRT has been accomplished. This will constitute an essential tool for the future clinical trials on pets at the ESRF. The MC engine is able to calculate dose distributions in micrometer-sized bins in complex voxelized CT structures in a reasonable amount of time. Minimization of the computation time by using several approaches has led to timings that are adequate for pet radiotherapy at synchrotron facilities. The next step will consist in its integration into a user-friendly graphical front-end.« less

Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy.

PubMed

Martinez-Rovira, I; Sempau, J; Prezado, Y

2012-05-01

Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-μm-wide microbeams spaced by 200-400 μm) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Good agreement between MC simulations and experimental results was achieved, even at the interfaces between two different media. Optimization of the simulation parameters and the use of VR techniques saved a significant amount of computation time. Finally, parallelization of the simulations improved even further the calculation time, which reached 1 day for a typical irradiation case envisaged in the forthcoming clinical trials in MRT. An example of MRT treatment in a dog's head is presented, showing the performance of the calculation engine. The development of the first MC-based calculation engine for the future TPS devoted to MRT has been accomplished. This will constitute an essential tool for the future clinical trials on pets at the ESRF. The MC engine is able to calculate dose distributions in micrometer-sized bins in complex voxelized CT structures in a reasonable amount of time. Minimization of the computation time by using several approaches has led to timings that are adequate for pet radiotherapy at synchrotron facilities. The next step will consist in its integration into a user-friendly graphical front-end.

GEANT4 benchmark with MCNPX and PHITS for activation of concrete

NASA Astrophysics Data System (ADS)

Tesse, Robin; Stichelbaut, Frédéric; Pauly, Nicolas; Dubus, Alain; Derrien, Jonathan

2018-02-01

The activation of concrete is a real problem from the point of view of waste management. Because of the complexity of the issue, Monte Carlo (MC) codes have become an essential tool to its study. But various codes or even nuclear models exist in MC. MCNPX and PHITS have already been validated for shielding studies but GEANT4 is also a suitable solution. In these codes, different models can be considered for a concrete activation study. The Bertini model is not the best model for spallation while BIC and INCL model agrees well with previous results in literature.

Analysis of dose rates received around the storage pool for irradiated control rods in a BWR nuclear power plant.

PubMed

Ródenas, J; Abarca, A; Gallardo, S

2011-08-01

BWR control rods are activated by neutron reactions in the reactor. The dose produced by this activity can affect workers in the area surrounding the storage pool, where activated rods are stored. Monte Carlo (MC) models for neutron activation and dose assessment around the storage pool have been developed and validated. In this work, the MC models are applied to verify the expected reduction of dose when the irradiated control rod is hanged in an inverted position into the pool. 2010 Elsevier Ltd. All rights reserved.

Feasibility of using Geant4 Monte Carlo simulation for IMRT dose calculations for the Novalis Tx with a HD-120 multi-leaf collimator

NASA Astrophysics Data System (ADS)

Jung, Hyunuk; Shin, Jungsuk; Chung, Kwangzoo; Han, Youngyih; Kim, Jinsung; Choi, Doo Ho

2015-05-01

The aim of this study was to develop an independent dose verification system by using a Monte Carlo (MC) calculation method for intensity modulated radiation therapy (IMRT) conducted by using a Varian Novalis Tx (Varian Medical Systems, Palo Alto, CA, USA) equipped with a highdefinition multi-leaf collimator (HD-120 MLC). The Geant4 framework was used to implement a dose calculation system that accurately predicted the delivered dose. For this purpose, the Novalis Tx Linac head was modeled according to the specifications acquired from the manufacturer. Subsequently, MC simulations were performed by varying the mean energy, energy spread, and electron spot radius to determine optimum values of irradiation with 6-MV X-ray beams by using the Novalis Tx system. Computed percentage depth dose curves (PDDs) and lateral profiles were compared to the measurements obtained by using an ionization chamber (CC13). To validate the IMRT simulation by using the MC model we developed, we calculated a simple IMRT field and compared the result with the EBT3 film measurements in a water-equivalent solid phantom. Clinical cases, such as prostate cancer treatment plans, were then selected, and MC simulations were performed. The accuracy of the simulation was assessed against the EBT3 film measurements by using a gamma-index criterion. The optimal MC model parameters to specify the beam characteristics were a 6.8-MeV mean energy, a 0.5-MeV energy spread, and a 3-mm electron radius. The accuracy of these parameters was determined by comparison of MC simulations with measurements. The PDDs and the lateral profiles of the MC simulation deviated from the measurements by 1% and 2%, respectively, on average. The computed simple MLC fields agreed with the EBT3 measurements with a 95% passing rate with 3%/3-mm gamma-index criterion. Additionally, in applying our model to clinical IMRT plans, we found that the MC calculations and the EBT3 measurements agreed well with a passing rate of greater than 95% on average with a 3%/3-mm gamma-index criterion. In summary, the Novalis Tx Linac head equipped with a HD-120 MLC was successfully modeled by using a Geant4 platform, and the accuracy of the Geant4 platform was successfully validated by comparisons with measurements. The MC model we have developed can be a useful tool for pretreatment quality assurance of IMRT plans and for commissioning of radiotherapy treatment planning.

Modelling exclusive meson pair production at hadron colliders

NASA Astrophysics Data System (ADS)

Harland-Lang, L. A.; Khoze, V. A.; Ryskin, M. G.

2014-04-01

We present a study of the central exclusive production of light meson pairs, concentrating on the region of lower invariant masses of the central system and/or meson transverse momentum, where perturbative QCD cannot be reliably applied. We describe in detail a phenomenological model, using the tools of Regge theory, that may be applied with some success in this regime, and we present the new, publicly available, Dime Monte Carlo (MC) implementation of this for , and production. The MC implementation includes a fully differential treatment of the survival factor, which in general depends on all kinematic variables, as well as allows for the so far reasonably unconstrained model parameters to be set by the user. We present predictions for the Tevatron and LHC, discuss and estimate the size of the proton-dissociative background, and show how future measurements may further test this Regge-based approach, as well as the soft hadronic model required to calculate the survival factor, in particular in the presence of tagged protons.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yee, Ben Chung; Wollaber, Allan Benton; Haut, Terry Scot

The high-order low-order (HOLO) method is a recently developed moment-based acceleration scheme for solving time-dependent thermal radiative transfer problems, and has been shown to exhibit orders of magnitude speedups over traditional time-stepping schemes. However, a linear stability analysis by Haut et al. (2015 Haut, T. S., Lowrie, R. B., Park, H., Rauenzahn, R. M., Wollaber, A. B. (2015). A linear stability analysis of the multigroup High-Order Low-Order (HOLO) method. In Proceedings of the Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method; Nashville, TN, April 19–23, 2015. American Nuclear Society.)more » revealed that the current formulation of the multigroup HOLO method was unstable in certain parameter regions. Since then, we have replaced the intensity-weighted opacity in the first angular moment equation of the low-order (LO) system with the Rosseland opacity. Furthermore, this results in a modified HOLO method (HOLO-R) that is significantly more stable.« less

A stable 1D multigroup high-order low-order method

DOE PAGES

Yee, Ben Chung; Wollaber, Allan Benton; Haut, Terry Scot; ...

2016-07-13

The high-order low-order (HOLO) method is a recently developed moment-based acceleration scheme for solving time-dependent thermal radiative transfer problems, and has been shown to exhibit orders of magnitude speedups over traditional time-stepping schemes. However, a linear stability analysis by Haut et al. (2015 Haut, T. S., Lowrie, R. B., Park, H., Rauenzahn, R. M., Wollaber, A. B. (2015). A linear stability analysis of the multigroup High-Order Low-Order (HOLO) method. In Proceedings of the Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method; Nashville, TN, April 19–23, 2015. American Nuclear Society.)more » revealed that the current formulation of the multigroup HOLO method was unstable in certain parameter regions. Since then, we have replaced the intensity-weighted opacity in the first angular moment equation of the low-order (LO) system with the Rosseland opacity. Furthermore, this results in a modified HOLO method (HOLO-R) that is significantly more stable.« less

Predictive process simulation of cryogenic implants for leading edge transistor design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gossmann, Hans-Joachim; Zographos, Nikolas; Park, Hugh

2012-11-06

Two cryogenic implant TCAD-modules have been developed: (i) A continuum-based compact model targeted towards a TCAD production environment calibrated against an extensive data-set for all common dopants. Ion-specific calibration parameters related to damage generation and dynamic annealing were used and resulted in excellent fits to the calibration data-set. (ii) A Kinetic Monte Carlo (kMC) model including the full time dependence of ion-exposure that a particular spot on the wafer experiences, as well as the resulting temperature vs. time profile of this spot. It was calibrated by adjusting damage generation and dynamic annealing parameters. The kMC simulations clearly demonstrate the importancemore » of the time-structure of the beam for the amorphization process: Assuming an average dose-rate does not capture all of the physics and may lead to incorrect conclusions. The model enables optimization of the amorphization process through tool parameters such as scan speed or beam height.« less

[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].

PubMed

Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang

2016-02-01

Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS

A fragment-based approach to the SAMPL3 Challenge

NASA Astrophysics Data System (ADS)

Kulp, John L.; Blumenthal, Seth N.; Wang, Qiang; Bryan, Richard L.; Guarnieri, Frank

2012-05-01

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands—regardless of the charged state in the active site—produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a ΔΔGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations.

The FLUKA Monte Carlo code coupled with the NIRS approach for clinical dose calculations in carbon ion therapy

NASA Astrophysics Data System (ADS)

Magro, G.; Dahle, T. J.; Molinelli, S.; Ciocca, M.; Fossati, P.; Ferrari, A.; Inaniwa, T.; Matsufuji, N.; Ytre-Hauge, K. S.; Mairani, A.

2017-05-01

Particle therapy facilities often require Monte Carlo (MC) simulations to overcome intrinsic limitations of analytical treatment planning systems (TPS) related to the description of the mixed radiation field and beam interaction with tissue inhomogeneities. Some of these uncertainties may affect the computation of effective dose distributions; therefore, particle therapy dedicated MC codes should provide both absorbed and biological doses. Two biophysical models are currently applied clinically in particle therapy: the local effect model (LEM) and the microdosimetric kinetic model (MKM). In this paper, we describe the coupling of the NIRS (National Institute for Radiological Sciences, Japan) clinical dose to the FLUKA MC code. We moved from the implementation of the model itself to its application in clinical cases, according to the NIRS approach, where a scaling factor is introduced to rescale the (carbon-equivalent) biological dose to a clinical dose level. A high level of agreement was found with published data by exploring a range of values for the MKM input parameters, while some differences were registered in forward recalculations of NIRS patient plans, mainly attributable to differences with the analytical TPS dose engine (taken as reference) in describing the mixed radiation field (lateral spread and fragmentation). We presented a tool which is being used at the Italian National Center for Oncological Hadrontherapy to support the comparison study between the NIRS clinical dose level and the LEM dose specification.

Protein-ion binding process on finite macromolecular concentration. A Poisson-Boltzmann and Monte Carlo study.

PubMed

de Carvalho, Sidney Jurado; Fenley, Márcia O; da Silva, Fernando Luís Barroso

2008-12-25

Electrostatic interactions are one of the key driving forces for protein-ligands complexation. Different levels for the theoretical modeling of such processes are available on the literature. Most of the studies on the Molecular Biology field are performed within numerical solutions of the Poisson-Boltzmann Equation and the dielectric continuum models framework. In such dielectric continuum models, there are two pivotal questions: (a) how the protein dielectric medium should be modeled, and (b) what protocol should be used when solving this effective Hamiltonian. By means of Monte Carlo (MC) and Poisson-Boltzmann (PB) calculations, we define the applicability of the PB approach with linear and nonlinear responses for macromolecular electrostatic interactions in electrolyte solution, revealing some physical mechanisms and limitations behind it especially due the raise of both macromolecular charge and concentration out of the strong coupling regime. A discrepancy between PB and MC for binding constant shifts is shown and explained in terms of the manner PB approximates the excess chemical potentials of the ligand, and not as a consequence of the nonlinear thermal treatment and/or explicit ion-ion interactions as it could be argued. Our findings also show that the nonlinear PB predictions with a low dielectric response well reproduce the pK shifts calculations carried out with an uniform dielectric model. This confirms and completes previous results obtained by both MC and linear PB calculations.

Mixing of Isotactic and Syndiotactic Polypropylenes in the Melt

DOE Office of Scientific and Technical Information (OSTI.GOV)

CLANCY,THOMAS C.; PUTZ,MATHIAS; WEINHOLD,JEFFREY D.

2000-07-14

The miscibility of polypropylene (PP) melts in which the chains differ only in stereochemical composition has been investigated by two different procedures. One approach used detailed local information from a Monte Carlo simulation of a single chain, and the other approach takes this information from a rotational isomeric state model devised decades ago, for another purpose. The first approach uses PRISM theory to deduce the intermolecular packing in the polymer blend, while the second approach uses a Monte Carlo simulation of a coarse-grained representation of independent chains, expressed on a high-coordination lattice. Both approaches find a positive energy change uponmore » mixing isotactic PP (iPP) and syndiotactic polypropylene (sPP) chains in the melt. This conclusion is qualitatively consistent with observations published recently by Muelhaupt and coworkers. The size of the energy chain on mixing is smaller in the MC/PRISM approach than in the RIS/MC simulation, with the smaller energy change being in better agreement with the experiment. The RIS/MC simulation finds no demixing for iPP and atactic polypropylene (aPP) in the melt, consistent with several experimental observations in the literature. The demixing of the iPP/sPP blend may arise from attractive interactions in the sPP melt that are disrupted when the sPP chains are diluted with aPP or iPP chains.« less

Parallelization of a Monte Carlo particle transport simulation code

NASA Astrophysics Data System (ADS)

Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.

2010-05-01

We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.

Properties of a planar electric double layer under extreme conditions investigated by classical density functional theory and Monte Carlo simulations.

PubMed

Zhou, Shiqi; Lamperski, Stanisław; Zydorczak, Maria

2014-08-14

Monte Carlo (MC) simulation and classical density functional theory (DFT) results are reported for the structural and electrostatic properties of a planar electric double layer containing ions having highly asymmetric diameters or valencies under extreme concentration condition. In the applied DFT, for the excess free energy contribution due to the hard sphere repulsion, a recently elaborated extended form of the fundamental measure functional is used, and coupling of Coulombic and short range hard-sphere repulsion is described by a traditional second-order functional perturbation expansion approximation. Comparison between the MC and DFT results indicates that validity interval of the traditional DFT approximation expands to high ion valences running up to 3 and size asymmetry high up to diameter ratio of 4 whether the high valence ions or the large size ion are co- or counter-ions; and to a high bulk electrolyte concentration being close to the upper limit of the electrolyte mole concentration the MC simulation can deal with well. The DFT accuracy dependence on the ion parameters can be self-consistently explained using arguments of liquid state theory, and new EDL phenomena such as overscreening effect due to monovalent counter-ions, extreme layering effect of counter-ions, and appearance of a depletion layer with almost no counter- and co-ions are observed.

Monte Carlo simulations of backscattering process in dislocation-containing SrTiO3 single crystal

NASA Astrophysics Data System (ADS)

Jozwik, P.; Sathish, N.; Nowicki, L.; Jagielski, J.; Turos, A.; Kovarik, L.; Arey, B.

2014-05-01

Studies of defects formation in crystals are of obvious importance in electronics, nuclear engineering and other disciplines where materials are exposed to different forms of irradiation. Rutherford Backscattering/Channeling (RBS/C) and Monte Carlo (MC) simulations are the most convenient tool for this purpose, as they allow one to determine several features of lattice defects: their type, concentration and damage accumulation kinetic. On the other hand various irradiation conditions can be efficiently modeled by ion irradiation method without leading to the radioactivity of the sample. Combination of ion irradiation with channeling experiment and MC simulations appears thus as a most versatile method in studies of radiation damage in materials. The paper presents the results on such a study performed on SrTiO3 (STO) single crystals irradiated with 320 keV Ar ions. The samples were analyzed also by using HRTEM as a complementary method which enables the measurement of geometrical parameters of crystal lattice deformation in the vicinity of dislocations. Once the parameters and their variations within the distance of several lattice constants from the dislocation core are known, they may be used in MC simulations for the quantitative determination of dislocation depth distribution profiles. The final outcome of the deconvolution procedure are cross-sections values calculated for two types of defects observed (RDA and dislocations).

GPU-BASED MONTE CARLO DUST RADIATIVE TRANSFER SCHEME APPLIED TO ACTIVE GALACTIC NUCLEI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heymann, Frank; Siebenmorgen, Ralf, E-mail: fheymann@pa.uky.edu

2012-05-20

A three-dimensional parallel Monte Carlo (MC) dust radiative transfer code is presented. To overcome the huge computing-time requirements of MC treatments, the computational power of vectorized hardware is used, utilizing either multi-core computer power or graphics processing units. The approach is a self-consistent way to solve the radiative transfer equation in arbitrary dust configurations. The code calculates the equilibrium temperatures of two populations of large grains and stochastic heated polycyclic aromatic hydrocarbons. Anisotropic scattering is treated applying the Heney-Greenstein phase function. The spectral energy distribution (SED) of the object is derived at low spatial resolution by a photon counting proceduremore » and at high spatial resolution by a vectorized ray tracer. The latter allows computation of high signal-to-noise images of the objects at any frequencies and arbitrary viewing angles. We test the robustness of our approach against other radiative transfer codes. The SED and dust temperatures of one- and two-dimensional benchmarks are reproduced at high precision. The parallelization capability of various MC algorithms is analyzed and included in our treatment. We utilize the Lucy algorithm for the optical thin case where the Poisson noise is high, the iteration-free Bjorkman and Wood method to reduce the calculation time, and the Fleck and Canfield diffusion approximation for extreme optical thick cells. The code is applied to model the appearance of active galactic nuclei (AGNs) at optical and infrared wavelengths. The AGN torus is clumpy and includes fluffy composite grains of various sizes made up of silicates and carbon. The dependence of the SED on the number of clumps in the torus and the viewing angle is studied. The appearance of the 10 {mu}m silicate features in absorption or emission is discussed. The SED of the radio-loud quasar 3C 249.1 is fit by the AGN model and a cirrus component to account for the far-infrared emission.« less

Optimisation of 12 MeV electron beam simulation using variance reduction technique

NASA Astrophysics Data System (ADS)

Jayamani, J.; Termizi, N. A. S. Mohd; Kamarulzaman, F. N. Mohd; Aziz, M. Z. Abdul

2017-05-01

Monte Carlo (MC) simulation for electron beam radiotherapy consumes a long computation time. An algorithm called variance reduction technique (VRT) in MC was implemented to speed up this duration. This work focused on optimisation of VRT parameter which refers to electron range rejection and particle history. EGSnrc MC source code was used to simulate (BEAMnrc code) and validate (DOSXYZnrc code) the Siemens Primus linear accelerator model with the non-VRT parameter. The validated MC model simulation was repeated by applying VRT parameter (electron range rejection) that controlled by global electron cut-off energy 1,2 and 5 MeV using 20 × 107 particle history. 5 MeV range rejection generated the fastest MC simulation with 50% reduction in computation time compared to non-VRT simulation. Thus, 5 MeV electron range rejection utilized in particle history analysis ranged from 7.5 × 107 to 20 × 107. In this study, 5 MeV electron cut-off with 10 × 107 particle history, the simulation was four times faster than non-VRT calculation with 1% deviation. Proper understanding and use of VRT can significantly reduce MC electron beam calculation duration at the same time preserving its accuracy.

Quantitative assessment of the accuracy of dose calculation using pencil beam and Monte Carlo algorithms and requirements for clinical quality assurance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, Imad, E-mail: iali@ouhsc.edu; Ahmad, Salahuddin

2013-10-01

To compare the doses calculated using the BrainLAB pencil beam (PB) and Monte Carlo (MC) algorithms for tumors located in various sites including the lung and evaluate quality assurance procedures required for the verification of the accuracy of dose calculation. The dose-calculation accuracy of PB and MC was also assessed quantitatively with measurement using ionization chamber and Gafchromic films placed in solid water and heterogeneous phantoms. The dose was calculated using PB convolution and MC algorithms in the iPlan treatment planning system from BrainLAB. The dose calculation was performed on the patient's computed tomography images with lesions in various treatmentmore » sites including 5 lungs, 5 prostates, 4 brains, 2 head and necks, and 2 paraspinal tissues. A combination of conventional, conformal, and intensity-modulated radiation therapy plans was used in dose calculation. The leaf sequence from intensity-modulated radiation therapy plans or beam shapes from conformal plans and monitor units and other planning parameters calculated by the PB were identical for calculating dose with MC. Heterogeneity correction was considered in both PB and MC dose calculations. Dose-volume parameters such as V95 (volume covered by 95% of prescription dose), dose distributions, and gamma analysis were used to evaluate the calculated dose by PB and MC. The measured doses by ionization chamber and EBT GAFCHROMIC film in solid water and heterogeneous phantoms were used to quantitatively asses the accuracy of dose calculated by PB and MC. The dose-volume histograms and dose distributions calculated by PB and MC in the brain, prostate, paraspinal, and head and neck were in good agreement with one another (within 5%) and provided acceptable planning target volume coverage. However, dose distributions of the patients with lung cancer had large discrepancies. For a plan optimized with PB, the dose coverage was shown as clinically acceptable, whereas in reality, the MC showed a systematic lack of dose coverage. The dose calculated by PB for lung tumors was overestimated by up to 40%. An interesting feature that was observed is that despite large discrepancies in dose-volume histogram coverage of the planning target volume between PB and MC, the point doses at the isocenter (center of the lesions) calculated by both algorithms were within 7% even for lung cases. The dose distributions measured with EBT GAFCHROMIC films in heterogeneous phantoms showed large discrepancies of nearly 15% lower than PB at interfaces between heterogeneous media, where these lower doses measured by the film were in agreement with those by MC. The doses (V95) calculated by MC and PB agreed within 5% for treatment sites with small tissue heterogeneities such as the prostate, brain, head and neck, and paraspinal tumors. Considerable discrepancies, up to 40%, were observed in the dose-volume coverage between MC and PB in lung tumors, which may affect clinical outcomes. The discrepancies between MC and PB increased for 15 MV compared with 6 MV indicating the importance of implementation of accurate clinical treatment planning such as MC. The comparison of point doses is not representative of the discrepancies in dose coverage and might be misleading in evaluating the accuracy of dose calculation between PB and MC. Thus, the clinical quality assurance procedures required to verify the accuracy of dose calculation using PB and MC need to consider measurements of 2- and 3-dimensional dose distributions rather than a single point measurement using heterogeneous phantoms instead of homogenous water-equivalent phantoms.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snow, Dr., Joel

This final report is presented by Langston University (LU) for the project entitled "Langston University High Energy Physics" (LUHEP) under the direction of principal investigator (PI) and project director Professor Joel Snow. The project encompassed high energy physics research performed at hadron colliders. The PI is a collaborator on the DZero experiment at Fermi National Accelerator Laboratory in Batavia, IL, USA and the ATLAS experiment at CERN in Geneva, Switzerland and was during the entire project period from April 1, 1999 until May 14, 2012. Both experiments seek to understand the fundamental constituents of the physical universe and the forcesmore » that govern their interactions. In 1999 as member of the Online Systems group for Run 2 the PI developed a cross-platform Python-based, Graphical User Interface (GUI) application for monitoring and control of EPICS based devices for control room use. This served as a model for other developers to enhance and build on for further monitoring and control tasks written in Python. Subsequently the PI created and developed a cross-platform C++ GUI utilizing a networked client-server paradigm and based on ROOT, the object oriented analysis framework from CERN. The GUI served as a user interface to the Examine tasks running in the D\\O\\ control room which monitored the status and integrity of data taking for Run 2. The PI developed the histogram server/control interface to the GUI client for the EXAMINE processes. The histogram server was built from the ROOT framework and was integrated into the D\\O\\ framework used for online monitoring programs and offline analysis. The PI developed the first implementation of displaying histograms dynamically generated by ROOT in a Web Browser. The PI's work resulted in several talks and papers at international conferences and workshops. The PI established computing software infrastructure at LU and U. Oklahoma (OU) to do analysis of DZero production data and produce simulation data for the experiment. Eventually this included the FNAL SAM data grid system, the SAMGrid (SG) infrastructure, and the Open Science Grid software stacks for computing and storage elements. At the end of 2003 Snow took on the role of global Monte Carlo production coordinator for the DØ experiment. A role which continues til this day. In January of 2004 Snow started working with the SAMGrid development team to help debug, deploy, and integrate SAMGrid with DØ Monte Carlo production. Snow installed and configured SG execution and client sites at LUHEP and OUHEP, and a SG scheduler site at LUHEP. The PI developed a python based GUI (DAJ) that acts as a front end for job submission to SAMGrid. The GUI interfaces to the DZero Mone Carlo (MC) request system that uses SAM to manage MC requests by the physics analysis groups. DAJ significantly simplified SG job submission and was deployed in DZero in an effort to increase the user base of SG. The following year was the advent of SAMGrid job submission to the Open Science Grid (OSG) and LHC Computing Grid (LCG) through a forwarding mechanism. The PI oversaw the integration of these grids into the existing production infrastructure. The PI developed an automatic MC (Automc) request processing system capable of operating without user intervention (other than getting grid credentials), and able to submit to any number of sites on various grids. The system manages production at all but 2 sites. The system was deployed at Fermilab and remains operating there today. The PI's work in distributed computing resulted in several talks at international conferences. UTA, OU, and LU were chosen as the collaborating institutions that form the Southwest Tier 2 Center (SWT2) for ATLAS. During the project period the PI contributed to the online and offline software infrastructure through his work with the Run 2 online group, and played a major role in Monte Carlo production for DZero. During the part of the project period in which the PI served as MC production coordinator MC production increased very significantly. In the first year of the PI's tenure as production coordinator production was 159M events and 6.7~TB of data. During the last year of the project period production was 2,342~M events and 262~TB of data. That is a factor of 15 increase in events and 39 in data volume. The increase occurred with improvements in computer hardware and networks, through the use of grid technology on diverse resources, and through increased automation and efficiency of the production process. LU HEP developed and deployed the automatic MC request processing system in use at FNAL. The complementary strategies of automation and grid production served DZero well. Fermilab has recognized LU HEP's contribution to DZero by allowing the PI to devote full time to research activities by appointing him a guest scientist for the last six years of the project period.« less

Fast calculation of tissue optical properties using MC and the experimental evaluation for diagnosis of cervical cancer

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Zhou, Xiaoqing; Qin, Zhuanping; Zhao, Huijuan

2011-02-01

This article aims at the development of the fast inverse Monte Carlo (MC) simulation for the reconstruction of optical properties (absorption coefficient μs and scattering coefficient μs) of cylindrical tissue, such as a cervix, from the measurement of near infrared diffuse light on frequency domain. Frequency domain information (amplitude and phase) is extracted from the time domain MC with a modified method. To shorten the computation time in reconstruction of optical properties, efficient and fast forward MC has to be achieved. To do this, firstly, databases of the frequency-domain information under a range of μa and μs were pre-built by combining MC simulation with Lambert-Beer's law. Then, a double polynomial model was adopted to quickly obtain the frequency-domain information in any optical properties. Based on the fast forward MC, the optical properties can be quickly obtained in a nonlinear optimization scheme. Reconstruction resulting from simulated data showed that the developed inverse MC method has the advantages in both the reconstruction accuracy and computation time. The relative errors in reconstruction of the μs and μs are less than +/-6% and +/-12% respectively, while another coefficient (μs or μs) is in a fixed value. When both μs and μs are unknown, the relative errors in reconstruction of the reduced scattering coefficient and absorption coefficient are mainly less than +/-10% in range of 45< μs <80 cm-1 and 0.25< a μ <0.55 cm-1. With the rapid reconstruction strategy developed in this article the computation time for reconstructing one set of the optical properties is less than 0.5 second. Endoscopic measurement on two tubular solid phantoms were also carried out to evaluate the system and the inversion scheme. The results demonstrated that less than 20% relative error can be achieved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cebe, M; Pacaci, P; Mabhouti, H

Purpose: In this study, the two available calculation algorithms of the Varian Eclipse treatment planning system(TPS), the electron Monte Carlo(eMC) and General Gaussian Pencil Beam(GGPB) algorithms were used to compare measured and calculated peripheral dose distribution of electron beams. Methods: Peripheral dose measurements were carried out for 6, 9, 12, 15, 18 and 22 MeV electron beams of Varian Triology machine using parallel plate ionization chamber and EBT3 films in the slab phantom. Measurements were performed for 6×6, 10×10 and 25×25cm{sup 2} cone sizes at dmax of each energy up to 20cm beyond the field edges. Using the same filmmore » batch, the net OD to dose calibration curve was obtained for each energy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution measured using parallel plate ionization chamber and EBT3 film and calculated by eMC and GGPB algorithms were compared. The measured and calculated data were then compared to find which algorithm calculates peripheral dose distribution more accurately. Results: The agreement between measurement and eMC was better than GGPB. The TPS underestimated the out of field doses. The difference between measured and calculated doses increase with the cone size. The largest deviation between calculated and parallel plate ionization chamber measured dose is less than 4.93% for eMC, but it can increase up to 7.51% for GGPB. For film measurement, the minimum gamma analysis passing rates between measured and calculated dose distributions were 98.2% and 92.7% for eMC and GGPB respectively for all field sizes and energies. Conclusion: Our results show that the Monte Carlo algorithm for electron planning in Eclipse is more accurate than previous algorithms for peripheral dose distributions. It must be emphasized that the use of GGPB for planning large field treatments with 6 MeV could lead to inaccuracies of clinical significance.« less

SU-E-T-454: Dosimetric Comparison between Pencil Beam and Monte Carlo Algorithms for SBRT Lung Treatment Using IPlan V4.1 TPS and CIRS Thorax Phantom.

PubMed

Fernandez, M Castrillon; Venencia, C; Garrigó, E; Caussa, L

2012-06-01

To compare measured and calculated doses using Pencil Beam (PB) and Monte Carlo (MC) algorithm on a CIRS thorax phantom for SBRT lung treatments. A 6MV photon beam generated by a Primus linac with an Optifocus MLC (Siemens) was used. Dose calculation was done using iPlan v4.1.2 TPS (BrainLAB) by PB and MC (dose to water and dose to medium) algorithms. The commissioning of both algorithms was done reproducing experimental measurements in water. A CIRS thorax phantom was used to compare doses using a Farmer type ion chamber (PTW) and EDR2 radiographic films (KODAK). The ionization chamber, into a tissue equivalent insert, was placed in two position of lung tissue and was irradiated using three treatments plans. Axial dose distributions were measured for four treatments plans using conformal and IMRT technique. Dose distribution comparisons were done by dose profiles and gamma index (3%/3mm). For the studied beam configurations, ion chamber measurements shows that PB overestimate the dose up to 8.5%, whereas MC has a maximum variation of 1.6%. Dosimetric analysis using dose profiles shows that PB overestimates the dose in the region corresponding to the lung up to 16%. For axial dose distribution comparison the percentage of pixels with gamma index bigger than one for MC and PB was, plan 1: 95.6% versus 87.4%, plan 2: 91.2% versus 77.6%, plan 3: 99.7% versus 93.1% and for plan 4: 98.8% versus 91.7%. It was confirmed that the lower dosimetric errors calculated applying MC algorithm appears when the spatial resolution and variance decrease at the expense of increased computation time. The agreement between measured and calculated doses, in a phantom with lung heterogeneities, is better with MC algorithm. PB algorithm overestimates the doses in lung tissue, which could have a clinical impact in SBRT lung treatments. © 2012 American Association of Physicists in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manohar, Nivedh; Jones, Bernard L.; Cho, Sang Hyun, E-mail: scho@mdanderson.org

Purpose: To develop an accurate and comprehensive Monte Carlo (MC) model of an experimental benchtop polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) setup and apply this MC model to optimize incident x-ray spectrum for improving production/detection of x-ray fluorescence photons from gold nanoparticles (GNPs). Methods: A detailed MC model, based on an experimental XFCT system, was created using the Monte Carlo N-Particle (MCNP) transport code. The model was validated by comparing MC results including x-ray fluorescence (XRF) and scatter photon spectra with measured data obtained under identical conditions using 105 kVp cone-beam x-rays filtered by either 1 mm of leadmore » (Pb) or 0.9 mm of tin (Sn). After validation, the model was used to investigate the effects of additional filtration of the incident beam with Pb and Sn. Supplementary incident x-ray spectra, representing heavier filtration (Pb: 2 and 3 mm; Sn: 1, 2, and 3 mm) were computationally generated and used with the model to obtain XRF/scatter spectra. Quasimonochromatic incident x-ray spectra (81, 85, 90, 95, and 100 keV with 10 keV full width at half maximum) were also investigated to determine the ideal energy for distinguishing gold XRF signal from the scatter background. Fluorescence signal-to-dose ratio (FSDR) and fluorescence-normalized scan time (FNST) were used as metrics to assess results. Results: Calculated XRF/scatter spectra for 1-mm Pb and 0.9-mm Sn filters matched (r ≥ 0.996) experimental measurements. Calculated spectra representing additional filtration for both filter materials showed that the spectral hardening improved the FSDR at the expense of requiring a much longer FNST. In general, using Sn instead of Pb, at a given filter thickness, allowed an increase of up to 20% in FSDR, more prominent gold XRF peaks, and up to an order of magnitude decrease in FNST. Simulations using quasimonochromatic spectra suggested that increasing source x-ray energy, in the investigated range of 81–100 keV, increased the FSDR up to a factor of 20, compared to 1 mm Pb, and further facilitated separation of gold XRF peaks from the scatter background. Conclusions: A detailed MC model of an experimental benchtop XFCT system has been developed and validated. In exemplary calculations to illustrate the usefulness of this model, it was shown that potential use of quasimonochromatic spectra or judicious choice of filter material/thickness to tailor the spectrum of a polychromatic x-ray source can significantly improve the performance of benchtop XFCT, while considering trade-offs between FSDR and FNST. As demonstrated, the current MC model is a reliable and powerful computational tool that can greatly expedite the further development of a benchtop XFCT system for routine preclinical molecular imaging with GNPs and other metal probes.« less

UNCERTAINTY AND SENSITIVITY ANALYSIS OF RUNOFF AND SEDIMENT YIELD IN A SMALL AGRICULTURAL WATERSHED WITH KINEROS2

EPA Science Inventory

Using the Monte Carlo (MC) method, this paper derives arithmetic and geometric means and associated variances of the net capillary drive parameter, G, that appears in the Parlange infiltration model, as a function of soil texture and antecedent soil moisture content. App...

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Room scatter effects in Total Skin Electron Irradiation: Monte Carlo simulation study.

PubMed

Nevelsky, Alexander; Borzov, Egor; Daniel, Shahar; Bar-Deroma, Raquel

2017-01-01

Total Skin Electron Irradiation (TSEI) is a complex technique which usually involves the use of large electron fields and the dual-field approach. In this situation, many electrons scattered from the treatment room floor are produced. However, no investigations of the effect of scattered electrons in TSEI treatments have been reported. The purpose of this work was to study the contribution of floor scattered electrons to skin dose during TSEI treatment using Monte Carlo (MC) simulations. All MC simulations were performed with the EGSnrc code. Influence of beam energy, dual-field angle, and floor material on the contribution of floor scatter was investigated. Spectrum of the scattered electrons was calculated. Measurements of dose profile were performed in order to verify MC calculations. Floor scatter dependency on the floor material was observed (at 20 cm from the floor, scatter contribution was about 21%, 18%, 15%, and 12% for iron, concrete, PVC, and water, respectively). Although total dose profiles exhibited slight variation as functions of beam energy and dual-field angle, no dependence of the floor scatter contribution on the beam energy or dual-field angle was found. The spectrum of the scattered electrons was almost uniform between a few hundred KeV to 4 MeV, and then decreased linearly to 6 MeV. For the TSEI technique, dose contribution due to the electrons scattered from the room floor may be clinically significant and should be taken into account during design and commissioning phases. MC calculations can be used for this task. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Serin, E.; Codel, G.; Mabhouti, H.

Purpose: In small field geometries, the electronic equilibrium can be lost, making it challenging for the dose-calculation algorithm to accurately predict the dose, especially in the presence of tissue heterogeneities. In this study, dosimetric accuracy of Monte Carlo (MC) advanced dose calculation and sequential algorithms of Multiplan treatment planning system were investigated for small radiation fields incident on homogeneous and heterogeneous geometries. Methods: Small open fields of fixed cones of Cyberknife M6 unit 100 to 500 mm2 were used for this study. The fields were incident on in house phantom containing lung, air, and bone inhomogeneities and also homogeneous phantom.more » Using the same film batch, the net OD to dose calibration curve was obtained using CK with the 60 mm fixed cone by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. The dosimetric accuracy of MC and sequential algorithms in the presence of the inhomogeneities was compared against EBT3 film dosimetry Results: Open field tests in a homogeneous phantom showed good agreement between two algorithms and film measurement For MC algorithm, the minimum gamma analysis passing rates between measured and calculated dose distributions were 99.7% and 98.3% for homogeneous and inhomogeneous fields in the case of lung and bone respectively. For sequential algorithm, the minimum gamma analysis passing rates were 98.9% and 92.5% for for homogeneous and inhomogeneous fields respectively for used all cone sizes. In the case of the air heterogeneity, the differences were larger for both calculation algorithms. Overall, when compared to measurement, the MC had better agreement than sequential algorithm. Conclusion: The Monte Carlo calculation algorithm in the Multiplan treatment planning system is an improvement over the existing sequential algorithm. Dose discrepancies were observed for in the presence of air inhomogeneities.« less

Poster — Thur Eve — 46: Monte Carlo model of the Novalis Classic 6MV stereotactic linear accelerator using the GATE simulation platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiebe, J; Department of Physics and Astronomy, University of Calgary, Calgary, AB; Ploquin, N

2014-08-15

Monte Carlo (MC) simulation is accepted as the most accurate method to predict dose deposition when compared to other methods in radiation treatment planning. Current dose calculation algorithms used for treatment planning can become inaccurate when small radiation fields and tissue inhomogeneities are present. At our centre the Novalis Classic linear accelerator (linac) is used for Stereotactic Radiosurgery (SRS). The first MC model to date of the Novalis Classic linac was developed at our centre using the Geant4 Application for Tomographic Emission (GATE) simulation platform. GATE is relatively new, open source MC software built from CERN's Geometry and Tracking 4more » (Geant4) toolkit. The linac geometry was modeled using manufacturer specifications, as well as in-house measurements of the micro MLC's. Among multiple model parameters, the initial electron beam was adjusted so that calculated depth dose curves agreed with measured values. Simulations were run on the European Grid Infrastructure through GateLab. Simulation time is approximately 8 hours on GateLab for a complete head model simulation to acquire a phase space file. Current results have a majority of points within 3% of the measured dose values for square field sizes ranging from 6×6 mm{sup 2} to 98×98 mm{sup 2} (maximum field size on the Novalis Classic linac) at 100 cm SSD. The x-ray spectrum was determined from the MC data as well. The model provides an investigation into GATE'S capabilities and has the potential to be used as a research tool and an independent dose calculation engine for clinical treatment plans.« less

Vertical drying of a suspension of sticks: Monte Carlo simulation for continuous two-dimensional problem

NASA Astrophysics Data System (ADS)

Lebovka, Nikolai I.; Tarasevich, Yuri Yu.; Vygornitskii, Nikolai V.

2018-02-01

The vertical drying of a two-dimensional colloidal film containing zero-thickness sticks (lines) was studied by means of kinetic Monte Carlo (MC) simulations. The continuous two-dimensional problem for both the positions and orientations was considered. The initial state before drying was produced using a model of random sequential adsorption with isotropic orientations of the sticks. During the evaporation, an upper interface falls with a linear velocity in the vertical direction, and the sticks undergo translational and rotational Brownian motions. The MC simulations were run at different initial number concentrations (the numbers of sticks per unit area), pi, and solvent evaporation rates, u . For completely dried films, the spatial distributions of the sticks, the order parameters, and the electrical conductivities of the films in both the horizontal, x , and vertical, y , directions were examined. Significant evaporation-driven self-assembly and stratification of the sticks in the vertical direction was observed. The extent of stratification increased with increasing values of u . The anisotropy of the electrical conductivity of the film can be finely regulated by changes in the values of pi and u .

Impact ionization and band-to-band tunneling in InxGa1-xAs PIN ungated devices: A Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Vasallo, B. G.; González, T.; Talbo, V.; Lechaux, Y.; Wichmann, N.; Bollaert, S.; Mateos, J.

2018-01-01

III-V Impact-ionization (II) metal-oxide-semiconductor FETs (I-MOSFETs) and tunnel FETs (TFETs) are being explored as promising devices for low-power digital applications. To assist the development of these devices from the physical point of view, a Monte Carlo (MC) model which includes impact ionization processes and band-to-band tunneling is presented. The MC simulator reproduces the I-V characteristics of experimental ungated In0.53Ga0.47As 100 nm PIN diodes, in which tunneling emerges for lower applied voltages than impact ionization events, thus being appropriate for TFETs. When the structure is enlarged up to 200 nm, the ON-state is achieved by means of impact ionization processes; however, the necessary applied voltage is higher, with the consequent drawback for low-power applications. In InAs PIN ungated structures, the onset of both impact ionization processes and band-to-band tunneling takes place for similar applied voltages, lower than 1 V; thus they are suitable for the design of low-power I-MOSFETs.

A dual resolution measurement based Monte Carlo simulation technique for detailed dose analysis of small volume organs in the skull base region

NASA Astrophysics Data System (ADS)

Yeh, Chi-Yuan; Tung, Chuan-Jung; Chao, Tsi-Chain; Lin, Mu-Han; Lee, Chung-Chi

2014-11-01

The purpose of this study was to examine dose distribution of a skull base tumor and surrounding critical structures in response to high dose intensity-modulated radiosurgery (IMRS) with Monte Carlo (MC) simulation using a dual resolution sandwich phantom. The measurement-based Monte Carlo (MBMC) method (Lin et al., 2009) was adopted for the study. The major components of the MBMC technique involve (1) the BEAMnrc code for beam transport through the treatment head of a Varian 21EX linear accelerator, (2) the DOSXYZnrc code for patient dose simulation and (3) an EPID-measured efficiency map which describes non-uniform fluence distribution of the IMRS treatment beam. For the simulated case, five isocentric 6 MV photon beams were designed to deliver a total dose of 1200 cGy in two fractions to the skull base tumor. A sandwich phantom for the MBMC simulation was created based on the patient's CT scan of a skull base tumor [gross tumor volume (GTV)=8.4 cm3] near the right 8th cranial nerve. The phantom, consisted of a 1.2-cm thick skull base region, had a voxel resolution of 0.05×0.05×0.1 cm3 and was sandwiched in between 0.05×0.05×0.3 cm3 slices of a head phantom. A coarser 0.2×0.2×0.3 cm3 single resolution (SR) phantom was also created for comparison with the sandwich phantom. A particle history of 3×108 for each beam was used for simulations of both the SR and the sandwich phantoms to achieve a statistical uncertainty of <2%. Our study showed that the planning target volume (PTV) receiving at least 95% of the prescribed dose (VPTV95) was 96.9%, 96.7% and 99.9% for the TPS, SR, and sandwich phantom, respectively. The maximum and mean doses to large organs such as the PTV, brain stem, and parotid gland for the TPS, SR and sandwich MC simulations did not show any significant difference; however, significant dose differences were observed for very small structures like the right 8th cranial nerve, right cochlea, right malleus and right semicircular canal. Dose volume histogram (DVH) analyses revealed much smoother DVH curves for the dual resolution sandwich phantom when compared to the SR phantom. In conclusion, MBMC simulations using a dual resolution sandwich phantom improved simulation spatial resolution for skull base IMRS therapy. More detailed dose analyses for small critical structures can be made available to help in clinical judgment.

Dosimetric perturbations due to an implanted cardiac pacemaker in MammoSite{sup Registered-Sign} treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sung, Wonmo; Kim, Siyong; Kim, Jung-in

2012-10-15

Purpose: To investigate dose perturbations for pacemaker-implanted patients in partial breast irradiation using high dose rate (HDR) balloon brachytherapy. Methods: Monte Carlo (MC) simulations were performed to calculate dose distributions involving a pacemaker in Ir-192 HDR balloon brachytherapy. Dose perturbations by varying balloon-to-pacemaker distances (BPD = 50 or 100 mm) and concentrations of iodine contrast medium (2.5%, 5.0%, 7.5%, and 10.0% by volume) in the balloon were investigated for separate parts of the pacemaker (i.e., battery and substrate). Relative measurements using an ion-chamber were also performed to confirm MC results. Results: The MC and measured results in homogeneous media withoutmore » a pacemaker agreed with published data within 2% from the balloon surface to 100 mm BPD. Further their dose distributions with a pacemaker were in a comparable agreement. The MC results showed that doses over the battery were increased by a factor of 3, compared to doses without a pacemaker. However, there was no significant dose perturbation in the middle of substrate but up to 70% dose increase in the substrate interface with the titanium capsule. The attenuation by iodine contrast medium lessened doses delivered to the pacemaker by up to 9%. Conclusions: Due to inhomogeneity of pacemaker and contrast medium as well as low-energy photons in Ir-192 HDR balloon brachytherapy, the actual dose received in a pacemaker is different from the homogeneous medium-based dose and the external beam-based dose. Therefore, the dose perturbations should be considered for pacemaker-implanted patients when evaluating a safe clinical distance between the balloon and pacemaker.« less

Forward and Inverse Modeling of Self-potential. A Tomography of Groundwater Flow and Comparison Between Deterministic and Stochastic Inversion Methods

NASA Astrophysics Data System (ADS)

Quintero-Chavarria, E.; Ochoa Gutierrez, L. H.

2016-12-01

Applications of the Self-potential Method in the fields of Hydrogeology and Environmental Sciences have had significant developments during the last two decades with a strong use on groundwater flows identification. Although only few authors deal with the forward problem's solution -especially in geophysics literature- different inversion procedures are currently being developed but in most cases they are compared with unconventional groundwater velocity fields and restricted to structured meshes. This research solves the forward problem based on the finite element method using the St. Venant's Principle to transform a point dipole, which is the field generated by a single vector, into a distribution of electrical monopoles. Then, two simple aquifer models were generated with specific boundary conditions and head potentials, velocity fields and electric potentials in the medium were computed. With the model's surface electric potential, the inverse problem is solved to retrieve the source of electric potential (vector field associated to groundwater flow) using deterministic and stochastic approaches. The first approach was carried out by implementing a Tikhonov regularization with a stabilized operator adapted to the finite element mesh while for the second a hierarchical Bayesian model based on Markov chain Monte Carlo (McMC) and Markov Random Fields (MRF) was constructed. For all implemented methods, the result between the direct and inverse models was contrasted in two ways: 1) shape and distribution of the vector field, and 2) magnitude's histogram. Finally, it was concluded that inversion procedures are improved when the velocity field's behavior is considered, thus, the deterministic method is more suitable for unconfined aquifers than confined ones. McMC has restricted applications and requires a lot of information (particularly in potentials fields) while MRF has a remarkable response especially when dealing with confined aquifers.

MC3, Version 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cawkwell, Marc Jon

2016-09-09

The MC3 code is used to perform Monte Carlo simulations in the isothermal-isobaric ensemble (constant number of particles, temperature, and pressure) on molecular crystals. The molecules within the periodic simulation cell are treated as rigid bodies, alleviating the requirement for a complex interatomic potential. Intermolecular interactions are described using generic, atom-centered pair potentials whose parameterization is taken from the literature [D. E. Williams, J. Comput. Chem., 22, 1154 (2001)] and electrostatic interactions arising from atom-centered, fixed, point partial charges. The primary uses of the MC3 code are the computation of i) the temperature and pressure dependence of lattice parameters andmore » thermal expansion coefficients, ii) tensors of elastic constants and compliances via the Parrinello and Rahman’s fluctuation formula [M. Parrinello and A. Rahman, J. Chem. Phys., 76, 2662 (1982)], and iii) the investigation of polymorphic phase transformations. The MC3 code is written in Fortran90 and requires LAPACK and BLAS linear algebra libraries to be linked during compilation. Computationally expensive loops are accelerated using OpenMP.« less