Poster — Thur Eve — 14: Improving Tissue Segmentation for Monte Carlo Dose Calculation using DECT

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

Di Salvio, A.; Bedwani, S.; Carrier, J-F.

2014-08-15

Purpose: To improve Monte Carlo dose calculation accuracy through a new tissue segmentation technique with dual energy CT (DECT). Methods: Electron density (ED) and effective atomic number (EAN) can be extracted directly from DECT data with a stoichiometric calibration method. Images are acquired with Monte Carlo CT projections using the user code egs-cbct and reconstructed using an FDK backprojection algorithm. Calibration is performed using projections of a numerical RMI phantom. A weighted parameter algorithm then uses both EAN and ED to assign materials to voxels from DECT simulated images. This new method is compared to a standard tissue characterization frommore » single energy CT (SECT) data using a segmented calibrated Hounsfield unit (HU) to ED curve. Both methods are compared to the reference numerical head phantom. Monte Carlo simulations on uniform phantoms of different tissues using dosxyz-nrc show discrepancies in depth-dose distributions. Results: Both SECT and DECT segmentation methods show similar performance assigning soft tissues. Performance is however improved with DECT in regions with higher density, such as bones, where it assigns materials correctly 8% more often than segmentation with SECT, considering the same set of tissues and simulated clinical CT images, i.e. including noise and reconstruction artifacts. Furthermore, Monte Carlo results indicate that kV photon beam depth-dose distributions can double between two tissues of density higher than muscle. Conclusions: A direct acquisition of ED and the added information of EAN with DECT data improves tissue segmentation and increases the accuracy of Monte Carlo dose calculation in kV photon beams.« less

Monte Carlo simulations for angular and spatial distributions in therapeutic-energy proton beams

NASA Astrophysics Data System (ADS)

Lin, Yi-Chun; Pan, C. Y.; Chiang, K. J.; Yuan, M. C.; Chu, C. H.; Tsai, Y. W.; Teng, P. K.; Lin, C. H.; Chao, T. C.; Lee, C. C.; Tung, C. J.; Chen, A. E.

2017-11-01

The purpose of this study is to compare the angular and spatial distributions of therapeutic-energy proton beams obtained from the FLUKA, GEANT4 and MCNP6 Monte Carlo codes. The Monte Carlo simulations of proton beams passing through two thin targets and a water phantom were investigated to compare the primary and secondary proton fluence distributions and dosimetric differences among these codes. The angular fluence distributions, central axis depth-dose profiles, and lateral distributions of the Bragg peak cross-field were calculated to compare the proton angular and spatial distributions and energy deposition. Benchmark verifications from three different Monte Carlo simulations could be used to evaluate the residual proton fluence for the mean range and to estimate the depth and lateral dose distributions and the characteristic depths and lengths along the central axis as the physical indices corresponding to the evaluation of treatment effectiveness. The results showed a general agreement among codes, except that some deviations were found in the penumbra region. These calculated results are also particularly helpful for understanding primary and secondary proton components for stray radiation calculation and reference proton standard determination, as well as for determining lateral dose distribution performance in proton small-field dosimetry. By demonstrating these calculations, this work could serve as a guide to the recent field of Monte Carlo methods for therapeutic-energy protons.

Estimation of whole-body radiation exposure from brachytherapy for oral cancer using a Monte Carlo simulation

PubMed Central

Ozaki, Y.; Kaida, A.; Miura, M.; Nakagawa, K.; Toda, K.; Yoshimura, R.; Sumi, Y.; Kurabayashi, T.

2017-01-01

Abstract Early stage oral cancer can be cured with oral brachytherapy, but whole-body radiation exposure status has not been previously studied. Recently, the International Commission on Radiological Protection Committee (ICRP) recommended the use of ICRP phantoms to estimate radiation exposure from external and internal radiation sources. In this study, we used a Monte Carlo simulation with ICRP phantoms to estimate whole-body exposure from oral brachytherapy. We used a Particle and Heavy Ion Transport code System (PHITS) to model oral brachytherapy with 192Ir hairpins and 198Au grains and to perform a Monte Carlo simulation on the ICRP adult reference computational phantoms. To confirm the simulations, we also computed local dose distributions from these small sources, and compared them with the results from Oncentra manual Low Dose Rate Treatment Planning (mLDR) software which is used in day-to-day clinical practice. We successfully obtained data on absorbed dose for each organ in males and females. Sex-averaged equivalent doses were 0.547 and 0.710 Sv with 192Ir hairpins and 198Au grains, respectively. Simulation with PHITS was reliable when compared with an alternative computational technique using mLDR software. We concluded that the absorbed dose for each organ and whole-body exposure from oral brachytherapy can be estimated with Monte Carlo simulation using PHITS on ICRP reference phantoms. Effective doses for patients with oral cancer were obtained. PMID:28339846

Reference hypernetted chain theory for ferrofluid bilayer: Distribution functions compared with Monte Carlo

NASA Astrophysics Data System (ADS)

Polyakov, Evgeny A.; Vorontsov-Velyaminov, Pavel N.

2014-08-01

Properties of ferrofluid bilayer (modeled as a system of two planar layers separated by a distance h and each layer carrying a soft sphere dipolar liquid) are calculated in the framework of inhomogeneous Ornstein-Zernike equations with reference hypernetted chain closure (RHNC). The bridge functions are taken from a soft sphere (1/r12) reference system in the pressure-consistent closure approximation. In order to make the RHNC problem tractable, the angular dependence of the correlation functions is expanded into special orthogonal polynomials according to Lado. The resulting equations are solved using the Newton-GRMES algorithm as implemented in the public-domain solver NITSOL. Orientational densities and pair distribution functions of dipoles are compared with Monte Carlo simulation results. A numerical algorithm for the Fourier-Hankel transform of any positive integer order on a uniform grid is presented.

FW-CADIS Method for Global and Semi-Global Variance Reduction of Monte Carlo Radiation Transport Calculations

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

Wagner, John C; Peplow, Douglas E.; Mosher, Scott W

2014-01-01

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development ofmore » an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.« less

A reliability analysis framework with Monte Carlo simulation for weld structure of crane's beam

NASA Astrophysics Data System (ADS)

Wang, Kefei; Xu, Hongwei; Qu, Fuzheng; Wang, Xin; Shi, Yanjun

2018-04-01

The reliability of the crane product in engineering is the core competitiveness of the product. This paper used Monte Carlo method analyzed the reliability of the weld metal structure of the bridge crane whose limit state function is mathematical expression. Then we obtained the minimum reliable welding feet height value for the welds between cover plate and web plate on main beam in different coefficients of variation. This paper provides a new idea and reference for the growth of the inherent reliability of crane.

A Monte-Carlo Benchmark of TRIPOLI-4® and MCNP on ITER neutronics

NASA Astrophysics Data System (ADS)

Blanchet, David; Pénéliau, Yannick; Eschbach, Romain; Fontaine, Bruno; Cantone, Bruno; Ferlet, Marc; Gauthier, Eric; Guillon, Christophe; Letellier, Laurent; Proust, Maxime; Mota, Fernando; Palermo, Iole; Rios, Luis; Guern, Frédéric Le; Kocan, Martin; Reichle, Roger

2017-09-01

Radiation protection and shielding studies are often based on the extensive use of 3D Monte-Carlo neutron and photon transport simulations. ITER organization hence recommends the use of MCNP-5 code (version 1.60), in association with the FENDL-2.1 neutron cross section data library, specifically dedicated to fusion applications. The MCNP reference model of the ITER tokamak, the `C-lite', is being continuously developed and improved. This article proposes to develop an alternative model, equivalent to the 'C-lite', but for the Monte-Carlo code TRIPOLI-4®. A benchmark study is defined to test this new model. Since one of the most critical areas for ITER neutronics analysis concerns the assessment of radiation levels and Shutdown Dose Rates (SDDR) behind the Equatorial Port Plugs (EPP), the benchmark is conducted to compare the neutron flux through the EPP. This problem is quite challenging with regard to the complex geometry and considering the important neutron flux attenuation ranging from 1014 down to 108 n•cm-2•s-1. Such code-to-code comparison provides independent validation of the Monte-Carlo simulations, improving the confidence in neutronic results.

AREVA Developments for an Efficient and Reliable use of Monte Carlo codes for Radiation Transport Applications

NASA Astrophysics Data System (ADS)

Chapoutier, Nicolas; Mollier, François; Nolin, Guillaume; Culioli, Matthieu; Mace, Jean-Reynald

2017-09-01

In the context of the rising of Monte Carlo transport calculations for any kind of application, AREVA recently improved its suite of engineering tools in order to produce efficient Monte Carlo workflow. Monte Carlo codes, such as MCNP or TRIPOLI, are recognized as reference codes to deal with a large range of radiation transport problems. However the inherent drawbacks of theses codes - laboring input file creation and long computation time - contrast with the maturity of the treatment of the physical phenomena. The goals of the recent AREVA developments were to reach similar efficiency as other mature engineering sciences such as finite elements analyses (e.g. structural or fluid dynamics). Among the main objectives, the creation of a graphical user interface offering CAD tools for geometry creation and other graphical features dedicated to the radiation field (source definition, tally definition) has been reached. The computations times are drastically reduced compared to few years ago thanks to the use of massive parallel runs, and above all, the implementation of hybrid variance reduction technics. From now engineering teams are capable to deliver much more prompt support to any nuclear projects dealing with reactors or fuel cycle facilities from conceptual phase to decommissioning.

Comparison of deterministic and stochastic methods for time-dependent Wigner simulations

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

Shao, Sihong, E-mail: sihong@math.pku.edu.cn; Sellier, Jean Michel, E-mail: jeanmichel.sellier@parallel.bas.bg

2015-11-01

Recently a Monte Carlo method based on signed particles for time-dependent simulations of the Wigner equation has been proposed. While it has been thoroughly validated against physical benchmarks, no technical study about its numerical accuracy has been performed. To this end, this paper presents the first step towards the construction of firm mathematical foundations for the signed particle Wigner Monte Carlo method. An initial investigation is performed by means of comparisons with a cell average spectral element method, which is a highly accurate deterministic method and utilized to provide reference solutions. Several different numerical tests involving the time-dependent evolution ofmore » a quantum wave-packet are performed and discussed in deep details. In particular, this allows us to depict a set of crucial criteria for the signed particle Wigner Monte Carlo method to achieve a satisfactory accuracy.« less

Monte Carlo simulation of energy-dispersive x-ray fluorescence and applications

NASA Astrophysics Data System (ADS)

Li, Fusheng

Four key components with regards to Monte Carlo Library Least Squares (MCLLS) have been developed by the author. These include: a comprehensive and accurate Monte Carlo simulation code - CEARXRF5 with Differential Operators (DO) and coincidence sampling, Detector Response Function (DRF), an integrated Monte Carlo - Library Least-Squares (MCLLS) Graphical User Interface (GUI) visualization System (MCLLSPro) and a new reproducible and flexible benchmark experiment setup. All these developments or upgrades enable the MCLLS approach to be a useful and powerful tool for a tremendous variety of elemental analysis applications. CEARXRF, a comprehensive and accurate Monte Carlo code for simulating the total and individual library spectral responses of all elements, has been recently upgraded to version 5 by the author. The new version has several key improvements: input file format fully compatible with MCNP5, a new efficient general geometry tracking code, versatile source definitions, various variance reduction techniques (e.g. weight window mesh and splitting, stratifying sampling, etc.), a new cross section data storage and accessing method which improves the simulation speed by a factor of four and new cross section data, upgraded differential operators (DO) calculation capability, and also an updated coincidence sampling scheme which including K-L and L-L coincidence X-Rays, while keeping all the capabilities of the previous version. The new Differential Operators method is powerful for measurement sensitivity study and system optimization. For our Monte Carlo EDXRF elemental analysis system, it becomes an important technique for quantifying the matrix effect in near real time when combined with the MCLLS approach. An integrated visualization GUI system has been developed by the author to perform elemental analysis using iterated Library Least-Squares method for various samples when an initial guess is provided. This software was built on the Borland C++ Builder platform and has a user-friendly interface to accomplish all qualitative and quantitative tasks easily. That is to say, the software enables users to run the forward Monte Carlo simulation (if necessary) or use previously calculated Monte Carlo library spectra to obtain the sample elemental composition estimation within a minute. The GUI software is easy to use with user-friendly features and has the capability to accomplish all related tasks in a visualization environment. It can be a powerful tool for EDXRF analysts. A reproducible experiment setup has been built and experiments have been performed to benchmark the system. Two types of Standard Reference Materials (SRM), stainless steel samples from National Institute of Standards and Technology (NIST) and aluminum alloy samples from Alcoa Inc., with certified elemental compositions, are tested with this reproducible prototype system using a 109Cd radioisotope source (20mCi) and a liquid nitrogen cooled Si(Li) detector. The results show excellent agreement between the calculated sample compositions and their reference values and the approach is very fast.

Estimation of whole-body radiation exposure from brachytherapy for oral cancer using a Monte Carlo simulation.

PubMed

Ozaki, Y; Watanabe, H; Kaida, A; Miura, M; Nakagawa, K; Toda, K; Yoshimura, R; Sumi, Y; Kurabayashi, T

2017-07-01

Early stage oral cancer can be cured with oral brachytherapy, but whole-body radiation exposure status has not been previously studied. Recently, the International Commission on Radiological Protection Committee (ICRP) recommended the use of ICRP phantoms to estimate radiation exposure from external and internal radiation sources. In this study, we used a Monte Carlo simulation with ICRP phantoms to estimate whole-body exposure from oral brachytherapy. We used a Particle and Heavy Ion Transport code System (PHITS) to model oral brachytherapy with 192Ir hairpins and 198Au grains and to perform a Monte Carlo simulation on the ICRP adult reference computational phantoms. To confirm the simulations, we also computed local dose distributions from these small sources, and compared them with the results from Oncentra manual Low Dose Rate Treatment Planning (mLDR) software which is used in day-to-day clinical practice. We successfully obtained data on absorbed dose for each organ in males and females. Sex-averaged equivalent doses were 0.547 and 0.710 Sv with 192Ir hairpins and 198Au grains, respectively. Simulation with PHITS was reliable when compared with an alternative computational technique using mLDR software. We concluded that the absorbed dose for each organ and whole-body exposure from oral brachytherapy can be estimated with Monte Carlo simulation using PHITS on ICRP reference phantoms. Effective doses for patients with oral cancer were obtained. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145.

PubMed

Rueda, Oscar M; Diaz-Uriarte, Ramon

2007-10-16

Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state. We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints. The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined. Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).

Reference dosimetry of proton pencil beams based on dose-area product: a proof of concept.

PubMed

Gomà, Carles; Safai, Sairos; Vörös, Sándor

2017-06-21

This paper describes a novel approach to the reference dosimetry of proton pencil beams based on dose-area product ([Formula: see text]). It depicts the calibration of a large-diameter plane-parallel ionization chamber in terms of dose-area product in a 60 Co beam, the Monte Carlo calculation of beam quality correction factors-in terms of dose-area product-in proton beams, the Monte Carlo calculation of nuclear halo correction factors, and the experimental determination of [Formula: see text] of a single proton pencil beam. This new approach to reference dosimetry proves to be feasible, as it yields [Formula: see text] values in agreement with the standard and well-established approach of determining the absorbed dose to water at the centre of a broad homogeneous field generated by the superposition of regularly-spaced proton pencil beams.

Monte Carlo study of disorder in HMTA

NASA Astrophysics Data System (ADS)

Goossens, D. J.; Welberry, T. R.

2001-12-01

We investigate disordered solids by automated fitting of a Monte Carlo simulation of a crystal to observed single-crystal diffuse X-ray scattering. This method has been extended to the study of crystals of relatively large organic molecules by using a z-matrix to describe the molecules. This allows exploration of motions within molecules. We refer to the correlated thermal motion observed in benzil, and to the occupational and thermal disorder in the 1:1 adduct of hexamethylenetetramine and azelaic acid, HMTA. The technique is capable of giving insight into modes of vibration within molecules and correlated motions between molecules.

Effective dose evaluation of NORM-added consumer products using Monte Carlo simulations and the ICRP computational human phantoms.

PubMed

Lee, Hyun Cheol; Yoo, Do Hyeon; Testa, Mauro; Shin, Wook-Geun; Choi, Hyun Joon; Ha, Wi-Ho; Yoo, Jaeryong; Yoon, Seokwon; Min, Chul Hee

2016-04-01

The aim of this study is to evaluate the potential hazard of naturally occurring radioactive material (NORM) added consumer products. Using the Monte Carlo method, the radioactive products were simulated with ICRP reference phantom and the organ doses were calculated with the usage scenario. Finally, the annual effective doses were evaluated as lower than the public dose limit of 1mSv y(-1) for 44 products. It was demonstrated that NORM-added consumer products could be quantitatively assessed for the safety regulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger

2008-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael

2007-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

Preliminary estimates of nucleon fluxes in a water target exposed to solar-flare protons: BRYNTRN versus Monte Carlo code

NASA Technical Reports Server (NTRS)

Shinn, Judy L.; Wilson, John W.; Lone, M. A.; Wong, P. Y.; Costen, Robert C.

1994-01-01

A baryon transport code (BRYNTRN) has previously been verified using available Monte Carlo results for a solar-flare spectrum as the reference. Excellent results were obtained, but the comparisons were limited to the available data on dose and dose equivalent for moderate penetration studies that involve minor contributions from secondary neutrons. To further verify the code, the secondary energy spectra of protons and neutrons are calculated using BRYNTRN and LAHET (Los Alamos High-Energy Transport code, which is a Monte Carlo code). These calculations are compared for three locations within a water slab exposed to the February 1956 solar-proton spectrum. Reasonable agreement was obtained when various considerations related to the calculational techniques and their limitations were taken into account. Although the Monte Carlo results are preliminary, it appears that the neutron albedo, which is not currently treated in BRYNTRN, might be a cause for the large discrepancy seen at small penetration depths. It also appears that the nonelastic neutron production cross sections in BRYNTRN may underestimate the number of neutrons produced in proton collisions with energies below 200 MeV. The notion that the poor energy resolution in BRYNTRN may cause a large truncation error in neutron elastic scattering requires further study.

Statistical methods for launch vehicle guidance, navigation, and control (GN&C) system design and analysis

NASA Astrophysics Data System (ADS)

Rose, Michael Benjamin

A novel trajectory and attitude control and navigation analysis tool for powered ascent is developed. The tool is capable of rapid trade-space analysis and is designed to ultimately reduce turnaround time for launch vehicle design, mission planning, and redesign work. It is streamlined to quickly determine trajectory and attitude control dispersions, propellant dispersions, orbit insertion dispersions, and navigation errors and their sensitivities to sensor errors, actuator execution uncertainties, and random disturbances. The tool is developed by applying both Monte Carlo and linear covariance analysis techniques to a closed-loop, launch vehicle guidance, navigation, and control (GN&C) system. The nonlinear dynamics and flight GN&C software models of a closed-loop, six-degree-of-freedom (6-DOF), Monte Carlo simulation are formulated and developed. The nominal reference trajectory (NRT) for the proposed lunar ascent trajectory is defined and generated. The Monte Carlo truth models and GN&C algorithms are linearized about the NRT, the linear covariance equations are formulated, and the linear covariance simulation is developed. The performance of the launch vehicle GN&C system is evaluated using both Monte Carlo and linear covariance techniques and their trajectory and attitude control dispersion, propellant dispersion, orbit insertion dispersion, and navigation error results are validated and compared. Statistical results from linear covariance analysis are generally within 10% of Monte Carlo results, and in most cases the differences are less than 5%. This is an excellent result given the many complex nonlinearities that are embedded in the ascent GN&C problem. Moreover, the real value of this tool lies in its speed, where the linear covariance simulation is 1036.62 times faster than the Monte Carlo simulation. Although the application and results presented are for a lunar, single-stage-to-orbit (SSTO), ascent vehicle, the tools, techniques, and mathematical formulations that are discussed are applicable to ascent on Earth or other planets as well as other rocket-powered systems such as sounding rockets and ballistic missiles.

SU-F-T-111: Investigation of the Attila Deterministic Solver as a Supplement to Monte Carlo for Calculating Out-Of-Field Radiotherapy Dose

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

Mille, M; Lee, C; Failla, G

Purpose: To use the Attila deterministic solver as a supplement to Monte Carlo for calculating out-of-field organ dose in support of epidemiological studies looking at the risks of second cancers. Supplemental dosimetry tools are needed to speed up dose calculations for studies involving large-scale patient cohorts. Methods: Attila is a multi-group discrete ordinates code which can solve the 3D photon-electron coupled linear Boltzmann radiation transport equation on a finite-element mesh. Dose is computed by multiplying the calculated particle flux in each mesh element by a medium-specific energy deposition cross-section. The out-of-field dosimetry capability of Attila is investigated by comparing averagemore » organ dose to that which is calculated by Monte Carlo simulation. The test scenario consists of a 6 MV external beam treatment of a female patient with a tumor in the left breast. The patient is simulated by a whole-body adult reference female computational phantom. Monte Carlo simulations were performed using MCNP6 and XVMC. Attila can export a tetrahedral mesh for MCNP6, allowing for a direct comparison between the two codes. The Attila and Monte Carlo methods were also compared in terms of calculation speed and complexity of simulation setup. A key perquisite for this work was the modeling of a Varian Clinac 2100 linear accelerator. Results: The solid mesh of the torso part of the adult female phantom for the Attila calculation was prepared using the CAD software SpaceClaim. Preliminary calculations suggest that Attila is a user-friendly software which shows great promise for our intended application. Computational performance is related to the number of tetrahedral elements included in the Attila calculation. Conclusion: Attila is being explored as a supplement to the conventional Monte Carlo radiation transport approach for performing retrospective patient dosimetry. The goal is for the dosimetry to be sufficiently accurate for use in retrospective epidemiological investigations.« less

Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy.

PubMed

Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe

2015-07-07

The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm(3) calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.

Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy

NASA Astrophysics Data System (ADS)

Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe

2015-07-01

The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm3 calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.

Development of Monte Carlo based real-time treatment planning system with fast calculation algorithm for boron neutron capture therapy.

PubMed

Takada, Kenta; Kumada, Hiroaki; Liem, Peng Hong; Sakurai, Hideyuki; Sakae, Takeji

2016-12-01

We simulated the effect of patient displacement on organ doses in boron neutron capture therapy (BNCT). In addition, we developed a faster calculation algorithm (NCT high-speed) to simulate irradiation more efficiently. We simulated dose evaluation for the standard irradiation position (reference position) using a head phantom. Cases were assumed where the patient body is shifted in lateral directions compared to the reference position, as well as in the direction away from the irradiation aperture. For three groups of neutron (thermal, epithermal, and fast), flux distribution using NCT high-speed with a voxelized homogeneous phantom was calculated. The three groups of neutron fluxes were calculated for the same conditions with Monte Carlo code. These calculated results were compared. In the evaluations of body movements, there were no significant differences even with shifting up to 9mm in the lateral directions. However, the dose decreased by about 10% with shifts of 9mm in a direction away from the irradiation aperture. When comparing both calculations in the phantom surface up to 3cm, the maximum differences between the fluxes calculated by NCT high-speed with those calculated by Monte Carlo code for thermal neutrons and epithermal neutrons were 10% and 18%, respectively. The time required for NCT high-speed code was about 1/10th compared to Monte Carlo calculation. In the evaluation, the longitudinal displacement has a considerable effect on the organ doses. We also achieved faster calculation of depth distribution of thermal neutron flux using NCT high-speed calculation code. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Whole body counter calibration using Monte Carlo modeling with an array of phantom sizes based on national anthropometric reference data

USDA-ARS?s Scientific Manuscript database

During construction of the whole body counter (WBC) at the Children’s Nutrition Research Center (CNRC), efficiency calibration was needed to translate acquired counts of 40K to actual grams of potassium for measurement of total body potassium (TBK) in a diverse subject population. The MCNP Monte Car...

NOTE: Monte Carlo simulation of correction factors for IAEA TLD holders

NASA Astrophysics Data System (ADS)

Hultqvist, Martha; Fernández-Varea, José M.; Izewska, Joanna

2010-03-01

The IAEA standard thermoluminescent dosimeter (TLD) holder has been developed for the IAEA/WHO TLD postal dose program for audits of high-energy photon beams, and it is also employed by the ESTRO-QUALity assurance network (EQUAL) and several national TLD audit networks. Factors correcting for the influence of the holder on the TL signal under reference conditions have been calculated in the present work from Monte Carlo simulations with the PENELOPE code for 60Co γ-rays and 4, 6, 10, 15, 18 and 25 MV photon beams. The simulation results are around 0.2% smaller than measured factors reported in the literature, but well within the combined standard uncertainties. The present study supports the use of the experimentally obtained holder correction factors in the determination of the absorbed dose to water from the TL readings; the factors calculated by means of Monte Carlo simulations may be adopted for the cases where there are no measured data.

High-Fidelity Coupled Monte-Carlo/Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Ivanov, Aleksandar; Sanchez, Victor; Ivanov, Kostadin

2014-06-01

Monte Carlo methods have been used as reference reactor physics calculation tools worldwide. The advance in computer technology allows the calculation of detailed flux distributions in both space and energy. In most of the cases however, those calculations are done under the assumption of homogeneous material density and temperature distributions. The aim of this work is to develop a consistent methodology for providing realistic three-dimensional thermal-hydraulic distributions by coupling the in-house developed sub-channel code SUBCHANFLOW with the standard Monte-Carlo transport code MCNP. In addition to the innovative technique of on-the fly material definition, a flux-based weight-window technique has been introduced to improve both the magnitude and the distribution of the relative errors. Finally, a coupled code system for the simulation of steady-state reactor physics problems has been developed. Besides the problem of effective feedback data interchange between the codes, the treatment of temperature dependence of the continuous energy nuclear data has been investigated.

Calculation of electron Dose Point Kernel in water with GEANT4 for medical application

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

Guimaraes, C. C.; Sene, F. F.; Martinelli, J. R.

2009-06-03

The rapid insertion of new technologies in medical physics in the last years, especially in nuclear medicine, has been followed by a great development of faster Monte Carlo algorithms. GEANT4 is a Monte Carlo toolkit that contains the tools to simulate the problems of particle transport through matter. In this work, GEANT4 was used to calculate the dose-point-kernel (DPK) for monoenergetic electrons in water, which is an important reference medium for nuclear medicine. The three different physical models of electromagnetic interactions provided by GEANT4 - Low Energy, Penelope and Standard - were employed. To verify the adequacy of these models,more » the results were compared with references from the literature. For all energies and physical models, the agreement between calculated DPKs and reported values is satisfactory.« less

EDITORIAL: Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009)

NASA Astrophysics Data System (ADS)

Spezi, Emiliano

2010-08-01

Sixty years after the paper 'The Monte Carlo method' by N Metropolis and S Ulam in The Journal of the American Statistical Association (Metropolis and Ulam 1949), use of the most accurate algorithm for computer modelling of radiotherapy linear accelerators, radiation detectors and three dimensional patient dose was discussed in Wales (UK). The Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) was held at the National Museum of Wales in Cardiff. The event, organized by Velindre NHS Trust, Cardiff University and Cancer Research Wales, lasted two and a half days, during which leading experts and contributing authors presented and discussed the latest advances in the field of Monte Carlo treatment planning (MCTP). MCTP2009 was highly successful, judging from the number of participants which was in excess of 140. Of the attendees, 24% came from the UK, 46% from the rest of Europe, 12% from North America and 18% from the rest of the World. Fifty-three oral presentations and 24 posters were delivered in a total of 12 scientific sessions. MCTP2009 follows the success of previous similar initiatives (Verhaegen and Seuntjens 2005, Reynaert 2007, Verhaegen and Seuntjens 2008), and confirms the high level of interest in Monte Carlo technology for radiotherapy treatment planning. The 13 articles selected for this special section (following Physics in Medicine and Biology's usual rigorous peer-review procedure) give a good picture of the high quality of the work presented at MCTP2009. The book of abstracts can be downloaded from http://www.mctp2009.org. I wish to thank the IOP Medical Physics and Computational Physics Groups for their financial support, Elekta Ltd and Dosisoft for sponsoring MCTP2009, and leading manufacturers such as BrainLab, Nucletron and Varian for showcasing their latest MC-based radiotherapy solutions during a dedicated technical session. I am also very grateful to the eight invited speakers who kindly accepted to give keynote presentations which contributed significantly to raising the quality of the event and capturing the interest of the medical physics community. I also wish to thank all those who contributed to the success of MCTP2009: the members of the local Organizing Committee and the Workshop Management Team who managed the event very efficiently, the members of the European Working Group in Monte Carlo Treatment Planning (EWG-MCTP) who acted as Guest Associate Editors for the MCTP2009 abstracts reviewing process, and all the authors who generated new, high quality work. Finally, I hope that you find the contents of this special section enjoyable and informative. Emiliano Spezi Chairman of MCTP2009 Organizing Committee and Guest Editor References Metropolis N and Ulam S 1949 The Monte Carlo method J. Amer. Stat. Assoc. 44 335-41 Reynaert N 2007 First European Workshop on Monte Carlo Treatment Planning J. Phys.: Conf. Ser. 74 011001 Verhaegen F and Seuntjens J 2005 International Workshop on Current Topics in Monte Carlo Treatment Planning Phys. Med. Biol. 50 Verhaegen F and Seuntjens J 2008 International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification J. Phys.: Conf. Ser. 102 011001

Modeling of thin-film GaAs growth

NASA Technical Reports Server (NTRS)

Heinbockel, J. H.

1981-01-01

Efforts to produce a Monte Carlo computer program for the analysis of crystal growth are briefly discussed. A literature survey was conducted of articles relating to the subject. A list of references reviewed is presented.

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.

The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…

(U) Introduction to Monte Carlo Methods

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

Hungerford, Aimee L.

2017-03-20

Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.

Automatic variance reduction for Monte Carlo simulations via the local importance function transform

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

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditionalmore » Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.« less

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

NASA Astrophysics Data System (ADS)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Monte Carlo dose calculations of beta-emitting sources for intravascular brachytherapy: a comparison between EGS4, EGSnrc, and MCNP.

PubMed

Wang, R; Li, X A

2001-02-01

The dose parameters for the beta-particle emitting 90Sr/90Y source for intravascular brachytherapy (IVBT) have been calculated by different investigators. At a distant distance from the source, noticeable differences are seen in these parameters calculated using different Monte Carlo codes. The purpose of this work is to quantify as well as to understand these differences. We have compared a series of calculations using an EGS4, an EGSnrc, and the MCNP Monte Carlo codes. Data calculated and compared include the depth dose curve for a broad parallel beam of electrons, and radial dose distributions for point electron sources (monoenergetic or polyenergetic) and for a real 90Sr/90Y source. For the 90Sr/90Y source, the doses at the reference position (2 mm radial distance) calculated by the three code agree within 2%. However, the differences between the dose calculated by the three codes can be over 20% in the radial distance range interested in IVBT. The difference increases with radial distance from source, and reaches 30% at the tail of dose curve. These differences may be partially attributed to the different multiple scattering theories and Monte Carlo models for electron transport adopted in these three codes. Doses calculated by the EGSnrc code are more accurate than those by the EGS4. The two calculations agree within 5% for radial distance <6 mm.

The structure of PX3 (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling.

PubMed

Pothoczki, Szilvia; Temleitner, László; Pusztai, László

2014-02-07

Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr3 electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl3 and PI3 are largely driven by steric effects.

SU-E-T-188: Film Dosimetry Verification of Monte Carlo Generated Electron Treatment Plans

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

Enright, S; Asprinio, A; Lu, L

2014-06-01

Purpose: The purpose of this study was to compare dose distributions from film measurements to Monte Carlo generated electron treatment plans. Irradiation with electrons offers the advantages of dose uniformity in the target volume and of minimizing the dose to deeper healthy tissue. Using the Monte Carlo algorithm will improve dose accuracy in regions with heterogeneities and irregular surfaces. Methods: Dose distributions from GafChromic{sup ™} EBT3 films were compared to dose distributions from the Electron Monte Carlo algorithm in the Eclipse{sup ™} radiotherapy treatment planning system. These measurements were obtained for 6MeV, 9MeV and 12MeV electrons at two depths. Allmore » phantoms studied were imported into Eclipse by CT scan. A 1 cm thick solid water template with holes for bonelike and lung-like plugs was used. Different configurations were used with the different plugs inserted into the holes. Configurations with solid-water plugs stacked on top of one another were also used to create an irregular surface. Results: The dose distributions measured from the film agreed with those from the Electron Monte Carlo treatment plan. Accuracy of Electron Monte Carlo algorithm was also compared to that of Pencil Beam. Dose distributions from Monte Carlo had much higher pass rates than distributions from Pencil Beam when compared to the film. The pass rate for Monte Carlo was in the 80%–99% range, where the pass rate for Pencil Beam was as low as 10.76%. Conclusion: The dose distribution from Monte Carlo agreed with the measured dose from the film. When compared to the Pencil Beam algorithm, pass rates for Monte Carlo were much higher. Monte Carlo should be used over Pencil Beam for regions with heterogeneities and irregular surfaces.« less

Optimized nested Markov chain Monte Carlo sampling: theory

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

Coe, Joshua D; Shaw, M Sam; Sewell, Thomas D

2009-01-01

Metropolis Monte Carlo sampling of a reference potential is used to build a Markov chain in the isothermal-isobaric ensemble. At the endpoints of the chain, the energy is reevaluated at a different level of approximation (the 'full' energy) and a composite move encompassing all of the intervening steps is accepted on the basis of a modified Metropolis criterion. By manipulating the thermodynamic variables characterizing the reference system we maximize the average acceptance probability of composite moves, lengthening significantly the random walk made between consecutive evaluations of the full energy at a fixed acceptance probability. This provides maximally decorrelated samples ofmore » the full potential, thereby lowering the total number required to build ensemble averages of a given variance. The efficiency of the method is illustrated using model potentials appropriate to molecular fluids at high pressure. Implications for ab initio or density functional theory (DFT) treatment are discussed.« less

Neutrino oscillation parameter sampling with MonteCUBES

NASA Astrophysics Data System (ADS)

Blennow, Mattias; Fernandez-Martinez, Enrique

2010-01-01

We present MonteCUBES ("Monte Carlo Utility Based Experiment Simulator"), a software package designed to sample the neutrino oscillation parameter space through Markov Chain Monte Carlo algorithms. MonteCUBES makes use of the GLoBES software so that the existing experiment definitions for GLoBES, describing long baseline and reactor experiments, can be used with MonteCUBES. MonteCUBES consists of two main parts: The first is a C library, written as a plug-in for GLoBES, implementing the Markov Chain Monte Carlo algorithm to sample the parameter space. The second part is a user-friendly graphical Matlab interface to easily read, analyze, plot and export the results of the parameter space sampling. Program summaryProgram title: MonteCUBES (Monte Carlo Utility Based Experiment Simulator) Catalogue identifier: AEFJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFJ_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.: 69 634 No. of bytes in distributed program, including test data, etc.: 3 980 776 Distribution format: tar.gz Programming language: C Computer: MonteCUBES builds and installs on 32 bit and 64 bit Linux systems where GLoBES is installed Operating system: 32 bit and 64 bit Linux RAM: Typically a few MBs Classification: 11.1 External routines: GLoBES [1,2] and routines/libraries used by GLoBES Subprograms used:Cat Id ADZI_v1_0, Title GLoBES, Reference CPC 177 (2007) 439 Nature of problem: Since neutrino masses do not appear in the standard model of particle physics, many models of neutrino masses also induce other types of new physics, which could affect the outcome of neutrino oscillation experiments. In general, these new physics imply high-dimensional parameter spaces that are difficult to explore using classical methods such as multi-dimensional projections and minimizations, such as those used in GLoBES [1,2]. Solution method: MonteCUBES is written as a plug-in to the GLoBES software [1,2] and provides the necessary methods to perform Markov Chain Monte Carlo sampling of the parameter space. This allows an efficient sampling of the parameter space and has a complexity which does not grow exponentially with the parameter space dimension. The integration of the MonteCUBES package with the GLoBES software makes sure that the experimental definitions already in use by the community can also be used with MonteCUBES, while also lowering the learning threshold for users who already know GLoBES. Additional comments: A Matlab GUI for interpretation of results is included in the distribution. Running time: The typical running time varies depending on the dimensionality of the parameter space, the complexity of the experiment, and how well the parameter space should be sampled. The running time for our simulations [3] with 15 free parameters at a Neutrino Factory with O(10) samples varied from a few hours to tens of hours. References:P. Huber, M. Lindner, W. Winter, Comput. Phys. Comm. 167 (2005) 195, hep-ph/0407333. P. Huber, J. Kopp, M. Lindner, M. Rolinec, W. Winter, Comput. Phys. Comm. 177 (2007) 432, hep-ph/0701187. S. Antusch, M. Blennow, E. Fernandez-Martinez, J. Lopez-Pavon, arXiv:0903.3986 [hep-ph].

Radiative characterization of random fibrous media with long cylindrical fibers: Comparison of single- and multi-RTE approaches

NASA Astrophysics Data System (ADS)

Randrianalisoa, Jaona; Haussener, Sophia; Baillis, Dominique; Lipiński, Wojciech

2017-11-01

Radiative heat transfer is analyzed in participating media consisting of long cylindrical fibers with a diameter in the limit of geometrical optics. The absorption and scattering coefficients and the scattering phase function of the medium are determined based on the discrete-level medium geometry and optical properties of individual fibers. The fibers are assumed to be randomly oriented and positioned inside the medium. Two approaches are employed: a volume-averaged two-intensity approach referred to as multi-RTE approach and a homogenized single-intensity approach referred to as the single-RTE approach. Both approaches require effective properties, determined using direct Monte Carlo ray tracing techniques. The macroscopic radiative transfer equations (for single intensity or two volume-averaged intensities) with the corresponding effective properties are solved using Monte Carlo techniques and allow for the determination of the radiative flux distribution as well as overall transmittance and reflectance of the medium. The results are compared against predictions by the direct Monte Carlo simulation on the exact morphology. The effects of fiber volume fraction and optical properties on the effective radiative properties and the overall slab radiative characteristics are investigated. The single-RTE approach gives accurate predictions for high porosity fibrous media (porosity about 95%). The multi-RTE approach is recommended for isotropic fibrous media with porosity in the range of 79-95%.

Tracking control of concentration profiles in a fed-batch bioreactor using a linear algebra methodology.

PubMed

Rómoli, Santiago; Serrano, Mario Emanuel; Ortiz, Oscar Alberto; Vega, Jorge Rubén; Eduardo Scaglia, Gustavo Juan

2015-07-01

Based on a linear algebra approach, this paper aims at developing a novel control law able to track reference profiles that were previously-determined in the literature. A main advantage of the proposed strategy is that the control actions are obtained by solving a system of linear equations. The optimal controller parameters are selected through Monte Carlo Randomized Algorithm in order to minimize a proposed cost index. The controller performance is evaluated through several tests, and compared with other controller reported in the literature. Finally, a Monte Carlo Randomized Algorithm is conducted to assess the performance of the proposed controller. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Recent advances and future prospects for Monte Carlo

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

Brown, Forrest B

2010-01-01

The history of Monte Carlo methods is closely linked to that of computers: The first known Monte Carlo program was written in 1947 for the ENIAC; a pre-release of the first Fortran compiler was used for Monte Carlo In 1957; Monte Carlo codes were adapted to vector computers in the 1980s, clusters and parallel computers in the 1990s, and teraflop systems in the 2000s. Recent advances include hierarchical parallelism, combining threaded calculations on multicore processors with message-passing among different nodes. With the advances In computmg, Monte Carlo codes have evolved with new capabilities and new ways of use. Production codesmore » such as MCNP, MVP, MONK, TRIPOLI and SCALE are now 20-30 years old (or more) and are very rich in advanced featUres. The former 'method of last resort' has now become the first choice for many applications. Calculations are now routinely performed on office computers, not just on supercomputers. Current research and development efforts are investigating the use of Monte Carlo methods on FPGAs. GPUs, and many-core processors. Other far-reaching research is exploring ways to adapt Monte Carlo methods to future exaflop systems that may have 1M or more concurrent computational processes.« less

Organ doses for reference adult male and female undergoing computed tomography estimated by Monte Carlo simulations

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

Lee, Choonsik; Kim, Kwang Pyo; Long, Daniel

2011-03-15

Purpose: To develop a computed tomography (CT) organ dose estimation method designed to readily provide organ doses in a reference adult male and female for different scan ranges to investigate the degree to which existing commercial programs can reasonably match organ doses defined in these more anatomically realistic adult hybrid phantomsMethods: The x-ray fan beam in the SOMATOM Sensation 16 multidetector CT scanner was simulated within the Monte Carlo radiation transport code MCNPX2.6. The simulated CT scanner model was validated through comparison with experimentally measured lateral free-in-air dose profiles and computed tomography dose index (CTDI) values. The reference adult malemore » and female hybrid phantoms were coupled with the established CT scanner model following arm removal to simulate clinical head and other body region scans. A set of organ dose matrices were calculated for a series of consecutive axial scans ranging from the top of the head to the bottom of the phantoms with a beam thickness of 10 mm and the tube potentials of 80, 100, and 120 kVp. The organ doses for head, chest, and abdomen/pelvis examinations were calculated based on the organ dose matrices and compared to those obtained from two commercial programs, CT-EXPO and CTDOSIMETRY. Organ dose calculations were repeated for an adult stylized phantom by using the same simulation method used for the adult hybrid phantom. Results: Comparisons of both lateral free-in-air dose profiles and CTDI values through experimental measurement with the Monte Carlo simulations showed good agreement to within 9%. Organ doses for head, chest, and abdomen/pelvis scans reported in the commercial programs exceeded those from the Monte Carlo calculations in both the hybrid and stylized phantoms in this study, sometimes by orders of magnitude. Conclusions: The organ dose estimation method and dose matrices established in this study readily provides organ doses for a reference adult male and female for different CT scan ranges and technical parameters. Organ doses from existing commercial programs do not reasonably match organ doses calculated for the hybrid phantoms due to differences in phantom anatomy, as well as differences in organ dose scaling parameters. The organ dose matrices developed in this study will be extended to cover different technical parameters, CT scanner models, and various age groups.« less

PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

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

Iandola, F N; O'Brien, M J; Procassini, R J

2010-11-29

Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improvesmore » usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.« less

Monte Carlo Modeling of the Initial Radiation Emitted by a Nuclear Device in the National Capital Region

DTIC Science & Technology

2013-07-01

also simulated in the models. Data was derived from calculations using the three-dimensional Monte Carlo radiation transport code MCNP (Monte Carlo N...32  B.  MCNP PHYSICS OPTIONS ......................................................................................... 33  C.  HAZUS...input deck’) for the MCNP , Monte Carlo N-Particle, radiation transport code. MCNP is a general-purpose code designed to simulate neutron, photon

Fixed-node quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Anderson, James B.

Quantum Monte Carlo methods cannot at present provide exact solutions of the Schrödinger equation for systems with more than a few electrons. But, quantum Monte Carlo calculations can provide very low energy, highly accurate solutions for many systems ranging up to several hundred electrons. These systems include atoms such as Be and Fe, molecules such as H2O, CH4, and HF, and condensed materials such as solid N2 and solid silicon. The quantum Monte Carlo predictions of their energies and structures may not be `exact', but they are the best available. Most of the Monte Carlo calculations for these systems have been carried out using approximately correct fixed nodal hypersurfaces and they have come to be known as `fixed-node quantum Monte Carlo' calculations. In this paper we review these `fixed node' calculations and the accuracies they yield.

Vectorized Monte Carlo methods for reactor lattice analysis

NASA Technical Reports Server (NTRS)

Brown, F. B.

1984-01-01

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Prompt Radiation Protection Factors

DTIC Science & Technology

2018-02-01

dimensional Monte-Carlo radiation transport code MCNP (Monte Carlo N-Particle) and the evaluation of the protection factors (ratio of dose in the open to...radiation was performed using the three dimensional Monte- Carlo radiation transport code MCNP (Monte Carlo N-Particle) and the evaluation of the protection...by detonation of a nuclear device have placed renewed emphasis on evaluation of the consequences in case of such an event. The Defense Threat

High order methods for the integration of the Bateman equations and other problems of the form of y‧ = F(y,t)y

NASA Astrophysics Data System (ADS)

Josey, C.; Forget, B.; Smith, K.

2017-12-01

This paper introduces two families of A-stable algorithms for the integration of y‧ = F (y , t) y: the extended predictor-corrector (EPC) and the exponential-linear (EL) methods. The structure of the algorithm families are described, and the method of derivation of the coefficients presented. The new algorithms are then tested on a simple deterministic problem and a Monte Carlo isotopic evolution problem. The EPC family is shown to be only second order for systems of ODEs. However, the EPC-RK45 algorithm had the highest accuracy on the Monte Carlo test, requiring at least a factor of 2 fewer function evaluations to achieve a given accuracy than a second order predictor-corrector method (center extrapolation / center midpoint method) with regards to Gd-157 concentration. Members of the EL family can be derived to at least fourth order. The EL3 and the EL4 algorithms presented are shown to be third and fourth order respectively on the systems of ODE test. In the Monte Carlo test, these methods did not overtake the accuracy of EPC methods before statistical uncertainty dominated the error. The statistical properties of the algorithms were also analyzed during the Monte Carlo problem. The new methods are shown to yield smaller standard deviations on final quantities as compared to the reference predictor-corrector method, by up to a factor of 1.4.

Monte Carlo modeling of spatial coherence: free-space diffraction

PubMed Central

Fischer, David G.; Prahl, Scott A.; Duncan, Donald D.

2008-01-01

We present a Monte Carlo method for propagating partially coherent fields through complex deterministic optical systems. A Gaussian copula is used to synthesize a random source with an arbitrary spatial coherence function. Physical optics and Monte Carlo predictions of the first- and second-order statistics of the field are shown for coherent and partially coherent sources for free-space propagation, imaging using a binary Fresnel zone plate, and propagation through a limiting aperture. Excellent agreement between the physical optics and Monte Carlo predictions is demonstrated in all cases. Convergence criteria are presented for judging the quality of the Monte Carlo predictions. PMID:18830335

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy

NASA Astrophysics Data System (ADS)

Marcatili, S.; Pettinato, C.; Daniels, S.; Lewis, G.; Edwards, P.; Fanti, S.; Spezi, E.

2013-04-01

We developed and validated a Monte-Carlo-based application (RAYDOSE) to generate patient-specific 3D dose maps on the basis of pre-treatment imaging studies. A CT DICOM image is used to model patient geometry, while repeated PET scans are employed to assess radionuclide kinetics and distribution at the voxel level. In this work, we describe the structure of this application and present the tests performed to validate it against reference data and experiments. We used the spheres of a NEMA phantom to calculate S values and total doses. The comparison with reference data from OLINDA/EXM showed an agreement within 2% for a sphere size above 2.8 cm diameter. A custom heterogeneous phantom composed of several layers of Perspex and lung equivalent material was used to compare TLD measurements of gamma radiation from 131I to Monte Carlo simulations. An agreement within 5% was found. RAYDOSE has been validated against reference data and experimental measurements and can be a useful multi-modality platform for treatment planning and research in MRT.

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".

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

NASA Astrophysics Data System (ADS)

Crevillén-García, D.; Power, H.

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

PubMed

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

PubMed Central

Power, H.

2017-01-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error. PMID:28878974

Structure and Thermodynamics of Polyolefin Melts

NASA Astrophysics Data System (ADS)

Weinhold, J. D.; Curro, J. G.; Habenschuss, A.; Londono, J. D.

1997-03-01

Subtle differences in the intermolecular packing of various polyolefins can create dissimilar permeability and mixing behavior. We have used a combination of the Polymer Reference Interaction Site Model (PRISM) and Monte Carlo simulation to study the structural and thermodynamic properties of realistic models for polyolefins. Results for polyisobutylene and syndiotactic polypropylene will be presented along with comparisons to wide-angle x-ray scattering experiments and properties determined from previous studies of polyethylene and isotactic polypropylene. Our technique uses a Monte Carlo simulation on an isolated molecule to determine the polymer's intramolecular structure. With this information, PRISM theory can predict the intermolecular packing for any liquid density and/or mixture composition in a computationally efficient manner. This approach will then be used to explore the mixing behavior of these polyolefins.

Dosimetry of 192Ir sources used for endovascular brachytherapy

NASA Astrophysics Data System (ADS)

Reynaert, N.; Van Eijkeren, M.; Taeymans, Y.; Thierens, H.

2001-02-01

An in-phantom calibration technique for 192Ir sources used for endovascular brachytherapy is presented. Three different source lengths were investigated. The calibration was performed in a solid phantom using a Farmer-type ionization chamber at source to detector distances ranging from 1 cm to 5 cm. The dosimetry protocol for medium-energy x-rays extended with a volume-averaging correction factor was used to convert the chamber reading to dose to water. The air kerma strength of the sources was determined as well. EGS4 Monte Carlo calculations were performed to determine the depth dose distribution at distances ranging from 0.6 mm to 10 cm from the source centre. In this way we were able to convert the absolute dose rate at 1 cm distance to the reference point chosen at 2 mm distance. The Monte Carlo results were confirmed by radiochromic film measurements, performed with a double-exposure technique. The dwell times to deliver a dose of 14 Gy at the reference point were determined and compared with results given by the source supplier (CORDIS). They determined the dwell times from a Sievert integration technique based on the source activity. The results from both methods agreed to within 2% for the 12 sources that were evaluated. A Visual Basic routine that superimposes dose distributions, based on the Monte Carlo calculations and the in-phantom calibration, onto intravascular ultrasound images is presented. This routine can be used as an online treatment planning program.

Minimal model for the secondary structures and conformational conversions in proteins

NASA Astrophysics Data System (ADS)

Imamura, Hideo

Better understanding of protein folding process can provide physical insights on the function of proteins and makes it possible to benefit from genetic information accumulated so far. Protein folding process normally takes place in less than seconds but even seconds are beyond reach of current computational power for simulations on a system of all-atom detail. Hence, to model and explore protein folding process it is crucial to construct a proper model that can adequately describe the physical process and mechanism for the relevant time scale. We discuss the reduced off-lattice model that can express _-helix and ?-hairpin conformations defined solely by a given sequence in order to investigate a protein folding mechanism of conformations such as a ?-hairpin and also to investigate conformational conversions in proteins. The first two chapters introduce and review essential concepts in protein folding modelling physical interaction in proteins, various simple models, and also review computational methods, in particular, the Metropolis Monte Carlo method, its dynamic interpretation and thermodynamic Monte Carlo algorithms. Chapter 3 describes the minimalist model that represents both _-helix and ?-sheet conformations using simple potentials. The native conformation can be specified by the sequence without particular conformational biases to a reference state. In Chapter 4, the model is used to investigate the folding mechanism of ?-hairpins exhaustively using the dynamic Monte Carlo and a thermodynamic Monte Carlo method an effcient combination of the multicanonical Monte Carlo and the weighted histogram analysis method. We show that the major folding pathways and folding rate depend on the location of a hydrophobic. The conformational conversions between _-helix and ?-sheet conformations are examined in Chapter 5 and 6. First, the conformational conversion due to mutation in a non-hydrophobic system and then the conformational conversion due to mutation with a hydrophobic pair at a different position at various temperatures are examined.

Quantum Gibbs ensemble Monte Carlo

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

Fantoni, Riccardo, E-mail: rfantoni@ts.infn.it; Moroni, Saverio, E-mail: moroni@democritos.it

We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of {sup 4}He in two dimensions.

Critical Analysis of Dual-Probe Heat-Pulse Technique Applied to Measuring Thermal Diffusivity

NASA Astrophysics Data System (ADS)

Bovesecchi, G.; Coppa, P.; Corasaniti, S.; Potenza, M.

2018-07-01

The paper presents an analysis of the experimental parameters involved in application of the dual-probe heat pulse technique, followed by a critical review of methods for processing thermal response data (e.g., maximum detection and nonlinear least square regression) and the consequent obtainable uncertainty. Glycerol was selected as testing liquid, and its thermal diffusivity was evaluated over the temperature range from - 20 °C to 60 °C. In addition, Monte Carlo simulation was used to assess the uncertainty propagation for maximum detection. It was concluded that maximum detection approach to process thermal response data gives the closest results to the reference data inasmuch nonlinear regression results are affected by major uncertainties due to partial correlation between the evaluated parameters. Besides, the interpolation of temperature data with a polynomial to find the maximum leads to a systematic difference between measured and reference data, as put into evidence by the Monte Carlo simulations; through its correction, this systematic error can be reduced to a negligible value, about 0.8 %.

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

Sudhyadhom, A; McGuinness, C; Descovich, M

Purpose: To develop a methodology for validation of a Monte-Carlo dose calculation model for robotic small field SRS/SBRT deliveries. Methods: In a robotic treatment planning system, a Monte-Carlo model was iteratively optimized to match with beam data. A two-part analysis was developed to verify this model. 1) The Monte-Carlo model was validated in a simulated water phantom versus a Ray-Tracing calculation on a single beam collimator-by-collimator calculation. 2) The Monte-Carlo model was validated to be accurate in the most challenging situation, lung, by acquiring in-phantom measurements. A plan was created and delivered in a CIRS lung phantom with film insert.more » Separately, plans were delivered in an in-house created lung phantom with a PinPoint chamber insert within a lung simulating material. For medium to large collimator sizes, a single beam was delivered to the phantom. For small size collimators (10, 12.5, and 15mm), a robotically delivered plan was created to generate a uniform dose field of irradiation over a 2×2cm{sup 2} area. Results: Dose differences in simulated water between Ray-Tracing and Monte-Carlo were all within 1% at dmax and deeper. Maximum dose differences occurred prior to dmax but were all within 3%. Film measurements in a lung phantom show high correspondence of over 95% gamma at the 2%/2mm level for Monte-Carlo. Ion chamber measurements for collimator sizes of 12.5mm and above were within 3% of Monte-Carlo calculated values. Uniform irradiation involving the 10mm collimator resulted in a dose difference of ∼8% for both Monte-Carlo and Ray-Tracing indicating that there may be limitations with the dose calculation. Conclusion: We have developed a methodology to validate a Monte-Carlo model by verifying that it matches in water and, separately, that it corresponds well in lung simulating materials. The Monte-Carlo model and algorithm tested may have more limited accuracy for 10mm fields and smaller.« less

Quasi-Monte Carlo Methods Applied to Tau-Leaping in Stochastic Biological Systems.

PubMed

Beentjes, Casper H L; Baker, Ruth E

2018-05-25

Quasi-Monte Carlo methods have proven to be effective extensions of traditional Monte Carlo methods in, amongst others, problems of quadrature and the sample path simulation of stochastic differential equations. By replacing the random number input stream in a simulation procedure by a low-discrepancy number input stream, variance reductions of several orders have been observed in financial applications. Analysis of stochastic effects in well-mixed chemical reaction networks often relies on sample path simulation using Monte Carlo methods, even though these methods suffer from typical slow [Formula: see text] convergence rates as a function of the number of sample paths N. This paper investigates the combination of (randomised) quasi-Monte Carlo methods with an efficient sample path simulation procedure, namely [Formula: see text]-leaping. We show that this combination is often more effective than traditional Monte Carlo simulation in terms of the decay of statistical errors. The observed convergence rate behaviour is, however, non-trivial due to the discrete nature of the models of chemical reactions. We explain how this affects the performance of quasi-Monte Carlo methods by looking at a test problem in standard quadrature.

APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

EPA Science Inventory

Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.

PubMed

Serebrinsky, Santiago A

2011-03-01

We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.

Implementation of Monte Carlo Dose calculation for CyberKnife treatment planning

NASA Astrophysics Data System (ADS)

Ma, C.-M.; Li, J. S.; Deng, J.; Fan, J.

2008-02-01

Accurate dose calculation is essential to advanced stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) especially for treatment planning involving heterogeneous patient anatomy. This paper describes the implementation of a fast Monte Carlo dose calculation algorithm in SRS/SRT treatment planning for the CyberKnife® SRS/SRT system. A superposition Monte Carlo algorithm is developed for this application. Photon mean free paths and interaction types for different materials and energies as well as the tracks of secondary electrons are pre-simulated using the MCSIM system. Photon interaction forcing and splitting are applied to the source photons in the patient calculation and the pre-simulated electron tracks are repeated with proper corrections based on the tissue density and electron stopping powers. Electron energy is deposited along the tracks and accumulated in the simulation geometry. Scattered and bremsstrahlung photons are transported, after applying the Russian roulette technique, in the same way as the primary photons. Dose calculations are compared with full Monte Carlo simulations performed using EGS4/MCSIM and the CyberKnife treatment planning system (TPS) for lung, head & neck and liver treatments. Comparisons with full Monte Carlo simulations show excellent agreement (within 0.5%). More than 10% differences in the target dose are found between Monte Carlo simulations and the CyberKnife TPS for SRS/SRT lung treatment while negligible differences are shown in head and neck and liver for the cases investigated. The calculation time using our superposition Monte Carlo algorithm is reduced up to 62 times (46 times on average for 10 typical clinical cases) compared to full Monte Carlo simulations. SRS/SRT dose distributions calculated by simple dose algorithms may be significantly overestimated for small lung target volumes, which can be improved by accurate Monte Carlo dose calculations.

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.

Monte Carlo Transport for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2015-11-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

TU-AB-BRC-03: Accurate Tissue Characterization for Monte Carlo Dose Calculation Using Dual-and Multi-Energy CT Data

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

Lalonde, A; Bouchard, H

Purpose: To develop a general method for human tissue characterization with dual-and multi-energy CT and evaluate its performance in determining elemental compositions and the associated proton stopping power relative to water (SPR) and photon mass absorption coefficients (EAC). Methods: Principal component analysis is used to extract an optimal basis of virtual materials from a reference dataset of tissues. These principal components (PC) are used to perform two-material decomposition using simulated DECT data. The elemental mass fraction and the electron density in each tissue is retrieved by measuring the fraction of each PC. A stoichiometric calibration method is adapted to themore » technique to make it suitable for clinical use. The present approach is compared with two others: parametrization and three-material decomposition using the water-lipid-protein (WLP) triplet. Results: Monte Carlo simulations using TOPAS for four reference tissues shows that characterizing them with only two PC is enough to get a submillimetric precision on proton range prediction. Based on the simulated DECT data of 43 references tissues, the proposed method is in agreement with theoretical values of protons SPR and low-kV EAC with a RMS error of 0.11% and 0.35%, respectively. In comparison, parametrization and WLP respectively yield RMS errors of 0.13% and 0.29% on SPR, and 2.72% and 2.19% on EAC. Furthermore, the proposed approach shows potential applications for spectral CT. Using five PC and five energy bins reduces the SPR RMS error to 0.03%. Conclusion: The proposed method shows good performance in determining elemental compositions from DECT data and physical quantities relevant to radiotherapy dose calculation and generally shows better accuracy and unbiased results compared to reference methods. The proposed method is particularly suitable for Monte Carlo calculations and shows promise in using more than two energies to characterize human tissue with CT.« less

Advanced Computational Methods for Monte Carlo Calculations

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

Brown, Forrest B.

This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.

Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study.

PubMed

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.

Monte Carlo efficiency calibration of a neutron generator-based total-body irradiator

USDA-ARS?s Scientific Manuscript database

The increasing prevalence of obesity world-wide has focused attention on the need for accurate body composition assessments, especially of large subjects. However, many body composition measurement systems are calibrated against a single-sized phantom, often based on the standard Reference Man mode...

Monte carlo efficiency calibration of a neutron generator-based total-body irradiator

USDA-ARS?s Scientific Manuscript database

The increasing prevalence of obesity world-wide has focused attention on the need for accurate body composition assessments, especially of large subjects. However, many body composition measurement systems are calibrated against a single-sized phantom, often based on the standard Reference Man mode...

Summarizing Monte Carlo Results in Methodological Research.

ERIC Educational Resources Information Center

Harwell, Michael R.

Monte Carlo studies of statistical tests are prominently featured in the methodological research literature. Unfortunately, the information from these studies does not appear to have significantly influenced methodological practice in educational and psychological research. One reason is that Monte Carlo studies lack an overarching theory to guide…

New Approaches and Applications for Monte Carlo Perturbation Theory

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

Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan

2017-02-01

This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.

A Monte Carlo Simulation of Brownian Motion in the Freshman Laboratory

ERIC Educational Resources Information Center

Anger, C. D.; Prescott, J. R.

1970-01-01

Describes a dry- lab" experiment for the college freshman laboratory, in which the essential features of Browian motion are given principles, using the Monte Carlo technique. Calculations principles, using the Monte Carlo technique. Calculations are carried out by a computation sheme based on computer language. Bibliography. (LC)

Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Hu, Xiaojing; Li, Qiang; Zhang, Hao; Guo, Ziming; Zhao, Kun; Li, Xinpeng

2018-06-01

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

A new approach to importance sampling for the simulation of false alarms. [in radar systems

NASA Technical Reports Server (NTRS)

Lu, D.; Yao, K.

1987-01-01

In this paper a modified importance sampling technique for improving the convergence of Importance Sampling is given. By using this approach to estimate low false alarm rates in radar simulations, the number of Monte Carlo runs can be reduced significantly. For one-dimensional exponential, Weibull, and Rayleigh distributions, a uniformly minimum variance unbiased estimator is obtained. For Gaussian distribution the estimator in this approach is uniformly better than that of previously known Importance Sampling approach. For a cell averaging system, by combining this technique and group sampling, the reduction of Monte Carlo runs for a reference cell of 20 and false alarm rate of lE-6 is on the order of 170 as compared to the previously known Importance Sampling approach.

An Introduction to Computational Physics

NASA Astrophysics Data System (ADS)

Pang, Tao

2010-07-01

Preface to first edition; Preface; Acknowledgements; 1. Introduction; 2. Approximation of a function; 3. Numerical calculus; 4. Ordinary differential equations; 5. Numerical methods for matrices; 6. Spectral analysis; 7. Partial differential equations; 8. Molecular dynamics simulations; 9. Modeling continuous systems; 10. Monte Carlo simulations; 11. Genetic algorithm and programming; 12. Numerical renormalization; References; Index.

Progress in lattice gauge theory

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

Creutz, M.

1983-01-01

These lectures first provide an overview of the current status of lattice gauge theory calculations. They then review some technical points on group integration, gauge fixing, and order parameters. Various Monte Carlo algorithms are discussed. Finally, alternatives to the Wilson action are considered in the context of universality for the continuum limit. 41 references.

How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

PubMed

Lecca, Paola

2018-01-01

We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of drug release, we point out how Monte Carlo heuristics can be integrated in an evolutionary algorithmic approach to infer the mode of MCS best fitting the observed data, and thus the observed release kinetics.•The software implementing the method is written in R language, the free most used language in the bioinformaticians community.

Evaluation of an analytic linear Boltzmann transport equation solver for high-density inhomogeneities

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

Lloyd, S. A. M.; Ansbacher, W.; Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia V8W 3P6

2013-01-15

Purpose: Acuros external beam (Acuros XB) is a novel dose calculation algorithm implemented through the ECLIPSE treatment planning system. The algorithm finds a deterministic solution to the linear Boltzmann transport equation, the same equation commonly solved stochastically by Monte Carlo methods. This work is an evaluation of Acuros XB, by comparison with Monte Carlo, for dose calculation applications involving high-density materials. Existing non-Monte Carlo clinical dose calculation algorithms, such as the analytic anisotropic algorithm (AAA), do not accurately model dose perturbations due to increased electron scatter within high-density volumes. Methods: Acuros XB, AAA, and EGSnrc based Monte Carlo are usedmore » to calculate dose distributions from 18 MV and 6 MV photon beams delivered to a cubic water phantom containing a rectangular high density (4.0-8.0 g/cm{sup 3}) volume at its center. The algorithms are also used to recalculate a clinical prostate treatment plan involving a unilateral hip prosthesis, originally evaluated using AAA. These results are compared graphically and numerically using gamma-index analysis. Radio-chromic film measurements are presented to augment Monte Carlo and Acuros XB dose perturbation data. Results: Using a 2% and 1 mm gamma-analysis, between 91.3% and 96.8% of Acuros XB dose voxels containing greater than 50% the normalized dose were in agreement with Monte Carlo data for virtual phantoms involving 18 MV and 6 MV photons, stainless steel and titanium alloy implants and for on-axis and oblique field delivery. A similar gamma-analysis of AAA against Monte Carlo data showed between 80.8% and 87.3% agreement. Comparing Acuros XB and AAA evaluations of a clinical prostate patient plan involving a unilateral hip prosthesis, Acuros XB showed good overall agreement with Monte Carlo while AAA underestimated dose on the upstream medial surface of the prosthesis due to electron scatter from the high-density material. Film measurements support the dose perturbations demonstrated by Monte Carlo and Acuros XB data. Conclusions: Acuros XB is shown to perform as well as Monte Carlo methods and better than existing clinical algorithms for dose calculations involving high-density volumes.« less

A Primer in Monte Carlo Integration Using Mathcad

ERIC Educational Resources Information Center

Hoyer, Chad E.; Kegerreis, Jeb S.

2013-01-01

The essentials of Monte Carlo integration are presented for use in an upper-level physical chemistry setting. A Mathcad document that aids in the dissemination and utilization of this information is described and is available in the Supporting Information. A brief outline of Monte Carlo integration is given, along with ideas and pedagogy for…

Monte Carlo calculated TG-60 dosimetry parameters for the {beta}{sup -} emitter {sup 153}Sm brachytherapy source

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

Sadeghi, Mahdi; Taghdiri, Fatemeh; Hamed Hosseini, S.

Purpose: The formalism recommended by Task Group 60 (TG-60) of the American Association of Physicists in Medicine (AAPM) is applicable for {beta} sources. Radioactive biocompatible and biodegradable {sup 153}Sm glass seed without encapsulation is a {beta}{sup -} emitter radionuclide with a short half-life and delivers a high dose rate to the tumor in the millimeter range. This study presents the results of Monte Carlo calculations of the dosimetric parameters for the {sup 153}Sm brachytherapy source. Methods: Version 5 of the (MCNP) Monte Carlo radiation transport code was used to calculate two-dimensional dose distributions around the source. The dosimetric parameters ofmore » AAPM TG-60 recommendations including the reference dose rate, the radial dose function, the anisotropy function, and the one-dimensional anisotropy function were obtained. Results: The dose rate value at the reference point was estimated to be 9.21{+-}0.6 cGy h{sup -1} {mu}Ci{sup -1}. Due to the low energy beta emitted from {sup 153}Sm sources, the dose fall-off profile is sharper than the other beta emitter sources. The calculated dosimetric parameters in this study are compared to several beta and photon emitting seeds. Conclusions: The results show the advantage of the {sup 153}Sm source in comparison with the other sources because of the rapid dose fall-off of beta ray and high dose rate at the short distances of the seed. The results would be helpful in the development of the radioactive implants using {sup 153}Sm seeds for the brachytherapy treatment.« less

An unbiased Hessian representation for Monte Carlo PDFs.

PubMed

Carrazza, Stefano; Forte, Stefano; Kassabov, Zahari; Latorre, José Ignacio; Rojo, Juan

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set.

Accurately modeling Gaussian beam propagation in the context of Monte Carlo techniques

NASA Astrophysics Data System (ADS)

Hokr, Brett H.; Winblad, Aidan; Bixler, Joel N.; Elpers, Gabriel; Zollars, Byron; Scully, Marlan O.; Yakovlev, Vladislav V.; Thomas, Robert J.

2016-03-01

Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, traditional Monte Carlo methods fail to account for diffraction because they treat light as a particle. This results in converging beams focusing to a point instead of a diffraction limited spot, greatly effecting the accuracy of Monte Carlo simulations near the focal plane. Here, we present a technique capable of simulating a focusing beam in accordance to the rules of Gaussian optics, resulting in a diffraction limited focal spot. This technique can be easily implemented into any traditional Monte Carlo simulation allowing existing models to be converted to include accurate focusing geometries with minimal effort. We will present results for a focusing beam in a layered tissue model, demonstrating that for different scenarios the region of highest intensity, thus the greatest heating, can change from the surface to the focus. The ability to simulate accurate focusing geometries will greatly enhance the usefulness of Monte Carlo for countless applications, including studying laser tissue interactions in medical applications and light propagation through turbid media.

Numerical integration of detector response functions via Monte Carlo simulations

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

Kelly, Keegan John; O'Donnell, John M.; Gomez, Jaime A.

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated inmore » this way can be used to create Monte Carlo simulation output spectra a factor of ~1000× faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. Here, this method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.« less

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.

Numerical integration of detector response functions via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Kelly, K. J.; O'Donnell, J. M.; Gomez, J. A.; Taddeucci, T. N.; Devlin, M.; Haight, R. C.; White, M. C.; Mosby, S. M.; Neudecker, D.; Buckner, M. Q.; Wu, C. Y.; Lee, H. Y.

2017-09-01

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated in this way can be used to create Monte Carlo simulation output spectra a factor of ∼ 1000 × faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. This method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.

Numerical integration of detector response functions via Monte Carlo simulations

DOE PAGES

Kelly, Keegan John; O'Donnell, John M.; Gomez, Jaime A.; ...

2017-06-13

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated inmore » this way can be used to create Monte Carlo simulation output spectra a factor of ~1000× faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. Here, this method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.« less

Monte Carlo Calculations of Polarized Microwave Radiation Emerging from Cloud Structures

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Roberti, Laura

1998-01-01

The last decade has seen tremendous growth in cloud dynamical and microphysical models that are able to simulate storms and storm systems with very high spatial resolution, typically of the order of a few kilometers. The fairly realistic distributions of cloud and hydrometeor properties that these models generate has in turn led to a renewed interest in the three-dimensional microwave radiative transfer modeling needed to understand the effect of cloud and rainfall inhomogeneities upon microwave observations. Monte Carlo methods, and particularly backwards Monte Carlo methods have shown themselves to be very desirable due to the quick convergence of the solutions. Unfortunately, backwards Monte Carlo methods are not well suited to treat polarized radiation. This study reviews the existing Monte Carlo methods and presents a new polarized Monte Carlo radiative transfer code. The code is based on a forward scheme but uses aliasing techniques to keep the computational requirements equivalent to the backwards solution. Radiative transfer computations have been performed using a microphysical-dynamical cloud model and the results are presented together with the algorithm description.

Monte Carlo simulations in X-ray imaging

NASA Astrophysics Data System (ADS)

Giersch, Jürgen; Durst, Jürgen

2008-06-01

Monte Carlo simulations have become crucial tools in many fields of X-ray imaging. They help to understand the influence of physical effects such as absorption, scattering and fluorescence of photons in different detector materials on image quality parameters. They allow studying new imaging concepts like photon counting, energy weighting or material reconstruction. Additionally, they can be applied to the fields of nuclear medicine to define virtual setups studying new geometries or image reconstruction algorithms. Furthermore, an implementation of the propagation physics of electrons and photons allows studying the behavior of (novel) X-ray generation concepts. This versatility of Monte Carlo simulations is illustrated with some examples done by the Monte Carlo simulation ROSI. An overview of the structure of ROSI is given as an example of a modern, well-proven, object-oriented, parallel computing Monte Carlo simulation for X-ray imaging.

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

NASA Technical Reports Server (NTRS)

Thipphavong, David

2010-01-01

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

TH-AB-207A-06: The Use of Realistic Phantoms to Predict CT Dose to Pediatric Patients

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

Carver, D; Kost, S; Fraser, N

Purpose: To predict pediatric patient dose from diagnostic CT scans using Monte Carlo simulation of realistic reference phantoms of various ages, weights, and heights. Methods: A series of deformable pediatric reference phantoms using Non-Uniform Rational B-Splines (NURBS) was developed for a large range of ages, percentiles, and reference anatomy. Individual bones were modeled using age-dependent factors, and red marrow was modeled as functions of age and spatial distribution based on Cristy1. Organ and effective doses for the phantom series were calculated using Monte Carlo simulation of chest, abdominopelvic, and chest-abdomen-pelvis CT exams. Non-linear regression was performed to determine the relationshipmore » between dose-length-product (DLP)-normalized organ and effective doses and phantom diameter. Patient-specific voxel computational phantoms were also created by manual segmentation of previously acquired CT images for 40 pediatric patients (0.7 to 17 years). Organ and effective doses were determined by Monte Carlo simulation of these patient-specific phantoms. Each patient was matched to the closest pediatric reference phantom based primarily on age and diameter for all major organs within the torso. Results: A total of 80 NURBS phantoms were created ranging from newborn to 15 years with height/weight percentiles from 10 to 90%. Organ and effective dose normalized by DLP correlated strongly with exponentially decreasing average phantom diameter (R{sup 2} > 0.95 for most organs). A similar relationship was determined for the patient-specific voxel phantoms. Differences between patient-phantom matched organ-dose values ranged from 0.37 to 2.39 mGy (2.87% to 22.1%). Conclusion: Dose estimation using NURBS-based pediatric reference phantoms offers the ability to predict patient dose before and after CT examinations, and physicians and scientists can use this information in their analysis of dose prescriptions for particular subjects and study types. This may lead to practices that minimize radiation dose while still achieving high quality images and, ultimately, improved patient care. NIH/NCI 1 R01 CA155400-01A1.« less

SU-E-T-254: Optimization of GATE and PHITS Monte Carlo Code Parameters for Uniform Scanning Proton Beam Based On Simulation with FLUKA General-Purpose Code

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

Kurosu, K; Department of Medical Physics ' Engineering, Osaka University Graduate School of Medicine, Osaka; Takashina, M

Purpose: Monte Carlo codes are becoming important tools for proton beam dosimetry. However, the relationships between the customizing parameters and percentage depth dose (PDD) of GATE and PHITS codes have not been reported which are studied for PDD and proton range compared to the FLUKA code and the experimental data. Methods: The beam delivery system of the Indiana University Health Proton Therapy Center was modeled for the uniform scanning beam in FLUKA and transferred identically into GATE and PHITS. This computational model was built from the blue print and validated with the commissioning data. Three parameters evaluated are the maximummore » step size, cut off energy and physical and transport model. The dependence of the PDDs on the customizing parameters was compared with the published results of previous studies. Results: The optimal parameters for the simulation of the whole beam delivery system were defined by referring to the calculation results obtained with each parameter. Although the PDDs from FLUKA and the experimental data show a good agreement, those of GATE and PHITS obtained with our optimal parameters show a minor discrepancy. The measured proton range R90 was 269.37 mm, compared to the calculated range of 269.63 mm, 268.96 mm, and 270.85 mm with FLUKA, GATE and PHITS, respectively. Conclusion: We evaluated the dependence of the results for PDDs obtained with GATE and PHITS Monte Carlo generalpurpose codes on the customizing parameters by using the whole computational model of the treatment nozzle. The optimal parameters for the simulation were then defined by referring to the calculation results. The physical model, particle transport mechanics and the different geometrybased descriptions need accurate customization in three simulation codes to agree with experimental data for artifact-free Monte Carlo simulation. This study was supported by Grants-in Aid for Cancer Research (H22-3rd Term Cancer Control-General-043) from the Ministry of Health, Labor and Welfare of Japan, Grants-in-Aid for Scientific Research (No. 23791419), and JSPS Core-to-Core program (No. 23003). The authors have no conflict of interest.« less

Discrete Diffusion Monte Carlo for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

2014-10-01

The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

Cell-veto Monte Carlo algorithm for long-range systems.

PubMed

Kapfer, Sebastian C; Krauth, Werner

2016-09-01

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of operations. For slowly decaying potentials such as Coulomb interactions, screening line charges allow us to take into account periodic boundary conditions. We discuss the performance of the cell-veto Monte Carlo algorithm for general inverse-power-law potentials, and illustrate how it provides a new outlook on one of the prominent bottlenecks in large-scale atomistic Monte Carlo simulations.

Nuclide Depletion Capabilities in the Shift Monte Carlo Code

DOE PAGES

Davidson, Gregory G.; Pandya, Tara M.; Johnson, Seth R.; ...

2017-12-21

A new depletion capability has been developed in the Exnihilo radiation transport code suite. This capability enables massively parallel domain-decomposed coupling between the Shift continuous-energy Monte Carlo solver and the nuclide depletion solvers in ORIGEN to perform high-performance Monte Carlo depletion calculations. This paper describes this new depletion capability and discusses its various features, including a multi-level parallel decomposition, high-order transport-depletion coupling, and energy-integrated power renormalization. Several test problems are presented to validate the new capability against other Monte Carlo depletion codes, and the parallel performance of the new capability is analyzed.

Ground state of excitonic molecules by the Green's-function Monte Carlo method

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

Lee, M.A.; Vashishta, P.; Kalia, R.K.

1983-12-26

The ground-state energy of excitonic molecules is evaluated as a function of the ratio of electron and hole masses, sigma, with use of the Green's-function Monte Carlo method. For all sigma, the Green's-function Monte Carlo energies are significantly lower than the variational estimates and in favorable agreement with experiments. In excitonic rydbergs, the binding energy of the positronium molecule (sigma = 1) is predicted to be -0.06 and for sigma<<1, the Green's-function Monte Carlo energies agree with the ''exact'' limiting behavior, E = -2.346+0.764sigma.

Measured and Monte Carlo calculated k{sub Q} factors: Accuracy and comparison

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

Muir, B. R.; McEwen, M. R.; Rogers, D. W. O.

2011-08-15

Purpose: The journal Medical Physics recently published two papers that determine beam quality conversion factors, k{sub Q}, for large sets of ion chambers. In the first paper [McEwen Med. Phys. 37, 2179-2193 (2010)], k{sub Q} was determined experimentally, while the second paper [Muir and Rogers Med. Phys. 37, 5939-5950 (2010)] provides k{sub Q} factors calculated using Monte Carlo simulations. This work investigates a variety of additional consistency checks to verify the accuracy of the k{sub Q} factors determined in each publication and a comparison of the two data sets. Uncertainty introduced in calculated k{sub Q} factors by possible variation ofmore » W/e with beam energy is investigated further. Methods: The validity of the experimental set of k{sub Q} factors relies on the accuracy of the NE2571 reference chamber measurements to which k{sub Q} factors for all other ion chambers are correlated. The stability of NE2571 absorbed dose to water calibration coefficients is determined and comparison to other experimental k{sub Q} factors is analyzed. Reliability of Monte Carlo calculated k{sub Q} factors is assessed through comparison to other publications that provide Monte Carlo calculations of k{sub Q} as well as an analysis of the sleeve effect, the effect of cavity length and self-consistencies between graphite-walled Farmer-chambers. Comparison between the two data sets is given in terms of the percent difference between the k{sub Q} factors presented in both publications. Results: Monitoring of the absorbed dose calibration coefficients for the NE2571 chambers over a period of more than 15 yrs exhibit consistency at a level better than 0.1%. Agreement of the NE2571 k{sub Q} factors with a quadratic fit to all other experimental data from standards labs for the same chamber is observed within 0.3%. Monte Carlo calculated k{sub Q} factors are in good agreement with most other Monte Carlo calculated k{sub Q} factors. Expected results are observed for the sleeve effect and the effect of cavity length on k{sub Q}. The mean percent differences between experimental and Monte Carlo calculated k{sub Q} factors are -0.08, -0.07, and -0.23% for the Elekta 6, 10, and 25 MV nominal beam energies, respectively. An upper limit on the variation of W/e in photon beams from cobalt-60 to 25 MV is determined as 0.4% with 95% confidence. The combined uncertainty on Monte Carlo calculated k{sub Q} factors is reassessed and amounts to between 0.40 and 0.49% depending on the wall material of the chamber. Conclusions: Excellent agreement (mean percent difference of only 0.13% for the entire data set) between experimental and calculated k{sub Q} factors is observed. For some chambers, k{sub Q} is measured for only one chamber of each type--the level of agreement observed in this study would suggest that for those chambers the measured k{sub Q} values are generally representative of the chamber type.« less

Monte Carlo treatment planning with modulated electron radiotherapy: framework development and application

NASA Astrophysics Data System (ADS)

Alexander, Andrew William

Within the field of medical physics, Monte Carlo radiation transport simulations are considered to be the most accurate method for the determination of dose distributions in patients. The McGill Monte Carlo treatment planning system (MMCTP), provides a flexible software environment to integrate Monte Carlo simulations with current and new treatment modalities. A developing treatment modality called energy and intensity modulated electron radiotherapy (MERT) is a promising modality, which has the fundamental capabilities to enhance the dosimetry of superficial targets. An objective of this work is to advance the research and development of MERT with the end goal of clinical use. To this end, we present the MMCTP system with an integrated toolkit for MERT planning and delivery of MERT fields. Delivery is achieved using an automated "few leaf electron collimator" (FLEC) and a controller. Aside from the MERT planning toolkit, the MMCTP system required numerous add-ons to perform the complex task of large-scale autonomous Monte Carlo simulations. The first was a DICOM import filter, followed by the implementation of DOSXYZnrc as a dose calculation engine and by logic methods for submitting and updating the status of Monte Carlo simulations. Within this work we validated the MMCTP system with a head and neck Monte Carlo recalculation study performed by a medical dosimetrist. The impact of MMCTP lies in the fact that it allows for systematic and platform independent large-scale Monte Carlo dose calculations for different treatment sites and treatment modalities. In addition to the MERT planning tools, various optimization algorithms were created external to MMCTP. The algorithms produced MERT treatment plans based on dose volume constraints that employ Monte Carlo pre-generated patient-specific kernels. The Monte Carlo kernels are generated from patient-specific Monte Carlo dose distributions within MMCTP. The structure of the MERT planning toolkit software and optimization algorithms are demonstrated. We investigated the clinical significance of MERT on spinal irradiation, breast boost irradiation, and a head and neck sarcoma cancer site using several parameters to analyze the treatment plans. Finally, we investigated the idea of mixed beam photon and electron treatment planning. Photon optimization treatment planning tools were included within the MERT planning toolkit for the purpose of mixed beam optimization. In conclusion, this thesis work has resulted in the development of an advanced framework for photon and electron Monte Carlo treatment planning studies and the development of an inverse planning system for photon, electron or mixed beam radiotherapy (MBRT). The justification and validation of this work is found within the results of the planning studies, which have demonstrated dosimetric advantages to using MERT or MBRT in comparison to clinical treatment alternatives.

pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

NASA Astrophysics Data System (ADS)

White, J.; Brakefield, L. K.

2015-12-01

The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.

The Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints

ERIC Educational Resources Information Center

Mao, Xiuzhen; Xin, Tao

2013-01-01

The Monte Carlo approach which has previously been implemented in traditional computerized adaptive testing (CAT) is applied here to cognitive diagnostic CAT to test the ability of this approach to address multiple content constraints. The performance of the Monte Carlo approach is compared with the performance of the modified maximum global…

Modifying the Monte Carlo Quiz to Increase Student Motivation, Participation, and Content Retention

ERIC Educational Resources Information Center

Simonson, Shawn R.

2017-01-01

Fernald developed the Monte Carlo Quiz format to enhance retention, encourage students to prepare for class, read with intention, and organize information in psychology classes. This author modified the Monte Carlo Quiz, combined it with the Minute Paper, and applied it to various courses. Students write quiz questions as part of the Minute Paper…

The Monte Carlo Method. Popular Lectures in Mathematics.

ERIC Educational Resources Information Center

Sobol', I. M.

The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…

An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

NASA Astrophysics Data System (ADS)

Prabhu Verleker, Akshay; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.

2015-03-01

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μs'=8.25mm-1, μa=0.005mm-1) and gray-matter (μs'=2.45mm-1, μa=0.035mm-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R2=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

Measurement of Thermal Conductivity of Porcine Liver in the Temperature Range of Cryotherapy and Hyperthermia (250~315k) by A Thermal Sensor Made of A Micron-Scale Enameled Copper Wire.

PubMed

Jiang, Z D; Zhao, G; Lu, G R

　　BACKGROUND: Cryotherapy and hyperthermia are effective treatments for several diseases, especially for liver cancers. Thermal conductivity is a significant thermal property for the prediction and guidance of surgical procedure. However, the thermal conductivities of organs and tissues, especially over the temperature range of both cryotherapy and hyperthermia are scarce. To provide comprehensive thermal conductivity of liver for both cryotherapy and hyperthermia. A hot probe made of stain steel needle and micron-sized copper wire is used for measurement. To verify data processing, both the least square method and the Monte Carlo inversion method are used to determine the hot probe constants, respectively, with reference materials of water and 29.9 % Ca 2 Cl aqueous solution. Then the thermal conductivities of Hanks solution and pork liver bathed in Hanks solution are measured. The effective length for two methods is nearly the same, but the heat capacity of probe calibrated by the Monte Carlo inversion is temperature dependent. Fairly comprehensive thermal conductivity of porcine liver measured with these two methods in the target temperature range is verified to be similar. We provide an integrated thermal conductivity of liver for cryotherapy and hyperthermia in two methods, and make more accurate predictions possible for surgery. The least square method and the Monte Carlo inversion method have their advantages and disadvantages. The least square method is available for measurement of liquids that not prone to convection or solids in a wide temperature range, while the Monte Carlo inversion method is available for accurate and rapid measurement.

Monte Carlo simulation of x-ray spectra in diagnostic radiology and mammography using MCNP4C

NASA Astrophysics Data System (ADS)

Ay, M. R.; Shahriari, M.; Sarkar, S.; Adib, M.; Zaidi, H.

2004-11-01

The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4-based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student's t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra.

Use of Fluka to Create Dose Calculations

NASA Technical Reports Server (NTRS)

Lee, Kerry T.; Barzilla, Janet; Townsend, Lawrence; Brittingham, John

2012-01-01

Monte Carlo codes provide an effective means of modeling three dimensional radiation transport; however, their use is both time- and resource-intensive. The creation of a lookup table or parameterization from Monte Carlo simulation allows users to perform calculations with Monte Carlo results without replicating lengthy calculations. FLUKA Monte Carlo transport code was used to develop lookup tables and parameterizations for data resulting from the penetration of layers of aluminum, polyethylene, and water with areal densities ranging from 0 to 100 g/cm^2. Heavy charged ion radiation including ions from Z=1 to Z=26 and from 0.1 to 10 GeV/nucleon were simulated. Dose, dose equivalent, and fluence as a function of particle identity, energy, and scattering angle were examined at various depths. Calculations were compared against well-known results and against the results of other deterministic and Monte Carlo codes. Results will be presented.

Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model

NASA Astrophysics Data System (ADS)

Ferrenberg, Alan M.; Xu, Jiahao; Landau, David P.

2018-04-01

While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.

Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

NASA Astrophysics Data System (ADS)

Sharma, Sanjib

2017-08-01

Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, efficient Monte Carlo based methods are continuously being developed and explored. In this review, we first explain the basics of Bayesian theory and discuss how to set up data analysis problems within this framework. Next, we provide an overview of various Monte Carlo based methods for performing Bayesian data analysis. Finally, we discuss advanced ideas that enable us to tackle complex problems and thus hold great promise for the future. We also distribute downloadable computer software (available at https://github.com/sanjibs/bmcmc/ ) that implements some of the algorithms and examples discussed here.

A modified Monte Carlo model for the ionospheric heating rates

NASA Technical Reports Server (NTRS)

Mayr, H. G.; Fontheim, E. G.; Robertson, S. C.

1972-01-01

A Monte Carlo method is adopted as a basis for the derivation of the photoelectron heat input into the ionospheric plasma. This approach is modified in an attempt to minimize the computation time. The heat input distributions are computed for arbitrarily small source elements that are spaced at distances apart corresponding to the photoelectron dissipation range. By means of a nonlinear interpolation procedure their individual heating rate distributions are utilized to produce synthetic ones that fill the gaps between the Monte Carlo generated distributions. By varying these gaps and the corresponding number of Monte Carlo runs the accuracy of the results is tested to verify the validity of this procedure. It is concluded that this model can reduce the computation time by more than a factor of three, thus improving the feasibility of including Monte Carlo calculations in self-consistent ionosphere models.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

NASA Astrophysics Data System (ADS)

Kim, Jeongnim; Baczewski, Andrew D.; Beaudet, Todd D.; Benali, Anouar; Chandler Bennett, M.; Berrill, Mark A.; Blunt, Nick S.; Josué Landinez Borda, Edgar; Casula, Michele; Ceperley, David M.; Chiesa, Simone; Clark, Bryan K.; Clay, Raymond C., III; Delaney, Kris T.; Dewing, Mark; Esler, Kenneth P.; Hao, Hongxia; Heinonen, Olle; Kent, Paul R. C.; Krogel, Jaron T.; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M. Graham; Luo, Ye; Malone, Fionn D.; Martin, Richard M.; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A.; Mitas, Lubos; Morales, Miguel A.; Neuscamman, Eric; Parker, William D.; Pineda Flores, Sergio D.; Romero, Nichols A.; Rubenstein, Brenda M.; Shea, Jacqueline A. R.; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F.; Townsend, Joshua P.; Tubman, Norm M.; Van Der Goetz, Brett; Vincent, Jordan E.; ChangMo Yang, D.; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-01

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater–Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids.

PubMed

Kim, Jeongnim; Baczewski, Andrew T; Beaudet, Todd D; Benali, Anouar; Bennett, M Chandler; Berrill, Mark A; Blunt, Nick S; Borda, Edgar Josué Landinez; Casula, Michele; Ceperley, David M; Chiesa, Simone; Clark, Bryan K; Clay, Raymond C; Delaney, Kris T; Dewing, Mark; Esler, Kenneth P; Hao, Hongxia; Heinonen, Olle; Kent, Paul R C; Krogel, Jaron T; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M Graham; Luo, Ye; Malone, Fionn D; Martin, Richard M; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A; Mitas, Lubos; Morales, Miguel A; Neuscamman, Eric; Parker, William D; Pineda Flores, Sergio D; Romero, Nichols A; Rubenstein, Brenda M; Shea, Jacqueline A R; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F; Townsend, Joshua P; Tubman, Norm M; Van Der Goetz, Brett; Vincent, Jordan E; Yang, D ChangMo; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-16

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

An efficient Monte Carlo-based algorithm for scatter correction in keV cone-beam CT

NASA Astrophysics Data System (ADS)

Poludniowski, G.; Evans, P. M.; Hansen, V. N.; Webb, S.

2009-06-01

A new method is proposed for scatter-correction of cone-beam CT images. A coarse reconstruction is used in initial iteration steps. Modelling of the x-ray tube spectra and detector response are included in the algorithm. Photon diffusion inside the imaging subject is calculated using the Monte Carlo method. Photon scoring at the detector is calculated using forced detection to a fixed set of node points. The scatter profiles are then obtained by linear interpolation. The algorithm is referred to as the coarse reconstruction and fixed detection (CRFD) technique. Scatter predictions are quantitatively validated against a widely used general-purpose Monte Carlo code: BEAMnrc/EGSnrc (NRCC, Canada). Agreement is excellent. The CRFD algorithm was applied to projection data acquired with a Synergy XVI CBCT unit (Elekta Limited, Crawley, UK), using RANDO and Catphan phantoms (The Phantom Laboratory, Salem NY, USA). The algorithm was shown to be effective in removing scatter-induced artefacts from CBCT images, and took as little as 2 min on a desktop PC. Image uniformity was greatly improved as was CT-number accuracy in reconstructions. This latter improvement was less marked where the expected CT-number of a material was very different to the background material in which it was embedded.

A Monte Carlo-based radiation safety assessment for astronauts in an environment with confined magnetic field shielding.

PubMed

Geng, Changran; Tang, Xiaobin; Gong, Chunhui; Guan, Fada; Johns, Jesse; Shu, Diyun; Chen, Da

2015-12-01

The active shielding technique has great potential for radiation protection in space exploration because it has the advantage of a significant mass saving compared with the passive shielding technique. This paper demonstrates a Monte Carlo-based approach to evaluating the shielding effectiveness of the active shielding technique using confined magnetic fields (CMFs). The International Commission on Radiological Protection reference anthropomorphic phantom, as well as the toroidal CMF, was modeled using the Monte Carlo toolkit Geant4. The penetrating primary particle fluence, organ-specific dose equivalent, and male effective dose were calculated for particles in galactic cosmic radiation (GCR) and solar particle events (SPEs). Results show that the SPE protons can be easily shielded against, even almost completely deflected, by the toroidal magnetic field. GCR particles can also be more effectively shielded against by increasing the magnetic field strength. Our results also show that the introduction of a structural Al wall in the CMF did not provide additional shielding for GCR; in fact it can weaken the total shielding effect of the CMF. This study demonstrated the feasibility of accurately determining the radiation field inside the environment and evaluating the organ dose equivalents for astronauts under active shielding using the CMF.

[The highest proportion of tobacco materials in the blend analysis using PPF projection method for the near-infrared spectrum and Monte Carlo method].

PubMed

Mi, Jin-Rui; Ma, Xiang; Zhang, Ya-Juan; Wang, Yi; Wen, Ya-Dong; Zhao, Long-Lian; Li, Jun-Hui; Zhang, Lu-Da

2011-04-01

The present paper builds a model based on Monte Carlo method in the projection of the blending tobacco. This model is made up of two parts: the projecting points of tobacco materials, whose coordinates are calculated by means of the PPF (projection based on principal component and Fisher criterion) projection method for the tobacco near-infrared spectrum; and the point of tobacco blend, which is produced by linear additive to the projecting point coordinates of tobacco materials. In order to analyze the projection points deviation from initial state levels, Monte Carlo method is introduced to simulate the differences and changes of raw material projection. The results indicate that there are two major factors affecting the relative deviation: the highest proportion of tobacco materials in the blend, which is too high to make the deviation under control; and the quantity of materials, which is so small to control the deviation. The conclusion is close to the principle of actual formulating designing, particularly, the more in the quantity while the lower in proportion of each. Finally the paper figures out the upper limit of the proportions in the different quantity of materials by theory. It also has important reference value for other agricultural products blend.

Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods

NASA Astrophysics Data System (ADS)

Koreň, Milan; Mokroš, Martin; Bucha, Tomáš

2017-12-01

This study compares the accuracies of diameter at breast height (DBH) estimations by three initial (minimum bounding box, centroid, and maximum distance) and two refining (Monte Carlo and optimal circle) circle-fitting methods The circle-fitting algorithms were evaluated in multi-scan mode and a simulated single-scan mode on 157 European beech trees (Fagus sylvatica L.). DBH measured by a calliper was used as reference data. Most of the studied circle-fitting algorithms significantly underestimated the mean DBH in both scanning modes. Only the Monte Carlo method in the single-scan mode significantly overestimated the mean DBH. The centroid method proved to be the least suitable and showed significantly different results from the other circle-fitting methods in both scanning modes. In multi-scan mode, the accuracy of the minimum bounding box method was not significantly different from the accuracies of the refining methods The accuracy of the maximum distance method was significantly different from the accuracies of the refining methods in both scanning modes. The accuracy of the Monte Carlo method was significantly different from the accuracy of the optimal circle method in only single-scan mode. The optimal circle method proved to be the most accurate circle-fitting method for DBH estimation from point clouds in both scanning modes.

TU-H-207A-02: Relative Importance of the Various Factors Influencing the Accuracy of Monte Carlo Simulated CT Dose Index

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

Marous, L; Muryn, J; Liptak, C

2016-06-15

Purpose: Monte Carlo simulation is a frequently used technique for assessing patient dose in CT. The accuracy of a Monte Carlo program is often validated using the standard CT dose index (CTDI) phantoms by comparing simulated and measured CTDI{sub 100}. To achieve good agreement, many input parameters in the simulation (e.g., energy spectrum and effective beam width) need to be determined. However, not all the parameters have equal importance. Our aim was to assess the relative importance of the various factors that influence the accuracy of simulated CTDI{sub 100}. Methods: A Monte Carlo program previously validated for a clinical CTmore » system was used to simulate CTDI{sub 100}. For the standard CTDI phantoms (32 and 16 cm in diameter), CTDI{sub 100} values from central and four peripheral locations at 70 and 120 kVp were first simulated using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which intentional errors were introduced into the input parameters, the effects of which on simulated CTDI{sub 100} were analyzed. Results: At 38.4-mm collimation, errors in effective beam width up to 5.0 mm showed negligible effects on simulated CTDI{sub 100} (<1.0%). Likewise, errors in acrylic density of up to 0.01 g/cm{sup 3} resulted in small CTDI{sub 100} errors (<2.5%). In contrast, errors in spectral HVL produced more significant effects: slight deviations (±0.2 mm Al) produced errors up to 4.4%, whereas more extreme deviations (±1.4 mm Al) produced errors as high as 25.9%. Lastly, ignoring the CT table introduced errors up to 13.9%. Conclusion: Monte Carlo simulated CTDI{sub 100} is insensitive to errors in effective beam width and acrylic density. However, they are sensitive to errors in spectral HVL. To obtain accurate results, the CT table should not be ignored. This work was supported by a Faculty Research and Development Award from Cleveland State University.« less

SU-E-T-391: Assessment and Elimination of the Angular Dependence of the Response of the NanoDot OSLD System in MV Beams

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

Lehmann, J; University of Sydney, Sydney; RMIT University, Melbourne

2014-06-01

Purpose: Assess the angular dependence of the nanoDot OSLD system in MV X-ray beams at depths and mitigate this dependence for measurements in phantoms. Methods: Measurements for 6 MV photons at 3 cm and 10 cm depth and Monte Carlo simulations were performed. Two special holders were designed which allow a nanoDot dosimeter to be rotated around the center of its sensitive volume (5 mm diameter disk). The first holder positions the dosimeter disk perpendicular to the beam (en-face). It then rotates until the disk is parallel with the beam (edge on). This is referred to as Setup 1. Themore » second holder positions the disk parallel to the beam (edge on) for all angles (Setup 2). Monte Carlo simulations using GEANT4 considered detector and housing in detail based on microCT data. Results: An average drop in response by 1.4±0.7% (measurement) and 2.1±0.3% (Monte Carlo) for the 90° orientation compared to 0° was found for Setup 1. Monte Carlo simulations also showed a strong dependence of the effect on the composition of the sensitive layer. Assuming 100% active material (Al??O??) results in a 7% drop in response for 90° compared to 0°. Assuming the layer to be completely water, results in a flat response (within simulation uncertainty of about 1%). For Setup 2, measurements and Monte Carlo simulations found the angular dependence of the dosimeter to be below 1% and within the measurement uncertainty. Conclusion: The nanoDot dosimeter system exhibits a small angular dependence off approximately 2%. Changing the orientation of the dosimeter so that a coplanar beam arrangement always hits the detector material edge on reduces the angular dependence to within the measurement uncertainty of about 1%. This makes the dosimeter more attractive for phantom based clinical measurements and audits with multiple coplanar beams. The Australian Clinical Dosimetry Service is a joint initiative between the Australian Department of Health and the Australian Radiation Protection and Nuclear Safety Agency.« less

Finding Effective Models in Transition Metals using Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Williams, Kiel; Wagner, Lucas K.

There is a gap between high-accuracy ab-initio calculations, like those produced from Quantum Monte Carlo (QMC), and effective lattice models such as the Hubbard model. We have developed a method that combines data produced from QMC with fitting techniques taken from data science, allowing us to determine which degrees of freedom are required to connect ab-initio and model calculations. We test this approach for transition metal atoms, where spectroscopic reference data exists. We report on the accuracy of several derived effective models that include different degrees of freedom, and comment on the quality of the parameter values we obtain from our fitting procedure. We gratefully acknowledge funding from the National Science Foundation Graduate Research Fellowship Program under Grant Number DGE-1144245 (K.T.W.) and from SciDAC Grant DE-FG02-12ER46875 (L.K.W.).

An improved target velocity sampling algorithm for free gas elastic scattering

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

Romano, Paul K.; Walsh, Jonathan A.

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

An improved target velocity sampling algorithm for free gas elastic scattering

DOE PAGES

Romano, Paul K.; Walsh, Jonathan A.

2018-02-03

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

All about MAX: a male adult voxel phantom for Monte Carlo calculations in radiation protection dosimetry

NASA Astrophysics Data System (ADS)

Kramer, R.; Vieira, J. W.; Khoury, H. J.; Lima, F. R. A.; Fuelle, D.

2003-05-01

The MAX (Male Adult voXel) phantom has been developed from existing segmented images of a male adult body, in order to achieve a representation as close as possible to the anatomical properties of the reference adult male specified by the ICRP. The study describes the adjustments of the soft-tissue organ masses, a new dosimetric model for the skin, a new model for skeletal dosimetry and a computational exposure model based on coupling the MAX phantom with the EGS4 Monte Carlo code. Conversion coefficients between equivalent dose to the red bone marrow as well as effective MAX dose and air-kerma free in air for external photon irradiation from the front and from the back, respectively, are presented and compared with similar data from other human phantoms.

Monte Carlo simulation of the operational quantities at the realistic mixed neutron-photon radiation fields CANEL and SIGMA.

PubMed

Lacoste, V; Gressier, V

2007-01-01

The Institute for Radiological Protection and Nuclear Safety owns two facilities producing realistic mixed neutron-photon radiation fields, CANEL, an accelerator driven moderator modular device, and SIGMA, a graphite moderated americium-beryllium assembly. These fields are representative of some of those encountered at nuclear workplaces, and the corresponding facilities are designed and used for calibration of various instruments, such as survey meters, personal dosimeters or spectrometric devices. In the framework of the European project EVIDOS, irradiations of personal dosimeters were performed at CANEL and SIGMA. Monte Carlo calculations were performed to estimate the reference values of the personal dose equivalent at both facilities. The Hp(10) values were calculated for three different angular positions, 0 degrees, 45 degrees and 75 degrees, of an ICRU phantom located at the position of irradiation.

An Introduction to Computational Physics - 2nd Edition

NASA Astrophysics Data System (ADS)

Pang, Tao

2006-01-01

Preface to first edition; Preface; Acknowledgements; 1. Introduction; 2. Approximation of a function; 3. Numerical calculus; 4. Ordinary differential equations; 5. Numerical methods for matrices; 6. Spectral analysis; 7. Partial differential equations; 8. Molecular dynamics simulations; 9. Modeling continuous systems; 10. Monte Carlo simulations; 11. Genetic algorithm and programming; 12. Numerical renormalization; References; Index.

Calibration of remotely sensed proportion or area estimates for misclassification error

Treesearch

Raymond L. Czaplewski; Glenn P. Catts

1992-01-01

Classifications of remotely sensed data contain misclassification errors that bias areal estimates. Monte Carlo techniques were used to compare two statistical methods that correct or calibrate remotely sensed areal estimates for misclassification bias using reference data from an error matrix. The inverse calibration estimator was consistently superior to the...

Monte Carlo Analysis of the Battery-Type High Temperature Gas Cooled Reactor

NASA Astrophysics Data System (ADS)

Grodzki, Marcin; Darnowski, Piotr; Niewiński, Grzegorz

2017-12-01

The paper presents a neutronic analysis of the battery-type 20 MWth high-temperature gas cooled reactor. The developed reactor model is based on the publicly available data being an `early design' variant of the U-battery. The investigated core is a battery type small modular reactor, graphite moderated, uranium fueled, prismatic, helium cooled high-temperature gas cooled reactor with graphite reflector. The two core alternative designs were investigated. The first has a central reflector and 30×4 prismatic fuel blocks and the second has no central reflector and 37×4 blocks. The SERPENT Monte Carlo reactor physics computer code, with ENDF and JEFF nuclear data libraries, was applied. Several nuclear design static criticality calculations were performed and compared with available reference results. The analysis covered the single assembly models and full core simulations for two geometry models: homogenous and heterogenous (explicit). A sensitivity analysis of the reflector graphite density was performed. An acceptable agreement between calculations and reference design was obtained. All calculations were performed for the fresh core state.

The Importance of Electron Correlation on Stacking Interaction of Adenine-Thymine Base-Pair Step in B-DNA: A Quantum Monte Carlo Study.

PubMed

Hongo, Kenta; Cuong, Nguyen Thanh; Maezono, Ryo

2013-02-12

We report fixed-node diffusion Monte Carlo (DMC) calculations of stacking interaction energy between two adenine(A)-thymine(T) base pairs in B-DNA (AA:TT), for which reference data are available, obtained from a complete basis set estimate of CCSD(T) (coupled-cluster with singles, doubles, and perturbative triples). We consider four sets of nodal surfaces obtained from self-consistent field calculations and examine how the different nodal surfaces affect the DMC potential energy curves of the AA:TT molecule and the resulting stacking energies. We find that the DMC potential energy curves using the different nodes look similar to each other as a whole. We also benchmark the performance of various quantum chemistry methods, including Hartree-Fock (HF) theory, second-order Møller-Plesset perturbation theory (MP2), and density functional theory (DFT). The DMC and recently developed DFT results of the stacking energy reasonably agree with the reference, while the HF, MP2, and conventional DFT methods give unsatisfactory results.

Improved method for implicit Monte Carlo

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

Brown, F. B.; Martin, W. R.

2001-01-01

The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and themore » accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.« less

MCNP Version 6.2 Release Notes

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

Werner, Christopher John; Bull, Jeffrey S.; Solomon, C. J.

Monte Carlo N-Particle or MCNP ® is a general-purpose Monte Carlo radiation-transport code designed to track many particle types over broad ranges of energies. This MCNP Version 6.2 follows the MCNP6.1.1 beta version and has been released in order to provide the radiation transport community with the latest feature developments and bug fixes for MCNP. Since the last release of MCNP major work has been conducted to improve the code base, add features, and provide tools to facilitate ease of use of MCNP version 6.2 as well as the analysis of results. These release notes serve as a general guidemore » for the new/improved physics, source, data, tallies, unstructured mesh, code enhancements and tools. For more detailed information on each of the topics, please refer to the appropriate references or the user manual which can be found at http://mcnp.lanl.gov. This release of MCNP version 6.2 contains 39 new features in addition to 172 bug fixes and code enhancements. There are still some 33 known issues the user should familiarize themselves with (see Appendix).« less

RECORDS: improved Reporting of montE CarlO RaDiation transport Studies: Report of the AAPM Research Committee Task Group 268.

PubMed

Sechopoulos, Ioannis; Rogers, D W O; Bazalova-Carter, Magdalena; Bolch, Wesley E; Heath, Emily C; McNitt-Gray, Michael F; Sempau, Josep; Williamson, Jeffrey F

2018-01-01

Studies involving Monte Carlo simulations are common in both diagnostic and therapy medical physics research, as well as other fields of basic and applied science. As with all experimental studies, the conditions and parameters used for Monte Carlo simulations impact their scope, validity, limitations, and generalizability. Unfortunately, many published peer-reviewed articles involving Monte Carlo simulations do not provide the level of detail needed for the reader to be able to properly assess the quality of the simulations. The American Association of Physicists in Medicine Task Group #268 developed guidelines to improve reporting of Monte Carlo studies in medical physics research. By following these guidelines, manuscripts submitted for peer-review will include a level of relevant detail that will increase the transparency, the ability to reproduce results, and the overall scientific value of these studies. The guidelines include a checklist of the items that should be included in the Methods, Results, and Discussion sections of manuscripts submitted for peer-review. These guidelines do not attempt to replace the journal reviewer, but rather to be a tool during the writing and review process. Given the varied nature of Monte Carlo studies, it is up to the authors and the reviewers to use this checklist appropriately, being conscious of how the different items apply to each particular scenario. It is envisioned that this list will be useful both for authors and for reviewers, to help ensure the adequate description of Monte Carlo studies in the medical physics literature. © 2017 American Association of Physicists in Medicine.

Analysis of Naval Ammunition Stock Positioning

DTIC Science & Technology

2015-12-01

model takes once the Monte -Carlo simulation determines the assigned probabilities for site-to-site locations. Column two shows how the simulation...stockpiles and positioning them at coastal Navy facilities. A Monte -Carlo simulation model was developed to simulate expected cost and delivery...TERMS supply chain management, Monte -Carlo simulation, risk, delivery performance, stock positioning 15. NUMBER OF PAGES 85 16. PRICE CODE 17

Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

ERIC Educational Resources Information Center

Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

Development of volume equations using data obtained by upper stem dendrometry with Monte Carlo integration: preliminary results for eastern redcedar

Treesearch

Thomas B. Lynch; Rodney E. Will; Rider Reynolds

2013-01-01

Preliminary results are given for development of an eastern redcedar (Juniperus virginiana) cubic-volume equation based on measurements of redcedar sample tree stem volume using dendrometry with Monte Carlo integration. Monte Carlo integration techniques can be used to provide unbiased estimates of stem cubic-foot volume based on upper stem diameter...

[Accuracy Check of Monte Carlo Simulation in Particle Therapy Using Gel Dosimeters].

PubMed

Furuta, Takuya

2017-01-01

Gel dosimeters are a three-dimensional imaging tool for dose distribution induced by radiations. They can be used for accuracy check of Monte Carlo simulation in particle therapy. An application was reviewed in this article. An inhomogeneous biological sample placing a gel dosimeter behind it was irradiated by carbon beam. The recorded dose distribution in the gel dosimeter reflected the inhomogeneity of the biological sample. Monte Carlo simulation was conducted by reconstructing the biological sample from its CT image. The accuracy of the particle transport by Monte Carlo simulation was checked by comparing the dose distribution in the gel dosimeter between simulation and experiment.

CONTINUOUS-ENERGY MONTE CARLO METHODS FOR CALCULATING GENERALIZED RESPONSE SENSITIVITIES USING TSUNAMI-3D

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

Perfetti, Christopher M; Rearden, Bradley T

2014-01-01

This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.

Deterministic theory of Monte Carlo variance

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

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias

2015-01-01

Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.

Recommender engine for continuous-time quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

Propagation of uncertainty in nasal spray in vitro performance models using Monte Carlo simulation: Part II. Error propagation during product performance modeling.

PubMed

Guo, Changning; Doub, William H; Kauffman, John F

2010-08-01

Monte Carlo simulations were applied to investigate the propagation of uncertainty in both input variables and response measurements on model prediction for nasal spray product performance design of experiment (DOE) models in the first part of this study, with an initial assumption that the models perfectly represent the relationship between input variables and the measured responses. In this article, we discard the initial assumption, and extended the Monte Carlo simulation study to examine the influence of both input variable variation and product performance measurement variation on the uncertainty in DOE model coefficients. The Monte Carlo simulations presented in this article illustrate the importance of careful error propagation during product performance modeling. Our results show that the error estimates based on Monte Carlo simulation result in smaller model coefficient standard deviations than those from regression methods. This suggests that the estimated standard deviations from regression may overestimate the uncertainties in the model coefficients. Monte Carlo simulations provide a simple software solution to understand the propagation of uncertainty in complex DOE models so that design space can be specified with statistically meaningful confidence levels. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry.

PubMed

Bostani, Maryam; Mueller, Jonathon W; McMillan, Kyle; Cody, Dianna D; Cagnon, Chris H; DeMarco, John J; McNitt-Gray, Michael F

2015-02-01

The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements. MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for all exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy. The calculated mean percent difference between TLD measurements and Monte Carlo simulations was -4.9% with standard deviation of 8.7% and a range of -22.7% to 5.7%. The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

Dose calculation accuracy of the Monte Carlo algorithm for CyberKnife compared with other commercially available dose calculation algorithms.

PubMed

Sharma, Subhash; Ott, Joseph; Williams, Jamone; Dickow, Danny

2011-01-01

Monte Carlo dose calculation algorithms have the potential for greater accuracy than traditional model-based algorithms. This enhanced accuracy is particularly evident in regions of lateral scatter disequilibrium, which can develop during treatments incorporating small field sizes and low-density tissue. A heterogeneous slab phantom was used to evaluate the accuracy of several commercially available dose calculation algorithms, including Monte Carlo dose calculation for CyberKnife, Analytical Anisotropic Algorithm and Pencil Beam convolution for the Eclipse planning system, and convolution-superposition for the Xio planning system. The phantom accommodated slabs of varying density; comparisons between planned and measured dose distributions were accomplished with radiochromic film. The Monte Carlo algorithm provided the most accurate comparison between planned and measured dose distributions. In each phantom irradiation, the Monte Carlo predictions resulted in gamma analysis comparisons >97%, using acceptance criteria of 3% dose and 3-mm distance to agreement. In general, the gamma analysis comparisons for the other algorithms were <95%. The Monte Carlo dose calculation algorithm for CyberKnife provides more accurate dose distribution calculations in regions of lateral electron disequilibrium than commercially available model-based algorithms. This is primarily because of the ability of Monte Carlo algorithms to implicitly account for tissue heterogeneities, density scaling functions; and/or effective depth correction factors are not required. Copyright © 2011 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Diagnosing Undersampling Biases in Monte Carlo Eigenvalue and Flux Tally Estimates

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

Perfetti, Christopher M.; Rearden, Bradley T.; Marshall, William J.

2017-02-08

Here, this study focuses on understanding the phenomena in Monte Carlo simulations known as undersampling, in which Monte Carlo tally estimates may not encounter a sufficient number of particles during each generation to obtain unbiased tally estimates. Steady-state Monte Carlo simulations were performed using the KENO Monte Carlo tools within the SCALE code system for models of several burnup credit applications with varying degrees of spatial and isotopic complexities, and the incidence and impact of undersampling on eigenvalue and flux estimates were examined. Using an inadequate number of particle histories in each generation was found to produce a maximum bias of ~100 pcm in eigenvalue estimates and biases that exceeded 10% in fuel pin flux tally estimates. Having quantified the potential magnitude of undersampling biases in eigenvalue and flux tally estimates in these systems, this study then investigated whether Markov Chain Monte Carlo convergence metrics could be integrated into Monte Carlo simulations to predict the onset and magnitude of undersampling biases. Five potential metrics for identifying undersampling biases were implemented in the SCALE code system and evaluated for their ability to predict undersampling biases by comparing the test metric scores with the observed undersampling biases. Finally, of the five convergence metrics that were investigated, three (the Heidelberger-Welch relative half-width, the Gelman-Rubin more » $$\\hat{R}_c$$ diagnostic, and tally entropy) showed the potential to accurately predict the behavior of undersampling biases in the responses examined.« less

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.

2004-01-01

The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…

Considerations of MCNP Monte Carlo code to be used as a radiotherapy treatment planning tool.

PubMed

Juste, B; Miro, R; Gallardo, S; Verdu, G; Santos, A

2005-01-01

The present work has simulated the photon and electron transport in a Theratron 780® (MDS Nordion)⁶⁰Co radiotherapy unit, using the Monte Carlo transport code, MCNP (Monte Carlo N-Particle). This project explains mainly the different methodologies carried out to speedup calculations in order to apply this code efficiently in radiotherapy treatment planning.

Hybrid Monte Carlo/deterministic methods for radiation shielding problems

NASA Astrophysics Data System (ADS)

Becker, Troy L.

For the past few decades, the most common type of deep-penetration (shielding) problem simulated using Monte Carlo methods has been the source-detector problem, in which a response is calculated at a single location in space. Traditionally, the nonanalog Monte Carlo methods used to solve these problems have required significant user input to generate and sufficiently optimize the biasing parameters necessary to obtain a statistically reliable solution. It has been demonstrated that this laborious task can be replaced by automated processes that rely on a deterministic adjoint solution to set the biasing parameters---the so-called hybrid methods. The increase in computational power over recent years has also led to interest in obtaining the solution in a region of space much larger than a point detector. In this thesis, we propose two methods for solving problems ranging from source-detector problems to more global calculations---weight windows and the Transform approach. These techniques employ sonic of the same biasing elements that have been used previously; however, the fundamental difference is that here the biasing techniques are used as elements of a comprehensive tool set to distribute Monte Carlo particles in a user-specified way. The weight window achieves the user-specified Monte Carlo particle distribution by imposing a particular weight window on the system, without altering the particle physics. The Transform approach introduces a transform into the neutron transport equation, which results in a complete modification of the particle physics to produce the user-specified Monte Carlo distribution. These methods are tested in a three-dimensional multigroup Monte Carlo code. For a basic shielding problem and a more realistic one, these methods adequately solved source-detector problems and more global calculations. Furthermore, they confirmed that theoretical Monte Carlo particle distributions correspond to the simulated ones, implying that these methods can be used to achieve user-specified Monte Carlo distributions. Overall, the Transform approach performed more efficiently than the weight window methods, but it performed much more efficiently for source-detector problems than for global problems.

Accelerated GPU based SPECT Monte Carlo simulations.

PubMed

Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

2016-06-07

Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency of SPECT imaging simulations.

Measuring and monitoring KIPT Neutron Source Facility Reactivity

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

Cao, Yan; Gohar, Yousry; Zhong, Zhaopeng

2015-08-01

Argonne National Laboratory (ANL) of USA and Kharkov Institute of Physics and Technology (KIPT) of Ukraine have been collaborating on developing and constructing a neutron source facility at Kharkov, Ukraine. The facility consists of an accelerator-driven subcritical system. The accelerator has a 100 kW electron beam using 100 MeV electrons. The subcritical assembly has k eff less than 0.98. To ensure the safe operation of this neutron source facility, the reactivity of the subcritical core has to be accurately determined and continuously monitored. A technique which combines the area-ratio method and the flux-to-current ratio method is purposed to determine themore » reactivity of the KIPT subcritical assembly at various conditions. In particular, the area-ratio method can determine the absolute reactivity of the subcritical assembly in units of dollars by performing pulsed-neutron experiments. It provides reference reactivities for the flux-to-current ratio method to track and monitor the reactivity deviations from the reference state while the facility is at other operation modes. Monte Carlo simulations are performed to simulate both methods using the numerical model of the KIPT subcritical assembly. It is found that the reactivities obtained from both the area-ratio method and the flux-to-current ratio method are spatially dependent on the neutron detector locations and types. Numerical simulations also suggest optimal neutron detector locations to minimize the spatial effects in the flux-to-current ratio method. The spatial correction factors are calculated using Monte Carlo methods for both measuring methods at the selected neutron detector locations. Monte Carlo simulations are also performed to verify the accuracy of the flux-to-current ratio method in monitoring the reactivity swing during a fuel burnup cycle.« less

Monte Carlo method for calculating the radiation skyshine produced by electron accelerators

NASA Astrophysics Data System (ADS)

Kong, Chaocheng; Li, Quanfeng; Chen, Huaibi; Du, Taibin; Cheng, Cheng; Tang, Chuanxiang; Zhu, Li; Zhang, Hui; Pei, Zhigang; Ming, Shenjin

2005-06-01

Using the MCNP4C Monte Carlo code, the X-ray skyshine produced by 9 MeV, 15 MeV and 21 MeV electron linear accelerators were calculated respectively with a new two-step method combined with the split and roulette variance reduction technique. Results of the Monte Carlo simulation, the empirical formulas used for skyshine calculation and the dose measurements were analyzed and compared. In conclusion, the skyshine dose measurements agreed reasonably with the results computed by the Monte Carlo method, but deviated from computational results given by empirical formulas. The effect on skyshine dose caused by different structures of accelerator head is also discussed in this paper.

Analytic continuation of quantum Monte Carlo data by stochastic analytical inference.

PubMed

Fuchs, Sebastian; Pruschke, Thomas; Jarrell, Mark

2010-05-01

We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte Carlo simulations, yielding as by-product also the distribution function as function of the regularization parameter. Our algorithm thus avoids the usual ad hoc assumptions introduced in similar algorithms to fix the regularization parameter. We apply the algorithm to imaginary-time quantum Monte Carlo data and compare the resulting energy spectra with those from a standard maximum-entropy calculation.

Self-learning Monte Carlo method

DOE PAGES

Liu, Junwei; Qi, Yang; Meng, Zi Yang; ...

2017-01-04

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. Lastly, we demonstrate the efficiency of SLMC in a spin model at the phasemore » transition point, achieving a 10–20 times speedup.« less

Random Numbers and Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Scherer, Philipp O. J.

Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

PubMed

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

DOE PAGES

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.; ...

2018-04-19

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

Collision of Physics and Software in the Monte Carlo Application Toolkit (MCATK)

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

Sweezy, Jeremy Ed

2016-01-21

The topic is presented in a series of slides organized as follows: MCATK overview, development strategy, available algorithms, problem modeling (sources, geometry, data, tallies), parallelism, miscellaneous tools/features, example MCATK application, recent areas of research, and summary and future work. MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library with continuous energy neutron and photon transport. Designed to build specialized applications and to provide new functionality in existing general-purpose Monte Carlo codes like MCNP, it reads ACE formatted nuclear data generated by NJOY. The motivation behind MCATK was to reduce costs. MCATK physics involves continuous energy neutron & gammamore » transport with multi-temperature treatment, static eigenvalue (k eff and α) algorithms, time-dependent algorithm, and fission chain algorithms. MCATK geometry includes mesh geometries and solid body geometries. MCATK provides verified, unit-test Monte Carlo components, flexibility in Monte Carlo application development, and numerous tools such as geometry and cross section plotters.« less

Monte Carlo simulation for kinetic chemotaxis model: An application to the traveling population wave

NASA Astrophysics Data System (ADS)

Yasuda, Shugo

2017-02-01

A Monte Carlo simulation of chemotactic bacteria is developed on the basis of the kinetic model and is applied to a one-dimensional traveling population wave in a microchannel. In this simulation, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to calculate the macroscopic transport of the chemical cues in the environment. The simulation method can successfully reproduce the traveling population wave of bacteria that was observed experimentally and reveal the microscopic dynamics of bacterium coupled with the macroscopic transports of the chemical cues and bacteria population density. The results obtained by the Monte Carlo method are also compared with the asymptotic solution derived from the kinetic chemotaxis equation in the continuum limit, where the Knudsen number, which is defined by the ratio of the mean free path of bacterium to the characteristic length of the system, vanishes. The validity of the Monte Carlo method in the asymptotic behaviors for small Knudsen numbers is numerically verified.

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

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

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

Benchmarking PARTISN with Analog Monte Carlo: Moments of the Neutron Number and the Cumulative Fission Number Probability Distributions

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

O'Rourke, Patrick Francis

The purpose of this report is to provide the reader with an understanding of how a Monte Carlo neutron transport code was written, developed, and evolved to calculate the probability distribution functions (PDFs) and their moments for the neutron number at a final time as well as the cumulative fission number, along with introducing several basic Monte Carlo concepts.

Sample Size and Power Estimates for a Confirmatory Factor Analytic Model in Exercise and Sport: A Monte Carlo Approach

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2011-01-01

Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…

MR Imaging Based Treatment Planning for Radiotherapy of Prostate Cancer

DTIC Science & Technology

2007-02-01

developed practical methods for heterogeneity correction for MRI - based dose calculations (Chen et al 2007). 6) We will use existing Monte Carlo ... Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system, Phys. Med. Biol., 45:2483-95 (2000) Ma...accuracy and consistency for MR based IMRT treatment planning for prostate cancer. A short paper entitled “ Monte Carlo dose verification of MR image based

Perturbative two- and three-loop coefficients from large β Monte Carlo

NASA Astrophysics Data System (ADS)

Lepage, G. P.; Mackenzie, P. B.; Shakespeare, N. H.; Trottier, H. D.

Perturbative coefficients for Wilson loops and the static quark self-energy are extracted from Monte Carlo simulations at large β on finite volumes, where all the lattice momenta are large. The Monte Carlo results are in excellent agreement with perturbation theory through second order. New results for third order coefficients are reported. Twisted boundary conditions are used to eliminate zero modes and to suppress Z3 tunneling.

Perturbative two- and three-loop coefficients from large b Monte Carlo

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

G.P. Lepage; P.B. Mackenzie; N.H. Shakespeare

1999-10-18

Perturbative coefficients for Wilson loops and the static quark self-energy are extracted from Monte Carlo simulations at large {beta} on finite volumes, where all the lattice momenta are large. The Monte Carlo results are in excellent agreement with perturbation theory through second order. New results for third order coefficients are reported. Twisted boundary conditions are used to eliminate zero modes and to suppress Z{sub 3} tunneling.

Fission matrix-based Monte Carlo criticality analysis of fuel storage pools

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

Farlotti, M.; Ecole Polytechnique, Palaiseau, F 91128; Larsen, E. W.

2013-07-01

Standard Monte Carlo transport procedures experience difficulties in solving criticality problems in fuel storage pools. Because of the strong neutron absorption between fuel assemblies, source convergence can be very slow, leading to incorrect estimates of the eigenvalue and the eigenfunction. This study examines an alternative fission matrix-based Monte Carlo transport method that takes advantage of the geometry of a storage pool to overcome this difficulty. The method uses Monte Carlo transport to build (essentially) a fission matrix, which is then used to calculate the criticality and the critical flux. This method was tested using a test code on a simplemore » problem containing 8 assemblies in a square pool. The standard Monte Carlo method gave the expected eigenfunction in 5 cases out of 10, while the fission matrix method gave the expected eigenfunction in all 10 cases. In addition, the fission matrix method provides an estimate of the error in the eigenvalue and the eigenfunction, and it allows the user to control this error by running an adequate number of cycles. Because of these advantages, the fission matrix method yields a higher confidence in the results than standard Monte Carlo. We also discuss potential improvements of the method, including the potential for variance reduction techniques. (authors)« less

Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry

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

Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Cagnon, Chris H.

Purpose: The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements. Methods: MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for allmore » exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy. Results: The calculated mean percent difference between TLD measurements and Monte Carlo simulations was −4.9% with standard deviation of 8.7% and a range of −22.7% to 5.7%. Conclusions: The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.« less

Using the Metropolis Algorithm to Calculate Thermodynamic Quantities: An Undergraduate Computational Experiment

ERIC Educational Resources Information Center

Beddard, Godfrey S.

2011-01-01

Thermodynamic quantities such as the average energy, heat capacity, and entropy are calculated using a Monte Carlo method based on the Metropolis algorithm. This method is illustrated with reference to the harmonic oscillator but is particularly useful when the partition function cannot be evaluated; an example using a one-dimensional spin system…

Assessing Beaked Whale Reproduction and Stress Response Relative to Sonar Activity at the Atlantic Undersea Test and Evaluation Center (AUTEC)

DTIC Science & Technology

2015-09-30

oil spills (unpublished data, Kellar). The second will be to conduct a more fine-scale analysis of the areas examined during this study. For this...REFERENCES Carlin BP , Chib S (1995) Bayesian model choice via Markov-chain Monte-Carlo methods. Journal of the Royal Statistical Society

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Massively parallel multicanonical simulations

NASA Astrophysics Data System (ADS)

Gross, Jonathan; Zierenberg, Johannes; Weigel, Martin; Janke, Wolfhard

2018-03-01

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free-energy landscapes. As Markov chain methods, they are inherently serial computationally. It was demonstrated recently, however, that a combination of independent simulations that communicate weight updates at variable intervals allows for the efficient utilization of parallel computational resources for multicanonical simulations. Implementing this approach for the many-thread architecture provided by current generations of graphics processing units (GPUs), we show how it can be efficiently employed with of the order of 104 parallel walkers and beyond, thus constituting a versatile tool for Monte Carlo simulations in the era of massively parallel computing. We provide the fully documented source code for the approach applied to the paradigmatic example of the two-dimensional Ising model as starting point and reference for practitioners in the field.

A Monte Carlo model for photoneutron generation by a medical LINAC

NASA Astrophysics Data System (ADS)

Sumini, M.; Isolan, L.; Cucchi, G.; Sghedoni, R.; Iori, M.

2017-11-01

For an optimal tuning of the radiation protection planning, a Monte Carlo model using the MCNPX code has been built, allowing an accurate estimate of the spectrometric and geometrical characteristics of photoneutrons generated by a Varian TrueBeam Stx© medical linear accelerator. We considered in our study a device working at the reference energy for clinical applications of 15 MV, stemmed from a Varian Clinac©2100 modeled starting from data collected thanks to several papers available in the literature. The model results were compared with neutron and photon dose measurements inside and outside the bunker hosting the accelerator obtaining a complete dose map. Normalized neutron fluences were tallied in different positions at the patient plane and at different depths. A sensitivity analysis with respect to the flattening filter material were performed to enlighten aspects that could influence the photoneutron production.

Calibration with MCNP of NaI detector for the determination of natural radioactivity levels in the field.

PubMed

Cinelli, Giorgia; Tositti, Laura; Mostacci, Domiziano; Baré, Jonathan

2016-05-01

In view of assessing natural radioactivity with on-site quantitative gamma spectrometry, efficiency calibration of NaI(Tl) detectors is investigated. A calibration based on Monte Carlo simulation of detector response is proposed, to render reliable quantitative analysis practicable in field campaigns. The method is developed with reference to contact geometry, in which measurements are taken placing the NaI(Tl) probe directly against the solid source to be analyzed. The Monte Carlo code used for the simulations was MCNP. Experimental verification of the calibration goodness is obtained by comparison with appropriate standards, as reported. On-site measurements yield a quick quantitative assessment of natural radioactivity levels present ((40)K, (238)U and (232)Th). On-site gamma spectrometry can prove particularly useful insofar as it provides information on materials from which samples cannot be taken. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

High-pT Physics in the Heavy Ion Era

NASA Astrophysics Data System (ADS)

Rak, Jan; Tannenbaum, Michael J.

2013-04-01

1. Introduction and overview; 2. Basic observables; 3. Some experimental techniques; 4. The search for structure; 5. Origins of high pT physics - the search for the W boson; 6. Discovery of hard scattering in p-p collisions; 7. Direct single lepton production and the discovery of charm; 8. J/ ψ, u and Drell-Yan pair production; 9. Two particle correlations; 10. Direct photon production; 11. The search for jets; 12. QCD in hard scattering; 13. Heavy ion physics in the high pT era; 14. RHIC and LHC; Appendix A. Probability and statistics; Appendix B. Methods of Monte Carlo calculations; Appendix C. TAB and the Glauber Monte Carlo calculation; Appendix D. Fits including systematic errors; Appendix E. The shape of the xE distribution triggered by a jet fragment, for example, π0; Appendix F. kT phenomenology and Gaussian smearing; References; Index.

Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer.

PubMed

Castonguay, Thomas C; Wang, Feng

2008-03-28

In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer

NASA Astrophysics Data System (ADS)

Castonguay, Thomas C.; Wang, Feng

2008-03-01

In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

Response Matrix Monte Carlo for electron transport

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

Ballinger, C.T.; Nielsen, D.E. Jr.; Rathkopf, J.A.

1990-11-01

A Response Matrix Monte Carol (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts tomore » combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. The combined effect of many collisions is modeled, like condensed history, except it is precalculated via an analog Monte Carol simulation. This avoids the scattering kernel assumptions associated with condensed history methods. Results show good agreement between the RMMC method and analog Monte Carlo. 11 refs., 7 figs., 1 tabs.« less

Verification and Validation of Monte Carlo n-Particle Code 6 (MCNP6) with Neutron Protection Factor Measurements of an Iron Box

DTIC Science & Technology

2014-03-27

VERIFICATION AND VALIDATION OF MONTE CARLO N- PARTICLE CODE 6 (MCNP6) WITH NEUTRON PROTECTION FACTOR... PARTICLE CODE 6 (MCNP6) WITH NEUTRON PROTECTION FACTOR MEASUREMENTS OF AN IRON BOX THESIS Presented to the Faculty Department of Engineering...STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED iv AFIT-ENP-14-M-05 VERIFICATION AND VALIDATION OF MONTE CARLO N- PARTICLE CODE 6

Study of the Transition Flow Regime using Monte Carlo Methods

NASA Technical Reports Server (NTRS)

Hassan, H. A.

1999-01-01

This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.

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.

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.

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

NASA Astrophysics Data System (ADS)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.

COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT

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

W. R. MARTIN; F. B. BROWN

2001-03-01

Five Monte Carlo methods for solving the nonlinear thermal radiation transport equations are compared. The methods include the well-known Implicit Monte Carlo method (IMC) developed by Fleck and Cummings, an alternative to IMC developed by Carter and Forest, an ''exact'' method recently developed by Ahrens and Larsen, and two methods recently proposed by Martin and Brown. The five Monte Carlo methods are developed and applied to the radiation transport equation in a medium assuming local thermodynamic equilibrium. Conservation of energy is derived and used to define appropriate material energy update equations for each of the methods. Details of the Montemore » Carlo implementation are presented, both for the random walk simulation and the material energy update. Simulation results for all five methods are obtained for two infinite medium test problems and a 1-D test problem, all of which have analytical solutions. Conclusions regarding the relative merits of the various schemes are presented.« less

Implementation of new physics models for low energy electrons in liquid water in Geant4-DNA.

PubMed

Bordage, M C; Bordes, J; Edel, S; Terrissol, M; Franceries, X; Bardiès, M; Lampe, N; Incerti, S

2016-12-01

A new alternative set of elastic and inelastic cross sections has been added to the very low energy extension of the Geant4 Monte Carlo simulation toolkit, Geant4-DNA, for the simulation of electron interactions in liquid water. These cross sections have been obtained from the CPA100 Monte Carlo track structure code, which has been a reference in the microdosimetry community for many years. They are compared to the default Geant4-DNA cross sections and show better agreement with published data. In order to verify the correct implementation of the CPA100 cross section models in Geant4-DNA, simulations of the number of interactions and ranges were performed using Geant4-DNA with this new set of models, and the results were compared with corresponding results from the original CPA100 code. Good agreement is observed between the implementations, with relative differences lower than 1% regardless of the incident electron energy. Useful quantities related to the deposited energy at the scale of the cell or the organ of interest for internal dosimetry, like dose point kernels, are also calculated using these new physics models. They are compared with results obtained using the well-known Penelope Monte Carlo code. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Pharmacokinetics of enrofloxacin HCl-2H2O (ENRO-C) in dogs and PK/PD Monte Carlo simulations against Leptospira sp.

PubMed

Sumano, Hector; Ocampo, Luis; Tapia, Graciela; Mendoza, C de Jesus; Gutierrez, Lilia

2018-04-12

Pharmacokinetics/pharmacodynamics (PK/PD) ratios of reference enrofloxacin (Enro-R) and enrofloxacin as HCl-2H 2 O (Enro-C), as well as Monte Carlo simulations based on composite MIC 50 and MIC 90 vs. Leptospira sp., were carried out in dogs after their IM and oral administration (10 mg/kg). Plasma determination of enrofloxacin was achieved by means of high performance liquid chromatography (HPLC). Maximum plasma concentration values after oral administration were 1.47 ± 0.19 µg/mL and 5.3 ± 0.84 µg/mL for Enro-R and Enro-C, respectively, and 1.6 ± 0.12 µg/mL and 7.6 ± 0.93 µg/mL after IM administration. Area under the plasma vs. time concentrations in 24 h (AUC 0-24 ) were 8.02 µg/mL/h and 36.2 µg/mL/h for Enro-R oral and Enro-C oral , respectively, and 8.55 ± 0.85 µg/mL/h and 56.4 ± 6.21 µg/mL/h after IM administration of these drugs. Only PK/PD ratios and Monte Carlo simulations obtained with Enro-C, anticipate that its IM administration to dogs will result in therapeutic concentrations to treat leptospirosis. This is the first time enrofloxacin has been recommended to treat this disease in dogs.

The use of Monte Carlo simulations for accurate dose determination with thermoluminescence dosemeters in radiation therapy beams.

PubMed

Mobit, P

2002-01-01

The energy responses of LiF-TLDs irradiated in megavoltage electron and photon beams have been determined experimentally by many investigators over the past 35 years but the results vary considerably. General cavity theory has been used to model some of the experimental findings but the predictions of these cavity theories differ from each other and from measurements by more than 13%. Recently, two groups or investigators using Monte Carlo simulations and careful experimental techniques showed that the energy response of 1 mm or 2 mm thick LiF-TLD irradiated by megavoltage photon and electron beams is not more than 5% less than unity for low-Z phantom materials like water or Perspex. However, when the depth of irradiation is significantly different from dmax and the TLD size is more than 5 mm, then the energy response is up to 12% less than unity for incident electron beams. Monte Carlo simulations of some of the experiments reported in the literature showed that some of the contradictory experimental results are reproducible with Monte Carlo simulations. Monte Carlo simulations show that the energy response of LiF-TLDs depends on the size of detector used in electron beams, the depth of irradiation and the incident electron energy. Other differences can be attributed to absolute dose determination and precision of the TL technique. Monte Carlo simulations have also been used to evaluate some of the published general cavity theories. The results show that some of the parameters used to evaluate Burlin's general cavity theory are wrong by factor of 3. Despite this, the estimation of the energy response for most clinical situations using Burlin's cavity equation agrees with Monte Carlo simulations within 1%.

[Benchmark experiment to verify radiation transport calculations for dosimetry in radiation therapy].

PubMed

Renner, Franziska

2016-09-01

Monte Carlo simulations are regarded as the most accurate method of solving complex problems in the field of dosimetry and radiation transport. In (external) radiation therapy they are increasingly used for the calculation of dose distributions during treatment planning. In comparison to other algorithms for the calculation of dose distributions, Monte Carlo methods have the capability of improving the accuracy of dose calculations - especially under complex circumstances (e.g. consideration of inhomogeneities). However, there is a lack of knowledge of how accurate the results of Monte Carlo calculations are on an absolute basis. A practical verification of the calculations can be performed by direct comparison with the results of a benchmark experiment. This work presents such a benchmark experiment and compares its results (with detailed consideration of measurement uncertainty) with the results of Monte Carlo calculations using the well-established Monte Carlo code EGSnrc. The experiment was designed to have parallels to external beam radiation therapy with respect to the type and energy of the radiation, the materials used and the kind of dose measurement. Because the properties of the beam have to be well known in order to compare the results of the experiment and the simulation on an absolute basis, the benchmark experiment was performed using the research electron accelerator of the Physikalisch-Technische Bundesanstalt (PTB), whose beam was accurately characterized in advance. The benchmark experiment and the corresponding Monte Carlo simulations were carried out for two different types of ionization chambers and the results were compared. Considering the uncertainty, which is about 0.7 % for the experimental values and about 1.0 % for the Monte Carlo simulation, the results of the simulation and the experiment coincide. Copyright © 2015. Published by Elsevier GmbH.

TASEP of interacting particles of arbitrary size

NASA Astrophysics Data System (ADS)

Narasimhan, S. L.; Baumgaertner, A.

2017-10-01

A mean-field description of the stationary state behaviour of interacting k-mers performing totally asymmetric exclusion processes (TASEP) on an open lattice segment is presented employing the discrete Takahashi formalism. It is shown how the maximal current and the phase diagram, including triple-points, depend on the strength of repulsive and attractive interactions. We compare the mean-field results with Monte Carlo simulation of three types interacting k-mers: monomers, dimers and trimers. (a) We find that the Takahashi estimates of the maximal current agree quantitatively with those of the Monte Carlo simulation in the absence of interaction as well as in both the the attractive and the strongly repulsive regimes. However, theory and Monte Carlo results disagree in the range of weak repulsion, where the Takahashi estimates of the maximal current show a monotonic behaviour, whereas the Monte Carlo data show a peaking behaviour. It is argued that the peaking of the maximal current is due to a correlated motion of the particles. In the limit of very strong repulsion the theory predicts a universal behavior: th maximal currents of k-mers correspond to that of non-interacting (k+1) -mers; (b) Monte Carlo estimates of the triple-points for monomers, dimers and trimers show an interesting general behaviour : (i) the phase boundaries α * and β* for entry and exit current, respectively, as function of interaction strengths show maxima for α* whereas β * exhibit minima at the same strength; (ii) in the attractive regime, however, the trend is reversed (β * > α * ). The Takahashi estimates of the triple-point for monomers show a similar trend as the Monte Carlo data except for the peaking of α * ; for dimers and trimers, however, the Takahashi estimates show an opposite trend as compared to the Monte Carlo data.

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

PubMed

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Simulation-Based Model Checking for Nondeterministic Systems and Rare Events

DTIC Science & Technology

2016-03-24

year, we have investigated AO* search and Monte Carlo Tree Search algorithms to complement and enhance CMU’s SMCMDP. 1 Final Report, March 14... tree , so we can use it to find the probability of reachability for a property in PRISM’s Probabilistic LTL. By finding the maximum probability of...savings, particularly when handling very large models. 2.3 Monte Carlo Tree Search The Monte Carlo sampling process in SMCMDP can take a long time to

Effect of the multiple scattering of electrons in Monte Carlo simulation of LINACS.

PubMed

Vilches, Manuel; García-Pareja, Salvador; Guerrero, Rafael; Anguiano, Marta; Lallena, Antonio M

2008-01-01

Results obtained from Monte Carlo simulations of the transport of electrons in thin slabs of dense material media and air slabs with different widths are analyzed. Various general purpose Monte Carlo codes have been used: PENELOPE, GEANT3, GEANT4, EGSNRC, MCNPX. Non-negligible differences between the angular and radial distributions after the slabs have been found. The effects of these differences on the depth doses measured in water are also discussed.

Discrepancy-based error estimates for Quasi-Monte Carlo III. Error distributions and central limits

NASA Astrophysics Data System (ADS)

Hoogland, Jiri; Kleiss, Ronald

1997-04-01

In Quasi-Monte Carlo integration, the integration error is believed to be generally smaller than in classical Monte Carlo with the same number of integration points. Using an appropriate definition of an ensemble of quasi-random point sets, we derive various results on the probability distribution of the integration error, which can be compared to the standard Central Limit Theorem for normal stochastic sampling. In many cases, a Gaussian error distribution is obtained.

Monte Carlos of the new generation: status and progress

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

Frixione, Stefano

2005-03-22

Standard parton shower monte carlos are designed to give reliable descriptions of low-pT physics. In the very high-energy regime of modern colliders, this is may lead to largely incorrect predictions of the basic reaction processes. This motivated the recent theoretical efforts aimed at improving monte carlos through the inclusion of matrix elements computed beyond the leading order in QCD. I briefly review the progress made, and discuss bottom production at the Tevatron.

Monte Carlo simulation of aorta autofluorescence

NASA Astrophysics Data System (ADS)

Kuznetsova, A. A.; Pushkareva, A. E.

2016-08-01

Results of numerical simulation of autofluorescence of the aorta by the method of Monte Carlo are reported. Two states of the aorta, normal and with atherosclerotic lesions, are studied. A model of the studied tissue is developed on the basis of information about optical, morphological, and physico-chemical properties. It is shown that the data obtained by numerical Monte Carlo simulation are in good agreement with experimental results indicating adequacy of the developed model of the aorta autofluorescence.

PRELIMINARY COUPLING OF THE MONTE CARLO CODE OPENMC AND THE MULTIPHYSICS OBJECT-ORIENTED SIMULATION ENVIRONMENT (MOOSE) FOR ANALYZING DOPPLER FEEDBACK IN MONTE CARLO SIMULATIONS

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

Matthew Ellis; Derek Gaston; Benoit Forget

In recent years the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open source Monte Carlo code OpenMC with the open source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes.more » An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two dimensional 17x17 PWR fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes Functional Expansion Tallies to accurately and efficiently transfer pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two dimensional PWR fuel assembly case also demonstrates that for a simplified model the pin-by-pin doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.« less

WARP

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

Bergmann, Ryan M.; Rowland, Kelly L.

2017-04-12

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currentlymore » not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.« less

Combined experimental and Monte Carlo verification of brachytherapy plans for vaginal applicators

NASA Astrophysics Data System (ADS)

Sloboda, Ron S.; Wang, Ruqing

1998-12-01

Dose rates in a phantom around a shielded and an unshielded vaginal applicator containing Selectron low-dose-rate sources were determined by experiment and Monte Carlo simulation. Measurements were performed with thermoluminescent dosimeters in a white polystyrene phantom using an experimental protocol geared for precision. Calculations for the same set-up were done using a version of the EGS4 Monte Carlo code system modified for brachytherapy applications into which a new combinatorial geometry package developed by Bielajew was recently incorporated. Measured dose rates agree with Monte Carlo estimates to within 5% (1 SD) for the unshielded applicator, while highlighting some experimental uncertainties for the shielded applicator. Monte Carlo calculations were also done to determine a value for the effective transmission of the shield required for clinical treatment planning, and to estimate the dose rate in water at points in axial and sagittal planes transecting the shielded applicator. Comparison with dose rates generated by the planning system indicates that agreement is better than 5% (1 SD) at most positions. The precision thermoluminescent dosimetry protocol and modified Monte Carlo code are effective complementary tools for brachytherapy applicator dosimetry.

Monte Carlo modelling the dosimetric effects of electrode material on diamond detectors.

PubMed

Baluti, Florentina; Deloar, Hossain M; Lansley, Stuart P; Meyer, Juergen

2015-03-01

Diamond detectors for radiation dosimetry were modelled using the EGSnrc Monte Carlo code to investigate the influence of electrode material and detector orientation on the absorbed dose. The small dimensions of the electrode/diamond/electrode detector structure required very thin voxels and the use of non-standard DOSXYZnrc Monte Carlo model parameters. The interface phenomena was investigated by simulating a 6 MV beam and detectors with different electrode materials, namely Al, Ag, Cu and Au, with thickens of 0.1 µm for the electrodes and 0.1 mm for the diamond, in both perpendicular and parallel detector orientation with regards to the incident beam. The smallest perturbations were observed for the parallel detector orientation and Al electrodes (Z = 13). In summary, EGSnrc Monte Carlo code is well suited for modelling small detector geometries. The Monte Carlo model developed is a useful tool to investigate the dosimetric effects caused by different electrode materials. To minimise perturbations cause by the detector electrodes, it is recommended that the electrodes should be made from a low-atomic number material and placed parallel to the beam direction.

Physical Principle for Generation of Randomness

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Parallel Monte Carlo transport modeling in the context of a time-dependent, three-dimensional multi-physics code

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

Procassini, R.J.

1997-12-31

The fine-scale, multi-space resolution that is envisioned for accurate simulations of complex weapons systems in three spatial dimensions implies flop-rate and memory-storage requirements that will only be obtained in the near future through the use of parallel computational techniques. Since the Monte Carlo transport models in these simulations usually stress both of these computational resources, they are prime candidates for parallelization. The MONACO Monte Carlo transport package, which is currently under development at LLNL, will utilize two types of parallelism within the context of a multi-physics design code: decomposition of the spatial domain across processors (spatial parallelism) and distribution ofmore » particles in a given spatial subdomain across additional processors (particle parallelism). This implementation of the package will utilize explicit data communication between domains (message passing). Such a parallel implementation of a Monte Carlo transport model will result in non-deterministic communication patterns. The communication of particles between subdomains during a Monte Carlo time step may require a significant level of effort to achieve a high parallel efficiency.« less

A High-Order Low-Order Algorithm with Exponentially Convergent Monte Carlo for Thermal Radiative Transfer

DOE PAGES

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

2016-10-21

In this paper, we have implemented a new high-order low-order (HOLO) algorithm for solving thermal radiative transfer problems. The low-order (LO) system is based on the spatial and angular moments of the transport equation and a linear-discontinuous finite-element spatial representation, producing equations similar to the standard S 2 equations. The LO solver is fully implicit in time and efficiently resolves the nonlinear temperature dependence at each time step. The high-order (HO) solver utilizes exponentially convergent Monte Carlo (ECMC) to give a globally accurate solution for the angular intensity to a fixed-source pure-absorber transport problem. This global solution is used tomore » compute consistency terms, which require the HO and LO solutions to converge toward the same solution. The use of ECMC allows for the efficient reduction of statistical noise in the Monte Carlo solution, reducing inaccuracies introduced through the LO consistency terms. Finally, we compare results with an implicit Monte Carlo code for one-dimensional gray test problems and demonstrate the efficiency of ECMC over standard Monte Carlo in this HOLO algorithm.« less

Monte Carlo capabilities of the SCALE code system

DOE PAGES

Rearden, Bradley T.; Petrie, Jr., Lester M.; Peplow, Douglas E.; ...

2014-09-12

SCALE is a broadly used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport asmore » well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. Finally, an overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.« less

The structure of liquid water by polarized neutron diffraction and reverse Monte Carlo modelling.

PubMed

Temleitner, László; Pusztai, László; Schweika, Werner

2007-08-22

The coherent static structure factor of water has been investigated by polarized neutron diffraction. Polarization analysis allows us to separate the huge incoherent scattering background from hydrogen and to obtain high quality data of the coherent scattering from four different mixtures of liquid H(2)O and D(2)O. The information obtained by the variation of the scattering contrast confines the configurational space of water and is used by the reverse Monte Carlo technique to model the total structure factors. Structural characteristics have been calculated directly from the resulting sets of particle coordinates. Consistency with existing partial pair correlation functions, derived without the application of polarized neutrons, was checked by incorporating them into our reverse Monte Carlo calculations. We also performed Monte Carlo simulations of a hard sphere system, which provides an accurate estimate of the information content of the measured data. It is shown that the present combination of polarized neutron scattering and reverse Monte Carlo structural modelling is a promising approach towards a detailed understanding of the microscopic structure of water.

Monte Carlo methods for multidimensional integration for European option pricing

NASA Astrophysics Data System (ADS)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.

Path integral Monte Carlo ground state approach: formalism, implementation, and applications

NASA Astrophysics Data System (ADS)

Yan, Yangqian; Blume, D.

2017-11-01

Monte Carlo techniques have played an important role in understanding strongly correlated systems across many areas of physics, covering a wide range of energy and length scales. Among the many Monte Carlo methods applicable to quantum mechanical systems, the path integral Monte Carlo approach with its variants has been employed widely. Since semi-classical or classical approaches will not be discussed in this review, path integral based approaches can for our purposes be divided into two categories: approaches applicable to quantum mechanical systems at zero temperature and approaches applicable to quantum mechanical systems at finite temperature. While these two approaches are related to each other, the underlying formulation and aspects of the algorithm differ. This paper reviews the path integral Monte Carlo ground state (PIGS) approach, which solves the time-independent Schrödinger equation. Specifically, the PIGS approach allows for the determination of expectation values with respect to eigen states of the few- or many-body Schrödinger equation provided the system Hamiltonian is known. The theoretical framework behind the PIGS algorithm, implementation details, and sample applications for fermionic systems are presented.

Monte Carlo Estimation of Absorbed Dose Distributions Obtained from Heterogeneous 106Ru Eye Plaques.

PubMed

Zaragoza, Francisco J; Eichmann, Marion; Flühs, Dirk; Sauerwein, Wolfgang; Brualla, Lorenzo

2017-09-01

The distribution of the emitter substance in 106 Ru eye plaques is usually assumed to be homogeneous for treatment planning purposes. However, this distribution is never homogeneous, and it widely differs from plaque to plaque due to manufacturing factors. By Monte Carlo simulation of radiation transport, we study the absorbed dose distribution obtained from the specific CCA1364 and CCB1256 106 Ru plaques, whose actual emitter distributions were measured. The idealized, homogeneous CCA and CCB plaques are also simulated. The largest discrepancy in depth dose distribution observed between the heterogeneous and the homogeneous plaques was 7.9 and 23.7% for the CCA and CCB plaques, respectively. In terms of isodose lines, the line referring to 100% of the reference dose penetrates 0.2 and 1.8 mm deeper in the case of heterogeneous CCA and CCB plaques, respectively, with respect to the homogeneous counterpart. The observed differences in absorbed dose distributions obtained from heterogeneous and homogeneous plaques are clinically irrelevant if the plaques are used with a lateral safety margin of at least 2 mm. However, these differences may be relevant if the plaques are used in eccentric positioning.

Impact of Non-Gaussian Error Volumes on Conjunction Assessment Risk Analysis

NASA Technical Reports Server (NTRS)

Ghrist, Richard W.; Plakalovic, Dragan

2012-01-01

An understanding of how an initially Gaussian error volume becomes non-Gaussian over time is an important consideration for space-vehicle conjunction assessment. Traditional assumptions applied to the error volume artificially suppress the true non-Gaussian nature of the space-vehicle position uncertainties. For typical conjunction assessment objects, representation of the error volume by a state error covariance matrix in a Cartesian reference frame is a more significant limitation than is the assumption of linearized dynamics for propagating the error volume. In this study, the impact of each assumption is examined and isolated for each point in the volume. Limitations arising from representing the error volume in a Cartesian reference frame is corrected by employing a Monte Carlo approach to probability of collision (Pc), using equinoctial samples from the Cartesian position covariance at the time of closest approach (TCA) between the pair of space objects. A set of actual, higher risk (Pc >= 10 (exp -4)+) conjunction events in various low-Earth orbits using Monte Carlo methods are analyzed. The impact of non-Gaussian error volumes on Pc for these cases is minimal, even when the deviation from a Gaussian distribution is significant.

Quantum speedup of Monte Carlo methods.

PubMed

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

Self-Learning Monte Carlo Method

NASA Astrophysics Data System (ADS)

Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of general and efficient update algorithm for large size systems close to phase transition or with strong frustrations, for which local updates perform badly. In this work, we propose a new general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup. This work is supported by the DOE Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-SC0010526.

Fixed forced detection for fast SPECT Monte-Carlo simulation

NASA Astrophysics Data System (ADS)

Cajgfinger, T.; Rit, S.; Létang, J. M.; Halty, A.; Sarrut, D.

2018-03-01

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Using MathCad to Evaluate Exact Integral Formulations of Spacecraft Orbital Heats for Primitive Surfaces at Any Orientation

NASA Technical Reports Server (NTRS)

Pinckney, John

2010-01-01

With the advent of high speed computing Monte Carlo ray tracing techniques has become the preferred method for evaluating spacecraft orbital heats. Monte Carlo has its greatest advantage where there are many interacting surfaces. However Monte Carlo programs are specialized programs that suffer from some inaccuracy, long calculation times and high purchase cost. A general orbital heating integral is presented here that is accurate, fast and runs on MathCad, a generally available engineering mathematics program. The integral is easy to read, understand and alter. The integral can be applied to unshaded primitive surfaces at any orientation. The method is limited to direct heating calculations. This integral formulation can be used for quick orbit evaluations and spot checking Monte Carlo results.

Fixed forced detection for fast SPECT Monte-Carlo simulation.

PubMed

Cajgfinger, T; Rit, S; Létang, J M; Halty, A; Sarrut, D

2018-03-02

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Calculation of radiation therapy dose using all particle Monte Carlo transport

DOEpatents

Chandler, William P.; Hartmann-Siantar, Christine L.; Rathkopf, James A.

1999-01-01

The actual radiation dose absorbed in the body is calculated using three-dimensional Monte Carlo transport. Neutrons, protons, deuterons, tritons, helium-3, alpha particles, photons, electrons, and positrons are transported in a completely coupled manner, using this Monte Carlo All-Particle Method (MCAPM). The major elements of the invention include: computer hardware, user description of the patient, description of the radiation source, physical databases, Monte Carlo transport, and output of dose distributions. This facilitated the estimation of dose distributions on a Cartesian grid for neutrons, photons, electrons, positrons, and heavy charged-particles incident on any biological target, with resolutions ranging from microns to centimeters. Calculations can be extended to estimate dose distributions on general-geometry (non-Cartesian) grids for biological and/or non-biological media.

Monte Carlo simulation: Its status and future

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

Murtha, J.A.

1997-04-01

Monte Carlo simulation is a statistics-based analysis tool that yields probability-vs.-value relationships for key parameters, including oil and gas reserves, capital exposure, and various economic yardsticks, such as net present value (NPV) and return on investment (ROI). Monte Carlo simulation is a part of risk analysis and is sometimes performed in conjunction with or as an alternative to decision [tree] analysis. The objectives are (1) to define Monte Carlo simulation in a more general context of risk and decision analysis; (2) to provide some specific applications, which can be interrelated; (3) to respond to some of the criticisms; (4) tomore » offer some cautions about abuses of the method and recommend how to avoid the pitfalls; and (5) to predict what the future has in store.« less

Quantum speedup of Monte Carlo methods

PubMed Central

Montanaro, Ashley

2015-01-01

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079

Calculation of radiation therapy dose using all particle Monte Carlo transport

DOEpatents

Chandler, W.P.; Hartmann-Siantar, C.L.; Rathkopf, J.A.

1999-02-09

The actual radiation dose absorbed in the body is calculated using three-dimensional Monte Carlo transport. Neutrons, protons, deuterons, tritons, helium-3, alpha particles, photons, electrons, and positrons are transported in a completely coupled manner, using this Monte Carlo All-Particle Method (MCAPM). The major elements of the invention include: computer hardware, user description of the patient, description of the radiation source, physical databases, Monte Carlo transport, and output of dose distributions. This facilitated the estimation of dose distributions on a Cartesian grid for neutrons, photons, electrons, positrons, and heavy charged-particles incident on any biological target, with resolutions ranging from microns to centimeters. Calculations can be extended to estimate dose distributions on general-geometry (non-Cartesian) grids for biological and/or non-biological media. 57 figs.

Multiscale Monte Carlo equilibration: Pure Yang-Mills theory

DOE PAGES

Endres, Michael G.; Brower, Richard C.; Orginos, Kostas; ...

2015-12-29

In this study, we present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

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.

PEPSI — a Monte Carlo generator for polarized leptoproduction

NASA Astrophysics Data System (ADS)

Mankiewicz, L.; Schäfer, A.; Veltri, M.

1992-09-01

We describe PEPSI (Polarized Electron Proton Scattering Interactions), a Monte Carlo program for polarized deep inelastic leptoproduction mediated by electromagnetic interaction, and explain how to use it. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering. The hard virtual gamma-parton scattering is generated according to the polarization-dependent QCD cross-section of the first order in α S. PEPSI requires the standard polarization-independent JETSET routines to simulate the fragmentation into final hadrons.

NUEN-618 Class Project: Actually Implicit Monte Carlo

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

Vega, R. M.; Brunner, T. A.

2017-12-14

This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.

Monte Carlo simulations of adult and pediatric computed tomography exams: Validation studies of organ doses with physical phantoms

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

Long, Daniel J.; Lee, Choonsik; Tien, Christopher

2013-01-15

Purpose: To validate the accuracy of a Monte Carlo source model of the Siemens SOMATOM Sensation 16 CT scanner using organ doses measured in physical anthropomorphic phantoms. Methods: The x-ray output of the Siemens SOMATOM Sensation 16 multidetector CT scanner was simulated within the Monte Carlo radiation transport code, MCNPX version 2.6. The resulting source model was able to perform various simulated axial and helical computed tomographic (CT) scans of varying scan parameters, including beam energy, filtration, pitch, and beam collimation. Two custom-built anthropomorphic phantoms were used to take dose measurements on the CT scanner: an adult male and amore » 9-month-old. The adult male is a physical replica of University of Florida reference adult male hybrid computational phantom, while the 9-month-old is a replica of University of Florida Series B 9-month-old voxel computational phantom. Each phantom underwent a series of axial and helical CT scans, during which organ doses were measured using fiber-optic coupled plastic scintillator dosimeters developed at University of Florida. The physical setup was reproduced and simulated in MCNPX using the CT source model and the computational phantoms upon which the anthropomorphic phantoms were constructed. Average organ doses were then calculated based upon these MCNPX results. Results: For all CT scans, good agreement was seen between measured and simulated organ doses. For the adult male, the percent differences were within 16% for axial scans, and within 18% for helical scans. For the 9-month-old, the percent differences were all within 15% for both the axial and helical scans. These results are comparable to previously published validation studies using GE scanners and commercially available anthropomorphic phantoms. Conclusions: Overall results of this study show that the Monte Carlo source model can be used to accurately and reliably calculate organ doses for patients undergoing a variety of axial or helical CT examinations on the Siemens SOMATOM Sensation 16 scanner.« less

TU-F-CAMPUS-T-05: A Cloud-Based Monte Carlo Dose Calculation for Electron Cutout Factors

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

Mitchell, T; Bush, K

Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identifymore » the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery.« less

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

Thomas, D; O’Connell, D; Lamb, J

Purpose: To demonstrate real-time dose calculation of free-breathing MRI guided Co−60 treatments, using a motion model and Monte-Carlo dose calculation to accurately account for the interplay between irregular breathing motion and an IMRT delivery. Methods: ViewRay Co-60 dose distributions were optimized on ITVs contoured from free-breathing CT images of lung cancer patients. Each treatment plan was separated into 0.25s segments, accounting for the MLC positions and beam angles at each time point. A voxel-specific motion model derived from multiple fast-helical free-breathing CTs and deformable registration was calculated for each patient. 3D images for every 0.25s of a simulated treatment weremore » generated in real time, here using a bellows signal as a surrogate to accurately account for breathing irregularities. Monte-Carlo dose calculation was performed every 0.25s of the treatment, with the number of histories in each calculation scaled to give an overall 1% statistical uncertainty. Each dose calculation was deformed back to the reference image using the motion model and accumulated. The static and real-time dose calculations were compared. Results: Image generation was performed in real time at 4 frames per second (GPU). Monte-Carlo dose calculation was performed at approximately 1frame per second (CPU), giving a total calculation time of approximately 30 minutes per treatment. Results show both cold- and hot-spots in and around the ITV, and increased dose to contralateral lung as the tumor moves in and out of the beam during treatment. Conclusion: An accurate motion model combined with a fast Monte-Carlo dose calculation allows almost real-time dose calculation of a free-breathing treatment. When combined with sagittal 2D-cine-mode MRI during treatment to update the motion model in real time, this will allow the true delivered dose of a treatment to be calculated, providing a useful tool for adaptive planning and assessing the effectiveness of gated treatments.« less

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches.

PubMed

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository.

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches

PubMed Central

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository. PMID:29551985

Analytical Applications of Monte Carlo Techniques.

ERIC Educational Resources Information Center

Guell, Oscar A.; Holcombe, James A.

1990-01-01

Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)

Rapid scatter estimation for CBCT using the Boltzmann transport equation

NASA Astrophysics Data System (ADS)

Sun, Mingshan; Maslowski, Alex; Davis, Ian; Wareing, Todd; Failla, Gregory; Star-Lack, Josh

2014-03-01

Scatter in cone-beam computed tomography (CBCT) is a significant problem that degrades image contrast, uniformity and CT number accuracy. One means of estimating and correcting for detected scatter is through an iterative deconvolution process known as scatter kernel superposition (SKS). While the SKS approach is efficient, clinically significant errors on the order 2-4% (20-40 HU) still remain. We have previously shown that the kernel method can be improved by perturbing the kernel parameters based on reference data provided by limited Monte Carlo simulations of a first-pass reconstruction. In this work, we replace the Monte Carlo modeling with a deterministic Boltzmann solver (AcurosCTS) to generate the reference scatter data in a dramatically reduced time. In addition, the algorithm is improved so that instead of adjusting kernel parameters, we directly perturb the SKS scatter estimates. Studies were conducted on simulated data and on a large pelvis phantom scanned on a tabletop system. The new method reduced average reconstruction errors (relative to a reference scan) from 2.5% to 1.8%, and significantly improved visualization of low contrast objects. In total, 24 projections were simulated with an AcurosCTS execution time of 22 sec/projection using an 8-core computer. We have ported AcurosCTS to the GPU, and current run-times are approximately 4 sec/projection using two GPU's running in parallel.

Monte Carlo simulation of proton track structure in biological matter

DOE PAGES

Quinto, Michele A.; Monti, Juan M.; Weck, Philippe F.; ...

2017-05-25

Here, understanding the radiation-induced effects at the cellular and subcellular levels remains crucial for predicting the evolution of irradiated biological matter. In this context, Monte Carlo track-structure simulations have rapidly emerged among the most suitable and powerful tools. However, most existing Monte Carlo track-structure codes rely heavily on the use of semi-empirical cross sections as well as water as a surrogate for biological matter. In the current work, we report on the up-to-date version of our homemade Monte Carlo code TILDA-V – devoted to the modeling of the slowing-down of 10 keV–100 MeV protons in both water and DNA –more » where the main collisional processes are described by means of an extensive set of ab initio differential and total cross sections.« less

Full 3D visualization tool-kit for Monte Carlo and deterministic transport codes

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

Frambati, S.; Frignani, M.

2012-07-01

We propose a package of tools capable of translating the geometric inputs and outputs of many Monte Carlo and deterministic radiation transport codes into open source file formats. These tools are aimed at bridging the gap between trusted, widely-used radiation analysis codes and very powerful, more recent and commonly used visualization software, thus supporting the design process and helping with shielding optimization. Three main lines of development were followed: mesh-based analysis of Monte Carlo codes, mesh-based analysis of deterministic codes and Monte Carlo surface meshing. The developed kit is considered a powerful and cost-effective tool in the computer-aided design formore » radiation transport code users of the nuclear world, and in particular in the fields of core design and radiation analysis. (authors)« less

Monte Carlo simulation of proton track structure in biological matter

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

Quinto, Michele A.; Monti, Juan M.; Weck, Philippe F.

Here, understanding the radiation-induced effects at the cellular and subcellular levels remains crucial for predicting the evolution of irradiated biological matter. In this context, Monte Carlo track-structure simulations have rapidly emerged among the most suitable and powerful tools. However, most existing Monte Carlo track-structure codes rely heavily on the use of semi-empirical cross sections as well as water as a surrogate for biological matter. In the current work, we report on the up-to-date version of our homemade Monte Carlo code TILDA-V – devoted to the modeling of the slowing-down of 10 keV–100 MeV protons in both water and DNA –more » where the main collisional processes are described by means of an extensive set of ab initio differential and total cross sections.« less

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media

NASA Astrophysics Data System (ADS)

Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique

2017-08-01

NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.

Optimization of the Monte Carlo code for modeling of photon migration in tissue.

PubMed

Zołek, Norbert S; Liebert, Adam; Maniewski, Roman

2006-10-01

The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.

Results for Phase I of the IAEA Coordinated Research Program on HTGR Uncertainties

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

Strydom, Gerhard; Bostelmann, Friederike; Yoon, Su Jong

2015-01-01

The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied. High Temperature Gas-cooled Reactors (HTGR) has its own peculiarities, coated particle design, large graphite quantities, different materials and high temperatures that also require other simulationmore » requirements. The IAEA has therefore launched a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modeling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the HTR-PM (INET, China). This report summarizes the contributions of the HTGR Methods Simulation group at Idaho National Laboratory (INL) up to this point of the CRP. The activities at INL have been focused so far on creating the problem specifications for the prismatic design, as well as providing reference solutions for the exercises defined for Phase I. An overview is provided of the HTGR UAM objectives and scope, and the detailed specifications for Exercises I-1, I-2, I-3 and I-4 are also included here for completeness. The main focus of the report is the compilation and discussion of reference results for Phase I (i.e. for input parameters at their nominal or best-estimate values), which is defined as the first step of the uncertainty quantification process. These reference results can be used by other CRP participants for comparison with other codes or their own reference results. The status on the Monte Carlo modeling of the experimental VHTRC facility is also discussed. Reference results were obtained for the neutronics stand-alone cases (Ex. I-1 and Ex. I-2) using the (relatively new) Monte Carlo code Serpent, and comparisons were performed with the more established Monte Carlo codes MCNP and KENO-VI. For the thermal-fluids stand-alone cases (Ex. I-3 and I-4) the commercial CFD code CFX was utilized to obtain reference results that can be compared with lower fidelity tools.« less

Implementing the Second-Order Fermi Process in a Kinetic Monte-Carlo Simulation

NASA Technical Reports Server (NTRS)

Summerlin, Errol J.

2010-01-01

Radio JOVE is an education and outreach project intended to give students and other interested individuals hands-on experience in learning radio astronomy. They can do this through building a radio telescope from a relatively inexpensive kit that includes the parts for a receiver and an antenna as well as software for a computer chart recorder emulator (Radio Skypipe) and other reference materials

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE PAGES

Hoffmann, Max J.; Bligaard, Thomas

2018-01-22

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

A Monte Carlo method for the simulation of coagulation and nucleation based on weighted particles and the concepts of stochastic resolution and merging

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

Kotalczyk, G., E-mail: Gregor.Kotalczyk@uni-due.de; Kruis, F.E.

Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named ‘stochastic resolution’ in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope ofmore » a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named ‘random removal’ in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose.« less

A path integral methodology for obtaining thermodynamic properties of nonadiabatic systems using Gaussian mixture distributions

NASA Astrophysics Data System (ADS)

Raymond, Neil; Iouchtchenko, Dmitri; Roy, Pierre-Nicholas; Nooijen, Marcel

2018-05-01

We introduce a new path integral Monte Carlo method for investigating nonadiabatic systems in thermal equilibrium and demonstrate an approach to reducing stochastic error. We derive a general path integral expression for the partition function in a product basis of continuous nuclear and discrete electronic degrees of freedom without the use of any mapping schemes. We separate our Hamiltonian into a harmonic portion and a coupling portion; the partition function can then be calculated as the product of a Monte Carlo estimator (of the coupling contribution to the partition function) and a normalization factor (that is evaluated analytically). A Gaussian mixture model is used to evaluate the Monte Carlo estimator in a computationally efficient manner. Using two model systems, we demonstrate our approach to reduce the stochastic error associated with the Monte Carlo estimator. We show that the selection of the harmonic oscillators comprising the sampling distribution directly affects the efficiency of the method. Our results demonstrate that our path integral Monte Carlo method's deviation from exact Trotter calculations is dominated by the choice of the sampling distribution. By improving the sampling distribution, we can drastically reduce the stochastic error leading to lower computational cost.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

DOE PAGES

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai; ...

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

Monte Carlo: in the beginning and some great expectations

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

Metropolis, N.

1985-01-01

The central theme will be on the historical setting and origins of the Monte Carlo Method. The scene was post-war Los Alamos Scientific Laboratory. There was an inevitability about the Monte Carlo Event: the ENIAC had recently enjoyed its meteoric rise (on a classified Los Alamos problem); Stan Ulam had returned to Los Alamos; John von Neumann was a frequent visitor. Techniques, algorithms, and applications developed rapidly at Los Alamos. Soon, the fascination of the Method reached wider horizons. The first paper was submitted for publication in the spring of 1949. In the summer of 1949, the first open conferencemore » was held at the University of California at Los Angeles. Of some interst perhaps is an account of Fermi's earlier, independent application in neutron moderation studies while at the University of Rome. The quantum leap expected with the advent of massively parallel processors will provide stimuli for very ambitious applications of the Monte Carlo Method in disciplines ranging from field theories to cosmology, including more realistic models in the neurosciences. A structure of multi-instruction sets for parallel processing is ideally suited for the Monte Carlo approach. One may even hope for a modest hardening of the soft sciences.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

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

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

PubMed Central

Lee, Anthony; Yau, Christopher; Giles, Michael B.; Doucet, Arnaud; Holmes, Christopher C.

2011-01-01

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers and can be thought of as prototypes of the next generation of many-core processors. For certain classes of population-based Monte Carlo algorithms they offer massively parallel simulation, with the added advantage over conventional distributed multi-core processors that they are cheap, easily accessible, easy to maintain, easy to code, dedicated local devices with low power consumption. On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we nd speedups from 35 to 500 fold over conventional single-threaded computer code. Our findings suggest that GPUs have the potential to facilitate the growth of statistical modelling into complex data rich domains through the availability of cheap and accessible many-core computation. We believe the speedup we observe should motivate wider use of parallelizable simulation methods and greater methodological attention to their design. PMID:22003276

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

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

Hoffmann, Max J.; Bligaard, Thomas

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo.

PubMed

McDaniel, T; D'Azevedo, E F; Li, Y W; Wong, K; Kent, P R C

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

NASA Astrophysics Data System (ADS)

McDaniel, T.; D'Azevedo, E. F.; Li, Y. W.; Wong, K.; Kent, P. R. C.

2017-11-01

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Criticality Calculations with MCNP6 - Practical Lectures

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

Brown, Forrest B.; Rising, Michael Evan; Alwin, Jennifer Louise

2016-11-29

These slides are used to teach MCNP (Monte Carlo N-Particle) usage to nuclear criticality safety analysts. The following are the lecture topics: course information, introduction, MCNP basics, criticality calculations, advanced geometry, tallies, adjoint-weighted tallies and sensitivities, physics and nuclear data, parameter studies, NCS validation I, NCS validation II, NCS validation III, case study 1 - solution tanks, case study 2 - fuel vault, case study 3 - B&W core, case study 4 - simple TRIGA, case study 5 - fissile mat. vault, criticality accident alarm systems. After completion of this course, you should be able to: Develop an input modelmore » for MCNP; Describe how cross section data impact Monte Carlo and deterministic codes; Describe the importance of validation of computer codes and how it is accomplished; Describe the methodology supporting Monte Carlo codes and deterministic codes; Describe pitfalls of Monte Carlo calculations; Discuss the strengths and weaknesses of Monte Carlo and Discrete Ordinants codes; The diffusion theory model is not strictly valid for treating fissile systems in which neutron absorption, voids, and/or material boundaries are present. In the context of these limitations, identify a fissile system for which a diffusion theory solution would be adequate.« less

Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

PubMed

Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend

2011-10-11

In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.

Mosaicing of airborne LiDAR bathymetry strips based on Monte Carlo matching

NASA Astrophysics Data System (ADS)

Yang, Fanlin; Su, Dianpeng; Zhang, Kai; Ma, Yue; Wang, Mingwei; Yang, Anxiu

2017-09-01

This study proposes a new methodology for mosaicing airborne light detection and ranging (LiDAR) bathymetry (ALB) data based on Monte Carlo matching. Various errors occur in ALB data due to imperfect system integration and other interference factors. To account for these errors, a Monte Carlo matching algorithm based on a nonlinear least-squares adjustment model is proposed. First, the raw data of strip overlap areas were filtered according to their relative drift of depths. Second, a Monte Carlo model and nonlinear least-squares adjustment model were combined to obtain seven transformation parameters. Then, the multibeam bathymetric data were used to correct the initial strip during strip mosaicing. Finally, to evaluate the proposed method, the experimental results were compared with the results of the Iterative Closest Points (ICP) and three-dimensional Normal Distributions Transform (3D-NDT) algorithms. The results demonstrate that the algorithm proposed in this study is more robust and effective. When the quality of the raw data is poor, the Monte Carlo matching algorithm can still achieve centimeter-level accuracy for overlapping areas, which meets the accuracy of bathymetry required by IHO Standards for Hydrographic Surveys Special Publication No.44.

Renyi entanglement entropy of interacting fermions calculated using the continuous-time quantum Monte Carlo method.

PubMed

Wang, Lei; Troyer, Matthias

2014-09-12

We present a new algorithm for calculating the Renyi entanglement entropy of interacting fermions using the continuous-time quantum Monte Carlo method. The algorithm only samples the interaction correction of the entanglement entropy, which by design ensures the efficient calculation of weakly interacting systems. Combined with Monte Carlo reweighting, the algorithm also performs well for systems with strong interactions. We demonstrate the potential of this method by studying the quantum entanglement signatures of the charge-density-wave transition of interacting fermions on a square lattice.

Monte Carlo Simulation of a Segmented Detector for Low-Energy Electron Antineutrinos

NASA Astrophysics Data System (ADS)

Qomi, H. Akhtari; Safari, M. J.; Davani, F. Abbasi

2017-11-01

Detection of low-energy electron antineutrinos is of importance for several purposes, such as ex-vessel reactor monitoring, neutrino oscillation studies, etc. The inverse beta decay (IBD) is the interaction that is responsible for detection mechanism in (organic) plastic scintillation detectors. Here, a detailed study will be presented dealing with the radiation and optical transport simulation of a typical segmented antineutrino detector withMonte Carlo method using MCNPX and FLUKA codes. This study shows different aspects of the detector, benefiting from inherent capabilities of the Monte Carlo simulation codes.

Proton Upset Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.

2009-01-01

The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.

SABRINA - An interactive geometry modeler for MCNP (Monte Carlo Neutron Photon)

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

West, J.T.; Murphy, J.

SABRINA is an interactive three-dimensional geometry modeler developed to produce complicated models for the Los Alamos Monte Carlo Neutron Photon program MCNP. SABRINA produces line drawings and color-shaded drawings for a wide variety of interactive graphics terminals. It is used as a geometry preprocessor in model development and as a Monte Carlo particle-track postprocessor in the visualization of complicated particle transport problem. SABRINA is written in Fortran 77 and is based on the Los Alamos Common Graphics System, CGS. 5 refs., 2 figs.

Surface entropy of liquids via a direct Monte Carlo approach - Application to liquid Si

NASA Technical Reports Server (NTRS)

Wang, Z. Q.; Stroud, D.

1990-01-01

Two methods are presented for a direct Monte Carlo evaluation of the surface entropy S(s) of a liquid interacting by specified, volume-independent potentials. The first method is based on an application of the approach of Ferrenberg and Swendsen (1988, 1989) to Monte Carlo simulations at two different temperatures; it gives much more reliable results for S(s) in liquid Si than previous calculations based on numerical differentiation. The second method expresses the surface entropy directly as a canonical average at fixed temperature.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Tally and geometry definition influence on the computing time in radiotherapy treatment planning with MCNP Monte Carlo code.

PubMed

Juste, B; Miro, R; Gallardo, S; Santos, A; Verdu, G

2006-01-01

The present work has simulated the photon and electron transport in a Theratron 780 (MDS Nordion) (60)Co radiotherapy unit, using the Monte Carlo transport code, MCNP (Monte Carlo N-Particle), version 5. In order to become computationally more efficient in view of taking part in the practical field of radiotherapy treatment planning, this work is focused mainly on the analysis of dose results and on the required computing time of different tallies applied in the model to speed up calculations.

Window for Optimal Frequency Operation and Reliability of 3DEG and 2DEG Channels for Oxide Microwave MESFETs and HFETs

DTIC Science & Technology

2016-04-01

noise, and energy relaxation for doped zinc-oxide and structured ZnO transistor materials with a 2-D electron gas (2DEG) channel subjected to a strong...function on the time delay. Closed symbols represent the Monte Carlo data with hot-phonon effect at different electron gas density: 1•1017 cm-3...Monte Carlo simulation is performed for electron gas density of 1•1018 cm-3. Figure 18. Monte Carlo simulation of density-dependent hot-electron energy

Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

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

Bates, Cameron Russell; Mckigney, Edward Allen

The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

Proceedings of the Nuclear Criticality Technology Safety Workshop

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

Rene G. Sanchez

1998-04-01

This document contains summaries of most of the papers presented at the 1995 Nuclear Criticality Technology Safety Project (NCTSP) meeting, which was held May 16 and 17 at San Diego, Ca. The meeting was broken up into seven sessions, which covered the following topics: (1) Criticality Safety of Project Sapphire; (2) Relevant Experiments For Criticality Safety; (3) Interactions with the Former Soviet Union; (4) Misapplications and Limitations of Monte Carlo Methods Directed Toward Criticality Safety Analyses; (5) Monte Carlo Vulnerabilities of Execution and Interpretation; (6) Monte Carlo Vulnerabilities of Representation; and (7) Benchmark Comparisons.

Invited review article: physics and Monte Carlo techniques as relevant to cryogenic, phonon, and ionization readout of Cryogenic Dark Matter Search radiation detectors.

PubMed

Leman, Steven W

2012-09-01

This review discusses detector physics and Monte Carlo techniques for cryogenic, radiation detectors that utilize combined phonon and ionization readout. A general review of cryogenic phonon and charge transport is provided along with specific details of the Cryogenic Dark Matter Search detector instrumentation. In particular, this review covers quasidiffusive phonon transport, which includes phonon focusing, anharmonic decay, and isotope scattering. The interaction of phonons in the detector surface is discussed along with the downconversion of phonons in superconducting films. The charge transport physics include a mass tensor which results from the crystal band structure and is modeled with a Herring-Vogt transformation. Charge scattering processes involve the creation of Neganov-Luke phonons. Transition-edge-sensor (TES) simulations include a full electric circuit description and all thermal processes including Joule heating, cooling to the substrate, and thermal diffusion within the TES, the latter of which is necessary to model normal-superconducting phase separation. Relevant numerical constants are provided for these physical processes in germanium, silicon, aluminum, and tungsten. Random number sampling methods including inverse cumulative distribution function (CDF) and rejection techniques are reviewed. To improve the efficiency of charge transport modeling, an additional second order inverse CDF method is developed here along with an efficient barycentric coordinate sampling method of electric fields. Results are provided in a manner that is convenient for use in Monte Carlo and references are provided for validation of these models.

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

SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

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

Chow, J

Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of computemore » node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.« less

SU-E-T-481: Dosimetric Effects of Tissue Heterogeneity in Proton Therapy: Monte Carlo Simulation and Experimental Study Using Animal Tissue Phantoms.

PubMed

Liu, Y; Zheng, Y

2012-06-01

Accurate determination of proton dosimetric effect for tissue heterogeneity is critical in proton therapy. Proton beams have finite range and consequently tissue heterogeneity plays a more critical role in proton therapy. The purpose of this study is to investigate the tissue heterogeneity effect in proton dosimetry based on anatomical-based Monte Carlo simulation using animal tissues. Animal tissues including a pig head and beef bulk were used in this study. Both pig head and beef were scanned using a GE CT scanner with 1.25 mm slice thickness. A treatment plan was created, using the CMS XiO treatment planning system (TPS) with a single proton spread-out-Bragg-peak beam (SOBP). Radiochromic films were placed at the distal falloff region. Image guidance was used to align the phantom before proton beams were delivered according to the treatment plan. The same two CT sets were converted to Monte Carlo simulation model. The Monte Carlo simulated dose calculations with/without tissue omposition were compared to TPS calculations and measurements. Based on the preliminary comparison, at the center of SOBP plane, the Monte Carlo simulation dose without tissue composition agreed generally well with TPS calculation. In the distal falloff region, the dose difference was large, and about 2 mm isodose line shift was observed with the consideration of tissue composition. The detailed comparison of dose distributions between Monte Carlo simulation, TPS calculations and measurements is underway. Accurate proton dose calculations are challenging in proton treatment planning for heterogeneous tissues. Tissue heterogeneity and tissue composition may lead to isodose line shifts up to a few millimeters in the distal falloff region. By simulating detailed particle transport and energy deposition, Monte Carlo simulations provide a verification method in proton dose calculation where inhomogeneous tissues are present. © 2012 American Association of Physicists in Medicine.

Monte Carlo verification of radiotherapy treatments with CloudMC.

PubMed

Miras, Hector; Jiménez, Rubén; Perales, Álvaro; Terrón, José Antonio; Bertolet, Alejandro; Ortiz, Antonio; Macías, José

2018-06-27

A new implementation has been made on CloudMC, a cloud-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way. A description of the architecture of the application and the new developments implemented is presented together with the results of the tests carried out to validate its performance. CloudMC has been developed over Microsoft Azure cloud. It is based on a map/reduce implementation for Monte Carlo calculations distribution over a dynamic cluster of virtual machines in order to reduce calculation time. CloudMC has been updated with new methods to read and process the information related to radiotherapy treatment verification: CT image set, treatment plan, structures and dose distribution files in DICOM format. Some tests have been designed in order to determine, for the different tasks, the most suitable type of virtual machines from those available in Azure. Finally, the performance of Monte Carlo verification in CloudMC is studied through three real cases that involve different treatment techniques, linac models and Monte Carlo codes. Considering computational and economic factors, D1_v2 and G1 virtual machines were selected as the default type for the Worker Roles and the Reducer Role respectively. Calculation times up to 33 min and costs of 16 € were achieved for the verification cases presented when a statistical uncertainty below 2% (2σ) was required. The costs were reduced to 3-6 € when uncertainty requirements are relaxed to 4%. Advantages like high computational power, scalability, easy access and pay-per-usage model, make Monte Carlo cloud-based solutions, like the one presented in this work, an important step forward to solve the long-lived problem of truly introducing the Monte Carlo algorithms in the daily routine of the radiotherapy planning process.

Design and Shielding of Radiotherapy Treatment Facilities; IPEM Report 75, 2nd Edition

NASA Astrophysics Data System (ADS)

Horton, Patrick; Eaton, David

2017-07-01

Design and Shielding of Radiotherapy Treatment Facilities provides readers with a single point of reference for protection advice to the construction and modification of radiotherapy facilities. The book assembles a faculty of national and international experts on all modalities including megavoltage and kilovoltage photons, brachytherapy and high-energy particles, and on conventional and Monte Carlo shielding calculations. This book is a comprehensive reference for qualified experts and radiation-shielding designers in radiation physics and also useful to anyone involved in the design of radiotherapy facilities.

Simulation of Nuclear Reactor Kinetics by the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gomin, E. A.; Davidenko, V. D.; Zinchenko, A. S.; Kharchenko, I. K.

2017-12-01

The KIR computer code intended for calculations of nuclear reactor kinetics using the Monte Carlo method is described. The algorithm implemented in the code is described in detail. Some results of test calculations are given.

Off-diagonal expansion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Light propagation along the pericardium meridian at human wrist as evidenced by the optical experiment and Monte Carlo method.

PubMed

Jiang, Yi-fan; Chen, Chang-shui; Liu, Xiao-mei; Liu, Rong-ting; Liu, Song-hao

2015-04-01

To explore the characteristics of light propagation along the Pericardium Meridian and its surrounding areas at human wrist by using optical experiment and Monte Carlo method. An experiment was carried out to obtain the distribution of diffuse light on Pericardium Meridian line and its surrounding areas at the wrist, and then a simplified model based on the anatomical structure was proposed to simulate the light transportation within the same area by using Monte Carlo method. The experimental results showed strong accordance with the Monte Carlo simulation that the light propagation along the Pericardium Meridian had an advantage over its surrounding areas at the wrist. The advantage of light transport along Pericardium Merdian line was related to components and structure of tissue, also the anatomical structure of the area that the Pericardium Meridian line runs.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography.

PubMed

Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2015-01-01

Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.

Event-chain Monte Carlo algorithms for three- and many-particle interactions

NASA Astrophysics Data System (ADS)

Harland, J.; Michel, M.; Kampmann, T. A.; Kierfeld, J.

2017-02-01

We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

Tool for Rapid Analysis of Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.

2011-01-01

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Degroh, Kim K.; Sechkar, Edward A.

1992-01-01

Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) will assist in understanding the mechanisms involved, and will lead to improved reliability in predicting in-space durability of materials based on ground laboratory testing. A computational simulation of atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of assumed mechanistic behavior of atomic oxygen and results of both ground laboratory and LDEF data, a predictive Monte Carlo model was developed which simulates the oxidation processes that occur on polymers with applied protective coatings that have defects. The use of high atomic oxygen fluence-directed ram LDEF results has enabled mechanistic implications to be made by adjusting Monte Carlo modeling assumptions to match observed results based on scanning electron microscopy. Modeling assumptions, implications, and predictions are presented, along with comparison of observed ground laboratory and LDEF results.

Monte Carlo-based Reconstruction in Water Cherenkov Detectors using Chroma

NASA Astrophysics Data System (ADS)

Seibert, Stanley; Latorre, Anthony

2012-03-01

We demonstrate the feasibility of event reconstruction---including position, direction, energy and particle identification---in water Cherenkov detectors with a purely Monte Carlo-based method. Using a fast optical Monte Carlo package we have written, called Chroma, in combination with several variance reduction techniques, we can estimate the value of a likelihood function for an arbitrary event hypothesis. The likelihood can then be maximized over the parameter space of interest using a form of gradient descent designed for stochastic functions. Although slower than more traditional reconstruction algorithms, this completely Monte Carlo-based technique is universal and can be applied to a detector of any size or shape, which is a major advantage during the design phase of an experiment. As a specific example, we focus on reconstruction results from a simulation of the 200 kiloton water Cherenkov far detector option for LBNE.

Markov chain Monte Carlo techniques applied to parton distribution functions determination: Proof of concept

NASA Astrophysics Data System (ADS)

Gbedo, Yémalin Gabin; Mangin-Brinet, Mariane

2017-07-01

We present a new procedure to determine parton distribution functions (PDFs), based on Markov chain Monte Carlo (MCMC) methods. The aim of this paper is to show that we can replace the standard χ2 minimization by procedures grounded on statistical methods, and on Bayesian inference in particular, thus offering additional insight into the rich field of PDFs determination. After a basic introduction to these techniques, we introduce the algorithm we have chosen to implement—namely Hybrid (or Hamiltonian) Monte Carlo. This algorithm, initially developed for Lattice QCD, turns out to be very interesting when applied to PDFs determination by global analyses; we show that it allows us to circumvent the difficulties due to the high dimensionality of the problem, in particular concerning the acceptance. A first feasibility study is performed and presented, which indicates that Markov chain Monte Carlo can successfully be applied to the extraction of PDFs and of their uncertainties.

Geometry and Dynamics for Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Barp, Alessandro; Briol, François-Xavier; Kennedy, Anthony D.; Girolami, Mark

2018-03-01

Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the intuitions and knowledge of users of the methodology and our deep understanding of these theoretical foundations. The aim of this review is to provide a comprehensive introduction to the geometric tools used in Hamiltonian Monte Carlo at a level accessible to statisticians, machine learners and other users of the methodology with only a basic understanding of Monte Carlo methods. This will be complemented with some discussion of the most recent advances in the field which we believe will become increasingly relevant to applied scientists.

Monte Carlo tests of the ELIPGRID-PC algorithm

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

Davidson, J.R.

1995-04-01

The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM{reg_sign} PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within {plus_minus}0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangularmore » sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error.« less

Off-diagonal expansion quantum Monte Carlo.

PubMed

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography*

PubMed Central

Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2015-01-01

Objective Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography. PMID:26811553

Two proposed convergence criteria for Monte Carlo solutions

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

Forster, R.A.; Pederson, S.P.; Booth, T.E.

1992-01-01

The central limit theorem (CLT) can be applied to a Monte Carlo solution if two requirements are satisfied: (1) The random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these two conditions are satisfied, a confidence interval (CI) based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the Monte Carlo tally being used. The Monte Carlo practitioner has a limited number of marginal methods to assess the fulfillment of the second requirement, such asmore » statistical error reduction proportional to 1/[radical]N with error magnitude guidelines. Two proposed methods are discussed in this paper to assist in deciding if N is large enough: estimating the relative variance of the variance (VOV) and examining the empirical history score probability density function (pdf).« less

Navigation Strategies for Primitive Solar System Body Rendezvous and Proximity Operations

NASA Technical Reports Server (NTRS)

Getzandanner, Kenneth M.

2011-01-01

A wealth of scientific knowledge regarding the composition and evolution of the solar system can be gained through reconnaissance missions to primitive solar system bodies. This paper presents analysis of a baseline navigation strategy designed to address the unique challenges of primitive body navigation. Linear covariance and Monte Carlo error analysis was performed on a baseline navigation strategy using simulated data from a· design reference mission (DRM). The objective of the DRM is to approach, rendezvous, and maintain a stable orbit about the near-Earth asteroid 4660 Nereus. The outlined navigation strategy and resulting analyses, however, are not necessarily limited to this specific target asteroid as they may he applicable to a diverse range of mission scenarios. The baseline navigation strategy included simulated data from Deep Space Network (DSN) radiometric tracking and optical image processing (OpNav). Results from the linear covariance and Monte Carlo analyses suggest the DRM navigation strategy is sufficient to approach and perform proximity operations in the vicinity of the target asteroid with meter-level accuracy.

Monte Carlo shock-like solutions to the Boltzmann equation with collective scattering

NASA Technical Reports Server (NTRS)

Ellison, D. C.; Eichler, D.

1984-01-01

The results of Monte Carlo simulations of steady state shocks generated by a collision operator that isotropizes the particles by means of elastic scattering in some locally defined frame of reference are presented. The simulations include both the back reaction of accelerated particles on the inflowing plasma and the free escape of high-energy particles from finite shocks. Energetic particles are found to be naturally extracted out of the background plasma by the shock process with an efficiency in good quantitative agreement with an earlier analytic approximation (Eichler, 1983 and 1984) and observations (Gosling et al., 1981) of the entire particle spectrum at a quasi-parallel interplanetary shock. The analytic approximation, which allows a self-consistent determination of the effective adiabatic index of the shocked gas, is used to calculate the overall acceleration efficiency and particle spectrum for cases where ultrarelativistic energies are obtained. It is found that shocks of the strength necessary to produce galactic cosmic rays put approximately 15 percent of the shock energy into relativistic particles.

Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods

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

Godfrey, Andrew T; Gehin, Jess C; Bekar, Kursat B

2014-01-01

The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highlymore » detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.« less

Application of hard sphere perturbation theory for thermodynamics of model liquid metals

NASA Astrophysics Data System (ADS)

Mon, K. K.

2001-06-01

Hard sphere perturbation theory (HSPT) has contributed toward the fundamental understanding of dense fluids for over 30 years. In recent decades, other techniques have been more popular. In this paper, we argue for the revival of hard sphere perturbation theory for the study of thermodynamics of dense liquid in general, and in liquid metal in particular. The weakness of HSPT is now well understood, and can be easily overcome by using a simple convenient Monte Carlo method to calculate the intrinsic error of HSPT free energy density. To demonstrate this approach, we consider models of liquid aluminum and sodium. We obtain the intrinsic error of HSPT with the Monte Carlo method. HSPT is shown to provide a lower free energy upper bound than one-component plasma (OCP) for alkali metals and polyvalent metals. We are thus able to provide insight into the long standing observation that a OCP is a better reference system than a HS for alkali metals.

Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles

PubMed Central

Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

2016-01-01

This article addresses the in silico–in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy. PMID:27920524

Properties of a soft-core model of methanol: An integral equation theory and computer simulation study

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

Huš, Matej; Urbic, Tomaz, E-mail: tomaz.urbic@fkkt.uni-lj.si; Munaò, Gianmarco

Thermodynamic and structural properties of a coarse-grained model of methanol are examined by Monte Carlo simulations and reference interaction site model (RISM) integral equation theory. Methanol particles are described as dimers formed from an apolar Lennard-Jones sphere, mimicking the methyl group, and a sphere with a core-softened potential as the hydroxyl group. Different closure approximations of the RISM theory are compared and discussed. The liquid structure of methanol is investigated by calculating site-site radial distribution functions and static structure factors for a wide range of temperatures and densities. Results obtained show a good agreement between RISM and Monte Carlo simulations.more » The phase behavior of methanol is investigated by employing different thermodynamic routes for the calculation of the RISM free energy, drawing gas-liquid coexistence curves that match the simulation data. Preliminary indications for a putative second critical point between two different liquid phases of methanol are also discussed.« less

Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles.

PubMed

Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

This article addresses the in silico-in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy.

FLUKA Monte Carlo simulations and benchmark measurements for the LHC beam loss monitors

NASA Astrophysics Data System (ADS)

Sarchiapone, L.; Brugger, M.; Dehning, B.; Kramer, D.; Stockner, M.; Vlachoudis, V.

2007-10-01

One of the crucial elements in terms of machine protection for CERN's Large Hadron Collider (LHC) is its beam loss monitoring (BLM) system. On-line loss measurements must prevent the superconducting magnets from quenching and protect the machine components from damages due to unforeseen critical beam losses. In order to ensure the BLM's design quality, in the final design phase of the LHC detailed FLUKA Monte Carlo simulations were performed for the betatron collimation insertion. In addition, benchmark measurements were carried out with LHC type BLMs installed at the CERN-EU high-energy Reference Field facility (CERF). This paper presents results of FLUKA calculations performed for BLMs installed in the collimation region, compares the results of the CERF measurement with FLUKA simulations and evaluates related uncertainties. This, together with the fact that the CERF source spectra at the respective BLM locations are comparable with those at the LHC, allows assessing the sensitivity of the performed LHC design studies.

Lunar Outpost Life Support Architecture Study Based on a High-Mobility Exploration Scenario

NASA Technical Reports Server (NTRS)

Lange, Kevin E.; Anderson, Molly S.

2010-01-01

This paper presents results of a life support architecture study based on a 2009 NASA lunar surface exploration scenario known as Scenario 12. The study focuses on the assembly complete outpost configuration and includes pressurized rovers as part of a distributed outpost architecture in both stand-alone and integrated configurations. A range of life support architectures are examined reflecting different levels of closure and distributed functionality. Monte Carlo simulations are used to assess the sensitivity of results to volatile high-impact mission variables, including the quantity of residual Lander oxygen and hydrogen propellants available for scavenging, the fraction of crew time away from the outpost on excursions, total extravehicular activity hours, and habitat leakage. Surpluses or deficits of water and oxygen are reported for each architecture, along with fixed and 10-year total equivalent system mass estimates relative to a reference case. System robustness is discussed in terms of the probability of no water or oxygen resupply as determined from the Monte Carlo simulations.

Apparently abnormal Wechsler Memory Scale index score patterns in the normal population.

PubMed

Carrasco, Roman Marcus; Grups, Josefine; Evans, Brittney; Simco, Edward; Mittenberg, Wiley

2015-01-01

Interpretation of the Wechsler Memory Scale-Fourth Edition may involve examination of multiple memory index score contrasts and similar comparisons with Wechsler Adult Intelligence Scale-Fourth Edition ability indexes. Standardization sample data suggest that 15-point differences between any specific pair of index scores are relatively uncommon in normal individuals, but these base rates refer to a comparison between a single pair of indexes rather than multiple simultaneous comparisons among indexes. This study provides normative data for the occurrence of multiple index score differences calculated by using Monte Carlo simulations and validated against standardization data. Differences of 15 points between any two memory indexes or between memory and ability indexes occurred in 60% and 48% of the normative sample, respectively. Wechsler index score discrepancies are normally common and therefore not clinically meaningful when numerous such comparisons are made. Explicit prior interpretive hypotheses are necessary to reduce the number of index comparisons and associated false-positive conclusions. Monte Carlo simulation accurately predicts these false-positive rates.

Hybrid Monte Carlo-Diffusion Method For Light Propagation in Tissue With a Low-Scattering Region

NASA Astrophysics Data System (ADS)

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Hybrid Monte Carlo-diffusion method for light propagation in tissue with a low-scattering region.

PubMed

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Application of dynamic Monte Carlo technique in proton beam radiotherapy using Geant4 simulation toolkit

NASA Astrophysics Data System (ADS)

Guan, Fada

Monte Carlo method has been successfully applied in simulating the particles transport problems. Most of the Monte Carlo simulation tools are static and they can only be used to perform the static simulations for the problems with fixed physics and geometry settings. Proton therapy is a dynamic treatment technique in the clinical application. In this research, we developed a method to perform the dynamic Monte Carlo simulation of proton therapy using Geant4 simulation toolkit. A passive-scattering treatment nozzle equipped with a rotating range modulation wheel was modeled in this research. One important application of the Monte Carlo simulation is to predict the spatial dose distribution in the target geometry. For simplification, a mathematical model of a human body is usually used as the target, but only the average dose over the whole organ or tissue can be obtained rather than the accurate spatial dose distribution. In this research, we developed a method using MATLAB to convert the medical images of a patient from CT scanning into the patient voxel geometry. Hence, if the patient voxel geometry is used as the target in the Monte Carlo simulation, the accurate spatial dose distribution in the target can be obtained. A data analysis tool---root was used to score the simulation results during a Geant4 simulation and to analyze the data and plot results after simulation. Finally, we successfully obtained the accurate spatial dose distribution in part of a human body after treating a patient with prostate cancer using proton therapy.

Modeling of an industrial environment: external dose calculations based on Monte Carlo simulations of photon transport.

PubMed

Kis, Zoltán; Eged, Katalin; Voigt, Gabriele; Meckbach, Reinhard; Müller, Heinz

2004-02-01

External gamma exposures from radionuclides deposited on surfaces usually result in the major contribution to the total dose to the public living in urban-industrial environments. The aim of the paper is to give an example for a calculation of the collective and averted collective dose due to the contamination and decontamination of deposition surfaces in a complex environment based on the results of Monte Carlo simulations. The shielding effects of the structures in complex and realistic industrial environments (where productive and/or commercial activity is carried out) were computed by the use of Monte Carlo method. Several types of deposition areas (walls, roofs, windows, streets, lawn) were considered. Moreover, this paper gives a summary about the time dependence of the source strengths relative to a reference surface and a short overview about the mechanical and chemical intervention techniques which can be applied in this area. An exposure scenario was designed based on a survey of average German and Hungarian supermarkets. In the first part of the paper the air kermas per photon per unit area due to each specific deposition area contaminated by 137Cs were determined at several arbitrary locations in the whole environment relative to a reference value of 8.39 x 10(-4) pGy per gamma m(-2). The calculations provide the possibility to assess the whole contribution of a specific deposition area to the collective dose, separately. According to the current results, the roof and the paved area contribute the most part (approximately 92%) to the total dose in the first year taking into account the relative contamination of the deposition areas. When integrating over 10 or 50 y, these two surfaces remain the most important contributors as well but the ratio will increasingly be shifted in favor of the roof. The decontamination of the roof and the paved area results in about 80-90% of the total averted collective dose in each calculated time period (1, 10, 50 y).

GE781: a Monte Carlo package for fixed target experiments

NASA Astrophysics Data System (ADS)

Davidenko, G.; Funk, M. A.; Kim, V.; Kuropatkin, N.; Kurshetsov, V.; Molchanov, V.; Rud, S.; Stutte, L.; Verebryusov, V.; Zukanovich Funchal, R.

The Monte Carlo package for the fixed target experiment B781 at Fermilab, a third generation charmed baryon experiment, is described. This package is based on GEANT 3.21, ADAMO database and DAFT input/output routines.

Improved Monte Carlo Renormalization Group Method

DOE R&D Accomplishments Database

Gupta, R.; Wilson, K. G.; Umrigar, C.

1985-01-01

An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.

Monte Carlo calculations of k{sub Q}, the beam quality conversion factor

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

Muir, B. R.; Rogers, D. W. O.

2010-11-15

Purpose: To use EGSnrc Monte Carlo simulations to directly calculate beam quality conversion factors, k{sub Q}, for 32 cylindrical ionization chambers over a range of beam qualities and to quantify the effect of systematic uncertainties on Monte Carlo calculations of k{sub Q}. These factors are required to use the TG-51 or TRS-398 clinical dosimetry protocols for calibrating external radiotherapy beams. Methods: Ionization chambers are modeled either from blueprints or manufacturers' user's manuals. The dose-to-air in the chamber is calculated using the EGSnrc user-code egs{sub c}hamber using 11 different tabulated clinical photon spectra for the incident beams. The dose to amore » small volume of water is also calculated in the absence of the chamber at the midpoint of the chamber on its central axis. Using a simple equation, k{sub Q} is calculated from these quantities under the assumption that W/e is constant with energy and compared to TG-51 protocol and measured values. Results: Polynomial fits to the Monte Carlo calculated k{sub Q} factors as a function of beam quality expressed as %dd(10){sub x} and TPR{sub 10}{sup 20} are given for each ionization chamber. Differences are explained between Monte Carlo calculated values and values from the TG-51 protocol or calculated using the computer program used for TG-51 calculations. Systematic uncertainties in calculated k{sub Q} values are analyzed and amount to a maximum of one standard deviation uncertainty of 0.99% if one assumes that photon cross-section uncertainties are uncorrelated and 0.63% if they are assumed correlated. The largest components of the uncertainty are the constancy of W/e and the uncertainty in the cross-section for photons in water. Conclusions: It is now possible to calculate k{sub Q} directly using Monte Carlo simulations. Monte Carlo calculations for most ionization chambers give results which are comparable to TG-51 values. Discrepancies can be explained using individual Monte Carlo calculations of various correction factors which are more accurate than previously used values. For small ionization chambers with central electrodes composed of high-Z materials, the effect of the central electrode is much larger than that for the aluminum electrodes in Farmer chambers.« less

Effects of Average Signed Area Between Two Item Characteristic Curves and Test Purification Procedures on the DIF Detection via the Mantel-Haenszel Method

ERIC Educational Resources Information Center

Wang, Wen-Chung; Su, Ya-Hui

2004-01-01

In this study we investigated the effects of the average signed area (ASA) between the item characteristic curves of the reference and focal groups and three test purification procedures on the uniform differential item functioning (DIF) detection via the Mantel-Haenszel (M-H) method through Monte Carlo simulations. The results showed that ASA,…

A study on the coagulation of polycyclic aromatic hydrocarbon clusters to determine their collision efficiency

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

Raj, Abhijeet; Sander, Markus; Janardhanan, Vinod

2010-03-15

This paper presents a theoretical study on the physical interaction between polycyclic aromatic hydrocarbons (PAHs) and their clusters of different sizes in laminar premixed flames. Two models are employed for this study: a detailed PAH growth model, referred to as the kinetic Monte Carlo - aromatic site (KMC-ARS) model [Raj et al., Combust. Flame 156 (2009) 896-913]; and a multivariate PAH population balance model, referred to as the PAH - primary particle (PAH-PP) model. Both the models are solved by kinetic Monte Carlo methods. PAH mass spectra are generated using the PAH-PP model, and compared to the experimentally observed spectramore » for a laminar premixed ethylene flame. The position of the maxima of PAH dimers in the spectra and their concentrations are found to depend strongly on the collision efficiency of PAH coagulation. The variation in the collision efficiency with various flame and PAH parameters is studied to determine the factors on which it may depend. A correlation for the collision efficiency is proposed by comparing the computed and the observed spectra for an ethylene flame. With this correlation, a good agreement between the computed and the observed spectra for a number of laminar premixed ethylene flames is found. (author)« less

Internal dosimetry with the Monte Carlo code GATE: validation using the ICRP/ICRU female reference computational model

NASA Astrophysics Data System (ADS)

Villoing, Daphnée; Marcatili, Sara; Garcia, Marie-Paule; Bardiès, Manuel

2017-03-01

The purpose of this work was to validate GATE-based clinical scale absorbed dose calculations in nuclear medicine dosimetry. GATE (version 6.2) and MCNPX (version 2.7.a) were used to derive dosimetric parameters (absorbed fractions, specific absorbed fractions and S-values) for the reference female computational model proposed by the International Commission on Radiological Protection in ICRP report 110. Monoenergetic photons and electrons (from 50 keV to 2 MeV) and four isotopes currently used in nuclear medicine (fluorine-18, lutetium-177, iodine-131 and yttrium-90) were investigated. Absorbed fractions, specific absorbed fractions and S-values were generated with GATE and MCNPX for 12 regions of interest in the ICRP 110 female computational model, thereby leading to 144 source/target pair configurations. Relative differences between GATE and MCNPX obtained in specific configurations (self-irradiation or cross-irradiation) are presented. Relative differences in absorbed fractions, specific absorbed fractions or S-values are below 10%, and in most cases less than 5%. Dosimetric results generated with GATE for the 12 volumes of interest are available as supplemental data. GATE can be safely used for radiopharmaceutical dosimetry at the clinical scale. This makes GATE a viable option for Monte Carlo modelling of both imaging and absorbed dose in nuclear medicine.

Monte Carlo Particle Lists: MCPL

NASA Astrophysics Data System (ADS)

Kittelmann, T.; Klinkby, E.; Knudsen, E. B.; Willendrup, P.; Cai, X. X.; Kanaki, K.

2017-09-01

A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular simulation packages.

OBJECT KINETIC MONTE CARLO SIMULATIONS OF CASCADE ANNEALING IN TUNGSTEN

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

Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard L.

2014-03-31

The objective of this work is to study the annealing of primary cascade damage created by primary knock-on atoms (PKAs) of various energies, at various temperatures in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.

Quantum interference and Monte Carlo simulations of multiparticle production

NASA Astrophysics Data System (ADS)

Bialas, A.; Krzywicki, A.

1995-02-01

We show that the effects of quantum interference can be implemented in Monte Carlo generators by modelling the generalized Wigner functions. A specific prescription for an appropriate modification of the weights of events produced by standard generators is proposed.

Scalable Domain Decomposed Monte Carlo Particle Transport

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

O'Brien, Matthew Joseph

2013-12-05

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

Baseball Monte Carlo Style.

ERIC Educational Resources Information Center

Houser, Larry L.

1981-01-01

Monte Carlo methods are used to simulate activities in baseball such as a team's "hot streak" and a hitter's "batting slump." Student participation in such simulations is viewed as a useful method of giving pupils a better understanding of the probability concepts involved. (MP)

A variational Monte Carlo study of different spin configurations of electron-hole bilayer

NASA Astrophysics Data System (ADS)

Sharma, Rajesh O.; Saini, L. K.; Bahuguna, Bhagwati Prasad

2018-05-01

We report quantum Monte Carlo results for mass-asymmetric electron-hole bilayer (EHBL) system with different-different spin configurations. Particularly, we apply a variational Monte Carlo method to estimate the ground-state energy, condensate fraction and pair-correlations function at fixed density rs = 5 and interlayer distance d = 1 a.u. We find that spin-configuration of EHBL system, which consists of only up-electrons in one layer and down-holes in other i.e. ferromagnetic arrangement within layers and anti-ferromagnetic across the layers, is more stable than the other spin-configurations considered in this study.

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

92 Years of the Ising Model: A High Resolution Monte Carlo Study

NASA Astrophysics Data System (ADS)

Xu, Jiahao; Ferrenberg, Alan M.; Landau, David P.

2018-04-01

Using extensive Monte Carlo simulations that employ the Wolff cluster flipping and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising model with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, we obtained the critical inverse temperature K c = 0.221 654 626(5) and the critical exponent of the correlation length ν = 0.629 912(86) with precision that improves upon previous Monte Carlo estimates.

Accelerate quasi Monte Carlo method for solving systems of linear algebraic equations through shared memory

NASA Astrophysics Data System (ADS)

Lai, Siyan; Xu, Ying; Shao, Bo; Guo, Menghan; Lin, Xiaola

2017-04-01

In this paper we study on Monte Carlo method for solving systems of linear algebraic equations (SLAE) based on shared memory. Former research demostrated that GPU can effectively speed up the computations of this issue. Our purpose is to optimize Monte Carlo method simulation on GPUmemoryachritecture specifically. Random numbers are organized to storein shared memory, which aims to accelerate the parallel algorithm. Bank conflicts can be avoided by our Collaborative Thread Arrays(CTA)scheme. The results of experiments show that the shared memory based strategy can speed up the computaions over than 3X at most.

Monte Carlo Simulation of Nonlinear Radiation Induced Plasmas. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Wang, B. S.

1972-01-01

A Monte Carlo simulation model for radiation induced plasmas with nonlinear properties due to recombination was, employing a piecewise linearized predict-correct iterative technique. Several important variance reduction techniques were developed and incorporated into the model, including an antithetic variates technique. This approach is especially efficient for plasma systems with inhomogeneous media, multidimensions, and irregular boundaries. The Monte Carlo code developed has been applied to the determination of the electron energy distribution function and related parameters for a noble gas plasma created by alpha-particle irradiation. The characteristics of the radiation induced plasma involved are given.

HepSim: A repository with predictions for high-energy physics experiments

DOE PAGES

Chekanov, S. V.

2015-02-03

A file repository for calculations of cross sections and kinematic distributions using Monte Carlo generators for high-energy collisions is discussed. The repository is used to facilitate effective preservation and archiving of data from theoretical calculations and for comparisons with experimental data. The HepSim data library is publicly accessible and includes a number of Monte Carlo event samples with Standard Model predictions for current and future experiments. The HepSim project includes a software package to automate the process of downloading and viewing online Monte Carlo event samples. Data streaming over a network for end-user analysis is discussed.

Multilevel sequential Monte Carlo samplers

DOE PAGES

Beskos, Alexandros; Jasra, Ajay; Law, Kody; ...

2016-08-24

Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h L. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h 0>h 1 ...>h L. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less

Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm

NASA Astrophysics Data System (ADS)

Gubernatis, James

2014-03-01

A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.

Validation of the Monte Carlo simulator GATE for indium-111 imaging.

PubMed

Assié, K; Gardin, I; Véra, P; Buvat, I

2005-07-07

Monte Carlo simulations are useful for optimizing and assessing single photon emission computed tomography (SPECT) protocols, especially when aiming at measuring quantitative parameters from SPECT images. Before Monte Carlo simulated data can be trusted, the simulation model must be validated. The purpose of this work was to validate the use of GATE, a new Monte Carlo simulation platform based on GEANT4, for modelling indium-111 SPECT data, the quantification of which is of foremost importance for dosimetric studies. To that end, acquisitions of (111)In line sources in air and in water and of a cylindrical phantom were performed, together with the corresponding simulations. The simulation model included Monte Carlo modelling of the camera collimator and of a back-compartment accounting for photomultiplier tubes and associated electronics. Energy spectra, spatial resolution, sensitivity values, images and count profiles obtained for experimental and simulated data were compared. An excellent agreement was found between experimental and simulated energy spectra. For source-to-collimator distances varying from 0 to 20 cm, simulated and experimental spatial resolution differed by less than 2% in air, while the simulated sensitivity values were within 4% of the experimental values. The simulation of the cylindrical phantom closely reproduced the experimental data. These results suggest that GATE enables accurate simulation of (111)In SPECT acquisitions.

Discrete Fractional Component Monte Carlo Simulation Study of Dilute Nonionic Surfactants at the Air-Water Interface.

PubMed

Yoo, Brian; Marin-Rimoldi, Eliseo; Mullen, Ryan Gotchy; Jusufi, Arben; Maginn, Edward J

2017-09-26

We present a newly developed Monte Carlo scheme to predict bulk surfactant concentrations and surface tensions at the air-water interface for various surfactant interfacial coverages. Since the concentration regimes of these systems of interest are typically very dilute (≪10 -5 mol. frac.), Monte Carlo simulations with the use of insertion/deletion moves can provide the ability to overcome finite system size limitations that often prohibit the use of modern molecular simulation techniques. In performing these simulations, we use the discrete fractional component Monte Carlo (DFCMC) method in the Gibbs ensemble framework, which allows us to separate the bulk and air-water interface into two separate boxes and efficiently swap tetraethylene glycol surfactants C 10 E 4 between boxes. Combining this move with preferential translations, volume biased insertions, and Wang-Landau biasing vastly enhances sampling and helps overcome the classical "insertion problem", often encountered in non-lattice Monte Carlo simulations. We demonstrate that this methodology is both consistent with the original molecular thermodynamic theory (MTT) of Blankschtein and co-workers, as well as their recently modified theory (MD/MTT), which incorporates the results of surfactant infinite dilution transfer free energies and surface tension calculations obtained from molecular dynamics simulations.

Harnessing graphical structure in Markov chain Monte Carlo learning

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

Stolorz, P.E.; Chew P.C.

1996-12-31

The Monte Carlo method is recognized as a useful tool in learning and probabilistic inference methods common to many datamining problems. Generalized Hidden Markov Models and Bayes nets are especially popular applications. However, the presence of multiple modes in many relevant integrands and summands often renders the method slow and cumbersome. Recent mean field alternatives designed to speed things up have been inspired by experience gleaned from physics. The current work adopts an approach very similar to this in spirit, but focusses instead upon dynamic programming notions as a basis for producing systematic Monte Carlo improvements. The idea is tomore » approximate a given model by a dynamic programming-style decomposition, which then forms a scaffold upon which to build successively more accurate Monte Carlo approximations. Dynamic programming ideas alone fail to account for non-local structure, while standard Monte Carlo methods essentially ignore all structure. However, suitably-crafted hybrids can successfully exploit the strengths of each method, resulting in algorithms that combine speed with accuracy. The approach relies on the presence of significant {open_quotes}local{close_quotes} information in the problem at hand. This turns out to be a plausible assumption for many important applications. Example calculations are presented, and the overall strengths and weaknesses of the approach are discussed.« less

Free energy and phase equilibria for the restricted primitive model of ionic fluids from Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Orkoulas, Gerassimos; Panagiotopoulos, Athanassios Z.

1994-07-01

In this work, we investigate the liquid-vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T*c=0.053, ρ*c=0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids.

Monte Carlo calculation of dose rate conversion factors for external exposure to photon emitters in soil

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

Clovas, A.; Zanthos, S.; Antonopoulos-Domis, M.

2000-03-01

The dose rate conversion factors {dot D}{sub CF} (absorbed dose rate in air per unit activity per unit of soil mass, nGy h{sup {minus}1} per Bq kg{sup {minus}1}) are calculated 1 m above ground for photon emitters of natural radionuclides uniformly distributed in the soil. Three Monte Carlo codes are used: (1) The MCNP code of Los Alamos; (2) The GEANT code of CERN; and (3) a Monte Carlo code developed in the Nuclear Technology Laboratory of the Aristotle University of Thessaloniki. The accuracy of the Monte Carlo results is tested by the comparison of the unscattered flux obtained bymore » the three Monte Carlo codes with an independent straightforward calculation. All codes and particularly the MCNP calculate accurately the absorbed dose rate in air due to the unscattered radiation. For the total radiation (unscattered plus scattered) the {dot D}{sub CF} values calculated from the three codes are in very good agreement between them. The comparison between these results and the results deduced previously by other authors indicates a good agreement (less than 15% of difference) for photon energies above 1,500 keV. Antithetically, the agreement is not as good (difference of 20--30%) for the low energy photons.« less

Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

PubMed Central

Pratx, Guillem; Xing, Lei

2011-01-01

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes. PMID:22191916

Determination of Rolling-Element Fatigue Life From Computer Generated Bearing Tests

NASA Technical Reports Server (NTRS)

Vlcek, Brian L.; Hendricks, Robert C.; Zaretsky, Erwin V.

2003-01-01

Two types of rolling-element bearings representing radial loaded and thrust loaded bearings were used for this study. Three hundred forty (340) virtual bearing sets totaling 31400 bearings were randomly assembled and tested by Monte Carlo (random) number generation. The Monte Carlo results were compared with endurance data from 51 bearing sets comprising 5321 bearings. A simple algebraic relation was established for the upper and lower L(sub 10) life limits as function of number of bearings failed for any bearing geometry. There is a fifty percent (50 percent) probability that the resultant bearing life will be less than that calculated. The maximum and minimum variation between the bearing resultant life and the calculated life correlate with the 90-percent confidence limits for a Weibull slope of 1.5. The calculated lives for bearings using a load-life exponent p of 4 for ball bearings and 5 for roller bearings correlated with the Monte Carlo generated bearing lives and the bearing data. STLE life factors for bearing steel and processing provide a reasonable accounting for differences between bearing life data and calculated life. Variations in Weibull slope from the Monte Carlo testing and bearing data correlated. There was excellent agreement between percent of individual components failed from Monte Carlo simulation and that predicted.

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis

NASA Technical Reports Server (NTRS)

Hanson, J. M.; Beard, B. B.

2010-01-01

This Technical Publication (TP) is meant to address a number of topics related to the application of Monte Carlo simulation to launch vehicle design and requirements analysis. Although the focus is on a launch vehicle application, the methods may be applied to other complex systems as well. The TP is organized so that all the important topics are covered in the main text, and detailed derivations are in the appendices. The TP first introduces Monte Carlo simulation and the major topics to be discussed, including discussion of the input distributions for Monte Carlo runs, testing the simulation, how many runs are necessary for verification of requirements, what to do if results are desired for events that happen only rarely, and postprocessing, including analyzing any failed runs, examples of useful output products, and statistical information for generating desired results from the output data. Topics in the appendices include some tables for requirements verification, derivation of the number of runs required and generation of output probabilistic data with consumer risk included, derivation of launch vehicle models to include possible variations of assembled vehicles, minimization of a consumable to achieve a two-dimensional statistical result, recontact probability during staging, ensuring duplicated Monte Carlo random variations, and importance sampling.

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

NASA Astrophysics Data System (ADS)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

Effects of Uncertainties in Electric Field Boundary Conditions for Ring Current Simulations

NASA Astrophysics Data System (ADS)

Chen, Margaret W.; O'Brien, T. Paul; Lemon, Colby L.; Guild, Timothy B.

2018-01-01

Physics-based simulation results can vary widely depending on the applied boundary conditions. As a first step toward assessing the effect of boundary conditions on ring current simulations, we analyze the uncertainty of cross-polar cap potentials (CPCP) on electric field boundary conditions applied to the Rice Convection Model-Equilibrium (RCM-E). The empirical Weimer model of CPCP is chosen as the reference model and Defense Meteorological Satellite Program CPCP measurements as the reference data. Using temporal correlations from a statistical analysis of the "errors" between the reference model and data, we construct a Monte Carlo CPCP discrete time series model that can be generalized to other model boundary conditions. RCM-E simulations using electric field boundary conditions from the reference model and from 20 randomly generated Monte Carlo discrete time series of CPCP are performed for two large storms. During the 10 August 2000 storm main phase, the proton density at 10 RE at midnight was observed to be low (< 1.4 cm-3) and the observed disturbance Dst index is bounded by the simulated Dst values. In contrast, the simulated Dst values during the recovery phases of the 10 August 2000 and 31 August 2005 storms tend to underestimate systematically the observed late Dst recovery. This suggests a need to improve the accuracy of particle loss calculations in the RCM-E model. Application of this technique can aid modelers to make efficient choices on either investing more effort on improving specification of boundary conditions or on improving descriptions of physical processes.

Sci-Thur PM: YIS - 07: Monte Carlo simulations to obtain several parameters required for electron beam dosimetry.

PubMed

Muir, B; Rogers, D; McEwen, M

2012-07-01

When current dosimetry protocols were written, electron beam data were limited and had uncertainties that were unacceptable for reference dosimetry. Protocols for high-energy reference dosimetry are currently being updated leading to considerable interest in accurate electron beam data. To this end, Monte Carlo simulations using the EGSnrc user-code egs_chamber are performed to extract relevant data for reference beam dosimetry. Calculations of the absorbed dose to water and the absorbed dose to the gas in realistic ion chamber models are performed as a function of depth in water for cobalt-60 and high-energy electron beams between 4 and 22 MeV. These calculations are used to extract several of the parameters required for electron beam dosimetry - the beam quality specifier, R 50 , beam quality conversion factors, k Q and k R50 , the electron quality conversion factor, k' R50 , the photon-electron conversion factor, k ecal , and ion chamber perturbation factors, P Q . The method used has the advantage that many important parameters can be extracted as a function of depth instead of determination at only the reference depth as has typically been done. Results obtained here are in good agreement with measured and other calculated results. The photon-electron conversion factors obtained for a Farmer-type NE2571 and plane-parallel PTW Roos, IBA NACP-02 and Exradin A11 chambers are 0.903, 0.896, 0.894 and 0.906, respectively. These typically differ by less than 0.7% from the contentious TG-51 values but have much smaller systematic uncertainties. These results are valuable for reference dosimetry of high-energy electron beams. © 2012 American Association of Physicists in Medicine.

Monte Carlo Simulations of Microchannel Plate Based, Fast-Gated X-Ray Imagers

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

Wu., M., Kruschwitz, C.

2011-02-01

This is a chapter in a book titled Applications of Monte Carlo Method in Science and Engineering Edited by: Shaul Mordechai ISBN 978-953-307-691-1, Hard cover, 950 pages Publisher: InTech Publication date: February 2011

MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD

EPA Science Inventory

A predictive screening model was developed for fate and transport
of viruses in the unsaturated zone. A database of input parameters
allowed Monte Carlo analysis with the model. The resulting kernel
densities of predicted attenuation during percolation indicated very ...

Structural Reliability and Monte Carlo Simulation.

ERIC Educational Resources Information Center

Laumakis, P. J.; Harlow, G.

2002-01-01

Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)

Time-dependent integral equations of neutron transport for calculating the kinetics of nuclear reactors by the Monte Carlo method

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

Davidenko, V. D., E-mail: Davidenko-VD@nrcki.ru; Zinchenko, A. S., E-mail: zin-sn@mail.ru; Harchenko, I. K.

2016-12-15

Integral equations for the shape functions in the adiabatic, quasi-static, and improved quasi-static approximations are presented. The approach to solving these equations by the Monte Carlo method is described.

Monte Carlo calculation of skyshine'' neutron dose from ALS (Advanced Light Source)

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

Moin-Vasiri, M.

1990-06-01

This report discusses the following topics on skyshine'' neutron dose from ALS: Sources of radiation; ALS modeling for skyshine calculations; MORSE Monte-Carlo; Implementation of MORSE; Results of skyshine calculations from storage ring; and Comparison of MORSE shielding calculations.

Reconstruction of Human Monte Carlo Geometry from Segmented Images

NASA Astrophysics Data System (ADS)

Zhao, Kai; Cheng, Mengyun; Fan, Yanchang; Wang, Wen; Long, Pengcheng; Wu, Yican

2014-06-01

Human computational phantoms have been used extensively for scientific experimental analysis and experimental simulation. This article presented a method for human geometry reconstruction from a series of segmented images of a Chinese visible human dataset. The phantom geometry could actually describe detailed structure of an organ and could be converted into the input file of the Monte Carlo codes for dose calculation. A whole-body computational phantom of Chinese adult female has been established by FDS Team which is named Rad-HUMAN with about 28.8 billion voxel number. For being processed conveniently, different organs on images were segmented with different RGB colors and the voxels were assigned with positions of the dataset. For refinement, the positions were first sampled. Secondly, the large sums of voxels inside the organ were three-dimensional adjacent, however, there were not thoroughly mergence methods to reduce the cell amounts for the description of the organ. In this study, the voxels on the organ surface were taken into consideration of the mergence which could produce fewer cells for the organs. At the same time, an indexed based sorting algorithm was put forward for enhancing the mergence speed. Finally, the Rad-HUMAN which included a total of 46 organs and tissues was described by the cuboids into the Monte Carlo Monte Carlo Geometry for the simulation. The Monte Carlo geometry was constructed directly from the segmented images and the voxels was merged exhaustively. Each organ geometry model was constructed without ambiguity and self-crossing, its geometry information could represent the accuracy appearance and precise interior structure of the organs. The constructed geometry largely retaining the original shape of organs could easily be described into different Monte Carlo codes input file such as MCNP. Its universal property was testified and high-performance was experimentally verified

Status of the Monte Carlo library least-squares (MCLLS) approach for non-linear radiation analyzer problems

NASA Astrophysics Data System (ADS)

Gardner, Robin P.; Xu, Libai

2009-10-01

The Center for Engineering Applications of Radioisotopes (CEAR) has been working for over a decade on the Monte Carlo library least-squares (MCLLS) approach for treating non-linear radiation analyzer problems including: (1) prompt gamma-ray neutron activation analysis (PGNAA) for bulk analysis, (2) energy-dispersive X-ray fluorescence (EDXRF) analyzers, and (3) carbon/oxygen tool analysis in oil well logging. This approach essentially consists of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required background libraries. These libraries are then used in the linear library least-squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. Iterations of this are used until the LLS values agree with the composition used to generate the libraries. The current status of the methods (and topics) necessary to implement the MCLLS approach is reported. This includes: (1) the Monte Carlo codes such as CEARXRF, CEARCPG, and CEARCO for forward generation of the necessary elemental library spectra for the LLS calculation for X-ray fluorescence, neutron capture prompt gamma-ray analyzers, and carbon/oxygen tools; (2) the correction of spectral pulse pile-up (PPU) distortion by Monte Carlo simulation with the code CEARIPPU; (3) generation of detector response functions (DRF) for detectors with linear and non-linear responses for Monte Carlo simulation of pulse-height spectra; and (4) the use of the differential operator (DO) technique to make the necessary iterations for non-linear responses practical. In addition to commonly analyzed single spectra, coincidence spectra or even two-dimensional (2-D) coincidence spectra can also be used in the MCLLS approach and may provide more accurate results.

Impact of reconstruction parameters on quantitative I-131 SPECT

NASA Astrophysics Data System (ADS)

van Gils, C. A. J.; Beijst, C.; van Rooij, R.; de Jong, H. W. A. M.

2016-07-01

Radioiodine therapy using I-131 is widely used for treatment of thyroid disease or neuroendocrine tumors. Monitoring treatment by accurate dosimetry requires quantitative imaging. The high energy photons however render quantitative SPECT reconstruction challenging, potentially requiring accurate correction for scatter and collimator effects. The goal of this work is to assess the effectiveness of various correction methods on these effects using phantom studies. A SPECT/CT acquisition of the NEMA IEC body phantom was performed. Images were reconstructed using the following parameters: (1) without scatter correction, (2) with triple energy window (TEW) scatter correction and (3) with Monte Carlo-based scatter correction. For modelling the collimator-detector response (CDR), both (a) geometric Gaussian CDRs as well as (b) Monte Carlo simulated CDRs were compared. Quantitative accuracy, contrast to noise ratios and recovery coefficients were calculated, as well as the background variability and the residual count error in the lung insert. The Monte Carlo scatter corrected reconstruction method was shown to be intrinsically quantitative, requiring no experimentally acquired calibration factor. It resulted in a more accurate quantification of the background compartment activity density compared with TEW or no scatter correction. The quantification error relative to a dose calibrator derived measurement was found to be  <1%,-26% and 33%, respectively. The adverse effects of partial volume were significantly smaller with the Monte Carlo simulated CDR correction compared with geometric Gaussian or no CDR modelling. Scatter correction showed a small effect on quantification of small volumes. When using a weighting factor, TEW correction was comparable to Monte Carlo reconstruction in all measured parameters, although this approach is clinically impractical since this factor may be patient dependent. Monte Carlo based scatter correction including accurately simulated CDR modelling is the most robust and reliable method to reconstruct accurate quantitative iodine-131 SPECT images.

Stopping power and dose calculations with analytical and Monte Carlo methods for protons and prompt gamma range verification

NASA Astrophysics Data System (ADS)

Usta, Metin; Tufan, Mustafa Çağatay; Aydın, Güral; Bozkurt, Ahmet

2018-07-01

In this study, we have performed the calculations stopping power, depth dose, and range verification for proton beams using dielectric and Bethe-Bloch theories and FLUKA, Geant4 and MCNPX Monte Carlo codes. In the framework, as analytical studies, Drude model was applied for dielectric theory and effective charge approach with Roothaan-Hartree-Fock charge densities was used in Bethe theory. In the simulations different setup parameters were selected to evaluate the performance of three distinct Monte Carlo codes. The lung and breast tissues were investigated are considered to be related to the most common types of cancer throughout the world. The results were compared with each other and the available data in literature. In addition, the obtained results were verified with prompt gamma range data. In both stopping power values and depth-dose distributions, it was found that the Monte Carlo values give better results compared with the analytical ones while the results that agree best with ICRU data in terms of stopping power are those of the effective charge approach between the analytical methods and of the FLUKA code among the MC packages. In the depth dose distributions of the examined tissues, although the Bragg curves for Monte Carlo almost overlap, the analytical ones show significant deviations that become more pronounce with increasing energy. Verifications with the results of prompt gamma photons were attempted for 100-200 MeV protons which are regarded important for proton therapy. The analytical results are within 2%-5% and the Monte Carlo values are within 0%-2% as compared with those of the prompt gammas.

Finite element model updating using the shadow hybrid Monte Carlo technique

NASA Astrophysics Data System (ADS)

Boulkaibet, I.; Mthembu, L.; Marwala, T.; Friswell, M. I.; Adhikari, S.

2015-02-01

Recent research in the field of finite element model updating (FEM) advocates the adoption of Bayesian analysis techniques to dealing with the uncertainties associated with these models. However, Bayesian formulations require the evaluation of the Posterior Distribution Function which may not be available in analytical form. This is the case in FEM updating. In such cases sampling methods can provide good approximations of the Posterior distribution when implemented in the Bayesian context. Markov Chain Monte Carlo (MCMC) algorithms are the most popular sampling tools used to sample probability distributions. However, the efficiency of these algorithms is affected by the complexity of the systems (the size of the parameter space). The Hybrid Monte Carlo (HMC) offers a very important MCMC approach to dealing with higher-dimensional complex problems. The HMC uses the molecular dynamics (MD) steps as the global Monte Carlo (MC) moves to reach areas of high probability where the gradient of the log-density of the Posterior acts as a guide during the search process. However, the acceptance rate of HMC is sensitive to the system size as well as the time step used to evaluate the MD trajectory. To overcome this limitation we propose the use of the Shadow Hybrid Monte Carlo (SHMC) algorithm. The SHMC algorithm is a modified version of the Hybrid Monte Carlo (HMC) and designed to improve sampling for large-system sizes and time steps. This is done by sampling from a modified Hamiltonian function instead of the normal Hamiltonian function. In this paper, the efficiency and accuracy of the SHMC method is tested on the updating of two real structures; an unsymmetrical H-shaped beam structure and a GARTEUR SM-AG19 structure and is compared to the application of the HMC algorithm on the same structures.

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.

Dosimetric verification of IMRT treatment planning using Monte Carlo simulations for prostate cancer

NASA Astrophysics Data System (ADS)

Yang, J.; Li, J.; Chen, L.; Price, R.; McNeeley, S.; Qin, L.; Wang, L.; Xiong, W.; Ma, C.-M.

2005-03-01

The purpose of this work is to investigate the accuracy of dose calculation of a commercial treatment planning system (Corvus, Normos Corp., Sewickley, PA). In this study, 30 prostate intensity-modulated radiotherapy (IMRT) treatment plans from the commercial treatment planning system were recalculated using the Monte Carlo method. Dose-volume histograms and isodose distributions were compared. Other quantities such as minimum dose to the target (Dmin), the dose received by 98% of the target volume (D98), dose at the isocentre (Diso), mean target dose (Dmean) and the maximum critical structure dose (Dmax) were also evaluated based on our clinical criteria. For coplanar plans, the dose differences between Monte Carlo and the commercial treatment planning system with and without heterogeneity correction were not significant. The differences in the isocentre dose between the commercial treatment planning system and Monte Carlo simulations were less than 3% for all coplanar cases. The differences on D98 were less than 2% on average. The differences in the mean dose to the target between the commercial system and Monte Carlo results were within 3%. The differences in the maximum bladder dose were within 3% for most cases. The maximum dose differences for the rectum were less than 4% for all the cases. For non-coplanar plans, the difference in the minimum target dose between the treatment planning system and Monte Carlo calculations was up to 9% if the heterogeneity correction was not applied in Corvus. This was caused by the excessive attenuation of the non-coplanar beams by the femurs. When the heterogeneity correction was applied in Corvus, the differences were reduced significantly. These results suggest that heterogeneity correction should be used in dose calculation for prostate cancer with non-coplanar beam arrangements.

WE-AB-204-11: Development of a Nuclear Medicine Dosimetry Module for the GPU-Based Monte Carlo Code ARCHER

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

Liu, T; Lin, H; Xu, X

Purpose: To develop a nuclear medicine dosimetry module for the GPU-based Monte Carlo code ARCHER. Methods: We have developed a nuclear medicine dosimetry module for the fast Monte Carlo code ARCHER. The coupled electron-photon Monte Carlo transport kernel included in ARCHER is built upon the Dose Planning Method code (DPM). The developed module manages the radioactive decay simulation by consecutively tracking several types of radiation on a per disintegration basis using the statistical sampling method. Optimization techniques such as persistent threads and prefetching are studied and implemented. The developed module is verified against the VIDA code, which is based onmore » Geant4 toolkit and has previously been verified against OLINDA/EXM. A voxelized geometry is used in the preliminary test: a sphere made of ICRP soft tissue is surrounded by a box filled with water. Uniform activity distribution of I-131 is assumed in the sphere. Results: The self-absorption dose factors (mGy/MBqs) of the sphere with varying diameters are calculated by ARCHER and VIDA respectively. ARCHER’s result is in agreement with VIDA’s that are obtained from a previous publication. VIDA takes hours of CPU time to finish the computation, while it takes ARCHER 4.31 seconds for the 12.4-cm uniform activity sphere case. For a fairer CPU-GPU comparison, more effort will be made to eliminate the algorithmic differences. Conclusion: The coupled electron-photon Monte Carlo code ARCHER has been extended to radioactive decay simulation for nuclear medicine dosimetry. The developed code exhibits good performance in our preliminary test. The GPU-based Monte Carlo code is developed with grant support from the National Institute of Biomedical Imaging and Bioengineering through an R01 grant (R01EB015478)« less

MCNP (Monte Carlo Neutron Photon) capabilities for nuclear well logging calculations

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

Forster, R.A.; Little, R.C.; Briesmeister, J.F.

The Los Alamos Radiation Transport Code System (LARTCS) consists of state-of-the-art Monte Carlo and discrete ordinates transport codes and data libraries. The general-purpose continuous-energy Monte Carlo code MCNP (Monte Carlo Neutron Photon), part of the LARTCS, provides a computational predictive capability for many applications of interest to the nuclear well logging community. The generalized three-dimensional geometry of MCNP is well suited for borehole-tool models. SABRINA, another component of the LARTCS, is a graphics code that can be used to interactively create a complex MCNP geometry. Users can define many source and tally characteristics with standard MCNP features. The time-dependent capabilitymore » of the code is essential when modeling pulsed sources. Problems with neutrons, photons, and electrons as either single particle or coupled particles can be calculated with MCNP. The physics of neutron and photon transport and interactions is modeled in detail using the latest available cross-section data. A rich collections of variance reduction features can greatly increase the efficiency of a calculation. MCNP is written in FORTRAN 77 and has been run on variety of computer systems from scientific workstations to supercomputers. The next production version of MCNP will include features such as continuous-energy electron transport and a multitasking option. Areas of ongoing research of interest to the well logging community include angle biasing, adaptive Monte Carlo, improved discrete ordinates capabilities, and discrete ordinates/Monte Carlo hybrid development. Los Alamos has requested approval by the Department of Energy to create a Radiation Transport Computational Facility under their User Facility Program to increase external interactions with industry, universities, and other government organizations. 21 refs.« less

MATSIM: Development of a Voxel Model of the MATROSHKA Astronaut Dosimetric Phantom

NASA Astrophysics Data System (ADS)

Beck, Peter; Zechner, Andrea; Rollet, Sofia; Berger, Thomas; Bergmann, Robert; Hajek, Michael; Hranitzky, Christian; Latocha, Marcin; Reitz, Günther; Stadtmann, Hannes; Vana, Norbert; Wind, Michael

2011-08-01

The AIT Austrian Institute of Technology coordinates the project MATSIM (MATROSHKA Simulation) in collaboration with the Vienna University of Technology and the German Aerospace Center, to perform FLUKA Monte Carlo simulations of the MATROSHKA numerical phantom irradiated under reference radiation field conditions as well as for the radiation environment at the International Space Station (ISS). MATSIM is carried out as co-investigation of the ESA ELIPS projects SORD and RADIS (commonly known as MATROSHKA), an international collaboration of more than 18 research institutes and space agencies from all over the world, under the science and project lead of the German Aerospace Center. During MATSIM a computer tomography scan of the MATROSHKA phantom has been converted into a high resolution 3-dimensional voxel model. The energy imparted and absorbed dose distribution inside the model is determined for various radiation fields. The major goal of the MATSIM project is the validation of the numerical model under reference radiation conditions and further investigations under the radiation environment at ISS. In this report we compare depth dose distributions inside the phantom measured with thermoluminescence detectors (TLDs) and an ionization chamber with FLUKA Monte Carlo particle transport simulations due to 60Co photon exposure. Further reference irradiations with neutrons, protons and heavy ions are planned. The fully validated numerical model MATSIM will provide a perfect tool to assess the radiation exposure to humans during current and future space missions to ISS, Moon, Mars and beyond.

A Variational Monte Carlo Approach to Atomic Structure

ERIC Educational Resources Information Center

Davis, Stephen L.

2007-01-01

The practicality and usefulness of variational Monte Carlo calculations to atomic structure are demonstrated. It is found to succeed in quantitatively illustrating electron shielding, effective nuclear charge, l-dependence of the orbital energies, and singlet-tripetenergy splitting and ionization energy trends in atomic structure theory.

Does standard Monte Carlo give justice to instantons?

NASA Astrophysics Data System (ADS)

Fucito, F.; Solomon, S.

1984-01-01

The results of the standard local Monte Carlo are changed by offering instantons as candidates in the Metropolis procedure. We also define an O(3) topological charge with no contribution from planar dislocations. The RG behavior is still not recovered. Bantrell Fellow in Theoretical Physics.

Using Stan for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Au, Chi Hang

2018-01-01

Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…

Backward and forward Monte Carlo method for vector radiative transfer in a two-dimensional graded index medium

NASA Astrophysics Data System (ADS)

Qian, Lin-Feng; Shi, Guo-Dong; Huang, Yong; Xing, Yu-Ming

2017-10-01

In vector radiative transfer, backward ray tracing is seldom used. We present a backward and forward Monte Carlo method to simulate vector radiative transfer in a two-dimensional graded index medium, which is new and different from the conventional Monte Carlo method. The backward and forward Monte Carlo method involves dividing the ray tracing into two processes backward tracing and forward tracing. In multidimensional graded index media, the trajectory of a ray is usually a three-dimensional curve. During the transport of a polarization ellipse, the curved ray trajectory will induce geometrical effects and cause Stokes parameters to continuously change. The solution processes for a non-scattering medium and an anisotropic scattering medium are analysed. We also analyse some parameters that influence the Stokes vector in two-dimensional graded index media. The research shows that the Q component of the Stokes vector cannot be ignored. However, the U and V components of the Stokes vector are very small.

Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo

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

Zou Yu, E-mail: yzou@Princeton.ED; Kavousanakis, Michail E., E-mail: mkavousa@Princeton.ED; Kevrekidis, Ioannis G., E-mail: yannis@Princeton.ED

2010-07-20

The study of particle coagulation and sintering processes is important in a variety of research studies ranging from cell fusion and dust motion to aerosol formation applications. These processes are traditionally simulated using either Monte-Carlo methods or integro-differential equations for particle number density functions. In this paper, we present a computational technique for cases where we believe that accurate closed evolution equations for a finite number of moments of the density function exist in principle, but are not explicitly available. The so-called equation-free computational framework is then employed to numerically obtain the solution of these unavailable closed moment equations bymore » exploiting (through intelligent design of computational experiments) the corresponding fine-scale (here, Monte-Carlo) simulation. We illustrate the use of this method by accelerating the computation of evolving moments of uni- and bivariate particle coagulation and sintering through short simulation bursts of a constant-number Monte-Carlo scheme.« less

Dynamic Monte Carlo description of thermal desorption processes

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1994-07-01

The applicability of the dynamic Monte Carlo method of Fichthorn and Weinberg, in which the time evolution of a system is described in terms of the absolute number of different microscopic possible events and their associated transition rates, is discussed for the case of thermal desorption simulations. It is shown that the definition of the time increment at each successful event leads naturally to the macroscopic differential equation of desorption, in the case of simple first- and second-order processes in which the only possible events are desorption and diffusion. This equivalence is numerically demonstrated for a second-order case. In the sequence, the equivalence of this method with the Monte Carlo method of Sales and Zgrablich for more complex desorption processes, allowing for lateral interactions between adsorbates, is shown, even though the dynamic Monte Carlo method does not bear their limitation of a rapid surface diffusion condition, thus being able to describe a more complex ``kinetics'' of surface reactive processes, and therefore be applied to a wider class of phenomena, such as surface catalysis.

Transforming high-dimensional potential energy surfaces into sum-of-products form using Monte Carlo methods

NASA Astrophysics Data System (ADS)

Schröder, Markus; Meyer, Hans-Dieter

2017-08-01

We propose a Monte Carlo method, "Monte Carlo Potfit," for transforming high-dimensional potential energy surfaces evaluated on discrete grid points into a sum-of-products form, more precisely into a Tucker form. To this end we use a variational ansatz in which we replace numerically exact integrals with Monte Carlo integrals. This largely reduces the numerical cost by avoiding the evaluation of the potential on all grid points and allows a treatment of surfaces up to 15-18 degrees of freedom. We furthermore show that the error made with this ansatz can be controlled and vanishes in certain limits. We present calculations on the potential of HFCO to demonstrate the features of the algorithm. To demonstrate the power of the method, we transformed a 15D potential of the protonated water dimer (Zundel cation) in a sum-of-products form and calculated the ground and lowest 26 vibrationally excited states of the Zundel cation with the multi-configuration time-dependent Hartree method.

ME(SSY)**2: Monte Carlo Code for Star Cluster Simulations

NASA Astrophysics Data System (ADS)

Freitag, Marc Dewi

2013-02-01

ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).

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

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

DOE PAGES

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

2016-01-01

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

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

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Semi-stochastic full configuration interaction quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Holmes, Adam; Petruzielo, Frank; Khadilkar, Mihir; Changlani, Hitesh; Nightingale, M. P.; Umrigar, C. J.

2012-02-01

In the recently proposed full configuration interaction quantum Monte Carlo (FCIQMC) [1,2], the ground state is projected out stochastically, using a population of walkers each of which represents a basis state in the Hilbert space spanned by Slater determinants. The infamous fermion sign problem manifests itself in the fact that walkers of either sign can be spawned on a given determinant. We propose an improvement on this method in the form of a hybrid stochastic/deterministic technique, which we expect will improve the efficiency of the algorithm by ameliorating the sign problem. We test the method on atoms and molecules, e.g., carbon, carbon dimer, N2 molecule, and stretched N2. [4pt] [1] Fermion Monte Carlo without fixed nodes: a Game of Life, death and annihilation in Slater Determinant space. George Booth, Alex Thom, Ali Alavi. J Chem Phys 131, 050106, (2009).[0pt] [2] Survival of the fittest: Accelerating convergence in full configuration-interaction quantum Monte Carlo. Deidre Cleland, George Booth, and Ali Alavi. J Chem Phys 132, 041103 (2010).

Stochastic, real-space, imaginary-time evaluation of third-order Feynman-Goldstone diagrams

NASA Astrophysics Data System (ADS)

Willow, Soohaeng Yoo; Hirata, So

2014-01-01

A new, alternative set of interpretation rules of Feynman-Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mEh after 106 Monte Carlo steps.

Monte-Carlo-based phase retardation estimator for polarization sensitive optical coherence tomography

NASA Astrophysics Data System (ADS)

Duan, Lian; Makita, Shuichi; Yamanari, Masahiro; Lim, Yiheng; Yasuno, Yoshiaki

2011-08-01

A Monte-Carlo-based phase retardation estimator is developed to correct the systematic error in phase retardation measurement by polarization sensitive optical coherence tomography (PS-OCT). Recent research has revealed that the phase retardation measured by PS-OCT has a distribution that is neither symmetric nor centered at the true value. Hence, a standard mean estimator gives us erroneous estimations of phase retardation, and it degrades the performance of PS-OCT for quantitative assessment. In this paper, the noise property in phase retardation is investigated in detail by Monte-Carlo simulation and experiments. A distribution transform function is designed to eliminate the systematic error by using the result of the Monte-Carlo simulation. This distribution transformation is followed by a mean estimator. This process provides a significantly better estimation of phase retardation than a standard mean estimator. This method is validated both by numerical simulations and experiments. The application of this method to in vitro and in vivo biological samples is also demonstrated.

Neutrality and evolvability of designed protein sequences

NASA Astrophysics Data System (ADS)

Bhattacherjee, Arnab; Biswas, Parbati

2010-07-01

The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.

Using hybrid implicit Monte Carlo diffusion to simulate gray radiation hydrodynamics

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

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Gentile, Nick

This work describes how to couple a hybrid Implicit Monte Carlo Diffusion (HIMCD) method with a Lagrangian hydrodynamics code to evaluate the coupled radiation hydrodynamics equations. This HIMCD method dynamically applies Implicit Monte Carlo Diffusion (IMD) [1] to regions of a problem that are opaque and diffusive while applying standard Implicit Monte Carlo (IMC) [2] to regions where the diffusion approximation is invalid. We show that this method significantly improves the computational efficiency as compared to a standard IMC/Hydrodynamics solver, when optically thick diffusive material is present, while maintaining accuracy. Two test cases are used to demonstrate the accuracy andmore » performance of HIMCD as compared to IMC and IMD. The first is the Lowrie semi-analytic diffusive shock [3]. The second is a simple test case where the source radiation streams through optically thin material and heats a thick diffusive region of material causing it to rapidly expand. We found that HIMCD proves to be accurate, robust, and computationally efficient for these test problems.« less

Entanglement and the fermion sign problem in auxiliary field quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Broecker, Peter; Trebst, Simon

2016-08-01

Quantum Monte Carlo simulations of fermions are hampered by the notorious sign problem whose most striking manifestation is an exponential growth of sampling errors with the number of particles. With the sign problem known to be an NP-hard problem and any generic solution thus highly elusive, the Monte Carlo sampling of interacting many-fermion systems is commonly thought to be restricted to a small class of model systems for which a sign-free basis has been identified. Here we demonstrate that entanglement measures, in particular the so-called Rényi entropies, can intrinsically exhibit a certain robustness against the sign problem in auxiliary-field quantum Monte Carlo approaches and possibly allow for the identification of global ground-state properties via their scaling behavior even in the presence of a strong sign problem. We corroborate these findings via numerical simulations of fermionic quantum phase transitions of spinless fermions on the honeycomb lattice at and below half filling.

VARIAN CLINAC 6 MeV Photon Spectra Unfolding using a Monte Carlo Meshed Model

NASA Astrophysics Data System (ADS)

Morató, S.; Juste, B.; Miró, R.; Verdú, G.

2017-09-01

Energy spectrum is the best descriptive function to determine photon beam quality of a Medical Linear Accelerator (LinAc). The use of realistic photon spectra in Monte Carlo simulations has a great importance to obtain precise dose calculations in Radiotherapy Treatment Planning (RTP). Reconstruction of photon spectra emitted by medical accelerators from measured depth dose distributions in a water cube is an important tool for commissioning a Monte Carlo treatment planning system. Regarding this, the reconstruction problem is an inverse radiation transport function which is ill conditioned and its solution may become unstable due to small perturbations in the input data. This paper presents a more stable spectral reconstruction method which can be used to provide an independent confirmation of source models for a given machine without any prior knowledge of the spectral distribution. Monte Carlo models used in this work are built with unstructured meshes to simulate with realism the linear accelerator head geometry.

SU-F-T-657: In-Room Neutron Dose From High Energy Photon Beams

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

Christ, D; Ding, G

Purpose: To estimate neutron dose inside the treatment room from photodisintegration events in high energy photon beams using Monte Carlo simulations and experimental measurements. Methods: The Monte Carlo code MCNP6 was used for the simulations. An Eberline ESP-1 Smart Portable Neutron Detector was used to measure neutron dose. A water phantom was centered at isocenter on the treatment couch, and the detector was placed near the phantom. A Varian 2100EX linear accelerator delivered an 18MV open field photon beam to the phantom at 400MU/min, and a camera captured the detector readings. The experimental setup was modeled in the Monte Carlomore » simulation. The source was modeled for two extreme cases: a) hemispherical photon source emitting from the target and b) cone source with an angle of the primary collimator cone. The model includes the target, primary collimator, flattening filter, secondary collimators, water phantom, detector and concrete walls. Energy deposition tallies were measured for neutrons in the detector and for photons at the center of the phantom. Results: For an 18MV beam with an open 10cm by 10cm field and the gantry at 180°, the Monte Carlo simulations predict the neutron dose in the detector to be 0.11% of the photon dose in the water phantom for case a) and 0.01% for case b). The measured neutron dose is 0.04% of the photon dose. Considering the range of neutron dose predicted by Monte Carlo simulations, the calculated results are in good agreement with measurements. Conclusion: We calculated in-room neutron dose by using Monte Carlo techniques, and the predicted neutron dose is confirmed by experimental measurements. If we remodel the source as an electron beam hitting the target for a more accurate representation of the bremsstrahlung fluence, it is feasible that the Monte Carlo simulations can be used to help in shielding designs.« less

Fast quantum Monte Carlo on a GPU

NASA Astrophysics Data System (ADS)

Lutsyshyn, Y.

2015-02-01

We present a scheme for the parallelization of quantum Monte Carlo method on graphical processing units, focusing on variational Monte Carlo simulation of bosonic systems. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent utilization of the accelerator. The CUDA code is provided along with a package that simulates liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the Kepler architecture K20 GPU. Special optimization was developed for the Kepler cards, including placement of data structures in the register space of the Kepler GPUs. Kepler-specific optimization is discussed.

Heterogeneous Hardware Parallelism Review of the IN2P3 2016 Computing School

NASA Astrophysics Data System (ADS)

Lafage, Vincent

2017-11-01

Parallel and hybrid Monte Carlo computation. The Monte Carlo method is the main workhorse for computation of particle physics observables. This paper provides an overview of various HPC technologies that can be used today: multicore (OpenMP, HPX), manycore (OpenCL). The rewrite of a twenty years old Fortran 77 Monte Carlo will illustrate the various programming paradigms in use beyond language implementation. The problem of parallel random number generator will be addressed. We will give a short report of the one week school dedicated to these recent approaches, that took place in École Polytechnique in May 2016.

Discrete ordinates-Monte Carlo coupling: A comparison of techniques in NERVA radiation analysis

NASA Technical Reports Server (NTRS)

Lindstrom, D. G.; Normand, E.; Wilcox, A. D.

1972-01-01

In the radiation analysis of the NERVA nuclear rocket system, two-dimensional discrete ordinates calculations are sufficient to provide detail in the pressure vessel and reactor assembly. Other parts of the system, however, require three-dimensional Monte Carlo analyses. To use these two methods in a single analysis, a means of coupling was developed whereby the results of a discrete ordinates calculation can be used to produce source data for a Monte Carlo calculation. Several techniques for producing source detail were investigated. Results of calculations on the NERVA system are compared and limitations and advantages of the coupling techniques discussed.

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

PubMed

Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

2005-01-01

The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

Bold Diagrammatic Monte Carlo for Fermionic and Fermionized Systems

NASA Astrophysics Data System (ADS)

Svistunov, Boris

2013-03-01

In three different fermionic cases--repulsive Hubbard model, resonant fermions, and fermionized spins-1/2 (on triangular lattice)--we observe the phenomenon of sign blessing: Feynman diagrammatic series features finite convergence radius despite factorial growth of the number of diagrams with diagram order. Bold diagrammatic Monte Carlo technique allows us to sample millions of skeleton Feynman diagrams. With the universal fermionization trick we can fermionize essentially any (bosonic, spin, mixed, etc.) lattice system. The combination of fermionization and Bold diagrammatic Monte Carlo yields a universal first-principle approach to strongly correlated lattice systems, provided the sign blessing is a generic fermionic phenomenon. Supported by NSF and DARPA

The Impact of Monte Carlo Dose Calculations on Intensity-Modulated Radiation Therapy

NASA Astrophysics Data System (ADS)

Siebers, J. V.; Keall, P. J.; Mohan, R.

The effect of dose calculation accuracy for IMRT was studied by comparing different dose calculation algorithms. A head and neck IMRT plan was optimized using a superposition dose calculation algorithm. Dose was re-computed for the optimized plan using both Monte Carlo and pencil beam dose calculation algorithms to generate patient and phantom dose distributions. Tumor control probabilities (TCP) and normal tissue complication probabilities (NTCP) were computed to estimate the plan outcome. For the treatment plan studied, Monte Carlo best reproduces phantom dose measurements, the TCP was slightly lower than the superposition and pencil beam results, and the NTCP values differed little.

Binding energies and spatial structures of small carrier complexes in monolayer transition-metal dichalcogenides via diffusion Monte Carlo

DOE PAGES

Mayers, Matthew Z.; Berkelbach, Timothy C.; Hybertsen, Mark S.; ...

2015-10-09

Ground-state diffusion Monte Carlo is used to investigate the binding energies and intercarrier radial probability distributions of excitons, trions, and biexcitons in a variety of two-dimensional transition-metal dichalcogenide materials. We compare these results to approximate variational calculations, as well as to analogous Monte Carlo calculations performed with simplified carrier interaction potentials. Our results highlight the successes and failures of approximate approaches as well as the physical features that determine the stability of small carrier complexes in monolayer transition-metal dichalcogenide materials. In conclusion, we discuss points of agreement and disagreement with recent experiments.

Geodesic Monte Carlo on Embedded Manifolds

PubMed Central

Byrne, Simon; Girolami, Mark

2013-01-01

Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024

Neoclassical toroidal viscosity calculations in tokamaks using a δf Monte Carlo simulation and their verifications.

PubMed

Satake, S; Park, J-K; Sugama, H; Kanno, R

2011-07-29

Neoclassical toroidal viscosities (NTVs) in tokamaks are investigated using a δf Monte Carlo simulation, and are successfully verified with a combined analytic theory over a wide range of collisionality. A Monte Carlo simulation has been required in the study of NTV since the complexities in guiding-center orbits of particles and their collisions cannot be fully investigated by any means of analytic theories alone. Results yielded the details of the complex NTV dependency on particle precessions and collisions, which were predicted roughly in a combined analytic theory. Both numerical and analytic methods can be utilized and extended based on these successful verifications.

Improved radial dose function estimation using current version MCNP Monte-Carlo simulation: Model 6711 and ISC3500 125I brachytherapy sources.

PubMed

Duggan, Dennis M

2004-12-01

Improved cross-sections in a new version of the Monte-Carlo N-particle (MCNP) code may eliminate discrepancies between radial dose functions (as defined by American Association of Physicists in Medicine Task Group 43) derived from Monte-Carlo simulations of low-energy photon-emitting brachytherapy sources and those from measurements on the same sources with thermoluminescent dosimeters. This is demonstrated for two 125I brachytherapy seed models, the Implant Sciences Model ISC3500 (I-Plant) and the Amersham Health Model 6711, by simulating their radial dose functions with two versions of MCNP, 4c2 and 5.

The Rational Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Clark, Michael

2006-12-01

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

Monte Carlo simulation of cutaneous absorption and reflectance for clear, matt and dark biological tissue with varicosities: an investigation for dermatological laser

NASA Astrophysics Data System (ADS)

Klouch, Nawel; Riane, Houaria; Hamdache, Fatima; Addi, Djamel

2013-05-01

We are interested in modeling the interaction between light and biological tissue from the Monte Carlo method which is an approach used to solve modeling problems in different physical domains. Through the Monte Carlo approach we are going to try to interpret the spectral response absorption, reflectance, transmittance of normal human tissue under its three dominant tints in the visible range (350-700) nm. Then we will focus on the spectral response of the human tissue with varicosities in order to determinate the optimal conditions of operating the semiconductor laser for esthetic aim.

Modulated phases in a three-dimensional Maier-Saupe model with competing interactions

NASA Astrophysics Data System (ADS)

Bienzobaz, P. F.; Xu, Na; Sandvik, Anders W.

2017-07-01

This work is dedicated to the study of the discrete version of the Maier-Saupe model in the presence of competing interactions. The competition between interactions favoring different orientational ordering produces a rich phase diagram including modulated phases. Using a mean-field approach and Monte Carlo simulations, we show that the proposed model exhibits isotropic and nematic phases and also a series of modulated phases that meet at a multicritical point, a Lifshitz point. Though the Monte Carlo and mean-field phase diagrams show some quantitative disagreements, the Monte Carlo simulations corroborate the general behavior found within the mean-field approximation.

Predictions of a Large Magnetocaloric Effect in Co- and Cr-Substituted Heusler Alloys Using First-Principles and Monte Carlo Approaches

NASA Astrophysics Data System (ADS)

Sokolovskiy, Vladimir V.; Buchelnikov, Vasiliy D.; Zagrebin, Mikhail A.; Grünebohm, Anna; Entel, Peter

The effect of Co- and Cr-doping on magnetic and magnetocaloric poperties of Ni-Mn-(In, Ga, Sn, and Al) Heusler alloys has been theoretically studied by combining first principles with Monte Carlo approaches. The magnetic and magnetocaloric properties are obtained as a function of temperature and magnetic field using a mixed type of Potts and Blume-Emery-Griffiths model where the model parameters are obtained from ab initio calculations. The Monte Carlo calculations allowed to make predictions of a giant inverse magnetocaloric effect in partially new hypothetical magnetic Heusler alloys across the martensitic transformation.

Accurate quantification of fluorescent targets within turbid media based on a decoupled fluorescence Monte Carlo model.

PubMed

Deng, Yong; Luo, Zhaoyang; Jiang, Xu; Xie, Wenhao; Luo, Qingming

2015-07-01

We propose a method based on a decoupled fluorescence Monte Carlo model for constructing fluorescence Jacobians to enable accurate quantification of fluorescence targets within turbid media. The effectiveness of the proposed method is validated using two cylindrical phantoms enclosing fluorescent targets within homogeneous and heterogeneous background media. The results demonstrate that our method can recover relative concentrations of the fluorescent targets with higher accuracy than the perturbation fluorescence Monte Carlo method. This suggests that our method is suitable for quantitative fluorescence diffuse optical tomography, especially for in vivo imaging of fluorophore targets for diagnosis of different diseases and abnormalities.

Particle tracking acceleration via signed distance fields in direct-accelerated geometry Monte Carlo

DOE PAGES

Shriwise, Patrick C.; Davis, Andrew; Jacobson, Lucas J.; ...

2017-08-26

Computer-aided design (CAD)-based Monte Carlo radiation transport is of value to the nuclear engineering community for its ability to conduct transport on high-fidelity models of nuclear systems, but it is more computationally expensive than native geometry representations. This work describes the adaptation of a rendering data structure, the signed distance field, as a geometric query tool for accelerating CAD-based transport in the direct-accelerated geometry Monte Carlo toolkit. Demonstrations of its effectiveness are shown for several problems. The beginnings of a predictive model for the data structure's utilization based on various problem parameters is also introduced.

A simple methodology for characterization of germanium coaxial detectors by using Monte Carlo simulation and evolutionary algorithms.

PubMed

Guerra, J G; Rubiano, J G; Winter, G; Guerra, A G; Alonso, H; Arnedo, M A; Tejera, A; Gil, J M; Rodríguez, R; Martel, P; Bolivar, J P

2015-11-01

The determination in a sample of the activity concentration of a specific radionuclide by gamma spectrometry needs to know the full energy peak efficiency (FEPE) for the energy of interest. The difficulties related to the experimental calibration make it advisable to have alternative methods for FEPE determination, such as the simulation of the transport of photons in the crystal by the Monte Carlo method, which requires an accurate knowledge of the characteristics and geometry of the detector. The characterization process is mainly carried out by Canberra Industries Inc. using proprietary techniques and methodologies developed by that company. It is a costly procedure (due to shipping and to the cost of the process itself) and for some research laboratories an alternative in situ procedure can be very useful. The main goal of this paper is to find an alternative to this costly characterization process, by establishing a method for optimizing the parameters of characterizing the detector, through a computational procedure which could be reproduced at a standard research lab. This method consists in the determination of the detector geometric parameters by using Monte Carlo simulation in parallel with an optimization process, based on evolutionary algorithms, starting from a set of reference FEPEs determined experimentally or computationally. The proposed method has proven to be effective and simple to implement. It provides a set of characterization parameters which it has been successfully validated for different source-detector geometries, and also for a wide range of environmental samples and certified materials. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measurement Uncertainty of Dew-Point Temperature in a Two-Pressure Humidity Generator

NASA Astrophysics Data System (ADS)

Martins, L. Lages; Ribeiro, A. Silva; Alves e Sousa, J.; Forbes, Alistair B.

2012-09-01

This article describes the measurement uncertainty evaluation of the dew-point temperature when using a two-pressure humidity generator as a reference standard. The estimation of the dew-point temperature involves the solution of a non-linear equation for which iterative solution techniques, such as the Newton-Raphson method, are required. Previous studies have already been carried out using the GUM method and the Monte Carlo method but have not discussed the impact of the approximate numerical method used to provide the temperature estimation. One of the aims of this article is to take this approximation into account. Following the guidelines presented in the GUM Supplement 1, two alternative approaches can be developed: the forward measurement uncertainty propagation by the Monte Carlo method when using the Newton-Raphson numerical procedure; and the inverse measurement uncertainty propagation by Bayesian inference, based on prior available information regarding the usual dispersion of values obtained by the calibration process. The measurement uncertainties obtained using these two methods can be compared with previous results. Other relevant issues concerning this research are the broad application to measurements that require hygrometric conditions obtained from two-pressure humidity generators and, also, the ability to provide a solution that can be applied to similar iterative models. The research also studied the factors influencing both the use of the Monte Carlo method (such as the seed value and the convergence parameter) and the inverse uncertainty propagation using Bayesian inference (such as the pre-assigned tolerance, prior estimate, and standard deviation) in terms of their accuracy and adequacy.

Fate of the open-shell singlet ground state in the experimentally accessible acenes: A quantum Monte Carlo study

NASA Astrophysics Data System (ADS)

Dupuy, Nicolas; Casula, Michele

2018-04-01

By means of the Jastrow correlated antisymmetrized geminal power (JAGP) wave function and quantum Monte Carlo (QMC) methods, we study the ground state properties of the oligoacene series, up to the nonacene. The JAGP is the accurate variational realization of the resonating-valence-bond (RVB) ansatz proposed by Pauling and Wheland to describe aromatic compounds. We show that the long-ranged RVB correlations built in the acenes' ground state are detrimental for the occurrence of open-shell diradical or polyradical instabilities, previously found by lower-level theories. We substantiate our outcome by a direct comparison with another wave function, tailored to be an open-shell singlet (OSS) for long-enough acenes. By comparing on the same footing the RVB and OSS wave functions, both optimized at a variational QMC level and further projected by the lattice regularized diffusion Monte Carlo method, we prove that the RVB wave function has always a lower variational energy and better nodes than the OSS, for all molecular species considered in this work. The entangled multi-reference RVB state acts against the electron edge localization implied by the OSS wave function and weakens the diradical tendency for higher oligoacenes. These properties are reflected by several descriptors, including wave function parameters, bond length alternation, aromatic indices, and spin-spin correlation functions. In this context, we propose a new aromatic index estimator suitable for geminal wave functions. For the largest acenes taken into account, the long-range decay of the charge-charge correlation functions is compatible with a quasi-metallic behavior.

A Monte Carlo Uncertainty Analysis of Ozone Trend Predictions in a Two Dimensional Model. Revision

NASA Technical Reports Server (NTRS)

Considine, D. B.; Stolarski, R. S.; Hollandsworth, S. M.; Jackman, C. H.; Fleming, E. L.

1998-01-01

We use Monte Carlo analysis to estimate the uncertainty in predictions of total O3 trends between 1979 and 1995 made by the Goddard Space Flight Center (GSFC) two-dimensional (2D) model of stratospheric photochemistry and dynamics. The uncertainty is caused by gas-phase chemical reaction rates, photolysis coefficients, and heterogeneous reaction parameters which are model inputs. The uncertainty represents a lower bound to the total model uncertainty assuming the input parameter uncertainties are characterized correctly. Each of the Monte Carlo runs was initialized in 1970 and integrated for 26 model years through the end of 1995. This was repeated 419 times using input parameter sets generated by Latin Hypercube Sampling. The standard deviation (a) of the Monte Carlo ensemble of total 03 trend predictions is used to quantify the model uncertainty. The 34% difference between the model trend in globally and annually averaged total O3 using nominal inputs and atmospheric trends calculated from Nimbus 7 and Meteor 3 total ozone mapping spectrometer (TOMS) version 7 data is less than the 46% calculated 1 (sigma), model uncertainty, so there is no significant difference between the modeled and observed trends. In the northern hemisphere midlatitude spring the modeled and observed total 03 trends differ by more than 1(sigma) but less than 2(sigma), which we refer to as marginal significance. We perform a multiple linear regression analysis of the runs which suggests that only a few of the model reactions contribute significantly to the variance in the model predictions. The lack of significance in these comparisons suggests that they are of questionable use as guides for continuing model development. Large model/measurement differences which are many multiples of the input parameter uncertainty are seen in the meridional gradients of the trend and the peak-to-peak variations in the trends over an annual cycle. These discrepancies unambiguously indicate model formulation problems and provide a measure of model performance which can be used in attempts to improve such models.

SU-E-T-552: Monte Carlo Calculation of Correction Factors for a Free-Air Ionization Chamber in Support of a National Air-Kerma Standard for Electronic Brachytherapy

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

Mille, M; Bergstrom, P

2015-06-15

Purpose: To use Monte Carlo radiation transport methods to calculate correction factors for a free-air ionization chamber in support of a national air-kerma standard for low-energy, miniature x-ray sources used for electronic brachytherapy (eBx). Methods: The NIST is establishing a calibration service for well-type ionization chambers used to characterize the strength of eBx sources prior to clinical use. The calibration approach involves establishing the well-chamber’s response to an eBx source whose air-kerma rate at a 50 cm distance is determined through a primary measurement performed using the Lamperti free-air ionization chamber. However, the free-air chamber measurements of charge or currentmore » can only be related to the reference air-kerma standard after applying several corrections, some of which are best determined via Monte Carlo simulation. To this end, a detailed geometric model of the Lamperti chamber was developed in the EGSnrc code based on the engineering drawings of the instrument. The egs-fac user code in EGSnrc was then used to calculate energy-dependent correction factors which account for missing or undesired ionization arising from effects such as: (1) attenuation and scatter of the x-rays in air; (2) primary electrons escaping the charge collection region; (3) lack of charged particle equilibrium; (4) atomic fluorescence and bremsstrahlung radiation. Results: Energy-dependent correction factors were calculated assuming a monoenergetic point source with the photon energy ranging from 2 keV to 60 keV in 2 keV increments. Sufficient photon histories were simulated so that the Monte Carlo statistical uncertainty of the correction factors was less than 0.01%. The correction factors for a specific eBx source will be determined by integrating these tabulated results over its measured x-ray spectrum. Conclusion: The correction factors calculated in this work are important for establishing a national standard for eBx which will help ensure that dose is accurately and consistently delivered to patients.« less

Updating the TSP Quality Plan Using Monte Carlo Simulation

DTIC Science & Technology

2010-08-01

TSP is the attention to quality or, more accurately, the ability to manage product defects. In fact, TSP creator Watts S . Humphrey says: ... defect...teams at Hill AFB recently started using this technique and are still gathering data on its useful- ness.u References 1. Humphrey , Watts S . TSP...Leading a Development Team. Upper Saddle River, NJ: Addison-Wesley, 2006. Page 138. 2. Humphrey , Watts S . TSP – Leading a Development Team. Upper Saddle

Particle-Based Simulations of Microscopic Thermal Properties of Confined Systems

DTIC Science & Technology

2014-11-01

velocity versus electric field in gallium arsenide (GaAs) computed with the original CMC table structure (squares) at temperature T=150K, and the new...computer-aided design Cellular Monte Carlo Ensemble Monte Carlo gallium arsenide Heat Transport Equation DARPA Defense Advanced Research Projects

The Use of Monte Carlo Techniques to Teach Probability.

ERIC Educational Resources Information Center

Newell, G. J.; MacFarlane, J. D.

1985-01-01

Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…

Computer program uses Monte Carlo techniques for statistical system performance analysis

NASA Technical Reports Server (NTRS)

Wohl, D. P.

1967-01-01

Computer program with Monte Carlo sampling techniques determines the effect of a component part of a unit upon the overall system performance. It utilizes the full statistics of the disturbances and misalignments of each component to provide unbiased results through simulated random sampling.

Monte Carlo Simulation of Microscopic Stock Market Models

NASA Astrophysics Data System (ADS)

Stauffer, Dietrich

Computer simulations with random numbers, that is, Monte Carlo methods, have been considerably applied in recent years to model the fluctuations of stock market or currency exchange rates. Here we concentrate on the percolation model of Cont and Bouchaud, to simulate, not to predict, the market behavior.

Comparison of space radiation calculations for deterministic and Monte Carlo transport codes

NASA Astrophysics Data System (ADS)

Lin, Zi-Wei; Adams, James; Barghouty, Abdulnasser; Randeniya, Sharmalee; Tripathi, Ram; Watts, John; Yepes, Pablo

For space radiation protection of astronauts or electronic equipments, it is necessary to develop and use accurate radiation transport codes. Radiation transport codes include deterministic codes, such as HZETRN from NASA and UPROP from the Naval Research Laboratory, and Monte Carlo codes such as FLUKA, the Geant4 toolkit and HETC-HEDS. The deterministic codes and Monte Carlo codes complement each other in that deterministic codes are very fast while Monte Carlo codes are more elaborate. Therefore it is important to investigate how well the results of deterministic codes compare with those of Monte Carlo transport codes and where they differ. In this study we evaluate these different codes in their space radiation applications by comparing their output results in the same given space radiation environments, shielding geometry and material. Typical space radiation environments such as the 1977 solar minimum galactic cosmic ray environment are used as the well-defined input, and simple geometries made of aluminum, water and/or polyethylene are used to represent the shielding material. We then compare various outputs of these codes, such as the dose-depth curves and the flux spectra of different fragments and other secondary particles. These comparisons enable us to learn more about the main differences between these space radiation transport codes. At the same time, they help us to learn the qualitative and quantitative features that these transport codes have in common.

Energy dispersive X-ray fluorescence spectroscopy/Monte Carlo simulation approach for the non-destructive analysis of corrosion patina-bearing alloys in archaeological bronzes: The case of the bowl from the Fareleira 3 site (Vidigueira, South Portugal)

NASA Astrophysics Data System (ADS)

Bottaini, C.; Mirão, J.; Figuereido, M.; Candeias, A.; Brunetti, A.; Schiavon, N.

2015-01-01

Energy dispersive X-ray fluorescence (EDXRF) is a well-known technique for non-destructive and in situ analysis of archaeological artifacts both in terms of the qualitative and quantitative elemental composition because of its rapidity and non-destructiveness. In this study EDXRF and realistic Monte Carlo simulation using the X-ray Monte Carlo (XRMC) code package have been combined to characterize a Cu-based bowl from the Iron Age burial from Fareleira 3 (Southern Portugal). The artifact displays a multilayered structure made up of three distinct layers: a) alloy substrate; b) green oxidized corrosion patina; and c) brownish carbonate soil-derived crust. To assess the reliability of Monte Carlo simulation in reproducing the composition of the bulk metal of the objects without recurring to potentially damaging patina's and crust's removal, portable EDXRF analysis was performed on cleaned and patina/crust coated areas of the artifact. Patina has been characterized by micro X-ray Diffractometry (μXRD) and Back-Scattered Scanning Electron Microscopy + Energy Dispersive Spectroscopy (BSEM + EDS). Results indicate that the EDXRF/Monte Carlo protocol is well suited when a two-layered model is considered, whereas in areas where the patina + crust surface coating is too thick, X-rays from the alloy substrate are not able to exit the sample.

CloudMC: a cloud computing application for Monte Carlo simulation.

PubMed

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

Experimental verification of a CT-based Monte Carlo dose-calculation method in heterogeneous phantoms.

PubMed

Wang, L; Lovelock, M; Chui, C S

1999-12-01

To further validate the Monte Carlo dose-calculation method [Med. Phys. 25, 867-878 (1998)] developed at the Memorial Sloan-Kettering Cancer Center, we have performed experimental verification in various inhomogeneous phantoms. The phantom geometries included simple layered slabs, a simulated bone column, a simulated missing-tissue hemisphere, and an anthropomorphic head geometry (Alderson Rando Phantom). The densities of the inhomogeneity range from 0.14 to 1.86 g/cm3, simulating both clinically relevant lunglike and bonelike materials. The data are reported as central axis depth doses, dose profiles, dose values at points of interest, such as points at the interface of two different media and in the "nasopharynx" region of the Rando head. The dosimeters used in the measurement included dosimetry film, TLD chips, and rods. The measured data were compared to that of Monte Carlo calculations for the same geometrical configurations. In the case of the Rando head phantom, a CT scan of the phantom was used to define the calculation geometry and to locate the points of interest. The agreement between the calculation and measurement is generally within 2.5%. This work validates the accuracy of the Monte Carlo method. While Monte Carlo, at present, is still too slow for routine treatment planning, it can be used as a benchmark against which other dose calculation methods can be compared.

Full Configuration Interaction Quantum Monte Carlo and Diffusion Monte Carlo: A Comparative Study of the 3D Homogeneous Electron Gas

NASA Astrophysics Data System (ADS)

Shepherd, James J.; López Ríos, Pablo; Needs, Richard J.; Drummond, Neil D.; Mohr, Jennifer A.-F.; Booth, George H.; Grüneis, Andreas; Kresse, Georg; Alavi, Ali

2013-03-01

Full configuration interaction quantum Monte Carlo1 (FCIQMC) and its initiator adaptation2 allow for exact solutions to the Schrödinger equation to be obtained within a finite-basis wavefunction ansatz. In this talk, we explore an application of FCIQMC to the homogeneous electron gas (HEG). In particular we use these exact finite-basis energies to compare with approximate quantum chemical calculations from the VASP code3. After removing the basis set incompleteness error by extrapolation4,5, we compare our energies with state-of-the-art diffusion Monte Carlo calculations from the CASINO package6. Using a combined approach of the two quantum Monte Carlo methods, we present the highest-accuracy thermodynamic (infinite-particle) limit energies for the HEG achieved to date. 1 G. H. Booth, A. Thom, and A. Alavi, J. Chem. Phys. 131, 054106 (2009). 2 D. Cleland, G. H. Booth, and A. Alavi, J. Chem. Phys. 132, 041103 (2010). 3 www.vasp.at (2012). 4 J. J. Shepherd, A. Grüneis, G. H. Booth, G. Kresse, and A. Alavi, Phys. Rev. B. 86, 035111 (2012). 5 J. J. Shepherd, G. H. Booth, and A. Alavi, J. Chem. Phys. 136, 244101 (2012). 6 R. Needs, M. Towler, N. Drummond, and P. L. Ríos, J. Phys.: Condensed Matter 22, 023201 (2010).

An Energy-Dispersive X-Ray Fluorescence Spectrometry and Monte Carlo simulation study of Iron-Age Nuragic small bronzes ("Navicelle") from Sardinia, Italy

NASA Astrophysics Data System (ADS)

Schiavon, Nick; de Palmas, Anna; Bulla, Claudio; Piga, Giampaolo; Brunetti, Antonio

2016-09-01

A spectrometric protocol combining Energy Dispersive X-Ray Fluorescence Spectrometry with Monte Carlo simulations of experimental spectra using the XRMC code package has been applied for the first time to characterize the elemental composition of a series of famous Iron Age small scale archaeological bronze replicas of ships (known as the ;Navicelle;) from the Nuragic civilization in Sardinia, Italy. The proposed protocol is a useful, nondestructive and fast analytical tool for Cultural Heritage sample. In Monte Carlo simulations, each sample was modeled as a multilayered object composed by two or three layers depending on the sample: when all present, the three layers are the original bronze substrate, the surface corrosion patina and an outermost protective layer (Paraloid) applied during past restorations. Monte Carlo simulations were able to account for the presence of the patina/corrosion layer as well as the presence of the Paraloid protective layer. It also accounted for the roughness effect commonly found at the surface of corroded metal archaeological artifacts. In this respect, the Monte Carlo simulation approach adopted here was, to the best of our knowledge, unique and enabled to determine the bronze alloy composition together with the thickness of the surface layers without the need for previously removing the surface patinas, a process potentially threatening preservation of precious archaeological/artistic artifacts for future generations.

Monte Carlo calculations of the impact of a hip prosthesis on the dose distribution

NASA Astrophysics Data System (ADS)

Buffard, Edwige; Gschwind, Régine; Makovicka, Libor; David, Céline

2006-09-01

Because of the ageing of the population, an increasing number of patients with hip prostheses are undergoing pelvic irradiation. Treatment planning systems (TPS) currently available are not always able to accurately predict the dose distribution around such implants. In fact, only Monte Carlo simulation has the ability to precisely calculate the impact of a hip prosthesis during radiotherapeutic treatment. Monte Carlo phantoms were developed to evaluate the dose perturbations during pelvic irradiation. A first model, constructed with the DOSXYZnrc usercode, was elaborated to determine the dose increase at the tissue-metal interface as well as the impact of the material coating the prosthesis. Next, CT-based phantoms were prepared, using the usercode CTCreate, to estimate the influence of the geometry and the composition of such implants on the beam attenuation. Thanks to a program that we developed, the study was carried out with CT-based phantoms containing a hip prosthesis without metal artefacts. Therefore, anthropomorphic phantoms allowed better definition of both patient anatomy and the hip prosthesis in order to better reproduce the clinical conditions of pelvic irradiation. The Monte Carlo results revealed the impact of certain coatings such as PMMA on dose enhancement at the tissue-metal interface. Monte Carlo calculations in CT-based phantoms highlighted the marked influence of the implant's composition, its geometry as well as its position within the beam on dose distribution.

Self-evolving atomistic kinetic Monte Carlo simulations of defects in materials

DOE PAGES

Xu, Haixuan; Beland, Laurent K.; Stoller, Roger E.; ...

2015-01-29

The recent development of on-the-fly atomistic kinetic Monte Carlo methods has led to an increased amount attention on the methods and their corresponding capabilities and applications. In this review, the framework and current status of Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) are discussed. SEAKMC particularly focuses on defect interaction and evolution with atomistic details without assuming potential defect migration/interaction mechanisms and energies. The strength and limitation of using an active volume, the key concept introduced in SEAKMC, are discussed. Potential criteria for characterizing an active volume are discussed and the influence of active volume size on saddle point energies ismore » illustrated. A procedure starting with a small active volume followed by larger active volumes was found to possess higher efficiency. Applications of SEAKMC, ranging from point defect diffusion, to complex interstitial cluster evolution, to helium interaction with tungsten surfaces, are summarized. A comparison of SEAKMC with molecular dynamics and conventional object kinetic Monte Carlo is demonstrated. Overall, SEAKMC is found to be complimentary to conventional molecular dynamics, especially when the harmonic approximation of transition state theory is accurate. However it is capable of reaching longer time scales than molecular dynamics and it can be used to systematically increase the accuracy of other methods such as object kinetic Monte Carlo. Furthermore, the challenges and potential development directions are also outlined.« less

Multivariate stochastic simulation with subjective multivariate normal distributions

Treesearch

P. J. Ince; J. Buongiorno

1991-01-01

In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal...

Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

EPA Science Inventory

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...

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...

Monte Carlo-based searching as a tool to study carbohydrate structure

USDA-ARS?s Scientific Manuscript database

A torsion angle-based Monte-Carlo searching routine was developed and applied to several carbohydrate modeling problems. The routine was developed as a Unix shell script that calls several programs, which allows it to be interfaced with multiple potential functions and various functions for evaluat...

Verification and Validation of Monte Carlo N-Particle 6 for Computing Gamma Protection Factors

DTIC Science & Technology

2015-03-26

methods for evaluating RPFs, which it used for the subsequent 30 years. These approaches included computational modeling, radioisotopes , and a high...1.2.1. Past Methods of Experimental Evaluation ........................................................ 2 1.2.2. Modeling Efforts...Other Considerations ......................................................................................... 14 2.4. Monte Carlo Methods

Monte Carlo Approach for Reliability Estimations in Generalizability Studies.

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

A Monte Carlo approach is proposed, using the Statistical Analysis System (SAS) programming language, for estimating reliability coefficients in generalizability theory studies. Test scores are generated by a probabilistic model that considers the probability for a person with a given ability score to answer an item with a given difficulty…

OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE ACCUMULATION IN TUNGSTEN

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

Nandipati, Giridhar; Setyawan, Wahyu; Roche, Kenneth J.

2016-09-01

The objective of this work is to understand the accumulation of radiation damage created by primary knock-on atoms (PKAs) of various energies, at 300 K and for a dose rate of 10-4 dpa/s in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.

Exploring Mass Perception with Markov Chain Monte Carlo

ERIC Educational Resources Information Center

Cohen, Andrew L.; Ross, Michael G.

2009-01-01

Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…

Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity

ERIC Educational Resources Information Center

Vaughan, Timothy S.; Berry, Kelly E.

2005-01-01

This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…

Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

DTIC Science & Technology

2009-07-01

simulation. The pilot described in this paper used this two-step approach within a Define, Measure, Analyze, Improve, and Control ( DMAIC ) framework to...networks, BBN, Monte Carlo simulation, DMAIC , Six Sigma, business case 15. NUMBER OF PAGES 35 16. PRICE CODE 17. SECURITY CLASSIFICATION OF

A Workstation Farm Optimized for Monte Carlo Shell Model Calculations : Alphleet

NASA Astrophysics Data System (ADS)

Watanabe, Y.; Shimizu, N.; Haruyama, S.; Honma, M.; Mizusaki, T.; Taketani, A.; Utsuno, Y.; Otsuka, T.

We have built a workstation farm named ``Alphleet" which consists of 140 COMPAQ's Alpha 21264 CPUs, for Monte Carlo Shell Model (MCSM) calculations. It has achieved more than 90 % scalable performance with 140 CPUs when the MCSM calculation with PVM and 61.2 Gflops of LINPACK.

Calculating Remote Sensing Reflectance Uncertainties Using an Instrument Model Propagated Through Atmospheric Correction via Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Karakoylu, E.; Franz, B.

2016-01-01

First attempt at quantifying uncertainties in ocean remote sensing reflectance satellite measurements. Based on 1000 iterations of Monte Carlo. Data source is a SeaWiFS 4-day composite, 2003. The uncertainty is for remote sensing reflectance (Rrs) at 443 nm.

Prediction of Breakthrough Curves for Conservative and Reactive Transport from the Structural Parameters of Highly Heterogeneous Media

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

Hansen, Scott; Haslauer, Claus P.; Cirpka, Olaf A.

2017-01-05

The key points of this presentation were to approach the problem of linking breakthrough curve shape (RP-CTRW transition distribution) to structural parameters from a Monte Carlo approach and to use the Monte Carlo analysis to determine any empirical error

Play It Again: Teaching Statistics with Monte Carlo Simulation

ERIC Educational Resources Information Center

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…

SIMCA T 1.0: A SAS Computer Program for Simulating Computer Adaptive Testing

ERIC Educational Resources Information Center

Raiche, Gilles; Blais, Jean-Guy

2006-01-01

Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…

Continuous-time quantum Monte Carlo impurity solvers

NASA Astrophysics Data System (ADS)

Gull, Emanuel; Werner, Philipp; Fuchs, Sebastian; Surer, Brigitte; Pruschke, Thomas; Troyer, Matthias

2011-04-01

Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states. Program summaryProgram title: dmft Catalogue identifier: AEIL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: ALPS LIBRARY LICENSE version 1.1 No. of lines in distributed program, including test data, etc.: 899 806 No. of bytes in distributed program, including test data, etc.: 32 153 916 Distribution format: tar.gz Programming language: C++ Operating system: The ALPS libraries have been tested on the following platforms and compilers: Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher) MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0) IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers Compaq Tru64 UNIX with Compq C++ Compiler (cxx) SGI IRIX with MIPSpro C++ Compiler (CC) HP-UX with HP C++ Compiler (aCC) Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher) RAM: 10 MB-1 GB Classification: 7.3 External routines: ALPS [1], BLAS/LAPACK, HDF5 Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as representations of quantum dots and molecular conductors and play an increasingly important role in the theory of "correlated electron" materials as auxiliary problems whose solution gives the "dynamical mean field" approximation to the self-energy and local correlation functions. Solution method: Quantum impurity models require a method of solution which provides access to both high and low energy scales and is effective for wide classes of physically realistic models. The continuous-time quantum Monte Carlo algorithms for which we present implementations here meet this challenge. Continuous-time quantum impurity methods are based on partition function expansions of quantum impurity models that are stochastically sampled to all orders using diagrammatic quantum Monte Carlo techniques. For a review of quantum impurity models and their applications and of continuous-time quantum Monte Carlo methods for impurity models we refer the reader to [2]. Additional comments: Use of dmft requires citation of this paper. Use of any ALPS program requires citation of the ALPS [1] paper. Running time: 60 s-8 h per iteration.

Accelerating Monte Carlo simulations with an NVIDIA ® graphics processor

NASA Astrophysics Data System (ADS)

Martinsen, Paul; Blaschke, Johannes; Künnemeyer, Rainer; Jordan, Robert

2009-10-01

Modern graphics cards, commonly used in desktop computers, have evolved beyond a simple interface between processor and display to incorporate sophisticated calculation engines that can be applied to general purpose computing. The Monte Carlo algorithm for modelling photon transport in turbid media has been implemented on an NVIDIA ® 8800 GT graphics card using the CUDA toolkit. The Monte Carlo method relies on following the trajectory of millions of photons through the sample, often taking hours or days to complete. The graphics-processor implementation, processing roughly 110 million scattering events per second, was found to run more than 70 times faster than a similar, single-threaded implementation on a 2.67 GHz desktop computer. Program summaryProgram title: Phoogle-C/Phoogle-G Catalogue identifier: AEEB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEB_v1_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.: 51 264 No. of bytes in distributed program, including test data, etc.: 2 238 805 Distribution format: tar.gz Programming language: C++ Computer: Designed for Intel PCs. Phoogle-G requires a NVIDIA graphics card with support for CUDA 1.1 Operating system: Windows XP Has the code been vectorised or parallelized?: Phoogle-G is written for SIMD architectures RAM: 1 GB Classification: 21.1 External routines: Charles Karney Random number library. Microsoft Foundation Class library. NVIDA CUDA library [1]. Nature of problem: The Monte Carlo technique is an effective algorithm for exploring the propagation of light in turbid media. However, accurate results require tracing the path of many photons within the media. The independence of photons naturally lends the Monte Carlo technique to implementation on parallel architectures. Generally, parallel computing can be expensive, but recent advances in consumer grade graphics cards have opened the possibility of high-performance desktop parallel-computing. Solution method: In this pair of programmes we have implemented the Monte Carlo algorithm described by Prahl et al. [2] for photon transport in infinite scattering media to compare the performance of two readily accessible architectures: a standard desktop PC and a consumer grade graphics card from NVIDIA. Restrictions: The graphics card implementation uses single precision floating point numbers for all calculations. Only photon transport from an isotropic point-source is supported. The graphics-card version has no user interface. The simulation parameters must be set in the source code. The desktop version has a simple user interface; however some properties can only be accessed through an ActiveX client (such as Matlab). Additional comments: The random number library used has a LGPL ( http://www.gnu.org/copyleft/lesser.html) licence. Running time: Runtime can range from minutes to months depending on the number of photons simulated and the optical properties of the medium. References:http://www.nvidia.com/object/cuda_home.html. S. Prahl, M. Keijzer, Sl. Jacques, A. Welch, SPIE Institute Series 5 (1989) 102.

Improved non-destructive method for 90Sr activity determination in aqueous solutions using Monte Carlo simulation.

PubMed

Samardžić, Selena; Milošević, Miodrag; Todorović, Nataša; Lakatoš, Robert

2018-04-04

The development of new methods and improvements of existing methods for the specific activity determination of 90 Sr and other distinct beta emitters has been of considerable interest. The reason for this interest is that the notably small number of methods that are able to meet all the set criteria, such as reliability of the results, measurement uncertainty and time, and minimum production of radioactive waste, as well as applicability to various samples with reference to their nature, geometry and composition. In this paper, two methods for rapid 90 Sr activity determination based on Monte Carlo simulations are used, one for a Si semiconductor detector for beta spectrometric measurements and the other for the Geiger-Muller (GM) ionization probe. To improve the reliability of the measurement results, samples with high and low strontium activity solutions were prepared in the form of dry residues. The results of the proposed methodology were verified with a standard method using a liquid scintillation counter, and notably good agreements are achieved. Copyright © 2018 Elsevier Ltd. All rights reserved.

Monte Carlo study of a 60Co calibration field of the Dosimetry Laboratory Seibersdorf.

PubMed

Hranitzky, C; Stadtmann, H

2007-01-01

The gamma radiation fields of the reference irradiation facility of the Dosimetry Laboratory Seibersdorf with collimated beam geometry are used for calibrating radiation protection dosemeters. A close-to-reality simulation model of the facility including the complex geometry of a 60Co source was set up using the Monte Carlo code MCNP. The goal of this study is to characterise the radionuclide gamma calibration field and resulting air-kerma distributions inside the measurement hall with a total of 20 m in length. For the whole range of source-detector-distances (SDD) along the central beam axis, simulated and measured relative air-kerma values are within +/-0.6%. Influences on the accuracy of the simulation results are investigated, including e.g., source mass density effects or detector volume dependencies. A constant scatter contribution from the lead ring-collimator of approximately 1% and an increasing scatter contribution from the concrete floor for distances above 7 m are identified, resulting in a total air-kerma scatter contribution below 5%, which is in accordance to the ISO 4037-1 recommendations.

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy.

PubMed

Shu, Xiao; Liu, Wenzhong; Zhang, Hao F

2015-10-01

The retinal pigment epithelium (RPE) melanin plays an important role in maintaining normal visual functions. A decrease in the RPE melanin concentration with aging is believed to be associated with several blinding diseases, including age-related macular degeneration. Quantifying the RPE melanin noninvasively is therefore important in evaluating the retinal health and aging conditions. Photoacoustic ophthalmoscopy (PAOM), as an optical absorption-based imaging technology, can potentially be applied to measure variations in the RPE melanin if the relationship between the detected photoacoustic (PA) signal amplitudes and the RPE melanin concentrations can be established. In this work, we tested the feasibility of using PA signals from retinal blood vessels as references to measure RPE melanin variation using Monte Carlo (MC) simulation. The influences from PAOM axial resolution, the depth and diameter of the retinal blood vessel, and the RPE thickness were examined. We proposed a calibration scheme by relating detected PA signals to the RPE melanin concentrations, and we found that the scheme is robust to these tested parameters. This study suggests that PAOM has the capability of quantitatively measuring the RPE melanin in vivo.

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

NASA Astrophysics Data System (ADS)

Shu, Xiao; Liu, Wenzhong; Zhang, Hao F.

2015-10-01

The retinal pigment epithelium (RPE) melanin plays an important role in maintaining normal visual functions. A decrease in the RPE melanin concentration with aging is believed to be associated with several blinding diseases, including age-related macular degeneration. Quantifying the RPE melanin noninvasively is therefore important in evaluating the retinal health and aging conditions. Photoacoustic ophthalmoscopy (PAOM), as an optical absorption-based imaging technology, can potentially be applied to measure variations in the RPE melanin if the relationship between the detected photoacoustic (PA) signal amplitudes and the RPE melanin concentrations can be established. In this work, we tested the feasibility of using PA signals from retinal blood vessels as references to measure RPE melanin variation using Monte Carlo (MC) simulation. The influences from PAOM axial resolution, the depth and diameter of the retinal blood vessel, and the RPE thickness were examined. We proposed a calibration scheme by relating detected PA signals to the RPE melanin concentrations, and we found that the scheme is robust to these tested parameters. This study suggests that PAOM has the capability of quantitatively measuring the RPE melanin in vivo.

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

Analysis of Monte Carlo accelerated iterative methods for sparse linear systems: Analysis of Monte Carlo accelerated iterative methods for sparse linear systems

DOE PAGES

Benzi, Michele; Evans, Thomas M.; Hamilton, Steven P.; ...

2017-03-05

Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.

Monte Carlo and analytical calculations for characterization of gas bremsstrahlung in ILSF insertion devices

NASA Astrophysics Data System (ADS)

Salimi, E.; Rahighi, J.; Sardari, D.; Mahdavi, S. R.; Lamehi Rachti, M.

2014-12-01

Gas bremsstrahlung is generated in high energy electron storage rings through interaction of the electron beam with the residual gas molecules in vacuum chamber. In this paper, Monte Carlo calculation has been performed to evaluate radiation hazard due to gas bremsstrahlung in the Iranian Light Source Facility (ILSF) insertion devices. Shutter/stopper dimensions is determined and dose rate from the photoneutrons via the giant resonance photonuclear reaction which takes place inside the shutter/stopper is also obtained. Some other characteristics of gas bremsstrahlung such as photon fluence, energy spectrum, angular distribution and equivalent dose in tissue equivalent phantom have also been investigated by FLUKA Monte Carlo code.

Finite-size scaling study of the two-dimensional Blume-Capel model

NASA Astrophysics Data System (ADS)

Beale, Paul D.

1986-02-01

The phase diagram of the two-dimensional Blume-Capel model is investigated by using the technique of phenomenological finite-size scaling. The location of the tricritical point and the values of the critical and tricritical exponents are determined. The location of the tricritical point (Tt=0.610+/-0.005, Dt=1.9655+/-0.0010) is well outside the error bars for the value quoted in previous Monte Carlo simulations but in excellent agreement with more recent Monte Carlo renormalization-group results. The values of the critical and tricritical exponents, with the exception of the leading thermal tricritical exponent, are in excellent agreement with previous calculations, conjectured values, and Monte Carlo renormalization-group studies.

Monte Carlo simulation of EAS generated by 10(14) - 10(16) eV protons

NASA Technical Reports Server (NTRS)

Fenyves, E. J.; Yunn, B. C.; Stanev, T.

1985-01-01

Detailed Monte Carlo simulations of extensive air showers to be detected by the Homestake Surface Underground Telescope and other similar detectors located at sea level and mountain altitudes have been performed for 10 to the 14th power to 10 to the 16th power eV primary energies. The results of these Monte Carlo calculations will provide an opportunity to compare the experimental data with different models for the composition and spectra of primaries and for the development of air showers. The results obtained for extensive air showers generated by 10 to the 14th power to 10 to the 16th power eV primary protons are reported.

An analysis on the theory of pulse oximetry by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Fan, Shangchun; Cai, Rui; Xing, Weiwei; Liu, Changting; Chen, Guangfei; Wang, Junfeng

2008-10-01

The pulse oximetry is a kind of electronic instrument that measures the oxygen saturation of arterial blood and pulse rate by non-invasive techniques. It enables prompt recognition of hypoxemia. In a conventional transmittance type pulse oximeter, the absorption of light by oxygenated and reduced hemoglobin is measured at two wavelength 660nm and 940nm. But the accuracy and measuring range of the pulse oximeter can not meet the requirement of clinical application. There are limitations in the theory of pulse oximetry, which is proved by Monte Carlo method. The mean paths are calculated in the Monte Carlo simulation. The results prove that the mean paths are not the same between the different wavelengths.

Monte Carlo study of four dimensional binary hard hypersphere mixtures

NASA Astrophysics Data System (ADS)

Bishop, Marvin; Whitlock, Paula A.

2012-01-01

A multithreaded Monte Carlo code was used to study the properties of binary mixtures of hard hyperspheres in four dimensions. The ratios of the diameters of the hyperspheres examined were 0.4, 0.5, 0.6, and 0.8. Many total densities of the binary mixtures were investigated. The pair correlation functions and the equations of state were determined and compared with other simulation results and theoretical predictions. At lower diameter ratios the pair correlation functions of the mixture agree with the pair correlation function of a one component fluid at an appropriately scaled density. The theoretical results for the equation of state compare well to the Monte Carlo calculations for all but the highest densities studied.

Gutzwiller Monte Carlo approach for a critical dissipative spin model

NASA Astrophysics Data System (ADS)

Casteels, Wim; Wilson, Ryan M.; Wouters, Michiel

2018-06-01

We use the Gutzwiller Monte Carlo approach to simulate the dissipative X Y Z model in the vicinity of a dissipative phase transition. This approach captures classical spatial correlations together with the full on-site quantum behavior while neglecting nonlocal quantum effects. By considering finite two-dimensional lattices of various sizes, we identify a ferromagnetic and two paramagnetic phases, in agreement with earlier studies. The greatly reduced numerical complexity of the Gutzwiller Monte Carlo approach facilitates efficient simulation of relatively large lattice sizes. The inclusion of the spatial correlations allows to capture parts of the phase diagram that are completely missed by the widely applied Gutzwiller decoupling of the density matrix.

A collision history-based approach to Sensitivity/Perturbation calculations in the continuous energy Monte Carlo code SERPENT

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

Giuseppe Palmiotti

In this work, the implementation of a collision history-based approach to sensitivity/perturbation calculations in the Monte Carlo code SERPENT is discussed. The proposed methods allow the calculation of the eects of nuclear data perturbation on several response functions: the eective multiplication factor, reaction rate ratios and bilinear ratios (e.g., eective kinetics parameters). SERPENT results are compared to ERANOS and TSUNAMI Generalized Perturbation Theory calculations for two fast metallic systems and for a PWR pin-cell benchmark. New methods for the calculation of sensitivities to angular scattering distributions are also presented, which adopts fully continuous (in energy and angle) Monte Carlo estimators.

Energy broadening in electron beams: A comparison of existing theories and Monte Carlo simulation

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

Jansen, G.H.; Groves, T.R.; Stickel, W.

1985-01-01

Different theories on the Boersch effect are applied to a simple beam geometry with one crossover in drift space.The results are compared with each other, with Monte Carlo simulations, and with the experiment. The most complete and accurate theory is given by van Leeuwen and Jansen. This theory predicts energy spreads within 10% of the Monte Carlo results for operating conditions usually given in systems with thermionic emission sources. No comprehensive theory, however, of energy broadening in electron guns has yet been presented. Nevertheless, the theory of van Leeuwen and Jansen was found to predict the experimental values by trendmore » and within a factor of 2.« less

Free energy and internal energy of electron-screened plasmas in a modified hypernetted-chain approximation

NASA Astrophysics Data System (ADS)

Perrot, F.

1991-12-01

We report results of Helmholtz-free-energy and internal-energy calculations using the modified hypernetted-chain (MHNC) equation method, in the formulation of Lado, Foiles, and Ashcroft [Phys. Rev. A 28, 2374 (1983)], for a model plasma of ions linearly screened by electrons. The results are compared with HNC calculations (no Bridge term), with variational calculations using a hard-spheres reference system, and with a numerical fit of Monte Carlo simulations.

Electronic Spectra from Molecular Dynamics: A Simple Approach.

DTIC Science & Technology

1983-10-01

82.30.Cr. 33.20K. S2.40.1s The authors provided phototypeset copy for this paper using REFER TlL EON, TOFF On UNIX I ELECTRONIC SPECTRA FROM MOLECULAR...Alamos National Laboratory Los Alamos, NM 87545 I. INTRODUCTION In this paper we show how molecular dynamics can be used in a simple manner to com...could equally use Monte Carlo or explicit integration over coordinates to compute equilibrium electronic absorption bands. How- ever, molecular

An Overview of Importance Splitting for Rare Event Simulation

ERIC Educational Resources Information Center

Morio, Jerome; Pastel, Rudy; Le Gland, Francois

2010-01-01

Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…

Theoretical Grounds for the Propagation of Uncertainties in Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Saracco, Paolo; Pia, Maria Grazia; Batic, Matej

2014-04-01

We introduce a theoretical framework for the calculation of uncertainties affecting observables produced by Monte Carlo particle transport, which derive from uncertainties in physical parameters input into simulation. The theoretical developments are complemented by a heuristic application, which illustrates the method of calculation in a streamlined simulation environment.

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

DTIC Science & Technology

2014-08-24

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering Isaac L. Manuel and Adrian N. Bishop Australian National University and...2 20 + vit , (21) where vit is Gaussian white noise with a random variance. We initialised the filters with the state xi0 = 0.1 for all i ∈ V . This

A Monte Carlo Approach for Adaptive Testing with Content Constraints

ERIC Educational Resources Information Center

Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander

2008-01-01

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…

Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

ERIC Educational Resources Information Center

Gergely, John Robert

2009-01-01

Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…

Estimating Uncertainty in N2O Emissions from US Cropland Soils

USDA-ARS?s Scientific Manuscript database

A Monte Carlo analysis was combined with an empirically-based approach to quantify uncertainties in soil N2O emissions from US croplands estimated with the DAYCENT simulation model. Only a subset of croplands was simulated in the Monte Carlo analysis which was used to infer uncertainties across the ...

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

2017-01-01

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

Variational Approach to Monte Carlo Renormalization Group

NASA Astrophysics Data System (ADS)

Wu, Yantao; Car, Roberto

2017-12-01

We present a Monte Carlo method for computing the renormalized coupling constants and the critical exponents within renormalization theory. The scheme, which derives from a variational principle, overcomes critical slowing down, by means of a bias potential that renders the coarse grained variables uncorrelated. The two-dimensional Ising model is used to illustrate the method.

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

PubMed

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Teaching Markov Chain Monte Carlo: Revealing the Basic Ideas behind the Algorithm

ERIC Educational Resources Information Center

Stewart, Wayne; Stewart, Sepideh

2014-01-01

For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…

Asteroid mass estimation with Markov-chain Monte Carlo

NASA Astrophysics Data System (ADS)

Siltala, L.; Granvik, M.

2017-09-01

We have developed a new Markov-chain Monte Carlo-based algorithm for asteroid mass estimation based on mutual encounters and tested it for several different asteroids. Our results are in line with previous literature values but suggest that uncertainties of prior estimates may be misleading as a consequence of using linearized methods.

A Monte Carlo Evaluation of Estimated Parameters of Five Shrinkage Estimate Formuli.

ERIC Educational Resources Information Center

Newman, Isadore; And Others

1979-01-01

A Monte Carlo simulation was employed to determine the accuracy with which the shrinkage in R squared can be estimated by five different shrinkage formulas. The study dealt with the use of shrinkage formulas for various sample sizes, different R squared values, and different degrees of multicollinearity. (Author/JKS)

Scaling GDL for Multi-cores to Process Planck HFI Beams Monte Carlo on HPC

NASA Astrophysics Data System (ADS)

Coulais, A.; Schellens, M.; Duvert, G.; Park, J.; Arabas, S.; Erard, S.; Roudier, G.; Hivon, E.; Mottet, S.; Laurent, B.; Pinter, M.; Kasradze, N.; Ayad, M.

2014-05-01

After reviewing the majors progress done in GDL -now in 0.9.4- on performance and plotting capabilities since ADASS XXI paper (Coulais et al. 2012), we detail how a large code for Planck HFI beams Monte Carlo was successfully transposed from IDL to GDL on HPC.

QUANTIFYING AGGREGATE CHLORPYRIFOS EXPOSURE AND DOSE TO CHILDREN USING A PHYSICALLY-BASED TWO-STAGE MONTE CARLO PROBABILISTIC MODEL

EPA Science Inventory

To help address the Food Quality Protection Act of 1996, a physically-based, two-stage Monte Carlo probabilistic model has been developed to quantify and analyze aggregate exposure and dose to pesticides via multiple routes and pathways. To illustrate model capabilities and ide...

Monte Carlo simulation models of breeding-population advancement.

Treesearch

J.N. King; G.R. Johnson

1993-01-01

Five generations of population improvement were modeled using Monte Carlo simulations. The model was designed to address questions that are important to the development of an advanced generation breeding population. Specifically we addressed the effects on both gain and effective population size of different mating schemes when creating a recombinant population for...

Monte Carlo chord length sampling for d-dimensional Markov binary mixtures

NASA Astrophysics Data System (ADS)

Larmier, Coline; Lam, Adam; Brantley, Patrick; Malvagi, Fausto; Palmer, Todd; Zoia, Andrea

2018-01-01

The Chord Length Sampling (CLS) algorithm is a powerful Monte Carlo method that models the effects of stochastic media on particle transport by generating on-the-fly the material interfaces seen by the random walkers during their trajectories. This annealed disorder approach, which formally consists of solving the approximate Levermore-Pomraning equations for linear particle transport, enables a considerable speed-up with respect to transport in quenched disorder, where ensemble-averaging of the Boltzmann equation with respect to all possible realizations is needed. However, CLS intrinsically neglects the correlations induced by the spatial disorder, so that the accuracy of the solutions obtained by using this algorithm must be carefully verified with respect to reference solutions based on quenched disorder realizations. When the disorder is described by Markov mixing statistics, such comparisons have been attempted so far only for one-dimensional geometries, of the rod or slab type. In this work we extend these results to Markov media in two-dimensional (extruded) and three-dimensional geometries, by revisiting the classical set of benchmark configurations originally proposed by Adams, Larsen and Pomraning [1] and extended by Brantley [2]. In particular, we examine the discrepancies between CLS and reference solutions for scalar particle flux and transmission/reflection coefficients as a function of the material properties of the benchmark specifications and of the system dimensionality.

Monte Carlo chord length sampling for d-dimensional Markov binary mixtures

DOE PAGES

Larmier, Coline; Lam, Adam; Brantley, Patrick; ...

2017-09-27

The Chord Length Sampling (CLS) algorithm is a powerful Monte Carlo method that models the effects of stochastic media on particle transport by generating on-the-fly the material interfaces seen by the random walkers during their trajectories. This annealed disorder approach, which formally consists of solving the approximate Levermore–Pomraning equations for linear particle transport, enables a considerable speed-up with respect to transport in quenched disorder, where ensemble-averaging of the Boltzmann equation with respect to all possible realizations is needed. However, CLS intrinsically neglects the correlations induced by the spatial disorder, so that the accuracy of the solutions obtained by using thismore » algorithm must be carefully verified with respect to reference solutions based on quenched disorder realizations. When the disorder is described by Markov mixing statistics, such comparisons have been attempted so far only for one-dimensional geometries, of the rod or slab type. In this work we extend these results to Markov media in two-dimensional (extruded) and three-dimensional geometries, by revisiting the classical set of benchmark configurations originally proposed by Adams, Larsen and Pomraning and extended by Brantley. In particular, we examine the discrepancies between CLS and reference solutions for scalar particle flux and transmission/reflection coefficients as a function of the material properties of the benchmark specifications and of the system dimensionality.« less

Monte Carlo chord length sampling for d-dimensional Markov binary mixtures

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

Larmier, Coline; Lam, Adam; Brantley, Patrick

The Chord Length Sampling (CLS) algorithm is a powerful Monte Carlo method that models the effects of stochastic media on particle transport by generating on-the-fly the material interfaces seen by the random walkers during their trajectories. This annealed disorder approach, which formally consists of solving the approximate Levermore–Pomraning equations for linear particle transport, enables a considerable speed-up with respect to transport in quenched disorder, where ensemble-averaging of the Boltzmann equation with respect to all possible realizations is needed. However, CLS intrinsically neglects the correlations induced by the spatial disorder, so that the accuracy of the solutions obtained by using thismore » algorithm must be carefully verified with respect to reference solutions based on quenched disorder realizations. When the disorder is described by Markov mixing statistics, such comparisons have been attempted so far only for one-dimensional geometries, of the rod or slab type. In this work we extend these results to Markov media in two-dimensional (extruded) and three-dimensional geometries, by revisiting the classical set of benchmark configurations originally proposed by Adams, Larsen and Pomraning and extended by Brantley. In particular, we examine the discrepancies between CLS and reference solutions for scalar particle flux and transmission/reflection coefficients as a function of the material properties of the benchmark specifications and of the system dimensionality.« less

A Novel Implementation of Massively Parallel Three Dimensional Monte Carlo Radiation Transport

NASA Astrophysics Data System (ADS)

Robinson, P. B.; Peterson, J. D. L.

2005-12-01

The goal of our summer project was to implement the difference formulation for radiation transport into Cosmos++, a multidimensional, massively parallel, magneto hydrodynamics code for astrophysical applications (Peter Anninos - AX). The difference formulation is a new method for Symbolic Implicit Monte Carlo thermal transport (Brooks and Szöke - PAT). Formerly, simultaneous implementation of fully implicit Monte Carlo radiation transport in multiple dimensions on multiple processors had not been convincingly demonstrated. We found that a combination of the difference formulation and the inherent structure of Cosmos++ makes such an implementation both accurate and straightforward. We developed a "nearly nearest neighbor physics" technique to allow each processor to work independently, even with a fully implicit code. This technique coupled with the increased accuracy of an implicit Monte Carlo solution and the efficiency of parallel computing systems allows us to demonstrate the possibility of massively parallel thermal transport. This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48

Experimental and Monte Carlo evaluation of Eclipse treatment planning system for effects on dose distribution of the hip prostheses

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

Çatlı, Serap, E-mail: serapcatli@hotmail.com; Tanır, Güneş

2013-10-01

The present study aimed to investigate the effects of titanium, titanium alloy, and stainless steel hip prostheses on dose distribution based on the Monte Carlo simulation method, as well as the accuracy of the Eclipse treatment planning system (TPS) at 6 and 18 MV photon energies. In the present study the pencil beam convolution (PBC) method implemented in the Eclipse TPS was compared to the Monte Carlo method and ionization chamber measurements. The present findings show that if high-Z material is used in prosthesis, large dose changes can occur due to scattering. The variance in dose observed in the presentmore » study was dependent on material type, density, and atomic number, as well as photon energy; as photon energy increased back scattering decreased. The dose perturbation effect of hip prostheses was significant and could not be predicted accurately by the PBC method for hip prostheses. The findings show that for accurate dose calculation the Monte Carlo-based TPS should be used in patients with hip prostheses.« less

Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Donzelli, Mattia; Bräuer-Krisch, Elke; Oelfke, Uwe; Wilkens, Jan J.; Bartzsch, Stefan

2018-02-01

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.

Determination of correction factors in beta radiation beams using Monte Carlo method.

PubMed

Polo, Ivón Oramas; Santos, William de Souza; Caldas, Linda V E

2018-06-15

The absorbed dose rate is the main characterization quantity for beta radiation. The extrapolation chamber is considered the primary standard instrument. To determine absorbed dose rates in beta radiation beams, it is necessary to establish several correction factors. In this work, the correction factors for the backscatter due to the collecting electrode and to the guard ring, and the correction factor for Bremsstrahlung in beta secondary standard radiation beams are presented. For this purpose, the Monte Carlo method was applied. The results obtained are considered acceptable, and they agree within the uncertainties. The differences between the backscatter factors determined by the Monte Carlo method and those of the ISO standard were 0.6%, 0.9% and 2.04% for 90 Sr/ 90 Y, 85 Kr and 147 Pm sources respectively. The differences between the Bremsstrahlung factors determined by the Monte Carlo method and those of the ISO were 0.25%, 0.6% and 1% for 90 Sr/ 90 Y, 85 Kr and 147 Pm sources respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Monte Carlo Methodology Serves Up a Software Success

NASA Technical Reports Server (NTRS)

2003-01-01

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Kinetic Activation-Relaxation Technique and Self-Evolving Atomistic Kinetic Monte Carlo: Comparison of on-the-fly kinetic Monte Carlo algorithms

DOE PAGES

Beland, Laurent Karim; Osetskiy, Yury N.; Stoller, Roger E.; ...

2015-02-07

Here, we present a comparison of the Kinetic Activation–Relaxation Technique (k-ART) and the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC), two off-lattice, on-the-fly Kinetic Monte Carlo (KMC) techniques that were recently used to solve several materials science problems. We show that if the initial displacements are localized the dimer method and the Activation–Relaxation Technique nouveau provide similar performance. We also show that k-ART and SEAKMC, although based on different approximations, are in agreement with each other, as demonstrated by the examples of 50 vacancies in a 1950-atom Fe box and of interstitial loops in 16,000-atom boxes. Generally speaking, k-ART’s treatment ofmore » geometry and flickers is more flexible, e.g. it can handle amorphous systems, and rigorous than SEAKMC’s, while the later’s concept of active volumes permits a significant speedup of simulations for the systems under consideration and therefore allows investigations of processes requiring large systems that are not accessible if not localizing calculations.« less

Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields.

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

Armas-Perez, Julio C.; Londono-Hurtado, Alejandro; Guzman, Orlando

2015-07-27

A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystalmore » droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.« less

Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields

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

Armas-Pérez, Julio C.; Londono-Hurtado, Alejandro; Guzmán, Orlando

2015-07-28

A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystalmore » droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.« less

Levofloxacin Penetration into Epithelial Lining Fluid as Determined by Population Pharmacokinetic Modeling and Monte Carlo Simulation

PubMed Central

Drusano, G. L.; Preston, S. L.; Gotfried, M. H.; Danziger, L. H.; Rodvold, K. A.

2002-01-01

Levofloxacin was administered orally to steady state to volunteers randomly in doses of 500 and 750 mg. Plasma and epithelial lining fluid (ELF) samples were obtained at 4, 12, and 24 h after the final dose. All data were comodeled in a population pharmacokinetic analysis employing BigNPEM. Penetration was evaluated from the population mean parameter vector values and from the results of a 1,000-subject Monte Carlo simulation. Evaluation from the population mean values demonstrated a penetration ratio (ELF/plasma) of 1.16. The Monte Carlo simulation provided a measure of dispersion, demonstrating a mean ratio of 3.18, with a median of 1.43 and a 95% confidence interval of 0.14 to 19.1. Population analysis with Monte Carlo simulation provides the best and least-biased estimate of penetration. It also demonstrates clearly that we can expect differences in penetration between patients. This analysis did not deal with inflammation, as it was performed in volunteers. The influence of lung pathology on penetration needs to be examined. PMID:11796385

Monte Carlo analyses of TRX slightly enriched uranium-H/sub 2/O critical experiments with ENDF/B-IV and related data sets (AWBA Development Program)

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

Hardy, J. Jr.

1977-12-01

Four H/sub 2/O-moderated, slightly-enriched-uranium critical experiments were analyzed by Monte Carlo methods with ENDF/B-IV data. These were simple metal-rod lattices comprising Cross Section Evaluation Working Group thermal reactor benchmarks TRX-1 through TRX-4. Generally good agreement with experiment was obtained for calculated integral parameters: the epi-thermal/thermal ratio of U238 capture (rho/sup 28/) and of U235 fission (delta/sup 25/), the ratio of U238 capture to U235 fission (CR*), and the ratio of U238 fission to U235 fission (delta/sup 28/). Full-core Monte Carlo calculations for two lattices showed good agreement with cell Monte Carlo-plus-multigroup P/sub l/ leakage corrections. Newly measured parameters for themore » low energy resonances of U238 significantly improved rho/sup 28/. In comparison with other CSEWG analyses, the strong correlation between K/sub eff/ and rho/sup 28/ suggests that U238 resonance capture is the major problem encountered in analyzing these lattices.« less

A novel Kinetic Monte Carlo algorithm for Non-Equilibrium Simulations

NASA Astrophysics Data System (ADS)

Jha, Prateek; Kuzovkov, Vladimir; Grzybowski, Bartosz; Olvera de La Cruz, Monica

2012-02-01

We have developed an off-lattice kinetic Monte Carlo simulation scheme for reaction-diffusion problems in soft matter systems. The definition of transition probabilities in the Monte Carlo scheme are taken identical to the transition rates in a renormalized master equation of the diffusion process and match that of the Glauber dynamics of Ising model. Our scheme provides several advantages over the Brownian dynamics technique for non-equilibrium simulations. Since particle displacements are accepted/rejected in a Monte Carlo fashion as opposed to moving particles following a stochastic equation of motion, nonphysical movements (e.g., violation of a hard core assumption) are not possible (these moves have zero acceptance). Further, the absence of a stochastic ``noise'' term resolves the computational difficulties associated with generating statistically independent trajectories with definitive mean properties. Finally, since the timestep is independent of the magnitude of the interaction forces, much longer time-steps can be employed than Brownian dynamics. We discuss the applications of this scheme for dynamic self-assembly of photo-switchable nanoparticles and dynamical problems in polymeric systems.

Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs

DOE PAGES

Bergmann, Ryan M.; Rowland, Kelly L.; Radnović, Nikola; ...

2017-05-01

In this companion paper to "Algorithmic Choices in WARP - A Framework for Continuous Energy Monte Carlo Neutron Transport in General 3D Geometries on GPUs" (doi:10.1016/j.anucene.2014.10.039), the WARP Monte Carlo neutron transport framework for graphics processing units (GPUs) is benchmarked against production-level central processing unit (CPU) Monte Carlo neutron transport codes for both performance and accuracy. We compare neutron flux spectra, multiplication factors, runtimes, speedup factors, and costs of various GPU and CPU platforms running either WARP, Serpent 2.1.24, or MCNP 6.1. WARP compares well with the results of the production-level codes, and it is shown that on the newestmore » hardware considered, GPU platforms running WARP are between 0.8 to 7.6 times as fast as CPU platforms running production codes. Also, the GPU platforms running WARP were between 15% and 50% as expensive to purchase and between 80% to 90% as expensive to operate as equivalent CPU platforms performing at an equal simulation rate.« less

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

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

In this paper, we have implemented a new high-order low-order (HOLO) algorithm for solving thermal radiative transfer problems. The low-order (LO) system is based on the spatial and angular moments of the transport equation and a linear-discontinuous finite-element spatial representation, producing equations similar to the standard S 2 equations. The LO solver is fully implicit in time and efficiently resolves the nonlinear temperature dependence at each time step. The high-order (HO) solver utilizes exponentially convergent Monte Carlo (ECMC) to give a globally accurate solution for the angular intensity to a fixed-source pure-absorber transport problem. This global solution is used tomore » compute consistency terms, which require the HO and LO solutions to converge toward the same solution. The use of ECMC allows for the efficient reduction of statistical noise in the Monte Carlo solution, reducing inaccuracies introduced through the LO consistency terms. Finally, we compare results with an implicit Monte Carlo code for one-dimensional gray test problems and demonstrate the efficiency of ECMC over standard Monte Carlo in this HOLO algorithm.« less

A Modified Monte Carlo Method for Carrier Transport in Germanium, Free of Isotropic Rates

NASA Astrophysics Data System (ADS)

Sundqvist, Kyle

2010-03-01

We present a new method for carrier transport simulation, relevant for high-purity germanium < 100 > at a temperature of 40 mK. In this system, the scattering of electrons and holes is dominated by spontaneous phonon emission. Free carriers are always out of equilibrium with the lattice. We must also properly account for directional effects due to band structure, but there are many cautions in the literature about treating germanium in particular. These objections arise because the germanium electron system is anisotropic to an extreme degree, while standard Monte Carlo algorithms maintain a reliance on isotropic, integrated rates. We re-examine Fermi's Golden Rule to produce a Monte Carlo method free of isotropic rates. Traditional Monte Carlo codes implement particle scattering based on an isotropically averaged rate, followed by a separate selection of the particle's final state via a momentum-dependent probability. In our method, the kernel of Fermi's Golden Rule produces analytical, bivariate rates which allow for the simultaneous choice of scatter and final state selection. Energy and momentum are automatically conserved. We compare our results to experimental data.

Geant4 hadronic physics for space radiation environment.

PubMed

Ivantchenko, Anton V; Ivanchenko, Vladimir N; Molina, Jose-Manuel Quesada; Incerti, Sebastien L

2012-01-01

To test and to develop Geant4 (Geometry And Tracking version 4) Monte Carlo hadronic models with focus on applications in a space radiation environment. The Monte Carlo simulations have been performed using the Geant4 toolkit. Binary (BIC), its extension for incident light ions (BIC-ion) and Bertini (BERT) cascades were used as main Monte Carlo generators. For comparisons purposes, some other models were tested too. The hadronic testing suite has been used as a primary tool for model development and validation against experimental data. The Geant4 pre-compound (PRECO) and de-excitation (DEE) models were revised and improved. Proton, neutron, pion, and ion nuclear interactions were simulated with the recent version of Geant4 9.4 and were compared with experimental data from thin and thick target experiments. The Geant4 toolkit offers a large set of models allowing effective simulation of interactions of particles with matter. We have tested different Monte Carlo generators with our hadronic testing suite and accordingly we can propose an optimal configuration of Geant4 models for the simulation of the space radiation environment.

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

PubMed

Badal, Andreu; Badano, Aldo

2009-11-01

It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDATM programming model (NVIDIA Corporation, Santa Clara, CA). An outline of the new code and a sample x-ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.

A New Monte Carlo Method for Estimating Marginal Likelihoods.

PubMed

Wang, Yu-Bo; Chen, Ming-Hui; Kuo, Lynn; Lewis, Paul O

2018-06-01

Evaluating the marginal likelihood in Bayesian analysis is essential for model selection. Estimators based on a single Markov chain Monte Carlo sample from the posterior distribution include the harmonic mean estimator and the inflated density ratio estimator. We propose a new class of Monte Carlo estimators based on this single Markov chain Monte Carlo sample. This class can be thought of as a generalization of the harmonic mean and inflated density ratio estimators using a partition weighted kernel (likelihood times prior). We show that our estimator is consistent and has better theoretical properties than the harmonic mean and inflated density ratio estimators. In addition, we provide guidelines on choosing optimal weights. Simulation studies were conducted to examine the empirical performance of the proposed estimator. We further demonstrate the desirable features of the proposed estimator with two real data sets: one is from a prostate cancer study using an ordinal probit regression model with latent variables; the other is for the power prior construction from two Eastern Cooperative Oncology Group phase III clinical trials using the cure rate survival model with similar objectives.

Chemical accuracy from quantum Monte Carlo for the benzene dimer.

PubMed

Azadi, Sam; Cohen, R E

2015-09-14

We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of -2.3(4) and -2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is -2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.

Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs

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

Bergmann, Ryan M.; Rowland, Kelly L.; Radnović, Nikola

In this companion paper to "Algorithmic Choices in WARP - A Framework for Continuous Energy Monte Carlo Neutron Transport in General 3D Geometries on GPUs" (doi:10.1016/j.anucene.2014.10.039), the WARP Monte Carlo neutron transport framework for graphics processing units (GPUs) is benchmarked against production-level central processing unit (CPU) Monte Carlo neutron transport codes for both performance and accuracy. We compare neutron flux spectra, multiplication factors, runtimes, speedup factors, and costs of various GPU and CPU platforms running either WARP, Serpent 2.1.24, or MCNP 6.1. WARP compares well with the results of the production-level codes, and it is shown that on the newestmore » hardware considered, GPU platforms running WARP are between 0.8 to 7.6 times as fast as CPU platforms running production codes. Also, the GPU platforms running WARP were between 15% and 50% as expensive to purchase and between 80% to 90% as expensive to operate as equivalent CPU platforms performing at an equal simulation rate.« less

Performance of quantum Monte Carlo for calculating molecular bond lengths

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

Cleland, Deidre M., E-mail: deidre.cleland@csiro.au; Per, Manolo C., E-mail: manolo.per@csiro.au

2016-03-28

This work investigates the accuracy of real-space quantum Monte Carlo (QMC) methods for calculating molecular geometries. We present the equilibrium bond lengths of a test set of 30 diatomic molecules calculated using variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods. The effect of different trial wavefunctions is investigated using single determinants constructed from Hartree-Fock (HF) and Density Functional Theory (DFT) orbitals with LDA, PBE, and B3LYP functionals, as well as small multi-configurational self-consistent field (MCSCF) multi-determinant expansions. When compared to experimental geometries, all DMC methods exhibit smaller mean-absolute deviations (MADs) than those given by HF, DFT, and MCSCF.more » The most accurate MAD of 3 ± 2 × 10{sup −3} Å is achieved using DMC with a small multi-determinant expansion. However, the more computationally efficient multi-determinant VMC method has a similar MAD of only 4.0 ± 0.9 × 10{sup −3} Å, suggesting that QMC forces calculated from the relatively simple VMC algorithm may often be sufficient for accurate molecular geometries.« less

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Calculation of absorbed fractions to human skeletal tissues due to alpha particles using the Monte Carlo and 3-D chord-based transport techniques.

PubMed

Hunt, J G; Watchman, C J; Bolch, W E

2007-01-01

Absorbed fraction (AF) calculations to the human skeletal tissues due to alpha particles are of interest to the internal dosimetry of occupationally exposed workers and members of the public. The transport of alpha particles through the skeletal tissue is complicated by the detailed and complex microscopic histology of the skeleton. In this study, both Monte Carlo and chord-based techniques were applied to the transport of alpha particles through 3-D microCT images of the skeletal microstructure of trabecular spongiosa. The Monte Carlo program used was 'Visual Monte Carlo--VMC'. VMC simulates the emission of the alpha particles and their subsequent energy deposition track. The second method applied to alpha transport is the chord-based technique, which randomly generates chord lengths across bone trabeculae and the marrow cavities via alternate and uniform sampling of their cumulative density functions. This paper compares the AF of energy to two radiosensitive skeletal tissues, active marrow and shallow active marrow, obtained with these two techniques.

Towards predicting the encoding capability of MR fingerprinting sequences.

PubMed

Sommer, K; Amthor, T; Doneva, M; Koken, P; Meineke, J; Börnert, P

2017-09-01

Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance fingerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To find such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different flip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

Gray: a ray tracing-based Monte Carlo simulator for PET

NASA Astrophysics Data System (ADS)

Freese, David L.; Olcott, Peter D.; Buss, Samuel R.; Levin, Craig S.

2018-05-01

Monte Carlo simulation software plays a critical role in PET system design. Performing complex, repeated Monte Carlo simulations can be computationally prohibitive, as even a single simulation can require a large amount of time and a computing cluster to complete. Here we introduce Gray, a Monte Carlo simulation software for PET systems. Gray exploits ray tracing methods used in the computer graphics community to greatly accelerate simulations of PET systems with complex geometries. We demonstrate the implementation of models for positron range, annihilation acolinearity, photoelectric absorption, Compton scatter, and Rayleigh scatter. For validation, we simulate the GATE PET benchmark, and compare energy, distribution of hits, coincidences, and run time. We show a speedup using Gray, compared to GATE for the same simulation, while demonstrating nearly identical results. We additionally simulate the Siemens Biograph mCT system with both the NEMA NU-2 scatter phantom and sensitivity phantom. We estimate the total sensitivity within % when accounting for differences in peak NECR. We also estimate the peak NECR to be kcps, or within % of published experimental data. The activity concentration of the peak is also estimated within 1.3%.

The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations

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

Sellier, J.M., E-mail: jeanmichel.sellier@parallel.bas.bg; Dimov, I.

2014-09-15

The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practicallymore » unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.« less

Present Status and Extensions of the Monte Carlo Performance Benchmark

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Petrovic, Bojan; Martin, William R.

2014-06-01

The NEA Monte Carlo Performance benchmark started in 2011 aiming to monitor over the years the abilities to perform a full-size Monte Carlo reactor core calculation with a detailed power production for each fuel pin with axial distribution. This paper gives an overview of the contributed results thus far. It shows that reaching a statistical accuracy of 1 % for most of the small fuel zones requires about 100 billion neutron histories. The efficiency of parallel execution of Monte Carlo codes on a large number of processor cores shows clear limitations for computer clusters with common type computer nodes. However, using true supercomputers the speedup of parallel calculations is increasing up to large numbers of processor cores. More experience is needed from calculations on true supercomputers using large numbers of processors in order to predict if the requested calculations can be done in a short time. As the specifications of the reactor geometry for this benchmark test are well suited for further investigations of full-core Monte Carlo calculations and a need is felt for testing other issues than its computational performance, proposals are presented for extending the benchmark to a suite of benchmark problems for evaluating fission source convergence for a system with a high dominance ratio, for coupling with thermal-hydraulics calculations to evaluate the use of different temperatures and coolant densities and to study the correctness and effectiveness of burnup calculations. Moreover, other contemporary proposals for a full-core calculation with realistic geometry and material composition will be discussed.

Monte Carlo algorithms for Brownian phylogenetic models.

PubMed

Horvilleur, Benjamin; Lartillot, Nicolas

2014-11-01

Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Obtaining identical results with double precision global accuracy on different numbers of processors in parallel particle Monte Carlo simulations

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

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Brunner, Thomas A.; Gentile, Nicholas A.

2013-10-15

We describe and compare different approaches for achieving numerical reproducibility in photon Monte Carlo simulations. Reproducibility is desirable for code verification, testing, and debugging. Parallelism creates a unique problem for achieving reproducibility in Monte Carlo simulations because it changes the order in which values are summed. This is a numerical problem because double precision arithmetic is not associative. Parallel Monte Carlo, both domain replicated and decomposed simulations, will run their particles in a different order during different runs of the same simulation because the non-reproducibility of communication between processors. In addition, runs of the same simulation using different domain decompositionsmore » will also result in particles being simulated in a different order. In [1], a way of eliminating non-associative accumulations using integer tallies was described. This approach successfully achieves reproducibility at the cost of lost accuracy by rounding double precision numbers to fewer significant digits. This integer approach, and other extended and reduced precision reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. Non-arbitrary precision approaches require a varying degree of rounding to achieve reproducibility. For the problems investigated in this work double precision global accuracy was achievable by using 100 bits of precision or greater on all unordered sums which where subsequently rounded to double precision at the end of every time-step.« less

SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations

NASA Astrophysics Data System (ADS)

Baes, M.; Camps, P.

2015-09-01

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.

A Monte Carlo method using octree structure in photon and electron transport

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

Ogawa, K.; Maeda, S.

Most of the early Monte Carlo calculations in medical physics were used to calculate absorbed dose distributions, and detector responses and efficiencies. Recently, data acquisition in Single Photon Emission CT (SPECT) has been simulated by a Monte Carlo method to evaluate scatter photons generated in a human body and a collimator. Monte Carlo simulations in SPECT data acquisition are generally based on the transport of photons only because the photons being simulated are low energy, and therefore the bremsstrahlung productions by the electrons generated are negligible. Since the transport calculation of photons without electrons is much simpler than that withmore » electrons, it is possible to accomplish the high-speed simulation in a simple object with one medium. Here, object description is important in performing the photon and/or electron transport using a Monte Carlo method efficiently. The authors propose a new description method using an octree representation of an object. Thus even if the boundaries of each medium are represented accurately, high-speed calculation of photon transport can be accomplished because the number of voxels is much fewer than that of the voxel-based approach which represents an object by a union of the voxels of the same size. This Monte Carlo code using the octree representation of an object first establishes the simulation geometry by reading octree string, which is produced by forming an octree structure from a set of serial sections for the object before the simulation; then it transports photons in the geometry. Using the code, if the user just prepares a set of serial sections for the object in which he or she wants to simulate photon trajectories, he or she can perform the simulation automatically using the suboptimal geometry simplified by the octree representation without forming the optimal geometry by handwriting.« less

SU-E-T-586: Field Size Dependence of Output Factor for Uniform Scanning Proton Beams: A Comparison of TPS Calculation, Measurement and Monte Carlo Simulation

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

Zheng, Y; Singh, H; Islam, M

2014-06-01

Purpose: Output dependence on field size for uniform scanning beams, and the accuracy of treatment planning system (TPS) calculation are not well studied. The purpose of this work is to investigate the dependence of output on field size for uniform scanning beams and compare it among TPS calculation, measurements and Monte Carlo simulations. Methods: Field size dependence was studied using various field sizes between 2.5 cm diameter to 10 cm diameter. The field size factor was studied for a number of proton range and modulation combinations based on output at the center of spread out Bragg peak normalized to amore » 10 cm diameter field. Three methods were used and compared in this study: 1) TPS calculation, 2) ionization chamber measurement, and 3) Monte Carlos simulation. The XiO TPS (Electa, St. Louis) was used to calculate the output factor using a pencil beam algorithm; a pinpoint ionization chamber was used for measurements; and the Fluka code was used for Monte Carlo simulations. Results: The field size factor varied with proton beam parameters, such as range, modulation, and calibration depth, and could decrease over 10% from a 10 cm to 3 cm diameter field for a large range proton beam. The XiO TPS predicted the field size factor relatively well at large field size, but could differ from measurements by 5% or more for small field and large range beams. Monte Carlo simulations predicted the field size factor within 1.5% of measurements. Conclusion: Output factor can vary largely with field size, and needs to be accounted for accurate proton beam delivery. This is especially important for small field beams such as in stereotactic proton therapy, where the field size dependence is large and TPS calculation is inaccurate. Measurements or Monte Carlo simulations are recommended for output determination for such cases.« less

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

PubMed Central

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2018-01-01

The goal of this study is to develop a generalized source model (GSM) for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology. PMID:28079526

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-171: Evaluation of the Analytical Anisotropic Algorithm in a Small Finger Joint Phantom Using Monte Carlo Simulation

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

Chow, J; Owrangi, A; Jiang, R

2014-06-01

Purpose: This study investigated the performance of the anisotropic analytical algorithm (AAA) in dose calculation in radiotherapy concerning a small finger joint. Monte Carlo simulation (EGSnrc code) was used in this dosimetric evaluation. Methods: Heterogeneous finger joint phantom containing a vertical water layer (bone joint or cartilage) sandwiched by two bones with dimension 2 × 2 × 2 cm{sup 3} was irradiated by the 6 MV photon beams (field size = 4 × 4 cm{sup 2}). The central beam axis was along the length of the bone joint and the isocenter was set to the center of the joint. Themore » joint width and beam angle were varied from 0.5–2 mm and 0°–15°, respectively. Depth doses were calculated using the AAA and DOSXYZnrc. For dosimetric comparison and normalization, dose calculations were repeated in water phantom using the same beam geometry. Results: Our AAA and Monte Carlo results showed that the AAA underestimated the joint doses by 10%–20%, and could not predict joint dose variation with changes of joint width and beam angle. The calculated bone dose enhancement for the AAA was lower than Monte Carlo and the depth of maximum dose for the phantom was smaller than that for the water phantom. From Monte Carlo results, there was a decrease of joint dose as its width increased. This reflected the smaller the joint width, the more the bone scatter contributed to the depth dose. Moreover, the joint dose was found slightly decreased with an increase of beam angle. Conclusion: The AAA could not handle variations of joint dose well with changes of joint width and beam angle based on our finger joint phantom. Monte Carlo results showed that the joint dose decreased with increase of joint width and beam angle. This dosimetry comparison should be useful to radiation staff in radiotherapy related to small bone joint.« less

Using Static Percentiles of AE9/AP9 to Approximate Dynamic Monte Carlo Runs for Radiation Analysis of Spiral Transfer Orbits

NASA Astrophysics Data System (ADS)

Kwan, Betty P.; O'Brien, T. Paul

2015-06-01

The Aerospace Corporation performed a study to determine whether static percentiles of AE9/AP9 can be used to approximate dynamic Monte Carlo runs for radiation analysis of spiral transfer orbits. Solar panel degradation is a major concern for solar-electric propulsion because solar-electric propulsion depends on the power output of the solar panel. Different spiral trajectories have different radiation environments that could lead to solar panel degradation. Because the spiral transfer orbits only last weeks to months, an average environment does not adequately address the possible transient enhancements of the radiation environment that must be accounted for in optimizing the transfer orbit trajectory. Therefore, to optimize the trajectory, an ensemble of Monte Carlo simulations of AE9/AP9 would normally be run for every spiral trajectory to determine the 95th percentile radiation environment. To avoid performing lengthy Monte Carlo dynamic simulations for every candidate spiral trajectory in the optimization, we found a static percentile that would be an accurate representation of the full Monte Carlo simulation for a representative set of spiral trajectories. For 3 LEO to GEO and 1 LEO to MEO trajectories, a static 90th percentile AP9 is a good approximation of the 95th percentile fluence with dynamics for 4-10 MeV protons, and a static 80th percentile AE9 is a good approximation of the 95th percentile fluence with dynamics for 0.5-2 MeV electrons. While the specific percentiles chosen cannot necessarily be used in general for other orbit trade studies, the concept of determining a static percentile as a quick approximation to a full Monte Carlo ensemble of simulations can likely be applied to other orbit trade studies. We expect the static percentile to depend on the region of space traversed, the mission duration, and the radiation effect considered.

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

NASA Astrophysics Data System (ADS)

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2017-03-01

The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.

Accurate Monte Carlo simulations for nozzle design, commissioning and quality assurance for a proton radiation therapy facility.

PubMed

Paganetti, H; Jiang, H; Lee, S Y; Kooy, H M

2004-07-01

Monte Carlo dosimetry calculations are essential methods in radiation therapy. To take full advantage of this tool, the beam delivery system has to be simulated in detail and the initial beam parameters have to be known accurately. The modeling of the beam delivery system itself opens various areas where Monte Carlo calculations prove extremely helpful, such as for design and commissioning of a therapy facility as well as for quality assurance verification. The gantry treatment nozzles at the Northeast Proton Therapy Center (NPTC) at Massachusetts General Hospital (MGH) were modeled in detail using the GEANT4.5.2 Monte Carlo code. For this purpose, various novel solutions for simulating irregular shaped objects in the beam path, like contoured scatterers, patient apertures or patient compensators, were found. The four-dimensional, in time and space, simulation of moving parts, such as the modulator wheel, was implemented. Further, the appropriate physics models and cross sections for proton therapy applications were defined. We present comparisons between measured data and simulations. These show that by modeling the treatment nozzle with millimeter accuracy, it is possible to reproduce measured dose distributions with an accuracy in range and modulation width, in the case of a spread-out Bragg peak (SOBP), of better than 1 mm. The excellent agreement demonstrates that the simulations can even be used to generate beam data for commissioning treatment planning systems. The Monte Carlo nozzle model was used to study mechanical optimization in terms of scattered radiation and secondary radiation in the design of the nozzles. We present simulations on the neutron background. Further, the Monte Carlo calculations supported commissioning efforts in understanding the sensitivity of beam characteristics and how these influence the dose delivered. We present the sensitivity of dose distributions in water with respect to various beam parameters and geometrical misalignments. This allows the definition of tolerances for quality assurance and the design of quality assurance procedures.