LMC: Logarithmantic Monte Carlo

NASA Astrophysics Data System (ADS)

Mantz, Adam B.

2017-06-01

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

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

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

Hong, X; Gao, H; Schuemann, J

2015-06-15

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

Atomistic Monte Carlo Simulation of Lipid Membranes

PubMed Central

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

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

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

PubMed Central

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

1995-01-01

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

Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods

DOE PAGES

Liu, Peigui; Elshall, Ahmed S.; Ye, Ming; ...

2016-02-05

Evaluating marginal likelihood is the most critical and computationally expensive task, when conducting Bayesian model averaging to quantify parametric and model uncertainties. The evaluation is commonly done by using Laplace approximations to evaluate semianalytical expressions of the marginal likelihood or by using Monte Carlo (MC) methods to evaluate arithmetic or harmonic mean of a joint likelihood function. This study introduces a new MC method, i.e., thermodynamic integration, which has not been attempted in environmental modeling. Instead of using samples only from prior parameter space (as in arithmetic mean evaluation) or posterior parameter space (as in harmonic mean evaluation), the thermodynamicmore » integration method uses samples generated gradually from the prior to posterior parameter space. This is done through a path sampling that conducts Markov chain Monte Carlo simulation with different power coefficient values applied to the joint likelihood function. The thermodynamic integration method is evaluated using three analytical functions by comparing the method with two variants of the Laplace approximation method and three MC methods, including the nested sampling method that is recently introduced into environmental modeling. The thermodynamic integration method outperforms the other methods in terms of their accuracy, convergence, and consistency. The thermodynamic integration method is also applied to a synthetic case of groundwater modeling with four alternative models. The application shows that model probabilities obtained using the thermodynamic integration method improves predictive performance of Bayesian model averaging. As a result, the thermodynamic integration method is mathematically rigorous, and its MC implementation is computationally general for a wide range of environmental problems.« less

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.

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

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

Pater, P; Vallieres, M; Seuntjens, J

2014-06-15

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

Reactive Monte Carlo sampling with an ab initio potential

NASA Astrophysics Data System (ADS)

Leiding, Jeff; Coe, Joshua D.

2016-05-01

We present the first application of reactive Monte Carlo in a first-principles context. The algorithm samples in a modified NVT ensemble in which the volume, temperature, and total number of atoms of a given type are held fixed, but molecular composition is allowed to evolve through stochastic variation of chemical connectivity. We discuss general features of the method, as well as techniques needed to enhance the efficiency of Boltzmann sampling. Finally, we compare the results of simulation of NH3 to those of ab initio molecular dynamics (AIMD). We find that there are regions of state space for which RxMC sampling is much more efficient than AIMD due to the "rare-event" character of chemical reactions.

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

PubMed

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

2017-01-07

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

PubMed Central

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

2016-01-01

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

Subtle Monte Carlo Updates in Dense Molecular Systems.

PubMed

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

2012-02-14

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

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

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

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

2016-10-01

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

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

PubMed

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

2010-01-01

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

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

PubMed

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

2007-07-15

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

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

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

Liangzhe Zhang; Anthony D. Rollett; Timothy Bartel

2012-02-01

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

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator

NASA Astrophysics Data System (ADS)

Suh, Donghyuk; Radak, Brian K.; Chipot, Christophe; Roux, Benoît

2018-01-01

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator.

PubMed

Suh, Donghyuk; Radak, Brian K; Chipot, Christophe; Roux, Benoît

2018-01-07

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

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

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Evans, Katherine

2018-03-01

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

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

DOE PAGES

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

2015-11-28

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

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

NASA Astrophysics Data System (ADS)

Vittaldev, Vivek; Russell, Ryan P.

2017-09-01

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

McStas 1.1: a tool for building neutron Monte Carlo simulations

NASA Astrophysics Data System (ADS)

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

2000-03-01

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

McStas-model of the delft SESANS

NASA Astrophysics Data System (ADS)

Knudsen, E.; Udby, L.; Willendrup, P. K.; Lefmann, K.; Bouwman, W. G.

2011-06-01

We present simulation results taking first virtual data from a model of the Spin-Echo Small Angle Scattering (SESANS) instrument situated in Delft, in the framework of the McStas Monte Carlo software package. The main focus has been on making a model of the Delft SESANS instrument, and we can now present the first virtual data from it, using a refracting prism-like sample model. In consequence, polarisation instrumentation is now included natively in the McStas kernel, including options for magnetic fields and a number of utility components. This development has brought us to a point where realistic models of polarisation-enabled instrumentation can be built.

Multilevel Monte Carlo for two phase flow and Buckley–Leverett transport in random heterogeneous porous media

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

Müller, Florian, E-mail: florian.mueller@sam.math.ethz.ch; Jenny, Patrick, E-mail: jenny@ifd.mavt.ethz.ch; Meyer, Daniel W., E-mail: meyerda@ethz.ch

2013-10-01

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared tomore » MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.« less

Efficient hybrid non-equilibrium molecular dynamics--Monte Carlo simulations with symmetric momentum reversal.

PubMed

Chen, Yunjie; Roux, Benoît

2014-09-21

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Efficient hybrid non-equilibrium molecular dynamics - Monte Carlo simulations with symmetric momentum reversal

NASA Astrophysics Data System (ADS)

Chen, Yunjie; Roux, Benoît

2014-09-01

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Reactive Monte Carlo sampling with an ab initio potential

DOE PAGES

Leiding, Jeff; Coe, Joshua D.

2016-05-04

Here, we present the first application of reactive Monte Carlo in a first-principles context. The algorithm samples in a modified NVT ensemble in which the volume, temperature, and total number of atoms of a given type are held fixed, but molecular composition is allowed to evolve through stochastic variation of chemical connectivity. We also discuss general features of the method, as well as techniques needed to enhance the efficiency of Boltzmann sampling. Finally, we compare the results of simulation of NH 3 to those of ab initio molecular dynamics (AIMD). Furthermore, we find that there are regions of state spacemore » for which RxMC sampling is much more efficient than AIMD due to the “rare-event” character of chemical reactions.« less

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

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

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

2015-01-01

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

Simulating adsorptive expansion of zeolites: application to biomass-derived solutions in contact with silicalite.

PubMed

Santander, Julian E; Tsapatsis, Michael; Auerbach, Scott M

2013-04-16

We have constructed and applied an algorithm to simulate the behavior of zeolite frameworks during liquid adsorption. We applied this approach to compute the adsorption isotherms of furfural-water and hydroxymethyl furfural (HMF)-water mixtures adsorbing in silicalite zeolite at 300 K for comparison with experimental data. We modeled these adsorption processes under two different statistical mechanical ensembles: the grand canonical (V-Nz-μg-T or GC) ensemble keeping volume fixed, and the P-Nz-μg-T (osmotic) ensemble allowing volume to fluctuate. To optimize accuracy and efficiency, we compared pure Monte Carlo (MC) sampling to hybrid MC-molecular dynamics (MD) simulations. For the external furfural-water and HMF-water phases, we assumed the ideal solution approximation and employed a combination of tabulated data and extended ensemble simulations for computing solvation free energies. We found that MC sampling in the V-Nz-μg-T ensemble (i.e., standard GCMC) does a poor job of reproducing both the Henry's law regime and the saturation loadings of these systems. Hybrid MC-MD sampling of the V-Nz-μg-T ensemble, which includes framework vibrations at fixed total volume, provides better results in the Henry's law region, but this approach still does not reproduce experimental saturation loadings. Pure MC sampling of the osmotic ensemble was found to approach experimental saturation loadings more closely, whereas hybrid MC-MD sampling of the osmotic ensemble quantitatively reproduces such loadings because the MC-MD approach naturally allows for locally anisotropic volume changes wherein some pores expand whereas others contract.

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.

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

Monte Carlo MP2 on Many Graphical Processing Units.

PubMed

Doran, Alexander E; Hirata, So

2016-10-11

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

LCG MCDB—a knowledgebase of Monte-Carlo simulated events

NASA Astrophysics Data System (ADS)

Belov, S.; Dudko, L.; Galkin, E.; Gusev, A.; Pokorski, W.; Sherstnev, A.

2008-02-01

In this paper we report on LCG Monte-Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC Collaborations by experts. In many cases, the modern Monte-Carlo simulation of physical processes requires expert knowledge in Monte-Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly dedicated to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project. Program summaryProgram title: LCG Monte-Carlo Data Base Catalogue identifier: ADZX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 30 129 No. of bytes in distributed program, including test data, etc.: 216 943 Distribution format: tar.gz Programming language: Perl Computer: CPU: Intel Pentium 4, RAM: 1 Gb, HDD: 100 Gb Operating system: Scientific Linux CERN 3/4 RAM: 1 073 741 824 bytes (1 Gb) Classification: 9 External routines:perl >= 5.8.5; Perl modules DBD-mysql >= 2.9004, File::Basename, GD::SecurityImage, GD::SecurityImage::AC, Linux::Statistics, XML::LibXML > 1.6, XML::SAX, XML::NamespaceSupport; Apache HTTP Server >= 2.0.59; mod auth external >= 2.2.9; edg-utils-system RPM package; gd >= 2.0.28; rpm package CASTOR-client >= 2.1.2-4; arc-server (optional) Nature of problem: Often, different groups of experimentalists prepare similar samples of particle collision events or turn to the same group of authors of Monte-Carlo (MC) generators to prepare the events. For example, the same MC samples of Standard Model (SM) processes can be employed for the investigations either in the SM analyses (as a signal) or in searches for new phenomena in Beyond Standard Model analyses (as a background). If the samples are made available publicly and equipped with corresponding and comprehensive documentation, it can speed up cross checks of the samples themselves and physical models applied. Some event samples require a lot of computing resources for preparation. So, a central storage of the samples prevents possible waste of researcher time and computing resources, which can be used to prepare the same events many times. Solution method: Creation of a special knowledgebase (MCDB) designed to keep event samples for the LHC experimental and phenomenological community. The knowledgebase is realized as a separate web-server ( http://mcdb.cern.ch). All event samples are kept on types at CERN. Documentation describing the events is the main contents of MCDB. Users can browse the knowledgebase, read and comment articles (documentation), and download event samples. Authors can upload new event samples, create new articles, and edit own articles. Restrictions: The software is adopted to solve the problems, described in the article and there are no any additional restrictions. Unusual features: The software provides a framework to store and document large files with flexible authentication and authorization system. Different external storages with large capacity can be used to keep the files. The WEB Content Management System provides all of the necessary interfaces for the authors of the files, end-users and administrators. Running time: Real time operations. References: [1] The main LCG MCDB server, http://mcdb.cern.ch/. [2] P. Bartalini, L. Dudko, A. Kryukov, I.V. Selyuzhenkov, A. Sherstnev, A. Vologdin, LCG Monte-Carlo data base, hep-ph/0404241. [3] J.P. Baud, B. Couturier, C. Curran, J.D. Durand, E. Knezo, S. Occhetti, O. Barring, CASTOR: status and evolution, cs.oh/0305047.

An Unsplit Monte-Carlo solver for the resolution of the linear Boltzmann equation coupled to (stiff) Bateman equations

NASA Astrophysics Data System (ADS)

Bernede, Adrien; Poëtte, Gaël

2018-02-01

In this paper, we are interested in the resolution of the time-dependent problem of particle transport in a medium whose composition evolves with time due to interactions. As a constraint, we want to use of Monte-Carlo (MC) scheme for the transport phase. A common resolution strategy consists in a splitting between the MC/transport phase and the time discretization scheme/medium evolution phase. After going over and illustrating the main drawbacks of split solvers in a simplified configuration (monokinetic, scalar Bateman problem), we build a new Unsplit MC (UMC) solver improving the accuracy of the solutions, avoiding numerical instabilities, and less sensitive to time discretization. The new solver is essentially based on a Monte Carlo scheme with time dependent cross sections implying the on-the-fly resolution of a reduced model for each MC particle describing the time evolution of the matter along their flight path.

TU-EF-304-07: Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Proton Therapy

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

Li, Y; UT Southwestern Medical Center, Dallas, TX; Tian, Z

2015-06-15

Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC intomore » IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical usages.« less

Monte Carlo simulations of backscattering process in dislocation-containing SrTiO3 single crystal

NASA Astrophysics Data System (ADS)

Jozwik, P.; Sathish, N.; Nowicki, L.; Jagielski, J.; Turos, A.; Kovarik, L.; Arey, B.

2014-05-01

Studies of defects formation in crystals are of obvious importance in electronics, nuclear engineering and other disciplines where materials are exposed to different forms of irradiation. Rutherford Backscattering/Channeling (RBS/C) and Monte Carlo (MC) simulations are the most convenient tool for this purpose, as they allow one to determine several features of lattice defects: their type, concentration and damage accumulation kinetic. On the other hand various irradiation conditions can be efficiently modeled by ion irradiation method without leading to the radioactivity of the sample. Combination of ion irradiation with channeling experiment and MC simulations appears thus as a most versatile method in studies of radiation damage in materials. The paper presents the results on such a study performed on SrTiO3 (STO) single crystals irradiated with 320 keV Ar ions. The samples were analyzed also by using HRTEM as a complementary method which enables the measurement of geometrical parameters of crystal lattice deformation in the vicinity of dislocations. Once the parameters and their variations within the distance of several lattice constants from the dislocation core are known, they may be used in MC simulations for the quantitative determination of dislocation depth distribution profiles. The final outcome of the deconvolution procedure are cross-sections values calculated for two types of defects observed (RDA and dislocations).

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

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

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

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

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

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

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

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.

On Fitting a Multivariate Two-Part Latent Growth Model

PubMed Central

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

2017-01-01

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

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.

Improved importance sampling technique for efficient simulation of digital communication systems

NASA Technical Reports Server (NTRS)

Lu, Dingqing; Yao, Kung

1988-01-01

A new, improved importance sampling (IIS) approach to simulation is considered. Some basic concepts of IS are introduced, and detailed evolutions of simulation estimation variances for Monte Carlo (MC) and IS simulations are given. The general results obtained from these evolutions are applied to the specific previously known conventional importance sampling (CIS) technique and the new IIS technique. The derivation for a linear system with no signal random memory is considered in some detail. For the CIS technique, the optimum input scaling parameter is found, while for the IIS technique, the optimum translation parameter is found. The results are generalized to a linear system with memory and signals. Specific numerical and simulation results are given which show the advantages of CIS over MC and IIS over CIS for simulations of digital communications systems.

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.

Calibration of the Top-Quark Monte Carlo Mass.

PubMed

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

2016-04-22

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

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

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

Chi, Y; Li, Y; Tian, Z

2015-06-15

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

Contrast of Backscattered Electron SEM Images of Nanoparticles on Substrates with Complex Structure

PubMed Central

Müller, Erich; Fritsch-Decker, Susanne; Hettler, Simon; Störmer, Heike; Weiss, Carsten; Gerthsen, Dagmar

2017-01-01

This study is concerned with backscattered electron scanning electron microscopy (BSE SEM) contrast of complex nanoscaled samples which consist of SiO2 nanoparticles (NPs) deposited on indium-tin-oxide covered bulk SiO2 and glassy carbon substrates. BSE SEM contrast of NPs is studied as function of the primary electron energy and working distance. Contrast inversions are observed which prevent intuitive interpretation of NP contrast in terms of material contrast. Experimental data is quantitatively compared with Monte-Carlo- (MC-) simulations. Quantitative agreement between experimental data and MC-simulations is obtained if the transmission characteristics of the annular semiconductor detector are taken into account. MC-simulations facilitate the understanding of NP contrast inversions and are helpful to derive conditions for optimum material and topography contrast. PMID:29109816

Contrast of Backscattered Electron SEM Images of Nanoparticles on Substrates with Complex Structure.

PubMed

Kowoll, Thomas; Müller, Erich; Fritsch-Decker, Susanne; Hettler, Simon; Störmer, Heike; Weiss, Carsten; Gerthsen, Dagmar

2017-01-01

This study is concerned with backscattered electron scanning electron microscopy (BSE SEM) contrast of complex nanoscaled samples which consist of SiO 2 nanoparticles (NPs) deposited on indium-tin-oxide covered bulk SiO 2 and glassy carbon substrates. BSE SEM contrast of NPs is studied as function of the primary electron energy and working distance. Contrast inversions are observed which prevent intuitive interpretation of NP contrast in terms of material contrast. Experimental data is quantitatively compared with Monte-Carlo- (MC-) simulations. Quantitative agreement between experimental data and MC-simulations is obtained if the transmission characteristics of the annular semiconductor detector are taken into account. MC-simulations facilitate the understanding of NP contrast inversions and are helpful to derive conditions for optimum material and topography contrast.

Top Quark Mass Calibration for Monte Carlo Event Generators.

PubMed

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

2016-12-02

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

Fast Monte Carlo simulation of a dispersive sample on the SEQUOIA spectrometer at the SNS

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

Granroth, Garrett E; Chen, Meili; Kohl, James Arthur

2007-01-01

Simulation of an inelastic scattering experiment, with a sample and a large pixilated detector, usually requires days of time because of finite processor speeds. We report simulations on an SNS (Spallation Neutron Source) instrument, SEQUOIA, that reduce the time to less than 2 hours by using parallelization and the resources of the TeraGrid. SEQUOIA is a fine resolution (∆E/Ei ~ 1%) chopper spectrometer under construction at the SNS. It utilizes incident energies from Ei = 20 meV to 2 eV and will have ~ 144,000 detector pixels covering 1.6 Sr of solid angle. The full spectrometer, including a 1-D dispersivemore » sample, has been simulated using the Monte Carlo package McStas. This paper summarizes the method of parallelization for and results from these simulations. In addition, limitations of and proposed improvements to current analysis software will be discussed.« less

Molecular dynamics and dynamic Monte-Carlo simulation of irradiation damage with focused ion beams

NASA Astrophysics Data System (ADS)

Ohya, Kaoru

2017-03-01

The focused ion beam (FIB) has become an important tool for micro- and nanostructuring of samples such as milling, deposition and imaging. However, this leads to damage of the surface on the nanometer scale from implanted projectile ions and recoiled material atoms. It is therefore important to investigate each kind of damage quantitatively. We present a dynamic Monte-Carlo (MC) simulation code to simulate the morphological and compositional changes of a multilayered sample under ion irradiation and a molecular dynamics (MD) simulation code to simulate dose-dependent changes in the backscattering-ion (BSI)/secondary-electron (SE) yields of a crystalline sample. Recent progress in the codes for research to simulate the surface morphology and Mo/Si layers intermixing in an EUV lithography mask irradiated with FIBs, and the crystalline orientation effect on BSI and SE yields relating to the channeling contrast in scanning ion microscopes, is also presented.

Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method

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

Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.

2015-01-01

The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysismore » that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR.« less

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

NASA Astrophysics Data System (ADS)

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

2001-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Monte Carlo simulations of neutron-scattering instruments using McStas

NASA Astrophysics Data System (ADS)

Nielsen, K.; Lefmann, K.

2000-06-01

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

Top Quark Mass Calibration for Monte Carlo Event Generators

DOE PAGES

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

2016-11-29

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

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

NASA Astrophysics Data System (ADS)

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

2007-07-01

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

TiOx deposited by magnetron sputtering: a joint modelling and experimental study

NASA Astrophysics Data System (ADS)

Tonneau, R.; Moskovkin, P.; Pflug, A.; Lucas, S.

2018-05-01

This paper presents a 3D multiscale simulation approach to model magnetron reactive sputter deposition of TiOx⩽2 at various O2 inlets and its validation against experimental results. The simulation first involves the transport of sputtered material in a vacuum chamber by means of a three-dimensional direct simulation Monte Carlo (DSMC) technique. Second, the film growth at different positions on a 3D substrate is simulated using a kinetic Monte Carlo (kMC) method. When simulating the transport of species in the chamber, wall chemistry reactions are taken into account in order to get the proper content of the reactive species in the volume. Angular and energy distributions of particles are extracted from DSMC and used for film growth modelling by kMC. Along with the simulation, experimental deposition of TiOx coatings on silicon samples placed at different positions on a curved sample holder was performed. The experimental results are in agreement with the simulated ones. For a given coater, the plasma phase hysteresis behaviour, film composition and film morphology are predicted. The used methodology can be applied to any coater and any films. This paves the way to the elaboration of a virtual coater allowing a user to predict composition and morphology of films deposited in silico.

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

PubMed Central

Gete, Ermias; Duzenli, Cheryl; Teke, Tony

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Ustinov, E. A.

2017-01-01

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

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

PubMed

Ustinov, E A; Do, D D

2012-08-21

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

Monte Carlo Simulations: Number of Iterations and Accuracy

DTIC Science & Technology

2015-07-01

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

A Comparison of Experimental EPMA Data and Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2004-01-01

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

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

DOE PAGES

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

2016-08-20

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

Top Quark Mass Calibration for Monte Carlo Event Generators

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2010-05-01

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

Monte Carlo based electron treatment planning and cutout output factor calculations

NASA Astrophysics Data System (ADS)

Mitrou, Ellis

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

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE PAGES

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk; ...

2017-11-07

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

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

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

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

PubMed

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

2018-04-01

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

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

PubMed Central

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

2018-01-01

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

A comparative study of history-based versus vectorized Monte Carlo methods in the GPU/CUDA environment for a simple neutron eigenvalue problem

NASA Astrophysics Data System (ADS)

Liu, Tianyu; Du, Xining; Ji, Wei; Xu, X. George; Brown, Forrest B.

2014-06-01

For nuclear reactor analysis such as the neutron eigenvalue calculations, the time consuming Monte Carlo (MC) simulations can be accelerated by using graphics processing units (GPUs). However, traditional MC methods are often history-based, and their performance on GPUs is affected significantly by the thread divergence problem. In this paper we describe the development of a newly designed event-based vectorized MC algorithm for solving the neutron eigenvalue problem. The code was implemented using NVIDIA's Compute Unified Device Architecture (CUDA), and tested on a NVIDIA Tesla M2090 GPU card. We found that although the vectorized MC algorithm greatly reduces the occurrence of thread divergence thus enhancing the warp execution efficiency, the overall simulation speed is roughly ten times slower than the history-based MC code on GPUs. Profiling results suggest that the slow speed is probably due to the memory access latency caused by the large amount of global memory transactions. Possible solutions to improve the code efficiency are discussed.

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

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

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

2014-06-15

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

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

PubMed

Hayati, Homa; Mesbahi, Asghar; Nazarpoor, Mahmood

2016-01-01

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

NOTE: Acceleration of Monte Carlo-based scatter compensation for cardiac SPECT

NASA Astrophysics Data System (ADS)

Sohlberg, A.; Watabe, H.; Iida, H.

2008-07-01

Single proton emission computed tomography (SPECT) images are degraded by photon scatter making scatter compensation essential for accurate reconstruction. Reconstruction-based scatter compensation with Monte Carlo (MC) modelling of scatter shows promise for accurate scatter correction, but it is normally hampered by long computation times. The aim of this work was to accelerate the MC-based scatter compensation using coarse grid and intermittent scatter modelling. The acceleration methods were compared to un-accelerated implementation using MC-simulated projection data of the mathematical cardiac torso (MCAT) phantom modelling 99mTc uptake and clinical myocardial perfusion studies. The results showed that when combined the acceleration methods reduced the reconstruction time for 10 ordered subset expectation maximization (OS-EM) iterations from 56 to 11 min without a significant reduction in image quality indicating that the coarse grid and intermittent scatter modelling are suitable for MC-based scatter compensation in cardiac SPECT.

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

PubMed

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

2010-03-01

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

Random number generators for large-scale parallel Monte Carlo simulations on FPGA

NASA Astrophysics Data System (ADS)

Lin, Y.; Wang, F.; Liu, B.

2018-05-01

Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

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

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

2015-12-31

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

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

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

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

1994-07-01

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

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

PubMed

Yuan, Jiankui; Rong, Yi; Chen, Quan

2015-01-08

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

A virtual source model for Monte Carlo simulation of helical tomotherapy

PubMed Central

Yuan, Jiankui; Rong, Yi

2015-01-01

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

Enhanced Sampling of an Atomic Model with Hybrid Nonequilibrium Molecular Dynamics-Monte Carlo Simulations Guided by a Coarse-Grained Model.

PubMed

Chen, Yunjie; Roux, Benoît

2015-08-11

Molecular dynamics (MD) trajectories based on a classical equation of motion provide a straightforward, albeit somewhat inefficient approach, to explore and sample the configurational space of a complex molecular system. While a broad range of techniques can be used to accelerate and enhance the sampling efficiency of classical simulations, only algorithms that are consistent with the Boltzmann equilibrium distribution yield a proper statistical mechanical computational framework. Here, a multiscale hybrid algorithm relying simultaneously on all-atom fine-grained (FG) and coarse-grained (CG) representations of a system is designed to improve sampling efficiency by combining the strength of nonequilibrium molecular dynamics (neMD) and Metropolis Monte Carlo (MC). This CG-guided hybrid neMD-MC algorithm comprises six steps: (1) a FG configuration of an atomic system is dynamically propagated for some period of time using equilibrium MD; (2) the resulting FG configuration is mapped onto a simplified CG model; (3) the CG model is propagated for a brief time interval to yield a new CG configuration; (4) the resulting CG configuration is used as a target to guide the evolution of the FG system; (5) the FG configuration (from step 1) is driven via a nonequilibrium MD (neMD) simulation toward the CG target; (6) the resulting FG configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-ends momentum reversal prescription is used for the neMD trajectories of the FG system to guarantee that the CG-guided hybrid neMD-MC algorithm obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The enhanced sampling achieved with the method is illustrated with a model system with hindered diffusion and explicit-solvent peptide simulations. Illustrative tests indicate that the method can yield a speedup of about 80 times for the model system and up to 21 times for polyalanine and (AAQAA)3 in water.

Enhanced Sampling of an Atomic Model with Hybrid Nonequilibrium Molecular Dynamics—Monte Carlo Simulations Guided by a Coarse-Grained Model

PubMed Central

2015-01-01

Molecular dynamics (MD) trajectories based on a classical equation of motion provide a straightforward, albeit somewhat inefficient approach, to explore and sample the configurational space of a complex molecular system. While a broad range of techniques can be used to accelerate and enhance the sampling efficiency of classical simulations, only algorithms that are consistent with the Boltzmann equilibrium distribution yield a proper statistical mechanical computational framework. Here, a multiscale hybrid algorithm relying simultaneously on all-atom fine-grained (FG) and coarse-grained (CG) representations of a system is designed to improve sampling efficiency by combining the strength of nonequilibrium molecular dynamics (neMD) and Metropolis Monte Carlo (MC). This CG-guided hybrid neMD-MC algorithm comprises six steps: (1) a FG configuration of an atomic system is dynamically propagated for some period of time using equilibrium MD; (2) the resulting FG configuration is mapped onto a simplified CG model; (3) the CG model is propagated for a brief time interval to yield a new CG configuration; (4) the resulting CG configuration is used as a target to guide the evolution of the FG system; (5) the FG configuration (from step 1) is driven via a nonequilibrium MD (neMD) simulation toward the CG target; (6) the resulting FG configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-ends momentum reversal prescription is used for the neMD trajectories of the FG system to guarantee that the CG-guided hybrid neMD-MC algorithm obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The enhanced sampling achieved with the method is illustrated with a model system with hindered diffusion and explicit-solvent peptide simulations. Illustrative tests indicate that the method can yield a speedup of about 80 times for the model system and up to 21 times for polyalanine and (AAQAA)3 in water. PMID:26574442

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

PubMed

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

2015-04-07

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

Optimization of beam shaping assembly based on D-T neutron generator and dose evaluation for BNCT

NASA Astrophysics Data System (ADS)

Naeem, Hamza; Chen, Chaobin; Zheng, Huaqing; Song, Jing

2017-04-01

The feasibility of developing an epithermal neutron beam for a boron neutron capture therapy (BNCT) facility based on a high intensity D-T fusion neutron generator (HINEG) and using the Monte Carlo code SuperMC (Super Monte Carlo simulation program for nuclear and radiation process) is proposed in this study. The Monte Carlo code SuperMC is used to determine and optimize the final configuration of the beam shaping assembly (BSA). The optimal BSA design in a cylindrical geometry which consists of a natural uranium sphere (14 cm) as a neutron multiplier, AlF3 and TiF3 as moderators (20 cm each), Cd (1 mm) as a thermal neutron filter, Bi (5 cm) as a gamma shield, and Pb as a reflector and collimator to guide neutrons towards the exit window. The epithermal neutron beam flux of the proposed model is 5.73 × 109 n/cm2s, and other dosimetric parameters for the BNCT reported by IAEA-TECDOC-1223 have been verified. The phantom dose analysis shows that the designed BSA is accurate, efficient and suitable for BNCT applications. Thus, the Monte Carlo code SuperMC is concluded to be capable of simulating the BSA and the dose calculation for BNCT, and high epithermal flux can be achieved using proposed BSA.

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

PubMed

Sakota, Daisuke; Takatani, Setsuo

2012-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

Kalantzis, Georgios; Tachibana, Hidenobu

2014-01-01

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

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

PubMed

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

2010-05-01

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

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

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

Cho, H; Brindle, J; Hepel, J

2015-06-15

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

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

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

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

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

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

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2016-10-01

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

Monte Carlo simulations in radiotherapy dosimetry.

PubMed

Andreo, Pedro

2018-06-27

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

PubMed Central

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

2016-01-01

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

Enabling Microscopic Simulators to Perform System Level Tasks: A System-Identification Based, Closure-on-Demand Toolkit for Multiscale Simulation Stability/Bifurcation Analysis, Optimization and Control

DTIC Science & Technology

2006-10-01

The objective was to construct a bridge between existing and future microscopic simulation codes ( kMC , MD, MC, BD, LB etc.) and traditional, continuum...kinetic Monte Carlo, kMC , equilibrium MC, Lattice-Boltzmann, LB, Brownian Dynamics, BD, or general agent-based, AB) simulators. It also, fortuitously...cond-mat/0310460 at arXiv.org. 27. Coarse Projective kMC Integration: Forward/Reverse Initial and Boundary Value Problems", R. Rico-Martinez, C. W

Nonlinear Spatial Inversion Without Monte Carlo Sampling

NASA Astrophysics Data System (ADS)

Curtis, A.; Nawaz, A.

2017-12-01

High-dimensional, nonlinear inverse or inference problems usually have non-unique solutions. The distribution of solutions are described by probability distributions, and these are usually found using Monte Carlo (MC) sampling methods. These take pseudo-random samples of models in parameter space, calculate the probability of each sample given available data and other information, and thus map out high or low probability values of model parameters. However, such methods would converge to the solution only as the number of samples tends to infinity; in practice, MC is found to be slow to converge, convergence is not guaranteed to be achieved in finite time, and detection of convergence requires the use of subjective criteria. We propose a method for Bayesian inversion of categorical variables such as geological facies or rock types in spatial problems, which requires no sampling at all. The method uses a 2-D Hidden Markov Model over a grid of cells, where observations represent localized data constraining the model in each cell. The data in our example application are seismic properties such as P- and S-wave impedances or rock density; our model parameters are the hidden states and represent the geological rock types in each cell. The observations at each location are assumed to depend on the facies at that location only - an assumption referred to as `localized likelihoods'. However, the facies at a location cannot be determined solely by the observation at that location as it also depends on prior information concerning its correlation with the spatial distribution of facies elsewhere. Such prior information is included in the inversion in the form of a training image which represents a conceptual depiction of the distribution of local geologies that might be expected, but other forms of prior information can be used in the method as desired. The method provides direct (pseudo-analytic) estimates of posterior marginal probability distributions over each variable, so these do not need to be estimated from samples as is required in MC methods. On a 2-D test example the method is shown to outperform previous methods significantly, and at a fraction of the computational cost. In many foreseeable applications there are therefore no serious impediments to extending the method to 3-D spatial models.

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

PubMed

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

2009-10-01

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

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.

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

MC ray-tracing optimization of lobster-eye focusing devices with RESTRAX

NASA Astrophysics Data System (ADS)

Šaroun, Jan; Kulda, Jiří

2006-11-01

The enhanced functionalities of the latest version of the RESTRAX software, providing a high-speed Monte Carlo (MC) ray-tracing code to represent a virtual three-axis neutron spectrometer, include representation of parabolic and elliptic guide profiles and facilities for numerical optimization of parameter values, characterizing the instrument components. As examples, we present simulations of a doubly focusing monochromator in combination with cold neutron guides and lobster-eye supermirror devices, concentrating a monochromatic beam to small sample volumes. A Levenberg-Marquardt minimization algorithm is used to optimize simultaneously several parameters of the monochromator and lobster-eye guides. We compare the performance of optimized configurations in terms of monochromatic neutron flux and energy spread and demonstrate the effect of lobster-eye optics on beam transformations in real and momentum subspaces.

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

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

Tian, Z; Folkerts, M; Jiang, S

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculationsmore » for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.« less

Integration of OpenMC methods into MAMMOTH and Serpent

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

Kerby, Leslie; DeHart, Mark; Tumulak, Aaron

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

Methods for calculating the absolute entropy and free energy of biological systems based on ideas from polymer physics.

PubMed

Meirovitch, Hagai

2010-01-01

The commonly used simulation techniques, Metropolis Monte Carlo (MC) and molecular dynamics (MD) are of a dynamical type which enables one to sample system configurations i correctly with the Boltzmann probability, P(i)(B), while the value of P(i)(B) is not provided directly; therefore, it is difficult to obtain the absolute entropy, S approximately -ln P(i)(B), and the Helmholtz free energy, F. With a different simulation approach developed in polymer physics, a chain is grown step-by-step with transition probabilities (TPs), and thus their product is the value of the construction probability; therefore, the entropy is known. Because all exact simulation methods are equivalent, i.e. they lead to the same averages and fluctuations of physical properties, one can treat an MC or MD sample as if its members have rather been generated step-by-step. Thus, each configuration i of the sample can be reconstructed (from nothing) by calculating the TPs with which it could have been constructed. This idea applies also to bulk systems such as fluids or magnets. This approach has led earlier to the "local states" (LS) and the "hypothetical scanning" (HS) methods, which are approximate in nature. A recent development is the hypothetical scanning Monte Carlo (HSMC) (or molecular dynamics, HSMD) method which is based on stochastic TPs where all interactions are taken into account. In this respect, HSMC(D) can be viewed as exact and the only approximation involved is due to insufficient MC(MD) sampling for calculating the TPs. The validity of HSMC has been established by applying it first to liquid argon, TIP3P water, self-avoiding walks (SAW), and polyglycine models, where the results for F were found to agree with those obtained by other methods. Subsequently, HSMD was applied to mobile loops of the enzymes porcine pancreatic alpha-amylase and acetylcholinesterase in explicit water, where the difference in F between the bound and free states of the loop was calculated. Currently, HSMD is being extended for calculating the absolute and relative free energies of ligand-enzyme binding. We describe the whole approach and discuss future directions. 2009 John Wiley & Sons, Ltd.

Time-dependent importance sampling in semiclassical initial value representation calculations for time correlation functions. II. A simplified implementation.

PubMed

Tao, Guohua; Miller, William H

2012-09-28

An efficient time-dependent (TD) Monte Carlo (MC) importance sampling method has recently been developed [G. Tao and W. H. Miller, J. Chem. Phys. 135, 024104 (2011)] for the evaluation of time correlation functions using the semiclassical (SC) initial value representation (IVR) methodology. In this TD-SC-IVR method, the MC sampling uses information from both time-evolved phase points as well as their initial values, and only the "important" trajectories are sampled frequently. Even though the TD-SC-IVR was shown in some benchmark examples to be much more efficient than the traditional time-independent sampling method (which uses only initial conditions), the calculation of the SC prefactor-which is computationally expensive, especially for large systems-is still required for accepted trajectories. In the present work, we present an approximate implementation of the TD-SC-IVR method that is completely prefactor-free; it gives the time correlation function as a classical-like magnitude function multiplied by a phase function. Application of this approach to flux-flux correlation functions (which yield reaction rate constants) for the benchmark H + H(2) system shows very good agreement with exact quantum results. Limitations of the approximate approach are also discussed.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

A LAMMPS implementation of volume-temperature replica exchange molecular dynamics

NASA Astrophysics Data System (ADS)

Liu, Liang-Chun; Kuo, Jer-Lai

2015-04-01

A driver module for executing volume-temperature replica exchange molecular dynamics (VTREMD) was developed for the LAMMPS package. As a patch code, the VTREMD module performs classical molecular dynamics (MD) with Monte Carlo (MC) decisions between MD runs. The goal of inserting the MC step was to increase the breadth of sampled configurational space. In this method, states receive better sampling by making temperature or density swaps with their neighboring states. As an accelerated sampling method, VTREMD is particularly useful to explore states at low temperatures, where systems are easily trapped in local potential wells. As functional examples, TIP4P/Ew and TIP4P/2005 water models were analyzed using VTREMD. The phase diagram in this study covered the deeply supercooled regime, and this test served as a suitable demonstration of the usefulness of VTREMD in overcoming the slow dynamics problem. To facilitate using the current code, attention was also paid on how to optimize the exchange efficiency by using grid allocation. VTREMD was useful for studying systems with rough energy landscapes, such as those with numerous local minima or multiple characteristic time scales.

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Fast CPU-based Monte Carlo simulation for radiotherapy dose calculation.

PubMed

Ziegenhein, Peter; Pirner, Sven; Ph Kamerling, Cornelis; Oelfke, Uwe

2015-08-07

Monte-Carlo (MC) simulations are considered to be the most accurate method for calculating dose distributions in radiotherapy. Its clinical application, however, still is limited by the long runtimes conventional implementations of MC algorithms require to deliver sufficiently accurate results on high resolution imaging data. In order to overcome this obstacle we developed the software-package PhiMC, which is capable of computing precise dose distributions in a sub-minute time-frame by leveraging the potential of modern many- and multi-core CPU-based computers. PhiMC is based on the well verified dose planning method (DPM). We could demonstrate that PhiMC delivers dose distributions which are in excellent agreement to DPM. The multi-core implementation of PhiMC scales well between different computer architectures and achieves a speed-up of up to 37[Formula: see text] compared to the original DPM code executed on a modern system. Furthermore, we could show that our CPU-based implementation on a modern workstation is between 1.25[Formula: see text] and 1.95[Formula: see text] faster than a well-known GPU implementation of the same simulation method on a NVIDIA Tesla C2050. Since CPUs work on several hundreds of GB RAM the typical GPU memory limitation does not apply for our implementation and high resolution clinical plans can be calculated.

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

NASA Astrophysics Data System (ADS)

Doronin, Alexander; Meglinski, Igor

2012-09-01

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

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

PubMed

Doronin, Alexander; Meglinski, Igor

2012-09-01

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

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

NASA Astrophysics Data System (ADS)

Sakota, Daisuke; Takatani, Setsuo

2011-07-01

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

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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

PubMed

Gorshkov, Anton V; Kirillin, Mikhail Yu

2015-08-01

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

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

NASA Astrophysics Data System (ADS)

Brdar, S.; Seifert, A.

2018-01-01

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

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

PubMed

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

Lépinoux, J.; Sigli, C.

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

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

PubMed

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

2006-01-01

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

[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].

PubMed

Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang

2016-02-01

Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS

EDITORIAL: International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification

NASA Astrophysics Data System (ADS)

Verhaegen, Frank; Seuntjens, Jan

2008-03-01

Monte Carlo particle transport techniques offer exciting tools for radiotherapy research, where they play an increasingly important role. Topics of research related to clinical applications range from treatment planning, motion and registration studies, brachytherapy, verification imaging and dosimetry. The International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification took place in a hotel in Montreal in French Canada, from 29 May-1 June 2007, and was the third workshop to be held on a related topic, which now seems to have become a tri-annual event. About one hundred workers from many different countries participated in the four-day meeting. Seventeen experts in the field were invited to review topics and present their latest work. About half of the audience was made up by young graduate students. In a very full program, 57 papers were presented and 10 posters were on display during most of the meeting. On the evening of the third day a boat trip around the island of Montreal allowed participants to enjoy the city views, and to sample the local cuisine. The topics covered at the workshop included the latest developments in the most popular Monte Carlo transport algorithms, fast Monte Carlo, statistical issues, source modeling, MC treatment planning, modeling of imaging devices for treatment verification, registration and deformation of images and a sizeable number of contributions on brachytherapy. In this volume you will find 27 short papers resulting from the workshop on a variety of topics, some of them on very new stuff such as graphics processing units for fast computing, PET modeling, dual-energy CT, calculations in dynamic phantoms, tomotherapy devices, . . . . We acknowledge the financial support of the National Cancer Institute of Canada, the Institute of Cancer Research of the Canadian Institutes of Health Research, the Association Québécoise des Physicien(ne)s Médicaux Clinique, the Institute of Physics, and MedicalPhysicsWeb. At McGill we thank the following departments for support: the Cancer Axis of the Research Institute of the McGill University Health Center, the Faculties of Medicine and Science, the Departments of Oncology and Physics and the Medical Physics Unit. The following companies are thanked: TomoTherapy and Standard Imaging. The American Association of Physicists in Medicine and the International Atomic Energy Agency are gratefully acknowledged for endorsing the meeting. A final word of thanks goes out to all of those who contributed to the successful Workshop: first of all our administrative assistant Ms Margery Knewstubb, the website developer Dr François DeBlois, the two heads of the logistics team, Ms Emily Poon and Ms Emily Heath, our local medical physics students and staff, the IOP staff and the authors who shared their new and exciting work with us. Editors: Frank Verhaegen and Jan Seuntjens (McGill University) Associate editors: Luc Beaulieu, Iwan Kawrakow, Tony Popescu and David Rogers

Using Computer-Based "Experiments" in the Analysis of Chemical Reaction Equilibria

ERIC Educational Resources Information Center

Li, Zhao; Corti, David S.

2018-01-01

The application of the Reaction Monte Carlo (RxMC) algorithm to standard textbook problems in chemical reaction equilibria is discussed. The RxMC method is a molecular simulation algorithm for studying the equilibrium properties of reactive systems, and therefore provides the opportunity to develop computer-based "experiments" for the…

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

NASA Astrophysics Data System (ADS)

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

1997-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-11-01

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

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images.

PubMed

Rydén, T; Heydorn Lagerlöf, J; Hemmingsson, J; Marin, I; Svensson, J; Båth, M; Gjertsson, P; Bernhardt, P

2018-01-04

Full Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA). This enabled simulations of parallel photon emissions from the voxels matrix (128 3 or 256 3 ). Each computed tomography (CT) number was converted to attenuation coefficients for photo absorption, coherent scattering, and incoherent scattering. For photon scattering, the deflection angle was determined by the differential scattering cross sections. An angular response function was developed and used to model the accepted angles for photon interaction with the crystal, and a detector scattering kernel was used for modeling the photon scattering in the detector. Predefined energy and spatial resolution kernels for the crystal were used. The MC code was implemented in the OSEM reconstruction of clinical and phantom 177 Lu SPECT/CT images. The Jaszczak image quality phantom was used to evaluate the performance of the MC reconstruction in comparison with attenuated corrected (AC) OSEM reconstructions and attenuated corrected OSEM reconstructions with resolution recovery corrections (RRC). The performance of the MC code was 3200 million photons/s. The required number of photons emitted per voxel to obtain a sufficiently low noise level in the simulated image was 200 for a 128 3 voxel matrix. With this number of emitted photons/voxel, the MC-based OSEM reconstruction with ten subsets was performed within 20 s/iteration. The images converged after around six iterations. Therefore, the reconstruction time was around 3 min. The activity recovery for the spheres in the Jaszczak phantom was clearly improved with MC-based OSEM reconstruction, e.g., the activity recovery was 88% for the largest sphere, while it was 66% for AC-OSEM and 79% for RRC-OSEM. The GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of 177 Lu-DOTATATE treatments revealed clearly improved resolution and contrast.

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

PubMed

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

2014-01-01

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

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

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

Perfetti, Christopher M; Rearden, Bradley T

2015-01-01

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

Monte Carlo isotopic inventory analysis for complex nuclear systems

NASA Astrophysics Data System (ADS)

Phruksarojanakun, Phiphat

Monte Carlo Inventory Simulation Engine (MCise) is a newly developed method for calculating isotopic inventory of materials. It offers the promise of modeling materials with complex processes and irradiation histories, which pose challenges for current, deterministic tools, and has strong analogies to Monte Carlo (MC) neutral particle transport. The analog method, including considerations for simple, complex and loop flows, is fully developed. In addition, six variance reduction tools provide unique capabilities of MCise to improve statistical precision of MC simulations. Forced Reaction forces an atom to undergo a desired number of reactions in a given irradiation environment. Biased Reaction Branching primarily focuses on improving statistical results of the isotopes that are produced from rare reaction pathways. Biased Source Sampling aims at increasing frequencies of sampling rare initial isotopes as the starting particles. Reaction Path Splitting increases the population by splitting the atom at each reaction point, creating one new atom for each decay or transmutation product. Delta Tracking is recommended for high-frequency pulsing to reduce the computing time. Lastly, Weight Window is introduced as a strategy to decrease large deviations of weight due to the uses of variance reduction techniques. A figure of merit is necessary to compare the efficiency of different variance reduction techniques. A number of possibilities for figure of merit are explored, two of which are robust and subsequently used. One is based on the relative error of a known target isotope (1/R 2T) and the other on the overall detection limit corrected by the relative error (1/DkR 2T). An automated Adaptive Variance-reduction Adjustment (AVA) tool is developed to iteratively define parameters for some variance reduction techniques in a problem with a target isotope. Sample problems demonstrate that AVA improves both precision and accuracy of a target result in an efficient manner. Potential applications of MCise include molten salt fueled reactors and liquid breeders in fusion blankets. As an example, the inventory analysis of a liquid actinide fuel in the In-Zinerator, a sub-critical power reactor driven by a fusion source, is examined. The result reassures MCise as a reliable tool for inventory analysis of complex nuclear systems.

A reversible-jump Markov chain Monte Carlo algorithm for 1D inversion of magnetotelluric data

NASA Astrophysics Data System (ADS)

Mandolesi, Eric; Ogaya, Xenia; Campanyà, Joan; Piana Agostinetti, Nicola

2018-04-01

This paper presents a new computer code developed to solve the 1D magnetotelluric (MT) inverse problem using a Bayesian trans-dimensional Markov chain Monte Carlo algorithm. MT data are sensitive to the depth-distribution of rock electric conductivity (or its reciprocal, resistivity). The solution provided is a probability distribution - the so-called posterior probability distribution (PPD) for the conductivity at depth, together with the PPD of the interface depths. The PPD is sampled via a reversible-jump Markov Chain Monte Carlo (rjMcMC) algorithm, using a modified Metropolis-Hastings (MH) rule to accept or discard candidate models along the chains. As the optimal parameterization for the inversion process is generally unknown a trans-dimensional approach is used to allow the dataset itself to indicate the most probable number of parameters needed to sample the PPD. The algorithm is tested against two simulated datasets and a set of MT data acquired in the Clare Basin (County Clare, Ireland). For the simulated datasets the correct number of conductive layers at depth and the associated electrical conductivity values is retrieved, together with reasonable estimates of the uncertainties on the investigated parameters. Results from the inversion of field measurements are compared with results obtained using a deterministic method and with well-log data from a nearby borehole. The PPD is in good agreement with the well-log data, showing as a main structure a high conductive layer associated with the Clare Shale formation. In this study, we demonstrate that our new code go beyond algorithms developend using a linear inversion scheme, as it can be used: (1) to by-pass the subjective choices in the 1D parameterizations, i.e. the number of horizontal layers in the 1D parameterization, and (2) to estimate realistic uncertainties on the retrieved parameters. The algorithm is implemented using a simple MPI approach, where independent chains run on isolated CPU, to take full advantage of parallel computer architectures. In case of a large number of data, a master/slave appoach can be used, where the master CPU samples the parameter space and the slave CPUs compute forward solutions.

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

PubMed

Beigi, Manije; Afarande, Fatemeh; Ghiasi, Hosein

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Golonka, P.; Pierzchała, T.; Waş, Z.

2004-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2005-01-01

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

A method for photon beam Monte Carlo multileaf collimator particle transport

NASA Astrophysics Data System (ADS)

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

2002-09-01

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

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

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

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

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

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

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

2015-04-15

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

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

PubMed

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

2014-12-16

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

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

NASA Astrophysics Data System (ADS)

Zhang, Guannan; Del-Castillo-Negrete, Diego

2017-10-01

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

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

NASA Technical Reports Server (NTRS)

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

A Monte Carlo simulation study of associated liquid crystals

NASA Astrophysics Data System (ADS)

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

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

MC EMiNEM maps the interaction landscape of the Mediator.

PubMed

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C; Martin, Dietmar E; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.

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

PubMed

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-28

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

Deviation from equilibrium conditions in molecular dynamic simulations of homogeneous nucleation

NASA Astrophysics Data System (ADS)

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-02-01

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

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain.

PubMed

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

2016-12-01

A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R²0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.

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

PubMed

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

2005-03-07

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

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

PubMed

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

2014-09-15

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

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

PubMed

Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin

2017-05-01

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

Efficient sampling of parsimonious inversion histories with application to genome rearrangement in Yersinia.

PubMed

Miklós, István; Darling, Aaron E

2009-06-22

Inversions are among the most common mutations acting on the order and orientation of genes in a genome, and polynomial-time algorithms exist to obtain a minimal length series of inversions that transform one genome arrangement to another. However, the minimum length series of inversions (the optimal sorting path) is often not unique as many such optimal sorting paths exist. If we assume that all optimal sorting paths are equally likely, then statistical inference on genome arrangement history must account for all such sorting paths and not just a single estimate. No deterministic polynomial algorithm is known to count the number of optimal sorting paths nor sample from the uniform distribution of optimal sorting paths. Here, we propose a stochastic method that uniformly samples the set of all optimal sorting paths. Our method uses a novel formulation of parallel Markov chain Monte Carlo. In practice, our method can quickly estimate the total number of optimal sorting paths. We introduce a variant of our approach in which short inversions are modeled to be more likely, and we show how the method can be used to estimate the distribution of inversion lengths and breakpoint usage in pathogenic Yersinia pestis. The proposed method has been implemented in a program called "MC4Inversion." We draw comparison of MC4Inversion to the sampler implemented in BADGER and a previously described importance sampling (IS) technique. We find that on high-divergence data sets, MC4Inversion finds more optimal sorting paths per second than BADGER and the IS technique and simultaneously avoids bias inherent in the IS technique.

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

PubMed Central

Beigi, Manije; Afarande, Fatemeh; Ghiasi, Hosein

2016-01-01

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

Absolute dose calculations for Monte Carlo simulations of radiotherapy beams.

PubMed

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

2005-07-21

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

A Simulation Study on the Performance of the Simple Difference and Covariance-Adjusted Scores in Randomized Experimental Designs.

PubMed

Petscher, Yaacov; Schatschneider, Christopher

2011-01-01

Research by Huck and McLean (1975) demonstrated that the covariance-adjusted score is more powerful than the simple difference score, yet recent reviews indicate researchers are equally likely to use either score type in two-wave randomized experimental designs. A Monte Carlo simulation was conducted to examine the conditions under which the simple difference and covariance-adjusted scores were more or less powerful to detect treatment effects when relaxing certain assumptions made by Huck and McLean (1975). Four factors were manipulated in the design including sample size, normality of the pretest and posttest distributions, the correlation between pretest and posttest, and posttest variance. A 5 × 5 × 4 × 3 mostly crossed design was run with 1,000 replications per condition, resulting in 226,000 unique samples. The gain score was nearly as powerful as the covariance-adjusted score when pretest and posttest variances were equal, and as powerful in fan-spread growth conditions; thus, under certain circumstances the gain score could be used in two-wave randomized experimental designs.

A Simulation Study on the Performance of the Simple Difference and Covariance-Adjusted Scores in Randomized Experimental Designs

PubMed Central

Petscher, Yaacov; Schatschneider, Christopher

2015-01-01

Research by Huck and McLean (1975) demonstrated that the covariance-adjusted score is more powerful than the simple difference score, yet recent reviews indicate researchers are equally likely to use either score type in two-wave randomized experimental designs. A Monte Carlo simulation was conducted to examine the conditions under which the simple difference and covariance-adjusted scores were more or less powerful to detect treatment effects when relaxing certain assumptions made by Huck and McLean (1975). Four factors were manipulated in the design including sample size, normality of the pretest and posttest distributions, the correlation between pretest and posttest, and posttest variance. A 5 × 5 × 4 × 3 mostly crossed design was run with 1,000 replications per condition, resulting in 226,000 unique samples. The gain score was nearly as powerful as the covariance-adjusted score when pretest and posttest variances were equal, and as powerful in fan-spread growth conditions; thus, under certain circumstances the gain score could be used in two-wave randomized experimental designs. PMID:26379310

Calibration of Ge gamma-ray spectrometers for complex sample geometries and matrices

NASA Astrophysics Data System (ADS)

Semkow, T. M.; Bradt, C. J.; Beach, S. E.; Haines, D. K.; Khan, A. J.; Bari, A.; Torres, M. A.; Marrantino, J. C.; Syed, U.-F.; Kitto, M. E.; Hoffman, T. J.; Curtis, P.

2015-11-01

A comprehensive study of the efficiency calibration and calibration verification of Ge gamma-ray spectrometers was performed using semi-empirical, computational Monte-Carlo (MC), and transfer methods. The aim of this study was to evaluate the accuracy of the quantification of gamma-emitting radionuclides in complex matrices normally encountered in environmental and food samples. A wide range of gamma energies from 59.5 to 1836.0 keV and geometries from a 10-mL jar to 1.4-L Marinelli beaker were studied on four Ge spectrometers with the relative efficiencies between 102% and 140%. Density and coincidence summing corrections were applied. Innovative techniques were developed for the preparation of artificial complex matrices from materials such as acidified water, polystyrene, ethanol, sugar, and sand, resulting in the densities ranging from 0.3655 to 2.164 g cm-3. They were spiked with gamma activity traceable to international standards and used for calibration verifications. A quantitative method of tuning MC calculations to experiment was developed based on a multidimensional chi-square paraboloid.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

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

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

2011-08-20

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

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

PubMed

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

2008-09-21

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

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

PubMed

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

2011-01-01

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

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

PubMed

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

2007-12-01

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

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

PubMed

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

2007-02-01

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

Exploiting molecular dynamics in Nested Sampling simulations of small peptides

NASA Astrophysics Data System (ADS)

Burkoff, Nikolas S.; Baldock, Robert J. N.; Várnai, Csilla; Wild, David L.; Csányi, Gábor

2016-04-01

Nested Sampling (NS) is a parameter space sampling algorithm which can be used for sampling the equilibrium thermodynamics of atomistic systems. NS has previously been used to explore the potential energy surface of a coarse-grained protein model and has significantly outperformed parallel tempering when calculating heat capacity curves of Lennard-Jones clusters. The original NS algorithm uses Monte Carlo (MC) moves; however, a variant, Galilean NS, has recently been introduced which allows NS to be incorporated into a molecular dynamics framework, so NS can be used for systems which lack efficient prescribed MC moves. In this work we demonstrate the applicability of Galilean NS to atomistic systems. We present an implementation of Galilean NS using the Amber molecular dynamics package and demonstrate its viability by sampling alanine dipeptide, both in vacuo and implicit solvent. Unlike previous studies of this system, we present the heat capacity curves of alanine dipeptide, whose calculation provides a stringent test for sampling algorithms. We also compare our results with those calculated using replica exchange molecular dynamics (REMD) and find good agreement. We show the computational effort required for accurate heat capacity estimation for small peptides. We also calculate the alanine dipeptide Ramachandran free energy surface for a range of temperatures and use it to compare the results using the latest Amber force field with previous theoretical and experimental results.

Monte-Carlo simulation of a stochastic differential equation

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations

NASA Astrophysics Data System (ADS)

Sempau, Josep; Wilderman, Scott J.; Bielajew, Alex F.

2000-08-01

A new Monte Carlo (MC) algorithm, the `dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high-accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 1283 voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a `mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The δ-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels.

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

NASA Astrophysics Data System (ADS)

Spezi, Emiliano; Leal, Antonio

2013-04-01

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

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Verhaegen, Frank; Seuntjens, Jan

2005-03-01

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

A fragment-based approach to the SAMPL3 Challenge

NASA Astrophysics Data System (ADS)

Kulp, John L.; Blumenthal, Seth N.; Wang, Qiang; Bryan, Richard L.; Guarnieri, Frank

2012-05-01

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands—regardless of the charged state in the active site—produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a ΔΔGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations.

A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model

DOE PAGES

Gan, Yanjun; Duan, Qingyun; Gong, Wei; ...

2014-01-01

Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin nearmore » Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LPτ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.« less

Monte Carlo calculation of proton stopping power and ranges in water for therapeutic energies

NASA Astrophysics Data System (ADS)

Bozkurt, Ahmet

2017-09-01

Monte Carlo is a statistical technique for obtaining numerical solutions to physical or mathematical problems that are analytically impractical, if not impossible, to solve. For charged particle transport problems, it presents many advantages over deterministic methods since such problems require a realistic description of the problem geometry, as well as detailed tracking of every source particle. Thus, MC can be considered as a powerful alternative to the well-known Bethe-Bloche equation where an equation with various corrections is used to obtain stopping power and ranges of electrons, positrons, protons, alphas, etc. This study presents how a stochastic method such as MC can be utilized to obtain certain quantities of practical importance related to charged particle transport. Sample simulation geometries were formed for water medium where disk shaped thin detectors were employed to compute average values of absorbed dose and flux at specific distances. For each detector cell, these quantities were utilized to evaluate the values of the range and the stopping power, as well as the shape of Bragg curve, for mono-energetic point source pencil beams of protons. The results were found to be ±2% compared to the data from the NIST compilation. It is safe to conclude that this approach can be extended to determine dosimetric quantities for other media, energies and charged particle types.

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

DTIC Science & Technology

2009-03-26

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

How to polarise all neutrons in one beam: a high performance polariser and neutron transport system

NASA Astrophysics Data System (ADS)

Rodriguez, D. Martin; Bentley, P. M.; Pappas, C.

2016-09-01

Polarised neutron beams are used in disciplines as diverse as magnetism,soft matter or biology. However, most of these applications often suffer from low flux also because the existing neutron polarising methods imply the filtering of one of the spin states, with a transmission of 50% at maximum. With the purpose of using all neutrons that are usually discarded, we propose a system that splits them according to their polarisation, flips them to match the spin direction, and then focuses them at the sample. Monte Carlo (MC) simulations show that this is achievable over a wide wavelength range and with an outstanding performance at the price of a more divergent neutron beam at the sample position.

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

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

Lee, Changho; Yang, Won Sik

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

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

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

Shin, J; Jee, K; Clasie, B

2016-06-15

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

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

PubMed

Thomson, R; Kawrakow, I

2012-06-01

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

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

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

Altsybeev, Igor

2016-01-22

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

MC EMiNEM Maps the Interaction Landscape of the Mediator

PubMed Central

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C.; Martin, Dietmar E.; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors. PMID:22737066

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

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

Adnani, N

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

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

PubMed

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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

PubMed

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

2017-06-07

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

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

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

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

2010-12-07

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

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

PubMed Central

2017-01-01

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

Absolute dose calculations for Monte Carlo simulations of radiotherapy beams

NASA Astrophysics Data System (ADS)

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

2005-07-01

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

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin I.

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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

PubMed

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

2015-10-07

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

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

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

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

2014-06-15

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

Monte Carlo decision curve analysis using aggregate data.

PubMed

Hozo, Iztok; Tsalatsanis, Athanasios; Djulbegovic, Benjamin

2017-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Multilevel UQ strategies for large-scale multiphysics applications: PSAAP II solar receiver

NASA Astrophysics Data System (ADS)

Jofre, Lluis; Geraci, Gianluca; Iaccarino, Gianluca

2017-06-01

Uncertainty quantification (UQ) plays a fundamental part in building confidence in predictive science. Of particular interest is the case of modeling and simulating engineering applications where, due to the inherent complexity, many uncertainties naturally arise, e.g. domain geometry, operating conditions, errors induced by modeling assumptions, etc. In this regard, one of the pacing items, especially in high-fidelity computational fluid dynamics (CFD) simulations, is the large amount of computing resources typically required to propagate incertitude through the models. Upcoming exascale supercomputers will significantly increase the available computational power. However, UQ approaches cannot entrust their applicability only on brute force Monte Carlo (MC) sampling; the large number of uncertainty sources and the presence of nonlinearities in the solution will make straightforward MC analysis unaffordable. Therefore, this work explores the multilevel MC strategy, and its extension to multi-fidelity and time convergence, to accelerate the estimation of the effect of uncertainties. The approach is described in detail, and its performance demonstrated on a radiated turbulent particle-laden flow case relevant to solar energy receivers (PSAAP II: Particle-laden turbulence in a radiation environment). Investigation funded by DoE's NNSA under PSAAP II.

An adaptive bias - hybrid MD/kMC algorithm for protein folding and aggregation.

PubMed

Peter, Emanuel K; Shea, Joan-Emma

2017-07-05

In this paper, we present a novel hybrid Molecular Dynamics/kinetic Monte Carlo (MD/kMC) algorithm and apply it to protein folding and aggregation in explicit solvent. The new algorithm uses a dynamical definition of biases throughout the MD component of the simulation, normalized in relation to the unbiased forces. The algorithm guarantees sampling of the underlying ensemble in dependency of one average linear coupling factor 〈α〉 τ . We test the validity of the kinetics in simulations of dialanine and compare dihedral transition kinetics with long-time MD-simulations. We find that for low 〈α〉 τ values, kinetics are in good quantitative agreement. In folding simulations of TrpCage and TrpZip4 in explicit solvent, we also find good quantitative agreement with experimental results and prior MD/kMC simulations. Finally, we apply our algorithm to study growth of the Alzheimer Amyloid Aβ 16-22 fibril by monomer addition. We observe two possible binding modes, one at the extremity of the fibril (elongation) and one on the surface of the fibril (lateral growth), on timescales ranging from ns to 8 μs.

Efficient Sampling of Parsimonious Inversion Histories with Application to Genome Rearrangement in Yersinia

PubMed Central

Darling, Aaron E.

2009-01-01

Inversions are among the most common mutations acting on the order and orientation of genes in a genome, and polynomial-time algorithms exist to obtain a minimal length series of inversions that transform one genome arrangement to another. However, the minimum length series of inversions (the optimal sorting path) is often not unique as many such optimal sorting paths exist. If we assume that all optimal sorting paths are equally likely, then statistical inference on genome arrangement history must account for all such sorting paths and not just a single estimate. No deterministic polynomial algorithm is known to count the number of optimal sorting paths nor sample from the uniform distribution of optimal sorting paths. Here, we propose a stochastic method that uniformly samples the set of all optimal sorting paths. Our method uses a novel formulation of parallel Markov chain Monte Carlo. In practice, our method can quickly estimate the total number of optimal sorting paths. We introduce a variant of our approach in which short inversions are modeled to be more likely, and we show how the method can be used to estimate the distribution of inversion lengths and breakpoint usage in pathogenic Yersinia pestis. The proposed method has been implemented in a program called “MC4Inversion.” We draw comparison of MC4Inversion to the sampler implemented in BADGER and a previously described importance sampling (IS) technique. We find that on high-divergence data sets, MC4Inversion finds more optimal sorting paths per second than BADGER and the IS technique and simultaneously avoids bias inherent in the IS technique. PMID:20333186

Game of Life on the Equal Degree Random Lattice

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Chen, Tao

2010-12-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2014-10-07

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Technical Reports Server (NTRS)

Wilson, Thomas L.

2007-01-01

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

Monte Carlo simulations within avalanche rescue

NASA Astrophysics Data System (ADS)

Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg

2016-04-01

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

The effect of dose enhancement near metal interfaces on synthetic diamond based X-ray dosimeters

NASA Astrophysics Data System (ADS)

Alamoudi, D.; Lohstroh, A.; Albarakaty, H.

2017-11-01

This study investigates the effects of dose enhancement on the photocurrent performance at metallic interfaces in synthetic diamond detectors based X-ray dosimeters as a function of bias voltages. Monte Carlo (MC) simulations with the BEAMnrc code were carried out to simulate the dose enhancement factor (DEF) and compared against the equivalent photocurrent ratio from experimental investigations. The MC simulation results show that the sensitive region for the absorbed dose distribution covers a few micrometers distances from the interface. Experimentally, two single crystals (SC) and one polycrystalline (PC) synthetic diamond samples were fabricated into detectors with carbon based electrodes by boron and carbon ion implantation. Subsequently; the samples were each mounted inside a tissue equivalent encapsulation to minimize unintended fluence perturbation. Dose enhancement was generated by placing copper, lead or gold near the active volume of the detectors using 50 kVp and 100 kVp X-rays relevant for medical dosimetry. The results show enhancement in the detectors' photocurrent performance when different metals are butted up to the diamond bulk as expected. The variation in the photocurrent measurement depends on the type of diamond samples, their electrodes' fabrication and the applied bias voltages indicating that the dose enhancement near the detector may modify their electronic performance.

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

NASA Astrophysics Data System (ADS)

Limbu, Dil; Biswas, Parthapratim

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

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

PubMed

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

2012-03-15

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

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

PubMed

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

2007-04-20

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

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

USGS Publications Warehouse

Kern, Christoph

2016-03-23

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

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

PubMed

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

2018-02-01

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

The Monte Carlo simulation of the Borexino detector

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Designing new guides and instruments using McStas

NASA Astrophysics Data System (ADS)

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

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

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

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

Abdel-Khalik, Hany S.; Zhang, Qiong

2014-05-20

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

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

Zhang, Jiangjiang; Li, Weixuan; Lin, Guang

In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters.more » To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.« less

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

NASA Astrophysics Data System (ADS)

Bieda, Bogusław; Grzesik, Katarzyna

2017-11-01

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

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

PubMed

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

2012-07-01

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

kmos: A lattice kinetic Monte Carlo framework

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

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

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

Abouelnasr, MKF; Smit, B

2012-01-01

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

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

PubMed

Abouelnasr, Mahmoud K F; Smit, Berend

2012-09-07

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

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

NASA Astrophysics Data System (ADS)

Tanaka, Ken; Tomeba, Hiromichi; Adachi, Fumiyuki

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

Conformational energy landscape of the acyl pocket loop in acetylcholinesterase: a Monte Carlo-generalized Born model study.

PubMed

Carlacci, Louis; Millard, Charles B; Olson, Mark A

2004-10-01

The X-ray crystal structure of the reaction product of acetylcholinesterase (AChE) with the inhibitor diisopropylphosphorofluoridate (DFP) showed significant structural displacement in a loop segment of residues 287-290. To understand this conformational selection, a Monte Carlo (MC) simulation study was performed of the energy landscape for the loop segment. A computational strategy was applied by using a combined simulated annealing and room temperature Metropolis sampling approach with solvent polarization modeled by a generalized Born (GB) approximation. Results from thermal annealing reveal a landscape topology of broader basin opening and greater distribution of energies for the displaced loop conformation, while the ensemble average of conformations at 298 K favored a shift in populations toward the native by a free-energy difference in good agreement with the estimated experimental value. Residue motions along a reaction profile of loop conformational reorganization are proposed where Arg-289 is critical in determining electrostatic effects of solvent interaction versus Coulombic charging.

CosmoSIS: A system for MC parameter estimation

DOE PAGES

Bridle, S.; Dodelson, S.; Jennings, E.; ...

2015-12-23

CosmoSIS is a modular system for cosmological parameter estimation, based on Markov Chain Monte Carlo and related techniques. It provides a series of samplers, which drive the exploration of the parameter space, and a series of modules, which calculate the likelihood of the observed data for a given physical model, determined by the location of a sample in the parameter space. While CosmoSIS ships with a set of modules that calculate quantities of interest to cosmologists, there is nothing about the framework itself, nor in the Markov Chain Monte Carlo technique, that is specific to cosmology. Thus CosmoSIS could bemore » used for parameter estimation problems in other fields, including HEP. This paper describes the features of CosmoSIS and show an example of its use outside of cosmology. Furthermore, it also discusses how collaborative development strategies differ between two different communities: that of HEP physicists, accustomed to working in large collaborations, and that of cosmologists, who have traditionally not worked in large groups.« less

Cs diffusion in SiC high-energy grain boundaries

NASA Astrophysics Data System (ADS)

Ko, Hyunseok; Szlufarska, Izabela; Morgan, Dane

2017-09-01

Cesium (Cs) is a radioactive fission product whose release is of concern for Tristructural-Isotropic fuel particles. In this work, Cs diffusion through high energy grain boundaries (HEGBs) of cubic-SiC is studied using an ab-initio based kinetic Monte Carlo (kMC) model. The HEGB environment was modeled as an amorphous SiC, and Cs defect energies were calculated using the density functional theory (DFT). From defect energies, it was suggested that the fastest diffusion mechanism is the diffusion of Cs interstitial in an amorphous SiC. The diffusion of Cs interstitial was simulated using a kMC model, based on the site and transition state energies sampled from the DFT. The Cs HEGB diffusion exhibited an Arrhenius type diffusion in the range of 1200-1600 °C. The comparison between HEGB results and the other studies suggests not only that the GB diffusion dominates the bulk diffusion but also that the HEGB is one of the fastest grain boundary paths for the Cs diffusion. The diffusion coefficients in HEGB are clearly a few orders of magnitude lower than the reported diffusion coefficients from in- and out-of-pile samples, suggesting that other contributions are responsible, such as radiation enhanced diffusion.

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.

Automated parton-shower variations in PYTHIA 8

DOE PAGES

Mrenna, S.; Skands, P.

2016-10-03

In the era of precision physics measurements at the LHC, efficient and exhaustive estimations of theoretical uncertainties play an increasingly crucial role. In the context of Monte Carlo (MC) event generators, the estimation of such uncertainties traditionally requires independent MC runs for each variation, for a linear increase in total run time. In this work, we report on an automated evaluation of the dominant (renormalization-scale and nonsingular) perturbative uncertainties in the pythia 8 event generator, with only a modest computational overhead. Each generated event is accompanied by a vector of alternative weights (one for each uncertainty variation), with each set separatelymore » preserving the total cross section. Explicit scale-compensating terms can be included, reflecting known coefficients of higher-order splitting terms and reducing the effect of the variations. In conclusion, the formalism also allows for the enhancement of rare partonic splittings, such as g→bb¯ and q→qγ, to obtain weighted samples enriched in these splittings while preserving the correct physical Sudakov factors.« less

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

NASA Astrophysics Data System (ADS)

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

2011-04-01

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

Improved cache performance in Monte Carlo transport calculations using energy banding

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.

PubMed

Tian, Zhen; Li, Yongbao; Folkerts, Michael; Shi, Feng; Jiang, Steve B; Jia, Xun

2015-10-21

Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum dose difference within 1.7%. The maximum relative difference of output factors was within 0.5%. Over 98.5% passing rate was achieved in 3D gamma-index tests with 2%/2 mm criteria in both an IMRT prostate patient case and a head-and-neck case. These results demonstrated the efficacy of our model in terms of accurately representing a reference phase-space file. We have also tested the efficiency gain of our source model over our previously developed phase-space-let file source model. The overall efficiency of dose calculation was found to be improved by ~1.3-2.2 times in water and patient cases using our analytical model.

Application of the Monte Carlo method to estimate doses due to neutron activation of different materials in a nuclear reactor

NASA Astrophysics Data System (ADS)

Ródenas, José

2017-11-01

All materials exposed to some neutron flux can be activated independently of the kind of the neutron source. In this study, a nuclear reactor has been considered as neutron source. In particular, the activation of control rods in a BWR is studied to obtain the doses produced around the storage pool for irradiated fuel of the plant when control rods are withdrawn from the reactor and installed into this pool. It is very important to calculate these doses because they can affect to plant workers in the area. The MCNP code based on the Monte Carlo method has been applied to simulate activation reactions produced in the control rods inserted into the reactor. Obtained activities are introduced as input into another MC model to estimate doses produced by them. The comparison of simulation results with experimental measurements allows the validation of developed models. The developed MC models have been also applied to simulate the activation of other materials, such as components of a stainless steel sample introduced into a training reactors. These models, once validated, can be applied to other situations and materials where a neutron flux can be found, not only nuclear reactors. For instance, activation analysis with an Am-Be source, neutrography techniques in both medical applications and non-destructive analysis of materials, civil engineering applications using a Troxler, analysis of materials in decommissioning of nuclear power plants, etc.

Relative frequencies of constrained events in stochastic processes: An analytical approach.

PubMed

Rusconi, S; Akhmatskaya, E; Sokolovski, D; Ballard, N; de la Cal, J C

2015-10-01

The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They relies on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least ≈10(4)). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications.

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

PubMed

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

2016-06-01

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

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

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

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

2013-07-01

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

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

PubMed Central

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

2015-01-01

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

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

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

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

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

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

PubMed

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

2014-11-01

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

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

PubMed

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

2015-02-21

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

Build-up and surface dose measurements on phantoms using micro-MOSFET in 6 and 10 MV x-ray beams and comparisons with Monte Carlo calculations.

PubMed

Xiang, Hong F; Song, Jun S; Chin, David W H; Cormack, Robert A; Tishler, Roy B; Makrigiorgos, G Mike; Court, Laurence E; Chin, Lee M

2007-04-01

This work is intended to investigate the application and accuracy of micro-MOSFET for superficial dose measurement under clinically used MV x-ray beams. Dose response of micro-MOSFET in the build-up region and on surface under MV x-ray beams were measured and compared to Monte Carlo calculations. First, percentage-depth-doses were measured with micro-MOSFET under 6 and 10 MV beams of normal incidence onto a flat solid water phantom. Micro-MOSFET data were compared with the measurements from a parallel plate ionization chamber and Monte Carlo dose calculation in the build-up region. Then, percentage-depth-doses were measured for oblique beams at 0 degrees-80 degrees onto the flat solid water phantom with micro-MOSFET placed at depths of 2 cm, 1 cm, and 2 mm below the surface. Measurements were compared to Monte Carlo calculations under these settings. Finally, measurements were performed with micro-MOSFET embedded in the first 1 mm layer of bolus placed on a flat phantom and a curved phantom of semi-cylindrical shape. Results were compared to superficial dose calculated from Monte Carlo for a 2 mm thin layer that extends from the surface to a depth of 2 mm. Results were (1) Comparison of measurements with MC calculation in the build-up region showed that micro-MOSFET has a water-equivalence thickness (WET) of 0.87 mm for 6 MV beam and 0.99 mm for 10 MV beam from the flat side, and a WET of 0.72 mm for 6 MV beam and 0.76 mm for 10 MV beam from the epoxy side. (2) For normal beam incidences, percentage depth dose agree within 3%-5% among micro-MOSFET measurements, parallel-plate ionization chamber measurements, and MC calculations. (3) For oblique incidence on the flat phantom with micro-MOSFET placed at depths of 2 cm, 1 cm, and 2 mm, measurements were consistent with MC calculations within a typical uncertainty of 3%-5%. (4) For oblique incidence on the flat phantom and a curved-surface phantom, measurements with micro-MOSFET placed at 1.0 mm agrees with the MC calculation within 6%, including uncertainties of micro-MOSFET measurements of 2%-3% (1 standard deviation), MOSFET angular dependence of 3.0%-3.5%, and 1%-2% systematical error due to phantom setup geometry asymmetry. Micro-MOSFET can be used for skin dose measurements in 6 and 10 MV beams with an estimated accuracy of +/- 6%.

Dosimetric response of variable-size cavities in photon-irradiated media and the behaviour of the Spencer-Attix cavity integral with increasing Δ.

PubMed

Kumar, Sudhir; Deshpande, Deepak D; Nahum, Alan E

2016-04-07

Cavity theory is fundamental to understanding and predicting dosimeter response. Conventional cavity theories have been shown to be consistent with one another by deriving the electron (+positron) and photon fluence spectra with the FLURZnrc user-code (EGSnrc Monte-Carlo system) in large volumes under quasi-CPE for photon beams of 1 MeV and 10 MeV in three materials (water, aluminium and copper) and then using these fluence spectra to evaluate and then inter-compare the Bragg-Gray, Spencer-Attix and 'large photon' 'cavity integrals'. The behaviour of the 'Spencer-Attix dose' (aka restricted cema), D S-A(▵), in a 1-MeV photon field in water has been investigated for a wide range of values of the cavity-size parameter ▵: D S-A(▵) decreases far below the Monte-Carlo dose (D MC) for ▵ greater than  ≈  30 keV due to secondary electrons with starting energies below ▵ not being 'counted'. We show that for a quasi-scatter-free geometry (D S-A(▵)/D MC) is closely equal to the proportion of energy transferred to Compton electrons with initial (kinetic) energies above ▵, derived from the Klein-Nishina (K-N) differential cross section. (D S-A(▵)/D MC) can be used to estimate the maximum size of a detector behaving as a Bragg-Gray cavity in a photon-irradiated medium as a function of photon-beam quality (under quasi CPE) e.g. a typical air-filled ion chamber is 'Bragg-Gray' at (monoenergetic) beam energies  ⩾260 keV. Finally, by varying the density of a silicon cavity (of 2.26 mm diameter and 2.0 mm thickness) in water, the response of different cavity 'sizes' was simulated; the Monte-Carlo-derived ratio D w/D Si for 6 MV and 15 MV photons varied from very close to the Spencer-Attix value at 'gas' densities, agreed well with Burlin cavity theory as ρ increased, and approached large photon behaviour for ρ  ≈  10 g cm(-3). The estimate of ▵ for the Si cavity was improved by incorporating a Monte-Carlo-derived correction for electron 'detours'. Excellent agreement was obtained between the Burlin 'd' factor for the Si cavity and D S-A(▵)/D MC at different (detour-corrected) ▵, thereby suggesting a further application for the D S-A(▵)/D MC ratio.

Photon beam dosimetry with EBT3 film in heterogeneous regions: Application to the evaluation of dose-calculation algorithms

NASA Astrophysics Data System (ADS)

Jung, Hyunuk; Kum, Oyeon; Han, Youngyih; Park, Byungdo; Cheong, Kwang-Ho

2014-12-01

For a better understanding of the accuracy of state-of-the-art-radiation therapies, 2-dimensional dosimetry in a patient-like environment will be helpful. Therefore, the dosimetry of EBT3 films in non-water-equivalent tissues was investigated, and the accuracy of commercially-used dose-calculation algorithms was evaluated with EBT3 measurement. Dose distributions were measured with EBT3 films for an in-house-designed phantom that contained a lung or a bone substitute, i.e., an air cavity (3 × 3 × 3 cm3) or teflon (2 × 2 × 2 cm3 or 3 × 3 × 3 cm3), respectively. The phantom was irradiated with 6-MV X-rays with field sizes of 2 × 2, 3 × 3, and 5 × 5 cm2. The accuracy of EBT3 dosimetry was evaluated by comparing the measured dose with the dose obtained from Monte Carlo (MC) simulations. A dose-to-bone-equivalent material was obtained by multiplying the EBT3 measurements by the stopping power ratio (SPR). The EBT3 measurements were then compared with the predictions from four algorithms: Monte Carlo (MC) in iPlan, acuros XB (AXB), analytical anisotropic algorithm (AAA) in Eclipse, and superposition-convolution (SC) in Pinnacle. For the air cavity, the EBT3 measurements agreed with the MC calculation to within 2% on average. For teflon, the EBT3 measurements differed by 9.297% (±0.9229%) on average from the Monte Carlo calculation before dose conversion, and by 0.717% (±0.6546%) after applying the SPR. The doses calculated by using the MC, AXB, AAA, and SC algorithms for the air cavity differed from the EBT3 measurements on average by 2.174, 2.863, 18.01, and 8.391%, respectively; for teflon, the average differences were 3.447, 4.113, 7.589, and 5.102%. The EBT3 measurements corrected with the SPR agreed with 2% on average both within and beyond the heterogeneities with MC results, thereby indicating that EBT3 dosimetry can be used in heterogeneous media. The MC and the AXB dose calculation algorithms exhibited clinically-acceptable accuracy (<5%) in heterogeneities.

Instrumental resolution of the chopper spectrometer 4SEASONS evaluated by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Kajimoto, Ryoichi; Sato, Kentaro; Inamura, Yasuhiro; Fujita, Masaki

2018-05-01

We performed simulations of the resolution function of the 4SEASONS spectrometer at J-PARC by using the Monte Carlo simulation package McStas. The simulations showed reasonably good agreement with analytical calculations of energy and momentum resolutions by using a simplified description. We implemented new functionalities in Utsusemi, the standard data analysis tool used in 4SEASONS, to enable visualization of the simulated resolution function and predict its shape for specific experimental configurations.

MCMEG: Simulations of both PDD and TPR for 6 MV LINAC photon beam using different MC codes

NASA Astrophysics Data System (ADS)

Fonseca, T. C. F.; Mendes, B. M.; Lacerda, M. A. S.; Silva, L. A. C.; Paixão, L.; Bastos, F. M.; Ramirez, J. V.; Junior, J. P. R.

2017-11-01

The Monte Carlo Modelling Expert Group (MCMEG) is an expert network specializing in Monte Carlo radiation transport and the modelling and simulation applied to the radiation protection and dosimetry research field. For the first inter-comparison task the group launched an exercise to model and simulate a 6 MV LINAC photon beam using the Monte Carlo codes available within their laboratories and validate their simulated results by comparing them with experimental measurements carried out in the National Cancer Institute (INCA) in Rio de Janeiro, Brazil. The experimental measurements were performed using an ionization chamber with calibration traceable to a Secondary Standard Dosimetry Laboratory (SSDL). The detector was immersed in a water phantom at different depths and was irradiated with a radiation field size of 10×10 cm2. This exposure setup was used to determine the dosimetric parameters Percentage Depth Dose (PDD) and Tissue Phantom Ratio (TPR). The validation process compares the MC calculated results to the experimental measured PDD20,10 and TPR20,10. Simulations were performed reproducing the experimental TPR20,10 quality index which provides a satisfactory description of both the PDD curve and the transverse profiles at the two depths measured. This paper reports in detail the modelling process using MCNPx, MCNP6, EGSnrc and Penelope Monte Carlo codes, the source and tally descriptions, the validation processes and the results.

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

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

Lee, K; Leung, R; Law, G

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

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

PubMed Central

Amoush, Ahmad; Wilkinson, Douglas A.

2015-01-01

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

Estimating the Standard Error of Robust Regression Estimates.

DTIC Science & Technology

1987-03-01

error is 0(n4/5). In another Monte Carlo study, McKean and Schrader (1984) found that the tests resulting from studentizing ; by _3d/1/2 with d =0(n4 /5...44 4 -:~~-~*v: -. *;~ ~ ~*t .~ # ~ 44 % * ~ .%j % % % * . ., ~ -%. -14- Sheather, S. J. and McKean, J. W. (1987). A comparison of testing and...Wiley, New York. Welsch, R. E. (1980). Regression Sensitivity Analysis and Bounded- Influence Estimation, in Evaluation of Econometric Models eds. J

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

Nagaoka, Masataka; Core Research for Evolutional Science and Technology; ESICB, Kyoto University, Kyodai Katsura, Nishikyo-ku, Kyoto 615-8520

A new efficient hybrid Monte Carlo (MC)/molecular dynamics (MD) reaction method with a rare event-driving mechanism is introduced as a practical ‘atomistic’ molecular simulation of large-scale chemically reactive systems. Starting its demonstrative application to the racemization reaction of (R)-2-chlorobutane in N,N-dimethylformamide solution, several other applications are shown from the practical viewpoint of molecular controlling of complex chemical reactions, stereochemistry and aggregate structures. Finally, I would like to mention the future applications of the hybrid MC/MD reaction method.

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

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

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

Yeo, Sang Chul; Lee, Hyuck Mo, E-mail: hmlee@kaist.ac.kr; Lo, Yu Chieh

2014-10-07

Ammonia (NH{sub 3}) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (E{sub b}) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (E{sub b}) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH{sub 3} nitridation rate onmore » the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH{sub 3} nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH{sub 3} nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH{sub 3} nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.« less

MC-TESTER v. 1.23: A universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

NASA Astrophysics Data System (ADS)

Davidson, N.; Golonka, P.; Przedziński, T.; Waş, Z.

2011-03-01

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be used for such tests of decays of intermediate states (particles or resonances) in a semi-automated way. Since 2002 new functionalities were introduced into the package. In particular, it now works with the HepMC event record, the standard for C++ programs. The complete set-up for benchmarking the interfaces, such as interface between τ-lepton production and decay, including QED bremsstrahlung effects is shown. The example is chosen to illustrate the new options introduced into the program. From the technical perspective, our paper documents software updates and supplements previous documentation. As in the past, our test consists of two steps. Distinct Monte Carlo programs are run separately; events with decays of a chosen particle are searched, and information is stored by MC-TESTER. Then, at the analysis step, information from a pair of runs may be compared and represented in the form of tables and plots. Updates introduced in the program up to version 1.24.4 are also documented. In particular, new configuration scripts or script to combine results from multitude of runs into single information file to be used in analysis step are explained. Program summaryProgram title: MC-TESTER, version 1.23 and version 1.24.4 Catalog identifier: ADSM_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSM_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 250 548 No. of bytes in distributed program, including test data, etc.: 4 290 610 Distribution format: tar.gz Programming language: C++, FORTRAN77 Tested and compiled with: gcc 3.4.6, 4.2.4 and 4.3.2 with g77/gfortran Computer: Tested on various platforms Operating system: Tested on operating systems: Linux SLC 4.6 and SLC 5, Fedora 8, Ubuntu 8.2 etc. Classification: 11.9 External routines: HepMC ( https://savannah.cern.ch/projects/hepmc/), PYTHIA8 ( http://home.thep.lu.se/~torbjorn/Pythia.html), LaTeX ( http://www.latex-project.org/) Catalog identifier of previous version: ADSM_v1_0 Journal reference of previous version: Comput. Phys. Comm. 157 (2004) 39 Does the new version supersede the previous version?: Yes Nature of problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast, semi-automatic way of comparing results from different programs is often desirable for the development of new programs, in order to check correctness of the installations or for discussion of uncertainties. Solution method: A typical HEP Monte Carlo program stores the generated events in event records such as HepMC, HEPEVT or PYJETS. MC-TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table. Reasons for new version: Interface for HepMC Event Record is introduced. Setup for benchmarking the interfaces, such as τ-lepton production and decay, including QED bremsstrahlung effects is introduced as well. This required significant changes in the algorithm. As a consequence, a new version of the code was introduced. Restrictions: Only the first 200 decay channels that were found will initialize histograms and if the multiplicity of decay products in a given channel was larger than 7, histograms will not be created for that channel. Additional comments: New features: HepMC interface, use of lists in definition of histograms and decay channels, filters for decay products or secondary decays to be omitted, bug fixing, extended flexibility in representation of program output, installation configuration scripts, merging multiple output files from separate generations. Running time: Varies substantially with the analyzed decay particle, but generally speed estimation of the old version remains valid. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100 000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; LATEX processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multiprocessor machines.

Competitive Adsorption and Ordered Packing of Counterions near Highly Charged Surfaces: From Mean-Field Theory to Monte Carlo Simulations

PubMed Central

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2013-01-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson’s equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both of the mean-field theory and MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling. PMID:22680474

Competitive adsorption and ordered packing of counterions near highly charged surfaces: From mean-field theory to Monte Carlo simulations.

PubMed

Wen, Jiayi; Zhou, Shenggao; Xu, Zhenli; Li, Bo

2012-04-01

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect-included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson's equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both the mean-field theory and the MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling.

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

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

Moskvin, V; Pirlepesov, F; Tsiamas, P

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

Monte Carlo simulations to replace film dosimetry in IMRT verification.

PubMed

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

2011-01-01

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

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

PubMed

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

2018-02-01

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

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

PubMed

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

2011-12-01

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

Modified Monte Carlo method for study of electron transport in degenerate electron gas in the presence of electron-electron interactions, application to graphene

NASA Astrophysics Data System (ADS)

Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek

2017-07-01

Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron-electron (e-e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e-e interactions. This required adapting the treatment of e-e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.

Systematic discrepancies in Monte Carlo predictions of k-ratios emitted from thin films on substrates

NASA Astrophysics Data System (ADS)

Statham, P.; Llovet, X.; Duncumb, P.

2012-03-01

We have assessed the reliability of different Monte Carlo simulation programmes using the two available Bastin-Heijligers databases of thin-film measurements by EPMA. The MC simulation programmes tested include Curgenven-Duncumb MSMC, NISTMonte, Casino and PENELOPE. Plots of the ratio of calculated to measured k-ratios ("kcalc/kmeas") against various parameters reveal error trends that are not apparent in simple error histograms. The results indicate that the MC programmes perform quite differently on the same dataset. However, they appear to show a similar pronounced trend with a "hockey stick" shape in the "kcalc/kmeas versus kmeas" plots. The most sophisticated programme PENELOPE gives the closest correspondence with experiment but still shows a tendency to underestimate experimental k-ratios by 10 % for films that are thin compared to the electron range. We have investigated potential causes for this systematic behaviour and extended the study to data not collected by Bastin and Heijligers.

Kinetic Monte Carlo study of vinyl acetate synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100)

NASA Astrophysics Data System (ADS)

Huang, Yanping; Dong, Xiuqin; Yu, Yingzhe; Zhang, Minhua

2017-11-01

On the basis of the activation barriers and reaction energies from DFT calculations, kinetic Monte Carlo (kMC) simulations of vinyl acetate (VA) synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100) were carried out. Through kMC simulation, it was found that VA synthesis from ethylene acetoxylation proceeds via Moiseev mechanism on both Pd(100) and Pd/Au(100). The addition of Au into Pd can suppress ethylene dehydrogenation while it can promote acetic acid dehydrogenation, which can eventually facilitate VA synthesis as a whole. The addition of Au into Pd can further improve the conversion and selectivity of VA synthesis from ethylene acetoxylation. When the reaction network is analyzed, besides the energetics of each elementary reaction, the surface coverage of each species and the occupancy of the surface sites on the catalyst should also be taken into consideration.

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.

Grid Block Design Based on Monte Carlo Simulated Dosimetry, the Linear Quadratic and Hug–Kellerer Radiobiological Models

PubMed Central

Gholami, Somayeh; Nedaie, Hassan Ali; Longo, Francesco; Ay, Mohammad Reza; Dini, Sharifeh A.; Meigooni, Ali S.

2017-01-01

Purpose: The clinical efficacy of Grid therapy has been examined by several investigators. In this project, the hole diameter and hole spacing in Grid blocks were examined to determine the optimum parameters that give a therapeutic advantage. Methods: The evaluations were performed using Monte Carlo (MC) simulation and commonly used radiobiological models. The Geant4 MC code was used to simulate the dose distributions for 25 different Grid blocks with different hole diameters and center-to-center spacing. The therapeutic parameters of these blocks, namely, the therapeutic ratio (TR) and geometrical sparing factor (GSF) were calculated using two different radiobiological models, including the linear quadratic and Hug–Kellerer models. In addition, the ratio of the open to blocked area (ROTBA) is also used as a geometrical parameter for each block design. Comparisons of the TR, GSF, and ROTBA for all of the blocks were used to derive the parameters for an optimum Grid block with the maximum TR, minimum GSF, and optimal ROTBA. A sample of the optimum Grid block was fabricated at our institution. Dosimetric characteristics of this Grid block were measured using an ionization chamber in water phantom, Gafchromic film, and thermoluminescent dosimeters in Solid Water™ phantom materials. Results: The results of these investigations indicated that Grid blocks with hole diameters between 1.00 and 1.25 cm and spacing of 1.7 or 1.8 cm have optimal therapeutic parameters (TR > 1.3 and GSF~0.90). The measured dosimetric characteristics of the optimum Grid blocks including dose profiles, percentage depth dose, dose output factor (cGy/MU), and valley-to-peak ratio were in good agreement (±5%) with the simulated data. Conclusion: In summary, using MC-based dosimetry, two radiobiological models, and previously published clinical data, we have introduced a method to design a Grid block with optimum therapeutic response. The simulated data were reproduced by experimental data. PMID:29296035

Independent Monte-Carlo dose calculation for MLC based CyberKnife radiotherapy

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Self-Consistent Monte Carlo Study of the Coulomb Interaction under Nano-Scale Device Structures

NASA Astrophysics Data System (ADS)

Sano, Nobuyuki

2011-03-01

It has been pointed that the Coulomb interaction between the electrons is expected to be of crucial importance to predict reliable device characteristics. In particular, the device performance is greatly degraded due to the plasmon excitation represented by dynamical potential fluctuations in high-doped source and drain regions by the channel electrons. We employ the self-consistent 3D Monte Carlo (MC) simulations, which could reproduce both the correct mobility under various electron concentrations and the collective plasma waves, to study the physical impact of dynamical potential fluctuations on device performance under the Double-gate MOSFETs. The average force experienced by an electron due to the Coulomb interaction inside the device is evaluated by performing the self-consistent MC simulations and the fixed-potential MC simulations without the Coulomb interaction. Also, the band-tailing associated with the local potential fluctuations in high-doped source region is quantitatively evaluated and it is found that the band-tailing becomes strongly dependent of position in real space even inside the uniform source region. This work was partially supported by Grants-in-Aid for Scientific Research B (No. 2160160) from the Ministry of Education, Culture, Sports, Science and Technology in Japan.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2011-02-01

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

Improved QM Methods and Their Application in QM/MM Studies of Enzymatic Reactions

NASA Astrophysics Data System (ADS)

Jorgensen, William L.

2007-03-01

Quantum mechanics (QM) and Monte Carlo statistical mechanics (MC) simulations have been used by us since the early 1980s to study reaction mechanisms and the origin of solvent effects on reaction rates. A goal was always to perform the QM and MC/MM calculations simultaneously in order to obtain free-energy surfaces in solution with no geometrical restrictions. This was achieved by 2002 and complete free-energy profiles and surfaces with full sampling of solute and solvent coordinates can now be obtained through one job submission using BOSS [JCC 2005, 26, 1689]. Speed and accuracy demands also led to development of the improved semiempirical QM method, PDDG-PM3 [JCC 1601 (2002); JCTC 817 (2005)]. The combined PDDG-PM3/MC/FEP methodology has provided excellent results for free energies of activation for many reactions in numerous solvents. Recent examples include Cope, Kemp and E1cb eliminations [JACS 8829 (2005), 6141 (2006); JOC 4896 (2006)], as well as enzymatic reactions catalyzed by the putative Diels-Alderase, macrophomate synthase, and fatty-acid amide hydrolase [JACS 3577 (2005); JACS (2006)]. The presentation will focus on the accuracy that is currently achievable in such QM/MM studies and the accuracy of the underlying QM methodology including extensive comparisons of results from PDDG-PM3 and ab initio DFT methods.

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

PubMed

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

2010-11-01

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

General Monte Carlo reliability simulation code including common mode failures and HARP fault/error-handling

NASA Technical Reports Server (NTRS)

Platt, M. E.; Lewis, E. E.; Boehm, F.

1991-01-01

A Monte Carlo Fortran computer program was developed that uses two variance reduction techniques for computing system reliability applicable to solving very large highly reliable fault-tolerant systems. The program is consistent with the hybrid automated reliability predictor (HARP) code which employs behavioral decomposition and complex fault-error handling models. This new capability is called MC-HARP which efficiently solves reliability models with non-constant failures rates (Weibull). Common mode failure modeling is also a specialty.

Probability of misclassifying biological elements in surface waters.

PubMed

Loga, Małgorzata; Wierzchołowska-Dziedzic, Anna

2017-11-24

Measurement uncertainties are inherent to assessment of biological indices of water bodies. The effect of these uncertainties on the probability of misclassification of ecological status is the subject of this paper. Four Monte-Carlo (M-C) models were applied to simulate the occurrence of random errors in the measurements of metrics corresponding to four biological elements of surface waters: macrophytes, phytoplankton, phytobenthos, and benthic macroinvertebrates. Long series of error-prone measurement values of these metrics, generated by M-C models, were used to identify cases in which values of any of the four biological indices lay outside of the "true" water body class, i.e., outside the class assigned from the actual physical measurements. Fraction of such cases in the M-C generated series was used to estimate the probability of misclassification. The method is particularly useful for estimating the probability of misclassification of the ecological status of surface water bodies in the case of short sequences of measurements of biological indices. The results of the Monte-Carlo simulations show a relatively high sensitivity of this probability to measurement errors of the river macrophyte index (MIR) and high robustness to measurement errors of the benthic macroinvertebrate index (MMI). The proposed method of using Monte-Carlo models to estimate the probability of misclassification has significant potential for assessing the uncertainty of water body status reported to the EC by the EU member countries according to WFD. The method can be readily applied also in risk assessment of water management decisions before adopting the status dependent corrective actions.

Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations

NASA Astrophysics Data System (ADS)

Saini, Jatinder; Maes, Dominic; Egan, Alexander; Bowen, Stephen R.; St. James, Sara; Janson, Martin; Wong, Tony; Bloch, Charles

2017-10-01

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and  >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations.

PubMed

Saini, Jatinder; Maes, Dominic; Egan, Alexander; Bowen, Stephen R; St James, Sara; Janson, Martin; Wong, Tony; Bloch, Charles

2017-09-12

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and  >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

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

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

Onizuka, R; Araki, F; Ohno, T

2016-06-15

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

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

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

Sakabe, D; Ohno, T; Araki, F

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

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

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

Wang, Z; Gao, M

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

Study of extracerebral contamination for three cerebral oximeters by Monte Carlo simulation using CT data

NASA Astrophysics Data System (ADS)

Tarasov, A. P.; Egorov, A. I.; Rogatkin, D. A.

2017-07-01

Using multidetector computed tomography, thicknesses of bone squame and soft tissues of human head were assessed. MC simulation revealed impropriety of source-detector separation distances for 3 oximeters, which can cause extracerebral contamination.

Electron Identification and Energy Measurement with Emulsion Cloud Chamber

NASA Astrophysics Data System (ADS)

Kitagawa, Nobuko; Komatsu, Masahiro

Charged particles undergo the Multiple Coulomb Scattering (MCS) when passing through a material. Their momentum can be estimated from the distribution of the scattering angle directly. Angle of electrons (or positrons) largely changes because of the energy loss in bremsstrahlung, and they are distinguished from other charged particles by making use of its feature. Electron energy is generally measured by counting of electromagnetic shower (e.m. shower) tracks in Emulsion Cloud Chamber (ECC), so enough absorber material is needed to develop the shower. In the range from sub-GeV to a few GeV, electrons don't develop noticeable showers. In order to estimate the energy of electrons in this range with a limited material, we established the new method which is based on the scattering angle considering the energy loss in bremsstrahlung. From the Monte Carlo simulation (MC) data, which is generated by electron beam (0.5 GeV, 1 GeV, 2 GeV) exposure to ECC, we derived the correlation between energy and scattering angle in each emulsion layer. We fixed the function and some parameters which 1 GeV MC sample would return 1 GeV as the center value, and then applied to 0.5 GeV and 2 GeV sample and confirmed the energy resolution about 50% within two radiation length.

Bayesian Orbit Computation Tools for Objects on Geocentric Orbits

NASA Astrophysics Data System (ADS)

Virtanen, J.; Granvik, M.; Muinonen, K.; Oszkiewicz, D.

2013-08-01

We consider the space-debris orbital inversion problem via the concept of Bayesian inference. The methodology has been put forward for the orbital analysis of solar system small bodies in early 1990's [7] and results in a full solution of the statistical inverse problem given in terms of a posteriori probability density function (PDF) for the orbital parameters. We demonstrate the applicability of our statistical orbital analysis software to Earth orbiting objects, both using well-established Monte Carlo (MC) techniques (for a review, see e.g. [13] as well as recently developed Markov-chain MC (MCMC) techniques (e.g., [9]). In particular, we exploit the novel virtual observation MCMC method [8], which is based on the characterization of the phase-space volume of orbital solutions before the actual MCMC sampling. Our statistical methods and the resulting PDFs immediately enable probabilistic impact predictions to be carried out. Furthermore, this can be readily done also for very sparse data sets and data sets of poor quality - providing that some a priori information on the observational uncertainty is available. For asteroids, impact probabilities with the Earth from the discovery night onwards have been provided, e.g., by [11] and [10], the latter study includes the sampling of the observational-error standard deviation as a random variable.

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

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

Biondo, Elliott D.; Wilson, Paul P. H.

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

DOE PAGES

Biondo, Elliott D.; Wilson, Paul P. H.

2017-05-08

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

Coarse-grained stochastic processes and kinetic Monte Carlo simulators for the diffusion of interacting particles

NASA Astrophysics Data System (ADS)

Katsoulakis, Markos A.; Vlachos, Dionisios G.

2003-11-01

We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.

Improvements in pencil beam scanning proton therapy dose calculation accuracy in brain tumor cases with a commercial Monte Carlo algorithm.

PubMed

Widesott, Lamberto; Lorentini, Stefano; Fracchiolla, Francesco; Farace, Paolo; Schwarz, Marco

2018-05-04

validation of a commercial Monte Carlo (MC) algorithm (RayStation ver6.0.024) for the treatment of brain tumours with pencil beam scanning (PBS) proton therapy, comparing it via measurements and analytical calculations in clinically realistic scenarios. Methods: For the measurements a 2D ion chamber array detector (MatriXX PT)) was placed underneath the following targets: 1) anthropomorphic head phantom (with two different thickness) and 2) a biological sample (i.e. half lamb's head). In addition, we compared the MC dose engine vs. the RayStation pencil beam (PB) algorithm clinically implemented so far, in critical conditions such as superficial targets (i.e. in need of range shifter), different air gaps and gantry angles to simulate both orthogonal and tangential beam arrangements. For every plan the PB and MC dose calculation were compared to measurements using a gamma analysis metrics (3%, 3mm). Results: regarding the head phantom the gamma passing rate (GPR) was always >96% and on average > 99% for the MC algorithm; PB algorithm had a GPR ≤90% for all the delivery configurations with single slab (apart 95 % GPR from gantry 0° and small air gap) and in case of two slabs of the head phantom the GPR was >95% only in case of small air gaps for all the three (0°, 45°,and 70°) simulated beam gantry angles. Overall the PB algorithm tends to overestimate the dose to the target (up to 25%) and underestimate the dose to the organ at risk (up to 30%). We found similar results (but a bit worse for PB algorithm) for the two targets of the lamb's head where only two beam gantry angles were simulated. Conclusions: our results suggest that in PBS proton therapy range shifter (RS) need to be used with extreme caution when planning the treatment with an analytical algorithm due to potentially great discrepancies between the planned dose and the dose delivered to the patients, also in case of brain tumours where this issue could be underestimated. Our results also suggest that a MC evaluation of the dose has to be performed every time the RS is used and, mostly, when it is used with large air gaps and beam directions tangential to the patient surface. . © 2018 Institute of Physics and Engineering in Medicine.

Monte Carlo calculations of positron emitter yields in proton radiotherapy.

PubMed

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

2012-03-21

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

Multileaf collimator tongue-and-groove effect on depth and off-axis doses: A comparison of treatment planning data with measurements and Monte Carlo calculations

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

Kim, Hee Jung; Department of Biomedical Engineering, Seoul National University, Seoul; Department of Radiation Oncology, Soonchunhyang University Hospital, Seoul

2015-01-01

To investigate how accurately treatment planning systems (TPSs) account for the tongue-and-groove (TG) effect, Monte Carlo (MC) simulations and radiochromic film (RCF) measurements were performed for comparison with TPS results. Two commercial TPSs computed the TG effect for Varian Millennium 120 multileaf collimator (MLC). The TG effect on off-axis dose profile at 3 depths of solid water was estimated as the maximum depth and the full width at half maximum (FWHM) of the dose dip at an interleaf position. When compared with the off-axis dose of open field, the maximum depth of the dose dip for MC and RCF rangedmore » from 10.1% to 20.6%; the maximum depth of the dose dip gradually decreased by up to 8.7% with increasing depths of 1.5 to 10 cm and also by up to 4.1% with increasing off-axis distances of 0 to 13 cm. However, TPS results showed at most a 2.7% decrease for the same depth range and a negligible variation for the same off-axis distances. The FWHM of the dose dip was approximately 0.19 cm for MC and 0.17 cm for RCF, but 0.30 cm for Eclipse TPS and 0.45 cm for Pinnacle TPS. Accordingly, the integrated value of TG dose dip for TPS was larger than that for MC and RCF and almost invariant along the depths and off-axis distances. We concluded that the TG dependence on depth and off-axis doses shown in the MC and RCF results could not be appropriately modeled by the TPS versions in this study.« less

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

PubMed

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

2011-09-07

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

An improved Monte-Carlo model of the Varian EPID separating support arm and rear-housing backscatter

NASA Astrophysics Data System (ADS)

Monville, M. E.; Kuncic, Z.; Greer, P. B.

2014-03-01

Previous investigators of EPID dosimetric properties have ascribed the backscatter, that contaminates dosimetric EPID images, to its supporting arm. Accordingly, Monte-Carlo (MC) EPID models have approximated the backscatter signal from the layers under the detector and the robotic support arm using either uniform or non-uniform solid water slabs, or through convolutions with back-scatter kernels. The aim of this work is to improve the existent MC models by measuring and modelling the separate backscatter contributions of the robotic arm and the rear plastic housing of the EPID. The EPID plastic housing is non-uniform with a 11.9 cm wide indented section that runs across the cross-plane direction in the superior half of the EPID which is 1.75 cm closer to the EPID sensitive layer than the rest of the housing. The thickness of the plastic housing is 0.5 cm. Experiments were performed with and without the housing present by removing all components of the EPID from the housing. The robotic support arm was not present for these measurements. A MC model of the linear accelerator and the EPID was modified to include the rear-housing indentation and results compared to the measurement. The rear housing was found to contribute a maximum of 3% additional signal. The rear housing contribution to the image is non-uniform in the in-plane direction with 2% asymmetry across the central 20 cm of an image irradiating the entire detector. The MC model was able to reproduce this non-uniform contribution. The EPID rear housing contributes a non-uniform backscatter component to the EPID image, which has not been previously characterized. This has been incorporated into an improved MC model of the EPID.

A Study of Neutron Leakage in Finite Objects

NASA Technical Reports Server (NTRS)

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

2015-01-01

A computationally efficient 3DHZETRN code capable of simulating High charge (Z) and Energy (HZE) and light ions (including neutrons) under space-like boundary conditions with enhanced neutron and light ion propagation was recently developed for simple shielded objects. Monte Carlo (MC) benchmarks were used to verify the 3DHZETRN methodology in slab and spherical geometry, and it was shown that 3DHZETRN agrees with MC codes to the degree that various MC codes agree among themselves. One limitation in the verification process is that all of the codes (3DHZETRN and three MC codes) utilize different nuclear models/databases. In the present report, the new algorithm, with well-defined convergence criteria, is used to quantify the neutron leakage from simple geometries to provide means of verifying 3D effects and to provide guidance for further code development.

Combined Molecular Algorithms for the Generation, Equilibration and Topological Analysis of Entangled Polymers: Methodology and Performance

PubMed Central

Karayiannis, Nikos Ch.; Kröger, Martin

2009-01-01

We review the methodology, algorithmic implementation and performance characteristics of a hierarchical modeling scheme for the generation, equilibration and topological analysis of polymer systems at various levels of molecular description: from atomistic polyethylene samples to random packings of freely-jointed chains of tangent hard spheres of uniform size. Our analysis focuses on hitherto less discussed algorithmic details of the implementation of both, the Monte Carlo (MC) procedure for the system generation and equilibration, and a postprocessing step, where we identify the underlying topological structure of the simulated systems in the form of primitive paths. In order to demonstrate our arguments, we study how molecular length and packing density (volume fraction) affect the performance of the MC scheme built around chain-connectivity altering moves. In parallel, we quantify the effect of finite system size, of polydispersity, and of the definition of the number of entanglements (and related entanglement molecular weight) on the results about the primitive path network. Along these lines we approve main concepts which had been previously proposed in the literature. PMID:20087477

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.

SU-F-19A-05: Experimental and Monte Carlo Characterization of the 1 Cm CivaString 103Pd Brachytherapy Source

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

Reed, J; Micka, J; Culberson, W

Purpose: To determine the in-air azimuthal anisotropy and in-water dose distribution for the 1 cm length of the CivaString {sup 103}Pd brachytherapy source through measurements and Monte Carlo (MC) simulations. American Association of Physicists in Medicine Task Group No. 43 (TG-43) dosimetry parameters were also determined for this source. Methods: The in-air azimuthal anisotropy of the source was measured with a NaI scintillation detector and simulated with the MCNP5 radiation transport code. Measured and simulated results were normalized to their respective mean values and compared. The TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function for this sourcemore » were determined from LiF:Mg,Ti thermoluminescent dosimeter (TLD) measurements and MC simulations. The impact of {sup 103}Pd well-loading variability on the in-water dose distribution was investigated using MC simulations by comparing the dose distribution for a source model with four wells of equal strength to that for a source model with strengths increased by 1% for two of the four wells. Results: NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy showed that ≥95% of the normalized data were within 1.2% of the mean value. TLD measurements and MC simulations of the TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function agreed to within the experimental TLD uncertainties (k=2). MC simulations showed that a 1% variability in {sup 103}Pd well-loading resulted in changes of <0.1%, <0.1%, and <0.3% in the TG-43 dose-rate constant, radial dose distribution, and polar dose distribution, respectively. Conclusion: The CivaString source has a high degree of azimuthal symmetry as indicated by the NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy. TG-43 dosimetry parameters for this source were determined from TLD measurements and MC simulations. {sup 103}Pd well-loading variability results in minimal variations in the in-water dose distribution according to MC simulations. This work was partially supported by CivaTech Oncology, Inc. through an educational grant for Joshua Reed, John Micka, Wesley Culberson, and Larry DeWerd and through research support for Mark Rivard.« less

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

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

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

2015-06-15

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

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

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

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

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

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

PubMed

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

2012-06-01

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

SU-F-T-74: Experimental Validation of Monaco Electron Monte Carlo Dose Calculation for Small Fields

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

Varadhan; Way, S; Arentsen, L

2016-06-15

Purpose: To verify experimentally the accuracy of Monaco (Elekta) electron Monte Carlo (eMC) algorithm to calculate small field size depth doses, monitor units and isodose distributions. Methods: Beam modeling of eMC algorithm was performed for electron energies of 6, 9, 12 15 and 18 Mev for a Elekta Infinity Linac and all available ( 6, 10, 14 20 and 25 cone) applicator sizes. Electron cutouts of incrementally smaller field sizes (20, 40, 60 and 80% blocked from open cone) were fabricated. Dose calculation was performed using a grid size smaller than one-tenth of the R{sub 80–20} electron distal falloff distancemore » and number of particle histories was set at 500,000 per cm{sup 2}. Percent depth dose scans and beam profiles at dmax, d{sub 90} and d{sub 80} depths were measured for each cutout and energy with Wellhoffer (IBA) Blue Phantom{sup 2} scanning system and compared against eMC calculated doses. Results: The measured dose and output factors of incrementally reduced cutout sizes (to 3cm diameter) agreed with eMC calculated doses within ± 2.5%. The profile comparisons at dmax, d{sub 90} and d{sub 80} depths and percent depth doses at reduced field sizes agreed within 2.5% or 2mm. Conclusion: Our results indicate that the Monaco eMC algorithm can accurately predict depth doses, isodose distributions, and monitor units in homogeneous water phantom for field sizes as small as 3.0 cm diameter for energies in the 6 to 18 MeV range at 100 cm SSD. Consequently, the old rule of thumb to approximate limiting cutout size for an electron field determined by the lateral scatter equilibrium (E (MeV)/2.5 in centimeters of water) does not apply to Monaco eMC algorithm.« less

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

PubMed

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

2014-05-01

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

Kinetic Monte Carlo Simulations of Rod Eutectics and the Surface Roughening Transition in Binary Alloys

NASA Technical Reports Server (NTRS)

Bentz, Daniel N.; Betush, William; Jackson, Kenneth A.

2003-01-01

In this paper we report on two related topics: Kinetic Monte Carlo simulations of the steady state growth of rod eutectics from the melt, and a study of the surface roughness of binary alloys. We have implemented a three dimensional kinetic Monte Carlo (kMC) simulation with diffusion by pair exchange only in the liquid phase. Entropies of fusion are first chosen to fit the surface roughness of the pure materials, and the bond energies are derived from the equilibrium phase diagram, by treating the solid and liquid as regular and ideal solutions respectively. A simple cubic lattice oriented in the {100} direction is used. Growth of the rods is initiated from columns of pure B material embedded in an A matrix, arranged in a close packed array with semi-periodic boundary conditions. The simulation cells typically have dimensions of 50 by 87 by 200 unit cells. Steady state growth is compliant with the Jackson-Hunt model. In the kMC simulations, using the spin-one Ising model, growth of each phase is faceted or nonfaceted phases depending on the entropy of fusion. There have been many studies of the surface roughening transition in single component systems, but none for binary alloy systems. The location of the surface roughening transition for the phases of a eutectic alloy determines whether the eutectic morphology will be regular or irregular. We have conducted a study of surface roughness on the spin-one Ising Model with diffusion using kMC. The surface roughness was found to scale with the melting temperature of the alloy as given by the liquidus line on the equilibrium phase diagram. The density of missing lateral bonds at the surface was used as a measure of surface roughness.

On the Monte Carlo simulation of electron transport in the sub-1 keV energy range.

PubMed

Thomson, Rowan M; Kawrakow, Iwan

2011-08-01

The validity of "classic" Monte Carlo (MC) simulations of electron and positron transport at sub-1 keV energies is investigated in the context of quantum theory. Quantum theory dictates that uncertainties on the position and energy-momentum four-vectors of radiation quanta obey Heisenberg's uncertainty relation; however, these uncertainties are neglected in "classical" MC simulations of radiation transport in which position and momentum are known precisely. Using the quantum uncertainty relation and electron mean free path, the magnitudes of uncertainties on electron position and momentum are calculated for different kinetic energies; a validity bound on the classical simulation of electron transport is derived. In order to satisfy the Heisenberg uncertainty principle, uncertainties of 5% must be assigned to position and momentum for 1 keV electrons in water; at 100 eV, these uncertainties are 17 to 20% and are even larger at lower energies. In gaseous media such as air, these uncertainties are much smaller (less than 1% for electrons with energy 20 eV or greater). The classical Monte Carlo transport treatment is questionable for sub-1 keV electrons in condensed water as uncertainties on position and momentum must be large (relative to electron momentum and mean free path) to satisfy the quantum uncertainty principle. Simulations which do not account for these uncertainties are not faithful representations of the physical processes, calling into question the results of MC track structure codes simulating sub-1 keV electron transport. Further, the large difference in the scale at which quantum effects are important in gaseous and condensed media suggests that track structure measurements in gases are not necessarily representative of track structure in condensed materials on a micrometer or a nanometer scale.

GATE Monte Carlo simulation in a cloud computing environment

NASA Astrophysics Data System (ADS)

Rowedder, Blake Austin

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

Parallel and Portable Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Lee, S. R.; Cummings, J. C.; Nolen, S. D.; Keen, N. D.

1997-08-01

We have developed a multi-group, Monte Carlo neutron transport code in C++ using object-oriented methods and the Parallel Object-Oriented Methods and Applications (POOMA) class library. This transport code, called MC++, currently computes k and α eigenvalues of the neutron transport equation on a rectilinear computational mesh. It is portable to and runs in parallel on a wide variety of platforms, including MPPs, clustered SMPs, and individual workstations. It contains appropriate classes and abstractions for particle transport and, through the use of POOMA, for portable parallelism. Current capabilities are discussed, along with physics and performance results for several test problems on a variety of hardware, including all three Accelerated Strategic Computing Initiative (ASCI) platforms. Current parallel performance indicates the ability to compute α-eigenvalues in seconds or minutes rather than days or weeks. Current and future work on the implementation of a general transport physics framework (TPF) is also described. This TPF employs modern C++ programming techniques to provide simplified user interfaces, generic STL-style programming, and compile-time performance optimization. Physics capabilities of the TPF will be extended to include continuous energy treatments, implicit Monte Carlo algorithms, and a variety of convergence acceleration techniques such as importance combing.

Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study

NASA Astrophysics Data System (ADS)

Lerendegui-Marco, J.; Cortés-Giraldo, M. A.; Guerrero, C.; Quesada, J. M.; Meo, S. Lo; Massimi, C.; Barbagallo, M.; Colonna, N.; Mancussi, D.; Mingrone, F.; Sabaté-Gilarte, M.; Vannini, G.; Vlachoudis, V.; Aberle, O.; Andrzejewski, J.; Audouin, L.; Bacak, M.; Balibrea, J.; Bečvář, F.; Berthoumieux, E.; Billowes, J.; Bosnar, D.; Brown, A.; Caamaño, M.; Calviño, F.; Calviani, M.; Cano-Ott, D.; Cardella, R.; Casanovas, A.; Cerutti, F.; Chen, Y. H.; Chiaveri, E.; Cortés, G.; Cosentino, L.; Damone, L. A.; Diakaki, M.; Domingo-Pardo, C.; Dressler, R.; Dupont, E.; Durán, I.; Fernández-Domínguez, B.; Ferrari, A.; Ferreira, P.; Finocchiaro, P.; Göbel, K.; Gómez-Hornillos, M. B.; García, A. R.; Gawlik, A.; Gilardoni, S.; Glodariu, T.; Gonçalves, I. F.; González, E.; Griesmayer, E.; Gunsing, F.; Harada, H.; Heinitz, S.; Heyse, J.; Jenkins, D. G.; Jericha, E.; Käppeler, F.; Kadi, Y.; Kalamara, A.; Kavrigin, P.; Kimura, A.; Kivel, N.; Kokkoris, M.; Krtička, M.; Kurtulgil, D.; Leal-Cidoncha, E.; Lederer, C.; Leeb, H.; Lonsdale, S. J.; Macina, D.; Marganiec, J.; Martínez, T.; Masi, A.; Mastinu, P.; Mastromarco, M.; Maugeri, E. A.; Mazzone, A.; Mendoza, E.; Mengoni, A.; Milazzo, P. M.; Musumarra, A.; Negret, A.; Nolte, R.; Oprea, A.; Patronis, N.; Pavlik, A.; Perkowski, J.; Porras, I.; Praena, J.; Radeck, D.; Rauscher, T.; Reifarth, R.; Rout, P. C.; Rubbia, C.; Ryan, J. A.; Saxena, A.; Schillebeeckx, P.; Schumann, D.; Smith, A. G.; Sosnin, N. V.; Stamatopoulos, A.; Tagliente, G.; Tain, J. L.; Tarifeño-Saldivia, A.; Tassan-Got, L.; Valenta, S.; Variale, V.; Vaz, P.; Ventura, A.; Vlastou, R.; Wallner, A.; Warren, S.; Woods, P. J.; Wright, T.; Žugec, P.

2017-09-01

Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field had been MCNPX and FLUKA. However, the Geant4 toolkit has also become a competitive code for the transport of neutrons after the development of the native Geant4 format for neutron data libraries, G4NDL. In this context, we present the Geant4 simulations of the neutron spallation target of the n_TOF facility at CERN, done with version 10.1.1 of the toolkit. The first goal was the validation of the intra-nuclear cascade models implemented in the code using, as benchmark, the characteristics of the neutron beam measured at the first experimental area (EAR1), especially the neutron flux and energy distribution, and the time distribution of neutrons of equal kinetic energy, the so-called Resolution Function. The second goal was the development of a Monte Carlo tool aimed to provide useful calculations for both the analysis and planning of the upcoming measurements at the new experimental area (EAR2) of the facility.

Neutron track length estimator for GATE Monte Carlo dose calculation in radiotherapy.

PubMed

Elazhar, H; Deschler, T; Létang, J M; Nourreddine, A; Arbor, N

2018-06-20

The out-of-field dose in radiation therapy is a growing concern in regards to the late side-effects and secondary cancer induction. In high-energy x-ray therapy, the secondary neutrons generated through photonuclear reactions in the accelerator are part of this secondary dose. The neutron dose is currently not estimated by the treatment planning system while it appears to be preponderant for distances greater than 50 cm from the isocenter. Monte Carlo simulation has become the gold standard for accurately calculating the neutron dose under specific treatment conditions but the method is also known for having a slow statistical convergence, which makes it difficult to be used on a clinical basis. The neutron track length estimator, a neutron variance reduction technique inspired by the track length estimator method has thus been developped for the first time in the Monte Carlo code GATE to allow a fast computation of the neutron dose in radiotherapy. The details of its implementation, as well as the comparison of its performances against the analog MC method, are presented here. A gain of time from 15 to 400 can be obtained by our method, with a mean difference in the dose calculation of about 1% in comparison with the analog MC method.

The SM and NLO Multileg and SM MC Working Groups: Summary Report

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

Alcaraz Maestre, J.; et al.

2012-03-01

The 2011 Les Houches workshop was the first to confront LHC data. In the two years since the previous workshop there have been significant advances in both soft and hard QCD, particularly in the areas of multi-leg NLO calculations, the inclusion of those NLO calculations into parton shower Monte Carlos, and the tuning of the non-perturbative parameters of those Monte Carlos. These proceedings describe the theoretical advances that have taken place, the impact of the early LHC data, and the areas for future development.

KMCThinFilm: A C++ Framework for the Rapid Development of Lattice Kinetic Monte Carlo (kMC) Simulations of Thin Film Growth

DTIC Science & Technology

2015-09-01

direction, so if the simulation domain is set to be a certain size, then that presents a hard ceiling on the thickness of a film that may be grown in...FFA, Los J, Cuppen HM, Bennema P, Meekes H. MONTY:  Monte Carlo crystal growth on any crystal structure in any crystallographic orientation...mhoffman.github.io/kmos/. 23. Kiravittaya S, Schmidt OG. Quantum-dot crystal defects. Applied Physics Letters. 2008;93:173109. 24. Leetmaa M

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation

NASA Astrophysics Data System (ADS)

Magro, G.; Molinelli, S.; Mairani, A.; Mirandola, A.; Panizza, D.; Russo, S.; Ferrari, A.; Valvo, F.; Fossati, P.; Ciocca, M.

2015-09-01

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo® TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus® chamber. An EBT3® film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation.

PubMed

Magro, G; Molinelli, S; Mairani, A; Mirandola, A; Panizza, D; Russo, S; Ferrari, A; Valvo, F; Fossati, P; Ciocca, M

2015-09-07

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo(®) TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus(®) chamber. An EBT3(®) film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

A compression algorithm for the combination of PDF sets.

PubMed

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

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

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

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

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

2015-04-21

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

Development of an effective dose coefficient database using a computational human phantom and Monte Carlo simulations to evaluate exposure dose for the usage of NORM-added consumer products.

PubMed

Yoo, Do Hyeon; Shin, Wook-Geun; Lee, Jaekook; Yeom, Yeon Soo; Kim, Chan Hyeong; Chang, Byung-Uck; Min, Chul Hee

2017-11-01

After the Fukushima accident in Japan, the Korean Government implemented the "Act on Protective Action Guidelines Against Radiation in the Natural Environment" to regulate unnecessary radiation exposure to the public. However, despite the law which came into effect in July 2012, an appropriate method to evaluate the equivalent and effective doses from naturally occurring radioactive material (NORM) in consumer products is not available. The aim of the present study is to develop and validate an effective dose coefficient database enabling the simple and correct evaluation of the effective dose due to the usage of NORM-added consumer products. To construct the database, we used a skin source method with a computational human phantom and Monte Carlo (MC) simulation. For the validation, the effective dose was compared between the database using interpolation method and the original MC method. Our result showed a similar equivalent dose across the 26 organs and a corresponding average dose between the database and the MC calculations of < 5% difference. The differences in the effective doses were even less, and the result generally show that equivalent and effective doses can be quickly calculated with the database with sufficient accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Monte Carlo grain growth modeling with local temperature gradients

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Comparison of doses calculated by the Monte Carlo method and measured by LiF TLD in the buildup region for a 60Co photon beam.

PubMed

Budanec, M; Knezević, Z; Bokulić, T; Mrcela, I; Vrtar, M; Vekić, B; Kusić, Z

2008-12-01

This work studied the percent depth doses of (60)Co photon beams in the buildup region of a plastic phantom by LiF TLD measurements and by Monte Carlo calculations. An agreement within +/-1.5% was found between PDDs measured by TLD and calculated by the Monte Carlo method with the TLD in a plastic phantom. The dose in the plastic phantom was scored in voxels, with thickness scaled by physical and electron density. PDDs calculated by electron density scaling showed a better match with PDD(TLD)(MC); the difference is within +/-1.5% in the buildup region for square and rectangular field sizes.

Spin polarisation of tt¯γγ production at NLO+PS with GoSam interfaced to MadGraph5_aMC@NLO

DOE PAGES

van Deurzen, Hans; Frederix, Rikkert; Hirschi, Valentin; ...

2016-04-22

Here, we present an interface between the multipurpose Monte Carlo tool MadGraph5_aMC@NLO and the automated amplitude generator GoSam. As a first application of this novel framework, we compute the NLO corrections to pp→ tt¯H and pp→ tt¯γγ matched to a parton shower. In the phenomenological analyses of these processes, we focus our attention on observables which are sensitive to the polarisation of the top quarks.

Spin polarisation of tt¯γγ production at NLO+PS with GoSam interfaced to MadGraph5_aMC@NLO

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

van Deurzen, Hans; Frederix, Rikkert; Hirschi, Valentin

Here, we present an interface between the multipurpose Monte Carlo tool MadGraph5_aMC@NLO and the automated amplitude generator GoSam. As a first application of this novel framework, we compute the NLO corrections to pp→ tt¯H and pp→ tt¯γγ matched to a parton shower. In the phenomenological analyses of these processes, we focus our attention on observables which are sensitive to the polarisation of the top quarks.

McStas 1.7 - a new version of the flexible Monte Carlo neutron scattering package

NASA Astrophysics Data System (ADS)

Willendrup, Peter; Farhi, Emmanuel; Lefmann, Kim

2004-07-01

Current neutron instrumentation is both complex and expensive, and accurate simulation has become essential both for building new instruments and for using them effectively. The McStas neutron ray-trace simulation package is a versatile tool for producing such simulations, developed in collaboration between Risø and ILL. The new version (1.7) has many improvements, among these added support for the popular Microsoft Windows platform. This presentation will demonstrate a selection of the new features through a simulation of the ILL IN6 beamline.

Interfacing MCNPX and McStas for simulation of neutron transport

NASA Astrophysics Data System (ADS)

Klinkby, Esben; Lauritzen, Bent; Nonbøl, Erik; Kjær Willendrup, Peter; Filges, Uwe; Wohlmuther, Michael; Gallmeier, Franz X.

2013-02-01

Simulations of target-moderator-reflector system at spallation sources are conventionally carried out using Monte Carlo codes such as MCNPX (Waters et al., 2007 [1]) or FLUKA (Battistoni et al., 2007; Ferrari et al., 2005 [2,3]) whereas simulations of neutron transport from the moderator and the instrument response are performed by neutron ray tracing codes such as McStas (Lefmann and Nielsen, 1999; Willendrup et al., 2004, 2011a,b [4-7]). The coupling between the two simulation suites typically consists of providing analytical fits of MCNPX neutron spectra to McStas. This method is generally successful but has limitations, as it e.g. does not allow for re-entry of neutrons into the MCNPX regime. Previous work to resolve such shortcomings includes the introduction of McStas inspired supermirrors in MCNPX. In the present paper different approaches to interface MCNPX and McStas are presented and applied to a simple test case. The direct coupling between MCNPX and McStas allows for more accurate simulations of e.g. complex moderator geometries, backgrounds, interference between beam-lines as well as shielding requirements along the neutron guides.

Improved Hybrid Modeling of Spent Fuel Storage Facilities

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

Bibber, Karl van

This work developed a new computational method for improving the ability to calculate the neutron flux in deep-penetration radiation shielding problems that contain areas with strong streaming. The “gold standard” method for radiation transport is Monte Carlo (MC) as it samples the physics exactly and requires few approximations. Historically, however, MC was not useful for shielding problems because of the computational challenge of following particles through dense shields. Instead, deterministic methods, which are superior in term of computational effort for these problems types but are not as accurate, were used. Hybrid methods, which use deterministic solutions to improve MC calculationsmore » through a process called variance reduction, can make it tractable from a computational time and resource use perspective to use MC for deep-penetration shielding. Perhaps the most widespread and accessible of these methods are the Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods. For problems containing strong anisotropies, such as power plants with pipes through walls, spent fuel cask arrays, active interrogation, and locations with small air gaps or plates embedded in water or concrete, hybrid methods are still insufficiently accurate. In this work, a new method for generating variance reduction parameters for strongly anisotropic, deep penetration radiation shielding studies was developed. This method generates an alternate form of the adjoint scalar flux quantity, Φ Ω, which is used by both CADIS and FW-CADIS to generate variance reduction parameters for local and global response functions, respectively. The new method, called CADIS-Ω, was implemented in the Denovo/ADVANTG software. Results indicate that the flux generated by CADIS-Ω incorporates localized angular anisotropies in the flux more effectively than standard methods. CADIS-Ω outperformed CADIS in several test problems. This initial work indicates that CADIS- may be highly useful for shielding problems with strong angular anisotropies. This is a benefit to the public by increasing accuracy for lower computational effort for many problems that have energy, security, and economic importance.« less

SU-F-T-115: Uncertainty in the Esophagus Dose in Retrospective Epidemiological Study of Breast Cancer Radiotherapy Patients

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

Mosher, E; Kim, S; Lee, C

Purpose: Epidemiological studies of second cancer risks in breast cancer radiotherapy patients often use generic patient anatomy to reconstruct normal tissue doses when CT images of patients are not available. To evaluate the uncertainty involved in the dosimetry approach, we evaluated the esophagus dose in five sample patients by simulating breast cancer treatments. Methods: We obtained the diagnostic CT images of five anonymized adult female patients in different Body Mass Index (BMI) categories (16– 36kg/m2) from National Institutes of Health Clinical Center. We contoured the esophagus on the CT images and imported them into a Treatment Planning System (TPS) tomore » create treatment plans and calculate esophagus doses. Esophagus dose was calculated once again via experimentally-validated Monte Carlo (MC) transport code, XVMC under the same geometries. We compared the esophagus doses from TPS and the MC method. We also investigated the degree of variation in the esophagus dose across the five patients and also the relationship between the patient characteristics and the esophagus doses. Results: Eclipse TPS using Analytical Anisotropic Algorithm (AAA) significantly underestimates the esophagus dose in breast cancer radiotherapy compared to MC. In the worst case, the esophagus dose from AAA was only 40% of the MC dose. The Coefficient of Variation across the patients was 48%. We found that the maximum esophagus dose was up to 2.7 times greater than the minimum. We finally observed linear relationship (Dose = 0.0218 × BMI – 0.1, R2=0.54) between patient’s BMI and the esophagus doses. Conclusion: We quantified the degree of uncertainty in the esophagus dose in five sample breast radiotherapy patients. The results of the study underscore the importance of individualized dose reconstruction for the study cohort to avoid misclassification in the risk analysis of second cancer. We are currently extending the number of patients up to 30.« less

Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems

DOE PAGES

Biondo, Elliott D.; Davidson, Gregory G.; Pandya, Tara M.; ...

2018-04-30

The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SPNSPN or SNSN solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solutionmore » parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. Here it is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.« less

Applications of Monte Carlo method to nonlinear regression of rheological data

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems

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

Biondo, Elliott D.; Davidson, Gregory G.; Pandya, Tara M.

The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SPNSPN or SNSN solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solutionmore » parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. Here it is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.« less

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

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

Sisniega, A; Zbijewski, W; Stayman, J

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

SU-F-T-371: Development of a Linac Monte Carlo Model to Calculate Surface Dose

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

Prajapati, S; Yan, Y; Gifford, K

2016-06-15

Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V4-2.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V4-2.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films weremore » placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and was 3.5% for MLC. For the 6 MV beam, the average root mean square(RMS) deviation for the central 80% of the beam profile for open fields was 1.5%, whereas it was 1.6% for MLC. For the 18 MV beam, the maximum RMS for open fields was 3%, and was 3.1% for MLC. Conclusion: The MC model of a linac agreed to within 4% of film measurements for depths ranging from the surface to dmax. Therefore, the MC linac model can predict surface dose for clinical applications. Future work will focus on adjusting the linac MC model to reduce RMS error and improve accuracy.« less

ProMC: Input-output data format for HEP applications using varint encoding

NASA Astrophysics Data System (ADS)

Chekanov, S. V.; May, E.; Strand, K.; Van Gemmeren, P.

2014-10-01

A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach is implemented in the PROMC library which produces smaller file sizes for MC records compared to the existing input-output libraries used in high-energy physics (HEP). Other important features of the proposed format are a separation of abstract data layouts from concrete programming implementations, self-description and random access. Data stored in PROMC files can be written, read and manipulated in a number of programming languages, such C++, JAVA, FORTRAN and PYTHON.

The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation

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

Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.

2015-12-01

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple becausemore » it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.« less

Hybrid computer optimization of systems with random parameters

NASA Technical Reports Server (NTRS)

White, R. C., Jr.

1972-01-01

A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

LRFD Resistance Factor Calibration for Axially Loaded Drilled Shafts in the Las Vegas Valley

DOT National Transportation Integrated Search

2016-07-19

Resistance factors for LRFD of axially loaded drilled shafts in the Las Vegas Valley are calibrated using data from 41 field load tests. In addition to the traditional implementation of Monte Carlo (MC) simulations for calibration, a more robust tech...

The effect of voxel size on dose distribution in Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Yani, Sitti; Dirgayussa, I. Gde E.; Rhani, Moh. Fadhillah; Haryanto, Freddy; Arif, Idam

2015-09-01

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. The MC code system (especially DOSXYZnrc) has been used to investigate the different voxel (volume elements) sizes effect on the accuracy of dose distributions. To investigate this effect on dosimetry parameters, calculations were made with three different voxel sizes. The effects were investigated with dose distribution calculations for seven voxel sizes: 1 × 1 × 0.1 cm3, 1 × 1 × 0.5 cm3, and 1 × 1 × 0.8 cm3. The 1 × 109 histories were simulated in order to get statistical uncertainties of 2%. This simulation takes about 9-10 hours to complete. Measurements are made with field sizes 10 × 10 cm2 for the 6 MV photon beams with Gaussian intensity distribution FWHM 0.1 cm and SSD 100.1 cm. MC simulated and measured dose distributions in a water phantom. The output of this simulation i.e. the percent depth dose and dose profile in dmax from the three sets of calculations are presented and comparisons are made with the experiment data from TTSH (Tan Tock Seng Hospital, Singapore) in 0-5 cm depth. Dose that scored in voxels is a volume averaged estimate of the dose at the center of a voxel. The results in this study show that the difference between Monte Carlo simulation and experiment data depend on the voxel size both for percent depth dose (PDD) and profile dose. PDD scan on Z axis (depth) of water phantom, the big difference obtain in the voxel size 1 × 1 × 0.8 cm3 about 17%. In this study, the profile dose focused on high gradient dose area. Profile dose scan on Y axis and the big difference get in the voxel size 1 × 1 × 0.1 cm3 about 12%. This study demonstrated that the arrange voxel in Monte Carlo simulation becomes important.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

NASA Astrophysics Data System (ADS)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Poster — Thur Eve — 47: Monte Carlo Simulation of Scp, Sc and Sp

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

Zhan, Lixin; Jiang, Runqing; Osei, Ernest K.

The in-water output ratio (Scp), in-air output ratio (Sc), and phantom scattering factor (Sp) are important parameters for radiotherapy dose calculation. Experimentally, Scp is obtained by measuring the dose rate ratio in water phantom, and Sc the water Kerma rate ratio in air. There is no method that allows direct measurement of Sp. Monte Carlo (MC) method has been used to simulate Scp and Sc in literatures, similar to experimental setup, but no MC direct simulation of Sp available yet to the best of our knowledge. We propose in this report a method of performing direct MC simulation of Sp.more » Starting from the definition, we derived that Sp of a clinical photon beam can be approximated by the ratio of the dose rates contributed from the primary beam for a given field size to the reference field size. Since only the primary beam is used, any Linac head scattering should be excluded from the simulation, which can be realized by using the incident electron as a scoring parameter for MU. We performed MC simulations for Scp, Sc and Sp. Scp matches well with golden beam data. Sp obtained by the proposed method agrees well with what is obtained using the traditional method, Sp=Scp/Sc. Since the smaller the field size, the more the primary beam dominates, our Sp simulation method is accurate for small field. By analyzing the calculated data, we found that this method can be used with no problem for large fields. The difference it introduced is clinically insignificant.« less

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

PubMed

Liu, T; Ding, A; Xu, X

2012-06-01

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

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

PubMed Central

2016-01-01

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

Dosimetry applications in GATE Monte Carlo toolkit.

PubMed

Papadimitroulas, Panagiotis

2017-09-01

Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Monte Carlo simulation of the resolution volume for the SEQUOIA spectrometer

NASA Astrophysics Data System (ADS)

Granroth, G. E.; Hahn, S. E.

2015-01-01

Monte Carlo ray tracing simulations, of direct geometry spectrometers, have been particularly useful in instrument design and characterization. However, these tools can also be useful for experiment planning and analysis. To this end, the McStas Monte Carlo ray tracing model of SEQUOIA, the fine resolution fermi chopper spectrometer at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (ORNL), has been modified to include the time of flight resolution sample and detector components. With these components, the resolution ellipsoid can be calculated for any detector pixel and energy bin of the instrument. The simulation is split in two pieces. First, the incident beamline up to the sample is simulated for 1 × 1011 neutron packets (4 days on 30 cores). This provides a virtual source for the backend that includes the resolution sample and monitor components. Next, a series of detector and energy pixels are computed in parallel. It takes on the order of 30 s to calculate a single resolution ellipsoid on a single core. Python scripts have been written to transform the ellipsoid into the space of an oriented single crystal, and to characterize the ellipsoid in various ways. Though this tool is under development as a planning tool, we have successfully used it to provide the resolution function for convolution with theoretical models. Specifically, theoretical calculations of the spin waves in YFeO3 were compared to measurements taken on SEQUOIA. Though the overall features of the spectra can be explained while neglecting resolution effects, the variation in intensity of the modes is well described once the resolution is included. As this was a single sharp mode, the simulated half intensity value of the resolution ellipsoid was used to provide the resolution width. A description of the simulation, its use, and paths forward for this technique will be discussed.

Two-dimensional molecular line transfer for a cometary coma

NASA Astrophysics Data System (ADS)

Szutowicz, S.

2017-09-01

In the proposed axisymmetric model of the cometary coma the gas density profile is described by an angular density function. Three methods for treating two-dimensional radiative transfer are compared: the Large Velocity Gradient (LVG) (the Sobolev method), Accelerated Lambda Iteration (ALI) and accelerated Monte Carlo (MC).

Microsolvation of Cl anion by water clusters: Pertubative Monte Carlo simulations using a hybrid HF/MM potential

NASA Astrophysics Data System (ADS)

Truong, Thanh N.; Stefanovich, Eugene V.

1997-05-01

We present a study of micro-solvation of Cl anion by water clusters of the size up to seven molecules using a perturbative Monte Carlo approach with a hybrid HF/MM potential. In this approach, a perturbation theory was used to avoid performing full SCF calculations at every Monte Carlo step. In this study, the anion is treated quantum mechanically at the HF/6-31G ∗ level of theory while interactions between solvent waters are presented by the TIP3P potential force field. Analysis on the solvent induced dipole moment of the ion indicates that the Cl anion resides most of the time on the surface of the clusters. Accuracy of the perturbative MC approach is also discussed.

Self-learning Monte Carlo with deep neural networks

NASA Astrophysics Data System (ADS)

Shen, Huitao; Liu, Junwei; Fu, Liang

2018-05-01

The self-learning Monte Carlo (SLMC) method is a general algorithm to speedup MC simulations. Its efficiency has been demonstrated in various systems by introducing an effective model to propose global moves in the configuration space. In this paper, we show that deep neural networks can be naturally incorporated into SLMC, and without any prior knowledge can learn the original model accurately and efficiently. Demonstrated in quantum impurity models, we reduce the complexity for a local update from O (β2) in Hirsch-Fye algorithm to O (β lnβ ) , which is a significant speedup especially for systems at low temperatures.

Monte Carlo simulation of particle-induced bit upsets

NASA Astrophysics Data System (ADS)

Wrobel, Frédéric; Touboul, Antoine; Vaillé, Jean-Roch; Boch, Jérôme; Saigné, Frédéric

2017-09-01

We investigate the issue of radiation-induced failures in electronic devices by developing a Monte Carlo tool called MC-Oracle. It is able to transport the particles in device, to calculate the energy deposited in the sensitive region of the device and to calculate the transient current induced by the primary particle and the secondary particles produced during nuclear reactions. We compare our simulation results with SRAM experiments irradiated with neutrons, protons and ions. The agreement is very good and shows that it is possible to predict the soft error rate (SER) for a given device in a given environment.

Evaluation of dosimetric properties of shielding disk used in intraoperative electron radiotherapy: A Monte Carlo study.

PubMed

Robatjazi, Mostafa; Baghani, Hamid Reza; Mahdavic, Seied Rabi; Felici, Giuseppe

2018-05-01

A shielding disk is used for IOERT procedures to absorb radiation behind the target and protect underlying healthy tissues. Setup variation of shielding disk can affect the corresponding in-vivo dose distribution. In this study, the changes of dosimetric parameters due to the disk setup variations is evaluated using EGSnrc Monte Carlo (MC) code. The results can help treatment team to decide about the level of accuracy in the setup procedure and delivered dose to the target volume during IOERT. Copyright © 2018 Elsevier Ltd. All rights reserved.

The multi-scattering model for calculations of positron spatial distribution in the multilayer stacks, useful for conventional positron measurements

NASA Astrophysics Data System (ADS)

Dryzek, Jerzy; Siemek, Krzysztof

2013-08-01

The spatial distribution of positrons emitted from radioactive isotopes into stacks or layered samples is a subject of the presented report. It was found that Monte Carlo (MC) simulations using GEANT4 code are not able to describe correctly the experimental data of the positron fractions in stacks. The mathematical model was proposed for calculations of the implantation profile or positron fractions in separated layers or foils being components of a stack. The model takes into account only two processes, i.e., the positron absorption and backscattering at interfaces. The mathematical formulas were applied in the computer program called LYS-1 (layers profile analysis). The theoretical predictions of the model were in the good agreement with the results of the MC simulations for the semi infinite sample. The experimental verifications of the model were performed on the symmetrical and non-symmetrical stacks of different foils. The good agreement between the experimental and calculated fractions of positrons in components of a stack was achieved. Also the experimental implantation profile obtained using the depth scanning of positron implantation technique is very well described by the theoretical profile obtained within the proposed model. The LYS-1 program allows us also to calculate the fraction of positrons which annihilate in the source, which can be useful in the positron spectroscopy.

Methods for modeling non-equilibrium degenerate statistics and quantum-confined scattering in 3D ensemble Monte Carlo transport simulations

NASA Astrophysics Data System (ADS)

Crum, Dax M.; Valsaraj, Amithraj; David, John K.; Register, Leonard F.; Banerjee, Sanjay K.

2016-12-01

Particle-based ensemble semi-classical Monte Carlo (MC) methods employ quantum corrections (QCs) to address quantum confinement and degenerate carrier populations to model tomorrow's ultra-scaled metal-oxide-semiconductor-field-effect-transistors. Here, we present the most complete treatment of quantum confinement and carrier degeneracy effects in a three-dimensional (3D) MC device simulator to date, and illustrate their significance through simulation of n-channel Si and III-V FinFETs. Original contributions include our treatment of far-from-equilibrium degenerate statistics and QC-based modeling of surface-roughness scattering, as well as considering quantum-confined phonon and ionized-impurity scattering in 3D. Typical MC simulations approximate degenerate carrier populations as Fermi distributions to model the Pauli-blocking (PB) of scattering to occupied final states. To allow for increasingly far-from-equilibrium non-Fermi carrier distributions in ultra-scaled and III-V devices, we instead generate the final-state occupation probabilities used for PB by sampling the local carrier populations as function of energy and energy valley. This process is aided by the use of fractional carriers or sub-carriers, which minimizes classical carrier-carrier scattering intrinsically incompatible with degenerate statistics. Quantum-confinement effects are addressed through quantum-correction potentials (QCPs) generated from coupled Schrödinger-Poisson solvers, as commonly done. However, we use these valley- and orientation-dependent QCPs not just to redistribute carriers in real space, or even among energy valleys, but also to calculate confinement-dependent phonon, ionized-impurity, and surface-roughness scattering rates. FinFET simulations are used to illustrate the contributions of each of these QCs. Collectively, these quantum effects can substantially reduce and even eliminate otherwise expected benefits of considered In0.53Ga0.47 As FinFETs over otherwise identical Si FinFETs despite higher thermal velocities in In0.53Ga0.47 As. It also may be possible to extend these basic uses of QCPs, however calculated, to still more computationally efficient drift-diffusion and hydrodynamic simulations, and the basic concepts even to compact device modeling.

Universal aspects of conformations and transverse fluctuations of a two-dimensional semi-flexible chain

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Huang, Aiqun; Bhattacharya, Aniket; Binder, Kurt

2015-03-01

In this talk we compare the results obtained from Monte Carlo (MC) and Brownian dynamics (BD) simulation for the universal properties of a semi-flexible chain. Specifically we compare MC results obtained using pruned-enriched Rosenbluth method (PERM) with those obtained from BD simulation. We find that the scaled plot of root-mean-square (RMS) end-to-end distance / 2 Llp and RMS transverse transverse fluctuations √{ } /lp as a function of L /lp (where L and lp are the contour length, and the persistence length respectively) are universal and independent of the definition of the persistence length used in MC and BD schemes. We further investigate to what extent these results agree for a semi-flexible polymer confined in a quasi one dimensional channel.

GEANT4 benchmark with MCNPX and PHITS for activation of concrete

NASA Astrophysics Data System (ADS)

Tesse, Robin; Stichelbaut, Frédéric; Pauly, Nicolas; Dubus, Alain; Derrien, Jonathan

2018-02-01

The activation of concrete is a real problem from the point of view of waste management. Because of the complexity of the issue, Monte Carlo (MC) codes have become an essential tool to its study. But various codes or even nuclear models exist in MC. MCNPX and PHITS have already been validated for shielding studies but GEANT4 is also a suitable solution. In these codes, different models can be considered for a concrete activation study. The Bertini model is not the best model for spallation while BIC and INCL model agrees well with previous results in literature.

Analysis of dose rates received around the storage pool for irradiated control rods in a BWR nuclear power plant.

PubMed

Ródenas, J; Abarca, A; Gallardo, S

2011-08-01

BWR control rods are activated by neutron reactions in the reactor. The dose produced by this activity can affect workers in the area surrounding the storage pool, where activated rods are stored. Monte Carlo (MC) models for neutron activation and dose assessment around the storage pool have been developed and validated. In this work, the MC models are applied to verify the expected reduction of dose when the irradiated control rod is hanged in an inverted position into the pool. 2010 Elsevier Ltd. All rights reserved.

Feasibility of using Geant4 Monte Carlo simulation for IMRT dose calculations for the Novalis Tx with a HD-120 multi-leaf collimator

NASA Astrophysics Data System (ADS)

Jung, Hyunuk; Shin, Jungsuk; Chung, Kwangzoo; Han, Youngyih; Kim, Jinsung; Choi, Doo Ho

2015-05-01

The aim of this study was to develop an independent dose verification system by using a Monte Carlo (MC) calculation method for intensity modulated radiation therapy (IMRT) conducted by using a Varian Novalis Tx (Varian Medical Systems, Palo Alto, CA, USA) equipped with a highdefinition multi-leaf collimator (HD-120 MLC). The Geant4 framework was used to implement a dose calculation system that accurately predicted the delivered dose. For this purpose, the Novalis Tx Linac head was modeled according to the specifications acquired from the manufacturer. Subsequently, MC simulations were performed by varying the mean energy, energy spread, and electron spot radius to determine optimum values of irradiation with 6-MV X-ray beams by using the Novalis Tx system. Computed percentage depth dose curves (PDDs) and lateral profiles were compared to the measurements obtained by using an ionization chamber (CC13). To validate the IMRT simulation by using the MC model we developed, we calculated a simple IMRT field and compared the result with the EBT3 film measurements in a water-equivalent solid phantom. Clinical cases, such as prostate cancer treatment plans, were then selected, and MC simulations were performed. The accuracy of the simulation was assessed against the EBT3 film measurements by using a gamma-index criterion. The optimal MC model parameters to specify the beam characteristics were a 6.8-MeV mean energy, a 0.5-MeV energy spread, and a 3-mm electron radius. The accuracy of these parameters was determined by comparison of MC simulations with measurements. The PDDs and the lateral profiles of the MC simulation deviated from the measurements by 1% and 2%, respectively, on average. The computed simple MLC fields agreed with the EBT3 measurements with a 95% passing rate with 3%/3-mm gamma-index criterion. Additionally, in applying our model to clinical IMRT plans, we found that the MC calculations and the EBT3 measurements agreed well with a passing rate of greater than 95% on average with a 3%/3-mm gamma-index criterion. In summary, the Novalis Tx Linac head equipped with a HD-120 MLC was successfully modeled by using a Geant4 platform, and the accuracy of the Geant4 platform was successfully validated by comparisons with measurements. The MC model we have developed can be a useful tool for pretreatment quality assurance of IMRT plans and for commissioning of radiotherapy treatment planning.

The FLUKA Monte Carlo code coupled with the NIRS approach for clinical dose calculations in carbon ion therapy

NASA Astrophysics Data System (ADS)

Magro, G.; Dahle, T. J.; Molinelli, S.; Ciocca, M.; Fossati, P.; Ferrari, A.; Inaniwa, T.; Matsufuji, N.; Ytre-Hauge, K. S.; Mairani, A.

2017-05-01

Particle therapy facilities often require Monte Carlo (MC) simulations to overcome intrinsic limitations of analytical treatment planning systems (TPS) related to the description of the mixed radiation field and beam interaction with tissue inhomogeneities. Some of these uncertainties may affect the computation of effective dose distributions; therefore, particle therapy dedicated MC codes should provide both absorbed and biological doses. Two biophysical models are currently applied clinically in particle therapy: the local effect model (LEM) and the microdosimetric kinetic model (MKM). In this paper, we describe the coupling of the NIRS (National Institute for Radiological Sciences, Japan) clinical dose to the FLUKA MC code. We moved from the implementation of the model itself to its application in clinical cases, according to the NIRS approach, where a scaling factor is introduced to rescale the (carbon-equivalent) biological dose to a clinical dose level. A high level of agreement was found with published data by exploring a range of values for the MKM input parameters, while some differences were registered in forward recalculations of NIRS patient plans, mainly attributable to differences with the analytical TPS dose engine (taken as reference) in describing the mixed radiation field (lateral spread and fragmentation). We presented a tool which is being used at the Italian National Center for Oncological Hadrontherapy to support the comparison study between the NIRS clinical dose level and the LEM dose specification.

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

NASA Astrophysics Data System (ADS)

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

2003-08-01

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

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

PubMed

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

2003-08-07

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

Protein-ion binding process on finite macromolecular concentration. A Poisson-Boltzmann and Monte Carlo study.

PubMed

de Carvalho, Sidney Jurado; Fenley, Márcia O; da Silva, Fernando Luís Barroso

2008-12-25

Electrostatic interactions are one of the key driving forces for protein-ligands complexation. Different levels for the theoretical modeling of such processes are available on the literature. Most of the studies on the Molecular Biology field are performed within numerical solutions of the Poisson-Boltzmann Equation and the dielectric continuum models framework. In such dielectric continuum models, there are two pivotal questions: (a) how the protein dielectric medium should be modeled, and (b) what protocol should be used when solving this effective Hamiltonian. By means of Monte Carlo (MC) and Poisson-Boltzmann (PB) calculations, we define the applicability of the PB approach with linear and nonlinear responses for macromolecular electrostatic interactions in electrolyte solution, revealing some physical mechanisms and limitations behind it especially due the raise of both macromolecular charge and concentration out of the strong coupling regime. A discrepancy between PB and MC for binding constant shifts is shown and explained in terms of the manner PB approximates the excess chemical potentials of the ligand, and not as a consequence of the nonlinear thermal treatment and/or explicit ion-ion interactions as it could be argued. Our findings also show that the nonlinear PB predictions with a low dielectric response well reproduce the pK shifts calculations carried out with an uniform dielectric model. This confirms and completes previous results obtained by both MC and linear PB calculations.

Mixing of Isotactic and Syndiotactic Polypropylenes in the Melt

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

CLANCY,THOMAS C.; PUTZ,MATHIAS; WEINHOLD,JEFFREY D.

2000-07-14

The miscibility of polypropylene (PP) melts in which the chains differ only in stereochemical composition has been investigated by two different procedures. One approach used detailed local information from a Monte Carlo simulation of a single chain, and the other approach takes this information from a rotational isomeric state model devised decades ago, for another purpose. The first approach uses PRISM theory to deduce the intermolecular packing in the polymer blend, while the second approach uses a Monte Carlo simulation of a coarse-grained representation of independent chains, expressed on a high-coordination lattice. Both approaches find a positive energy change uponmore » mixing isotactic PP (iPP) and syndiotactic polypropylene (sPP) chains in the melt. This conclusion is qualitatively consistent with observations published recently by Muelhaupt and coworkers. The size of the energy chain on mixing is smaller in the MC/PRISM approach than in the RIS/MC simulation, with the smaller energy change being in better agreement with the experiment. The RIS/MC simulation finds no demixing for iPP and atactic polypropylene (aPP) in the melt, consistent with several experimental observations in the literature. The demixing of the iPP/sPP blend may arise from attractive interactions in the sPP melt that are disrupted when the sPP chains are diluted with aPP or iPP chains.« less

Parallelization of a Monte Carlo particle transport simulation code

NASA Astrophysics Data System (ADS)

Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.

2010-05-01

We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.

Properties of a planar electric double layer under extreme conditions investigated by classical density functional theory and Monte Carlo simulations.

PubMed

Zhou, Shiqi; Lamperski, Stanisław; Zydorczak, Maria

2014-08-14

Monte Carlo (MC) simulation and classical density functional theory (DFT) results are reported for the structural and electrostatic properties of a planar electric double layer containing ions having highly asymmetric diameters or valencies under extreme concentration condition. In the applied DFT, for the excess free energy contribution due to the hard sphere repulsion, a recently elaborated extended form of the fundamental measure functional is used, and coupling of Coulombic and short range hard-sphere repulsion is described by a traditional second-order functional perturbation expansion approximation. Comparison between the MC and DFT results indicates that validity interval of the traditional DFT approximation expands to high ion valences running up to 3 and size asymmetry high up to diameter ratio of 4 whether the high valence ions or the large size ion are co- or counter-ions; and to a high bulk electrolyte concentration being close to the upper limit of the electrolyte mole concentration the MC simulation can deal with well. The DFT accuracy dependence on the ion parameters can be self-consistently explained using arguments of liquid state theory, and new EDL phenomena such as overscreening effect due to monovalent counter-ions, extreme layering effect of counter-ions, and appearance of a depletion layer with almost no counter- and co-ions are observed.

Optimisation of 12 MeV electron beam simulation using variance reduction technique

NASA Astrophysics Data System (ADS)

Jayamani, J.; Termizi, N. A. S. Mohd; Kamarulzaman, F. N. Mohd; Aziz, M. Z. Abdul

2017-05-01

Monte Carlo (MC) simulation for electron beam radiotherapy consumes a long computation time. An algorithm called variance reduction technique (VRT) in MC was implemented to speed up this duration. This work focused on optimisation of VRT parameter which refers to electron range rejection and particle history. EGSnrc MC source code was used to simulate (BEAMnrc code) and validate (DOSXYZnrc code) the Siemens Primus linear accelerator model with the non-VRT parameter. The validated MC model simulation was repeated by applying VRT parameter (electron range rejection) that controlled by global electron cut-off energy 1,2 and 5 MeV using 20 × 107 particle history. 5 MeV range rejection generated the fastest MC simulation with 50% reduction in computation time compared to non-VRT simulation. Thus, 5 MeV electron range rejection utilized in particle history analysis ranged from 7.5 × 107 to 20 × 107. In this study, 5 MeV electron cut-off with 10 × 107 particle history, the simulation was four times faster than non-VRT calculation with 1% deviation. Proper understanding and use of VRT can significantly reduce MC electron beam calculation duration at the same time preserving its accuracy.

Quantitative assessment of the accuracy of dose calculation using pencil beam and Monte Carlo algorithms and requirements for clinical quality assurance

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

Ali, Imad, E-mail: iali@ouhsc.edu; Ahmad, Salahuddin

2013-10-01

To compare the doses calculated using the BrainLAB pencil beam (PB) and Monte Carlo (MC) algorithms for tumors located in various sites including the lung and evaluate quality assurance procedures required for the verification of the accuracy of dose calculation. The dose-calculation accuracy of PB and MC was also assessed quantitatively with measurement using ionization chamber and Gafchromic films placed in solid water and heterogeneous phantoms. The dose was calculated using PB convolution and MC algorithms in the iPlan treatment planning system from BrainLAB. The dose calculation was performed on the patient's computed tomography images with lesions in various treatmentmore » sites including 5 lungs, 5 prostates, 4 brains, 2 head and necks, and 2 paraspinal tissues. A combination of conventional, conformal, and intensity-modulated radiation therapy plans was used in dose calculation. The leaf sequence from intensity-modulated radiation therapy plans or beam shapes from conformal plans and monitor units and other planning parameters calculated by the PB were identical for calculating dose with MC. Heterogeneity correction was considered in both PB and MC dose calculations. Dose-volume parameters such as V95 (volume covered by 95% of prescription dose), dose distributions, and gamma analysis were used to evaluate the calculated dose by PB and MC. The measured doses by ionization chamber and EBT GAFCHROMIC film in solid water and heterogeneous phantoms were used to quantitatively asses the accuracy of dose calculated by PB and MC. The dose-volume histograms and dose distributions calculated by PB and MC in the brain, prostate, paraspinal, and head and neck were in good agreement with one another (within 5%) and provided acceptable planning target volume coverage. However, dose distributions of the patients with lung cancer had large discrepancies. For a plan optimized with PB, the dose coverage was shown as clinically acceptable, whereas in reality, the MC showed a systematic lack of dose coverage. The dose calculated by PB for lung tumors was overestimated by up to 40%. An interesting feature that was observed is that despite large discrepancies in dose-volume histogram coverage of the planning target volume between PB and MC, the point doses at the isocenter (center of the lesions) calculated by both algorithms were within 7% even for lung cases. The dose distributions measured with EBT GAFCHROMIC films in heterogeneous phantoms showed large discrepancies of nearly 15% lower than PB at interfaces between heterogeneous media, where these lower doses measured by the film were in agreement with those by MC. The doses (V95) calculated by MC and PB agreed within 5% for treatment sites with small tissue heterogeneities such as the prostate, brain, head and neck, and paraspinal tumors. Considerable discrepancies, up to 40%, were observed in the dose-volume coverage between MC and PB in lung tumors, which may affect clinical outcomes. The discrepancies between MC and PB increased for 15 MV compared with 6 MV indicating the importance of implementation of accurate clinical treatment planning such as MC. The comparison of point doses is not representative of the discrepancies in dose coverage and might be misleading in evaluating the accuracy of dose calculation between PB and MC. Thus, the clinical quality assurance procedures required to verify the accuracy of dose calculation using PB and MC need to consider measurements of 2- and 3-dimensional dose distributions rather than a single point measurement using heterogeneous phantoms instead of homogenous water-equivalent phantoms.« less

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2017-07-17

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

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

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

Kim, S; Rangaraj, D

2016-06-15

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

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

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

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

2016-06-15

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

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

Cebe, M; Pacaci, P; Mabhouti, H

Purpose: In this study, the two available calculation algorithms of the Varian Eclipse treatment planning system(TPS), the electron Monte Carlo(eMC) and General Gaussian Pencil Beam(GGPB) algorithms were used to compare measured and calculated peripheral dose distribution of electron beams. Methods: Peripheral dose measurements were carried out for 6, 9, 12, 15, 18 and 22 MeV electron beams of Varian Triology machine using parallel plate ionization chamber and EBT3 films in the slab phantom. Measurements were performed for 6×6, 10×10 and 25×25cm{sup 2} cone sizes at dmax of each energy up to 20cm beyond the field edges. Using the same filmmore » batch, the net OD to dose calibration curve was obtained for each energy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution measured using parallel plate ionization chamber and EBT3 film and calculated by eMC and GGPB algorithms were compared. The measured and calculated data were then compared to find which algorithm calculates peripheral dose distribution more accurately. Results: The agreement between measurement and eMC was better than GGPB. The TPS underestimated the out of field doses. The difference between measured and calculated doses increase with the cone size. The largest deviation between calculated and parallel plate ionization chamber measured dose is less than 4.93% for eMC, but it can increase up to 7.51% for GGPB. For film measurement, the minimum gamma analysis passing rates between measured and calculated dose distributions were 98.2% and 92.7% for eMC and GGPB respectively for all field sizes and energies. Conclusion: Our results show that the Monte Carlo algorithm for electron planning in Eclipse is more accurate than previous algorithms for peripheral dose distributions. It must be emphasized that the use of GGPB for planning large field treatments with 6 MeV could lead to inaccuracies of clinical significance.« less

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

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

PubMed

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

2018-01-01

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

Reliability of dose volume constraint inference from clinical data.

PubMed

Lutz, C M; Møller, D S; Hoffmann, L; Knap, M M; Alber, M

2017-04-21

Dose volume histogram points (DVHPs) frequently serve as dose constraints in radiotherapy treatment planning. An experiment was designed to investigate the reliability of DVHP inference from clinical data for multiple cohort sizes and complication incidence rates. The experimental background was radiation pneumonitis in non-small cell lung cancer and the DVHP inference method was based on logistic regression. From 102 NSCLC real-life dose distributions and a postulated DVHP model, an 'ideal' cohort was generated where the most predictive model was equal to the postulated model. A bootstrap and a Cohort Replication Monte Carlo (CoRepMC) approach were applied to create 1000 equally sized populations each. The cohorts were then analyzed to establish inference frequency distributions. This was applied to nine scenarios for cohort sizes of 102 (1), 500 (2) to 2000 (3) patients (by sampling with replacement) and three postulated DVHP models. The Bootstrap was repeated for a 'non-ideal' cohort, where the most predictive model did not coincide with the postulated model. The Bootstrap produced chaotic results for all models of cohort size 1 for both the ideal and non-ideal cohorts. For cohort size 2 and 3, the distributions for all populations were more concentrated around the postulated DVHP. For the CoRepMC, the inference frequency increased with cohort size and incidence rate. Correct inference rates  >[Formula: see text] were only achieved by cohorts with more than 500 patients. Both Bootstrap and CoRepMC indicate that inference of the correct or approximate DVHP for typical cohort sizes is highly uncertain. CoRepMC results were less spurious than Bootstrap results, demonstrating the large influence that randomness in dose-response has on the statistical analysis.

THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites

PubMed Central

Chang, Hsiao-Han; Worby, Colin J.; Yeka, Adoke; Nankabirwa, Joaniter; Kamya, Moses R.; Staedke, Sarah G.; Hubbart, Christina; Amato, Roberto; Kwiatkowski, Dominic P.

2017-01-01

As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings. PMID:28125584

Reliability of dose volume constraint inference from clinical data

NASA Astrophysics Data System (ADS)

Lutz, C. M.; Møller, D. S.; Hoffmann, L.; Knap, M. M.; Alber, M.

2017-04-01

Dose volume histogram points (DVHPs) frequently serve as dose constraints in radiotherapy treatment planning. An experiment was designed to investigate the reliability of DVHP inference from clinical data for multiple cohort sizes and complication incidence rates. The experimental background was radiation pneumonitis in non-small cell lung cancer and the DVHP inference method was based on logistic regression. From 102 NSCLC real-life dose distributions and a postulated DVHP model, an ‘ideal’ cohort was generated where the most predictive model was equal to the postulated model. A bootstrap and a Cohort Replication Monte Carlo (CoRepMC) approach were applied to create 1000 equally sized populations each. The cohorts were then analyzed to establish inference frequency distributions. This was applied to nine scenarios for cohort sizes of 102 (1), 500 (2) to 2000 (3) patients (by sampling with replacement) and three postulated DVHP models. The Bootstrap was repeated for a ‘non-ideal’ cohort, where the most predictive model did not coincide with the postulated model. The Bootstrap produced chaotic results for all models of cohort size 1 for both the ideal and non-ideal cohorts. For cohort size 2 and 3, the distributions for all populations were more concentrated around the postulated DVHP. For the CoRepMC, the inference frequency increased with cohort size and incidence rate. Correct inference rates  >85 % were only achieved by cohorts with more than 500 patients. Both Bootstrap and CoRepMC indicate that inference of the correct or approximate DVHP for typical cohort sizes is highly uncertain. CoRepMC results were less spurious than Bootstrap results, demonstrating the large influence that randomness in dose-response has on the statistical analysis.

Dynamic Conformations of Nucleosome Arrays in Solution from Small-Angle X-ray Scattering

NASA Astrophysics Data System (ADS)

Howell, Steven C.

Chromatin conformation and dynamics remains unsolved despite the critical role of the chromatin in fundamental genetic functions such as transcription, replication, and repair. At the molecular level, chromatin can be viewed as a linear array of nucleosomes, each consisting of 147 base pairs (bp) of double-stranded DNA (dsDNA) wrapped around a protein core and connected by 10 to 90 bp of linker dsDNA. Using small-angle X-ray scattering (SAXS), we investigated how the conformations of model nucleosome arrays in solution are modulated by ionic condition as well as the effect of linker histone proteins. To facilitate ensemble modeling of these SAXS measurements, we developed a simulation method that treats coarse-grained DNA as a Markov chain, then explores possible DNA conformations using Metropolis Monte Carlo (MC) sampling. This algorithm extends the functionality of SASSIE, a program used to model intrinsically disordered biological molecules, adding to the previous methods for simulating protein, carbohydrates, and single-stranded DNA. Our SAXS measurements of various nucleosome arrays together with the MC generated models provide valuable solution structure information identifying specific differences from the structure of crystallized arrays.

Constant-pH molecular dynamics using stochastic titration

NASA Astrophysics Data System (ADS)

Baptista, António M.; Teixeira, Vitor H.; Soares, Cláudio M.

2002-09-01

A new method is proposed for performing constant-pH molecular dynamics (MD) simulations, that is, MD simulations where pH is one of the external thermodynamic parameters, like the temperature or the pressure. The protonation state of each titrable site in the solute is allowed to change during a molecular mechanics (MM) MD simulation, the new states being obtained from a combination of continuum electrostatics (CE) calculations and Monte Carlo (MC) simulation of protonation equilibrium. The coupling between the MM/MD and CE/MC algorithms is done in a way that ensures a proper Markov chain, sampling from the intended semigrand canonical distribution. This stochastic titration method is applied to succinic acid, aimed at illustrating the method and examining the choice of its adjustable parameters. The complete titration of succinic acid, using constant-pH MD simulations at different pH values, gives a clear picture of the coupling between the trans/gauche isomerization and the protonation process, making it possible to reconcile some apparently contradictory results of previous studies. The present constant-pH MD method is shown to require a moderate increase of computational cost when compared to the usual MD method.

SU-E-T-454: Dosimetric Comparison between Pencil Beam and Monte Carlo Algorithms for SBRT Lung Treatment Using IPlan V4.1 TPS and CIRS Thorax Phantom.

PubMed

Fernandez, M Castrillon; Venencia, C; Garrigó, E; Caussa, L

2012-06-01

To compare measured and calculated doses using Pencil Beam (PB) and Monte Carlo (MC) algorithm on a CIRS thorax phantom for SBRT lung treatments. A 6MV photon beam generated by a Primus linac with an Optifocus MLC (Siemens) was used. Dose calculation was done using iPlan v4.1.2 TPS (BrainLAB) by PB and MC (dose to water and dose to medium) algorithms. The commissioning of both algorithms was done reproducing experimental measurements in water. A CIRS thorax phantom was used to compare doses using a Farmer type ion chamber (PTW) and EDR2 radiographic films (KODAK). The ionization chamber, into a tissue equivalent insert, was placed in two position of lung tissue and was irradiated using three treatments plans. Axial dose distributions were measured for four treatments plans using conformal and IMRT technique. Dose distribution comparisons were done by dose profiles and gamma index (3%/3mm). For the studied beam configurations, ion chamber measurements shows that PB overestimate the dose up to 8.5%, whereas MC has a maximum variation of 1.6%. Dosimetric analysis using dose profiles shows that PB overestimates the dose in the region corresponding to the lung up to 16%. For axial dose distribution comparison the percentage of pixels with gamma index bigger than one for MC and PB was, plan 1: 95.6% versus 87.4%, plan 2: 91.2% versus 77.6%, plan 3: 99.7% versus 93.1% and for plan 4: 98.8% versus 91.7%. It was confirmed that the lower dosimetric errors calculated applying MC algorithm appears when the spatial resolution and variance decrease at the expense of increased computation time. The agreement between measured and calculated doses, in a phantom with lung heterogeneities, is better with MC algorithm. PB algorithm overestimates the doses in lung tissue, which could have a clinical impact in SBRT lung treatments. © 2012 American Association of Physicists in Medicine.

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

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

Zheng, D; Zhang, Q; Zhou, S

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

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

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

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

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

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-06-01

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

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

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

Randeniya, S; Mirkovic, D; Titt, U

2014-06-01

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

The special case of the 2 × 2 table: asymptotic unconditional McNemar test can be used to estimate sample size even for analysis based on GEE.

PubMed

Borkhoff, Cornelia M; Johnston, Patrick R; Stephens, Derek; Atenafu, Eshetu

2015-07-01

Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. The asymptotic unconditional McNemar test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar test can be used to estimate sample size. We do not recommend using an exact McNemar test. Copyright © 2015 Elsevier Inc. All rights reserved.

Study of the impact of artificial articulations on the dose distribution under medical irradiation

NASA Astrophysics Data System (ADS)

Buffard, E.; Gschwind, R.; Makovicka, L.; Martin, E.; Meunier, C.; David, C.

2005-02-01

Perturbations due to the presence of high density heterogeneities in the body are not correctly taken into account in the Treatment Planning Systems currently available for external radiotherapy. For this reason, the accuracy of the dose distribution calculations has to be improved by using Monte Carlo simulations. In a previous study, we established a theoretical model by using the Monte Carlo code EGSnrc [I. Kawrakow, D.W.O. Rogers, The EGSnrc code system: MC simulation of electron and photon transport. Technical Report PIRS-701, NRCC, Ottawa, Canada, 2000] in order to obtain the dose distributions around simple heterogeneities. These simulations were then validated by experimental results obtained with thermoluminescent dosemeters and an ionisation chamber. The influence of samples composed of hip prostheses materials (titanium alloy and steel) and a substitute of bone were notably studied. A more complex model was then developed with the Monte Carlo code BEAMnrc [D.W.O. Rogers, C.M. MA, G.X. Ding, B. Walters, D. Sheikh-Bagheri, G.G. Zhang, BEAMnrc Users Manual. NRC Report PPIRS 509(a) rev F, 2001] in order to take into account the hip prosthesis geometry. The simulation results were compared to experimental measurements performed in a water phantom, in the case of a standard treatment of a pelvic cancer for one of the beams passing through the implant. These results have shown the great influence of the prostheses on the dose distribution.

UNCERTAINTY AND SENSITIVITY ANALYSIS OF RUNOFF AND SEDIMENT YIELD IN A SMALL AGRICULTURAL WATERSHED WITH KINEROS2

EPA Science Inventory

Using the Monte Carlo (MC) method, this paper derives arithmetic and geometric means and associated variances of the net capillary drive parameter, G, that appears in the Parlange infiltration model, as a function of soil texture and antecedent soil moisture content. App...

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Room scatter effects in Total Skin Electron Irradiation: Monte Carlo simulation study.

PubMed

Nevelsky, Alexander; Borzov, Egor; Daniel, Shahar; Bar-Deroma, Raquel

2017-01-01

Total Skin Electron Irradiation (TSEI) is a complex technique which usually involves the use of large electron fields and the dual-field approach. In this situation, many electrons scattered from the treatment room floor are produced. However, no investigations of the effect of scattered electrons in TSEI treatments have been reported. The purpose of this work was to study the contribution of floor scattered electrons to skin dose during TSEI treatment using Monte Carlo (MC) simulations. All MC simulations were performed with the EGSnrc code. Influence of beam energy, dual-field angle, and floor material on the contribution of floor scatter was investigated. Spectrum of the scattered electrons was calculated. Measurements of dose profile were performed in order to verify MC calculations. Floor scatter dependency on the floor material was observed (at 20 cm from the floor, scatter contribution was about 21%, 18%, 15%, and 12% for iron, concrete, PVC, and water, respectively). Although total dose profiles exhibited slight variation as functions of beam energy and dual-field angle, no dependence of the floor scatter contribution on the beam energy or dual-field angle was found. The spectrum of the scattered electrons was almost uniform between a few hundred KeV to 4 MeV, and then decreased linearly to 6 MeV. For the TSEI technique, dose contribution due to the electrons scattered from the room floor may be clinically significant and should be taken into account during design and commissioning phases. MC calculations can be used for this task. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

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

PubMed

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

2008-07-01

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

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

Serin, E.; Codel, G.; Mabhouti, H.

Purpose: In small field geometries, the electronic equilibrium can be lost, making it challenging for the dose-calculation algorithm to accurately predict the dose, especially in the presence of tissue heterogeneities. In this study, dosimetric accuracy of Monte Carlo (MC) advanced dose calculation and sequential algorithms of Multiplan treatment planning system were investigated for small radiation fields incident on homogeneous and heterogeneous geometries. Methods: Small open fields of fixed cones of Cyberknife M6 unit 100 to 500 mm2 were used for this study. The fields were incident on in house phantom containing lung, air, and bone inhomogeneities and also homogeneous phantom.more » Using the same film batch, the net OD to dose calibration curve was obtained using CK with the 60 mm fixed cone by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. The dosimetric accuracy of MC and sequential algorithms in the presence of the inhomogeneities was compared against EBT3 film dosimetry Results: Open field tests in a homogeneous phantom showed good agreement between two algorithms and film measurement For MC algorithm, the minimum gamma analysis passing rates between measured and calculated dose distributions were 99.7% and 98.3% for homogeneous and inhomogeneous fields in the case of lung and bone respectively. For sequential algorithm, the minimum gamma analysis passing rates were 98.9% and 92.5% for for homogeneous and inhomogeneous fields respectively for used all cone sizes. In the case of the air heterogeneity, the differences were larger for both calculation algorithms. Overall, when compared to measurement, the MC had better agreement than sequential algorithm. Conclusion: The Monte Carlo calculation algorithm in the Multiplan treatment planning system is an improvement over the existing sequential algorithm. Dose discrepancies were observed for in the presence of air inhomogeneities.« less

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

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

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

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

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

PubMed

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

2016-11-14

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

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

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.

2017-12-01

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

Poster — Thur Eve — 46: Monte Carlo model of the Novalis Classic 6MV stereotactic linear accelerator using the GATE simulation platform

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

Wiebe, J; Department of Physics and Astronomy, University of Calgary, Calgary, AB; Ploquin, N

2014-08-15

Monte Carlo (MC) simulation is accepted as the most accurate method to predict dose deposition when compared to other methods in radiation treatment planning. Current dose calculation algorithms used for treatment planning can become inaccurate when small radiation fields and tissue inhomogeneities are present. At our centre the Novalis Classic linear accelerator (linac) is used for Stereotactic Radiosurgery (SRS). The first MC model to date of the Novalis Classic linac was developed at our centre using the Geant4 Application for Tomographic Emission (GATE) simulation platform. GATE is relatively new, open source MC software built from CERN's Geometry and Tracking 4more » (Geant4) toolkit. The linac geometry was modeled using manufacturer specifications, as well as in-house measurements of the micro MLC's. Among multiple model parameters, the initial electron beam was adjusted so that calculated depth dose curves agreed with measured values. Simulations were run on the European Grid Infrastructure through GateLab. Simulation time is approximately 8 hours on GateLab for a complete head model simulation to acquire a phase space file. Current results have a majority of points within 3% of the measured dose values for square field sizes ranging from 6×6 mm{sup 2} to 98×98 mm{sup 2} (maximum field size on the Novalis Classic linac) at 100 cm SSD. The x-ray spectrum was determined from the MC data as well. The model provides an investigation into GATE'S capabilities and has the potential to be used as a research tool and an independent dose calculation engine for clinical treatment plans.« less

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

PubMed

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

2017-06-01

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

Vertical drying of a suspension of sticks: Monte Carlo simulation for continuous two-dimensional problem

NASA Astrophysics Data System (ADS)

Lebovka, Nikolai I.; Tarasevich, Yuri Yu.; Vygornitskii, Nikolai V.

2018-02-01

The vertical drying of a two-dimensional colloidal film containing zero-thickness sticks (lines) was studied by means of kinetic Monte Carlo (MC) simulations. The continuous two-dimensional problem for both the positions and orientations was considered. The initial state before drying was produced using a model of random sequential adsorption with isotropic orientations of the sticks. During the evaporation, an upper interface falls with a linear velocity in the vertical direction, and the sticks undergo translational and rotational Brownian motions. The MC simulations were run at different initial number concentrations (the numbers of sticks per unit area), pi, and solvent evaporation rates, u . For completely dried films, the spatial distributions of the sticks, the order parameters, and the electrical conductivities of the films in both the horizontal, x , and vertical, y , directions were examined. Significant evaporation-driven self-assembly and stratification of the sticks in the vertical direction was observed. The extent of stratification increased with increasing values of u . The anisotropy of the electrical conductivity of the film can be finely regulated by changes in the values of pi and u .

Impact ionization and band-to-band tunneling in InxGa1-xAs PIN ungated devices: A Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Vasallo, B. G.; González, T.; Talbo, V.; Lechaux, Y.; Wichmann, N.; Bollaert, S.; Mateos, J.

2018-01-01

III-V Impact-ionization (II) metal-oxide-semiconductor FETs (I-MOSFETs) and tunnel FETs (TFETs) are being explored as promising devices for low-power digital applications. To assist the development of these devices from the physical point of view, a Monte Carlo (MC) model which includes impact ionization processes and band-to-band tunneling is presented. The MC simulator reproduces the I-V characteristics of experimental ungated In0.53Ga0.47As 100 nm PIN diodes, in which tunneling emerges for lower applied voltages than impact ionization events, thus being appropriate for TFETs. When the structure is enlarged up to 200 nm, the ON-state is achieved by means of impact ionization processes; however, the necessary applied voltage is higher, with the consequent drawback for low-power applications. In InAs PIN ungated structures, the onset of both impact ionization processes and band-to-band tunneling takes place for similar applied voltages, lower than 1 V; thus they are suitable for the design of low-power I-MOSFETs.

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

PubMed

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

2012-07-01

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

MC3, Version 1

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

Cawkwell, Marc Jon

2016-09-09

The MC3 code is used to perform Monte Carlo simulations in the isothermal-isobaric ensemble (constant number of particles, temperature, and pressure) on molecular crystals. The molecules within the periodic simulation cell are treated as rigid bodies, alleviating the requirement for a complex interatomic potential. Intermolecular interactions are described using generic, atom-centered pair potentials whose parameterization is taken from the literature [D. E. Williams, J. Comput. Chem., 22, 1154 (2001)] and electrostatic interactions arising from atom-centered, fixed, point partial charges. The primary uses of the MC3 code are the computation of i) the temperature and pressure dependence of lattice parameters andmore » thermal expansion coefficients, ii) tensors of elastic constants and compliances via the Parrinello and Rahman’s fluctuation formula [M. Parrinello and A. Rahman, J. Chem. Phys., 76, 2662 (1982)], and iii) the investigation of polymorphic phase transformations. The MC3 code is written in Fortran90 and requires LAPACK and BLAS linear algebra libraries to be linked during compilation. Computationally expensive loops are accelerated using OpenMP.« less

MO-FG-BRA-01: 4D Monte Carlo Simulations for Verification of Dose Delivered to a Moving Anatomy

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

Gholampourkashi, S; Cygler, J E.; The Ottawa Hospital Cancer Centre, Ottawa, ON

Purpose: To validate 4D Monte Carlo (MC) simulations of dose delivery by an Elekta Agility linear accelerator to a moving phantom. Methods: Monte Carlo simulations were performed using the 4DdefDOSXYZnrc/EGSnrc user code which samples a new geometry for each incident particle and calculates the dose in a continuously moving anatomy. A Quasar respiratory motion phantom with a lung insert containing a 3 cm diameter tumor was used for dose measurements on an Elekta Agility linac with the phantom in stationary and moving states. Dose to the center of tumor was measured using calibrated EBT3 film and the RADPOS 4D dosimetrymore » system. A VMAT plan covering the tumor was created on the static CT scan of the phantom using Monaco V.5.10.02. A validated BEAMnrc model of our Elekta Agility linac was used for Monte Carlo simulations on stationary and moving anatomies. To compare the planned and delivered doses, linac log files recorded during measurements were used for the simulations. For 4D simulations, deformation vectors that modeled the rigid translation of the lung insert were generated as input to the 4DdefDOSXYZnrc code as well as the phantom motion trace recorded with RADPOS during the measurements. Results: Monte Carlo simulations and film measurements were found to agree within 2mm/2% for 97.7% of points in the film in the static phantom and 95.5% in the moving phantom. Dose values based on film and RADPOS measurements are within 2% of each other and within 2σ of experimental uncertainties with respect to simulations. Conclusion: Our 4D Monte Carlo simulation using the defDOSXYZnrc code accurately calculates dose delivered to a moving anatomy. Future work will focus on more investigation of VMAT delivery on a moving phantom to improve the agreement between simulation and measurements, as well as establishing the accuracy of our method in a deforming anatomy. This work was supported by the Ontario Consortium of Adaptive Interventions in Radiation Oncology (OCAIRO), funded by the Ontario Research Fund Research Excellence program.« less

Dose Enhancement near Metal Interfaces in Synthetic Diamond Based X-ray Dosimeters

NASA Astrophysics Data System (ADS)

Alamoudi, Dalal

Diamond is an attractive material for medical dosimetry due to its radiation hardness, fast response, chemical resilience, small sensitive volume, high spatial resolution, near-tissue equivalence, and energy and dose rate independence. These properties make diamond a promising material for medical dosimetry compared to other semiconductor detector materials and wider radiation detection applications. This study is focused on one of the important factors to consider in the radiation detector; the influence of dose enhancement on the photocurrent performance at metallic interfaces in synthetic diamond radiation dosimeters with carbon based electrodes as a function of bias voltages. Monte Carlo (MC) simulations with BEAMnrc code were carried out to simulate the dose enhancement factor (DEF) and compared against the equivalent photocurrent ratio from experimental investigation. MC simulations show that the sensitive region for the absorbed dose distribution covers a few micrometers distances from the interface. Experimentally, two single crystal (SC) and one polycrystalline (PC) samples with carbon based electrodes were used. The samples were each mounted inside a tissue equivalent encapsulation design in order to minimize fluence perturbations. Copper, Gold and Lead have been investigated experimentally as generators of photoelectrons using 50 kVp and 100 kVp X-rays relevant for medical dosimetry. The results show enhancement in the detectors' photocurrent performance when different metals are butted up to the diamond detector. The variation in the photocurrent ratio measurements depends on the type of diamond samples, their electrode fabrication and the applied bias voltages indicating that the dose enhancement from diamond-metal interface modifies the electronic performance of the detector.

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

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

Wulff, J; Abel, E

2016-06-15

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

SU-E-T-627: Precision Modelling of the Leaf-Bank Rotation in Elekta’s Agility MLC: Is It Necessary?

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

Vujicic, M; Belec, J; Heath, E

Purpose: To demonstrate the method used to determine the leaf bank rotation angle (LBROT) as a parameter for modeling the Elekta Agility multi-leaf collimator (MLC) for Monte Carlo simulations and to evaluate the clinical impact of LBROT. Methods: A detailed model of an Elekta Infinity linac including an Agility MLC was built using the EGSnrc/BEAMnrc Monte Carlo code. The Agility 160-leaf MLC is modelled using the MLCE component module which allows for leaf bank rotation using the parameter LBROT. A precise value of LBROT is obtained by comparing measured and simulated profiles of a specific field, which has leaves arrangedmore » in a repeated pattern such that one leaf is opened and the adjacent one is closed. Profile measurements from an Agility linac are taken with gafchromic film, and an ion chamber is used to set the absolute dose. The measurements are compared to Monte Carlo (MC) simulations and the LBROT is adjusted until a match is found. The clinical impact of LBROT is evaluated by observing how an MC dose calculation changes with LBROT. A clinical Stereotactic Body Radiation Treatment (SBRT) plan is calculated using BEAMnrc/DOSXYZnrc simulations with different input values for LBROT. Results: Using the method outlined above, the LBROT is determined to be 9±1 mrad. Differences as high as 4% are observed in a clinical SBRT plan between the extreme case (LBROT not modeled) and the nominal case. Conclusion: In small-field radiation therapy treatment planning, it is important to properly account for LBROT as an input parameter for MC dose calculations with the Agility MLC. More work is ongoing to elucidate the observed differences by determining the contributions from transmission dose, change in field size, and source occlusion, which are all dependent on LBROT. This work was supported by OCAIRO (Ontario Consortium of Adaptive Interventions in Radiation Oncology), funded by the Ontario Research Fund.« less

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

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

Jin, L; Fan, J; Eldib, A

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

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

PubMed

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

2016-02-21

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

On two-sample McNemar test.

PubMed

Xiang, Jim X

2016-01-01

Measuring a change in the existence of disease symptoms before and after a treatment is examined for statistical significance by means of the McNemar test. When comparing two treatments, Feuer and Kessler (1989) proposed a two-sample McNemar test. In this article, we show that this test usually inflates the type I error in the hypothesis testing, and propose a new two-sample McNemar test that is superior in terms of preserving type I error. We also make the connection between the two-sample McNemar test and the test statistic for the equal residual effects in a 2 × 2 crossover design. The limitations of the two-sample McNemar test are also discussed.

A Monte Carlo study of the spin-1 Blume-Emery-Griffiths phase diagrams within biquadratic exchange anisotropy

NASA Astrophysics Data System (ADS)

Dani, Ibtissam; Tahiri, Najim; Ez-Zahraouy, Hamid; Benyoussef, Abdelilah

2014-08-01

The effect of the bi-quadratic exchange coupling anisotropy on the phase diagram of the spin-1 Blume-Emery-Griffiths model on simple-cubic lattice is investigated using mean field theory (MFT) and Monte Carlo simulation (MC). It is found that the anisotropy of the biquadratic coupling favors the stability of the ferromagnetic phase. By decreasing the parallel and/or perpendicular bi-quadratic coupling, the ferrimagnetic and the antiquadrupolar phases broaden in contrast, the ferromagnetic and the disordered phases become narrow. The behavior of magnetization and quadrupolar moment as a function of temperature is also computed, especially in the ferrimagnetic phase.

Kinetic Monte Carlo simulation of self-organized pattern formation induced by ion beam sputtering using crater functions

NASA Astrophysics Data System (ADS)

Yang, Zhangcan; Lively, Michael A.; Allain, Jean Paul

2015-02-01

The production of self-organized nanostructures by ion beam sputtering has been of keen interest to researchers for many decades. Despite numerous experimental and theoretical efforts to understand ion-induced nanostructures, there are still many basic questions open to discussion, such as the role of erosion or curvature-dependent sputtering. In this work, a hybrid MD/kMC (molecular dynamics/kinetic Monte Carlo) multiscale atomistic model is developed to investigate these knowledge gaps, and its predictive ability is validated across the experimental parameter space. This model uses crater functions, which were obtained from MD simulations, to model the prompt mass redistribution due to single-ion impacts. Defect migration, which is missing from previous models that use crater functions, is treated by a kMC Arrhenius method. Using this model, a systematic study was performed for silicon bombarded by Ar+ ions of various energies (100 eV, 250 eV, 500 eV, 700 eV, and 1000 eV) at incidence angles of 0∘ to 80∘. The simulation results were compared with experimental findings, showing good agreement in many aspects of surface evolution, such as the phase diagram. The underestimation of the ripple wavelength by the simulations suggests that surface diffusion is not the main smoothening mechanism for ion-induced pattern formation. Furthermore, the simulated results were compared with moment-description continuum theory and found to give better results, as the simulation did not suffer from the same mathematical inconsistencies as the continuum model. The key finding was that redistributive effects are dominant in the formation of flat surfaces and parallel-mode ripples, but erosive effects are dominant at high angles when perpendicular-mode ripples are formed. Ion irradiation with simultaneous sample rotation was also simulated, resulting in arrays of square-ordered dots. The patterns obtained from sample rotation were strongly correlated to the rotation speed and to the pattern types formed without sample rotation, and a critical value of about 5 rpm was found between disordered ripples and square-ordered dots. Finally, simulations of dual-beam sputtering were performed, with the resulting patterns determined by the flux ratio of the two beams and the pattern types resulting from single-beam sputtering under the same conditions.

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

PubMed

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

2015-03-21

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

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

NASA Astrophysics Data System (ADS)

Doronin, Alexander; Meglinski, Igor

2017-02-01

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

Simulation of temperature distribution in tumor Photothermal treatment

NASA Astrophysics Data System (ADS)

Zhang, Xiyang; Qiu, Shaoping; Wu, Shulian; Li, Zhifang; Li, Hui

2018-02-01

The light transmission in biological tissue and the optical properties of biological tissue are important research contents of biomedical photonics. It is of great theoretical and practical significance in medical diagnosis and light therapy of disease. In this paper, the temperature feedback-controller was presented for monitoring photothermal treatment in realtime. Two-dimensional Monte Carlo (MC) and diffuse approximation were compared and analyzed. The results demonstrated that diffuse approximation using extrapolated boundary conditions by finite element method is a good approximation to MC simulation. Then in order to minimize thermal damage, real-time temperature monitoring was appraised by proportional-integral-differential (PID) controller in the process of photothermal treatment.

Statistical homogeneity tests applied to large data sets from high energy physics experiments

NASA Astrophysics Data System (ADS)

Trusina, J.; Franc, J.; Kůs, V.

2017-12-01

Homogeneity tests are used in high energy physics for the verification of simulated Monte Carlo samples, it means if they have the same distribution as a measured data from particle detector. Kolmogorov-Smirnov, χ 2, and Anderson-Darling tests are the most used techniques to assess the samples’ homogeneity. Since MC generators produce plenty of entries from different models, each entry has to be re-weighted to obtain the same sample size as the measured data has. One way of the homogeneity testing is through the binning. If we do not want to lose any information, we can apply generalized tests based on weighted empirical distribution functions. In this paper, we propose such generalized weighted homogeneity tests and introduce some of their asymptotic properties. We present the results based on numerical analysis which focuses on estimations of the type-I error and power of the test. Finally, we present application of our homogeneity tests to data from the experiment DØ in Fermilab.

SU-C-204-06: Monte Carlo Dose Calculation for Kilovoltage X-Ray-Psoralen Activated Cancer Therapy (X-PACT): Preliminary Results

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

Mein, S; Gunasingha, R; Nolan, M

Purpose: X-PACT is an experimental cancer therapy where kV x-rays are used to photo-activate anti-cancer therapeutics through phosphor intermediaries (phosphors that absorb x-rays and re-radiate as UV light). Clinical trials in pet dogs are currently underway (NC State College of Veterinary Medicine) and an essential component is the ability to model the kV dose in these dogs. Here we report the commissioning and characterization of a Monte Carlo (MC) treatment planning simulation tool to calculate X-PACT radiation doses in canine trials. Methods: FLUKA multi-particle MC simulation package was used to simulate a standard X-PACT radiation treatment beam of 80kVp withmore » the Varian OBI x-ray source geometry. The beam quality was verified by comparing measured and simulated attenuation of the beam by various thicknesses of aluminum (2–4.6 mm) under narrow beam conditions (HVL). The beam parameters at commissioning were then corroborated using MC, characterized and verified with empirically collected commissioning data, including: percent depth dose curves (PDD), back-scatter factors (BSF), collimator scatter factor(s), and heel effect, etc. All simulations were conducted for N=30M histories at M=100 iterations. Results: HVL and PDD simulation data agreed with an average percent error of 2.42%±0.33 and 6.03%±1.58, respectively. The mean square error (MSE) values for HVL and PDD (0.07% and 0.50%) were low, as expected; however, longer simulations are required to validate convergence to the expected values. Qualitatively, pre- and post-filtration source spectra matched well with 80kVp references generated via SPEKTR software. Further validation of commissioning data simulation is underway in preparation for first-time 3D dose calculations with canine CBCT data. Conclusion: We have prepared a Monte Carlo simulation capable of accurate dose calculation for use with ongoing X-PACT canine clinical trials. Preliminary results show good agreement with measured data and hold promise for accurate quantification of dose for this novel psoralen X-ray therapy. Funding Support, Disclosures, & Conflict of Interest: The Monte Carlo simulation work was not funded; Drs. Adamson & Oldham have received funding from Immunolight LLC for X-PACT research.« less

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

PubMed

Siebers, Jeffrey V

2008-04-04

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

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

SU-E-CAMPUS-T-02: Exploring Radiation Acoustics CT Dosimeter Design Aspects for Proton Therapy

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

Alsanea, F; Moskvin, V; Stantz, K

2014-06-15

Purpose: Investigate the design aspects and imaging dose capabilities of the Radiation Acoustics Computed Tomography (RA CT) dosimeter for Proton induced acoustics, with the objective to characterize a pulsed pencil proton beam. The focus includes scanner geometry, transducer array, and transducer bandwidth on image quality. Methods: The geometry of the dosimeter is a cylindrical water phantom (length 40cm, radius 15cm) with 71 ultrasound transducers placed along the length and end of the cylinder to achieve a weighted set of projections with spherical sampling. A 3D filtered backprojection algorithm was used to reconstruct the dosimetric images and compared to MC dosemore » distribution. First, 3D Monte Carlo (MC) Dose distributions for proton beam energies (range of 12cm, 16cm, 20cm, and 27cm) were used to simulate the acoustic pressure signal within this scanner for a pulsed proton beam of 1.8x107 protons, with a pulse width of 1 microsecond and a rise time of 0.1 microseconds. Dose comparison within the Bragg peak and distal edge were compared to MC analysis, where the integrated Gaussian was used to locate the 50% dose of the distal edge. To evaluate spatial fidelity, a set of point sources within the scanner field of view (15×15×15cm3) were simulated implementing a low-pass bandwidth response function (0 to 1MHz) equivalent to a multiple frequency transducer array, and the FWHM of the point-spread-function determined. Results: From the reconstructed images, RACT and MC range values are within 0.5mm, and the average variation of the dose within the Bragg peak are within 2%. The spatial resolution tracked with transducer bandwidth and projection angle sampling, and can be kept at 1.5mm. Conclusion: This design is ready for fabrication to start acquiring measurements. The 15 cm FOV is an optimum size for imaging dosimetry. Currently, simulations comparing transducer sensitivity, bandwidth, and proton beam parameters are being evaluated to assess signal-to-noise.« less

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

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

Taleei, R; Qin, N; Jiang, S

2016-06-15

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

Kinetic Monte Carlo Simulation of Oxygen and Cation Diffusion in Yttria-Stabilized Zirconia

NASA Technical Reports Server (NTRS)

Good, Brian

2011-01-01

Yttria-stabilized zirconia (YSZ) is of interest to the aerospace community, notably for its application as a thermal barrier coating for turbine engine components. In such an application, diffusion of both oxygen ions and cations is of concern. Oxygen diffusion can lead to deterioration of a coated part, and often necessitates an environmental barrier coating. Cation diffusion in YSZ is much slower than oxygen diffusion. However, such diffusion is a mechanism by which creep takes place, potentially affecting the mechanical integrity and phase stability of the coating. In other applications, the high oxygen diffusivity of YSZ is useful, and makes the material of interest for use as a solid-state electrolyte in fuel cells. The kinetic Monte Carlo (kMC) method offers a number of advantages compared with the more widely known molecular dynamics simulation method. In particular, kMC is much more efficient for the study of processes, such as diffusion, that involve infrequent events. We describe the results of kinetic Monte Carlo computer simulations of oxygen and cation diffusion in YSZ. Using diffusive energy barriers from ab initio calculations and from the literature, we present results on the temperature dependence of oxygen and cation diffusivity, and on the dependence of the diffusivities on yttria concentration and oxygen sublattice vacancy concentration. We also present results of the effect on diffusivity of oxygen vacancies in the vicinity of the barrier cations that determine the oxygen diffusion energy barriers.

Pairwise Multiple Comparisons in Single Group Repeated Measures Analysis.

ERIC Educational Resources Information Center

Barcikowski, Robert S.; Elliott, Ronald S.

Research was conducted to provide educational researchers with a choice of pairwise multiple comparison procedures (P-MCPs) to use with single group repeated measures designs. The following were studied through two Monte Carlo (MC) simulations: (1) The T procedure of J. W. Tukey (1953); (2) a modification of Tukey's T (G. Keppel, 1973); (3) the…

Assessment of Person Fit Using Resampling-Based Approaches

ERIC Educational Resources Information Center

Sinharay, Sandip

2016-01-01

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

Efficient Implementation of MrBayes on Multi-GPU

PubMed Central

Zhou, Jianfu; Liu, Xiaoguang; Wang, Gang

2013-01-01

MrBayes, using Metropolis-coupled Markov chain Monte Carlo (MCMCMC or (MC)3), is a popular program for Bayesian inference. As a leading method of using DNA data to infer phylogeny, the (MC)3 Bayesian algorithm and its improved and parallel versions are now not fast enough for biologists to analyze massive real-world DNA data. Recently, graphics processor unit (GPU) has shown its power as a coprocessor (or rather, an accelerator) in many fields. This article describes an efficient implementation a(MC)3 (aMCMCMC) for MrBayes (MC)3 on compute unified device architecture. By dynamically adjusting the task granularity to adapt to input data size and hardware configuration, it makes full use of GPU cores with different data sets. An adaptive method is also developed to split and combine DNA sequences to make full use of a large number of GPU cards. Furthermore, a new “node-by-node” task scheduling strategy is developed to improve concurrency, and several optimizing methods are used to reduce extra overhead. Experimental results show that a(MC)3 achieves up to 63× speedup over serial MrBayes on a single machine with one GPU card, and up to 170× speedup with four GPU cards, and up to 478× speedup with a 32-node GPU cluster. a(MC)3 is dramatically faster than all the previous (MC)3 algorithms and scales well to large GPU clusters. PMID:23493260

Efficient implementation of MrBayes on multi-GPU.

PubMed

Bao, Jie; Xia, Hongju; Zhou, Jianfu; Liu, Xiaoguang; Wang, Gang

2013-06-01

MrBayes, using Metropolis-coupled Markov chain Monte Carlo (MCMCMC or (MC)(3)), is a popular program for Bayesian inference. As a leading method of using DNA data to infer phylogeny, the (MC)(3) Bayesian algorithm and its improved and parallel versions are now not fast enough for biologists to analyze massive real-world DNA data. Recently, graphics processor unit (GPU) has shown its power as a coprocessor (or rather, an accelerator) in many fields. This article describes an efficient implementation a(MC)(3) (aMCMCMC) for MrBayes (MC)(3) on compute unified device architecture. By dynamically adjusting the task granularity to adapt to input data size and hardware configuration, it makes full use of GPU cores with different data sets. An adaptive method is also developed to split and combine DNA sequences to make full use of a large number of GPU cards. Furthermore, a new "node-by-node" task scheduling strategy is developed to improve concurrency, and several optimizing methods are used to reduce extra overhead. Experimental results show that a(MC)(3) achieves up to 63× speedup over serial MrBayes on a single machine with one GPU card, and up to 170× speedup with four GPU cards, and up to 478× speedup with a 32-node GPU cluster. a(MC)(3) is dramatically faster than all the previous (MC)(3) algorithms and scales well to large GPU clusters.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

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

PubMed

Bieda, Bogusław

2014-05-15

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

Improving x-ray fluorescence signal for benchtop polychromatic cone-beam x-ray fluorescence computed tomography by incident x-ray spectrum optimization: A Monte Carlo study

PubMed Central

Manohar, Nivedh; Jones, Bernard L.; Cho, Sang Hyun

2014-01-01

Purpose: To develop an accurate and comprehensive Monte Carlo (MC) model of an experimental benchtop polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) setup and apply this MC model to optimize incident x-ray spectrum for improving production/detection of x-ray fluorescence photons from gold nanoparticles (GNPs). Methods: A detailed MC model, based on an experimental XFCT system, was created using the Monte Carlo N-Particle (MCNP) transport code. The model was validated by comparing MC results including x-ray fluorescence (XRF) and scatter photon spectra with measured data obtained under identical conditions using 105 kVp cone-beam x-rays filtered by either 1 mm of lead (Pb) or 0.9 mm of tin (Sn). After validation, the model was used to investigate the effects of additional filtration of the incident beam with Pb and Sn. Supplementary incident x-ray spectra, representing heavier filtration (Pb: 2 and 3 mm; Sn: 1, 2, and 3 mm) were computationally generated and used with the model to obtain XRF/scatter spectra. Quasimonochromatic incident x-ray spectra (81, 85, 90, 95, and 100 keV with 10 keV full width at half maximum) were also investigated to determine the ideal energy for distinguishing gold XRF signal from the scatter background. Fluorescence signal-to-dose ratio (FSDR) and fluorescence-normalized scan time (FNST) were used as metrics to assess results. Results: Calculated XRF/scatter spectra for 1-mm Pb and 0.9-mm Sn filters matched (r ≥ 0.996) experimental measurements. Calculated spectra representing additional filtration for both filter materials showed that the spectral hardening improved the FSDR at the expense of requiring a much longer FNST. In general, using Sn instead of Pb, at a given filter thickness, allowed an increase of up to 20% in FSDR, more prominent gold XRF peaks, and up to an order of magnitude decrease in FNST. Simulations using quasimonochromatic spectra suggested that increasing source x-ray energy, in the investigated range of 81–100 keV, increased the FSDR up to a factor of 20, compared to 1 mm Pb, and further facilitated separation of gold XRF peaks from the scatter background. Conclusions: A detailed MC model of an experimental benchtop XFCT system has been developed and validated. In exemplary calculations to illustrate the usefulness of this model, it was shown that potential use of quasimonochromatic spectra or judicious choice of filter material/thickness to tailor the spectrum of a polychromatic x-ray source can significantly improve the performance of benchtop XFCT, while considering trade-offs between FSDR and FNST. As demonstrated, the current MC model is a reliable and powerful computational tool that can greatly expedite the further development of a benchtop XFCT system for routine preclinical molecular imaging with GNPs and other metal probes. PMID:25281958

Improving x-ray fluorescence signal for benchtop polychromatic cone-beam x-ray fluorescence computed tomography by incident x-ray spectrum optimization: a Monte Carlo study.

PubMed

Manohar, Nivedh; Jones, Bernard L; Cho, Sang Hyun

2014-10-01

To develop an accurate and comprehensive Monte Carlo (MC) model of an experimental benchtop polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) setup and apply this MC model to optimize incident x-ray spectrum for improving production/detection of x-ray fluorescence photons from gold nanoparticles (GNPs). A detailed MC model, based on an experimental XFCT system, was created using the Monte Carlo N-Particle (MCNP) transport code. The model was validated by comparing MC results including x-ray fluorescence (XRF) and scatter photon spectra with measured data obtained under identical conditions using 105 kVp cone-beam x-rays filtered by either 1 mm of lead (Pb) or 0.9 mm of tin (Sn). After validation, the model was used to investigate the effects of additional filtration of the incident beam with Pb and Sn. Supplementary incident x-ray spectra, representing heavier filtration (Pb: 2 and 3 mm; Sn: 1, 2, and 3 mm) were computationally generated and used with the model to obtain XRF/scatter spectra. Quasimonochromatic incident x-ray spectra (81, 85, 90, 95, and 100 keV with 10 keV full width at half maximum) were also investigated to determine the ideal energy for distinguishing gold XRF signal from the scatter background. Fluorescence signal-to-dose ratio (FSDR) and fluorescence-normalized scan time (FNST) were used as metrics to assess results. Calculated XRF/scatter spectra for 1-mm Pb and 0.9-mm Sn filters matched (r ≥ 0.996) experimental measurements. Calculated spectra representing additional filtration for both filter materials showed that the spectral hardening improved the FSDR at the expense of requiring a much longer FNST. In general, using Sn instead of Pb, at a given filter thickness, allowed an increase of up to 20% in FSDR, more prominent gold XRF peaks, and up to an order of magnitude decrease in FNST. Simulations using quasimonochromatic spectra suggested that increasing source x-ray energy, in the investigated range of 81-100 keV, increased the FSDR up to a factor of 20, compared to 1 mm Pb, and further facilitated separation of gold XRF peaks from the scatter background. A detailed MC model of an experimental benchtop XFCT system has been developed and validated. In exemplary calculations to illustrate the usefulness of this model, it was shown that potential use of quasimonochromatic spectra or judicious choice of filter material/thickness to tailor the spectrum of a polychromatic x-ray source can significantly improve the performance of benchtop XFCT, while considering trade-offs between FSDR and FNST. As demonstrated, the current MC model is a reliable and powerful computational tool that can greatly expedite the further development of a benchtop XFCT system for routine preclinical molecular imaging with GNPs and other metal probes.

Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code

DOE PAGES

Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; ...

2015-12-21

This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Somemore » specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000 ® problems. These benchmark and scaling studies show promising results.« less

Forward-backward multiplicity correlation in high-energy nucleus-nucleus interactions at a few AGeV/c

NASA Astrophysics Data System (ADS)

Bhattacharyya, Swarnapratim; Haiduc, Maria; Neagu, Alina Tania; Firu, Elena

2014-07-01

We have presented a systematic study of two-particle rapidity correlations in terms of investigating the dynamical fluctuation observable \\sigma _c^2 in the forward-backward pseudo-rapidity windows by analyzing the experimental data of {}_{}^{16} O{--}AgBr interactions at 4.5 AGeV/c, {}_{}^{22} Ne{--}AgBr interactions at 4.1 AGeV/c, {}_{}^{28} Si{--}AgBr and {}_{}^{32} S{--}AgBr interactions at 4.5 AGeV/c. The experimental results have been compared with the results obtained from the analysis of event sample simulated (MC-RAND) by generating random numbers and also with the analysis of events generated by the UrQMD and AMPT model. Our study confirms the presence of strong short-range correlations among the produced particles in the forward and the backward pseudo-rapidity region. The analysis of the simple Monte Carlo-simulated (MC-RAND) events signifies that the observed correlations are not due to mere statistics only; explanation of such correlations can be attributed to the presence of dynamical fluctuations during the production of charged pions. Comparisons of the experimental results with the results obtained from analyzing the UrQMD data sample indicate that the UrQMD model cannot reproduce the experimental findings. The AMPT model also cannot explain the experimental results satisfactorily. Comparisons of our experimental results with the results obtained from the analysis of higher energy emulsion data and with the results of the RHIC data have also been presented.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Equilibrium statistical mechanics of self-consistent wave-particle system

NASA Astrophysics Data System (ADS)

Elskens, Yves

2005-10-01

The equilibrium distribution of N particles and M waves (e.g. Langmuir) is analysed in the weak-coupling limit for the self-consistent hamiltonian model H = ∑rpr^2 /(2m) + ∑jφjIj+ ɛ∑r,j(βj/ kj) (kjxr- θj) [1]. In the canonical ensemble, with temperature T and reservoir velocity v < jφj/kj, the wave intensities are almost independent and exponentially distributed, with expectation = kBT / (φj- kjv). These equilibrium predictions are in agreement with Monte Carlo samplings [2] and with direct simulations of the dynamics, indicating equivalence between canonical and microcanonical ensembles. [1] Y. Elskens and D.F. Escande, Microscopic dynamics of plasmas and chaos (IoP publishing, Bristol, 2003). [2] M-C. Firpo and F. Leyvraz, 30th EPS conf. contr. fusion and plasma phys., P-2.8 (2003).

Study on detection geometry and detector shielding for portable PGNAA system using PHITS

NASA Astrophysics Data System (ADS)

Ithnin, H.; Dahing, L. N. S.; Lip, N. M.; Rashid, I. Q. Abd; Mohamad, E. J.

2018-01-01

Prompt gamma-ray neutron activation analysis (PGNAA) measurements require efficient detectors for gamma-ray detection. Apart from experimental studies, the Monte Carlo (MC) method has become one of the most popular tools in detector studies. The absolute efficiency for a 2 × 2 inch cylindrical Sodium Iodide (NaI) detector has been modelled using the PHITS software and compared with previous studies in literature. In the present work, PHITS code is used for optimization of portable PGNAA system using the validated NaI detector. The detection geometry is optimized by moving the detector along the sample to find the highest intensity of the prompt gamma generated from the sample. Shielding material for the validated NaI detector is also studied to find the best option for the PGNAA system setup. The result shows the optimum distance for detector is on the surface of the sample and around 15 cm from the source. The results specify that this process can be followed to determine the best setup for PGNAA system for a different sample size and detector type. It can be concluded that data from PHITS code is a strong tool not only for efficiency studies but also for optimization of PGNAA system.

OpenMC In Situ Source Convergence Detection

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

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

2016-05-07

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

Singular Spectrum Analysis for Astronomical Time Series: Constructing a Parsimonious Hypothesis Test

NASA Astrophysics Data System (ADS)

Greco, G.; Kondrashov, D.; Kobayashi, S.; Ghil, M.; Branchesi, M.; Guidorzi, C.; Stratta, G.; Ciszak, M.; Marino, F.; Ortolan, A.

We present a data-adaptive spectral method - Monte Carlo Singular Spectrum Analysis (MC-SSA) - and its modification to tackle astrophysical problems. Through numerical simulations we show the ability of the MC-SSA in dealing with 1/f β power-law noise affected by photon counting statistics. Such noise process is simulated by a first-order autoregressive, AR(1) process corrupted by intrinsic Poisson noise. In doing so, we statistically estimate a basic stochastic variation of the source and the corresponding fluctuations due to the quantum nature of light. In addition, MC-SSA test retains its effectiveness even when a significant percentage of the signal falls below a certain level of detection, e.g., caused by the instrument sensitivity. The parsimonious approach presented here may be broadly applied, from the search for extrasolar planets to the extraction of low-intensity coherent phenomena probably hidden in high energy transients.

FAST TRACK COMMUNICATION: The origin of Bohm diffusion, investigated by a comparison of different modelling methods

NASA Astrophysics Data System (ADS)

Bultinck, E.; Mahieu, S.; Depla, D.; Bogaerts, A.

2010-07-01

'Bohm diffusion' causes the electrons to diffuse perpendicularly to the magnetic field lines. However, its origin is not yet completely understood: low and high frequency electric field fluctuations are both named to cause Bohm diffusion. The importance of including this process in a Monte Carlo (MC) model is demonstrated by comparing calculated ionization rates with particle-in-cell/Monte Carlo collisions (PIC/MCC) simulations. A good agreement is found with a Bohm diffusion parameter of 0.05, which corresponds well to experiments. Since the PIC/MCC method accounts for fast electric field fluctuations, we conclude that Bohm diffusion is caused by fast electric field phenomena.

Monte Carlo simulation for light propagation in 3D tooth model

NASA Astrophysics Data System (ADS)

Fu, Yongji; Jacques, Steven L.

2011-03-01

Monte Carlo (MC) simulation was implemented in a three dimensional tooth model to simulate the light propagation in the tooth for antibiotic photodynamic therapy and other laser therapy. The goal of this research is to estimate the light energy deposition in the target region of tooth with given light source information, tooth optical properties and tooth structure. Two use cases were presented to demonstrate the practical application of this model. One case was comparing the isotropic point source and narrow beam dosage distribution and the other case was comparing different incident points for the same light source. This model will help the doctor for PDT design in the tooth.

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

DOE PAGES

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

2017-02-15

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

A Simulation Study on the Performance of the Simple Difference and Covariance-Adjusted Scores in Randomized Experimental Designs

ERIC Educational Resources Information Center

Petscher, Yaacov; Schatschneider, Christopher

2011-01-01

Research by Huck and McLean (1975) demonstrated that the covariance-adjusted score is more powerful than the simple difference score, yet recent reviews indicate researchers are equally likely to use either score type in two-wave randomized experimental designs. A Monte Carlo simulation was conducted to examine the conditions under which the…

Break the Data-Bank with Monte Carlo? Statistical Problems in the Dispute between Conroy (1996) and Crinella, McCleary, and Swanson (1998).

ERIC Educational Resources Information Center

Heifetz, Louis J.

1998-01-01

Comments on "The Small ICF/MR Program: Dimensions of Quality and Cost" (Conroy), that found small Intermediate Care Facilities (ICF) for individuals with mental retardation are inferior to other community programs. Acknowledges that while some research problems exist, no important evidence against the findings has been provided. (CR)

Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique

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

Sampson, Andrew; Le Yi; Williamson, Jeffrey F.

2012-02-15

Purpose: To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. Methods: CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, {Delta}D, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled inmore » a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 {sup 125}I seeds. The breast case consisted of 87 Model-200 {sup 103}Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D{sub 90}, as well as for various anatomical regions. Results: Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 x 1 x 1 mm{sup 3} dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 x 1 x 1 mm{sup 3}) and breast (0.67 x 0.67 x 0.8 mm{sup 3}) CTVs, respectively. Conclusions: CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.« less

Dosimetric and microdosimetric analyses for blood exposed to reactor-derived thermal neutrons.

PubMed

Ali, F; Atanackovic, J; Boyer, C; Festarini, A; Kildea, J; Paterson, L C; Rogge, R; Stuart, M; Richardson, R B

2018-06-06

Thermal neutrons are found in reactor, radiotherapy, aircraft, and space environments. The purpose of this study was to characterise the dosimetry and microdosimetry of thermal neutron exposures, using three simulation codes, as a precursor to quantitative radiobiological studies using blood samples. An irradiation line was designed employing a pyrolytic graphite crystal or-alternatively-a super mirror to expose blood samples to thermal neutrons from the National Research Universal reactor to determine radiobiological parameters. The crystal was used when assessing the relative biological effectiveness for dicentric chromosome aberrations, and other biomarkers, in lymphocytes over a low absorbed dose range of 1.2-14 mGy. Higher exposures using a super mirror will allow the additional quantification of mitochondrial responses. The physical size of the thermal neutron fields and their respective wavelength distribution was determined using the McStas Monte Carlo code. Spinning the blood samples produced a spatially uniform absorbed dose as determined from Monte Carlo N-Particle version 6 simulations. The major part (71%) of the total absorbed dose to blood was determined to be from the 14 N(n,p) 14 C reaction and the remainder from the 1 H(n,γ) 2 H reaction. Previous radiobiological experiments at Canadian Nuclear Laboratories involving thermal neutron irradiation of blood yielded a relative biological effectiveness of 26 ± 7. Using the Particle and Heavy Ion Transport Code System, a similar value of ∼19 for the quality factor of thermal neutrons initiating the 14 N(n,p) 14 C reaction in soft tissue was determined by microdosimetric simulations. This calculated quality factor is of similar high value to the experimentally-derived relative biological effectiveness, and indicates the potential of thermal neutrons to induce deleterious health effects in superficial organs such as cataracts of the eye lens.

Leveraging Gibbs Ensemble Molecular Dynamics and Hybrid Monte Carlo/Molecular Dynamics for Efficient Study of Phase Equilibria.

PubMed

Gartner, Thomas E; Epps, Thomas H; Jayaraman, Arthi

2016-11-08

We describe an extension of the Gibbs ensemble molecular dynamics (GEMD) method for studying phase equilibria. Our modifications to GEMD allow for direct control over particle transfer between phases and improve the method's numerical stability. Additionally, we found that the modified GEMD approach had advantages in computational efficiency in comparison to a hybrid Monte Carlo (MC)/MD Gibbs ensemble scheme in the context of the single component Lennard-Jones fluid. We note that this increase in computational efficiency does not compromise the close agreement of phase equilibrium results between the two methods. However, numerical instabilities in the GEMD scheme hamper GEMD's use near the critical point. We propose that the computationally efficient GEMD simulations can be used to map out the majority of the phase window, with hybrid MC/MD used as a follow up for conditions under which GEMD may be unstable (e.g., near-critical behavior). In this manner, we can capitalize on the contrasting strengths of these two methods to enable the efficient study of phase equilibria for systems that present challenges for a purely stochastic GEMC method, such as dense or low temperature systems, and/or those with complex molecular topologies.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Development of a photon-cell interactive monte carlo simulation for non-invasive measurement of blood glucose level by Raman spectroscopy.

PubMed

Sakota, Daisuke; Kosaka, Ryo; Nishida, Masahiro; Maruyama, Osamu

2015-01-01

Turbidity variation is one of the major limitations in Raman spectroscopy for quantifying blood components, such as glucose, non-invasively. To overcome this limitation, we have developed a Raman scattering simulation using a photon-cell interactive Monte Carlo (pciMC) model that tracks photon migration in both the extra- and intracellular spaces without relying on the macroscopic scattering phase function and anisotropy factor. The interaction of photons at the plasma-cell boundary of randomly oriented three-dimensionally biconcave red blood cells (RBCs) is modeled using geometric optics. The validity of the developed pciMCRaman was investigated by comparing simulation and experimental results of Raman spectroscopy of glucose level in a bovine blood sample. The scattering of the excitation laser at a wavelength of 785 nm was simulated considering the changes in the refractive index of the extracellular solution. Based on the excitation laser photon distribution within the blood, the Raman photon derived from the hemoglobin and glucose molecule at the Raman shift of 1140 cm(-1) = 862 nm was generated, and the photons reaching the detection area were counted. The simulation and experimental results showed good correlation. It is speculated that pciMCRaman can provide information about the ability and limitations of the measurement of blood glucose level.

Comparison of selected dose calculation algorithms in radiotherapy treatment planning for tissues with inhomogeneities

NASA Astrophysics Data System (ADS)

Woon, Y. L.; Heng, S. P.; Wong, J. H. D.; Ung, N. M.

2016-03-01

Inhomogeneity correction is recommended for accurate dose calculation in radiotherapy treatment planning since human body are highly inhomogeneous with the presence of bones and air cavities. However, each dose calculation algorithm has its own limitations. This study is to assess the accuracy of five algorithms that are currently implemented for treatment planning, including pencil beam convolution (PBC), superposition (SP), anisotropic analytical algorithm (AAA), Monte Carlo (MC) and Acuros XB (AXB). The calculated dose was compared with the measured dose using radiochromic film (Gafchromic EBT2) in inhomogeneous phantoms. In addition, the dosimetric impact of different algorithms on intensity modulated radiotherapy (IMRT) was studied for head and neck region. MC had the best agreement with the measured percentage depth dose (PDD) within the inhomogeneous region. This was followed by AXB, AAA, SP and PBC. For IMRT planning, MC algorithm is recommended for treatment planning in preference to PBC and SP. The MC and AXB algorithms were found to have better accuracy in terms of inhomogeneity correction and should be used for tumour volume within the proximity of inhomogeneous structures.

Monte Carlo evaluation of RapidArc™ oropharynx treatment planning strategies for sparing of midline structures

NASA Astrophysics Data System (ADS)

Bush, K.; Zavgorodni, S.; Gagne, I.; Townson, R.; Ansbacher, W.; Beckham, W.

2010-08-01

The aim of the study was to perform the Monte Carlo (MC) evaluation of RapidArc™ (Varian Medical Systems, Palo Alto, CA) dose calculations for four oropharynx midline sparing planning strategies. Six patients with squamous cell cancer of the oropharynx were each planned with four RapidArc head and neck treatment strategies consisting of single and double photon arcs. In each case, RTOG0522 protocol objectives were used during planning optimization. Dose calculations performed with the analytical anisotropic algorithm (AAA) are compared against BEAMnrc/DOSXYZnrc dose calculations for the 24-plan dataset. Mean dose and dose-to-98%-of-structure-volume (D98%) were used as metrics in the evaluation of dose to planning target volumes (PTVs). Mean dose and dose-to-2%-of-structure-volume (D2%) were used to evaluate dose differences within organs at risk (OAR). Differences in the conformity index (CI) and the homogeneity index (HI) as well as 3D dose distributions were also observed. AAA calculated PTV mean dose, D98%, and HIs showed very good agreement with MC dose calculations within the 0.8% MC (statistical) calculation uncertainty. Regional node volume (PTV-80%) mean dose and D98% were found to be overestimated (1.3%, σ = 0.8% and 2.3%, σ = 0.8%, respectively) by the AAA with respect to MC calculations. Mean dose and D2% to OAR were also observed to be consistently overestimated by the AAA. Increasing dose calculation differences were found in planning strategies exhibiting a higher overall fluence modulation. From the plan dataset, the largest local dose differences were observed in heavily shielded regions and within the esophageal and sinus cavities. AAA dose calculations as implemented in RapidArc™ demonstrate excellent agreement with MC calculations in unshielded regions containing moderate inhomogeneities. Acceptable agreement is achieved in regions of increased MLC shielding. Differences in dose are attributed to inaccuracies in the AAA-modulated fluence modeling, modeling of material inhomogeneities and dose deposition within low-density materials. The use of MC dose calculations leads to the same general conclusion as using AAA that a two arc delivery with limited collimator opening can provide the greatest amount of midline sparing compared to the other techniques investigated.

Understanding and Predicting Geomagnetic Dipole Reversals Via Low Dimensional Models and Data Assimilation

NASA Astrophysics Data System (ADS)

Morzfeld, M.; Fournier, A.; Hulot, G.

2014-12-01

We investigate the geophysical relevance of low-dimensional models of the geomagnetic dipole fieldby comparing these models to the signed relative paleomagnetic intensity over the past 2 Myr.The comparison is done via Bayesian statistics, implemented numerically by Monte Carlo (MC) sampling.We consider several MC schemes, as well as two data sets to show the robustness of our approach with respect to its numerical implementation and to the details of how the data are collected.The data we consider are the Sint-2000 [1] and PADM2M [2] data sets.We consider three stochastic differential equation (SDE) models and one deterministic model. Experiments with synthetic data show that it is feasible that a low dimensional modelcan learn the geophysical state from data of only the dipole field,and reveal the limitations of the low-dimensional models.For example, the G12 model [3] (a deterministic model that generates dipole reversals by crisis induced intermittency)can only match either one of the two important time scales we find in the data. The MC sampling approach also allows usto use the models to make predictions of the dipole field.We assess how reliably dipole reversals can be predictedwith our approach by hind-casting five reversals documented over the past 2 Myr. We find that, besides its limitations, G12 can be used to predict reversals reliably,however only with short lead times and over short horizons. The scalar SDE models on the other hand are not useful for prediction of dipole reversals.References Valet, J.P., Maynadier,L and Guyodo, Y., 2005, Geomagnetic field strength and reversal rate over the past 2 Million years, Nature, 435, 802-805. Ziegler, L.B., Constable, C.G., Johnson, C.L. and Tauxe, L., 2011, PADM2M: a penalized maximum likelihood model of the 0-2 Ma paleomagnetic axial dipole moment, Geophysical Journal International, 184, 1069-1089. Gissinger, C., 2012, A new deterministic model for chaotic reversals, European Physical Journal B, 85:137.

SU-F-BRD-16: Under Dose Regions Recalculated by Monte Carlo Cannot Predict the Local Failure for NSCLC Patients Treated with SBRT

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

Liu, H; Cherian, S; Stephans, K

2014-06-15

Purpose: To investigate whether Monte Carlo (MC) recalculated dose distributions can predict the geometric location of the recurrence for nonsmall cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). Methods: Thirty NSCLC patients with local recurrence were retrospectively selected for this study. The recurred gross target volumes (rGTV) were delineated on the follow-up CT/PET images and then rigidly transferred via imaging fusion to the original planning CTs. Failure pattern was defined according to the overlap between the rGTV and planning GTV (pGTV) as: (a) in-field failure (≥80%), (b) marginal failure (20%–80%), and (c) out-of-field failure (≤20%). All clinicalmore » plans were calculated initially with pencil beam (PB) with or without heterogeneity correction dependent of protocols. These plans were recalculated with MC with heterogeneity correction. Because of non-uniform dose distributions in the rGTVs, the rGTVs were further divided into four regions: inside the pGTV (GTVin), inside the PTV (PTVin), outside the pGTV (GTVout), and outside the PTV (PTVout). The mean doses to these regions were reported and analyzed separately. Results: Among 30 patients, 10 patients had infield recurrences, 15 marginal and 5 out-of-field failures. With MC calculations, D95 and D99 of the PTV were reduced by (10.6 ± 7.4)% and (11.7 ± 7.9)%. The average MC calculated mean doses of GTVin, GTVout, PTVin and PTVout were 48.2 ± 5.3 Gy, 48.2 ± 5.5 Gy, 46.3 ± 6.2 Gy and 46.6 ± 5.6 Gy, respectively. No significant dose differences between GTVin and GTVout (p=0.65), PTVin and PTVout (p=0.19) were observed, using the paired students t-test. Conclusion: Although the PB calculations underestimated the tumor target doses, the geometric location of the recurrence did not correlate with the mean doses of subsections of the recurrent GTV. Under dose regions recalculated by MC cannot predict the local failure for NSCLC patients treated with SBRT.« less

SU-F-T-610: Comparison of Output Factors for Small Radiation Fields Used in SBRT Treatment

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

Gupta, R; Eldib, A; Li, J

2016-06-15

Purpose: In order to fundamentally understand our previous dose verification results between measurements and calculations from treatment planning system (TPS) for SBRT plans for different sized targets, the goal of the present work was to compare output factors for small fields measured using EDR2 films with TPS and Monet Carlo (MC) simulations. Methods: 6MV beam was delivered to EDR2 films for each of the following field sizes; 1×1 cm{sup 2}, 1.5×1.5 cm{sup 2}, 2×2 cm{sup 2}, 3×3 cm{sup 2}, 4×4 cm{sup 2}, 5×5 cm{sup 2} and 10×10 cm{sup 2}. The films were developed in a film processer, then scanned withmore » a Vidar VXR-16 scanner and analyzed using RIT113 version 6.1. A standard calibration curve was obtained with the 6MV beam and was used to get absolute dose for measured field sizes. Similar plans for all fields sizes mentioned above were generated using Eclipse with the Analytical Anisotropic Algorithm. Similarly, MC simulations were carried out using the MCSIM, an in-house MC code for different field sizes. Output factors normalized to 10×10 cm{sup 2} reference field were calculated for different field sizes in all the three cases and compared. Results: For field sizes ranging from 1×1 cm{sup 2} to 2×2 cm{sup 2}, the differences in output factors between measurements (films), TPS and MC simulations were within 0.22%. For field sizes ranging from 3×3cm{sup 2} to 5×5cm{sup 2}, differences in output factors were within 0.10%. Conclusion: No clinically significant difference was obtained in output factors for different field sizes acquired from films, TPS and MC simulations. Our results showed that the output factors are predicted accurately from TPS when compared to the actual measurements and superior dose calculation Monte Carlo method. This study would help us in understanding our previously obtained dose verification results for small fields used in the SBRT treatment.« less

SU-G-201-13: Investigation of Dose Variation Induced by HDR Ir-192 Source Global Shift Within the Varian Ring Applicator Using Monte Carlo Methods

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

Yang, Y; Cai, J; Meltsner, S

2016-06-15

Purpose: The Varian tandem and ring applicators are used to deliver HDR Ir-192 brachytherapy for cervical cancer. The source path within the ring is hard to predict due to the larger interior ring lumen. Some studies showed the source could be several millimeters different from planned positions, while other studies demonstrated minimal dosimetric impact. A global shift can be applied to limit the effect of positioning offsets. The purpose of this study was to assess the necessities of implementing a global source shift using Monte Carlo (MC) simulations. Methods: The MCNP5 radiation transport code was used for all MC simulations.more » To accommodate TG-186 guidelines and eliminate inter-source attenuation, a BrachyVision plan with 10 dwell positions (0.5cm step sizes) was simulated as the summation of 10 individual sources with equal dwell times for simplification. To simplify the study, the tandem was also excluded from the MC model. Global shifts of ±0.1, ±0.3, ±0.5 cm were then simulated as distal and proximal from the reference positions. Dose was scored in water for all MC simulations and was normalized to 100% at the normalization point 0.5 cm from the cap in the ring plane. For dose comparison, Point A was 2 cm caudal from the buildup cap and 2 cm lateral on either side of the ring axis. With seventy simulations, 108 photon histories gave a statistical uncertainties (k=1) <2% for (0.1 cm)3 voxels. Results: Compared to no global shift, average Point A doses were 0.0%, 0.4%, and 2.2% higher for distal global shifts, and 0.4%, 2.8%, and 5.1% higher for proximal global shifts, respectively. The MC Point A doses differed by < 1% when compared to BrachyVision. Conclusion: Dose variations were not substantial for ±0.3 cm global shifts, which is common in clinical practice.« less

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

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

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

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

Chesneau, H; Lazaro, D; Blideanu, V

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

Systematic investigation on the validity of partition model dosimetry for 90Y radioembolization using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Aziz Hashikin, Nurul Ab; Yeong, Chai-Hong; Guatelli, Susanna; Jeet Abdullah, Basri Johan; Ng, Kwan-Hoong; Malaroda, Alessandra; Rosenfeld, Anatoly; Perkins, Alan Christopher

2017-09-01

We aimed to investigate the validity of the partition model (PM) in estimating the absorbed doses to liver tumour ({{D}T} ), normal liver tissue ({{D}NL} ) and lungs ({{D}L} ), when cross-fire irradiations between these compartments are being considered. MIRD-5 phantom incorporated with various treatment parameters, i.e. tumour involvement (TI), tumour-to-normal liver uptake ratio (T/N) and lung shunting (LS), were simulated using the Geant4 Monte Carlo (MC) toolkit. 108 track histories were generated for each combination of the three parameters to obtain the absorbed dose per activity uptake in each compartment (DT{{AT}} , DNL{{ANL}} , and DL{{AL}} ). The administered activities, A were estimated using PM, so as to achieve either limiting doses to normal liver, DNLlim or lungs, ~DLlim (70 or 30 Gy, respectively). Using these administered activities, the activity uptake in each compartment ({{A}T} , {{A}NL} , and {{A}L} ) was estimated and multiplied with the absorbed dose per activity uptake attained using the MC simulations, to obtain the actual dose received by each compartment. PM overestimated {{D}L} by 11.7% in all cases, due to the escaped particles from the lungs. {{D}T} and {{D}NL} by MC were largely affected by T/N, which were not considered by PM due to cross-fire exclusion at the tumour-normal liver boundary. These have resulted in the overestimation of {{D}T} by up to 8% and underestimation of {{D}NL} by as high as  -78%, by PM. When DNLlim was estimated via PM, the MC simulations showed significantly higher {{D}NL} for cases with higher T/N, and LS  ⩽  10%. All {{D}L} and {{D}T} by MC were overestimated by PM, thus DLlim were never exceeded. PM leads to inaccurate dose estimations due to the exclusion of cross-fire irradiation, i.e. between the tumour and normal liver tissue. Caution should be taken for cases with higher TI and T/N, and lower LS, as they contribute to major underestimation of {{D}NL} . For {{D}L} , a different correction factor for dose calculation may be used for improved accuracy.

Multi-fidelity uncertainty quantification in large-scale predictive simulations of turbulent flow

NASA Astrophysics Data System (ADS)

Geraci, Gianluca; Jofre-Cruanyes, Lluis; Iaccarino, Gianluca

2017-11-01

The performance characterization of complex engineering systems often relies on accurate, but computationally intensive numerical simulations. It is also well recognized that in order to obtain a reliable numerical prediction the propagation of uncertainties needs to be included. Therefore, Uncertainty Quantification (UQ) plays a fundamental role in building confidence in predictive science. Despite the great improvement in recent years, even the more advanced UQ algorithms are still limited to fairly simplified applications and only moderate parameter dimensionality. Moreover, in the case of extremely large dimensionality, sampling methods, i.e. Monte Carlo (MC) based approaches, appear to be the only viable alternative. In this talk we describe and compare a family of approaches which aim to accelerate the convergence of standard MC simulations. These methods are based on hierarchies of generalized numerical resolutions (multi-level) or model fidelities (multi-fidelity), and attempt to leverage the correlation between Low- and High-Fidelity (HF) models to obtain a more accurate statistical estimator without introducing additional HF realizations. The performance of these methods are assessed on an irradiated particle laden turbulent flow (PSAAP II solar energy receiver). This investigation was funded by the United States Department of Energy's (DoE) National Nuclear Security Administration (NNSA) under the Predicitive Science Academic Alliance Program (PSAAP) II at Stanford University.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

A single-source photon source model of a linear accelerator for Monte Carlo dose calculation

PubMed Central

Glatting, Gerhard; Wenz, Frederik; Fleckenstein, Jens

2017-01-01

Purpose To introduce a new method of deriving a virtual source model (VSM) of a linear accelerator photon beam from a phase space file (PSF) for Monte Carlo (MC) dose calculation. Materials and methods A PSF of a 6 MV photon beam was generated by simulating the interactions of primary electrons with the relevant geometries of a Synergy linear accelerator (Elekta AB, Stockholm, Sweden) and recording the particles that reach a plane 16 cm downstream the electron source. Probability distribution functions (PDFs) for particle positions and energies were derived from the analysis of the PSF. These PDFs were implemented in the VSM using inverse transform sampling. To model particle directions, the phase space plane was divided into a regular square grid. Each element of the grid corresponds to an area of 1 mm2 in the phase space plane. The average direction cosines, Pearson correlation coefficient (PCC) between photon energies and their direction cosines, as well as the PCC between the direction cosines were calculated for each grid element. Weighted polynomial surfaces were then fitted to these 2D data. The weights are used to correct for heteroscedasticity across the phase space bins. The directions of the particles created by the VSM were calculated from these fitted functions. The VSM was validated against the PSF by comparing the doses calculated by the two methods for different square field sizes. The comparisons were performed with profile and gamma analyses. Results The doses calculated with the PSF and VSM agree to within 3% /1 mm (>95% pixel pass rate) for the evaluated fields. Conclusion A new method of deriving a virtual photon source model of a linear accelerator from a PSF file for MC dose calculation was developed. Validation results show that the doses calculated with the VSM and the PSF agree to within 3% /1 mm. PMID:28886048

A single-source photon source model of a linear accelerator for Monte Carlo dose calculation.

PubMed

Nwankwo, Obioma; Glatting, Gerhard; Wenz, Frederik; Fleckenstein, Jens

2017-01-01

To introduce a new method of deriving a virtual source model (VSM) of a linear accelerator photon beam from a phase space file (PSF) for Monte Carlo (MC) dose calculation. A PSF of a 6 MV photon beam was generated by simulating the interactions of primary electrons with the relevant geometries of a Synergy linear accelerator (Elekta AB, Stockholm, Sweden) and recording the particles that reach a plane 16 cm downstream the electron source. Probability distribution functions (PDFs) for particle positions and energies were derived from the analysis of the PSF. These PDFs were implemented in the VSM using inverse transform sampling. To model particle directions, the phase space plane was divided into a regular square grid. Each element of the grid corresponds to an area of 1 mm2 in the phase space plane. The average direction cosines, Pearson correlation coefficient (PCC) between photon energies and their direction cosines, as well as the PCC between the direction cosines were calculated for each grid element. Weighted polynomial surfaces were then fitted to these 2D data. The weights are used to correct for heteroscedasticity across the phase space bins. The directions of the particles created by the VSM were calculated from these fitted functions. The VSM was validated against the PSF by comparing the doses calculated by the two methods for different square field sizes. The comparisons were performed with profile and gamma analyses. The doses calculated with the PSF and VSM agree to within 3% /1 mm (>95% pixel pass rate) for the evaluated fields. A new method of deriving a virtual photon source model of a linear accelerator from a PSF file for MC dose calculation was developed. Validation results show that the doses calculated with the VSM and the PSF agree to within 3% /1 mm.

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

Wronski, M; Sarfehnia, A; Sahgal, A

Purpose: To evaluate the interface effects when irradiating through a hip prosthesis in the presence of an orthogonal 1.5 T magnetic field using Monte Carlo simulations. Methods: A 20×20×38 cm virtual phantom with two 5×5×5 cm sections of bilateral titanium hip prosthesis was created in GPU-based Monte Carlo (MC) algorithm (GPUMCD, Elekta AB, Stockholm Sweden). The lateral prosthesis spacing was based on a representative patient CT scan. A treatment SAD of 143.5 cm was chosen, corresponding to the Elekta AB MRI Linac and the beam energy distribution was sampled from a histogram representing the true MRI Linac spectrum. A magneticmore » field of 1.5 T was applied perpendicular to the plane of irradiation. Dose was calculated, in voxels of side 1 mm, for 2×2, 5×5, and 10×10 cm treatment field sizes with normal beam incidence (gantry at 90° or 270°) and at 5° and 10° from normal, representing the range of incidence through the bilateral prosthesis. Results: With magnetic field ON (B-On) and normal beam incidence the backscatter dose at the interfaces of proximal and distal implants is reduced for all the field sizes compared to the magnetic field OFF (B-Off) case. The absolute reduction in doses at the interface was in the range of 12.93% to 13.16% for the proximal implant and 13.57% to 16.12% for the distal implant. Similarly for the oblique incidences of 5o and 10o the dose in the plane adjacent to the prosthetic implants is lower when the magnetic field is ON. Conclusion: The dosimetric effects of irradiating through a hip prosthesis in the presence of a transverse magnetic field have been determined using MC simulation. The backscatter dose reduction translates into significantly lower hot spots at the prosthetic interfaces, which are otherwise substantially high in the absence of the magnetic field. This project was supported through funding provided by ElektaTM.« less

Analytical, experimental, and Monte Carlo system response matrix for pinhole SPECT reconstruction

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

Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es; Pino, Francisco; Silva-Rodríguez, Jesús

2014-03-15

Purpose: To assess the performance of two approaches to the system response matrix (SRM) calculation in pinhole single photon emission computed tomography (SPECT) reconstruction. Methods: Evaluation was performed using experimental data from a low magnification pinhole SPECT system that consisted of a rotating flat detector with a monolithic scintillator crystal. The SRM was computed following two approaches, which were based on Monte Carlo simulations (MC-SRM) and analytical techniques in combination with an experimental characterization (AE-SRM). The spatial response of the system, obtained by using the two approaches, was compared with experimental data. The effect of the MC-SRM and AE-SRM approachesmore » on the reconstructed image was assessed in terms of image contrast, signal-to-noise ratio, image quality, and spatial resolution. To this end, acquisitions were carried out using a hot cylinder phantom (consisting of five fillable rods with diameters of 5, 4, 3, 2, and 1 mm and a uniform cylindrical chamber) and a custom-made Derenzo phantom, with center-to-center distances between adjacent rods of 1.5, 2.0, and 3.0 mm. Results: Good agreement was found for the spatial response of the system between measured data and results derived from MC-SRM and AE-SRM. Only minor differences for point sources at distances smaller than the radius of rotation and large incidence angles were found. Assessment of the effect on the reconstructed image showed a similar contrast for both approaches, with values higher than 0.9 for rod diameters greater than 1 mm and higher than 0.8 for rod diameter of 1 mm. The comparison in terms of image quality showed that all rods in the different sections of a custom-made Derenzo phantom could be distinguished. The spatial resolution (FWHM) was 0.7 mm at iteration 100 using both approaches. The SNR was lower for reconstructed images using MC-SRM than for those reconstructed using AE-SRM, indicating that AE-SRM deals better with the projection noise than MC-SRM. Conclusions: The authors' findings show that both approaches provide good solutions to the problem of calculating the SRM in pinhole SPECT reconstruction. The AE-SRM was faster to create and handle the projection noise better than MC-SRM. Nevertheless, the AE-SRM required a tedious experimental characterization of the intrinsic detector response. Creation of the MC-SRM required longer computation time and handled the projection noise worse than the AE-SRM. Nevertheless, the MC-SRM inherently incorporates extensive modeling of the system and therefore experimental characterization was not required.« less

Microcystin distribution in physical size class separations of natural plankton communities

USGS Publications Warehouse

Graham, J.L.; Jones, J.R.

2007-01-01

Phytoplankton communities in 30 northern Missouri and Iowa lakes were physically separated into 5 size classes (>100 ??m, 53-100 ??m, 35-53 ??m, 10-35 ??m, 1-10 ??m) during 15-21 August 2004 to determine the distribution of microcystin (MC) in size fractionated lake samples and assess how net collections influence estimates of MC concentration. MC was detected in whole water (total) from 83% of takes sampled, and total MC values ranged from 0.1-7.0 ??g/L (mean = 0.8 ??g/L). On average, MC in the > 100 ??m size class comprised ???40% of total MC, while other individual size classes contributed 9-20% to total MC. MC values decreased with size class and were significantly greater in the >100 ??m size class (mean = 0.5 ??g /L) than the 35-53 ??m (mean = 0.1 ??g/L), 10-35 ??m (mean = 0.0 ??g/L), and 1-10 ??m (mean = 0.0 ??g/L) size classes (p < 0.01). MC values in nets with 100-??m, 53-??m, 35-??m, and 10-??m mesh were cumulatively summed to simulate the potential bias of measuring MC with various size plankton nets. On average, a 100-??m net underestimated total MC by 51%, compared to 37% for a 53-??m net, 28% for a 35-??m net, and 17% for a 10-??m net. While plankton nets consistently underestimated total MC, concentration of algae with net sieves allowed detection of MC at low levels (???0.01 ??/L); 93% of lakes had detectable levels of MC in concentrated samples. Thus, small mesh plankton nets are an option for documenting MC occurrence, but whole water samples should be collected to characterize total MC concentrations. ?? Copyright by the North American Lake Management Society 2007.

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

SCALE 6.2 Continuous-Energy TSUNAMI-3D Capabilities

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

Perfetti, Christopher M; Rearden, Bradley T

2015-01-01

The TSUNAMI (Tools for Sensitivity and UNcertainty Analysis Methodology Implementation) capabilities within the SCALE code system make use of sensitivity coefficients for an extensive number of criticality safety applications, such as quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different systems, quantifying computational biases, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved ease of use and fidelity and the desire to extend TSUNAMI analysis to advanced applications have motivated the development of a SCALE 6.2 module for calculating sensitivity coefficients using three-dimensional (3D) continuous-energy (CE) Montemore » Carlo methods: CE TSUNAMI-3D. This paper provides an overview of the theory, implementation, and capabilities of the CE TSUNAMI-3D sensitivity analysis methods. CE TSUNAMI contains two methods for calculating sensitivity coefficients in eigenvalue sensitivity applications: (1) the Iterated Fission Probability (IFP) method and (2) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method. This work also presents the GEneralized Adjoint Response in Monte Carlo method (GEAR-MC), a first-of-its-kind approach for calculating adjoint-weighted, generalized response sensitivity coefficients—such as flux responses or reaction rate ratios—in CE Monte Carlo applications. The accuracy and efficiency of the CE TSUNAMI-3D eigenvalue sensitivity methods are assessed from a user perspective in a companion publication, and the accuracy and features of the CE TSUNAMI-3D GEAR-MC methods are detailed in this paper.« less

An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations

DOE PAGES

Lu, Dan; Zhang, Guannan; Webster, Clayton G.; ...

2016-12-30

In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore » in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less

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

PubMed

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

2015-01-01

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

SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement

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

Chamberlain, S; Roswell Park Cancer Institute, Buffalo, NY; French, S

Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3more » × 10{sup 6} to 3 × 10{sup 7}); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10{sup 6} was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10{sup 6} have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.« less

Bayesian Atmospheric Radiative Transfer (BART): Model, Statistics Driver, and Application to HD 209458b

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Blecic, Jasmina; Stemm, Madison M.; Lust, Nate B.; Foster, Andrew S.; Rojo, Patricio M.; Loredo, Thomas J.

2014-11-01

Multi-wavelength secondary-eclipse and transit depths probe the thermo-chemical properties of exoplanets. In recent years, several research groups have developed retrieval codes to analyze the existing data and study the prospects of future facilities. However, the scientific community has limited access to these packages. Here we premiere the open-source Bayesian Atmospheric Radiative Transfer (BART) code. We discuss the key aspects of the radiative-transfer algorithm and the statistical package. The radiation code includes line databases for all HITRAN molecules, high-temperature H2O, TiO, and VO, and includes a preprocessor for adding additional line databases without recompiling the radiation code. Collision-induced absorption lines are available for H2-H2 and H2-He. The parameterized thermal and molecular abundance profiles can be modified arbitrarily without recompilation. The generated spectra are integrated over arbitrary bandpasses for comparison to data. BART's statistical package, Multi-core Markov-chain Monte Carlo (MC3), is a general-purpose MCMC module. MC3 implements the Differental-evolution Markov-chain Monte Carlo algorithm (ter Braak 2006, 2009). MC3 converges 20-400 times faster than the usual Metropolis-Hastings MCMC algorithm, and in addition uses the Message Passing Interface (MPI) to parallelize the MCMC chains. We apply the BART retrieval code to the HD 209458b data set to estimate the planet's temperature profile and molecular abundances. This work was supported by NASA Planetary Atmospheres grant NNX12AI69G and NASA Astrophysics Data Analysis Program grant NNX13AF38G. JB holds a NASA Earth and Space Science Fellowship.

The effect of tandem-ovoid titanium applicator on points A, B, bladder, and rectum doses in gynecological brachytherapy using 192Ir.

PubMed

Sadeghi, Mohammad Hosein; Sina, Sedigheh; Mehdizadeh, Amir; Faghihi, Reza; Moharramzadeh, Vahed; Meigooni, Ali Soleimani

2018-02-01

The dosimetry procedure by simple superposition accounts only for the self-shielding of the source and does not take into account the attenuation of photons by the applicators. The purpose of this investigation is an estimation of the effects of the tandem and ovoid applicator on dose distribution inside the phantom by MCNP5 Monte Carlo simulations. In this study, the superposition method is used for obtaining the dose distribution in the phantom without using the applicator for a typical gynecological brachytherapy (superposition-1). Then, the sources are simulated inside the tandem and ovoid applicator to identify the effect of applicator attenuation (superposition-2), and the dose at points A, B, bladder, and rectum were compared with the results of superposition. The exact dwell positions, times of the source, and positions of the dosimetry points were determined in images of a patient and treatment data of an adult woman patient from a cancer center. The MCNP5 Monte Carlo (MC) code was used for simulation of the phantoms, applicators, and the sources. The results of this study showed no significant differences between the results of superposition method and the MC simulations for different dosimetry points. The difference in all important dosimetry points was found to be less than 5%. According to the results, applicator attenuation has no significant effect on the calculated points dose, the superposition method, adding the dose of each source obtained by the MC simulation, can estimate the dose to points A, B, bladder, and rectum with good accuracy.

SHIELD-HIT12A - a Monte Carlo particle transport program for ion therapy research

NASA Astrophysics Data System (ADS)

Bassler, N.; Hansen, D. C.; Lühr, A.; Thomsen, B.; Petersen, J. B.; Sobolevsky, N.

2014-03-01

Purpose: The Monte Carlo (MC) code SHIELD-HIT simulates the transport of ions through matter. Since SHIELD-HIT08 we added numerous features that improves speed, usability and underlying physics and thereby the user experience. The "-A" fork of SHIELD-HIT also aims to attach SHIELD-HIT to a heavy ion dose optimization algorithm to provide MC-optimized treatment plans that include radiobiology. Methods: SHIELD-HIT12A is written in FORTRAN and carefully retains platform independence. A powerful scoring engine is implemented scoring relevant quantities such as dose and track-average LET. It supports native formats compatible with the heavy ion treatment planning system TRiP. Stopping power files follow ICRU standard and are generated using the libdEdx library, which allows the user to choose from a multitude of stopping power tables. Results: SHIELD-HIT12A runs on Linux and Windows platforms. We experienced that new users quickly learn to use SHIELD-HIT12A and setup new geometries. Contrary to previous versions of SHIELD-HIT, the 12A distribution comes along with easy-to-use example files and an English manual. A new implementation of Vavilov straggling resulted in a massive reduction of computation time. Scheduled for later release are CT import and photon-electron transport. Conclusions: SHIELD-HIT12A is an interesting alternative ion transport engine. Apart from being a flexible particle therapy research tool, it can also serve as a back end for a MC ion treatment planning system. More information about SHIELD-HIT12A and a demo version can be found on http://www.shieldhit.org.

In vitro Dosimetric Study of Biliary Stent Loaded with Radioactive 125I Seeds

PubMed Central

Yao, Li-Hong; Wang, Jun-Jie; Shang, Charles; Jiang, Ping; Lin, Lei; Sun, Hai-Tao; Liu, Lu; Liu, Hao; He, Di; Yang, Rui-Jie

2017-01-01

Background: A novel radioactive 125I seed-loaded biliary stent has been used for patients with malignant biliary obstruction. However, the dosimetric characteristics of the stents remain unclear. Therefore, we aimed to describe the dosimetry of the stents of different lengths — with different number as well as activities of 125I seeds. Methods: The radiation dosimetry of three representative radioactive stent models was evaluated using a treatment planning system (TPS), thermoluminescent dosimeter (TLD) measurements, and Monte Carlo (MC) simulations. In the process of TPS calculation and TLD measurement, two different water-equivalent phantoms were designed to obtain cumulative radial dose distribution. Calibration procedures using TLD in the designed phantom were also conducted. MC simulations were performed using the Monte Carlo N-Particle eXtended version 2.5 general purpose code to calculate the radioactive stent's three-dimensional dose rate distribution in liquid water. Analysis of covariance was used to examine the factors influencing radial dose distribution of the radioactive stent. Results: The maximum reduction in cumulative radial dose was 26% when the seed activity changed from 0.5 mCi to 0.4 mCi for the same length of radioactive stents. The TLD's dose response in the range of 0–10 mGy irradiation by 137Cs γ-ray was linear: y = 182225x − 6651.9 (R2= 0.99152; y is the irradiation dose in mGy, x is the TLDs’ reading in nC). When TLDs were irradiated by different energy radiation sources to a dose of 1 mGy, reading of TLDs was different. Doses at a distance of 0.1 cm from the three stents’ surface simulated by MC were 79, 93, and 97 Gy. Conclusions: TPS calculation, TLD measurement, and MC simulation were performed and were found to be in good agreement. Although the whole experiment was conducted in water-equivalent phantom, data in our evaluation may provide a theoretical basis for dosimetry for the clinical application. PMID:28469106

Rotating and translating anthropomorphic head voxel models to establish an horizontal Frankfort plane for dental CBCT Monte Carlo simulations: a dose comparison study

NASA Astrophysics Data System (ADS)

Stratis, A.; Zhang, G.; Jacobs, R.; Bogaerts, R.; Bosmans, H.

2016-12-01

In order to carry out Monte Carlo (MC) dosimetry studies, voxel phantoms, modeling human anatomy, and organ-based segmentation of CT image data sets are applied to simulation frameworks. The resulting voxel phantoms preserve patient CT acquisition geometry; in the case of head voxel models built upon head CT images, the head support with which CT scanners are equipped introduces an inclination to the head, and hence to the head voxel model. In dental cone beam CT (CBCT) imaging, patients are always positioned in such a way that the Frankfort line is horizontal, implying that there is no head inclination. The orientation of the head is important, as it influences the distance of critical radiosensitive organs like the thyroid and the esophagus from the x-ray tube. This work aims to propose a procedure to adjust head voxel phantom orientation, and to investigate the impact of head inclination on organ doses in dental CBCT MC dosimetry studies. The female adult ICRP, and three in-house-built paediatric voxel phantoms were in this study. An EGSnrc MC framework was employed to simulate two commonly used protocols; a Morita Accuitomo 170 dental CBCT scanner (FOVs: 60  ×  60 mm2 and 80  ×  80 mm2, standard resolution), and a 3D Teeth protocol (FOV: 100  ×  90 mm2) in a Planmeca Promax 3D MAX scanner. Result analysis revealed large absorbed organ dose differences in radiosensitive organs between the original and the geometrically corrected voxel models of this study, ranging from  -45.6% to 39.3%. Therefore, accurate dental CBCT MC dose calculations require geometrical adjustments to be applied to head voxel models.

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

PubMed

Chi, Yujie; Tian, Zhen; Jia, Xun

2016-08-07

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

SU-E-T-795: Validations of Dose Calculation Accuracy of Acuros BV in High-Dose-Rate (HDR) Brachytherapy with a Shielded Cylinder Applicator Using Monte Carlo Simulation

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

Li, Y; Department of Engineering Physics, Tsinghua University, Beijing; Tian, Z

Purpose: Acuros BV has become available to perform accurate dose calculations in high-dose-rate (HDR) brachytherapy with phantom heterogeneity considered by solving the Boltzmann transport equation. In this work, we performed validation studies regarding the dose calculation accuracy of Acuros BV in cases with a shielded cylinder applicator using Monte Carlo (MC) simulations. Methods: Fifteen cases were considered in our studies, covering five different diameters of the applicator and three different shielding degrees. For each case, a digital phantom was created in Varian BrachyVision with the cylinder applicator inserted in the middle of a large water phantom. A treatment plan withmore » eight dwell positions was generated for these fifteen cases. Dose calculations were performed with Acuros BV. We then generated a voxelized phantom of the same geometry, and the materials were modeled according to the vendor’s specifications. MC dose calculations were then performed using our in-house developed fast MC dose engine for HDR brachytherapy (gBMC) on a GPU platform, which is able to simulate both photon transport and electron transport in a voxelized geometry. A phase-space file for the Ir-192 HDR source was used as a source model for MC simulations. Results: Satisfactory agreements between the dose distributions calculated by Acuros BV and those calculated by gBMC were observed in all cases. Quantitatively, we computed point-wise dose difference within the region that receives a dose higher than 10% of the reference dose, defined to be the dose at 5mm outward away from the applicator surface. The mean dose difference was ∼0.45%–0.51% and the 95-percentile maximum difference was ∼1.24%–1.47%. Conclusion: Acuros BV is able to accurately perform dose calculations in HDR brachytherapy with a shielded cylinder applicator.« less

Effect of Gold Nanoparticles on Prostate Dose Distribution under Ir-192 Internal and 18 MV External Radiotherapy Procedures Using Gel Dosimetry and Monte Carlo Method.

PubMed

Khosravi, H; Hashemi, B; Mahdavi, S R; Hejazi, P

2015-03-01

Gel polymers are considered as new dosimeters for determining radiotherapy dose distribution in three dimensions. The ability of a new formulation of MAGIC-f polymer gel was assessed by experimental measurement and Monte Carlo (MC) method for studying the effect of gold nanoparticles (GNPs) in prostate dose distributions under the internal Ir-192 and external 18MV radiotherapy practices. A Plexiglas phantom was made representing human pelvis. The GNP shaving 15 nm in diameter and 0.1 mM concentration were synthesized using chemical reduction method. Then, a new formulation of MAGIC-f gel was synthesized. The fabricated gel was poured in the tubes located at the prostate (with and without the GNPs) and bladder locations of the phantom. The phantom was irradiated to an Ir-192 source and 18 MV beam of a Varian linac separately based on common radiotherapy procedures used for prostate cancer. After 24 hours, the irradiated gels were read using a Siemens 1.5 Tesla MRI scanner. The absolute doses at the reference points and isodose curves resulted from the experimental measurement of the gels and MC simulations following the internal and external radiotherapy practices were compared. The mean absorbed doses measured with the gel in the presence of the GNPs in prostate were 15% and 8 % higher than the corresponding values without the GNPs under the internal and external radiation therapies, respectively. MC simulations also indicated a dose increase of 14 % and 7 % due to presence of the GNPs, for the same experimental internal and external radiotherapy practices, respectively. There was a good agreement between the dose enhancement factors (DEFs) estimated with MC simulations and experiment gel measurements due to the GNPs. The results indicated that the polymer gel dosimetry method as developed and used in this study, can be recommended as a reliable method for investigating the DEF of GNPs in internal and external radiotherapy practices.

SU-D-BRC-01: An Automatic Beam Model Commissioning Method for Monte Carlo Simulations in Pencil-Beam Scanning Proton Therapy

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

Qin, N; Shen, C; Tian, Z

Purpose: Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam-model commissioning method for pencil-beam scanning proton therapy via an optimization approach. Methods: We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy,more » and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero-size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies. Results: We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%. Conclusion: The developed automatic MC beam-model commissioning method for pencil-beam scanning proton therapy can determine beam model parameters with satisfactory accuracy.« less

Predicting Military Recruiter Effectiveness: A Literature Review

DTIC Science & Technology

1987-04-01

employing commanding officer nominations and/or supervisor ratings as criteria for success in recruiting. Wollack and KiDnis (1960). Commanding officer...ratings can be used to predict field recruiter performance. The authors attribute the failure to predict field recruiter performance to the...Time to Complete -12 -27 -5 -09 5. MC 431 Completion/ Failure 08 Studies 1. Cross-validities obtained via rMonte Carlo procedure by Borman, Toquam

The Model-Size Effect on Traditional and Modified Tests of Covariance Structures

ERIC Educational Resources Information Center

Herzog, Walter; Boomsma, Anne; Reinecke, Sven

2007-01-01

According to Kenny and McCoach (2003), chi-square tests of structural equation models produce inflated Type I error rates when the degrees of freedom increase. So far, the amount of this bias in large models has not been quantified. In a Monte Carlo study of confirmatory factor models with a range of 48 to 960 degrees of freedom it was found that…