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

NASA Astrophysics Data System (ADS)

Orkoulas, Gerassimos; Panagiotopoulos, Athanassios Z.

1994-07-01

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

SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations

NASA Astrophysics Data System (ADS)

Baes, M.; Camps, P.

2015-09-01

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.

Fission yield calculation using toy model based on Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Jubaidah, Kurniadi, Rizal

2015-09-01

Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (Rc), mean of left curve (μL) and mean of right curve (μR), deviation of left curve (σL) and deviation of right curve (σR). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90

Fission yield calculation using toy model based on Monte Carlo simulation

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

Jubaidah, E-mail: jubaidah@student.itb.ac.id; Physics Department, Faculty of Mathematics and Natural Science – State University of Medan. Jl. Willem Iskandar Pasar V Medan Estate – North Sumatera, Indonesia 20221; Kurniadi, Rizal, E-mail: rijalk@fi.itb.ac.id

2015-09-30

Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. Theremore » are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90« less

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.

Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques.

PubMed

Kilinc, Deniz; Demir, Alper

2017-08-01

The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

Understanding quantum tunneling using diffusion Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Inack, E. M.; Giudici, G.; Parolini, T.; Santoro, G.; Pilati, S.

2018-03-01

In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1 /Δ2 , where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1 /Δ , i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.

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

PubMed

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

2015-02-01

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

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

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

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

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

Monte Carlo Simulations for VLBI2010

NASA Astrophysics Data System (ADS)

Wresnik, J.; Böhm, J.; Schuh, H.

2007-07-01

Monte Carlo simulations are carried out at the Institute of Geodesy and Geophysics (IGG), Vienna, and at Goddard Space Flight Center (GSFC), Greenbelt (USA), with the goal to design a new geodetic Very Long Baseline Interferometry (VLBI) system. Influences of the schedule, the network geometry and the main stochastic processes on the geodetic results are investigated. Therefore schedules are prepared with the software package SKED (Vandenberg 1999), and different strategies are applied to produce temporally very dense schedules which are compared in terms of baseline length repeatabilities. For the simulation of VLBI observations a Monte Carlo Simulator was set up which creates artificial observations by randomly simulating wet zenith delay and clock values as well as additive white noise representing the antenna errors. For the simulation at IGG the VLBI analysis software OCCAM (Titov et al. 2004) was adapted. Random walk processes with power spectrum densities of 0.7 and 0.1 psec2/sec are used for the simulation of wet zenith delays. The clocks are simulated with Allan Standard Deviations of 1*10^-14 @ 50 min and 2*10^-15 @ 15 min and three levels of white noise, 4 psec, 8 psec and, 16 psec, are added to the artificial observations. The variations of the power spectrum densities of the clocks and wet zenith delays, and the application of different white noise levels show clearly that the wet delay is the critical factor for the improvement of the geodetic VLBI system. At GSFC the software CalcSolve is used for the VLBI analysis, therefore a comparison between the software packages OCCAM and CalcSolve was done with simulated data. For further simulations the wet zenith delay was modeled by a turbulence model. This data was provided by Nilsson T. and was added to the simulation work. Different schedules have been run.

Monte Carlo simulations in X-ray imaging

NASA Astrophysics Data System (ADS)

Giersch, Jürgen; Durst, Jürgen

2008-06-01

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

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

NASA Astrophysics Data System (ADS)

Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.

2016-02-01

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn's Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

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

Pfeiffer, M., E-mail: mpfeiffer@irs.uni-stuttgart.de; Nizenkov, P., E-mail: nizenkov@irs.uni-stuttgart.de; Mirza, A., E-mail: mirza@irs.uni-stuttgart.de

2016-02-15

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methodsmore » are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.« less

Monte-Carlo simulations of a coarse-grained model for α-oligothiophenes

NASA Astrophysics Data System (ADS)

Almutairi, Amani; Luettmer-Strathmann, Jutta

The interfacial layer of an organic semiconductor in contact with a metal electrode has important effects on the performance of thin-film devices. However, the structure of this layer is not easy to model. Oligothiophenes are small, π-conjugated molecules with applications in organic electronics that also serve as small-molecule models for polythiophenes. α-hexithiophene (6T) is a six-ring molecule, whose adsorption on noble metal surfaces has been studied extensively (see, e.g., Ref.). In this work, we develop a coarse-grained model for α-oligothiophenes. We describe the molecules as linear chains of bonded, discotic particles with Gay-Berne potential interactions between non-bonded ellipsoids. We perform Monte Carlo simulations to study the structure of isolated and adsorbed molecules

State-to-state models of vibrational relaxation in Direct Simulation Monte Carlo (DSMC)

NASA Astrophysics Data System (ADS)

Oblapenko, G. P.; Kashkovsky, A. V.; Bondar, Ye A.

2017-02-01

In the present work, the application of state-to-state models of vibrational energy exchanges to the Direct Simulation Monte Carlo (DSMC) is considered. A state-to-state model for VT transitions of vibrational energy in nitrogen and oxygen, based on the application of the inverse Laplace transform to results of quasiclassical trajectory calculations (QCT) of vibrational energy transitions, along with the Forced Harmonic Oscillator (FHO) state-to-state model is implemented in DSMC code and applied to flows around blunt bodies. Comparisons are made with the widely used Larsen-Borgnakke model and the in uence of multi-quantum VT transitions is assessed.

Monte Carlo simulations of lattice models for single polymer systems

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping

2014-10-01

Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N ˜ O(10^4). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and sqrt{10}, we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior.

Monte Carlo modelling of Schottky diode for rectenna simulation

NASA Astrophysics Data System (ADS)

Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.

2017-09-01

Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.

Gray: a ray tracing-based Monte Carlo simulator for PET.

PubMed

Freese, David L; Olcott, Peter D; Buss, Samuel R; Levin, Craig S

2018-05-21

Monte Carlo simulation software plays a critical role in PET system design. Performing complex, repeated Monte Carlo simulations can be computationally prohibitive, as even a single simulation can require a large amount of time and a computing cluster to complete. Here we introduce Gray, a Monte Carlo simulation software for PET systems. Gray exploits ray tracing methods used in the computer graphics community to greatly accelerate simulations of PET systems with complex geometries. We demonstrate the implementation of models for positron range, annihilation acolinearity, photoelectric absorption, Compton scatter, and Rayleigh scatter. For validation, we simulate the GATE PET benchmark, and compare energy, distribution of hits, coincidences, and run time. We show a [Formula: see text] speedup using Gray, compared to GATE for the same simulation, while demonstrating nearly identical results. We additionally simulate the Siemens Biograph mCT system with both the NEMA NU-2 scatter phantom and sensitivity phantom. We estimate the total sensitivity within [Formula: see text]% when accounting for differences in peak NECR. We also estimate the peak NECR to be [Formula: see text] kcps, or within [Formula: see text]% of published experimental data. The activity concentration of the peak is also estimated within 1.3%.

Gray: a ray tracing-based Monte Carlo simulator for PET

NASA Astrophysics Data System (ADS)

Freese, David L.; Olcott, Peter D.; Buss, Samuel R.; Levin, Craig S.

2018-05-01

Monte Carlo simulation software plays a critical role in PET system design. Performing complex, repeated Monte Carlo simulations can be computationally prohibitive, as even a single simulation can require a large amount of time and a computing cluster to complete. Here we introduce Gray, a Monte Carlo simulation software for PET systems. Gray exploits ray tracing methods used in the computer graphics community to greatly accelerate simulations of PET systems with complex geometries. We demonstrate the implementation of models for positron range, annihilation acolinearity, photoelectric absorption, Compton scatter, and Rayleigh scatter. For validation, we simulate the GATE PET benchmark, and compare energy, distribution of hits, coincidences, and run time. We show a speedup using Gray, compared to GATE for the same simulation, while demonstrating nearly identical results. We additionally simulate the Siemens Biograph mCT system with both the NEMA NU-2 scatter phantom and sensitivity phantom. We estimate the total sensitivity within % when accounting for differences in peak NECR. We also estimate the peak NECR to be kcps, or within % of published experimental data. The activity concentration of the peak is also estimated within 1.3%.

A Monte Carlo simulation based inverse propagation method for stochastic model updating

NASA Astrophysics Data System (ADS)

Bao, Nuo; Wang, Chunjie

2015-08-01

This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.

Direct Simulation Monte Carlo Simulations of Low Pressure Semiconductor Plasma Processing

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

Gochberg, L. A.; Ozawa, T.; Deng, H.

2008-12-31

The two widely used plasma deposition tools for semiconductor processing are Ionized Metal Physical Vapor Deposition (IMPVD) of metals using either planar or hollow cathode magnetrons (HCM), and inductively-coupled plasma (ICP) deposition of dielectrics in High Density Plasma Chemical Vapor Deposition (HDP-CVD) reactors. In these systems, the injected neutral gas flows are generally in the transonic to supersonic flow regime. The Hybrid Plasma Equipment Model (HPEM) has been developed and is strategically and beneficially applied to the design of these tools and their processes. For the most part, the model uses continuum-based techniques, and thus, as pressures decrease below 10more » mTorr, the continuum approaches in the model become questionable. Modifications have been previously made to the HPEM to significantly improve its accuracy in this pressure regime. In particular, the Ion Monte Carlo Simulation (IMCS) was added, wherein a Monte Carlo simulation is used to obtain ion and neutral velocity distributions in much the same way as in direct simulation Monte Carlo (DSMC). As a further refinement, this work presents the first steps towards the adaptation of full DSMC calculations to replace part of the flow module within the HPEM. Six species (Ar, Cu, Ar*, Cu*, Ar{sup +}, and Cu{sup +}) are modeled in DSMC. To couple SMILE as a module to the HPEM, source functions for species, momentum and energy from plasma sources will be provided by the HPEM. The DSMC module will then compute a quasi-converged flow field that will provide neutral and ion species densities, momenta and temperatures. In this work, the HPEM results for a hollow cathode magnetron (HCM) IMPVD process using the Boltzmann distribution are compared with DSMC results using portions of those HPEM computations as an initial condition.« less

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

Improved radial dose function estimation using current version MCNP Monte-Carlo simulation: Model 6711 and ISC3500 125I brachytherapy sources.

PubMed

Duggan, Dennis M

2004-12-01

Improved cross-sections in a new version of the Monte-Carlo N-particle (MCNP) code may eliminate discrepancies between radial dose functions (as defined by American Association of Physicists in Medicine Task Group 43) derived from Monte-Carlo simulations of low-energy photon-emitting brachytherapy sources and those from measurements on the same sources with thermoluminescent dosimeters. This is demonstrated for two 125I brachytherapy seed models, the Implant Sciences Model ISC3500 (I-Plant) and the Amersham Health Model 6711, by simulating their radial dose functions with two versions of MCNP, 4c2 and 5.

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

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Reed, Erik; Cavanagh, Peter

2011-01-01

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

A stochastic Markov chain approach for tennis: Monte Carlo simulation and modeling

NASA Astrophysics Data System (ADS)

Aslam, Kamran

This dissertation describes the computational formulation of probability density functions (pdfs) that facilitate head-to-head match simulations in tennis along with ranking systems developed from their use. A background on the statistical method used to develop the pdfs , the Monte Carlo method, and the resulting rankings are included along with a discussion on ranking methods currently being used both in professional sports and in other applications. Using an analytical theory developed by Newton and Keller in [34] that defines a tennis player's probability of winning a game, set, match and single elimination tournament, a computational simulation has been developed in Matlab that allows further modeling not previously possible with the analytical theory alone. Such experimentation consists of the exploration of non-iid effects, considers the concept the varying importance of points in a match and allows an unlimited number of matches to be simulated between unlikely opponents. The results of these studies have provided pdfs that accurately model an individual tennis player's ability along with a realistic, fair and mathematically sound platform for ranking them.

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

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

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

Modeling the self-assembly of functionalized fullerenes on solid surfaces using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Bubnis, Gregory J.

Since their discovery 25 years ago, carbon fullerenes have been widely studied for their unique physicochemical properties and for applications including organic electronics and photovoltaics. For these applications it is highly desirable for crystalline fullerene thin films to spontaneously self-assemble on surfaces. Accordingly, many studies have functionalized fullerenes with the aim of tailoring their intermolecular interactions and controlling interactions with the solid substrate. The success of these rational design approaches hinges on the subtle interplay of intermolecular forces and molecule-substrate interactions. Molecular modeling is well-suited to studying these interactions by directly simulating self-assembly. In this work, we consider three different fullerene functionalization approaches and for each approach we carry out Monte Carlo simulations of the self-assembly process. In all cases, we use a "coarse-grained" molecular representation that preserves the dominant physical interactions between molecules and maximizes computational efficiency. The first approach we consider is the traditional gold-thiolate SAM (self-assembled monolayer) strategy which tethers molecules to a gold substrate via covalent sulfur-gold bonds. For this we study an asymmetric fullerene thiolate bridged by a phenyl group. Clusters of 40 molecules are simulated on the Au(111) substrate at different temperatures and surface coverage densities. Fullerenes and S atoms are found to compete for Au(111) surface sites, and this competition prevents self-assembly of highly ordered monolayers. Next, we investigate self-assembled monolayers formed by fullerenes with hydrogen-bonding carboxylic acid substituents. We consider five molecules with different dimensions and symmetries. Monte Carlo cooling simulations are used to find the most stable solid structures of clusters adsorbed to Au(111). The results show cases where fullerene-Au(111) attraction, fullerene close-packing, and

Three-Dimensional Electron Microscopy Simulation with the CASINO Monte Carlo Software

PubMed Central

Demers, Hendrix; Poirier-Demers, Nicolas; Couture, Alexandre Réal; Joly, Dany; Guilmain, Marc; de Jonge, Niels; Drouin, Dominique

2011-01-01

Monte Carlo softwares are widely used to understand the capabilities of electron microscopes. To study more realistic applications with complex samples, 3D Monte Carlo softwares are needed. In this paper, the development of the 3D version of CASINO is presented. The software feature a graphical user interface, an efficient (in relation to simulation time and memory use) 3D simulation model, accurate physic models for electron microscopy applications, and it is available freely to the scientific community at this website: www.gel.usherbrooke.ca/casino/index.html. It can be used to model backscattered, secondary, and transmitted electron signals as well as absorbed energy. The software features like scan points and shot noise allow the simulation and study of realistic experimental conditions. This software has an improved energy range for scanning electron microscopy and scanning transmission electron microscopy applications. PMID:21769885

Monte Carlo Simulation Using HyperCard and Lotus 1-2-3.

ERIC Educational Resources Information Center

Oulman, Charles S.; Lee, Motoko Y.

Monte Carlo simulation is a computer modeling procedure for mimicking observations on a random variable. A random number generator is used in generating the outcome for the events that are being modeled. The simulation can be used to obtain results that otherwise require extensive testing or complicated computations. This paper describes how Monte…

Macroion solutions in the cell model studied by field theory and Monte Carlo simulations.

PubMed

Lue, Leo; Linse, Per

2011-12-14

Aqueous solutions of charged spherical macroions with variable dielectric permittivity and their associated counterions are examined within the cell model using a field theory and Monte Carlo simulations. The field theory is based on separation of fields into short- and long-wavelength terms, which are subjected to different statistical-mechanical treatments. The simulations were performed by using a new, accurate, and fast algorithm for numerical evaluation of the electrostatic polarization interaction. The field theory provides counterion distributions outside a macroion in good agreement with the simulation results over the full range from weak to strong electrostatic coupling. A low-dielectric macroion leads to a displacement of the counterions away from the macroion. © 2011 American Institute of Physics

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

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

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

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.

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

NASA Technical Reports Server (NTRS)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Monte Carlo simulation: Its status and future

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

Murtha, J.A.

1997-04-01

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

Monte Carlo computer simulations of Venus equilibrium and global resurfacing models

NASA Technical Reports Server (NTRS)

Dawson, D. D.; Strom, R. G.; Schaber, G. G.

1992-01-01

Two models have been proposed for the resurfacing history of Venus: (1) equilibrium resurfacing and (2) global resurfacing. The equilibrium model consists of two cases: in case 1, areas less than or equal to 0.03 percent of the planet are spatially randomly resurfaced at intervals of less than or greater than 150,000 yr to produce the observed spatially random distribution of impact craters and average surface age of about 500 m.y.; and in case 2, areas greater than or equal to 10 percent of the planet are resurfaced at intervals of greater than or equal to 50 m.y. The global resurfacing model proposes that the entire planet was resurfaced about 500 m.y. ago, destroying the preexisting crater population and followed by significantly reduced volcanism and tectonism. The present crater population has accumulated since then with only 4 percent of the observed craters having been embayed by more recent lavas. To test the equilibrium resurfacing model we have run several Monte Carlo computer simulations for the two proposed cases. It is shown that the equilibrium resurfacing model is not a valid model for an explanation of the observed crater population characteristics or Venus' resurfacing history. The global resurfacing model is the most likely explanation for the characteristics of Venus' cratering record. The amount of resurfacing since that event, some 500 m.y. ago, can be estimated by a different type of Monte Carolo simulation. To date, our initial simulation has only considered the easiest case to implement. In this case, the volcanic events are randomly distributed across the entire planet and, therefore, contrary to observation, the flooded craters are also randomly distributed across the planet.

Three-dimensional electron microscopy simulation with the CASINO Monte Carlo software.

PubMed

Demers, Hendrix; Poirier-Demers, Nicolas; Couture, Alexandre Réal; Joly, Dany; Guilmain, Marc; de Jonge, Niels; Drouin, Dominique

2011-01-01

Monte Carlo softwares are widely used to understand the capabilities of electron microscopes. To study more realistic applications with complex samples, 3D Monte Carlo softwares are needed. In this article, the development of the 3D version of CASINO is presented. The software feature a graphical user interface, an efficient (in relation to simulation time and memory use) 3D simulation model, accurate physic models for electron microscopy applications, and it is available freely to the scientific community at this website: www.gel.usherbrooke.ca/casino/index.html. It can be used to model backscattered, secondary, and transmitted electron signals as well as absorbed energy. The software features like scan points and shot noise allow the simulation and study of realistic experimental conditions. This software has an improved energy range for scanning electron microscopy and scanning transmission electron microscopy applications. Copyright © 2011 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Efficient Simulation of Secondary Fluorescence Via NIST DTSA-II Monte Carlo.

PubMed

Ritchie, Nicholas W M

2017-06-01

Secondary fluorescence, the final term in the familiar matrix correction triumvirate Z·A·F, is the most challenging for Monte Carlo models to simulate. In fact, only two implementations of Monte Carlo models commonly used to simulate electron probe X-ray spectra can calculate secondary fluorescence-PENEPMA and NIST DTSA-II a (DTSA-II is discussed herein). These two models share many physical models but there are some important differences in the way each implements X-ray emission including secondary fluorescence. PENEPMA is based on PENELOPE, a general purpose software package for simulation of both relativistic and subrelativistic electron/positron interactions with matter. On the other hand, NIST DTSA-II was designed exclusively for simulation of X-ray spectra generated by subrelativistic electrons. NIST DTSA-II uses variance reduction techniques unsuited to general purpose code. These optimizations help NIST DTSA-II to be orders of magnitude more computationally efficient while retaining detector position sensitivity. Simulations execute in minutes rather than hours and can model differences that result from detector position. Both PENEPMA and NIST DTSA-II are capable of handling complex sample geometries and we will demonstrate that both are of similar accuracy when modeling experimental secondary fluorescence data from the literature.

Experimental validation of a direct simulation by Monte Carlo molecular gas flow model

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

Shufflebotham, P.K.; Bartel, T.J.; Berney, B.

1995-07-01

The Sandia direct simulation Monte Carlo (DSMC) molecular/transition gas flow simulation code has significant potential as a computer-aided design tool for the design of vacuum systems in low pressure plasma processing equipment. The purpose of this work was to verify the accuracy of this code through direct comparison to experiment. To test the DSMC model, a fully instrumented, axisymmetric vacuum test cell was constructed, and spatially resolved pressure measurements made in N{sub 2} at flows from 50 to 500 sccm. In a ``blind`` test, the DSMC code was used to model the experimental conditions directly, and the results compared tomore » the measurements. It was found that the model predicted all the experimental findings to a high degree of accuracy. Only one modeling issue was uncovered. The axisymmetric model showed localized low pressure spots along the axis next to surfaces. Although this artifact did not significantly alter the accuracy of the results, it did add noise to the axial data. {copyright} {ital 1995} {ital American} {ital Vacuum} {ital Society}« less

DNA strand breaks induced by electrons simulated with Nanodosimetry Monte Carlo Simulation Code: NASIC.

PubMed

Li, Junli; Li, Chunyan; Qiu, Rui; Yan, Congchong; Xie, Wenzhang; Wu, Zhen; Zeng, Zhi; Tung, Chuanjong

2015-09-01

The method of Monte Carlo simulation is a powerful tool to investigate the details of radiation biological damage at the molecular level. In this paper, a Monte Carlo code called NASIC (Nanodosimetry Monte Carlo Simulation Code) was developed. It includes physical module, pre-chemical module, chemical module, geometric module and DNA damage module. The physical module can simulate physical tracks of low-energy electrons in the liquid water event-by-event. More than one set of inelastic cross sections were calculated by applying the dielectric function method of Emfietzoglou's optical-data treatments, with different optical data sets and dispersion models. In the pre-chemical module, the ionised and excited water molecules undergo dissociation processes. In the chemical module, the produced radiolytic chemical species diffuse and react. In the geometric module, an atomic model of 46 chromatin fibres in a spherical nucleus of human lymphocyte was established. In the DNA damage module, the direct damages induced by the energy depositions of the electrons and the indirect damages induced by the radiolytic chemical species were calculated. The parameters should be adjusted to make the simulation results be agreed with the experimental results. In this paper, the influence study of the inelastic cross sections and vibrational excitation reaction on the parameters and the DNA strand break yields were studied. Further work of NASIC is underway. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling.

PubMed

Schaefer, C; Jansen, A P J

2013-02-07

We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

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.

Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model

NASA Astrophysics Data System (ADS)

Morin, Mario A.; Ficarazzo, Francesco

2006-04-01

Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.

High-Precision Monte Carlo Simulation of the Ising Models on the Penrose Lattice and the Dual Penrose Lattice

NASA Astrophysics Data System (ADS)

Komura, Yukihiro; Okabe, Yutaka

2016-04-01

We study the Ising models on the Penrose lattice and the dual Penrose lattice by means of the high-precision Monte Carlo simulation. Simulating systems up to the total system size N = 20633239, we estimate the critical temperatures on those lattices with high accuracy. For high-speed calculation, we use the generalized method of the single-GPU-based computation for the Swendsen-Wang multi-cluster algorithm of Monte Carlo simulation. As a result, we estimate the critical temperature on the Penrose lattice as Tc/J = 2.39781 ± 0.00005 and that of the dual Penrose lattice as Tc*/J = 2.14987 ± 0.00005. Moreover, we definitely confirm the duality relation between the critical temperatures on the dual pair of quasilattices with a high degree of accuracy, sinh (2J/Tc)sinh (2J/Tc*) = 1.00000 ± 0.00004.

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

NASA Astrophysics Data System (ADS)

Guan, Fada

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

Modelling of electronic excitation and radiation in the Direct Simulation Monte Carlo Macroscopic Chemistry Method

NASA Astrophysics Data System (ADS)

Goldsworthy, M. J.

2012-10-01

One of the most useful tools for modelling rarefied hypersonic flows is the Direct Simulation Monte Carlo (DSMC) method. Simulator particle movement and collision calculations are combined with statistical procedures to model thermal non-equilibrium flow-fields described by the Boltzmann equation. The Macroscopic Chemistry Method for DSMC simulations was developed to simplify the inclusion of complex thermal non-equilibrium chemistry. The macroscopic approach uses statistical information which is calculated during the DSMC solution process in the modelling procedures. Here it is shown how inclusion of macroscopic information in models of chemical kinetics, electronic excitation, ionization, and radiation can enhance the capabilities of DSMC to model flow-fields where a range of physical processes occur. The approach is applied to the modelling of a 6.4 km/s nitrogen shock wave and results are compared with those from existing shock-tube experiments and continuum calculations. Reasonable agreement between the methods is obtained. The quality of the comparison is highly dependent on the set of vibrational relaxation and chemical kinetic parameters employed.

Numerical integration of detector response functions via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Numerical integration of detector response functions via Monte Carlo simulations

DOE PAGES

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

2017-06-13

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

Numerical integration of detector response functions via Monte Carlo simulations

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

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

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

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Voxel2MCNP: a framework for modeling, simulation and evaluation of radiation transport scenarios for Monte Carlo codes.

PubMed

Pölz, Stefan; Laubersheimer, Sven; Eberhardt, Jakob S; Harrendorf, Marco A; Keck, Thomas; Benzler, Andreas; Breustedt, Bastian

2013-08-21

The basic idea of Voxel2MCNP is to provide a framework supporting users in modeling radiation transport scenarios using voxel phantoms and other geometric models, generating corresponding input for the Monte Carlo code MCNPX, and evaluating simulation output. Applications at Karlsruhe Institute of Technology are primarily whole and partial body counter calibration and calculation of dose conversion coefficients. A new generic data model describing data related to radiation transport, including phantom and detector geometries and their properties, sources, tallies and materials, has been developed. It is modular and generally independent of the targeted Monte Carlo code. The data model has been implemented as an XML-based file format to facilitate data exchange, and integrated with Voxel2MCNP to provide a common interface for modeling, visualization, and evaluation of data. Also, extensions to allow compatibility with several file formats, such as ENSDF for nuclear structure properties and radioactive decay data, SimpleGeo for solid geometry modeling, ImageJ for voxel lattices, and MCNPX's MCTAL for simulation results have been added. The framework is presented and discussed in this paper and example workflows for body counter calibration and calculation of dose conversion coefficients is given to illustrate its application.

Monte Carlo simulation of ferroelectric domain growth

NASA Astrophysics Data System (ADS)

Li, B. L.; Liu, X. P.; Fang, F.; Zhu, J. L.; Liu, J.-M.

2006-01-01

The kinetics of two-dimensional isothermal domain growth in a quenched ferroelectric system is investigated using Monte Carlo simulation based on a realistic Ginzburg-Landau ferroelectric model with cubic-tetragonal (square-rectangle) phase transitions. The evolution of the domain pattern and domain size with annealing time is simulated, and the stability of trijunctions and tetrajunctions of domain walls is analyzed. It is found that in this much realistic model with strong dipole alignment anisotropy and long-range Coulomb interaction, the powerlaw for normal domain growth still stands applicable. Towards the late stage of domain growth, both the average domain area and reciprocal density of domain wall junctions increase linearly with time, and the one-parameter dynamic scaling of the domain growth is demonstrated.

Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network.

PubMed

Groth, Detlef

2017-04-01

Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later

Monte Carlo Simulation of Massive Absorbers for Cryogenic Calorimeters

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

Brandt, D.; Asai, M.; Brink, P.L.

There is a growing interest in cryogenic calorimeters with macroscopic absorbers for applications such as dark matter direct detection and rare event search experiments. The physics of energy transport in calorimeters with absorber masses exceeding several grams is made complex by the anisotropic nature of the absorber crystals as well as the changing mean free paths as phonons decay to progressively lower energies. We present a Monte Carlo model capable of simulating anisotropic phonon transport in cryogenic crystals. We have initiated the validation process and discuss the level of agreement between our simulation and experimental results reported in the literature,more » focusing on heat pulse propagation in germanium. The simulation framework is implemented using Geant4, a toolkit originally developed for high-energy physics Monte Carlo simulations. Geant4 has also been used for nuclear and accelerator physics, and applications in medical and space sciences. We believe that our current work may open up new avenues for applications in material science and condensed matter physics.« less

Structural Reliability and Monte Carlo Simulation.

ERIC Educational Resources Information Center

Laumakis, P. J.; Harlow, G.

2002-01-01

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

Methods for Monte Carlo simulations of biomacromolecules

PubMed Central

Vitalis, Andreas; Pappu, Rohit V.

2010-01-01

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

Fermi-level effects in semiconductor processing: A modeling scheme for atomistic kinetic Monte Carlo simulators

NASA Astrophysics Data System (ADS)

Martin-Bragado, I.; Castrillo, P.; Jaraiz, M.; Pinacho, R.; Rubio, J. E.; Barbolla, J.; Moroz, V.

2005-09-01

Atomistic process simulation is expected to play an important role for the development of next generations of integrated circuits. This work describes an approach for modeling electric charge effects in a three-dimensional atomistic kinetic Monte Carlo process simulator. The proposed model has been applied to the diffusion of electrically active boron and arsenic atoms in silicon. Several key aspects of the underlying physical mechanisms are discussed: (i) the use of the local Debye length to smooth out the atomistic point-charge distribution, (ii) algorithms to correctly update the charge state in a physically accurate and computationally efficient way, and (iii) an efficient implementation of the drift of charged particles in an electric field. High-concentration effects such as band-gap narrowing and degenerate statistics are also taken into account. The efficiency, accuracy, and relevance of the model are discussed.

Efficient Monte Carlo Methods for Biomolecular Simulations.

NASA Astrophysics Data System (ADS)

Bouzida, Djamal

A new approach to efficient Monte Carlo simulations of biological molecules is presented. By relaxing the usual restriction to Markov processes, we are able to optimize performance while dealing directly with the inhomogeneity and anisotropy inherent in these systems. The advantage of this approach is that we can introduce a wide variety of Monte Carlo moves to deal with complicated motions of the molecule, while maintaining full optimization at every step. This enables the use of a variety of collective rotational moves that relax long-wavelength modes. We were able to show by explicit simulations that the resulting algorithms substantially increase the speed of the simulation while reproducing the correct equilibrium behavior. This approach is particularly intended for simulations of macromolecules, although we expect it to be useful in other situations. The dynamic optimization of the new Monte Carlo methods makes them very suitable for simulated annealing experiments on all systems whose state space is continuous in general, and to the protein folding problem in particular. We introduce an efficient annealing schedule using preferential bias moves. Our simulated annealing experiments yield structures whose free energies were lower than the equilibrated X-ray structure, which leads us to believe that the empirical energy function used does not fully represent the interatomic interactions. Furthermore, we believe that the largest discrepancies involve the solvent effects in particular.

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

A Fast Monte Carlo Simulation for the International Linear Collider Detector

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

Furse, D.; /Georgia Tech

2005-12-15

The following paper contains details concerning the motivation for, implementation and performance of a Java-based fast Monte Carlo simulation for a detector designed to be used in the International Linear Collider. This simulation, presently included in the SLAC ILC group's org.lcsim package, reads in standard model or SUSY events in STDHEP file format, stochastically simulates the blurring in physics measurements caused by intrinsic detector error, and writes out an LCIO format file containing a set of final particles statistically similar to those that would have found by a full Monte Carlo simulation. In addition to the reconstructed particles themselves, descriptionsmore » of the calorimeter hit clusters and tracks that these particles would have produced are also included in the LCIO output. These output files can then be put through various analysis codes in order to characterize the effectiveness of a hypothetical detector at extracting relevant physical information about an event. Such a tool is extremely useful in preliminary detector research and development, as full simulations are extremely cumbersome and taxing on processor resources; a fast, efficient Monte Carlo can facilitate and even make possible detector physics studies that would be very impractical with the full simulation by sacrificing what is in many cases inappropriate attention to detail for valuable gains in time required for results.« less

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

NASA Technical Reports Server (NTRS)

Wang, B. S.

1972-01-01

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

Radiotherapy Monte Carlo simulation using cloud computing technology.

PubMed

Poole, C M; Cornelius, I; Trapp, J V; Langton, C M

2012-12-01

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

A novel Kinetic Monte Carlo algorithm for Non-Equilibrium Simulations

NASA Astrophysics Data System (ADS)

Jha, Prateek; Kuzovkov, Vladimir; Grzybowski, Bartosz; Olvera de La Cruz, Monica

2012-02-01

We have developed an off-lattice kinetic Monte Carlo simulation scheme for reaction-diffusion problems in soft matter systems. The definition of transition probabilities in the Monte Carlo scheme are taken identical to the transition rates in a renormalized master equation of the diffusion process and match that of the Glauber dynamics of Ising model. Our scheme provides several advantages over the Brownian dynamics technique for non-equilibrium simulations. Since particle displacements are accepted/rejected in a Monte Carlo fashion as opposed to moving particles following a stochastic equation of motion, nonphysical movements (e.g., violation of a hard core assumption) are not possible (these moves have zero acceptance). Further, the absence of a stochastic ``noise'' term resolves the computational difficulties associated with generating statistically independent trajectories with definitive mean properties. Finally, since the timestep is independent of the magnitude of the interaction forces, much longer time-steps can be employed than Brownian dynamics. We discuss the applications of this scheme for dynamic self-assembly of photo-switchable nanoparticles and dynamical problems in polymeric systems.

On recontamination and directional-bias problems in Monte Carlo simulation of PDF turbulence models. [probability density function

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1992-01-01

Turbulent combustion can not be simulated adequately by conventional moment closure turbulent models. The probability density function (PDF) method offers an attractive alternative: in a PDF model, the chemical source terms are closed and do not require additional models. Because the number of computational operations grows only linearly in the Monte Carlo scheme, it is chosen over finite differencing schemes. A grid dependent Monte Carlo scheme following J.Y. Chen and W. Kollmann has been studied in the present work. It was found that in order to conserve the mass fractions absolutely, one needs to add further restrictions to the scheme, namely alpha(sub j) + gamma(sub j) = alpha(sub j - 1) + gamma(sub j + 1). A new algorithm was devised that satisfied this restriction in the case of pure diffusion or uniform flow problems. Using examples, it is shown that absolute conservation can be achieved. Although for non-uniform flows absolute conservation seems impossible, the present scheme has reduced the error considerably.

Monte Carlo simulations of particle acceleration at oblique shocks

NASA Technical Reports Server (NTRS)

Baring, Matthew G.; Ellison, Donald C.; Jones, Frank C.

1994-01-01

The Fermi shock acceleration mechanism may be responsible for the production of high-energy cosmic rays in a wide variety of environments. Modeling of this phenomenon has largely focused on plane-parallel shocks, and one of the most promising techniques for its study is the Monte Carlo simulation of particle transport in shocked fluid flows. One of the principal problems in shock acceleration theory is the mechanism and efficiency of injection of particles from the thermal gas into the accelerated population. The Monte Carlo technique is ideally suited to addressing the injection problem directly, and previous applications of it to the quasi-parallel Earth bow shock led to very successful modeling of proton and heavy ion spectra, as well as other observed quantities. Recently this technique has been extended to oblique shock geometries, in which the upstream magnetic field makes a significant angle Theta(sub B1) to the shock normal. Spectral resutls from test particle Monte Carlo simulations of cosmic-ray acceleration at oblique, nonrelativistic shocks are presented. The results show that low Mach number shocks have injection efficiencies that are relatively insensitive to (though not independent of) the shock obliquity, but that there is a dramatic drop in efficiency for shocks of Mach number 30 or more as the obliquity increases above 15 deg. Cosmic-ray distributions just upstream of the shock reveal prominent bumps at energies below the thermal peak; these disappear far upstream but might be observable features close to astrophysical shocks.

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

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

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

2017-01-01

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

Tool for Rapid Analysis of Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

The proton therapy nozzles at Samsung Medical Center: A Monte Carlo simulation study using TOPAS

NASA Astrophysics Data System (ADS)

Chung, Kwangzoo; Kim, Jinsung; Kim, Dae-Hyun; Ahn, Sunghwan; Han, Youngyih

2015-07-01

To expedite the commissioning process of the proton therapy system at Samsung Medical Center (SMC), we have developed a Monte Carlo simulation model of the proton therapy nozzles by using TOol for PArticle Simulation (TOPAS). At SMC proton therapy center, we have two gantry rooms with different types of nozzles: a multi-purpose nozzle and a dedicated scanning nozzle. Each nozzle has been modeled in detail following the geometry information provided by the manufacturer, Sumitomo Heavy Industries, Ltd. For this purpose, the novel features of TOPAS, such as the time feature or the ridge filter class, have been used, and the appropriate physics models for proton nozzle simulation have been defined. Dosimetric properties, like percent depth dose curve, spreadout Bragg peak (SOBP), and beam spot size, have been simulated and verified against measured beam data. Beyond the Monte Carlo nozzle modeling, we have developed an interface between TOPAS and the treatment planning system (TPS), RayStation. An exported radiotherapy (RT) plan from the TPS is interpreted by using an interface and is then translated into the TOPAS input text. The developed Monte Carlo nozzle model can be used to estimate the non-beam performance, such as the neutron background, of the nozzles. Furthermore, the nozzle model can be used to study the mechanical optimization of the design of the nozzle.

Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation

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

Shang, Yu; Lin, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

2014-05-12

Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αD{sub B}) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αD{sub B}. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo strokemore » model of mouse. Computer simulations shows that the high-order (N ≥ 5) linear algorithm was more accurate in extracting αD{sub B} (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: −5.3% to −18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD{sub B} variations, the mean values of errors in extracting αD{sub B} were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD{sub B} using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.« less

Fixed forced detection for fast SPECT Monte-Carlo simulation

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Fixed forced detection for fast SPECT Monte-Carlo simulation.

PubMed

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

2018-03-02

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

Monte Carlo simulation for coherent backscattering with diverging illumination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wu, Wenli; Radosevich, Andrew J.; Eshein, Adam; Nguyen, The-Quyen; Backman, Vadim

2016-03-01

Diverging beam illumination is widely used in many optical techniques especially in fiber optic applications and coherence phenomenon is one of the most important properties to consider for these applications. Until now, people have used Monte Carlo simulations to study the backscattering coherence phenomenon in collimated beam illumination only. We are the first one to study the coherence phenomenon under the exact diverging beam geometry by taking into account the impossibility of the existence for the exact time-reversed path pairs of photons, which is the main contribution to the backscattering coherence pattern in collimated beam. In this work, we present a Monte Carlo simulation that considers the influence of the illumination numerical aperture. The simulation tracks the electric field for the unique paths of forward path and reverse path in time-reversed pairs of photons as well as the same path shared by them. With this approach, we can model the coherence pattern formed between the pairs by considering their phase difference at the collection plane directly. To validate this model, we use the Low-coherence Enhanced Backscattering Spectroscopy, one of the instruments looking at the coherence pattern using diverging beam illumination, as the benchmark to compare with. In the end, we show how this diverging configuration would significantly change the coherent pattern under coherent light source and incoherent light source. This Monte Carlo model we developed can be used to study the backscattering phenomenon in both coherence and non-coherence situation with both collimated beam and diverging beam setups.

Monte Carlo Simulations and Generation of the SPI Response

NASA Technical Reports Server (NTRS)

Sturner, S. J.; Shrader, C. R.; Weidenspointner, G.; Teegarden, B. J.; Attie, D.; Diehl, R.; Ferguson, C.; Jean, P.; vonKienlin, A.

2003-01-01

In this paper we discuss the methods developed for the production of the INTEGRAL/SPI instrument response. The response files were produced using a suite of Monte Carlo simulation software developed at NASA/GSFC based on the GEANT-3 package available from CERN. The production of the INTEGRAL/SPI instrument response also required the development of a detailed computer mass model for SPI. We discuss our extensive investigations into methods to reduce both the computation time and storage requirements for the SPI response. We also discuss corrections to the simulated response based on our comparison of ground and inflight calibration data with MGEANT simulation.

Monte Carlo Simulations and Generation of the SPI Response

NASA Technical Reports Server (NTRS)

Sturner, S. J.; Shrader, C. R.; Weidenspointner, G.; Teegarden, B. J.; Attie, D.; Cordier, B.; Diehl, R.; Ferguson, C.; Jean, P.; vonKienlin, A.

2003-01-01

In this paper we discuss the methods developed for the production of the INTEGRAL/SPI instrument response. The response files were produced using a suite of Monte Carlo simulation software developed at NASA/GSFC based on the GEANT-3 package available from CERN. The production of the INTEGRAL/SPI instrument response also required the development of a detailed computer mass model for SPI. We discuss ow extensive investigations into methods to reduce both the computation time and storage requirements for the SPI response. We also discuss corrections to the simulated response based on our comparison of ground and infiight Calibration data with MGEANT simulations.

Comparison of effects of copropagated and precomputed atmosphere profiles on Monte Carlo trajectory simulation

NASA Technical Reports Server (NTRS)

Queen, Eric M.; Omara, Thomas M.

1990-01-01

A realization of a stochastic atmosphere model for use in simulations is presented. The model provides pressure, density, temperature, and wind velocity as a function of latitude, longitude, and altitude, and is implemented in a three degree of freedom simulation package. This implementation is used in the Monte Carlo simulation of an aeroassisted orbital transfer maneuver and results are compared to those of a more traditional approach.

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

Direct Simulation Monte Carlo Calculations in Support of the Columbia Shuttle Orbiter Accident Investigation

NASA Technical Reports Server (NTRS)

Gallis, Michael A.; LeBeau, Gerald J.; Boyles, Katie A.

2003-01-01

The Direct Simulation Monte Carlo method was used to provide 3-D simulations of the early entry phase of the Shuttle Orbiter. Undamaged and damaged scenarios were modeled to provide calibration points for engineering "bridging function" type of analysis. Currently the simulation technology (software and hardware) are mature enough to allow realistic simulations of three dimensional vehicles.

Simulation of charge breeding of rubidium using Monte Carlo charge breeding code and generalized ECRIS model

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

Zhao, L.; Cluggish, B.; Kim, J. S.

2010-02-15

A Monte Carlo charge breeding code (MCBC) is being developed by FAR-TECH, Inc. to model the capture and charge breeding of 1+ ion beam in an electron cyclotron resonance ion source (ECRIS) device. The ECRIS plasma is simulated using the generalized ECRIS model which has two choices of boundary settings, free boundary condition and Bohm condition. The charge state distribution of the extracted beam ions is calculated by solving the steady state ion continuity equations where the profiles of the captured ions are used as source terms. MCBC simulations of the charge breeding of Rb+ showed good agreement with recentmore » charge breeding experiments at Argonne National Laboratory (ANL). MCBC correctly predicted the peak of highly charged ion state outputs under free boundary condition and similar charge state distribution width but a lower peak charge state under the Bohm condition. The comparisons between the simulation results and ANL experimental measurements are presented and discussed.« less

Levofloxacin Penetration into Epithelial Lining Fluid as Determined by Population Pharmacokinetic Modeling and Monte Carlo Simulation

PubMed Central

Drusano, G. L.; Preston, S. L.; Gotfried, M. H.; Danziger, L. H.; Rodvold, K. A.

2002-01-01

Levofloxacin was administered orally to steady state to volunteers randomly in doses of 500 and 750 mg. Plasma and epithelial lining fluid (ELF) samples were obtained at 4, 12, and 24 h after the final dose. All data were comodeled in a population pharmacokinetic analysis employing BigNPEM. Penetration was evaluated from the population mean parameter vector values and from the results of a 1,000-subject Monte Carlo simulation. Evaluation from the population mean values demonstrated a penetration ratio (ELF/plasma) of 1.16. The Monte Carlo simulation provided a measure of dispersion, demonstrating a mean ratio of 3.18, with a median of 1.43 and a 95% confidence interval of 0.14 to 19.1. Population analysis with Monte Carlo simulation provides the best and least-biased estimate of penetration. It also demonstrates clearly that we can expect differences in penetration between patients. This analysis did not deal with inflammation, as it was performed in volunteers. The influence of lung pathology on penetration needs to be examined. PMID:11796385

Monte Carlo Simulations of Radiative and Neutrino Transport under Astrophysical Conditions

NASA Astrophysics Data System (ADS)

Krivosheyev, Yu. M.; Bisnovatyi-Kogan, G. S.

2018-05-01

Monte Carlo simulations are utilized to model radiative and neutrino transfer in astrophysics. An algorithm that can be used to study radiative transport in astrophysical plasma based on simulations of photon trajectories in a medium is described. Formation of the hard X-ray spectrum of the Galactic microquasar SS 433 is considered in detail as an example. Specific requirements for applying such simulations to neutrino transport in a densemedium and algorithmic differences compared to its application to photon transport are discussed.

A New Approach to Monte Carlo Simulations in Statistical Physics

NASA Astrophysics Data System (ADS)

Landau, David P.

2002-08-01

Monte Carlo simulations [1] have become a powerful tool for the study of diverse problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, most often in the canonical ensemble, and over the past several decades enormous improvements have been made in performance. Nonetheless, difficulties arise near phase transitions-due to critical slowing down near 2nd order transitions and to metastability near 1st order transitions, and these complications limit the applicability of the method. We shall describe a new Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is known, all thermodynamic properties can be calculated. This approach can be extended to multi-dimensional parameter spaces and should be effective for systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc. Generalizations should produce a broadly applicable optimization tool. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

Probabilistic approach of resource assessment in Kerinci geothermal field using numerical simulation coupling with monte carlo simulation

NASA Astrophysics Data System (ADS)

Hidayat, Iki; Sutopo; Pratama, Heru Berian

2017-12-01

The Kerinci geothermal field is one phase liquid reservoir system in the Kerinci District, western part of Jambi Province. In this field, there are geothermal prospects that identified by the heat source up flow inside a National Park area. Kerinci field was planned to develop 1×55 MWe by Pertamina Geothermal Energy. To define reservoir characterization, the numerical simulation of Kerinci field is developed by using TOUGH2 software with information from conceptual model. The pressure and temperature profile well data of KRC-B1 are validated with simulation data to reach natural state condition. The result of the validation is suitable matching. Based on natural state simulation, the resource assessment of Kerinci geothermal field is estimated by using Monte Carlo simulation with the result P10-P50-P90 are 49.4 MW, 64.3 MW and 82.4 MW respectively. This paper is the first study of resource assessment that has been estimated successfully in Kerinci Geothermal Field using numerical simulation coupling with Monte carlo simulation.

Cluster expansion modeling and Monte Carlo simulation of alnico 5-7 permanent magnets

NASA Astrophysics Data System (ADS)

Nguyen, Manh Cuong; Zhao, Xin; Wang, Cai-Zhuang; Ho, Kai-Ming

2015-03-01

The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5-7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5-7 at atomistic and nano scales. The alnico 5-7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at low temperature. The boundary between these two phases is quite sharp (˜2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. A small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5-7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. The results from our Monte Carlo simulations are consistent with available experimental results.

Monte Carlo simulation of near-infrared light propagation in realistic adult head models with hair follicles

NASA Astrophysics Data System (ADS)

Pan, Boan; Fang, Xiang; Liu, Weichao; Li, Nanxi; Zhao, Ke; Li, Ting

2018-02-01

Near infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) has been used to measure brain activation, which are clinically important. Monte Carlo simulation has been applied to the near infrared light propagation model in biological tissue, and has the function of predicting diffusion and brain activation. However, previous studies have rarely considered hair and hair follicles as a contributing factor. Here, we attempt to use MCVM (Monte Carlo simulation based on 3D voxelized media) to examine light transmission, absorption, fluence, spatial sensitivity distribution (SSD) and brain activation judgement in the presence or absence of the hair follicles. The data in this study is a series of high-resolution cryosectional color photograph of a standing Chinse male adult. We found that the number of photons transmitted under the scalp decreases dramatically and the photons exported to detector is also decreasing, as the density of hair follicles increases. If there is no hair follicle, the above data increase and has the maximum value. Meanwhile, the light distribution and brain activation have a stable change along with the change of hair follicles density. The findings indicated hair follicles make influence of NIRS in light distribution and brain activation judgement.

Monte Carlo simulation of proton track structure in biological matter

DOE PAGES

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

2017-05-25

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

Monte Carlo simulation of proton track structure in biological matter

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

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

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

Monte Carlo simulation of biomolecular systems with BIOMCSIM

NASA Astrophysics Data System (ADS)

Kamberaj, H.; Helms, V.

2001-12-01

A new Monte Carlo simulation program, BIOMCSIM, is presented that has been developed in particular to simulate the behaviour of biomolecular systems, leading to insights and understanding of their functions. The computational complexity in Monte Carlo simulations of high density systems, with large molecules like proteins immersed in a solvent medium, or when simulating the dynamics of water molecules in a protein cavity, is enormous. The program presented in this paper seeks to provide these desirable features putting special emphasis on simulations in grand canonical ensembles. It uses different biasing techniques to increase the convergence of simulations, and periodic load balancing in its parallel version, to maximally utilize the available computer power. In periodic systems, the long-ranged electrostatic interactions can be treated by Ewald summation. The program is modularly organized, and implemented using an ANSI C dialect, so as to enhance its modifiability. Its performance is demonstrated in benchmark applications for the proteins BPTI and Cytochrome c Oxidase.

Monte Carlo simulation of quantum Zeno effect in the brain

NASA Astrophysics Data System (ADS)

Georgiev, Danko

2015-12-01

Environmental decoherence appears to be the biggest obstacle for successful construction of quantum mind theories. Nevertheless, the quantum physicist Henry Stapp promoted the view that the mind could utilize quantum Zeno effect to influence brain dynamics and that the efficacy of such mental efforts would not be undermined by environmental decoherence of the brain. To address the physical plausibility of Stapp's claim, we modeled the brain using quantum tunneling of an electron in a multiple-well structure such as the voltage sensor in neuronal ion channels and performed Monte Carlo simulations of quantum Zeno effect exerted by the mind upon the brain in the presence or absence of environmental decoherence. The simulations unambiguously showed that the quantum Zeno effect breaks down for timescales greater than the brain decoherence time. To generalize the Monte Carlo simulation results for any n-level quantum system, we further analyzed the change of brain entropy due to the mind probing actions and proved a theorem according to which local projections cannot decrease the von Neumann entropy of the unconditional brain density matrix. The latter theorem establishes that Stapp's model is physically implausible but leaves a door open for future development of quantum mind theories provided the brain has a decoherence-free subspace.

Modeling of molecular nitrogen collisions and dissociation processes for direct simulation Monte Carlo.

PubMed

Parsons, Neal; Levin, Deborah A; van Duin, Adri C T; Zhu, Tong

2014-12-21

The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N2(Σg+1)-N2(Σg+1) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections.

Dendrimer-magnetic nanostructure: a Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Jabar, A.; Masrour, R.

2017-11-01

In this paper, the magnetic properties of ternary mixed spins (σ,S,q) Ising model on a dendrimer nanostructure are studied using Monte Carlo simulations. The ground state phase diagrams of dendrimer nanostructure with ternary mixed spins σ = 1/2, S = 1 and q = 3/2 Ising model are found. The variation of the thermal total and partial magnetizations with the different exchange interactions, the external magnetic fields and the crystal fields have been also studied. The reduced critical temperatures have been deduced. The magnetic hysteresis cycles have been discussed. In particular, the corresponding magnetic coercive filed values have been deduced. The multiples hysteresis cycles are found. The dendrimer nanostructure has several applications in the medicine.

Accurate Monte Carlo simulations for nozzle design, commissioning and quality assurance for a proton radiation therapy facility.

PubMed

Paganetti, H; Jiang, H; Lee, S Y; Kooy, H M

2004-07-01

Monte Carlo dosimetry calculations are essential methods in radiation therapy. To take full advantage of this tool, the beam delivery system has to be simulated in detail and the initial beam parameters have to be known accurately. The modeling of the beam delivery system itself opens various areas where Monte Carlo calculations prove extremely helpful, such as for design and commissioning of a therapy facility as well as for quality assurance verification. The gantry treatment nozzles at the Northeast Proton Therapy Center (NPTC) at Massachusetts General Hospital (MGH) were modeled in detail using the GEANT4.5.2 Monte Carlo code. For this purpose, various novel solutions for simulating irregular shaped objects in the beam path, like contoured scatterers, patient apertures or patient compensators, were found. The four-dimensional, in time and space, simulation of moving parts, such as the modulator wheel, was implemented. Further, the appropriate physics models and cross sections for proton therapy applications were defined. We present comparisons between measured data and simulations. These show that by modeling the treatment nozzle with millimeter accuracy, it is possible to reproduce measured dose distributions with an accuracy in range and modulation width, in the case of a spread-out Bragg peak (SOBP), of better than 1 mm. The excellent agreement demonstrates that the simulations can even be used to generate beam data for commissioning treatment planning systems. The Monte Carlo nozzle model was used to study mechanical optimization in terms of scattered radiation and secondary radiation in the design of the nozzles. We present simulations on the neutron background. Further, the Monte Carlo calculations supported commissioning efforts in understanding the sensitivity of beam characteristics and how these influence the dose delivered. We present the sensitivity of dose distributions in water with respect to various beam parameters and geometrical misalignments

On recontamination and directional-bias problems in Monte Carlo simulation of PDF turbulence models

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1991-01-01

Turbulent combustion can not be simulated adequately by conventional moment closure turbulence models. The difficulty lies in the fact that the reaction rate is in general an exponential function of the temperature, and the higher order correlations in the conventional moment closure models of the chemical source term can not be neglected, making the applications of such models impractical. The probability density function (pdf) method offers an attractive alternative: in a pdf model, the chemical source terms are closed and do not require additional models. A grid dependent Monte Carlo scheme was studied, since it is a logical alternative, wherein the number of computer operations increases only linearly with the increase of number of independent variables, as compared to the exponential increase in a conventional finite difference scheme. A new algorithm was devised that satisfies a restriction in the case of pure diffusion or uniform flow problems. Although for nonuniform flows absolute conservation seems impossible, the present scheme has reduced the error considerably.

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

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

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach.more » The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.« less

Modeling and simulation of radiation from hypersonic flows with Monte Carlo methods

NASA Astrophysics Data System (ADS)

Sohn, Ilyoup

approximately 1 % was achieved with an efficiency about three times faster than the NEQAIR code. To perform accurate and efficient analyses of chemically reacting flowfield - radiation interactions, the direct simulation Monte Carlo (DSMC) and the photon Monte Carlo (PMC) radiative transport methods are used to simulate flowfield - radiation coupling from transitional to peak heating freestream conditions. The non-catalytic and fully catalytic surface conditions were modeled and good agreement of the stagnation-point convective heating between DSMC and continuum fluid dynamics (CFD) calculation under the assumption of fully catalytic surface was achieved. Stagnation-point radiative heating, however, was found to be very different. To simulate three-dimensional radiative transport, the finite-volume based PMC (FV-PMC) method was employed. DSMC - FV-PMC simulations with the goal of understanding the effect of radiation on the flow structure for different degrees of hypersonic non-equilibrium are presented. It is found that except for the highest altitudes, the coupling of radiation influences the flowfield, leading to a decrease in both heavy particle translational and internal temperatures and a decrease in the convective heat flux to the vehicle body. The DSMC - FV-PMC coupled simulations are compared with the previous coupled simulations and correlations obtained using continuum flow modeling and one-dimensional radiative transport. The modeling of radiative transport is further complicated by radiative transitions occurring during the excitation process of the same radiating gas species. This interaction affects the distribution of electronic state populations and, in turn, the radiative transport. The radiative transition rate in the excitation/de-excitation processes and the radiative transport equation (RTE) must be coupled simultaneously to account for non-local effects. The QSS model is presented to predict the electronic state populations of radiating gas species taking

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.

Studies of Low Luminosity Active Galactic Nuclei with Monte Carlo and Magnetohydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Hilburn, Guy Louis

Results from several studies are presented which detail explorations of the physical and spectral properties of low luminosity active galactic nuclei. An initial Sagittarius A* general relativistic magnetohydrodynamic simulation and Monte Carlo radiation transport model suggests accretion rate changes as the dominant flaring method. A similar study on M87 introduces new methods to the Monte Carlo model for increased consistency in highly energetic sources. Again, accretion rate variation seems most appropriate to explain spectral transients. To more closely resolve the methods of particle energization in active galactic nuclei accretion disks, a series of localized shearing box simulations explores the effect of numerical resolution on the development of current sheets. A particular focus on numerically describing converged current sheet formation will provide new methods for consideration of turbulence in accretion disks.

Effective Thermal Conductivity of Spherical Particulate Nanocomposites: Comparison with Theoretical Models, Monte Carlo Simulations and Experiments

NASA Astrophysics Data System (ADS)

Machrafi, Hatim; Lebon, Georgy

2014-11-01

The purpose of this work is to study heat conduction in systems that are composed out of spherical micro-and nanoparticles dispersed in a bulk matrix. Special emphasis will be put on the dependence of the effective heat conductivity on various selected parameters as dimension and density of particles, interface interaction with the matrix. This is achieved by combining the effective medium approximation and extended irreversible thermodynamics, whose main feature is to elevate the heat flux vector to the status of independent variable. The model is illustrated by three examples: Silicium-Germanium, Silica-epoxy-resin and Copper-Silicium systems. Predictions of our model are in good agreement with other theoretical models, Monte-Carlo simulations and experimental data.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

Commissioning of a Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

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

Dirgayussa, I Gde Eka, E-mail: ekadirgayussa@gmail.com; Yani, Sitti; Haryanto, Freddy, E-mail: freddy@fi.itb.ac.id

2015-09-30

Monte Carlo modelling of a linear accelerator is the first and most important step in Monte Carlo dose calculations in radiotherapy. Monte Carlo is considered today to be the most accurate and detailed calculation method in different fields of medical physics. In this research, we developed a photon beam model for Varian Clinac iX 6 MV equipped with MilleniumMLC120 for dose calculation purposes using BEAMnrc/DOSXYZnrc Monte Carlo system based on the underlying EGSnrc particle transport code. Monte Carlo simulation for this commissioning head LINAC divided in two stages are design head Linac model using BEAMnrc, characterize this model using BEAMDPmore » and analyze the difference between simulation and measurement data using DOSXYZnrc. In the first step, to reduce simulation time, a virtual treatment head LINAC was built in two parts (patient-dependent component and patient-independent component). The incident electron energy varied 6.1 MeV, 6.2 MeV and 6.3 MeV, 6.4 MeV, and 6.6 MeV and the FWHM (full width at half maximum) of source is 1 mm. Phase-space file from the virtual model characterized using BEAMDP. The results of MC calculations using DOSXYZnrc in water phantom are percent depth doses (PDDs) and beam profiles at depths 10 cm were compared with measurements. This process has been completed if the dose difference of measured and calculated relative depth-dose data along the central-axis and dose profile at depths 10 cm is ≤ 5%. The effect of beam width on percentage depth doses and beam profiles was studied. Results of the virtual model were in close agreement with measurements in incident energy electron 6.4 MeV. Our results showed that photon beam width could be tuned using large field beam profile at the depth of maximum dose. The Monte Carlo model developed in this study accurately represents the Varian Clinac iX with millennium MLC 120 leaf and can be used for reliable patient dose calculations. In this commissioning process, the

Monte Carlo modeling and simulations of the High Definition (HD120) micro MLC and validation against measurements for a 6 MV beam

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

Borges, C.; Zarza-Moreno, M.; Heath, E.

2012-01-15

Purpose: The most recent Varian micro multileaf collimator (MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRC Monte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian Trilogy (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. Themore » HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of

An example of complex modelling in dentistry using Markov chain Monte Carlo (MCMC) simulation.

PubMed

Helfenstein, Ulrich; Menghini, Giorgio; Steiner, Marcel; Murati, Francesca

2002-09-01

In the usual regression setting one regression line is computed for a whole data set. In a more complex situation, each person may be observed for example at several points in time and thus a regression line might be calculated for each person. Additional complexities, such as various forms of errors in covariables may make a straightforward statistical evaluation difficult or even impossible. During recent years methods have been developed allowing convenient analysis of problems where the data and the corresponding models show these and many other forms of complexity. The methodology makes use of a Bayesian approach and Markov chain Monte Carlo (MCMC) simulations. The methods allow the construction of increasingly elaborate models by building them up from local sub-models. The essential structure of the models can be represented visually by directed acyclic graphs (DAG). This attractive property allows communication and discussion of the essential structure and the substantial meaning of a complex model without needing algebra. After presentation of the statistical methods an example from dentistry is presented in order to demonstrate their application and use. The dataset of the example had a complex structure; each of a set of children was followed up over several years. The number of new fillings in permanent teeth had been recorded at several ages. The dependent variables were markedly different from the normal distribution and could not be transformed to normality. In addition, explanatory variables were assumed to be measured with different forms of error. Illustration of how the corresponding models can be estimated conveniently via MCMC simulation, in particular, 'Gibbs sampling', using the freely available software BUGS is presented. In addition, how the measurement error may influence the estimates of the corresponding coefficients is explored. It is demonstrated that the effect of the independent variable on the dependent variable may be markedly

Monte Carlo modeling of the Siemens Optifocus multileaf collimator.

PubMed

Laliena, Victor; García-Romero, Alejandro

2015-05-01

We have developed a new component module for the BEAMnrc software package, called SMLC, which models the tongue-and-groove structure of the Siemens Optifocus multileaf collimator. The ultimate goal is to perform accurate Monte Carlo simulations of the IMRT treatments carried out with Optifocus. SMLC has been validated by direct geometry checks and by comparing quantitatively the results of simulations performed with it and with the component module VARMLC. Measurements and Monte Carlo simulations of absorbed dose distributions of radiation fields sensitive to the tongue-and-groove effect have been performed to tune the free parameters of SMLC. The measurements cannot be accurately reproduced with VARMLC. Finally, simulations of a typical IMRT field showed that SMLC improves the agreement with experimental measurements with respect to VARMLC in clinically relevant cases. 87.55. K. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Skin fluorescence model based on the Monte Carlo technique

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2003-10-01

The novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account spatial distribution of fluorophores following the collagen fibers packing, whereas in epidermis and stratum corneum the distribution of fluorophores assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the NIR spectral region, while fluorescence of sensor layer embedded in epidermis is localized at the adjusted depth. The model is also able to simulate the skin fluorescence spectra.

Million-body star cluster simulations: comparisons between Monte Carlo and direct N-body

NASA Astrophysics Data System (ADS)

Rodriguez, Carl L.; Morscher, Meagan; Wang, Long; Chatterjee, Sourav; Rasio, Frederic A.; Spurzem, Rainer

2016-12-01

We present the first detailed comparison between million-body globular cluster simulations computed with a Hénon-type Monte Carlo code, CMC, and a direct N-body code, NBODY6++GPU. Both simulations start from an identical cluster model with 106 particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes `frozen' (no fine-tuning of any free parameters or internal algorithms of the codes) we find good agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (>1000) are retained for 12 Gyr. Thus, the very accurate direct N-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-N dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct N-body, is capable of producing an accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.

Antihydrogen from positronium impact with cold antiprotons: a Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Cassidy, D. B.; Merrison, J. P.; Charlton, M.; Mitroy, J.; Ryzhikh, G.

1999-04-01

A Monte Carlo simulation of the reaction to form antihydrogen by positronium impact upon antiprotons has been undertaken. Total and differential cross sections have been utilized as inputs to the simulation which models the conditions foreseen in planned antihydrogen formation experiments using positrons and antiprotons held in Penning traps. Thus, predictions of antihydrogen production rates, angular distributions and the variation of the mean antihydrogen temperature as a function of incident positronium kinetic energy have been produced.

GPU accelerated Monte-Carlo simulation of SEM images for metrology

NASA Astrophysics Data System (ADS)

Verduin, T.; Lokhorst, S. R.; Hagen, C. W.

2016-03-01

In this work we address the computation times of numerical studies in dimensional metrology. In particular, full Monte-Carlo simulation programs for scanning electron microscopy (SEM) image acquisition are known to be notoriously slow. Our quest in reducing the computation time of SEM image simulation has led us to investigate the use of graphics processing units (GPUs) for metrology. We have succeeded in creating a full Monte-Carlo simulation program for SEM images, which runs entirely on a GPU. The physical scattering models of this GPU simulator are identical to a previous CPU-based simulator, which includes the dielectric function model for inelastic scattering and also refinements for low-voltage SEM applications. As a case study for the performance, we considered the simulated exposure of a complex feature: an isolated silicon line with rough sidewalls located on a at silicon substrate. The surface of the rough feature is decomposed into 408 012 triangles. We have used an exposure dose of 6 mC/cm2, which corresponds to 6 553 600 primary electrons on average (Poisson distributed). We repeat the simulation for various primary electron energies, 300 eV, 500 eV, 800 eV, 1 keV, 3 keV and 5 keV. At first we run the simulation on a GeForce GTX480 from NVIDIA. The very same simulation is duplicated on our CPU-based program, for which we have used an Intel Xeon X5650. Apart from statistics in the simulation, no difference is found between the CPU and GPU simulated results. The GTX480 generates the images (depending on the primary electron energy) 350 to 425 times faster than a single threaded Intel X5650 CPU. Although this is a tremendous speedup, we actually have not reached the maximum throughput because of the limited amount of available memory on the GTX480. Nevertheless, the speedup enables the fast acquisition of simulated SEM images for metrology. We now have the potential to investigate case studies in CD-SEM metrology, which otherwise would take unreasonable

Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

NASA Astrophysics Data System (ADS)

Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.

2018-02-01

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.

Grand canonical Monte Carlo simulation of the adsorption isotherms of water molecules on model soot particles

NASA Astrophysics Data System (ADS)

Moulin, F.; Picaud, S.; Hoang, P. N. M.; Jedlovszky, P.

2007-10-01

The grand canonical Monte Carlo method is used to simulate the adsorption isotherms of water molecules on different types of model soot particles. The soot particles are modeled by graphite-type layers arranged in an onionlike structure that contains randomly distributed hydrophilic sites, such as OH and COOH groups. The calculated water adsorption isotherm at 298K exhibits different characteristic shapes depending both on the type and the location of the hydrophilic sites and also on the size of the pores inside the soot particle. The different shapes of the adsorption isotherms result from different ways of water aggregation in or/and around the soot particle. The present results show the very weak influence of the OH sites on the water adsorption process when compared to the COOH sites. The results of these simulations can help in interpreting the experimental isotherms of water adsorbed on aircraft soot.

A Monte Carlo model for 3D grain evolution during welding

NASA Astrophysics Data System (ADS)

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

2017-09-01

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

A Monte Carlo model for 3D grain evolution during welding

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

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

A Monte Carlo model for 3D grain evolution during welding

DOE PAGES

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

2017-08-04

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

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

DTIC Science & Technology

2013-07-01

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

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

PubMed

Furuta, Takuya

2017-01-01

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

Validation of a Monte Carlo model used for simulating tube current modulation in computed tomography over a wide range of phantom conditions/challenges

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

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

2014-11-01

Purpose: Monte Carlo (MC) simulation methods have been widely used in patient dosimetry in computed tomography (CT), including estimating patient organ doses. However, most simulation methods have undergone a limited set of validations, often using homogeneous phantoms with simple geometries. As clinical scanning has become more complex and the use of tube current modulation (TCM) has become pervasive in the clinic, MC simulations should include these techniques in their methodologies and therefore should also be validated using a variety of phantoms with different shapes and material compositions to result in a variety of differently modulated tube current profiles. The purposemore » of this work is to perform the measurements and simulations to validate a Monte Carlo model under a variety of test conditions where fixed tube current (FTC) and TCM were used. Methods: A previously developed MC model for estimating dose from CT scans that models TCM, built using the platform of MCNPX, was used for CT dose quantification. In order to validate the suitability of this model to accurately simulate patient dose from FTC and TCM CT scan, measurements and simulations were compared over a wide range of conditions. Phantoms used for testing range from simple geometries with homogeneous composition (16 and 32 cm computed tomography dose index phantoms) to more complex phantoms including a rectangular homogeneous water equivalent phantom, an elliptical shaped phantom with three sections (where each section was a homogeneous, but different material), and a heterogeneous, complex geometry anthropomorphic phantom. Each phantom requires varying levels of x-, y- and z-modulation. Each phantom was scanned on a multidetector row CT (Sensation 64) scanner under the conditions of both FTC and TCM. Dose measurements were made at various surface and depth positions within each phantom. Simulations using each phantom were performed for FTC, detailed x–y–z TCM, and z-axis-only TCM to

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

Force field development with GOMC, a fast new Monte Carlo molecular simulation code

NASA Astrophysics Data System (ADS)

Mick, Jason Richard

In this work GOMC (GPU Optimized Monte Carlo) a new fast, flexible, and free molecular Monte Carlo code for the simulation atomistic chemical systems is presented. The results of a large Lennard-Jonesium simulation in the Gibbs ensemble is presented. Force fields developed using the code are also presented. To fit the models a quantitative fitting process is outlined using a scoring function and heat maps. The presented n-6 force fields include force fields for noble gases and branched alkanes. These force fields are shown to be the most accurate LJ or n-6 force fields to date for these compounds, capable of reproducing pure fluid behavior and binary mixture behavior to a high degree of accuracy.

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.

Monte Carlo Simulation of Endlinking Oligomers

NASA Technical Reports Server (NTRS)

Hinkley, Jeffrey A.; Young, Jennifer A.

1998-01-01

This report describes initial efforts to model the endlinking reaction of phenylethynyl-terminated oligomers. Several different molecular weights were simulated using the Bond Fluctuation Monte Carlo technique on a 20 x 20 x 20 unit lattice with periodic boundary conditions. After a monodisperse "melt" was equilibrated, chain ends were linked whenever they came within the allowed bond distance. Ends remained reactive throughout, so that multiple links were permitted. Even under these very liberal crosslinking assumptions, geometrical factors limited the degree of crosslinking. Average crosslink functionalities were 2.3 to 2.6; surprisingly, they did not depend strongly on the chain length. These results agreed well with the degrees of crosslinking inferred from experiment in a cured phenylethynyl-terminated polyimide oligomer.

Entanglement and the fermion sign problem in auxiliary field quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Broecker, Peter; Trebst, Simon

2016-08-01

Quantum Monte Carlo simulations of fermions are hampered by the notorious sign problem whose most striking manifestation is an exponential growth of sampling errors with the number of particles. With the sign problem known to be an NP-hard problem and any generic solution thus highly elusive, the Monte Carlo sampling of interacting many-fermion systems is commonly thought to be restricted to a small class of model systems for which a sign-free basis has been identified. Here we demonstrate that entanglement measures, in particular the so-called Rényi entropies, can intrinsically exhibit a certain robustness against the sign problem in auxiliary-field quantum Monte Carlo approaches and possibly allow for the identification of global ground-state properties via their scaling behavior even in the presence of a strong sign problem. We corroborate these findings via numerical simulations of fermionic quantum phase transitions of spinless fermions on the honeycomb lattice at and below half filling.

Gutzwiller Monte Carlo approach for a critical dissipative spin model

NASA Astrophysics Data System (ADS)

Casteels, Wim; Wilson, Ryan M.; Wouters, Michiel

2018-06-01

We use the Gutzwiller Monte Carlo approach to simulate the dissipative X Y Z model in the vicinity of a dissipative phase transition. This approach captures classical spatial correlations together with the full on-site quantum behavior while neglecting nonlocal quantum effects. By considering finite two-dimensional lattices of various sizes, we identify a ferromagnetic and two paramagnetic phases, in agreement with earlier studies. The greatly reduced numerical complexity of the Gutzwiller Monte Carlo approach facilitates efficient simulation of relatively large lattice sizes. The inclusion of the spatial correlations allows to capture parts of the phase diagram that are completely missed by the widely applied Gutzwiller decoupling of the density matrix.

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

PubMed

Badal, Andreu; Badano, Aldo

2009-11-01

It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDATM programming model (NVIDIA Corporation, Santa Clara, CA). An outline of the new code and a sample x-ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.

Direct simulation Monte Carlo investigation of the Richtmyer-Meshkov instability

DOE PAGES

Gallis, Michail A.; Koehler, Timothy P.; Torczynski, John R.; ...

2015-08-14

The Rayleigh-Taylor instability (RTI) is investigated using the Direct Simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce all qualitative features of the RTI and are in reasonable quantitative agreement with existing theoretical and empirical models in the linear, nonlinear, and self-similar regimes. At late times, the instability is seen to exhibit a self-similar behavior, in agreement with experimental observations. Formore » the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Direct simulation Monte Carlo investigation of the Rayleigh-Taylor instability

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

Gallis, M. A.; Koehler, T. P.; Torczynski, J. R.

In this paper, the Rayleigh-Taylor instability (RTI) is investigated using the direct simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce many qualitative features of the growth of the mixing layer and are in reasonable quantitative agreement with theoretical and empirical models in the linear, nonlinear, and self-similar regimes. In some of the simulations at late times, the instability enters themore » self-similar regime, in agreement with experimental observations. Finally, for the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Direct simulation Monte Carlo investigation of the Rayleigh-Taylor instability

DOE PAGES

Gallis, M. A.; Koehler, T. P.; Torczynski, J. R.; ...

2016-08-31

In this paper, the Rayleigh-Taylor instability (RTI) is investigated using the direct simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce many qualitative features of the growth of the mixing layer and are in reasonable quantitative agreement with theoretical and empirical models in the linear, nonlinear, and self-similar regimes. In some of the simulations at late times, the instability enters themore » self-similar regime, in agreement with experimental observations. Finally, for the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Monte Carlo Simulation of the Rapid Crystallization of Bismuth-Doped Silicon

NASA Technical Reports Server (NTRS)

Jackson, Kenneth A.; Gilmer, George H.; Temkin, Dmitri E.

1995-01-01

In this Letter we report Ising model simulations of the growth of alloys which predict quite different behavior near and far from equilibrium. Our simulations reproduce the phenomenon which has been termed 'solute trapping,' where concentrations of solute, which are far in excess of the equilibrium concentrations, are observed in the crystal after rapid crystallization. This phenomenon plays an important role in many processes which involve first order phase changes which take place under conditions far from equilibrium. The underlying physical basis for it has not been understood, but these Monte Carlo simulations provide a powerful means for investigating it.

Investigation of radiative interaction in laminar flows using Monte Carlo simulation

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is employed to study the radiative interactions in fully developed laminar flow between two parallel plates. Taking advantage of the characteristics of easy mathematical treatment of the MCM, a general numerical procedure is developed for nongray radiative interaction. The nongray model is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. To validate the Monte Carlo simulation for nongray radiation problems, the results of radiative dissipation from the MCM are compared with two available solutions for a given temperature profile between two plates. After this validation, the MCM is employed to solve the present physical problem and results for the bulk temperature are compared with available solutions. In general, good agreement is noted and reasons for some discrepancies in certain ranges of parameters are explained.

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

PubMed Central

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

2011-01-01

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

A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

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

Morton, April M; McManamay, Ryan A; Nagle, Nicholas N

Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may thereforemore » not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.« less

Experimental validation of a Monte Carlo proton therapy nozzle model incorporating magnetically steered protons.

PubMed

Peterson, S W; Polf, J; Bues, M; Ciangaru, G; Archambault, L; Beddar, S; Smith, A

2009-05-21

The purpose of this study is to validate the accuracy of a Monte Carlo calculation model of a proton magnetic beam scanning delivery nozzle developed using the Geant4 toolkit. The Monte Carlo model was used to produce depth dose and lateral profiles, which were compared to data measured in the clinical scanning treatment nozzle at several energies. Comparisons were also made between measured and simulated off-axis profiles to test the accuracy of the model's magnetic steering. Comparison of the 80% distal dose fall-off values for the measured and simulated depth dose profiles agreed to within 1 mm for the beam energies evaluated. Agreement of the full width at half maximum values for the measured and simulated lateral fluence profiles was within 1.3 mm for all energies. The position of measured and simulated spot positions for the magnetically steered beams agreed to within 0.7 mm of each other. Based on these results, we found that the Geant4 Monte Carlo model of the beam scanning nozzle has the ability to accurately predict depth dose profiles, lateral profiles perpendicular to the beam axis and magnetic steering of a proton beam during beam scanning proton therapy.

Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit.

PubMed

Bernal, M A; Bordage, M C; Brown, J M C; Davídková, M; Delage, E; El Bitar, Z; Enger, S A; Francis, Z; Guatelli, S; Ivanchenko, V N; Karamitros, M; Kyriakou, I; Maigne, L; Meylan, S; Murakami, K; Okada, S; Payno, H; Perrot, Y; Petrovic, I; Pham, Q T; Ristic-Fira, A; Sasaki, T; Štěpán, V; Tran, H N; Villagrasa, C; Incerti, S

2015-12-01

Understanding the fundamental mechanisms involved in the induction of biological damage by ionizing radiation remains a major challenge of today's radiobiology research. The Monte Carlo simulation of physical, physicochemical and chemical processes involved may provide a powerful tool for the simulation of early damage induction. The Geant4-DNA extension of the general purpose Monte Carlo Geant4 simulation toolkit aims to provide the scientific community with an open source access platform for the mechanistic simulation of such early damage. This paper presents the most recent review of the Geant4-DNA extension, as available to Geant4 users since June 2015 (release 10.2 Beta). In particular, the review includes the description of new physical models for the description of electron elastic and inelastic interactions in liquid water, as well as new examples dedicated to the simulation of physicochemical and chemical stages of water radiolysis. Several implementations of geometrical models of biological targets are presented as well, and the list of Geant4-DNA examples is described. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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

Development of a Space Radiation Monte Carlo Computer Simulation

NASA Technical Reports Server (NTRS)

Pinsky, Lawrence S.

1997-01-01

The ultimate purpose of this effort is to undertake the development of a computer simulation of the radiation environment encountered in spacecraft which is based upon the Monte Carlo technique. The current plan is to adapt and modify a Monte Carlo calculation code known as FLUKA, which is presently used in high energy and heavy ion physics, to simulate the radiation environment present in spacecraft during missions. The initial effort would be directed towards modeling the MIR and Space Shuttle environments, but the long range goal is to develop a program for the accurate prediction of the radiation environment likely to be encountered on future planned endeavors such as the Space Station, a Lunar Return Mission, or a Mars Mission. The longer the mission, especially those which will not have the shielding protection of the earth's magnetic field, the more critical the radiation threat will be. The ultimate goal of this research is to produce a code that will be useful to mission planners and engineers who need to have detailed projections of radiation exposures at specified locations within the spacecraft and for either specific times during the mission or integrated over the entire mission. In concert with the development of the simulation, it is desired to integrate it with a state-of-the-art interactive 3-D graphics-capable analysis package known as ROOT, to allow easy investigation and visualization of the results. The efforts reported on here include the initial development of the program and the demonstration of the efficacy of the technique through a model simulation of the MIR environment. This information was used to write a proposal to obtain follow-on permanent funding for this project.

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.

A fortran program for Monte Carlo simulation of oil-field discovery sequences

USGS Publications Warehouse

Bohling, Geoffrey C.; Davis, J.C.

1993-01-01

We have developed a program for performing Monte Carlo simulation of oil-field discovery histories. A synthetic parent population of fields is generated as a finite sample from a distribution of specified form. The discovery sequence then is simulated by sampling without replacement from this parent population in accordance with a probabilistic discovery process model. The program computes a chi-squared deviation between synthetic and actual discovery sequences as a function of the parameters of the discovery process model, the number of fields in the parent population, and the distributional parameters of the parent population. The program employs the three-parameter log gamma model for the distribution of field sizes and employs a two-parameter discovery process model, allowing the simulation of a wide range of scenarios. ?? 1993.

Modeling the biophysical effects in a carbon beam delivery line by using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Cho, Ilsung; Yoo, SeungHoon; Cho, Sungho; Kim, Eun Ho; Song, Yongkeun; Shin, Jae-ik; Jung, Won-Gyun

2016-09-01

The Relative biological effectiveness (RBE) plays an important role in designing a uniform dose response for ion-beam therapy. In this study, the biological effectiveness of a carbon-ion beam delivery system was investigated using Monte Carlo simulations. A carbon-ion beam delivery line was designed for the Korea Heavy Ion Medical Accelerator (KHIMA) project. The GEANT4 simulation tool kit was used to simulate carbon-ion beam transport into media. An incident energy carbon-ion beam with energy in the range between 220 MeV/u and 290 MeV/u was chosen to generate secondary particles. The microdosimetric-kinetic (MK) model was applied to describe the RBE of 10% survival in human salivary-gland (HSG) cells. The RBE weighted dose was estimated as a function of the penetration depth in the water phantom along the incident beam's direction. A biologically photon-equivalent Spread Out Bragg Peak (SOBP) was designed using the RBE-weighted absorbed dose. Finally, the RBE of mixed beams was predicted as a function of the depth in the water phantom.

Kinetic Monte Carlo simulations of travelling pulses and spiral waves in the lattice Lotka-Volterra model.

PubMed

Makeev, Alexei G; Kurkina, Elena S; Kevrekidis, Ioannis G

2012-06-01

Kinetic Monte Carlo simulations are used to study the stochastic two-species Lotka-Volterra model on a square lattice. For certain values of the model parameters, the system constitutes an excitable medium: travelling pulses and rotating spiral waves can be excited. Stable solitary pulses travel with constant (modulo stochastic fluctuations) shape and speed along a periodic lattice. The spiral waves observed persist sometimes for hundreds of rotations, but they are ultimately unstable and break-up (because of fluctuations and interactions between neighboring fronts) giving rise to complex dynamic behavior in which numerous small spiral waves rotate and interact with each other. It is interesting that travelling pulses and spiral waves can be exhibited by the model even for completely immobile species, due to the non-local reaction kinetics.

Investigations in thunderstorm energetics using satellite instrumentation and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Brunner, K. N.; Bitzer, P. M.

2017-12-01

The electrical energy dissipated by lightning is a fundamental question in lightning physics and may be used in severe weather applications. However, the electrical energy, flash area/extent and spectral energy density (radiance) are all influenced by the geometry of the lightning channel. We present details of a Monte Carlo based model simulating the optical emission from lightning and compare with observations. Using time-of-arrival techniques and the electric field change measurements from the Huntsville Alabama Marx Meter Array (HAMMA), the 4D lightning channel is reconstructed. The located sources and lightning channel emit optical emission, calibrated by the ground based electric field, that scatters until absorbed or a cloud boundary is reached within the model. At cloud top, the simulation is gridded as LIS pixels (events) and contiguous events (groups). The radiance is related via the LIS calibration and the estimated lightning electrical energy is calculated at the LIS/GLM time resolution. Previous Monte Carlo simulations have relied on a simplified lightning channel and scattering medium. This work considers the cloud a stratified medium of graupel/ice and inhomogeneous at flash scale. The impact of cloud inhomogeneity on the scattered optical emission at cloud top and at the time resolution of LIS and GLM are also considered. The simulation results and energy metrics provide an estimation of the electrical energy using GLM and LIS on the International Space Station (ISS-LIS).

Mathematical modeling, analysis and Markov Chain Monte Carlo simulation of Ebola epidemics

NASA Astrophysics Data System (ADS)

Tulu, Thomas Wetere; Tian, Boping; Wu, Zunyou

Ebola virus infection is a severe infectious disease with the highest case fatality rate which become the global public health treat now. What makes the disease the worst of all is no specific effective treatment available, its dynamics is not much researched and understood. In this article a new mathematical model incorporating both vaccination and quarantine to study the dynamics of Ebola epidemic has been developed and comprehensively analyzed. The existence as well as uniqueness of the solution to the model is also verified and the basic reproduction number is calculated. Besides, stability conditions are also checked and finally simulation is done using both Euler method and one of the top ten most influential algorithm known as Markov Chain Monte Carlo (MCMC) method. Different rates of vaccination to predict the effect of vaccination on the infected individual over time and that of quarantine are discussed. The results show that quarantine and vaccination are very effective ways to control Ebola epidemic. From our study it was also seen that there is less possibility of an individual for getting Ebola virus for the second time if they survived his/her first infection. Last but not least real data has been fitted to the model, showing that it can used to predict the dynamic of Ebola epidemic.

An ab initio chemical reaction model for the direct simulation Monte Carlo study of non-equilibrium nitrogen flows.

PubMed

Mankodi, T K; Bhandarkar, U V; Puranik, B P

2017-08-28

A new ab initio based chemical model for a Direct Simulation Monte Carlo (DSMC) study suitable for simulating rarefied flows with a high degree of non-equilibrium is presented. To this end, Collision Induced Dissociation (CID) cross sections for N 2 +N 2 →N 2 +2N are calculated and published using a global complete active space self-consistent field-complete active space second order perturbation theory N 4 potential energy surface and quasi-classical trajectory algorithm for high energy collisions (up to 30 eV). CID cross sections are calculated for only a selected set of ro-vibrational combinations of the two nitrogen molecules, and a fitting scheme based on spectroscopic weights is presented to interpolate the CID cross section for all possible ro-vibrational combinations. The new chemical model is validated by calculating equilibrium reaction rate coefficients that can be compared well with existing shock tube and computational results. High-enthalpy hypersonic nitrogen flows around a cylinder in the transition flow regime are simulated using DSMC to compare the predictions of the current ab initio based chemical model with the prevailing phenomenological model (the total collision energy model). The differences in the predictions are discussed.

A dental public health approach based on computational mathematics: Monte Carlo simulation of childhood dental decay.

PubMed

Tennant, Marc; Kruger, Estie

2013-02-01

This study developed a Monte Carlo simulation approach to examining the prevalence and incidence of dental decay using Australian children as a test environment. Monte Carlo simulation has been used for a half a century in particle physics (and elsewhere); put simply, it is the probability for various population-level outcomes seeded randomly to drive the production of individual level data. A total of five runs of the simulation model for all 275,000 12-year-olds in Australia were completed based on 2005-2006 data. Measured on average decayed/missing/filled teeth (DMFT) and DMFT of highest 10% of sample (Sic10) the runs did not differ from each other by more than 2% and the outcome was within 5% of the reported sampled population data. The simulations rested on the population probabilities that are known to be strongly linked to dental decay, namely, socio-economic status and Indigenous heritage. Testing the simulated population found DMFT of all cases where DMFT<>0 was 2.3 (n = 128,609) and DMFT for Indigenous cases only was 1.9 (n = 13,749). In the simulation population the Sic25 was 3.3 (n = 68,750). Monte Carlo simulations were created in particle physics as a computational mathematical approach to unknown individual-level effects by resting a simulation on known population-level probabilities. In this study a Monte Carlo simulation approach to childhood dental decay was built, tested and validated. © 2013 FDI World Dental Federation.

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

OBJECT KINETIC MONTE CARLO SIMULATIONS OF MICROSTRUCTURE EVOLUTION

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

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

2013-09-30

The objective is to report the development of the flexible object kinetic Monte Carlo (OKMC) simulation code KSOME (kinetic simulation of microstructure evolution) which can be used to simulate microstructure evolution of complex systems under irradiation. In this report we briefly describe the capabilities of KSOME and present preliminary results for short term annealing of single cascades in tungsten at various primary-knock-on atom (PKA) energies and temperatures.

How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

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

Liu, Changzheng; Oak Ridge National Lab.; Lin, Zhenhong

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market sharemore » variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Here, continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.« less

How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

DOE PAGES

Liu, Changzheng; Oak Ridge National Lab.; Lin, Zhenhong; ...

2016-12-08

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market sharemore » variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Here, continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.« less

Cluster expansion modeling and Monte Carlo simulation of alnico 5–7 permanent magnets

DOE PAGES

Nguyen, Manh Cuong; Zhao, Xin; Wang, Cai -Zhuang; ...

2015-03-05

The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5–7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5–7 at atomistic and nano scales. The alnico 5–7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at lowmore » temperature. The boundary between these two phases is quite sharp (~2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. In addition, a small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5–7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. Furthermore, the results from our Monte Carlo simulations are consistent with available experimental results.« less

Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

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

Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James

2013-12-14

Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. Moremore » recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.« less

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.

2012-11-01

A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.

Monte Carlo simulation of a simple gene network yields new evolutionary insights.

PubMed

Andrecut, M; Cloud, D; Kauffman, S A

2008-02-07

Monte Carlo simulations of a genetic toggle switch show that its behavior can be more complex than analytic models would suggest. We show here that as a result of the interplay between frequent and infrequent reaction events, such a switch can have more stable states than an analytic model would predict, and that the number and character of these states depend to a large extent on the propensity of transcription factors to bind to and dissociate from promoters. The effects of gene duplications differ even more; in analytic models, these seem to result in the disappearance of bi-stability and thus a loss of the switching function, but a Monte Carlo simulation shows that they can result in the appearance of new stable states without the loss of old ones, and thus in an increase of the complexity of the switch's behavior which may facilitate the evolution of new cellular functions. These differences are of interest with respect to the evolution of gene networks, particularly in clonal lines of cancer cells, where the duplication of active genes is an extremely common event, and often seems to result in the appearance of viable new cellular phenotypes.

Learning About Ares I from Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Hanson, John M.; Hall, Charlie E.

2008-01-01

This paper addresses Monte Carlo simulation analyses that are being conducted to understand the behavior of the Ares I launch vehicle, and to assist with its design. After describing the simulation and modeling of Ares I, the paper addresses the process used to determine what simulations are necessary, and the parameters that are varied in order to understand how the Ares I vehicle will behave in flight. Outputs of these simulations furnish a significant group of design customers with data needed for the development of Ares I and of the Orion spacecraft that will ride atop Ares I. After listing the customers, examples of many of the outputs are described. Products discussed in this paper include those that support structural loads analysis, aerothermal analysis, flight control design, failure/abort analysis, determination of flight performance reserve, examination of orbit insertion accuracy, determination of the Upper Stage impact footprint, analysis of stage separation, analysis of launch probability, analysis of first stage recovery, thrust vector control and reaction control system design, liftoff drift analysis, communications analysis, umbilical release, acoustics, and design of jettison systems.

Risk assessment predictions of open dumping area after closure using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Pauzi, Nur Irfah Mohd; Radhi, Mohd Shahril Mat; Omar, Husaini

2017-10-01

Currently, there are many abandoned open dumping areas that were left without any proper mitigation measures. These open dumping areas could pose serious hazard to human and pollute the environment. The objective of this paper is to determine the risk assessment at the open dumping area after they has been closed using Monte Carlo Simulation method. The risk assessment exercise is conducted at the Kuala Lumpur dumping area. The rapid urbanisation of Kuala Lumpur coupled with increase in population lead to increase in waste generation. It leads to more dumping/landfill area in Kuala Lumpur. The first stage of this study involve the assessment of the dumping area and samples collections. It followed by measurement of settlement of dumping area using oedometer. The risk of the settlement is predicted using Monte Carlo simulation method. Monte Carlo simulation calculates the risk and the long-term settlement. The model simulation result shows that risk level of the Kuala Lumpur open dumping area ranges between Level III to Level IV i.e. between medium risk to high risk. These settlement (ΔH) is between 3 meters to 7 meters. Since the risk is between medium to high, it requires mitigation measures such as replacing the top waste soil with new sandy gravel soil. This will increase the strength of the soil and reduce the settlement.

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit

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

Badal, Andreu; Badano, Aldo

Purpose: It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). Methods: A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDA programming model (NVIDIA Corporation, Santa Clara, CA). Results: An outline of the new code and a sample x-raymore » imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. Conclusions: The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.« less

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

PubMed

Pothoczki, Szilvia; Temleitner, László; Pusztai, László

2014-02-07

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

The Cherenkov Telescope Array production system for Monte Carlo simulations and analysis

NASA Astrophysics Data System (ADS)

Arrabito, L.; Bernloehr, K.; Bregeon, J.; Cumani, P.; Hassan, T.; Haupt, A.; Maier, G.; Moralejo, A.; Neyroud, N.; pre="for the"> CTA Consortium, DIRAC Consortium,

2017-10-01

The Cherenkov Telescope Array (CTA), an array of many tens of Imaging Atmospheric Cherenkov Telescopes deployed on an unprecedented scale, is the next-generation instrument in the field of very high energy gamma-ray astronomy. An average data stream of about 0.9 GB/s for about 1300 hours of observation per year is expected, therefore resulting in 4 PB of raw data per year and a total of 27 PB/year, including archive and data processing. The start of CTA operation is foreseen in 2018 and it will last about 30 years. The installation of the first telescopes in the two selected locations (Paranal, Chile and La Palma, Spain) will start in 2017. In order to select the best site candidate to host CTA telescopes (in the Northern and in the Southern hemispheres), massive Monte Carlo simulations have been performed since 2012. Once the two sites have been selected, we have started new Monte Carlo simulations to determine the optimal array layout with respect to the obtained sensitivity. Taking into account that CTA may be finally composed of 7 different telescope types coming in 3 different sizes, many different combinations of telescope position and multiplicity as a function of the telescope type have been proposed. This last Monte Carlo campaign represented a huge computational effort, since several hundreds of telescope positions have been simulated, while for future instrument response function simulations, only the operating telescopes will be considered. In particular, during the last 18 months, about 2 PB of Monte Carlo data have been produced and processed with different analysis chains, with a corresponding overall CPU consumption of about 125 M HS06 hours. In these proceedings, we describe the employed computing model, based on the use of grid resources, as well as the production system setup, which relies on the DIRAC interware. Finally, we present the envisaged evolutions of the CTA production system for the off-line data processing during CTA operations and

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

2017-01-01

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

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.

Radiative interactions in chemically reacting compressible nozzle flows using Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Liu, J.; Tiwari, Surendra N.

1994-01-01

The two-dimensional spatially elliptic Navier-Stokes equations have been used to investigate the radiative interactions in chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The radiative heat transfer term in the energy equation is simulated using the Monte Carlo method (MCM). The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The spectral correlation has been considered in the Monte Carlo formulations. Results obtained demonstrate that the effect of radiation on the flow field is minimal but its effect on the wall heat transfer is significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and the nozzle size on the radiative and conductive wall fluxes.

Using Monte Carlo Simulation to Prioritize Key Maritime Environmental Impacts of Port Infrastructure

NASA Astrophysics Data System (ADS)

Perez Lespier, L. M.; Long, S.; Shoberg, T.

2016-12-01

This study creates a Monte Carlo simulation model to prioritize key indicators of environmental impacts resulting from maritime port infrastructure. Data inputs are derived from LandSat imagery, government databases, and industry reports to create the simulation. Results are validated using subject matter experts and compared with those returned from time-series regression to determine goodness of fit. The Port of Prince Rupert, Canada is used as the location for the study.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

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

PubMed

Mobit, P

2002-01-01

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

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

NASA Astrophysics Data System (ADS)

Freitag, Marc Dewi

2013-02-01

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

Monte Carlo model of light transport in multi-layered tubular organs

NASA Astrophysics Data System (ADS)

Zhang, Yunyao; Zhu, Jingping; Zhang, Ning

2017-02-01

We present a Monte Carlo static light migration model (Endo-MCML) to simulate endoscopic optical spectroscopy for tubular organs such as esophagus and colon. The model employs multi-layered hollow cylinder which emitting and receiving light both from the inner boundary to meet the conditions of endoscopy. Inhomogeneous sphere can be added in tissue layers to model cancer or other abnormal changes. The 3D light distribution and exit angle would be recorded as results. The accuracy of the model has been verified by Multi-layered Monte Carlo(MCML) method and NIRFAST. This model can be used for the forward modeling of light transport during endoscopically diffuse optical spectroscopy, light scattering spectroscopy, reflectance spectroscopy and other static optical detection or imaging technologies.

Kinetic Monte Carlo simulations of nucleation and growth in electrodeposition.

PubMed

Guo, Lian; Radisic, Aleksandar; Searson, Peter C

2005-12-22

Nucleation and growth during bulk electrodeposition is studied using kinetic Monte Carlo (KMC) simulations. Ion transport in solution is modeled using Brownian dynamics, and the kinetics of nucleation and growth are dependent on the probabilities of metal-on-substrate and metal-on-metal deposition. Using this approach, we make no assumptions about the nucleation rate, island density, or island distribution. The influence of the attachment probabilities and concentration on the time-dependent island density and current transients is reported. Various models have been assessed by recovering the nucleation rate and island density from the current-time transients.

Monte Carlo simulation of the back-diffusion of electrons in nitrogen

NASA Astrophysics Data System (ADS)

Radmilović-Radjenović, M.; Nina, A.; Nikitović, Ž.

2009-01-01

In this paper, the process of back-diffusion in nitrogen is studied by means of Monte Carlo simulations. In particular we analyze the influence of different aspects of back-diffusion in order to simplify the models of plasma displays, low pressure gas breakdown and detectors of high energy particles. The obtained simulation results show that the escape coefficient depends strongly on the reflection coefficient and the initial energy of electrons. It was also found that the back-diffusion range and number of collisions before returning to the cathode in nitrogen are smaller than those in argon for similar conditions.

Geometrical Monte Carlo simulation of atmospheric turbulence

NASA Astrophysics Data System (ADS)

Yuksel, Demet; Yuksel, Heba

2013-09-01

Atmospheric turbulence has a significant impact on the quality of a laser beam propagating through the atmosphere over long distances. Turbulence causes intensity scintillation and beam wander from propagation through turbulent eddies of varying sizes and refractive index. This can severely impair the operation of target designation and Free-Space Optical (FSO) communications systems. In addition, experimenting on an FSO communication system is rather tedious and difficult. The interferences of plentiful elements affect the result and cause the experimental outcomes to have bigger error variance margins than they are supposed to have. Especially when we go into the stronger turbulence regimes the simulation and analysis of the turbulence induced beams require delicate attention. We propose a new geometrical model to assess the phase shift of a laser beam propagating through turbulence. The atmosphere along the laser beam propagation path will be modeled as a spatial distribution of spherical bubbles with refractive index discontinuity calculated from a Gaussian distribution with the mean value being the index of air. For each statistical representation of the atmosphere, the path of rays will be analyzed using geometrical optics. These Monte Carlo techniques will assess the phase shift as a summation of the phases that arrive at the same point at the receiver. Accordingly, there would be dark and bright spots at the receiver that give an idea regarding the intensity pattern without having to solve the wave equation. The Monte Carlo analysis will be compared with the predictions of wave theory.

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

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

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Monte Carlo simulations of coherent backscatter for identification of the optical coefficients of biological tissues in vivo

NASA Astrophysics Data System (ADS)

Eddowes, M. H.; Mills, T. N.; Delpy, D. T.

1995-05-01

A Monte Carlo model of light backscattered from turbid media has been used to simulate the effects of weak localization in biological tissues. A validation technique is used that implies that for the scattering and absorption coefficients and for refractive index mismatches found in tissues, the Monte Carlo method is likely to provide more accurate results than the methods previously used. The model also has the ability to simulate the effects of various illumination profiles and other laboratory-imposed conditions. A curve-fitting routine has been developed that might be used to extract the optical coefficients from the angular intensity profiles seen in experiments on turbid biological tissues, data that could be obtained in vivo.

Multi-Conformation Monte Carlo: A Method for Introducing Flexibility in Efficient Simulations of Many-Protein Systems.

PubMed

Prytkova, Vera; Heyden, Matthias; Khago, Domarin; Freites, J Alfredo; Butts, Carter T; Martin, Rachel W; Tobias, Douglas J

2016-08-25

We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.

Development of a Monte Carlo Simulation for APD-Based PET Detectors Using a Continuous Scintillating Crystal

NASA Astrophysics Data System (ADS)

Clowes, P.; Mccallum, S.; Welch, A.

2006-10-01

We are currently developing a multilayer avalanche photodiode (APD)-based detector for use in positron emission tomography (PET), which utilizes thin continuous crystals. In this paper, we developed a Monte Carlo-based simulation to aid in the design of such detectors. We measured the performance of a detector comprising a single thin continuous crystal (3.1 mm times 9.5 mm times 9.5 mm) of lutetium yttrium ortho-silicate (LYSO) and an APD array (4times4) elements; each element 1.6 mm2 and on a 2.3 mm pitch. We showed that a spatial resolution of better than 2.12 mm is achievable throughout the crystal provided that we adopt a Statistics Based Positioning (SBP) Algorithm. We then used Monte Carlo simulation to model the behavior of the detector. The accuracy of the Monte Carlo simulation was verified by comparing measured and simulated parent datasets (PDS) for the SBP algorithm. These datasets consisted of data for point sources at 49 positions uniformly distributed over the detector area. We also calculated the noise in the detector circuit and verified this value by measurement. The noise value was included in the simulation. We show that the performance of the simulation closely matches the measured performance. The simulations were extended to investigate the effect of different noise levels on positioning accuracy. This paper showed that if modest improvements could be made in the circuit noise then positioning accuracy would be greatly improved. In summary, we have developed a model that can be used to simulate the performance of a variety of APD-based continuous crystal PET detectors

Conditional Monte Carlo randomization tests for regression models.

PubMed

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

SCOUT: A Fast Monte-Carlo Modeling Tool of Scintillation Camera Output

PubMed Central

Hunter, William C. J.; Barrett, Harrison H.; Lewellen, Thomas K.; Miyaoka, Robert S.; Muzi, John P.; Li, Xiaoli; McDougald, Wendy; MacDonald, Lawrence R.

2011-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:22072297

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.

Accelerated rescaling of single Monte Carlo simulation runs with the Graphics Processing Unit (GPU).

PubMed

Yang, Owen; Choi, Bernard

2013-01-01

To interpret fiber-based and camera-based measurements of remitted light from biological tissues, researchers typically use analytical models, such as the diffusion approximation to light transport theory, or stochastic models, such as Monte Carlo modeling. To achieve rapid (ideally real-time) measurement of tissue optical properties, especially in clinical situations, there is a critical need to accelerate Monte Carlo simulation runs. In this manuscript, we report on our approach using the Graphics Processing Unit (GPU) to accelerate rescaling of single Monte Carlo runs to calculate rapidly diffuse reflectance values for different sets of tissue optical properties. We selected MATLAB to enable non-specialists in C and CUDA-based programming to use the generated open-source code. We developed a software package with four abstraction layers. To calculate a set of diffuse reflectance values from a simulated tissue with homogeneous optical properties, our rescaling GPU-based approach achieves a reduction in computation time of several orders of magnitude as compared to other GPU-based approaches. Specifically, our GPU-based approach generated a diffuse reflectance value in 0.08ms. The transfer time from CPU to GPU memory currently is a limiting factor with GPU-based calculations. However, for calculation of multiple diffuse reflectance values, our GPU-based approach still can lead to processing that is ~3400 times faster than other GPU-based approaches.

Monte Carlo simulation methodology for the reliabilty of aircraft structures under damage tolerance considerations

NASA Astrophysics Data System (ADS)

Rambalakos, Andreas

Current federal aviation regulations in the United States and around the world mandate the need for aircraft structures to meet damage tolerance requirements through out the service life. These requirements imply that the damaged aircraft structure must maintain adequate residual strength in order to sustain its integrity that is accomplished by a continuous inspection program. The multifold objective of this research is to develop a methodology based on a direct Monte Carlo simulation process and to assess the reliability of aircraft structures. Initially, the structure is modeled as a parallel system with active redundancy comprised of elements with uncorrelated (statistically independent) strengths and subjected to an equal load distribution. Closed form expressions for the system capacity cumulative distribution function (CDF) are developed by expanding the current expression for the capacity CDF of a parallel system comprised by three elements to a parallel system comprised with up to six elements. These newly developed expressions will be used to check the accuracy of the implementation of a Monte Carlo simulation algorithm to determine the probability of failure of a parallel system comprised of an arbitrary number of statistically independent elements. The second objective of this work is to compute the probability of failure of a fuselage skin lap joint under static load conditions through a Monte Carlo simulation scheme by utilizing the residual strength of the fasteners subjected to various initial load distributions and then subjected to a new unequal load distribution resulting from subsequent fastener sequential failures. The final and main objective of this thesis is to present a methodology for computing the resulting gradual deterioration of the reliability of an aircraft structural component by employing a direct Monte Carlo simulation approach. The uncertainties associated with the time to crack initiation, the probability of crack detection, the

Predicting absorption and dispersion in acoustics by direct simulation Monte Carlo: Quantum and classical models for molecular relaxation.

PubMed

Hanford, Amanda D; O'Connor, Patrick D; Anderson, James B; Long, Lyle N

2008-06-01

In the current study, real gas effects in the propagation of sound waves are simulated using the direct simulation Monte Carlo method for a wide range of frequencies. This particle method allows for treatment of acoustic phenomena at high Knudsen numbers, corresponding to low densities and a high ratio of the molecular mean free path to wavelength. Different methods to model the internal degrees of freedom of diatomic molecules and the exchange of translational, rotational and vibrational energies in collisions are employed in the current simulations of a diatomic gas. One of these methods is the fully classical rigid-rotor/harmonic-oscillator model for rotation and vibration. A second method takes into account the discrete quantum energy levels for vibration with the closely spaced rotational levels classically treated. This method gives a more realistic representation of the internal structure of diatomic and polyatomic molecules. Applications of these methods are investigated in diatomic nitrogen gas in order to study the propagation of sound and its attenuation and dispersion along with their dependence on temperature. With the direct simulation method, significant deviations from continuum predictions are also observed for high Knudsen number flows.

Stationkeeping Monte Carlo Simulation for the James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Dichmann, Donald J.; Alberding, Cassandra M.; Yu, Wayne H.

2014-01-01

The James Webb Space Telescope (JWST) is scheduled to launch in 2018 into a Libration Point Orbit (LPO) around the Sun-Earth/Moon (SEM) L2 point, with a planned mission lifetime of 10.5 years after a six-month transfer to the mission orbit. This paper discusses our approach to Stationkeeping (SK) maneuver planning to determine an adequate SK delta-V budget. The SK maneuver planning for JWST is made challenging by two factors: JWST has a large Sunshield, and JWST will be repointed regularly producing significant changes in Solar Radiation Pressure (SRP). To accurately model SRP we employ the Solar Pressure and Drag (SPAD) tool, which uses ray tracing to accurately compute SRP force as a function of attitude. As an additional challenge, the future JWST observation schedule will not be known at the time of SK maneuver planning. Thus there will be significant variation in SRP between SK maneuvers, and the future variation in SRP is unknown. We have enhanced an earlier SK simulation to create a Monte Carlo simulation that incorporates random draws for uncertainties that affect the budget, including random draws of the observation schedule. Each SK maneuver is planned to optimize delta-V magnitude, subject to constraints on spacecraft pointing. We report the results of the Monte Carlo simulations and discuss possible improvements during flight operations to reduce the SK delta-V budget.

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

PubMed

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

2015-03-01

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

Monte Carlo simulations in Nuclear Medicine

NASA Astrophysics Data System (ADS)

Loudos, George K.

2007-11-01

Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

Simulating complex atomistic processes: On-the-fly kinetic Monte Carlo scheme with selective active volumes

NASA Astrophysics Data System (ADS)

Xu, Haixuan; Osetsky, Yury N.; Stoller, Roger E.

2011-10-01

An accelerated atomistic kinetic Monte Carlo (KMC) approach for evolving complex atomistic structures has been developed. The method incorporates on-the-fly calculations of transition states (TSs) with a scheme for defining active volumes (AVs) in an off-lattice (relaxed) system. In contrast to conventional KMC models that require all reactions to be predetermined, this approach is self-evolving and any physically relevant motion or reaction may occur. Application of this self-evolving atomistic kinetic Monte Carlo (SEAK-MC) approach is illustrated by predicting the evolution of a complex defect configuration obtained in a molecular dynamics (MD) simulation of a displacement cascade in Fe. Over much longer times, it was shown that interstitial clusters interacting with other defects may change their structure, e.g., from glissile to sessile configuration. The direct comparison with MD modeling confirms the atomistic fidelity of the approach, while the longer time simulation demonstrates the unique capability of the model.

SPH/N-Body simulations of small (D = 10km) asteroidal breakups and improved parametric relations for Monte-Carlo collisional models

NASA Astrophysics Data System (ADS)

Ševeček, P.; Brož, M.; Nesvorný, D.; Enke, B.; Durda, D.; Walsh, K.; Richardson, D. C.

2017-11-01

We report on our study of asteroidal breakups, i.e. fragmentations of targets, subsequent gravitational reaccumulation and formation of small asteroid families. We focused on parent bodies with diameters Dpb = 10km . Simulations were performed with a smoothed-particle hydrodynamics (SPH) code combined with an efficient N-body integrator. We assumed various projectile sizes, impact velocities and impact angles (125 runs in total). Resulting size-frequency distributions are significantly different from scaled-down simulations with Dpb = 100km targets (Durda et al., 2007). We derive new parametric relations describing fragment distributions, suitable for Monte-Carlo collisional models. We also characterize velocity fields and angular distributions of fragments, which can be used as initial conditions for N-body simulations of small asteroid families. Finally, we discuss a number of uncertainties related to SPH simulations.

Flexible Charged Macromolecules on Mixed Fluid Lipid Membranes: Theory and Monte Carlo Simulations

PubMed Central

Tzlil, Shelly; Ben-Shaul, Avinoam

2005-01-01

Fluid membranes containing charged lipids enhance binding of oppositely charged proteins by mobilizing these lipids into the interaction zone, overcoming the concomitant entropic losses due to lipid segregation and lower conformational freedom upon macromolecule adsorption. We study this energetic-entropic interplay using Monte Carlo simulations and theory. Our model system consists of a flexible cationic polyelectrolyte, interacting, via Debye-Hückel and short-ranged repulsive potentials, with membranes containing neutral lipids, 1% tetravalent, and 10% (or 1%) monovalent anionic lipids. Adsorption onto a fluid membrane is invariably stronger than to an equally charged frozen or uniform membrane. Although monovalent lipids may suffice for binding rigid macromolecules, polyvalent counter-lipids (e.g., phosphatidylinositol 4,5 bisphosphate), whose entropy loss upon localization is negligible, are crucial for binding flexible macromolecules, which lose conformational entropy upon adsorption. Extending Rosenbluth's Monte Carlo scheme we directly simulate polymer adsorption on fluid membranes. Yet, we argue that similar information could be derived from a biased superposition of quenched membrane simulations. Using a simple cell model we account for surface concentration effects, and show that the average adsorption probabilities on annealed and quenched membranes coincide at vanishing surface concentrations. We discuss the relevance of our model to the electrostatic-switch mechanism of, e.g., the myristoylated alanine-rich C kinase substrate protein. PMID:16126828

Carrier trajectory tracking equations for Simple-band Monte Carlo simulation of avalanche multiplication processes

NASA Astrophysics Data System (ADS)

Ong, J. S. L.; Charin, C.; Leong, J. H.

2017-12-01

Avalanche photodiodes (APDs) with steep electric field gradients generally have low excess noise that arises from carrier multiplication within the internal gain of the devices, and the Monte Carlo (MC) method is among popular device simulation tools for such devices. However, there are few articles relating to carrier trajectory modeling in MC models for such devices. In this work, a set of electric-field-gradient-dependent carrier trajectory tracking equations are developed and used to update the positions of carriers along the path during Simple-band Monte Carlo (SMC) simulations of APDs with non-uniform electric fields. The mean gain and excess noise results obtained from the SMC model employing these equations show good agreement with the results reported for a series of silicon diodes, including a p+n diode with steep electric field gradients. These results confirm the validity and demonstrate the feasibility of the trajectory tracking equations applied in SMC models for simulating mean gain and excess noise in APDs with non-uniform electric fields. Also, the simulation results of mean gain, excess noise, and carrier ionization positions obtained from the SMC model of this work agree well with those of the conventional SMC model employing the concept of a uniform electric field within a carrier free-flight. These results demonstrate that the electric field variation within a carrier free-flight has an insignificant effect on the predicted mean gain and excess noise results. Therefore, both the SMC model of this work and the conventional SMC model can be used to predict the mean gain and excess noise in APDs with highly non-uniform electric fields.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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.

From force-fields to photons: MD simulations of dye-labeled nucleic acids and Monte Carlo modeling of FRET

NASA Astrophysics Data System (ADS)

Goldner, Lori

2012-02-01

Fluorescence resonance energy transfer (FRET) is a powerful technique for understanding the structural fluctuations and transformations of RNA, DNA and proteins. Molecular dynamics (MD) simulations provide a window into the nature of these fluctuations on a different, faster, time scale. We use Monte Carlo methods to model and compare FRET data from dye-labeled RNA with what might be predicted from the MD simulation. With a few notable exceptions, the contribution of fluorophore and linker dynamics to these FRET measurements has not been investigated. We include the dynamics of the ground state dyes and linkers in our study of a 16mer double-stranded RNA. Water is included explicitly in the simulation. Cyanine dyes are attached at either the 3' or 5' ends with a 3 carbon linker, and differences in labeling schemes are discussed.[4pt] Work done in collaboration with Peker Milas, Benjamin D. Gamari, and Louis Parrot.

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

Monte Carlo simulation of nonadiabatic expansion in cometary atmospheres - Halley

NASA Astrophysics Data System (ADS)

Hodges, R. R.

1990-02-01

Monte Carlo methods developed for the characterization of velocity-dependent collision processes and ballistic transports in planetary exospheres form the basis of the present computer simulation of icy comet atmospheres, which iteratively undertakes the simultaneous determination of velocity distribution for five neutral species (water, together with suprathermal OH, H2, O, and H) in a flow regime varying from the hydrodynamic to the ballistic. Experimental data from the neutral mass spectrometer carried by Giotto for its March, 1986 encounter with Halley are compared with a model atmosphere.

Monte Carlo Simulations of Arterial Imaging with Optical Coherence Tomography

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

Amendt, P.; Estabrook, K.; Everett, M.

2000-02-01

The laser-tissue interaction code LATIS [London et al., Appl. Optics 36, 9068 ( 1998)] is used to analyze photon scattering histories representative of optical coherence tomography (OCT) experiment performed at Lawrence Livermore National Laboratory. Monte Carlo photonics with Henyey-Greenstein anisotropic scattering is implemented and used to simulate signal discrimination of intravascular structure. An analytic model is developed and used to obtain a scaling law relation for optimization of the OCT signal and to validate Monte Carlo photonics. The appropriateness of the Henyey-Greenstein phase function is studied by direct comparison with more detailed Mie scattering theory using an ensemble of sphericalmore » dielectric scatterers. Modest differences are found between the two prescriptions for describing photon angular scattering in tissue. In particular, the Mie scattering phase functions provide less overall reflectance signal but more signal contrast compared to the Henyey-Greenstein formulation.« less

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.

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.

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

USDA-ARS?s Scientific Manuscript database

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

Evaluation of effective dose with chest digital tomosynthesis system using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Kim, Dohyeon; Jo, Byungdu; Lee, Youngjin; Park, Su-Jin; Lee, Dong-Hoon; Kim, Hee-Joung

2015-03-01

Chest digital tomosynthesis (CDT) system has recently been introduced and studied. This system offers the potential to be a substantial improvement over conventional chest radiography for the lung nodule detection and reduces the radiation dose with limited angles. PC-based Monte Carlo program (PCXMC) simulation toolkit (STUK, Helsinki, Finland) is widely used to evaluate radiation dose in CDT system. However, this toolkit has two significant limits. Although PCXMC is not possible to describe a model for every individual patient and does not describe the accurate X-ray beam spectrum, Geant4 Application for Tomographic Emission (GATE) simulation describes the various size of phantom for individual patient and proper X-ray spectrum. However, few studies have been conducted to evaluate effective dose in CDT system with the Monte Carlo simulation toolkit using GATE. The purpose of this study was to evaluate effective dose in virtual infant chest phantom of posterior-anterior (PA) view in CDT system using GATE simulation. We obtained the effective dose at different tube angles by applying dose actor function in GATE simulation which was commonly used to obtain the medical radiation dosimetry. The results indicated that GATE simulation was useful to estimate distribution of absorbed dose. Consequently, we obtained the acceptable distribution of effective dose at each projection. These results indicated that GATE simulation can be alternative method of calculating effective dose in CDT applications.

Shielding analyses of an AB-BNCT facility using Monte Carlo simulations and simplified methods

NASA Astrophysics Data System (ADS)

Lai, Bo-Lun; Sheu, Rong-Jiun

2017-09-01

Accurate Monte Carlo simulations and simplified methods were used to investigate the shielding requirements of a hypothetical accelerator-based boron neutron capture therapy (AB-BNCT) facility that included an accelerator room and a patient treatment room. The epithermal neutron beam for BNCT purpose was generated by coupling a neutron production target with a specially designed beam shaping assembly (BSA), which was embedded in the partition wall between the two rooms. Neutrons were produced from a beryllium target bombarded by 1-mA 30-MeV protons. The MCNP6-generated surface sources around all the exterior surfaces of the BSA were established to facilitate repeated Monte Carlo shielding calculations. In addition, three simplified models based on a point-source line-of-sight approximation were developed and their predictions were compared with the reference Monte Carlo results. The comparison determined which model resulted in better dose estimation, forming the basis of future design activities for the first ABBNCT facility in Taiwan.

SCOUT: a fast Monte-Carlo modeling tool of scintillation camera output†

PubMed Central

Hunter, William C J; Barrett, Harrison H.; Muzi, John P.; McDougald, Wendy; MacDonald, Lawrence R.; Miyaoka, Robert S.; Lewellen, Thomas K.

2013-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout of a scintillation camera. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:23640136

Direct calculation of liquid-vapor phase equilibria from transition matrix Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Errington, Jeffrey R.

2003-06-01

An approach for directly determining the liquid-vapor phase equilibrium of a model system at any temperature along the coexistence line is described. The method relies on transition matrix Monte Carlo ideas developed by Fitzgerald, Picard, and Silver [Europhys. Lett. 46, 282 (1999)]. During a Monte Carlo simulation attempted transitions between states along the Markov chain are monitored as opposed to tracking the number of times the chain visits a given state as is done in conventional simulations. Data collection is highly efficient and very precise results are obtained. The method is implemented in both the grand canonical and isothermal-isobaric ensemble. The main result from a simulation conducted at a given temperature is a density probability distribution for a range of densities that includes both liquid and vapor states. Vapor pressures and coexisting densities are calculated in a straightforward manner from the probability distribution. The approach is demonstrated with the Lennard-Jones fluid. Coexistence properties are directly calculated at temperatures spanning from the triple point to the critical point.

Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources

NASA Astrophysics Data System (ADS)

Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi

2017-01-01

Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.

Validation of a Monte Carlo simulation of the Inveon PET scanner using GATE

NASA Astrophysics Data System (ADS)

Lu, Lijun; Zhang, Houjin; Bian, Zhaoying; Ma, Jianhua; Feng, Qiangjin; Chen, Wufan

2016-08-01

The purpose of this study is to validate the application of GATE (Geant4 Application for Tomographic Emission) Monte Carlo simulation toolkit in order to model the performance characteristics of Siemens Inveon small animal PET system. The simulation results were validated against experimental/published data in accordance with the NEMA NU-4 2008 protocol for standardized evaluation of spatial resolution, sensitivity, scatter fraction (SF) and noise equivalent counting rate (NECR) of a preclinical PET system. An agreement of less than 18% was obtained between the radial, tangential and axial spatial resolutions of the simulated and experimental results. The simulated peak NECR of mouse-size phantom agreed with the experimental result, while for the rat-size phantom simulated value was higher than experimental result. The simulated and experimental SFs of mouse- and rat- size phantom both reached an agreement of less than 2%. It has been shown the feasibility of our GATE model to accurately simulate, within certain limits, all major performance characteristics of Inveon PET system.

Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer

PubMed Central

Harriss-Phillips, W M; Bezak, E; Yeoh, E K

2011-01-01

Objective A temporal Monte Carlo tumour growth and radiotherapy effect model (HYP-RT) simulating hypoxia in head and neck cancer has been developed and used to analyse parameters influencing cell kill during conventionally fractionated radiotherapy. The model was designed to simulate individual cell division up to 108 cells, while incorporating radiobiological effects, including accelerated repopulation and reoxygenation during treatment. Method Reoxygenation of hypoxic tumours has been modelled using randomised increments of oxygen to tumour cells after each treatment fraction. The process of accelerated repopulation has been modelled by increasing the symmetrical stem cell division probability. Both phenomena were onset immediately or after a number of weeks of simulated treatment. Results The extra dose required to control (total cell kill) hypoxic vs oxic tumours was 15–25% (8–20 Gy for 5×2 Gy per week) depending on the timing of accelerated repopulation onset. Reoxygenation of hypoxic tumours resulted in resensitisation and reduction in total dose required by approximately 10%, depending on the time of onset. When modelled simultaneously, accelerated repopulation and reoxygenation affected cell kill in hypoxic tumours in a similar manner to when the phenomena were modelled individually; however, the degree was altered, with non-additive results. Simulation results were in good agreement with standard linear quadratic theory; however, differed for more complex comparisons where hypoxia, reoxygenation as well as accelerated repopulation effects were considered. Conclusion Simulations have quantitatively confirmed the need for patient individualisation in radiotherapy for hypoxic head and neck tumours, and have shown the benefits of modelling complex and dynamic processes using Monte Carlo methods. PMID:21933980

Calculation of out-of-field dose distribution in carbon-ion radiotherapy by Monte Carlo simulation.

PubMed

Yonai, Shunsuke; Matsufuji, Naruhiro; Namba, Masao

2012-08-01

Recent radiotherapy technologies including carbon-ion radiotherapy can improve the dose concentration in the target volume, thereby not only reducing side effects in organs at risk but also the secondary cancer risk within or near the irradiation field. However, secondary cancer risk in the low-dose region is considered to be non-negligible, especially for younger patients. To achieve a dose estimation of the whole body of each patient receiving carbon-ion radiotherapy, which is essential for risk assessment and epidemiological studies, Monte Carlo simulation plays an important role because the treatment planning system can provide dose distribution only in∕near the irradiation field and the measured data are limited. However, validation of Monte Carlo simulations is necessary. The primary purpose of this study was to establish a calculation method using the Monte Carlo code to estimate the dose and quality factor in the body and to validate the proposed method by comparison with experimental data. Furthermore, we show the distributions of dose equivalent in a phantom and identify the partial contribution of each radiation type. We proposed a calculation method based on a Monte Carlo simulation using the PHITS code to estimate absorbed dose, dose equivalent, and dose-averaged quality factor by using the Q(L)-L relationship based on the ICRP 60 recommendation. The values obtained by this method in modeling the passive beam line at the Heavy-Ion Medical Accelerator in Chiba were compared with our previously measured data. It was shown that our calculation model can estimate the measured value within a factor of 2, which included not only the uncertainty of this calculation method but also those regarding the assumptions of the geometrical modeling and the PHITS code. Also, we showed the differences in the doses and the partial contributions of each radiation type between passive and active carbon-ion beams using this calculation method. These results indicated that

Exploring glycogen biosynthesis through Monte Carlo simulation.

PubMed

Zhang, Peng; Nada, Sharif S; Tan, Xinle; Deng, Bin; Sullivan, Mitchell A; Gilbert, Robert G

2018-05-08

Glycogen, a complex branched polymer of glucose (average chain length ~10 monomer units), is the blood-sugar reservoir in humans and other animals. Certain aspects of its molecular structure relevant to its biological functions are currently unamenable to experimental exploration. Knowledge of these is needed to develop future models for quantitative data-fitting to obtain mechanistic understanding of the biosynthetic processes that give rise to glycogen structure. Monte Carlo simulations of the biosynthesis of this structure with realistic macromolecular parameters reveal how chain growth and stoppage (the latter assumed to be through both the action of glycogen branching enzyme and other degradative enzymes, and by hindrance) control structural features. The simulated chain-length, pair-distance and radial density distributions agree semi-quantitatively with the limited available data. The simulations indicate that a steady state in molecular structure and size is rapidly obtained, that molecular density reaches a maximum near the center of the particle (not at the periphery, as is the case with dendrimers), and that particle size is controlled by both enzyme activity and hindrance. This knowledge will aid in the understanding of diabetes (loss of blood-sugar control), which has been found to involve subtle differences in glycogen molecular structure. Copyright © 2018 Elsevier B.V. All rights reserved.

Probabilistic biosphere modeling for the long-term safety assessment of geological disposal facilities for radioactive waste using first- and second-order Monte Carlo simulation.

PubMed

Ciecior, Willy; Röhlig, Klaus-Jürgen; Kirchner, Gerald

2018-10-01

In the present paper, deterministic as well as first- and second-order probabilistic biosphere modeling approaches are compared. Furthermore, the sensitivity of the influence of the probability distribution function shape (empirical distribution functions and fitted lognormal probability functions) representing the aleatory uncertainty (also called variability) of a radioecological model parameter as well as the role of interacting parameters are studied. Differences in the shape of the output distributions for the biosphere dose conversion factor from first-order Monte Carlo uncertainty analysis using empirical and fitted lognormal distribution functions for input parameters suggest that a lognormal approximation is possibly not always an adequate representation of the aleatory uncertainty of a radioecological parameter. Concerning the comparison of the impact of aleatory and epistemic parameter uncertainty on the biosphere dose conversion factor, the latter here is described using uncertain moments (mean, variance) while the distribution itself represents the aleatory uncertainty of the parameter. From the results obtained, the solution space of second-order Monte Carlo simulation is much larger than that from first-order Monte Carlo simulation. Therefore, the influence of epistemic uncertainty of a radioecological parameter on the output result is much larger than that one caused by its aleatory uncertainty. Parameter interactions are only of significant influence in the upper percentiles of the distribution of results as well as only in the region of the upper percentiles of the model parameters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Monte Carlo simulations support non-Cerenkov radioluminescence production in tissue

NASA Astrophysics Data System (ADS)

Ackerman, Nicole L.; Boschi, Federico; Spinelli, Antonello E.

2017-08-01

There is experimental evidence for the production of non-Cerenkov radioluminescence in a variety of materials, including tissue. We constructed a Geant4 Monte Carlo simulation of the radiation from P32 and Tc99m interacting in chicken breast and used experimental imaging data to model a scintillation-like emission. The same radioluminescence spectrum is visible from both isotopes and cannot otherwise be explained through fluorescence or filter miscalibration. We conclude that chicken breast has a near-infrared scintillation-like response with a light yield three orders of magnitude smaller than BGO.

Heterogeneity in ultrathin films simulated by Monte Carlo method

NASA Astrophysics Data System (ADS)

Sun, Jiebing; Hannon, James B.; Kellogg, Gary L.; Pohl, Karsten

2007-03-01

The 3D composition profile of ultra-thin Pd films on Cu(001) has been experimentally determined using low energy electron microscopy (LEEM).^[1] Quantitative measurements of the alloy concentration profile near steps show that the Pd distribution in the 3^rd layer is heterogeneous due to step overgrowth during Pd deposition. Interestingly, the Pd distribution in the 2^nd layer is also heterogeneous, and appears to be correlated with the distribution in the 1^st layer. We describe Monte Carlo simulations that show that correlation is due to Cu-Pd attraction, and that the 2^nd layer Pd is, in fact, laterally equilibrated. By comparing measured and simulated concentration profiles, we can estimate this attraction within a simple bond counting model. [1] J. B. Hannon, J. Sun, K. Pohl, G. L. Kellogg, Phys. Rev. Lett. 96, 246103 (2006)

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; Hurtado, John E.

2011-01-01

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Dendritic growth shapes in kinetic Monte Carlo models

NASA Astrophysics Data System (ADS)

Krumwiede, Tim R.; Schulze, Tim P.

2017-02-01

For the most part, the study of dendritic crystal growth has focused on continuum models featuring surface energies that yield six pointed dendrites. In such models, the growth shape is a function of the surface energy anisotropy, and recent work has shown that considering a broader class of anisotropies yields a correspondingly richer set of growth morphologies. Motivated by this work, we generalize nanoscale models of dendritic growth based on kinetic Monte Carlo simulation. In particular, we examine the effects of extending the truncation radius for atomic interactions in a bond-counting model. This is done by calculating the model’s corresponding surface energy and equilibrium shape, as well as by running KMC simulations to obtain nanodendritic growth shapes. Additionally, we compare the effects of extending the interaction radius in bond-counting models to that of extending the number of terms retained in the cubic harmonic expansion of surface energy anisotropy in the context of continuum models.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

Investigation of attenuation correction in SPECT using textural features, Monte Carlo simulations, and computational anthropomorphic models.

PubMed

Spirou, Spiridon V; Papadimitroulas, Panagiotis; Liakou, Paraskevi; Georgoulias, Panagiotis; Loudos, George

2015-09-01

To present and evaluate a new methodology to investigate the effect of attenuation correction (AC) in single-photon emission computed tomography (SPECT) using textural features analysis, Monte Carlo techniques, and a computational anthropomorphic model. The GATE Monte Carlo toolkit was used to simulate SPECT experiments using the XCAT computational anthropomorphic model, filled with a realistic biodistribution of (99m)Tc-N-DBODC. The simulated gamma camera was the Siemens ECAM Dual-Head, equipped with a parallel hole lead collimator, with an image resolution of 3.54 × 3.54 mm(2). Thirty-six equispaced camera positions, spanning a full 360° arc, were simulated. Projections were calculated after applying a ± 20% energy window or after eliminating all scattered photons. The activity of the radioisotope was reconstructed using the MLEM algorithm. Photon attenuation was accounted for by calculating the radiological pathlength in a perpendicular line from the center of each voxel to the gamma camera. Twenty-two textural features were calculated on each slice, with and without AC, using 16 and 64 gray levels. A mask was used to identify only those pixels that belonged to each organ. Twelve of the 22 features showed almost no dependence on AC, irrespective of the organ involved. In both the heart and the liver, the mean and SD were the features most affected by AC. In the liver, six features were affected by AC only on some slices. Depending on the slice, skewness decreased by 22-34% with AC, kurtosis by 35-50%, long-run emphasis mean by 71-91%, and long-run emphasis range by 62-95%. In contrast, gray-level non-uniformity mean increased by 78-218% compared with the value without AC and run percentage mean by 51-159%. These results were not affected by the number of gray levels (16 vs. 64) or the data used for reconstruction: with the energy window or without scattered photons. The mean and SD were the main features affected by AC. In the heart, no other feature was

VARIAN CLINAC 6 MeV Photon Spectra Unfolding using a Monte Carlo Meshed Model

NASA Astrophysics Data System (ADS)

Morató, S.; Juste, B.; Miró, R.; Verdú, G.

2017-09-01

Energy spectrum is the best descriptive function to determine photon beam quality of a Medical Linear Accelerator (LinAc). The use of realistic photon spectra in Monte Carlo simulations has a great importance to obtain precise dose calculations in Radiotherapy Treatment Planning (RTP). Reconstruction of photon spectra emitted by medical accelerators from measured depth dose distributions in a water cube is an important tool for commissioning a Monte Carlo treatment planning system. Regarding this, the reconstruction problem is an inverse radiation transport function which is ill conditioned and its solution may become unstable due to small perturbations in the input data. This paper presents a more stable spectral reconstruction method which can be used to provide an independent confirmation of source models for a given machine without any prior knowledge of the spectral distribution. Monte Carlo models used in this work are built with unstructured meshes to simulate with realism the linear accelerator head geometry.

Experimental benchmarking of a Monte Carlo dose simulation code for pediatric CT

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Yoshizumi, Terry; Colsher, James G.; Jones, Robert P.; Frush, Donald P.

2007-03-01

In recent years, there has been a desire to reduce CT radiation dose to children because of their susceptibility and prolonged risk for cancer induction. Concerns arise, however, as to the impact of dose reduction on image quality and thus potentially on diagnostic accuracy. To study the dose and image quality relationship, we are developing a simulation code to calculate organ dose in pediatric CT patients. To benchmark this code, a cylindrical phantom was built to represent a pediatric torso, which allows measurements of dose distributions from its center to its periphery. Dose distributions for axial CT scans were measured on a 64-slice multidetector CT (MDCT) scanner (GE Healthcare, Chalfont St. Giles, UK). The same measurements were simulated using a Monte Carlo code (PENELOPE, Universitat de Barcelona) with the applicable CT geometry including bowtie filter. The deviations between simulated and measured dose values were generally within 5%. To our knowledge, this work is one of the first attempts to compare measured radial dose distributions on a cylindrical phantom with Monte Carlo simulated results. It provides a simple and effective method for benchmarking organ dose simulation codes and demonstrates the potential of Monte Carlo simulation for investigating the relationship between dose and image quality for pediatric CT patients.

Coupled particle-in-cell and Monte Carlo transport modeling of intense radiographic sources

NASA Astrophysics Data System (ADS)

Rose, D. V.; Welch, D. R.; Oliver, B. V.; Clark, R. E.; Johnson, D. L.; Maenchen, J. E.; Menge, P. R.; Olson, C. L.; Rovang, D. C.

2002-03-01

Dose-rate calculations for intense electron-beam diodes using particle-in-cell (PIC) simulations along with Monte Carlo electron/photon transport calculations are presented. The electromagnetic PIC simulations are used to model the dynamic operation of the rod-pinch and immersed-B diodes. These simulations include algorithms for tracking electron scattering and energy loss in dense materials. The positions and momenta of photons created in these materials are recorded and separate Monte Carlo calculations are used to transport the photons to determine the dose in far-field detectors. These combined calculations are used to determine radiographer equations (dose scaling as a function of diode current and voltage) that are compared directly with measured dose rates obtained on the SABRE generator at Sandia National Laboratories.

Conserved directed percolation: exact quasistationary distribution of small systems and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

César Mansur Filho, Júlio; Dickman, Ronald

2011-05-01

We study symmetric sleepy random walkers, a model exhibiting an absorbing-state phase transition in the conserved directed percolation (CDP) universality class. Unlike most examples of this class studied previously, this model possesses a continuously variable control parameter, facilitating analysis of critical properties. We study the model using two complementary approaches: analysis of the numerically exact quasistationary (QS) probability distribution on rings of up to 22 sites, and Monte Carlo simulation of systems of up to 32 000 sites. The resulting estimates for critical exponents β, \\beta /\

OWL: A scalable Monte Carlo simulation suite for finite-temperature study of materials

NASA Astrophysics Data System (ADS)

Li, Ying Wai; Yuk, Simuck F.; Cooper, Valentino R.; Eisenbach, Markus; Odbadrakh, Khorgolkhuu

The OWL suite is a simulation package for performing large-scale Monte Carlo simulations. Its object-oriented, modular design enables it to interface with various external packages for energy evaluations. It is therefore applicable to study the finite-temperature properties for a wide range of systems: from simple classical spin models to materials where the energy is evaluated by ab initio methods. This scheme not only allows for the study of thermodynamic properties based on first-principles statistical mechanics, it also provides a means for massive, multi-level parallelism to fully exploit the capacity of modern heterogeneous computer architectures. We will demonstrate how improved strong and weak scaling is achieved by employing novel, parallel and scalable Monte Carlo algorithms, as well as the applications of OWL to a few selected frontier materials research problems. This research was supported by the Office of Science of the Department of Energy under contract DE-AC05-00OR22725.

Phase transition in nonuniform Josephson arrays: Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Lozovik, Yu. E.; Pomirchy, L. M.

1994-01-01

Disordered 2D system with Josephson interactions is considered. Disordered XY-model describes the granular films, Josephson arrays etc. Two types of disorder are analyzed: (1) randomly diluted system: Josephson coupling constants J ij are equal to J with probability p or zero (bond percolation problem); (2) coupling constants J ij are positive and distributed randomly and uniformly in some interval either including the vicinity of zero or apart from it. These systems are simulated by Monte Carlo method. Behaviour of potential energy, specific heat, phase correlation function and helicity modulus are analyzed. The phase diagram of the diluted system in T c-p plane is obtained.

Monte Carlo modeling and meteor showers

NASA Technical Reports Server (NTRS)

Kulikova, N. V.

1987-01-01

Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.

Risk analysis of gravity dam instability using credibility theory Monte Carlo simulation model.

PubMed

Xin, Cao; Chongshi, Gu

2016-01-01

Risk analysis of gravity dam stability involves complicated uncertainty in many design parameters and measured data. Stability failure risk ratio described jointly by probability and possibility has deficiency in characterization of influence of fuzzy factors and representation of the likelihood of risk occurrence in practical engineering. In this article, credibility theory is applied into stability failure risk analysis of gravity dam. Stability of gravity dam is viewed as a hybrid event considering both fuzziness and randomness of failure criterion, design parameters and measured data. Credibility distribution function is conducted as a novel way to represent uncertainty of influence factors of gravity dam stability. And combining with Monte Carlo simulation, corresponding calculation method and procedure are proposed. Based on a dam section, a detailed application of the modeling approach on risk calculation of both dam foundation and double sliding surfaces is provided. The results show that, the present method is feasible to be applied on analysis of stability failure risk for gravity dams. The risk assessment obtained can reflect influence of both sorts of uncertainty, and is suitable as an index value.

Self-learning Monte Carlo method

DOE PAGES

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

2017-01-04

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

Microstructure engineering of Pt-Al alloy thin films through Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Harris, R. A.; Terblans, J. J.; Swart, H. C.

2014-06-01

A kinetic algorithm, based on the regular solution model, was used in conjunction with the Monte Carlo method to simulate the evolution of a micro-scaled thin film system during exposure to a high temperature environment. Pt-Al thin films were prepared via electron beam physical vapor deposition (EB-PVD) with an atomic concentration ratio of Pt63:Al37. These films were heat treated at an annealing temperature of 400 °C for 16 and 49 minutes. Scanning Auger Microscopy (SAM) (PHI 700) was used to obtain elemental maps while sputtering through the thin films. Simulations were run for the same annealing temperatures and thin-film composition. From these simulations theoretical depth profiles and simulated microstructures were obtained. These were compared to the experimentally measured depth profiles and elemental maps.

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

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

2004-01-01

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

Monte-Carlo simulation of defect-cluster nucleation in metals during irradiation

NASA Astrophysics Data System (ADS)

Nakasuji, Toshiki; Morishita, Kazunori; Ruan, Xiaoyong

2017-02-01

A multiscale modeling approach was applied to investigate the nucleation process of CRPs (copper rich precipitates, i.e., copper-vacancy clusters) in α-Fe containing 1 at.% Cu during irradiation. Monte-Carlo simulations were performed to investigate the nucleation process, with the rate theory equation analysis to evaluate the concentration of displacement defects, along with the molecular dynamics technique to know CRP thermal stabilities in advance. Our MC simulations showed that there is long incubation period at first, followed by a rapid growth of CRPs. The incubation period depends on irradiation conditions such as the damage rate and temperature. CRP's composition during nucleation varies with time. The copper content of CRPs shows relatively rich at first, and then becomes poorer as the precipitate size increases. A widely-accepted model of CRP nucleation process is finally proposed.

Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method

NASA Technical Reports Server (NTRS)

Boyd, Iain D.

1991-01-01

A new model is proposed for energy transfer between the vibrational and translational modes for use in the direct simulation Monte Carlo method (DSMC). The model modifies the Landau-Teller theory for a harmonic oscillator and the rate transition is related to an experimental correlation for the vibrational relaxation time. Assessment of the model is made with respect to three different computations: relaxation in a heat bath, a one-dimensional shock wave, and hypersonic flow over a two-dimensional wedge. These studies verify that the model achieves detailed balance, and excellent agreement with experimental data is obtained in the shock wave calculation. The wedge flow computation reveals that the usual phenomenological method for simulating vibrational nonequilibrium in the DSMC technique predicts much higher vibrational temperatures in the wake region.

Monte Carlo Studies of Phase Separation in Compressible 2-dim Ising Models

NASA Astrophysics Data System (ADS)

Mitchell, S. J.; Landau, D. P.

2006-03-01

Using high resolution Monte Carlo simulations, we study time-dependent domain growth in compressible 2-dim ferromagnetic (s=1/2) Ising models with continuous spin positions and spin-exchange moves [1]. Spins interact with slightly modified Lennard-Jones potentials, and we consider a model with no lattice mismatch and one with 4% mismatch. For comparison, we repeat calculations for the rigid Ising model [2]. For all models, large systems (512^2) and long times (10^ 6 MCS) are examined over multiple runs, and the growth exponent is measured in the asymptotic scaling regime. For the rigid model and the compressible model with no lattice mismatch, the growth exponent is consistent with the theoretically expected value of 1/3 [1] for Model B type growth. However, we find that non-zero lattice mismatch has a significant and unexpected effect on the growth behavior.Supported by the NSF.[1] D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, second ed. (Cambridge University Press, New York, 2005).[2] J. Amar, F. Sullivan, and R.D. Mountain, Phys. Rev. B 37, 196 (1988).

Monte Carlo simulation of EAS generated by 10(14) - 10(16) eV protons

NASA Technical Reports Server (NTRS)

Fenyves, E. J.; Yunn, B. C.; Stanev, T.

1985-01-01

Detailed Monte Carlo simulations of extensive air showers to be detected by the Homestake Surface Underground Telescope and other similar detectors located at sea level and mountain altitudes have been performed for 10 to the 14th power to 10 to the 16th power eV primary energies. The results of these Monte Carlo calculations will provide an opportunity to compare the experimental data with different models for the composition and spectra of primaries and for the development of air showers. The results obtained for extensive air showers generated by 10 to the 14th power to 10 to the 16th power eV primary protons are reported.

A reappraisal of drug release laws using Monte Carlo simulations: the prevalence of the Weibull function.

PubMed

Kosmidis, Kosmas; Argyrakis, Panos; Macheras, Panos

2003-07-01

To verify the Higuchi law and study the drug release from cylindrical and spherical matrices by means of Monte Carlo computer simulation. A one-dimensional matrix, based on the theoretical assumptions of the derivation of the Higuchi law, was simulated and its time evolution was monitored. Cylindrical and spherical three-dimensional lattices were simulated with sites at the boundary of the lattice having been denoted as leak sites. Particles were allowed to move inside it using the random walk model. Excluded volume interactions between the particles was assumed. We have monitored the system time evolution for different lattice sizes and different initial particle concentrations. The Higuchi law was verified using the Monte Carlo technique in a one-dimensional lattice. It was found that Fickian drug release from cylindrical matrices can be approximated nicely with the Weibull function. A simple linear relation between the Weibull function parameters and the specific surface of the system was found. Drug release from a matrix, as a result of a diffusion process assuming excluded volume interactions between the drug molecules, can be described using a Weibull function. This model, although approximate and semiempirical, has the benefit of providing a simple physical connection between the model parameters and the system geometry, which was something missing from other semiempirical models.

Multi-pass Monte Carlo simulation method in nuclear transmutations.

PubMed

Mateescu, Liviu; Kadambi, N Prasad; Ravindra, Nuggehalli M

2016-12-01

Monte Carlo methods, in their direct brute simulation incarnation, bring realistic results if the involved probabilities, be they geometrical or otherwise, remain constant for the duration of the simulation. However, there are physical setups where the evolution of the simulation represents a modification of the simulated system itself. Chief among such evolving simulated systems are the activation/transmutation setups. That is, the simulation starts with a given set of probabilities, which are determined by the geometry of the system, the components and by the microscopic interaction cross-sections. However, the relative weight of the components of the system changes along with the steps of the simulation. A natural measure would be adjusting probabilities after every step of the simulation. On the other hand, the physical system has typically a number of components of the order of Avogadro's number, usually 10 25 or 10 26 members. A simulation step changes the characteristics for just a few of these members; a probability will therefore shift by a quantity of 1/10 25 . Such a change cannot be accounted for within a simulation, because then the simulation should have then a number of at least 10 28 steps in order to have some significance. This is not feasible, of course. For our computing devices, a simulation of one million steps is comfortable, but a further order of magnitude becomes too big a stretch for the computing resources. We propose here a method of dealing with the changing probabilities, leading to the increasing of the precision. This method is intended as a fast approximating approach, and also as a simple introduction (for the benefit of students) in the very branched subject of Monte Carlo simulations vis-à-vis nuclear reactors. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Kinetic Monte Carlo simulations of scintillation processes in NaI(Tl)

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

Kerisit, Sebastien N.; Wang, Zhiguo; Williams, Richard

2014-04-26

Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this work to simulate the kinetics of scintillation for a range of temperaturesmore » and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.« less

Kinetic Monte Carlo Simulations of Scintillation Processes in NaI(Tl)

NASA Astrophysics Data System (ADS)

Kerisit, Sebastien; Wang, Zhiguo; Williams, Richard T.; Grim, Joel Q.; Gao, Fei

2014-04-01

Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this paper to simulate the kinetics of scintillation for a range of temperatures and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.

A Monte Carlo Simulation of Prompt Gamma Emission from Fission Fragments

NASA Astrophysics Data System (ADS)

Regnier, D.; Litaize, O.; Serot, O.

2013-03-01

The prompt fission gamma spectra and multiplicities are investigated through the Monte Carlo code FIFRELIN which is developed at the Cadarache CEA research center. Knowing the fully accelerated fragment properties, their de-excitation is simulated through a cascade of neutron, gamma and/or electron emissions. This paper presents the recent developments in the FIFRELIN code and the results obtained on the spontaneous fission of 252Cf. Concerning the decay cascades simulation, a fully Hauser-Feshbach model is compared with a previous one using a Weisskopf spectrum for neutron emission. A particular attention is paid to the treatment of the neutron/gamma competition. Calculations lead using different level density and gamma strength function models show significant discrepancies of the slope of the gamma spectra at high energy. The underestimation of the prompt gamma spectra obtained regardless our de-excitation cascade modeling choice is discussed. This discrepancy is probably linked to an underestimation of the post-neutron fragments spin in our calculation.

Monte Carlo simulation of Alaska wolf survival

NASA Astrophysics Data System (ADS)

Feingold, S. J.

1996-02-01

Alaskan wolves live in a harsh climate and are hunted intensively. Penna's biological aging code, using Monte Carlo methods, has been adapted to simulate wolf survival. It was run on the case in which hunting causes the disruption of wolves' social structure. Social disruption was shown to increase the number of deaths occurring at a given level of hunting. For high levels of social disruption, the population did not survive.

A Monte Carlo model for the internal dosimetry of choroid plexuses in nuclear medicine procedures.

PubMed

Amato, Ernesto; Cicone, Francesco; Auditore, Lucrezia; Baldari, Sergio; Prior, John O; Gnesin, Silvano

2018-05-01

Choroid plexuses are vascular structures located in the brain ventricles, showing specific uptake of some diagnostic and therapeutic radiopharmaceuticals currently under clinical investigation, such as integrin-binding arginine-glycine-aspartic acid (RGD) peptides. No specific geometry for choroid plexuses has been implemented in commercially available software for internal dosimetry. The aims of the present study were to assess the dependence of absorbed dose to the choroid plexuses on the organ geometry implemented in Monte Carlo simulations, and to propose an analytical model for the internal dosimetry of these structures for 18 F, 64 Cu, 67 Cu, 68 Ga, 90 Y, 131 I and 177 Lu nuclides. A GAMOS Monte Carlo simulation based on direct organ segmentation was taken as the gold standard to validate a second simulation based on a simplified geometrical model of the choroid plexuses. Both simulations were compared with the OLINDA/EXM sphere model. The gold standard and the simplified geometrical model gave similar dosimetry results (dose difference < 3.5%), indicating that the latter can be considered as a satisfactory approximation of the real geometry. In contrast, the sphere model systematically overestimated the absorbed dose compared to both Monte Carlo models (range: 4-50% dose difference), depending on the isotope energy and organ mass. Therefore, the simplified geometric model was adopted to introduce an analytical approach for choroid plexuses dosimetry in the mass range 2-16 g. The proposed model enables the estimation of the choroid plexuses dose by a simple bi-parametric function, once the organ mass and the residence time of the radiopharmaceutical under investigation are provided. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Dosimetry of gamma chamber blood irradiator using PAGAT gel dosimeter and Monte Carlo simulations

PubMed Central

Mohammadyari, Parvin; Zehtabian, Mehdi; Sina, Sedigheh; Tavasoli, Ali Reza

2014-01-01

Currently, the use of blood irradiation for inactivating pathogenic microbes in infected blood products and preventing graft‐versus‐host disease (GVHD) in immune suppressed patients is greater than ever before. In these systems, dose distribution and uniformity are two important concepts that should be checked. In this study, dosimetry of the gamma chamber blood irradiator model Gammacell 3000 Elan was performed by several dosimeter methods including thermoluminescence dosimeters (TLD), PAGAT gel dosimetry, and Monte Carlo simulations using MCNP4C code. The gel dosimeter was put inside a glass phantom and the TL dosimeters were placed on its surface, and the phantom was then irradiated for 5 min and 27 sec. The dose values at each point inside the vials were obtained from the magnetic resonance imaging of the phantom. For Monte Carlo simulations, all components of the irradiator were simulated and the dose values in a fine cubical lattice were calculated using tally F6. This study shows that PAGAT gel dosimetry results are in close agreement with the results of TL dosimetry, Monte Carlo simulations, and the results given by the vendor, and the percentage difference between the different methods is less than 4% at different points inside the phantom. According to the results obtained in this study, PAGAT gel dosimetry is a reliable method for dosimetry of the blood irradiator. The major advantage of this kind of dosimetry is that it is capable of 3D dose calculation. PACS number: 87.53.Bn PMID:24423829

Density matrix Monte Carlo modeling of quantum cascade lasers

NASA Astrophysics Data System (ADS)

Jirauschek, Christian

2017-10-01

By including elements of the density matrix formalism, the semiclassical ensemble Monte Carlo method for carrier transport is extended to incorporate incoherent tunneling, known to play an important role in quantum cascade lasers (QCLs). In particular, this effect dominates electron transport across thick injection barriers, which are frequently used in terahertz QCL designs. A self-consistent model for quantum mechanical dephasing is implemented, eliminating the need for empirical simulation parameters. Our modeling approach is validated against available experimental data for different types of terahertz QCL designs.

Simulation of variation of apparent resistivity in resistivity surveys using finite difference modelling with Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Aguirre, E. E.; Karchewski, B.

2017-12-01

DC resistivity surveying is a geophysical method that quantifies the electrical properties of the subsurface of the earth by applying a source current between two electrodes and measuring potential differences between electrodes at known distances from the source. Analytical solutions for a homogeneous half-space and simple subsurface models are well known, as the former is used to define the concept of apparent resistivity. However, in situ properties are heterogeneous meaning that simple analytical models are only an approximation, and ignoring such heterogeneity can lead to misinterpretation of survey results costing time and money. The present study examines the extent to which random variations in electrical properties (i.e. electrical conductivity) affect potential difference readings and therefore apparent resistivities, relative to an assumed homogeneous subsurface model. We simulate the DC resistivity survey using a Finite Difference (FD) approximation of an appropriate simplification of Maxwell's equations implemented in Matlab. Electrical resistivity values at each node in the simulation were defined as random variables with a given mean and variance, and are assumed to follow a log-normal distribution. The Monte Carlo analysis for a given variance of electrical resistivity was performed until the mean and variance in potential difference measured at the surface converged. Finally, we used the simulation results to examine the relationship between variance in resistivity and variation in surface potential difference (or apparent resistivity) relative to a homogeneous half-space model. For relatively low values of standard deviation in the material properties (<10% of mean), we observed a linear correlation between variance of resistivity and variance in apparent resistivity.

Markov Chain Monte Carlo Estimation of Item Parameters for the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

de la Torre, Jimmy; Stark, Stephen; Chernyshenko, Oleksandr S.

2006-01-01

The authors present a Markov Chain Monte Carlo (MCMC) parameter estimation procedure for the generalized graded unfolding model (GGUM) and compare it to the marginal maximum likelihood (MML) approach implemented in the GGUM2000 computer program, using simulated and real personality data. In the simulation study, test length, number of response…

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

A Monte Carlo Ray Tracing Model to Improve Simulations of Solar-Induced Chlorophyll Fluorescence Radiative Transfer

NASA Astrophysics Data System (ADS)

Halubok, M.; Gu, L.; Yang, Z. L.

2017-12-01

A model of light transport in a three-dimensional vegetation canopy is being designed and evaluated. The model employs Monte Carlo ray tracing technique which offers simple yet rigorous approach of quantifying the photon transport in a plant canopy. This method involves simulation of a chain of scattering and absorption events incurred by a photon on its path from the light source. Implementation of weighting mechanism helps avoid `all-or-nothing' type of interaction between a photon packet and a canopy element, i.e. at each interaction a photon packet is split into three parts, namely, reflected, transmitted and absorbed, instead of assuming complete absorption, reflection or transmission. Canopy scenes in the model are represented by a number of polygons with specified set of reflectances and transmittances. The performance of the model is being evaluated through comparison against established plant canopy reflectance models, such as 3D Radiosity-Graphics combined model which calculates bidirectional reflectance distribution function of a 3D canopy scene. This photon transport model is to be coupled to a leaf level solar-induced chlorophyll fluorescence (SIF) model with the aim of further advancing of accuracy of the modeled SIF, which, in its turn, has a potential of improving our predictive capability of terrestrial carbon uptake.

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

SPH/N-body simulations of small (D = 10 km) monolithic asteroidal breakups and improved parametric relations for Monte-Carlo collisional models

NASA Astrophysics Data System (ADS)

Ševecek, Pavel; Broz, Miroslav; Nesvorny, David; Durda, Daniel D.; Asphaug, Erik; Walsh, Kevin J.; Richardson, Derek C.

2016-10-01

Detailed models of asteroid collisions can yield important constrains for the evolution of the Main Asteroid Belt, but the respective parameter space is large and often unexplored. We thus performed a new set of simulations of asteroidal breakups, i.e. fragmentations of intact targets, subsequent gravitational reaccumulation and formation of small asteroid families, focusing on parent bodies with diameters D = 10 km.Simulations were performed with a smoothed-particle hydrodynamics (SPH) code (Benz & Asphaug 1994), combined with an efficient N-body integrator (Richardson et al. 2000). We assumed a number of projectile sizes, impact velocities and impact angles. The rheology used in the physical model does not include friction nor crushing; this allows for a direct comparison to results of Durda et al. (2007). Resulting size-frequency distributions are significantly different from scaled-down simulations with D = 100 km monolithic targets, although they may be even more different for pre-shattered targets.We derive new parametric relations describing fragment distributions, suitable for Monte-Carlo collisional models. We also characterize velocity fields and angular distributions of fragments, which can be used as initial conditions in N-body simulations of small asteroid families. Finally, we discuss various uncertainties related to SPH simulations.

APS undulator and wiggler sources: Monte-Carlo simulation

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

Xu, S.L.; Lai, B.; Viccaro, P.J.

1992-02-01

Standard insertion devices will be provided to each sector by the Advanced Photon Source. It is important to define the radiation characteristics of these general purpose devices. In this document,results of Monte-Carlo simulation are presented. These results, based on the SHADOW program, include the APS Undulator A (UA), Wiggler A (WA), and Wiggler B (WB).

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

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

Alcaraz, Olga; Trullàs, Joaquim, E-mail: quim.trullas@upc.edu; Tahara, Shuta

2016-09-07

The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å{sup −1} related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.

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.

Measuring Renyi entanglement entropy in quantum Monte Carlo simulations.

PubMed

Hastings, Matthew B; González, Iván; Kallin, Ann B; Melko, Roger G

2010-04-16

We develop a quantum Monte Carlo procedure, in the valence bond basis, to measure the Renyi entanglement entropy of a many-body ground state as the expectation value of a unitary Swap operator acting on two copies of the system. An improved estimator involving the ratio of Swap operators for different subregions enables convergence of the entropy in a simulation time polynomial in the system size. We demonstrate convergence of the Renyi entropy to exact results for a Heisenberg chain. Finally, we calculate the scaling of the Renyi entropy in the two-dimensional Heisenberg model and confirm that the Néel ground state obeys the expected area law for systems up to linear size L=32.

Calculation of dose distribution in compressible breast tissues using finite element modeling, Monte Carlo simulation and thermoluminescence dosimeters

NASA Astrophysics Data System (ADS)

Mohammadyari, Parvin; Faghihi, Reza; Mosleh-Shirazi, Mohammad Amin; Lotfi, Mehrzad; Rahim Hematiyan, Mohammad; Koontz, Craig; Meigooni, Ali S.

2015-12-01

Compression is a technique to immobilize the target or improve the dose distribution within the treatment volume during different irradiation techniques such as AccuBoost® brachytherapy. However, there is no systematic method for determination of dose distribution for uncompressed tissue after irradiation under compression. In this study, the mechanical behavior of breast tissue between compressed and uncompressed states was investigated. With that, a novel method was developed to determine the dose distribution in uncompressed tissue after irradiation of compressed breast tissue. Dosimetry was performed using two different methods, namely, Monte Carlo simulations using the MCNP5 code and measurements using thermoluminescent dosimeters (TLD). The displacement of the breast elements was simulated using a finite element model and calculated using ABAQUS software. From these results, the 3D dose distribution in uncompressed tissue was determined. The geometry of the model was constructed from magnetic resonance images of six different women volunteers. The mechanical properties were modeled by using the Mooney-Rivlin hyperelastic material model. Experimental dosimetry was performed by placing the TLD chips into the polyvinyl alcohol breast equivalent phantom. The results determined that the nodal displacements, due to the gravitational force and the 60 Newton compression forces (with 43% contraction in the loading direction and 37% expansion in the orthogonal direction) were determined. Finally, a comparison of the experimental data and the simulated data showed agreement within 11.5%  ±  5.9%.

Calculation of dose distribution in compressible breast tissues using finite element modeling, Monte Carlo simulation and thermoluminescence dosimeters.

PubMed

Mohammadyari, Parvin; Faghihi, Reza; Mosleh-Shirazi, Mohammad Amin; Lotfi, Mehrzad; Hematiyan, Mohammad Rahim; Koontz, Craig; Meigooni, Ali S

2015-12-07

Compression is a technique to immobilize the target or improve the dose distribution within the treatment volume during different irradiation techniques such as AccuBoost(®) brachytherapy. However, there is no systematic method for determination of dose distribution for uncompressed tissue after irradiation under compression. In this study, the mechanical behavior of breast tissue between compressed and uncompressed states was investigated. With that, a novel method was developed to determine the dose distribution in uncompressed tissue after irradiation of compressed breast tissue. Dosimetry was performed using two different methods, namely, Monte Carlo simulations using the MCNP5 code and measurements using thermoluminescent dosimeters (TLD). The displacement of the breast elements was simulated using a finite element model and calculated using ABAQUS software. From these results, the 3D dose distribution in uncompressed tissue was determined. The geometry of the model was constructed from magnetic resonance images of six different women volunteers. The mechanical properties were modeled by using the Mooney-Rivlin hyperelastic material model. Experimental dosimetry was performed by placing the TLD chips into the polyvinyl alcohol breast equivalent phantom. The results determined that the nodal displacements, due to the gravitational force and the 60 Newton compression forces (with 43% contraction in the loading direction and 37% expansion in the orthogonal direction) were determined. Finally, a comparison of the experimental data and the simulated data showed agreement within 11.5%  ±  5.9%.

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

PubMed Central

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

2017-01-01

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

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

From force-fields to photons: MD simulations of dye-labeled nucleic acids and Monte Carlo modeling of FRET

NASA Astrophysics Data System (ADS)

Milas, Peker; Gamari, Ben; Parrot, Louis; Buckman, Richard; Goldner, Lori

2011-11-01

Fluorescence resonance energy transfer (FRET) is a powerful experimental technique for understanding the structural fluctuations and transformations of RNA, DNA and proteins. Molecular dynamics (MD) simulations provide a window into the nature of these fluctuations on a faster time scale inaccessible to experiment. We use Monte Carlo methods to model and compare FRET data from dye-labeled RNA with what might be predicted from the MD simulation. With a few notable exceptions, the contribution of fluorophore and linker dynamics to these FRET measurements has not been investigated. We include the dynamics of the ground state dyes and linkers along with an explicit water solvent in our study of a 16mer double-stranded RNA. Cyanine dyes are attached at either the 3' or 5' ends with a three carbon linker, providing a basis for contrasting the dynamics of similar but not identical molecular structures.

Kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying

NASA Astrophysics Data System (ADS)

Kameya, Yuki

2017-06-01

A kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying is presented. The proposed two-dimensional model addresses the dynamics of nanoparticles in the vertical plane of a drying nanocolloid film. The gas-liquid interface movement due to solvent evaporation was controlled by a time-dependent chemical potential, and the resultant particle dynamics including Brownian diffusion and aggregate growth were calculated. Simulations were performed at various Peclet numbers defined based on the rate ratio of solvent evaporation and nanoparticle diffusion. At high Peclet numbers, nanoparticles accumulated at the top layer of the liquid film and eventually formed a skin layer, causing the formation of a particulate film with a densely packed structure. At low Peclet numbers, enhanced particle diffusion led to significant particle aggregation in the bulk colloid, and the resulting film structure became highly porous. The simulated results showed some typical characteristics of a drying nanocolloid that had been reported experimentally. Finally, the potential of the model as well as the remaining challenges are discussed.

Simulation modeling for the health care manager.

PubMed

Kennedy, Michael H

2009-01-01

This article addresses the use of simulation software to solve administrative problems faced by health care managers. Spreadsheet add-ins, process simulation software, and discrete event simulation software are available at a range of costs and complexity. All use the Monte Carlo method to realistically integrate probability distributions into models of the health care environment. Problems typically addressed by health care simulation modeling are facility planning, resource allocation, staffing, patient flow and wait time, routing and transportation, supply chain management, and process improvement.

Monte Carlo simulations of nematic and chiral nematic shells

NASA Astrophysics Data System (ADS)

Wand, Charlie R.; Bates, Martin A.

2015-01-01

We present a systematic Monte Carlo simulation study of thin nematic and cholesteric shells with planar anchoring using an off-lattice model. The results obtained using the simple model correspond with previously published results for lattice-based systems, with the number, type, and position of defects observed dependent on the shell thickness with four half-strength defects in a tetrahedral arrangement found in very thin shells and a pair of defects in a bipolar (boojum) configuration observed in thicker shells. A third intermediate defect configuration is occasionally observed for intermediate thickness shells, which is stabilized in noncentrosymmetric shells of nonuniform thickness. Chiral nematic (cholesteric) shells are investigated by including a chiral term in the potential. Decreasing the pitch of the chiral nematic leads to a twisted bipolar (chiral boojum) configuration with the director twist increasing from the inner to the outer surface.

Monte Carlo modeling of spatially complex wrist tissue for the optimization of optical pulse oximeters

NASA Astrophysics Data System (ADS)

Robinson, Mitchell; Butcher, Ryan; Coté, Gerard L.

2017-02-01

Monte Carlo modeling of photon propagation has been used in the examination of particular areas of the body to further enhance the understanding of light propagation through tissue. This work seeks to improve upon the established simulation methods through more accurate representations of the simulated tissues in the wrist as well as the characteristics of the light source. The Monte Carlo simulation program was developed using Matlab. Generation of different tissue domains, such as muscle, vasculature, and bone, was performed in Solidworks, where each domain was saved as a separate .stl file that was read into the program. The light source was altered to give considerations to both viewing angle of the simulated LED as well as the nominal diameter of the source. It is believed that the use of these more accurate models generates results that more closely match those seen in-vivo, and can be used to better guide the design of optical wrist-worn measurement devices.

An information-carrying and knowledge-producing molecular machine. A Monte-Carlo simulation.

PubMed

Kuhn, Christoph

2012-02-01

The concept called Knowledge is a measure of the quality of genetically transferred information. Its usefulness is demonstrated quantitatively in a Monte-Carlo simulation on critical steps in a origin of life model. The model describes the origin of a bio-like genetic apparatus by a long sequence of physical-chemical steps: it starts with the presence of a self-replicating oligomer and a specifically structured environment in time and space that allow for the formation of aggregates such as assembler-hairpins-devices and, at a later stage, an assembler-hairpins-enzyme device-a first translation machine.

Accuracy of Monte Carlo photon transport simulation in characterizing brachytherapy dosimeter energy-response artefacts.

PubMed

Das, R K; Li, Z; Perera, H; Williamson, J F

1996-06-01

Practical dosimeters in brachytherapy, such as thermoluminescent dosimeters (TLD) and diodes, are usually calibrated against low-energy megavoltage beams. To measure absolute dose rate near a brachytherapy source, it is necessary to establish the energy response of the detector relative to that of the calibration energy. The purpose of this paper is to assess the accuracy of Monte Carlo photon transport (MCPT) simulation in modelling the absolute detector response as a function of detector geometry and photon energy. We have exposed two different sizes of TLD-100 (LiF chips) and p-type silicon diode detectors to calibrated 60Co, HDR source (192Ir) and superficial x-ray beams. For the Scanditronix electron-field diode, the relative detector response, defined as the measured detector readings per measured unit of air kerma, varied from 38.46 V cGy-1 (40 kVp beam) to 6.22 V cGy-1 (60Co beam). Similarly for the large and small chips the same quantity varied from 2.08-3.02 nC cGy-1 and 0.171-0.244 nC cGy-1, respectively. Monte Carlo simulation was used to calculate the absorbed dose to the active volume of the detector per unit air kerma. If the Monte Carlo simulation is accurate, then the absolute detector response, which is defined as the measured detector reading per unit dose absorbed by the active detector volume, and is calculated by Monte Carlo simulation, should be a constant. For the diode, the absolute response is 5.86 +/- 0.15 (V cGy-1). For TLDs of size 3 x 3 x 1 mm3 the absolute response is 2.47 +/- 0.07 (nC cGy-1) and for TLDs of 1 x 1 x 1 mm3 it is 0.201 +/- 0.008 (nC cGy-1). From the above results we can conclude that the absolute response function of detectors (TLDs and diodes) is directly proportional to absorbed dose by the active volume of the detector and is independent of beam quality.

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

PubMed

Serebrinsky, Santiago A

2011-03-01

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

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

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

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

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

GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications

NASA Astrophysics Data System (ADS)

Lemaréchal, Yannick; Bert, Julien; Falconnet, Claire; Després, Philippe; Valeri, Antoine; Schick, Ulrike; Pradier, Olivier; Garcia, Marie-Paule; Boussion, Nicolas; Visvikis, Dimitris

2015-07-01

In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400  × 250  × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10-6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications.

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

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.

Play It Again: Teaching Statistics with Monte Carlo Simulation

ERIC Educational Resources Information Center

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…

Monte Carlo simulations of medical imaging modalities

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

Estes, G.P.

Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computermore » power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.« less

Self-Learning Monte Carlo Method

NASA Astrophysics Data System (ADS)

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

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

Miming the cancer-immune system competition by kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Lemarchand, Annie

2016-10-01

In order to mimic the interactions between cancer and the immune system at cell scale, we propose a minimal model of cell interactions that is similar to a chemical mechanism including autocatalytic steps. The cells are supposed to bear a quantity called activity that may increase during the interactions. The fluctuations of cell activity are controlled by a so-called thermostat. We develop a kinetic Monte Carlo algorithm to simulate the cell interactions and thermalization of cell activity. The model is able to reproduce the well-known behavior of tumors treated by immunotherapy: the first apparent elimination of the tumor by the immune system is followed by a long equilibrium period and the final escape of cancer from immunosurveillance.

Pediatric personalized CT-dosimetry Monte Carlo simulations, using computational phantoms

NASA Astrophysics Data System (ADS)

Papadimitroulas, P.; Kagadis, G. C.; Ploussi, A.; Kordolaimi, S.; Papamichail, D.; Karavasilis, E.; Syrgiamiotis, V.; Loudos, G.

2015-09-01

The last 40 years Monte Carlo (MC) simulations serve as a “gold standard” tool for a wide range of applications in the field of medical physics and tend to be essential in daily clinical practice. Regarding diagnostic imaging applications, such as computed tomography (CT), the assessment of deposited energy is of high interest, so as to better analyze the risks and the benefits of the procedure. The last few years a big effort is done towards personalized dosimetry, especially in pediatric applications. In the present study the GATE toolkit was used and computational pediatric phantoms have been modeled for the assessment of CT examinations dosimetry. The pediatric models used come from the XCAT and IT'IS series. The X-ray spectrum of a Brightspeed CT scanner was simulated and validated with experimental data. Specifically, a DCT-10 ionization chamber was irradiated twice using 120 kVp with 100 mAs and 200 mAs, for 1 sec in 1 central axial slice (thickness = 10mm). The absorbed dose was measured in air resulting in differences lower than 4% between the experimental and simulated data. The simulations were acquired using ˜1010 number of primaries in order to achieve low statistical uncertainties. Dose maps were also saved for quantification of the absorbed dose in several children critical organs during CT acquisition.

Monte-Carlo Geant4 numerical simulation of experiments at 247-MeV proton microscope

NASA Astrophysics Data System (ADS)

Kantsyrev, A. V.; Skoblyakov, A. V.; Bogdanov, A. V.; Golubev, A. A.; Shilkin, N. S.; Yuriev, D. S.; Mintsev, V. B.

2018-01-01

A radiographic facility for an investigation of fast dynamic processes with areal density of targets up to 5 g/cm2 is under development on the basis of high-current proton linear accelerator at the Institute for Nuclear Research (Troitsk, Russia). A virtual model of the proton microscope developed in a software toolkit Geant4 is presented in the article. Fullscale Monte-Carlo numerical simulation of static radiographic experiments at energy of a proton beam 247 MeV was performed. The results of simulation of proton radiography experiments with static model of shock-compressed xenon are presented. The results of visualization of copper and polymethyl methacrylate step wedges static targets also described.

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

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

Procassini, R.J.

1997-12-31

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

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

NASA Astrophysics Data System (ADS)

Li, Fusheng

Four key components with regards to Monte Carlo Library Least Squares (MCLLS) have been developed by the author. These include: a comprehensive and accurate Monte Carlo simulation code - CEARXRF5 with Differential Operators (DO) and coincidence sampling, Detector Response Function (DRF), an integrated Monte Carlo - Library Least-Squares (MCLLS) Graphical User Interface (GUI) visualization System (MCLLSPro) and a new reproducible and flexible benchmark experiment setup. All these developments or upgrades enable the MCLLS approach to be a useful and powerful tool for a tremendous variety of elemental analysis applications. CEARXRF, a comprehensive and accurate Monte Carlo code for simulating the total and individual library spectral responses of all elements, has been recently upgraded to version 5 by the author. The new version has several key improvements: input file format fully compatible with MCNP5, a new efficient general geometry tracking code, versatile source definitions, various variance reduction techniques (e.g. weight window mesh and splitting, stratifying sampling, etc.), a new cross section data storage and accessing method which improves the simulation speed by a factor of four and new cross section data, upgraded differential operators (DO) calculation capability, and also an updated coincidence sampling scheme which including K-L and L-L coincidence X-Rays, while keeping all the capabilities of the previous version. The new Differential Operators method is powerful for measurement sensitivity study and system optimization. For our Monte Carlo EDXRF elemental analysis system, it becomes an important technique for quantifying the matrix effect in near real time when combined with the MCLLS approach. An integrated visualization GUI system has been developed by the author to perform elemental analysis using iterated Library Least-Squares method for various samples when an initial guess is provided. This software was built on the Borland C++ Builder

Monte Carlo Simulations of the Kinetics of Protein Adsorption

NASA Astrophysics Data System (ADS)

Zhdanov, V. P.; Kasemo, B.

The past decade has been characterized by rapid progress in Monte Carlo simulations of protein folding in a solution. This review summarizes the main results obtained in the field, as a background to the major topic, namely corresponding advances in simulations of protein adsorption kinetics at solid-liquid interfaces. The latter occur via diffusion in the liquid towards the interface followed by actual adsorption, and subsequent irreversible conformational changes, resulting in more or less pronounced denaturation of the native protein structure. The conventional kinetic models describing these steps are based on the assumption that the denaturation transitions obey the first-order law with a single value of the denaturation rate constant kr. The validity of this assumption has been studied in recent lattice Monte Carlo simulations of denaturation of model protein-like molecules with different types of the monomer-monomer interactions. The results obtained indicate that, due to trapping in metastable states, (i) the transition of a molecule to the denatured state is usually nonexponential in time, i.e. it does not obey the first-order law, and (ii) the denaturation transitions of an ensemble of different molecules are characterized by different time scales, i.e. the denaturation process cannot be described by a single rate constant kr. One should, rather, introduce a distribution of values of this rate constant (physically, different values of kr reflect the fact that the transitions to the altered state occurs via different metastable states). The phenomenological kinetics of irreversible adsorption of proteins with and without a distribution of the denaturation rate constant values have been calculated in the limits where protein diffusion in the solution is, respectively, rapid or slow. In both cases, the adsorption kinetics with a distribution of kr are found to be close to those with a single-valued rate constant kr, provided that the average value of kr in

Multi-Subband Ensemble Monte Carlo simulations of scaled GAA MOSFETs

NASA Astrophysics Data System (ADS)

Donetti, L.; Sampedro, C.; Ruiz, F. G.; Godoy, A.; Gamiz, F.

2018-05-01

We developed a Multi-Subband Ensemble Monte Carlo simulator for non-planar devices, taking into account two-dimensional quantum confinement. It couples self-consistently the solution of the 3D Poisson equation, the 2D Schrödinger equation, and the 1D Boltzmann transport equation with the Ensemble Monte Carlo method. This simulator was employed to study MOS devices based on ultra-scaled Gate-All-Around Si nanowires with diameters in the range from 4 nm to 8 nm with gate length from 8 nm to 14 nm. We studied the output and transfer characteristics, interpreting the behavior in the sub-threshold region and in the ON state in terms of the spatial charge distribution and the mobility computed with the same simulator. We analyzed the results, highlighting the contribution of different valleys and subbands and the effect of the gate bias on the energy and velocity profiles. Finally the scaling behavior was studied, showing that only the devices with D = 4nm maintain a good control of the short channel effects down to the gate length of 8nm .

Model-Averaged ℓ1 Regularization using Markov Chain Monte Carlo Model Composition

PubMed Central

Fraley, Chris; Percival, Daniel

2014-01-01

Bayesian Model Averaging (BMA) is an effective technique for addressing model uncertainty in variable selection problems. However, current BMA approaches have computational difficulty dealing with data in which there are many more measurements (variables) than samples. This paper presents a method for combining ℓ1 regularization and Markov chain Monte Carlo model composition techniques for BMA. By treating the ℓ1 regularization path as a model space, we propose a method to resolve the model uncertainty issues arising in model averaging from solution path point selection. We show that this method is computationally and empirically effective for regression and classification in high-dimensional datasets. We apply our technique in simulations, as well as to some applications that arise in genomics. PMID:25642001

Monte Carlo simulation of zinc protoporphyrin fluorescence in the retina

NASA Astrophysics Data System (ADS)

Chen, Xiaoyan; Lane, Stephen

2010-02-01

We have used Monte Carlo simulation of autofluorescence in the retina to determine that noninvasive detection of nutritional iron deficiency is possible. Nutritional iron deficiency (which leads to iron deficiency anemia) affects more than 2 billion people worldwide, and there is an urgent need for a simple, noninvasive diagnostic test. Zinc protoporphyrin (ZPP) is a fluorescent compound that accumulates in red blood cells and is used as a biomarker for nutritional iron deficiency. We developed a computational model of the eye, using parameters that were identified either by literature search, or by direct experimental measurement to test the possibility of detecting ZPP non-invasively in retina. By incorporating fluorescence into Steven Jacques' original code for multi-layered tissue, we performed Monte Carlo simulation of fluorescence in the retina and determined that if the beam is not focused on a blood vessel in a neural retina layer or if part of light is hitting the vessel, ZPP fluorescence will be 10-200 times higher than background lipofuscin fluorescence coming from the retinal pigment epithelium (RPE) layer directly below. In addition we found that if the light can be focused entirely onto a blood vessel in the neural retina layer, the fluorescence signal comes only from ZPP. The fluorescence from layers below in this second situation does not contribute to the signal. Therefore, the possibility that a device could potentially be built and detect ZPP fluorescence in retina looks very promising.

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

PubMed

Liu, Y; Zheng, Y

2012-06-01

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

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

PubMed

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

2017-07-01

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

Nuclear reaction measurements on tissue-equivalent materials and GEANT4 Monte Carlo simulations for hadrontherapy

NASA Astrophysics Data System (ADS)

De Napoli, M.; Romano, F.; D'Urso, D.; Licciardello, T.; Agodi, C.; Candiano, G.; Cappuzzello, F.; Cirrone, G. A. P.; Cuttone, G.; Musumarra, A.; Pandola, L.; Scuderi, V.

2014-12-01

When a carbon beam interacts with human tissues, many secondary fragments are produced into the tumor region and the surrounding healthy tissues. Therefore, in hadrontherapy precise dose calculations require Monte Carlo tools equipped with complex nuclear reaction models. To get realistic predictions, however, simulation codes must be validated against experimental results; the wider the dataset is, the more the models are finely tuned. Since no fragmentation data for tissue-equivalent materials at Fermi energies are available in literature, we measured secondary fragments produced by the interaction of a 55.6 MeV u-1 12C beam with thick muscle and cortical bone targets. Three reaction models used by the Geant4 Monte Carlo code, the Binary Light Ions Cascade, the Quantum Molecular Dynamic and the Liege Intranuclear Cascade, have been benchmarked against the collected data. In this work we present the experimental results and we discuss the predictive power of the above mentioned models.

Multi-wavelength simulations of atmospheric radiation from Io with a 3-D spherical-shell backward Monte Carlo radiative transfer model

NASA Astrophysics Data System (ADS)

Gratiy, Sergey L.; Walker, Andrew C.; Levin, Deborah A.; Goldstein, David B.; Varghese, Philip L.; Trafton, Laurence M.; Moore, Chris H.

2010-05-01

Conflicting observations regarding the dominance of either sublimation or volcanism as the source of the atmosphere on Io and disparate reports on the extent of its spatial distribution and the absolute column abundance invite the development of detailed computational models capable of improving our understanding of Io's unique atmospheric structure and origin. Improving upon previous models, Walker et al. (Walker, A.C., Gratiy, S.L., Levin, D.A., Goldstein, D.B., Varghese, P.L., Trafton, L.M., Moore, C.H., Stewart, B. [2009]. Icarus) developed a fully 3-D global rarefied gas dynamics model of Io's atmosphere including both sublimation and volcanic sources of SO 2 gas. The fidelity of the model is tested by simulating remote observations at selected wavelength bands and comparing them to the corresponding astronomical observations of Io's atmosphere. The simulations are performed with a new 3-D spherical-shell radiative transfer code utilizing a backward Monte Carlo method. We present: (1) simulations of the mid-infrared disk-integrated spectra of Io's sunlit hemisphere at 19 μm, obtained with TEXES during 2001-2004; (2) simulations of disk-resolved images at Lyman- α obtained with the Hubble Space Telescope (HST), Space Telescope Imaging Spectrograph (STIS) during 1997-2001; and (3) disk-integrated simulations of emission line profiles in the millimeter wavelength range obtained with the IRAM-30 m telescope in October-November 1999. We found that the atmospheric model generally reproduces the longitudinal variation in band depth from the mid-infrared data; however, the best match is obtained when our simulation results are shifted ˜30° toward lower orbital longitudes. The simulations of Lyman- α images do not reproduce the mid-to-high latitude bright patches seen in the observations, suggesting that the model atmosphere sustains columns that are too high at those latitudes. The simulations of emission line profiles in the millimeter spectral region support

Monte Carlo technique for very large ising models

NASA Astrophysics Data System (ADS)

Kalle, C.; Winkelmann, V.

1982-08-01

Rebbi's multispin coding technique is improved and applied to the kinetic Ising model with size 600*600*600. We give the central part of our computer program (for a CDC Cyber 76), which will be helpful also in a simulation of smaller systems, and describe the other tricks necessary to go to large lattices. The magnetization M at T=1.4* T c is found to decay asymptotically as exp(-t/2.90) if t is measured in Monte Carlo steps per spin, and M( t = 0) = 1 initially.

Radial-based tail methods for Monte Carlo simulations of cylindrical interfaces

NASA Astrophysics Data System (ADS)

Goujon, Florent; Bêche, Bruno; Malfreyt, Patrice; Ghoufi, Aziz

2018-03-01

In this work, we implement for the first time the radial-based tail methods for Monte Carlo simulations of cylindrical interfaces. The efficiency of this method is then evaluated through the calculation of surface tension and coexisting properties. We show that the inclusion of tail corrections during the course of the Monte Carlo simulation impacts the coexisting and the interfacial properties. We establish that the long range corrections to the surface tension are the same order of magnitude as those obtained from planar interface. We show that the slab-based tail method does not amend the localization of the Gibbs equimolar dividing surface. Additionally, a non-monotonic behavior of surface tension is exhibited as a function of the radius of the equimolar dividing surface.

Monte Carlo simulations of nanoscale focused neon ion beam sputtering.

PubMed

Timilsina, Rajendra; Rack, Philip D

2013-12-13

A Monte Carlo simulation is developed to model the physical sputtering of aluminum and tungsten emulating nanoscale focused helium and neon ion beam etching from the gas field ion microscope. Neon beams with different beam energies (0.5-30 keV) and a constant beam diameter (Gaussian with full-width-at-half-maximum of 1 nm) were simulated to elucidate the nanostructure evolution during the physical sputtering of nanoscale high aspect ratio features. The aspect ratio and sputter yield vary with the ion species and beam energy for a constant beam diameter and are related to the distribution of the nuclear energy loss. Neon ions have a larger sputter yield than the helium ions due to their larger mass and consequently larger nuclear energy loss relative to helium. Quantitative information such as the sputtering yields, the energy-dependent aspect ratios and resolution-limiting effects are discussed.

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

PubMed

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

2016-04-01

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

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

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

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

2016-04-15

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

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.

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

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

Romano, Paul K.; Lund, Amanda L.; Siegel, Andrew R.

2017-06-19

The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulationmore » that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.« less

One-dimensional model of interacting-step fluctuations on vicinal surfaces: Analytical formulas and kinetic Monte-Carlo simulations

NASA Astrophysics Data System (ADS)

Patrone, Paul; Einstein, T. L.; Margetis, Dionisios

2011-03-01

We study a 1+1D, stochastic, Burton-Cabrera-Frank (BCF) model of interacting steps fluctuating on a vicinal crystal. The step energy accounts for entropic and nearest-neighbor elastic-dipole interactions. Our goal is to formulate and validate a self-consistent mean-field (MF) formalism to approximately solve the system of coupled, nonlinear stochastic differential equations (SDEs) governing fluctuations in surface motion. We derive formulas for the time-dependent terrace width distribution (TWD) and its steady-state limit. By comparison with kinetic Monte-Carlo simulations, we show that our MF formalism improves upon models in which step interactions are linearized. We also indicate how fitting parameters of our steady state MF TWD may be used to determine the mass transport regime and step interaction energy of certain experimental systems. PP and TLE supported by NSF MRSEC under Grant DMR 05-20471 at U. of Maryland; DM supported by NSF under Grant DMS 08-47587.

Radiative interactions in multi-dimensional chemically reacting flows using Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, Surendra N.

1994-01-01

chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The governing equations are based on the fully elliptic Navier-Stokes equations. Chemical reaction mechanisms were described by a finite rate chemistry model. The correlated Monte Carlo method developed earlier was employed to simulate multi-dimensional radiative heat transfer. Results obtained demonstrate that radiative effects on the flowfield are minimal but radiative effects on the wall heat transfer are significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and nozzle size on the radiative and conductive wall fluxes.

Monte Carlo simulations of precise timekeeping in the Milstar communication satellite system

NASA Technical Reports Server (NTRS)

Camparo, James C.; Frueholz, R. P.

1995-01-01

The Milstar communications satellite system will provide secure antijam communication capabilities for DOD operations into the next century. In order to accomplish this task, the Milstar system will employ precise timekeeping on its satellites and at its ground control stations. The constellation will consist of four satellites in geosynchronous orbit, each carrying a set of four rubidium (Rb) atomic clocks. Several times a day, during normal operation, the Mission Control Element (MCE) will collect timing information from the constellation, and after several days use this information to update the time and frequency of the satellite clocks. The MCE will maintain precise time with a cesium (Cs) atomic clock, synchronized to UTC(USNO) via a GPS receiver. We have developed a Monte Carlo simulation of Milstar's space segment timekeeping. The simulation includes the effects of: uplink/downlink time transfer noise; satellite crosslink time transfer noise; satellite diurnal temperature variations; satellite and ground station atomic clock noise; and also quantization limits regarding satellite time and frequency corrections. The Monte Carlo simulation capability has proven to be an invaluable tool in assessing the performance characteristics of various timekeeping algorithms proposed for Milstar, and also in highlighting the timekeeping capabilities of the system. Here, we provide a brief overview of the basic Milstar timekeeping architecture as it is presently envisioned. We then describe the Monte Carlo simulation of space segment timekeeping, and provide examples of the simulation's efficacy in resolving timekeeping issues.

Coarse-Grained Molecular Monte Carlo Simulations of Liquid Crystal-Nanoparticle Mixtures

NASA Astrophysics Data System (ADS)

Neufeld, Ryan; Kimaev, Grigoriy; Fu, Fred; Abukhdeir, Nasser M.

Coarse-grained intermolecular potentials have proven capable of capturing essential details of interactions between complex molecules, while substantially reducing the number of degrees of freedom of the system under study. In the domain of liquid crystals, the Gay-Berne (GB) potential has been successfully used to model the behavior of rod-like and disk-like mesogens. However, only ellipsoid-like interaction potentials can be described with GB, making it a poor fit for many real-world mesogens. In this work, the results of Monte Carlo simulations of liquid crystal domains using the Zewdie-Corner (ZC) potential are presented. The ZC potential is constructed from an orthogonal series of basis functions, allowing for potentials of essentially arbitrary shapes to be modeled. We also present simulations of mixtures of liquid crystalline mesogens with nanoparticles. Experimentally these mixtures have been observed to exhibit microphase separation and formation of long-range networks under some conditions. This highlights the need for a coarse-grained approach which can capture salient details on the molecular scale while simulating sufficiently large domains to observe these phenomena. We compare the phase behavior of our simulations with that of a recently presented continuum theory. This work was made possible by the Natural Sciences and Engineering Research Council of Canada and Compute Ontario.

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).

Using Monte-Carlo Simulations to Study the Disk Structure in Cygnus X-1

NASA Technical Reports Server (NTRS)

Yao, Y.; Zhang, S. N.; Zhang, X. L.; Feng, Y. X.

2002-01-01

As the first dynamically determined black hole X-ray binary system, Cygnus X-1 has been studied extensively. However, its broad-band spectra in hard state with BeppoSAX is still not well understood. Besides the soft excess described by the multi-color disk model (MCD), the power- law component and a broad excess feature above 10 keV (disk reflection component), there is also an additional soft component around 1 keV, whose origin is not known currently.We propose that the additional soft component is due to the thermal Comptonization process between the s oft disk photon and the warm plasma cloud just above the disk.i.e., a warm layer. We use Monte-Carlo technique t o simulate this Compton scattering process and build several table models based on our simulation results.

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

PubMed Central

Amoush, Ahmad; Wilkinson, Douglas A.

2015-01-01

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

Monte Carlo simulation of air sampling methods for the measurement of radon decay products.

PubMed

Sima, Octavian; Luca, Aurelian; Sahagia, Maria

2017-08-01

A stochastic model of the processes involved in the measurement of the activity of the 222 Rn decay products was developed. The distributions of the relevant factors, including air sampling and radionuclide collection, are propagated using Monte Carlo simulation to the final distribution of the measurement results. The uncertainties of the 222 Rn decay products concentrations in the air are realistically evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parallel distributed, reciprocal Monte Carlo radiation in coupled, large eddy combustion simulations

NASA Astrophysics Data System (ADS)

Hunsaker, Isaac L.

Radiation is the dominant mode of heat transfer in high temperature combustion environments. Radiative heat transfer affects the gas and particle phases, including all the associated combustion chemistry. The radiative properties are in turn affected by the turbulent flow field. This bi-directional coupling of radiation turbulence interactions poses a major challenge in creating parallel-capable, high-fidelity combustion simulations. In this work, a new model was developed in which reciprocal monte carlo radiation was coupled with a turbulent, large-eddy simulation combustion model. A technique wherein domain patches are stitched together was implemented to allow for scalable parallelism. The combustion model runs in parallel on a decomposed domain. The radiation model runs in parallel on a recomposed domain. The recomposed domain is stored on each processor after information sharing of the decomposed domain is handled via the message passing interface. Verification and validation testing of the new radiation model were favorable. Strong scaling analyses were performed on the Ember cluster and the Titan cluster for the CPU-radiation model and GPU-radiation model, respectively. The model demonstrated strong scaling to over 1,700 and 16,000 processing cores on Ember and Titan, respectively.

A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

USGS Publications Warehouse

Ward, Adam S.; Kelleher, Christa A.; Mason, Seth J. K.; Wagener, Thorsten; McIntyre, Neil; McGlynn, Brian L.; Runkel, Robert L.; Payn, Robert A.

2017-01-01

Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.

Lattice Boltzmann accelerated direct simulation Monte Carlo for dilute gas flow simulations.

PubMed

Di Staso, G; Clercx, H J H; Succi, S; Toschi, F

2016-11-13

Hybrid particle-continuum computational frameworks permit the simulation of gas flows by locally adjusting the resolution to the degree of non-equilibrium displayed by the flow in different regions of space and time. In this work, we present a new scheme that couples the direct simulation Monte Carlo (DSMC) with the lattice Boltzmann (LB) method in the limit of isothermal flows. The former handles strong non-equilibrium effects, as they typically occur in the vicinity of solid boundaries, whereas the latter is in charge of the bulk flow, where non-equilibrium can be dealt with perturbatively, i.e. according to Navier-Stokes hydrodynamics. The proposed concurrent multiscale method is applied to the dilute gas Couette flow, showing major computational gains when compared with the full DSMC scenarios. In addition, it is shown that the coupling with LB in the bulk flow can speed up the DSMC treatment of the Knudsen layer with respect to the full DSMC case. In other words, LB acts as a DSMC accelerator.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Monte Carlo simulation of random, porous (foam) structures for neutron detection

NASA Astrophysics Data System (ADS)

Reichenberger, Michael A.; Fronk, Ryan G.; Shultis, J. Kenneth; Roberts, Jeremy A.; Edwards, Nathaniel S.; Stevenson, Sarah R.; Tiner, Christopher N.; McGregor, Douglas S.

2017-01-01

Porous media incorporating highly neutron-sensitive materials are of interest for use in the development of neutron detectors. Previous studies have shown experimentally the feasibility of 6LiF-saturated, multi-layered detectors; however, the random geometry of porous materials has limited the effectiveness of simulation efforts. The results of scatterless neutron transport and subsequent charged reaction product ion energy deposition are reported here using a novel Monte Carlo method and compared to results obtained by MCNP6. This new Dynamic Path Generation (DPG) Monte Carlo method was developed in order to overcome the complexities of modeling a random porous geometry in MCNP6. The DPG method is then applied to determine the optimal coating thickness for 10B4C-coated reticulated vitreous-carbon (RVC) foams. The optimal coating thickness for 4.1275 cm-thick 10B4C-coated reticulated vitreous carbon foams with porosities of 5, 10, 20, 30, 45, and 80 pores per inch (PPI) were determined for ionizing gas pressures of 1.0 and 2.8 atm. A simulated, maximum, intrinsic thermal-neutron detection efficiency of 62.8±0.25% was predicted for an 80 PPI RVC foam with a 0.2 μm thick coating of 10B4C, for a lower level discriminator setting of 75 keV and an argon pressure of 2.8 atm.

Mercedes-Benz water molecules near hydrophobic wall: Integral equation theories vs Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Urbic, T.; Holovko, M. F.

2011-10-01

Associative version of Henderson-Abraham-Barker theory is applied for the study of Mercedes-Benz model of water near hydrophobic surface. We calculated density profiles and adsorption coefficients using Percus-Yevick and soft mean spherical associative approximations. The results are compared with Monte Carlo simulation data. It is shown that at higher temperatures both approximations satisfactory reproduce the simulation data. For lower temperatures, soft mean spherical approximation gives good agreement at low and at high densities while in at mid range densities, the prediction is only qualitative. The formation of a depletion layer between water and hydrophobic surface was also demonstrated and studied.

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Procedure for Adapting Direct Simulation Monte Carlo Meshes

NASA Technical Reports Server (NTRS)

Woronowicz, Michael S.; Wilmoth, Richard G.; Carlson, Ann B.; Rault, Didier F. G.

1992-01-01

A technique is presented for adapting computational meshes used in the G2 version of the direct simulation Monte Carlo method. The physical ideas underlying the technique are discussed, and adaptation formulas are developed for use on solutions generated from an initial mesh. The effect of statistical scatter on adaptation is addressed, and results demonstrate the ability of this technique to achieve more accurate results without increasing necessary computational resources.

Monte Carlo simulation of MOSFET dosimeter for electron backscatter using the GEANT4 code.

PubMed

Chow, James C L; Leung, Michael K K

2008-06-01

The aim of this study is to investigate the influence of the body of the metal-oxide-semiconductor field effect transistor (MOSFET) dosimeter in measuring the electron backscatter from lead. The electron backscatter factor (EBF), which is defined as the ratio of dose at the tissue-lead interface to the dose at the same point without the presence of backscatter, was calculated by the Monte Carlo simulation using the GEANT4 code. Electron beams with energies of 4, 6, 9, and 12 MeV were used in the simulation. It was found that in the presence of the MOSFET body, the EBFs were underestimated by about 2%-0.9% for electron beam energies of 4-12 MeV, respectively. The trend of the decrease of EBF with an increase of electron energy can be explained by the small MOSFET dosimeter, mainly made of epoxy and silicon, not only attenuated the electron fluence of the electron beam from upstream, but also the electron backscatter generated by the lead underneath the dosimeter. However, this variation of the EBF underestimation is within the same order of the statistical uncertainties as the Monte Carlo simulations, which ranged from 1.3% to 0.8% for the electron energies of 4-12 MeV, due to the small dosimetric volume. Such small EBF deviation is therefore insignificant when the uncertainty of the Monte Carlo simulation is taken into account. Corresponding measurements were carried out and uncertainties compared to Monte Carlo results were within +/- 2%. Spectra of energy deposited by the backscattered electrons in dosimetric volumes with and without the lead and MOSFET were determined by Monte Carlo simulations. It was found that in both cases, when the MOSFET body is either present or absent in the simulation, deviations of electron energy spectra with and without the lead decrease with an increase of the electron beam energy. Moreover, the softer spectrum of the backscattered electron when lead is present can result in a reduction of the MOSFET response due to stronger

GATE Monte Carlo simulation of GE Discovery 600 and a uniformity phantom

NASA Astrophysics Data System (ADS)

Sheen, Heesoon; Im, Ki Chun; Choi, Yong; Shin, Hanback; Han, Youngyih; Chung, Kwangzoo; Cho, Junsang; Ahn, Sang Hee

2014-12-01

GATE (Geant4 Application Tomography Emission) Monte Carlo simulations have been successful in the application of emission tomography for precise modeling of various physical processes. Most previous studies on Monte Carlo simulations have only involved performance assessments using virtual phantoms. Although that allows the performance of simulated positron emission tomography (PET) to be evaluated, it does not reflect the reality of practical conditions. This restriction causes substantial drawbacks in GATE simulations of real situations. To overcome the described limitation and to provide a method to enable simulation research relevant to clinically important issues, we conducted a GATE simulation using real data from a scanner rather than a virtual phantom and evaluated the scanner is performance. For that purpose, the system and the geometry of a commercial GE PET/ CT (computed tomography) scanner, BGO-based Discovery 600 (D600), was developed for the first time. The performance of the modeled PET system was evaluated by using the National Electrical Manufacturers Association NEMA NU 2-2007 protocols and results were compared with those of the reference data. The sensitivity, scatter fraction, noise-equivalent count rate (NECR), and resolution were estimated by using the protocol of the NEMA NU2-2007. Sensitivities were 9.01 cps/kBq at 0 cm and 9.43 cps/kBq at 10 cm. Scatter fractions were 39.5%. The NECR peak was 89.7 kcps @ 14.7 kBq/cc. Resolutions were 4.8 mm in the transaxial plane and 5.9 mm in the axial plane at 1 cm, and 6.2 mm in the transaxial plane and 6.4 mm in the axial plane at 10 cm. The resolutions exceeded the limited value provided by the manufacturer. The uniformity phantom was simulated using the CT and the PET data. The output data in a ROOT format were converted and then reconstructed by using the C program and STIR (Software for Tomographic Image Reconstruction). The reconstructed images of the simulated uniformity phantom data had

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue.

PubMed

Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A

2011-11-01

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.

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

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.

Monte Carlo simulation of Hamaker nanospheres coated with dipolar particles

NASA Astrophysics Data System (ADS)

Meyra, Ariel G.; Zarragoicoechea, Guillermo J.; Kuz, Victor A.

2012-01-01

Parallel tempering Monte Carlo simulation is carried out in systems of N attractive Hamaker spheres dressed with n dipolar particles, able to move on the surface of the spheres. Different cluster configurations emerge for given values of the control parameters. Energy per sphere, pair distribution functions of spheres and dipoles as function of temperature, density, external electric field, and/or the angular orientation of dipoles are used to analyse the state of aggregation of the system. As a consequence of the non-central interaction, the model predicts complex structures like self-assembly of spheres by a double crown of dipoles. This interesting result could be of help in understanding some recent experiments in colloidal science and biology.

Monte Carlo Simulations of Background Spectra in Integral Imager Detectors

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.; Dietz, K. L.; Ramsey, B. D.; Weisskopf, M. C.

1998-01-01

Predictions of the expected gamma-ray backgrounds in the ISGRI (CdTe) and PiCsIT (Csl) detectors on INTEGRAL due to cosmic-ray interactions and the diffuse gamma-ray background have been made using a coupled set of Monte Carlo radiation transport codes (HETC, FLUKA, EGS4, and MORSE) and a detailed, 3-D mass model of the spacecraft and detector assemblies. The simulations include both the prompt background component from induced hadronic and electromagnetic cascades and the delayed component due to emissions from induced radioactivity. Background spectra have been obtained with and without the use of active (BGO) shielding and charged particle rejection to evaluate the effectiveness of anticoincidence counting on background rejection.

Monte Carlo modeling of recrystallization processes in α-uranium

DOE PAGES

Steiner, M. A.; McCabe, R. J.; Garlea, E.; ...

2017-08-01

In this study, starting with electron backscattered diffraction (EBSD) data obtained from a warm clock-rolled α-uranium deformation microstructure, a Potts Monte Carlo model was used to simulate static site-saturated recrystallization while testing a number of different conditions for the assignment of recrystallized nuclei within the microstructure. The simulations support observations that recrystallized nuclei within α-uranium form preferentially on non-twin high-angle grain boundary sites at 450 °C, and demonstrate that the most likely nucleation sites on these boundaries can be identified by the surrounding degree of Kernel Average Misorientation (KAM), which may be considered as a proxy for the local geometricallymore » necessary dislocation (GND) density.« less

A brief history of the introduction of generalized ensembles to Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Berg, Bernd A.

2017-03-01

The most efficient weights for Markov chain Monte Carlo calculations of physical observables are not necessarily those of the canonical ensemble. Generalized ensembles, which do not exist in nature but can be simulated on computers, lead often to a much faster convergence. In particular, they have been used for simulations of first order phase transitions and for simulations of complex systems in which conflicting constraints lead to a rugged free energy landscape. Starting off with the Metropolis algorithm and Hastings' extension, I present a minireview which focuses on the explosive use of generalized ensembles in the early 1990s. Illustrations are given, which range from spin models to peptides.

Reconstructing in-vivo reflectance spectrum of pigmented skin lesion by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wang, Shuang; He, Qingli; Zhao, Jianhua; Lui, Harvey; Zeng, Haishan

2012-03-01

In dermatology applications, diffuse reflectance spectroscopy has been extensively investigated as a promising tool for the noninvasive method to distinguish melanoma from benign pigmented skin lesion (nevus), which is concentrated with the skin chromophores like melanin and hemoglobin. We carried out a theoretical study to examine melanin distribution in human skin tissue and establish a practical optical model for further pigmented skin investigation. The theoretical simulation was using junctional nevus as an example. A multiple layer skin optical model was developed on established anatomy structures of skin, the published optical parameters of different skin layers, blood and melanin. Monte Carlo simulation was used to model the interaction between excitation light and skin tissue and rebuild the diffuse reflectance process from skin tissue. A testified methodology was adopted to determine melanin contents in human skin based on in vivo diffuse reflectance spectra. The rebuild diffuse reflectance spectra were investigated by adding melanin into different layers of the theoretical model. One of in vivo reflectance spectra from Junctional nevi and their surrounding normal skin was studied by compare the ratio between nevus and normal skin tissue in both the experimental and simulated diffuse reflectance spectra. The simulation result showed a good agreement with our clinical measurements, which indicated that our research method, including the spectral ratio method, skin optical model and modifying the melanin content in the model, could be applied in further theoretical simulation of pigmented skin lesions.

Inverse Monte Carlo method in a multilayered tissue model for diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Fredriksson, Ingemar; Larsson, Marcus; Strömberg, Tomas

2012-04-01

Model based data analysis of diffuse reflectance spectroscopy data enables the estimation of optical and structural tissue parameters. The aim of this study was to present an inverse Monte Carlo method based on spectra from two source-detector distances (0.4 and 1.2 mm), using a multilayered tissue model. The tissue model variables include geometrical properties, light scattering properties, tissue chromophores such as melanin and hemoglobin, oxygen saturation and average vessel diameter. The method utilizes a small set of presimulated Monte Carlo data for combinations of different levels of epidermal thickness and tissue scattering. The path length distributions in the different layers are stored and the effect of the other parameters is added in the post-processing. The accuracy of the method was evaluated using Monte Carlo simulations of tissue-like models containing discrete blood vessels, evaluating blood tissue fraction and oxygenation. It was also compared to a homogeneous model. The multilayer model performed better than the homogeneous model and all tissue parameters significantly improved spectral fitting. Recorded in vivo spectra were fitted well at both distances, which we previously found was not possible with a homogeneous model. No absolute intensity calibration is needed and the algorithm is fast enough for real-time processing.

Approximate Bayesian Computation Using Markov Chain Monte Carlo Simulation: Theory, Concepts, and Applications

NASA Astrophysics Data System (ADS)

Sadegh, M.; Vrugt, J. A.

2013-12-01

The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex hydrologic models that simulate soil moisture flow, groundwater recharge, surface runoff, root water uptake, and river discharge at increasingly finer spatial and temporal scales. Reconciling these system models with field and remote sensing data is a difficult task, particularly because average measures of model/data similarity inherently lack the power to provide a meaningful comparative evaluation of the consistency in model form and function. The very construction of the likelihood function - as a summary variable of the (usually averaged) properties of the error residuals - dilutes and mixes the available information into an index having little remaining correspondence to specific behaviors of the system (Gupta et al., 2008). The quest for a more powerful method for model evaluation has inspired Vrugt and Sadegh [2013] to introduce "likelihood-free" inference as vehicle for diagnostic model evaluation. This class of methods is also referred to as Approximate Bayesian Computation (ABC) and relaxes the need for an explicit likelihood function in favor of one or multiple different summary statistics rooted in hydrologic theory that together have a much stronger and compelling diagnostic power than some aggregated measure of the size of the error residuals. Here, we will introduce an efficient ABC sampling method that is orders of magnitude faster in exploring the posterior parameter distribution than commonly used rejection and Population Monte Carlo (PMC) samplers. Our methodology uses Markov Chain Monte Carlo simulation with DREAM, and takes advantage of a simple computational trick to resolve discontinuity problems with the application of set-theoretic summary statistics. We will also demonstrate a set of summary statistics that are rather insensitive to

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

Monte Carlo simulation of secondary neutron dose for scanning proton therapy using FLUKA

PubMed Central

Lee, Chaeyeong; Lee, Sangmin; Lee, Seung-Jae; Song, Hankyeol; Kim, Dae-Hyun; Cho, Sungkoo; Jo, Kwanghyun; Han, Youngyih; Chung, Yong Hyun

2017-01-01

Proton therapy is a rapidly progressing field for cancer treatment. Globally, many proton therapy facilities are being commissioned or under construction. Secondary neutrons are an important issue during the commissioning process of a proton therapy facility. The purpose of this study is to model and validate scanning nozzles of proton therapy at Samsung Medical Center (SMC) by Monte Carlo simulation for beam commissioning. After the commissioning, a secondary neutron ambient dose from proton scanning nozzle (Gantry 1) was simulated and measured. This simulation was performed to evaluate beam properties such as percent depth dose curve, Bragg peak, and distal fall-off, so that they could be verified with measured data. Using the validated beam nozzle, the secondary neutron ambient dose was simulated and then compared with the measured ambient dose from Gantry 1. We calculated secondary neutron dose at several different points. We demonstrated the validity modeling a proton scanning nozzle system to evaluate various parameters using FLUKA. The measured secondary neutron ambient dose showed a similar tendency with the simulation result. This work will increase the knowledge necessary for the development of radiation safety technology in medical particle accelerators. PMID:29045491

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

NASA Astrophysics Data System (ADS)

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

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

Simulating the Generalized Gibbs Ensemble (GGE): A Hilbert space Monte Carlo approach

NASA Astrophysics Data System (ADS)

Alba, Vincenzo

By combining classical Monte Carlo and Bethe ansatz techniques we devise a numerical method to construct the Truncated Generalized Gibbs Ensemble (TGGE) for the spin-1/2 isotropic Heisenberg (XXX) chain. The key idea is to sample the Hilbert space of the model with the appropriate GGE probability measure. The method can be extended to other integrable systems, such as the Lieb-Liniger model. We benchmark the approach focusing on GGE expectation values of several local observables. As finite-size effects decay exponentially with system size, moderately large chains are sufficient to extract thermodynamic quantities. The Monte Carlo results are in agreement with both the Thermodynamic Bethe Ansatz (TBA) and the Quantum Transfer Matrix approach (QTM). Remarkably, it is possible to extract in a simple way the steady-state Bethe-Gaudin-Takahashi (BGT) roots distributions, which encode complete information about the GGE expectation values in the thermodynamic limit. Finally, it is straightforward to simulate extensions of the GGE, in which, besides the local integral of motion (local charges), one includes arbitrary functions of the BGT roots. As an example, we include in the GGE the first non-trivial quasi-local integral of motion.

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

PubMed

Castonguay, Thomas C; Wang, Feng

2008-03-28

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

Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer

NASA Astrophysics Data System (ADS)

Castonguay, Thomas C.; Wang, Feng

2008-03-01

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

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

PubMed

Temleitner, László; Pusztai, László; Schweika, Werner

2007-08-22

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

Monte Carlo simulations of particle acceleration at oblique shocks: Including cross-field diffusion

NASA Technical Reports Server (NTRS)

Baring, M. G.; Ellison, D. C.; Jones, F. C.

1995-01-01

The Monte Carlo technique of simulating diffusive particle acceleration at shocks has made spectral predictions that compare extremely well with particle distributions observed at the quasi-parallel region of the earth's bow shock. The current extension of this work to compare simulation predictions with particle spectra at oblique interplanetary shocks has required the inclusion of significant cross-field diffusion (strong scattering) in the simulation technique, since oblique shocks are intrinsically inefficient in the limit of weak scattering. In this paper, we present results from the method we have developed for the inclusion of cross-field diffusion in our simulations, namely model predictions of particle spectra downstream of oblique subluminal shocks. While the high-energy spectral index is independent of the shock obliquity and the strength of the scattering, the latter is observed to profoundly influence the efficiency of injection of cosmic rays into the acceleration process.

Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics

NASA Technical Reports Server (NTRS)

Good, Brian

2013-01-01

Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.

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

PubMed

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

2017-09-26

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

Modeling of multi-band drift in nanowires using a full band Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Hathwar, Raghuraj; Saraniti, Marco; Goodnick, Stephen M.

2016-07-01

We report on a new numerical approach for multi-band drift within the context of full band Monte Carlo (FBMC) simulation and apply this to Si and InAs nanowires. The approach is based on the solution of the Krieger and Iafrate (KI) equations [J. B. Krieger and G. J. Iafrate, Phys. Rev. B 33, 5494 (1986)], which gives the probability of carriers undergoing interband transitions subject to an applied electric field. The KI equations are based on the solution of the time-dependent Schrödinger equation, and previous solutions of these equations have used Runge-Kutta (RK) methods to numerically solve the KI equations. This approach made the solution of the KI equations numerically expensive and was therefore only applied to a small part of the Brillouin zone (BZ). Here we discuss an alternate approach to the solution of the KI equations using the Magnus expansion (also known as "exponential perturbation theory"). This method is more accurate than the RK method as the solution lies on the exponential map and shares important qualitative properties with the exact solution such as the preservation of the unitary character of the time evolution operator. The solution of the KI equations is then incorporated through a modified FBMC free-flight drift routine and applied throughout the nanowire BZ. The importance of the multi-band drift model is then demonstrated for the case of Si and InAs nanowires by simulating a uniform field FBMC and analyzing the average carrier energies and carrier populations under high electric fields. Numerical simulations show that the average energy of the carriers under high electric field is significantly higher when multi-band drift is taken into consideration, due to the interband transitions allowing carriers to achieve higher energies.

The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations

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

Sellier, J.M., E-mail: jeanmichel.sellier@parallel.bas.bg; Dimov, I.

2014-09-15

The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practicallymore » unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.« less

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2014-01-01

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

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

PubMed

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

2011-10-11

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

Heterogeneous multiscale Monte Carlo simulations for gold nanoparticle radiosensitization.

PubMed

Martinov, Martin P; Thomson, Rowan M

2017-02-01

To introduce the heterogeneous multiscale (HetMS) model for Monte Carlo simulations of gold nanoparticle dose-enhanced radiation therapy (GNPT), a model characterized by its varying levels of detail on different length scales within a single phantom; to apply the HetMS model in two different scenarios relevant for GNPT and to compare computed results with others published. The HetMS model is implemented using an extended version of the EGSnrc user-code egs_chamber; the extended code is tested and verified via comparisons with recently published data from independent GNP simulations. Two distinct scenarios for the HetMS model are then considered: (a) monoenergetic photon beams (20 keV to 1 MeV) incident on a cylinder (1 cm radius, 3 cm length); (b) isotropic point source (brachytherapy source spectra) at the center of a 2.5 cm radius sphere with gold nanoparticles (GNPs) diffusing outwards from the center. Dose enhancement factors (DEFs) are compared for different source energies, depths in phantom, gold concentrations, GNP sizes, and modeling assumptions, as well as with independently published values. Simulation efficiencies are investigated. The HetMS MC simulations account for the competing effects of photon fluence perturbation (due to gold in the scatter media) coupled with enhanced local energy deposition (due to modeling discrete GNPs within subvolumes). DEFs are most sensitive to these effects for the lower source energies, varying with distance from the source; DEFs below unity (i.e., dose decreases, not enhancements) can occur at energies relevant for brachytherapy. For example, in the cylinder scenario, the 20 keV photon source has a DEF of 3.1 near the phantom's surface, decreasing to less than unity by 0.7 cm depth (for 20 mg/g). Compared to discrete modeling of GNPs throughout the gold-containing (treatment) volume, efficiencies are enhanced by up to a factor of 122 with the HetMS approach. For the spherical phantom, DEFs vary with time for diffusion

First-principles Monte Carlo simulations of reaction equilibria in compressed vapors

DOE PAGES

Fetisov, Evgenii O.; Kuo, I-Feng William; Knight, Chris; ...

2016-06-13

Predictive modeling of reaction equilibria presents one of the grand challenges in the field of molecular simulation. Difficulties in the study of such systems arise from the need (i) to accurately model both strong, short-ranged interactions leading to the formation of chemical bonds and weak interactions arising from the environment, and (ii) to sample the range of time scales involving frequent molecular collisions, slow diffusion, and infrequent reactive events. Here we present a novel reactive first-principles Monte Carlo (RxFPMC) approach that allows for investigation of reaction equilibria without the need to prespecify a set of chemical reactions and their ideal-gasmore » equilibrium constants. We apply RxFPMC to investigate a nitrogen/oxygen mixture at T = 3000 K and p = 30 GPa, i.e., conditions that are present in atmospheric lightning strikes and explosions. The RxFPMC simulations show that the solvation environment leads to a significantly enhanced NO concentration that reaches a maximum when oxygen is present in slight excess. In addition, the RxFPMC simulations indicate the formation of NO 2 and N 2O in mole fractions approaching 1%, whereas N 3 and O 3 are not observed. Lastly, the equilibrium distributions obtained from the RxFPMC simulations agree well with those from a thermochemical computer code parametrized to experimental data.« less

First-principles Monte Carlo simulations of reaction equilibria in compressed vapors

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

Fetisov, Evgenii O.; Kuo, I-Feng William; Knight, Chris

Predictive modeling of reaction equilibria presents one of the grand challenges in the field of molecular simulation. Difficulties in the study of such systems arise from the need (i) to accurately model both strong, short-ranged interactions leading to the formation of chemical bonds and weak interactions arising from the environment, and (ii) to sample the range of time scales involving frequent molecular collisions, slow diffusion, and infrequent reactive events. Here we present a novel reactive first-principles Monte Carlo (RxFPMC) approach that allows for investigation of reaction equilibria without the need to prespecify a set of chemical reactions and their ideal-gasmore » equilibrium constants. We apply RxFPMC to investigate a nitrogen/oxygen mixture at T = 3000 K and p = 30 GPa, i.e., conditions that are present in atmospheric lightning strikes and explosions. The RxFPMC simulations show that the solvation environment leads to a significantly enhanced NO concentration that reaches a maximum when oxygen is present in slight excess. In addition, the RxFPMC simulations indicate the formation of NO 2 and N 2O in mole fractions approaching 1%, whereas N 3 and O 3 are not observed. Lastly, the equilibrium distributions obtained from the RxFPMC simulations agree well with those from a thermochemical computer code parametrized to experimental data.« less

First-Principles Monte Carlo Simulations of Reaction Equilibria in Compressed Vapors

PubMed Central

2016-01-01

Predictive modeling of reaction equilibria presents one of the grand challenges in the field of molecular simulation. Difficulties in the study of such systems arise from the need (i) to accurately model both strong, short-ranged interactions leading to the formation of chemical bonds and weak interactions arising from the environment, and (ii) to sample the range of time scales involving frequent molecular collisions, slow diffusion, and infrequent reactive events. Here we present a novel reactive first-principles Monte Carlo (RxFPMC) approach that allows for investigation of reaction equilibria without the need to prespecify a set of chemical reactions and their ideal-gas equilibrium constants. We apply RxFPMC to investigate a nitrogen/oxygen mixture at T = 3000 K and p = 30 GPa, i.e., conditions that are present in atmospheric lightning strikes and explosions. The RxFPMC simulations show that the solvation environment leads to a significantly enhanced NO concentration that reaches a maximum when oxygen is present in slight excess. In addition, the RxFPMC simulations indicate the formation of NO2 and N2O in mole fractions approaching 1%, whereas N3 and O3 are not observed. The equilibrium distributions obtained from the RxFPMC simulations agree well with those from a thermochemical computer code parametrized to experimental data. PMID:27413785

Mercedes–Benz water molecules near hydrophobic wall: Integral equation theories vs Monte Carlo simulations

PubMed Central

Urbic, T.; Holovko, M. F.

2011-01-01

Associative version of Henderson-Abraham-Barker theory is applied for the study of Mercedes–Benz model of water near hydrophobic surface. We calculated density profiles and adsorption coefficients using Percus-Yevick and soft mean spherical associative approximations. The results are compared with Monte Carlo simulation data. It is shown that at higher temperatures both approximations satisfactory reproduce the simulation data. For lower temperatures, soft mean spherical approximation gives good agreement at low and at high densities while in at mid range densities, the prediction is only qualitative. The formation of a depletion layer between water and hydrophobic surface was also demonstrated and studied. PMID:21992334

Mercedes-Benz water molecules near hydrophobic wall: integral equation theories vs Monte Carlo simulations.

PubMed

Urbic, T; Holovko, M F

2011-10-07

Associative version of Henderson-Abraham-Barker theory is applied for the study of Mercedes-Benz model of water near hydrophobic surface. We calculated density profiles and adsorption coefficients using Percus-Yevick and soft mean spherical associative approximations. The results are compared with Monte Carlo simulation data. It is shown that at higher temperatures both approximations satisfactory reproduce the simulation data. For lower temperatures, soft mean spherical approximation gives good agreement at low and at high densities while in at mid range densities, the prediction is only qualitative. The formation of a depletion layer between water and hydrophobic surface was also demonstrated and studied. © 2011 American Institute of Physics

A review: Functional near infrared spectroscopy evaluation in muscle tissues using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Halim, A. A. A.; Laili, M. H.; Salikin, M. S.; Rusop, M.

2018-05-01

Monte Carlo Simulation has advanced their quantification based on number of the photon counting to solve the propagation of light inside the tissues including the absorption, scattering coefficient and act as preliminary study for functional near infrared application. The goal of this paper is to identify the optical properties using Monte Carlo simulation for non-invasive functional near infrared spectroscopy (fNIRS) evaluation of penetration depth in human muscle. This paper will describe the NIRS principle and the basis for its proposed used in Monte Carlo simulation which focused on several important parameters include ATP, ADP and relate with blow flow and oxygen content at certain exercise intensity. This will cover the advantages and limitation of such application upon this simulation. This result may help us to prove that our human muscle is transparent to this near infrared region and could deliver a lot of information regarding to the oxygenation level in human muscle. Thus, this might be useful for non-invasive technique for detecting oxygen status in muscle from living people either athletes or working people and allowing a lots of investigation muscle physiology in future.

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

PubMed

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

2006-10-01

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

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

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

New Monte Carlo model of cylindrical diffusing fibers illustrates axially heterogeneous fluorescence detection: simulation and experimental validation

PubMed Central

Baran, Timothy M.; Foster, Thomas H.

2011-01-01

We present a new Monte Carlo model of cylindrical diffusing fibers that is implemented with a graphics processing unit. Unlike previously published models that approximate the diffuser as a linear array of point sources, this model is based on the construction of these fibers. This allows for accurate determination of fluence distributions and modeling of fluorescence generation and collection. We demonstrate that our model generates fluence profiles similar to a linear array of point sources, but reveals axially heterogeneous fluorescence detection. With axially homogeneous excitation fluence, approximately 90% of detected fluorescence is collected by the proximal third of the diffuser for μs'/μa = 8 in the tissue and 70 to 88% is collected in this region for μs'/μa = 80. Increased fluorescence detection by the distal end of the diffuser relative to the center section is also demonstrated. Validation of these results was performed by creating phantoms consisting of layered fluorescent regions. Diffusers were inserted into these layered phantoms and fluorescence spectra were collected. Fits to these spectra show quantitative agreement between simulated fluorescence collection sensitivities and experimental results. These results will be applicable to the use of diffusers as detectors for dosimetry in interstitial photodynamic therapy. PMID:21895311

Monte Carlo Simulation Tool Installation and Operation Guide

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

Aguayo Navarrete, Estanislao; Ankney, Austin S.; Berguson, Timothy J.

2013-09-02

This document provides information on software and procedures for Monte Carlo simulations based on the Geant4 toolkit, the ROOT data analysis software and the CRY cosmic ray library. These tools have been chosen for its application to shield design and activation studies as part of the simulation task for the Majorana Collaboration. This document includes instructions for installation, operation and modification of the simulation code in a high cyber-security computing environment, such as the Pacific Northwest National Laboratory network. It is intended as a living document, and will be periodically updated. It is a starting point for information collection bymore » an experimenter, and is not the definitive source. Users should consult with one of the authors for guidance on how to find the most current information for their needs.« less

Effect of electron Monte Carlo collisions on a hybrid simulation of a low-pressure capacitively coupled plasma

NASA Astrophysics Data System (ADS)

Hwang, Seok Won; Lee, Ho-Jun; Lee, Hae June

2014-12-01

Fluid models have been widely used and conducted successfully in high pressure plasma simulations where the drift-diffusion and the local-field approximation are valid. However, fluid models are not able to demonstrate non-local effects related to large electron energy relaxation mean free path in low pressure plasmas. To overcome this weakness, a hybrid model coupling electron Monte Carlo collision (EMCC) method with the fluid model is introduced to obtain precise electron energy distribution functions using pseudo-particles. Steady state simulation results by a one-dimensional hybrid model which includes EMCC method for the collisional reactions but uses drift-diffusion approximation for electron transport in a fluid model are compared with those of a conventional particle-in-cell (PIC) and a fluid model for low pressure capacitively coupled plasmas. At a wide range of pressure, the hybrid model agrees well with the PIC simulation with a reduced calculation time while the fluid model shows discrepancy in the results of the plasma density and the electron temperature.

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.

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

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

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

2013-01-15

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

Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

DTIC Science & Technology

2009-07-01

simulation. The pilot described in this paper used this two-step approach within a Define, Measure, Analyze, Improve, and Control ( DMAIC ) framework to...networks, BBN, Monte Carlo simulation, DMAIC , Six Sigma, business case 15. NUMBER OF PAGES 35 16. PRICE CODE 17. SECURITY CLASSIFICATION OF

A Monte Carlo Simulation for Understanding Energy Measurements of Beta Particles Detected by the UCNb Experiment

NASA Astrophysics Data System (ADS)

Feng, Chi; UCNb Collaboration

2011-10-01

It is theorized that contributions to the Fierz interference term from scalar interaction beyond the Standard Model could be detectable in the spectrum of neutron beta-decay. The UCNb experiment run at the Los Alamos Neutron Science Center aims to accurately measure the neutron beta-decay energy spectrum to detect a nonzero interference term. The instrument consists of a cubic ``integrating sphere'' calorimeter attached with up to 4 photomultiplier tubes. The inside of the calorimeter is coated with white paint and a thin UV scintillating layer made of deuterated polystyrene to contain the ultracold neutrons. A Monte Carlo simulation using the Geant4 toolkit is developed in order to provide an accurate method of energy reconstruction. Offline calibration with the Kellogg Radiation Laboratory 140 keV electron gun and conversion electron sources will be used to validate the Monte Carlo simulation to give confidence in the energy reconstruction methods and to better understand systematics in the experiment data.

Renormalization Group Studies and Monte Carlo Simulation for Quantum Spin Systems.

NASA Astrophysics Data System (ADS)

Pan, Ching-Yan

We have discussed the extended application of various real space renormalization group methods to the quantum spin systems. At finite temperature, we extended both the reliability and range of application of the decimation renormalization group method (DRG) for calculating the thermal and magnetic properties of low-dimensional quantum spin chains, in which we have proposed general models of the three-state Potts model and the general Heisenberg model. Some interesting finite-temperature behavior of the models has been obtained. We also proposed a general formula for the critical properties of the n-dimensional q-state Potts model by using a modified migdal-Kadanoff approach which is in very good agreement with all available results for general q and d. For high-spin systems, we have investigated the famous Haldane's prediction by using a modified block renormalization group approach in spin -1over2, spin-1 and spin-3 over2 cases. Our result supports Haldane's prediction and a novel property of the spin-1 Heisenberg antiferromagnet has been predicted. A modified quantum monte Carlo simulation approach has been developed in this study which we use to treat quantum interacting problems (we only work on quantum spin systems in this study) without the "negative sign problem". We also obtain with the Monte Carlo approach the numerical derivative directly. Furthermore, using this approach we have obtained the energy spectrum and the thermodynamic properties of the antiferromagnetic q-state Potts model, and have studied the q-color problem with the result which supports Mattis' recent conjecture of entropy for the n -dimensional q-state Potts antiferromagnet. We also find a general solution for the q-color problem in d dimensions.

Monte Carlo Methodology Serves Up a Software Success

NASA Technical Reports Server (NTRS)

2003-01-01

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Monte Carlo simulations of secondary electron emission due to ion beam milling

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

Mahady, Kyle; Tan, Shida; Greenzweig, Yuval

We present a Monte Carlo simulation study of secondary electron emission resulting from focused ion beam milling of a copper target. The basis of this study is a simulation code which simulates ion induced excitation and emission of secondary electrons, in addition to simulating focused ion beam sputtering and milling. This combination of features permits the simulation of the interaction between secondary electron emission, and the evolving target geometry as the ion beam sputters material. Previous ion induced SE Monte Carlo simulation methods have been restricted to predefined target geometries, while the dynamic target in the presented simulations makes thismore » study relevant to image formation in ion microscopy, and chemically assisted ion beam etching, where the relationship between sputtering, and its effects on secondary electron emission, is important. We focus on a copper target, and validate our simulation against experimental data for a range of: noble gas ions, ion energies, ion/substrate angles and the energy distribution of the secondary electrons. We then provide a detailed account of the emission of secondary electrons resulting from ion beam milling; we quantify both the evolution of the yield as high aspect ratio valleys are milled, as well as the emission of electrons within these valleys that do not escape the target, but which are important to the secondary electron contribution to chemically assisted ion induced etching.« less

Monte Carlo simulations shed light on Bathsheba's suspect breast.

PubMed

Heijblom, Michelle; Meijer, Linda M; van Leeuwen, Ton G; Steenbergen, Wiendelt; Manohar, Srirang

2014-05-01

In 1654, Rembrandt van Rijn painted his famous painting Bathsheba at her Bath. Over the years, the depiction of Bathsheba's left breast and especially the presence of local discoloration, has generated debate on whether Rembrandt's Bathsheba suffered from breast cancer. Historical, medical and artistic arguments appeared to be not sufficient to prove if Bathsheba's model truly suffered from breast cancer. However, the bluish discoloration of the breast is an intriguing aspect from a biomedical optics point of view that might help us ending the old debate. By using Monte Carlo simulations in combination with the retinex theory of color vision, we showed that is highly unlikely that breast cancer results in a local bluish discoloration of the skin as is present on Bathsheba's breast. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

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

Brown, Forrest B.

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. Thesemore » lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo

Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.

PubMed

Berry, Hugues

2002-10-01

Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes.

Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.

PubMed Central

Berry, Hugues

2002-01-01

Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes. PMID:12324410

Numerical heating in Particle-In-Cell simulations with Monte Carlo binary collisions

NASA Astrophysics Data System (ADS)

Alves, E. Paulo; Mori, Warren; Fiuza, Frederico

2017-10-01

The binary Monte Carlo collision (BMCC) algorithm is a robust and popular method to include Coulomb collision effects in Particle-in-Cell (PIC) simulations of plasmas. While a number of works have focused on extending the validity of the model to different physical regimes of temperature and density, little attention has been given to the fundamental coupling between PIC and BMCC algorithms. Here, we show that the coupling between PIC and BMCC algorithms can give rise to (nonphysical) numerical heating of the system, that can be far greater than that observed when these algorithms operate independently. This deleterious numerical heating effect can significantly impact the evolution of the simulated system particularly for long simulation times. In this work, we describe the source of this numerical heating, and derive scaling laws for the numerical heating rates based on the numerical parameters of PIC-BMCC simulations. We compare our theoretical scalings with PIC-BMCC numerical experiments, and discuss strategies to minimize this parasitic effect. This work is supported by DOE FES under FWP 100237 and 100182.

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.

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.

Monte Carlo simulations of polyelectrolytes inside viral capsids.

PubMed

Angelescu, Daniel George; Bruinsma, Robijn; Linse, Per

2006-04-01

Structural features of polyelectrolytes as single-stranded RNA or double-stranded DNA confined inside viral capsids and the thermodynamics of the encapsidation of the polyelectrolyte into the viral capsid have been examined for various polyelectrolyte lengths by using a coarse-grained model solved by Monte Carlo simulations. The capsid was modeled as a spherical shell with embedded charges and the genome as a linear jointed chain of oppositely charged beads, and their sizes corresponded to those of a scaled-down T=3 virus. Counterions were explicitly included, but no salt was added. The encapisdated chain was found to be predominantly located at the inner capsid surface, in a disordered manner for flexible chains and in a spool-like structure for stiff chains. The distribution of the small ions was strongly dependent on the polyelectrolyte-capsid charge ratio. The encapsidation enthalpy was negative and its magnitude decreased with increasing polyelectrolyte length, whereas the encapsidation entropy displayed a maximum when the capsid and polyelectrolyte had equal absolute charge. The encapsidation process remained thermodynamically favorable for genome charges ca. 3.5 times the capsid charge. The chain stiffness had only a relatively weak effect on the thermodynamics of the encapsidation.

Particle behavior simulation in thermophoresis phenomena by direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

Wada, Takao

2014-07-01

A particle motion considering thermophoretic force is simulated by using direct simulation Monte Carlo (DSMC) method. Thermophoresis phenomena, which occur for a particle size of 1 μm, are treated in this paper. The problem of thermophoresis simulation is computation time which is proportional to the collision frequency. Note that the time step interval becomes much small for the simulation considering the motion of large size particle. Thermophoretic forces calculated by DSMC method were reported, but the particle motion was not computed because of the small time step interval. In this paper, the molecule-particle collision model, which computes the collision between a particle and multi molecules in a collision event, is considered. The momentum transfer to the particle is computed with a collision weight factor, where the collision weight factor means the number of molecules colliding with a particle in a collision event. The large time step interval is adopted by considering the collision weight factor. Furthermore, the large time step interval is about million times longer than the conventional time step interval of the DSMC method when a particle size is 1 μm. Therefore, the computation time becomes about one-millionth. We simulate the graphite particle motion considering thermophoretic force by DSMC-Neutrals (Particle-PLUS neutral module) with above the collision weight factor, where DSMC-Neutrals is commercial software adopting DSMC method. The size and the shape of the particle are 1 μm and a sphere, respectively. The particle-particle collision is ignored. We compute the thermophoretic forces in Ar and H2 gases of a pressure range from 0.1 to 100 mTorr. The results agree well with Gallis' analytical results. Note that Gallis' analytical result for continuum limit is the same as Waldmann's result.

Canopy polarized BRDF simulation based on non-stationary Monte Carlo 3-D vector RT modeling

NASA Astrophysics Data System (ADS)

Kallel, Abdelaziz; Gastellu-Etchegorry, Jean Philippe

2017-03-01

Vector radiative transfer (VRT) has been largely used to simulate polarized reflectance of atmosphere and ocean. However it is still not properly used to describe vegetation cover polarized reflectance. In this study, we try to propose a 3-D VRT model based on a modified Monte Carlo (MC) forward ray tracing simulation to analyze vegetation canopy reflectance. Two kinds of leaf scattering are taken into account: (i) Lambertian diffuse reflectance and transmittance and (ii) specular reflection. A new method to estimate the condition on leaf orientation to produce reflection is proposed, and its probability to occur, Pl,max, is computed. It is then shown that Pl,max is low, but when reflection happens, the corresponding radiance Stokes vector, Io, is very high. Such a phenomenon dramatically increases the MC variance and yields to an irregular reflectance distribution function. For better regularization, we propose a non-stationary MC approach that simulates reflection for each sunny leaf assuming that its orientation is randomly chosen according to its angular distribution. It is shown in this case that the average canopy reflection is proportional to Pl,max ·Io which produces a smooth distribution. Two experiments are conducted: (i) assuming leaf light polarization is only due to the Fresnel reflection and (ii) the general polarization case. In the former experiment, our results confirm that in the forward direction, canopy polarizes horizontally light. In addition, they show that in inclined forward direction, diagonal polarization can be observed. In the latter experiment, polarization is produced in all orientations. It is particularly pointed out that specular polarization explains just a part of the forward polarization. Diffuse scattering polarizes light horizontally and vertically in forward and backward directions, respectively. Weak circular polarization signal is also observed near the backscattering direction. Finally, validation of the non

Monte-Carlo background simulations of present and future detectors in x-ray astronomy

NASA Astrophysics Data System (ADS)

Tenzer, C.; Kendziorra, E.; Santangelo, A.

2008-07-01

Reaching a low-level and well understood internal instrumental background is crucial for the scientific performance of an X-ray detector and, therefore, a main objective of the instrument designers. Monte-Carlo simulations of the physics processes and interactions taking place in a space-based X-ray detector as a result of its orbital environment can be applied to explain the measured background of existing missions. They are thus an excellent tool to predict and optimize the background of future observatories. Weak points of a design and the main sources of the background can be identified and methods to reduce them can be implemented and studied within the simulations. Using the Geant4 Monte-Carlo toolkit, we have created a simulation environment for space-based detectors and we present results of such background simulations for XMM-Newton's EPIC pn-CCD camera. The environment is also currently used to estimate and optimize the background of the future instruments Simbol-X and eRosita.

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

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

Lai, Chao-Jen, E-mail: cjlai3711@gmail.com; Zhong, Yuncheng; Yi, Ying

2015-06-15

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimatemore » average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm{sup 2} field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

PubMed Central

Lai, Chao-Jen; Zhong, Yuncheng; Yi, Ying; Wang, Tianpeng; Shaw, Chris C.

2015-01-01

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm2 field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical measurements

Validation of Cross Sections for Monte Carlo Simulation of the Photoelectric Effect

NASA Astrophysics Data System (ADS)

Han, Min Cheol; Kim, Han Sung; Pia, Maria Grazia; Basaglia, Tullio; Batič, Matej; Hoff, Gabriela; Kim, Chan Hyeong; Saracco, Paolo

2016-04-01

Several total and partial photoionization cross section calculations, based on both theoretical and empirical approaches, are quantitatively evaluated with statistical analyses using a large collection of experimental data retrieved from the literature to identify the state of the art for modeling the photoelectric effect in Monte Carlo particle transport. Some of the examined cross section models are available in general purpose Monte Carlo systems, while others have been implemented and subjected to validation tests for the first time to estimate whether they could improve the accuracy of particle transport codes. The validation process identifies Scofield's 1973 non-relativistic calculations, tabulated in the Evaluated Photon Data Library (EPDL), as the one best reproducing experimental measurements of total cross sections. Specialized total cross section models, some of which derive from more recent calculations, do not provide significant improvements. Scofield's non-relativistic calculations are not surpassed regarding the compatibility with experiment of K and L shell photoionization cross sections either, although in a few test cases Ebel's parameterization produces more accurate results close to absorption edges. Modifications to Biggs and Lighthill's parameterization implemented in Geant4 significantly reduce the accuracy of total cross sections at low energies with respect to its original formulation. The scarcity of suitable experimental data hinders a similar extensive analysis for the simulation of the photoelectron angular distribution, which is limited to a qualitative appraisal.

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

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

Comparison of penumbra regions produced by ancient Gamma knife model C and Gamma ART 6000 using Monte Carlo MCNP6 simulation.

PubMed

Banaee, Nooshin; Asgari, Sepideh; Nedaie, Hassan Ali

2018-07-01

The accuracy of penumbral measurements in radiotherapy is pivotal because dose planning computers require accurate data to adequately modeling the beams, which in turn are used to calculate patient dose distributions. Gamma knife is a non-invasive intracranial technique based on principles of the Leksell stereotactic system for open deep brain surgeries, invented and developed by Professor Lars Leksell. The aim of this study is to compare the penumbra widths of Leksell Gamma Knife model C and Gamma ART 6000. Initially, the structure of both systems were simulated by using Monte Carlo MCNP6 code and after validating the accuracy of simulation, beam profiles of different collimators were plotted. MCNP6 beam profile calculations showed that the penumbra values of Leksell Gamma knife model C and Gamma ART 6000 for 18, 14, 8 and 4 mm collimators are 9.7, 7.9, 4.3, 2.6 and 8.2, 6.9, 3.6, 2.4, respectively. The results of this study showed that since Gamma ART 6000 has larger solid angle in comparison with Gamma Knife model C, it produces better beam profile penumbras than Gamma Knife model C in the direct plane. Copyright © 2017 Elsevier Ltd. All rights reserved.

Monte Carlo simulation study of positron generation in ultra-intense laser-solid interactions

NASA Astrophysics Data System (ADS)