Metropolis Methods for Quantum Monte Carlo Simulations
Ceperley, D. M.
2003-01-01
Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
Quantum Monte Carlo simulation
Wang, Yazhen
2011-01-01
Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for the estimator. The theory is used to design a computational scheme for minimizing the mean square er...
Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo
Energy Technology Data Exchange (ETDEWEB)
Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)
2011-07-01
This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)
Bardenet, R.
2012-01-01
ISBN:978-2-7598-1032-1; International audience; Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC) methods. We give intuition on the theoretic...
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
Multi-pass Monte Carlo simulation method in nuclear transmutations.
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.
Lectures on Monte Carlo methods
Madras, Neal
2001-01-01
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati
The Monte Carlo Simulation Method for System Reliability and Risk Analysis
Zio, Enrico
2013-01-01
Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...
Applications of Monte Carlo Methods in Calculus.
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
Exact special twist method for quantum Monte Carlo simulations
Dagrada, Mario; Karakuzu, Seher; Vildosola, Verónica Laura; Casula, Michele; Sorella, Sandro
2016-12-01
We present a systematic investigation of the special twist method introduced by Rajagopal et al. [Phys. Rev. B 51, 10591 (1995), 10.1103/PhysRevB.51.10591] for reducing finite-size effects in correlated calculations of periodic extended systems with Coulomb interactions and Fermi statistics. We propose a procedure for finding special twist values which, at variance with previous applications of this method, reproduce the energy of the mean-field infinite-size limit solution within an adjustable (arbitrarily small) numerical error. This choice of the special twist is shown to be the most accurate single-twist solution for curing one-body finite-size effects in correlated calculations. For these reasons we dubbed our procedure "exact special twist" (EST). EST only needs a fully converged independent-particles or mean-field calculation within the primitive cell and a simple fit to find the special twist along a specific direction in the Brillouin zone. We first assess the performances of EST in a simple correlated model such as the three-dimensional electron gas. Afterwards, we test its efficiency within ab initio quantum Monte Carlo simulations of metallic elements of increasing complexity. We show that EST displays an overall good performance in reducing finite-size errors comparable to the widely used twist average technique but at a much lower computational cost since it involves the evaluation of just one wave function. We also demonstrate that the EST method shows similar performances in the calculation of correlation functions, such as the ionic forces for structural relaxation and the pair radial distribution function in liquid hydrogen. Our conclusions point to the usefulness of EST for correlated supercell calculations; our method will be particularly relevant when the physical problem under consideration requires large periodic cells.
Mean field simulation for Monte Carlo integration
Del Moral, Pierre
2013-01-01
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko
Efficient kinetic Monte Carlo simulation
Schulze, Tim P.
2008-02-01
This paper concerns kinetic Monte Carlo (KMC) algorithms that have a single-event execution time independent of the system size. Two methods are presented—one that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the Marsaglia-Norman-Cannon algorithm. The resulting algorithms apply to models with rates that are determined by the local environment but are otherwise arbitrary, time-dependent and spatially heterogeneous. While especially useful for crystal growth simulation, the algorithms are presented from the point of view that KMC is the numerical task of simulating a single realization of a Markov process, allowing application to a broad range of areas where heterogeneous random walks are the dominate simulation cost.
Energy Technology Data Exchange (ETDEWEB)
Morillon, B.
1996-12-31
With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.
An introduction to Monte Carlo methods
Walter, J. -C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim
An introduction to Monte Carlo methods
Walter, J. -C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim
Monte Carlo methods for electromagnetics
Sadiku, Matthew NO
2009-01-01
Until now, novices had to painstakingly dig through the literature to discover how to use Monte Carlo techniques for solving electromagnetic problems. Written by one of the foremost researchers in the field, Monte Carlo Methods for Electromagnetics provides a solid understanding of these methods and their applications in electromagnetic computation. Including much of his own work, the author brings together essential information from several different publications.Using a simple, clear writing style, the author begins with a historical background and review of electromagnetic theory. After addressing probability and statistics, he introduces the finite difference method as well as the fixed and floating random walk Monte Carlo methods. The text then applies the Exodus method to Laplace's and Poisson's equations and presents Monte Carlo techniques for handing Neumann problems. It also deals with whole field computation using the Markov chain, applies Monte Carlo methods to time-varying diffusion problems, and ...
Lee, Anthony; Yau, Christopher; Giles, Michael B; Doucet, Arnaud; Holmes, Christopher C
2010-12-01
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.
Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water
Gergely, John Robert
2009-01-01
Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…
Monte carlo simulation for soot dynamics
Zhou, Kun
2012-01-01
A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
MONTE CARLO METHOD AND APPLICATION IN @RISK SIMULATION SYSTEM
Directory of Open Access Journals (Sweden)
Gabriela Ižaríková
2015-12-01
Full Text Available The article is an example of using the software simulation @Risk designed for simulation in Microsoft Excel spread sheet, demonstrated the possibility of its usage in order to show a universal method of solving problems. The simulation is experimenting with computer models based on the real production process in order to optimize the production processes or the system. The simulation model allows performing a number of experiments, analysing them, evaluating, optimizing and afterwards applying the results to the real system. A simulation model in general is presenting modelling system by using mathematical formulations and logical relations. In the model is possible to distinguish controlled inputs (for instance investment costs and random outputs (for instance demand, which are by using a model transformed into outputs (for instance mean value of profit. In case of a simulation experiment at the beginning are chosen controlled inputs and random (stochastic outputs are generated randomly. Simulations belong into quantitative tools, which can be used as a support for a decision making.
Sharma, Anupam; Long, Lyle N.
2004-10-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.
Simulação do equilíbrio: o método de Monte Carlo Equilibrium simulation: Monte Carlo method
Directory of Open Access Journals (Sweden)
Alejandro López-Castillo
2007-01-01
Full Text Available We make several simulations using the Monte Carlo method in order to obtain the chemical equilibrium for several first-order reactions and one second-order reaction. We study several direct, reverse and consecutive reactions. These simulations show the fluctuations and relaxation time and help to understand the solution of the corresponding differential equations of chemical kinetics. This work was done in an undergraduate physical chemistry course at UNIFIEO.
Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources
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.
Proton Upset Monte Carlo Simulation
O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.
2009-01-01
The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.
Simulations of a typical CMOS amplifier circuit using the Monte Carlo method
Borges, Jacques Cousteau da Silva
2016-01-01
In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence...
GPU-accelerated Monte Carlo simulation of particle coagulation based on the inverse method
Wei, J.; Kruis, F. E.
2013-09-01
Simulating particle coagulation using Monte Carlo methods is in general a challenging computational task due to its numerical complexity and the computing cost. Currently, the lowest computing costs are obtained when applying a graphic processing unit (GPU) originally developed for speeding up graphic processing in the consumer market. In this article we present an implementation of accelerating a Monte Carlo method based on the Inverse scheme for simulating particle coagulation on the GPU. The abundant data parallelism embedded within the Monte Carlo method is explained as it will allow an efficient parallelization of the MC code on the GPU. Furthermore, the computation accuracy of the MC on GPU was validated with a benchmark, a CPU-based discrete-sectional method. To evaluate the performance gains by using the GPU, the computing time on the GPU against its sequential counterpart on the CPU were compared. The measured speedups show that the GPU can accelerate the execution of the MC code by a factor 10-100, depending on the chosen particle number of simulation particles. The algorithm shows a linear dependence of computing time with the number of simulation particles, which is a remarkable result in view of the n2 dependence of the coagulation.
Shahla Ahmadi; Hossein Rajabi; Farshid Babapoor; Faraz Kalantari
2011-01-01
Introduction: The main goal of SPECT imaging is to determine activity distribution inside the organs of the body. However, due to photon attenuation, it is almost impossible to do a quantitative study. In this paper, we suggest a mathematical relationship between activity distribution and its corresponding projections using a transfer matrix. Monte Carlo simulation was used to find a precise transfer matrix including the effects of photon attenuation. Material and Methods: List mode output o...
Methods for Monte Carlo simulation of the exospheres of the moon and Mercury
Hodges, R. R., Jr.
1980-01-01
A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.
Simulation model based on Monte Carlo method for traffic assignment in local area road network
Institute of Scientific and Technical Information of China (English)
Yuchuan DU; Yuanjing GENG; Lijun SUN
2009-01-01
For a local area road network, the available traffic data of traveling are the flow volumes in the key intersections, not the complete OD matrix. Considering the circumstance characteristic and the data availability of a local area road network, a new model for traffic assignment based on Monte Carlo simulation of intersection turning movement is provided in this paper. For good stability in temporal sequence, turning ratio is adopted as the important parameter of this model. The formulation for local area road network assignment problems is proposed on the assumption of random turning behavior. The traffic assignment model based on the Monte Carlo method has been used in traffic analysis for an actual urban road network. The results comparing surveying traffic flow data and determining flow data by the previous model verify the applicability and validity of the proposed methodology.
A brief introduction to Monte Carlo simulation.
Bonate, P L
2001-01-01
Simulation affects our life every day through our interactions with the automobile, airline and entertainment industries, just to name a few. The use of simulation in drug development is relatively new, but its use is increasing in relation to the speed at which modern computers run. One well known example of simulation in drug development is molecular modelling. Another use of simulation that is being seen recently in drug development is Monte Carlo simulation of clinical trials. Monte Carlo simulation differs from traditional simulation in that the model parameters are treated as stochastic or random variables, rather than as fixed values. The purpose of this paper is to provide a brief introduction to Monte Carlo simulation methods.
A general method for spatially coarse-graining Metropolis Monte Carlo simulations onto a lattice.
Liu, Xiao; Seider, Warren D; Sinno, Talid
2013-03-21
A recently introduced method for coarse-graining standard continuous Metropolis Monte Carlo simulations of atomic or molecular fluids onto a rigid lattice of variable scale [X. Liu, W. D. Seider, and T. Sinno, Phys. Rev. E 86, 026708 (2012)] is further analyzed and extended. The coarse-grained Metropolis Monte Carlo technique is demonstrated to be highly consistent with the underlying full-resolution problem using a series of detailed comparisons, including vapor-liquid equilibrium phase envelopes and spatial density distributions for the Lennard-Jones argon and simple point charge water models. In addition, the principal computational bottleneck associated with computing a coarse-grained interaction function for evolving particle positions on the discretized domain is addressed by the introduction of new closure approximations. In particular, it is shown that the coarse-grained potential, which is generally a function of temperature and coarse-graining level, can be computed at multiple temperatures and scales using a single set of free energy calculations. The computational performance of the method relative to standard Monte Carlo simulation is also discussed.
Equilibrium Statistics: Monte Carlo Methods
Kröger, Martin
Monte Carlo methods use random numbers, or ‘random’ sequences, to sample from a known shape of a distribution, or to extract distribution by other means. and, in the context of this book, to (i) generate representative equilibrated samples prior being subjected to external fields, or (ii) evaluate high-dimensional integrals. Recipes for both topics, and some more general methods, are summarized in this chapter. It is important to realize, that Monte Carlo should be as artificial as possible to be efficient and elegant. Advanced Monte Carlo ‘moves’, required to optimize the speed of algorithms for a particular problem at hand, are outside the scope of this brief introduction. One particular modern example is the wavelet-accelerated MC sampling of polymer chains [406].
Reliability Assessment of Active Distribution System Using Monte Carlo Simulation Method
Directory of Open Access Journals (Sweden)
Shaoyun Ge
2014-01-01
Full Text Available In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.
GPU implementation of the Rosenbluth generation method for static Monte Carlo simulations
Guo, Yachong; Baulin, Vladimir A.
2017-07-01
We present parallel version of Rosenbluth Self-Avoiding Walk generation method implemented on Graphics Processing Units (GPUs) using CUDA libraries. The method scales almost linearly with the number of CUDA cores and the method efficiency has only hardware limitations. The method is introduced in two realizations: on a cubic lattice and in real space. We find a good agreement between serial and parallel implementations and consistent results between lattice and real space realizations of the method for linear chain statistics. The developed GPU implementations of Rosenbluth algorithm can be used in Monte Carlo simulations and other computational methods that require large sampling of molecules conformations.
On-the-fly nuclear data processing methods for Monte Carlo simulations of fast spectrum systems
Energy Technology Data Exchange (ETDEWEB)
Walsh, Jon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-08-31
The presentation summarizes work performed over summer 2015 related to Monte Carlo simulations. A flexible probability table interpolation scheme has been implemented and tested with results comparing favorably to the continuous phase-space on-the-fly approach.
Energy Technology Data Exchange (ETDEWEB)
Datema, C.P. E-mail: c.datema@iri.tudelft.nl; Bom, V.R.; Eijk, C.W.E. van
2002-08-01
Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.
Datema, C P; Eijk, C W E
2002-01-01
Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.
A virtual source method for Monte Carlo simulation of Gamma Knife Model C
Energy Technology Data Exchange (ETDEWEB)
Kim, Tae Hoon; Kim, Yong Kyun [Hanyang University, Seoul (Korea, Republic of); Chung, Hyun Tai [Seoul National University College of Medicine, Seoul (Korea, Republic of)
2016-05-15
The Monte Carlo simulation method has been used for dosimetry of radiation treatment. Monte Carlo simulation is the method that determines paths and dosimetry of particles using random number. Recently, owing to the ability of fast processing of the computers, it is possible to treat a patient more precisely. However, it is necessary to increase the simulation time to improve the efficiency of accuracy uncertainty. When generating the particles from the cobalt source in a simulation, there are many particles cut off. So it takes time to simulate more accurately. For the efficiency, we generated the virtual source that has the phase space distribution which acquired a single gamma knife channel. We performed the simulation using the virtual sources on the 201 channel and compared the measurement with the simulation using virtual sources and real sources. A virtual source file was generated to reduce the simulation time of a Gamma Knife Model C. Simulations with a virtual source executed about 50 times faster than the original source code and there was no statistically significant difference in simulated results.
The adaptation method in the Monte Carlo simulation for computed tomography
Energy Technology Data Exchange (ETDEWEB)
Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)
2015-06-15
The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
The adaptation method in the Monte Carlo simulation for computed tomography
Directory of Open Access Journals (Sweden)
Hyounggun Lee
2015-06-01
Full Text Available The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT. To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA and a human-like voxel phantom (KTMAN-2 (Los Alamos National Laboratory, Los Alamos, NM, USA. For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations—assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
Simulations of a typical CMOS amplifier circuit using the Monte Carlo method
Directory of Open Access Journals (Sweden)
Borges, Jacques Cousteau da Silva
2016-11-01
Full Text Available In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence of the threshold voltage Vth was analyzed.
Three-dimensional hypersonic rarefied flow calculations using direct simulation Monte Carlo method
Celenligil, M. Cevdet; Moss, James N.
1993-01-01
A summary of three-dimensional simulations on the hypersonic rarefied flows in an effort to understand the highly nonequilibrium flows about space vehicles entering the Earth's atmosphere for a realistic estimation of the aerothermal loads is presented. Calculations are performed using the direct simulation Monte Carlo method with a five-species reacting gas model, which accounts for rotational and vibrational internal energies. Results are obtained for the external flows about various bodies in the transitional flow regime. For the cases considered, convective heating, flowfield structure and overall aerodynamic coefficients are presented and comparisons are made with the available experimental data. The agreement between the calculated and measured results are very good.
Shuttle vertical fin flowfield by the direct simulation Monte Carlo method
Hueser, J. E.; Brock, F. J.; Melfi, L. T.
1985-01-01
The flow properties in a model flowfield, simulating the shuttle vertical fin, determined using the Direct Simulation Monte Carlo method. The case analyzed corresponds to an orbit height of 225 km with the freestream velocity vector orthogonal to the fin surface. Contour plots of the flowfield distributions of density, temperature, velocity and flow angle are presented. The results also include mean molecular collision frequency (which reaches 1/60 sec near the surface), collision frequency density (approaches 7 x 10 to the 18/cu m sec at the surface) and the mean free path (19 m at the surface).
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Directory of Open Access Journals (Sweden)
Shahla Ahmadi
2011-09-01
Full Text Available Introduction: The main goal of SPECT imaging is to determine activity distribution inside the organs of the body. However, due to photon attenuation, it is almost impossible to do a quantitative study. In this paper, we suggest a mathematical relationship between activity distribution and its corresponding projections using a transfer matrix. Monte Carlo simulation was used to find a precise transfer matrix including the effects of photon attenuation. Material and Methods: List mode output of the SIMIND Monte Carlo simulator was used to find the relationship between activity distribution and pixel values in projections. The MLEM iterative reconstruction method was then used to reconstruct the activity distribution from the projections. Attenuation-free projections were also simulated. Reconstructed images from these projections were used as reference images. Our suggested attenuation correction method was evaluated using three different phantom configurations: uniform activity and uniform attenuation phantom, non-uniform activity and non-uniform attenuation phantom, and NCAT torso phantom. The mean pixel values and fits between profiles were used as quantitative parameters. Results: Images free from attenuation-related artifacts were reconstructed by our suggested method. A significant increase in pixel values was found after attenuation correction. Better fits between profiles of the corrected and reference images were also found for all phantom configurations. Discussion and Conclusion: Using a Monte Carlo method, it is possible to find the most precise relationship between activity distribution and its projections. Therefore, it is possible to create mathematical projections that include the effects of attenuation. This helps to have a more realistic comparison between mathematical and real projections, which is a necessary step for image reconstruction using MLEM. This results in images with much better quantitative accuracy at a cost of
Comparing Subspace Methods for Closed Loop Subspace System Identification by Monte Carlo Simulations
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David Di Ruscio
2009-10-01
Full Text Available A novel promising bootstrap subspace system identification algorithm for both open and closed loop systems is presented. An outline of the SSARX algorithm by Jansson (2003 is given and a modified SSARX algorithm is presented. Some methods which are consistent for closed loop subspace system identification presented in the literature are discussed and compared to a recently published subspace algorithm which works for both open as well as for closed loop data, i.e., the DSR_e algorithm as well as the bootstrap method. Experimental comparisons are performed by Monte Carlo simulations.
Puibasset, Joël
2005-04-01
The effect of confinement on phase behavior of simple fluids is still an area of intensive research. In between experiment and theory, molecular simulation is a powerful tool to study the effect of confinement in realistic porous materials, containing some disorder. Previous simulation works aiming at establishing the phase diagram of a confined Lennard-Jones-type fluid, concentrated on simple pore geometries (slits or cylinders). The development of the Gibbs ensemble Monte Carlo technique by Panagiotopoulos [Mol. Phys. 61, 813 (1987)], greatly favored the study of such simple geometries for two reasons. First, the technique is very efficient to calculate the phase diagram, since each run (at a given temperature) converges directly to an equilibrium between a gaslike and a liquidlike phase. Second, due to volume exchange procedure between the two phases, at least one invariant direction of space is required for applicability of this method, which is the case for slits or cylinders. Generally, the introduction of some disorder in such simple pores breaks the initial invariance in one of the space directions and prevents to work in the Gibbs ensemble. The simulation techniques for such disordered systems are numerous (grand canonical Monte Carlo, molecular dynamics, histogram reweighting, N-P-T+test method, Gibbs-Duhem integration procedure, etc.). However, the Gibbs ensemble technique, which gives directly the coexistence between phases, was never generalized to such systems. In this work, we focus on two weakly disordered pores for which a modified Gibbs ensemble Monte Carlo technique can be applied. One of the pores is geometrically undulated, whereas the second is cylindrical but presents a chemical variation which gives rise to a modulation of the wall potential. In the first case almost no change in the phase diagram is observed, whereas in the second strong modifications are reported.
A numerical study of rays in random media. [Monte Carlo method simulation
Youakim, M. Y.; Liu, C. H.; Yeh, K. C.
1973-01-01
Statistics of electromagnetic rays in a random medium are studied numerically by the Monte Carlo method. Two dimensional random surfaces with prescribed correlation functions are used to simulate the random media. Rays are then traced in these sample media. Statistics of the ray properties such as the ray positions and directions are computed. Histograms showing the distributions of the ray positions and directions at different points along the ray path as well as at given points in space are given. The numerical experiment is repeated for different cases corresponding to weakly and strongly random media with isotropic and anisotropic irregularities. Results are compared with those derived from theoretical investigations whenever possible.
Application of the direct simulation Monte Carlo method to the full shuttle geometry
Bird, G. A.
1990-01-01
A new set of programs has been developed for the application of the direct simulation Monte Carlo (or DSMC) method to rarefied gas flows with complex three-dimensional boundaries. The programs are efficient in terms of the computational load and also in terms of the effort required to set up particular cases. This efficiency is illustrated through computations of the flow about the Shuttle Orbiter. The general flow features are illustrated for altitudes from 170 to 100 km. Also, the computed lift-drag ratio during re-entry is compared with flight measurements.
Zhang, G.; Lu, D.; Webster, C.
2014-12-01
The rational management of oil and gas reservoir requires an understanding of its response to existing and planned schemes of exploitation and operation. Such understanding requires analyzing and quantifying the influence of the subsurface uncertainties on predictions of oil and gas production. As the subsurface properties are typically heterogeneous causing a large number of model parameters, the dimension independent Monte Carlo (MC) method is usually used for uncertainty quantification (UQ). Recently, multilevel Monte Carlo (MLMC) methods were proposed, as a variance reduction technique, in order to improve computational efficiency of MC methods in UQ. In this effort, we propose a new acceleration approach for MLMC method to further reduce the total computational cost by exploiting model hierarchies. Specifically, for each model simulation on a new added level of MLMC, we take advantage of the approximation of the model outputs constructed based on simulations on previous levels to provide better initial states of new simulations, which will help improve efficiency by, e.g. reducing the number of iterations in linear system solving or the number of needed time-steps. This is achieved by using mesh-free interpolation methods, such as Shepard interpolation and radial basis approximation. Our approach is applied to a highly heterogeneous reservoir model from the tenth SPE project. The results indicate that the accelerated MLMC can achieve the same accuracy as standard MLMC with a significantly reduced cost.
Adiabatic optimization versus diffusion Monte Carlo methods
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
Self-learning Monte Carlo method
Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang
2017-01-01
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. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup.
A subset multicanonical Monte Carlo method for simulating rare failure events
Chen, Xinjuan; Li, Jinglai
2017-09-01
Estimating failure probabilities of engineering systems is an important problem in many engineering fields. In this work we consider such problems where the failure probability is extremely small (e.g. ≤10-10). In this case, standard Monte Carlo methods are not feasible due to the extraordinarily large number of samples required. To address these problems, we propose an algorithm that combines the main ideas of two very powerful failure probability estimation approaches: the subset simulation (SS) and the multicanonical Monte Carlo (MMC) methods. Unlike the standard MMC which samples in the entire domain of the input parameter in each iteration, the proposed subset MMC algorithm adaptively performs MMC simulations in a subset of the state space, which improves the sampling efficiency. With numerical examples we demonstrate that the proposed method is significantly more efficient than both of the SS and the MMC methods. Moreover, like the standard MMC, the proposed algorithm can reconstruct the complete distribution function of the parameter of interest and thus can provide more information than just the failure probabilities of the systems.
(U) Introduction to Monte Carlo Methods
Energy Technology Data Exchange (ETDEWEB)
Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-20
Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.
Institute of Scientific and Technical Information of China (English)
Du Gang; Liu Xiao-Yan; Han Ru-Qi
2006-01-01
A two-dimensional (2D) full band self-consistent ensemble Monte Carlo (MC) method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to extend the MC method to the study of nano-scale semiconductor devices with obvious quantum mechanical (QM) effects. The quantum effects both in real space and momentum space in nano-scale semiconductor devices can be simulated. The effective mobility in the inversion layer of n and p channel MOSFET is simulated and compared with experimental data to verify this method. With this method 50nm ultra thin body silicon on insulator MOSFET are simulated. Results indicate that this method can be used to simulate the 2D QM effects in semiconductor devices including tunnelling effect.
Wind Turbine Placement Optimization by means of the Monte Carlo Simulation Method
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S. Brusca
2014-01-01
Full Text Available This paper defines a new procedure for optimising wind farm turbine placement by means of Monte Carlo simulation method. To verify the algorithm’s accuracy, an experimental wind farm was tested in a wind tunnel. On the basis of experimental measurements, the error on wind farm power output was less than 4%. The optimization maximises the energy production criterion; wind turbines’ ground positions were used as independent variables. Moreover, the mathematical model takes into account annual wind intensities and directions and wind turbine interaction. The optimization of a wind farm on a real site was carried out using measured wind data, dominant wind direction, and intensity data as inputs to run the Monte Carlo simulations. There were 30 turbines in the wind park, each rated at 20 kW. This choice was based on wind farm economics. The site was proportionally divided into 100 square cells, taking into account a minimum windward and crosswind distance between the turbines. The results highlight that the dominant wind intensity factor tends to overestimate the annual energy production by about 8%. Thus, the proposed method leads to a more precise annual energy evaluation and to a more optimal placement of the wind turbines.
A method based on Monte Carlo simulation for the determination of the G(E) function.
Chen, Wei; Feng, Tiancheng; Liu, Jun; Su, Chuanying; Tian, Yanjie
2015-02-01
The G(E) function method is a spectrometric method for the exposure dose estimation; this paper describes a method based on Monte Carlo method to determine the G(E) function of a 4″ × 4″ × 16″ NaI(Tl) detector. Simulated spectrums of various monoenergetic gamma rays in the region of 40 -3200 keV and the corresponding deposited energy in an air ball in the energy region of full-energy peak were obtained using Monte Carlo N-particle Transport Code. Absorbed dose rate in air was obtained according to the deposited energy and divided by counts of corresponding full-energy peak to get the G(E) function value at energy E in spectra. Curve-fitting software 1st0pt was used to determine coefficients of the G(E) function. Experimental results show that the calculated dose rates using the G(E) function determined by the authors' method are accordant well with those values obtained by ionisation chamber, with a maximum deviation of 6.31 %.
Sample Duplication Method for Monte Carlo Simulation of Large Reaction-Diffusion System
Institute of Scientific and Technical Information of China (English)
张红东; 陆建明; 杨玉良
1994-01-01
The sample duplication method for the Monte Carlo simulation of large reaction-diffusion system is proposed in this paper. It is proved that the sample duplication method will effectively raise the efficiency and statistical precision of the simulation without changing the kinetic behaviour of the reaction-diffusion system and the critical condition for the bifurcation of the steady-states. The method has been applied to the simulation of spatial and time dissipative structure of Brusselator under the Dirichlet boundary condition. The results presented in this paper definitely show that the sample duplication method provides a very efficient way to sol-’e the master equation of large reaction-diffusion system. For the case of two-dimensional system, it is found that the computation time is reduced at least by a factor of two orders of magnitude compared to the algorithm reported in literature.
A Variable Coefficient Method for Accurate Monte Carlo Simulation of Dynamic Asset Price
Li, Yiming; Hung, Chih-Young; Yu, Shao-Ming; Chiang, Su-Yun; Chiang, Yi-Hui; Cheng, Hui-Wen
2007-07-01
In this work, we propose an adaptive Monte Carlo (MC) simulation technique to compute the sample paths for the dynamical asset price. In contrast to conventional MC simulation with constant drift and volatility (μ,σ), our MC simulation is performed with variable coefficient methods for (μ,σ) in the solution scheme, where the explored dynamic asset pricing model starts from the formulation of geometric Brownian motion. With the method of simultaneously updated (μ,σ), more than 5,000 runs of MC simulation are performed to fulfills basic accuracy of the large-scale computation and suppresses statistical variance. Daily changes of stock market index in Taiwan and Japan are investigated and analyzed.
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Matsumiya, T. [Nippon Steel Corporation, Tokyo (Japan)
1996-08-20
The Monte Carlo method was used to simulate an equilibrium diagram, and structural formation of transformation and recrystallization. In simulating the Cu-A equilibrium diagram, the calculation was performed by laying 24 face centered cubic lattices including four lattice points in all of the three directions, and using a simulation cell consisting of lattice points of a total of 24{sup 3}{times}4 points. Although this method has a possibility to discover existence of an unknown phase as a result of the calculation, problems were found left in handling of lattice mitigation, and in simulation of phase diagrams over phases with different crystal structures. In simulation of the transformation and recrystallization, discussions were given on correspondence of 1MCS to time when the lattice point size is increased, and on handling of nucleus formation. As a result, it was estimated that in three-dimensional grain growth, the average grain size is proportional to 1/3 power of the MCS number, and the real time against 1MCS is proportional to three power of the lattice point size. 11 refs., 8 figs., 2 tabs.
Pavlyuchenkov, Ya; Henning, T; Guilloteau, St; Pietu, V; Launhardt, R; Dutrey, A
2007-01-01
We analyze the line radiative transfer in protoplanetary disks using several approximate methods and a well-tested Accelerated Monte Carlo code. A low-mass flaring disk model with uniform as well as stratified molecular abundances is adopted. Radiative transfer in low and high rotational lines of CO, C18O, HCO+, DCO+, HCN, CS, and H2CO is simulated. The corresponding excitation temperatures, synthetic spectra, and channel maps are derived and compared to the results of the Monte Carlo calculations. A simple scheme that describes the conditions of the line excitation for a chosen molecular transition is elaborated. We find that the simple LTE approach can safely be applied for the low molecular transitions only, while it significantly overestimates the intensities of the upper lines. In contrast, the Full Escape Probability (FEP) approximation can safely be used for the upper transitions ($J_{\\rm up} \\ga 3$) but it is not appropriate for the lowest transitions because of the maser effect. In general, the molec...
DSMC calculations for the double ellipse. [direct simulation Monte Carlo method
Moss, James N.; Price, Joseph M.; Celenligil, M. Cevdet
1990-01-01
The direct simulation Monte Carlo (DSMC) method involves the simultaneous computation of the trajectories of thousands of simulated molecules in simulated physical space. Rarefied flow about the double ellipse for test case 6.4.1 has been calculated with the DSMC method of Bird. The gas is assumed to be nonreacting nitrogen flowing at a 30 degree incidence with respect to the body axis, and for the surface boundary conditions, the wall is assumed to be diffuse with full thermal accommodation and at a constant wall temperature of 620 K. A parametric study is presented that considers the effect of variations of computational domain, gas model, cell size, and freestream density on surface quantities.
Monte Carlo Simulations: Number of Iterations and Accuracy
2015-07-01
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Versluis, R.; Dorsman, R.; Thielen, L.; Roos, M.E.
2009-01-01
A new approach for performing numerical direct simulation Monte Carlo (DSMC) simulations on turbomolecular pumps in the free molecular and transitional flow regimes is described. The chosen approach is to use surfaces that move relative to the grid to model the effect of rotors and stators on a gas
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method
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.
Rosenfeld, Anatoly; Wroe, Andrew; Carolan, Martin; Cornelius, Iwan
2006-01-01
In hadron therapy the spectra of secondary particles can be very broad in type and energy. The most accurate calculations of tissue equivalent (TE) absorbed dose and biological effect can be achieved using Monte Carlo (MC) simulations followed by the application of an appropriate radiobiological model. The verification of MC simulations is therefore an important quality assurance (QA) issue in dose planning. We propose a method of verification for MC dose calculations based on measurements of either the integral absorbed dose or the spectra of deposited energies from single secondary particles in non-TE material detectors embedded in a target of interest (phantom). This method was tested in boron neutron capture therapy and fast neutron therapy beams.
Time-quantifiable Monte Carlo method for simulating a magnetization-reversal process
Cheng, X. Z.; Jalil, M. B. A.; Lee, H. K.; Okabe, Y.
2005-09-01
We propose a time-quantifiable Monte Carlo (MC) method to simulate the thermally induced magnetization reversal for an isolated single domain particle system. The MC method involves the determination of density of states and the use of Master equation for time evolution. We derive an analytical factor to convert MC steps into real time intervals. Unlike a previous time-quantified MC method, our method is readily scalable to arbitrarily long time scales, and can be repeated for different temperatures with minimal computational effort. Based on the conversion factor, we are able to make a direct comparison between the results obtained from MC and Langevin dynamics methods and find excellent agreement between them. An analytical formula for the magnetization reversal time is also derived, which agrees very well with both numerical Langevin and time-quantified MC results, over a large temperature range and for parallel and oblique easy axis orientations.
Samejima, Masaki; Akiyoshi, Masanori; Mitsukuni, Koshichiro; Komoda, Norihisa
We propose a business scenario evaluation method using qualitative and quantitative hybrid model. In order to evaluate business factors with qualitative causal relations, we introduce statistical values based on propagation and combination of effects of business factors by Monte Carlo simulation. In propagating an effect, we divide a range of each factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we decide an effect of each arc using contribution degree and sum all effects. Through applied results to practical models, it is confirmed that there are no differences between results obtained by quantitative relations and results obtained by the proposed method at the risk rate of 5%.
Study of spatial resolution in a single GEM simulated by Monte-Carlo method
Lan-Lan, Yang; Shan-Le, MA; Pan-Pan, Zhang
2013-01-01
Spatial resolution is a significant factor in the GEM performance in view of X-rays radiography and UV, visible light imaging. Monte-Carlo method is used to investigate the spatial resolution determined by the transverse diffusion in the device. The simulation results indicate that the electrical parameters, such as the GEM voltages and the electric field at the drift and induction regions, only have minor effects on the spatial resolution. The geometrical parameters and the working gases chosen, on the other hand, are the main parameters that determine the spatial resolution. The spatial resolution is determined more on the drift and diffusion processes than on the avalanche process. Especially for the different working gases, the square root function of the ratio of the electron diffusion coefficient and the mobility has a significant effect on the spatial resolution.
Lu, Dan; Zhang, Guannan; Webster, Clayton; Barbier, Charlotte
2016-12-01
In this work, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.
Directory of Open Access Journals (Sweden)
Tsu-Ming Yeh
2013-10-01
Full Text Available Measurements are required to maintain the consistent quality of all finished and semi-finished products in a production line. Many firms in the automobile and general precision industries apply the TS 16949:2009 Technical Specifications and Measurement System Analysis (MSA manual to establish measurement systems. This work is undertaken to evaluate gauge repeatability and reproducibility (GR&R to verify the measuring ability and quality of the measurement frame, as well as to continuously improve and maintain the verification process. Nevertheless, the implementation of GR&R requires considerable time and manpower, and is likely to affect production adversely. In addition, the evaluation value for GR&R is always different owing to the sum of man-made and machine-made variations. Using a Monte Carlo simulation and the prediction of the repeatability and reproducibility of the measurement system analysis, this study aims to determine the distribution of %GR&R and the related number of distinct categories (ndc. This study uses two case studies of an automobile parts manufacturer and the combination of a Monte Carlo simulation, statistical bases, and the prediction of the repeatability and reproducibility of the measurement system analysis to determine the probability density function, the distribution of %GR&R, and the related number of distinct categories (ndc. The method used in this study could evaluate effectively the possible range of the GR&R of the measurement capability, in order to establish a prediction model for the evaluation of the measurement capacity of a measurement system.
A variance-reduced electrothermal Monte Carlo method for semiconductor device simulation
Energy Technology Data Exchange (ETDEWEB)
Muscato, Orazio; Di Stefano, Vincenza [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) Leibniz-Institut im Forschungsverbund Berlin e.V., Berlin (Germany)
2012-11-01
This paper is concerned with electron transport and heat generation in semiconductor devices. An improved version of the electrothermal Monte Carlo method is presented. This modification has better approximation properties due to reduced statistical fluctuations. The corresponding transport equations are provided and results of numerical experiments are presented.
Energy Technology Data Exchange (ETDEWEB)
Oramas Polo, I.
2014-07-01
This paper presents the simulation of the gamma camera Park Isocam II by Monte Carlo code SIMIND. This simulation allows detailed assessment of the functioning of the gamma camera. The parameters evaluated by means of the simulation are: the intrinsic uniformity with different window amplitudes, the system uniformity, the extrinsic spatial resolution, the maximum rate of counts, the intrinsic sensitivity, the system sensitivity, the energy resolution and the pixel size. The results of the simulation are compared and evaluated against the specifications of the manufacturer of the gamma camera and taking into account the National Protocol for Quality Control of Nuclear Medicine Instruments of the Cuban Medical Equipment Control Center. The simulation reported here demonstrates the validity of the SIMIND Monte Carlo code to evaluate the performance of the gamma camera Park Isocam II and as result a computational model of the camera has been obtained. (Author)
Numerical simulations of blast-impact problems using the direct simulation Monte Carlo method
Sharma, Anupam
There is an increasing need to design protective structures that can withstand or mitigate the impulsive loading due to the impact of a blast or a shock wave. A preliminary step in designing such structures is the prediction of the pressure loading on the structure. This is called the "load definition." This thesis is focused on a numerical approach to predict the load definition on arbitrary geometries for a given strength of the incident blast/shock wave. A particle approach, namely the Direct Simulation Monte Carlo (DSMC) method, is used as the numerical model. A three-dimensional, time-accurate DSMC flow solver is developed as a part of this study. Embedded surfaces, modeled as triangulations, are used to represent arbitrary-shaped structures. Several techniques to improve the computational efficiency of the algorithm of particle-structure interaction are presented. The code is designed using the Object Oriented Programming (OOP) paradigm. Domain decomposition with message passing is used to solve large problems in parallel. The solver is extensively validated against analytical results and against experiments. Two kinds of geometries, a box and an I-shaped beam are investigated for blast impact. These simulations are performed in both two- and three-dimensions. A major portion of the thesis is dedicated to studying the uncoupled fluid dynamics problem where the structure is assumed to remain stationary and intact during the simulation. A coupled, fluid-structure dynamics problem is solved in one spatial dimension using a simple, spring-mass-damper system to model the dynamics of the structure. A parametric study, by varying the mass, spring constant, and the damping coefficient, to study their effect on the loading and the displacement of the structure is also performed. Finally, the parallel performance of the solver is reported for three sample-size problems on two Beowulf clusters.
QUANTUM MONTE-CARLO SIMULATIONS - ALGORITHMS, LIMITATIONS AND APPLICATIONS
DERAEDT, H
1992-01-01
A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown
Quantum Monte Carlo Simulations : Algorithms, Limitations and Applications
Raedt, H. De
1992-01-01
A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G.
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states.
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states.
The Monte Carlo Method. Popular Lectures in Mathematics.
Sobol', I. M.
The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…
Kadoura, Ahmad
2011-06-06
Lennard‐Jones (L‐J) and Buckingham exponential‐6 (exp‐6) potential models were used to produce isotherms for methane at temperatures below and above critical one. Molecular simulation approach, particularly Monte Carlo simulations, were employed to create these isotherms working with both canonical and Gibbs ensembles. Experiments in canonical ensemble with each model were conducted to estimate pressures at a range of temperatures above methane critical temperature. Results were collected and compared to experimental data existing in literature; both models showed an elegant agreement with the experimental data. In parallel, experiments below critical temperature were run in Gibbs ensemble using L‐J model only. Upon comparing results with experimental ones, a good fit was obtained with small deviations. The work was further developed by adding some statistical studies in order to achieve better understanding and interpretation to the estimated quantities by the simulation. Methane phase diagrams were successfully reproduced by an efficient molecular simulation technique with different potential models. This relatively simple demonstration shows how powerful molecular simulation methods could be, hence further applications on more complicated systems are considered. Prediction of phase behavior of elemental sulfur in sour natural gases has been an interesting and challenging field in oil and gas industry. Determination of elemental sulfur solubility conditions helps avoiding all kinds of problems caused by its dissolution in gas production and transportation processes. For this purpose, further enhancement to the methods used is to be considered in order to successfully simulate elemental sulfur phase behavior in sour natural gases mixtures.
Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods
Ren, Wei; Liu, Hong; Jin, Shi
2014-12-01
In the rarefied gas dynamics, the DSMC method is one of the most popular numerical tools. It performs satisfactorily in simulating hypersonic flows surrounding re-entry vehicles and micro-/nano- flows. However, the computational cost is expensive, especially when Kn → 0. Even for flows in the near-continuum regime, pure DSMC simulations require a number of computational efforts for most cases. Albeit several DSMC/NS hybrid methods are proposed to deal with this, those methods still suffer from the boundary treatment, which may cause nonphysical solutions. Filbet and Jin [1] proposed a framework of new numerical methods of Boltzmann equation, called asymptotic preserving schemes, whose computational costs are affordable as Kn → 0. Recently, Ren et al. [2] realized the AP schemes with Monte Carlo methods (AP-DSMC), which have better performance than counterpart methods. In this paper, AP-DSMC is applied in simulating nonequilibrium hypersonic flows. Several numerical results are computed and analyzed to study the efficiency and capability of capturing complicated flow characteristics.
Lattice gauge theories and Monte Carlo simulations
Rebbi, Claudio
1983-01-01
This volume is the most up-to-date review on Lattice Gauge Theories and Monte Carlo Simulations. It consists of two parts. Part one is an introductory lecture on the lattice gauge theories in general, Monte Carlo techniques and on the results to date. Part two consists of important original papers in this field. These selected reprints involve the following: Lattice Gauge Theories, General Formalism and Expansion Techniques, Monte Carlo Simulations. Phase Structures, Observables in Pure Gauge Theories, Systems with Bosonic Matter Fields, Simulation of Systems with Fermions.
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc.
Quantum Monte Carlo methods algorithms for lattice models
Gubernatis, James; Werner, Philipp
2016-01-01
Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in ...
A backward Monte-Carlo method for time-dependent runaway electron simulations
Zhang, Guannan; del-Castillo-Negrete, Diego
2017-09-01
Kinetic descriptions of runaway electrons (REs) are usually based on Fokker-Planck models that determine the probability distribution function of REs in 2-dimensional momentum space. Despite the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches [e.g., continuum and particle-based Monte Carlo (MC)] can be time consuming, especially in the computation of asymptotic-type observables including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here, we present a novel backward MC approach to these problems based on backward stochastic differential equations that describe the dynamics of the runaway probability by means of the Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than direct MC methods (by significantly reducing the number of particles required to achieve a prescribed accuracy) while at the same time maintaining the advantages of particle-based methods (compared to continuum approaches). The proposed algorithm is unconditionally stable and can be parallelized as easy as the direct MC method, and its extension to dimensions higher than two is straightforward, thus paving the way for conducting large-scale RE simulation.
An introduction to Monte Carlo methods
Walter, J.-C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo simulations are ergodicity and detailed balance. The Ising model is a lattice spin system with nearest neighbor interactions that is appropriate to illustrate different examples of Monte Carlo simulations. It displays a second order phase transition between disordered (high temperature) and ordered (low temperature) phases, leading to different strategies of simulations. The Metropolis algorithm and the Glauber dynamics are efficient at high temperature. Close to the critical temperature, where the spins display long range correlations, cluster algorithms are more efficient. We introduce the rejection free (or continuous time) algorithm and describe in details an interesting alternative representation of the Ising model using graphs instead of spins with the so-called Worm algorithm. We conclude with an important discussion of the dynamical effects such as thermalization and correlation time.
Monte-carlo method for simulations of ring polymers in the melt.
Vettorel, Thomas; Reigh, Shang Yik; Yoon, Do Y; Kremer, Kurt
2009-02-18
A detailed analysis of the efficiency of a Monte-Carlo (MC) method employing non-local moves for simple lattice ring polymers is presented. While the introduction of kink-translocation moves for linear chains results in the expected speedup by a factor of the order of the number of sites, this is significantly reduced for a melt of rings. Copyright © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods
Energy Technology Data Exchange (ETDEWEB)
Godfrey, Andrew T [ORNL; Gehin, Jess C [ORNL; Bekar, Kursat B [ORNL; Celik, Cihangir [ORNL
2014-01-01
The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.
Zhang, Guannan; Del-Castillo-Negrete, Diego
2016-10-01
Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE in the 2 dimensional momentum space. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.
Burns, Gregory Scott
Monte Carlo simulation methods were used to investigate the absorbed dose distribution around several preliminary source configurations and the 3M Company models 6701, 6702, and 6711 I-125 seeds in water. Simulations for the preliminary sources, all of which were structurally simpler than the seeds, were conducted to demonstrate correct behavior of the computer software. The relative dose distributions of the three seed models were found to be anisotropic, and distinct. Observed differences in the relative dose distributions of the three models are attributable to differences in seed design and photon emission spectrum. Variations in end weld thicknesses and radioactivity distributions within the seeds were found to have substantial influence on the relative dose distributions. Dosimetry estimates along the longitudinal axis of the seeds are particularly uncertain due to such variations. Finally, perturbations of the single seed dose distribution created by neighboring seeds within the implant were determined. Such perturbations are strongly dependent on the seed model used and on the separation between seeds. Simple superposition of single seed dose distributions in multiple seed implants causes overestimation of dose within seed planes. Errors may be quite large for single plane implants with small seed separations. The results of this study provide a means to reduce errors in iodine seed implant dosimetry through the use of seed design-specific two-dimensional dosimetry data, and through improved understanding of the causes of uncertainties in iodine seed relative dose distributions.
Hueser, J. E.; Brock, F. J.; Melfi, L. T., Jr.; Bird, G. A.
1984-01-01
A new solution procedure has been developed to analyze the flowfield properties in the vicinity of the Inertial Upper Stage/Spacecraft during the 1st stage (SRMI) burn. Continuum methods are used to compute the nozzle flow and the exhaust plume flowfield as far as the boundary where the breakdown of translational equilibrium leaves these methods invalid. The Direct Simulation Monte Carlo (DSMC) method is applied everywhere beyond this breakdown boundary. The flowfield distributions of density, velocity, temperature, relative abundance, surface flux density, and pressure are discussed for each species for 2 sets of boundary conditions: vacuum and freestream. The interaction of the exhaust plume and the freestream with the spacecraft and the 2-stream direct interaction are discussed. The results show that the low density, high velocity, counter flowing free-stream substantially modifies the flowfield properties and the flux density incident on the spacecraft. A freestream bow shock is observed in the data, located forward of the high density region of the exhaust plume into which the freestream gas does not penetrate. The total flux density incident on the spacecraft, integrated over the SRM1 burn interval is estimated to be of the order of 10 to the 22nd per sq m (about 1000 atomic layers).
Olynick, David P.; Hassan, H. A.; Moss, James N.
1988-01-01
A grid generation and adaptation procedure based on the method of transfinite interpolation is incorporated into the Direct Simulation Monte Carlo Method of Bird. In addition, time is advanced based on a local criterion. The resulting procedure is used to calculate steady flows past wedges and cones. Five chemical species are considered. In general, the modifications result in a reduced computational effort. Moreover, preliminary results suggest that the simulation method is time step dependent if requirements on cell sizes are not met.
Institute of Scientific and Technical Information of China (English)
ZHANG Jun; GUO Fan
2015-01-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system’s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system’s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
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.
Zhu, Caigang; Liu, Quan
2012-01-01
We present a hybrid method that combines a multilayered scaling method and a perturbation method to speed up the Monte Carlo simulation of diffuse reflectance from a multilayered tissue model with finite-size tumor-like heterogeneities. The proposed method consists of two steps. In the first step, a set of photon trajectory information generated from a baseline Monte Carlo simulation is utilized to scale the exit weight and exit distance of survival photons for the multilayered tissue model. In the second step, another set of photon trajectory information, including the locations of all collision events from the baseline simulation and the scaling result obtained from the first step, is employed by the perturbation Monte Carlo method to estimate diffuse reflectance from the multilayered tissue model with tumor-like heterogeneities. Our method is demonstrated to shorten simulation time by several orders of magnitude. Moreover, this hybrid method works for a larger range of probe configurations and tumor models than the scaling method or the perturbation method alone.
Monte Carlo simulations for plasma physics
Energy Technology Data Exchange (ETDEWEB)
Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X. [National Inst. for Fusion Science, Toki, Gifu (Japan)
2000-07-01
Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)
Cluster hybrid Monte Carlo simulation algorithms
Plascak, J. A.; Ferrenberg, Alan M.; Landau, D. P.
2002-06-01
We show that addition of Metropolis single spin flips to the Wolff cluster-flipping Monte Carlo procedure leads to a dramatic increase in performance for the spin-1/2 Ising model. We also show that adding Wolff cluster flipping to the Metropolis or heat bath algorithms in systems where just cluster flipping is not immediately obvious (such as the spin-3/2 Ising model) can substantially reduce the statistical errors of the simulations. A further advantage of these methods is that systematic errors introduced by the use of imperfect random-number generation may be largely healed by hybridizing single spin flips with cluster flipping.
Bonfiglio, Andrea; Francesco CHELLI
2007-01-01
The paper aims to analyse the tendency of a battery of non-survey techniques of constructing regional I-O tables to over-(under-)estimate impact. The behaviour of the regionalization methods is assessed relatively to the techniques analysed. For this aim, a Monte Carlo simulation has been carried out. Then, a multidimensional scaling procedure has been applied to search for a common and repeated structure of differences among the methods and to give an immediate picture of possible implicatio...
Response of thermoluminescent dosimeters to photons simulated with the Monte Carlo method
Moralles, M.; Guimarães, C. C.; Okuno, E.
2005-06-01
Personal monitors composed of thermoluminescent dosimeters (TLDs) made of natural fluorite (CaF 2:NaCl) and lithium fluoride (Harshaw TLD-100) were exposed to gamma and X rays of different qualities. The GEANT4 radiation transport Monte Carlo toolkit was employed to calculate the energy depth deposition profile in the TLDs. X-ray spectra of the ISO/4037-1 narrow-spectrum series, with peak voltage (kVp) values in the range 20-300 kV, were obtained by simulating a X-ray Philips MG-450 tube associated with the recommended filters. A realistic photon distribution of a 60Co radiotherapy source was taken from results of Monte Carlo simulations found in the literature. Comparison between simulated and experimental results revealed that the attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account, while this effect is negligible for lithium fluoride. Differences between results obtained by heating the dosimeter from the irradiated side and from the opposite side allowed the determination of the light attenuation coefficient for CaF 2:NaCl (mass proportion 60:40) as 2.2 mm -1.
Monte Carlo particle-in-cell methods for the simulation of the Vlasov-Maxwell gyrokinetic equations
Bottino, A.; Sonnendrücker, E.
2015-10-01
> The particle-in-cell (PIC) algorithm is the most popular method for the discretisation of the general 6D Vlasov-Maxwell problem and it is widely used also for the simulation of the 5D gyrokinetic equations. The method consists of coupling a particle-based algorithm for the Vlasov equation with a grid-based method for the computation of the self-consistent electromagnetic fields. In this review we derive a Monte Carlo PIC finite-element model starting from a gyrokinetic discrete Lagrangian. The variations of the Lagrangian are used to obtain the time-continuous equations of motion for the particles and the finite-element approximation of the field equations. The Noether theorem for the semi-discretised system implies a certain number of conservation properties for the final set of equations. Moreover, the PIC method can be interpreted as a probabilistic Monte Carlo like method, consisting of calculating integrals of the continuous distribution function using a finite set of discrete markers. The nonlinear interactions along with numerical errors introduce random effects after some time. Therefore, the same tools for error analysis and error reduction used in Monte Carlo numerical methods can be applied to PIC simulations.
Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods
NeuroData; Paninski, L
2015-01-01
Vogelstein JT, Paninski L. Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods. Statistical and Applied Mathematical Sciences Institute (SAMSI) Program on Sequential Monte Carlo Methods, 2008
Parallel Markov chain Monte Carlo simulations.
Ren, Ruichao; Orkoulas, G
2007-06-07
With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.
Efendiev, Yalchin R.
2013-08-21
In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate
Improved Monte Carlo Renormalization Group Method
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
1995-01-01
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
Monte Carlo methods for particle transport
Haghighat, Alireza
2015-01-01
The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...
Spray cooling simulation implementing time scale analysis and the Monte Carlo method
Kreitzer, Paul Joseph
Spray cooling research is advancing the field of heat transfer and heat rejection in high power electronics. Smaller and more capable electronics packages are producing higher amounts of waste heat, along with smaller external surface areas, and the use of active cooling is becoming a necessity. Spray cooling has shown extremely high levels of heat rejection, of up to 1000 W/cm 2 using water. Simulations of spray cooling are becoming more realistic, but this comes at a price. A previous researcher has used CFD to successfully model a single 3D droplet impact into a liquid film using the level set method. However, the complicated multiphysics occurring during spray impingement and surface interactions increases computation time to more than 30 days. Parallel processing on a 32 processor system has reduced this time tremendously, but still requires more than a day. The present work uses experimental and computational results in addition to numerical correlations representing the physics occurring on a heated impingement surface. The current model represents the spray behavior of a Spraying Systems FullJet 1/8-g spray nozzle. Typical spray characteristics are indicated as follows: flow rate of 1.05x10-5 m3/s, normal droplet velocity of 12 m/s, droplet Sauter mean diameter of 48 microm, and heat flux values ranging from approximately 50--100 W/cm2 . This produces non-dimensional numbers of: We 300--1350, Re 750--3500, Oh 0.01--0.025. Numerical and experimental correlations have been identified representing crater formation, splashing, film thickness, droplet size, and spatial flux distributions. A combination of these methods has resulted in a Monte Carlo spray impingement simulation model capable of simulating hundreds of thousands of droplet impingements or approximately one millisecond. A random sequence of droplet impingement locations and diameters is generated, with the proper radial spatial distribution and diameter distribution. Hence the impingement, lifetime
Monte-Carlo simulation-based statistical modeling
Chen, John
2017-01-01
This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Monte carlo simulations of organic photovoltaics.
Groves, Chris; Greenham, Neil C
2014-01-01
Monte Carlo simulations are a valuable tool to model the generation, separation, and collection of charges in organic photovoltaics where charges move by hopping in a complex nanostructure and Coulomb interactions between charge carriers are important. We review the Monte Carlo techniques that have been applied to this problem, and describe the results of simulations of the various recombination processes that limit device performance. We show how these processes are influenced by the local physical and energetic structure of the material, providing information that is useful for design of efficient photovoltaic systems.
Monte Carlo Simulation of Optical Properties of Wake Bubbles
Institute of Scientific and Technical Information of China (English)
CAO Jing; WANG Jiang-An; JIANG Xing-Zhou; SHI Sheng-Wei
2007-01-01
Based on Mie scattering theory and the theory of multiple light scattering, the light scattering properties of air bubbles in a wake are analysed by Monte Carlo simulation. The results show that backscattering is enhanced obviously due to the existence of bubbles, especially with the increase of bubble density, and that it is feasible to use the Monte Carlo method to study the properties of light scattering by air bubbles.
Simulation of Cone Beam CT System Based on Monte Carlo Method
Wang, Yu; Cao, Ruifen; Hu, Liqin; Li, Bingbing
2014-01-01
Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established based on Monte Carlo program and validated against the measurement. The BEAMnrc program was adopted to the KV x-ray tube. Both IOURCE-13 and ISOURCE-24 were chosen to simulate the path of beam particles. The measured Percentage Depth Dose (PDD) and lateral dose profiles under 1cm water were compared with the dose calculated by DOSXYZnrc program. The calculated PDD was better than 1% within the depth of 10cm. More than 85% points of calculated lateral dose profiles was within 2%. The correct CBCT system model helps to improve CBCT image quality for dose verification in ART and assess the CBCT image concomitant dose risk.
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls).xml
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls).
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
Directory of Open Access Journals (Sweden)
Samuel Livingstone
2014-06-01
Full Text Available Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo simulation for statistical inference and molecular dynamics is provided, with particular emphasis on methods based on Langevin diffusions. After this, geometric concepts in Markov chain Monte Carlo are introduced. A full derivation of the Langevin diffusion on a Riemannian manifold is given, together with a discussion of the appropriate Riemannian metric choice for different problems. A survey of applications is provided, and some open questions are discussed.
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential......Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction......, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....
Modeling and simulation of radiation from hypersonic flows with Monte Carlo methods
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
Jin, Shengye; Tamura, Masayuki
2013-10-01
Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is
Monte Carlo Simulation of Counting Experiments.
Ogden, Philip M.
A computer program to perform a Monte Carlo simulation of counting experiments was written. The program was based on a mathematical derivation which started with counts in a time interval. The time interval was subdivided to form a binomial distribution with no two counts in the same subinterval. Then the number of subintervals was extended to…
Hart, Vern P; Doyle, Timothy E
2013-09-01
A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.
Discrete range clustering using Monte Carlo methods
Chatterji, G. B.; Sridhar, B.
1993-01-01
For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.
Study of the Transition Flow Regime using Monte Carlo Methods
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro
2001-01-01
This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.
Lillhök, J E; Grindborg, J-E; Lindborg, L; Gudowska, I; Carlsson, G Alm; Söderberg, J; Kopeć, M; Medin, J
2007-08-21
Nanodosimetric single-event distributions or their mean values may contribute to a better understanding of how radiation induced biological damages are produced. They may also provide means for radiation quality characterization in therapy beams. Experimental nanodosimetry is however technically challenging and Monte Carlo simulations are valuable as a complementary tool for such investigations. The dose-mean lineal energy was determined in a therapeutic p(65)+Be neutron beam and in a (60)Co gamma beam using low-pressure gas detectors and the variance-covariance method. The neutron beam was simulated using the condensed history Monte Carlo codes MCNPX and SHIELD-HIT. The dose-mean lineal energy was calculated using the simulated dose and fluence spectra together with published data from track-structure simulations. A comparison between simulated and measured results revealed some systematic differences and different dependencies on the simulated object size. The results show that both experimental and theoretical approaches are needed for an accurate dosimetry in the nanometer region. In line with previously reported results, the dose-mean lineal energy determined at 10 nm was shown to be related to clinical RBE values in the neutron beam and in a simulated 175 MeV proton beam as well.
Perturbation Monte Carlo methods for tissue structure alterations.
Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Spanier, Jerome
2013-01-01
This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ∼15-25% of the scattering parameters.
The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature
Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V
2010-01-01
A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.
DSMC calculations for the delta wing. [Direct Simulation Monte Carlo method
Celenligil, M. Cevdet; Moss, James N.
1990-01-01
Results are reported from three-dimensional direct simulation Monte Carlo (DSMC) computations, using a variable-hard-sphere molecular model, of hypersonic flow on a delta wing. The body-fitted grid is made up of deformed hexahedral cells divided into six tetrahedral subcells with well defined triangular faces; the simulation is carried out for 9000 time steps using 150,000 molecules. The uniform freestream conditions include M = 20.2, T = 13.32 K, rho = 0.00001729 kg/cu m, and T(wall) = 620 K, corresponding to lambda = 0.00153 m and Re = 14,000. The results are presented in graphs and briefly discussed. It is found that, as the flow expands supersonically around the leading edge, an attached leeside flow develops around the wing, and the near-surface density distribution has a maximum downstream from the stagnation point. Coefficients calculated include C(H) = 0.067, C(DP) = 0.178, C(DF) = 0.110, C(L) = 0.714, and C(D) = 1.089. The calculations required 56 h of CPU time on the NASA Langley Voyager CRAY-2 supercomputer.
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo Simulation for Particle Detectors
Pia, Maria Grazia
2012-01-01
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...
Quantum speedup of Monte Carlo methods.
Montanaro, Ashley
2015-09-08
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.
Cu-Au Alloys Using Monte Carlo Simulations and the BFS Method for Alloys
Bozzolo, Guillermo; Good, Brian; Ferrante, John
1996-01-01
Semi empirical methods have shown considerable promise in aiding in the calculation of many properties of materials. Materials used in engineering applications have defects that occur for various reasons including processing. In this work we present the first application of the BFS method for alloys to describe some aspects of microstructure due to processing for the Cu-Au system (Cu-Au, CuAu3, and Cu3Au). We use finite temperature Monte Carlo calculations, in order to show the influence of 'heat treatment' in the low-temperature phase of the alloy. Although relatively simple, it has enough features that could be used as a first test of the reliability of the technique. The main questions to be answered in this work relate to the existence of low temperature ordered structures for specific concentrations, for example, the ability to distinguish between rather similar phases for equiatomic alloys (CuAu I and CuAu II, the latter characterized by an antiphase boundary separating two identical phases).
Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations
Institute of Scientific and Technical Information of China (English)
仲昕; 杨汝清; 周兵
2003-01-01
Monte Carlo simulation was applied to Assembly Success Rate (ASR) analyses.ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes,manufacturing tolerances and robot repeatability into account.A statistic arithmetic expression was proposed and deduced in this paper,which offers an alternative method of estimating the accuracy of ASR,without having to repeat the simulations.This statistic method also helps to choose a suitable sample size,if error reduction is desired.Monte Carlo simulation results demonstrated the feasibility of the method.
Directory of Open Access Journals (Sweden)
Amir Kariznoee
2015-06-01
Full Text Available Making decision to choose the appropriate target market is one of the key decisions in the success of firms, which has direct effect in the amount of their profits. The aim of this paper is to introduce and use of new hybrid method of AHP, Monte Carlo simulation and PROMETHEE to prioritize cities to establish retailers, considering different indices. The problem of this study is related to a factory, constructing premade pieces of buildings, that to introduce and distribute its new products is searching the new retailers in different cities. To prioritize cities, with the interview with experts and the studying of the previous works the indices have been determined and the hierarchy pattern has been made. Then using the hybrid method of AHP and Monte Carlo simulation the weights of the indices have been determined and then using PROMETHEE method the best city has been chosen and the other ones have been prioritized. From the benefits of the new introduced hybrid method with respect to other ways of selecting target markets is decreasing the risk and increasing the power of decision making.
Jehan, Musarrat
The response of a dynamic system is random. There is randomness in both the applied loads and the strength of the system. Therefore, to account for the uncertainty, the safety of the system must be quantified using its probability of survival (reliability). Monte Carlo Simulation (MCS) is a widely used method for probabilistic analysis because of its robustness. However, a challenge in reliability assessment using MCS is that the high computational cost limits the accuracy of MCS. Haftka et al. [2010] developed an improved sampling technique for reliability assessment called separable Monte Carlo (SMC) that can significantly increase the accuracy of estimation without increasing the cost of sampling. However, this method was applied to time-invariant problems involving two random variables only. This dissertation extends SMC to random vibration problems with multiple random variables. This research also develops a novel method for estimation of the standard deviation of the probability of failure of a structure under static or random vibration. The method is demonstrated on quarter car models and a wind turbine. The proposed method is validated using repeated standard MCS.
Monte Carlo Simulation in Statistical Physics An Introduction
Binder, Kurt
2010-01-01
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...
An Introduction to Monte Carlo Methods
Raeside, D. E.
1974-01-01
Reviews the principles of Monte Carlo calculation and random number generation in an attempt to introduce the direct and the rejection method of sampling techniques as well as the variance-reduction procedures. Indicates that the increasing availability of computers makes it possible for a wider audience to learn about these powerful methods. (CC)
Determining MTF of digital detector system with Monte Carlo simulation
Jeong, Eun Seon; Lee, Hyung Won; Nam, Sang Hee
2005-04-01
We have designed a detector based on a-Se(amorphous Selenium) and done simulation the detector with Monte Carlo method. We will apply the cascaded linear system theory to determine the MTF for whole detector system. For direct comparison with experiment, we have simulated 139um pixel pitch and used simulated X-ray tube spectrum.
Atomistic Monte Carlo simulation of lipid membranes.
Wüstner, Daniel; Sklenar, Heinz
2014-01-24
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.
Atomistic Monte Carlo Simulation of Lipid Membranes
Directory of Open Access Journals (Sweden)
Daniel Wüstner
2014-01-01
Full Text Available Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA for the phospholipid dipalmitoylphosphatidylcholine (DPPC. We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
Parallel Monte Carlo Simulation of Aerosol Dynamics
Directory of Open Access Journals (Sweden)
Kun Zhou
2014-02-01
Full Text Available A highly efficient Monte Carlo (MC algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process. Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI. The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles.
Parallel Monte Carlo simulation of aerosol dynamics
Zhou, K.
2014-01-01
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Monte Carlo simulation code modernization
CERN. Geneva
2015-01-01
The continual development of sophisticated transport simulation algorithms allows increasingly accurate description of the effect of the passage of particles through matter. This modelling capability finds applications in a large spectrum of fields from medicine to astrophysics, and of course HEP. These new capabilities however come at the cost of a greater computational intensity of the new models, which has the effect of increasing the demands of computing resources. This is particularly true for HEP, where the demand for more simulation are driven by the need of both more accuracy and more precision, i.e. better models and more events. Usually HEP has relied on the "Moore's law" evolution, but since almost ten years the increase in clock speed has withered and computing capacity comes in the form of hardware architectures of many-core or accelerated processors. To harness these opportunities we need to adapt our code to concurrent programming models taking advantages of both SIMD and SIMT architectures. Th...
Institute of Scientific and Technical Information of China (English)
马峰; 恽寿榕; 黄风雷
2003-01-01
A model is constructed and used in computing the coagulation probability of free carbon during the detonation of explosives. A direct simulation Monte Carlo (DSMC) program is constructed to simulate the coagulation of free carbon particles. The evaluation of the distribution spectrum of particles in the system is obtained. The simulation result is consistent with the experimental curve.
Monte Carlo simulations on SIMD computer architectures
Energy Technology Data Exchange (ETDEWEB)
Burmester, C.P.; Gronsky, R. [Lawrence Berkeley Lab., CA (United States); Wille, L.T. [Florida Atlantic Univ., Boca Raton, FL (United States). Dept. of Physics
1992-03-01
Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SMM) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.
Direct determination of liquid phase coexistence by Monte Carlo simulations
Zweistra, H.J.A.; Besseling, N.A.M.
2006-01-01
A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase.
Research of Monte Carlo Simulation in Commercial Bank Risk Management
Institute of Scientific and Technical Information of China (English)
BeimingXiao
2004-01-01
Simulation method is an important-tool in financial risk management. It can simulate financial variable or economic wriable and deal with non-linear or non-nominal issue. This paper analyzes the usage of "Monte Carlo" approach in commercial bank risk management.
Energy Technology Data Exchange (ETDEWEB)
Guimaraes, Carla da Costa
2005-07-01
In this work, we have evaluated the possibility of applying the Monte Carlo simulation technique in photon dosimetry of external individual monitoring. The GEANT4 toolkit was employed to simulate experiments with radiation monitors containing TLD-100 and CaF{sub 2}:NaCl thermoluminescent detectors. As a first step, X ray spectra were generated impinging electrons on a tungsten target. Then, the produced photon beam was filtered in a beryllium window and additional filters to obtain the radiation with desired qualities. This procedure, used to simulate radiation fields produced by a X ray tube, was validated by comparing characteristics such as half value layer, which was also experimentally measured, mean photon energy and the spectral resolution of simulated spectra with that of reference spectra established by international standards. In the construction of thermoluminescent dosimeter, two approaches for improvements have. been introduced. The first one was the inclusion of 6% of air in the composition of the CaF{sub 2}:NaCl detector due to the difference between measured and calculated values of its density. Also, comparison between simulated and experimental results showed that the self-attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account. Then, in the second approach, the light attenuation coefficient of CaF{sub 2}:NaCl compound estimated by simulation to be 2,20(25) mm{sup -1} was introduced. Conversion coefficients C{sub p} from air kerma to personal dose equivalent were calculated using a slab water phantom with polymethyl-metacrilate (PMMA) walls, for reference narrow and wide X ray spectrum series [ISO 4037-1], and also for the wide spectra implanted and used in routine at Laboratorio de Dosimetria. Simulations of backscattered radiations by PMMA slab water phantom and slab phantom of ICRU tissue-equivalent material produced very similar results. Therefore, the PMMA slab water phantom that can be easily
Monte Carlo simulation of laser attenuation characteristics in fog
Wang, Hong-Xia; Sun, Chao; Zhu, You-zhang; Sun, Hong-hui; Li, Pan-shi
2011-06-01
Based on the Mie scattering theory and the gamma size distribution model, the scattering extinction parameter of spherical fog-drop is calculated. For the transmission attenuation of the laser in the fog, a Monte Carlo simulation model is established, and the impact of attenuation ratio on visibility and field angle is computed and analysed using the program developed by MATLAB language. The results of the Monte Carlo method in this paper are compared with the results of single scattering method. The results show that the influence of multiple scattering need to be considered when the visibility is low, and single scattering calculations have larger errors. The phenomenon of multiple scattering can be interpreted more better when the Monte Carlo is used to calculate the attenuation ratio of the laser transmitting in the fog.
Meaningful timescales from Monte Carlo simulations of molecular systems
Costa, Liborio I
2016-01-01
A new Markov Chain Monte Carlo method for simulating the dynamics of molecular systems with atomistic detail is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.
Fission source sampling in coupled Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Olsen, Boerge; Dufek, Jan [KTH Royal Inst. of Technology, Stockholm (Sweden). Div. of Nuclear Research Technology
2017-05-15
We study fission source sampling methods suitable for the iterative way of solving coupled Monte Carlo neutronics problems. Specifically, we address the question as to how the initial Monte Carlo fission source should be optimally sampled at the beginning of each iteration step. We compare numerically two approaches of sampling the initial fission source; the tested techniques are derived from well-known methods for iterating the neutron flux in coupled simulations. The first technique samples the initial fission source using the source from the previous iteration step, while the other technique uses a combination of all previous steps for this purpose. We observe that the previous-step approach performs the best.
Monte Carlo simulations of Protein Adsorption
Sharma, Sumit; Kumar, Sanat K.; Belfort, Georges
2008-03-01
Amyloidogenic diseases, such as, Alzheimer's are caused by adsorption and aggregation of partially unfolded proteins. Adsorption of proteins is a concern in design of biomedical devices, such as dialysis membranes. Protein adsorption is often accompanied by conformational rearrangements in protein molecules. Such conformational rearrangements are thought to affect many properties of adsorbed protein molecules such as their adhesion strength to the surface, biological activity, and aggregation tendency. It has been experimentally shown that many naturally occurring proteins, upon adsorption to hydrophobic surfaces, undergo a helix to sheet or random coil secondary structural rearrangement. However, to better understand the equilibrium structural complexities of this phenomenon, we have performed Monte Carlo (MC) simulations of adsorption of a four helix bundle, modeled as a lattice protein, and studied the adsorption behavior and equilibrium protein conformations at different temperatures and degrees of surface hydrophobicity. To study the free energy and entropic effects on adsorption, Canonical ensemble MC simulations have been combined with Weighted Histogram Analysis Method(WHAM). Conformational transitions of proteins on surfaces will be discussed as a function of surface hydrophobicity and compared to analogous bulk transitions.
Computer Simulation of the E.C.C.S. Buckling Curve using a Monte-Carlo Method
Strating, J.; Vos, H.
1973-01-01
The application of a Monte-Carlo simulation procedure to obtain the distribution function of the maximum load of a hinged column with imperfections is discussed. Buckling tests carried out by the E.C.C.S. on IPE 160 sections have been simulated. Information concerning the column variables is obtaine
A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions
Liang, Yihao; Xing, Xiangjun; Li, Yaohang
2017-06-01
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures, and adopts the sequential updating scheme of Metropolis algorithm. It makes no approximation in the computation of energy, and reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We further use this method to simulate primitive model electrolytes, and measure very precisely all ion-ion pair correlation functions at high concentrations. From these data, we extract the renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.
A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
Liang, Yihao; Li, Yaohang
2016-01-01
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures. It adopts the sequential updating scheme of Metropolis algorithm, and makes no approximation in the computation of energy. It reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We use this method to simulate primitive model electrolytes. We measure very precisely all ion-ion pair correlation functions at high concentrations, and extract renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
Cemgil, A T; 10.1613/jair.1121
2011-01-01
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...
Monte Carlo simulation for the transport beamline
Energy Technology Data Exchange (ETDEWEB)
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)
2013-07-26
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Mosaic crystal algorithm for Monte Carlo simulations
Seeger, P A
2002-01-01
An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)
TRIGA IPR-R1 reactor simulation using Monte Carlo transport methods
Hugo Moura Dalle
2005-01-01
Resumo: A utilização do método Monte Carlo na simulação do transporte de partículas em reatores nucleares é crescente e constitui uma tendência mundial. O maior inconveniente dessa técnica, a grande exigência de capacidade de processamento, vem sendo superado pelo contínuo desenvolvimento de processadores cada vez mais rápidos. Esse contexto permitiu o desenvolvimento de metodologias de cálculo neutrônico de reatores nas quais se acopla a parte do transporte de partículas, feita com um código...
Energy Technology Data Exchange (ETDEWEB)
Huthmacher, Klaus [Department of Physics and OPTIMAS Research Center, University of Kaiserslautern (Germany); Molberg, Andreas K. [Department of Chemistry and OPTIMAS Research Center, University of Kaiserslautern (Germany); Rethfeld, Bärbel [Department of Physics and OPTIMAS Research Center, University of Kaiserslautern (Germany); Gulley, Jeremy R., E-mail: jgulley@kennesaw.edu [Department of Physics, Kennesaw State University, Kennesaw, GA 30144 (United States)
2016-10-01
A split-step numerical method for calculating ultrafast free-electron dynamics in dielectrics is introduced. The two split steps, independently programmed in C++11 and FORTRAN 2003, are interfaced via the presented open source wrapper. The first step solves a deterministic extended multi-rate equation for the ionization, electron–phonon collisions, and single photon absorption by free-carriers. The second step is stochastic and models electron–electron collisions using Monte-Carlo techniques. This combination of deterministic and stochastic approaches is a unique and efficient method of calculating the nonlinear dynamics of 3D materials exposed to high intensity ultrashort pulses. Results from simulations solving the proposed model demonstrate how electron–electron scattering relaxes the non-equilibrium electron distribution on the femtosecond time scale.
Huthmacher, Klaus; Molberg, Andreas K.; Rethfeld, Bärbel; Gulley, Jeremy R.
2016-10-01
A split-step numerical method for calculating ultrafast free-electron dynamics in dielectrics is introduced. The two split steps, independently programmed in C++11 and FORTRAN 2003, are interfaced via the presented open source wrapper. The first step solves a deterministic extended multi-rate equation for the ionization, electron-phonon collisions, and single photon absorption by free-carriers. The second step is stochastic and models electron-electron collisions using Monte-Carlo techniques. This combination of deterministic and stochastic approaches is a unique and efficient method of calculating the nonlinear dynamics of 3D materials exposed to high intensity ultrashort pulses. Results from simulations solving the proposed model demonstrate how electron-electron scattering relaxes the non-equilibrium electron distribution on the femtosecond time scale.
Direct Monte Carlo simulation of nanoscale mixed gas bearings
Directory of Open Access Journals (Sweden)
Kyaw Sett Myo
2015-06-01
Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.
Quasi-Monte Carlo methods for the Heston model
Jan Baldeaux; Dale Roberts
2012-01-01
In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not available in closed-form, the Linear Transformation method due to Imai and Tan, a popular and widely applicable method to improve the effectiveness of quasi-Monte Carlo methods, cannot be employed in the context of path-dependent options when the underlying pr...
Monte Carlo simulation of quantum statistical lattice models
Raedt, Hans De; Lagendijk, Ad
1985-01-01
In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used t
Monte Carlo Simulation Optimizing Design of Grid Ionization Chamber
Institute of Scientific and Technical Information of China (English)
ZHENG; Yu-lai; WANG; Qiang; YANG; Lu
2013-01-01
The grid ionization chamber detector is often used for measuring charged particles.Based on Monte Carlo simulation method,the energy loss distribution and electron ion pairs of alpha particle with different energy have been calculated to determine suitable filling gas in the ionization chamber filled with
Play It Again: Teaching Statistics with Monte Carlo Simulation
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…
Simulating Strongly Correlated Electron Systems with Hybrid Monte Carlo
Institute of Scientific and Technical Information of China (English)
LIU Chuan
2000-01-01
Using the path integral representation, the Hubbard and the periodic Anderson model on D-dimensional cubic lattice are transformed into field theories of fermions in D + 1 dimensions. These theories at half-filling possess a positive definite real symmetry fermion matrix and can be simulated using the hybrid Monte Carlo method.
Inglis, Stephen; Melko, Roger G
2013-01-01
We implement a Wang-Landau sampling technique in quantum Monte Carlo (QMC) simulations for the purpose of calculating the Rényi entanglement entropies and associated mutual information. The algorithm converges an estimate for an analog to the density of states for stochastic series expansion QMC, allowing a direct calculation of Rényi entropies without explicit thermodynamic integration. We benchmark results for the mutual information on two-dimensional (2D) isotropic and anisotropic Heisenberg models, a 2D transverse field Ising model, and a three-dimensional Heisenberg model, confirming a critical scaling of the mutual information in cases with a finite-temperature transition. We discuss the benefits and limitations of broad sampling techniques compared to standard importance sampling methods.
Pasini, J M; Cordero, P
2001-04-01
We study a one-dimensional granular gas of pointlike particles not subject to gravity between two walls at temperatures T(left) and T(right). The system exhibits two distinct regimes, depending on the normalized temperature difference Delta=(T(right)-T(left))/(T(right)+T(left)): one completely fluidized and one in which a cluster coexists with the fluidized gas. When Delta is above a certain threshold, cluster formation is fully inhibited, obtaining a completely fluidized state. The mechanism that produces these two phases is explained. In the fluidized state the velocity distribution function exhibits peculiar non-Gaussian features. For this state, comparison between integration of the Boltzmann equation using the direct-simulation Monte Carlo method and results stemming from microscopic Newtonian molecular dynamics gives good coincidence, establishing that the non-Gaussian features observed do not arise from the onset of correlations.
Ustinov, E. A.
2017-01-01
The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.
Archimedes, the Free Monte Carlo simulator
Sellier, Jean Michel D
2012-01-01
Archimedes is the GNU package for Monte Carlo simulations of electron transport in semiconductor devices. The first release appeared in 2004 and since then it has been improved with many new features like quantum corrections, magnetic fields, new materials, GUI, etc. This document represents the first attempt to have a complete manual. Many of the Physics models implemented are described and a detailed description is presented to make the user able to write his/her own input deck. Please, feel free to contact the author if you want to contribute to the project.
Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia
Energy Technology Data Exchange (ETDEWEB)
Granero Cabanero, D.
2015-07-01
The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)
Puranik, Bhalchandra; Watvisave, Deepak; Bhandarkar, Upendra
2016-11-01
The interaction of a shock with a density interface is observed in several technological applications such as supersonic combustion, inertial confinement fusion, and shock-induced fragmentation of kidney and gall-stones. The central physical process in this interaction is the mechanism of the Richtmyer-Meshkov Instability (RMI). The specific situation where the density interface is initially an isolated spherical or cylindrical gas bubble presents a relatively simple geometry that exhibits all the essential RMI processes such as reflected and refracted shocks, secondary instabilities, turbulence and mixing of the species. If the incident shocks are strong, the calorically imperfect nature needs to be modelled. In the present work, we have carried out simulations of the shock-bubble interaction using the DSMC method for such situations. Specifically, an investigation of the shock-bubble interaction with diatomic gases involving rotational and vibrational excitations at high temperatures is performed, and the effects of such high temperature phenomena will be presented.
Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules
Lester, William A; Reynolds, PJ
1994-01-01
This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n
Energy Technology Data Exchange (ETDEWEB)
Olaya D, H.; Diaz M, J. A.; Martinez O, S. A. [Universidad Pedagogica y Tecnologica de Colombia, Grupo de Fisica Nuclear Aplicada y Simulacion, 150003 Tunja, Boyaca (Colombia); Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas, Zac. (Mexico)
2016-10-15
Were performed experimental setups using an X-ray equipment continuous emission Pantak DXT-3000 and three types of leaded aprons with thickness of 0.25, 0.5 and 0.75 mm coated with Mylar Fiber coated Mylar on its surface. Apron was located at a distance of 2.5 m with respect focus in order to cover a radiation field size of a meter in diameter. At the beam output were added aluminum filtration in order to reproduce qualities of narrow beams N-40 (E{sub efective} = 33 keV), N-80 (E{sub efective} = 65 keV) and N-100 (E{sub efective} = 83 keV) according to the ISO standard 4037 (1-3). Each lead apron were fixed 10 TLD dosimeters over its surface, 5 dosimeters before and 5 dosimeters after with respect to X-ray beam and were calibrated for Harshaw 4500 thermoluminescent reader system order to assess the attenuation of each apron. Were performed dosimeters readings and were calculated the attenuation coefficients for each effective energy of X-ray quality. In order to confirm the method of effective energy of ISO-4037 and evaluate effectiveness of lead aprons based on energy range for each medical practice was made a Monte Carlo simulation using code GEANT-4, calculating the fluence and absorbed dose in each one of the dosimeters Monte Carlo, then coefficients of linear attenuation were calculated and compared with the experimental data and reported by the National Institute of Standards and Technology (Nist). Finally, results are consistent between theoretical calculation and experimental measures. This work will serve to make assessments for other personalized leaded protections. (Author)
Monte Carlo Simulation Of Emission Tomography And Other Medical Imaging Techniques.
Harrison, Robert L
2010-01-05
An introduction to Monte Carlo simulation of emission tomography. This paper reviews the history and principles of Monte Carlo simulation, then applies these principles to emission tomography using the public domain simulation package SimSET (a Simulation System for Emission Tomography) as an example. Finally, the paper discusses how the methods are modified for X-ray computed tomography and radiotherapy simulations.
Kotalczyk, G.; Kruis, F. E.
2017-07-01
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 of 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.
Energy Technology Data Exchange (ETDEWEB)
Kotalczyk, G., E-mail: Gregor.Kotalczyk@uni-due.de; Kruis, F.E.
2017-07-01
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 of 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.
Wada, Takao; Ueda, Noriaki
2013-04-21
The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature.
Accelerated GPU based SPECT Monte Carlo simulations
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
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, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Accelerated GPU based SPECT Monte Carlo simulations.
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
Díez, A; Largo, J; Solana, J R
2006-08-21
Computer simulations have been performed for fluids with van der Waals potential, that is, hard spheres with attractive inverse power tails, to determine the equation of state and the excess energy. On the other hand, the first- and second-order perturbative contributions to the energy and the zero- and first-order perturbative contributions to the compressibility factor have been determined too from Monte Carlo simulations performed on the reference hard-sphere system. The aim was to test the reliability of this "exact" perturbation theory. It has been found that the results obtained from the Monte Carlo perturbation theory for these two thermodynamic properties agree well with the direct Monte Carlo simulations. Moreover, it has been found that results from the Barker-Henderson [J. Chem. Phys. 47, 2856 (1967)] perturbation theory are in good agreement with those from the exact perturbation theory.
Channon, H A; Hamilton, A J; D'Souza, D N; Dunshea, F R
2016-06-01
Monte Carlo simulation was investigated as a potential methodology to estimate sensory tenderness, flavour and juiciness scores of pork following the implementation of key pathway interventions known to influence eating quality. Correction factors were established using mean data from published studies investigating key production, processing and cooking parameters. Probability distributions of correction factors were developed for single pathway parameters only, due to lack of interaction data. Except for moisture infusion, ageing period, aitchbone hanging and cooking pork to an internal temperature of >74°C, only small shifts in the mean of the probability distributions of correction factors were observed for the majority of pathway parameters investigated in this study. Output distributions of sensory scores, generated from Monte Carlo simulations of input distributions of correction factors and for individual pigs, indicated that this methodology may be useful in estimating both the shift and variability in pork eating traits when different pathway interventions are applied.
Validation of Compton Scattering Monte Carlo Simulation Models
Weidenspointner, Georg; Hauf, Steffen; Hoff, Gabriela; Kuster, Markus; Pia, Maria Grazia; Saracco, Paolo
2014-01-01
Several models for the Monte Carlo simulation of Compton scattering on electrons are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. Some of these models are currently implemented in general purpose Monte Carlo systems; some have been implemented and evaluated for possible use in Monte Carlo particle transport for the first time in this study. Here we present first and preliminary results concerning total and differential Compton scattering cross sections.
Modeling neutron guides using Monte Carlo simulations
Wang, D Q; Crow, M L; Wang, X L; Lee, W T; Hubbard, C R
2002-01-01
Four neutron guide geometries, straight, converging, diverging and curved, were characterized using Monte Carlo ray-tracing simulations. The main areas of interest are the transmission of the guides at various neutron energies and the intrinsic time-of-flight (TOF) peak broadening. Use of a delta-function time pulse from a uniform Lambert neutron source allows one to quantitatively simulate the effect of guides' geometry on the TOF peak broadening. With a converging guide, the intensity and the beam divergence increases while the TOF peak width decreases compared with that of a straight guide. By contrast, use of a diverging guide decreases the intensity and the beam divergence, and broadens the width (in TOF) of the transmitted neutron pulse.
Wang, Zhen; Cui, Shengcheng; Yang, Jun; Gao, Haiyang; Liu, Chao; Zhang, Zhibo
2017-03-01
We present a novel hybrid scattering order-dependent variance reduction method to accelerate the convergence rate in both forward and backward Monte Carlo radiative transfer simulations involving highly forward-peaked scattering phase function. This method is built upon a newly developed theoretical framework that not only unifies both forward and backward radiative transfer in scattering-order-dependent integral equation, but also generalizes the variance reduction formalism in a wide range of simulation scenarios. In previous studies, variance reduction is achieved either by using the scattering phase function forward truncation technique or the target directional importance sampling technique. Our method combines both of them. A novel feature of our method is that all the tuning parameters used for phase function truncation and importance sampling techniques at each order of scattering are automatically optimized by the scattering order-dependent numerical evaluation experiments. To make such experiments feasible, we present a new scattering order sampling algorithm by remodeling integral radiative transfer kernel for the phase function truncation method. The presented method has been implemented in our Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model for validation and evaluation. The main advantage of the method is that it greatly improves the trade-off between numerical efficiency and accuracy order by order.
Monte Carlo simulation of photon migration path in turbid media
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A new method of Monte Carlo simulation is developed to simulate the photon migration path in a scattering medium after an ultrashort-pulse laser beam comes into the medium.The most probable trajectory of photons at an instant can be obtained with this method.How the photon migration paths are affected by the optical parameters of the scattering medium is analyzed.It is also concluded that the absorption coefficient has no effect on the most probable trajectory of photons.
Global Monte Carlo Simulation with High Order Polynomial Expansions
Energy Technology Data Exchange (ETDEWEB)
William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin
2007-12-13
The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as “local” piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi’s method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source
Coherent Scattering Imaging Monte Carlo Simulation
Hassan, Laila Abdulgalil Rafik
Conventional mammography has poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter potentially provides more information because interference of coherently scattered radiation depends on the average intermolecular spacing, and can be used to characterize tissue types. However, typical coherent scatter analysis techniques are not compatible with rapid low dose screening techniques. Coherent scatter slot scan imaging is a novel imaging technique which provides new information with higher contrast. In this work a simulation of coherent scatter was performed for slot scan imaging to assess its performance and provide system optimization. In coherent scatter imaging, the coherent scatter is exploited using a conventional slot scan mammography system with anti-scatter grids tilted at the characteristic angle of cancerous tissues. A Monte Carlo simulation was used to simulate the coherent scatter imaging. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The contrast increased as the grid tilt angle increased beyond the characteristic angle for the modeled carcinoma. A grid tilt angle of 16 degrees yielded the highest contrast and signal to noise ratio (SNR). Also, contrast increased as the source voltage increased. Increasing grid ratio improved contrast at the expense of decreasing SNR. A grid ratio of 10:1 was sufficient to give a good contrast without reducing the intensity to a noise level. The optimal source to sample distance was determined to be such that the source should be located at the focal distance of the grid. A carcinoma lump of 0.5x0.5x0.5 cm3 in size was detectable which is reasonable considering the high noise due to the usage of relatively small number of incident photons for computational reasons. A further study is needed to study the effect of breast density and breast thickness
Monte Carlo simulation of neutron scattering instruments
Energy Technology Data Exchange (ETDEWEB)
Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.
1998-12-01
A code package consisting of the Monte Carlo Library MCLIB, the executing code MC{_}RUN, the web application MC{_}Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC{_}RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown.
Multiple-time-stepping generalized hybrid Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Bozzolo, Guillermo H.; Good, Brian; Noebe, Ronald D.; Honecy, Frank; Abel, Phillip
1999-01-01
Large-scale simulations of dynamic processes at the atomic level have developed into one of the main areas of work in computational materials science. Until recently, severe computational restrictions, as well as the lack of accurate methods for calculating the energetics, resulted in slower growth in the area than that required by current alloy design programs. The Computational Materials Group at the NASA Lewis Research Center is devoted to the development of powerful, accurate, economical tools to aid in alloy design. These include the BFS (Bozzolo, Ferrante, and Smith) method for alloys (ref. 1) and the development of dedicated software for large-scale simulations based on Monte Carlo- Metropolis numerical techniques, as well as state-of-the-art visualization methods. Our previous effort linking theoretical and computational modeling resulted in the successful prediction of the microstructure of a five-element intermetallic alloy, in excellent agreement with experimental results (refs. 2 and 3). This effort also produced a complete description of the role of alloying additions in intermetallic binary, ternary, and higher order alloys (ref. 4).
Stock Price Simulation Using Bootstrap and Monte Carlo
Directory of Open Access Journals (Sweden)
Pažický Martin
2017-06-01
Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.
Sensitivity of Monte Carlo simulations to input distributions
Energy Technology Data Exchange (ETDEWEB)
RamoRao, B. S.; Srikanta Mishra, S.; McNeish, J.; Andrews, R. W.
2001-07-01
The sensitivity of the results of a Monte Carlo simulation to the shapes and moments of the probability distributions of the input variables is studied. An economical computational scheme is presented as an alternative to the replicate Monte Carlo simulations and is explained with an illustrative example. (Author) 4 refs.
CONDENSED MONTE-CARLO SIMULATIONS FOR THE DESCRIPTION OF LIGHT TRANSPORT
GRAAFF, R; KOELINK, MH; DEMUL, FFM; ZIJLSTRA, WG; DASSEL, ACM; AARNOUDSE, JG
1993-01-01
A novel method, condensed Monte Carlo simulation, is presented that applies the results of a single Monte Carlo simulation for a given albedo mu(s)/(mu(a) + mu(s)) to obtaining results for other albedos; mu(s) and mu(a) are the scattering and absorption coefficients, respectively. The method require
Harvey, J.-P.; Gheribi, A. E.; Chartrand, P.
2011-08-01
The design of multicomponent alloys used in different applications based on specific thermo-physical properties determined experimentally or predicted from theoretical calculations is of major importance in many engineering applications. A procedure based on Monte Carlo simulations (MCS) and the thermodynamic integration (TI) method to improve the quality of the predicted thermodynamic properties calculated from classical thermodynamic calculations is presented in this study. The Gibbs energy function of the liquid phase of the Cu-Zr system at 1800 K has been determined based on this approach. The internal structure of Cu-Zr melts and amorphous alloys at different temperatures, as well as other physical properties were also obtained from MCS in which the phase trajectory was modeled by the modified embedded atom model formalism. A rigorous comparison between available experimental data and simulated thermo-physical properties obtained from our MCS is presented in this work. The modified quasichemical model in the pair approximation was parameterized using the internal structure data obtained from our MCS and the precise Gibbs energy function calculated at 1800 K from the TI method. The predicted activity of copper in Cu-Zr melts at 1499 K obtained from our thermodynamic optimization was corroborated by experimental data found in the literature. The validity of the amplitude of the entropy of mixing obtained from the in silico procedure presented in this work was analyzed based on the thermodynamic description of hard sphere mixtures.
Energy Technology Data Exchange (ETDEWEB)
Grau Carles, A.; Garcia Gomez-Tejedor, G.
2001-07-01
The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs.
Karpetas, G. E.; Michail, C. M.; Fountos, G. P.; Kalyvas, N. I.; Valais, I. G.; Kandarakis, I. S.; Panayiotakis, G. S.
2014-03-01
The aim of the present study was to propose a comprehensive method for PET scanners image quality assessment, by the simulation of a thin layer chromatography (TLC) flood source with a previous validated Monte-Carlo (MC) model. The model was developed by using the GATE MC package and reconstructed images were obtained using the STIR software, with cluster computing. The PET scanner simulated was the GE Discovery-ST. The TLC source was immersed in 18F-FDG bath solution (1MBq) in order to assess image quality. The influence of different scintillating crystals on PET scanner's image quality, in terms of the MTF, the NNPS and the DQE, was investigated. Images were reconstructed by the commonly used FBP2D, FPB3DRP and the OSMAPOSL (15 subsets, 3 iterations) reprojection algorithms. The PET scanner configuration, incorporating LuAP crystals, provided the optimum MTF values in both 2D and 3DFBP whereas the corresponding configuration with BGO crystals was found with the higher MTF values after OSMAPOSL. The scanner incorporating BGO crystals were also found with the lowest noise levels and the highest DQE values after all image reconstruction algorithms. The plane source can be also useful for the experimental image quality assessment of PET and SPECT scanners in clinical practice.
Institute of Scientific and Technical Information of China (English)
万文应; 夏庆
2015-01-01
With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors’ effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.
Lysak, Y. V.; Klimanov, V. A.; Narkevich, B. Ya
2017-01-01
One of the most difficult problems of modern radionuclide therapy (RNT) is control of the absorbed dose in pathological volume. This research presents new approach based on estimation of radiopharmaceutical (RP) accumulated activity value in tumor volume, based on planar scintigraphic images of the patient and calculated radiation transport using Monte Carlo method, including absorption and scattering in biological tissues of the patient, and elements of gamma camera itself. In our research, to obtain the data, we performed modeling scintigraphy of the vial with administered to the patient activity of RP in gamma camera, the vial was placed at the certain distance from the collimator, and the similar study was performed in identical geometry, with the same values of activity of radiopharmaceuticals in the pathological target in the body of the patient. For correct calculation results, adapted Fisher-Snyder human phantom was simulated in MCNP program. In the context of our technique, calculations were performed for different sizes of pathological targets and various tumors deeps inside patient’s body, using radiopharmaceuticals based on a mixed β-γ-radiating (131I, 177Lu), and clear β- emitting (89Sr, 90Y) therapeutic radionuclides. Presented method can be used for adequate implementing in clinical practice estimation of absorbed doses in the regions of interest on the basis of planar scintigraphy of the patient with sufficient accuracy.
Energy Technology Data Exchange (ETDEWEB)
Ortiz Lora, A.; Miras del Rio, H.; Terron Leon, J. A.
2013-07-01
Following the recommendations of the IAEA, and as a further check, they have been Monte Carlo simulation of each one of the plates that are arranged at the Hospital. The objective of the work is the verification of the certificates of calibration and intends to establish criteria of action for its acceptance. (Author)
Cassandra: An open source Monte Carlo package for molecular simulation.
Shah, Jindal K; Marin-Rimoldi, Eliseo; Mullen, Ryan Gotchy; Keene, Brian P; Khan, Sandip; Paluch, Andrew S; Rai, Neeraj; Romanielo, Lucienne L; Rosch, Thomas W; Yoo, Brian; Maginn, Edward J
2017-07-15
Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Time accelerated Monte Carlo simulations of biological networks using the binomial tau-leap method.
Chatterjee, Abhijit; Mayawala, Kapil; Edwards, Jeremy S; Vlachos, Dionisios G
2005-05-01
Developing a quantitative understanding of intracellular networks requires simulations and computational analyses. However, traditional differential equation modeling tools are often inadequate due to the stochasticity of intracellular reaction networks that can potentially influence the phenotypic characteristics. Unfortunately, stochastic simulations are computationally too intense for most biological systems. Herein, we have utilized the recently developed binomial tau-leap method to carry out stochastic simulations of the epidermal growth factor receptor induced mitogen activated protein kinase cascade. Results indicate that the binomial tau-leap method is computationally 100-1000 times more efficient than the exact stochastic simulation algorithm of Gillespie. Furthermore, the binomial tau-leap method avoids negative populations and accurately captures the species populations along with their fluctuations despite the large difference in their size. http://www.dion.che.udel.edu/multiscale/Introduction.html. Fortran 90 code available for academic use by email. Details about the binomial tau-leap algorithm, software and a manual are available at the above website.
Application of Monte Carlo Simulations to Improve Basketball Shooting Strategy
Min, Byeong June
2016-01-01
The underlying physics of basketball shooting seems to be a straightforward example of the Newtonian mechanics that can easily be traced by numerical methods. However, a human basketball player does not make use of all the possible basketball trajectories. Instead, a basketball player will build up a database of successful shots and select the trajectory that has the greatest tolerance to small variations of the real world. We simulate the basketball player's shooting training as a Monte Carlo sequence to build optimal shooting strategies, such as the launch speed and angle of the basketball, and whether to take a direct shot or a bank shot, as a function of the player's court positions and height. The phase space volume that belongs to the successful launch velocities generated by Monte Carlo simulations are then used as the criterion to optimize a shooting strategy that incorporates not only mechanical, but human factors as well.
Monte Carlo Simulations of the Photospheric Process
Santana, Rodolfo; Hernandez, Roberto A; Kumar, Pawan
2015-01-01
We present a Monte Carlo (MC) code we wrote to simulate the photospheric process and to study the photospheric spectrum above the peak energy. Our simulations were performed with a photon to electron ratio $N_{\\gamma}/N_{e} = 10^{5}$, as determined by observations of the GRB prompt emission. We searched an exhaustive parameter space to determine if the photospheric process can match the observed high-energy spectrum of the prompt emission. If we do not consider electron re-heating, we determined that the best conditions to produce the observed high-energy spectrum are low photon temperatures and high optical depths. However, for these simulations, the spectrum peaks at an energy below 300 keV by a factor $\\sim 10$. For the cases we consider with higher photon temperatures and lower optical depths, we demonstrate that additional energy in the electrons is required to produce a power-law spectrum above the peak-energy. By considering electron re-heating near the photosphere, the spectrum for these simulations h...
Tubman, Norm; Hammes-Schiffer, Sharon; Ceperley, David
2016-01-01
Simulating nonadiabatic effects with many-body wave function approaches is an open field with many challenges. Recent interest has been driven by new algorithmic developments and improved theoretical understanding of properties unique to electron-ion wave functions. Fixed-node diffusion Monte Caro is one technique that has shown promising results for simulating electron-ion systems. In particular, we focus on the CH molecule for which previous results suggested a relatively significant contribution to the energy from nonadiabatic effects. We propose a new wave function ansatz for diatomic systems which involves interpolating the determinant coefficients calculated from configuration interaction methods. We find this to be an improvement beyond previous wave function forms that have been considered. The calculated nonadiabatic contribution to the energy in the CH molecule is reduced compared to our previous results, but still remains the largest among the molecules under consideration.
Improved Direct Simulation Monte Carlo method for solving modern problems of rarefied gases dynamics
Maltsev, Roman V
2012-01-01
First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important improvement is the scheme of temporal factors, allowing the use of different time step for different sorts of particles, thus reducing the complexity and/or resource usage in simulation of stationary problems with very different collisional cross-sections between components of a mixture. Other improvements include the similarity parameter for efficient estimation of the number of simulational particles required for 1D, 2D and 3D computations, the new scheme for solving axisymmetric problems, an approach to detect and reject repetitive collisions. Also, some advice on technical optimization of algorithm for modern computers is offered.
Monte Carlo Simulation as a Research Management Tool
Energy Technology Data Exchange (ETDEWEB)
Douglas, L. J.
1986-06-01
Monte Carlo simulation provides a research manager with a performance monitoring tool to supplement the standard schedule- and resource-based tools such as the Program Evaluation and Review Technique (PERT) and Critical Path Method (CPM). The value of the Monte Carlo simulation in a research environment is that it 1) provides a method for ranking competing processes, 2) couples technical improvements to the process economics, and 3) provides a mechanism to determine the value of research dollars. In this paper the Monte Carlo simulation approach is developed and applied to the evaluation of three competing processes for converting lignocellulosic biomass to ethanol. The technique is shown to be useful for ranking the processes and illustrating the importance of the timeframe of the analysis on the decision process. The results show that acid hydrolysis processes have higher potential for near-term application (2-5 years), while the enzymatic hydrolysis approach has an equal chance to be competitive in the long term (beyond 10 years).
Accelerated Monte Carlo simulations with restricted Boltzmann machines
Huang, Li; Wang, Lei
2017-01-01
Despite their exceptional flexibility and popularity, Monte Carlo methods often suffer from slow mixing times for challenging statistical physics problems. We present a general strategy to overcome this difficulty by adopting ideas and techniques from the machine learning community. We fit the unnormalized probability of the physical model to a feed-forward neural network and reinterpret the architecture as a restricted Boltzmann machine. Then, exploiting its feature detection ability, we utilize the restricted Boltzmann machine to propose efficient Monte Carlo updates to speed up the simulation of the original physical system. We implement these ideas for the Falicov-Kimball model and demonstrate an improved acceptance ratio and autocorrelation time near the phase transition point.
Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines
Huang, Li
2016-01-01
Despite their exceptional flexibility and popularity, the Monte Carlo methods often suffer from slow mixing times for challenging statistical physics problems. We present a general strategy to overcome this difficulty by adopting ideas and techniques from the machine learning community. We fit the unnormalized probability of the physical model to a feedforward neural network and reinterpret the architecture as a restricted Boltzmann machine. Then, exploiting its feature detection ability, we utilize the restricted Boltzmann machine for efficient Monte Carlo updates and to speed up the simulation of the original physical system. We implement these ideas for the Falicov-Kimball model and demonstrate improved acceptance ratio and autocorrelation time near the phase transition point.
Assessment of high-fidelity collision models in the direct simulation Monte Carlo method
Weaver, Andrew B.
Advances in computer technology over the decades has allowed for more complex physics to be modeled in the DSMC method. Beginning with the first paper on DSMC in 1963, 30,000 collision events per hour were simulated using a simple hard sphere model. Today, more than 10 billion collision events can be simulated per hour for the same problem. Many new and more physically realistic collision models such as the Lennard-Jones potential and the forced harmonic oscillator model have been introduced into DSMC. However, the fact that computer resources are more readily available and higher-fidelity models have been developed does not necessitate their usage. It is important to understand how such high-fidelity models affect the output quantities of interest in engineering applications. The effect of elastic and inelastic collision models on compressible Couette flow, ground-state atomic oxygen transport properties, and normal shock waves have therefore been investigated. Recommendations for variable soft sphere and Lennard-Jones model parameters are made based on a critical review of recent ab-initio calculations and experimental measurements of transport properties.
A zero-variance based scheme for Monte Carlo criticality simulations
Christoforou, S.
2010-01-01
The ability of the Monte Carlo method to solve particle transport problems by simulating the particle behaviour makes it a very useful technique in nuclear reactor physics. However, the statistical nature of Monte Carlo implies that there will always be a variance associated with the estimate obtain
Estimating return period of landslide triggering by Monte Carlo simulation
Peres, D. J.; Cancelliere, A.
2016-10-01
Assessment of landslide hazard is a crucial step for landslide mitigation planning. Estimation of the return period of slope instability represents a quantitative method to map landslide triggering hazard on a catchment. The most common approach to estimate return periods consists in coupling a triggering threshold equation, derived from an hydrological and slope stability process-based model, with a rainfall intensity-duration-frequency (IDF) curve. Such a traditional approach generally neglects the effect of rainfall intensity variability within events, as well as the variability of initial conditions, which depend on antecedent rainfall. We propose a Monte Carlo approach for estimating the return period of shallow landslide triggering which enables to account for both variabilities. Synthetic hourly rainfall-landslide data generated by Monte Carlo simulations are analysed to compute return periods as the mean interarrival time of a factor of safety less than one. Applications are first conducted to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed in order to evaluate the traditional IDF-based method by comparison with the Monte Carlo one. Results show that return period is affected significantly by variability of both rainfall intensity within events and of initial conditions, and that the traditional IDF-based approach may lead to an overestimation of the return period of landslide triggering, or, in other words, a non-conservative assessment of landslide hazard.
A New Approach to Monte Carlo Simulations in Statistical Physics
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).
Monte Carlo simulations for focusing elliptical guides
Energy Technology Data Exchange (ETDEWEB)
Valicu, Roxana [FRM2 Garching, Muenchen (Germany); Boeni, Peter [E20, TU Muenchen (Germany)
2009-07-01
The aim of the Monte Carlo simulations using McStas Programme was to improve the focusing of the neutron beam existing at PGAA (FRM II) by prolongation of the existing elliptic guide (coated now with supermirrors with m=3) with a new part. First we have tried with an initial length of the additional guide of 7,5cm and coatings for the neutron guide of supermirrors with m=4,5 and 6. The gain (calculated by dividing the intensity in the focal point after adding the guide by the intensity at the focal point with the initial guide) obtained for this coatings indicated that a coating with m=5 would be appropriate for a first trial. The next step was to vary the length of the additional guide for this m value and therefore choosing the appropriate length for the maximal gain. With the m value and the length of the guide fixed we have introduced an aperture 1 cm before the focal point and we have varied the radius of this aperture in order to obtain a focused beam. We have observed a dramatic decrease in the size of the beam in the focal point after introducing this aperture. The simulation results, the gains obtained and the evolution of the beam size will be presented.
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
Simulation of 12C+12C elastic scattering at high energy by using the Monte Carlo method
Institute of Scientific and Technical Information of China (English)
GUO Chen-Lei; ZHANG Gao-Long; I. Tanihata; LE Xiao-Yun
2012-01-01
The Monte Carlo method is used to simulate the 12C+12C reaction process.Taking into account the size of the incident 12C beam spot and the thickness of the 12C target,the distributions of scattered 12C on the MWPC and the CsI detectors at a detective distance have been simulated.In order to separate elastic scattering from the inelastic scattering with 4.4 MeV excited energy,we set several variables:the kinetic energy of incident 12C,the thickness of the 12C target,the ratio of the excited state,the wire spacing of the MWPC,the energy resolution of the CsI detector and the time resolution of the plastic scintillator.From the simulation results,the preliminary establishment of the experiment system can be determined to be that the beam size of the incident 12C is φ5 mm,the incident kinetic energy is 200-400 A MeV,the target thickness is 2 mm,the ratio of the excited state is 20％,the flight distance of scattered 12C is 3 m,the energy resolution of the CsI detectors is 1％,the time resolution of the plastic scintillator is 0.5％,and the size of the CsI detectors is 7 cm×7 cm,and we need at least 16 CsI detectors to cover a 0° to 5° angular distribution.
Monte Carlo Simulation for Statistical Decay of Compound Nucleus
Directory of Open Access Journals (Sweden)
Chadwick M.B.
2012-02-01
Full Text Available We perform Monte Carlo simulations for neutron and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory. This Monte Carlo Hauser-Feshbach (MCHF method calculation, which gives us correlated information between emitted particles and γ-rays. It will be a powerful tool in many applications, as nuclear reactions can be probed in a more microscopic way. We have been developing the MCHF code, CGM, which solves the Hauser-Feshbach theory with the Monte Carlo method. The code includes all the standard models that used in a standard Hauser-Feshbach code, namely the particle transmission generator, the level density module, interface to the discrete level database, and so on. CGM can emit multiple neutrons, as long as the excitation energy of the compound nucleus is larger than the neutron separation energy. The γ-ray competition is always included at each compound decay stage, and the angular momentum and parity are conserved. Some calculations for a fission fragment 140Xe are shown as examples of the MCHF method, and the correlation between the neutron and γ-ray is discussed.
Monte Carlo simulations for heavy ion dosimetry
Energy Technology Data Exchange (ETDEWEB)
Geithner, O.
2006-07-26
Water-to-air stopping power ratio (s{sub w,air}) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)
Monte Carlo simulations of the NIMROD diffractometer
Energy Technology Data Exchange (ETDEWEB)
Botti, A. [University of Roma TRE, Rome (Italy)]. E-mail: botti@fis.uniroma3.it; Ricci, M.A. [University of Roma TRE, Rome (Italy); Bowron, D.T. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom); Soper, A.K. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom)
2006-11-15
The near and intermediate range order diffractometer (NIMROD) has been selected as a day one instrument on the second target station at ISIS. Uniquely, NIMROD will provide continuous access to particle separations ranging from the interatomic (<1A) to the mesoscopic (<300A). This instrument is mainly designed for structural investigations, although the possibility of putting a Fermi chopper (and corresponding NIMONIC chopper) in the incident beam line, will potentially allow the performance of low resolution inelastic scattering measurements. The performance characteristics of the TOF diffractometer have been simulated by means of a series of Monte Carlo calculations. In particular, the flux as a function of the transferred momentum Q as well as the resolution in Q and transferred energy have been estimated. Moreover, the possibility of including a honeycomb collimator in order to achieve better resolution has been tested. Here, we want to present the design of this diffractometer that will bridge the gap between wide- and small-angle neutron scattering experiments.
Monte Carlo Simulation of River Meander Modelling
Posner, A. J.; Duan, J. G.
2010-12-01
This study first compares the first order analytical solutions for flow field by Ikeda et. al. (1981) and Johanesson and Parker (1989b). Ikeda et. al.’s (1981) linear bank erosion model was implemented to predict the rate of bank erosion in which the bank erosion coefficient is treated as a stochastic variable that varies with physical properties of the bank (e.g. cohesiveness, stratigraphy, vegetation density). The developed model was used to predict the evolution of meandering planforms. Then, the modeling results were analyzed and compared to the observed data. Since the migration of meandering channel consists of downstream translation, lateral expansion, and downstream or upstream rotations. Several measures are formulated in order to determine which of the resulting planform is closest to the experimental measured one. Results from the deterministic model highly depend on the calibrated erosion coefficient. Since field measurements are always limited, the stochastic model yielded more realistic predictions of meandering planform evolutions. Due to the random nature of bank erosion coefficient, the meandering planform evolution is a stochastic process that can only be accurately predicted by a stochastic model. Quasi-2D Ikeda (1989) flow solution with Monte Carlo Simulation of Bank Erosion Coefficient.
Monte Carlo Methods in ICF (LIRPP Vol. 13)
Zimmerman, George B.
2016-10-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved SOX in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
Monte Carlo Methods for Bridging the Timescale Gap
Wilding, Nigel; Landau, David P.
We identify the origin, and elucidate the character of the extended time-scales that plague computer simulation studies of first and second order phase transitions. A brief survey is provided of a number of new and existing techniques that attempt to circumvent these problems. Attention is then focused on two novel methods with which we have particular experience: “Wang-Landau sampling” and Phase Switch Monte Carlo. Detailed case studies are made of the application of the Wang-Landau approach to calculate the density of states of the 2D Ising model and the Edwards-Anderson spin glass. The principles and operation of Phase Switch Monte Carlo are described and its utility in tackling ‘difficult’ first order phase transitions is illustrated via a case study of hard-sphere freezing. We conclude with a brief overview of promising new methods for the improvement of deterministic, spin dynamics simulations.
Xu, Yuan; Bai, Ti; Yan, Hao; Ouyang, Luo; Pompos, Arnold; Wang, Jing; Zhou, Linghong; Jiang, Steve B; Jia, Xun
2015-05-07
Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 to 3 HU and from 78 to 9 HU in the full-fan and the half-fan cases, respectively. In both the phantom and the patient cases, image artifacts caused by scatter, such as ring artifacts around the bowtie area, were reduced. With all the techniques employed, we achieved computation time of less than 30 s including the
Monte Carlo simulation of neutron scattering instruments
Energy Technology Data Exchange (ETDEWEB)
Seeger, P.A.
1995-12-31
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width.
Institute of Scientific and Technical Information of China (English)
李海普; 钟志辉; 李星; 宋振伟
2012-01-01
Monte Carlo method and its characteristic were introduced,its advantages in the conformation simulation of polymer were further analyzed,and two simulation models were also described.With emphasis on the development of Monte Carlo in conformation simulations,the applications of the method during the research of polymer conformation in confined space and non-confined space were summarized,and the trends and prospects for the Monte Carlo simulations of polymer conformations for future were speculated.%介绍了Monte Carlo方法及其特点,进而分析了Monte Carlo用于高分子模拟的优势,并描述了两类模拟模型。论文重点综述了近年来Monte Carlo方法在高分子构象模拟中的一些研究与应用,并展望了Monte Carlo方法在高分子构象模拟中的发展趋势和前景。
Carsey, Thomas M.; Harden, Jeffrey J.
2015-01-01
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
Carsey, Thomas M.; Harden, Jeffrey J.
2015-01-01
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
Development of ray tracing visualization program by Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro
1997-09-01
Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)
Development of ray tracing visualization program by Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro
1997-09-01
Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)
Li, Jun
2013-09-01
We present a single-particle Lennard-Jones (L-J) model for CO2 and N2. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO2 and N2 agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH4, CO2 and N2 are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. Since the single-particle model reduces the particle number and avoids the time-consuming Ewald summation used to evaluate Coulomb interactions, the proposed model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available. © 2013 Elsevier Inc.
Recent Developments in Quantum Monte Carlo: Methods and Applications
Aspuru-Guzik, Alan; Austin, Brian; Domin, Dominik; Galek, Peter T. A.; Handy, Nicholas; Prasad, Rajendra; Salomon-Ferrer, Romelia; Umezawa, Naoto; Lester, William A.
2007-12-01
The quantum Monte Carlo method in the diffusion Monte Carlo form has become recognized for its capability of describing the electronic structure of atomic, molecular and condensed matter systems to high accuracy. This talk will briefly outline the method with emphasis on recent developments connected with trial function construction, linear scaling, and applications to selected systems.
MONTE CARLO SIMULATION OF CHARGED PARTICLE IN AN ELECTRONEGATIVE PLASMA
Directory of Open Access Journals (Sweden)
L SETTAOUTI
2003-12-01
Full Text Available Interest in radio frequency (rf discharges has grown tremendously in recent years due to their importance in microelectronic technologies. Especially interesting are the properties of discharges in electronegative gases which are most frequently used for technological applications. Monte Carlo simulation have become increasingly important as a simulation tool particularly in the area of plasma physics. In this work, we present some detailed properties of rf plasmas obtained by Monte Carlo simulation code, in SF6
Monte Carlo methods for pricing ﬁnancial options
Indian Academy of Sciences (India)
N Bolia; S Juneja
2005-04-01
Pricing ﬁnancial options is amongst the most important and challenging problems in the modern ﬁnancial industry. Except in the simplest cases, the prices of options do not have a simple closed form solution and efﬁcient computational methods are needed to determine them. Monte Carlo methods have increasingly become a popular computational tool to price complex ﬁnancial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the ‘curse of dimensionality’. However, even Monte-Carlo techniques can be quite slow as the problem-size increases, motivating research in variance reduction techniques to increase the efﬁciency of the simulations. In this paper, we review some of the popular variance reduction techniques and their application to pricing options. We particularly focus on the recent Monte-Carlo techniques proposed to tackle the difﬁcult problem of pricing American options. These include: regression-based methods, random tree methods and stochastic mesh methods. Further, we show how importance sampling, a popular variance reduction technique, may be combined with these methods to enhance their effectiveness. We also brieﬂy review the evolving options market in India.
Monte Carlo simulation of large electron fields
Faddegon, Bruce A.; Perl, Joseph; Asai, Makoto
2008-03-01
Two Monte Carlo systems, EGSnrc and Geant4, the latter with two different 'physics lists,' were used to calculate dose distributions in large electron fields used in radiotherapy. Source and geometry parameters were adjusted to match calculated results to measurement. Both codes were capable of accurately reproducing the measured dose distributions of the six electron beams available on the accelerator. Depth penetration matched the average measured with a diode and parallel-plate chamber to 0.04 cm or better. Calculated depth dose curves agreed to 2% with diode measurements in the build-up region, although for the lower beam energies there was a discrepancy of up to 5% in this region when calculated results are compared to parallel-plate measurements. Dose profiles at the depth of maximum dose matched to 2-3% in the central 25 cm of the field, corresponding to the field size of the largest applicator. A 4% match was obtained outside the central region. The discrepancy observed in the bremsstrahlung tail in published results that used EGS4 is no longer evident. Simulations with the different codes and physics lists used different source energies, incident beam angles, thicknesses of the primary foils, and distance between the primary and secondary foil. The true source and geometry parameters were not known with sufficient accuracy to determine which parameter set, including the energy of the source, was closest to the truth. These results underscore the requirement for experimental benchmarks of depth penetration and electron scatter for beam energies and foils relevant to radiotherapy.
Public Infrastructure for Monte Carlo Simulation: publicMC@BATAN
Waskita, A A; Akbar, Z; Handoko, L T; 10.1063/1.3462759
2010-01-01
The first cluster-based public computing for Monte Carlo simulation in Indonesia is introduced. The system has been developed to enable public to perform Monte Carlo simulation on a parallel computer through an integrated and user friendly dynamic web interface. The beta version, so called publicMC@BATAN, has been released and implemented for internal users at the National Nuclear Energy Agency (BATAN). In this paper the concept and architecture of publicMC@BATAN are presented.
Vectorized Monte Carlo methods for reactor lattice analysis
Brown, F. B.
1984-01-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
SKIRT: the design of a suite of input models for Monte Carlo radiative transfer simulations
Baes, Maarten
2015-01-01
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...
Investigating Transmission Efficiency of Light Guide by Monte Carlo Simulation
Institute of Scientific and Technical Information of China (English)
LiChen; XiaoGuoqing; GuoZhongyan; ZhanWenlongt; SunZhiyu; WangMeng; ChenZhiqiang; MaoRuishi; BaiJie; HuZhengguo; ChenLixin
2003-01-01
A large area neutron detector to detect the energy of about 1 GeV neutron by time-of flight method will be installed at RIBLL II of CSR. To obtain good energy resolution, the time resolution of the detector is a crucial parameter. For this purpose, the transmission efficiency of the light guide to transport the photons from detec-tor unit to light sensitive detector has been investigated by Monte-Carlo simulation. Here, the simulations were done mainly with two types of the light guides, namely type A and type B as shown in Figs.1 and 2 respectively.
Monte Carlo simulation of charge mediated magnetoelectricity in multiferroic bilayers
Energy Technology Data Exchange (ETDEWEB)
Ortiz-Álvarez, H.H. [Universidad de Caldas, Manizales (Colombia); Universidad Nacional de Colombia Sede Manizales, Manizales, Caldas (Colombia); Bedoya-Hincapié, C.M. [Universidad Nacional de Colombia Sede Manizales, Manizales, Caldas (Colombia); Universidad Santo Tomás, Bogotá (Colombia); Restrepo-Parra, E., E-mail: erestrepopa@unal.edu.co [Universidad Nacional de Colombia Sede Manizales, Manizales, Caldas (Colombia)
2014-12-01
Simulations of a bilayer ferroelectric/ferromagnetic multiferroic system were carried out, based on the Monte Carlo method and Metropolis dynamics. A generic model was implemented with a Janssen-like Hamiltonian, taking into account magnetoelectric interactions due to charge accumulation at the interface. Two different magnetic exchange constants were considered for accumulation and depletion states. Several screening lengths were also included. Simulations exhibit considerable magnetoelectric effects not only at low temperature, but also at temperature near to the transition point of the ferromagnetic layer. The results match experimental observations for this kind of structure and mechanism.
Monte Carlo Simulation Of Emission Tomography And Other Medical Imaging Techniques
Harrison, Robert L.
2010-01-01
An introduction to Monte Carlo simulation of emission tomography. This paper reviews the history and principles of Monte Carlo simulation, then applies these principles to emission tomography using the public domain simulation package SimSET (a Simulation System for Emission Tomography) as an example. Finally, the paper discusses how the methods are modified for X-ray computed tomography and radiotherapy simulations. PMID:20733931
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James
2012-03-01
Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.
Directory of Open Access Journals (Sweden)
Md Nabiul Islam Khan
Full Text Available In the Point-Centred Quarter Method (PCQM, the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1 and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns plant populations and empirical ones.PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3 show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition. If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1/(π ∑ R2 but not 12N/(π ∑ R2, of PCQM2 is 4(8N - 1/(π ∑ R2 but not 28N/(π ∑ R2 and of PCQM3 is 4(12N - 1/(π ∑ R2 but not 44N/(π ∑ R2 as published.If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Quantifying uncertainties in primordial nucleosynthesis without Monte Carlo simulations
Fiorentini, G; Sarkar, S; Villante, F L
1998-01-01
We present a simple method for determining the (correlated) uncertainties of the light element abundances expected from big bang nucleosynthesis, which avoids the need for lengthy Monte Carlo simulations. Our approach helps to clarify the role of the different nuclear reactions contributing to a particular elemental abundance and makes it easy to implement energy-independent changes in the measured reaction rates. As an application, we demonstrate how this method simplifies the statistical estimation of the nucleon-to-photon ratio through comparison of the standard BBN predictions with the observationally inferred abundances.
Monte Carlo simulations: Hidden errors from ``good'' random number generators
Ferrenberg, Alan M.; Landau, D. P.; Wong, Y. Joanna
1992-12-01
The Wolff algorithm is now accepted as the best cluster-flipping Monte Carlo algorithm for beating ``critical slowing down.'' We show how this method can yield incorrect answers due to subtle correlations in ``high quality'' random number generators.
Monte Carlo simulation for simultaneous particle coagulation and deposition
Institute of Scientific and Technical Information of China (English)
ZHAO; Haibo; ZHENG; Chuguang
2006-01-01
The process of dynamic evolution in dispersed systems due to simultaneous particle coagulation and deposition is described mathematically by general dynamic equation (GDE). Monte Carlo (MC) method is an important approach of numerical solutions of GDE. However, constant-volume MC method exhibits the contradictory of low computation cost and high computation precision owing to the fluctuation of the number of simulation particles; constant-number MC method can hardly be applied to engineering application and general scientific quantitative analysis due to the continual contraction or expansion of computation domain. In addition, the two MC methods depend closely on the "subsystem" hypothesis, which constraints their expansibility and the scope of application. A new multi-Monte Carlo (MMC) method is promoted to take account of GDE for simultaneous particle coagulation and deposition. MMC method introduces the concept of "weighted fictitious particle" and is based on the "time-driven" technique. Furthermore MMC method maintains synchronously the computational domain and the total number of fictitious particles, which results in the latent expansibility of simulation for boundary condition, the space evolution of particle size distribution and even particle dynamics. The simulation results of MMC method for two special cases in which analytical solutions exist agree with analytical solutions well, which proves that MMC method has high and stable computational precision and low computation cost because of the constant and limited number of fictitious particles. Lastly the source of numerical error and the relative error of MMC method are analyzed, respectively.
Monte Carlo simulation of the standardization of {sup 22}Na using scintillation detector arrays
Energy Technology Data Exchange (ETDEWEB)
Sato, Y., E-mail: yss.sato@aist.go.j [National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan); Murayama, H. [National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage, Chiba 263-8555 (Japan); Yamada, T. [Japan Radioisotope Association, 2-28-45, Hon-komagome, Bunkyo, Tokyo 113-8941 (Japan); National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan); Tohoku University, 6-6, Aoba, Aramaki, Aoba, Sendai 980-8579 (Japan); Hasegawa, T. [Kitasato University, 1-15-1, Kitasato, Sagamihara, Kanagawa 228-8555 (Japan); Oda, K. [Tokyo Metropolitan Institute of Gerontology, 1-1 Nakacho, Itabashi-ku, Tokyo 173-0022 (Japan); Unno, Y.; Yunoki, A. [National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan)
2010-07-15
In order to calibrate PET devices by a sealed point source, we contrived an absolute activity measurement method for the sealed point source using scintillation detector arrays. This new method was verified by EGS5 Monte Carlo simulation.
Kovtanyuk, Andrey E.
2012-01-01
Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.
A generalized hard-sphere model for Monte Carlo simulation
Hassan, H. A.; Hash, David B.
1993-01-01
A new molecular model, called the generalized hard-sphere, or GHS model, is introduced. This model contains, as a special case, the variable hard-sphere model of Bird (1981) and is capable of reproducing all of the analytic viscosity coefficients available in the literature that are derived for a variety of interaction potentials incorporating attraction and repulsion. In addition, a new procedure for determining interaction potentials in a gas mixture is outlined. Expressions needed for implementing the new model in the direct simulation Monte Carlo methods are derived. This development makes it possible to employ interaction models that have the same level of complexity as used in Navier-Stokes calculations.
Monte Carlo simulation experiments on box-type radon dosimeter
Jamil, Khalid; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid
2014-11-01
Epidemiological studies show that inhalation of radon gas (222Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the 222Rn concentrations (Bq/m3) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter's dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (ηint) and alpha hit efficiency (ηhit). The ηint depends upon only on the dimensions of the dosimeter and ηhit depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper explains that how radon concentration from the
Monte Carlo simulation experiments on box-type radon dosimeter
Energy Technology Data Exchange (ETDEWEB)
Jamil, Khalid, E-mail: kjamil@comsats.edu.pk; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid
2014-11-11
Epidemiological studies show that inhalation of radon gas ({sup 222}Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the {sup 222}Rn concentrations (Bq/m{sup 3}) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η{sub int}) and alpha hit efficiency (η{sub hit}). The η{sub int} depends upon only on the dimensions of the dosimeter and η{sub hit} depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper
On the time scale associated with Monte Carlo simulations.
Bal, Kristof M; Neyts, Erik C
2014-11-28
Uniform-acceptance force-bias Monte Carlo (fbMC) methods have been shown to be a powerful technique to access longer timescales in atomistic simulations allowing, for example, phase transitions and growth. Recently, a new fbMC method, the time-stamped force-bias Monte Carlo (tfMC) method, was derived with inclusion of an estimated effective timescale; this timescale, however, does not seem able to explain some of the successes the method. In this contribution, we therefore explicitly quantify the effective timescale tfMC is able to access for a variety of systems, namely a simple single-particle, one-dimensional model system, the Lennard-Jones liquid, an adatom on the Cu(100) surface, a silicon crystal with point defects and a highly defected graphene sheet, in order to gain new insights into the mechanisms by which tfMC operates. It is found that considerable boosts, up to three orders of magnitude compared to molecular dynamics, can be achieved for solid state systems by lowering of the apparent activation barrier of occurring processes, while not requiring any system-specific input or modifications of the method. We furthermore address the pitfalls of using the method as a replacement or complement of molecular dynamics simulations, its ability to explicitly describe correct dynamics and reaction mechanisms, and the association of timescales to MC simulations in general.
On the time scale associated with Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Bal, Kristof M., E-mail: kristof.bal@uantwerpen.be; Neyts, Erik C. [Department of Chemistry, University of Antwerp, Research Group PLASMANT, Universiteitsplein 1, 2610 Wilrijk, Antwerp (Belgium)
2014-11-28
Uniform-acceptance force-bias Monte Carlo (fbMC) methods have been shown to be a powerful technique to access longer timescales in atomistic simulations allowing, for example, phase transitions and growth. Recently, a new fbMC method, the time-stamped force-bias Monte Carlo (tfMC) method, was derived with inclusion of an estimated effective timescale; this timescale, however, does not seem able to explain some of the successes the method. In this contribution, we therefore explicitly quantify the effective timescale tfMC is able to access for a variety of systems, namely a simple single-particle, one-dimensional model system, the Lennard-Jones liquid, an adatom on the Cu(100) surface, a silicon crystal with point defects and a highly defected graphene sheet, in order to gain new insights into the mechanisms by which tfMC operates. It is found that considerable boosts, up to three orders of magnitude compared to molecular dynamics, can be achieved for solid state systems by lowering of the apparent activation barrier of occurring processes, while not requiring any system-specific input or modifications of the method. We furthermore address the pitfalls of using the method as a replacement or complement of molecular dynamics simulations, its ability to explicitly describe correct dynamics and reaction mechanisms, and the association of timescales to MC simulations in general.
Dynamical Monte Carlo method for stochastic epidemic models
Aiello, O E
2002-01-01
A new approach to Dynamical Monte Carlo Methods is introduced to simulate markovian processes. We apply this approach to formulate and study an epidemic Generalized SIRS model. The results are in excellent agreement with the forth order Runge-Kutta method in a region of deterministic solution. Introducing local stochastic interactions, the Runge-Kutta method is not applicable, and we solve and check it self-consistently with a stochastic version of the Euler Method. The results are also analyzed under the herd-immunity concept.
Monte Carlo method for solving a parabolic problem
Directory of Open Access Journals (Sweden)
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
On the Markov Chain Monte Carlo (MCMC) method
Indian Academy of Sciences (India)
Rajeeva L Karandikar
2006-04-01
Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be speciﬁed indirectly. In this article, we give an introduction to this method along with some examples.
Non-Boltzmann Ensembles and Monte Carlo Simulations
Murthy, K. P. N.
2016-10-01
Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc. This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g(E, M), as a function of both energy E, and order parameter M. This is carried out in two stages. We estimate g(E) in the first stage. Employing g
Monte Carlo methods for light propagation in biological tissues
Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine
2016-01-01
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis–Hastings algori...
Application of Monte Carlo methods in tomotherapy and radiation biophysics
Hsiao, Ya-Yun
Helical tomotherapy is an attractive treatment for cancer therapy because highly conformal dose distributions can be achieved while the on-board megavoltage CT provides simultaneous images for accurate patient positioning. The convolution/superposition (C/S) dose calculation methods typically used for Tomotherapy treatment planning may overestimate skin (superficial) doses by 3-13%. Although more accurate than C/S methods, Monte Carlo (MC) simulations are too slow for routine clinical treatment planning. However, the computational requirements of MC can be reduced by developing a source model for the parts of the accelerator that do not change from patient to patient. This source model then becomes the starting point for additional simulations of the penetration of radiation through patient. In the first section of this dissertation, a source model for a helical tomotherapy is constructed by condensing information from MC simulations into series of analytical formulas. The MC calculated percentage depth dose and beam profiles computed using the source model agree within 2% of measurements for a wide range of field sizes, which suggests that the proposed source model provides an adequate representation of the tomotherapy head for dose calculations. Monte Carlo methods are a versatile technique for simulating many physical, chemical and biological processes. In the second major of this thesis, a new methodology is developed to simulate of the induction of DNA damage by low-energy photons. First, the PENELOPE Monte Carlo radiation transport code is used to estimate the spectrum of initial electrons produced by photons. The initial spectrum of electrons are then combined with DNA damage yields for monoenergetic electrons from the fast Monte Carlo damage simulation (MCDS) developed earlier by Semenenko and Stewart (Purdue University). Single- and double-strand break yields predicted by the proposed methodology are in good agreement (1%) with the results of published
Grand Canonical Ensemble Monte Carlo Simulation of Depletion Interactions in Colloidal Suspensions
Institute of Scientific and Technical Information of China (English)
GUO Ji-Yuan; XIAO Chang-Ming
2008-01-01
Depletion interactions in colloidal suspensions confined between two parallel plates are investigated by using acceptance ratio method with grand canonical ensemble Monte Carlo simulation.The numerical results show that both the depletion potential and depletion force are affected by the confinement from the two parallel plates.Furthermore,it is found that in the grand canonical ensemble Monte Carlo simulation,the depletion interactions are strongly affected by the generalized chemical potential.
Energy Technology Data Exchange (ETDEWEB)
Albuquerque, M.A.G.; David, M.G.; Almeida, C.E. de; Magalhaes, L.A.G., E-mail: malbuqueque@hotmail.com [Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ (Brazil). Lab. de Ciencias Radiologicas; Bernal, M. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil); Braz, D. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)
2015-07-01
Breast cancer is the most common type of cancer among women. The main strategy to increase the long-term survival of patients with this disease is the early detection of the tumor, and mammography is the most appropriate method for this purpose. Despite the reduction of cancer deaths, there is a big concern about the damage caused by the ionizing radiation to the breast tissue. To evaluate these measures it was modeled a mammography equipment, and obtained the depth spectra using the Monte Carlo method - PENELOPE code. The average energies of the spectra in depth and the half value layer of the mammography output spectrum. (author)
Monte Carlo and analytic simulations in nanoparticle-enhanced radiation therapy
Directory of Open Access Journals (Sweden)
Paro AD
2016-09-01
Full Text Available Autumn D Paro,1 Mainul Hossain,2 Thomas J Webster,1,3,4 Ming Su1,4 1Department of Chemical Engineering, Northeastern University, Boston, MA, USA; 2NanoScience Technology Center and School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida, USA; 3Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, Saudi Arabia; 4Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Science, Wenzhou Medical University, Zhejiang, People’s Republic of China Abstract: Analytical and Monte Carlo simulations have been used to predict dose enhancement factors in nanoparticle-enhanced X-ray radiation therapy. Both simulations predict an increase in dose enhancement in the presence of nanoparticles, but the two methods predict different levels of enhancement over the studied energy, nanoparticle materials, and concentration regime for several reasons. The Monte Carlo simulation calculates energy deposited by electrons and photons, while the analytical one only calculates energy deposited by source photons and photoelectrons; the Monte Carlo simulation accounts for electron–hole recombination, while the analytical one does not; and the Monte Carlo simulation randomly samples photon or electron path and accounts for particle interactions, while the analytical simulation assumes a linear trajectory. This study demonstrates that the Monte Carlo simulation will be a better choice to evaluate dose enhancement with nanoparticles in radiation therapy. Keywords: nanoparticle, dose enhancement, Monte Carlo simulation, analytical simulation, radiation therapy, tumor cell, X-ray
Directory of Open Access Journals (Sweden)
Giuliano Carrozza Uzêda Iorio de Souza
2011-08-01
Full Text Available This article presents a practical case in which two of the most efficient numerical procedures developed for derivative analysis are applied to evaluate the POP (Investment Protection with Participation, a structured operation created by São Paulo Stock Exchange - BM&FBOVESPA. The first procedure solves the differential equation through the use of implicit finite differences method. Due to its characteristics, the approach makes it possible to run sensitivity analysis as well as price estimation. In the second, the problem is solved by Monte Carlo simulation, which facilitates the identification of the probability related to the exercise of the embedded options.
Institute of Scientific and Technical Information of China (English)
殷雯; 张国锋; 杜建红; 梁九卿
2003-01-01
The Monte Carlo simulation and the finite element methods have been used to calculate the heat deposition and temperature distribution in tungsten plate target when the target is bombarded by high-energy protons from the accelerator with nuclear power of 100 kW. The results show that the heat deposition in the target, reflector and shield will be 48 kW, 15 kW and 11 kW, respectively, and the highest temperature in the target plates will be lower than 100 ℃when the surfaces of plates are cooled by water.
LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events
Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V
2008-01-01
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 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.
Monte Carlo methods and applications in nuclear physics
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Probabilistic fire simulator - Monte Carlo simulation tool for fire scenarios
Energy Technology Data Exchange (ETDEWEB)
Hostikka, S.; Keski-Rahkonen, O. [VTT Building and Transport, Espoo (Finland)
2002-11-01
Risk analysis tool is developed for computing of the distributions of fire model output variables. The tool, called Probabilistic Fire Simulator, combines Monte Carlo simulation and CFAST two-zone fire model. In this work, it is used to calculate failure probability of redundant cables and fire detector activation times in a cable tunnel fire. Sensitivity of the output variables to the input variables is calculated in terms of the rank order correlations. (orig.)
Spatial distribution sampling and Monte Carlo simulation of radioactive isotopes
Krainer, Alexander Michael
2015-01-01
This work focuses on the implementation of a program for random sampling of uniformly spatially distributed isotopes for Monte Carlo particle simulations and in specific FLUKA. With FLUKA it is possible to calculate the radio nuclide production in high energy fields. The decay of these nuclide, and therefore the resulting radiation field, however can only be simulated in the same geometry. This works gives the tool to simulate the decay of the produced nuclide in other geometries. With that the radiation field from an irradiated object can be simulated in arbitrary environments. The sampling of isotope mixtures was tested by simulating a 50/50 mixture of $Cs^{137}$ and $Co^{60}$. These isotopes are both well known and provide therefore a first reliable benchmark in that respect. The sampling of uniformly distributed coordinates was tested using the histogram test for various spatial distributions. The advantages and disadvantages of the program compared to standard methods are demonstrated in the real life ca...
Accelerating particle-in-cell simulations using multilevel Monte Carlo
Ricketson, Lee
2015-11-01
Particle-in-cell (PIC) simulations have been an important tool in understanding plasmas since the dawn of the digital computer. Much more recently, the multilevel Monte Carlo (MLMC) method has accelerated particle-based simulations of a variety of systems described by stochastic differential equations (SDEs), from financial portfolios to porous media flow. The fundamental idea of MLMC is to perform correlated particle simulations using a hierarchy of different time steps, and to use these correlations for variance reduction on the fine-step result. This framework is directly applicable to the Langevin formulation of Coulomb collisions, as demonstrated in previous work, but in order to apply to PIC simulations of realistic scenarios, MLMC must be generalized to incorporate self-consistent evolution of the electromagnetic fields. We present such a generalization, with rigorous results concerning its accuracy and efficiency. We present examples of the method in the collisionless, electrostatic context, and discuss applications and extensions for the future.
Successful combination of the stochastic linearization and Monte Carlo methods
Elishakoff, I.; Colombi, P.
1993-01-01
A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.
Zhang, Ying; Feng, Yuanming; Wang, Wei; Yang, Chengwen; Wang, Ping
2017-01-01
A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy. PMID:28322329
Zhang, Ying; Feng, Yuanming; Wang, Wei; Yang, Chengwen; Wang, Ping
2017-03-01
A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy.
Energy Technology Data Exchange (ETDEWEB)
Brunetti, Antonio; Golosio, Bruno [Universita degli Studi di Sassari, Dipartimento di Scienze Politiche, Scienze della Comunicazione e Ingegneria dell' Informazione, Sassari (Italy); Melis, Maria Grazia [Universita degli Studi di Sassari, Dipartimento di Storia, Scienze dell' Uomo e della Formazione, Sassari (Italy); Mura, Stefania [Universita degli Studi di Sassari, Dipartimento di Agraria e Nucleo di Ricerca sulla Desertificazione, Sassari (Italy)
2014-11-08
X-ray fluorescence (XRF) is a well known nondestructive technique. It is also applied to multilayer characterization, due to its possibility of estimating both composition and thickness of the layers. Several kinds of cultural heritage samples can be considered as a complex multilayer, such as paintings or decorated objects or some types of metallic samples. Furthermore, they often have rough surfaces and this makes a precise determination of the structure and composition harder. The standard quantitative XRF approach does not take into account this aspect. In this paper, we propose a novel approach based on a combined use of X-ray measurements performed with a polychromatic beam and Monte Carlo simulations. All the information contained in an X-ray spectrum is used. This approach allows obtaining a very good estimation of the sample contents both in terms of chemical elements and material thickness, and in this sense, represents an improvement of the possibility of XRF measurements. Some examples will be examined and discussed. (orig.)
Reaction Ensemble Monte Carlo Simulation of Complex Molecular Systems.
Rosch, Thomas W; Maginn, Edward J
2011-02-08
Acceptance rules for reaction ensemble Monte Carlo (RxMC) simulations containing classically modeled atomistic degrees of freedom are derived for complex molecular systems where insertions and deletions are achieved gradually by utilizing the continuous fractional component (CFC) method. A self-consistent manner in which to utilize statistical mechanical data contained in ideal gas free energy parameters during RxMC moves is presented. The method is tested by applying it to two previously studied systems containing intramolecular degrees of freedom: the propene metathesis reaction and methyl-tert-butyl-ether (MTBE) synthesis. Quantitative agreement is found between the current results and those of Keil et al. (J. Chem. Phys. 2005, 122, 164705) for the propene metathesis reaction. Differences are observed between the equilibrium concentrations of the present study and those of Lísal et al. (AIChE J. 2000, 46, 866-875) for the MTBE reaction. It is shown that most of this difference can be attributed to an incorrect formulation of the Monte Carlo acceptance rule. Efficiency gains using CFC MC as opposed to single stage molecule insertions are presented.
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Jadach, S.
2017-01-01
We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Jadach, S; Placzek, W; Sapeta, S; Siodmok, A; Skrzypek, M
2016-01-01
We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...
Quasi-Monte Carlo methods for lattice systems: a first look
Jansen, K; Nube, A; Griewank, A; Müller-Preussker, M
2013-01-01
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like 1/Sqrt(N), where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to 1/N. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
Monte Carlo simulation of electron slowing down in indium
Energy Technology Data Exchange (ETDEWEB)
Rouabah, Z.; Hannachi, M. [Materials and Electronic Systems Laboratory (LMSE), University of Bordj Bou Arreridj, Bordj Bou Arreridj (Algeria); Champion, C. [Université de Bordeaux 1, CNRS/IN2P3, Centre d’Etudes Nucléaires de Bordeaux-Gradignan, (CENBG), Gradignan (France); Bouarissa, N., E-mail: n_bouarissa@yahoo.fr [Laboratory of Materials Physics and its Applications, University of M' sila, 28000 M' sila (Algeria)
2015-07-15
Highlights: • Electron scattering in indium targets. • Modeling of elastic cross-sections. • Monte Carlo simulation of low energy electrons. - Abstract: In the current study, we aim at simulating via a detailed Monte Carlo code, the electron penetration in a semi-infinite indium medium for incident energies ranging from 0.5 to 5 keV. Electron range, backscattering coefficients, mean penetration depths as well as stopping profiles are then reported. The results may be seen as the first predictions for low-energy electron penetration in indium target.
Utilising Monte Carlo Simulation for the Valuation of Mining Concessions
Directory of Open Access Journals (Sweden)
Rosli Said
2005-12-01
Full Text Available Valuation involves the analyses of various input data to produce an estimated value. Since each input is itself often an estimate, there is an element of uncertainty in the input. This leads to uncertainty in the resultant output value. It is argued that a valuation must also convey information on the uncertainty, so as to be more meaningful and informative to the user. The Monte Carlo simulation technique can generate the information on uncertainty and is therefore potentially useful to valuation. This paper reports on the investigation that has been conducted to apply Monte Carlo simulation technique in mineral valuation, more specifically, in the valuation of a quarry concession.
THE APPLICATION OF MONTE CARLO SIMULATION FOR A DECISION PROBLEM
Directory of Open Access Journals (Sweden)
Çiğdem ALABAŞ
2001-01-01
Full Text Available The ultimate goal of the standard decision tree approach is to calculate the expected value of a selected performance measure. In the real-world situations, the decision problems become very complex as the uncertainty factors increase. In such cases, decision analysis using standard decision tree approach is not useful. One way of overcoming this difficulty is the Monte Carlo simulation. In this study, a Monte Carlo simulation model is developed for a complex problem and statistical analysis is performed to make the best decision.
Monte Carlo simulation of electrons in dense gases
Tattersall, Wade; Boyle, Greg; Cocks, Daniel; Buckman, Stephen; White, Ron
2014-10-01
We implement a Monte-Carlo simulation modelling the transport of electrons and positrons in dense gases and liquids, by using a dynamic structure factor that allows us to construct structure-modified effective cross sections. These account for the coherent effects caused by interactions with the relatively dense medium. The dynamic structure factor also allows us to model thermal gases in the same manner, without needing to directly sample the velocities of the neutral particles. We present the results of a series of Monte Carlo simulations that verify and apply this new technique, and make comparisons with macroscopic predictions and Boltzmann equation solutions. Financial support of the Australian Research Council.
Hinzke, Denise; Nowak, Ulrich
1999-01-01
Using Monte Carlo methods we investigate the thermally activated magnetization switching of small ferromagnetic particles driven by an external magnetic field. For low uniaxial anisotropy one expects that the spins rotate coherently while for sufficiently large anisotropy the reversal should be due to nucleation. The latter case has been investigated extensively by Monte Carlo simulation of corresponding Ising models. In order to study the crossover from coherent rotation to nucleation we use...
Energy Technology Data Exchange (ETDEWEB)
NONE
2001-01-01
In the report, research results discussed in 1999 fiscal year at Nuclear Code Evaluation Committee of Nuclear Code Research Committee were summarized. Present status of Monte Carlo simulation on nuclear energy study was described. Especially, besides of criticality, shielding and core analyses, present status of applications to risk and radiation damage analyses, high energy transport and nuclear theory calculations of Monte Carlo Method was described. The 18 papers are indexed individually. (J.P.N.)
Benchmarking of Proton Transport in Super Monte Carlo Simulation Program
Wang, Yongfeng; Li, Gui; Song, Jing; Zheng, Huaqing; Sun, Guangyao; Hao, Lijuan; Wu, Yican
2014-06-01
The Monte Carlo (MC) method has been traditionally applied in nuclear design and analysis due to its capability of dealing with complicated geometries and multi-dimensional physics problems as well as obtaining accurate results. The Super Monte Carlo Simulation Program (SuperMC) is developed by FDS Team in China for fusion, fission, and other nuclear applications. The simulations of radiation transport, isotope burn-up, material activation, radiation dose, and biology damage could be performed using SuperMC. Complicated geometries and the whole physical process of various types of particles in broad energy scale can be well handled. Bi-directional automatic conversion between general CAD models and full-formed input files of SuperMC is supported by MCAM, which is a CAD/image-based automatic modeling program for neutronics and radiation transport simulation. Mixed visualization of dynamical 3D dataset and geometry model is supported by RVIS, which is a nuclear radiation virtual simulation and assessment system. Continuous-energy cross section data from hybrid evaluated nuclear data library HENDL are utilized to support simulation. Neutronic fixed source and critical design parameters calculates for reactors of complex geometry and material distribution based on the transport of neutron and photon have been achieved in our former version of SuperMC. Recently, the proton transport has also been intergrated in SuperMC in the energy region up to 10 GeV. The physical processes considered for proton transport include electromagnetic processes and hadronic processes. The electromagnetic processes include ionization, multiple scattering, bremsstrahlung, and pair production processes. Public evaluated data from HENDL are used in some electromagnetic processes. In hadronic physics, the Bertini intra-nuclear cascade model with exitons, preequilibrium model, nucleus explosion model, fission model, and evaporation model are incorporated to treat the intermediate energy nuclear
Kinetic Monte Carlo simulation of the classical nucleation process
Filipponi, A.; Giammatteo, P.
2016-12-01
We implemented a kinetic Monte Carlo computer simulation of the nucleation process in the framework of the coarse grained scenario of the Classical Nucleation Theory (CNT). The computational approach is efficient for a wide range of temperatures and sample sizes and provides a reliable simulation of the stochastic process. The results for the nucleation rate are in agreement with the CNT predictions based on the stationary solution of the set of differential equations for the continuous variables representing the average population distribution of nuclei size. Time dependent nucleation behavior can also be simulated with results in agreement with previous approaches. The method, here established for the case in which the excess free-energy of a crystalline nucleus is a smooth-function of the size, can be particularly useful when more complex descriptions are required.
A Monte Carlo Simulation Framework for Testing Cosmological Models
Directory of Open Access Journals (Sweden)
Heymann Y.
2014-10-01
Full Text Available We tested alternative cosmologies using Monte Carlo simulations based on the sam- pling method of the zCosmos galactic survey. The survey encompasses a collection of observable galaxies with respective redshifts that have been obtained for a given spec- troscopic area of the sky. Using a cosmological model, we can convert the redshifts into light-travel times and, by slicing the survey into small redshift buckets, compute a curve of galactic density over time. Because foreground galaxies obstruct the images of more distant galaxies, we simulated the theoretical galactic density curve using an average galactic radius. By comparing the galactic density curves of the simulations with that of the survey, we could assess the cosmologies. We applied the test to the expanding-universe cosmology of de Sitter and to a dichotomous cosmology.
Implementation of Monte Carlo Simulations for the Gamma Knife System
Energy Technology Data Exchange (ETDEWEB)
Xiong, W [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Huang, D [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Lee, L [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Feng, J [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Morris, K [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Calugaru, E [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Burman, C [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Li, J [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States); Ma, C-M [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States)
2007-06-15
Currently the Gamma Knife system is accompanied with a treatment planning system, Leksell GammaPlan (LGP) which is a standard, computer-based treatment planning system for Gamma Knife radiosurgery. In LGP, the dose calculation algorithm does not consider the scatter dose contributions and the inhomogeneity effect due to the skull and air cavities. To improve the dose calculation accuracy, Monte Carlo simulations have been implemented for the Gamma Knife planning system. In this work, the 201 Cobalt-60 sources in the Gamma Knife unit are considered to have the same activity. Each Cobalt-60 source is contained in a cylindric stainless steel capsule. The particle phase space information is stored in four beam data files, which are collected in the inner sides of the 4 treatment helmets, after the Cobalt beam passes through the stationary and helmet collimators. Patient geometries are rebuilt from patient CT data. Twenty two Patients are included in the Monte Carlo simulation for this study. The dose is calculated using Monte Carlo in both homogenous and inhomogeneous geometries with identical beam parameters. To investigate the attenuation effect of the skull bone the dose in a 16cm diameter spherical QA phantom is measured with and without a 1.5mm Lead-covering and also simulated using Monte Carlo. The dose ratios with and without the 1.5mm Lead-covering are 89.8% based on measurements and 89.2% according to Monte Carlo for a 18mm-collimator Helmet. For patient geometries, the Monte Carlo results show that although the relative isodose lines remain almost the same with and without inhomogeneity corrections, the difference in the absolute dose is clinically significant. The average inhomogeneity correction is (3.9 {+-} 0.90) % for the 22 patients investigated. These results suggest that the inhomogeneity effect should be considered in the dose calculation for Gamma Knife treatment planning.
A survey of sequential Monte Carlo methods for economics and finance
Creal, D.D.
2009-01-01
This paper serves as an introduction and survey for economists to the field of sequential Monte Carlo methods which are also known as particle filters. Sequential Monte Carlo methods are simulation based algorithms used to compute the high-dimensional and/or complex integrals that arise regularly in applied work. These methods are becoming increasingly popular in economics and finance; from dynamic stochastic general equilibrium models in macro-economics to option pricing. The objective of th...
Markov chain Monte Carlo simulation for Bayesian Hidden Markov Models
Chan, Lay Guat; Ibrahim, Adriana Irawati Nur Binti
2016-10-01
A hidden Markov model (HMM) is a mixture model which has a Markov chain with finite states as its mixing distribution. HMMs have been applied to a variety of fields, such as speech and face recognitions. The main purpose of this study is to investigate the Bayesian approach to HMMs. Using this approach, we can simulate from the parameters' posterior distribution using some Markov chain Monte Carlo (MCMC) sampling methods. HMMs seem to be useful, but there are some limitations. Therefore, by using the Mixture of Dirichlet processes Hidden Markov Model (MDPHMM) based on Yau et. al (2011), we hope to overcome these limitations. We shall conduct a simulation study using MCMC methods to investigate the performance of this model.
CORPORATE VALUATION USING TWO-DIMENSIONAL MONTE CARLO SIMULATION
Directory of Open Access Journals (Sweden)
Toth Reka
2010-12-01
Full Text Available In this paper, we have presented a corporate valuation model. The model combine several valuation methods in order to get more accurate results. To determine the corporate asset value we have used the Gordon-like two-stage asset valuation model based on the calculation of the free cash flow to the firm. We have used the free cash flow to the firm to determine the corporate market value, which was calculated with use of the Black-Scholes option pricing model in frame of the two-dimensional Monte Carlo simulation method. The combined model and the use of the two-dimensional simulation model provides a better opportunity for the corporate value estimation.
Cosmological Markov Chain Monte Carlo simulation with Cmbeasy
Müller, C M
2004-01-01
We introduce a Markov Chain Monte Carlo simulation and data analysis package for the cosmological computation package Cmbeasy. We have taken special care in implementing an adaptive step algorithm for the Markov Chain Monte Carlo in order to improve convergence. Data analysis routines are provided which allow to test models of the Universe against up-to-date measurements of the Cosmic Microwave Background, Supernovae Ia and Large Scale Structure. The observational data is provided with the software for convenient usage. The package is publicly available as part of the Cmbeasy software at www.cmbeasy.org.
Monte Carlo Simulation of Magnetization Behaviour of Co Nanowires
Institute of Scientific and Technical Information of China (English)
ZHONG Ke-Hua; HUANG Zhi-Gao; FENG Qian; JIANG Li-Qin; YANG Yan-Min; CHEN Zhi-Gao
2006-01-01
Based on the Monte Carlo method, we simulate the magnetization curves with various magnetic field orientations for various single Co nanowires at room temperature. The simulated switching field as a function of angle θ between the field and the wire axis is consistent well with the experimental data. Correspondingly, the coercivity as a function of angle θ is presented, which together with the switching field plays an important role on explaining the magnetic reversal mechanism. It is found that the angular dependence of coercivity depends on the diameter of nanowires, and the coercivity and switching field versus θ deviate markedly from the prediction from the classical uniform rotation mode in the chain-of-sphere model. Furthermore, the magnetic reversal configurations display that magnetization reversal in the wires with small diameters is a nucleation-propagation process, and it is similar to the curling spread process in the larger wires.
Monte Carlo simulation of electrical corona discharge in air
Energy Technology Data Exchange (ETDEWEB)
Settaouti, A.; Settaouti, L. [Electrotechnic Department, University of Sciences and Technology, P.O. Box 1505, El-M' naouar, Oran (Algeria)
2011-01-15
Electrical discharges play a key role in technologies; there are many industrial applications where the corona discharge is used. Air as insulator is probably the best compromise solution for many applications. All of this reflects on the great importance of the evaluation of the corona performance characteristics. Numerical simulation of the corona discharge helps to better understand the involved phenomena and optimize the corona devices. This paper is aimed at calculating the corona discharge in negative point-plane air gaps. To describe the non-equilibrium behavior of the electronic avalanches and to simulate the development of corona discharge the method of Monte Carlo has been used. This model provides the spatial-temporal local field and particles charged densities variations as well as the ionization front velocity. (author)
Monte Carlo simulations of landmine detection using neutron backscattering imaging
Energy Technology Data Exchange (ETDEWEB)
Datema, Cor P. E-mail: c.datema@iri.tudelft.nl; Bom, Victor R.; Eijk, Carel W.E. van
2003-11-01
Neutron backscattering is a technique that has successfully been applied to the detection of non-metallic landmines. Most of the effort in this field has concentrated on single detectors that are scanned across the soil. Here, two new approaches are presented in which a two-dimensional image of the hydrogen distribution in the soil is made. The first method uses an array of position-sensitive {sup 3}He-tubes that is placed in close proximity of the soil. The second method is based on coded aperture imaging. Here, thermal neutrons from the soil are projected onto a detector which is typically placed one to several meters above the soil. Both methods use a pulsed D/D neutron source. The Monte Carlo simulation package GEANT 4 was used to investigate the performance of both imaging systems.
Monte Carlo Simulation of Partially Confined Flexible Polymers
Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias
2002-01-01
We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the por
Monte Carlo simulation of magnetic nanostructured thin films
Institute of Scientific and Technical Information of China (English)
Guan Zhi-Qiang; Yutaka Abe; Jiang Dong-Hua; Lin Hai; Yoshitake Yamazakia; Wu Chen-Xu
2004-01-01
@@ Using Monte Carlo simulation, we have compared the magnetic properties between nanostructured thin films and two-dimensional crystalline solids. The dependence of nanostructured properties on the interaction between particles that constitute the nanostructured thin films is also studied. The result shows that the parameters in the interaction potential have an important effect on the properties of nanostructured thin films at the transition temperatures.
Quantum Monte Carlo simulation of topological phase transitions
Yamamoto, Arata; Kimura, Taro
2016-12-01
We study the electron-electron interaction effects on topological phase transitions by the ab initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.
Testing Dependent Correlations with Nonoverlapping Variables: A Monte Carlo Simulation
Silver, N. Clayton; Hittner, James B.; May, Kim
2004-01-01
The authors conducted a Monte Carlo simulation of 4 test statistics or comparing dependent correlations with no variables in common. Empirical Type 1 error rates and power estimates were determined for K. Pearson and L. N. G. Filon's (1898) z, O. J. Dunn and V. A. Clark's (1969) z, J. H. Steiger's (1980) original modification of Dunn and Clark's…
Quantum Monte Carlo simulation of topological phase transitions
Yamamoto, Arata
2016-01-01
We study the electron-electron interaction effects on topological phase transitions by the ab-initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.
Monte Carlo Simulation on Glueball Search at BESⅢ
Institute of Scientific and Technical Information of China (English)
QIN Hu; SHEN Xiao-Yan
2007-01-01
The J/ψ radiative decays are suggested as promising modes for glueball search. A full Monte Carlo simulation of J/ψ→γηη and γηη', based on the design of BESⅢ detector, is performed to study the sensitivity of searching for a possible tensor glueball at BESⅢ.
Monte Carlo Simulation of Partially Confined Flexible Polymers
Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias
2002-01-01
We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the
Whitmore, Alexander Jason
Concentrating solar power systems are currently the predominant solar power technology for generating electricity at the utility scale. The central receiver system, which is a concentrating solar power system, uses a field of mirrors to concentrate solar radiation onto a receiver where a working fluid is heated to drive a turbine. Current central receiver systems operate on a Rankine cycle, which has a large demand for cooling water. This demand for water presents a challenge for the current central receiver systems as the ideal locations for solar power plants have arid climates. An alternative to the current receiver technology is the small particle receiver. The small particle receiver has the potential to produce working fluid temperatures suitable for use in a Brayton cycle which can be more efficient when pressurized to 0.5 MPa. Using a fused quartz window allows solar energy into the receiver while maintaining a pressurized small particle receiver. In this thesis, a detailed numerical investigation for a spectral, three dimensional, cylindrical glass window for a small particle receiver was performed. The window is 1.7 meters in diameter and 0.0254 meters thick. There are three Monte Carlo Ray Trace codes used within this research. The first MCRT code, MIRVAL, was developed by Sandia National Laboratory and modified by a fellow San Diego State University colleague Murat Mecit. This code produces the solar rays on the exterior surface of the window. The second MCRT code was developed by Steve Ruther and Pablo Del Campo. This code models the small particle receiver, which creates the infrared spectral direction flux on the interior surface of the window used in this work. The third MCRT, developed for this work, is used to model radiation heat transfer within the window itself and is coupled to an energy equation solver to produce a temperature distribution. The MCRT program provides a source term to the energy equation. This in turn, produces a new
Radiation shielding design for neutron diffractometers assisted by Monte Carlo methods
Osborn, John C.; Ersez, Tunay; Braoudakis, George
2006-11-01
Monte Carlo simulations may be used to model radiation shielding for neutron diffractometers. The use of the MCNP computer program to assess shielding for a diffractometer is discussed. A comparison is made of shielding requirements for radiation generated by several materials commonly used in neutron optical elements and beam stops, including lithium-6 based absorbers where the Monte Carlo method can model the effects of fast neutrons generated by this material.
Complete Monte Carlo Simulation of Neutron Scattering Experiments
Drosg, M.
2011-12-01
In the far past, it was not possible to accurately correct for the finite geometry and the finite sample size of a neutron scattering set-up. The limited calculation power of the ancient computers as well as the lack of powerful Monte Carlo codes and the limitation in the data base available then prevented a complete simulation of the actual experiment. Using e.g. the Monte Carlo neutron transport code MCNPX [1], neutron scattering experiments can be simulated almost completely with a high degree of precision using a modern PC, which has a computing power that is ten thousand times that of a super computer of the early 1970s. Thus, (better) corrections can also be obtained easily for previous published data provided that these experiments are sufficiently well documented. Better knowledge of reference data (e.g. atomic mass, relativistic correction, and monitor cross sections) further contributes to data improvement. Elastic neutron scattering experiments from liquid samples of the helium isotopes performed around 1970 at LANL happen to be very well documented. Considering that the cryogenic targets are expensive and complicated, it is certainly worthwhile to improve these data by correcting them using this comparatively straightforward method. As two thirds of all differential scattering cross section data of 3He(n,n)3He are connected to the LANL data, it became necessary to correct the dependent data measured in Karlsruhe, Germany, as well. A thorough simulation of both the LANL experiments and the Karlsruhe experiment is presented, starting from the neutron production, followed by the interaction in the air, the interaction with the cryostat structure, and finally the scattering medium itself. In addition, scattering from the hydrogen reference sample was simulated. For the LANL data, the multiple scattering corrections are smaller by a factor of five at least, making this work relevant. Even more important are the corrections to the Karlsruhe data due to the
Energy Technology Data Exchange (ETDEWEB)
Graefe, J.L., E-mail: grafejl@mcmaster.ca [Department of Medical Physics and Applied Radiation Sciences, McMaster University, Hamilton, Ontario, L8S 4K1 (Canada); McNeill, F.E.; Chettle, D.R.; Byun, S.H. [Department of Medical Physics and Applied Radiation Sciences, McMaster University, Hamilton, Ontario, L8S 4K1 (Canada)
2012-06-15
We have extended our previous experimental and Monte-Carlo work on the detection of Gd by in vivo prompt gamma neutron activation analysis to include X ray emission. In this paper we incorporate the characteristic K X ray emission that occurs due to internal conversion from the de-excitation of the {sup 155}Gd(n,{gamma}){sup 156}Gd{sup Asterisk-Operator} and {sup 157}Gd(n,{gamma}){sup 158}Gd{sup Asterisk-Operator} reactions. The experimental Gd K X ray intensities are compared with the Monte-Carlo model and demonstrate excellent agreement. The experiment was consistently higher than simulation by 5%. For the detection system used, the Gd K{sub {alpha}} X rays are about 1.5 times as intense as the most dominant prompt gamma ray from the {sup 157}Gd(n,{gamma}) reaction. The partial elemental cross section for K{sub {alpha}} X ray emission is {approx}1.35 times larger than that of the most dominant prompt gamma ray from neutron capture of {sup 157}Gd alone. The use of the K X rays was found to improve the sensitivity of the proposed system to measure Gd retention after exposure to a Gd-based MRI contrast agent. The detection limit in phantoms was {approx}30% better when the X ray signal was incorporated into the analysis method, reducing the detection limit from 0.89 to 0.64 ppm Gd.
Residual entropy of ice III from Monte Carlo simulation.
Kolafa, Jiří
2016-03-28
We calculated the residual entropy of ice III as a function of the occupation probabilities of hydrogen positions α and β assuming equal energies of all configurations. To do this, a discrete ice model with Bjerrum defect energy penalty and harmonic terms to constrain the occupation probabilities was simulated by the Metropolis Monte Carlo method for a range of temperatures and sizes followed by thermodynamic integration and extrapolation to N = ∞. Similarly as for other ices, the residual entropies are slightly higher than the mean-field (no-loop) approximation. However, the corrections caused by fluctuation of energies of ice samples calculated using molecular models of water are too large for accurate determination of the chemical potential and phase equilibria.
Monte Carlo simulations of systems with complex energy landscapes
Wüst, T.; Landau, D. P.; Gervais, C.; Xu, Y.
2009-04-01
Non-traditional Monte Carlo simulations are a powerful approach to the study of systems with complex energy landscapes. After reviewing several of these specialized algorithms we shall describe the behavior of typical systems including spin glasses, lattice proteins, and models for "real" proteins. In the Edwards-Anderson spin glass it is now possible to produce probability distributions in the canonical ensemble and thermodynamic results of high numerical quality. In the hydrophobic-polar (HP) lattice protein model Wang-Landau sampling with an improved move set (pull-moves) produces results of very high quality. These can be compared with the results of other methods of statistical physics. A more realistic membrane protein model for Glycophorin A is also examined. Wang-Landau sampling allows the study of the dimerization process including an elucidation of the nature of the process.
MONTE CARLO SIMULATION OF MULTIFOCAL STOCHASTIC SCANNING SYSTEM
Directory of Open Access Journals (Sweden)
LIXIN LIU
2014-01-01
Full Text Available Multifocal multiphoton microscopy (MMM has greatly improved the utilization of excitation light and imaging speed due to parallel multiphoton excitation of the samples and simultaneous detection of the signals, which allows it to perform three-dimensional fast fluorescence imaging. Stochastic scanning can provide continuous, uniform and high-speed excitation of the sample, which makes it a suitable scanning scheme for MMM. In this paper, the graphical programming language — LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanners by using white noise signals to control the x and y mirrors independently. Moreover, the stochastic scanning process is simulated by using Monte Carlo method. Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N × N foci array. Therefore, continuous and uniform scanning in the whole field of view is implemented.
Modelling a gamma irradiation process using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Soares, Gabriela A.; Pereira, Marcio T., E-mail: gas@cdtn.br, E-mail: mtp@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2011-07-01
In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)
Kinetic Monte Carlo method applied to nucleic acid hairpin folding.
Sauerwine, Ben; Widom, Michael
2011-12-01
Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure, is advantageous for being able to access behavior at long time scales, even minutes or hours. Transition rates between coarse-grained states depend upon intermediate barriers, which are not directly simulated. We propose an Arrhenius rate model and an intermediate energy model that incorporates the effects of the barrier between simulated states without enlarging the state space itself. Applying our Arrhenius rate model to DNA hairpin folding, we demonstrate improved agreement with experiment compared to the usual kinetic Monte Carlo model. Further improvement results from including rigidity of single-stranded stacking.
Elhatisari, Serdar; Lee, Dean
2014-12-01
We present lattice Monte Carlo calculations of fermion-dimer scattering in the limit of zero-range interactions using the adiabatic projection method. The adiabatic projection method uses a set of initial cluster states and Euclidean time projection to give a systematically improvable description of the low-lying scattering cluster states in a finite volume. We use Lüscher's finite-volume relations to determine the s -wave, p -wave, and d -wave phase shifts. For comparison, we also compute exact lattice results using Lanczos iteration and continuum results using the Skorniakov-Ter-Martirosian equation. For our Monte Carlo calculations we use a new lattice algorithm called impurity lattice Monte Carlo. This algorithm can be viewed as a hybrid technique which incorporates elements of both worldline and auxiliary-field Monte Carlo simulations.
Fermion-Dimer Scattering using Impurity Lattice Monte Carlo and the Adiabatic Projection Method
Elhatisari, Serdar
2014-01-01
We present lattice Monte Carlo calculations of fermion-dimer scattering in the limit of zero-range interactions using the adiabatic projection method. The adiabatic projection method uses a set of initial cluster states and Euclidean time projection to give a systematically improvable description of the low-lying scattering cluster states in a finite volume. We use L\\"uscher's finite-volume relations to determine the $s$-wave, $p$-wave, and $d$-wave phase shifts. For comparison, we also compute exact lattice results using Lanczos iteration and continuum results using the Skorniakov-Ter-Martirosian equation. For our Monte Carlo calculations we use a new lattice algorithm called impurity lattice Monte Carlo. This algorithm can be viewed as a hybrid technique which incorporates elements of both worldline and auxiliary-field Monte Carlo simulations.
Nonequilibrium Candidate Monte Carlo Simulations with Configurational Freezing Schemes.
Giovannelli, Edoardo; Gellini, Cristina; Pietraperzia, Giangaetano; Cardini, Gianni; Chelli, Riccardo
2014-10-14
Nonequilibrium Candidate Monte Carlo simulation [Nilmeier et al., Proc. Natl. Acad. Sci. U.S.A. 2011, 108, E1009-E1018] is a tool devised to design Monte Carlo moves with high acceptance probabilities that connect uncorrelated configurations. Such moves are generated through nonequilibrium driven dynamics, producing candidate configurations accepted with a Monte Carlo-like criterion that preserves the equilibrium distribution. The probability of accepting a candidate configuration as the next sample in the Markov chain basically depends on the work performed on the system during the nonequilibrium trajectory and increases with decreasing such a work. It is thus strategically relevant to find ways of producing nonequilibrium moves with low work, namely moves where dissipation is as low as possible. This is the goal of our methodology, in which we combine Nonequilibrium Candidate Monte Carlo with Configurational Freezing schemes developed by Nicolini et al. (J. Chem. Theory Comput. 2011, 7, 582-593). The idea is to limit the configurational sampling to particles of a well-established region of the simulation sample, namely the region where dissipation occurs, while leaving fixed the other particles. This allows to make the system relaxation faster around the region perturbed by the finite-time switching move and hence to reduce the dissipated work, eventually enhancing the probability of accepting the generated move. Our combined approach enhances significantly configurational sampling, as shown by the case of a bistable dimer immersed in a dense fluid.
Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks
Moraes, Alvaro
2015-01-07
Stochastic reaction networks (SRNs) is a class of continuous-time Markov chains intended to describe, from the kinetic point of view, the time-evolution of chemical systems in which molecules of different chemical species undergo a finite set of reaction channels. This talk is based on articles [4, 5, 6], where we are interested in the following problem: given a SRN, X, defined though its set of reaction channels, and its initial state, x0, estimate E (g(X(T))); that is, the expected value of a scalar observable, g, of the process, X, at a fixed time, T. This problem lead us to define a series of Monte Carlo estimators, M, such that, with high probability can produce values close to the quantity of interest, E (g(X(T))). More specifically, given a user-selected tolerance, TOL, and a small confidence level, η, find an estimator, M, based on approximate sampled paths of X, such that, P (|E (g(X(T))) − M| ≤ TOL) ≥ 1 − η; even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.
Energy Technology Data Exchange (ETDEWEB)
Mangiarotti, A. [Laboratorio de Instrumentacao e Fisica Experimental de Particulas, Coimbra (Portugal); Departamento de Fisica, Faculdade de Ciencias e Tecnologia, Universidade de Coimbra, Coimbra (Portugal); Sona, P., E-mail: pietro.sona@fi.infn.it [Dipartimento di Fisica, Universita degli Studi di Firenze, Polo Scientifico, Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); INFN, Sezione di Firenze, Polo Scientifico, Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Ballestrero, S. [Department of Physics, University of Johannesburg, Johannesburg (South Africa); PH/ADT, CERN, CH-1211, Geneve (Switzerland); Uggerhoj, U.I. [Department of Physics and Astronomy, University of Aarhus, Aarhus (Denmark)
2011-09-15
A computer code for Monte-Carlo simulations in the framework of the GEANT 3 toolkit has been implemented for the description of the discrete bremsstrahlung radiation from high energy electrons crossing thick (semi-infinite) targets. The code is based on the Migdal theory which includes the LPM and dielectric suppression. Validation of the code has been performed by a comparison with the data from the SLAC E-146 experiment. The agreement between simulations and experimental data is generally very good.
Institute of Scientific and Technical Information of China (English)
YU Dingsheng; WU Mingguang; JIAO Shuke
1993-01-01
A program of Monte Carlo simulation of binary copolymerization for E-SBR (emulsion polymn.SB rubber) was made according to the terminal model.The simulation results obtained by this program were in good agreement with those experimental ones.A detail microstructure information of E-SBR molecular chain has been provided.
Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry
Energy Technology Data Exchange (ETDEWEB)
Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Cagnon, Chris H.; McNitt-Gray, Michael F. [Departments of Biomedical Physics and Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024 (United States); Mueller, Jonathon W. [United States Air Force, Keesler Air Force Base, Biloxi, Mississippi 39534 (United States); Cody, Dianna D. [University of Texas M.D. Anderson Cancer Center, Houston, Texas 77030 (United States); DeMarco, John J. [Departments of Biomedical Physics and Radiation Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024 (United States)
2015-02-15
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 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. 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.
The Monte Carlo method in quantum field theory
Morningstar, C
2007-01-01
This series of six lectures is an introduction to using the Monte Carlo method to carry out nonperturbative studies in quantum field theories. Path integrals in quantum field theory are reviewed, and their evaluation by the Monte Carlo method with Markov-chain based importance sampling is presented. Properties of Markov chains are discussed in detail and several proofs are presented, culminating in the fundamental limit theorem for irreducible Markov chains. The example of a real scalar field theory is used to illustrate the Metropolis-Hastings method and to demonstrate the effectiveness of an action-preserving (microcanonical) local updating algorithm in reducing autocorrelations. The goal of these lectures is to provide the beginner with the basic skills needed to start carrying out Monte Carlo studies in quantum field theories, as well as to present the underlying theoretical foundations of the method.
Monte Carlo methods and models in finance and insurance
Korn, Ralf
2010-01-01
Offering a unique balance between applications and calculations, this book incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The book enables readers to find the right algorithm for a desired application and illustrates complicated methods and algorithms with simple applicat
Monte Carlo molecular simulation of phase-coexistence for oil production and processing
Li, Jun
2011-01-01
The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components, the Gibbs-NPT ensemble Monte Carlo method is employed in the simulation while the mole fraction of each component in each phase is modeled as a Leonard-Jones fluid. As the results of Monte Carlo simulations usually contain huge statistical error, the blocking method is used to estimate the variance of the simulation results. Additionally, in order to improve the simulation efficiency, the step sizes of different trial moves is adjusted automatically so that their acceptance probabilities can approach to the preset values.
Introduction to the variational and diffusion Monte Carlo methods
Toulouse, Julien; Umrigar, C J
2015-01-01
We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on the subject, we review in depth the Metropolis-Hastings algorithm used in VMC for sampling the square of an approximate wave function, discussing details important for applications to electronic systems. We also review in detail the more sophisticated DMC algorithm within the fixed-node approximation, introduced to avoid the infamous Fermionic sign problem, which allows one to sample a more accurate approximation to the ground-state wave function. Throughout this review, we discuss the statistical methods used for evaluating expectation values and statistical uncertainties. In particular, we show how to estimate nonlinear functions of expectation values and their statistical uncertainties.
Applications of quantum Monte Carlo methods in condensed systems
Kolorenc, Jindrich
2010-01-01
The quantum Monte Carlo methods represent a powerful and broadly applicable computational tool for finding very accurate solutions of the stationary Schroedinger equation for atoms, molecules, solids and a variety of model systems. The algorithms are intrinsically parallel and are able to take full advantage of the present-day high-performance computing systems. This review article concentrates on the fixed-node/fixed-phase diffusion Monte Carlo method with emphasis on its applications to electronic structure of solids and other extended many-particle systems.
Energy Technology Data Exchange (ETDEWEB)
Gonzalez, Jorge A. Carrazana; Ferrera, Eduardo A. Capote; Gomez, Isis M. Fernandez; Castro, Gloria V. Rodriguez; Ricardo, Niury Martinez, E-mail: cphr@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones (CPHR), La Habana (Cuba)
2013-07-01
This work shows how is established the traceability of the analytical determinations using this calibration method. Highlights the advantages offered by Monte Carlo simulation for the application of corrections by differences in chemical composition, density and height of the samples analyzed. Likewise, the results obtained by the LVRA in two exercises organized by the International Agency for Atomic Energy (IAEA) are presented. In these exercises (an intercomparison and a proficiency test) all reported analytical results were obtained based on calibrations in efficiency by Monte Carlo simulation using the DETEFF program.
Directory of Open Access Journals (Sweden)
José Luiz Ferreira Martins
2011-09-01
. From these data was taken at random samples with, respectively, 10, 15 and 20 elements and were performed simulations by Monte Carlo method. Comparing the results of the sample with 160 elements and the data generated by simulation is observed that good results can be obtained by using Monte Carlo method in estimating productivity of industrial welding. On the other hand in Brazilian construction industry the value of productivity average is normally used as a productivity indicator and is based on historical data from other projects collected and measured only after project completion, which is a limitation. This article presents a tool for evaluation of the implementation in real time, enabling adjustments in estimates and monitoring productivity during the project. Similarly, in biddings, budgets and schedule estimations, the use of this tool could enable the adoption of other estimative different from of the average productivity, which is commonly used and as an alternative are suggested three criteria: optimistic, average and pessimistic productivity.
Institute of Scientific and Technical Information of China (English)
H.M. Li; Z.J. Ding
2005-01-01
A new parallel Monte Carlo simulation method of secondary electron (SE) and backscattered electron images (BSE) of scanning electron microscopy (SEM) for a complex geometric structure has been developed. This paper describes briefly the simulation method and the modification to the conventional sampling method for the step length. Example simulation results have been obtained for several artificial structures.
基于蒙特卡洛法的弹着点散布仿真%Simulation of Impact Position Based on Monte-Carlo Method
Institute of Scientific and Technical Information of China (English)
路航; 石全; 胡起伟; 朱战飞
2011-01-01
Simulation of impact position is an important step of the damage simulation. The impact position model is set up by Monte-Carlo method based on analyzing the components and calculating methods of firing error, and the visual simulation of impact position which is codetermined by concentrated fire, optimum width fire and three-distance fire is realized. The results accord with tactics of artillery, therefore the model can be used in damage simulatioa The case of artillery battalion to position of towed gun company is analyzed, the results of which shows that it is facility, credible and general to calculate damage probability of any point targets using the impact model.%弹着点散布仿真是对敌火力打击目标毁伤仿真的重要环节.在分析地面炮兵射击误差构成与计算方法的基础上,研究建立了炮兵射击的弹着点散布蒙特卡洛(Monte-Carlo)仿真模型,实现了对集火射向、适宽射向、三距离射击等多种火力打击方式共同作用下的弹着点散布的可视化仿真,仿真结果符合相关战术数据,为目标毁伤仿真研究提供了模型支持.以炮兵营对牵引炮兵连阵地射击为例进行了算例分析,结果表明,采用弹着点散布的蒙特卡洛仿真模型计算对任意形状点目标群的毁伤效能方便可靠且通用性强.
Monte Carlo Simulation of Argon in Nano-Space
Institute of Scientific and Technical Information of China (English)
CHEN Min; YANG Chun; GUO Zeng-Yuan
2000-01-01
Monte Carlo simulations are performed to investigate the thermodynamic properties of argon confined in nano-scale cubes constructed of graphite walls. A remarkable depression of the system pressures is observed. The simulations reveal that the length-scale of the cube, the magnitude of the interaction between the fluid and the graphite wall and the density of the fluid exhibit reasonable effects on the thermodynamic property shifts of the luid.
Assessing Excel VBA Suitability for Monte Carlo Simulation
2015-01-01
Monte Carlo (MC) simulation includes a wide range of stochastic techniques used to quantitatively evaluate the behavior of complex systems or processes. Microsoft Excel spreadsheets with Visual Basic for Applications (VBA) software is, arguably, the most commonly employed general purpose tool for MC simulation. Despite the popularity of the Excel in many industries and educational institutions, it has been repeatedly criticized for its flaws and often described as questionable, if not complet...
Quantum Monte Carlo diagonalization method as a variational calculation
Energy Technology Data Exchange (ETDEWEB)
Mizusaki, Takahiro; Otsuka, Takaharu [Tokyo Univ. (Japan). Dept. of Physics; Honma, Michio
1997-05-01
A stochastic method for performing large-scale shell model calculations is presented, which utilizes the auxiliary field Monte Carlo technique and diagonalization method. This method overcomes the limitation of the conventional shell model diagonalization and can extremely widen the feasibility of shell model calculations with realistic interactions for spectroscopic study of nuclear structure. (author)
Auxiliary-field quantum Monte Carlo methods in nuclei
Alhassid, Y
2016-01-01
Auxiliary-field quantum Monte Carlo methods enable the calculation of thermal and ground state properties of correlated quantum many-body systems in model spaces that are many orders of magnitude larger than those that can be treated by conventional diagonalization methods. We review recent developments and applications of these methods in nuclei using the framework of the configuration-interaction shell model.
Monte Carlo simulation of quantum Zeno effect in the brain
Georgiev, Danko
2014-01-01
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 ...
Monte Carlo Simulations of Neutron Oil well Logging Tools
Azcurra, M
2002-01-01
Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented.The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively.The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation.The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B.Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation.In particular, the ratio C/O was analyzed as an indicator of oil saturation.Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition
Energy Technology Data Exchange (ETDEWEB)
Ono, Kiminori, E-mail: kiminori@tranpo.che.tohoku.ac.jp; Matsukawa, Yoshiya; Saito, Yasuhiro; Matsushita, Yohsuke; Aoki, Hideyuki [Tohoku University, Department of Chemical Engineering, Graduate School of Engineering (Japan); Era, Koki; Aoki, Takayuki; Yamaguchi, Togo [ASAHI CARBON CO., LTD. (Japan)
2015-06-15
This study presents the validity and ability of an aggregate mean free path cluster–cluster aggregation (AMP-CCA) model, which is a direct Monte Carlo simulation, to predict the aggregate morphology with diameters form about 15–200 nm by comparing the particle size distributions (PSDs) with the results of the previous stochastic approach. The PSDs calculated by the AMP-CCA model with the calculated aggregate as a coalesced spherical particle are in reasonable agreement with the results of the previous stochastic model regardless of the initial number concentration of particles. The shape analysis using two methods, perimeter fractal dimension and the shape categories, has demonstrated that the aggregate structures become complex with increasing the initial number concentration of particles. The AMP-CCA model provides a useful tool to calculate the aggregate morphology and PSD with reasonable accuracy.
Observations on variational and projector Monte Carlo methods.
Umrigar, C J
2015-10-28
Variational Monte Carlo and various projector Monte Carlo (PMC) methods are presented in a unified manner. Similarities and differences between the methods and choices made in designing the methods are discussed. Both methods where the Monte Carlo walk is performed in a discrete space and methods where it is performed in a continuous space are considered. It is pointed out that the usual prescription for importance sampling may not be advantageous depending on the particular quantum Monte Carlo method used and the observables of interest, so alternate prescriptions are presented. The nature of the sign problem is discussed for various versions of PMC methods. A prescription for an exact PMC method in real space, i.e., a method that does not make a fixed-node or similar approximation and does not have a finite basis error, is presented. This method is likely to be practical for systems with a small number of electrons. Approximate PMC methods that are applicable to larger systems and go beyond the fixed-node approximation are also discussed.
Energy Technology Data Exchange (ETDEWEB)
Winnischofer, Herbert; Araujo, Marcio Peres de; Dias Junior, Lauro Camargo; Novo, Joao Batista Marques [Universidade Federal do Parana (UFPR), Curitiba, PR (Brazil)
2010-07-01
A software based in the Monte Carlo method have been developed aiming the teaching of important cases of mechanisms found in luminescence and in excited states decay kinetics, including: multiple decays, consecutive decays and coupled systems decays. The Monte Carlo Method allows the student to easily simulate and visualize the luminescence mechanisms, focusing on the probabilities of the related steps. The software CINESTEX was written for FreeBASIC compiler; it assumes first-order kinetics and any number of excited states, where the pathways are allowed with probabilities assigned by the user. (author)
Kim, Kyeong-Hyeon; Kim, Dong-Su; Kim, Tae-Ho; Kang, Seong-Hee; Cho, Min-Seok; Suh, Tae Suk
2015-11-01
The phantom-alignment error is one of the factors affecting delivery quality assurance (QA) accuracy in intensity-modulated radiation therapy (IMRT). Accordingly, a possibility of inadequate use of spatial information in gamma evaluation may exist for patient-specific IMRT QA. The influence of the phantom-alignment error on gamma evaluation can be demonstrated experimentally by using the gamma passing rate and the gamma value. However, such experimental methods have a limitation regarding the intrinsic verification of the influence of the phantom set-up error because experimentally measuring the phantom-alignment error accurately is impossible. To overcome this limitation, we aimed to verify the effect of the phantom set-up error within the gamma evaluation formula by using a Monte Carlo simulation. Artificial phantom set-up errors were simulated, and the concept of the true point (TP) was used to represent the actual coordinates of the measurement point for the mathematical modeling of these effects on the gamma. Using dose distributions acquired from the Monte Carlo simulation, performed gamma evaluations in 2D and 3D. The results of the gamma evaluations and the dose difference at the TP were classified to verify the degrees of dose reflection at the TP. The 2D and the 3D gamma errors were defined by comparing gamma values between the case of the imposed phantom set-up error and the TP in order to investigate the effect of the set-up error on the gamma value. According to the results for gamma errors, the 3D gamma evaluation reflected the dose at the TP better than the 2D one. Moreover, the gamma passing rates were higher for 3D than for 2D, as is widely known. Thus, the 3D gamma evaluation can increase the precision of patient-specific IMRT QA by applying stringent acceptance criteria and setting a reasonable action level for the 3D gamma passing rate.
Interacting multiagent systems kinetic equations and Monte Carlo methods
Pareschi, Lorenzo
2014-01-01
The description of emerging collective phenomena and self-organization in systems composed of large numbers of individuals has gained increasing interest from various research communities in biology, ecology, robotics and control theory, as well as sociology and economics. Applied mathematics is concerned with the construction, analysis and interpretation of mathematical models that can shed light on significant problems of the natural sciences as well as our daily lives. To this set of problems belongs the description of the collective behaviours of complex systems composed by a large enough number of individuals. Examples of such systems are interacting agents in a financial market, potential voters during political elections, or groups of animals with a tendency to flock or herd. Among other possible approaches, this book provides a step-by-step introduction to the mathematical modelling based on a mesoscopic description and the construction of efficient simulation algorithms by Monte Carlo methods. The ar...
Optimal mesh hierarchies in Multilevel Monte Carlo methods
Von Schwerin, Erik
2016-01-08
I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods
Bijmolt, T.H.A.; Wedel, M.
1996-01-01
We compare three alternative Maximum Likelihood Multidimensional Scaling methods for pairwise dissimilarity ratings, namely MULTISCALE, MAXSCAL, and PROSCAL in a Monte Carlo study.The three MLMDS methods recover the true con gurations very well.The recovery of the true dimensionality depends on the
The Metropolis Monte Carlo Method in Statistical Physics
Landau, David P.
2003-11-01
A brief overview is given of some of the advances in statistical physics that have been made using the Metropolis Monte Carlo method. By complementing theory and experiment, these have increased our understanding of phase transitions and other phenomena in condensed matter systems. A brief description of a new method, commonly known as "Wang-Landau sampling," will also be presented.
Monte Carlo simulations of dense gas flow and heat transfer in micro- and nano-channels
Institute of Scientific and Technical Information of China (English)
WANG Moran; LI Zhixin
2005-01-01
The dense gas flow and heat transfer in micro- and nano-channels was simulated using the Enskog simulation Monte Carlo (ESMC) method. The results were compared with those from the direct simulation Monte Carlo (DSMC) method and from the consistent Boltzmann algorithm (CBA). The dense gas flow and heat transfer characteristics were thus analyzed. The results showed that when the gas density was large enough, the finite gas density effect on the flow and heat transfer cannot be ignored, which decreased the skin friction coefficient and changed the heat transfer characteristics on the channel wall surfaces.
Dynamic Monte Carlo simulation of chain growth polymerization and its concentration effect
Institute of Scientific and Technical Information of China (English)
LüWenqi
2005-01-01
[1]He, J., Zhang, H., Chen, J. et al., Monte Carlo simulation of kinetics and chain length distributions in living free-radical polymerization, Macromolecules, 1997, 30: 8010-8018.[2]Li, L., He, J., Yang, Y., Monte Carlo simulation on living radical polymerization with RAFT process, Chem. J. Chinese Univ. (in Chinese), 2000, 21(7): 1146-1148.[3]Ling, J., Shen, Z., Chen W., Algorithm and application of Monte Carlo simulation for multi-dispersive copolymerization system, Science in China, Series B, 2002, 45(3): 243-250.[4]Butte, A., Storti, G., Morbidelli, M., Evaluation of the chain length distribution in free-radical polymerization, 1. Bulk polymerization, Macromol. Theory Simul., 2002, 11: 22-36.[5]Smith, G. B., Russell, G. T., Heuts, J. P. A., Termination in dilute-solution free-radical polymerization: A composite model, Macromol. Theory Simul., 2003, 12: 299-314.[6]Zetterlund, P. B., Yamazoe, H., Yamada, B., Free radical bulk po- lymerization of styrene: Simulation of molecular weight distribu- tions to high conversion using experimentally obtained rate coef- ficients, Macromol. Theory Simul., 2003, 12: 379-385.[7]Binder, K., Paul, W., Monte Carlo simulations of polymer dy- namics: Recent advances, J. Polym. Sci., Polym. Phys. Ed., 1997, 35(1): 1-31.[8]Rouault, Y., Milchev, A., Monte Carlo study of living polymers with the bond-fluctuation method, Phys. Rev. E, 1995, 51(6): 5905-5910.[9]Jo, W. H., Lee, J. W., Lee, M. S. et al., Effect of interchange reactions on the molecular weight distribution of poly(ethylene terephthalate): A Monte Carlo simulation, J. Polym. Sci., Polym. Phys. Ed., 1996, 34: 725-729.[10]Jang, S. S., Ha, W. S., Jo, W. H. et al., Monte Carlo simulation of copolymerization by ester interchange reaction in miscible polyester blends, J. Polym. Sci., Polym. Phys. Ed., 1998, 36: 1637-1645.[11]Lee, Y. U., Jang, S. S., Jo, W. H., Off-lattice Monte Carlo simulation of hyperbranched polymers, 1. Polycondensation of AB2 type monomers, Macromol. Theory
Stabilization effect of fission source in coupled Monte Carlo simulations
Directory of Open Access Journals (Sweden)
Börge Olsen
2017-08-01
Full Text Available A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.
Conceptual design and Monte Carlo simulations of the AGATA array
Energy Technology Data Exchange (ETDEWEB)
Farnea, E., E-mail: Enrico.Farnea@pd.infn.i [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, Padova (Italy); Recchia, F.; Bazzacco, D. [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, Padova (Italy); Kroell, Th. [Institut fuer Kernphysik, Technische Universitaet Darmstadt, Darmstadt (Germany); Podolyak, Zs. [Department of Physics, University of Surrey, Guildford (United Kingdom); Quintana, B. [Departamento de Fisica Fundamental, Universidad de Salamanca, Salamanca (Spain); Gadea, A. [Instituto de Fisica Corpuscular, CSIC-Universidad de Valencia, Valencia (Spain)
2010-09-21
The aim of the Advanced GAmma Tracking Array (AGATA) project is the construction of an array based on the novel concepts of pulse shape analysis and {gamma}-ray tracking with highly segmented Ge semiconductor detectors. The conceptual design of AGATA and its performance evaluation under different experimental conditions has required the development of a suitable Monte Carlo code. In this article, the description of the code as well as simulation results relevant for AGATA, are presented.
An Introduction to Monte Carlo Simulation of Statistical physics Problem
Murthy, K. P. N.
2001-01-01
A brief introduction to the technique of Monte Carlo simulations in statistical physics is presented. The topics covered include statistical ensembles random and pseudo random numbers, random sampling techniques, importance sampling, Markov chain, Metropolis algorithm, continuous phase transition, statistical errors from correlated and uncorrelated data, finite size scaling, n-fold way, critical slowing down, blocking technique,percolation, cluster algorithms, cluster counting, histogram tech...
Two Dimensional Nucleation Process by Monte Carlo Simulation
T., Irisawa; K., Matsumoto; Y., Arima; T., Kan; Computer Center, Gakushuin University; Department of Physics, Gakushuin University
1997-01-01
Two dimensional nucleation process on substrate is investigated by Monte Carlo simulation, and the critical nucleus size and its waiting time are measured with a high accuracy. In order to measure the critical nucleus with a high accuracy, we calculate the attachment and the detachment rate to the nucleus directly, and define the critical nucleus size when both rate are equal. Using the kinematical nucleation theory by Nishioka, it is found that, our obtained kinematical two dimensional criti...
Calculating coherent pair production with Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Bottcher, C.; Strayer, M.R.
1989-01-01
We discuss calculations of the coherent electromagnetic pair production in ultra-relativistic hadron collisions. This type of production, in lowest order, is obtained from three diagrams which contain two virtual photons. We discuss simple Monte Carlo methods for evaluating these classes of diagrams without recourse to involved algebraic reduction schemes. 19 refs., 11 figs.
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...
Bayesian Monte Carlo Method for Nuclear Data Evaluation
Energy Technology Data Exchange (ETDEWEB)
Koning, A.J., E-mail: koning@nrg.eu
2015-01-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using TALYS. The result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by an experiment based weight.
Monte Carlo method for magnetic impurities in metals
Hirsch, J. E.; Fye, R. M.
1986-01-01
The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.
An Overview of the Monte Carlo Methods, Codes, & Applications Group
Energy Technology Data Exchange (ETDEWEB)
Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-08-30
This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.
Direct determination of liquid phase coexistence by Monte Carlo simulations.
Zweistra, Henk J A; Besseling, N A M
2006-07-01
A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase. The compositions of these boxes yield coexisting points on the binodal. However, since the overall composition is fixed, at least one of the boxes will contain an interface. We show that this does not affect the results, provided that the interface has no net curvature. We coin the name "Helmholtz-ensemble method," because the method is related to the well-known Gibbs-ensemble method, but the volume of the boxes is constant. Since the box volumes are constant, we expect that this method will be particularly useful for lattice models. The accuracy of the Helmholtz-ensemble method is benchmarked against known coexistence curves of the three-dimensional Ising model with excellent results.
In silico radiobiology: Have we reached the limit of Monte Carlo simulations?
Gholami, Y.; Toghyani, M.; Champion, C.; Kuncic, Z.
2014-03-01
Monte Carlo radiation transport models are increasingly being used to simulate biological damage. However, such radiation biophysics simulations require realistic molecular models for water, whereas existing Monte Carlo models are limited by their use of atomic cross-sections, which become inadequate for accurately modelling interactions of the very low-energy electrons that are responsible for biological damage. In this study, we borrow theoretical methods commonly employed in molecular dynamics simulations to model the molecular wavefunction of the water molecule as the first step towards deriving new molecular cross-sections. We calculate electron charge distributions for molecular water and find non-negligible differences between the vapor and liquid phases that can be attributed to intermolecular bonding in the condensed phase. We propose that a hybrid Monte Carlo - Molecular Dynamics (MC-MD) approach to modelling radiation biophysics will provide new insights into radiation damage and new opportunities to develop targeted molecular therapy strategies.
Directory of Open Access Journals (Sweden)
P.Orea
2003-01-01
Full Text Available We have performed Monte Carlo simulations in the canonical ensemble of a hard-sphere fluid adsorbed in microporous media. The pressure of the adsorbed fluid is calculated by using an original procedure that includes the calculations of the pressure tensor components during the simulation. In order to confirm the equivalence of bulk and adsorbed fluid pressures, we have exploited the mechanical condition of equilibrium and performed additional canonical Monte Carlo simulations in a super system "bulk fluid + adsorbed fluid". When the configuration of a model porous media permits each of its particles to be in contact with adsorbed fluid particles, we found that these pressures are equal. Unlike the grand canonical Monte Carlo method, the proposed calculation approach can be used efficiently to obtain adsorption isotherms over a wide range of fluid densities and porosities of adsorbent.
Monte Carlo Simulations of Arterial Imaging with Optical Coherence Tomography
Energy Technology Data Exchange (ETDEWEB)
Amendt, P.; Estabrook, K.; Everett, M.; London, R.A.; Maitland, D.; Zimmerman, G.; Colston, B.; da Silva, L.; Sathyam, U.
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 spherical 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.
A separable shadow Hamiltonian hybrid Monte Carlo method.
Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D; Izaguirre, Jesús A
2009-11-07
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
Monte Carlo methods for multidimensional integration for European option pricing
Todorov, V.; Dimov, I. T.
2016-10-01
In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.
Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran
2017-01-01
Analytical expressions for sampling the scattering angle from a phase function in Monte Carlo simulations of light propagation are available only for a limited number of phase functions. Consequently, numerical sampling methods based on tabulated values are often required instead. By using Monte Carlo simulated reflectance, we compare two existing and propose an improved numerical sampling method and show that both the number of the tabulated values and the numerical sampling method significantly influence the accuracy of the simulated reflectance. The provided results and guidelines should serve as a good starting point for conducting computationally efficient Monte Carlo simulations with numerical phase function sampling. PMID:28663872
Sampling uncertainty evaluation for data acquisition board based on Monte Carlo method
Ge, Leyi; Wang, Zhongyu
2008-10-01
Evaluating the data acquisition board sampling uncertainty is a difficult problem in the field of signal sampling. This paper analyzes the sources of dada acquisition board sampling uncertainty in the first, then introduces a simulation theory of dada acquisition board sampling uncertainty evaluation based on Monte Carlo method and puts forward a relation model of sampling uncertainty results, sampling numbers and simulation times. In the case of different sample numbers and different signal scopes, the author establishes a random sampling uncertainty evaluation program of a PCI-6024E data acquisition board to execute the simulation. The results of the proposed Monte Carlo simulation method are in a good agreement with the GUM ones, and the validities of Monte Carlo method are represented.
Estimation of beryllium ground state energy by Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)
2015-05-15
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
Monte Carlo Simulation for LINAC Standoff Interrogation of Nuclear Material
Energy Technology Data Exchange (ETDEWEB)
Clarke, Shaun D [ORNL; Flaska, Marek [ORNL; Miller, Thomas Martin [ORNL; Protopopescu, Vladimir A [ORNL; Pozzi, Sara A [ORNL
2007-06-01
The development of new techniques for the interrogation of shielded nuclear materials relies on the use of Monte Carlo codes to accurately simulate the entire system, including the interrogation source, the fissile target and the detection environment. The objective of this modeling effort is to develop analysis tools and methods-based on a relevant scenario-which may be applied to the design of future systems for active interrogation at a standoff. For the specific scenario considered here, the analysis will focus on providing the information needed to determine the type and optimum position of the detectors. This report describes the results of simulations for a detection system employing gamma rays to interrogate fissile and nonfissile targets. The simulations were performed using specialized versions of the codes MCNPX and MCNP-PoliMi. Both prompt neutron and gamma ray and delayed neutron fluxes have been mapped in three dimensions. The time dependence of the prompt neutrons in the system has also been characterized For this particular scenario, the flux maps generated with the Monte Carlo model indicate that the detectors should be placed approximately 50 cm behind the exit of the accelerator, 40 cm away from the vehicle, and 150 cm above the ground. This position minimizes the number of neutrons coming from the accelerator structure and also receives the maximum flux of prompt neutrons coming from the source. The lead shielding around the accelerator minimizes the gamma-ray background from the accelerator in this area. The number of delayed neutrons emitted from the target is approximately seven orders of magnitude less than the prompt neutrons emitted from the system. Therefore, in order to possibly detect the delayed neutrons, the detectors should be active only after all prompt neutrons have scattered out of the system. Preliminary results have shown this time to be greater than 5 ?s after the accelerator pulse. This type of system is illustrative of a
Directory of Open Access Journals (Sweden)
Yun Hsing Cheung
2012-12-01
Full Text Available The three main Value at Risk (VaR methodologies are historical, parametric and Monte Carlo Simulation.Cheung & Powell (2012, using a step-by-step teaching study, showed how a nonparametric historical VaRmodel could be constructed using Excel, thus benefitting teachers and researchers by providing them with areadily useable teaching study and an inexpensive and flexible VaR modelling option. This article extends thatwork by demonstrating how parametric and Monte Carlo Simulation VaR models can also be constructed inExcel, thus providing a total Excel modelling package encompassing all three VaR methods.
Sona, P; Mangiarotti, A; Uggerhoj, U I
2011-01-01
A computer code for Monte-Carlo simulations in the framework of the GEANT 3 toolkit has been implemented for the description of the discrete bremsstrahlung radiation from high energy electrons crossing thick (semi-infinite) targets. The code is based on the Migdal theory which includes the LPM and dielectric suppression. Validation of the code has been performed by a comparison with the data from the SLAC E-146 experiment. The agreement between simulations and experimental data is generally very good. (C) 2011 Elsevier B.V. All rights reserved.
Continuous Time Quantum Monte Carlo simulation of Kondo shuttling
Zhang, Peng; Assaad, Fakher; Jarrell, Mark
2010-03-01
The Kondo shuttling problem is investigated by using the Continuous Time Quantum Monte Carlo method in both the anti-adiabatic limit φTK and the intermediate regime φ˜TK, where φ is the phonon modulation frequency and TK is the Kondo temperature. We investigate the potential emergence of Kondo effect or Kondo breakdown as a function of the phonon modulation frequency and electron-phonon coupling. This research is supported by grant OISE-0952300.
Vexler, Albert; Kim, Young Min; Yu, Jihnhee; Lazar, Nicole A; Hutson, Aland
2014-12-01
Various exact tests for statistical inference are available for powerful and accurate decision rules provided that corresponding critical values are tabulated or evaluated via Monte Carlo methods. This article introduces a novel hybrid method for computing p-values of exact tests by combining Monte Carlo simulations and statistical tables generated a priori. To use the data from Monte Carlo generations and tabulated critical values jointly, we employ kernel density estimation within Bayesian-type procedures. The p-values are linked to the posterior means of quantiles. In this framework, we present relevant information from the Monte Carlo experiments via likelihood-type functions, whereas tabulated critical values are used to reflect prior distributions. The local maximum likelihood technique is employed to compute functional forms of prior distributions from statistical tables. Empirical likelihood functions are proposed to replace parametric likelihood functions within the structure of the posterior mean calculations to provide a Bayesian-type procedure with a distribution-free set of assumptions. We derive the asymptotic properties of the proposed nonparametric posterior means of quantiles process. Using the theoretical propositions, we calculate the minimum number of needed Monte Carlo resamples for desired level of accuracy on the basis of distances between actual data characteristics (e.g. sample sizes) and characteristics of data used to present corresponding critical values in a table. The proposed approach makes practical applications of exact tests simple and rapid. Implementations of the proposed technique are easily carried out via the recently developed STATA and R statistical packages.
Monte Carlo simulation of proton track structure in biological matter
Quinto, Michele A.; Monti, Juan M.; Weck, Philippe F.; Fojón, Omar A.; Hanssen, Jocelyn; Rivarola, Roberto D.; Senot, Philippe; Champion, Christophe
2017-05-01
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 - where the main collisional processes are described by means of an extensive set of ab initio differential and total cross sections. Contribution to the Topical Issue "Many Particle Spectroscopy of Atoms, Molecules, Clusters and Surfaces", edited by A.N. Grum-Grzhimailo, E.V. Gryzlova, Yu V. Popov, and A.V. Solov'yov.
A Monte Carlo algorithm for simulating fermions on Lefschetz thimbles
Alexandru, Andrei; Bedaque, Paulo
2016-01-01
A possible solution of the notorious sign problem preventing direct Monte Carlo calculations for systems with non-zero chemical potential is to deform the integration region in the complex plane to a Lefschetz thimble. We investigate this approach for a simple fermionic model. We introduce an easy to implement Monte Carlo algorithm to sample the dominant thimble. Our algorithm relies only on the integration of the gradient flow in the numerically stable direction, which gives it a distinct advantage over the other proposed algorithms. We demonstrate the stability and efficiency of the algorithm by applying it to an exactly solvable fermionic model and compare our results with the analytical ones. We report a very good agreement for a certain region in the parameter space where the dominant contribution comes from a single thimble, including a region where standard methods suffer from a severe sign problem. However, we find that there are also regions in the parameter space where the contribution from multiple...
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2015-01-01
For non-linear systems the estimation of fatigue damage under stochastic loadings can be rather time-consuming. Usually Monte Carlo simulation (MCS) is applied, but the coefficient-of-variation (COV) can be large if only a small set of simulations can be done due to otherwise excessive CPU time. ...... the COV. For a specific example dealing with stresses in a tendon in a tension leg platform the COV is thereby reduced by a factor of three....
Monte Carlo Simulation of HERD Calorimeter
Xu, M; Dong, Y W; Lu, J G; Quan, Z; Wang, L; Wang, Z G; Wu, B B; Zhang, S N
2014-01-01
The High Energy cosmic-Radiation Detection (HERD) facility onboard China's Space Station is planned for operation starting around 2020 for about 10 years. It is designed as a next generation space facility focused on indirect dark matter search, precise cosmic ray spectrum and composition measurements up to the knee energy, and high energy gamma-ray monitoring and survey. The calorimeter plays an essential role in the main scientific objectives of HERD. A 3-D cubic calorimeter filled with high granularity crystals as active material is a very promising choice for the calorimeter. HERD is mainly composed of a 3-D calorimeter (CALO) surrounded by silicon trackers (TK) from all five sides except the bottom. CALO is made of 9261 cubes of LYSO crystals, corresponding to about 55 radiation lengths and 3 nuclear interaction lengths, respectively. Here the simulation results of the performance of CALO with GEANT4 and FLUKA are presented: 1) the total absorption CALO and its absorption depth for precise energy measure...
Ainscow, E K; Brand, M D
1998-09-21
The errors associated with experimental application of metabolic control analysis are difficult to assess. In this paper, we give examples where Monte-Carlo simulations of published experimental data are used in error analysis. Data was simulated according to the mean and error obtained from experimental measurements and the simulated data was used to calculate control coefficients. Repeating the simulation 500 times allowed an estimate to be made of the error implicit in the calculated control coefficients. In the first example, state 4 respiration of isolated mitochondria, Monte-Carlo simulations based on the system elasticities were performed. The simulations gave error estimates similar to the values reported within the original paper and those derived from a sensitivity analysis of the elasticities. This demonstrated the validity of the method. In the second example, state 3 respiration of isolated mitochondria, Monte-Carlo simulations were based on measurements of intermediates and fluxes. A key feature of this simulation was that the distribution of the simulated control coefficients did not follow a normal distribution, despite simulation of the original data being based on normal distributions. Consequently, the error calculated using simulation was greater and more realistic than the error calculated directly by averaging the original results. The Monte-Carlo simulations are also demonstrated to be useful in experimental design. The individual data points that should be repeated in order to reduce the error in the control coefficients can be highlighted.
MULTILEVEL MONTE CARLO (MLMC) SIMULATIONS: PERFORMANCE RESULTS FOR SPE10 (XY SLICES)
Energy Technology Data Exchange (ETDEWEB)
Kalchev, Delyan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-02-26
In this report we first describe a generic multilevel Monte Carlo method and then illustrate its superior performance over a traditional single-level Monte Carlo method for second order elliptic PDEs corresponding to two-dimensional layers in (x, y)-direction of the Tenth SPE Comparative Solution project (SPE 10) which gives high-contrast permeability coefficients. The SPE10 data set is used as a coarse level in the Monte Carlo method and the respective permeability coefficient k (provided in the SPE10 dataset) is used as a mean in the simulation. The actual coefficients are drawn based on a KL-expansion assuming that the log-mean is perturbed by a log-normal distributed samples.
Energy-Driven Kinetic Monte Carlo Method and Its Application in Fullerene Coalescence.
Ding, Feng; Yakobson, Boris I
2014-09-04
Mimicking the conventional barrier-based kinetic Monte Carlo simulation, an energy-driven kinetic Monte Carlo (EDKMC) method was developed to study the structural transformation of carbon nanomaterials. The new method is many orders magnitude faster than standard molecular dynamics or Monte Marlo (MC) simulations and thus allows us to explore rare events within a reasonable computational time. As an example, the temperature dependence of fullerene coalescence was studied. The simulation, for the first time, revealed that short capped single-walled carbon nanotubes (SWNTs) appear as low-energy metastable structures during the structural evolution.
Maucec, M.; Rigollet, C.
2004-01-01
The performance of a detection system based on the pulsed fast/thermal neutron analysis technique was assessed using Monte Carlo simulations. The aim was to develop and implement simulation methods, to support and advance the data analysis techniques of the characteristic gamma-ray spectra, potentia
Meaningful timescales from Monte Carlo simulations of particle systems with hard-core interactions
Costa, Liborio I.
2016-12-01
A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
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.
Parallel cluster labeling for large-scale Monte Carlo simulations
Flanigan, M; Flanigan, M; Tamayo, P
1995-01-01
We present an optimized version of a cluster labeling algorithm previously introduced by the authors. This algorithm is well suited for large-scale Monte Carlo simulations of spin models using cluster dynamics on parallel computers with large numbers of processors. The algorithm divides physical space into rectangular cells which are assigned to processors and combines a serial local labeling procedure with a relaxation process across nearest-neighbor processors. By controlling overhead and reducing inter-processor communication this method attains good computational speed-up and efficiency. Large systems of up to 65536 X 65536 spins have been simulated at updating speeds of 11 nanosecs/site (90.7 million spin updates/sec) using state-of-the-art supercomputers. In the second part of the article we use the cluster algorithm to study the relaxation of magnetization and energy on large Ising models using Swendsen-Wang dynamics. We found evidence that exponential and power law factors are present in the relaxatio...
Energy Technology Data Exchange (ETDEWEB)
Garcia, Claudio; Costa, Artur; Bittencourt, Euclides [TRANSPETRO - PETROBRAS Transporte, Rio de Janeiro, RJ (Brazil)
2005-07-01
Due to the growing relevance of safety and environmental protection policies in PETROBRAS and its subsidiaries, as well as official regulatory agencies and population requirements, integrity management of oil and gas pipelines became a priority activity in TRANSPETRO, involving several sectors of the company's Support Management Department. Inspection activities using intelligent PIGs, field correlations and replacement of pipeline segments are known as high cost operations and request complex logistics. Thus, it is imperative the adoption of management tools that optimize the available resources. This study presents Monte Carlo simulation method as an additional tool for evaluation and management of pipeline structural integrity. The method consists in foreseeing future physical conditions of most significant defects found in intelligent PIG In Line Inspections based on a probabilistic approach. Through Monte Carlo simulation, probability functions of failure for each defect are produced, helping managers to decide which repairs should be executed in order to reach the desired or accepted risk level. The case that illustrates this study refers to the reconditioning of ORSOL 14'' (35,56 mm) pipeline. This pipeline was constructed to transfer petroleum from Urucu's production fields to Solimoes port, in Coari, city in Brazilian Amazon Region. The result of this analysis indicated critical points for repair, in addition to the results obtained by the conventional evaluation (deterministic ASME B-31G method). Due to the difficulties to mobilize staff and execute necessary repairs in remote areas like Amazon forest, the probabilistic tool was extremely useful, improving pipeline integrity level and avoiding future additional costs. (author)
Deasy, Joseph O; Wickerhauser, M Victor; Picard, Mathieu
2002-10-01
The Monte Carlo dose calculation method works by simulating individual energetic photons or electrons as they traverse a digital representation of the patient anatomy. However, Monte Carlo results fluctuate until a large number of particles are simulated. We propose wavelet threshold de-noising as a postprocessing step to accelerate convergence of Monte Carlo dose calculations. A sampled rough function (such as Monte Carlo noise) gives wavelet transform coefficients which are more nearly equal in amplitude than those of a sampled smooth function. Wavelet hard-threshold de-noising sets to zero those wavelet coefficients which fall below a threshold; the image is then reconstructed. We implemented the computationally efficient 9,7-biorthogonal filters in the C language. Transform results were averaged over transform origin selections to reduce artifacts. A method for selecting best threshold values is described. The algorithm requires about 336 floating point arithmetic operations per dose grid point. We applied wavelet threshold de-noising to two two-dimensional dose distributions: a dose distribution generated by 10 MeV electrons incident on a water phantom with a step-heterogeneity, and a slice from a lung heterogeneity phantom. Dose distributions were simulated using the Integrated Tiger Series Monte Carlo code. We studied threshold selection, resulting dose image smoothness, and resulting dose image accuracy as a function of the number of source particles. For both phantoms, with a suitable value of the threshold parameter, voxel-to-voxel noise was suppressed with little introduction of bias. The roughness of wavelet de-noised dose distributions (according to a Laplacian metric) was nearly independent of the number of source electrons, though the accuracy of the de-noised dose image improved with increasing numbers of source electrons. We conclude that wavelet shrinkage de-noising is a promising method for effectively accelerating Monte Carlo dose calculations
A Monte Carlo simulation technique to determine the optimal portfolio
Directory of Open Access Journals (Sweden)
Hassan Ghodrati
2014-03-01
Full Text Available During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR, which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.
Monte Carlo simulation of a prototype photodetector used in radiotherapy
Kausch, C; Albers, D; Schmidt, R; Schreiber, B
2000-01-01
The imaging performance of prototype electronic portal imaging devices (EPID) has been investigated. Monte Carlo simulations have been applied to calculate the modulation transfer function (MTF( f )), the noise power spectrum (NPS( f )) and the detective quantum efficiency (DQE( f )) for different new type of EPIDs, which consist of a detector combination of metal or polyethylene (PE), a phosphor layer of Gd sub 2 O sub 2 S and a flat array of photodiodes. The simulated results agree well with measurements. Based on simulated results, possible optimization of these devices is discussed.
Computed radiography simulation using the Monte Carlo code MCNPX
Energy Technology Data Exchange (ETDEWEB)
Correa, S.C.A. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Centro Universitario Estadual da Zona Oeste (CCMAT)/UEZO, Av. Manuel Caldeira de Alvarenga, 1203, Campo Grande, 23070-200, Rio de Janeiro, RJ (Brazil); Souza, E.M. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Silva, A.X., E-mail: ademir@con.ufrj.b [PEN/COPPE-DNC/Poli CT, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Cassiano, D.H. [Instituto de Radioprotecao e Dosimetria/CNEN Av. Salvador Allende, s/n, Recreio, 22780-160, Rio de Janeiro, RJ (Brazil); Lopes, R.T. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil)
2010-09-15
Simulating X-ray images has been of great interest in recent years as it makes possible an analysis of how X-ray images are affected owing to relevant operating parameters. In this paper, a procedure for simulating computed radiographic images using the Monte Carlo code MCNPX is proposed. The sensitivity curve of the BaFBr image plate detector as well as the characteristic noise of a 16-bit computed radiography system were considered during the methodology's development. The results obtained confirm that the proposed procedure for simulating computed radiographic images is satisfactory, as it allows obtaining results comparable with experimental data.
Inclusion of Quantum Confinement Effects in Self-Consistent Monte Carlo Device Simulations
Directory of Open Access Journals (Sweden)
R. W. Kelsall
1998-01-01
Full Text Available The design of Monte Carlo FET simulations is discussed, with specific attention to the methods used to describe quantum confinement effects. A new model is presented, which employs self-consistent coupling of Schrodinger, Poisson and Monte Carlo algorithms, and explicit calculation of the scattering rates between confined and unconfined states. Comparisons between the new model and a standard semi-classical Monte Carlo model are presented for a 0.1 μm gate-length In0.52Al0.48As/In0.53 Ga0.47As/InP MODFET. Whilst the quantum model yields minor corrections in the predicted output characteristics, it is found that these results can be achieved without repeated iterations of the Schrodinger equation.
A unified Monte Carlo interpretation of particle simulations and applications to nonneutral plasmas
Energy Technology Data Exchange (ETDEWEB)
Aydemir, A.Y.
1993-09-01
Using a ``Monte Carlo interpretation`` a particle simulations, a general description of low-noise techniques is developed in terms well-known Monte Carlo variance reduction methods. Some of these techniques then are applied to linear and nonlinear studies of pure electron plasmas in cylindrical geometry, with emphasis on the generation and nonlinear evolution of electron vortices. Long-lived l = 1 and l and l = 2 vortices, and others produced by unstable diocotron modes in hollow profiles, are studies. It is shown that low-noise techniques make it possible to follow the linear evolution and saturation of even the very weakly unstable resonant diocotron modes.
A Monte Carlo simulation to study the effect of surface roughness on the performance of RPC
Energy Technology Data Exchange (ETDEWEB)
Ghosh, Tapasi, E-mail: tapasi03@gmail.com [Variable Energy Cyclotron Centre, 1/AF BidhanNagar, Kolkata 700 064 (India); Chattopadhyay, Subhasis [Variable Energy Cyclotron Centre, 1/AF BidhanNagar, Kolkata 700 064 (India)
2012-01-01
The electric field inside a Resistive Plate Chamber (RPC) is likely to be influenced by the non-uniform inner surfaces of the RPC electrodes. We have studied the effect of this field perturbation on the performance of the RPC by a Monte Carlo method, which simulates the generation of signal from the detector. For the present study, we have analyzed the effect of the field variation on the time resolution and efficiency of a 0.3 mm single-gap timing RPC. Finally the results obtained from the Monte Carlo study are compared with an analytical calculation.
Monte Carlo Simulation of SATs in 2D
Institute of Scientific and Technical Information of China (English)
无
1996-01-01
In this paper we use Monte Carlo simulation method to deal with SATs on a square lattice and a triangular lattice in two dimensions in the T→∞ limit.Besides that,the SAT model has been generalized in the coordination number q→∞ limit.The characteristics of SATs in the two limits q=3 and q→∞ have been qualitatively discussed.The obtained results reveal that the SATs have intermediate behaviors between that of SAWs and RWs.The critical exponents of SATs have intermediate behaviors between that of SAWs and RWs.The critical exponents of SATs are monotonous functions of q.With different q,SATs correspondingly belong to different universality classes.For example,on a hexagonal lattice,SATs and SAWs belong to the same universality class;in the limiting situation q→∞,SATs and RWs belong to the same universality class;when q=4 or q=6,SATs and SAWs or RWs belong to the different universality class.
Monte Carlo simulations of the SANS instrument in Petten
Energy Technology Data Exchange (ETDEWEB)
Uca, O. [European Commission, Joint Research Centre, Institute for Energy, Westerduinweg 3, 1755 LE, Petten (Netherlands)], E-mail: oktay.uca@jrc.nl; Ohms, C. [European Commission, Joint Research Centre, Institute for Energy, Westerduinweg 3, 1755 LE, Petten (Netherlands)], E-mail: carsten.ohms@jrc.nl
2008-11-30
The small-angle neutron-scattering facility at the 45 MW high-flux reactor in Petten, The Netherlands, was constructed in the late 1980s. It has a q-range of 5x10{sup -3} to 0.4 A{sup -1}, operating at a fixed wavelength of 4.75 A, which is realized by six pairs of double pyrolytic graphite monochromators. In this paper, we study the flux gain for the instrument installed at a neutron guide by Monte Carlo simulations using the program packages McStas [L. Lefmann, K. Nielsen, Neutron News 10 (1999) 320; P. Willendrup, E. Farhi and K. Lefmann, Physica B 350 (2004) 735] and Vitess [G. Zsigmond et al., Nucl. Instrum. Methods A 529 (2004) 218; (http://www.hmi.de/projects/ess/vitess/)]. In doing so, the instrument is relocated from its current position to the HB10 radial beam tube, the double monochromator is replaced by a velocity selector and neutron guides are used for transporting the neutrons.
Monte Carlo simulations of the SANS instrument in Petten
Uca, O.; Ohms, C.
2008-11-01
The small-angle neutron-scattering facility at the 45 MW high-flux reactor in Petten, The Netherlands, was constructed in the late 1980s. It has a q-range of 5×10 -3 to 0.4 Å -1, operating at a fixed wavelength of 4.75 Å, which is realized by six pairs of double pyrolytic graphite monochromators. In this paper, we study the flux gain for the instrument installed at a neutron guide by Monte Carlo simulations using the program packages McStas [L. Lefmann, K. Nielsen, Neutron News 10 (1999) 320; P. Willendrup, E. Farhi and K. Lefmann, Physica B 350 (2004) 735] and Vitess [G. Zsigmond et al., Nucl. Instrum. Methods A 529 (2004) 218; http://www.hmi.de/projects/ess/vitess/]. In doing so, the instrument is relocated from its current position to the HB10 radial beam tube, the double monochromator is replaced by a velocity selector and neutron guides are used for transporting the neutrons.
Monte Carlo methods for light propagation in biological tissues.
Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine
2015-11-01
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis-Hastings algorithm. The resulting estimating methods are then compared to the so-called Wang-Prahl (or Wang) method. Finally, the formal representation allows to derive a non-linear optimization algorithm close to Levenberg-Marquardt that is used for the estimation of the scattering and absorption coefficients of the tissue from measurements.
Monte Carlo Simulation of Kinesin Movement with a Lattice Model
Institute of Scientific and Technical Information of China (English)
WANG Hong; DOU Shuo-Xing; WANG Peng-Ye
2005-01-01
@@ Kinesin is a processive double-headed molecular motor that moves along a microtubule by taking about 8nm steps. It generally hydrolyzes one ATP molecule for taking each forward step. The processive movement of the kinesin molecular motors is numerically simulated with a lattice model. The motors are considered as Brownian particles and the ATPase processes of both heads are taken into account. The Monte Carlo simulation results agree well with recent experimental observations, especially on the relation of velocity versus ATP and ADP concentrations.
More about Zener drag studies with Monte Carlo simulations
Di Prinzio, Carlos L.; Druetta, Esteban; Nasello, Olga Beatriz
2013-03-01
Grain growth (GG) processes in the presence of second-phase and stationary particles have been widely studied but the results found are inconsistent. We present new GG simulations in two- and three-dimensional (2D and 3D) polycrystalline samples with second phase stationary particles, using the Monte Carlo technique. Simulations using values of particle concentration greater than 15% and particle radii different from 1 or 3 are performed, thus covering a range of particle radii and concentrations not previously studied. It is shown that only the results for 3D samples follow Zener's law.
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A matrix stripping method for the conversion of in-situ gamma ray spectrum, obtained with portable Ge detector, to photon flux energy distribution is proposed. The detector response is fully described by its stripping matrix and full absorption efficiency curve. A charge collection efficiency function is introduced in the simulation to take into account the existence of a transition zone of increasing charge collection after the inactive Ge layer. Good agreement is obtained between simulated and experimental full absorption efficiencies. The characteristic stripping matrix is determined by Monte Carlo simulation for different incident photon energies using the Geant4 toolkit system. The photon flux energy distribution is deduced by stripping the measured spectrum of the partial absorption and cosmic ray events and then applying the full absorption efficiency curve. The stripping method is applied to a measured in-situ spectrum. The value of the absorbed dose rate in air deduced from the corresponding flux energy distribution agrees well with the value measured directly in-situ.
Bayesian Monte Carlo method for nuclear data evaluation
Energy Technology Data Exchange (ETDEWEB)
Koning, A.J. [Nuclear Research and Consultancy Group NRG, P.O. Box 25, ZG Petten (Netherlands)
2015-12-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight. (orig.)
Bayesian Monte Carlo method for nuclear data evaluation
Koning, A. J.
2015-12-01
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight.
On adaptive resampling strategies for sequential Monte Carlo methods
Del Moral, Pierre; Doucet, Arnaud; Jasra, Ajay
2012-01-01
Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for...
Monte Carlo methods in continuous time for lattice Hamiltonians
Huffman, Emilie
2016-01-01
We solve a variety of sign problems for models in lattice field theory using the Hamiltonian formulation, including Yukawa models and simple lattice gauge theories. The solutions emerge naturally in continuous time and use the dual representation for the bosonic fields. These solutions allow us to construct quantum Monte Carlo methods for these problems. The methods could provide an alternative approach to understanding non-perturbative dynamics of some lattice field theories.
Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications
Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne
2014-01-01
The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.
Monte Carlo Radiation Hydrodynamics: Methods, Tests and Application to Supernova Type Ia Ejecta
Noebauer, U M; Kromer, M; Röpke, F K; Hillebrandt, W
2012-01-01
In astrophysical systems, radiation-matter interactions are important in transferring energy and momentum between the radiation field and the surrounding material. This coupling often makes it necessary to consider the role of radiation when modelling the dynamics of astrophysical fluids. During the last few years, there have been rapid developments in the use of Monte Carlo methods for numerical radiative transfer simulations. Here, we present an approach to radiation hydrodynamics that is based on coupling Monte Carlo radiative transfer techniques with finite-volume hydrodynamical methods in an operator-split manner. In particular, we adopt an indivisible packet formalism to discretize the radiation field into an ensemble of Monte Carlo packets and employ volume-based estimators to reconstruct the radiation field characteristics. In this paper the numerical tools of this method are presented and their accuracy is verified in a series of test calculations. Finally, as a practical example, we use our approach...
Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study
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,…
McStas 1.1: a tool for building neutron Monte Carlo simulations
Lefmann, K.; Nielsen, K.; Tennant, A.; Lake, B.
2000-03-01
McStas is a project to develop general tools for the creation of simulations of neutron scattering experiments. In this paper, we briefly introduce McStas and describe a particular application of the program: the Monte Carlo calculation of the resolution function of a standard triple-axis neutron scattering instrument. The method compares well with the analytical calculations of Popovici.
Cluster Monte Carlo methods for the FePt Hamiltonian
Lyberatos, A.; Parker, G. J.
2016-02-01
Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen-Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L10-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium.
Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce.
Pratx, Guillem; Xing, Lei
2011-12-01
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.
On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses.
Koehler, Elizabeth; Brown, Elizabeth; Haneuse, Sebastien J-P A
2009-05-01
Statistical experiments, more commonly referred to as Monte Carlo or simulation studies, are used to study the behavior of statistical methods and measures under controlled situations. Whereas recent computing and methodological advances have permitted increased efficiency in the simulation process, known as variance reduction, such experiments remain limited by their finite nature and hence are subject to uncertainty; when a simulation is run more than once, different results are obtained. However, virtually no emphasis has been placed on reporting the uncertainty, referred to here as Monte Carlo error, associated with simulation results in the published literature, or on justifying the number of replications used. These deserve broader consideration. Here we present a series of simple and practical methods for estimating Monte Carlo error as well as determining the number of replications required to achieve a desired level of accuracy. The issues and methods are demonstrated with two simple examples, one evaluating operating characteristics of the maximum likelihood estimator for the parameters in logistic regression and the other in the context of using the bootstrap to obtain 95% confidence intervals. The results suggest that in many settings, Monte Carlo error may be more substantial than traditionally thought.
Monte Carlo simulation for kinetic chemotaxis model: An application to the traveling population wave
Yasuda, Shugo
2017-02-01
A Monte Carlo simulation of chemotactic bacteria is developed on the basis of the kinetic model and is applied to a one-dimensional traveling population wave in a microchannel. In this simulation, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to calculate the macroscopic transport of the chemical cues in the environment. The simulation method can successfully reproduce the traveling population wave of bacteria that was observed experimentally and reveal the microscopic dynamics of bacterium coupled with the macroscopic transports of the chemical cues and bacteria population density. The results obtained by the Monte Carlo method are also compared with the asymptotic solution derived from the kinetic chemotaxis equation in the continuum limit, where the Knudsen number, which is defined by the ratio of the mean free path of bacterium to the characteristic length of the system, vanishes. The validity of the Monte Carlo method in the asymptotic behaviors for small Knudsen numbers is numerically verified.
Monte Carlo simulation on backward steps of single kinesin molecule
Institute of Scientific and Technical Information of China (English)
Wang Hong; Zhang Yong; Dou Shuo-Xing; Wang Peng-Ye
2008-01-01
Kinesin is a stepping molecular motor travelling along the microtubule. It moves primarily in the plus end direction of the microtubule and occasionally in the minus-end, backward, direction. Recently, the backward steps of kinesin under different loads and temperatures start to attract interests, and the relations among them are revealed. This paper aims to theoretically understand these relations observed in experiments. After introducing a backward pathway into the previous model of the ATPase cycle of kinesin movement, the dependence of the backward movement on the load and the temperature is explored through Monte Carlo simulation. Our results agree well with previous experiments.
Monte-Carlo Simulation on Neutron Instruments at CARR
Institute of Scientific and Technical Information of China (English)
2001-01-01
The design of high resolution neutron powder diffractometer(HRPD) and two cold neutron guides(CNGs) to be built at China advanced research reactor(CARR) are studied by Monte-Carlo simulation technique.The HRPD instrument is desiged to have a minimum resolution of 0.2% and neutron fluence rate of greater than 106 cm-2 ·s-1 at sample position. The resolution curves, neutron fluence rate and effective neutron beam size at sample position are given. Differences in resolutions and intensity between the
Monte Carlo simulation of AB-copolymers with saturating bonds
DEFF Research Database (Denmark)
Chertovich, A.C.; Ivanov, V.A.; Khokhlov, A.R.
2003-01-01
Structural transitions in a single AB-copolymer chain where saturating bonds can be formed between A- and B-units are studied by means of Monte Carlo computer simulations using the bond fluctuation model. Three transitions are found, coil-globule, coil-hairpin and globule-hairpin, depending...... to those of diblock sequences than to the properties of random sequences. The model (although quite rough) is expected to represent some basic features of real RNA molecules, i.e. the formation of secondary structure of RNA due to hydrogen bonding of corresponding bases and stacking interactions...
Monte Carlo Simulation for the MAGIC-II System
Carmona, E; Moralejo, A; Vitale, V; Sobczynska, D; Haffke, M; Bigongiari, C; Otte, N; Cabras, G; De Maria, M; De Sabata, F
2007-01-01
Within the year 2007, MAGIC will be upgraded to a two telescope system at La Palma. Its main goal is to improve the sensitivity in the stereoscopic/coincident operational mode. At the same time it will lower the analysis threshold of the currently running single MAGIC telescope. Results from the Monte Carlo simulations of this system will be discussed. A comparison of the two telescope system with the performance of one single telescope will be shown in terms of sensitivity, angular resolution and energy resolution.
Cluster Monte Carlo simulations of the nematic-isotropic transition
Priezjev, N. V.; Pelcovits, Robert A.
2001-06-01
We report the results of simulations of the three-dimensional Lebwohl-Lasher model of the nematic-isotropic transition using a single cluster Monte Carlo algorithm. The algorithm, first introduced by Kunz and Zumbach to study two-dimensional nematics, is a modification of the Wolff algorithm for spin systems, and greatly reduces critical slowing down. We calculate the free energy in the neighborhood of the transition for systems up to linear size 70. We find a double well structure with a barrier that grows with increasing system size. We thus obtain an upper estimate of the value of the transition temperature in the thermodynamic limit.
Implict Monte Carlo Radiation Transport Simulations of Four Test Problems
Energy Technology Data Exchange (ETDEWEB)
Gentile, N
2007-08-01
Radiation transport codes, like almost all codes, are difficult to develop and debug. It is helpful to have small, easy to run test problems with known answers to use in development and debugging. It is also prudent to re-run test problems periodically during development to ensure that previous code capabilities have not been lost. We describe four radiation transport test problems with analytic or approximate analytic answers. These test problems are suitable for use in debugging and testing radiation transport codes. We also give results of simulations of these test problems performed with an Implicit Monte Carlo photonics code.
Proceedings of the first symposium on Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
NONE
2001-01-01
The first symposium on Monte Carlo simulation was held at Mitsubishi Research Institute, Otemachi, Tokyo, on 10th and 11st of September, 1998. This symposium was organized by Nuclear Code Research Committee at Japan Atomic Energy Research Institute. In the sessions, were presented orally 21 papers on code development, parallel calculation, reactor physics, burn-up, criticality, shielding safety, dose evaluation, nuclear fusion reactor, thermonuclear fusion plasma, nuclear transmutation, electromagnetic cascade, fuel cycle facility. Those presented papers are compiled in this proceedings. The 21 of the presented papers are indexed individually. (J.P.N.)
Probabilistic Assessments of the Plate Using Monte Carlo Simulation
Energy Technology Data Exchange (ETDEWEB)
Ismail, A E [Department of Mechanical Engineering, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Batu Pahat, 86400 Johor (Malaysia); Ariffin, A K; Abdullah, S; Ghazali, M J, E-mail: kamal@eng.ukm.my, E-mail: shahrum@eng.ukm.my, E-mail: maryam@eng.ukm.my, E-mail: emran@uthm.edu.my [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)
2011-02-15
This paper presents the probabilistic analysis of the plate with a hole using several multiaxial high cycle fatigue criteria (MHFC). Dang Van, Sines, Crossland criteria were used and von Mises criterion was also considered for comparison purpose. Parametric finite element model of the plate was developed and several important random variable parameters were selected and Latin Hypercube Sampling Monte-Carlo Simulation (LHS-MCS) was used for probabilistic analysis tool. It was found that, different structural reliability and sensitivity factors were obtained using different failure criteria. According to the results multiaxial fatigue criteria are the most significant criteria need to be considered in assessing all the structural behavior especially under complex loadings.
Probabilistic Assessments of the Plate Using Monte Carlo Simulation
Ismail, A. E.; Ariffin, A. K.; Abdullah, S.; Ghazali, M. J.
2011-02-01
This paper presents the probabilistic analysis of the plate with a hole using several multiaxial high cycle fatigue criteria (MHFC). Dang Van, Sines, Crossland criteria were used and von Mises criterion was also considered for comparison purpose. Parametric finite element model of the plate was developed and several important random variable parameters were selected and Latin Hypercube Sampling Monte-Carlo Simulation (LHS-MCS) was used for probabilistic analysis tool. It was found that, different structural reliability and sensitivity factors were obtained using different failure criteria. According to the results multiaxial fatigue criteria are the most significant criteria need to be considered in assessing all the structural behavior especially under complex loadings.
Monte Carlo simulations of charge transport in heterogeneous organic semiconductors
Aung, Pyie Phyo; Khanal, Kiran; Luettmer-Strathmann, Jutta
2015-03-01
The efficiency of organic solar cells depends on the morphology and electronic properties of the active layer. Research teams have been experimenting with different conducting materials to achieve more efficient solar panels. In this work, we perform Monte Carlo simulations to study charge transport in heterogeneous materials. We have developed a coarse-grained lattice model of polymeric photovoltaics and use it to generate active layers with ordered and disordered regions. We determine carrier mobilities for a range of conditions to investigate the effect of the morphology on charge transport.
New electron multiple scattering distributions for Monte Carlo transport simulation
Energy Technology Data Exchange (ETDEWEB)
Chibani, Omar (Haut Commissariat a la Recherche (C.R.S.), 2 Boulevard Franz Fanon, Alger B.P. 1017, Alger-Gare (Algeria)); Patau, Jean Paul (Laboratoire de Biophysique et Biomathematiques, Faculte des Sciences Pharmaceutiques, Universite Paul Sabatier, 35 Chemin des Maraichers, 31062 Toulouse cedex (France))
1994-10-01
New forms of electron (positron) multiple scattering distributions are proposed. The first is intended for use in the conditions of validity of the Moliere theory. The second distribution takes place when the electron path is so short that only few elastic collisions occur. These distributions are adjustable formulas. The introduction of some parameters allows impositions of the correct value of the first moment. Only positive and analytic functions were used in constructing the present expressions. This makes sampling procedures easier. Systematic tests are presented and some Monte Carlo simulations, as benchmarks, are carried out. ((orig.))
Quasi-Monte Carlo methods for lattice systems. A first look
Energy Technology Data Exchange (ETDEWEB)
Jansen, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; Leovey, H.; Griewank, A. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Mathematik; Nube, A. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik; Mueller-Preussker, M. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik
2013-02-15
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N{sup -1/2}, where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to N{sup -1}. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
Roé-Vellvé, N.; Pino, F.; Falcon, C.; Cot, A.; Gispert, J. D.; Marin, C.; Pavía, J.; Ros, D.
2014-08-01
SPECT studies with 123I-ioflupane facilitate the diagnosis of Parkinson’s disease (PD). The effect on quantification of image degradations has been extensively evaluated in human studies but their impact on studies of experimental PD models is still unclear. The aim of this work was to assess the effect of compensating for the degrading phenomena on the quantification of small animal SPECT studies using 123I-ioflupane. This assessment enabled us to evaluate the feasibility of quantitatively detecting small pathological changes using different reconstruction methods and levels of compensation for the image degrading phenomena. Monte Carlo simulated studies of a rat phantom were reconstructed and quantified. Compensations for point spread function (PSF), scattering, attenuation and partial volume effect were progressively included in the quantification protocol. A linear relationship was found between calculated and simulated specific uptake ratio (SUR) in all cases. In order to significantly distinguish disease stages, noise-reduction during the reconstruction process was the most relevant factor, followed by PSF compensation. The smallest detectable SUR interval was determined by biological variability rather than by image degradations or coregistration errors. The quantification methods that gave the best results allowed us to distinguish PD stages with SUR values that are as close as 0.5 using groups of six rats to represent each stage.
Comparison of uncertainty in fatigue tests obtained by the Monte Carlo method in two softwares
Trevisan, Lisiane; Kapper Fabricio, Daniel Antonio; Reguly, Afonso
2016-07-01
The Supplement 1 to the “Guide to the expression of uncertainty in measurement” indicates the Monte Carlo method for calculating the expanded measurement uncertainty. The objective of this work is to compare the measurement uncertainty values obtained via Monte Carlo method through two commercial softwares (Matlab® and Crystal Ball®) for the parameter ‘adjusted strain’, obtained from fatigue tests. Simulations were carried out using different number of iterations and different levels of confidence. The results showed that there are short differences between the measurement uncertainty values generated by different software.
Pain, F.; Dhenain, M.; Gurden, H.; Routier, A. L.; Lefebvre, F.; Mastrippolito, R.; Lanièce, P.
2008-10-01
The β-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using 18F, 11C and 15O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous β-microprobe reports. In the context of realistic experiments (binding of 11C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with 18F-FDG and H2O15 blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed β-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the different sources of beta signal. Finally, since stereotaxic accuracy is
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.
Cluster Monte Carlo methods for the FePt Hamiltonian
Energy Technology Data Exchange (ETDEWEB)
Lyberatos, A., E-mail: lyb@materials.uoc.gr [Materials Science and Technology Department, P.O. Box 2208, 71003 Heraklion (Greece); Parker, G.J. [HGST, A Western Digital Company, 3403 Yerba Buena Road, San Jose, CA 95135 (United States)
2016-02-15
Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen–Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L1{sub 0}-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium. - Highlights: • A new cluster Monte Carlo algorithm was applied to FePt nanoparticles. • Magnetic anisotropy imposes a restriction on cluster moves. • Inclusion of Metropolis steps is required to satisfy ergodicity. • In the critical region a percolating cluster occurs for any grain size. • Critical slowing down is not solved by the new cluster algorithms.
Monte Carlo simulations of the stability of delta-Pu
DEFF Research Database (Denmark)
Landa, A.; Soderlind, P.; Ruban, Andrei
2003-01-01
The transition temperature (T-c) for delta-Pu has been calculated for the first time. A Monte Carlo method is employed for this purpose and the effective cluster interactions are obtained from first-principles calculations incorporated with the Connolly-Williams and generalized perturbation methods....... It is found that at T-c similar to 548 K, delta-Pu undergoes transformation from a disordered magnetic state to a structure with an anti ferromagnetic spin alignment that is mechanically unstable with respect to tetragonal distortion. The calculated transition temperature is in good agreement...
Monte Carlo simulations of the stability of delta-Pu
Landa, A; Ruban, A
2003-01-01
The transition temperature (T sub c) for delta-Pu has been calculated for the first time. A Monte Carlo method is employed for this purpose and the effective cluster interactions are obtained from first-principles calculations incorporated with the Connolly-Williams and generalized perturbation methods. It is found that at T sub c approx 548 K, delta-Pu undergoes transformation from a disordered magnetic state to a structure with an antiferromagnetic spin alignment that is mechanically unstable with respect to tetragonal distortion. The calculated transition temperature is in good agreement with the temperature measured at the gamma -> delta transition (593 K). (letter to the editor)
Z_3 Polyakov Loop Models and Inverse Monte-Carlo Methods
Wozar, Christian; Uhlmann, Sebastian; Wipf, Andreas; Heinzl, Thomas
2007-01-01
We study effective Polyakov loop models for SU(3) Yang-Mills theory at finite temperature. A comprehensive mean field analysis of the phase diagram is carried out and compared to the results obtained from Monte-Carlo simulations. We find a rich phase structure including ferromagnetic and antiferromagnetic phases. Due to the presence of a tricritical point the mean field approximation agrees very well with the numerical data. Critical exponents associated with second-order transitions coincide with those of the Z_3 Potts model. Finally, we employ inverse Monte-Carlo methods to determine the effective couplings in order to match the effective models to Yang-Mills theory.
A Monte Carlo Study of Eight Confidence Interval Methods for Coefficient Alpha
Romano, Jeanine L.; Kromrey, Jeffrey D.; Hibbard, Susan T.
2010-01-01
The purpose of this research is to examine eight of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions. In general, the differences in…
Monte Carlo simulation of quantum Zeno effect in the brain
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.
Jonane, Inga; Timoshenko, Janis; Kuzmin, Alexei
2016-10-01
Atomistic simulations of the experimental Fe K-edge extended x-ray absorption fine structure (EXAFS) of rhombohedral (space group R\\bar{3}c) FeF3 at T = 300 K were performed using classical molecular dynamics and reverse Monte Carlo (RMC) methods. The use of two complementary theoretical approaches allowed us to account accurately for thermal disorder effects in EXAFS and to validate the developed force-field model, which was constructed as a sum of two-body Buckingham-type (Fe-F and F-F), three-body harmonic (Fe-F-Fe) and Coulomb potentials. We found that the shape of the Fe K-edge EXAFS spectrum of FeF3 is a more sensitive probe for the determination of potential parameters than the values of structural parameters (a, c, x(F)) available from diffraction studies. The best overall agreement between the experimental and theoretical EXAFS spectra calculated using ab initio multiple-scattering approach was obtained for the iron effective charge q(Fe) = 1.71. The RMC method coupled with the evolutionary algorithm was used for more elaborate analysis of the EXAFS data. The obtained results suggest that our force-field model slightly underestimates the amplitude of thermal vibrations of fluorine atoms in the direction perpendicular to the Fe-F bonds.
Energy Technology Data Exchange (ETDEWEB)
Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)
2007-09-21
The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.
Monte Carlo simulation of zinc protoporphyrin fluorescence in the retina
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.
Utilizing Monte Carlo Simulations to Optimize Institutional Empiric Antipseudomonal Therapy
Directory of Open Access Journals (Sweden)
Sarah J. Tennant
2015-12-01
Full Text Available Pseudomonas aeruginosa is a common pathogen implicated in nosocomial infections with increasing resistance to a limited arsenal of antibiotics. Monte Carlo simulation provides antimicrobial stewardship teams with an additional tool to guide empiric therapy. We modeled empiric therapies with antipseudomonal β-lactam antibiotic regimens to determine which were most likely to achieve probability of target attainment (PTA of ≥90%. Microbiological data for P. aeruginosa was reviewed for 2012. Antibiotics modeled for intermittent and prolonged infusion were aztreonam, cefepime, meropenem, and piperacillin/tazobactam. Using minimum inhibitory concentrations (MICs from institution-specific isolates, and pharmacokinetic and pharmacodynamic parameters from previously published studies, a 10,000-subject Monte Carlo simulation was performed for each regimen to determine PTA. MICs from 272 isolates were included in this analysis. No intermittent infusion regimens achieved PTA ≥90%. Prolonged infusions of cefepime 2000 mg Q8 h, meropenem 1000 mg Q8 h, and meropenem 2000 mg Q8 h demonstrated PTA of 93%, 92%, and 100%, respectively. Prolonged infusions of piperacillin/tazobactam 4.5 g Q6 h and aztreonam 2 g Q8 h failed to achieved PTA ≥90% but demonstrated PTA of 81% and 73%, respectively. Standard doses of β-lactam antibiotics as intermittent infusion did not achieve 90% PTA against P. aeruginosa isolated at our institution; however, some prolonged infusions were able to achieve these targets.
Nishizawa, Manami; Nishizawa, Kazuhisa
2002-12-01
To study the mechanisms for local evolutionary changes in DNA sequences involving slippage-type insertions and deletions, an alignment approach is explored that can consider the posterior probabilities of alignment models. Various patterns of insertion and deletion that can link the ancestor and descendant sequences are proposed and evaluated by simulation and compared by the Markov chain Monte Carlo (MCMC) method. Analyses of pseudogenes reveal that the introduction of the parameters that control the probability of slippage-type events markedly augments the probability of the observed sequence evolution, arguing that a cryptic involvement of slippage occurrences is manifested as insertions and deletions of short nucleotide segments. Strikingly, approximately 80% of insertions in human pseudogenes and approximately 50% of insertions in murids pseudogenes are likely to be caused by the slippage-mediated process, as represented by BC in ABCD --> ABCBCD. We suggest that, in both human and murids, even very short repetitive motifs, such as CAGCAG, CACACA, and CCCC, have approximately 10- to 15-fold susceptibility to insertions and deletions, compared to nonrepetitive sequences. Our protocol, namely, indel-MCMC, thus seems to be a reasonable approach for statistical analyses of the early phase of microsatellite evolution.
Dumenci, Levent; Windle, Michael
2001-01-01
Used Monte Carlo methods to evaluate the adequacy of cluster analysis to recover group membership based on simulated latent growth curve (LCG) models. Cluster analysis failed to recover growth subtypes adequately when the difference between growth curves was shape only. Discusses circumstances under which it was more successful. (SLD)
Monte Carlo simulations in small animal PET imaging
Energy Technology Data Exchange (ETDEWEB)
Branco, Susana [Universidade de Lisboa, Faculdade de Ciencias, Instituto de Biofisica e Engenharia Biomedica, Lisbon (Portugal)], E-mail: susana.silva@fc.ul.pt; Jan, Sebastien [Service Hospitalier Frederic Joliot, CEA/DSV/DRM, Orsay (France); Almeida, Pedro [Universidade de Lisboa, Faculdade de Ciencias, Instituto de Biofisica e Engenharia Biomedica, Lisbon (Portugal)
2007-10-01
This work is based on the use of an implemented Positron Emission Tomography (PET) simulation system dedicated for small animal PET imaging. Geant4 Application for Tomographic Emission (GATE), a Monte Carlo simulation platform based on the Geant4 libraries, is well suited for modeling the microPET FOCUS system and to implement realistic phantoms, such as the MOBY phantom, and data maps from real examinations. The use of a microPET FOCUS simulation model with GATE has been validated for spatial resolution, counting rates performances, imaging contrast recovery and quantitative analysis. Results from realistic studies of the mouse body using {sup -}F and [{sup 18}F]FDG imaging protocols are presented. These simulations include the injection of realistic doses into the animal and realistic time framing. The results have shown that it is possible to simulate small animal PET acquisitions under realistic conditions, and are expected to be useful to improve the quantitative analysis in PET mouse body studies.
Sun, Shuyu
2013-06-01
This paper introduces an efficient technique to generate new molecular simulation Markov chains for different temperature and density conditions, which allow for rapid extrapolation of canonical ensemble averages at a range of temperatures and densities different from the original conditions where a single simulation is conducted. Obtained information from the original simulation are reweighted and even reconstructed in order to extrapolate our knowledge to the new conditions. Our technique allows not only the extrapolation to a new temperature or density, but also the double extrapolation to both new temperature and density. The method was implemented for Lennard-Jones fluid with structureless particles in single-gas phase region. Extrapolation behaviors as functions of extrapolation ranges were studied. Limits of extrapolation ranges showed a remarkable capability especially along isochors where only reweighting is required. Various factors that could affect the limits of extrapolation ranges were investigated and compared. In particular, these limits were shown to be sensitive to the number of particles used and starting point where the simulation was originally conducted.
Quantum-trajectory Monte Carlo method for study of electron-crystal interaction in STEM.
Ruan, Z; Zeng, R G; Ming, Y; Zhang, M; Da, B; Mao, S F; Ding, Z J
2015-07-21
In this paper, a novel quantum-trajectory Monte Carlo simulation method is developed to study electron beam interaction with a crystalline solid for application to electron microscopy and spectroscopy. The method combines the Bohmian quantum trajectory method, which treats electron elastic scattering and diffraction in a crystal, with a Monte Carlo sampling of electron inelastic scattering events along quantum trajectory paths. We study in this work the electron scattering and secondary electron generation process in crystals for a focused incident electron beam, leading to understanding of the imaging mechanism behind the atomic resolution secondary electron image that has been recently achieved in experiment with a scanning transmission electron microscope. According to this method, the Bohmian quantum trajectories have been calculated at first through a wave function obtained via a numerical solution of the time-dependent Schrödinger equation with a multislice method. The impact parameter-dependent inner-shell excitation cross section then enables the Monte Carlo sampling of ionization events produced by incident electron trajectories travelling along atom columns for excitation of high energy knock-on secondary electrons. Following cascade production, transportation and emission processes of true secondary electrons of very low energies are traced by a conventional Monte Carlo simulation method to present image signals. Comparison of the simulated image for a Si(110) crystal with the experimental image indicates that the dominant mechanism of atomic resolution of secondary electron image is the inner-shell ionization events generated by a high-energy electron beam.
Burrows, John
2013-04-01
An introduction to the use of the mathematical technique of Monte Carlo simulations to evaluate least squares regression calibration is described. Monte Carlo techniques involve the repeated sampling of data from a population that may be derived from real (experimental) data, but is more conveniently generated by a computer using a model of the analytical system and a randomization process to produce a large database. Datasets are selected from this population and fed into the calibration algorithms under test, thus providing a facile way of producing a sufficiently large number of assessments of the algorithm to enable a statically valid appraisal of the calibration process to be made. This communication provides a description of the technique that forms the basis of the results presented in Parts II and III of this series, which follow in this issue, and also highlights the issues arising from the use of small data populations in bioanalysis.
SIMIND Monte Carlo simulation of a single photon emission CT
Directory of Open Access Journals (Sweden)
Bahreyni Toossi M
2010-01-01
Full Text Available In this study, we simulated a Siemens E.CAM SPECT system using SIMIND Monte Carlo program to acquire its experimental characterization in terms of energy resolution, sensitivity, spatial resolution and imaging of phantoms using 99m Tc. The experimental and simulation data for SPECT imaging was acquired from a point source and Jaszczak phantom . Verification of the simulation was done by comparing two sets of images and related data obtained from the actual and simulated systems. Image quality was assessed by comparing image contrast and resolution. Simulated and measured energy spectra (with or without a collimator and spatial resolution from point sources in air were compared. The resulted energy spectra present similar peaks for the gamma energy of 99m Tc at 140 KeV. FWHM for the simulation calculated to14.01 KeV and 13.80 KeV for experimental data, corresponding to energy resolution of 10.01and 9.86% compared to defined 9.9% for both systems, respectively. Sensitivities of the real and virtual gamma cameras were calculated to 85.11 and 85.39 cps/MBq, respectively. The energy spectra of both simulated and real gamma cameras were matched. Images obtained from Jaszczak phantom, experimentally and by simulation, showed similarity in contrast and resolution. SIMIND Monte Carlo could successfully simulate the Siemens E.CAM gamma camera. The results validate the use of the simulated system for further investigation, including modification, planning, and developing a SPECT system to improve the quality of images.
Institute of Scientific and Technical Information of China (English)
丁雨田; 王海南; 许广济; 李传军
2001-01-01
The forming processes of microstructure under uni-dire ctional, bi-directional, multi-directional and overall solidification conditio ns were simulated with Monte Carlo method. The simulation results were close to the realities. The problems and failures of Monte Carlo method used for simulation of microstructure were analyzed also.%应用Monte Carlo方法模拟了定向凝固条件下微观组织的形成过程，同时还模拟了双向凝固，四边由表面向中心凝固及整体凝固的微观组织形成过程，模拟结果与实际情况非常接近。 同时分析了Monte Carlo方法用于微观组织模拟存在的问题和不足之处。
GATE Monte Carlo simulation in a cloud computing environment
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.
Monte Carlo simulations for design of the KFUPM PGNAA facility
Naqvi, A A; Maslehuddin, M; Kidwai, S
2003-01-01
Monte Carlo simulations were carried out to design a 2.8 MeV neutron-based prompt gamma ray neutron activation analysis (PGNAA) setup for elemental analysis of cement samples. The elemental analysis was carried out using prompt gamma rays produced through capture of thermal neutrons in sample nuclei. The basic design of the PGNAA setup consists of a cylindrical cement sample enclosed in a cylindrical high-density polyethylene moderator placed between a neutron source and a gamma ray detector. In these simulations the predominant geometrical parameters of the PGNAA setup were optimized, including moderator size, sample size and shielding of the detector. Using the results of the simulations, an experimental PGNAA setup was then fabricated at the 350 kV Accelerator Laboratory of this University. The design calculations were checked experimentally through thermal neutron flux measurements inside the PGNAA moderator. A test prompt gamma ray spectrum of the PGNAA setup was also acquired from a Portland cement samp...
Monte Carlo Simulation Tool Installation and Operation Guide
Energy Technology Data Exchange (ETDEWEB)
Aguayo Navarrete, Estanislao; Ankney, Austin S.; Berguson, Timothy J.; Kouzes, Richard T.; Orrell, John L.; Troy, Meredith D.; Wiseman, Clinton G.
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 by 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.
Monte Carlo simulation of classical spin models with chaotic billiards.
Suzuki, Hideyuki
2013-11-01
It has recently been shown that the computing abilities of Boltzmann machines, or Ising spin-glass models, can be implemented by chaotic billiard dynamics without any use of random numbers. In this paper, we further numerically investigate the capabilities of the chaotic billiard dynamics as a deterministic alternative to random Monte Carlo methods by applying it to classical spin models in statistical physics. First, we verify that the billiard dynamics can yield samples that converge to the true distribution of the Ising model on a small lattice, and we show that it appears to have the same convergence rate as random Monte Carlo sampling. Second, we apply the billiard dynamics to finite-size scaling analysis of the critical behavior of the Ising model and show that the phase-transition point and the critical exponents are correctly obtained. Third, we extend the billiard dynamics to spins that take more than two states and show that it can be applied successfully to the Potts model. We also discuss the possibility of extensions to continuous-valued models such as the XY model.
Monte Carlo methods for medical physics a practical introduction
Schuemann, Jan; Paganetti, Harald
2018-01-01
The Monte Carlo (MC) method, established as the gold standard to predict results of physical processes, is now fast becoming a routine clinical tool for applications that range from quality control to treatment verification. This book provides a basic understanding of the fundamental principles and limitations of the MC method in the interpretation and validation of results for various scenarios. It shows how user-friendly and speed optimized MC codes can achieve online image processing or dose calculations in a clinical setting. It introduces this essential method with emphasis on applications in hardware design and testing, radiological imaging, radiation therapy, and radiobiology.
Novel Extrapolation Method in the Monte Carlo Shell Model
Shimizu, Noritaka; Mizusaki, Takahiro; Otsuka, Takaharu; Abe, Takashi; Honma, Michio
2010-01-01
We propose an extrapolation method utilizing energy variance in the Monte Carlo shell model in order to estimate the energy eigenvalue and observables accurately. We derive a formula for the energy variance with deformed Slater determinants, which enables us to calculate the energy variance efficiently. The feasibility of the method is demonstrated for the full $pf$-shell calculation of $^{56}$Ni, and the applicability of the method to a system beyond current limit of exact diagonalization is shown for the $pf$+$g_{9/2}$-shell calculation of $^{64}$Ge.
On adaptive resampling strategies for sequential Monte Carlo methods
Del Moral, Pierre; Jasra, Ajay; 10.3150/10-BEJ335
2012-01-01
Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for these methods. By combining semigroup techniques with an original coupling argument, we obtain functional central limit theorems and uniform exponential concentration estimates for these algorithms.
Basics of Monte-Carlo Simulation: Focusing on Dose-to-medium and Dose-to-water.
Tadano, Kiichi; Isobe, Tomonori; Sato, Eisuke; Takei, Hideyuki; Kobayashi, Daisuke; Mori, Yutaro; Tomita, Tetsuya; Sakae, Takeji
Treatment planning systems with highly accurate dose calculation algorithms such as Monte-Carlo method and linear Boltzmann transport equation are becoming popular thanks to a development of the computer technology. These algorithms use new concepts, dose-to-medium and dose-to-water. However, introducing these concepts can cause confusion in clinical sites. Basic knowledges about Monte-Carlo simulation and other corresponding algorithms were explained in this article such as the principles, the parameters and words of caution.
Kumar, Sudhir; Srinivasan, P; Sharma, S D
2010-06-01
A cylindrical graphite ionization chamber of sensitive volume 1002.4 cm(3) was designed and fabricated at Bhabha Atomic Research Centre (BARC) for use as a reference dosimeter to measure the strength of high dose rate (HDR) (192)Ir brachytherapy sources. The air kerma calibration coefficient (N(K)) of this ionization chamber was estimated analytically using Burlin general cavity theory and by the Monte Carlo method. In the analytical method, calibration coefficients were calculated for each spectral line of an HDR (192)Ir source and the weighted mean was taken as N(K). In the Monte Carlo method, the geometry of the measurement setup and physics related input data of the HDR (192)Ir source and the surrounding material were simulated using the Monte Carlo N-particle code. The total photon energy fluence was used to arrive at the reference air kerma rate (RAKR) using mass energy absorption coefficients. The energy deposition rates were used to simulate the value of charge rate in the ionization chamber and N(K) was determined. The Monte Carlo calculated N(K) agreed within 1.77 % of that obtained using the analytical method. The experimentally determined RAKR of HDR (192)Ir sources, using this reference ionization chamber by applying the analytically estimated N(K), was found to be in agreement with the vendor quoted RAKR within 1.43%.
Directory of Open Access Journals (Sweden)
He Deyu
2016-09-01
Full Text Available Assessing the risks of steering system faults in underwater vehicles is a human-machine-environment (HME systematic safety field that studies faults in the steering system itself, the driver’s human reliability (HR and various environmental conditions. This paper proposed a fault risk assessment method for an underwater vehicle steering system based on virtual prototyping and Monte Carlo simulation. A virtual steering system prototype was established and validated to rectify a lack of historic fault data. Fault injection and simulation were conducted to acquire fault simulation data. A Monte Carlo simulation was adopted that integrated randomness due to the human operator and environment. Randomness and uncertainty of the human, machine and environment were integrated in the method to obtain a probabilistic risk indicator. To verify the proposed method, a case of stuck rudder fault (SRF risk assessment was studied. This method may provide a novel solution for fault risk assessment of a vehicle or other general HME system.
Combining cellular automata and Monte Carlo algorithm to simulate three-dimensional grain growth
Institute of Scientific and Technical Information of China (English)
WANG Wei; CHEN Ju-hua; GUO Pei-quan; ZHAO Ping
2006-01-01
A 3-D simulation of grain growth was conducted by utilizing cellular automata (CA) and Monte Carlo (MC) algorithm. In the simulating procedure, the three-dimensional space is divided into a large number of 2-D isometric planes. Then, each of the planes is divided into identical square cells. Finally, the cellular automata and Monte Carlo algorithm are combined together to simulate the grain growth. Through an evolutionary simulation, the recrystallized microstructure, the grain growth rate and the grain size distribution are acceptably predicted. The simulation routine can be used to simulate the real physical-metallurgy processes and to predict quantitative dynamic information of the evolution of microstructure. Further more, the method is also useful for optimization of materials properties by controlling the microstructure evolution.
Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.
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.
Multidiscontinuity algorithm for world-line Monte Carlo simulations.
Kato, Yasuyuki
2013-01-01
We introduce a multidiscontinuity algorithm for the efficient global update of world-line configurations in Monte Carlo simulations of interacting quantum systems. This algorithm is a generalization of the two-discontinuity algorithms introduced in Refs. [N. Prokof'ev, B. Svistunov, and I. Tupitsyn, Phys. Lett. A 238, 253 (1998)] and [O. F. Syljuåsen and A. W. Sandvik, Phys. Rev. E 66, 046701 (2002)]. This generalization is particularly effective for studying Bose-Einstein condensates (BECs) of composite particles. In particular, we demonstrate the utility of the generalized algorithm by simulating a Hamiltonian for an S=1 antiferromagnet with strong uniaxial single-ion anisotropy. The multidiscontinuity algorithm not only solves the freezing problem that arises in this limit, but also allows the efficient computing of the off-diagonal correlator that characterizes a BEC of composite particles.
Treatment planning in radiosurgery: parallel Monte Carlo simulation software
Energy Technology Data Exchange (ETDEWEB)
Scielzo, G. [Galliera Hospitals, Genova (Italy). Dept. of Hospital Physics; Grillo Ruggieri, F. [Galliera Hospitals, Genova (Italy) Dept. for Radiation Therapy; Modesti, M.; Felici, R. [Electronic Data System, Rome (Italy); Surridge, M. [University of South Hampton (United Kingdom). Parallel Apllication Centre
1995-12-01
The main objective of this research was to evaluate the possibility of direct Monte Carlo simulation for accurate dosimetry with short computation time. We made us of: graphics workstation, linear accelerator, water, PMMA and anthropomorphic phantoms, for validation purposes; ionometric, film and thermo-luminescent techniques, for dosimetry; treatment planning system for comparison. Benchmarking results suggest that short computing times can be obtained with use of the parallel version of EGS4 that was developed. Parallelism was obtained assigning simulation incident photons to separate processors, and the development of a parallel random number generator was necessary. Validation consisted in: phantom irradiation, comparison of predicted and measured values good agreement in PDD and dose profiles. Experiments on anthropomorphic phantoms (with inhomogeneities) were carried out, and these values are being compared with results obtained with the conventional treatment planning system.
Quantitative application of Monte Carlo simulation in Fire-PSA
Energy Technology Data Exchange (ETDEWEB)
Mangs, J.; Hostikka, S.; Korhonen, T. [Valtion Teknillinen Tutkimuskeskus, Espoo (Finland); Keski-Rahkonen, O.
2007-05-15
In a power plant a fire cell forms the basic subunit. Since the fire is initially located there, the full-scale time dependent fire simulation and estimation of target response must be performed within the fire cell. Conditional, time dependent damage probabilities in a fire cell can now be calculated for arbitrary targets (component or a subsystem) combining probabilistic (Monte Carlo) and deterministic simulation. For the latter a spectrum from simple correlations up to latest computational fluid dynamics models is available. Selection of the code is made according to the requirements form the target cell. Although calculations are numerically heavy, it is now economically possible and feasible to carry out quantitative fire-PSA for a complete plant iteratively with the main PSA. From real applications examples are shown on assessment of fire spread possibility in a relay room, and potential of fire spread on cables in a tunnel. (orig.)
Monte Carlo simulations of nanoscale focused neon ion beam sputtering.
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.
Virtual detector characterisation with Monte-Carlo simulations
Sukowski, F.; Yaneu Yaneu, J. F.; Salamon, M.; Ebert, S.; Uhlmann, N.
2009-08-01
In the field of X-ray imaging flat-panel detectors which convert X-rays into electrical signals, are widely used. For different applications, detectors differ in several specific parameters that can be used for characterizing the detector. At the Development Center X-ray Technology EZRT we studied the question how well these characteristics can be determined by only knowing the layer composition of a detector. In order to determine the required parameters, the Monte-Carlo (MC) simulation program ROSI [J. Giersch et al., Nucl. Instr. and Meth. A 509 (2003) 151] was used while taking into account all primary and secondary particle interactions as well as the focal spot size of the X-ray tube. For the study, the Hamamatsu C9311DK [Technical Datasheet Hamamatsu C9311DK flat panel sensor, Hamamatsu Photonics, ( www.hamamatsu.com)], a scintillator-based detector, and the Ajat DIC 100TL [Technical description of Ajat DIC 100TL, Ajat Oy Ltd., ( www.ajat.fi)], a direct converting semiconductor detector, were used. The layer compositions of the two detectors were implemented into the MC simulation program. The following characteristics were measured [N. Uhlmann et al., Nucl. Instr. and Meth. A 591 (2008) 46] and compared to simulation results: The basic spatial resolution (BSR), the modulation transfer function (MTF), the contrast sensitivity (CS) and the specific material thickness range (SMTR). To take scattering of optical photons into account DETECT2000 [C. Moisan et al., DETECT2000—A Program for Modeling Optical Properties of Scintillators, Department of Electrical and Computer Engineering, Laval University, Quebec City, 2000], another Monte-Carlo simulation was used.
Energy Technology Data Exchange (ETDEWEB)
Rojas C, E. L., E-mail: leticia.rojas@inin.gob.m [ININ, Gerencia de Ciencias Ambientales, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2010-07-01
At the present time the computers use to solve important problems extends to all the areas. These areas can be of social, economic, of engineering, of basic and applied science, etc. With and appropriate handling of computation programs and information can be carried out calculations and simulations of real models, to study them and to solve theoretical or application problems. The processes that contain random variables are susceptible of being approached with the Monte Carlo method. This is a numeric method that, thanks to the improvements in the processors of the computers, it can apply in many tasks more than what was made in the principles of their practical application (at the beginning of the decade of 1950). In this work the application of the Monte Carlo method will be approached in the simulation of the radiation interaction with the matter, to investigate dosimetric aspects of some problems that exist in the medical physics area. Also, contain an introduction about some historical data and some general concepts related with the Monte Carlo simulation are revised. (Author)
Eigenvalue analysis using a full-core Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Okafor, K.C.; Zino, J.F. (Westinghouse Savannah River Co., Aiken, SC (United States))
1992-01-01
The reactor physics codes used at the Savannah River Site (SRS) to predict reactor behavior have been continually benchmarked against experimental and operational data. A particular benchmark variable is the observed initial critical control rod position. Historically, there has been some difficulty predicting this position because of the difficulties inherent in using computer codes to model experimental or operational data. The Monte Carlo method is applied in this paper to study the initial critical control rod positions for the SRS K Reactor. A three-dimensional, full-core MCNP model of the reactor was developed for this analysis.
Yasuda, Shugo
2015-01-01
A Monte Carlo simulation for the chemotactic bacteria is developed on the basis of the kinetic modeling, i.e., the Boltzmann transport equation, and applied to the one-dimensional traveling population wave in a micro channel.In this method, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to solve the macroscopic transport of the chemical cues in the field. The simulation method can successfully reproduce the traveling population wave of bacteria which was observed experimentally. The microscopic dynamics of bacteria, e.g., the velocity autocorrelation function and velocity distribution function of bacteria, are also investigated. It is found that the bacteria which form the traveling population wave create quasi-periodic motions as well as a migratory movement along with the traveling population wave. Simulations are also performed with changing the sensitivity and modulation parameters in the response function of bacteria. It is found th...
2006-01-01
of Mathematics and ICES, University of Texas at Austin, Austin, TX 78712, USA gamba@math.utexas.edu Armando Majorana Dipartimento di Matematica e...factors important for the comparison between deterministic BTE and stochastic DSMC solvers. The simulation results demonstrate the superior capability of
Yuan, Jiankui; Zheng, Yiran; Wessels, Barry; Lo, Simon S; Ellis, Rodney; Machtay, Mitchell; Yao, Min
2016-12-01
A virtual source model for Monte Carlo simulations of helical TomoTherapy has been developed previously by the authors. The purpose of this work is to perform experiments in an anthropomorphic (RANDO) phantom with the same order of complexity as in clinical treatments to validate the virtual source model to be used for quality assurance secondary check on TomoTherapy patient planning dose. Helical TomoTherapy involves complex delivery pattern with irregular beam apertures and couch movement during irradiation. Monte Carlo simulation, as the most accurate dose algorithm, is desirable in radiation dosimetry. Current Monte Carlo simulations for helical TomoTherapy adopt the full Monte Carlo model, which includes detailed modeling of individual machine component, and thus, large phase space files are required at different scoring planes. As an alternative approach, we developed a virtual source model without using the large phase space files for the patient dose calculations previously. In this work, we apply the simulation system to recompute the patient doses, which were generated by the treatment planning system in an anthropomorphic phantom to mimic the real patient treatments. We performed thermoluminescence dosimeter point dose and film measurements to compare with Monte Carlo results. Thermoluminescence dosimeter measurements show that the relative difference in both Monte Carlo and treatment planning system is within 3%, with the largest difference less than 5% for both the test plans. The film measurements demonstrated 85.7% and 98.4% passing rate using the 3 mm/3% acceptance criterion for the head and neck and lung cases, respectively. Over 95% passing rate is achieved if 4 mm/4% criterion is applied. For the dose-volume histograms, very good agreement is obtained between the Monte Carlo and treatment planning system method for both cases. The experimental results demonstrate that the virtual source model Monte Carlo system can be a viable option for the
Direct simulation Monte Carlo schemes for Coulomb interactions in plasmas
Dimarco, Giacomo; Pareschi, Lorenzo
2010-01-01
We consider the development of Monte Carlo schemes for molecules with Coulomb interactions. We generalize the classic algorithms of Bird and Nanbu-Babovsky for rarefied gas dynamics to the Coulomb case thanks to the approximation introduced by Bobylev and Nanbu (Theory of collision algorithms for gases and plasmas based on the Boltzmann equation and the Landau-Fokker-Planck equation, Physical Review E, Vol. 61, 2000). Thus, instead of considering the original Boltzmann collision operator, the schemes are constructed through the use of an approximated Boltzmann operator. With the above choice larger time steps are possible in simulations; moreover the expensive acceptance-rejection procedure for collisions is avoided and every particle collides. Error analysis and comparisons with the original Bobylev-Nanbu (BN) scheme are performed. The numerical results show agreement with the theoretical convergence rate of the approximated Boltzmann operator and the better performance of Bird-type schemes with respect to t...
Monte Carlo modelling of Schottky diode for rectenna simulation
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.
Measuring Renyi entanglement entropy in quantum Monte Carlo simulations.
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.
Monte Carlo Simulation of Diamond Deposition at Low Temperature
Institute of Scientific and Technical Information of China (English)
董丽芳; 张玉红
2001-01-01
Diamond deposition at low temperatures is investigated and the relationship between substrate temperature for diamond growth and the energy of the carbonaceous species is given. The electron energy distribution and velocity distribution during the electron assisted chemical vapour deposition have been obtained by using Monte Carlo simulation. The main results obtained are as follows. (1) The substrate temperature for diamond growth will be lower than 800 C when the carbonaceous species on the substrate have mobility energy. For example, if the energy of the carbonaceous species is 0. 75 eV, the substrate temperature will be 380℃-600℃. (2) The greatnumber of atomic H on the substrate is of importance to the growth of diamond films.
Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations
DEFF Research Database (Denmark)
Kamran, Faisal; Andersen, Peter E.
2015-01-01
Oblique incidence reflectometry has developed into an effective, noncontact, and noninvasive measurement technology for the quantification of both the reduced scattering and absorption coefficients of a sample. The optical properties are deduced by analyzing only the shape of the reflectance...... profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...... properties in which system demands vary to be able to detect subtle changes in the structure of the medium, translated as measured optical properties. Effects of variation in anisotropy are discussed and results presented. Finally, experimental data of milk products with different fat content are considered...
Monte Carlo simulations of ABC stacked kagome lattice films.
Yerzhakov, H V; Plumer, M L; Whitehead, J P
2016-05-18
Properties of films of geometrically frustrated ABC stacked antiferromagnetic kagome layers are examined using Metropolis Monte Carlo simulations. The impact of having an easy-axis anisotropy on the surface layers and cubic anisotropy in the interior layers is explored. The spin structure at the surface is shown to be different from that of the bulk 3D fcc system, where surface axial anisotropy tends to align spins along the surface [1 1 1] normal axis. This alignment then propagates only weakly to the interior layers through exchange coupling. Results are shown for the specific heat, magnetization and sub-lattice order parameters for both surface and interior spins in three and six layer films as a function of increasing axial surface anisotropy. Relevance to the exchange bias phenomenon in IrMn3 films is discussed.
Monte Carlo simulations and benchmark studies at CERN's accelerator chain
AUTHOR|(CDS)2083190; Brugger, Markus
2016-01-01
Mixed particle and energy radiation fields present at the Large Hadron Collider (LHC) and its accelerator chain are responsible for failures on electronic devices located in the vicinity of the accelerator beam lines. These radiation effects on electronics and, more generally, the overall radiation damage issues have a direct impact on component and system lifetimes, as well as on maintenance requirements and radiation exposure to personnel who have to intervene and fix existing faults. The radiation environments and respective radiation damage issues along the CERN’s accelerator chain were studied in the framework of the CERN Radiation to Electronics (R2E) project and are hereby presented. The important interplay between Monte Carlo simulations and radiation monitoring is also highlighted.
Monte Carlo simulations of ABC stacked kagome lattice films
Yerzhakov, H. V.; Plumer, M. L.; Whitehead, J. P.
2016-05-01
Properties of films of geometrically frustrated ABC stacked antiferromagnetic kagome layers are examined using Metropolis Monte Carlo simulations. The impact of having an easy-axis anisotropy on the surface layers and cubic anisotropy in the interior layers is explored. The spin structure at the surface is shown to be different from that of the bulk 3D fcc system, where surface axial anisotropy tends to align spins along the surface [1 1 1] normal axis. This alignment then propagates only weakly to the interior layers through exchange coupling. Results are shown for the specific heat, magnetization and sub-lattice order parameters for both surface and interior spins in three and six layer films as a function of increasing axial surface anisotropy. Relevance to the exchange bias phenomenon in IrMn3 films is discussed.
Effect of doping of graphene structure: A Monte Carlo simulations
Masrour, R.; Jabar, A.
2016-10-01
In this work, we have studied the effect of magnetic atom doping of graphene structure using Monte Carlo simulation. The reduced critical temperature with the magnetic atom doping x has been deduced from the thermal variation of magnetization and magnetic susceptibility. The variation of magnetization versus the crystal field of grapheme structure for different x and for different reduced temperatures has been established. We also have measured the coercive field (hC) as a function x in grapheme structure, finding that hC increases with increasing x concentration as predicted experimentally. The doping-induced magnetism in graphene. Magnetically atom doping in graphene systems are potential candidates for application in future spintronic devices, magnetometry requires macroscopic quantities of graphene to detect magnetic moments directly.
Energy Technology Data Exchange (ETDEWEB)
Glaser, R E; Johannesson, G; Sengupta, S; Kosovic, B; Carle, S; Franz, G A; Aines, R D; Nitao, J J; Hanley, W G; Ramirez, A L; Newmark, R L; Johnson, V M; Dyer, K M; Henderson, K A; Sugiyama, G A; Hickling, T L; Pasyanos, M E; Jones, D A; Grimm, R J; Levine, R A
2004-03-11
Accurate prediction of complex phenomena can be greatly enhanced through the use of data and observations to update simulations. The ability to create these data-driven simulations is limited by error and uncertainty in both the data and the simulation. The stochastic engine project addressed this problem through the development and application of a family of Markov Chain Monte Carlo methods utilizing importance sampling driven by forward simulators to minimize time spent search very large state spaces. The stochastic engine rapidly chooses among a very large number of hypothesized states and selects those that are consistent (within error) with all the information at hand. Predicted measurements from the simulator are used to estimate the likelihood of actual measurements, which in turn reduces the uncertainty in the original sample space via a conditional probability method called Bayesian inferencing. This highly efficient, staged Metropolis-type search algorithm allows us to address extremely complex problems and opens the door to solving many data-driven, nonlinear, multidimensional problems. A key challenge has been developing representation methods that integrate the local details of real data with the global physics of the simulations, enabling supercomputers to efficiently solve the problem. Development focused on large-scale problems, and on examining the mathematical robustness of the approach in diverse applications. Multiple data types were combined with large-scale simulations to evaluate systems with {approx}{sup 10}20,000 possible states (detecting underground leaks at the Hanford waste tanks). The probable uses of chemical process facilities were assessed using an evidence-tree representation and in-process updating. Other applications included contaminant flow paths at the Savannah River Site, locating structural flaws in buildings, improving models for seismic travel times systems used to monitor nuclear proliferation, characterizing the source
Monte Carlo simulation of ICRF discharge initiation in ITER
Tripský, M.; Wauters, T.; Lyssoivan, A.; Křivská, A.; Louche, F.; Van Schoor, M.; Noterdaeme, J.-M.
2015-12-01
Discharges produced and sustained by ion cyclotron range of frequency (ICRF) waves in absence of plasma current will be used on ITER for (ion cyclotron-) wall conditioning (ICWC). The here presented simulations aim at ensuring that the ITER ICRH&CD system can be safely employed for ICWC and at finding optimal parameters to initiate the plasma. The 1D Monte Carlo code RFdinity1D3V was developed to simulate ICRF discharge initiation. The code traces the electron motion along one toroidal magnetic field line, accelerated by the RF field in front of the ICRF antenna. Electron collisions in the calculations are handled by a Monte Carlo procedure taking into account their energies and the related electron collision cross sections for collisions with H2, H2+ and H+. The code also includes Coulomb collisions between electrons and ions (e - e, e - H2+ , e - H+). We study the electron multiplication rate as a function of the RF discharge parameters (i) antenna input power (0.1-5MW), and (ii) the neutral pressure (H2) for two antenna phasing (monopole [0000]-phasing and small dipole [0π0π]-phasing). Furthermore, we investigate the electron multiplication rate dependency on the distance from the antenna straps. This radial dependency results from the decreasing electric amplitude and field smoothening with increasing distance from the antenna straps. The numerical plasma breakdown definition used in the code corresponds to the moment when a critical electron density nec for the low hybrid resonance (ω = ωLHR) is reached. This numerical definition was previously found in qualitative agreement with experimental breakdown times obtained from the literature and from experiments on the ASDEX Upgrade and TEXTOR.
Monte-Carlo Simulation on the Failure of Fiber in a Single Filament Composite
Institute of Scientific and Technical Information of China (English)
邢孟秋; 严灏景
2001-01-01
A Monte-Carlo method is used to simulate gradual fracture of fiber in a single filament composite with the increase of virtual stress. A simple computational algorithm is developed to judge where breaking point will happen in the composite and a probability model based on Weibull- distribution is designed to calculate the average fragment length by producing stable and uniform random number in (0, 1). Compared to the published experiment results, the simulating average fragment length is quite perfect.
Energy Technology Data Exchange (ETDEWEB)
Mendes, Hitalo R.; Tomal, Alessandra [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil). Instituto de Fisica Gleb Wataghin
2016-07-01
The dosimetry in pediatric radiology is essential due to the higher risk that children have in comparison to adults. The focus of this study is to present how the dose varies depending on the depth in a 10 year old and a newborn, for this purpose simulations are made using the Monte Carlo method. Potential differences were considered 70 and 90 kVp for the 10 year old and 70 and 80 kVp for the newborn. The results show that in both cases, the dose at the skin surface is larger for smaller potential value, however, it decreases faster for larger potential values. Another observation made is that because the newborn is less thick the ratio between the initial dose and the final is lower compared to the case of a 10 year old, showing that it is possible to make an image using a smaller entrance dose in the skin, keeping the same level of exposure at the detector. (author)
Monte Carlo computer simulation of sedimentation of charged hard spherocylinders
Energy Technology Data Exchange (ETDEWEB)
Viveros-Méndez, P. X., E-mail: xviveros@fisica.uaz.edu.mx; Aranda-Espinoza, S. [Unidad Académica de Física, Universidad Autónoma de Zacatecas, Calzada Solidaridad esq. Paseo, La Bufa s/n, 98060 Zacatecas, Zacatecas, México (Mexico); Gil-Villegas, Alejandro [Departamento de Ingeniería Física, División de Ciencias e Ingenierías, Campus León, Universidad de Guanajuato, Loma del Bosque 103, Lomas del Campestre, 37150 León, Guanajuato, México (Mexico)
2014-07-28
In this article we present a NVT Monte Carlo computer simulation study of sedimentation of an electroneutral mixture of oppositely charged hard spherocylinders (CHSC) with aspect ratio L/σ = 5, where L and σ are the length and diameter of the cylinder and hemispherical caps, respectively, for each particle. This system is an extension of the restricted primitive model for spherical particles, where L/σ = 0, and it is assumed that the ions are immersed in an structureless solvent, i.e., a continuum with dielectric constant D. The system consisted of N = 2000 particles and the Wolf method was implemented to handle the coulombic interactions of the inhomogeneous system. Results are presented for different values of the strength ratio between the gravitational and electrostatic interactions, Γ = (mgσ)/(e{sup 2}/Dσ), where m is the mass per particle, e is the electron's charge and g is the gravitational acceleration value. A semi-infinite simulation cell was used with dimensions L{sub x} ≈ L{sub y} and L{sub z} = 5L{sub x}, where L{sub x}, L{sub y}, and L{sub z} are the box dimensions in Cartesian coordinates, and the gravitational force acts along the z-direction. Sedimentation effects were studied by looking at every layer formed by the CHSC along the gravitational field. By increasing Γ, particles tend to get more packed at each layer and to arrange in local domains with an orientational ordering along two perpendicular axis, a feature not observed in the uncharged system with the same hard-body geometry. This type of arrangement, known as tetratic phase, has been observed in two-dimensional systems of hard-rectangles and rounded hard-squares. In this way, the coupling of gravitational and electric interactions in the CHSC system induces the arrangement of particles in layers, with the formation of quasi-two dimensional tetratic phases near the surface.
Monte Carlo Simulation and Experimental Characterization of a Dual Head Gamma Camera
Rodrigues, S; Abreu, M C; Santos, N; Rato-Mendes, P; Peralta, L
2007-01-01
The GEANT4 Monte Carlo simulation and experimental characterization of the Siemens E.Cam Dual Head gamma camera hosted in the Particular Hospital of Algarve have been done. Imaging tests of thyroid and other phantoms have been made "in situ" and compared with the results obtained with the Monte Carlo simulation.
Burt, Jonathan M.; Josyula, Eswar
2016-11-01
A modification to DSMC collision routines is proposed to eliminate or reduce collision separation error in numerical transport coefficients. This modification follows from earlier DSMC error analysis based on Green-Kubo theory, and is currently limited to the case of a hard sphere monatomic simple gas simulation with approximately isotropic collision separation statistics. Further adjustments to the DSMC collision algorithm are proposed to reduce collision separation error associated with a finite time step interval. It is shown analytically that, for random collision partner selection at the small time step limit with a cell size equal to the mean free path, collision separation error in viscosity is reduced by approximately 37% while thermal conductivity error is completely removed. In a demonstration case involving hypersonic flow over a cylinder, the proposed modification is found to allow for large error reductions in both the total force and heat transfer rate. Although this modification is not intended as a general solution to the problem of DSMC collision separation error, it is hoped that the concept demonstrated here of utilizing Green-Kubo analysis for DSMC error reduction will in the future find more widespread applicability.
Monte Carlo simulation of the hysteresis phenomena on ferromagnetic nanotubes.
Salazar-Enríquez, C D; Restrepo, J; Restrepo-Parra, E
2012-06-01
In this work the hysteretic properties of single wall ferromagnetic nanotubes were studied. Hysteresis loops were computed on the basis of a classical Heisenberg model involving nearest neighbor interactions and using a Monte Carlo method implemented with a single spin movement Metropolis dynamics. Nanotubes with square and hexagonal unit cells were studied varying their diameter, temperature and magneto-crystalline anisotropy. Effects of the diameter were found stronger in the square unit cell magnetic nanotubes (SMNTs) than in the hexagonal unit cell magnetic nanotubes (HMNTs). The ferromagnetic behavior was observed in SMNTs at higher temperature than in HMNTs. Moreover in both cases, SMNTs and HMNTs, the magneto-crystalline anisotropy in the longitudinal direction showed a linear correspondence with the coercive field.
Number of iterations needed in Monte Carlo Simulation using reliability analysis for tunnel supports
Directory of Open Access Journals (Sweden)
E. Bukaçi
2016-06-01
Full Text Available There are many methods in geotechnical engineering which could take advantage of Monte Carlo Simulation to establish probability of failure, since closed form solutions are almost impossible to use in most cases. The problem that arises with using Monte Carlo Simulation is the number of iterations needed for a particular simulation.This article will show why it’s important to calculate number of iterations needed for Monte Carlo Simulation used in reliability analysis for tunnel supports using convergence – confinement method. Number if iterations needed will be calculated with two methods. In the first method, the analyst has to accept a distribution function for the performance function. The other method suggested by this article is to calculate number of iterations based on the convergence of the factor the analyst is interested in the calculation. Reliability analysis will be performed for the diversion tunnel in Rrëshen, Albania, by using both methods mentioned and results will be confronted
Rapid Monte Carlo simulation of detector DQE(f)
Energy Technology Data Exchange (ETDEWEB)
Star-Lack, Josh, E-mail: josh.starlack@varian.com; Sun, Mingshan; Abel, Eric [Varian Medical Systems, Palo Alto, California 94304-1030 (United States); Meyer, Andre; Morf, Daniel [Varian Medical Systems, CH-5405, Baden-Dattwil (Switzerland); Constantin, Dragos; Fahrig, Rebecca [Department of Radiology, Stanford University, Stanford, California 94305 (United States)
2014-03-15
Purpose: Performance optimization of indirect x-ray detectors requires proper characterization of both ionizing (gamma) and optical photon transport in a heterogeneous medium. As the tool of choice for modeling detector physics, Monte Carlo methods have failed to gain traction as a design utility, due mostly to excessive simulation times and a lack of convenient simulation packages. The most important figure-of-merit in assessing detector performance is the detective quantum efficiency (DQE), for which most of the computational burden has traditionally been associated with the determination of the noise power spectrum (NPS) from an ensemble of flood images, each conventionally having 10{sup 7} − 10{sup 9} detected gamma photons. In this work, the authors show that the idealized conditions inherent in a numerical simulation allow for a dramatic reduction in the number of gamma and optical photons required to accurately predict the NPS. Methods: The authors derived an expression for the mean squared error (MSE) of a simulated NPS when computed using the International Electrotechnical Commission-recommended technique based on taking the 2D Fourier transform of flood images. It is shown that the MSE is inversely proportional to the number of flood images, and is independent of the input fluence provided that the input fluence is above a minimal value that avoids biasing the estimate. The authors then propose to further lower the input fluence so that each event creates a point-spread function rather than a flood field. The authors use this finding as the foundation for a novel algorithm in which the characteristic MTF(f), NPS(f), and DQE(f) curves are simultaneously generated from the results of a single run. The authors also investigate lowering the number of optical photons used in a scintillator simulation to further increase efficiency. Simulation results are compared with measurements performed on a Varian AS1000 portal imager, and with a previously published
Kinetic Monte Carlo simulation of physical vapor deposition of thin Cu film
Institute of Scientific and Technical Information of China (English)
WANG Jun; CHEN Chang-qi; ZHU Wu
2004-01-01
A two-dimensional Kinetic Monte Carlo method has been developed for simulating the physical vapor deposition of thin Cu films on Cu substrate. An improved embedded atom method was used to calculate the interatomic potential and determine the diffusion barrier energy and residence time. Parameters, including incident angle,deposition rate and substrate temperature, were investigated and discussed in order to find their influences on the thin film morphology.
Monte Carlo Molecular Simulation with Isobaric-Isothermal and Gibbs-NPT Ensembles
Du, Shouhong
2012-05-01
This thesis presents Monte Carlo methods for simulations of phase behaviors of Lennard-Jones fluids. The isobaric-isothermal (NPT) ensemble and Gibbs-NPT ensemble are introduced in detail. NPT ensemble is employed to determine the phase diagram of pure component. The reduced simulation results are verified by comparison with the equation of state by by Johnson et al. and results with L-J parameters of methane agree considerably with the experiment measurements. We adopt the blocking method for variance estimation and error analysis of the simulation results. The relationship between variance and number of Monte Carlo cycles, error propagation and Random Number Generator performance are also investigated. We review the Gibbs-NPT ensemble employed for phase equilibrium of binary mixture. The phase equilibrium is achieved by performing three types of trial move: particle displacement, volume rearrangement and particle transfer. The simulation models and the simulation details are introduced. The simulation results of phase coexistence for methane and ethane are reported with comparison of the experimental data. Good agreement is found for a wide range of pressures. The contribution of this thesis work lies in the study of the error analysis with respect to the Monte Carlo cycles and number of particles in some interesting aspects.
Large-scale Monte Carlo simulations for the depinning transition in Ising-type lattice models
Si, Lisha; Liao, Xiaoyun; Zhou, Nengji
2016-12-01
With the developed "extended Monte Carlo" (EMC) algorithm, we have studied the depinning transition in Ising-type lattice models by extensive numerical simulations, taking the random-field Ising model with a driving field and the driven bond-diluted Ising model as examples. In comparison with the usual Monte Carlo method, the EMC algorithm exhibits greater efficiency of the simulations. Based on the short-time dynamic scaling form, both the transition field and critical exponents of the depinning transition are determined accurately via the large-scale simulations with the lattice size up to L = 8912, significantly refining the results in earlier literature. In the strong-disorder regime, a new universality class of the Ising-type lattice model is unveiled with the exponents β = 0.304(5) , ν = 1.32(3) , z = 1.12(1) , and ζ = 0.90(1) , quite different from that of the quenched Edwards-Wilkinson equation.
Quantum Monte Carlo simulations of bosons with complex interactions
Rousseau, Valery
2015-03-01
Many of the most exciting materials and phenomena being studied today, from oxide heterostructures to topological insulators or iron-based superconductors, are the ones in which an understanding of how quantum particles interact with each other is essential. In the last decade, the development and the improvement of quantum Monte Carlo algorithms combined with the increased power of computers has opened the way to the exact simulation of Hamiltonians that include various types of interactions, such as inter-species conversion terms or ring-exchange terms. Simultaneously, developments made in the field of optical lattices, laser cooling and magneto/optical trapping techniques have led to ideal realizations of such Hamiltonians. A wide variety of phases can be present, including Mott insulators and superfluids, as well as more exotic phases such as Haldane insulators, supersolids, counter-superfluids, or the recently proposed Feshbach insulator. These experimental realizations of the various forms of the Hubbard model can have interesting applications, in particular they provide a possible way of performing quantum computing, and have also given rise to a new field known as Atomtronics, the equivalent of Electronics where the carriers are replaced by atoms. I will illustrate these ideas with examples of Hamiltonians that have been studied and some results. In order to study these systems, it is crucial to identify the various phases that are present, which can be characterized by a set of order parameters. Of particular importance in this task is the superfluid density. It is well known that the superfluid density can be related to the response of the free energy to a boundary phase twist, or to the fluctuations of the winding number. However, these relationships break down when complex interactions are involved. To address this problem, I will propose a general expression of the superfluid density, derived from real and thought experiments. I will discuss two
Time-step limits for a Monte Carlo Compton-scattering method
Energy Technology Data Exchange (ETDEWEB)
Densmore, Jeffery D [Los Alamos National Laboratory; Warsa, James S [Los Alamos National Laboratory; Lowrie, Robert B [Los Alamos National Laboratory
2008-01-01
Compton scattering is an important aspect of radiative transfer in high energy density applications. In this process, the frequency and direction of a photon are altered by colliding with a free electron. The change in frequency of a scattered photon results in an energy exchange between the photon and target electron and energy coupling between radiation and matter. Canfield, Howard, and Liang have presented a Monte Carlo method for simulating Compton scattering that models the photon-electron collision kinematics exactly. However, implementing their technique in multiphysics problems that include the effects of radiation-matter energy coupling typically requires evaluating the material temperature at its beginning-of-time-step value. This explicit evaluation can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and present time-step limits that avoid instabilities and nonphysical oscillations by considering a spatially independent, purely scattering radiative-transfer problem. Examining a simplified problem is justified because it isolates the effects of Compton scattering, and existing Monte Carlo techniques can robustly model other physics (such as absorption, emission, sources, and photon streaming). Our analysis begins by simplifying the equations that are solved via Monte Carlo within each time step using the Fokker-Planck approximation. Next, we linearize these approximate equations about an equilibrium solution such that the resulting linearized equations describe perturbations about this equilibrium. We then solve these linearized equations over a time step and determine the corresponding eigenvalues, quantities that can predict the behavior of solutions generated by a Monte Carlo simulation as a function of time-step size and other physical parameters. With these results, we develop our time-step limits. This approach is similar to our recent investigation of time discretizations for the
Ficaro, Edward Patrick
The ^{252}Cf -source-driven noise analysis (CSDNA) requires the measurement of the cross power spectral density (CPSD) G_ {23}(omega), between a pair of neutron detectors (subscripts 2 and 3) located in or near the fissile assembly, and the CPSDs, G_{12}( omega) and G_{13}( omega), between the neutron detectors and an ionization chamber 1 containing ^{252}Cf also located in or near the fissile assembly. The key advantage of this method is that the subcriticality of the assembly can be obtained from the ratio of spectral densities,{G _sp{12}{*}(omega)G_ {13}(omega)over G_{11 }(omega)G_{23}(omega) },using a point kinetic model formulation which is independent of the detector's properties and a reference measurement. The multigroup, Monte Carlo code, KENO-NR, was developed to eliminate the dependence of the measurement on the point kinetic formulation. This code utilizes time dependent, analog neutron tracking to simulate the experimental method, in addition to the underlying nuclear physics, as closely as possible. From a direct comparison of simulated and measured data, the calculational model and cross sections are validated for the calculation, and KENO-NR can then be rerun to provide a distributed source k_ {eff} calculation. Depending on the fissile assembly, a few hours to a couple of days of computation time are needed for a typical simulation executed on a desktop workstation. In this work, KENO-NR demonstrated the ability to accurately estimate the measured ratio of spectral densities from experiments using capture detectors performed on uranium metal cylinders, a cylindrical tank filled with aqueous uranyl nitrate, and arrays of safe storage bottles filled with uranyl nitrate. Good agreement was also seen between simulated and measured values of the prompt neutron decay constant from the fitted CPSDs. Poor agreement was seen between simulated and measured results using composite ^6Li-glass-plastic scintillators at large subcriticalities for the tank of
Energy Technology Data Exchange (ETDEWEB)
Richet, Y
2006-12-15
Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)
Kinetic Monte Carlo and Cellular Particle Dynamics Simulations of Multicellular Systems
Flenner, Elijah; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan
2011-01-01
Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Computer simulations based on Metropolis Monte Carlo (MMC) algorithms were successful in explaining and predicting the resulting stationary structures (corresponding to the lowest adhesion energy state). Here we introduce two alternatives to the MMC approach for modeling cellular motion and self-assembly: (1) a kinetic Monte Carlo (KMC), and (2) a cellular particle dynamics (CPD) method. Unlike MMC, both KMC and CPD methods are capable of simulating the dynamics of the cellular system in real time. In the KMC approach a transition rate is associated with possible rearrangements of the cellular system, and the corresponding time evolution is expressed in terms of these rates. In the CPD approach cells are modeled as interacting cellular ...