Energy Technology Data Exchange (ETDEWEB)
Vieira, Jose Wilson
2004-07-15
The MAX phantom has been developed from existing segmented images of a male adult body, in order to achieve a representation as close as possible to the anatomical properties of the reference adult male specified by the ICRP. In computational dosimetry, MAX can simulate the geometry of a human body under exposure to ionizing radiations, internal or external, with the objective of calculating the equivalent dose in organs and tissues for occupational, medical or environmental purposes of the radiation protection. This study presents a methodology used to build a new computational exposure model MAX/EGS4: the geometric construction of the phantom; the development of the algorithm of one-directional, divergent, and isotropic radioactive sources; new methods for calculating the equivalent dose in the red bone marrow and in the skin, and the coupling of the MAX phantom with the EGS4 Monte Carlo code. Finally, some results of radiation protection, in the form of conversion coefficients between equivalent dose (or effective dose) and free air-kerma for external photon irradiation are presented and discussed. Comparing the results presented with similar data from other human phantoms it is possible to conclude that the coupling MAX/EGS4 is satisfactory for the calculation of the equivalent dose in radiation protection. (author)
Energy Technology Data Exchange (ETDEWEB)
Liu, J
2004-07-12
Significantly improved upon its predecessor PHOTON, STAC8 is a valuable analytic code for quick and conservative beamline shielding designs for synchrotron radiation (SR) facilities. To check the applicability, accuracy, and limitations of STAC8, studies were conducted to compare STAC8 and PHOTON results with calculations using the FLUKA and EGS4 Monte Carlo codes. Doses and spectra for scattered SR in a few beam-target-shield geometries were calculated, with and without photon linear polarization effects. Areas for expanding the STAC8 capabilities, e.g., features of the mirror-reflected lights and double-Compton light calculations, and use of monochromatic light, etc., have been identified. Some of these features have been implemented and benchmarked against Monte Carlo calculations. Reasonable agreements were found between the STAC8 and Monte Carlo calculations.
EGS4 in `94: A decade of enhancements
Energy Technology Data Exchange (ETDEWEB)
Nelson, W.R. [Stanford Univ., CA (United States); Bielajew, A.F.; Rogers, D.W.O. [National Research Council of Canada, Ottawa (Canada). Institute for National Measurement Standards; Hirayama, H. [National Lab. for High Energy Physics, Ibaraki-ken (Japan)
1994-08-18
This paper presents an overview of the developments made to the EGS4 code over the past decade. This code is a Monte Carlo code developed to study electron-photon transport properties. It is widely used, in particular in the medical physics field, it has been updated, expanded, benchmarked, and applied to a wide array of problems. The paper covers precursors to this code, a basic snapshop of its physics and calculation methods, and an overview of how it has been expanded during the past decade.
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
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 ...
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
Advanced Multilevel Monte Carlo Methods
Jasra, Ajay
2017-04-24
This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.
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, ...
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Markov Chain Monte Carlo Methods. 2. The Markov Chain Case. K B Athreya, Mohan Delampady and T Krishnan. K B Athreya is a Professor at. Cornell University. His research interests include mathematical analysis, probability theory and its application and statistics. He enjoys writing for Resonance. His spare time is ...
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Introduction. In parts 1 and 2 of this series it was shown how Markov chain Monte Carlo (MCMC) methods can be employed to obtain satisfactory approximations for integrals that are not easy to evaluate analytically. Such integrals arise routinely in statistical problems. Some of the statistical concepts that are relevant for the ...
EGS4 in '97: A decade of enhancements
Energy Technology Data Exchange (ETDEWEB)
Nelson, W.R. [Stanford Univ., CA (US). Stanford Linear Accelerator Center; Bielajew, A.F.; Rogers, D.W.O. [National Research Council of Canada, Ottawa, Ontario (Canada). Inst. for National Measurement Standards; Hirayama, H.; Namito, Y. [National Lab. for High Energy Physics, Tsukuba, Ibaraki (Japan)
1997-08-05
This report consists of vugraphs concerning the EGS4 code system. It begins with a brief history of EGS codes. Then a description of the EGS4 code system is given including: (1) how it is organized and the physics within it; (2) basic features of the code; and (3) mechanics of running the code. It concludes with a discussion on benchmarks.
Shell model Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Koonin, S.E. [California Inst. of Tech., Pasadena, CA (United States). W.K. Kellogg Radiation Lab.; Dean, D.J. [Oak Ridge National Lab., TN (United States)
1996-10-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of {gamma}-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs.
(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.
Advanced Computational Methods for Monte Carlo Calculations
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-12
This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Monte Carlo is a city in Monaco, famous for its casinos offering games of chance. Games of chance ex- hibit random behaviour, much like the random variables generated for the statistical simulation exercises. Early ideas of probability and simulation were developed in the context of gambling here and hence these simula-.
Hybrid Monte Carlo methods in computational finance
Leitao Rodriguez, A.
2017-01-01
Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the
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 ...
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...
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.
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
Monte Carlo methods for preference learning
DEFF Research Database (Denmark)
Viappiani, P.
2012-01-01
Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....
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
by means of FLUKA Monte Carlo method
Directory of Open Access Journals (Sweden)
Ermis Elif Ebru
2015-01-01
Full Text Available Calculations of gamma-ray mass attenuation coefficients of various detector materials (crystals were carried out by means of FLUKA Monte Carlo (MC method at different gamma-ray energies. NaI, PVT, GSO, GaAs and CdWO4 detector materials were chosen in the calculations. Calculated coefficients were also compared with the National Institute of Standards and Technology (NIST values. Obtained results through this method were highly in accordance with those of the NIST values. It was concluded from the study that FLUKA MC method can be an alternative way to calculate the gamma-ray mass attenuation coefficients of the detector materials.
The macro response Monte Carlo method for electron transport
Svatos, Michelle Marie
1998-10-01
This thesis proves the feasibility of basing depth dose calculations for electron radiotherapy on first- principles single scatter physics, in an amount of time that is comparable to or better than current electron Monte Carlo methods. The Macro Response Monte Carlo (MRMC) method achieves run times that have potential to be much faster than conventional electron transport methods such as condensed history. This is possible because MRMC is a Local-to- Global method, meaning the problem is broken down into two separate transport calculations. The first stage is a local, single scatter calculation, which generates probability distribution functions (PDFs) to describe the electron's energy, position and trajectory after leaving the local geometry, a small sphere or 'kugel'. A number of local kugel calculations were run for calcium and carbon, creating a library of kugel data sets over a range of incident energies (0.25 MeV-8 MeV) and sizes (0.025 cm to 0.1 cm in radius). The second transport stage is a global calculation, where steps that conform to the size of the kugels in the library are taken through the global geometry, which in this case is a CT (computed tomography) scan of a patient or phantom. For each step, the appropriate PDFs from the MRMC library are sampled to determine the electron's new energy, position and trajectory. The electron is immediately advanced to the end of the step and then chooses another kugel to sample, which continues until transport is completed. The MRMC global stepping code was benchmarked as a series of subroutines inside of the Peregrine Monte Carlo code against EGS4 and MCNP for depth dose in simple phantoms having density inhomogeneities. The energy deposition algorithms for spreading dose across 5-10 zones per kugel were tested. Most resulting depth dose calculations were within 2-3% of well-benchmarked codes, with one excursion to 4%. This thesis shows that the concept of using single scatter-based physics in clinical radiation
Methods for Monte Carlo simulations of biomacromolecules.
Vitalis, Andreas; Pappu, Rohit V
2009-01-01
The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.
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.
Accelerated Monte Carlo Methods for Coulomb Collisions
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
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)
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. ...
Approximating Sievert Integrals to Monte Carlo Methods to calculate ...
African Journals Online (AJOL)
Radiation dose rates along the transverse axis of a miniature P192PIr source were calculated using Sievert Integral (considered simple and inaccurate), and by the sophisticated and accurate Monte Carlo method. Using data obt-ained by the Monte Carlo method as benchmark and applying least squares regression curve ...
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
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 Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
Home; Journals; Journal of Earth System Science; Volume 126; Issue 7. A Monte Carlo adapted finite element method for dislocation ... However, geological features of a fault cannot be measured exactly, and therefore these features and data involve uncertainties. This paper presents a Monte Carlo based random model of ...
Quantum Monte Carlo method for attractive Coulomb potentials
Kole, J.S.; Raedt, H. De
2001-01-01
Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quantum Monte Carlo method that can handle singular attractive potentials. We illustrate the basic ideas of this quantum Monte Carlo algorithm by simulating the ground state of hydrogen and helium.
On the Markov Chain Monte Carlo (MCMC) method
Indian Academy of Sciences (India)
Abstract. 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.
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.
An EGS4 user code developed for design and optimization of gamma-ray detection systems
Oishi, T; Yoshida, M; Sugita, T
2003-01-01
An EGS4 user code is developed to design and optimize gamma-ray detection systems for various types of radiation sources. The code is fundamentally based on the PRESTA-CG, which is the user code introducing the PRESTA algorithm and a combinatorial geometry method. The additional and existing functions are integrated in the present code, and the handling is simplified. The latest techniques related to the calculation of material cross section are also incorporated in the code for the accurate simulation. The main additional functions are classified into two parts of the definition of radiation sources and the photon tracing. The former includes the functions on the simple handling of source geometry and the use of redefined radiation source. In the latter functions, it is possible to estimate the simultaneous events among plural detectors and the trace of photon in the interested regions. The developed user code is applied to detection systems in order to demonstrate its availability. As the result, it is foun...
Self-learning Monte Carlo method: Continuous-time algorithm
Nagai, Yuki; Shen, Huitao; Qi, Yang; Liu, Junwei; Fu, Liang
2017-10-01
The recently introduced self-learning Monte Carlo method is a general-purpose numerical method that speeds up Monte Carlo simulations by training an effective model to propose uncorrelated configurations in the Markov chain. We implement this method in the framework of a continuous-time Monte Carlo method with an auxiliary field in quantum impurity models. We introduce and train a diagram generating function (DGF) to model the probability distribution of auxiliary field configurations in continuous imaginary time, at all orders of diagrammatic expansion. By using DGF to propose global moves in configuration space, we show that the self-learning continuous-time Monte Carlo method can significantly reduce the computational complexity of the simulation.
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.)
Recommender engine for continuous-time quantum Monte Carlo methods
Huang, Li; Yang, Yi-feng; Wang, Lei
2017-03-01
Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.
Application of biasing techniques to the contributon Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Dubi, A.; Gerstl, S.A.W.
1980-01-01
Recently, a new Monte Carlo Method called the Contribution Monte Carlo Method was developed. The method is based on the theory of contributions, and uses a new receipe for estimating target responses by a volume integral over the contribution current. The analog features of the new method were discussed in previous publications. The application of some biasing methods to the new contribution scheme is examined here. A theoretical model is developed that enables an analytic prediction of the benefit to be expected when these biasing schemes are applied to both the contribution method and regular Monte Carlo. This model is verified by a variety of numerical experiments and is shown to yield satisfying results, especially for deep-penetration problems. Other considerations regarding the efficient use of the new method are also discussed, and remarks are made as to the application of other biasing methods. 14 figures, 1 tables.
Comparison of the Batho, ETAR and Monte Carlo dose calculation methods in CT based patient models.
du Plessis, F C; Willemse, C A; Lötter, M G; Goedhals, L
2001-04-01
This paper shows the contribution that Monte Carlo methods make in regard to dose distribution calculations in CT based patient models and the role it plays as a gold standard to evaluate other dose calculation algorithms. The EGS4 based BEAM code was used to construct a generic 8 MV accelerator to obtain a series of x-ray field sources. These were used in the EGS4 based DOSXYZ code to generate beam data in a mathematical water phantom to set up a beam model in a commercial treatment planning system (TPS), CADPLAN V.2.7.9. Dose distributions were calculated with the Batho and ETAR inhomogeneity correction algorithms in head/sinus, lung, and prostate patient models for 2 x 2, 5 x 5, and 10 X 10 cm2 open x-ray beams. Corresponding dose distributions were calculated with DOSXYZ that were used as a benchmark. The dose comparisons are expressed in terms of 2D isodose distributions, percentage depth dose data, and dose difference volume histograms (DDVH's). Results indicated that the Batho and ETAR methods contained inaccuracies of 20%-70% in the maxillary sinus region in the head model. Large lung inhomogeneities irradiated with small fields gave rise to absorbed dose deviations of 10%-20%. It is shown for a 10 x 10 cm2 field that DOSXYZ models lateral scatter in lung that is not present in the Batho and ETAR methods. The ETAR and Batho methods are accurate within 3% in a prostate model. We showed how the performance of these inhomogeneity correction methods can be understood in realistic patient models using validated Monte Carlo codes such as BEAM and DOSXYZ.
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.
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)
Monte Carlo methods of PageRank computation
Litvak, Nelli
2004-01-01
We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink
Monte Carlo Form-Finding Method for Tensegrity Structures
Li, Yue; Feng, Xi-Qiao; Cao, Yan-Ping
2010-05-01
In this paper, we propose a Monte Carlo-based approach to solve tensegrity form-finding problems. It uses a stochastic procedure to find the deterministic equilibrium configuration of a tensegrity structure. The suggested Monte Carlo form-finding (MCFF) method is highly efficient because it does not involve complicated matrix operations and symmetry analysis and it works for arbitrary initial configurations. Both regular and non-regular tensegrity problems of large scale can be solved. Some representative examples are presented to demonstrate the efficiency and accuracy of this versatile method.
Monte Carlo methods: Application to hydrogen gas and hard spheres
Dewing, Mark Douglas
2001-08-01
Quantum Monte Carlo (QMC) methods are among the most accurate for computing ground state properties of quantum systems. The two major types of QMC we use are Variational Monte Carlo (VMC), which evaluates integrals arising from the variational principle, and Diffusion Monte Carlo (DMC), which stochastically projects to the ground state from a trial wave function. These methods are applied to a system of boson hard spheres to get exact, infinite system size results for the ground state at several densities. The kinds of problems that can be simulated with Monte Carlo methods are expanded through the development of new algorithms for combining a QMC simulation with a classical Monte Carlo simulation, which we call Coupled Electronic-Ionic Monte Carlo (CEIMC). The new CEIMC method is applied to a system of molecular hydrogen at temperatures ranging from 2800K to 4500K and densities from 0.25 to 0.46 g/cm3. VMC requires optimizing a parameterized wave function to find the minimum energy. We examine several techniques for optimizing VMC wave functions, focusing on the ability to optimize parameters appearing in the Slater determinant. Classical Monte Carlo simulations use an empirical interatomic potential to compute equilibrium properties of various states of matter. The CEIMC method replaces the empirical potential with a QMC calculation of the electronic energy. This is similar in spirit to the Car-Parrinello technique, which uses Density Functional Theory for the electrons and molecular dynamics for the nuclei. The challenges in constructing an efficient CEIMC simulation center mostly around the noisy results generated from the QMC computations of the electronic energy. We introduce two complementary techniques, one for tolerating the noise and the other for reducing it. The penalty method modifies the Metropolis acceptance ratio to tolerate noise without introducing a bias in the simulation of the nuclei. For reducing the noise, we introduce the two-sided energy
A Semi-Analytic Monte Carlo Method for Optimization Problems
Sale, Kenneth E.
1997-10-01
Presently available Monte Carlo radiation transport codes require all aspects of a problem to be fixed so that optimizing a system involves running the code multiple times, once for each alternative value of the parameters that characterize the system (e.g. thickness or shape of an attenuator). By combining the standard Monte Carlo(Lux, Ivan and Koblinger, Laszlo, Monte Carlo Particle Transport Methods: Neutron and Photon Calculations, CRC Press, 1991) algorithm with the Next-Event point flux estimator and a computer algebra system it is possible to calculate the flux at a point as a function of parameters describing the problem rather as a single number for one specific set of parameter values. The calculated flux function is a perturbative estimate about the default values of the problem parameters. Parametric descriptions can be used in the geometry or material specifications. Several examples will be presented.
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.
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.
The Smoothed Monte Carlo Method in Robustness Optimization
Hendrix, E.M.T.; Olieman, N.J.
2008-01-01
The concept of robustness as the probability mass of a design-dependent set has been introduced in the literature. Optimization of robustness can be seen as finding the design that has the highest robustness. The reference method for estimating the robustness is the Monte Carlo (MC) simulation, and
Bayesian methods, maximum entropy, and quantum Monte Carlo
Energy Technology Data Exchange (ETDEWEB)
Gubernatis, J.E.; Silver, R.N. (Los Alamos National Lab., NM (United States)); Jarrell, M. (Cincinnati Univ., OH (United States))
1991-01-01
We heuristically discuss the application of the method of maximum entropy to the extraction of dynamical information from imaginary-time, quantum Monte Carlo data. The discussion emphasizes the utility of a Bayesian approach to statistical inference and the importance of statistically well-characterized data. 14 refs.
Influence of breast characteristics in myocardial scintigraphy through the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Oliveira, Anderson; Meguerian, Berdj Aram; Mesquita, Claudio Tinoco, E-mail: anderol@oi.com.b, E-mail: anderson@cnen.gov.b [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil); Hospital Pro-Cardiaco, Rio de Janeiro, RJ (Brazil); Instituto Nacional do Cancer (INCA), Rio de Janeiro, RJ (Brazil); Universidade Federal Fluminense (UFF), Niteroi, RJ (Brazil); Universidade Gama Filho (UGF), Rio de Janeiro, RJ (Brazil)
2011-01-15
Background: by reducing the specificity associated with loss of information, the influence of attenuation of the breasts is very important in myocardial perfusion studies. However, although several studies have been conducted over the past years, little has been developed to determine accurately the influence of the characteristics of the breasts on the quality of myocardial scintigraphy, avoiding additional exposure to radiation. Objective: the purpose of this study is to quantify the attenuation of photons by the breasts, in myocardial perfusion studies with {sup 99m}Tc according to different sizes and compositions. Methods: each breast was assumed to be a cube composed of fibroglandular and adipose tissue. The data related to {sup 99m}Tc photons were analyzed in a Monte Carlo model. We varied the thickness and composition of breasts and analyzed the interference in attenuation. The EGS 4 software was used in the simulations. Results: setting the thickness of a breast, the variation of its composition causes a maximum increase of 2.3% in the number of photons attenuated. By contrast, maintaining a fixed composition of breast tissue, the difference in photon attenuation was 45.0%, averaging 6.0% for each additional centimeter in the breast thickness. Conclusion: Monte Carlo simulation showed that the influence of the thickness of the breasts in the attenuation of photons in myocardial scintigraphy with {sup 99m}Tc is much greater than the influence of their compositions. (author)
New format for storage of voxel phantom, and exposure computer model EGS4/MAX to EGSnrc/MASH update
Energy Technology Data Exchange (ETDEWEB)
Leal Neto, Viriato [Departamento de Energia Nuclear (DEN). Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil); Instituto Federal de Educacao, Ciencia e Tecnologia de Pernambuco. Recife, PE (Brazil); Vieira, Jose W. [Escola Politecnica de Pernambuco. UPE, Recife, PE (Brazil); Lima, Fernando R.A., E-mail: falima@cnen.gov.br [Centro Regional de Ciencias Nucleares (CRCN/NE-CNEN-PE), Recife, PE (Brazil); Lima, Lindeval F., E-mail: lindeval@dmat.ufrr.br [Departamento de Matematica. Universidade Federal de Roraima (UFRR), Boa Vista, RR (Brazil)
2011-07-01
In order to estimate the dosage absorbed by those subjected to ionizing radiation, it is necessary to perform simulations using the exposure computational model (ECM). Such models are consists essentially of an anthropomorphic phantom and a Monte Carlo code (MC). The conjunction of a voxel phantom of the MC code is a complex process and often results in solving a specific problem. This is partly due to the way the phantom voxel is stored on a computer. It is usually required a substantial amount of space to store a static representation of the human body and also a significant amount of memory for reading and processing a given simulation. This paper presents a new way to store data concerning the geometry irradiated (similar to the technique of repeated structures used in the geometry of MCNP code), reducing by 52% the disk space required for storage when compared to the previous format applied by Grupo de Dosimetria Numerica (GDN/CNPq). On the other hand, research in numerical dosimetry leads to a constant improvement on the resolution of voxel phantoms leading thus to a new requirement, namely, to develop new estimates of dose. Therefore, this work also performs an update of the MAX (Male Adult voXel)/EGS4 ECM for the MASH (Adult MaleMeSH)/EGSnrc ECM and presents instances of dosimetric evaluations using the new ECM. Besides the update of the phantom and the MC code, the algorithm of the source used has also been improved in contrast to previous publications. (author)
Energy Technology Data Exchange (ETDEWEB)
Demirkaya, Gokmen [Department of Mechanical Engineering, Middle East Technical University, Inonu Bulvari, 06531 Ankara (Turkey); Arinc, Faruk [Department of Mechanical Engineering, Middle East Technical University, Inonu Bulvari, 06531 Ankara (Turkey); Selcuk, Nevin [Department of Chemical Engineering, Middle East Technical University, Inonu Bulvari, 06531 Ankara (Turkey)]. E-mail: selcuk@metu.edu.tr; Ayranci, Isil [Department of Chemical Engineering, Middle East Technical University, Inonu Bulvari, 06531 Ankara (Turkey)
2005-06-15
Monte Carlo method was used to predict the incident radiative heat fluxes on the freeboard walls of the METU 0.3 MW{sub t} atmospheric bubbling fluidized bed combustor based on the data reported previously. The freeboard was treated as a rectangular enclosure with gray interior walls and gray, absorbing, emitting and isotropically scattering medium. A Monte Carlo solver was developed and the performance of the solver was assessed by comparing its predictions with those of method of lines solution of discrete ordinates method and experimental measurements reported previously. Parametric studies were carried out to examine the effects of particle load and anisotropic scattering on the predicted incident radiative heat fluxes. The comparisons show that Monte Carlo method reproduces the measured incident radiative heat fluxes reasonably well for the freeboard problem.
Projector Quantum Monte Carlo Method for Nonlinear Wave Functions
Schwarz, Lauretta R.; Alavi, A.; Booth, George H.
2017-04-01
We reformulate the projected imaginary-time evolution of the full configuration interaction quantum Monte Carlo method in terms of a Lagrangian minimization. This naturally leads to the admission of polynomial complex wave function parametrizations, circumventing the exponential scaling of the approach. While previously these functions have traditionally inhabited the domain of variational Monte Carlo approaches, we consider recent developments for the identification of deep-learning neural networks to optimize this Lagrangian, which can be written as a modification of the propagator for the wave function dynamics. We demonstrate this approach with a form of tensor network state, and use it to find solutions to the strongly correlated Hubbard model, as well as its application to a fully periodic ab initio graphene sheet. The number of variables which can be simultaneously optimized greatly exceeds alternative formulations of variational Monte Carlo methods, allowing for systematic improvability of the wave function flexibility towards exactness for a number of different forms, while blurring the line between traditional variational and projector quantum Monte Carlo approaches.
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.
An EGS4 user code with voxel geometry and a voxel phantom generation system
Energy Technology Data Exchange (ETDEWEB)
Funabiki, J.; Terabe, M. [Mitsubishi Research Institute, Inc., Tokyo (Japan); Zankl, M. [GSF, Neuherberg, Oberschleissheim (Germany); Koga, S. [Fujita Health Univ., Toyoake, Aichi (Japan); Saito, K. [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
2000-12-01
An EGS4 (Electron Gamma Shower Version 4) user code with voxel geometry (the UCPIXEL code) has been developed in order to make accurate dose evaluation by using human voxel phantoms. The voxel data have a format devised by GSF. This format can compress so large amount of high-resolution voxel data that required memory for computation is greatly reduced. UCPIXEL can treat 8 basic irradiation geometries (AP, PA, RLAT, LLAT, ROT, ISO, AB, BA) and cylindrical pseudo-environmental radiation source with arbitrary size, energy and directional distribution. In addition, UCPIXEL can model contaminated soil with arbitrary area and depth under a phantom and radiation from the soil. By using a post-processor, effective dose equivalent, effective dose and organ doses can be evaluated from the output of UCPIXEL. Preliminary results of effective dose calculated by using UCPIXEL for a Japanese voxel phantom are demonstrated and compared with the previous results for MIRD-type phantoms. We have also developed an intelligent system which automatically constructs a voxel phantom from CT data. We introduce this system and preliminary results are shown. (author)
Calculations of the giant-dipole-resonance photoneutrons using a coupled EGS4-morse code
Energy Technology Data Exchange (ETDEWEB)
Liu, J.C.; Nelson, W.R.; Kase, K.R.; Mao, X.S.
1995-10-01
The production and transport of the photoneutrons from the giant-dipoleresonance reaction have been implemented in a coupled EGS4-MORSE code. The total neutron yield (including both the direct neutron and evaporation neutron components) is calculated by folding the photoneutron yield cross sections with the photon track length distribution in the target. Empirical algorithms based on the measurements have been developed to estimate the fraction and energy of the direct neutron component for each photon. The statistical theory in the EVAP4 code, incorporated as a MORSE subroutine, is used to determine the energies of the evaporation neutrons. These represent major improvements over other calculations that assumed no direct neutrons, a constant fraction of direct neutrons, monoenergetic direct neutron, or a constant nuclear temperature for the evaporation neutrons. It was also assumed that the slow neutrons (< 2.5 MeV) are emitted isotropically and the fast neutrons are emitted anisotropically in the form of 1+Csin{sup 2}{theta}, which have a peak emission at 900. Comparisons between the calculated and the measured photoneutron results (spectra of the direct, evaporation and total neutrons; nuclear temperatures; direct neutron fractions) for materials of lead, tungsten, tantalum and copper have been made. The results show that the empirical algorithms, albeit simple, can produce reasonable results over the interested photon energy range.
Khrushcheva, O; Malerba, L; Becquart, C S; Domain, C; Hou, M
2003-01-01
Several variants are possible in the suite of programs forming multiscale predictive tools to estimate the yield strength increase caused by irradiation in RPV steels. For instance, at the atomic scale, both the Metropolis and the lattice kinetic Monte Carlo methods (MMC and LKMC respectively) allow predicting copper precipitation under irradiation conditions. Since these methods are based on different physical models, the present contribution discusses their consistency on the basis of a realistic case study. A cascade debris in iron containing 0.2% of copper was modelled by molecular dynamics with the DYMOKA code, which is part of the REVE suite. We use this debris as input for both the MMC and the LKMC simulations. Thermal motion and lattice relaxation can be avoided in the MMC, making the model closer to the LKMC (LMMC method). The predictions and the complementarity of the three methods for modelling the same phenomenon are then discussed.
Application to radiation damage simulation calculation of Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Aruga, Takeo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
2001-01-01
Recent progress in Monte Carlo calculation for radiation damage simulation of structural materials to be used in fast breeder reactors or thermonuclear fusion reactors under energetic neutron or charged particle bombardment is reviewed. Specifically usefulness of employing Monte Carlo methods in molecular dynamics calculations to understand mechanical properties change such as dimensional change, strength, creep, fatigue, corrosion, and crack growth of materials under irradiation on the basis of atomic collision processes is stressed. Structure and spatial distribution of point defects in iron, gold, or cooper as demonstrative examples at several hundreds of ps after the movement of primary knock-on atom (PKA) takes place are calculated as a function of PKA energy. The results are compared with those obtained by the method developed by Norgett, Robinson and Torrens and the usefulness is discussed. (S. Ohno)
Distributional monte carlo methods for the boltzmann equation
Schrock, Christopher R.
Stochastic particle methods (SPMs) for the Boltzmann equation, such as the Direct Simulation Monte Carlo (DSMC) technique, have gained popularity for the prediction of flows in which the assumptions behind the continuum equations of fluid mechanics break down; however, there are still a number of issues that make SPMs computationally challenging for practical use. In traditional SPMs, simulated particles may possess only a single velocity vector, even though they may represent an extremely large collection of actual particles. This limits the method to converge only in law to the Boltzmann solution. This document details the development of new SPMs that allow the velocity of each simulated particle to be distributed. This approach has been termed Distributional Monte Carlo (DMC). A technique is described which applies kernel density estimation to Nanbu's DSMC algorithm. It is then proven that the method converges not just in law, but also in solution for Linfinity(R 3) solutions of the space homogeneous Boltzmann equation. This provides for direct evaluation of the velocity density function. The derivation of a general Distributional Monte Carlo method is given which treats collision interactions between simulated particles as a relaxation problem. The framework is proven to converge in law to the solution of the space homogeneous Boltzmann equation, as well as in solution for Linfinity(R3) solutions. An approach based on the BGK simplification is presented which computes collision outcomes deterministically. Each technique is applied to the well-studied Bobylev-Krook-Wu solution as a numerical test case. Accuracy and variance of the solutions are examined as functions of various simulation parameters. Significantly improved accuracy and reduced variance are observed in the normalized moments for the Distributional Monte Carlo technique employing discrete BGK collision modeling.
Advanced Markov chain Monte Carlo methods learning from past samples
Liang, Faming; Carrol, Raymond J
2010-01-01
This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem have been developed include, the modified Gibbs sampler, the methods based on auxiliary variables and the methods making use of past samples. The focus of this book is on the algorithms that make use of past samples. This book includes the multicanonical algorithm, dynamic weighting, dynamically weight
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.
Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods
Ralph, Jason F.; Maskell, Simon; Jacobs, Kurt
2017-11-01
This paper proposes an efficient method for the simultaneous estimation of the state of a quantum system and the classical parameters that govern its evolution. This hybrid approach benefits from efficient numerical methods for the integration of stochastic master equations for the quantum system, and efficient parameter estimation methods from classical signal processing. The classical techniques use sequential Monte Carlo (SMC) methods, which aim to optimize the selection of points within the parameter space, conditioned by the measurement data obtained. We illustrate these methods using a specific example, an SMC sampler applied to a nonlinear system, the Duffing oscillator, where the evolution of the quantum state of the oscillator and three Hamiltonian parameters are estimated simultaneously.
Tally efficiency analysis for Monte Carlo Wielandt method
Energy Technology Data Exchange (ETDEWEB)
Shim, Hyung Jin, E-mail: shimhj@kaeri.re.k [Korea Atomic Energy Research Institute, 1045 Daedeokdaero, Yuseong-gu, Daejeon 305-353 (Korea, Republic of); Kim, Chang Hyo [Seoul National University, 599 Gwanakro, Gwanak-gu, Seoul 151-742 (Korea, Republic of)
2009-11-15
The Monte Carlo Wielandt method has the potential to eliminate most of a variance bias because it can reduce the dominance ratio by properly controlling the estimated eigenvalue (k{sub e}). However, it requires increasingly more computation time to simulate additional fission neutrons as the estimated eigenvalue becomes closer to the effective multiplication factor (k{sub eff}). Therefore, its advantage over the conventional Monte Carlo (MC) power method in the calculation efficiency may not always be ensured. Its efficiency of the tally estimation needs to be assessed in terms of a figure of merit based on a real variance as a function of k{sub e}. In this paper, the real variance is estimated by using an inter-cycle correlation of the fission source distribution for the MC Wielandt calculations. Then, the tally efficiency of the MC Wielandt method is analyzed for a 2 x 2 fission matrix system and weakly coupled fissile array problems with different dominance ratios (DRs). It is shown that the tally efficiency of the MC Wielandt method depends strongly on k{sub e}, there is a k{sub e} value resulting in the best efficiency for a problem with a large DR, and the efficiency curve as a function of L, the average number of fission neutrons per history, follows a long tail after the best efficiency.
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.
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
Radiative heat transfer by the Monte Carlo method
Hartnett †, James P; Cho, Young I; Greene, George A; Taniguchi, Hiroshi; Yang, Wen-Jei; Kudo, Kazuhiko
1995-01-01
This book presents the basic principles and applications of radiative heat transfer used in energy, space, and geo-environmental engineering, and can serve as a reference book for engineers and scientists in researchand development. A PC disk containing software for numerical analyses by the Monte Carlo method is included to provide hands-on practice in analyzing actual radiative heat transfer problems.Advances in Heat Transfer is designed to fill the information gap between regularly scheduled journals and university level textbooks by providing in-depth review articles over a broader scope than journals or texts usually allow.Key Features* Offers solution methods for integro-differential formulation to help avoid difficulties* Includes a computer disk for numerical analyses by PC* Discusses energy absorption by gas and scattering effects by particles* Treats non-gray radiative gases* Provides example problems for direct applications in energy, space, and geo-environmental engineering
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 1025 or 1026 members. A simulation step changes the characteristics for just a few of these members; a probability will therefore shift by a quantity of 1/1025. Such a change cannot be accounted for within a simulation, because then the simulation should have then a number of at least 1028 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.
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.
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...
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
The present paper considers the sequential decision optimization problem. This is an important class of decision problems in engineering. Important examples include decision problems on the quality control of manufactured products and engineering components, timing of the implementation of climate...... 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...... is proposed by Longstaff and Schwartz (2001) for pricing of American options. The present paper formulates the decision problem in a more general manner and explains how the solution scheme proposed by Anders and Nishijima (2011) is implemented for the optimization of the formulated decision problem...
Underwater Optical Wireless Channel Modeling Using Monte-Carlo Method
Saini, P. Sri; Prince, Shanthi
2011-10-01
At present, there is a lot of interest in the functioning of the marine environment. Unmanned or Autonomous Underwater Vehicles (UUVs or AUVs) are used in the exploration of the underwater resources, pollution monitoring, disaster prevention etc. Underwater, where radio waves do not propagate, acoustic communication is being used. But, underwater communication is moving towards Optical Communication which has higher bandwidth when compared to Acoustic Communication but has shorter range comparatively. Underwater Optical Wireless Communication (OWC) is mainly affected by the absorption and scattering of the optical signal. In coastal waters, both inherent and apparent optical properties (IOPs and AOPs) are influenced by a wide array of physical, biological and chemical processes leading to optical variability. The scattering effect has two effects: the attenuation of the signal and the Inter-Symbol Interference (ISI) of the signal. However, the Inter-Symbol Interference is ignored in the present paper. Therefore, in order to have an efficient underwater OWC link it is necessary to model the channel efficiently. In this paper, the underwater optical channel is modeled using Monte-Carlo method. The Monte Carlo approach provides the most general and most flexible technique for numerically solving the equations of Radiative transfer. The attenuation co-efficient of the light signal is studied as a function of the absorption (a) and scattering (b) coefficients. It has been observed that for pure sea water and for less chlorophyll conditions blue wavelength is less absorbed whereas for chlorophyll rich environment red wavelength signal is absorbed less comparative to blue and green wavelength.
Crop canopy BRDF simulation and analysis using Monte Carlo method
Huang, J.; Wu, B.; Tian, Y.; Zeng, Y.
2006-01-01
This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and
Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael
2017-01-01
The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…
Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters
Energy Technology Data Exchange (ETDEWEB)
Owen, R.K.
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Quantum Monte Carlo methods and lithium cluster properties
Energy Technology Data Exchange (ETDEWEB)
Owen, Richard Kent [Univ. of California, Berkeley, CA (United States)
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) [0.1981], 0.1895(9) [0.1874(4)], 0.1530(34) [0.1599(73)], 0.1664(37) [0.1724(110)], 0.1613(43) [0.1675(110)] Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) [0.0203(12)], 0.0188(10) [0.0220(21)], 0.0247(8) [0.0310(12)], 0.0253(8) [0.0351(8)] Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Latent uncertainties of the precalculated track Monte Carlo method.
Renaud, Marc-André; Roberge, David; Seuntjens, Jan
2015-01-01
While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Particle tracks were pregenerated for electrons and protons using EGSnrc and geant4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (cuda) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a "ground truth" benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of Dmax. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the maximum dose. In proton
Energy Technology Data Exchange (ETDEWEB)
Scherer, J.; Bogner, L.; Herbst, M. [Univ. Regensburg (Germany). Klinik und Poliklinik fuer Strahlentherapie und Radioonkologie; Paretzke, H.G.; Petoussi-Henss, N.; Zankl, M. [Gesellschaft fuer Strahlen- und Umweltforschung mbH Muenchen, Neuherberg (Germany). Inst. fuer Strahlenschutz
1998-12-31
Even with state of the art treatment planning systems the photon dose calculation can be erroneous under certain circumstances. In these cases Monte Carlo methods promise a higher accuracy. We have used the photon transport code CHILD of the GSF-Forschungszentrum, which was developed to calculate dose in diagnostic radiation protection matters. The code was refined for application in radiotherapy for high energy photon irradiation and should serve for dose verification in individual cases. The irradiation phantom can be entered as any desired 3D matrix or be generated automatically from an individual CT database. The particle transport takes into account pair production, photo, and Compton effect with certain approximations. Efficiency is increased by the method of `fractional photons`. The generated secondary electrons are followed by the unscattered continuous-slowing-down-approximation (CSDA). The developed Monte Carlo code Monaco Matrix was tested with simple homogeneous and heterogeneous phantoms through comparisons with simulations of the well known but slower EGS4 code. The use of a point source with a direction independent energy spectrum as simplest model of the radiation field from the accelerator head is shown to be sufficient for simulation of actual accelerator depth dose curves. Good agreement (<2%) was found for depth dose curves in water and in bone. With complex test phantoms and comparisons with EGS4 calculated dose profiles some drawbacks in the code were found. Thus, the implementation of the electron multiple-scattering should lead us to step by step improvement of the algorithm. (orig.) [Deutsch] Die Photonendosisberechnung kann auch mit modernen Planungssystemen unter gewissen Umstaenden mit Fehlern behaftet sein. Dagegen verspricht man sich von Monte-Carlo-Verfahren eine hoehere Genauigkeit. Wir haben den im GSF-Forschungszentrum fuer diagnostische Strahlenschutzberechnungen entwickelten Photonentransport-Code CHILD zur Anwendung bei
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...
Evaluation of measurement uncertainty and its numerical calculation by a Monte Carlo method
Wübbeler, Gerd; Krystek, Michael; Elster, Clemens
2008-08-01
The Guide to the Expression of Uncertainty in Measurement (GUM) is the de facto standard for the evaluation of measurement uncertainty in metrology. Recently, evaluation of measurement uncertainty has been proposed on the basis of probability density functions (PDFs) using a Monte Carlo method. The relation between this PDF approach and the standard method described in the GUM is outlined. The Monte Carlo method required for the numerical calculation of the PDF approach is described and illustrated by its application to two examples. The results obtained by the Monte Carlo method for the two examples are compared to the corresponding results when applying the GUM.
Diamantis, Nikolaos G; Manousakis, Efstratios
2013-10-01
The diagrammatic Monte Carlo (DiagMC) method is a numerical technique which samples the entire diagrammatic series of the Green's function in quantum many-body systems. In this work, we incorporate the flat histogram principle in the diagrammatic Monte Carlo method, and we term the improved version the "flat histogram diagrammatic Monte Carlo" method. We demonstrate the superiority of this method over the standard DiagMC in extracting the long-imaginary-time behavior of the Green's function, without incorporating any a priori knowledge about this function, by applying the technique to the polaron problem.
Energy Technology Data Exchange (ETDEWEB)
Perfetti, Christopher M [ORNL; Rearden, Bradley T [ORNL
2014-01-01
This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.
EGS4 and MCNP4b MC Simulation of a Siemens KD2 Accelerator in 6 MV Photon Mode
Chaves, A; Fragoso, M; Lopes, C; Oliveira, C; Peralta, L; Rodrigues, P; Seco, J; Trindade, A
2001-01-01
The geometry of a Siemens Mevatron KD2 linear accelerator in 6 MV photon mode was modeled with EGS4 and MCNP4b. Energy spectra and other phase space distributions have been extensively compared in different plans along the beam line. The differences found have been evaluated both qualitative and quantitatively. The final aim was that both codes, running in different operating systems and with a common set of simulation conditions, met the requirement of fitting the experimental depth dose curves and dose profiles, measured in water for different field sizes. Whereas depth dose calculations are in a certain extent insensible to some simulation parameters like electron nominal energy, dose profiles have revealed to be a much better indicator to appreciate that feature. Fine energy tuning has been tried and the best fit was obtained for a nominal electron energy of 6.15 MeV.
DEVELOPMENT OF INTELLIGENT SYSTEM FOR SOLVING OF IN INDUSTRIAL POLICY BY MONTE CARLO METHOD
Taisiya N. Mironenko; Ekaterina I. Bragina
2014-01-01
The article considers one of the prioritiesin the ﬁeld of artiﬁcial intelligence - Markovchains. The problem of forecasting the strategic investment directions in industrial policy by using a Monte Carlo method issolved.
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA
Directory of Open Access Journals (Sweden)
SEUNG WOOK LEE
2014-08-01
Full Text Available An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks’ formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks’ formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks’ first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks’ formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.
Directory of Open Access Journals (Sweden)
José Luiz Ferreira Martins
2011-09-01
Full Text Available O objetivo deste artigo é o de analisar a viabilidade da utilização do método de Monte Carlo para estimar a produtividade na soldagem de tubulações industriais de aço carbono com base em amostras pequenas. O estudo foi realizado através de uma análise de uma amostra de referência contendo dados de produtividade de 160 juntas soldadas pelo processo Eletrodo Revestido na REDUC (refinaria de Duque de Caxias, utilizando o software ControlTub 5.3. A partir desses dados foram retiradas de forma aleatória, amostras com, respectivamente, 10, 15 e 20 elementos e executadas simulações pelo método de Monte Carlo. Comparando-se os resultados da amostra com 160 elementos e os dados gerados por simulação se observa que bons resultados podem ser obtidos usando o método de Monte Carlo para estimativa da produtividade da soldagem. Por outro lado, na indústria da construção brasileira o valor da média de produtividade é normalmente usado como um indicador de produtividade e é baseado em dados históricos de outros projetos coletados e avaliados somente após a conclusão do projeto, o que é uma limitação. Este artigo apresenta uma ferramenta para avaliação da execução em tempo real, permitindo ajustes nas estimativas e monitoramento de produtividade durante o empreendimento. Da mesma forma, em licitações, orçamentos e estimativas de prazo, a utilização desta técnica permite a adoção de outras estimativas diferentes da produtividade média, que é comumente usada e como alternativa, se sugerem três critérios: produtividade otimista, média e pessimista.The aim of this article is to analyze the feasibility of using Monte Carlo method to estimate productivity in industrial pipes welding of carbon steel based on small samples. The study was carried out through an analysis of a reference sample containing productivity data of 160 welded joints by SMAW process in REDUC (Duque de Caxias Refinery, using ControlTub 5.3 software
Development of a Monte-Carlo based method for calculating the effect of stationary fluctuations
DEFF Research Database (Denmark)
Pettersen, E. E.; Demazire, C.; Jareteg, K.
2015-01-01
that corresponds to the real part of the neutron balance, and one that corresponds to the imaginary part. The two equivalent problems are in nature similar to two subcritical systems driven by external neutron sources, and can thus be treated as such in a Monte Carlo framework. The definition of these two...... of light water reactor conditions in an infinite lattice of fuel pins surrounded by water. The test case highlights flux gradients that are steeper in the Monte Carlo-based transport solution than in the diffusion-based solution. Compared to other Monte Carlo-based methods earlier proposed for carrying out...
A Monte Carlo Method for Low Pressure Radio Frequency Discharges
Directory of Open Access Journals (Sweden)
Lahouaria Settaouti
2003-06-01
Full Text Available There is increasing interest in glow discharges because of their importance to a large number of application fields, like the microelectronics industry, flat plasma display panel technology, the laser and light industry and analytical spectrochemistry. To improve the capabilities of rf glow discharges, a good understanding of the discharge physics is highly desirable. The typical calculated results include the radio frequency (rf voltage, the electrical field distribution, the density of argon ions and electrons, the electron energy distribution function and information about the collision processes of the electrons with the Monte Carlo model. These results are presented throughout the discharge axis and as a function of time in the rf cycle. Moreover, we have investigated how many rf cycles have to be followed before a periodic steady state is reached.
Bayesian Monte Carlo method for monotonic models applying the Generalized Beta distribution
Rajabali Nejad, Mohammadreza; Demirbilek, Z.
2011-01-01
A novel Bayesian Monte Carlo method for monotonic models (BMCM) is described in this paper. The BMCM method enjoys the advantages of the recently developed method of Dynamic Bounds [1] for the reliability assessment of monotonic models, and incorporates weighted logical dependence between
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.
Multivariate Monte Carlo Methods for the Reflection Grating Spectrometers on XMM-Newton
Energy Technology Data Exchange (ETDEWEB)
Peterson, J.
2004-11-10
We propose a novel multivariate Monte Carlo method as an efficient and flexible approach to analyzing extended X-ray sources with the Reflection Grating Spectrometer (RGS) on XMM Newton. A multi-dimensional interpolation method is used to efficiently calculate the response function for the RGS in conjunction with an arbitrary spatially-varying spectral model. Several methods of event comparison that effectively compare the multivariate RGS data are discussed. The use of a multi-dimensional instrument Monte Carlo also creates many opportunities for the use of complex astrophysical Monte Carlo calculations in diffuse X-ray spectroscopy. The methods presented here could be generalized to other X-ray instruments as well.
Monte Carlo methods for pricing ﬁnancial options
Indian Academy of Sciences (India)
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.
Self-learning quantum Monte Carlo method in interacting fermion systems
Xu, Xiao Yan; Qi, Yang; Liu, Junwei; Fu, Liang; Meng, Zi Yang
2017-07-01
The self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally reduce the computational complexity and moreover can greatly suppress the autocorrelation time near a critical point. This enables us to simulate an interacting fermion system on a 100 ×100 lattice even at the critical point and obtain critical exponents with high precision.
New simpler method of matching NLO corrections with parton shower Monte Carlo
Jadach, Stanislaw; Sapeta, Sebastian; Siodmok, Andrzej Konrad; Skrzypek, Maciej
2016-01-01
Next steps in development of the KrkNLO method of implementing NLO QCD corrections to hard processes in parton shower Monte Carlo programs are presented. This new method is a simpler alternative to other well-known approaches, such as MC@NLO and POWHEG. The KrkNLO method owns its simplicity to the use of parton distribution functions (PDFs) in a new, so-called Monte Carlo (MC), factorization scheme which was recently fully defined for the first time. Preliminary numerical results for the Higgs-boson production process are also presented.
Methods of Monte Carlo electron transport in particle-in-cell codes
Energy Technology Data Exchange (ETDEWEB)
Kwan, T.J.T.; Snell, C.M.
1985-01-01
An algorithm has been implemented in CCUBE and ISIS to treat electron transport in materials using a Monte Carlo method in addition to the electron dynamics determined by the self-consistent electromagnetic, relativistic, particle-in-cell simulation codes that have been used extensively to model generation of electron beams and intense microwave production. Incorporation of a Monte Carlo method to model the transport of electrons in materials (conductors and dielectrics) in a particle-in-cell code represents a giant step toward realistic simulation of the physics of charged-particle beams. The basic Monte Carlo method used in the implementation includes both scattering of electrons by background atoms and energy degradation.
Metric conjoint segmentation methods : A Monte Carlo comparison
Vriens, M; Wedel, M; Wilms, T
The authors compare nine metric conjoint segmentation methods. Four methods concern two-stage procedures in which the estimation of conjoint models and the partitioning of the sample are performed separately; in five, the estimation and segmentation stages are integrated. The methods are compared
Comparison of the Monte Carlo adjoint-weighted and differential operator perturbation methods
Energy Technology Data Exchange (ETDEWEB)
Kiedrowski, Brian C [Los Alamos National Laboratory; Brown, Forrest B [Los Alamos National Laboratory
2010-01-01
Two perturbation theory methodologies are implemented for k-eigenvalue calculations in the continuous-energy Monte Carlo code, MCNP6. A comparison of the accuracy of these techniques, the differential operator and adjoint-weighted methods, is performed numerically and analytically. Typically, the adjoint-weighted method shows better performance over a larger range; however, there are exceptions.
Markov chain Monte Carlo methods in directed graphical models
DEFF Research Database (Denmark)
Højbjerre, Malene
have primarily been based on a Bayesian paradigm, i.e. prior information on the parameters is a prerequisite, but questions about undesirable side effects from the priors are raised. We present a method, based on MCMC methods, that approximates profile log-likelihood functions in directed graphical...... with-in person and with-in family dependences. In the second study we compare four different screening methods for cervical cancer. The methods have been performed on a number of women, and the data possess a complicated dependence structure due to the replicate test results for the same woman. We...
Speed-Up of the Monte Carlo Method by Using a Physical Model of the Dempster-Shafer Theory
Resconi, G.; Wal, A.J. van der; Ruan, D.
1998-01-01
By using the Monte Carlo method, we can obtain the minimum value of a function V(r) that is generally associated with the potential energy. In this paper we present a method that makes it possible to speed up the classical Monte Carlo method. The new method is based on the observation that the
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.
Directory of Open Access Journals (Sweden)
GHAREHPETIAN, G. B.
2009-06-01
Full Text Available The analysis of the risk of partial and total blackouts has a crucial role to determine safe limits in power system design, operation and upgrade. Due to huge cost of blackouts, it is very important to improve risk assessment methods. In this paper, Monte Carlo simulation (MCS was used to analyze the risk and Gaussian Mixture Method (GMM has been used to estimate the probability density function (PDF of the load curtailment, in order to improve the power system risk assessment method. In this improved method, PDF and a suggested index have been used to analyze the risk of loss of load. The effect of considering the number of generation units of power plants in the risk analysis has been studied too. The improved risk assessment method has been applied to IEEE 118 bus and the network of Khorasan Regional Electric Company (KREC and the PDF of the load curtailment has been determined for both systems. The effect of various network loadings, transmission unavailability, transmission capacity and generation unavailability conditions on blackout risk has been investigated too.
The Simulation-Tabulation Method for Classical Diffusion Monte Carlo
Hwang, Chi-Ok; Given, James A.; Mascagni, Michael
2001-12-01
Many important classes of problems in materials science and biotechnology require the solution of the Laplace or Poisson equation in disordered two-phase domains in which the phase interface is extensive and convoluted. Green's function first-passage (GFFP) methods solve such problems efficiently by generalizing the “walk on spheres” (WOS) method to allow first-passage (FP) domains to be not just spheres but a wide variety of geometrical shapes. (In particular, this solves the difficulty of slow convergence with WOS by allowing FP domains that contain patches of the phase interface.) Previous studies accomplished this by using geometries for which the Green's function was available in quasi-analytic form. Here, we extend these studies by using the simulation-tabulation (ST) method. We simulate and then tabulate surface Green's functions that cannot be obtained analytically. The ST method is applied to the Solc-Stockmayer model with zero potential, to the mean trapping rate of a diffusing particle in a domain of nonoverlapping spherical traps, and to the effective conductivity for perfectly insulating, nonoverlapping spherical inclusions in a matrix of finite conductivity. In all cases, this class of algorithms provides the most efficient methods known to solve these problems to high accuracy.
On performance measures for infinite swapping Monte Carlo methods.
Doll, J D; Dupuis, Paul
2015-01-14
We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters.
Applications of Malliavin calculus to Monte Carlo methods in finance
Eric Fournié; Jean-Michel Lasry; Pierre-Louis Lions; Jérôme Lebuchoux; Nizar Touzi
1999-01-01
This paper presents an original probabilistic method for the numerical computations of Greeks (i.e. price sensitivities) in finance. Our approach is based on the {\\it integration-by-parts} formula, which lies at the core of the theory of variational stochastic calculus, as developed in the Malliavin calculus. The Greeks formulae, both with respect to initial conditions and for smooth perturbations of the local volatility, are provided for general discontinuous path-dependent payoff functional...
Diener, K P O; Spira, Michael; Diener, Kai-Peer O.; Schwanenberger, Christian; Spira, Michael
2003-01-01
A procedure of implementing QCD corrections in Monte Carlo programs by a reweighting method is described for the photoproduction of W bosons at HERA. Tables for W boson production in LO and NLO are given in bins of the transverse momentum of the W boson and its rapidity.
DEFF Research Database (Denmark)
Debrabant, Kristian; Samaey, Giovanni; Zieliński, Przemysław
2017-01-01
We present and analyse a micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations with separation between the (fast) time-scale of individual trajectories and the (slow) time-scale of the macroscopic function of interest. The algorithm combines short...
An Evaluation of a Markov Chain Monte Carlo Method for the Rasch Model.
Kim, Seock-Ho
2001-01-01
Examined the accuracy of the Gibbs sampling Markov chain Monte Carlo procedure for estimating item and person (theta) parameters in the one-parameter logistic model. Analyzed four empirical datasets using the Gibbs sampling, conditional maximum likelihood, marginal maximum likelihood, and joint maximum likelihood methods. Discusses the conditions…
A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods
D. David (David); N. Basturk (Nalan); L.F. Hoogerheide (Lennart); H.K. van Dijk (Herman)
2010-01-01
textabstractStrategic choices for efficient and accurate evaluation of marginal likelihoods by means of Monte Carlo simulation methods are studied for the case of highly non-elliptical posterior distributions. A comparative analysis is presented of possible advantages and limitations of different
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"…
Lee, Anthony; Yau, Christopher; Giles, Michael B.; Doucet, Arnaud; Holmes, Christopher C.
2011-01-01
We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers and can be thought of as prototypes of the next generation of many-core processors. For certain classes of population-based Monte Carlo algorithms they offer massively parallel simulation, with the added advantage over conventional distributed multi-core processors that they are cheap, easily accessible, easy to maintain, easy to code, dedicated local devices with low power consumption. On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we nd speedups from 35 to 500 fold over conventional single-threaded computer code. Our findings suggest that GPUs have the potential to facilitate the growth of statistical modelling into complex data rich domains through the availability of cheap and accessible many-core computation. We believe the speedup we observe should motivate wider use of parallelizable simulation methods and greater methodological attention to their design. PMID:22003276
Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method
Gilbreth, C. N.; Alhassid, Y.
2015-03-01
Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.
Fission yield covariances for JEFF: A Bayesian Monte Carlo method
Leray, Olivier; Rochman, Dimitri; Fleming, Michael; Sublet, Jean-Christophe; Koning, Arjan; Vasiliev, Alexander; Ferroukhi, Hakim
2017-09-01
The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties) and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.
Fission yield covariances for JEFF: A Bayesian Monte Carlo method
Directory of Open Access Journals (Sweden)
Leray Olivier
2017-01-01
Full Text Available The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.
Distributional Monte Carlo Methods for the Boltzmann Equation
2013-03-01
real valued function over R3 such that ∫ R3 φ (v) Q ( f , f ) dv exists. Cercignani shows [29] ∫ R3 φ (v) Q ( f , f ) dv = 1 4 ∫ R3 ∫ R3 ∫ S + [ f ( v...1957. [26] Cercignani , C. “Existence and Uniqueness in the Large for Boundary Value Problems in Kinetic Theory”. Journal of Mathematical Physics, 8(8...1653–1656, 1967. [27] Cercignani , C. The Boltzmann Equation and Its Applications. Springer-Verlag, 1988. [28] Cercignani , C. Mathematical Methods in
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.
Evaluation of Investment Risks in CBA with Monte Carlo Method
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Jana Korytárová
2015-01-01
Full Text Available Investment decisions are at the core of any development strategy. Economic growth and welfare depend on productive capital, infrastructure, human capital, knowledge, total factor productivity and the quality of institutions. Decision-making process on the selection of suitable projects in the public sector is in some aspects more difficult than in the private sector. Evaluating projects on the basis of their financial profitability, where the basic parameter is the value of the potential profit, can be misleading in these cases. One of the basic objectives of the allocation of public resources is respecting of the 3E principle (Economy, Effectiveness, Efficiency in their whole life cycle. The life cycle of the investment projects consists of four main phases. The first pre-investment phase is very important for decision-making process whether to accept or reject a public project for its realization. A well-designed feasibility study as well as cost-benefit analysis (CBA in this phase are important assumptions for future success of the project. A future financial and economical CF which represent the fundamental basis for calculation of economic effectiveness indicators are formed and modelled in these documents. This paper deals with the possibility to calculate the financial and economic efficiency of the public investment projects more accurately by simulation methods used.
An Implicit Monte Carlo Method for Simulation of Impurity Transport in Divertor Plasma
Suzuki, Akiko; Takizuka, Tomonori; Shimizu, Katsuhiro; Hayashi, Nobuhiko; Hatayama, Akiyoshi; Ogasawara, Masatada
1997-02-01
A new "implicit" Monte Carlo (IMC) method has been developed to simulate ionization and recombination processes of impurity ions in divertor plasmas. The IMC method takes into account many ionization and recombination processes during a time step Δ t. The time step is not limited by a condition, Δ t≪ τ min(τ min; the minimum characteristic time of atomic processes), which is forced to be adopted in conventional Monte Carlo methods. We incorporate this method into a one-dimensional impurity transport model. In this transport calculation, impurity ions are followed with the time step about 10 times larger than that used in conventional methods. The average charge state of impurities, , and the radiative cooling rate, L( Te), are calculated at the electron temperature Tein divertor plasmas. These results are compared with thosed obtained from the simple noncoronal model.
Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling
Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.
2018-02-01
A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.
Uniform-acceptance force-bias Monte Carlo method with time scale to study solid-state diffusion
Mees, M.J.; Pourtois, G.; Neyts, E.C.; Thijsse, B.J.; Stesmans, A.
2012-01-01
Monte Carlo (MC) methods have a long-standing history as partners of molecular dynamics (MD) to simulate the evolution of materials at the atomic scale. Among these techniques, the uniform-acceptance force-bias Monte Carlo (UFMC) method [ G. Dereli Mol. Simul. 8 351 (1992)] has recently attracted
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.
POSSIBILITIES OF USING MONTE CARLO METHOD FOR SOLVING MACHINING OPTIMIZATION PROBLEMS
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Miloš Madić
2014-04-01
Full Text Available Companies operating in today's machining environment are focused on improving their product quality and decreasing manufacturing cost and time. In their attempts to meet these objectives, the machining processes optimization is of prime importance. Among the traditional optimization methods, in recent years, modern meta-heuristic algorithms are being increasingly applied to solving machining optimization problems. Regardless of numerous capabilities of the Monte Carlo method, its application for solving machining optimization problems has been given less attention by researchers and practitioners. The aim of this paper is to investigate the Monte Carlo method applicability for solving single-objective machining optimization problems and to analyze its efficiency by comparing the optimization solutions to those obtained by the past researchers using meta-heuristic algorithms. For this purpose, five machining optimization case studies taken from the literature are considered and discussed.
A Monte Carlo method for solving the one-dimensional telegraph equations with boundary conditions
Acebrón, Juan A.; Ribeiro, Marco A.
2016-01-01
A Monte Carlo algorithm is derived to solve the one-dimensional telegraph equations in a bounded domain subject to resistive and non-resistive boundary conditions. The proposed numerical scheme is more efficient than the classical Kac's theory because it does not require the discretization of time. The algorithm has been validated by comparing the results obtained with theory and the Finite-difference time domain (FDTD) method for a typical two-wire transmission line terminated at both ends with general boundary conditions. We have also tested transmission line heterogeneities to account for wave propagation in multiple media. The algorithm is inherently parallel, since it is based on Monte Carlo simulations, and does not suffer from the numerical dispersion and dissipation issues that arise in finite difference-based numerical schemes on a lossy medium. This allowed us to develop an efficient numerical method, capable of outperforming the classical FDTD method for large scale problems and high frequency signals.
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
Application de la methode des sous-groupes au calcul Monte-Carlo multigroupe
Martin, Nicolas
This thesis is dedicated to the development of a Monte Carlo neutron transport solver based on the subgroup (or multiband) method. In this formalism, cross sections for resonant isotopes are represented in the form of probability tables on the whole energy spectrum. This study is intended in order to test and validate this approach in lattice physics and criticality-safety applications. The probability table method seems promising since it introduces an alternative computational way between the legacy continuous-energy representation and the multigroup method. In the first case, the amount of data invoked in continuous-energy Monte Carlo calculations can be very important and tend to slow down the overall computational time. In addition, this model preserves the quality of the physical laws present in the ENDF format. Due to its cheap computational cost, the multigroup Monte Carlo way is usually at the basis of production codes in criticality-safety studies. However, the use of a multigroup representation of the cross sections implies a preliminary calculation to take into account self-shielding effects for resonant isotopes. This is generally performed by deterministic lattice codes relying on the collision probability method. Using cross-section probability tables on the whole energy range permits to directly take into account self-shielding effects and can be employed in both lattice physics and criticality-safety calculations. Several aspects have been thoroughly studied: (1) The consistent computation of probability tables with a energy grid comprising only 295 or 361 groups. The CALENDF moment approach conducted to probability tables suitable for a Monte Carlo code. (2) The combination of the probability table sampling for the energy variable with the delta-tracking rejection technique for the space variable, and its impact on the overall efficiency of the proposed Monte Carlo algorithm. (3) The derivation of a model for taking into account anisotropic
Monte Carlo method for photon heating using temperature-dependent optical properties.
Slade, Adam Broadbent; Aguilar, Guillermo
2015-02-01
The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. Copyright
Convergence Studies on Monte Carlo Methods for Pricing Mortgage-Backed Securities
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Tao Pang
2015-05-01
Full Text Available Monte Carlo methods are widely-used simulation tools for market practitioners from trading to risk management. When pricing complex instruments, like mortgage-backed securities (MBS, strong path-dependency and high dimensionality make the Monte Carlo method the most suitable, if not the only, numerical method. In practice, while simulation processes in option-adjusted valuation can be relatively easy to implement, it is a well-known challenge that the convergence and the desired accuracy can only be achieved at the cost of lengthy computational times. In this paper, we study the convergence of Monte Carlo methods in calculating the option-adjusted spread (OAS, effective duration (DUR and effective convexity (CNVX of MBS instruments. We further define two new concepts, absolute convergence and relative convergence, and show that while the convergence of OAS requires thousands of simulation paths (absolute convergence, only hundreds of paths may be needed to obtain the desired accuracy for effective duration and effective convexity (relative convergence. These results suggest that practitioners can reduce the computational time substantially without sacrificing simulation accuracy.
Mesh-based Monte Carlo method in time-domain widefield fluorescence molecular tomography
Chen, Jin; Fang, Qianqian; Intes, Xavier
2012-10-01
We evaluated the potential of mesh-based Monte Carlo (MC) method for widefield time-gated fluorescence molecular tomography, aiming to improve accuracy in both shape discretization and photon transport modeling in preclinical settings. An optimized software platform was developed utilizing multithreading and distributed parallel computing to achieve efficient calculation. We validated the proposed algorithm and software by both simulations and in vivo studies. The results establish that the optimized mesh-based Monte Carlo (mMC) method is a computationally efficient solution for optical tomography studies in terms of both calculation time and memory utilization. The open source code, as part of a new release of mMC, is publicly available at http://mcx.sourceforge.net/mmc/.
Kerr, Rex A; Bartol, Thomas M; Kaminsky, Boris; Dittrich, Markus; Chang, Jen-Chien Jack; Baden, Scott B; Sejnowski, Terrence J; Stiles, Joel R
2008-10-13
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods.
Development of a Monte-Carlo based method for calculating the effect of stationary fluctuations
DEFF Research Database (Denmark)
Pettersen, E. E.; Demazire, C.; Jareteg, K.
2015-01-01
This paper deals with the development of a novel method for performing Monte Carlo calculations of the effect, on the neutron flux, of stationary fluctuations in macroscopic cross-sections. The basic principle relies on the formulation of two equivalent problems in the frequency domain: one...... that corresponds to the real part of the neutron balance, and one that corresponds to the imaginary part. The two equivalent problems are in nature similar to two subcritical systems driven by external neutron sources, and can thus be treated as such in a Monte Carlo framework. The definition of these two...... part of the neutron balance plays a significant role and for driving fluctuations leading to neutron sources having the same sign in the two equivalent sub-critical problems. A semi-analytical diffusion-based solution is used to verily the implementation of the method on a test case representative...
Integrated Building Energy Design of a Danish Office Building Based on Monte Carlo Simulation Method
DEFF Research Database (Denmark)
Sørensen, Mathias Juul; Myhre, Sindre Hammer; Hansen, Kasper Kingo
2017-01-01
and improve the collaboration efficiency. Monte Carlo Simulation method is adopted to simulate both the energy performance and indoor climate of the building. Building physics parameters, including characteristics of facades, walls, windows, etc., are taken into consideration, and thousands of combinations...... fulfil the requirements and leaves additional design freedom for the architects. This study utilizes global design exploration with Monte Carlo Simulations, in order to form feasible solutions for architects and improves the collaboration efficiency between architects and engineers....... office building located in Aarhus, Denmark. Building geometry, floor plans and employee schedules were obtained from the architects which is the basis for this study. This study aims to simplify the iterative design process that is based on the traditional trial and error method in the late design phases...
Crevillén-García, D; Power, H
2017-08-01
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.
Multilevel Monte Carlo and Improved Timestepping Methods in Atmospheric Dispersion Modelling
Katsiolides, G; Muller, EH; Scheichl, R.; Shardlow, T.; Giles, MB; Thomson, DJ
2017-01-01
A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an ef...
A new fuzzy Monte Carlo method for solving SLAE with ergodic fuzzy Markov chains
Directory of Open Access Journals (Sweden)
Maryam Gharehdaghi
2015-05-01
Full Text Available In this paper we introduce a new fuzzy Monte Carlo method for solving system of linear algebraic equations (SLAE over the possibility theory and max-min algebra. To solve the SLAE, we first define a fuzzy estimator and prove that this is an unbiased estimator of the solution. To prove unbiasedness, we apply the ergodic fuzzy Markov chains. This new approach works even for cases with coefficients matrix with a norm greater than one.
A Monte Carlo Method for Multi-Objective Correlated Geometric Optimization
2014-05-01
rooftops (red) and four targets located at entryways to buildings (green).. . . . . . . . . . . . . . . . . . . . . 6 Figure 2. Shown in yellow is the...given threat and target positions, and • AMonte Carlo method development in the OpenCL programming model for vendor-agnostic architecture support and...optimization problem of determining the placement of blue force Soldiers. The parallelism of processing architectures , which is rampant and unavoidable
Multilevel markov chain monte carlo method for high-contrast single-phase flow problems
Efendiev, Yalchin R.
2014-12-19
In this paper we propose a general framework for the uncertainty quantification of quantities of interest for high-contrast single-phase flow problems. It is based on the generalized multiscale finite element method (GMsFEM) and multilevel Monte Carlo (MLMC) methods. The former provides a hierarchy of approximations of different resolution, whereas the latter gives an efficient way to estimate quantities of interest using samples on different levels. The number of basis functions in the online GMsFEM stage can be varied to determine the solution resolution and the computational cost, and to efficiently generate samples at different levels. In particular, it is cheap to generate samples on coarse grids but with low resolution, and it is expensive to generate samples on fine grids with high accuracy. By suitably choosing the number of samples at different levels, one can leverage the expensive computation in larger fine-grid spaces toward smaller coarse-grid spaces, while retaining the accuracy of the final Monte Carlo estimate. Further, we describe a multilevel Markov chain Monte Carlo method, which sequentially screens the proposal with different levels of approximations and reduces the number of evaluations required on fine grids, while combining the samples at different levels to arrive at an accurate estimate. The framework seamlessly integrates the multiscale features of the GMsFEM with the multilevel feature of the MLMC methods following the work in [26], and our numerical experiments illustrate its efficiency and accuracy in comparison with standard Monte Carlo estimates. © Global Science Press Limited 2015.
Investigation of Multicritical Phenomena in ANNNI Model by Monte Carlo Methods
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A. K. Murtazaev
2012-01-01
Full Text Available The anisotropic Ising model with competing interactions is investigated in wide temperature range and |J1/J| parameters by means of Monte Carlo methods. Static critical exponents of the magnetization, susceptibility, heat capacity, and correlation radius are calculated in the neighborhood of Lifshitz point. According to obtained results, a phase diagram is plotted, the coordinates of Lifshitz point are defined, and a character of multicritical behavior of the system is detected.
Multilevel and Multi-index Monte Carlo methods for the McKean–Vlasov equation
Haji-Ali, Abdul-Lateef
2017-09-12
We address the approximation of functionals depending on a system of particles, described by stochastic differential equations (SDEs), in the mean-field limit when the number of particles approaches infinity. This problem is equivalent to estimating the weak solution of the limiting McKean–Vlasov SDE. To that end, our approach uses systems with finite numbers of particles and a time-stepping scheme. In this case, there are two discretization parameters: the number of time steps and the number of particles. Based on these two parameters, we consider different variants of the Monte Carlo and Multilevel Monte Carlo (MLMC) methods and show that, in the best case, the optimal work complexity of MLMC, to estimate the functional in one typical setting with an error tolerance of $$\\\\mathrm {TOL}$$TOL, is when using the partitioning estimator and the Milstein time-stepping scheme. We also consider a method that uses the recent Multi-index Monte Carlo method and show an improved work complexity in the same typical setting of . Our numerical experiments are carried out on the so-called Kuramoto model, a system of coupled oscillators.
Kinetics of electron-positron pair plasmas using an adaptive Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Pilla, R.P.; Shaham, J. [Department of Physics, Columbia University, 538 West 120th Street, New York, New York 10027 (United States)
1997-09-01
A new algorithm for implementing the adaptive Monte Carlo method is given. It is used to solve the Boltzmann equations that describe the time evolution of a nonequilibrium electron-positron pair plasma containing high-energy photons. These are coupled nonlinear integro-differential equations. The collision kernels for the photons as well as pairs are evaluated for Compton scattering, pair annihilation and creation, bremsstrahlung, and Coulomb collisions. They are given as multidimensional integrals which are valid for all energies. For an homogeneous and isotropic plasma with no particle escape, the equilibrium solution is expressed analytically in terms of the initial conditions. For two specific cases, for which the photon and the pair spectra are initially constant or have a power-law distribution within the given limits, the time evolution of the plasma is analyzed using the new method. The final spectra are found to be in a good agreement with the analytical solutions. The new algorithm is faster than the Monte Carlo scheme based on uniform sampling and more flexible than the numerical methods used in the past, which do not involve Monte Carlo sampling. It is also found to be very stable. Some astrophysical applications of this technique are discussed. {copyright} {ital 1997} {ital The American Astronomical Society}
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.
Quasi-Monte Carlo methods for lattice systems: A first look
Jansen, K.; Leovey, H.; Ammon, A.; Griewank, A.; Müller-Preussker, M.
2014-03-01
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 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 to N-1, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling. Catalogue identifier: AERJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERJ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence version 3 No. of lines in distributed program, including test data, etc.: 67759 No. of bytes in distributed program, including test data, etc.: 2165365 Distribution format: tar.gz Programming language: C and C++. Computer: PC. Operating system: Tested on GNU/Linux, should be portable to other operating systems with minimal efforts. Has the code been vectorized or parallelized?: No RAM: The memory usage directly scales with the number of samples and dimensions: Bytes used = “number of samples” × “number of dimensions” × 8 Bytes (double precision). Classification: 4.13, 11.5, 23. External routines: FFTW 3 library (http://www.fftw.org) Nature of problem: Certain physical models formulated as a quantum field theory through the Feynman path integral, such as quantum chromodynamics, require a non-perturbative treatment of the path integral. The only known approach that achieves this is the lattice regularization. In this formulation the path integral is discretized to a finite, but very high dimensional integral. So far only Monte
Boos, Dennis D; Osborne, Jason A
2015-08-01
Good statistical practice dictates that summaries in Monte Carlo studies should always be accompanied by standard errors. Those standard errors are easy to provide for summaries that are sample means over the replications of the Monte Carlo output: for example, bias estimates, power estimates for tests, and mean squared error estimates. But often more complex summaries are of interest: medians (often displayed in boxplots), sample variances, ratios of sample variances, and non-normality measures like skewness and kurtosis. In principle standard errors for most of these latter summaries may be derived from the Delta Method, but that extra step is often a barrier for standard errors to be provided. Here we highlight the simplicity of using the jackknife and bootstrap to compute these standard errors, even when the summaries are somewhat complicated.
Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method
Chen, Chaobin; Huang, Qunying; Wu, Yican
2005-04-01
A few CT-based voxel phantoms were produced to investigate the sensitivity of Monte Carlo simulations of x-ray beam and electron beam to the proportions of elements and the mass densities of the materials used to express the patient's anatomical structure. The human body can be well outlined by air, lung, adipose, muscle, soft bone and hard bone to calculate the dose distribution with Monte Carlo method. The effects of the calibration curves established by using various CT scanners are not clinically significant based on our investigation. The deviation from the values of cumulative dose volume histogram derived from CT-based voxel phantoms is less than 1% for the given target.
Determination of cascade summing correction for HPGe spectrometers by the Monte Carlo method
Takeda, M N
2001-01-01
The present work describes the methodology developed for calculating the cascade sum correction to be applied to experimental efficiencies obtained by means of HPGe spectrometers. The detection efficiencies have been numerically calculated by the Monte Carlo Method for point sources. Another Monte Carlo algorithm has been developed to follow the path in the decay scheme from the beginning state at the precursor radionuclide decay level, down to the ground state of the daughter radionuclide. Each step in the decay scheme is selected by random numbers taking into account the transition probabilities and internal transition coefficients. The selected transitions are properly tagged according to the type of interaction has occurred, giving rise to a total or partial energy absorption events inside the detector crystal. Once the final state has been reached, the selected transitions were accounted for verifying each pair of transitions which occurred simultaneously. With this procedure it was possible to calculate...
SOLVATION STRUCTURE DETERMINATION OF Ni2+ ION IN WATER BY MEANS OF MONTE CARLO METHOD
Directory of Open Access Journals (Sweden)
Tutik Arindah
2010-06-01
Full Text Available Determination of solvation structure of Ni2+ ion in water has been achieved using Monte Carlo method using canonic assemble (NVT constant. Simulation of a Ni2+ ion in 215 H2O molecules has been done under NVT condition (298.15 K. The results showed that number of H2O molecules surround Ni2+ ion were 8 molecules in first shell and 17 molecules in second shell, interaction energy of Ni2+-H2O in first shell was -68.7 kcal/mol and in second shell was -9.8 kcal/mol, and there were two angles of O-Ni2+-O, i.e. 74o and 142o. According to those results, the solvation structure of Ni2+ ion in water was cubic antisymetric. Keywords: Water simulation, Monte Carlo simulation
Analysis of single Monte Carlo methods for prediction of reflectance from turbid media
Martinelli, Michele; Gardner, Adam; Cuccia, David; Hayakawa, Carole; Spanier, Jerome; Venugopalan, Vasan
2011-01-01
Starting from the radiative transport equation we derive the scaling relationships that enable a single Monte Carlo (MC) simulation to predict the spatially- and temporally-resolved reflectance from homogeneous semi-infinite media with arbitrary scattering and absorption coefficients. This derivation shows that a rigorous application of this single Monte Carlo (sMC) approach requires the rescaling to be done individually for each photon biography. We examine the accuracy of the sMC method when processing simulations on an individual photon basis and also demonstrate the use of adaptive binning and interpolation using non-uniform rational B-splines (NURBS) to achieve order of magnitude reductions in the relative error as compared to the use of uniform binning and linear interpolation. This improved implementation for sMC simulation serves as a fast and accurate solver to address both forward and inverse problems and is available for use at http://www.virtualphotonics.org/. PMID:21996904
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.
Geant4 based Monte Carlo simulation for verifying the modified sum-peak method.
Aso, Tsukasa; Ogata, Yoshimune; Makino, Ryuta
2017-09-14
The modified sum-peak method can practically estimate radioactivity by using solely the peak and the sum peak count rate. In order to efficiently verify the method in various experimental conditions, a Geant4 based Monte Carlo simulation for a high-purity germanium detector system was applied. The energy spectra in the detector were simulated for a 60Co point source in various source to detector distances. The calculated radioactivity shows good agreement with the number of decays in the simulation. Copyright © 2017 Elsevier Ltd. All rights reserved.
A study of potential energy curves from the model space quantum Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Ohtsuka, Yuhki; Ten-no, Seiichiro, E-mail: tenno@cs.kobe-u.ac.jp [Department of Computational Sciences, Graduate School of System Informatics, Kobe University, Nada-ku, Kobe 657-8501 (Japan)
2015-12-07
We report on the first application of the model space quantum Monte Carlo (MSQMC) to potential energy curves (PECs) for the excited states of C{sub 2}, N{sub 2}, and O{sub 2} to validate the applicability of the method. A parallel MSQMC code is implemented with the initiator approximation to enable efficient sampling. The PECs of MSQMC for various excited and ionized states are compared with those from the Rydberg-Klein-Rees and full configuration interaction methods. The results indicate the usefulness of MSQMC for precise PECs in a wide range obviating problems concerning quasi-degeneracy.
Remarks on a financial inverse problem by means of Monte Carlo Methods
Cuomo, Salvatore; Di Somma, Vittorio; Sica, Federica
2017-10-01
Estimating the price of a barrier option is a typical inverse problem. In this paper we present a numerical and statistical framework for a market with risk-free interest rate and a risk asset, described by a Geometric Brownian Motion (GBM). After approximating the risk asset with a numerical method, we find the final option price by following an approach based on sequential Monte Carlo methods. All theoretical results are applied to the case of an option whose underlying is a real stock.
Shielding analyses of an AB-BNCT facility using Monte Carlo simulations and simplified methods
Directory of Open Access Journals (Sweden)
Lai Bo-Lun
2017-01-01
Full Text Available Accurate Monte Carlo simulations and simplified methods were used to investigate the shielding requirements of a hypothetical accelerator-based boron neutron capture therapy (AB-BNCT facility that included an accelerator room and a patient treatment room. The epithermal neutron beam for BNCT purpose was generated by coupling a neutron production target with a specially designed beam shaping assembly (BSA, which was embedded in the partition wall between the two rooms. Neutrons were produced from a beryllium target bombarded by 1-mA 30-MeV protons. The MCNP6-generated surface sources around all the exterior surfaces of the BSA were established to facilitate repeated Monte Carlo shielding calculations. In addition, three simplified models based on a point-source line-of-sight approximation were developed and their predictions were compared with the reference Monte Carlo results. The comparison determined which model resulted in better dose estimation, forming the basis of future design activities for the first ABBNCT facility in Taiwan.
Shielding analyses of an AB-BNCT facility using Monte Carlo simulations and simplified methods
Lai, Bo-Lun; Sheu, Rong-Jiun
2017-09-01
Accurate Monte Carlo simulations and simplified methods were used to investigate the shielding requirements of a hypothetical accelerator-based boron neutron capture therapy (AB-BNCT) facility that included an accelerator room and a patient treatment room. The epithermal neutron beam for BNCT purpose was generated by coupling a neutron production target with a specially designed beam shaping assembly (BSA), which was embedded in the partition wall between the two rooms. Neutrons were produced from a beryllium target bombarded by 1-mA 30-MeV protons. The MCNP6-generated surface sources around all the exterior surfaces of the BSA were established to facilitate repeated Monte Carlo shielding calculations. In addition, three simplified models based on a point-source line-of-sight approximation were developed and their predictions were compared with the reference Monte Carlo results. The comparison determined which model resulted in better dose estimation, forming the basis of future design activities for the first ABBNCT facility in Taiwan.
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 %. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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.
Solid 4He and the diffusion Monte Carlo method: A study of their properties
Rugeles, E. J.; Ujevic, Sebastian; Vitiello, S. A.
2017-10-01
Properties of helium atoms in the solid phase are investigated using the multiweight diffusion Monte Carlo method. Two different importance function transformations are used in two series of independent calculations. The kinetic energy is estimated for both the solid and liquid phases of 4He. We estimate the melting and freezing densities, among other properties of interest. Our estimates are compared with experimental values. We discuss why walkers biased by two distinctly different guiding functions do not lead to noticeable changes in the reported results. Criticisms concerning the bias introduced into our estimates by population control and system size effects are considered.
DEFF Research Database (Denmark)
Debrabant, Kristian; Samaey, Giovanni; Zieliński, Przemysław
2017-01-01
We present and analyse a micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations with separation between the (fast) time-scale of individual trajectories and the (slow) time-scale of the macroscopic function of interest. The algorithm combines short...... bursts of path simulations with extrapolation of a number of macroscopic state variables forward in time. The new microscopic state, consistent with the extrapolated variables, is obtained by a matching operator that minimises the perturbation caused by the extrapolation. We provide a proof...
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.
Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek
2017-07-01
Monte Carlo method allowing to account for the effect of Pauli Exclusion Principle in the case of spin polarized electron gas is demonstrated. Modeling requires calculation of electron states occupancy accounting for the direction of the spin of the scattered electron. As an example of application, calculations for the case of spin and energy relaxation of initially polarized electrons in monolayer graphene have been performed. Model includes D'yakonov-Perel' and Elliot-Yafet relaxation mechanisms. It is demonstrated that electron distribution function and energy relaxation follow the spin polarization relaxation and they are mainly governed by spin related scattering processes.
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.
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).
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.
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.
Fast Monte Carlo Electron-Photon Transport Method and Application in Accurate Radiotherapy
Hao, Lijuan; Sun, Guangyao; Zheng, Huaqing; Song, Jing; Chen, Zhenping; Li, Gui
2014-06-01
Monte Carlo (MC) method is the most accurate computational method for dose calculation, but its wide application on clinical accurate radiotherapy is hindered due to its poor speed of converging and long computation time. In the MC dose calculation research, the main task is to speed up computation while high precision is maintained. The purpose of this paper is to enhance the calculation speed of MC method for electron-photon transport with high precision and ultimately to reduce the accurate radiotherapy dose calculation time based on normal computer to the level of several hours, which meets the requirement of clinical dose verification. Based on the existing Super Monte Carlo Simulation Program (SuperMC), developed by FDS Team, a fast MC method for electron-photon coupled transport was presented with focus on two aspects: firstly, through simplifying and optimizing the physical model of the electron-photon transport, the calculation speed was increased with slightly reduction of calculation accuracy; secondly, using a variety of MC calculation acceleration methods, for example, taking use of obtained information in previous calculations to avoid repeat simulation of particles with identical history; applying proper variance reduction techniques to accelerate MC method convergence rate, etc. The fast MC method was tested by a lot of simple physical models and clinical cases included nasopharyngeal carcinoma, peripheral lung tumor, cervical carcinoma, etc. The result shows that the fast MC method for electron-photon transport was fast enough to meet the requirement of clinical accurate radiotherapy dose verification. Later, the method will be applied to the Accurate/Advanced Radiation Therapy System ARTS as a MC dose verification module.
DYNAMIC PARAMETERS ESTIMATION OF INTERFEROMETRIC SIGNALS BASED ON SEQUENTIAL MONTE CARLO METHOD
Directory of Open Access Journals (Sweden)
M. A. Volynsky
2014-05-01
Full Text Available The paper deals with sequential Monte Carlo method applied to problem of interferometric signals parameters estimation. The method is based on the statistical approximation of the posterior probability density distribution of parameters. Detailed description of the algorithm is given. The possibility of using the residual minimum between prediction and observation as a criterion for the selection of multitude elements generated at each algorithm step is shown. Analysis of input parameters influence on performance of the algorithm has been conducted. It was found that the standard deviation of the amplitude estimation error for typical signals is about 10% of the maximum amplitude value. The phase estimation error was shown to have a normal distribution. Analysis of the algorithm characteristics depending on input parameters is done. In particular, the influence analysis for a number of selected vectors of parameters on evaluation results is carried out. On the basis of simulation results for the considered class of signals, it is recommended to select 30% of the generated vectors number. The increase of the generated vectors number over 150 does not give significant improvement of the obtained estimates quality. The sequential Monte Carlo method is recommended for usage in dynamic processing of interferometric signals for the cases when high immunity is required to non-linear changes of signal parameters and influence of random noise.
Directory of Open Access Journals (Sweden)
S. J. Noh
2011-10-01
Full Text Available Data assimilation techniques have received growing attention due to their capability to improve prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC methods, known as "particle filters", are a Bayesian learning process that has the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response times of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until the uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on the Markov chain Monte Carlo (MCMC methods is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, water and energy transfer processes (WEP, is implemented for the sequential data assimilation through the updating of state variables. The lagged regularized particle filter (LRPF and the sequential importance resampling (SIR particle filter are implemented for hindcasting of streamflow at the Katsura catchment, Japan. Control state variables for filtering are soil moisture content and overland flow. Streamflow measurements are used for data assimilation. LRPF shows consistent forecasts regardless of the process noise assumption, while SIR has different values of optimal process noise and shows sensitive variation of confidential intervals, depending on the process noise. Improvement of LRPF forecasts compared to SIR is particularly found for rapidly varied high flows due to preservation of sample diversity from the kernel, even if particle impoverishment takes place.
Efficient implementation of a Monte Carlo method for uncertainty evaluation in dynamic measurements
Eichstädt, S.; Link, A.; Harris, P.; Elster, C.
2012-06-01
Measurement of quantities having time-dependent values such as force, acceleration or pressure is a topic of growing importance in metrology. The application of the Guide to the Expression of Uncertainty in Measurement (GUM) and its Supplements to the evaluation of uncertainty for such quantities is challenging. We address the efficient implementation of the Monte Carlo method described in GUM Supplements 1 and 2 for this task. The starting point is a time-domain observation equation. The steps of deriving a corresponding measurement model, the assignment of probability distributions to the input quantities in the model, and the propagation of the distributions through the model are all considered. A direct implementation of a Monte Carlo method can be intractable on many computers since the storage requirement of the method can be large compared with the available computer memory. Two memory-efficient alternatives to the direct implementation are proposed. One approach is based on applying updating formulae for calculating means, variances and point-wise histograms. The second approach is based on evaluating the measurement model sequentially in time. A simulated example is used to compare the performance of the direct and alternative procedures.
The applicability of certain Monte Carlo methods to the analysis of interacting polymers
Energy Technology Data Exchange (ETDEWEB)
Krapp, Jr., Donald M. [Univ. of California, Berkeley, CA (United States)
1998-05-01
The authors consider polymers, modeled as self-avoiding walks with interactions on a hexagonal lattice, and examine the applicability of certain Monte Carlo methods for estimating their mean properties at equilibrium. Specifically, the authors use the pivoting algorithm of Madras and Sokal and Metroplis rejection to locate the phase transition, which is known to occur at β_{crit} ~ 0.99, and to recalculate the known value of the critical exponent η ~ 0.58 of the system for β = β_{crit}. Although the pivoting-Metropolis algorithm works well for short walks (N < 300), for larger N the Metropolis criterion combined with the self-avoidance constraint lead to an unacceptably small acceptance fraction. In addition, the algorithm becomes effectively non-ergodic, getting trapped in valleys whose centers are local energy minima in phase space, leading to convergence towards different values of η. The authors use a variety of tools, e.g. entropy estimation and histograms, to improve the results for large N, but they are only of limited effectiveness. Their estimate of β_{crit} using smaller values of N is 1.01 ± 0.01, and the estimate for η at this value of β is 0.59 ± 0.005. They conclude that even a seemingly simple system and a Monte Carlo algorithm which satisfies, in principle, ergodicity and detailed balance conditions, can in practice fail to sample phase space accurately and thus not allow accurate estimations of thermal averages. This should serve as a warning to people who use Monte Carlo methods in complicated polymer folding calculations. The structure of the phase space combined with the algorithm itself can lead to surprising behavior, and simply increasing the number of samples in the calculation does not necessarily lead to more accurate results.
Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr [Korea Advanced Institute of Science and Technology 291 Daehak-ro, Yuseong-gu, Daejeon, Korea 305-701 (Korea, Republic of)
2015-12-31
The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problem are presented.
A Deterministic-Monte Carlo Hybrid Method for Time-Dependent Neutron Transport Problems
Energy Technology Data Exchange (ETDEWEB)
Justin Pounders; Farzad Rahnema
2001-10-01
A new deterministic-Monte Carlo hybrid solution technique is derived for the time-dependent transport equation. This new approach is based on dividing the time domain into a number of coarse intervals and expanding the transport solution in a series of polynomials within each interval. The solutions within each interval can be represented in terms of arbitrary source terms by using precomputed response functions. In the current work, the time-dependent response function computations are performed using the Monte Carlo method, while the global time-step march is performed deterministically. This work extends previous work by coupling the time-dependent expansions to space- and angle-dependent expansions to fully characterize the 1D transport response/solution. More generally, this approach represents and incremental extension of the steady-state coarse-mesh transport method that is based on global-local decompositions of large neutron transport problems. An example of a homogeneous slab is discussed as an example of the new developments.
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.
Model of electronic energy relaxation in the test-particle Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Roblin, P.; Rosengard, A. [CEA Centre d`Etudes de Saclay, 91 - Gif-sur-Yvette (France). Dept. des Procedes d`Enrichissement; Nguyen, T.T. [Compagnie Internationale de Services en Informatique (CISI) - Centre d`Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France)
1994-12-31
We previously presented a new test-particle Monte Carlo method (1) (which we call PTMC), an iterative method for solving the Boltzmann equation, and now improved and very well-suited to the collisional steady gas flows. Here, we apply a statistical method, described by Anderson (2), to treat electronic translational energy transfer by a collisional process, to atomic uranium vapor. For our study, only three levels of its multiple energy states are considered: 0,620 cm{sup -1} and an average level grouping upper levels. After presenting two-dimensional results, we apply this model to the evaporation of uranium by electron bombardment and show that the PTMC results, for given initial electronic temperatures, are in good agreement with experimental radial velocity measurements. (author). 12 refs., 1 fig.
Torsional diffusion Monte Carlo: A method for quantum simulations of proteins
Clary, David C.
2001-06-01
The quantum diffusion Monte Carlo (DMC) method is extended to the treatment of coupled torsional motions in proteins. A general algorithm and computer program has been developed by interfacing this torsional-DMC method with all-atom force-fields for proteins. The method gives the zero-point energy and atomic coordinates averaged over the coupled torsional motions in the quantum ground state of the protein. Application of the new algorithm is made to the proteins gelsolin (356 atoms and 142 torsions) and gp41-HIV (1101 atoms and 452 torsions). The results indicate that quantum-dynamical effects are important for the energies and geometries of typical proteins such as these.
DEFF Research Database (Denmark)
Anders, Annett; Nishijima, Kazuyoshi
The present paper aims at enhancing a solution approach proposed by Anders & Nishijima (2011) to real-time decision problems in civil engineering. The approach takes basis in the Least Squares Monte Carlo method (LSM) originally proposed by Longstaff & Schwartz (2001) for computing American option...... prices. In Anders & Nishijima (2011) the LSM is adapted for a real-time operational decision problem; however it is found that further improvement is required in regard to the computational efficiency, in order to facilitate it for practice. This is the focus in the present paper. The idea behind...... the improvement of the computational efficiency is to “best utilize” the least squares method; i.e. least squares method is applied for estimating the expected utility for terminal decisions, conditional on realizations of underlying random phenomena at respective times in a parametric way. The implementation...
DEFF Research Database (Denmark)
Tycho, Andreas; Jørgensen, Thomas Martini; Andersen, Peter E.
2002-01-01
A Monte Carlo (MC) method for modeling optical coherence tomography (OCT) measurements of a diffusely reflecting discontinuity emb edded in a scattering medium is presented. For the first time to the authors' knowledge it is shown analytically that the applicability of an MC approach...... from the sample will have a finite spatial coherence that cannot be accounted for by MC simulation. To estimate this intensity distribution adequately we have developed a novel method for modeling a focused Gaussian beam in MC simulation. This approach is valid for a softly as well as for a strongly...... focused beam, and it is shown that in free space the full three-dimensional intensity distribution of a Gaussian beam is obtained. The OCT signal and the intensity distribution in a scattering medium have been obtained for several geometries with the suggested MC method; when this model and a recently...
Quantum Monte Carlo methods and strongly correlated electrons on honeycomb structures
Energy Technology Data Exchange (ETDEWEB)
Lang, Thomas C.
2010-12-16
In this thesis we apply recently developed, as well as sophisticated quantum Monte Carlo methods to numerically investigate models of strongly correlated electron systems on honeycomb structures. The latter are of particular interest owing to their unique properties when simulating electrons on them, like the relativistic dispersion, strong quantum fluctuations and their resistance against instabilities. This work covers several projects including the advancement of the weak-coupling continuous time quantum Monte Carlo and its application to zero temperature and phonons, quantum phase transitions of valence bond solids in spin-1/2 Heisenberg systems using projector quantum Monte Carlo in the valence bond basis, and the magnetic field induced transition to a canted antiferromagnet of the Hubbard model on the honeycomb lattice. The emphasis lies on two projects investigating the phase diagram of the SU(2) and the SU(N)-symmetric Hubbard model on the hexagonal lattice. At sufficiently low temperatures, condensed-matter systems tend to develop order. An exception are quantum spin-liquids, where fluctuations prevent a transition to an ordered state down to the lowest temperatures. Previously elusive in experimentally relevant microscopic two-dimensional models, we show by means of large-scale quantum Monte Carlo simulations of the SU(2) Hubbard model on the honeycomb lattice, that a quantum spin-liquid emerges between the state described by massless Dirac fermions and an antiferromagnetically ordered Mott insulator. This unexpected quantum-disordered state is found to be a short-range resonating valence bond liquid, akin to the one proposed for high temperature superconductors. Inspired by the rich phase diagrams of SU(N) models we study the SU(N)-symmetric Hubbard Heisenberg quantum antiferromagnet on the honeycomb lattice to investigate the reliability of 1/N corrections to large-N results by means of numerically exact QMC simulations. We study the melting of phases
Sadi, M; Dabir, B
2003-01-01
Monte Carlo Method is one of the most powerful techniques to model different processes, such as polymerization reactions. By this method, without any need to solve moment equations, a very detailed information on the structure and properties of polymers are obtained. The number of algorithm repetitions (selected volumes of reactor for modelling which represent the number of initial molecules) is very important in this method. In Monte Carlo method calculations are based on the random number of generations and reaction probability determinations. so the number of algorithm repetition is very important. In this paper, the initiation reaction was considered alone and the importance of number of initiator molecules on the result were studied. It can be concluded that Monte Carlo method will not give accurate results if the number of molecules is not satisfied to be big enough, because in that case , selected volume would not be representative of the whole system.
Energy Technology Data Exchange (ETDEWEB)
Bianchini, G.; Burgio, N.; Carta, M. [ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy); Peluso, V. [ENEA C.R. BOLOGNA, Via Martiri di Monte Sole, 4, 40129 Bologna (Italy); Fabrizio, V.; Ricci, L. [Univ. of Rome La Sapienza, C/o ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy)
2012-07-01
The GUINEVERE experiment (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) is an experimental program in support of the ADS technology presently carried out at SCK-CEN in Mol (Belgium). In the experiment a modified lay-out of the original thermal VENUS critical facility is coupled to an accelerator, built by the French body CNRS in Grenoble, working in both continuous and pulsed mode and delivering 14 MeV neutrons by bombardment of deuterons on a tritium-target. The modified lay-out of the facility consists of a fast subcritical core made of 30% U-235 enriched metallic Uranium in a lead matrix. Several off-line and on-line reactivity measurement techniques will be investigated during the experimental campaign. This report is focused on the simulation by deterministic (ERANOS French code) and Monte Carlo (MCNPX US code) calculations of three reactivity measurement techniques, Slope ({alpha}-fitting), Area-ratio and Source-jerk, applied to a GUINEVERE subcritical configuration (namely SC1). The inferred reactivity, in dollar units, by the Area-ratio method shows an overall agreement between the two deterministic and Monte Carlo computational approaches, whereas the MCNPX Source-jerk results are affected by large uncertainties and allow only partial conclusions about the comparison. Finally, no particular spatial dependence of the results is observed in the case of the GUINEVERE SC1 subcritical configuration. (authors)
On stochastic error and computational efficiency of the Markov Chain Monte Carlo method
Li, Jun
2014-01-01
In Markov Chain Monte Carlo (MCMC) simulations, thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. These samples are selected in accordance with the probability distribution function, known from the partition function of equilibrium state. As the stochastic error of the simulation results is significant, it is desirable to understand the variance of the estimation by ensemble average, which depends on the sample size (i.e., the total number of samples in the set) and the sampling interval (i.e., cycle number between two consecutive samples). Although large sample sizes reduce the variance, they increase the computational cost of the simulation. For a given CPU time, the sample size can be reduced greatly by increasing the sampling interval, while having the corresponding increase in variance be negligible if the original sampling interval is very small. In this work, we report a few general rules that relate the variance with the sample size and the sampling interval. These results are observed and confirmed numerically. These variance rules are derived for theMCMCmethod but are also valid for the correlated samples obtained using other Monte Carlo methods. The main contribution of this work includes the theoretical proof of these numerical observations and the set of assumptions that lead to them. © 2014 Global-Science Press.
Gong, Xingchu; Li, Yao; Chen, Huali; Qu, Haibin
2015-01-01
A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10,000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.
Monte Carlo methods for optimizing the piecewise constant Mumford-Shah segmentation model
Energy Technology Data Exchange (ETDEWEB)
Watanabe, Hiroshi; Sashida, Satoshi; Okabe, Yutaka [Department of Physics, Tokyo Metropolitan University, Hachioji, Tokyo 192-0397 (Japan); Lee, Hwee Kuan, E-mail: leehk@bii.a-star.edu.sg [Bioinformatics Institute, 30 Biopolis Street, No. 07-01, Matrix, Singapore 138671 (Singapore)
2011-02-15
Natural images are depicted in a computer as pixels on a square grid and neighboring pixels are generally highly correlated. This representation can be mapped naturally to a statistical physics framework on a square lattice. In this paper, we developed an effective use of statistical mechanics to solve the image segmentation problem, which is an outstanding problem in image processing. Our Monte Carlo method using several advanced techniques, including block-spin transformation, Eden clustering and simulated annealing, seeks the solution of the celebrated Mumford-Shah image segmentation model. In particular, the advantage of our method is prominent for the case of multiphase segmentation. Our results verify that statistical physics can be a very efficient approach for image processing.
DEFF Research Database (Denmark)
Debrabant, Kristian; Samaey, Giovanni; Zieliński, Przemysław
2017-01-01
We present and analyse a micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations with separation between the (fast) time-scale of individual trajectories and the (slow) time-scale of the macroscopic function of interest. The algorithm combines short...... bursts of path simulations with extrapolation of a number of macroscopic state variables forward in time. The new microscopic state, consistent with the extrapolated variables, is obtained by a matching operator that minimises the perturbation caused by the extrapolation. We provide a proof...... of the convergence of this method, in the absence of statistical error, and we analyse various strategies for matching, as an operator on probability measures. Finally, we present numerical experiments that illustrate the effects of the different approximations on the resulting error in macroscopic predictions....
Integrated Building Energy Design of a Danish Office Building Based on Monte Carlo Simulation Method
DEFF Research Database (Denmark)
Sørensen, Mathias Juul; Myhre, Sindre Hammer; Hansen, Kasper Kingo
2017-01-01
and improve the collaboration efficiency. Monte Carlo Simulation method is adopted to simulate both the energy performance and indoor climate of the building. Building physics parameters, including characteristics of facades, walls, windows, etc., are taken into consideration, and thousands of combinations......The focus on reducing buildings energy consumption is gradually increasing, and the optimization of a building’s performance and maximizing its potential leads to great challenges between architects and engineers. In this study, we collaborate with a group of architects on a design project of a new...... office building located in Aarhus, Denmark. Building geometry, floor plans and employee schedules were obtained from the architects which is the basis for this study. This study aims to simplify the iterative design process that is based on the traditional trial and error method in the late design phases...
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.
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.
Akhmatskaya, Elena; Fernández-Pendás, Mario; Radivojević, Tijana; Sanz-Serna, J M
2017-10-24
The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modified Hamiltonians within a Hybrid Monte Carlo (HMC) framework, often outperform in sampling efficiency standard techniques such as molecular dynamics (MD) and HMC. The performance of MHMC may be enhanced further through the rational choice of the simulation parameters and by replacing the standard Verlet integrator with more sophisticated splitting algorithms. Unfortunately, it is not easy to identify the appropriate values of the parameters that appear in those algorithms. We propose a technique, that we call MAIA (Modified Adaptive Integration Approach), which, for a given simulation system and a given time step, automatically selects the optimal integrator within a useful family of two-stage splitting formulas. Extended MAIA (or e-MAIA) is an enhanced version of MAIA, which additionally supplies a value of the method-specific parameter that, for the problem under consideration, keeps the momentum acceptance rate at a user-desired level. The MAIA and e-MAIA algorithms have been implemented, with no computational overhead during simulations, in MultiHMC-GROMACS, a modified version of the popular software package GROMACS. Tests performed on well-known molecular models demonstrate the superiority of the suggested approaches over a range of integrators (both standard and recently developed), as well as their capacity to improve the sampling efficiency of GSHMC, a noticeable method for molecular simulation in the MHMC family. GSHMC combined with e-MAIA shows a remarkably good performance when compared to MD and HMC coupled with the appropriate adaptive integrators.
Hybrid Monte Carlo/Deterministic Methods for Accelerating Active Interrogation Modeling
Energy Technology Data Exchange (ETDEWEB)
Peplow, Douglas E. [ORNL; Miller, Thomas Martin [ORNL; Patton, Bruce W [ORNL; Wagner, John C [ORNL
2013-01-01
The potential for smuggling special nuclear material (SNM) into the United States is a major concern to homeland security, so federal agencies are investigating a variety of preventive measures, including detection and interdiction of SNM during transport. One approach for SNM detection, called active interrogation, uses a radiation source, such as a beam of neutrons or photons, to scan cargo containers and detect the products of induced fissions. In realistic cargo transport scenarios, the process of inducing and detecting fissions in SNM is difficult due to the presence of various and potentially thick materials between the radiation source and the SNM, and the practical limitations on radiation source strength and detection capabilities. Therefore, computer simulations are being used, along with experimental measurements, in efforts to design effective active interrogation detection systems. The computer simulations mostly consist of simulating radiation transport from the source to the detector region(s). Although the Monte Carlo method is predominantly used for these simulations, difficulties persist related to calculating statistically meaningful detector responses in practical computing times, thereby limiting their usefulness for design and evaluation of practical active interrogation systems. In previous work, the benefits of hybrid methods that use the results of approximate deterministic transport calculations to accelerate high-fidelity Monte Carlo simulations have been demonstrated for source-detector type problems. In this work, the hybrid methods are applied and evaluated for three example active interrogation problems. Additionally, a new approach is presented that uses multiple goal-based importance functions depending on a particle s relevance to the ultimate goal of the simulation. Results from the examples demonstrate that the application of hybrid methods to active interrogation problems dramatically increases their calculational efficiency.
An improved random walk algorithm for the implicit Monte Carlo method
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Keady, Kendra P., E-mail: keadyk@lanl.gov; Cleveland, Mathew A.
2017-01-01
In this work, we introduce a modified Implicit Monte Carlo (IMC) Random Walk (RW) algorithm, which increases simulation efficiency for multigroup radiative transfer problems with strongly frequency-dependent opacities. To date, the RW method has only been implemented in “fully-gray” form; that is, the multigroup IMC opacities are group-collapsed over the full frequency domain of the problem to obtain a gray diffusion problem for RW. This formulation works well for problems with large spatial cells and/or opacities that are weakly dependent on frequency; however, the efficiency of the RW method degrades when the spatial cells are thin or the opacities are a strong function of frequency. To address this inefficiency, we introduce a RW frequency group cutoff in each spatial cell, which divides the frequency domain into optically thick and optically thin components. In the modified algorithm, opacities for the RW diffusion problem are obtained by group-collapsing IMC opacities below the frequency group cutoff. Particles with frequencies above the cutoff are transported via standard IMC, while particles below the cutoff are eligible for RW. This greatly increases the total number of RW steps taken per IMC time-step, which in turn improves the efficiency of the simulation. We refer to this new method as Partially-Gray Random Walk (PGRW). We present numerical results for several multigroup radiative transfer problems, which show that the PGRW method is significantly more efficient than standard RW for several problems of interest. In general, PGRW decreases runtimes by a factor of ∼2–4 compared to standard RW, and a factor of ∼3–6 compared to standard IMC. While PGRW is slower than frequency-dependent Discrete Diffusion Monte Carlo (DDMC), it is also easier to adapt to unstructured meshes and can be used in spatial cells where DDMC is not applicable. This suggests that it may be optimal to employ both DDMC and PGRW in a single simulation.
Seismic wavefield imaging based on the replica exchange Monte Carlo method
Kano, Masayuki; Nagao, Hiromichi; Ishikawa, Daichi; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2017-01-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas that have capital functions. To reduce the number and severity of secondary disasters, it is important to evaluate seismic hazards rapidly by analysing the seismic responses of individual structures to input ground motions. We propose a method that integrates physics-based and data-driven approaches in order to obtain a seismic wavefield for use as input to a seismic response analysis. The new contribution of this study is the use of the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for estimation of a seismic wavefield, together with a 1-D local subsurface structure and source information. Numerical tests were conducted to verify the proposed method, using synthetic observation data obtained from analytical solutions for two horizontally layered subsurface structure models. The geometries of the observation sites were determined from the dense seismic observation array called the Metropolitan Seismic Observation network, which has been in operation in the Tokyo metropolitan area in Japan since 2007. The results of the numerical tests show that the proposed method is able to search the parameters related to the source and the local subsurface structure in a broader parameter space than the Metropolis method, which is an ordinary MCMC method. The proposed method successfully reproduces a seismic wavefield consistent with a true wavefield. In contrast, ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce a true wavefield, even in the low frequency bands. This suggests that it is essential to employ both physics-based and data-driven approaches in seismic wavefield imaging, utilizing seismograms from a dense seismic array. The REMC method, which provides not only
Barrier heights of hydrogen-transfer reactions with diffusion quantum monte carlo method.
Zhou, Xiaojun; Wang, Fan
2017-04-30
Hydrogen-transfer reactions are an important class of reactions in many chemical and biological processes. Barrier heights of H-transfer reactions are underestimated significantly by popular exchange-correlation functional with density functional theory (DFT), while coupled-cluster (CC) method is quite expensive and can be applied only to rather small systems. Quantum Monte-Carlo method can usually provide reliable results for large systems. Performance of fixed-node diffusion quantum Monte-Carlo method (FN-DMC) on barrier heights of the 19 H-transfer reactions in the HTBH38/08 database is investigated in this study with the trial wavefunctions of the single-Slater-Jastrow form and orbitals from DFT using local density approximation. Our results show that barrier heights of these reactions can be calculated rather accurately using FN-DMC and the mean absolute error is 1.0 kcal/mol in all-electron calculations. Introduction of pseudopotentials (PP) in FN-DMC calculations improves efficiency pronouncedly. According to our results, error of the employed PPs is smaller than that of the present CCSD(T) and FN-DMC calculations. FN-DMC using PPs can thus be applied to investigate H-transfer reactions involving larger molecules reliably. In addition, bond dissociation energies of the involved molecules using FN-DMC are in excellent agreement with reference values and they are even better than results of the employed CCSD(T) calculations using the aug-cc-pVQZ basis set. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
A modular method to handle multiple time-dependent quantities in Monte Carlo simulations
Shin, J.; Perl, J.; Schümann, J.; Paganetti, H.; Faddegon, B. A.
2012-06-01
A general method for handling time-dependent quantities in Monte Carlo simulations was developed to make such simulations more accessible to the medical community for a wide range of applications in radiotherapy, including fluence and dose calculation. To describe time-dependent changes in the most general way, we developed a grammar of functions that we call ‘Time Features’. When a simulation quantity, such as the position of a geometrical object, an angle, a magnetic field, a current, etc, takes its value from a Time Feature, that quantity varies over time. The operation of time-dependent simulation was separated into distinct parts: the Sequence samples time values either sequentially at equal increments or randomly from a uniform distribution (allowing quantities to vary continuously in time), and then each time-dependent quantity is calculated according to its Time Feature. Due to this modular structure, time-dependent simulations, even in the presence of multiple time-dependent quantities, can be efficiently performed in a single simulation with any given time resolution. This approach has been implemented in TOPAS (TOol for PArticle Simulation), designed to make Monte Carlo simulations with Geant4 more accessible to both clinical and research physicists. To demonstrate the method, three clinical situations were simulated: a variable water column used to verify constancy of the Bragg peak of the Crocker Lab eye treatment facility of the University of California, the double-scattering treatment mode of the passive beam scattering system at Massachusetts General Hospital (MGH), where a spinning range modulator wheel accompanied by beam current modulation produces a spread-out Bragg peak, and the scanning mode at MGH, where time-dependent pulse shape, energy distribution and magnetic fields control Bragg peak positions. Results confirm the clinical applicability of the method.
Dose Assessment of Eye and Its Components in Proton Therapy by Monte Carlo Method
Directory of Open Access Journals (Sweden)
Marzieh Tavakol
2014-04-01
Full Text Available Introduction Proton therapy is used to treat malignant tumors such as melanoma inside the eye. Proton particles are adjusted according to various parameters such as tumor size and position and patient’s distance from the proton source. The purpose of this study was to assess absorbed doses in eyes and various tumors found in the area of sclera and choroid and the adjacent tissues in radiotherapy while changing most important proton therapy parameters such as moderators thickness (1.5-1.9 cm, exposure radius (0.5-0.8 cm, and proton energy beam (53.5-65 MeV. Materials and Methods A proton therapy system of Laboratori Nazionali del Sud-INFNwas simulated by Monte Carlo method. Moreover, the eye and its components were simulated using concentric spheres. To obtain a more accurate results, real density of eye components such as cornea and lens, were applied for simulation. Then, the absorbed dose of eye and eye tumor, in choroid and sclera areas, were calculated by Monte Carlo method. Results The absorbed dose in tumoral region of eye was calculated to be about 12.5 ±0.006Gy in one day with energy 62 MeV for a therapy session, which is suitable for treatment. However, normal eye cells received at most 11.01 Gy which is high. Conclusion The amount of absorbed dose in tumoral cells is noticeable. Therefore, accurate treatment planning, patient immobility and fine calibration of proton-therapy system and its simulator are very important to reduce the absorbed dose of healthy cells.
Directory of Open Access Journals (Sweden)
A. Sosa
2012-03-01
Full Text Available A study of the dielectric and magnetic properties of multiferroic materials using the Monte Carlo (MC method is presented. Two different systems are considered: the first, ferroelectric-antiferromagnetic (FE-AFM recently studied by X. S. Gaoand J. M. Liu and the second antiferroelectric-ferromagnetic (AFE-FM. Based on the DIFFOUR-Ising hybrid microscopic model developed by Janssen, a Hamiltonian that takes into account the magnetoelectric coupling in both ferroic phases is proposed. The obtained results show that the existence of such coupling modifies the ferroelectric and magnetic ordering in both phases. Additionally, it is shown that the presence of a magnetic or an electric field influences the electric polarization and the magnetization, respectively, making evident the magnetoelectric effect.
The FLUKA code for application of Monte Carlo methods to promote high precision ion beam therapy
Parodi, K; Cerutti, F; Ferrari, A; Mairani, A; Paganetti, H; Sommerer, F
2010-01-01
Monte Carlo (MC) methods are increasingly being utilized to support several aspects of commissioning and clinical operation of ion beam therapy facilities. In this contribution two emerging areas of MC applications are outlined. The value of MC modeling to promote accurate treatment planning is addressed via examples of application of the FLUKA code to proton and carbon ion therapy at the Heidelberg Ion Beam Therapy Center in Heidelberg, Germany, and at the Proton Therapy Center of Massachusetts General Hospital (MGH) Boston, USA. These include generation of basic data for input into the treatment planning system (TPS) and validation of the TPS analytical pencil-beam dose computations. Moreover, we review the implementation of PET/CT (Positron-Emission-Tomography / Computed- Tomography) imaging for in-vivo verification of proton therapy at MGH. Here, MC is used to calculate irradiation-induced positron-emitter production in tissue for comparison with the +-activity measurement in order to infer indirect infor...
A constrained-equilibrium Monte Carlo method for quantum dots-the problem of intermixing
Energy Technology Data Exchange (ETDEWEB)
Kelires, P C [Physics Department, University of Crete, PO Box 2208, 710 03 Heraclion, Crete (Greece); Foundation for Research and Technology-Hellas (FORTH), PO Box 1527, 711 10 Heraclion, Crete (Greece)
2004-05-05
Islands grown during semiconductor heteroepitaxy are in a thermodynamically metastable state. Experiments show that diffusion at the surface region, including the interior of the islands, is fast enough to establish local equilibrium. I review here applications of a Monte Carlo method which takes advantage of the quasi-equilibrium nature of quantum dots and is able to address the issue of intermixing and island composition. Both Ge islands grown on the bare Si(100) surface and C-induced Ge islands grown on Si(100) precovered with C are discussed. In the bare case, the interlinking of the stress field with the composition is revealed. Both are strongly inhomogeneous. In the C-induced case, the interplay of strain and chemical effects is the dominant key factor. Islands do not contain C under any conditions of coverage and temperature.
Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review
Directory of Open Access Journals (Sweden)
Ammar M. A. Abu Znaid
2017-01-01
Full Text Available The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages and disadvantages. The similarities and differences of each scheme are investigated on the basis of significant parameters, namely, localization accuracy, computational cost, communication cost, and number of samples. We discuss the challenges and direction of the future research work for each parameter.
Direct simulation Monte Carlo method for gas cluster ion beam technology
Insepov, Z
2003-01-01
A direct simulation Monte Carlo method has been developed and applied for the simulation of a supersonic Ar gas expansion through a converging-diverging nozzle, with the stagnation pressures of P sub 0 =0.1-10 atm, at various temperatures. A body-fitted coordinate system has been developed that allows modeling nozzles of arbitrary shape. A wide selection of nozzle sizes, apex angles, with diffuse and specular atomic reflection laws from the nozzle walls, has been studied. The results of nozzle simulation were used to obtain a scaling law P sub 0 T sub 0 sup 1 sup 9 sup / sup 8 d supalpha L sub n supbeta=const. for the constant mean cluster sizes that are formed in conical nozzles. The Hagena's formula, valid for the conical nozzles with a constant length, has further been extended to the conical nozzles with variable lengths, based on our simulation results.
Accelerating mesh-based Monte Carlo method on modern CPU architectures.
Fang, Qianqian; Kaeli, David R
2012-12-01
In this report, we discuss the use of contemporary ray-tracing techniques to accelerate 3D mesh-based Monte Carlo photon transport simulations. Single Instruction Multiple Data (SIMD) based computation and branch-less design are exploited to accelerate ray-tetrahedron intersection tests and yield a 2-fold speed-up for ray-tracing calculations on a multi-core CPU. As part of this work, we have also studied SIMD-accelerated random number generators and math functions. The combination of these techniques achieved an overall improvement of 22% in simulation speed as compared to using a non-SIMD implementation. We applied this new method to analyze a complex numerical phantom and both the phantom data and the improved code are available as open-source software at http://mcx.sourceforge.net/mmc/.
Monte Carlo method for critical systems in infinite volume: The planar Ising model.
Herdeiro, Victor; Doyon, Benjamin
2016-10-01
In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three-, and four-point of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.
Electric conduction in semiconductors: a pedagogical model based on the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Capizzo, M C; Sperandeo-Mineo, R M; Zarcone, M [UoP-PERG, University of Palermo Physics Education Research Group and Dipartimento di Fisica e Tecnologie Relative, Universita di Palermo (Italy)], E-mail: sperandeo@difter.unipa.it
2008-05-15
We present a pedagogic approach aimed at modelling electric conduction in semiconductors in order to describe and explain some macroscopic properties, such as the characteristic behaviour of resistance as a function of temperature. A simple model of the band structure is adopted for the generation of electron-hole pairs as well as for the carrier transport in moderate electric fields. The semiconductor behaviour is described by substituting the traditional statistical approach (requiring a deep mathematical background) with microscopic models, based on the Monte Carlo method, in which simple rules applied to microscopic particles and quasi-particles determine the macroscopic properties. We compare measurements of electric properties of matter with 'virtual experiments' built by using some models where the physical concepts can be presented at different formalization levels.
Directory of Open Access Journals (Sweden)
Ertekin Öztekin Öztekin
2015-12-01
Full Text Available Design of the distance of bolts to each other and design of the distance of bolts to the edge of connection plates are made based on minimum and maximum boundary values proposed by structural codes. In this study, reliabilities of those distances were investigated. For this purpose, loading types, bolt types and plate thicknesses were taken as variable parameters. Monte Carlo Simulation (MCS method was used in the reliability computations performed for all combination of those parameters. At the end of study, all reliability index values for all those distances were presented in graphics and tables. Results obtained from this study compared with the values proposed by some structural codes and finally some evaluations were made about those comparisons. Finally, It was emphasized in the end of study that, it would be incorrect of the usage of the same bolt distances in the both traditional designs and the higher reliability level designs.
Calculation of backscatter factors for diagnostic radiology using Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Petoussi-Henss, N.; Zankl, M.; Drexler, G.; Panzer, W.; Regulla, D. [GSF-National Research Center for Environment and Health, Institute of Radiation Protection, Ingolstaedter Landstrasse 1, D-85764 Neuherberg (Germany)
1998-08-01
Backscatter factors were determined for x-ray beams relevant to diagnostic radiology using Monte Carlo methods. The phantom size considered most suitable for calibration of dosimeters is a cuboid of 30x30cm{sup 2} front surface and 15 cm depth. This phantom size also provides a good approximation to adult patients. Three different media were studied: water, PMMA and ICRU tissue; the source geometry was a point source with varying field size and source-to-phantom distance. The variations of the backscatter factor with phantom medium and field geometry were examined. From the obtained data, a set of backscatter factors was selected and proposed for adoption as a standard set for the calibration of dosimeters to be used to measure diagnostic reference doses. (author)
An Approach in Radiation Therapy Treatment Planning: A Fast, GPU-Based Monte Carlo Method.
Karbalaee, Mojtaba; Shahbazi-Gahrouei, Daryoush; Tavakoli, Mohammad B
2017-01-01
An accurate and fast radiation dose calculation is essential for successful radiation radiotherapy. The aim of this study was to implement a new graphic processing unit (GPU) based radiation therapy treatment planning for accurate and fast dose calculation in radiotherapy centers. A program was written for parallel running based on GPU. The code validation was performed by EGSnrc/DOSXYZnrc. Moreover, a semi-automatic, rotary, asymmetric phantom was designed and produced using a bone, the lung, and the soft tissue equivalent materials. All measurements were performed using a Mapcheck dosimeter. The accuracy of the code was validated using the experimental data, which was obtained from the anthropomorphic phantom as the gold standard. The findings showed that, compared with those of DOSXYZnrc in the virtual phantom and for most of the voxels (>95%), GPU-based Monte Carlo method in dose calculation may be useful in routine radiation therapy centers as the core and main component of a treatment planning verification system.
Application of multi-stage Monte Carlo method for solving machining optimization problems
Directory of Open Access Journals (Sweden)
Miloš Madić
2014-08-01
Full Text Available Enhancing the overall machining performance implies optimization of machining processes, i.e. determination of optimal machining parameters combination. Optimization of machining processes is an active field of research where different optimization methods are being used to determine an optimal combination of different machining parameters. In this paper, multi-stage Monte Carlo (MC method was employed to determine optimal combinations of machining parameters for six machining processes, i.e. drilling, turning, turn-milling, abrasive waterjet machining, electrochemical discharge machining and electrochemical micromachining. Optimization solutions obtained by using multi-stage MC method were compared with the optimization solutions of past researchers obtained by using meta-heuristic optimization methods, e.g. genetic algorithm, simulated annealing algorithm, artificial bee colony algorithm and teaching learning based optimization algorithm. The obtained results prove the applicability and suitability of the multi-stage MC method for solving machining optimization problems with up to four independent variables. Specific features, merits and drawbacks of the MC method were also discussed.
Multi-Index Monte Carlo and stochastic collocation methods for random PDEs
Nobile, Fabio
2016-01-09
In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.
Qian, Lin-Feng; Shi, Guo-Dong; Huang, Yong; Xing, Yu-Ming
2017-10-01
In vector radiative transfer, backward ray tracing is seldom used. We present a backward and forward Monte Carlo method to simulate vector radiative transfer in a two-dimensional graded index medium, which is new and different from the conventional Monte Carlo method. The backward and forward Monte Carlo method involves dividing the ray tracing into two processes backward tracing and forward tracing. In multidimensional graded index media, the trajectory of a ray is usually a three-dimensional curve. During the transport of a polarization ellipse, the curved ray trajectory will induce geometrical effects and cause Stokes parameters to continuously change. The solution processes for a non-scattering medium and an anisotropic scattering medium are analysed. We also analyse some parameters that influence the Stokes vector in two-dimensional graded index media. The research shows that the Q component of the Stokes vector cannot be ignored. However, the U and V components of the Stokes vector are very small.
A First-Passage Kinetic Monte Carlo method for reaction-drift-diffusion processes
Mauro, Ava J.; Sigurdsson, Jon Karl; Shrake, Justin; Atzberger, Paul J.; Isaacson, Samuel A.
2014-02-01
Stochastic reaction-diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker-Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift-diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.
Energy Technology Data Exchange (ETDEWEB)
Li, M
1998-08-01
In this thesis, two methods for solving the multigroup Boltzmann equation have been studied: the interface-current method and the Monte Carlo method. A new version of interface-current (IC) method has been develop in the TDT code at SERMA, where the currents of interface are represented by piecewise constant functions in the solid angle space. The convergence of this method to the collision probability (CP) method has been tested. Since the tracking technique is used for both the IC and CP methods, it is necessary to normalize he collision probabilities obtained by this technique. Several methods for this object have been studied and implemented in our code, we have compared their performances and chosen the best one as the standard choice. The transfer matrix treatment has been a long-standing difficulty for the multigroup Monte Carlo method: when the cross-sections are converted into multigroup form, important negative parts will appear in the angular transfer laws represented by low-order Legendre polynomials. Several methods based on the preservation of the first moments, such as the discrete angles methods and the equally-probable step function method, have been studied and implemented in the TRIMARAN-II code. Since none of these codes has been satisfactory, a new method, the non equally-probably step function method, has been proposed and realized in our code. The comparisons for these methods have been done in several aspects: the preservation of the moments required, the calculation of a criticality problem and the calculation of a neutron-transfer in water problem. The results have showed that the new method is the best one in all these comparisons, and we have proposed that it should be a standard choice for the multigroup transfer matrix. (author) 76 refs.
The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations
Energy Technology Data Exchange (ETDEWEB)
Sellier, J.M., E-mail: jeanmichel.sellier@parallel.bas.bg; Dimov, I.
2014-09-15
The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practically unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.
Le Foll, S.; André, F.; Delmas, A.; Bouilly, J. M.; Aspa, Y.
2012-06-01
A backward Monte Carlo method for modelling the spectral directional emittance of fibrous media has been developed. It uses Mie theory to calculate the radiative properties of single fibres, modelled as infinite cylinders, and the complex refractive index is computed by a Drude-Lorenz model for the dielectric function. The absorption and scattering coefficient are homogenised over several fibres, but the scattering phase function of a single one is used to determine the scattering direction of energy inside the medium. Sensitivity analysis based on several Monte Carlo results has been performed to estimate coefficients for a Multi-Linear Model (MLM) specifically developed for inverse analysis of experimental data. This model concurs with the Monte Carlo method and is highly computationally efficient. In contrast, the surface emissivity model, which assumes an opaque medium, shows poor agreement with the reference Monte Carlo calculations.
Energy Technology Data Exchange (ETDEWEB)
Oh, Kye Min [KHNP Central Research Institute, Daejeon (Korea, Republic of); Han, Sang Hoon; Park, Jin Hee; Lim, Ho Gon; Yang, Joon Yang [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of)
2017-06-15
In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.
Directory of Open Access Journals (Sweden)
Kyemin Oh
2017-06-01
Full Text Available In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA. One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.
Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods
Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.
1994-01-01
Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.
Haji Ali, Abdul Lateef
2016-01-08
I discuss using single level and multilevel Monte Carlo methods to compute quantities of interests of a stochastic particle system in the mean-field. In this context, the stochastic particles follow a coupled system of Ito stochastic differential equations (SDEs). Moreover, this stochastic particle system converges to a stochastic mean-field limit as the number of particles tends to infinity. I start by recalling the results of applying different versions of Multilevel Monte Carlo (MLMC) for particle systems, both with respect to time steps and the number of particles and using a partitioning estimator. Next, I expand on these results by proposing the use of our recent Multi-index Monte Carlo method to obtain improved convergence rates.
Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks
Ben Hammouda, Chiheb
2015-05-12
In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for
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.
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).
Risk assessment of water quality using Monte Carlo simulation and artificial neural network method.
Jiang, Yunchao; Nan, Zhongren; Yang, Sucai
2013-06-15
There is always uncertainty in any water quality risk assessment. A Monte Carlo simulation (MCS) is regarded as a flexible, efficient method for characterizing such uncertainties. However, the required computational effort for MCS-based risk assessment is great, particularly when the number of random variables is large and the complicated water quality models have to be calculated by a computationally expensive numerical method, such as the finite element method (FEM). To address this issue, this paper presents an improved method that incorporates an artificial neural network (ANN) into the MCS to enhance the computational efficiency of conventional risk assessment. The conventional risk assessment uses the FEM to create multiple water quality models, which can be time consuming or cumbersome. In this paper, an ANN model was used as a substitute for the iterative FEM runs, and thus, the number of water quality models that must be calculated can be dramatically reduced. A case study on the chemical oxygen demand (COD) pollution risks in the Lanzhou section of the Yellow River in China was taken as a reference. Compared with the conventional risk assessment method, the ANN-MCS-based method can save much computational effort without a loss of accuracy. The results show that the proposed method in this paper is more applicable to assess water quality risks. Because the characteristics of this ANN-MCS-based technique are quite general, it is hoped that the technique can also be applied to other MCS-based uncertainty analysis in the environmental field. Copyright © 2013 Elsevier Ltd. All rights reserved.
Guerra, Marta L.
2009-02-23
We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.
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.
Goto, Makoto; Kondoh, Yoshiomi
1998-01-01
A self-consistent Monte Carlo modelling technique has been developed to study normal and abnormal glow discharge plasmas. To simulate nonequilibrium particles, a limited weight probability method is introduced and a fine subslab system is used. These two methods are applied to a DC Ar-like gas discharge simulation. The simulations are performed for conditions corresponding to the experimental voltage and current sets of normal and abnormal glow disharges. The characteristic spatial profiles of plasmas for normal and abnormal glow discharges with high nonequilibrium electron energy distributions are obtained. The increase in the current and the voltage from the normal glow leads to the following: (1) the density peak of the ions rises in the cathode region, (2) the density peak of electrons rises and catches up with that of ions and the peak position occurs closer to the cathode simultaneously; instead of a small increase of plasma density in the bulk plasma region, (3) reversal field strength next to the cathode fall increases and (4) the two groups of the enregy distribution separates into three groups at the cathode fall edge.
Multiscale Finite-Difference-Diffusion-Monte-Carlo Method for Simulating Dendritic Solidification
Plapp, Mathis; Karma, Alain
2000-12-01
We present a novel hybrid computational method to simulate accurately dendritic solidification in the low undercooling limit where the dendrite tip radius is one or more orders of magnitude smaller than the characteristic spatial scale of variation of the surrounding thermal or solutal diffusion field. The first key feature of this method is an efficient multiscale diffusion Monte Carlo (DMC) algorithm which allows off-lattice random walkers to take longer and concomitantly rarer steps with increasing distance away from the solid-liquid interface. As a result, the computational cost of evolving the large-scale diffusion field becomes insignificant when compared to that of calculating the interface evolution. The second key feature is that random walks are only permitted outside of a thin liquid layer surrounding the interface. Inside this layer and in the solid, the diffusion equation is solved using a standard finite difference algorithm that is interfaced with the DMC algorithm using the local conservation law for the diffusing quantity. Here we combine this algorithm with a previously developed phase-field formulation of the interface dynamics and demonstrate that it can accurately simulate three-dimensional dendritic growth in a previously unreachable range of low undercoolings that is of direct experimental relevance.
Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods
Directory of Open Access Journals (Sweden)
Qian Liu
2015-01-01
Full Text Available Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.
Verification of Transformer Restricted Earth Fault Protection by using the Monte Carlo Method
Directory of Open Access Journals (Sweden)
KRSTIVOJEVIC, J. P.
2015-08-01
Full Text Available The results of a comprehensive investigation of the influence of current transformer (CT saturation on restricted earth fault (REF protection during power transformer magnetization inrush are presented. Since the inrush current during switch-on of unloaded power transformer is stochastic, its values are obtained by: (i laboratory measurements and (ii calculations based on the input data obtained by the Monte Carlo (MC simulation. To make a detailed assessment of the current transformer performance the uncertain input data for the CT model were obtained by applying the MC method. In this way, different levels of remanent flux in CT core are taken into consideration. By the generated CT secondary currents, the algorithm for REF protection based on phase comparison in time domain is tested. On the basis of the obtained results, a method of adjustment of the triggering threshold in order to ensure safe operation during transients, and thereby improve the algorithm security, has been proposed. The obtained results indicate that power transformer REF protection would be enhanced by using the proposed adjustment of triggering threshold in the algorithm which is based on phase comparison in time domain.
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).
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.
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe
2010-01-01
limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...
Energy Technology Data Exchange (ETDEWEB)
Agudelo-Giraldo, J.D. [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo-Parra, E., E-mail: erestrepopa@unal.edu.co [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo, J. [Grupo de Magnetismo y Simulación, Instituto de Física, Universidad de Antioquia, A.A. 1226, Medellín (Colombia)
2015-10-01
The Metropolis algorithm and the classical Heisenberg approximation were implemented by the Monte Carlo method to design a computational approach to the magnetization and resistivity of La{sub 2/3}Ca{sub 1/3}MnO{sub 3}, which depends on the Mn ion vacancies as the external magnetic field increases. This compound is ferromagnetic, and it exhibits the colossal magnetoresistance (CMR) effect. The monolayer was built with L×L×d dimensions, and it had L=30 umc (units of magnetic cells) for its dimension in the x–y plane and was d=12 umc in thickness. The Hamiltonian that was used contains interactions between first neighbors, the magnetocrystalline anisotropy effect and the external applied magnetic field response. The system that was considered contains mixed-valence bonds: Mn{sup 3+eg’}–O–Mn{sup 3+eg}, Mn{sup 3+eg}–O–Mn{sup 4+d3} and Mn{sup 3+eg’}–O–Mn{sup 4+d3}. The vacancies were placed randomly in the sample, replacing any type of Mn ion. The main result shows that without vacancies, the transitions T{sub C} (Curie temperature) and T{sub MI} (metal–insulator temperature) are similar, whereas with the increase in the vacancy percentage, T{sub MI} presented lower values than T{sub C}. This situation is caused by the competition between the external magnetic field, the vacancy percentage and the magnetocrystalline anisotropy, which favors the magnetoresistive effect at temperatures below T{sub MI}. Resistivity loops were also observed, which shows a direct correlation with the hysteresis loops of magnetization at temperatures below T{sub C}. - Highlights: • Changes in the resistivity of FM materials as a function of the temperature and external magnetic field can be obtained by the Monte Carlo method, Metropolis algorithm, classical Heisenberg and Kronig–Penney approximation for magnetic clusters. • Increases in the magnetoresistive effect were observed at temperatures below T{sub MI} by the vacancies effect. • The resistive hysteresis
Directory of Open Access Journals (Sweden)
Vicente D. Estruch
2017-08-01
Full Text Available The concept of random variable is a mathematical construct that presents some theoretical complexity. However, learning this concept can be facilitated if it is presented as the end of a sequential process of modeling of a real event. More specifically, to learn the concept of discrete random variable, the Monte Carlo simulation can provide an extremely useful tool because in the process of modeling / simulation one can approach the theoretical concept of random variable, while the random variable is observed \\in action". This paper presents a Research and Study Course (RSC based on series of activities related to random variables such as training and introduction of simulation elements, then the construction of the model is presented, which is the substantial part of the activity, generating a random variable and its probability function. Starting from a simple situation related to reproduction and survival of the litter of a rodent, with random components, step by step, the model that represents the real raised situation is built obtaining an \\original" random variable. In the intermediate stages of the construction of the model have a fundamental role the uniform discrete and binomial distributions. The trajectory of these stages allows reinforcing the concept of random variable while exploring the possibilities offered by Monte Carlo methods to simulate real cases and the simplicity of implementing these methods by means of the Matlab© programming language.
Energy Technology Data Exchange (ETDEWEB)
Matsuno, Y. [Kumamoto University, Kumamoto (Japan). Faculty of Engineering; Oshima, K. [Kyocera Corp., Kyoto (Japan); Ogata, S. [Kubota Corp., Osaka (Japan)
1995-02-25
This paper presents an investigation on the configuration of the particles of a magnetic fluid and its magnetization characteristic based on Monte Carlo method. The interparticle interactions caused by the magneto static energy, the repulsion energy, the van der Waals energy and the external magnetic field energy are calculated. In the calculation, the distribution of magnetic particles is assumed to be a lognormal distribution estimated from that of a magnetic fluid under the investigation. The calculation results for a magnetization characteristic and for the orientation of magnetic particles of a magnetic fluid are compared with magnetization curves constructed from measured values and with an electron micrograph of magnetic particles, respectively. 10 refs., 17 figs., 4 tabs.
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.
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.
Constant-pH Hybrid Nonequilibrium Molecular Dynamics-Monte Carlo Simulation Method.
Chen, Yunjie; Roux, Benoît
2015-08-11
A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys. 2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD-MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD-MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems.
Constant-pH Hybrid Nonequilibrium Molecular Dynamics–Monte Carlo Simulation Method
2016-01-01
A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys.2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD–MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD–MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems. PMID:26300709
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.
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
Evaluation of the scattered radiation components produced in a gamma camera using Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Polo, Ivon Oramas, E-mail: ivonoramas67@gmail.com [Department of Nuclear Engineering, Faculty of Nuclear Sciences and Technologies, Higher Institute of Applied Science and Technology (InSTEC), La Habana (Cuba)
2014-07-01
Introduction: this paper presents a simulation for evaluation of the scattered radiation components produced in a gamma camera PARK using Monte Carlo code SIMIND. It simulates a whole body study with MDP (Methylene Diphosphonate) radiopharmaceutical based on Zubal anthropomorphic phantom, with some spinal lesions. Methods: the simulation was done by comparing 3 configurations for the detected photons. The corresponding energy spectra were obtained using Low Energy High Resolution collimator. The parameters related with the interactions and the fraction of events in the energy window, the simulated events of the spectrum and scatter events were calculated. Results: the simulation confirmed that the images without influence of scattering events have a higher number of valid recorded events and it improved the statistical quality of them. A comparison among different collimators was made. The parameters and detector energy spectrum were calculated for each simulation configuration with these collimators using {sup 99m}Tc. Conclusion: the simulation corroborated that LEHS collimator has higher sensitivity and HEHR collimator has lower sensitivity when they are used with low energy photons. (author)
Absorbed dose calculations using mesh-based human phantoms and Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Kramer, Richard [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil)
2010-07-01
Full text. Health risks attributable to ionizing radiation are considered to be a function of the absorbed dose to radiosensitive organs and tissues of the human body. However, as human tissue cannot express itself in terms of absorbed dose, exposure models have to be used to determine the distribution of absorbed dose throughout the human body. An exposure model, be it physical or virtual, consists of a representation of the human body, called phantom, plus a method for transporting ionizing radiation through the phantom and measuring or calculating the absorbed dose to organ and tissues of interest. Female Adult meSH (FASH) and the Male Adult meSH (MASH) virtual phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools. Representing standing adults, FASH and MASH have organ and tissue masses, body height and mass adjusted to the anatomical data published by the International Commission on Radiological Protection for the reference male and female adult. For the purposes of absorbed dose calculations the phantoms have been coupled to the EGSnrc Monte Carlo code, which transports photons, electrons and positrons through arbitrary media. This presentation reports on the development of the FASH and the MASH phantoms and will show dosimetric applications for X-ray diagnosis and for prostate brachytherapy. (author)
Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William
2017-09-01
Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.
Optimization of Control Points Number at Coordinate Measurements based on the Monte-Carlo Method
Korolev, A. A.; Kochetkov, A. V.; Zakharov, O. V.
2018-01-01
Improving the quality of products causes an increase in the requirements for the accuracy of the dimensions and shape of the surfaces of the workpieces. This, in turn, raises the requirements for accuracy and productivity of measuring of the workpieces. The use of coordinate measuring machines is currently the most effective measuring tool for solving similar problems. The article proposes a method for optimizing the number of control points using Monte Carlo simulation. Based on the measurement of a small sample from batches of workpieces, statistical modeling is performed, which allows one to obtain interval estimates of the measurement error. This approach is demonstrated by examples of applications for flatness, cylindricity and sphericity. Four options of uniform and uneven arrangement of control points are considered and their comparison is given. It is revealed that when the number of control points decreases, the arithmetic mean decreases, the standard deviation of the measurement error increases and the probability of the measurement α-error increases. In general, it has been established that it is possible to repeatedly reduce the number of control points while maintaining the required measurement accuracy.
Improving Bayesian analysis for LISA Pathfinder using an efficient Markov Chain Monte Carlo method
Ferraioli, Luigi; Porter, Edward K.; Armano, Michele; Audley, Heather; Congedo, Giuseppe; Diepholz, Ingo; Gibert, Ferran; Hewitson, Martin; Hueller, Mauro; Karnesis, Nikolaos; Korsakova, Natalia; Nofrarias, Miquel; Plagnol, Eric; Vitale, Stefano
2014-02-01
We present a parameter estimation procedure based on a Bayesian framework by applying a Markov Chain Monte Carlo algorithm to the calibration of the dynamical parameters of the LISA Pathfinder satellite. The method is based on the Metropolis-Hastings algorithm and a two-stage annealing treatment in order to ensure an effective exploration of the parameter space at the beginning of the chain. We compare two versions of the algorithm with an application to a LISA Pathfinder data analysis problem. The two algorithms share the same heating strategy but with one moving in coordinate directions using proposals from a multivariate Gaussian distribution, while the other uses the natural logarithm of some parameters and proposes jumps in the eigen-space of the Fisher Information matrix. The algorithm proposing jumps in the eigen-space of the Fisher Information matrix demonstrates a higher acceptance rate and a slightly better convergence towards the equilibrium parameter distributions in the application to LISA Pathfinder data. For this experiment, we return parameter values that are all within ˜1 σ of the injected values. When we analyse the accuracy of our parameter estimation in terms of the effect they have on the force-per-unit of mass noise, we find that the induced errors are three orders of magnitude less than the expected experimental uncertainty in the power spectral density.
Non-Local effective SU(2) Polyakov-loop models from inverse Monte-Carlo methods
Bahrampour, Bardiya; von Smekal, Lorenz
2016-01-01
The strong-coupling expansion of the lattice gauge action leads to Polyakov-loop models that effectively describe gluodynamics at low temperatures, and together with the hopping expansion of the fermion determinant provides insight into the QCD phase diagram at finite density and low temperatures, although for rather heavy quarks. At higher temperatures the strong-coupling expansion breaks down and it is expected that the interactions between Polyakov loops become non-local. Here, we therefore test how well pure SU(2) gluodynamics can be mapped onto different non-local Polyakov models with inverse Monte-Carlo methods. We take into account Polyakov loops in higher representations and gradually add interaction terms at larger distances. We are particularly interested in extrapolating the range of non-local terms in sufficiently large volumes and higher representations. We study the characteristic fall-off in strength of the non-local couplings with the interaction distance, and its dependence on the gauge coupl...
Zhang, Guannan; Del-Castillo-Negrete, Diego
2017-10-01
Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.
Reliability analysis of crankshaft for high-speed punch based on Monte-Carlo method
Zhang, Xinzhou; Chen, Lan; Gan, Shuyuan; Wang, Yuan; Ren, Naifei; Zhou, Jian
2017-10-01
The crankshaft, which has fateful consequence to the performance and reliability, is a key component of high-speed punch. In manufacturing process, the high reliability value of crankshaft contributes to the increasing of the reliability of the whole punch system. The study builds a reliability analysis model of the crankshaft for punching process under the premise of regarding design parameters as random variables. Monte-Carlo method is employed to make reliability analysis for crankshaft based on ANSYS. The numerical results present that the failure probability of strength and stiffness for crankshaft satisfied the use requirement. The impact of every input variable on reliability are obtained from the sensitivity analysis of status function factors. The design variable D4 and PRXY have the greatest impact on the strength of crankshaft and the design variable YOUNG and L3 have the greatest impact on the stiffness of crankshaft. And the result matches up with the response surface graph. The reliability analysis result provides some useful information for the improvement of the reliability of crankshaft for high-speed punch.
Beam neutron energy optimization for boron neutron capture therapy using Monte Carlo method
Directory of Open Access Journals (Sweden)
Ali Pazirandeh
2006-06-01
Full Text Available In last two decades the optimal neutron energy for the treatment of deep seated tumors in boron neutron capture therapy in view of neutron physics and chemical compounds of boron carrier has been under thorough study. Although neutron absorption cross section of boron is high (3836b, the treatment of deep seated tumors such as gliobelastoma multiform (GBM requires beam of neutrons of higher energy that can penetrate deeply into the brain and thermalize in the proximity of the tumor. Dosage from recoil proton associated with fast neutrons however poses some constraints on maximum neutron energy that can be used in the treatment. For this reason neutrons in the epithermal energy range of 10eV-10keV are generally to be the most appropriate. The simulation carried out by Monte Carlo methods using MCBNCT and MCNP4C codes along with the cross section library in 290 groups extracted from ENDF/B6 main library. The optimal neutron energy for deep seated tumors depends on the size and depth of tumor. Our estimated optimized energy for the tumor of 5cm wide and 1-2cm thick stands at 5cm depth is in the range of 3-5keV
Zhang, D.; Liao, Q.
2016-12-01
The Bayesian inference provides a convenient framework to solve statistical inverse problems. In this method, the parameters to be identified are treated as random variables. The prior knowledge, the system nonlinearity, and the measurement errors can be directly incorporated in the posterior probability density function (PDF) of the parameters. The Markov chain Monte Carlo (MCMC) method is a powerful tool to generate samples from the posterior PDF. However, since the MCMC usually requires thousands or even millions of forward simulations, it can be a computationally intensive endeavor, particularly when faced with large-scale flow and transport models. To address this issue, we construct a surrogate system for the model responses in the form of polynomials by the stochastic collocation method. In addition, we employ interpolation based on the nested sparse grids and takes into account the different importance of the parameters, under the condition of high random dimensions in the stochastic space. Furthermore, in case of low regularity such as discontinuous or unsmooth relation between the input parameters and the output responses, we introduce an additional transform process to improve the accuracy of the surrogate model. Once we build the surrogate system, we may evaluate the likelihood with very little computational cost. We analyzed the convergence rate of the forward solution and the surrogate posterior by Kullback-Leibler divergence, which quantifies the difference between probability distributions. The fast convergence of the forward solution implies fast convergence of the surrogate posterior to the true posterior. We also tested the proposed algorithm on water-flooding two-phase flow reservoir examples. The posterior PDF calculated from a very long chain with direct forward simulation is assumed to be accurate. The posterior PDF calculated using the surrogate model is in reasonable agreement with the reference, revealing a great improvement in terms of
Evaluation of radiation dose to patients in intraoral dental radiography using Monte Carlo Method
Energy Technology Data Exchange (ETDEWEB)
Park, Il; Kim, Kyeong Ho; Oh, Seung Chul; Song, Ji Young [Dept. of Nuclear Engineering, Kyung Hee University, Yongin (Korea, Republic of)
2016-11-15
The use of dental radiographic examinations is common although radiation dose resulting from the dental radiography is relatively small. Therefore, it is required to evaluate radiation dose from the dental radiography for radiation safety purpose. The objectives of the present study were to develop dosimetry method for intraoral dental radiography using a Monte Carlo method based radiation transport code and to calculate organ doses and effective doses of patients from different types of intraoral radiographies. Radiological properties of dental radiography equipment were characterized for the evaluation of patient radiation dose. The properties including x-ray energy spectrum were simulated using MCNP code. Organ doses and effective doses to patients were calculated by MCNP simulation with computational adult phantoms. At the typical equipment settings (60 kVp, 7 mA, and 0.12 sec), the entrance air kerma was 1.79 mGy and the measured half value layer was 1.82 mm. The half value layer calculated by MCNP simulation was well agreed with the measurement values. Effective doses from intraoral radiographies ranged from 1 μSv for maxilla premolar to 3 μSv for maxilla incisor. Oral cavity layer (23⁓82 μSv) and salivary glands (10⁓68 μSv) received relatively high radiation dose. Thyroid also received high radiation dose (3⁓47 μSv) for examinations. The developed dosimetry method and evaluated radiation doses in this study can be utilized for policy making, patient dose management, and development of low-dose equipment. In addition, this study can ultimately contribute to decrease radiation dose to patients for radiation safety.
Casula, Michele; Moroni, Saverio; Sorella, Sandro; Filippi, Claudia
2010-04-01
We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regularized diffusion Monte Carlo (LRDMC) algorithms. For the DMC method, we refine a scheme recently devised to treat nonlocal pseudopotential in a variational way. We show that such scheme—when applied to large enough systems—maintains its effectiveness only at correspondingly small enough time-steps, and we present two simple upgrades of the method which guarantee the variational property in a size-consistent manner. For the LRDMC method, which is size-consistent and variational by construction, we enhance the computational efficiency by introducing: (i) an improved definition of the effective lattice Hamiltonian which remains size-consistent and entails a small lattice-space error with a known leading term and (ii) a new randomization method for the positions of the lattice knots which requires a single lattice-space.
Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling.
Kraan, Aafke Christine
2015-01-01
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including β (+) emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.
Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling
Kraan, Aafke Christine
2015-01-01
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including β+ emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects. PMID:26217586
Kumada, H; Saito, K; Nakamura, T; Sakae, T; Sakurai, H; Matsumura, A; Ono, K
2011-12-01
Treatment planning for boron neutron capture therapy generally utilizes Monte-Carlo methods for calculation of the dose distribution. The new treatment planning system JCDS-FX employs the multi-purpose Monte-Carlo code PHITS to calculate the dose distribution. JCDS-FX allows to build a precise voxel model consisting of pixel based voxel cells in the scale of 0.4×0.4×2.0 mm(3) voxel in order to perform high-accuracy dose estimation, e.g. for the purpose of calculating the dose distribution in a human body. However, the miniaturization of the voxel size increases calculation time considerably. The aim of this study is to investigate sophisticated modeling methods which can perform Monte-Carlo calculations for human geometry efficiently. Thus, we devised a new voxel modeling method "Multistep Lattice-Voxel method," which can configure a voxel model that combines different voxel sizes by utilizing the lattice function over and over. To verify the performance of the calculation with the modeling method, several calculations for human geometry were carried out. The results demonstrated that the Multistep Lattice-Voxel method enabled the precise voxel model to reduce calculation time substantially while keeping the high-accuracy of dose estimation. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Forward treatment planning for modulated electron radiotherapy (MERT) employing Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Henzen, D., E-mail: henzen@ams.unibe.ch; Manser, P.; Frei, D.; Volken, W.; Born, E. J.; Lössl, K.; Aebersold, D. M.; Fix, M. K. [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010 Berne (Switzerland); Neuenschwander, H. [Clinic for Radiation-Oncology, Lindenhofspital Bern, CH-3012 Berne (Switzerland); Stampanoni, M. F. M. [Institute for Biomedical Engineering, ETH Zürich and Paul Scherrer Institut, CH-5234 Villigen (Switzerland)
2014-03-15
Purpose: This paper describes the development of a forward planning process for modulated electron radiotherapy (MERT). The approach is based on a previously developed electron beam model used to calculate dose distributions of electron beams shaped by a photon multi leaf collimator (pMLC). Methods: As the electron beam model has already been implemented into the Swiss Monte Carlo Plan environment, the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) can be included in the planning process for MERT. In a first step, CT data are imported into Eclipse and a pMLC shaped electron beam is set up. This initial electron beam is then divided into segments, with the electron energy in each segment chosen according to the distal depth of the planning target volume (PTV) in beam direction. In order to improve the homogeneity of the dose distribution in the PTV, a feathering process (Gaussian edge feathering) is launched, which results in a number of feathered segments. For each of these segments a dose calculation is performed employing the in-house developed electron beam model along with the macro Monte Carlo dose calculation algorithm. Finally, an automated weight optimization of all segments is carried out and the total dose distribution is read back into Eclipse for display and evaluation. One academic and two clinical situations are investigated for possible benefits of MERT treatment compared to standard treatments performed in our clinics and treatment with a bolus electron conformal (BolusECT) method. Results: The MERT treatment plan of the academic case was superior to the standard single segment electron treatment plan in terms of organs at risk (OAR) sparing. Further, a comparison between an unfeathered and a feathered MERT plan showed better PTV coverage and homogeneity for the feathered plan, with V{sub 95%} increased from 90% to 96% and V{sub 107%} decreased from 8% to nearly 0%. For a clinical breast boost irradiation, the MERT plan
Simulating the proton transfer in gramicidin A by a sequential dynamical Monte Carlo method.
Till, Mirco S; Essigke, Timm; Becker, Torsten; Ullmann, G Matthias
2008-10-23
The large interest in long-range proton transfer in biomolecules is triggered by its importance for many biochemical processes such as biological energy transduction and drug detoxification. Since long-range proton transfer occurs on a microsecond time scale, simulating this process on a molecular level is still a challenging task and not possible with standard simulation methods. In general, the dynamics of a reactive system can be described by a master equation. A natural way to describe long-range charge transfer in biomolecules is to decompose the process into elementary steps which are transitions between microstates. Each microstate has a defined protonation pattern. Although such a master equation can in principle be solved analytically, it is often too demanding to solve this equation because of the large number of microstates. In this paper, we describe a new method which solves the master equation by a sequential dynamical Monte Carlo algorithm. Starting from one microstate, the evolution of the system is simulated as a stochastic process. The energetic parameters required for these simulations are determined by continuum electrostatic calculations. We apply this method to simulate the proton transfer through gramicidin A, a transmembrane proton channel, in dependence on the applied membrane potential and the pH value of the solution. As elementary steps in our reaction, we consider proton uptake and release, proton transfer along a hydrogen bond, and rotations of water molecules that constitute a proton wire through the channel. A simulation of 8 mus length took about 5 min on an Intel Pentium 4 CPU with 3.2 GHz. We obtained good agreement with experimental data for the proton flux through gramicidin A over a wide range of pH values and membrane potentials. We find that proton desolvation as well as water rotations are equally important for the proton transfer through gramicidin A at physiological membrane potentials. Our method allows to simulate long
A Projector Quantum Monte Carlo Method for non-linear wavefunctions
Schwarz, Lauretta R; Booth, George H
2016-01-01
We reformulate the projected imaginary-time evolution of Full Configuration Interaction Quantum Monte Carlo in terms of a Lagrangian minimization. This naturally leads to the admission of polynomial complex wavefunction parameterizations, circumventing the exponential scaling of the approach. While previously these functions have traditionally inhabited the domain of Variational Monte Carlo, we consider recently developments for the identification of deep-learning neural networks to optimize this Lagrangian, which can be written as a modification of the propagator for the wavefunction dynamics. We demonstrate this approach with a form of Tensor Network State, and use it to find solutions to the strongly-correlated Hubbard model, as well as its application to a fully periodic ab-initio Graphene sheet. The number of variables which can be simultaneously optimized greatly exceeds alternative formulations of Variational Monte Carlo, allowing for systematic improvability of the wavefunction flexibility towards exa...
Directory of Open Access Journals (Sweden)
M. Kotbi
2013-03-01
Full Text Available The choice of appropriate interaction models is among the major disadvantages of conventional methods such as Molecular Dynamics (MD and Monte Carlo (MC simulations. On the other hand, the so-called Reverse Monte Carlo (RMC method, based on experimental data, can be applied without any interatomic and/or intermolecular interactions. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term into the acceptance criteria. This method is referred to as the Hybrid Reverse Monte Carlo (HRMC method. The idea of this paper is to test the validity of a combined potential model of coulomb and Lennard-Jones in a Fluoride glass system BaMnMF7 (M = Fe,V using HRMC method. The results show a good agreement between experimental and calculated characteristics, as well as a meaningful improvement in partial pair distribution functions (PDFs. We suggest that this model should be used in calculating the structural properties and in describing the average correlations between components of fluoride glass or a similar system. We also suggest that HRMC could be useful as a tool for testing the interaction potential models, as well as for conventional applications.
Monte Carlo Methods Development and Applications in Conformational Sampling of Proteins
DEFF Research Database (Denmark)
Tian, Pengfei
such as protein folding and aggregation. Second, by combining Monte Carlo sampling with a flexible probabilistic model of NMR chemical shifts, a series of simulation strategies are developed to accelerate the equilibrium sampling of free energy landscapes of proteins. Finally, a novel approach is presented...... are not sufficient to provide an accurate structural and dynamical description of certain properties of proteins, (2), it is difficult to obtain correct statistical weights of the samples generated, due to lack of equilibrium sampling. In this dissertation I present several new methodologies based on Monte Carlo...
Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues
Energy Technology Data Exchange (ETDEWEB)
Harris, G.; Van Horn, R.
1996-06-01
The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL.
Ishii, Ayako; Ohnishi, Naofumi; Nagakura, Hiroki; Ito, Hirotaka; Yamada, Shoichi
2017-11-01
We developed a three-dimensional radiative transfer code for an ultra-relativistic background flow-field by using the Monte Carlo (MC) method in the context of gamma-ray burst (GRB) emission. For obtaining reliable simulation results in the coupled computation of MC radiation transport with relativistic hydrodynamics which can reproduce GRB emission, we validated radiative transfer computation in the ultra-relativistic regime and assessed the appropriate simulation conditions. The radiative transfer code was validated through two test calculations: (1) computing in different inertial frames and (2) computing in flow-fields with discontinuous and smeared shock fronts. The simulation results of the angular distribution and spectrum were compared among three different inertial frames and in good agreement with each other. If the time duration for updating the flow-field was sufficiently small to resolve a mean free path of a photon into ten steps, the results were thoroughly converged. The spectrum computed in the flow-field with a discontinuous shock front obeyed a power-law in frequency whose index was positive in the range from 1 to 10 MeV. The number of photons in the high-energy side decreased with the smeared shock front because the photons were less scattered immediately behind the shock wave due to the small electron number density. The large optical depth near the shock front was needed for obtaining high-energy photons through bulk Compton scattering. Even one-dimensional structure of the shock wave could affect the results of radiation transport computation. Although we examined the effect of the shock structure on the emitted spectrum with a large number of cells, it is hard to employ so many computational cells per dimension in multi-dimensional simulations. Therefore, a further investigation with a smaller number of cells is required for obtaining realistic high-energy photons with multi-dimensional computations.
Environmental dose rate assessment of ITER using the Monte Carlo method
Directory of Open Access Journals (Sweden)
Karimian Alireza
2014-01-01
Full Text Available Exposure to radiation is one of the main sources of risk to staff employed in reactor facilities. The staff of a tokamak is exposed to a wide range of neutrons and photons around the tokamak hall. The International Thermonuclear Experimental Reactor (ITER is a nuclear fusion engineering project and the most advanced experimental tokamak in the world. From the radiobiological point of view, ITER dose rates assessment is particularly important. The aim of this study is the assessment of the amount of radiation in ITER during its normal operation in a radial direction from the plasma chamber to the tokamak hall. To achieve this goal, the ITER system and its components were simulated by the Monte Carlo method using the MCNPX 2.6.0 code. Furthermore, the equivalent dose rates of some radiosensitive organs of the human body were calculated by using the medical internal radiation dose phantom. Our study is based on the deuterium-tritium plasma burning by 14.1 MeV neutron production and also photon radiation due to neutron activation. As our results show, the total equivalent dose rate on the outside of the bioshield wall of the tokamak hall is about 1 mSv per year, which is less than the annual occupational dose rate limit during the normal operation of ITER. Also, equivalent dose rates of radiosensitive organs have shown that the maximum dose rate belongs to the kidney. The data may help calculate how long the staff can stay in such an environment, before the equivalent dose rates reach the whole-body dose limits.
Energy Technology Data Exchange (ETDEWEB)
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.
IMRT dose delivery effects in radiotherapy treatment planning using Monte Carlo methods
Tyagi, Neelam
Inter- and intra-leaf transmission and head scatter can play significant roles in Intensity Modulated Radiation Therapy (IMRT)-based treatment deliveries. In order to accurately calculate the dose in the IMRT planning process, it is therefore important that the detailed geometry of the multi-leaf collimator (MLC), in addition to other components in the accelerator treatment head be accurately modeled. In this thesis Monte Carlo (MC) methods have been used to model the treatment head of a Varian linear accelerator. A comprehensive model of the Varian 120-leaf MLC has been developed within the DPM MC code and has been verified against measurements in homogeneous and heterogeneous phantom geometries under different IMRT delivery circumstances. Accuracy of the MLC model in simulating details in the leaf geometry has been established over a range of arbitrarily shaped fields and IMRT fields. A sensitivity analysis of the effect of the electron-on-target parameters and the structure of the flattening filter on the accuracy of calculated dose distributions has been conducted. Adjustment of the electron-on-target parameters resulting in optimal agreement with measurements was an iterative process, with the final parameters representing a tradeoff between small (3x3 cm2) and large (40x40 cm2) field sizes. A novel method based on adaptive kernel density estimation, in the phase space simulation process is also presented as an alternative to particle recycling. Using this model dosimetric differences between MLC-based static (SMLC) and dynamic (DMLC) deliveries have been investigated. Differences between SMLC and DMLC, possibly related to fluence and/or spectral changes, appear to vary systematically with the density of the medium. The effect of fluence modulation due to leaf sequencing shows differences, up to 10% between plans developed with 1% and 10% fluence intervals for both SMLC and DMLC-delivered sequences. Dose differences between planned and delivered leaf sequences
A Bayesian analysis of rare B decays with advanced Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Beaujean, Frederik
2012-11-12
Searching for new physics in rare B meson decays governed by b {yields} s transitions, we perform a model-independent global fit of the short-distance couplings C{sub 7}, C{sub 9}, and C{sub 10} of the {Delta}B=1 effective field theory. We assume the standard-model set of b {yields} s{gamma} and b {yields} sl{sup +}l{sup -} operators with real-valued C{sub i}. A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B{yields}K{sup *}{gamma}, B{yields}K{sup (*)}l{sup +}l{sup -}, and B{sub s}{yields}{mu}{sup +}{mu}{sup -} decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit
An Evaluation of a Markov Chain Monte Carlo Method for the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of the Markov Chain Monte Carlo (MCMC) procedure Gibbs sampling was considered for estimation of item parameters of the two-parameter logistic model. Data for the Law School Admission Test (LSAT) Section 6 were analyzed to illustrate the MCMC procedure. In addition, simulated data sets were analyzed using the MCMC, marginal Bayesian…
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
Propagating probability distributions of stand variables using sequential Monte Carlo methods
Jeffrey H. Gove
2009-01-01
A general probabilistic approach to stand yield estimation is developed based on sequential Monte Carlo filters, also known as particle filters. The essential steps in the development of the sampling importance resampling (SIR) particle filter are presented. The SIR filter is then applied to simulated and observed data showing how the 'predictor - corrector'...
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Mendonca, Dalila; Neves, Lucio P.; Perini, Ana P., E-mail: anapaula.perini@ufu.br [Universidade Federal de Uberlandia (INFIS/UFU), Uberlandia, MG (Brazil). Instituto de Fisica; Santos, William S.; Caldas, Linda V.E. [Instituto de Pesquisas Energeticas e Nucleres (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2015-07-01
A special pencil type ionization chamber, developed at the Instituto de Pesquisas Energeticas e Nucleares, was characterized by means of Monte Carlo simulation to determine the influence of its components on its response. The main differences between this ionization chamber and commercial ionization chambers are related to its configuration and constituent materials. The simulations were made employing the MCNP-4C Monte Carlo code. The highest influence was obtained for the body of PMMA: 7.0%. (author)
Davidson, Valerie J; Ryks, Joanne
2003-10-01
The objective of food safety risk assessment is to quantify levels of risk for consumers as well as to design improved processing, distribution, and preparation systems that reduce exposure to acceptable limits. Monte Carlo simulation tools have been used to deal with the inherent variability in food systems, but these tools require substantial data for estimates of probability distributions. The objective of this study was to evaluate the use of fuzzy values to represent uncertainty. Fuzzy mathematics and Monte Carlo simulations were compared to analyze the propagation of uncertainty through a number of sequential calculations in two different applications: estimation of biological impacts and economic cost in a general framework and survival of Campylobacter jejuni in a sequence of five poultry processing operations. Estimates of the proportion of a population requiring hospitalization were comparable, but using fuzzy values and interval arithmetic resulted in more conservative estimates of mortality and cost, in terms of the intervals of possible values and mean values, compared to Monte Carlo calculations. In the second application, the two approaches predicted the same reduction in mean concentration (-4 log CFU/ ml of rinse), but the limits of the final concentration distribution were wider for the fuzzy estimate (-3.3 to 5.6 log CFU/ml of rinse) compared to the probability estimate (-2.2 to 4.3 log CFU/ml of rinse). Interval arithmetic with fuzzy values considered all possible combinations in calculations and maximum membership grade for each possible result. Consequently, fuzzy results fully included distributions estimated by Monte Carlo simulations but extended to broader limits. When limited data defines probability distributions for all inputs, fuzzy mathematics is a more conservative approach for risk assessment than Monte Carlo simulations.
Kumar, Sudhir; Srinivasan, P; Sharma, S D; Saxena, Sanjay Kumar; Bakshi, A K; Dash, Ashutosh; Babu, D A R; Sharma, D N
2015-09-01
Isotope production and Application Division of Bhabha Atomic Research Center developed (32)P patch sources for treatment of superficial tumors. Surface dose rate of a newly developed (32)P patch source of nominal diameter 25 mm was measured experimentally using standard extrapolation ionization chamber and Gafchromic EBT film. Monte Carlo model of the (32)P patch source along with the extrapolation chamber was also developed to estimate the surface dose rates from these sources. The surface dose rates to tissue (cGy/min) measured using extrapolation chamber and radiochromic films are 82.03±4.18 (k=2) and 79.13±2.53 (k=2) respectively. The two values of the surface dose rates measured using the two independent experimental methods are in good agreement to each other within a variation of 3.5%. The surface dose rate to tissue (cGy/min) estimated using the MCNP Monte Carlo code works out to be 77.78±1.16 (k=2). The maximum deviation between the surface dose rates to tissue obtained by Monte Carlo and the extrapolation chamber method is 5.2% whereas the difference between the surface dose rates obtained by radiochromic film measurement and the Monte Carlo simulation is 1.7%. The three values of the surface dose rates of the (32)P patch source obtained by three independent methods are in good agreement to one another within the uncertainties associated with their measurements and calculation. This work has demonstrated that MCNP based electron transport simulations are accurate enough for determining the dosimetry parameters of the indigenously developed (32)P patch sources for contact brachytherapy applications. Copyright © 2015 Elsevier Ltd. All rights reserved.
Suzuki, Teppei; Tani, Yuji; Ogasawara, Katsuhiko
2016-07-25
Consistent with the "attention, interest, desire, memory, action" (AIDMA) model of consumer behavior, patients collect information about available medical institutions using the Internet to select information for their particular needs. Studies of consumer behavior may be found in areas other than medical institution websites. Such research uses Web access logs for visitor search behavior. At this time, research applying the patient searching behavior model to medical institution website visitors is lacking. We have developed a hospital website search behavior model using a Bayesian approach to clarify the behavior of medical institution website visitors and determine the probability of their visits, classified by search keyword. We used the website data access log of a clinic of internal medicine and gastroenterology in the Sapporo suburbs, collecting data from January 1 through June 31, 2011. The contents of the 6 website pages included the following: home, news, content introduction for medical examinations, mammography screening, holiday person-on-duty information, and other. The search keywords we identified as best expressing website visitor needs were listed as the top 4 headings from the access log: clinic name, clinic name + regional name, clinic name + medical examination, and mammography screening. Using the search keywords as the explaining variable, we built a binomial probit model that allows inspection of the contents of each purpose variable. Using this model, we determined a beta value and generated a posterior distribution. We performed the simulation using Markov Chain Monte Carlo methods with a noninformation prior distribution for this model and determined the visit probability classified by keyword for each category. In the case of the keyword "clinic name," the visit probability to the website, repeated visit to the website, and contents page for medical examination was positive. In the case of the keyword "clinic name and regional name," the
Development of CT scanner models for patient organ dose calculations using Monte Carlo methods
Gu, Jianwei
There is a serious and growing concern about the CT dose delivered by diagnostic CT examinations or image-guided radiation therapy imaging procedures. To better understand and to accurately quantify radiation dose due to CT imaging, Monte Carlo based CT scanner models are needed. This dissertation describes the development, validation, and application of detailed CT scanner models including a GE LightSpeed 16 MDCT scanner and two image guided radiation therapy (IGRT) cone beam CT (CBCT) scanners, kV CBCT and MV CBCT. The modeling process considered the energy spectrum, beam geometry and movement, and bowtie filter (BTF). The methodology of validating the scanner models using reported CTDI values was also developed and implemented. Finally, the organ doses to different patients undergoing CT scan were obtained by integrating the CT scanner models with anatomically-realistic patient phantoms. The tube current modulation (TCM) technique was also investigated for dose reduction. It was found that for RPI-AM, thyroid, kidneys and thymus received largest dose of 13.05, 11.41 and 11.56 mGy/100 mAs from chest scan, abdomen-pelvis scan and CAP scan, respectively using 120 kVp protocols. For RPI-AF, thymus, small intestine and kidneys received largest dose of 10.28, 12.08 and 11.35 mGy/100 mAs from chest scan, abdomen-pelvis scan and CAP scan, respectively using 120 kVp protocols. The dose to the fetus of the 3 month pregnant patient phantom was 0.13 mGy/100 mAs and 0.57 mGy/100 mAs from the chest and kidney scan, respectively. For the chest scan of the 6 month patient phantom and the 9 month patient phantom, the fetal doses were 0.21 mGy/100 mAs and 0.26 mGy/100 mAs, respectively. For MDCT with TCM schemas, the fetal dose can be reduced with 14%-25%. To demonstrate the applicability of the method proposed in this dissertation for modeling the CT scanner, additional MDCT scanner was modeled and validated by using the measured CTDI values. These results demonstrated that the
Medhat, M. E.; Demir, Nilgun; Akar Tarim, Urkiye; Gurler, Orhan
2014-08-01
Monte Carlo simulations, FLUKA and Geant4, were performed to study mass attenuation for various types of soil at 59.5, 356.5, 661.6, 1173.2 and 1332.5 keV photon energies. Appreciable variations are noted for all parameters by changing the photon energy and the chemical composition of the sample. The simulations parameters were compared with experimental data and the XCOM program. The simulations show that the calculated mass attenuation coefficient values were closer to experimental values better than those obtained theoretically using the XCOM database for the same soil samples. The results indicate that Geant4 and FLUKA can be applied to estimate mass attenuation for various biological materials at different energies. The Monte Carlo method may be employed to make additional calculations on the photon attenuation characteristics of different soil samples collected from other places.
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
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Cirrone, G.A.P., E-mail: cirrone@lns.infn.it [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Bucciolini, M. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Bruzzi, M. [Energetic Department, University of Florence, Via S. Marta 3, I-50139 Florence (Italy); Candiano, G. [Laboratorio di Tecnologie Oncologiche HSR, Giglio Contrada, Pietrapollastra-Pisciotto, 90015 Cefalu, Palermo (Italy); Civinini, C. [National Institute for Nuclear Physics INFN, Section of Florence, Via G. Sansone 1, Sesto Fiorentino, I-50019 Florence (Italy); Cuttone, G. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Guarino, P. [Nuclear Engineering Department, University of Palermo, Via... Palermo (Italy); Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Lo Presti, D. [Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Mazzaglia, S.E. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Pallotta, S. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Randazzo, N. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Sipala, V. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Stancampiano, C. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); and others
2011-12-01
In this paper the use of the Filtered Back Projection (FBP) Algorithm, in order to reconstruct tomographic images using the high energy (200-250 MeV) proton beams, is investigated. The algorithm has been studied in detail with a Monte Carlo approach and image quality has been analysed and compared with the total absorbed dose. A proton Computed Tomography (pCT) apparatus, developed by our group, has been fully simulated to exploit the power of the Geant4 Monte Carlo toolkit. From the simulation of the apparatus, a set of tomographic images of a test phantom has been reconstructed using the FBP at different absorbed dose values. The images have been evaluated in terms of homogeneity, noise, contrast, spatial and density resolution.
Monte Carlo simulation of air sampling methods for the measurement of radon decay products.
Sima, Octavian; Luca, Aurelian; Sahagia, Maria
2017-08-01
A stochastic model of the processes involved in the measurement of the activity of the 222Rn decay products was developed. The distributions of the relevant factors, including air sampling and radionuclide collection, are propagated using Monte Carlo simulation to the final distribution of the measurement results. The uncertainties of the 222Rn decay products concentrations in the air are realistically evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wu, Di M.; Zhao, S. S.; Lu, Jun Q.; Hu, Xin-Hua
2000-06-01
In Monte Carlo simulations of light propagating in biological tissues, photons propagating in the media are described as classic particles being scattered and absorbed randomly in the media, and their path are tracked individually. To obtain any statistically significant results, however, a large number of photons is needed in the simulations and the calculations are time consuming and sometime impossible with existing computing resource, especially when considering the inhomogeneous boundary conditions. To overcome this difficulty, we have implemented a parallel computing technique into our Monte Carlo simulations. And this moment is well justified due to the nature of the Monte Carlo simulation. Utilizing the PVM (Parallel Virtual Machine, a parallel computing software package), parallel codes in both C and Fortran have been developed on the massive parallel computer of Cray T3E and a local PC-network running Unix/Sun Solaris. Our results show that parallel computing can significantly reduce the running time and make efficient usage of low cost personal computers. In this report, we present a numerical study of light propagation in a slab phantom of skin tissue using the parallel computing technique.
Calculation of the Effective Delayed Neutron Fraction by Deterministic and Monte Carlo Methods
Directory of Open Access Journals (Sweden)
M. Carta
2011-01-01
Full Text Available The studies on Accelerator-Driven Systems (ADSs have renewed the interest in the theoretical and computational evaluation of the main integral parameters characterizing subcritical systems (e.g., reactivity, effective delayed neutron fraction βeff, and mean prompt neutron generation time. In particular, some kinetic parameters, as the effective delayed neutron fraction, are evaluated in Monte Carlo codes by formulations which do not require the calculation of the adjoint flux. This paper is focused on a theoretical and computational analysis about how the different βeff definitions are connected and which are the approximations inherent to the Monte Carlo definition with respect to the standard definition involving weighted integrals. By means of a refined transport computational analysis carried out in a coherent and consistent way, that is, using the same deterministic code and neutron data library for the βeff evaluation in different ways, the theoretical analysis is numerically confirmed. Both theoretical and numerical results confirm the effectiveness of the Monte Carlo βeff evaluation, at least in cases where spectral differences between total and prompt fluxes are negligible with respect to the value of the functionals entering the classical βeff formulation.
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
Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang
2017-07-10
In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.
National Research Council Canada - National Science Library
Yifan Nie; Chaoping Liang; Pil-Ryung Cha; Luigi Colombo; Robert M Wallace; Kyeongjae Cho
2017-01-01
.... Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW...
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Zhaoyuan Liu; Kord Smith; Benoit Forget; Javier Ortensi
2016-05-01
A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices. Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.
Simulation of Cone Beam CT System Based on Monte Carlo Method
Wang, Yu; Chen, Chaobin; 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 ...
Directory of Open Access Journals (Sweden)
Anton G. Pavlov
2008-02-01
Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.
Directory of Open Access Journals (Sweden)
Bruno MarceloGS
2008-01-01
Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.
Use of δ f Monte Carlo Method to Study Pressure Anisotropy
Williams, Jeffrey
1998-11-01
Using a δ f Monte Carlo simulation, we are studying the anisotropy in the pressure tensor at low collisionality in a stellarator. This anisotropy causes the plasma to shield out small (less than a few tenths of a percent) Fourier terms in the magne tic field strength when the pressure is incorporated in the equilibrium [Physics of Plasmas , 4620 (1996)]. These terms, if unshielded, can cause a large enhancement over neoclassical transport and can have large effects for stellarator configurations if they are not shielded.
Energy Technology Data Exchange (ETDEWEB)
Trubey, D.K.; McGill, B.L. (eds.)
1980-08-01
This report consists of 24 papers which were presented at the seminar on Theory and Application of Monte Carlo Methods, held in Oak Ridge on April 21-23, plus a summary of the three-man panel discussion which concluded the seminar and two papers which were not given orally. These papers constitute a current statement of the state of the art of the theory and application of Monte Carlo methods for radiation transport problems in shielding and reactor physics.
Moskowitz, Jules W.; Schmidt, K. E.; Lee, Michael A.; Kalos, M. H.
1982-07-01
The potential energy surface of the LiH molecule is calculated using the Green's function Monte Carlo method. The calculated correlation energy is 0.078±0.001 hartree and the binding energy is 2.56 eV. These results are within 6% and 2% of the experimental values, respectively. The Green's function Monte Carlo method is discussed in some detail with particular emphasis on problems of chemical interest.
Sakamoto, Hiroki; Yamamoto, Toshihiro
2017-09-01
This paper presents improvement and performance evaluation of the ;perturbation source method;, which is one of the Monte Carlo perturbation techniques. The formerly proposed perturbation source method was first-order accurate, although it is known that the method can be easily extended to an exact perturbation method. A transport equation for calculating an exact flux difference caused by a perturbation is solved. A perturbation particle representing a flux difference is explicitly transported in the perturbed system, instead of in the unperturbed system. The source term of the transport equation is defined by the unperturbed flux and the cross section (or optical parameter) changes. The unperturbed flux is provided by an ;on-the-fly; technique during the course of the ordinary fixed source calculation for the unperturbed system. A set of perturbation particle is started at the collision point in the perturbed region and tracked until death. For a perturbation in a smaller portion of the whole domain, the efficiency of the perturbation source method can be improved by using a virtual scattering coefficient or cross section in the perturbed region, forcing collisions. Performance is evaluated by comparing the proposed method to other Monte Carlo perturbation methods. Numerical tests performed for a particle transport in a two-dimensional geometry reveal that the perturbation source method is less effective than the correlated sampling method for a perturbation in a larger portion of the whole domain. However, for a perturbation in a smaller portion, the perturbation source method outperforms the correlated sampling method. The efficiency depends strongly on the adjustment of the new virtual scattering coefficient or cross section.
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.
Evaluation of high packing density powder X-ray screens by Monte Carlo methods
Liaparinos, P.; Kandarakis, I.; Cavouras, D.; Kalivas, N.; Delis, H.; Panayiotakis, G.
2007-09-01
Phosphor materials are employed in intensifying screens of both digital and conventional X-ray imaging detectors. High packing density powder screens have been developed (e.g. screens in ceramic form) exhibiting high-resolution and light emission properties, and thus contributing to improved image transfer characteristics and higher radiation to light conversion efficiency. For the present study, a custom Monte Carlo simulation program was used in order to examine the performance of ceramic powder screens, under various radiographic conditions. The model was developed using Mie scattering theory for the description of light interactions, based on the physical characteristics (e.g. complex refractive index, light wavelength) of the phosphor material. Monte Carlo simulations were carried out assuming: (a) X-ray photon energy ranging from 18 up to 49 keV, (b) Gd 2O 2S:Tb phosphor material with packing density of 70% and grain size of 7 μm and (c) phosphor thickness ranging between 30 and 70 mg/cm 2. The variation of the Modulation Transfer Function (MTF) and the Luminescence Efficiency (LE) with respect to the X-ray energy and the phosphor thickness was evaluated. Both aforementioned imaging characteristics were shown to take high values at 49 keV X-ray energy and 70 mg/cm 2 phosphor thickness. It was found that high packing density screens may be appropriate for use in medical radiographic systems.
Directory of Open Access Journals (Sweden)
Ke Tang
2014-04-01
Full Text Available Loops in proteins are flexible regions connecting regular secondary structures. They are often involved in protein functions through interacting with other molecules. The irregularity and flexibility of loops make their structures difficult to determine experimentally and challenging to model computationally. Conformation sampling and energy evaluation are the two key components in loop modeling. We have developed a new method for loop conformation sampling and prediction based on a chain growth sequential Monte Carlo sampling strategy, called Distance-guided Sequential chain-Growth Monte Carlo (DISGRO. With an energy function designed specifically for loops, our method can efficiently generate high quality loop conformations with low energy that are enriched with near-native loop structures. The average minimum global backbone RMSD for 1,000 conformations of 12-residue loops is 1:53 A° , with a lowest energy RMSD of 2:99 A° , and an average ensembleRMSD of 5:23 A° . A novel geometric criterion is applied to speed up calculations. The computational cost of generating 1,000 conformations for each of the x loops in a benchmark dataset is only about 10 cpu minutes for 12-residue loops, compared to ca 180 cpu minutes using the FALCm method. Test results on benchmark datasets show that DISGRO performs comparably or better than previous successful methods, while requiring far less computing time. DISGRO is especially effective in modeling longer loops (10-17 residues.
Žukauskaite, A; Plukiene, R; Plukis, A
2007-01-01
Particle accelerators and other high energy facilities produce penetrating ionizing radiation (neutrons and γ-rays) that must be shielded. The objective of this work was to model photon and neutron transport in various materials, usually used as shielding, such as concrete, iron or graphite. Monte Carlo method allows obtaining answers by simulating individual particles and recording some aspects of their average behavior. In this work several nuclear experiments were modeled: AVF 65 – γ-ray beams (1-10 MeV), HIMAC and ISIS-800 – high energy neutrons (20-800 MeV) transport in iron and concrete. The results were then compared with experimental data.
Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi
2017-10-01
This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.
Lin, Uei-Tyng; Chu, Chien-Hau
2006-05-01
Monte Carlo method was used to simulate the correction factors for electron loss and scattered photons for two improved cylindrical free-air ionization chambers (FACs) constructed at the Institute of Nuclear Energy Research (INER, Taiwan). The method is based on weighting correction factors for mono-energetic photons with X-ray spectra. The newly obtained correction factors for the medium-energy free-air chamber were compared with the current values, which were based on a least-squares fit to experimental data published in the NBS Handbook 64 [Wyckoff, H.O., Attix, F.H., 1969. Design of free-air ionization chambers. National Bureau Standards Handbook, No. 64. US Government Printing Office, Washington, DC, pp. 1-16; Chen, W.L., Su, S.H., Su, L.L., Hwang, W.S., 1999. Improved free-air ionization chamber for the measurement of X-rays. Metrologia 36, 19-24]. The comparison results showed the agreement between the Monte Carlo method and experimental data is within 0.22%. In addition, mono-energetic correction factors for the low-energy free-air chamber were calculated. Average correction factors were then derived for measured and theoretical X-ray spectra at 30-50 kVp. Although the measured and calculated spectra differ slightly, the resulting differences in the derived correction factors are less than 0.02%.
Ma, L X; Wang, F Q; Wang, C A; Wang, C C; Tan, J Y
2015-11-20
Spectral properties of sea foam greatly affect ocean color remote sensing and aerosol optical thickness retrieval from satellite observation. This paper presents a combined Mie theory and Monte Carlo method to investigate visible and near-infrared spectral reflectance and bidirectional reflectance distribution function (BRDF) of sea foam layers. A three-layer model of the sea foam is developed in which each layer is composed of large air bubbles coated with pure water. A pseudo-continuous model and Mie theory for coated spheres is used to determine the effective radiative properties of sea foam. The one-dimensional Cox-Munk surface roughness model is used to calculate the slope density functions of the wind-blown ocean surface. A Monte Carlo method is used to solve the radiative transfer equation. Effects of foam layer thickness, bubble size, wind speed, solar zenith angle, and wavelength on the spectral reflectance and BRDF are investigated. Comparisons between previous theoretical results and experimental data demonstrate the feasibility of our proposed method. Sea foam can significantly increase the spectral reflectance and BRDF of the sea surface. The absorption coefficient of seawater near the surface is not the only parameter that influences the spectral reflectance. Meanwhile, the effects of bubble size, foam layer thickness, and solar zenith angle also cannot be obviously neglected.
Comparisons of Wilks’ and Monte Carlo Methods in Response to the 10CFR50.46(c) Proposed Rulemaking
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Zhang, Hongbin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Szilard, Ronaldo [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zou, Ling [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2016-10-01
The Nuclear Regulatory Commission (NRC) is proposing a new rulemaking on emergency core system/loss-of-coolant accident (LOCA) performance analysis. In the proposed rulemaking, designated as 10CFR50.46(c), the US NRC put forward an equivalent cladding oxidation criterion as a function of cladding pre-transient hydrogen content. The proposed rulemaking imposes more restrictive and burnup-dependent cladding embrittlement criteria; consequently nearly all the fuel rods in a reactor core need to be analyzed under LOCA conditions to demonstrate compliance to the safety limits. New analysis methods are required to provide a thorough characterization of the reactor core in order to identify the locations of the limiting rods as well as to quantify the safety margins under LOCA conditions. With the new analysis method presented in this work, the limiting transient case and the limiting rods can be easily identified to quantify the safety margins in response to the proposed new rulemaking. In this work, the best-estimate plus uncertainty (BEPU) analysis capability for large break LOCA with the new cladding embrittlement criteria using the RELAP5-3D code is established and demonstrated with a reduced set of uncertainty parameters. Both the direct Monte Carlo method and the Wilks’ nonparametric statistical method can be used to perform uncertainty quantification. Wilks’ method has become the de-facto industry standard to perform uncertainty quantification in BEPU LOCA analyses. Despite its widespread adoption by the industry, the use of small sample sizes to infer statement of compliance to the existing 10CFR50.46 rule, has been a major cause of unrealized operational margin in today’s BEPU methods. Moreover the debate on the proper interpretation of the Wilks’ theorem in the context of safety analyses is not fully resolved yet, even more than two decades after its introduction in the frame of safety analyses in the nuclear industry. This represents both a regulatory
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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)
Ground-state properties of LiH by reptation quantum Monte Carlo methods.
Ospadov, Egor; Oblinsky, Daniel G; Rothstein, Stuart M
2011-05-07
We apply reptation quantum Monte Carlo to calculate one- and two-electron properties for ground-state LiH, including all tensor components for static polarizabilities and hyperpolarizabilities to fourth-order in the field. The importance sampling is performed with a large (QZ4P) STO basis set single determinant, directly obtained from commercial software, without incurring the overhead of optimizing many-parameter Jastrow-type functions of the inter-electronic and internuclear distances. We present formulas for the electrical response properties free from the finite-field approximation, which can be problematic for the purposes of stochastic estimation. The α, γ, A and C polarizability values are reasonably consistent with recent determinations reported in the literature, where they exist. A sum rule is obeyed for components of the B tensor, but B(zz,zz) as well as β(zzz) differ from what was reported in the literature. This journal is © the Owner Societies 2011
Research on output signal of piezoelectric lead zirconate titanate detector using Monte Carlo method
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Takechi, Seiji, E-mail: takechi@elec.eng.osaka-cu.ac.jp [Graduate School of Engineering, Osaka City University, Osaka 558-8585 (Japan); Mitsuhashi, Tomoaki; Miura, Yoshinori [Graduate School of Engineering, Osaka City University, Osaka 558-8585 (Japan); Miyachi, Takashi; Kobayashi, Masanori; Okudaira, Osamu [Planetary Exploration Research Center, Chiba Institute of Technology, Narashino, Chiba 275-0016 (Japan); Shibata, Hiromi [The Institute of Scientific and Industrial Research, Osaka University, Ibaraki, Osaka 567-0047 (Japan); Fujii, Masayuki [Famscience Co., Ltd., Tsukubamirai, Ibaraki 300-2435 (Japan); Okada, Nagaya [Honda Electronics Co., Ltd., Toyohashi, Aichi 441-3193 (Japan); Murakami, Takeshi; Uchihori, Yukio [National Institute of Radiological Sciences, Chiba 263-8555 (Japan)
2017-06-21
The response of a radiation detector fabricated from piezoelectric lead zirconate titanate (PZT) was studied. The response signal due to a single 400 MeV/n xenon (Xe) ion was assumed to have a simple form that was composed of two variables, the amplitude and time constant. These variables were estimated by comparing two output waveforms obtained from a computer simulation and an experiment on Xe beam irradiation. Their values appeared to be dependent on the beam intensity. - Highlights: • The performance of PZT detector was studied by irradiation of a 400 MeV/n Xe beam. • Monte Carlo simulation was used to examine the formation process of the output. • The response signal due to a single Xe ion was assumed to have a simple form. • The form was composed of two variables, the amplitude and time constant. • These variables appeared to be dependent on the beam intensity.
Modeling of radiation-induced bystander effect using Monte Carlo methods
Xia, Junchao; Liu, Liteng; Xue, Jianming; Wang, Yugang; Wu, Lijun
2009-03-01
Experiments showed that the radiation-induced bystander effect exists in cells, or tissues, or even biological organisms when irradiated with energetic ions or X-rays. In this paper, a Monte Carlo model is developed to study the mechanisms of bystander effect under the cells sparsely populated conditions. This model, based on our previous experiment which made the cells sparsely located in a round dish, focuses mainly on the spatial characteristics. The simulation results successfully reach the agreement with the experimental data. Moreover, other bystander effect experiment is also computed by this model and finally the model succeeds in predicting the results. The comparison of simulations with the experimental results indicates the feasibility of the model and the validity of some vital mechanisms assumed.
A fuzzy development for attribute control chart with Monte Carlo simulation method
Directory of Open Access Journals (Sweden)
Mohammad Hadi Madadi
2017-11-01
Full Text Available This paper presents the case study of fuzzy statistical process control which has been simulated for variable and discontinuous production within a particular time frame in a key manufacturing work-shop. In order to reduce waste production and increase productivity, dimensional inspection from raw product is categorized into three groups: product of type A, product of type B, and discard. In first part, the appearance characteristics of product is defined as fuzzy membership function as the input of the system in order to allocate the output obtained from fuzzy inference of product to one of the three quality levels. Afterwards, each quality level is assigned to its own group by means of Monte Carlo simulation techniques. In the second part, with fuzzy development of a multinomial p chart, the production process is illustrated as a control chart within the particular period of time.
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McGraw, David [Desert Research Inst. (DRI), Reno, NV (United States); Hershey, Ronald L. [Desert Research Inst. (DRI), Reno, NV (United States)
2016-06-01
Methods were developed to quantify uncertainty and sensitivity for NETPATH inverse water-rock reaction models and to calculate dissolved inorganic carbon, carbon-14 groundwater travel times. The NETPATH models calculate upgradient groundwater mixing fractions that produce the downgradient target water chemistry along with amounts of mineral phases that are either precipitated or dissolved. Carbon-14 groundwater travel times are calculated based on the upgradient source-water fractions, carbonate mineral phase changes, and isotopic fractionation. Custom scripts and statistical code were developed for this study to facilitate modifying input parameters, running the NETPATH simulations, extracting relevant output, postprocessing the results, and producing graphs and summaries. The scripts read userspecified values for each constituent’s coefficient of variation, distribution, sensitivity parameter, maximum dissolution or precipitation amounts, and number of Monte Carlo simulations. Monte Carlo methods for analysis of parametric uncertainty assign a distribution to each uncertain variable, sample from those distributions, and evaluate the ensemble output. The uncertainty in input affected the variability of outputs, namely source-water mixing, phase dissolution and precipitation amounts, and carbon-14 travel time. Although NETPATH may provide models that satisfy the constraints, it is up to the geochemist to determine whether the results are geochemically reasonable. Two example water-rock reaction models from previous geochemical reports were considered in this study. Sensitivity analysis was also conducted to evaluate the change in output caused by a small change in input, one constituent at a time. Results were standardized to allow for sensitivity comparisons across all inputs, which results in a representative value for each scenario. The approach yielded insight into the uncertainty in water-rock reactions and travel times. For example, there was little
Qin, Mingpu; Zhang, Shiwei
2016-01-01
Ground state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3, 0.5, 0.6, 0.75, and 0.875. At half-filling, the results are numerically exact. Away from half-filling, the constrained path Monte Carlo method is employed to control the sign problem. Our results are obtained with several advances in the computational algorithm, which are described in detail. We discuss the advantages of generalized Hartree-Fock trial wave functions and its connection to pairing wave functions, as well as the interplay with different forms of Hubbard-Stratonovich decompositions. We study the use of different twist angle sets when applying the twist averaged boundary conditions. We propose the use of quasi-random sequences, whi...
Directory of Open Access Journals (Sweden)
Karimian Alireza
2014-01-01
Full Text Available Nowadays, dual energy X-ray absorptiometry is used in bone mineral density systems to assess the amount of osteoporosis. The purpose of this research is to evaluate patient organ doses from dual X-ray absorptiometry by thermoluminescence dosimeters chips and Monte Carlo method. To achieve this goal, in the first step, the surface dose of the cervix, kidney, abdomen region, and thyroid were measured by using TLD-GR 200 at various organ locations. Then, to evaluate the absorbed dose by simulation, the BMD system, patient's body, X-ray source and radiosensitive tissues were simulated by the Monte Carlo method. The results showed, for the spine (left femur bone mineral density scan by using thermoluminescence dosimeters, the absorbed doses of the cervix and kidney were 4.5 (5.64 and 162.17 (3.99(mGy, respectively. For spine (left femur bone mineral density scan in simulation, the absorbed doses of the cervix and kidney were 4.19 (5.88 and 175 (3.68(mGy, respectively. The data obtained showed that the absorbed dose of the kidney in the spine scan is noticeable. Furthermore, because of the small relative difference between the simulation and experimental results, the radiation absorbed dose may be assessed by simulation and software, especially for internal organs, and at different depths of otherwise inaccessible organs which is not possible in experiments.
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Stoller, Roger E [ORNL; Golubov, Stanislav I [ORNL; Becquart, C. S. [Universite de Lille; Domain, C. [EDF R& D, Clamart, France
2007-08-01
The multiscale modeling scheme encompasses models from the atomistic to the continuum scale. Phenomena at the mesoscale are typically simulated using reaction rate theory, Monte Carlo, or phase field models. These mesoscale models are appropriate for application to problems that involve intermediate length scales, and timescales from those characteristic of diffusion to long-term microstructural evolution (~s to years). Although the rate theory and Monte Carlo models can be used simulate the same phenomena, some of the details are handled quite differently in the two approaches. Models employing the rate theory have been extensively used to describe radiation-induced phenomena such as void swelling and irradiation creep. The primary approximations in such models are time- and spatial averaging of the radiation damage source term, and spatial averaging of the microstructure into an effective medium. Kinetic Monte Carlo models can account for these spatial and temporal correlations; their primary limitation is the computational burden which is related to the size of the simulation cell. A direct comparison of RT and object kinetic MC simulations has been made in the domain of point defect cluster dynamics modeling, which is relevant to the evolution (both nucleation and growth) of radiation-induced defect structures. The primary limitations of the OKMC model are related to computational issues. Even with modern computers, the maximum simulation cell size and the maximum dose (typically much less than 1 dpa) that can be simulated are limited. In contrast, even very detailed RT models can simulate microstructural evolution for doses up 100 dpa or greater in clock times that are relatively short. Within the context of the effective medium, essentially any defect density can be simulated. Overall, the agreement between the two methods is best for irradiation conditions which produce a high density of defects (lower temperature and higher displacement rate), and for
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Moskvin, Vadim [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN (United States)]. E-mail: vmoskvin@iupui.edu; DesRosiers, Colleen; Papiez, Lech; Timmerman, Robert; Randall, Marcus; DesRosiers, Paul [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN (United States)
2002-06-21
The Monte Carlo code PENELOPE has been used to simulate photon flux from the Leksell Gamma Knife, a precision method for treating intracranial lesions. Radiation from a single {sup 60}Co assembly traversing the collimator system was simulated, and phase space distributions at the output surface of the helmet for photons and electrons were calculated. The characteristics describing the emitted final beam were used to build a two-stage Monte Carlo simulation of irradiation of a target. A dose field inside a standard spherical polystyrene phantom, usually used for Gamma Knife dosimetry, has been computed and compared with experimental results, with calculations performed by other authors with the use of the EGS4 Monte Carlo code, and data provided by the treatment planning system Gamma Plan. Good agreement was found between these data and results of simulations in homogeneous media. Owing to this established accuracy, PENELOPE is suitable for simulating problems relevant to stereotactic radiosurgery. (author)
Directory of Open Access Journals (Sweden)
Song Hyun Kim
2015-08-01
Full Text Available Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.
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Vieira, Jose Wilson
2001-08-01
Brachytherapy is a special form of cancer treatment in which the radioactive source is very close to or inside the tumor with the objective of causing the necrosis of the cancerous tissue. The intensity of cell response to the radiation varies according to the tissue type and degree of differentiation. Since the malign cells are less differentiated than the normal ones, they are more sensitive to the radiation. This is the basis for radiotherapy techniques. Institutes that work with the application of high dose rates use sophisticated computer programs to calculate the necessary dose to achieve the necrosis of the tumor and the same time, minimizing the irradiation of tissues and organs of the neighborhood. With knowledge the characteristics of the source and the tumor, it is possible to trace isodose curves with the necessary information for planning the brachytherapy in patients. The objective of this work is, using Monte Carlo techniques, to develop a computer program - the ISODOSE - which allows to determine isodose curves in turn of linear radioactive sources used in brachytherapy. The development of ISODOSE is important because the available commercial programs, in general, are very expensive and practically inaccessible to small clinics. The use of Monte Carlo techniques is viable because they avoid problems inherent to analytic solutions as, for instance , the integration of functions with singularities in its domain. The results of ISODOSE were compared with similar data found in the literature and also with those obtained at the institutes of radiotherapy of the 'Hospital do Cancer do Recife' and of the 'Hospital Portugues do Recife'. ISODOSE presented good performance, mainly, due to the Monte Carlo techniques, that allowed a quite detailed drawing of the isodose curves in turn of linear sources. (author)
Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange.
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Andreas Hula
2015-06-01
Full Text Available Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP. However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference.
Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange.
Hula, Andreas; Montague, P Read; Dayan, Peter
2015-06-01
Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference.
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.
Size dependence study of the ordering temperature in the Fast Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Velasquez, E. A., E-mail: eavelas@gmail.com [Universidad de San Buenaventura Seccional Medellin, Grupo de Investigacion en Modelamiento y Simulacion Computacional, Facultad de Ingenierias (Colombia); Mazo-Zuluaga, J., E-mail: johanmazo@gmail.com [Universidad de Antioquia, Grupo de Estado Solido, Grupo de Instrumentacion Cientifica y Microelectronica, Instituto de Fisica-FCEN (Colombia); Mejia-Lopez, J., E-mail: jmejia@puc.cl [Universidad de Antioquia, Instituto de Fisica-FCEN (Colombia)
2013-02-15
Based on the framework of the Fast Monte Carlo approach, we study the diameter dependence of the ordering temperature in magnetic nanostructures of cylindrical shape. For the purposes of this study, Fe cylindrical-shaped samples of different sizes (20 nm height, 30-100 nm in diameter) have been chosen, and their magnetic properties have been computed as functions of the scaled temperature. Two main set of results are concluded: (a) the ordering temperature of nanostructures follows a linear scaling relationship as a function of the scaling factor x, for all the studied sizes. This finding rules out a scaling relation T Prime {sub c} = x{sup 3{eta}}T{sub c} (where {eta} is a scaling exponent, and T Prime {sub c} and T{sub c} are the scaled and true ordering temperatures) that has been proposed in the literature, and suggests that temperature should scale linearly with the scaling factor x. (b) For the nanostructures, there are three different order-disorder magnetic transition modes depending on the system's size, in very good agreement with previous experimental reports.
Was, Z.
2017-06-01
Status of τ lepton decay Monte Carlo generator TAUOLA, its main applications and recent developments are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care: lesson from comparison and fits to the BaBar and Belle data is recalled. It was found, that as in the past at a time of comparisons with CLEO and ALEPH data, proper fitting, to as detailed as possible representation of the experimental data, is essential for appropriate developments of models of τ decay dynamic. This multi-dimensional nature of distributions is also important for observables where τ leptons are used to constrain experimental data. In later part of the presentation, use of the TAUOLA program for phenomenology of W, Z, H decays at LHC is addressed, in particular in the context of the Higgs boson parity measurements. Some new results, relevant for QED lepton pair emission are mentioned as well.
Directory of Open Access Journals (Sweden)
Ródenas José
2017-01-01
Full Text Available An X-ray fluorescence equipment is used for practical exercises in the laboratory of Nuclear Engineering of the Polytechnic University of Valencia (Spain. This equipment includes a compact X-ray tube, ECLIPSE-III, and a Si–PIN XR-100T detector. The voltage (30 kV, and the current (100 μA of the tube are low enough so that expected doses around the tube do not represent a risk for students working in the laboratory. Nevertheless, doses and shielding should be evaluated to accomplish the ALARA criterion. The Monte Carlo method has been applied to evaluate the dose rate around the installation provided with a shielding composed by a box of methacrylate. Dose rates calculated are compared with experimental measurements to validate the model. Obtained results show that doses are below allowable limits. Hence, no extra shielding is required for the X-ray beam. A previous Monte Carlo model was also developed to obtain the tube spectrum and validated by comparison with data from manufacturer.
Ródenas, José; Juste, Belén; Gallardo, Sergio; Querol, Andrea
2017-09-01
An X-ray fluorescence equipment is used for practical exercises in the laboratory of Nuclear Engineering of the Polytechnic University of Valencia (Spain). This equipment includes a compact X-ray tube, ECLIPSE-III, and a Si-PIN XR-100T detector. The voltage (30 kV), and the current (100 μA) of the tube are low enough so that expected doses around the tube do not represent a risk for students working in the laboratory. Nevertheless, doses and shielding should be evaluated to accomplish the ALARA criterion. The Monte Carlo method has been applied to evaluate the dose rate around the installation provided with a shielding composed by a box of methacrylate. Dose rates calculated are compared with experimental measurements to validate the model. Obtained results show that doses are below allowable limits. Hence, no extra shielding is required for the X-ray beam. A previous Monte Carlo model was also developed to obtain the tube spectrum and validated by comparison with data from manufacturer.
Energy Technology Data Exchange (ETDEWEB)
Dieudonne, C.; Dumonteil, E.; Malvagi, F.; Diop, C. M. [Commissariat a l' Energie Atomique et aux Energies Alternatives CEA, Service d' Etude des Reacteurs et de Mathematiques Appliquees, DEN/DANS/DM2S/SERMA/LTSD, F91191 Gif-sur-Yvette cedex (France)
2013-07-01
For several years, Monte Carlo burnup/depletion codes have appeared, which couple a Monte Carlo code to simulate the neutron transport to a deterministic method that computes the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3 dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the time-expensive Monte Carlo solver called at each time step. Therefore, great improvements in term of calculation time could be expected if one could get rid of Monte Carlo transport sequences. For example, it may seem interesting to run an initial Monte Carlo simulation only once, for the first time/burnup step, and then to use the concentration perturbation capability of the Monte Carlo code to replace the other time/burnup steps (the different burnup steps are seen like perturbations of the concentrations of the initial burnup step). This paper presents some advantages and limitations of this technique and preliminary results in terms of speed up and figure of merit. Finally, we will detail different possible calculation scheme based on that method. (authors)
Directory of Open Access Journals (Sweden)
Zhe Zhang
Full Text Available The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.
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Ramos M, D.; Yera S, Y.; Lopez B, G. M.; Acosta R, N.; Vergara G, A., E-mail: dayana@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones, Calle 20 No. 4113 e/ 41 y 47, Playa, 10600 La Habana (Cuba)
2014-08-15
This work is based on the determination of the detection efficiency of {sup 125}I and {sup 131}I in thyroid of the identiFINDER detector using the Monte Carlo method. The suitability of the calibration method is analyzed, when comparing the results of the direct Monte Carlo method with the corrected, choosing the latter because the differences with the real efficiency stayed below 10%. To simulate the detector their geometric parameters were optimized using a tomographic study, what allowed the uncertainties minimization of the estimates. Finally were obtained the simulations of the detector geometry-point source to find the correction factors to 5 cm, 15 cm and 25 cm, and those corresponding to the detector-simulator arrangement for the method validation and final calculation of the efficiency, demonstrating that in the Monte Carlo method implementation if simulates at a greater distance than the used in the Laboratory measurements an efficiency overestimation can be obtained, while if simulates at a shorter distance this will be underestimated, so should be simulated at the same distance to which will be measured in the reality. Also, is achieved the obtaining of the efficiency curves and minimum detectable activity for the measurement of {sup 131}I and {sup 125}I. In general is achieved the implementation of the Monte Carlo methodology for the identiFINDER calibration with the purpose of estimating the measured activity of iodine in thyroid. This method represents an ideal way to replace the lack of patterns solutions and simulators assuring the capacities of the Internal Contamination Laboratory of the Centro de Proteccion e Higiene de las Radiaciones are always calibrated for the iodine measurement in thyroid. (author)
Ustinov, E A
2017-01-21
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.
Energy Technology Data Exchange (ETDEWEB)
Cacais, F.L.; Delgado, J.U., E-mail: facacais@gmail.com [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Loayza, V.M. [Instituto Nacional de Metrologia (INMETRO), Rio de Janeiro, RJ (Brazil). Qualidade e Tecnologia
2016-07-01
In preparing solutions for the production of radionuclide metrology standards is necessary measuring the quantity Activity by mass. The gravimetric method by elimination is applied to perform weighing with smaller uncertainties. At this work is carried out the validation, by the Monte Carlo method, of the uncertainty calculation approach implemented by Lourenco and Bobin according to ISO GUM for the method by elimination. The results obtained by both uncertainty calculation methods were consistent indicating that were fulfilled the conditions for the application of ISO GUM in the preparation of radioactive standards. (author)
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2010-01-01
It is well known from linear analyses in stochastic seaway that the mean out-crossing rate of a level r is given through the reliability index, defined as r divided by the standard deviation. Hence, the reliability index becomes inversely proportional to the significant wave height. For non......-linear processes the mean out-crossing rate depends non-linearly on the response level r and a good estimate can be found using the First Order Reliability Method (FORM), see e.g. Jensen and Capul (2006). The FORM analysis also shows that the reliability index is strictly inversely proportional to the significant...... wave height irrespectively of the non-linearity in the system. However, the FORM analysis only gives an approximation to the mean out-crossing rate. A more exact result can be obtained by Monte Carlo simulations, but the necessary length of the time domain simulations for very low out-crossing rates...
Žukauskaitėa, A; Plukienė, R; Ridikas, D
2007-01-01
Particle accelerators and other high energy facilities produce penetrating ionizing radiation (neutrons and γ-rays) that must be shielded. The objective of this work was to model photon and neutron transport in various materials, usually used as shielding, such as concrete, iron or graphite. Monte Carlo method allows obtaining answers by simulating individual particles and recording some aspects of their average behavior. In this work several nuclear experiments were modeled: AVF 65 (AVF cyclotron of Research Center of Nuclear Physics, Osaka University, Japan) – γ-ray beams (1-10 MeV), HIMAC (heavy-ion synchrotron of the National Institute of Radiological Sciences in Chiba, Japan) and ISIS-800 (ISIS intensive spallation neutron source facility of the Rutherford Appleton laboratory, UK) – high energy neutron (20-800 MeV) transport in iron and concrete. The calculation results were then compared with experimental data.compared with experimental data.
Ganesh, P; Kim, Jeongnim; Park, Changwon; Yoon, Mina; Reboredo, Fernando A; Kent, Paul R C
2014-12-09
Highly accurate diffusion quantum Monte Carlo (QMC) studies of the adsorption and diffusion of atomic lithium in AA-stacked graphite are compared with van der Waals-including density functional theory (DFT) calculations. Predicted QMC lattice constants for pure AA graphite agree with experiment. Pure AA-stacked graphite is shown to challenge many van der Waals methods even when they are accurate for conventional AB graphite. Highest overall DFT accuracy, considering pure AA-stacked graphite as well as lithium binding and diffusion, is obtained by the self-consistent van der Waals functional vdW-DF2, although errors in binding energies remain. Empirical approaches based on point charges such as DFT-D are inaccurate unless the local charge transfer is assessed. The results demonstrate that the lithium-carbon system requires a simultaneous highly accurate description of both charge transfer and van der Waals interactions, favoring self-consistent approaches.
Absorbed dose measurements in mammography using Monte Carlo method and ZrO{sub 2}+PTFE dosemeters
Energy Technology Data Exchange (ETDEWEB)
Duran M, H. A.; Hernandez O, M. [Departamento de Investigacion en Polimeros y Materiales, Universidad de Sonora, Blvd. Luis Encinas y Rosales s/n, Col. Centro, 83190 Hermosillo, Sonora (Mexico); Salas L, M. A.; Hernandez D, V. M.; Vega C, H. R. [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Cipres 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Pinedo S, A.; Ventura M, J.; Chacon, F. [Hospital General de Zona No. 1, IMSS, Interior Alameda 45, 98000 Zacatecas (Mexico); Rivera M, T. [Centro de Investigacion en Ciencia Aplicada y Tecnologia Avanzada, IPN, Av. Legaria 694, Col. Irrigacion, 11500 Mexico D. F.(Mexico)], e-mail: hduran20_1@hotmail.com
2009-10-15
Mammography test is a central tool for breast cancer diagnostic. In addition, programs are conducted periodically to detect the asymptomatic women in certain age groups; these programs have shown a reduction on breast cancer mortality. Early detection of breast cancer is achieved through a mammography, which contrasts the glandular and adipose tissue with a probable calcification. The parameters used for mammography are based on the thickness and density of the breast, their values depend on the voltage, current, focal spot and anode-filter combination. To achieve an image clear and a minimum dose must be chosen appropriate irradiation conditions. Risk associated with mammography should not be ignored. This study was performed in the General Hospital No. 1 IMSS in Zacatecas. Was used a glucose phantom and measured air Kerma at the entrance of the breast that was calculated using Monte Carlo methods and ZrO{sub 2}+PTFE thermoluminescent dosemeters, this calculation was completed with calculating the absorbed dose. (author)
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.
Energy Technology Data Exchange (ETDEWEB)
Moralles, M. [Centro do Reator de Pesquisas, Instituto de Pesquisas Energeticas e Nucleares, Caixa Postal 11049, CEP 05422-970, Sao Paulo SP (Brazil)], E-mail: moralles@ipen.br; Bonifacio, D.A.B. [Centro do Reator de Pesquisas, Instituto de Pesquisas Energeticas e Nucleares, Caixa Postal 11049, CEP 05422-970, Sao Paulo SP (Brazil); Bottaro, M.; Pereira, M.A.G. [Instituto de Eletrotecnica e Energia, Universidade de Sao Paulo, Av. Prof. Luciano Gualberto, 1289, CEP 05508-010, Sao Paulo SP (Brazil)
2007-09-21
Spectra of calibration sources and X-ray beams were measured with a cadmium telluride (CdTe) detector. The response function of the detector was simulated using the GEANT4 Monte Carlo toolkit. Trapping of charge carriers were taken into account using the Hecht equation in the active zone of the CdTe crystal associated with a continuous function to produce drop of charge collection efficiency near the metallic contacts and borders. The rise time discrimination is approximated by a cut in the depth of the interaction relative to cathode and corrections that depend on the pulse amplitude. The least-squares method with truncation was employed to unfold X-ray spectra typically used in medical diagnostics and the results were compared with reference data.
Moralles, M.; Bonifácio, D. A. B.; Bottaro, M.; Pereira, M. A. G.
2007-09-01
Spectra of calibration sources and X-ray beams were measured with a cadmium telluride (CdTe) detector. The response function of the detector was simulated using the GEANT4 Monte Carlo toolkit. Trapping of charge carriers were taken into account using the Hecht equation in the active zone of the CdTe crystal associated with a continuous function to produce drop of charge collection efficiency near the metallic contacts and borders. The rise time discrimination is approximated by a cut in the depth of the interaction relative to cathode and corrections that depend on the pulse amplitude. The least-squares method with truncation was employed to unfold X-ray spectra typically used in medical diagnostics and the results were compared with reference data.
Directory of Open Access Journals (Sweden)
Qinming Liu
2012-01-01
Full Text Available Health management for a complex nonlinear system is becoming more important for condition-based maintenance and minimizing the related risks and costs over its entire life. However, a complex nonlinear system often operates under dynamically operational and environmental conditions, and it subjects to high levels of uncertainty and unpredictability so that effective methods for online health management are still few now. This paper combines hidden semi-Markov model (HSMM with sequential Monte Carlo (SMC methods. HSMM is used to obtain the transition probabilities among health states and health state durations of a complex nonlinear system, while the SMC method is adopted to decrease the computational and space complexity, and describe the probability relationships between multiple health states and monitored observations of a complex nonlinear system. This paper proposes a novel method of multisteps ahead health recognition based on joint probability distribution for health management of a complex nonlinear system. Moreover, a new online health prognostic method is developed. A real case study is used to demonstrate the implementation and potential applications of the proposed methods for online health management of complex nonlinear systems.
Vozinaki, Anthi Eirini K.; Karatzas, George P.; Sibetheros, Ioannis A.; Varouchakis, Emmanouil A.
2014-05-01
Damage curves are the most significant component of the flood loss estimation models. Their development is quite complex. Two types of damage curves exist, historical and synthetic curves. Historical curves are developed from historical loss data from actual flood events. However, due to the scarcity of historical data, synthetic damage curves can be alternatively developed. Synthetic curves rely on the analysis of expected damage under certain hypothetical flooding conditions. A synthetic approach was developed and presented in this work for the development of damage curves, which are subsequently used as the basic input to a flood loss estimation model. A questionnaire-based survey took place among practicing and research agronomists, in order to generate rural loss data based on the responders' loss estimates, for several flood condition scenarios. In addition, a similar questionnaire-based survey took place among building experts, i.e. civil engineers and architects, in order to generate loss data for the urban sector. By answering the questionnaire, the experts were in essence expressing their opinion on how damage to various crop types or building types is related to a range of values of flood inundation parameters, such as floodwater depth and velocity. However, the loss data compiled from the completed questionnaires were not sufficient for the construction of workable damage curves; to overcome this problem, a Weighted Monte Carlo method was implemented, in order to generate extra synthetic datasets with statistical properties identical to those of the questionnaire-based data. The data generated by the Weighted Monte Carlo method were processed via Logistic Regression techniques in order to develop accurate logistic damage curves for the rural and the urban sectors. A Python-based code was developed, which combines the Weighted Monte Carlo method and the Logistic Regression analysis into a single code (WMCLR Python code). Each WMCLR code execution
Frenkel, D.; Ladd, A.J.C.
1984-01-01
We present a new method to compute the absolute free energy of arbitrary solid phases by Monte Carlo simulation. The method is based on the construction of a reversible path from the solid phase under consideration to an Einstein crystal with the same crystallographic structure. As an application of
Tsang, L.; Lou, S. H.; Chan, C. H.
1991-01-01
The extended boundary condition method is applied to Monte Carlo simulations of two-dimensional random rough surface scattering. The numerical results are compared with one-dimensional random rough surfaces obtained from the finite-element method. It is found that the mean scattered intensity from two-dimensional rough surfaces differs from that of one dimension for rough surfaces with large slopes.
Directory of Open Access Journals (Sweden)
Manuele Aufiero
2017-09-01
Full Text Available This paper proposes the adoption of Monte Carlo perturbation theory to approximate the Jacobian matrix of coupled neutronics/thermal-hydraulics problems. The projected Jacobian is obtained from the eigenvalue decomposition of the fission matrix, and it is adopted to solve the coupled problem via the Newton method. This avoids numerical differentiations commonly adopted in Jacobian-free Newton–Krylov methods that tend to become expensive and inaccurate in the presence of Monte Carlo statistical errors in the residual. The proposed approach is presented and preliminarily demonstrated for a simple two-dimensional pressurized water reactor case study.
Sharma, Diksha; Badal, Andreu; Badano, Aldo
2012-04-21
The computational modeling of medical imaging systems often requires obtaining a large number of simulated images with low statistical uncertainty which translates into prohibitive computing times. We describe a novel hybrid approach for Monte Carlo simulations that maximizes utilization of CPUs and GPUs in modern workstations. We apply the method to the modeling of indirect x-ray detectors using a new and improved version of the code MANTIS, an open source software tool used for the Monte Carlo simulations of indirect x-ray imagers. We first describe a GPU implementation of the physics and geometry models in fastDETECT2 (the optical transport model) and a serial CPU version of the same code. We discuss its new features like on-the-fly column geometry and columnar crosstalk in relation to the MANTIS code, and point out areas where our model provides more flexibility for the modeling of realistic columnar structures in large area detectors. Second, we modify PENELOPE (the open source software package that handles the x-ray and electron transport in MANTIS) to allow direct output of location and energy deposited during x-ray and electron interactions occurring within the scintillator. This information is then handled by optical transport routines in fastDETECT2. A load balancer dynamically allocates optical transport showers to the GPU and CPU computing cores. Our hybridMANTIS approach achieves a significant speed-up factor of 627 when compared to MANTIS and of 35 when compared to the same code running only in a CPU instead of a GPU. Using hybridMANTIS, we successfully hide hours of optical transport time by running it in parallel with the x-ray and electron transport, thus shifting the computational bottleneck from optical tox-ray transport. The new code requires much less memory than MANTIS and, asa result, allows us to efficiently simulate large area detectors.
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)
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…
The Dynamic Monte Carlo Method for Transient Analysis of Nuclear Reactors
Sjenitzer, B.L.
2013-01-01
In this thesis a new method for the analysis of power transients in a nuclear reactor is developed, which is more accurate than the present state-of-the-art methods. Transient analysis is important tool when designing nuclear reactors, since they predict the behaviour of a reactor during changing
Benhdech, Yassine; Beaumont, Stéphane; Guédon, Jean-Pierre; Torfeh, Tarraf
2010-04-01
In this paper, we deepen the R&D program named DTO-DC (Digital Object Test and Dosimetric Console), which goal is to develop an efficient, accurate and full method to achieve dosimetric quality control (QC) of radiotherapy treatment planning system (TPS). This method is mainly based on Digital Test Objects (DTOs) and on Monte Carlo (MC) simulation using the PENELOPE code [1]. These benchmark simulations can advantageously replace experimental measures typically used as reference for comparison with TPS calculated dose. Indeed, the MC simulations rather than dosimetric measurements allow contemplating QC without tying treatment devices and offer in many situations (i.p. heterogeneous medium, lack of scattering volume...) better accuracy compared to dose measurements with classical dosimetry equipment of a radiation therapy department. Furthermore using MC simulations and DTOs, i.e. a totally numerical QC tools, will also simplify QC implementation, and enable process automation; this allows radiotherapy centers to have a more complete and thorough QC. The program DTO-DC was established primarily on ELEKTA accelerator (photons mode) using non-anatomical DTOs [2]. Today our aim is to complete and apply this program on VARIAN accelerator (photons and electrons mode) using anatomical DTOs. First, we developed, modeled and created three anatomical DTOs in DICOM format: 'Head and Neck', Thorax and Pelvis. We parallelized the PENELOPE code using MPI libraries to accelerate their calculation, we have modeled in PENELOPE geometry Clinac head of Varian Clinac 2100CD (photons mode). Then, to implement this method, we calculated the dose distributions in Pelvis DTO using PENELOPE and ECLIPSE TPS. Finally we compared simulated and calculated dose distributions employing the relative difference proposed by Venselaar [3]. The results of this work demonstrate the feasibility of this method that provides a more accurate and easily achievable QC. Nonetheless, this method, implemented
López-López, José Antonio; Van den Noortgate, Wim; Tanner-Smith, Emily E; Wilson, Sandra Jo; Lipsey, Mark W
2017-12-01
Dependent effect sizes are ubiquitous in meta-analysis. Using Monte Carlo simulation, we compared the performance of 2 methods for meta-regression with dependent effect sizes-robust variance estimation (RVE) and 3-level modeling-with the standard meta-analytic method for independent effect sizes. We further compared bias-reduced linearization and jackknife estimators as small-sample adjustments for RVE and Wald-type and likelihood ratio tests for 3-level models. The bias in the slope estimates, width of the confidence intervals around those estimates, and empirical type I error and statistical power rates of the hypothesis tests from these different methods were compared for mixed-effects meta-regression analysis with one moderator either at the study or at the effect size level. All methods yielded nearly unbiased slope estimates under most scenarios, but as expected, the standard method ignoring dependency provided inflated type I error rates when testing the significance of the moderators. Robust variance estimation methods yielded not only the best results in terms of type I error rate but also the widest confidence intervals and the lowest power rates, especially when using the jackknife adjustments. Three-level models showed a promising performance with a moderate to large number of studies, especially with the likelihood ratio test, and yielded narrower confidence intervals around the slope and higher power rates than those obtained with the RVE approach. All methods performed better when the moderator was at the effect size level, the number of studies was moderate to large, and the between-studies variance was small. Our results can help meta-analysts deal with dependency in their data. © 2017 Crown copyright. Research Synthesis Methods © 2017 John Wiley and Sons, Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Energy Technology Data Exchange (ETDEWEB)
Jadach, S.; Skrzypek, M. [Polish Academy of Sciences, Institute of Nuclear Physics, Krakow (Poland); Nail, G. [University of Manchester, Particle Physics Group, School of Physics and Astronomy, Manchester (United Kingdom); Karlsruhe Institute of Technology, Institute for Theoretical Physics, Karlsruhe (Germany); Placzek, W. [Jagiellonian University, Marian Smoluchowski Institute of Physics, Krakow (Poland); Sapeta, S.; Siodmok, A. [Polish Academy of Sciences, Institute of Nuclear Physics, Krakow (Poland); Theoretical Physics Department, CERN, Geneva (Switzerland)
2017-03-15
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 (NLO+PS). This method was described in detail in our previous publications, where it was also compared with other NLO+PS matching approaches (MC rate at NLO and POWHEG) as well as fixed-order NLO and NNLO calculations. Here we concentrate on presenting some numerical results (cross sections and distributions) for Z/γ* (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 Higgs production in gluon-gluon fusion at the LHC and compare them with MC rate at NLO and POWHEG predictions from Herwig 7, fixed-order results from HNNLO and a resummed calculation from HqT, as well as with experimental data from the ATLAS collaboration. (orig.)
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...
Seo, InSeok; You, Joon S; Hayakawa, Carole K; Venugopalan, Vasan
2007-01-01
The use of perturbation and differential Monte Carlo (pMC/dMC) methods in conjunction with nonlinear optimization algorithms were proposed recently as a means to solve inverse photon migration problems in regionwise heterogeneous turbid media. We demonstrate the application of pMC/dMC methods for the recovery of optical properties in a two-layer extended epithelial tissue model from experimental measurements of spatially resolved diffuse reflectance. The results demonstrate that pMC/dMC methods provide a rapid and accurate approach to solve two-region inverse photon migration problems in the transport regime, that is, on spatial scales smaller than a transport mean free path and in media where optical scattering need not dominate absorption. The pMC/dMC approach is found to be effective over a broad range of absorption (50 to 400%) and scattering (70 to 130%) perturbations. The recovery of optical properties from spatially resolved diffuse reflectance measurements is examined for different sets of source-detector separation. These results provide some guidance for the design of compact fiber-based probes to determine and isolate optical properties from both epithelial and stromal layers of superficial tissues.
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).
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)
Energy Technology Data Exchange (ETDEWEB)
David, Mariano Gazineu; Salata, Camila; Almeida, Carlos Eduardo, E-mail: marianogd08@gmail.com [Universidade do Estado do Rio de Janeiro (UERJ/LCR), Rio de Janeiro (Brazil). Lab. de Ciencias Radiologicas
2014-07-01
The Laboratorio de Ciencias Radiologicas develops a methodology for the determination of the absorbed dose to water by Fricke chemical dosimetry method for brachytherapy sources of {sup 192}Ir high dose rate and have compared their results with the laboratory of the National Research Council Canada. This paper describes the determination of the correction factors by Monte Carlo method, with the Penelope code. Values for all factors are presented, with a maximum difference of 0.22% for their determination by an alternative way. (author)
DEFF Research Database (Denmark)
Møller, Jesper; Pettitt, A. N.; Reeves, R.
2006-01-01
Maximum likelihood parameter estimation and sampling from Bayesian posterior distributions are problematic when the probability density for the parameter of interest involves an intractable normalising constant which is also a function of that parameter. In this paper, an auxiliary variable method...... is presented which requires only that independent samples can be drawn from the unnormalised density at any particular parameter value. The proposal distribution is constructed so that the normalising constant cancels from the Metropolis–Hastings ratio. The method is illustrated by producing posterior samples...
Monte Carlo methods in PageRank computation: When one iteration is sufficient
Avrachenkov, K.; Litvak, Nelli; Nemirovsky, D.; Osipova, N.
2005-01-01
PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. Google computes the PageRank using the power iteration method which requires
Monte Carlo methods in PageRank computation: When one iteration is sufficient
Avrachenkov, K.; Litvak, Nelli; Nemirovsky, D.; Osipova, N.
PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer, and thus it reflects the popularity of a Web page. Google computes the PageRank using the power iteration method, which requires
Markov chain Monte Carlo methods for statistical analysis of RF photonic devices
DEFF Research Database (Denmark)
Piels, Molly; Zibar, Darko
2016-01-01
The microwave reflection coefficient is commonly used to characterize the impedance of high-speed optoelectronic devices. Error and uncertainty in equivalent circuit parameters measured using this data are systematically evaluated. The commonly used nonlinear least-squares method for estimating u...
de Graaf, C.S.L.; Kandhai, D.; Sloot, P.M.A.
According to Basel III, financial institutions have to charge a credit valuation adjustment (CVA) to account for a possible counterparty default. Calculating this measure and its sensitivities is one of the biggest challenges in risk management. Here, we introduce an efficient method for the
C.S.L. de Graaf (Kees); B.D. Kandhai; P.M.A. Sloot
2017-01-01
htmlabstractAccording to Basel III, financial institutions have to charge a credit valuation adjustment (CVA) to account for a possible counterparty default. Calculating this measure and its sensitivities is one of the biggest challenges in risk management. Here, we introduce an efficient method
Energy Technology Data Exchange (ETDEWEB)
Parreno Z, F.; Paucar J, R.; Picon C, C. [Instituto Peruano de Energia Nuclear, Av. Canada 1470, San Borja, Lima 41 (Peru)
1998-12-31
The simulation by Monte Carlo is tool which Medical Physics counts with it for the development of its research, the interest by this tool is growing, as we may observe in the main scientific journals for the years 1995-1997 where more than 27 % of the papers treat over Monte Carlo and/or its applications in the radiation transport.In the Peruvian Institute of Nuclear Energy we are implementing and making use of the MCNP4 and EGS4 codes. In this work are presented the general features of the Monte Carlo method and its more useful applications in Medical Physics. Likewise, it is made a simulation of the calculation of isodose curves in an interstitial treatment with Ir-192 wires in a mammary gland carcinoma. (Author)
An automated Monte-Carlo based method for the calculation of cascade summing factors
Jackson, M. J.; Britton, R.; Davies, A. V.; McLarty, J. L.; Goodwin, M.
2016-10-01
A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ-γ, γ-X, γ-511 and γ-e- coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted.
A computationally effcient moment-preserving Monte Carlo proton transport method in Geant4
Dixon, D. A.; Prinja, A. K.; McCartney, A. P.; Hughes, H. G.
2017-09-01
The moment-preserving method, demonstrated as a viable alternative to condensed history for electrons, is extended to protons. Given the generality and the flexibility of the method, a discrete Coulomb scattering and discrete impactionization differential cross-section library for protons was readily developed and existing Geant4 electron discrete process and model classes were extended to make use of the new proton library. It is shown that levels of effciency and accuracy similar to those demonstrated for electrons are obtainable for protons in straight-ahead, energy-loss problems. However, in problems with deflection, agreement is strongly dependent on the proton energy. That is, good agreement was observed in the few MeV range, while unsatisfactory agreement was observed in problems with proton energies above 100-MeV.
An automated Monte-Carlo based method for the calculation of cascade summing factors
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Jackson, M.J., E-mail: mark.j.jackson@awe.co.uk; Britton, R.; Davies, A.V.; McLarty, J.L.; Goodwin, M.
2016-10-21
A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ–γ, γ–X, γ–511 and γ–e{sup −} coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted. - Highlights: • Versatile method to calculate coincidence summing factors for gamma-spectrometry analysis. • Based solely on ENSDF format nuclear data and detector efficiency characterisations. • Enables generation of a CSF library for any detector, geometry and radionuclide. • Improves measurement accuracy and reduces acquisition times required to meet MDA.
Bodammer, N. C.; Kaufmann, J.; Kanowski, M.; Tempelmann, C.
2009-02-01
Diffusion tensor tractography (DTT) allows one to explore axonal connectivity patterns in neuronal tissue by linking local predominant diffusion directions determined by diffusion tensor imaging (DTI). The majority of existing tractography approaches use continuous coordinates for calculating single trajectories through the diffusion tensor field. The tractography algorithm we propose is characterized by (1) a trajectory propagation rule that uses voxel centres as vertices and (2) orientation probabilities for the calculated steps in a trajectory that are obtained from the diffusion tensors of either two or three voxels. These voxels include the last voxel of each previous step and one or two candidate successor voxels. The precision and the accuracy of the suggested method are explored with synthetic data. Results clearly favour probabilities based on two consecutive successor voxels. Evidence is also provided that in any voxel-centre-based tractography approach, there is a need for a probability correction that takes into account the geometry of the acquisition grid. Finally, we provide examples in which the proposed fibre-tracking method is applied to the human optical radiation, the cortico-spinal tracts and to connections between Broca's and Wernicke's area to demonstrate the performance of the proposed method on measured data.
A scatter correction method for dual-energy digital mammography: Monte Carlo simulation.
Ai, Kai; Gao, Yanhua; Yu, Gang
2014-01-01
To develop a novel scatter correction method without additional patient dose for dual-energy digital mammography (DEDM) to reduce scatter's impacts and enhance microcalcification detectability in dual-energy X-ray subtraction image. Combining scatter radiation is lower spatial frequency component and calcifications are sparsely distributed in digital mammogram, we develop a new scatter correction strategy. First, an adaptive sampling scheme is presented to find possible noncalcification (zero calcification) pixels. Then the maximum likelihood expectation maximization (MLEM) algorithm is applied to evaluate initial scatter surface. The accurate scatter radiation of sampling pixels is obtained by solving dual-energy computational formula with zero calcification constraint and scatter surface constraint. After scatter correction, the scatter-to-primary ratio (SPR) of wedge phantom is reduced from ~36.0% to ~3.1% for low-energy (LE) image and ~29.6% to ~0.6% for high-energy (HE) image. For step phantom, the SPR is reduced from ~42.1% and ~30.3% to ~3.9% and ~0.9% for LE and HE image, respectively. The calcification contrast-to-noise ratio is improved by two orders of magnitudes in calcification images. The proposed method shows an excellent performance on scatter reduction and calcification detection. Compared with hardware based scatter correction strategy, our method need no extra exposure and is easy to implementation.
Dosimetry in thyroid follicles due to low-energy electrons of iodine using the Monte Carlo method
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Campos, Laelia; Silva, Frank da [Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE (Brazil). Dept. of Statistics and Information Technology]. E-mail: lpbcampos@gmail.com; l.campos@deinfo.ufrpe.br
2008-11-15
Objective: To evaluate the absorbed dose in thyroid follicles due to low-energy electrons such as Auger and internal conversion electrons, besides beta particles, for iodine radioisotopes ({sup 131}I, {sup 132}I, {sup 13}'3I, {sup 134}I and {sup 135}I) utilizing the Monte Carlo method. Materials And Methods: The dose calculation was performed at follicular level, simulating Auger, internal conversion electrons and beta particles, with the MCNP4C code. The follicles (colloid and follicular cells) were modeled as spheres with colloid diameter ranging from 30 to 500 {mu}m, and with the same density of water (1.0 g.cm{sup -3}). Results: Considering low-energy particles, the contribution of {sup 131}I for total absorbed dose to the colloid is about 25%, while the contribution due to short-lived isotopes is 75%. For follicular cells, this contribution is still higher achieving 87% due to short-lived iodine and 13% due to {sup 131}I. Conclusion: The results of the present study demonstrate the importance of considering low energy particles in the contribution for the total absorbed dose at follicular level (colloid and follicular cells) due to iodine radioisotopes ({sup 13}'1I, {sup 13}'2I, {sup 1}'3'3I, {sup 1}'3{sup 4}I and {sup 135}I). (author)
Karimi, Hamed; Rosenberg, Gili; Katzgraber, Helmut G.
2017-10-01
We present and apply a general-purpose, multistart algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are smaller and less connected, and samplers tend to give better low-energy samples for these problems. The algorithm is trivially parallelizable since each start in the multistart algorithm is independent, and could be applied to any heuristic solver that can be run multiple times to give a sample. We present results for several classes of hard problems solved using simulated annealing, path-integral quantum Monte Carlo, parallel tempering with isoenergetic cluster moves, and a quantum annealer, and show that the success metrics and the scaling are improved substantially. When combined with this algorithm, the quantum annealer's scaling was substantially improved for native Chimera graph problems. In addition, with this algorithm the scaling of the time to solution of the quantum annealer is comparable to the Hamze-de Freitas-Selby algorithm on the weak-strong cluster problems introduced by Boixo et al. Parallel tempering with isoenergetic cluster moves was able to consistently solve three-dimensional spin glass problems with 8000 variables when combined with our method, whereas without our method it could not solve any.
Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.
Kumar, Ashwani; Chauhan, Shilpi
2017-01-01
SIRT1 inhibitors offer therapeutic potential for the treatment of a number of diseases including cancer and human immunodeficiency virus infection. A diverse series of 45 compounds with reported SIRT1 inhibitory activity has been employed for the development of quantitative structure-activity relationship (QSAR) models using the Monte Carlo optimization method. This method makes use of simplified molecular input line entry system notation of the molecular structure. The QSAR models were built up according to OECD principles. Three subsets of three splits were examined and validated by respective external sets. All the three described models have good statistical quality. The best model has the following statistical characteristics: R 2 = 0.8350, Q 2 test = 0.7491 for the test set and R 2 = 0.9655, Q 2 ext = 0.9261 for the validation set. In the mechanistic interpretation, structural attributes responsible for the endpoint increase and decrease are defined. Further, the design of some prospective SIRT1 inhibitors is also presented on the basis of these structural attributes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Balaji, S.P.; Gangarapu, S.; Ramdin, M.; Torres-Knoop, A.; Zuilhof, H.; Goetheer, E.; Dubbeldam, D.; Vlugt, T.
2015-01-01
Molecular simulations were used to compute the equilibrium concentrations of the different species in CO2/monoethanolamine solutions for different CO2 loadings. Simulations were performed in the Reaction Ensemble using the continuous fractional component Monte Carlo method at temperatures of 293,
LIU, B.; Liang, Y.
2015-12-01
Markov chain Monte Carlo (MCMC) simulation is a powerful statistical method in solving inverse problems that arise from a wide range of applications, such as nuclear physics, computational biology, financial engineering, among others. In Earth sciences applications of MCMC are primarily in the field of geophysics [1]. The purpose of this study is to introduce MCMC to geochemical inverse problems related to trace element fractionation during concurrent melting, melt transport and melt-rock reaction in the mantle. MCMC method has several advantages over linearized least squares methods in inverting trace element patterns in basalts and mantle rocks. First, MCMC can handle equations that have no explicit analytical solutions which are required by linearized least squares methods for gradient calculation. Second, MCMC converges to global minimum while linearized least squares methods may be stuck at a local minimum or converge slowly due to nonlinearity. Furthermore, MCMC can provide insight into uncertainties of model parameters with non-normal trade-off. We use MCMC to invert for extent of melting, amount of trapped melt, and extent of chemical disequilibrium between the melt and residual solid from REE data in abyssal peridotites from Central Indian Ridge and Mid-Atlantic Ridge. In the first step, we conduct forward calculation of REE evolution with melting models in a reasonable model space. We then build up a chain of melting models according to Metropolis-Hastings algorithm to represent the probability of specific model. We show that chemical disequilibrium is likely to play an important role in fractionating LREE in residual peridotites. In the future, MCMC will be applied to more realistic but also more complicated melting models in which partition coefficients, diffusion coefficients, as well as melting and melt suction rates vary as functions of temperature, pressure and mineral compositions. [1]. Sambridge & Mosegarrd [2002] Rev. Geophys.
Matilainen, Kaarina; Mäntysaari, Esa A; Lidauer, Martin H; Strandén, Ismo; Thompson, Robin
2013-01-01
Estimation of variance components by Monte Carlo (MC) expectation maximization (EM) restricted maximum likelihood (REML) is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR), where the information matrix was generated via sampling; MC average information(AI), where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.
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Kaarina Matilainen
Full Text Available Estimation of variance components by Monte Carlo (MC expectation maximization (EM restricted maximum likelihood (REML is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR, where the information matrix was generated via sampling; MC average information(AI, where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.
Assaraf, Roland
2014-12-01
We show that the recently proposed correlated sampling without reweighting procedure extends the locality (asymptotic independence of the system size) of a physical property to the statistical fluctuations of its estimator. This makes the approach potentially vastly more efficient for computing space-localized properties in large systems compared with standard correlated methods. A proof is given for a large collection of noninteracting fragments. Calculations on hydrogen chains suggest that this behavior holds not only for systems displaying short-range correlations, but also for systems with long-range correlations.
Monte Carlo Methods to Establish Confidence in Planets Discovered by Transit Photometry
Jenkins, J. M.; Caldwell, D. A.
2000-12-01
With the astonishing discovery of about a dozen super giant short-period (attention on the problem of assessing the significance of a candidate transit signature. There are two fundamental quantities of interest required to establish the confidence in a planetary candidate. These are: 1) the equivalent number of independent statistical tests conducted in searching the light curve of one star for transiting planets over a given range of periods, and 2) the characteristics of the observation noise for the light curve in question. The latter quantity determines the false alarm rate for a single test for that particular star as a function of the detection threshold. The former quantity, together with the total number of target stars in the observing program, dictate the requisite single-test false alarm rate based on the acceptable total number of false alarms. The methods described do not make any presumptions about the distribution of the observational noise. In addition they either provide conservative results for non-white noise or take the correlation structure of the noise into account. The results of this paper show that transit photometry is a promising method for detecting planets even in the presence of colored, non-Gaussian noise and with the required large number of target stars (>100,000 stars in the case of the Kepler Mission) for the small geometric probability of transit alignment. Support for this work was received from NASA's Discovery Program.
Xu, Yuan; Bai, Ti; Yan, Hao; Ouyang, Luo; Pompos, Arnold; Wang, Jing; Zhou, Linghong; Jiang, Steve B.; Jia, Xun
2015-05-01
Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 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
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Hossein Khosravi
2016-11-01
Full Text Available Purpose: In this work, gold nanoparticles (GNPs were embedded in the MAGIC-f polymer gel irradiated with the 192 Ir brachytherapy sources. Material and methods: At the first plexiglas phantom was made as the human pelvis. The GNPs were synthesized with 15 nm in diameter and 0.1 mM (0.0197 mg/ml in concentration by using a chemical reduction method. Then, the MAGIC-f gel was synthesized. The fabricated gel was poured into the tubes located at the prostate (with and without the GNPs locations of the phantom. The phantom was irradiated with 192 Ir brachytherapy sources for prostate cancer. After 24 hours, the irradiated gels was read by using Siemens 1.5 Tesla MRI scanner. Following the brachytherapy practices, the absolute doses at the reference points and isodose curves were extracted and compared by experimental measurements and Monte Carlo (MC simulations. Results : The mean absorbed doses in the presence of the GNPs in prostate were 14% higher than the corresponding values without the GNPs in the brachytherapy. The gamma index analysis (between gel and MC using 7%/7 mm was also applied to the data and a high pass rate achieved (91.7% and 86.4% for analysis with/without GNPs, respectively. Conclusions : The real three-dimensional analysis shows the comparison of the dose-volume histograms measured for planning volumes and the expected one from the MC calculation. The results indicate that the polymer gel dosimetry method, which developed and used in this study, could be recommended as a reliable method for investigating the dose enhancement factor of GNPs in brachytherapy.
Research of Fiber Composite Heat Conductivity by Monte-Carlo Method
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O. V. Pugachev
2015-01-01
Full Text Available The work objective is to evaluate the effective heat conductivity coefficient of a material with parallel cylindrical inclusions with equal diameters.Since an analytical solution of the heat conductivity equation is quite difficult, we apply a mathematical model, in which a random motion of the imaginary "heat particles" represents the process of heat conduction. These particles represent a sample of distribution, which has density being, at every moment, proportional to that of the heat energy. Thus, using the Wiener processes enables obtaining the solution of the heat conductivity equation. The velocity of "heat particles" depends on the temperature conductivity coefficient of the material in which the particles are moving at the moment.The paper considers a layer fragment of the composite material whose effective temperature conductivity coefficient is to be evaluated. As a criterion of heat conduction, we consider the probability P, assuming that a heat particle, having started from one surface of the layer, reaches its opposite surface for a time less than T. For a homogeneous isotropic material, this probability is analytically found.We perform a series of computer experiments to simulate heat conduction through a layer of the composite material, the source of heat being applied to one surface of the layer, and heat being absorbed at the opposite surface. By statistical elaboration of their results we find confidence intervals for P. Therefrom we find confidence intervals for the effective temperature conductivity coefficients (by comparing with homogeneous materials yielding the same value of P. Next, the effective heat conductivity coefficients are obtained through multiplying the effective temperature conductivity by the average volume heat capacity.We took various proportions between cylinder diameters and distances between them. The results obtained are consistent with analytical ones. The method elaborated allows finding effective
Ródenas, José
2017-11-01
All materials exposed to some neutron flux can be activated independently of the kind of the neutron source. In this study, a nuclear reactor has been considered as neutron source. In particular, the activation of control rods in a BWR is studied to obtain the doses produced around the storage pool for irradiated fuel of the plant when control rods are withdrawn from the reactor and installed into this pool. It is very important to calculate these doses because they can affect to plant workers in the area. The MCNP code based on the Monte Carlo method has been applied to simulate activation reactions produced in the control rods inserted into the reactor. Obtained activities are introduced as input into another MC model to estimate doses produced by them. The comparison of simulation results with experimental measurements allows the validation of developed models. The developed MC models have been also applied to simulate the activation of other materials, such as components of a stainless steel sample introduced into a training reactors. These models, once validated, can be applied to other situations and materials where a neutron flux can be found, not only nuclear reactors. For instance, activation analysis with an Am-Be source, neutrography techniques in both medical applications and non-destructive analysis of materials, civil engineering applications using a Troxler, analysis of materials in decommissioning of nuclear power plants, etc.
Simulation of 12C+12C elastic scattering at high energy by using the Monte Carlo method
Guo, Chen-Lei; Zhang, Gao-Long; Tanihata, I.; Le, Xiao-Yun
2012-03-01
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 phi5 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.
Su, Lin; Du, Xining; Liu, Tianyu; Xu, X. George
2014-06-01
An electron-photon coupled Monte Carlo code ARCHER - Accelerated Radiation-transport Computations in Heterogeneous EnviRonments - is being developed at Rensselaer Polytechnic Institute as a software testbed for emerging heterogeneous high performance computers that utilize accelerators such as GPUs. This paper presents the preliminary code development and the testing involving radiation dose related problems. In particular, the paper discusses the electron transport simulations using the class-II condensed history method. The considered electron energy ranges from a few hundreds of keV to 30 MeV. For photon part, photoelectric effect, Compton scattering and pair production were modeled. Voxelized geometry was supported. A serial CPU code was first written in C++. The code was then transplanted to the GPU using the CUDA C 5.0 standards. The hardware involved a desktop PC with an Intel Xeon X5660 CPU and six NVIDIA Tesla™ M2090 GPUs. The code was tested for a case of 20 MeV electron beam incident perpendicularly on a water-aluminum-water phantom. The depth and later dose profiles were found to agree with results obtained from well tested MC codes. Using six GPU cards, 6x106 electron histories were simulated within 2 seconds. In comparison, the same case running the EGSnrc and MCNPX codes required 1645 seconds and 9213 seconds, respectively. On-going work continues to test the code for different medical applications such as radiotherapy and brachytherapy.
Chen, Lei; Li, JiaRui; Zhang, Yu-Hang; Feng, KaiYan; Wang, ShaoPeng; Zhang, YunHua; Huang, Tao; Kong, Xiangyin; Cai, Yu-Dong
2017-11-11
Adult neural stem cells (NSCs) are a group of multi-potent, self-renewing progenitor cells that contribute to the generation of new neurons and oligodendrocytes. Three subtypes of NSCs can be isolated based on the stages of the NSC lineage, including quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs). Although it is widely accepted that these three groups of NSCs play different roles in the development of the nervous system, their molecular signatures are poorly understood. In this study, we applied the Monte-Carlo Feature Selection (MCFS) method to identify the gene expression signatures, which can yield a Matthews correlation coefficient (MCC) value of 0.918 with a support vector machine evaluated by ten-fold cross-validation. In addition, some classification rules yielded by the MCFS program for distinguishing above three subtypes were reported. Our results not only demonstrate a high classification capacity and subtype-specific gene expression patterns but also quantitatively reflect the pattern of the gene expression levels across the NSC lineage, providing insight into deciphering the molecular basis of NSC differentiation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Khrystyna Moskalova
2017-01-01
Full Text Available Considering that modern building materials impose increasing performance requirements, it is necessary to expand the range of building materials and improve their multicomponent composition. The effects of polymer and porous components (expanded perlite sand and carbonate filler – limestone-shell rock in cement-lime light plaster on the physico-mechanical properties of the mixtures under equal workability conditions of mixtures are analyzed based on experimental-statistical modeling. The results of the physico-mechanical and operational experiments confirm the rationality of using porous fillers and additives to improve certain specific properties of the final product. The so-called Monte-Carlo method is implemented for determining an optimal composition of multicomponent cement-lime light plaster, based on multivariate statistical modeling and iterative random scanning of property fields. According to the results of the computational experiment, a composition that reduces the number of expensive mixture components and improves the physical and mechanical characteristics of the resulting composition is selected.
Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya
2017-10-01
Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.
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Palmans, H. [Ghent Univ. (Belgium). Dept. of Biomedical Physics; Verhaegen, F.
1995-12-01
In the last decade, several clinical proton beam therapy facilities have been developed. To satisfy the demand for uniformity in clinical (routine) proton beam dosimetry two dosimetry protocols (ECHED and AAPM) have been published. Both protocols neglect the influence of ion chamber dependent parameters on dose determination in proton beams because of the scatter properties of these beams, although the problem has not been studied thoroughly yet. A comparison between water calorimetry and ionisation chamber dosimetry showed a discrepancy of 2.6% between the former method and ionometry following the ECHED protocol. Possibly, a small part of this difference can be attributed to chamber dependent correction factors. Indications for this possibility are found in ionometry measurements. To allow the simulation of complex geometries with different media necessary for the study of those corrections, an existing proton Monte Carlo code (PTRAN, Berger) has been modified. The original code, that applies Mollire`s multiple scattering theory and Vavilov`s energy straggling theory, calculates depth dose profiles, energy distributions and radial distributions for pencil beams in water. Comparisons with measurements and calculations reported in the literature are done to test the program`s accuracy. Preliminary results of the influence of chamber design and chamber materials on dose to water determination are presented.
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Jalid Abdelilah
2016-01-01
Full Text Available In engineering industry, control of manufactured parts is usually done on a coordinate measuring machine (CMM, a sensor mounted at the end of the machine probes a set of points on the surface to be inspected. Data processing is performed subsequently using software, and the result of this measurement process either validates or not the conformity of the part. Measurement uncertainty is a crucial parameter for making the right decisions, and not taking into account this parameter can, therefore, sometimes lead to aberrant decisions. The determination of the uncertainty measurement on CMM is a complex task for the variety of influencing factors. Through this study, we aim to check if the uncertainty propagation model developed according to the guide to the expression of uncertainty in measurement (GUM approach is valid, we present here a comparison of the GUM and Monte Carlo methods. This comparison is made to estimate a flatness deviation of a surface belonging to an industrial part and the uncertainty associated to the measurement result.
Kohno, R; Hotta, K; Nishioka, S; Matsubara, K; Tansho, R; Suzuki, T
2011-11-21
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
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Christelle Garnier
2008-05-01
Full Text Available We address the problem of phase noise (PHN and carrier frequency offset (CFO mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE and the intercarrier interference (ICI which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER and mean square error (MSE to illustrate the efficiency and the robustness of the proposed algorithm.
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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
Song, Sangha; Elgezua, Inko; Kobayashi, Yo; Fujie, Masakatsu G
2013-01-01
In biomedical, Monte-carlo simulation is commonly used for simulation of light diffusion in tissue. But, most of previous studies did not consider a radial beam LED as light source. Therefore, we considered characteristics of a radial beam LED and applied them on MC simulation as light source. In this paper, we consider 3 characteristics of radial beam LED. The first is an initial launch area of photons. The second is an incident angle of a photon at an initial photon launching area. The third is the refraction effect according to contact area between LED and a turbid medium. For the verification of the MC simulation, we compared simulation and experimental results. The average of the correlation coefficient between simulation and experimental results is 0.9954. Through this study, we show an effective method to simulate light diffusion on tissue with characteristics for radial beam LED based on MC simulation.
Watté, Rodrigo; Aernouts, Ben; Van Beers, Robbe; Herremans, Els; Ho, Quang Tri; Verboven, Pieter; Nicolaï, Bart; Saeys, Wouter
2015-06-29
Monte Carlo methods commonly used in tissue optics are limited to a layered tissue geometry and thus provide only a very rough approximation for many complex media such as biological structures. To overcome these limitations, a Meshed Monte Carlo method with flexible phase function choice (fpf-MC) has been developed to function in a mesh. This algorithm can model the light propagation in any complexly shaped structure, by attributing optical properties to the different mesh elements. Furthermore, this code allows the use of different discretized phase functions for each tissue type, which can be simulated from the microstructural properties of the tissue, in combination with a tool for simulating the bulk optical properties of polydisperse suspensions. As a result, the scattering properties of tissues can be estimated from information on the microstructural properties of the tissue. This is important for the estimation of the bulk optical properties that can be used for the light propagation model, since many types of tissue have never been characterized in literature. The combination of these contributions, made it possible to use the MMC-fpf for modeling the light porapagation in plant tissue. The developed Meshed Monte Carlo code with flexible phase function choice (MMC-fpf) was successfully validated in simulation through comparison with the Monte Carlo code in Multi-Layered tissues (R2 > 0.9999) and experimentally by comparing the measured and simulated reflectance (RMSE = 0.015%) and transmittance (RMSE = 0.0815%) values for tomato leaves.
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Vincenzo Del Giudice
2017-11-01
Full Text Available This paper experiments an artificial neural networks model with Bayesian approach on a small real estate sample. The output distribution has been calculated operating a numerical integration on the weights space with the Markov Chain Hybrid Monte Carlo Method (MCHMCM. On the same real estate sample, MCHMCM has been compared with a neural networks model (NNs, traditional multiple regression analysis (MRA and the Penalized Spline Semiparametric Method (PSSM. All four methods have been developed for testing the forecasting capacity and reliability of MCHMCM in the real estate field. The Markov Chain Hybrid Monte Carlo Method has proved to be the best model with an absolute average percentage error of 6.61%.
Reibnegger, Gilbert; Schrabmair, Walter
2014-11-25
Using Monte Carlo simulations, we compare different methods (maximizing Youden index, maximizing mutual information, and logistic regression) for their ability to determine optimum binary cut-off thresholds for a ratio-scaled diagnostic test variable. Special attention is given to the stability and precision of the results in dependence on the distributional characteristics as well as the pre-test probabilities of the diagnostic categories in the test population. Fictitious data sets of a ratio-scaled diagnostic test with different distributional characteristics are generated for 50, 100 and 200 fictitious "individuals" with systematic variation of pre-test probabilities of two diagnostic categories. For each data set, optimum binary cut-off limits are determined employing different methods. Based on these optimum cut-off thresholds, sensitivities and specificities are calculated for the respective data sets. Mean values and SD of these variables are computed for 1000 repetitions each. Optimizations of cut-off limits using Youden index and logistic regression-derived likelihood ratio functions with correct adaption for pre-test probabilities both yield reasonably stable results, being nearly independent from pre-test probabilities actually used. Maximizing mutual information yields cut-off levels decreasing with increasing pre-test probability of disease. The most precise results (in terms of the smallest SD) are usually seen for the likelihood ratio method. With this parametric method, however, cut-off values show a significant positive bias and, hence, specificities are usually slightly higher, and sensitivities are consequently slightly lower than with the two non-parametric methods. In terms of stability and bias, Youden index is best suited for determining optimal cut-off limits of a diagnostic variable. The results of Youden method and likelihood ratio method are surprisingly insensitive against distributional differences as well as pre-test probabilities of
Czyzycki, Mateusz; Lankosz, Marek; Bielewski, Marek
2010-04-01
Recently a considerable interest has been triggered in the investigation of the composition of individual particles by X-ray fluorescence microanalysis. The sources of these micro-samples are mostly diversified. These samples come from space dust, air and ash, soil as well as environment and take the shape of a sphere or an oval. In analysis this kind of samples the geometrical effects caused by different sizes and shapes influence on accuracy of results. This fact arises from the matrix effect. For these samples it is not possible to find analytically a solution of equation taking into account an absorption of X-rays. Hence, a way out is to approximate the real sample shape with the other one or to use Monte Carlo (MC) simulation method. In current work authors utilized the iterative MC simulation to assess an elemental percentage of individual particles. The set of glass micro-spheres, made of NIST K3089 material of known chemical composition, with diameters in the range between 25 and 45 μm was investigated. The microspheres were scanned with X-ray tube primary radiation. Results of MC simulation were compared with these of some analytical approaches based on particle shape approximation. An investigation showed that the low-Z elements (Si, Ca, Ti) were the most sensitive on changes of particle shape and sizes. For high-Z elements (Fe—Pb) concentrations were nearly equal regardless of method used. However, for the all elements considered, results of MC simulation were more accurate then these of analytical relationships taken into comparison.
Modeling kinetics of a large-scale fed-batch CHO cell culture by Markov chain Monte Carlo method.
Xing, Zizhuo; Bishop, Nikki; Leister, Kirk; Li, Zheng Jian
2010-01-01
Markov chain Monte Carlo (MCMC) method was applied to model kinetics of a fed-batch Chinese hamster ovary cell culture process in 5,000-L bioreactors. The kinetic model consists of six differential equations, which describe dynamics of viable cell density and concentrations of glucose, glutamine, ammonia, lactate, and the antibody fusion protein B1 (B1). The kinetic model has 18 parameters, six of which were calculated from the cell culture data, whereas the other 12 were estimated from a training data set that comprised of seven cell culture runs using a MCMC method. The model was confirmed in two validation data sets that represented a perturbation of the cell culture condition. The agreement between the predicted and measured values of both validation data sets may indicate high reliability of the model estimates. The kinetic model uniquely incorporated the ammonia removal and the exponential function of B1 protein concentration. The model indicated that ammonia and lactate play critical roles in cell growth and that low concentrations of glucose (0.17 mM) and glutamine (0.09 mM) in the cell culture medium may help reduce ammonia and lactate production. The model demonstrated that 83% of the glucose consumed was used for cell maintenance during the late phase of the cell cultures, whereas the maintenance coefficient for glutamine was negligible. Finally, the kinetic model suggests that it is critical for B1 production to sustain a high number of viable cells. The MCMC methodology may be a useful tool for modeling kinetics of a fed-batch mammalian cell culture process.
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D. Zaldívar
1999-01-01
Full Text Available Copolymers of furfuryl acrylate (A with 2-hydroxyethyl methacrylate (H were prepared by free radical copolymerization in DMF solution at 50°C, using 2,2'-azobisisobutyronitrile (AIBN as initiator. The reactivity ratios of both monomers were calculated according to the general copolymerization equation using the Fineman-Röss and Kelen-Tüdos 1inearization methods, as well as the Tidwell-Mortimer non linear least-squares treatment and the Monte Carlo random method. The reactivity ratios obtained were rA = 0.93 and rH = 1.42. Similar results were obtained by both, the Monte Carlo and the non-linear least squares methods. The microstructure of copolymer chains based on the first order Markov statistics is described.
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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.
Mahjoub, Mehdi
La resolution de l'equation de Boltzmann demeure une etape importante dans la prediction du comportement d'un reacteur nucleaire. Malheureusement, la resolution de cette equation presente toujours un defi pour une geometrie complexe (reacteur) tout comme pour une geometrie simple (cellule). Ainsi, pour predire le comportement d'un reacteur nucleaire,un schema de calcul a deux etapes est necessaire. La premiere etape consiste a obtenir les parametres nucleaires d'une cellule du reacteur apres une etape d'homogeneisation et condensation. La deuxieme etape consiste en un calcul de diffusion pour tout le reacteur en utilisant les resultats de la premiere etape tout en simplifiant la geometrie du reacteur a un ensemble de cellules homogenes le tout entoure de reflecteur. Lors des transitoires (accident), ces deux etapes sont insuffisantes pour pouvoir predire le comportement du reacteur. Comme la resolution de l'equation de Boltzmann dans sa forme dependante du temps presente toujours un defi de taille pour tous types de geometries,un autre schema de calcul est necessaire. Afin de contourner cette difficulte, l'hypothese adiabatique est utilisee. Elle se concretise en un schema de calcul a quatre etapes. La premiere et deuxieme etapes demeurent les memes pour des conditions nominales du reacteur. La troisieme etape se resume a obtenir les nouvelles proprietes nucleaires de la cellule a la suite de la perturbation pour les utiliser, au niveau de la quatrieme etape, dans un nouveau calcul de reacteur et obtenir l'effet de la perturbation sur le reacteur. Ce projet vise a verifier cette hypothese. Ainsi, un nouveau schema de calcul a ete defini. La premiere etape de ce projet a ete de creer un nouveau logiciel capable de resoudre l'equation de Boltzmann dependante du temps par la methode stochastique Monte Carlo dans le but d'obtenir des sections efficaces qui evoluent dans le temps. Ce code a ete utilise pour simuler un accident LOCA dans un reacteur nucleaire de type
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.
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
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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
Khan, Md Nabiul Islam; Hijbeek, Renske; Berger, Uta; Koedam, Nico; Grueters, Uwe; Islam, S M Zahirul; Hasan, Md Asadul; Dahdouh-Guebas, Farid
2016-01-01
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
Theodorou, Dimitrios; Meligotsidou, Loukia; Karavoltsos, Sotirios; Burnetas, Apostolos; Dassenakis, Manos; Scoullos, Michael
2011-02-15
The propagation stage of uncertainty evaluation, known as the propagation of distributions, is in most cases approached by the GUM (Guide to the Expression of Uncertainty in Measurement) uncertainty framework which is based on the law of propagation of uncertainty assigned to various input quantities and the characterization of the measurand (output quantity) by a Gaussian or a t-distribution. Recently, a Supplement to the ISO-GUM was prepared by the JCGM (Joint Committee for Guides in Metrology). This Guide gives guidance on propagating probability distributions assigned to various input quantities through a numerical simulation (Monte Carlo Method) and determining a probability distribution for the measurand. In the present work the two approaches were used to estimate the uncertainty of the direct determination of cadmium in water by graphite furnace atomic absorption spectrometry (GFAAS). The expanded uncertainty results (at 95% confidence levels) obtained with the GUM Uncertainty Framework and the Monte Carlo Method at the concentration level of 3.01 μg/L were ±0.20 μg/L and ±0.18 μg/L, respectively. Thus, the GUM Uncertainty Framework slightly overestimates the overall uncertainty by 10%. Even after taking into account additional sources of uncertainty that the GUM Uncertainty Framework considers as negligible, the Monte Carlo gives again the same uncertainty result (±0.18 μg/L). The main source of this difference is the approximation used by the GUM Uncertainty Framework in estimating the standard uncertainty of the calibration curve produced by least squares regression. Although the GUM Uncertainty Framework proves to be adequate in this particular case, generally the Monte Carlo Method has features that avoid the assumptions and the limitations of the GUM Uncertainty Framework. Copyright © 2010 Elsevier B.V. All rights reserved.
Application of MINERVA Monte Carlo simulations to targeted radionuclide therapy.
Descalle, Marie-Anne; Hartmann Siantar, Christine L; Dauffy, Lucile; Nigg, David W; Wemple, Charles A; Yuan, Aina; DeNardo, Gerald L
2003-02-01
Recent clinical results have demonstrated the promise of targeted radionuclide therapy for advanced cancer. As the success of this emerging form of radiation therapy grows, accurate treatment planning and radiation dose simulations are likely to become increasingly important. To address this need, we have initiated the development of a new, Monte Carlo transport-based treatment planning system for molecular targeted radiation therapy as part of the MINERVA system. The goal of the MINERVA dose calculation system is to provide 3-D Monte Carlo simulation-based dosimetry for radiation therapy, focusing on experimental and emerging applications. For molecular targeted radionuclide therapy applications, MINERVA calculates patient-specific radiation dose estimates using computed tomography to describe the patient anatomy, combined with a user-defined 3-D radiation source. This paper describes the validation of the 3-D Monte Carlo transport methods to be used in MINERVA for molecular targeted radionuclide dosimetry. It reports comparisons of MINERVA dose simulations with published absorbed fraction data for distributed, monoenergetic photon and electron sources, and for radioisotope photon emission. MINERVA simulations are generally within 2% of EGS4 results and 10% of MCNP results, but differ by up to 40% from the recommendations given in MIRD Pamphlets 3 and 8 for identical medium composition and density. For several representative source and target organs in the abdomen and thorax, specific absorbed fractions calculated with the MINERVA system are generally within 5% of those published in the revised MIRD Pamphlet 5 for 100 keV photons. However, results differ by up to 23% for the adrenal glands, the smallest of our target organs. Finally, we show examples of Monte Carlo simulations in a patient-like geometry for a source of uniform activity located in the kidney.
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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.
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David, Mariano G.; Pires, Evandro J.; Magalhaes, Luis A.; Almeida, Carlos E. de; Alves, Carlos F.E., E-mail: marianogd08@gmail.com [Universidade do Estado do Rio de Janeiro (UERJ), RJ (Brazil). Lab. Ciencias Radiologicas; Albuquerque, Marcos A. [Coordenacao dos Programas de Pos-Graduacao de Engenharia (COPPE/UFRJ), RJ (Brazil). Instituto Alberto Luiz Coimbra; Bernal, Mario A. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil). Instituto de Fisica Gleb Wataghin; Peixoto, Jose G. [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil)
2012-08-15
This paper focuses on the obtainment, using experimental and Monte Carlo-simulated (MMC) methods, of the photon spectra at various depths and depth-dose deposition curves for x-rays beams used in mammography, obtained on a polymethylmethacrylate (PMMA) breast phantom. Spectra were obtained for 28 and 30 kV quality-beams and the corresponding average energy values (Emed) were calculated. For the experimental acquisition was used a Si-PIN photodiode spectrometer and for the MMC simulations the PENELOPE code was employed. The simulated and the experimental spectra show a very good agreement, which was corroborated by the low differences found between the Emed values. An increase in the Emed values and a strong attenuation of the beam through the depth of the PMMA phantom was also observed. (author)
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Costa, Priscila
2014-07-01
The Cuno filter is part of the water processing circuit of the IEA-R1 reactor and, when saturated, it is replaced and becomes a radioactive waste, which must be managed. In this work, the primary characterization of the Cuno filter of the IEA-R1 nuclear reactor at IPEN was carried out using gamma spectrometry associated with the Monte Carlo method. The gamma spectrometry was performed using a hyperpure germanium detector (HPGe). The germanium crystal represents the detection active volume of the HPGe detector, which has a region called dead layer or inactive layer. It has been reported in the literature a difference between the theoretical and experimental values when obtaining the efficiency curve of these detectors. In this study we used the MCNP-4C code to obtain the detector calibration efficiency for the geometry of the Cuno filter, and the influence of the dead layer and the effect of sum in cascade at the HPGe detector were studied. The correction of the dead layer values were made by varying the thickness and the radius of the germanium crystal. The detector has 75.83 cm{sup 3} of active volume of detection, according to information provided by the manufacturer. Nevertheless, the results showed that the actual value of active volume is less than the one specified, where the dead layer represents 16% of the total volume of the crystal. A Cuno filter analysis by gamma spectrometry has enabled identifying energy peaks. Using these peaks, three radionuclides were identified in the filter: {sup 108m}Ag, {sup 110m}Ag and {sup 60}Co. From the calibration efficiency obtained by the Monte Carlo method, the value of activity estimated for these radionuclides is in the order of MBq. (author)
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Rodenas, Jose [Departamento de Ingenieria Quimica y Nuclear, Universidad Politecnica de Valencia, Apartado 22012, E-46071 Valencia (Spain)], E-mail: jrodenas@iqn.upv.es; Gallardo, Sergio; Ballester, Silvia; Primault, Virginie [Departamento de Ingenieria Quimica y Nuclear, Universidad Politecnica de Valencia, Apartado 22012, E-46071 Valencia (Spain); Ortiz, Josefina [Laboratorio de Radiactividad Ambiental, Universidad Politecnica de Valencia, Apartado 22012, E-46071 Valencia (Spain)
2007-10-15
A gamma spectrometer including an HP Ge detector is commonly used for environmental radioactivity measurements. The efficiency of the detector should be calibrated for each geometry considered. Simulation of the calibration procedure with a validated computer program is an important auxiliary tool for environmental radioactivity laboratories. The MCNP code based on the Monte Carlo method has been applied to simulate the detection process in order to obtain spectrum peaks and determine the efficiency curve for each modelled geometry. The source used for measurements was a calibration mixed radionuclide gamma reference solution, covering a wide energy range (50-2000 keV). Two measurement geometries - Marinelli beaker and Petri boxes - as well as different materials - water, charcoal, sand - containing the source have been considered. Results obtained from the Monte Carlo model have been compared with experimental measurements in the laboratory in order to validate the model.
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. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hotta, Kenji; Kohno, Ryosuke; Takada, Yoshihisa; Hara, Yousuke; Tansho, Ryohei; Himukai, Takeshi; Kameoka, Satoru; Matsuura, Taeko; Nishio, Teiji; Ogino, Takashi
2010-06-01
Treatment planning for proton tumor therapy requires a fast and accurate dose-calculation method. We have implemented a simplified Monte Carlo (SMC) method in the treatment planning system of the National Cancer Center Hospital East for the double-scattering beam delivery scheme. The SMC method takes into account the scattering effect in materials more accurately than the pencil beam algorithm by tracking individual proton paths. We confirmed that the SMC method reproduced measured dose distributions in a heterogeneous slab phantom better than the pencil beam method. When applied to a complex anthropomorphic phantom, the SMC method reproduced the measured dose distribution well, satisfying an accuracy tolerance of 3 mm and 3% in the gamma index analysis. The SMC method required approximately 30 min to complete the calculation over a target volume of 500 cc, much less than the time required for the full Monte Carlo calculation. The SMC method is a candidate for a practical calculation technique with sufficient accuracy for clinical application.
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Wittner, Manuel [Physikalisches Institut, Universitaet Heidelberg, Heidelberg (Germany); Collaboration: ALICE-Collaboration
2015-07-01
One particularly interesting measurement detected by the ALICE set-up at the LHC are electrons from charm and beauty hadron decays. Heavy quarks originate from initial hard scattering processes and thus experience the whole history of a heavy ion collision. Therefore, they are valuable probes to study the mechanisms of energy loss and hadronization in the hot and dense state of matter, that is expected to be formed in a heavy-ion collision at LHC. One important task is the distinction of the different electron sources, for which a method was developed. Hereby, the impact parameter distribution of the measurement data is compared with impact parameter distributions for the individual sources, which are created through Monte Carlo simulations. Afterwards, a maximum likelihood fit is applied. However, creating a posterior distribution of the likelihood according to Bayes' theorem and sampling it with Markov Chain Monte Carlo algorithms provides several advantages, e.g. a mathematically correct estimation of the uncertainties or the usage of prior knowledge. Hence for the first time in this particular problem, a Markov Chain Monte Carlo algorithm, namely the Metropolis algorithm, was implemented and investigated for its applicability in heavy flavor physics. First studies indicate its great usefulness in this field of physics.
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J. M. Vali Samani
2016-02-01
Full Text Available Introduction: The greatest part of constructed dams belongs to embankment dams and there are many examples of their failures throughout history. About one-third of the world’s dam failures have been caused by flood overtopping, which indicates that flood overtopping is an important factor affecting reservoir projects’ safety. Moreover, because of a poor understanding of the randomness of floods, reservoir water levels during flood seasons are often lowered artificially in order to avoid overtopping and protect the lives and property of downstream residents. So, estimation of dam overtopping risk with regard to uncertainties is more important than achieving the dam’s safety. This study presents the procedure for risk evaluation of dam overtopping due to various uncertaintiess in inﬂows and reservoir initial condition. Materials and Methods: This study aims to present a practical approach and compare the different uncertainty analysis methods in the evaluation of dam overtopping risk due to flood. For this purpose, Monte Carlo simulation and Latin hypercube sampling methods were used to calculate the overtopping risk, evaluate the uncertainty, and calculate the highest water level during different flood events. To assess these methods from a practical point of view, the Maroon dam was chosen for the case study. Figure. 1 indicates the work procedure, including three parts: 1 Identification and evaluation of effective factors on flood routing and dam overtopping, 2 Data collection and analysis for reservoir routing and uncertainty analysis, 3 Uncertainty and risk analysis. Figure 1- Diagram of dam overtopping risk evaluation Results and Discussion: Figure 2 shows the results of the computed overtopping risks for the Maroon Dam without considering the wind effect, for the initial water level of 504 m as an example. As it is shown in Figure. 2, the trends of the risk curves computed by the different uncertainty analysis methods are similar
Monte Carlo and nonlinearities
Dauchet, Jérémi; Blanco, Stéphane; Caliot, Cyril; Charon, Julien; Coustet, Christophe; Hafi, Mouna El; Eymet, Vincent; Farges, Olivier; Forest, Vincent; Fournier, Richard; Galtier, Mathieu; Gautrais, Jacques; Khuong, Anaïs; Pelissier, Lionel; Piaud, Benjamin; Roger, Maxime; Terrée, Guillaume; Weitz, Sebastian
2016-01-01
The Monte Carlo method is widely used to numerically predict systems behaviour. However, its powerful incremental design assumes a strong premise which has severely limited application so far: the estimation process must combine linearly over dimensions. Here we show that this premise can be alleviated by projecting nonlinearities on a polynomial basis and increasing the configuration-space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles and concentrated-solar-power-plant productions, we prove the real world usability of this advance on four test-cases that were so far regarded as impracticable by Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to sharp problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise o...
Direct simulation Monte Carlo method for gas flows in micro-channels with bends with added curvature
Directory of Open Access Journals (Sweden)
Tisovský Tomáš
2017-01-01
Full Text Available Gas flows in micro-channels are simulated using an open source Direct Simulation Monte Carlo (DSMC code dsmcFOAM for general application to rarefied gas flow written within the framework of the open source C++ toolbox called OpenFOAM. Aim of this paper is to investigate the flow in micro-channel with bend with added curvature. Results are compared with flows in channel without added curvature and equivalent straight channel. Effects of micro-channel bend was already thoroughly investigated by White et al. Geometry proposed by White is also used here for refference.
Querlioz, Damien
2013-01-01
This book gives an overview of the quantum transport approaches for nanodevices and focuses on the Wigner formalism. It details the implementation of a particle-based Monte Carlo solution of the Wigner transport equation and how the technique is applied to typical devices exhibiting quantum phenomena, such as the resonant tunnelling diode, the ultra-short silicon MOSFET and the carbon nanotube transistor. In the final part, decoherence theory is used to explain the emergence of the semi-classical transport in nanodevices.
2004-11-01
ET, e-’J. This is the same as the second Monte Carlo estimator PMC2 considered previously. Before considering IS estimation in more detail, we...and given Y. Hence P’A = Eo [g(7oY)], suggesting that IS estimation can be performed by biasing Y and estinmating the expecta- tion of g(roY). The...clutter and noise is non-Gaussian. The IS estimation techniques are also not restricted to CA-CFAR, but can be applied to other CFAR schemes. This will be
Energy Technology Data Exchange (ETDEWEB)
Carvalho Junior, Alberico B. de; Silva, Ademir X. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]. E-mail: ajunior@con.ufrj.br; Hunt, John G. [Instituto de Radioprotecao e Dosimetria (IRD/CNEN), Rio de Janeiro, RJ (Brazil)]. E-mail: john@ird.gov.br
2007-07-01
In this work, using the Visual Monte Carlo code and the voxel phantom FAX, elaborated similar scenes of irradiation to the treatments used in the nuclear medicine, with the intention of estimate the effective dose in individuals from exposure the patients treated with {sup 131}I. We considered often specific situations, such as doses to others while sleeping, using public or private transportation, or being in a cinema for a few hours. In the possible situations that has been considered, the value of the effective dose did not overcome 0.05 mSv, demonstrating that, for the considered parameters the patient could be release without receiving instructions from radioprotection. (author)
Uncertainty Propagation with Fast Monte Carlo Techniques
Rochman, D.; van der Marck, S. C.; Koning, A. J.; Sjöstrand, H.; Zwermann, W.
2014-04-01
Two new and faster Monte Carlo methods for the propagation of nuclear data uncertainties in Monte Carlo nuclear simulations are presented (the "Fast TMC" and "Fast GRS" methods). They are addressing the main drawback of the original Total Monte Carlo method (TMC), namely the necessary large time multiplication factor compared to a single calculation. With these new methods, Monte Carlo simulations can now be accompanied with uncertainty propagation (other than statistical), with small additional calculation time. The new methods are presented and compared with the TMC methods for criticality benchmarks.
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Granville, DA [Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa (Canada); Sawakuchi, GO [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX (United States)
2014-08-15
In this work, we demonstrate inconsistencies in commonly used Monte Carlo methods of scoring linear energy transfer (LET) in proton therapy beams. In particle therapy beams, the LET is an important parameter because the relative biological effectiveness (RBE) depends on it. LET is often determined using Monte Carlo techniques. We used a realistic Monte Carlo model of a proton therapy nozzle to score proton LET in spread-out Bragg peak (SOBP) depth-dose distributions. We used three different scoring and calculation techniques to determine average LET at varying depths within a 140 MeV beam with a 4 cm SOBP and a 250 MeV beam with a 10 cm SOBP. These techniques included fluence-weighted (Φ-LET) and dose-weighted average (D-LET) LET calculations from: 1) scored energy spectra converted to LET spectra through a lookup table, 2) directly scored LET spectra and 3) accumulated LET scored ‘on-the-fly’ during simulations. All protons (primary and secondary) were included in the scoring. Φ-LET was found to be less sensitive to changes in scoring technique than D-LET. In addition, the spectral scoring methods were sensitive to low-energy (high-LET) cutoff values in the averaging. Using cutoff parameters chosen carefully for consistency between techniques, we found variations in Φ-LET values of up to 1.6% and variations in D-LET values of up to 11.2% for the same irradiation conditions, depending on the method used to score LET. Variations were largest near the end of the SOBP, where the LET and energy spectra are broader.
Kozlenko, D P; Knorr, K; McGreevy, R L; Savenko, B N; Zetterström, P
2000-01-01
Structure and orientational disorder of ammonium ions in the high temperature phase I of ND_{4}I were studied by reverse Monte Carlo and maximum entropy methods using powder neutron diffraction data. The ammonium ions were found to perform a librational motion with an average angular libration amplitude of gamma =20^o and reorientational motion by 39^o jumps of the N-D bonds between (xxx) and (xxz) positions in the structure. Reorientations by 90^o jumps were found to have a low probability.
Directory of Open Access Journals (Sweden)
M. S. Grishko
2014-11-01
Full Text Available The solution of the study of self-assembly and self-organization of compact nanoparticles from the swarm of atomical nanoparticles by the example of Fe-Co is set out in the report. To perform the numerical experiment was used Monte Carlo method. The analysis of synthesis atomic clusters of magnetic nanoparticles of iron subgroup in quantum-entangled (η = 1 and quantum -nonentangled (η = 0 states is given. It is shown that the result nanosynthesis depends not only on the outside thermodynamic parameters, but also on the self-assembly and self-organization of nanosystem due to activation of the inner quantum electron degrees of freedom.
Energy Technology Data Exchange (ETDEWEB)
Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
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Jiang, H; Lee, Y; Pokhrel, D; Badkul, R [University of Kansas Hospital, Kansas City, KS (United States)
2015-06-15
Purpose: As an alternative to cylindrical applicators, air inflated balloon applicators have been introduced into HDR vaginal cuff brachytherapy treatment to achieve sufficient dose to vagina mucosa as well as to spare rectum and bladder. In general, TG43 formulae based treatment planning systems do not take into account tissue inhomogeneity, and air in the balloon applicator can cause higher delivered dose to mucosa than treatment plan reported. We investigated dosimetric effect of air in balloon applicator using the Monte Carlo method. Methods: The thirteen-catheter Capri applicator with a Nucletron Ir-192 seed was modeled for various balloon diameters (2cm to 3.5cm) using the MCNP Monte Carlo code. Ir-192 seed was placed in both central and peripheral catheters to replicate real patient situations. Existence of charged particle equilibrium (CPE) with air balloon was evaluated by comparing kerma and dose at various distances (1mm to 70mm) from surface of air-filled applicator. Also mucosa dose by an air-filled applicator was compared with by a water-filled applicator to evaluate dosimetry accuracy of planning system without tissue inhomogeneity correction. Results: Beyond 1mm from air/tissue interface, the difference between kerma and dose was within 2%. CPE (or transient CPE) condition was deemed existent, and in this region no electron transport was necessary in Monte Carlo simulations. At 1mm or less, the deviation of dose from kerma became more apparent. Increase of dose to mucosa depended on diameter of air balloon. The increment of dose to mucosa was 2.5% and 4.3% on average for 2cm and 3.5cm applicators, respectively. Conclusion: After introduction of air balloon applicator, CPE fails only at the proximity of air/tissue interface. Although dose to mucosa is increased, there is no significant dosimetric difference (<5%) between air and water filled applicators. Tissue inhomogeneity correction is not necessary for air-filled applicators.
Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M
2016-12-01
A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R20.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.
Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.
2017-01-01
A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R2 > 0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo. PMID:27958483
Energy Technology Data Exchange (ETDEWEB)
Domin, D.; Braida, Benoit; Lester Jr., William A.
2008-05-30
This study explores the use of breathing orbital valence bond (BOVB) trial wave functions for diffusion Monte Carlo (DMC). The approach is applied to the computation of the carbon-hydrogen (C-H) bond dissociation energy (BDE) of acetylene. DMC with BOVB trial wave functions yields a C-H BDE of 132.4 {+-} 0.9 kcal/mol, which is in excellent accord with the recommended experimental value of 132.8 {+-} 0.7 kcal/mol. These values are to be compared with DMC results obtained with single determinant trial wave functions, using Hartree-Fock orbitals (137.5 {+-} 0.5 kcal/mol) and local spin density (LDA) Kohn-Sham orbitals (135.6 {+-} 0.5 kcal/mol).
Bosa, Ivana; Rothstein, Stuart M.
2004-03-01
Our objective is to develop a Diffusion Monte Carlo (DMC) algorithm to estimate the exact expectation values of non-differential operators, such as polarizabilities and high-order hyperpolarizabilities, for isolated atoms and molecules: . The existing Ground State Distribution DMC (GSD DMC) algorithm which attempts this has a serious bias. On the other hand, the Pure DMC algorithm with minimal stochastic reconfiguration has a reduced bias, but the expectation values are contaminated by Ψ, an inputted, approximate wave function. We modified the latter algorithm to obtain the exact expectation values, while at the same time, eliminating the bias. To compare the efficiency of GSD DMC and the modified Pure DMC algorithms we calculated simple properties of the H atom, such as various functions of coordinates and polarizabilities. Using two non-exact wavefunctions, one of moderate quality and the other very crude, in each case the results are within statistical error of the exact values.
Waller, Niels G
2016-01-01
For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.
Hoel, Hakon
2016-06-13
A formal mean square error expansion (MSE) is derived for Euler-Maruyama numerical solutions of stochastic differential equations (SDE). The error expansion is used to construct a pathwise, a posteriori, adaptive time-stepping Euler-Maruyama algorithm for numerical solutions of SDE, and the resulting algorithm is incorporated into a multilevel Monte Carlo (MLMC) algorithm for weak approximations of SDE. This gives an efficient MSE adaptive MLMC algorithm for handling a number of low-regularity approximation problems. In low-regularity numerical example problems, the developed adaptive MLMC algorithm is shown to outperform the uniform time-stepping MLMC algorithm by orders of magnitude, producing output whose error with high probability is bounded by TOL > 0 at the near-optimal MLMC cost rate б(TOL log(TOL)) that is achieved when the cost of sample generation is б(1).
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Kim, Dongjin; Kim, Seok Goo; Choi, Jooho; Lee, Jaewook [Korea Aerospace Univ., Koyang (Korea, Republic of); Song, Hwa Seob; Park, Sang Hui [Hyosung Corporation, Seoul (Korea, Republic of)
2016-10-15
Remaining useful life (RUL) estimation of the Li-ion battery has gained great interest because it is necessary for quality assurance, operation planning, and determination of the exchange period. This paper presents the RUL estimation of an Li-ion battery for an energy storage system using exponential function for the degradation model and Markov Chain Monte Carlo (MCMC) approach for parameter estimation. The MCMC approach is dependent upon information such as model initial parameters and input setting parameters which highly affect the estimation result. To overcome this difficulty, this paper offers a guideline for model initial parameters based on the regression result, and MCMC input parameters derived by comparisons with a thorough search of theoretical results.
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Türkmen, Mehmet, E-mail: tm@hacettepe.edu.tr [Nuclear Engineering Department, Hacettepe University, Beytepe Campus, Ankara (Turkey); Çolak, Üner [Energy Institute, Istanbul Technical University, Ayazağa Campus, Maslak, Istanbul (Turkey); Ergün, Şule [Nuclear Engineering Department, Hacettepe University, Beytepe Campus, Ankara (Turkey)
2015-12-15
Highlights: • Optimum core maps were generated for the ITU TRIGA Mark II Research Reactor. • Calculations were performed using a Monte Carlo based reactor physics code, MCNP. • Single-Objective and Multi-Objective Genetic Algorithms were used for the optimization. • k{sub eff} and ppf{sub max} were considered as the optimization objectives. • The generated core maps were compared with the fresh core map. - Abstract: The main purpose of this study is to present the results of Core Map (CM) generation calculations for the İstanbul Technical University TRIGA Mark II Research Reactor by using Genetic Algorithms (GA) coupled with a Monte Carlo (MC) based-particle transport code. Optimization problems under consideration are: (i) maximization of the core excess reactivity (ρ{sub ex}) using Single-Objective GA when the burned fuel elements with no fresh fuel elements are used, (ii) maximization of the ρ{sub ex} and minimization of maximum power peaking factor (ppf{sub max}) using Multi-Objective GA when the burned fuels with fresh fuels are used. The results were obtained when all the control rods are fully withdrawn. ρ{sub ex} and ppf{sub max} values of the produced best CMs were provided. Core-averaged neutron spectrum, and variation of neutron fluxes with respect to radial distance were presented for the best CMs. The results show that it is possible to find an optimum CM with an excess reactivity of 1.17 when the burned fuels are used. In the case of a mix of burned fuels and fresh fuels, the best pattern has an excess reactivity of 1.19 with a maximum peaking factor of 1.4843. In addition, when compared with the fresh CM, the thermal fluxes of the generated CMs decrease by about 2% while change in the fast fluxes is about 1%.Classification: J. Core physics.
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
Haryanto, Freddy
2010-06-01
In medical linear accelerator, the energy parameter of electron plays important role to produce electron beam. The percentage depth dose of electron beams takes account not only on the value of electron's energy, but also on the type of electron's energy. The aims of this work are to carry on the effect of energy parameter of electron on the percentage depth dose of electron beam. Monte Carlo method is chosen in this project, due to the superior of this method for simulating the random process such as the transport particle in matter. The DOSXYZnrc usercode was used to simulate the electron transport in water phantom. Two aspects of electron's energy parameter were investigated using Monte Carlo simulations. In the first aspect, electron energy's value was varied also its spectrum. In the second aspect, the geometry of electron's energy was taken account on. The parallel beam and the point source were chosen as the geometry of The measurements of percentage depth dose were conducted to compare with its simulation. The ionization chamber was used in these measurements. Presentation of the results of this work is given not only based on the shape of the percentage depth dose from the simulation and measurement, but also on the other aspect in its curve. The result of comparison between the simulation and its measurement shows that the shape of its curve depends on the energy value of electron and the type of its energy. The energy value of electron affected the depth maximum of dose.
Energy Technology Data Exchange (ETDEWEB)
Vergnaud, Th.; Nimal, J.C.; Chiron, M
2001-07-01
The TRIPOLI-3 code applies the Monte Carlo method to neutron, gamma-ray and coupled neutron and gamma-ray transport calculations in three-dimensional geometries, either in steady-state conditions or having a time dependence. It can be used to study problems where there is a high flux attenuation between the source zone and the result zone (studies of shielding configurations or source driven sub-critical systems, with fission being taken into account), as well as problems where there is a low flux attenuation (neutronic calculations -- in a fuel lattice cell, for example -- where fission is taken into account, usually with the calculation on the effective multiplication factor, fine structure studies, numerical experiments to investigate methods approximations, etc). TRIPOLI-3 has been operational since 1995 and is the version of the TRIPOLI code that follows on from TRIPOLI-2; it can be used on SUN, RISC600 and HP workstations and on PC using the Linux or Windows/NT operating systems. The code uses nuclear data libraries generated using the THEMIS/NJOY system. The current libraries were derived from ENDF/B6 and JEF2. There is also a response function library based on a number of evaluations, notably the dosimetry libraries IRDF/85, IRDF/90 and also evaluations from JEF2. The treatment of particle transport is the same in version 3.5 as in version 3.4 of the TRIPOLI code; but the version 3.5 is more convenient for preparing the input data and for reading the output. The french version of the user's manual exists. (authors)
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.
Teng, Jingjing; Duan, Huawei; Zheng, Yuxin
2015-12-01
To estimate the reference value for micronucleus frequency of peripheral blood lymphocytes in general Chinese population, and to guide the genotoxicity evaluation and risk analysis for populations exposed to environmental or occupational chemicals. A fulltext search was performed in CNKI with the key words of "micronucleus" and "human", and PubMed was searched with "cytokinesis-block micronucleus","CBMN","humans", and "adults", to obtain the articles published at home and abroad from 2001 to 2014 in which cytokinesis-block micronucleus (CBMN)assay was applied for micronucleus detection and populations not exposed to genotoxins were established as a control. Monte Carlo simulation was performed based on the micronucleus frequency, standard deviation, and sample size provided in these articles to calculate the micronucleus frequency for general population and to analyze the influence of sex, smoking, and drinking on micronucleus frequency. A total of 23 articles were included in the final analysis. The minimum mean micronucleus frequency was 0.39‰, and the maximum mean micronucleus frequency was 25.3‰. There were 1623 subjects in the control group in total (range 22~178, mean 70.6). Monte Carlo simulation was performed 100 times, and the mode of micronucleus frequency was 0 or 1‰; the values of P0, P25, P50 , P75, and P95 were 0‰, 1‰, 2‰~3‰, 5‰~6‰, and 14‰~19‰, respectively; the mean value was 4.36‰(range 4.22‰~4.57‰). With the application of one-sided 95% range(x±1.64 s), the upper limit of the range of reference value was calculated to be 13.46‰~14.75‰. The micronucleus frequency of peripheral blood lymphocytes in general Chinese population is 4.36‰, the interquartile range is 1‰~5‰ or 1‰~6‰, and the upper limit of reference value is 14.17‰. The factors of living area, sex, smoking, and drinking may influence micronucleus frequency.
Energy Technology Data Exchange (ETDEWEB)
Chen, X; Xing, L; Luxton, G; Bush, K [Stanford University, Palo Alto, CA (United States); Azcona, J [Clinica Universidad de Navarra, Pamplona (Spain)
2014-06-01
Purpose: Patient-specific QA for VMAT is incapable of providing full 3D dosimetric information and is labor intensive in the case of severe heterogeneities or small-aperture beams. A cloud-based Monte Carlo dose reconstruction method described here can perform the evaluation in entire 3D space and rapidly reveal the source of discrepancies between measured and planned dose. Methods: This QA technique consists of two integral parts: measurement using a phantom containing array of dosimeters, and a cloud-based voxel Monte Carlo algorithm (cVMC). After a VMAT plan was approved by a physician, a dose verification plan was created and delivered to the phantom using our Varian Trilogy or TrueBeam system. Actual delivery parameters (i.e., dose fraction, gantry angle, and MLC at control points) were extracted from Dynalog or trajectory files. Based on the delivery parameters, the 3D dose distribution in the phantom containing detector were recomputed using Eclipse dose calculation algorithms (AAA and AXB) and cVMC. Comparison and Gamma analysis is then conducted to evaluate the agreement between measured, recomputed, and planned dose distributions. To test the robustness of this method, we examined several representative VMAT treatments. Results: (1) The accuracy of cVMC dose calculation was validated via comparative studies. For cases that succeeded the patient specific QAs using commercial dosimetry systems such as Delta- 4, MAPCheck, and PTW Seven29 array, agreement between cVMC-recomputed, Eclipse-planned and measured doses was obtained with >90% of the points satisfying the 3%-and-3mm gamma index criteria. (2) The cVMC method incorporating Dynalog files was effective to reveal the root causes of the dosimetric discrepancies between Eclipse-planned and measured doses and provide a basis for solutions. Conclusion: The proposed method offers a highly robust and streamlined patient specific QA tool and provides a feasible solution for the rapidly increasing use of VMAT
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Zhang, Hai-Feng, E-mail: hanlor@163.com [College of Optoelectronic Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210023 ,China (China); Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016 (China); Liu, Shao-Bin [Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016 (China)
2016-08-15
In this paper, the properties of photonic band gaps (PBGs) in two types of two-dimensional plasma-dielectric photonic crystals (2D PPCs) under a transverse-magnetic (TM) wave are theoretically investigated by a modified plane wave expansion (PWE) method where Monte Carlo method is introduced. The proposed PWE method can be used to calculate the band structures of 2D PPCs which possess arbitrary-shaped filler and any lattice. The efficiency and convergence of the present method are discussed by a numerical example. The configuration of 2D PPCs is the square lattices with fractal Sierpinski gasket structure whose constituents are homogeneous and isotropic. The type-1 PPCs is filled with the dielectric cylinders in the plasma background, while its complementary structure is called type-2 PPCs, in which plasma cylinders behave as the fillers in the dielectric background. The calculated results reveal that the enough accuracy and good convergence can be obtained, if the number of random sampling points of Monte Carlo method is large enough. The band structures of two types of PPCs with different fractal orders of Sierpinski gasket structure also are theoretically computed for a comparison. It is demonstrate that the PBGs in higher frequency region are more easily produced in the type-1 PPCs rather than in the type-2 PPCs. Sierpinski gasket structure introduced in the 2D PPCs leads to a larger cutoff frequency, enhances and induces more PBGs in high frequency region. The effects of configurational parameters of two types of PPCs on the PBGs are also investigated in detail. The results show that the PBGs of the PPCs can be easily manipulated by tuning those parameters. The present type-1 PPCs are more suitable to design the tunable compacted devices.
LMC: Logarithmantic Monte Carlo
Mantz, Adam B.
2017-06-01
LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).
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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.)
Mondal, A.
2010-03-01
In this paper, we study the uncertainty quantification in inverse problems for flows in heterogeneous porous media. Reversible jump Markov chain Monte Carlo algorithms (MCMC) are used for hierarchical modeling of channelized permeability fields. Within each channel, the permeability is assumed to have a lognormal distribution. Uncertainty quantification in history matching is carried out hierarchically by constructing geologic facies boundaries as well as permeability fields within each facies using dynamic data such as production data. The search with Metropolis-Hastings algorithm results in very low acceptance rate, and consequently, the computations are CPU demanding. To speed-up the computations, we use a two-stage MCMC that utilizes upscaled models to screen the proposals. In our numerical results, we assume that the channels intersect the wells and the intersection locations are known. Our results show that the proposed algorithms are capable of capturing the channel boundaries and describe the permeability variations within the channels using dynamic production history at the wells. © 2009 Elsevier Ltd. All rights reserved.
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Medeiros, Marcos P.C.; Rebello, Wilson F.; Andrade, Edson R., E-mail: rebello@ime.eb.br, E-mail: daltongirao@yahoo.com.br [Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ (Brazil). Secao de Engenharia Nuclear; Silva, Ademir X., E-mail: ademir@nuclear.ufrj.br [Corrdenacao dos Programas de Pos-Graduacao em Egenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear
2015-07-01
Nuclear explosions are usually described in terms of its total yield and associated shock wave, thermal radiation and nuclear radiation effects. The nuclear radiation produced in such events has several components, consisting mainly of alpha and beta particles, neutrinos, X-rays, neutrons and gamma rays. For practical purposes, the radiation from a nuclear explosion is divided into {sup i}nitial nuclear radiation{sup ,} referring to what is issued within one minute after the detonation, and 'residual nuclear radiation' covering everything else. The initial nuclear radiation can also be split between 'instantaneous or 'prompt' radiation, which involves neutrons and gamma rays from fission and from interactions between neutrons and nuclei of surrounding materials, and 'delayed' radiation, comprising emissions from the decay of fission products and from interactions of neutrons with nuclei of the air. This work aims at presenting isodose curves calculations at ground level by Monte Carlo simulation, allowing risk assessment and consequences modeling in radiation protection context. The isodose curves are related to neutrons produced by the prompt nuclear radiation from a hypothetical nuclear explosion with a total yield of 20 KT. Neutron fluency and emission spectrum were based on data available in the literature. Doses were calculated in the form of ambient dose equivalent due to neutrons H*(10){sub n}{sup -}. (author)
Ng, C M
2013-10-01
The development of a population PK/PD model, an essential component for model-based drug development, is both time- and labor-intensive. A graphical-processing unit (GPU) computing technology has been proposed and used to accelerate many scientific computations. The objective of this study was to develop a hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization (MCPEM) estimation algorithm for population PK data analysis. A hybrid GPU-CPU implementation of the MCPEM algorithm (MCPEMGPU) and identical algorithm that is designed for the single CPU (MCPEMCPU) were developed using MATLAB in a single computer equipped with dual Xeon 6-Core E5690 CPU and a NVIDIA Tesla C2070 GPU parallel computing card that contained 448 stream processors. Two different PK models with rich/sparse sampling design schemes were used to simulate population data in assessing the performance of MCPEMCPU and MCPEMGPU. Results were analyzed by comparing the parameter estimation and model computation times. Speedup factor was used to assess the relative benefit of parallelized MCPEMGPU over MCPEMCPU in shortening model computation time. The MCPEMGPU consistently achieved shorter computation time than the MCPEMCPU and can offer more than 48-fold speedup using a single GPU card. The novel hybrid GPU-CPU implementation of parallelized MCPEM algorithm developed in this study holds a great promise in serving as the core for the next-generation of modeling software for population PK/PD analysis.
Koger, B.; Kirkby, C.
2016-03-01
Gold nanoparticles (GNPs) have shown potential in recent years as a means of therapeutic dose enhancement in radiation therapy. However, a major challenge in moving towards clinical implementation is the exact characterisation of the dose enhancement they provide. Monte Carlo studies attempt to explore this property, but they often face computational limitations when examining macroscopic scenarios. In this study, a method of converting dose from macroscopic simulations, where the medium is defined as a mixture containing both gold and tissue components, to a mean dose-to-tissue on a microscopic scale was established. Monte Carlo simulations were run for both explicitly-modeled GNPs in tissue and a homogeneous mixture of tissue and gold. A dose ratio was obtained for the conversion of dose scored in a mixture medium to dose-to-tissue in each case. Dose ratios varied from 0.69 to 1.04 for photon sources and 0.97 to 1.03 for electron sources. The dose ratio is highly dependent on the source energy as well as GNP diameter and concentration, though this effect is less pronounced for electron sources. By appropriately weighting the monoenergetic dose ratios obtained, the dose ratio for any arbitrary spectrum can be determined. This allows complex scenarios to be modeled accurately without explicitly simulating each individual GNP.
Austin, Peter C
2009-02-01
Propensity-score matching is increasingly being used to reduce the impact of treatment-selection bias when estimating causal treatment effects using observational data. Several propensity-score matching methods are currently employed in the medical literature: matching on the logit of the propensity score using calipers of width either 0.2 or 0.6 of the standard deviation of the logit of the propensity score; matching on the propensity score using calipers of 0.005, 0.01, 0.02, 0.03, and 0.1; and 5 --> 1 digit matching on the propensity score. We conducted empirical investigations and Monte Carlo simulations to investigate the relative performance of these competing methods. Using a large sample of patients hospitalized with a heart attack and with exposure being receipt of a statin prescription at hospital discharge, we found that the 8 different methods produced propensity-score matched samples in which qualitatively equivalent balance in measured baseline variables was achieved between treated and untreated subjects. Seven of the 8 propensity-score matched samples resulted in qualitatively similar estimates of the reduction in mortality due to statin exposure. 5 --> 1 digit matching resulted in a qualitatively different estimate of relative risk reduction compared to the other 7 methods. Using Monte Carlo simulations, we found that matching using calipers of width of 0.2 of the standard deviation of the logit of the propensity score and the use of calipers of width 0.02 and 0.03 tended to have superior performance for estimating treatment effects. 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Monte Carlo techniques in radiation therapy
Verhaegen, Frank
2013-01-01
Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...
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Bezerra, Luis R.A.; Vieira, Jose W.; Amaral, Romilton dos S.; Santos Junior, Jose A. dos; Silva, Arykerne N.C. da; Silva, Alberto A. da; Damascena, Kennedy F.; Santos Junior, Otavio P.; Medeiros, Nilson V.S.; Santos, Josineide M.N. dos, E-mail: jaraujo@ufpe.br, E-mail: romilton@ufpe.br, E-mail: kennedy.eng.ambiental@gmail.com, E-mail: nvsmedeiros@gmail.com, E-mail: josineide.santos@ufpe.br, E-mail: arykerne.silva@ufpe.br, E-mail: luis.rodrigo@vitoria.ifpe.edu.br, E-mail: otavio.santos@vitoria.ifpe.edu.br, E-mail: s, E-mail: jose.wilson@recife.ifpe.edu.br, E-mail: alberto.silva@barreiros.ifpe.edu.br, E-mail: jose.wilson59@uol.com.br [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Departamento de Energia Nuclear; Instituto Federal de Educacao, Ciencia e Tecnologia de Pernambuco (IFPE), PE (Brazil); Universidade de Pernambuco (UPE), Recife, PE (Brazil)
2017-11-01
One of the means of exposure that the world population is subjected to daily is natural radiation, which covers exposure to sources of cosmic origin and terrestrial origin, which accounts for about 84.1% of all exposure due to natural radiation. Some research groups have been estimating the distribution of the dose by the radiosensitive organs and tissues of people submitted to gamma radiation using Computational Exposure Models (MCE). The MCE is composed, fundamentally, of an anthropomorphic simulator (phantom), a Monte Carlo code and a radioactive source algorithm. The Group of Computational Dosimetry and Embedded Systems (DCSE), together with the group of Radioecology (RAE), have been developing a variety of MCEs to simulate exposure to natural environmental gamma radiation. Such models estimate the dose distribution absorbed by the organs and tissues radiosensitive to ionizing radiation from a flat portion of the ground in which photons emerge from within a circle of radius r, reaching a person in an orthostatic position and centered on the circumference. We investigated in this work the exposure of an individual by a radioactive cloud of gamma emission of Potassium-40, which emits a photon characteristic of energy 1461 keV. It was optimized the number of histories to obtain Dose/Kerma values in the air, with low dispersion and viable computational time for the available PCs, statistically validating the results. To do so, was adapted the MCE MSTA, composed by the MASH (Male Adult meSH) phantom in an orthostatic position coupled to the EGSnrc, with the planar source algorithm. (author)
SU-E-T-493: Accelerated Monte Carlo Methods for Photon Dosimetry Using a Dual-GPU System and CUDA.
Liu, T; Ding, A; Xu, X
2012-06-01
To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that accelerates dose calculations on a dual-GPU system. We simulated a clinical case of prostate cancer treatment. A voxelized abdomen phantom derived from 120 CT slices was used containing 218×126×60 voxels, and a GE LightSpeed 16-MDCT scanner was modeled. A CPU version of the MC code was first developed in C++ and tested on Intel Xeon X5660 2.8GHz CPU, then it was translated into GPU version using CUDA C 4.1 and run on a dual Tesla m 2 090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy- and material- dependent cross-sections. Double-precision floating point format was used for accuracy. Doses to the rectum, prostate, bladder and femoral heads were calculated. When running on a single GPU, the MC GPU code was found to be ×19 times faster than the CPU code and ×42 times faster than MCNPX. These speedup factors were doubled on the dual-GPU system. The dose Result was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. A GPU-based MC code was developed for dose calculations using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual-GPU system. © 2012 American Association of Physicists in Medicine.
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Authier, N
1998-12-01
One of the questions asked in radiation shielding problems is the estimation of the radiation level in particular to determine accessibility of working persons in controlled area (nuclear power plants, nuclear fuel reprocessing plants) or to study the dose gradients encountered in material (iron nuclear vessel, medical therapy, electronics in satellite). The flux and reaction rate estimators used in Monte Carlo codes give average values in volumes or on surfaces of the geometrical description of the system. But in certain configurations, the knowledge of punctual deposited energy and dose estimates are necessary. The Monte Carlo estimate of the flux at a point of interest is a calculus which presents an unbounded variance. The central limit theorem cannot be applied thus no easy confidencelevel may be calculated. The convergence rate is then very poor. We propose in this study a new solution for the photon flux at a point estimator. The method is based on the 'once more collided flux estimator' developed earlier for neutron calculations. It solves the problem of the unbounded variance and do not add any bias to the estimation. We show however that our new sampling schemes specially developed to treat the anisotropy of the photon coherent scattering is necessary for a good and regular behavior of the estimator. This developments integrated in the TRIPOLI-4 Monte Carlo code add the possibility of an unbiased punctual estimate on media interfaces. (author)
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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)
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Application of Monte Carlo Simulation of Total Skin Electron Therapy for Treatment Optimization.
Shokrani, Parvaneh
A technique for treatment of total skin irradiation was simulated using the Monte Carlo method. By application of this simulation, optimization of the Total Skin Electron Therapy (TSET) technique was accomplished. The purpose of the optimization process was to select the properties of the optimal TSET secondary scatterer. The optimization process was divided into four steps. First, the geometry of the treatment head of a Phillips SL-20 linear accelerator and the geometry of the TSET technique were simulated. Using a combination of the EGS4 Monte Carlo code system, geometry routines, and a package of variance reduction techniques, spectrum of the electron beam, at the exit window of the treatment head and at the treatment plane (located at 300 cm), was calculated. Second, to confirm the accuracy of calculations, the calculated depth dose curves, field uniformity and bremsstrahlung contamination for a control scatterer were compared to the measurement values. Third, a group of materials were selected to perform as a candidate for the optimal TSET scatterer. The treatment field characteristics produced by these materials were calculated and the optimal scatterer was selected. Forth, selection of the optimal scatterer was confirmed by way of physical measurements. Physical measurements showed that the EGS4 Monte Carlo code system, together with the TSET user code, developed in this research, simulated the TSET technique accurately. However there were some problem areas. The central axis surface dose was underestimated by simulations and there was inconsistency associated with radial distribution of bremsstrahlung contamination. Monte Carlo simulation of the TSET technique predicted a 0.059 mm thickness of lead as the optimal scatterer. This scatterer was predicted to produce a minimum uniformity of 73%, a d_{80%} of between 1.8-2.1 cm and a 30% increase in dose rate (as compared to the control scatterer). Moreover, the Monte Carlo simulations TSET technique and
Liu, Jing-Jing; Peng, Qiu-He; Liu, Dong-Mei
2017-09-01
The death of massive stars due to supernova explosions is a key ingredient in stellar evolution and stellar population synthesis. Electron capture (EC) plays a vital role in supernova explosions. Using the Shell-Model Monte Carlo method, based on the nuclear random phase approximation and linear response theory model for electrons, we study the strong screening EC rates of 52, 53, 59, 60Fe in pre-supernovae. The results show that the screening rates can decrease by about 18.66%. Our results may become a good foundation for future investigation of the evolution of late-type stars, supernova explosion mechanisms and numerical simulations. Supported by National Natural Science Foundation of China (11565020), Counterpart Foundation of Sanya (2016PT43), Special Foundation of Science and Technology Cooperation for Advanced Academy and Regional of Sanya (2016YD28), Scientific Research Staring Foundation for 515 Talented Project of Hainan Tropical Ocean University (RHDRC201701) and Natural Science Foundation of Hainan Province (114012)
Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek
2017-07-01
Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron-electron (e-e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e-e interactions. This required adapting the treatment of e-e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.
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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.
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Borowik, Piotr, E-mail: pborow@poczta.onet.pl [Warsaw University of Technology, Faculty of Physics, ul. Koszykowa 75, 00-662 Warszawa (Poland); Thobel, Jean-Luc, E-mail: jean-luc.thobel@iemn.univ-lille1.fr [Institut d' Electronique, de Microélectronique et de Nanotechnologies, UMR CNRS 8520, Université Lille 1, Avenue Poincaré, CS 60069, 59652 Villeneuve d' Ascq Cédex (France); Adamowicz, Leszek, E-mail: adamo@if.pw.edu.pl [Warsaw University of Technology, Faculty of Physics, ul. Koszykowa 75, 00-662 Warszawa (Poland)
2017-07-15
Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron–electron (e–e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e–e interactions. This required adapting the treatment of e–e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.
Khajepour, Abolhasan; Rahmani, Faezeh
2017-01-01
In this study, a 90Sr radioisotope thermoelectric generator (RTG) with power of milliWatt was designed to operate in the determined temperature (300-312K). For this purpose, the combination of analytical and Monte Carlo methods with ANSYS and COMSOL software as well as the MCNP code was used. This designed RTG contains 90Sr as a radioisotope heat source (RHS) and 127 coupled thermoelectric modules (TEMs) based on bismuth telluride. Kapton (2.45mm in thickness) and Cryotherm sheets (0.78mm in thickness) were selected as the thermal insulators of the RHS, as well as a stainless steel container was used as a generator chamber. The initial design of the RHS geometry was performed according to the amount of radioactive material (strontium titanate) as well as the heat transfer calculations and mechanical strength considerations. According to the Monte Carlo simulation performed by the MCNP code, approximately 0.35 kCi of 90Sr is sufficient to generate heat power in the RHS. To determine the optimal design of the RTG, the distribution of temperature as well as the dissipated heat and input power to the module were calculated in different parts of the generator using the ANSYS software. Output voltage according to temperature distribution on TEM was calculated using COMSOL. Optimization of the dimension of the RHS and heat insulator was performed to adapt the average temperature of the hot plate of TEM to the determined hot temperature value. This designed RTG generates 8mW in power with an efficiency of 1%. This proposed approach of combination method can be used for the precise design of various types of RTGs. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
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Le Cocq, A
1998-11-23
The aim of this work is the performances improvement of the Monte-Carlo codes for the criticality studies. MORET IV is especially concerned. With multigroup approximations, the anisotropy equations are very irregular and show quick variations. In a Monte-Carlo codes, they are estimated only by the first coefficients of Legendre polynomials development. Many methods have been characterised using variable number of these coefficients, allowing their reconstruction. So reference representations were defined. Thus they showed that the approximation by only one Dirac could lead to a reactivity under-evaluations. Referring to these representations, new methods have been introduced in MORET IV and instructions have been proposed. Two methods (the correlated samples method and the derivatives sampling method) have been studied to define the divergence between two closely configurations result. A few variance formula of the collision density variation for an infinite medium to an energy group, have been established. These formula have been perfected by simulation for a finite medium. (A.L.B.)
Path integral Monte Carlo simulations of silicates
Rickwardt, Chr.; Nielaba, P.; Müser, M. H.; Binder, K.
2000-01-01
We investigate the thermal expansion of crystalline SiO$_2$ in the $\\beta$-- cristobalite and the $\\beta$-quartz structure with path integral Monte Carlo (PIMC) techniques. This simulation method allows to treat low-temperature quantum effects properly. At temperatures below the Debye temperature, thermal properties obtained with PIMC agree better with experimental results than those obtained with classical Monte Carlo methods.
Mielke, Steven L; Dinpajooh, Mohammadhasan; Siepmann, J Ilja; Truhlar, Donald G
2013-01-07
We present a procedure to calculate ensemble averages, thermodynamic derivatives, and coordinate distributions by effective classical potential methods. In particular, we consider the displaced-points path integral (DPPI) method, which yields exact quantal partition functions and ensemble averages for a harmonic potential and approximate quantal ones for general potentials, and we discuss the implementation of the new procedure in two Monte Carlo simulation codes, one that uses uncorrelated samples to calculate absolute free energies, and another that employs Metropolis sampling to calculate relative free energies. The results of the new DPPI method are compared to those from accurate path integral calculations as well as to results of two other effective classical potential schemes for the case of an isolated water molecule. In addition to the partition function, we consider the heat capacity and expectation values of the energy, the potential energy, the bond angle, and the OH distance. We also consider coordinate distributions. The DPPI scheme performs best among the three effective potential schemes considered and achieves very good accuracy for all of the properties considered. A key advantage of the effective potential schemes is that they display much lower statistical sampling variances than those for accurate path integral calculations. The method presented here shows great promise for including quantum effects in calculations on large systems.
Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae
2017-06-07
Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.
Wenner, Michael T.
Obtaining the solution to the linear Boltzmann equation is often is often a daunting task. The time-independent form is an equation of six independent variables which cannot be solved analytically in all but some special problems. Instead, numerical approaches have been devised. This work focuses on improving Monte Carlo methods for its solution in eigenvalue form. First, a statistical method of stationarity detection called the KPSS test adapted as a Monte Carlo eigenvalue source convergence test. The KPSS test analyzes the source center of mass series which was chosen since it should be indicative of overall source behavior, and is physically easy to understand. A source center of mass plot alone serves as a good visual source convergence diagnostic. The KPSS test and three different information theoretic diagnostics were implemented into the well known KENOV.a code inside of the SCALE (version 5) code package from Oak Ridge National Laboratory and compared through analysis of a simple problem and several difficult source convergence benchmarks. Results showed that the KPSS test can add to the overall confidence by identifying more problematic simulations than without its usage. Not only this, the source center of mass information on hand visually aids in the understanding of the problem physics. The second major focus of this dissertation concerned variance reduction methodologies for Monte Carlo eigenvalue problems. The CADIS methodology, based on importance sampling, was adapted to the eigenvalue problems. It was shown that the straight adaption of importance sampling can provide a significant variance reduction in determination of keff (in cases studied up to 30%?). A modified version of this methodology was developed which utilizes independent deterministic importance simulations. In this new methodology, each particle is simulated multiple times, once to every other discretized source region utilizing the importance for that region only. Since each particle
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Sharma, D; Badano, A [Division of Imaging, Diagnostics and Software Reliability, OSEL/CDRH, Food & Drug Administration, MD (United States); Sempau, J [Technical University of Catalonia, Barcelona (Spain)
2016-06-15
Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.
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Nikolopoulos, Dimitrios [Department of Medical Instruments Technology, Technological Educational Institution of Athens, Ag. Spiridonos 12210, Athens (Greece); Kandarakis, Ioannis [Department of Medical Instruments Technology, Technological Educational Institution of Athens, Ag. Spiridonos 12210, Athens (Greece)]. E-mail: kandarakis@teiath.gr; Tsantilas, Xenophon [Department of Medical Physics, University of Athens, Athens (Greece); Valais, Ioannis [Department of Medical Instruments Technology, Technological Educational Institution of Athens, Ag. Spiridonos 12210, Athens (Greece); Cavouras, Dionisios [Department of Medical Instruments Technology, Technological Educational Institution of Athens, Ag. Spiridonos 12210, Athens (Greece); Louizi, Anna [Department of Medical Physics, University of Athens, Athens (Greece)
2006-12-20
The radiation detection efficiency of four scintillators employed, or designed to be employed, in positron emission imaging (PET) was evaluated as a function of the crystal thickness by applying Monte Carlo Methods. The scintillators studied were the LuSiO{sub 5} (LSO), LuAlO{sub 3} (LuAP), Gd{sub 2}SiO{sub 5} (GSO) and the YAlO{sub 3} (YAP). Crystal thicknesses ranged from 0 to 50 mm. The study was performed via a previously generated photon transport Monte Carlo code. All photon track and energy histories were recorded and the energy transferred or absorbed in the scintillator medium was calculated together with the energy redistributed and retransported as secondary characteristic fluorescence radiation. Various parameters were calculated e.g. the fraction of the incident photon energy absorbed, transmitted or redistributed as fluorescence radiation, the scatter to primary ratio, the photon and energy distribution within each scintillator block etc. As being most significant, the fraction of the incident photon energy absorbed was found to increase with increasing crystal thickness tending to form a plateau above the 30 mm thickness. For LSO, LuAP, GSO and YAP scintillators, respectively, this fraction had the value of 44.8, 36.9 and 45.7% at the 10 mm thickness and 96.4, 93.2 and 96.9% at the 50 mm thickness. Within the plateau area approximately (57-59)% (59-63)% (52-63)% and (58-61)% of this fraction was due to scattered and reabsorbed radiation for the LSO, GSO, YAP and LuAP scintillators, respectively. In all cases, a negligible fraction (<0.1%) of the absorbed energy was found to escape the crystal as fluorescence radiation.
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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.
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Nordenfors, C
1999-02-01
To determine dose rate in a gamma radiation field, based on measurements with a semiconductor detector, it is necessary to know how the detector effects the field. This work aims to describe this effect with Monte Carlo simulations and calculations, that is to identify the detector response function. This is done for a germanium gamma detector. The detector is normally used in the in-situ measurements that is carried out regularly at the department. After the response function is determined it is used to reconstruct a spectrum from an in-situ measurement, a so called unfolding. This is done to be able to calculate fluence rate and dose rate directly from a measured (and unfolded) spectrum. The Monte Carlo code used in this work is EGS4 developed mainly at Stanford Linear Accelerator Center. It is a widely used code package to simulate particle transport. The results of this work indicates that the method could be used as-is since the accuracy of this method compares to other methods already in use to measure dose rate. Bearing in mind that this method provides the nuclide specific dose it is useful, in radiation protection, since knowing what the relations between different nuclides are and how they change is very important when estimating the risks
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Nasrollah Jabbari
2009-03-01
Full Text Available Introduction: In clinical electron beams, most of bremsstrahlung radiation is produced by various linac head structures. This bremsstrahlung radiation dose is influenced by the geometry and construction of every component of the linac treatment head structures. Thus, it can be expected that the amount of the contaminated photon dose due to bremsstrahlung radiation varies among different linacs, even for the same electron beam energy. The aims of this study were to simulate the NEPTUN 10PC linac electron beams and to calculate the photon contamination dose due to bremsstrahlung radiation in these beams using a Monte Carlo method. Materials and methods: A NEPTUN 10PC linac was simulated in its electron mode using the BEAMnrc code. This linac can provide three electron beam energies of 6, 8 and 10 MeV. Detailed information required for the simulation, including the geometry and materials of various components of the linac treatment head, was provided by the vender. For all simulations, the cut-off energies for electron and photon transport were set at ECUT=0.521 MeV and PCUT=0.010 MeV, respectively. The KS statistical test was used for validation of the simulated models. Then, relevant bremsstrahlung radiation doses for the three electron beam energies of the linac were calculated for the reference field using the Monte Carlo method. Results: The KS test showed a good agreement between the calculated values (resulting from the simulations and the measured ones. The results showed that the amount of contaminated photon dose due to bremsstrahlung radiation from various components of the simulated linac at the surface of the phantom was between 0.2%-0.5% of the maximum dose for the three electron beam energies. Conclusion: Considering the good agreement between the measured and simulated data, it can be concluded that the simulation method as well as the calculated bremsstrahlung doses have been made at a good level of accuracy and precision
Zhao, Hui-Hai; Ido, Kota; Morita, Satoshi; Imada, Masatoshi
2017-08-01
The conventional tensor-network states employ real-space product states as reference wave functions. Here, we propose a many-variable variational Monte Carlo (mVMC) method combined with tensor networks by taking advantages of both to study fermionic models. The variational wave function is composed of a pair product wave function operated by real-space correlation factors and tensor networks. Moreover, we can apply quantum number projections, such as spin, momentum, and lattice symmetry projections, to recover the symmetry of the wave function to further improve the accuracy. We benchmark our method for one- and two-dimensional Hubbard models, which show significant improvement over the results obtained individually either by mVMC or by tensor network. We have applied the present method to a hole-doped Hubbard model on the square lattice, which indicates the stripe charge/spin order coexisting with a weak d -wave superconducting order in the ground state for the doping concentration of less than 0.3, where the stripe oscillation period gets longer with increasing hole concentration. The charge homogeneous and highly superconducting state also exists as a metastable excited state for the doping concentration less than 0.25.
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A. T. Till; M. Hanuš; J. Lou; J. E. Morel; M. L. Adams
2016-05-01
The standard multigroup (MG) method for energy discretization of the transport equation can be sensitive to approximations in the weighting spectrum chosen for cross-section averaging. As a result, MG often inaccurately treats important phenomena such as self-shielding variations across a material. From a finite-element viewpoint, MG uses a single fixed basis function (the pre-selected spectrum) within each group, with no mechanism to adapt to local solution behavior. In this work, we introduce the Finite-Element-with-Discontiguous-Support (FEDS) method, whose only approximation with respect to energy is that the angular flux is a linear combination of unknowns multiplied by basis functions. A basis function is non-zero only in the discontiguous set of energy intervals associated with its energy element. Discontiguous energy elements are generalizations of bands and are determined by minimizing a norm of the difference between snapshot spectra and their averages over the energy elements. We begin by presenting the theory of the FEDS method. We then compare to continuous-energy Monte Carlo for one-dimensional slab and two-dimensional pin-cell problem. We find FEDS to be accurate and efficient at producing quantities of interest such as reaction rates and eigenvalues. Results show that FEDS converges at a rate that is approximately first-order in the number of energy elements and that FEDS is less sensitive to weighting spectrum than standard MG.
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Jo, Yu Gwon; Oh, Yoo Min; Park, Hyang Kyu; Park, Kang Soon; Cho, Nam Zin [KAIST, Daejeon (Korea, Republic of)
2016-05-15
In this paper, two issues in the FSS iteration method, i.e., the waiting time for surface source data and the variance biases in local tallies are investigated for the domain decomposed, 3-D continuous-energy whole-core calculation. The fission sources are provided as usual, while the surface sources are provided by banking MC particles crossing local domain boundaries. The surface sources serve as boundary conditions for nonoverlapping local problems, so that each local problem can be solved independently. In this paper, two issues in the FSS iteration are investigated. One is quantifying the waiting time of processors to receive surface source data. By using nonblocking communication, 'time penalty' to wait for the arrival of the surface source data is reduced. The other important issue is underestimation of the sample variance of the tally because of additional inter-iteration correlations in surface sources. From the numerical results on a 3-D whole-core test problem, it is observed that the time penalty is negligible in the FSS iteration method and that the real variances of both pin powers and assembly powers are estimated by the HB method. For those purposes, three cases; Case 1 (1 local domain), Case 2 (4 local domains), Case 3 (16 local domains) are tested. For both Cases 2 and 3, the time penalties for waiting are negligible compared to the source-tracking times. However, for finer divisions of local domains, the loss of parallel efficiency caused by the different number of sources for local domains in symmetric locations becomes larger due to the stochastic errors in source distributions. For all test cases, the HB method very well estimates the real variances of local tallies. However, it is also noted that the real variances of local tallies estimated by the HB method show slightly smaller than the real variances obtained from 30 independent batch runs and the deviations become larger for finer divisions of local domains. The batch size used
Monte Carlo simulation of model Spin systemsr
Indian Academy of Sciences (India)
three~dimensional Ising models and Heisenberg models are dealt with in some detail. Recent applications of the Monte Carlo method to spin glass systems and to estimate renormalisation group critical exponents are reviewod. Keywords. _ Monte-carlo simulation; critical phenomena; Ising models; Heisenberg models ...
Monte Carlo Simulation of Phase Transitions
村井, 信行; N., MURAI; 中京大学教養部
1983-01-01
In the Monte Carlo simulation of phase transition, a simple heat bath method is applied to the classical Heisenberg model in two dimensions. It reproduces the correlation length predicted by the Monte Carlo renor-malization group and also computed in the non-linear σ model
Exact Monte Carlo for molecules
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Lester, W.A. Jr.; Reynolds, P.J.
1985-03-01
A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H2, and the singlet-triplet splitting in methylene are presented and discussed. 17 refs.
Padurariu, Leontin; Mitoseriu, Liliana
2017-10-01
In the last few years, the interest in developing ferroelectric systems with high recording density close to 1Tb/in.2 has strongly increased. The ferroelectric thin films are subjected to the electric field applied by using nanocapacitors (diameters of ˜70 nm) containing a ferroelectric active material. In order to increase the memory density, the nanocapacitor dimensions and the distance between them have to be strongly decreased. However, if the lateral distance between the nanoelectrodes is reduced too much, a domain wall propagation from the nanocapacitor subjected to the voltage to the neighboring capacitors (so-called "cross talk") is observed. This phenomenon is undesired because the memory spatial resolution is affected. In the present paper, the role of the geometrical characteristics (electrode radius, lateral distance between the electrodes and the film thickness) is investigated, by using a combined Finite Element Method with the Monte Carlo model to describe the local switching properties. The distributions of the electrical potential and local fields were computed by using the Finite Element Method. After describing the conditions for the appearance of the "cross-talk" phenomenon in ferroelectric nanocapacitor systems, some valuable solutions to avoid it are presented.
Liu, Boda; Liang, Yan
2017-04-01
Markov chain Monte Carlo (MCMC) simulation is a powerful statistical method in solving inverse problems that arise from a wide range of applications. In Earth sciences applications of MCMC simulations are primarily in the field of geophysics. The purpose of this study is to introduce MCMC methods to geochemical inverse problems related to trace element fractionation during mantle melting. MCMC methods have several advantages over least squares methods in deciphering melting processes from trace element abundances in basalts and mantle rocks. Here we use an MCMC method to invert for extent of melting, fraction of melt present during melting, and extent of chemical disequilibrium between the melt and residual solid from REE abundances in clinopyroxene in abyssal peridotites from Mid-Atlantic Ridge, Central Indian Ridge, Southwest Indian Ridge, Lena Trough, and American-Antarctic Ridge. We consider two melting models: one with exact analytical solution and the other without. We solve the latter numerically in a chain of melting models according to the Metropolis-Hastings algorithm. The probability distribution of inverted melting parameters depends on assumptions of the physical model, knowledge of mantle source composition, and constraints from the REE data. Results from MCMC inversion are consistent with and provide more reliable uncertainty estimates than results based on nonlinear least squares inversion. We show that chemical disequilibrium is likely to play an important role in fractionating LREE in residual peridotites during partial melting beneath mid-ocean ridge spreading centers. MCMC simulation is well suited for more complicated but physically more realistic melting problems that do not have analytical solutions.
Williams, Michael S; Cao, Yong; Ebel, Eric D
2013-07-15
Levels of pathogenic organisms in food and water have steadily declined in many parts of the world. A consequence of this reduction is that the proportion of samples that test positive for the most contaminated product-pathogen pairings has fallen to less than 0.1. While this is unequivocally beneficial to public health, datasets with very few enumerated samples present an analytical challenge because a large proportion of the observations are censored values. One application of particular interest to risk assessors is the fitting of a statistical distribution function to datasets collected at some point in the farm-to-table continuum. The fitted distribution forms an important component of an exposure assessment. A number of studies have compared different fitting methods and proposed lower limits on the proportion of samples where the organisms of interest are identified and enumerated, with the recommended lower limit of enumerated samples being 0.2. This recommendation may not be applicable to food safety risk assessments for a number of reasons, which include the development of new Bayesian fitting methods, the use of highly sensitive screening tests, and the generally larger sample sizes found in surveys of food commodities. This study evaluates the performance of a Markov chain Monte Carlo fitting method when used in conjunction with a screening test and enumeration of positive samples by the Most Probable Number technique. The results suggest that levels of contamination for common product-pathogen pairs, such as Salmonella on poultry carcasses, can be reliably estimated with the proposed fitting method and samples sizes in excess of 500 observations. The results do, however, demonstrate that simple guidelines for this application, such as the proportion of positive samples, cannot be provided. Published by Elsevier B.V.
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.
Directory of Open Access Journals (Sweden)
Boris Fomin
2012-10-01
Full Text Available This paper presents a new version of radiative transfer model called the Fast Line-by-Line Model (FLBLM, which is based on the Line-by-Line (LbL and Monte Carlo (MC methods and rigorously treats particulate and molecular scattering alongside absorption. The advantage of this model consists in the use of the line-by-line model that allows for the computing of high-resolution spectra quite quickly. We have developed the model by taking into account the polarization state of light and carried out some validations by comparison against benchmark results. FLBLM calculates the Stokes parameters spectra of shortwave radiation in vertically inhomogeneous atmospheres. This update makes the model applicable for the assessment of cloud and aerosol influence on radiances as measured by the SW high-resolution polarization spectrometers. In sample results we demonstrate that the high-resolution spectra of the Stokes parameters contain more detailed information about clouds and aerosols than the medium- and low-resolution spectra wherein lines are not resolved. The presented model is rapid enough for many practical applications (e.g., validations and might be useful especially for the remote sensing. FLBLM is suitable for development of the reliable technique for retrieval of optical and microphysical properties of clouds and aerosols from high-resolution satellites data.
Peng, C.; Zhou, X.
2015-12-01
To reduce simulation uncertainties due to inaccurate model parameters, the Markov Chain Monte Carlo (MCMC) method was applied in this study to improve the estimations of four key parameters used in the process-based ecosystem model of TRIPLEX-FLUX. These four key parameters include a maximum photosynthetic carboxylation rate of 25°C (Vcmax), an electron transport (Jmax) light-saturated rate within the photosynthetic carbon reduction cycle of leaves, a coefficient of stomatal conductance (m), and a reference respiration rate of 10ºC (R10). Seven forest flux tower sites located across North America were used to investigate and facilitate understanding of the daily variation in model parameters for three deciduous forests, three evergreen temperate forests, and one evergreen boreal forest. Eddy covariance CO2 exchange measurements were assimilated to optimize the parameters in the year 2006. After parameter optimization and adjustment took place, net ecosystem production prediction significantly improved (by approximately 25%) compared to the CO2 flux measurements taken at the seven forest ecosystem sites.
Liu, Tianyu; Du, Xining; Ji, Wei; Xu, X. George; Brown, Forrest B.
2014-06-01
For nuclear reactor analysis such as the neutron eigenvalue calculations, the time consuming Monte Carlo (MC) simulations can be accelerated by using graphics processing units (GPUs). However, traditional MC methods are often history-based, and their performance on GPUs is affected significantly by the thread divergence problem. In this paper we describe the development of a newly designed event-based vectorized MC algorithm for solving the neutron eigenvalue problem. The code was implemented using NVIDIA's Compute Unified Device Architecture (CUDA), and tested on a NVIDIA Tesla M2090 GPU card. We found that although the vectorized MC algorithm greatly reduces the occurrence of thread divergence thus enhancing the warp execution efficiency, the overall simulation speed is roughly ten times slower than the history-based MC code on GPUs. Profiling results suggest that the slow speed is probably due to the memory access latency caused by the large amount of global memory transactions. Possible solutions to improve the code efficiency are discussed.
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Pomp, S., E-mail: stephan.pomp@physics.uu.se [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden); Al-Adili, A.; Alhassan, E.; Gustavsson, C.; Helgesson, P.; Hellesen, C. [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden); Koning, A.J. [Nuclear Research and Consultancy Group NRG, P.O.Box 25, 1755 ZG Petten (Netherlands); Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden); Lantz, M.; Österlund, M. [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden); Rochman, D. [Nuclear Research and Consultancy Group NRG, P.O.Box 25, 1755 ZG Petten (Netherlands); Simutkin, V.; Sjöstrand, H.; Solders, A. [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden)
2015-01-15
We describe the research program of the nuclear reactions research group at Uppsala University concerning experimental and theoretical efforts to quantify and reduce nuclear data uncertainties relevant for the nuclear fuel cycle. We briefly describe the Total Monte Carlo (TMC) methodology and how it can be used to study fuel cycle and accident scenarios, and summarize our relevant experimental activities. Input from the latter is to be used to guide the nuclear models and constrain parameter space for TMC. The TMC method relies on the availability of good nuclear models. For this we use the TALYS code which is currently being extended to include the GEF model for the fission channel. We present results from TALYS-1.6 using different versions of GEF with both default and randomized input parameters and compare calculations with experimental data for {sup 234}U(n,f) in the fast energy range. These preliminary studies reveal some systematic differences between experimental data and calculations but give overall good and promising results.
Directory of Open Access Journals (Sweden)
Chalinee Thanasupsombat
2018-01-01
Full Text Available The quality of images obtained from cone-beam computed tomography (CBCT is important in diagnosis and treatment planning for dental and maxillofacial applications. However, X-ray scattering inside a human head is one of the main factors that cause a drop in image quality, especially in the CBCT system with a wide-angle cone-beam X-ray source and a large area detector. In this study, the X-ray scattering distribution within a standard head phantom was estimated using the Monte Carlo method based on Geant4. Due to small variation of low-frequency scattering signals, the scattering signals from the head phantom can be represented as the simple predetermined scattering signals from a patient’s head and subtracted the projection data for scatter reduction. The results showed higher contrast and less cupping artifacts on the reconstructed images of the head phantom and real patients. Furthermore, the same simulated scattering signals can also be applied to process with higher-resolution projection data.
Thorn, Graeme J; King, John R
2016-01-01
The Gram-positive bacterium Clostridium acetobutylicum is an anaerobic endospore-forming species which produces acetone, butanol and ethanol via the acetone-butanol (AB) fermentation process, leading to biofuels including butanol. In previous work we looked to estimate the parameters in an ordinary differential equation model of the glucose metabolism network using data from pH-controlled continuous culture experiments. Here we combine two approaches, namely the approximate Bayesian computation via an existing sequential Monte Carlo (ABC-SMC) method (to compute credible intervals for the parameters), and the profile likelihood estimation (PLE) (to improve the calculation of confidence intervals for the same parameters), the parameters in both cases being derived from experimental data from forward shift experiments. We also apply the ABC-SMC method to investigate which of the models introduced previously (one non-sporulation and four sporulation models) have the greatest strength of evidence. We find that the joint approximate posterior distribution of the parameters determines the same parameters as previously, including all of the basal and increased enzyme production rates and enzyme reaction activity parameters, as well as the Michaelis-Menten kinetic parameters for glucose ingestion, while other parameters are not as well-determined, particularly those connected with the internal metabolites acetyl-CoA, acetoacetyl-CoA and butyryl-CoA. We also find that the approximate posterior is strongly non-Gaussian, indicating that our previous assumption of elliptical contours of the distribution is not valid, which has the effect of reducing the numbers of pairs of parameters that are (linearly) correlated with each other. Calculations of confidence intervals using the PLE method back this up. Finally, we find that all five of our models are equally likely, given the data available at present. Copyright © 2015 Elsevier Inc. All rights reserved.
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Yongshuai Jiang
Full Text Available Traditional permutation (TradPerm tests are usually considered the gold standard for multiple testing corrections. However, they can be difficult to complete for the meta-analyses of genetic association studies based on multiple single nucleotide polymorphism loci as they depend on individual-level genotype and phenotype data to perform random shuffles, which are not easy to obtain. Most meta-analyses have therefore been performed using summary statistics from previously published studies. To carry out a permutation using only genotype counts without changing the size of the TradPerm P-value, we developed a Monte Carlo permutation (MCPerm method. First, for each study included in the meta-analysis, we used a two-step hypergeometric distribution to generate a random number of genotypes in cases and controls. We then carried out a meta-analysis using these random genotype data. Finally, we obtained the corrected permutation P-value of the meta-analysis by repeating the entire process N times. We used five real datasets and five simulation datasets to evaluate the MCPerm method and our results showed the following: (1 MCPerm requires only the summary statistics of the genotype, without the need for individual-level data; (2 Genotype counts generated by our two-step hypergeometric distributions had the same distributions as genotype counts generated by shuffling; (3 MCPerm had almost exactly the same permutation P-values as TradPerm (r = 0.999; P<2.2e-16; (4 The calculation speed of MCPerm is much faster than that of TradPerm. In summary, MCPerm appears to be a viable alternative to TradPerm, and we have developed it as a freely available R package at CRAN: http://cran.r-project.org/web/packages/MCPerm/index.html.
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
2. Application of Metropolis-Hastings Algorithm. We shall illustrate applications of the Metropolis-Hast- ings (M-H) algorithm described in Part 2 of this series of articles to the generation of a random sample fronl a gamma distribution and from the posterior distribution of Weibull parameters in a Bayesian context. But before.
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Author Affiliations. K B Athreya1 Mohan Delampady2 T Krishnan3. School of ORIE Rhodes Hall Cornell University, Ithaca New York 14853, USA. Indian Statistical Institute 8th Mile, Mysore Rood Bangalore 560 059, India. Systat Software Asia-Pacific Ltd. Floor 5, 'C' Tower Golden Enclave, Airport Rood Bangalore 560 017, ...
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Author Affiliations. K B Athreya1 Mohan Delampady2 T Krishnan3. School of ORIE Rhodes Hall Cornell University, Ithaca New York 14853, USA; Indian Statistical Institute 8th Mile, Mysore Road Bangalore 560 059, India. Systat Software Asia-Pacific Ltd. Floor 5, 'C' Tower Golden Enclave, Airport Road Bangalore 560 017, ...
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
K B Athreya1 Mohan Delampady2 T Krishnan3. School of ORIE Rhodes Hall Cornell University, Ithaca New York 14853, USA; Indian Statistical Institute 8th Mile, Mysore Road Bangalore 560059, India. Systat Software Asia-Pacific Ltd. Floor 5, 'C' Tower Golden Enclave, Airport Road Bangalore 560 017, India.
Energy Technology Data Exchange (ETDEWEB)
Takeda, Mauro Noriaki
2006-07-01
The present work described a new methodology for modelling the behaviour of the activity in a 4{pi}{beta}-{gamma} coincidence system. The detection efficiency for electrons in the proportional counter and gamma radiation in the NaI(Tl) detector was calculated using the Monte Carlo program MCNP4C. Another Monte Carlo code was developed which follows the path in the disintegration scheme from the initial state of the precursor radionuclide, until the ground state of the daughter nucleus. Every step of the disintegration scheme is sorted by random numbers taking into account the probabilities of all {beta}{sup -} branches, electronic capture branches, transitions probabilities and internal conversion coefficients. Once the final state was reached beta, electronic capture events and gamma transitions are accounted for the three spectra: beta, gamma and coincidence variation in the beta efficiency was performed simulating energy cut off or use of absorbers (Collodion). The selected radionuclides for simulation were: {sup 134}Cs, {sup 72}Ga which disintegrate by {beta}{sup -} transition, {sup 133}Ba which disintegrates by electronic capture and {sup 35}S which is a beta pure emitter. For the latter, the Efficiency Tracing technique was simulated. The extrapolation curves obtained by Monte Carlo were filled by the Least Square Method with the experimental points and the results were compared to the Linear Extrapolation method. (author)
ROESSEL, ROBERT A., JR.
THE FIRST SECTION OF THIS BOOK COVERS THE HISTORICAL AND CULTURAL BACKGROUND OF THE SAN CARLOS APACHE INDIANS, AS WELL AS AN HISTORICAL SKETCH OF THE DEVELOPMENT OF THEIR FORMAL EDUCATIONAL SYSTEM. THE SECOND SECTION IS DEVOTED TO THE PROBLEMS OF TEACHERS OF THE INDIAN CHILDREN IN GLOBE AND SAN CARLOS, ARIZONA. IT IS DIVIDED INTO THREE PARTS--(1)…
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Meireles, Ramiro Conceicao
2016-07-01
The shielding calculation methodology for radiotherapy services adopted in Brazil and in several countries is that described in publication 151 of the National Council on Radiation Protection and Measurements (NCRP 151). This methodology however, markedly employs several approaches that can impact both in the construction cost and in the radiological safety of the facility. Although this methodology is currently well established by the high level of use, some parameters employed in the calculation methodology did not undergo to a detailed assessment to evaluate the impact of the various approaches considered. In this work the MCNP5 Monte Carlo code was used with the purpose of evaluating the above mentioned approaches. TVLs values were obtained for photons in conventional concrete (2.35g / cm{sup 3}), considering the energies of 6, 10 and 25 MeV, respectively, first considering an isotropic radiation source impinging perpendicular to the barriers, and subsequently a lead head shielding emitting a shaped beam, in the format of a pyramid trunk. Primary barriers safety margins, taking in account the head shielding emitting photon beam pyramid-shaped in the energies of 6, 10, 15 and 18 MeV were assessed. A study was conducted considering the attenuation provided by the patient's body in the energies of 6,10, 15 and 18 MeV, leading to new attenuation factors. Experimental measurements were performed in a real radiotherapy room, in order to map the leakage radiation emitted by the accelerator head shielding and the results obtained were employed in the Monte Carlo simulation, as well as to validate the entire study. The study results indicate that the TVLs values provided by (NCRP, 2005) show discrepancies in comparison with the values obtained by simulation and that there may be some barriers that are calculated with insufficient thickness. Furthermore, the simulation results show that the additional safety margins considered when calculating the width of the
Multilevel Monte Carlo in Approximate Bayesian Computation
Jasra, Ajay
2017-02-13
In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.
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Yang, Y; Cai, J; Meltsner, S; Chang, Z; Craciunescu, O [Duke University Medical Center, Durham, NC (United States)
2016-06-15
Purpose: The Varian tandem and ring applicators are used to deliver HDR Ir-192 brachytherapy for cervical cancer. The source path within the ring is hard to predict due to the larger interior ring lumen. Some studies showed the source could be several millimeters different from planned positions, while other studies demonstrated minimal dosimetric impact. A global shift can be applied to limit the effect of positioning offsets. The purpose of this study was to assess the necessities of implementing a global source shift using Monte Carlo (MC) simulations. Methods: The MCNP5 radiation transport code was used for all MC simulations. To accommodate TG-186 guidelines and eliminate inter-source attenuation, a BrachyVision plan with 10 dwell positions (0.5cm step sizes) was simulated as the summation of 10 individual sources with equal dwell times for simplification. To simplify the study, the tandem was also excluded from the MC model. Global shifts of ±0.1, ±0.3, ±0.5 cm were then simulated as distal and proximal from the reference positions. Dose was scored in water for all MC simulations and was normalized to 100% at the normalization point 0.5 cm from the cap in the ring plane. For dose comparison, Point A was 2 cm caudal from the buildup cap and 2 cm lateral on either side of the ring axis. With seventy simulations, 108 photon histories gave a statistical uncertainties (k=1) <2% for (0.1 cm)3 voxels. Results: Compared to no global shift, average Point A doses were 0.0%, 0.4%, and 2.2% higher for distal global shifts, and 0.4%, 2.8%, and 5.1% higher for proximal global shifts, respectively. The MC Point A doses differed by < 1% when compared to BrachyVision. Conclusion: Dose variations were not substantial for ±0.3 cm global shifts, which is common in clinical practice.
Using the Markov chain Monte Carlo method to study the physical properties of GeV-TeV BL Lac objects
Qin, Longhua; Wang, Jiancheng; Yang, Chuyuan; Yuan, Zunli; Mao, Jirong; Kang, Shiju
2018-01-01
We fit the spectral energy distributions (SEDs) of 46 GeV-TeV BL Lac objects in the frame of leptonic one-zone synchrotron self-Compton (SSC) model and investigate the physical properties of these objects. We use the Markov chain Monte Carlo (MCMC) method to obtain the basic parameters, such as magnetic field (B), the break energy of the relativistic electron distribution (γ ^' }b), and the electron energy spectral index. Based on the modeling results, we support the following scenarios for GeV-TeV BL Lac objects. (1) Some sources have large Doppler factors, implying other radiation mechanism should be considered. (2) Compared with flat spectrum quasars (FSRQs), GeV-TeV BL Lac objects have weaker magnetic fields and larger Doppler factors, which cause the ineffective cooling and shift the SEDs to higher bands. Their jet powers are around 4.0 × 1045 erg s-1, compared with radiation power, 5.0 × 1042 erg s-1, indicating that only a small fraction of jet power is transformed into the emission power. (3) For some BL Lacs with large Doppler factors, their jet components could have two substructures, e.g., the fast core and the slow sheath. For most GeV-TeV BL Lacs, Kelvin-Helmholtz instabilities are suppressed by their higher magnetic fields, leading to micro-variability or intro-day variability in the optical bands. (4) Combined with a sample of FSRQs, an anti-correlation between the peak luminosity, Lpk, and the peak frequency, νpk, is obtained, favoring the blazar sequence scenario. In addition, an anti-correlation between the jet power, Pjet, and the break Lorentz factor, γb, also supports the blazar sequence.
Ceria, Paul; Ducourtieux, Sebastien; Boukellal, Younes; Allard, Alexandre; Fischer, Nicolas; Feltin, Nicolas
2017-03-01
In order to evaluate the uncertainty budget of the LNE’s mAFM, a reference instrument dedicated to the calibration of nanoscale dimensional standards, a numerical model has been developed to evaluate the measurement uncertainty of the metrology loop involved in the XYZ positioning of the tip relative to the sample. The objective of this model is to overcome difficulties experienced when trying to evaluate some uncertainty components which cannot be experimentally determined and more specifically, the one linked to the geometry of the metrology loop. The model is based on object-oriented programming and developed under Matlab. It integrates one hundred parameters that allow the control of the geometry of the metrology loop without using analytical formulae. The created objects, mainly the reference and the mobile prism and their mirrors, the interferometers and their laser beams, can be moved and deformed freely to take into account several error sources. The Monte Carlo method is then used to determine the positioning uncertainty of the instrument by randomly drawing the parameters according to their associated tolerances and their probability density functions (PDFs). The whole process follows Supplement 2 to ‘The Guide to the Expression of the Uncertainty in Measurement’ (GUM). Some advanced statistical tools like Morris design and Sobol indices are also used to provide a sensitivity analysis by identifying the most influential parameters and quantifying their contribution to the XYZ positioning uncertainty. The approach validated in the paper shows that the actual positioning uncertainty is about 6 nm. As the final objective is to reach 1 nm, we engage in a discussion to estimate the most effective way to reduce the uncertainty.
Energy Technology Data Exchange (ETDEWEB)
Lujan, Paul Joseph [Univ. of California, Berkeley, CA (United States)
2009-12-01
This thesis presents a measurement of the top quark mass obtained from p$\\bar{p}$ collisions at √s = 1.96 TeV at the Fermilab Tevatron using the CDF II detector. The measurement uses a matrix element integration method to calculate a t$\\bar{t}$ likelihood, employing a Quasi-Monte Carlo integration, which enables us to take into account effects due to finite detector angular resolution and quark mass effects. We calculate a t$\\bar{t}$ likelihood as a 2-D function of the top pole mass m_{t} and Δ_{JES}, where Δ_{JES} parameterizes the uncertainty in our knowledge of the jet energy scale; it is a shift applied to all jet energies in units of the jet-dependent systematic error. By introducing Δ_{JES} into the likelihood, we can use the information contained in W boson decays to constrain Δ_{JES} and reduce error due to this uncertainty. We use a neural network discriminant to identify events likely to be background, and apply a cut on the peak value of individual event likelihoods to reduce the effect of badly reconstructed events. This measurement uses a total of 4.3 fb^{-1} of integrated luminosity, requiring events with a lepton, large E_{T}, and exactly four high-energy jets in the pseudorapidity range |η| < 2.0, of which at least one must be tagged as coming from a b quark. In total, we observe 738 events before and 630 events after applying the likelihood cut, and measure m_{t} = 172.6 ± 0.9 (stat.) ± 0.7 (JES) ± 1.1 (syst.) GeV/c^{2}, or m_{t} = 172.6 ± 1.6 (tot.) GeV/c^{2}.
Energy Technology Data Exchange (ETDEWEB)
Fonseca, R.B.; Amaral, A. [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear; Campos, L., E-mail: amaral@ufpe.br [Universidade Federal de Sergipe (UFS), Aracaju, SE (Brazil). Dept. de Fisica
2012-07-01
In positron emission tomography (PET), health staff is exposed to 511-keV photons, which is a result of the positron annihilation process. This energy is about four times greater than the 140 keV commonly found in studies based on single photon emission computed tomography (SPECT). Besides this different level of energy, 0.5 mm lead-equivalent aprons have being used either in SPECT or PET procedures. In this context, this work was designed for evaluating the effectiveness of such aprons in individual radioprotection of health professionals involved in positron emission tomography. For this, by using MCNP4C-based Monte Carlo simulations, the average energy delivered per particle to the regions corresponding to operational quantities Hp(10) and Hp(0.07) were calculated for two conditions of individual exposures: wearing and not wearing a 0.05 mm lead-equivalent apron. The results obtained pointed out that Hp(10) has similar value in both situations. On the other hand, for the region corresponding to Hp(0.07), wearing this lead apron will improve this dose in about 26%. On the basis of this work, 0.5 mm lead equivalent aprons do not offer adequate protection for medical staff working on positron emission tomography. (author)
forecasting with nonlinear time series model: a monte-carlo ...
African Journals Online (AJOL)
PUBLICATIONS1
ABSTRACT. In this paper, we propose a new method of forecasting with nonlinear time series model using. Monte-Carlo Bootstrap method. This new method gives better result in terms of forecast root mean squared error (RMSE) when compared with the traditional Bootstrap method and Monte-. Carlo method of forecasting ...
Forecasting with nonlinear time series model: A Monte-Carlo ...
African Journals Online (AJOL)
In this paper, we propose a new method of forecasting with nonlinear time series model using Monte-Carlo Bootstrap method. This new method gives better result in terms of forecast root mean squared error (RMSE) when compared with the traditional Bootstrap method and Monte-Carlo method of forecasting using a ...
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)
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...
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).
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.
Wormhole Hamiltonian Monte Carlo.
Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak
2014-07-31
In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function.
Quantum Monte Carlo approaches for correlated systems
Becca, Federico
2017-01-01
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...
Fernández, María; Hänscheid, Heribert; Mauxion, Thibault; Bardiès, Manuel; Kletting, Peter; Glatting, Gerhard; Lassmann, Michael
2013-08-01
In targeted radionuclide therapy, patient-specific dosimetry based on voxel S values (VSVs) is preferable to dosimetry based on mathematical phantoms. Monte-Carlo (MC) simulations are necessary to deduce VSVs for those voxel sizes required by quantitative imaging. The aim of this study is, starting from a single set of high-resolution VSVs obtained by MC simulations for a small voxel size along one single axis perpendicular to the source voxel, to present a suitable method to accurately calculate VSVs for larger voxel sizes. Accurate sets of VSVs for target voxel to source voxel distances up to 10 cm were obtained for high-resolution voxel sizes (0.5 mm for electrons and 1.0 mm for photons) from MC simulations for Y-90, Lu-177, and I-131 using the radiation transport code MCNPX v.2.7a. To make these values suitable to any larger voxel size, different analytical methods (based on resamplings, interpolations, and fits) were tested and compared to values obtained by direct MC simulations. As a result, an optimal calculation procedure is proposed. This procedure consisted of: (1) MC simulation for obtaining of a starting set of VSVs along a single line of voxels for a small voxel size for each radionuclide and type of radiation; (2) interpolation within the values obtained in point (1) for obtaining the VSVs for voxels within a spherical volume; (3) resampling of the data obtained in (1) and (2) for obtaining VSVs for voxels sizes larger than the one used for the MC calculation for integer voxel ratios (voxel ratio=new voxel size∕voxel size MC simulation); (4) interpolation on within the data obtained in (3) for integer voxel ratios. The results were also compared to results from other authors. The results obtained with the method proposed in this work show deviations relative to the source voxel below 1% for I-131 and Lu-177 and below 1.5% for Y-90 as compared with values obtained by direct MC simulations for voxel sizes ranging between 1.0 and 10.0 cm. The results
Monte Carlo calculations of atoms and molecules
Schmidt, K. E.; Moskowitz, J. W.
1986-06-01
The variational and Green's function Monte Carlo (GFMC) methods can treat many interesting atomic and molecular problems. These methods can give chemical accuracy for up to 10 or so electrons. The various implementations of the GFMC method, including the domain Green's function method and the short-time approximation, are discussed. Results are presented for several representative atoms and molecules.
Monte Carlo Particle Lists: MCPL
DEFF Research Database (Denmark)
Kittelmann, Thomas; Klinkby, Esben Bryndt; Bergbäck Knudsen, Erik
2017-01-01
simulation packages. Program summary: Program Title: MCPL. Program Files doi: http://dx.doi.org/10.17632/cby92vsv5g.1 Licensing provisions: CC0 for core MCPL, see LICENSE file for details. Programming language: C and C++ External routines/libraries: Geant4, MCNP, McStas, McXtrace Nature of problem: Saving......A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular...... particle states in Monte Carlo simulations, for interchange between simulation packages or for reuse within a single package. Solution method: Binary interchange format with associated code written in portable C along with tools and interfaces for relevant simulation packages....
Crum, Dax M.; Valsaraj, Amithraj; David, John K.; Register, Leonard F.; Banerjee, Sanjay K.
2016-12-01
Particle-based ensemble semi-classical Monte Carlo (MC) methods employ quantum corrections (QCs) to address quantum confinement and degenerate carrier populations to model tomorrow's ultra-scaled metal-oxide-semiconductor-field-effect-transistors. Here, we present the most complete treatment of quantum confinement and carrier degeneracy effects in a three-dimensional (3D) MC device simulator to date, and illustrate their significance through simulation of n-channel Si and III-V FinFETs. Original contributions include our treatment of far-from-equilibrium degenerate statistics and QC-based modeling of surface-roughness scattering, as well as considering quantum-confined phonon and ionized-impurity scattering in 3D. Typical MC simulations approximate degenerate carrier populations as Fermi distributions to model the Pauli-blocking (PB) of scattering to occupied final states. To allow for increasingly far-from-equilibrium non-Fermi carrier distributions in ultra-scaled and III-V devices, we instead generate the final-state occupation probabilities used for PB by sampling the local carrier populations as function of energy and energy valley. This process is aided by the use of fractional carriers or sub-carriers, which minimizes classical carrier-carrier scattering intrinsically incompatible with degenerate statistics. Quantum-confinement effects are addressed through quantum-correction potentials (QCPs) generated from coupled Schrödinger-Poisson solvers, as commonly done. However, we use these valley- and orientation-dependent QCPs not just to redistribute carriers in real space, or even among energy valleys, but also to calculate confinement-dependent phonon, ionized-impurity, and surface-roughness scattering rates. FinFET simulations are used to illustrate the contributions of each of these QCs. Collectively, these quantum effects can substantially reduce and even eliminate otherwise expected benefits of considered In0.53Ga0.47 As FinFETs over otherwise identical