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
Directory of Open Access Journals (Sweden)
Bardenet Rémi
2013-07-01
Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.
Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method
Cave, H. M.; Tseng, K.-C.; Wu, J.-S.; Jermy, M. C.; Huang, J.-C.; Krumdieck, S. P.
2008-06-01
An unsteady sampling routine for a general parallel direct simulation Monte Carlo method called PDSC is introduced, allowing the simulation of time-dependent flow problems in the near continuum range. A post-processing procedure called DSMC rapid ensemble averaging method (DREAM) is developed to improve the statistical scatter in the results while minimising both memory and simulation time. This method builds an ensemble average of repeated runs over small number of sampling intervals prior to the sampling point of interest by restarting the flow using either a Maxwellian distribution based on macroscopic properties for near equilibrium flows (DREAM-I) or output instantaneous particle data obtained by the original unsteady sampling of PDSC for strongly non-equilibrium flows (DREAM-II). The method is validated by simulating shock tube flow and the development of simple Couette flow. Unsteady PDSC is found to accurately predict the flow field in both cases with significantly reduced run-times over single processor code and DREAM greatly reduces the statistical scatter in the results while maintaining accurate particle velocity distributions. Simulations are then conducted of two applications involving the interaction of shocks over wedges. The results of these simulations are compared to experimental data and simulations from the literature where there these are available. In general, it was found that 10 ensembled runs of DREAM processing could reduce the statistical uncertainty in the raw PDSC data by 2.5-3.3 times, based on the limited number of cases in the present study.
Kalos, Melvin H
2008-01-01
This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application. Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research.The book focuses on two basic themes: The first is the importance of random walks as they occur both in natural stochastic systems and in their relationship to integral and differential equations. The second theme is that of variance reduction in general and importance sampling in particular as a technique for efficient use of the methods. Random walks are introduced with an elementary example in which the modeling of radiation transport arises directly from a schematic probabilistic description of the interaction of radiation with matter. Building on this example, the relationship between random walks and integral equations is outlined
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
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.
1996-01-01
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 γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
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.
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.
Monte Carlo Methods in Physics
International Nuclear Information System (INIS)
Santoso, B.
1997-01-01
Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained
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
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.
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, ...
Monte Carlo methods for shield design calculations
International Nuclear Information System (INIS)
Grimstone, M.J.
1974-01-01
A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)
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)
GENERAL ! ARTICLE. Markov Chain Monte Carlo Methods. 3. Statistical Concepts. 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.
Zimmerman, George B.
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
International Nuclear Information System (INIS)
Zimmerman, G.B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics
International Nuclear Information System (INIS)
Zimmerman, George B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials
Extending canonical Monte Carlo methods
International Nuclear Information System (INIS)
Velazquez, L; Curilef, S
2010-01-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model
(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.
Handbook of Monte Carlo methods
National Research Council Canada - National Science Library
Kroese, Dirk P; Taimre, Thomas; Botev, Zdravko I
2011-01-01
... in rapid succession, the staggering number of related techniques, ideas, concepts and algorithms makes it difficult to maintain an overall picture of the Monte Carlo approach. This book attempts to encapsulate the emerging dynamics of this field of study"--
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
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)
time Technical Consultant to. Systat Software Asia-Pacific. (P) Ltd., in Bangalore, where the technical work for the development of the statistical software Systat takes place. His research interests have been in statistical pattern recognition and biostatistics. Keywords. Markov chain, Monte Carlo sampling, Markov chain Monte.
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
ter of the 20th century, due to rapid developments in computing technology ... early part of this development saw a host of Monte ... These iterative. Monte Carlo procedures typically generate a random se- quence with the Markov property such that the Markov chain is ergodic with a limiting distribution coinciding with 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 ...
International Nuclear Information System (INIS)
Ohta, Shigemi
1996-01-01
The Self-Test Monte Carlo (STMC) method resolves the main problems in using algebraic pseudo-random numbers for Monte Carlo (MC) calculations: that they can interfere with MC algorithms and lead to erroneous results, and that such an error often cannot be detected without known exact solution. STMC is based on good randomness of about 10 10 bits available from physical noise or transcendental numbers like π = 3.14---. Various bit modifiers are available to get more bits for applications that demands more than 10 10 random bits such as lattice quantum chromodynamics (QCD). These modifiers are designed so that a) each of them gives a bit sequence comparable in randomness as the original if used separately from each other, and b) their mutual interference when used jointly in a single MC calculation is adjustable. Intermediate data of the MC calculation itself are used to quantitatively test and adjust the mutual interference of the modifiers in respect of the MC algorithm. STMC is free of systematic error and gives reliable statistical error. Also it can be easily implemented on vector and parallel supercomputers. (author)
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...
Bayesian statistics and Monte Carlo methods
Koch, K. R.
2018-03-01
The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
A Multivariate Time Series Method for Monte Carlo Reactor Analysis
International Nuclear Information System (INIS)
Taro Ueki
2008-01-01
A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor
Adiabatic optimization versus diffusion Monte Carlo methods
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
A keff calculation method by Monte Carlo
International Nuclear Information System (INIS)
Shen, H; Wang, K.
2008-01-01
The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)
Monte Carlo method in neutron activation analysis
International Nuclear Information System (INIS)
Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.
2009-01-01
Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA
Monte Carlo method for random surfaces
International Nuclear Information System (INIS)
Berg, B.
1985-01-01
Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)
Introduction to the Monte Carlo methods
International Nuclear Information System (INIS)
Uzhinskij, V.V.
1993-01-01
Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab
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
Continuous energy Monte Carlo method based lattice homogeinzation
International Nuclear Information System (INIS)
Li Mancang; Yao Dong; Wang Kan
2014-01-01
Based on the Monte Carlo code MCNP, the continuous energy Monte Carlo multi-group constants generation code MCMC has been developed. The track length scheme has been used as the foundation of cross section generation. The scattering matrix and Legendre components require special techniques, and the scattering event method has been proposed to solve this problem. Three methods have been developed to calculate the diffusion coefficients for diffusion reactor core codes and the Legendre method has been applied in MCMC. To the satisfaction of the equivalence theory, the general equivalence theory (GET) and the superhomogenization method (SPH) have been applied to the Monte Carlo method based group constants. The super equivalence method (SPE) has been proposed to improve the equivalence. GET, SPH and SPE have been implemented into MCMC. The numerical results showed that generating the homogenization multi-group constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum, thus provides more accuracy parameters. Besides, the same code and data library can be used for a wide range of applications due to the versatility. The MCMC scheme can be seen as a potential alternative to the widely used deterministic lattice codes. (authors)
Clinical implementation of full Monte Carlo dose calculation in proton beam therapy
International Nuclear Information System (INIS)
Paganetti, Harald; Jiang, Hongyu; Parodi, Katia; Slopsema, Roelf; Engelsman, Martijn
2008-01-01
The goal of this work was to facilitate the clinical use of Monte Carlo proton dose calculation to support routine treatment planning and delivery. The Monte Carlo code Geant4 was used to simulate the treatment head setup, including a time-dependent simulation of modulator wheels (for broad beam modulation) and magnetic field settings (for beam scanning). Any patient-field-specific setup can be modeled according to the treatment control system of the facility. The code was benchmarked against phantom measurements. Using a simulation of the ionization chamber reading in the treatment head allows the Monte Carlo dose to be specified in absolute units (Gy per ionization chamber reading). Next, the capability of reading CT data information was implemented into the Monte Carlo code to model patient anatomy. To allow time-efficient dose calculation, the standard Geant4 tracking algorithm was modified. Finally, a software link of the Monte Carlo dose engine to the patient database and the commercial planning system was established to allow data exchange, thus completing the implementation of the proton Monte Carlo dose calculation engine ('DoC++'). Monte Carlo re-calculated plans are a valuable tool to revisit decisions in the planning process. Identification of clinically significant differences between Monte Carlo and pencil-beam-based dose calculations may also drive improvements of current pencil-beam methods. As an example, four patients (29 fields in total) with tumors in the head and neck regions were analyzed. Differences between the pencil-beam algorithm and Monte Carlo were identified in particular near the end of range, both due to dose degradation and overall differences in range prediction due to bony anatomy in the beam path. Further, the Monte Carlo reports dose-to-tissue as compared to dose-to-water by the planning system. Our implementation is tailored to a specific Monte Carlo code and the treatment planning system XiO (Computerized Medical Systems Inc
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....
Markov Chain Monte Carlo Methods-Simple Monte Carlo
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 4. Markov Chain Monte Carlo ... New York 14853, USA. Indian Statistical Institute 8th Mile, Mysore Road Bangalore 560 059, India. Systat Software Asia-Pacific (PI Ltd., Floor 5, 'C' Tower Golden Enclave, Airport Road Bangalore 560017, India.
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.
Implementation of Monte Carlo Production in LCG-2
García-Abia, J
2005-01-01
In this note we present the implementation of the CMS Monte Carlo production system on LCG-2. We have introduced novel concepts which have made running the full production chain possible on LCG, from the generation of events to the publication of data for analysis, through all the intermediate steps. We have also coupled production and the CMS data transfer system and made the tools more robust, significantly improving the performance of production in LCG.
A general framework for implementing NLO calculations in shower Monte Carlo programs. The POWHEG BOX
Energy Technology Data Exchange (ETDEWEB)
Alioli, Simone [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Nason, Paolo [INFN, Milano-Bicocca (Italy); Oleari, Carlo [INFN, Milano-Bicocca (Italy); Milano-Bicocca Univ. (Italy); Re, Emanuele [Durham Univ. (United Kingdom). Inst. for Particle Physics Phenomenology
2010-02-15
In this work we illustrate the POWHEG BOX, a general computer code framework for implementing NLO calculations in shower Monte Carlo programs according to the POWHEG method. Aim of this work is to provide an illustration of the needed theoretical ingredients, a view of how the code is organized and a description of what a user should provide in order to use it. (orig.)
A general framework for implementing NLO calculations in shower Monte Carlo programs. The POWHEG BOX
International Nuclear Information System (INIS)
Alioli, Simone; Nason, Paolo; Oleari, Carlo; Re, Emanuele
2010-02-01
In this work we illustrate the POWHEG BOX, a general computer code framework for implementing NLO calculations in shower Monte Carlo programs according to the POWHEG method. Aim of this work is to provide an illustration of the needed theoretical ingredients, a view of how the code is organized and a description of what a user should provide in order to use it. (orig.)
Monte Carlo method in radiation transport problems
International Nuclear Information System (INIS)
Dejonghe, G.; Nimal, J.C.; Vergnaud, T.
1986-11-01
In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media [fr
Monte carlo methods and models in finance and insurance
Korn, Ralf; Kroisandt, Gerald
2010-01-01
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...
Monte Carlo methods and models in finance and insurance
Korn, Ralf; Kroisandt, Gerald
2010-01-01
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...
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.
Generalized hybrid Monte Carlo - CMFD methods for fission source convergence
International Nuclear Information System (INIS)
Wolters, Emily R.; Larsen, Edward W.; Martin, William R.
2011-01-01
In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo methods for pricing financial options
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
Now we discuss the antithetic variate method. Like the control variate method, it is very easy to implement in fairly general situations. It also combines well with other variance reduction techniques. The essential idea behind this method is straightforward. Consider two continuous random variables X1 and X2. The variance ...
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which......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....... For the purpose to demonstrate the use and advantages two numerical examples are provided, which is on the quality control of manufactured products....
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.
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)
Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.
2016-03-01
This work discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package authored at Oak Ridge National Laboratory. Shift has been developed to scale well from laptops to small computing clusters to advanced supercomputers and includes features such as support for multiple geometry and physics engines, hybrid capabilities for variance reduction methods such as the Consistent Adjoint-Driven Importance Sampling methodology, advanced parallel decompositions, and tally methods optimized for scalability on supercomputing architectures. The scaling studies presented in this paper demonstrate good weak and strong scaling behavior for the implemented algorithms. Shift has also been validated and verified against various reactor physics benchmarks, including the Consortium for Advanced Simulation of Light Water Reactors' Virtual Environment for Reactor Analysis criticality test suite and several Westinghouse AP1000® problems presented in this paper. These benchmark results compare well to those from other contemporary Monte Carlo codes such as MCNP5 and KENO.
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. ...
Monte Carlo methods for pricing ﬁnancial options
Indian Academy of Sciences (India)
Monte Carlo methods have increasingly become a popular computational tool to price complex ﬁnancial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the 'curse of dimensionality'. However, even Monte-Carlo ...
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 ...
Implementation and analysis of an adaptive multilevel Monte Carlo algorithm
Hoel, Hakon
2014-01-01
We present an adaptive multilevel Monte Carlo (MLMC) method for weak approximations of solutions to Itô stochastic dierential equations (SDE). The work [11] proposed and analyzed an MLMC method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a single level Euler-Maruyama Monte Carlo method from O(TOL-3) to O(TOL-2 log(TOL-1)2) for a mean square error of O(TOL2). Later, the work [17] presented an MLMC method using a hierarchy of adaptively re ned, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform time discretizationMLMC method. This work improves the adaptiveMLMC algorithms presented in [17] and it also provides mathematical analysis of the improved algorithms. In particular, we show that under some assumptions our adaptive MLMC algorithms are asymptotically accurate and essentially have the correct complexity but with improved control of the complexity constant factor in the asymptotic analysis. Numerical tests include one case with singular drift and one with stopped diusion, where the complexity of a uniform single level method is O(TOL-4). For both these cases the results con rm the theory, exhibiting savings in the computational cost for achieving the accuracy O(TOL) from O(TOL-3) for the adaptive single level algorithm to essentially O(TOL-2 log(TOL-1)2) for the adaptive MLMC algorithm. © 2014 by Walter de Gruyter Berlin/Boston 2014.
Monte Carlo method for solving a parabolic problem
Directory of Open Access Journals (Sweden)
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
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
Multiple histogram method and static Monte Carlo sampling
Inda, M.A.; Frenkel, D.
2004-01-01
We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From
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.
New Zero-Variance Methods for Monte Carlo Criticality and Source-Detector Problems
International Nuclear Information System (INIS)
Larsen, Edward W.; Densmore, Jeffery D.
2001-01-01
A zero-variance (ZV) Monte Carlo transport method is a theoretical construct that, if it could be implemented on a practical computer, would produce the exact result after any number of histories. Unfortunately, ZV methods are impractical; nevertheless, ZV methods are of practical interest because it is possible to approximate them in ways that yield efficient variance-reduction schemes. New ZV methods for Monte Carlo criticality and source-detector problems are described. Although these methods have the same requirements and disadvantages of earlier methods, their implementation is very different; thus, the concept of approximating them to obtain practical variance-reduction schemes opens new possibilities. The relationships between the new ZV schemes, conventional ZV schemes, and recently proposed variational variance-reduction techniques are discussed. The goal is the development of more efficient Monte Carlo variance-reduction methods
GPU-accelerated Monte Carlo convolution/superposition implementation for dose calculation.
Zhou, Bo; Yu, Cedric X; Chen, Danny Z; Hu, X Sharon
2010-11-01
Dose calculation is a key component in radiation treatment planning systems. Its performance and accuracy are crucial to the quality of treatment plans as emerging advanced radiation therapy technologies are exerting ever tighter constraints on dose calculation. A common practice is to choose either a deterministic method such as the convolution/superposition (CS) method for speed or a Monte Carlo (MC) method for accuracy. The goal of this work is to boost the performance of a hybrid Monte Carlo convolution/superposition (MCCS) method by devising a graphics processing unit (GPU) implementation so as to make the method practical for day-to-day usage. Although the MCCS algorithm combines the merits of MC fluence generation and CS fluence transport, it is still not fast enough to be used as a day-to-day planning tool. To alleviate the speed issue of MC algorithms, the authors adopted MCCS as their target method and implemented a GPU-based version. In order to fully utilize the GPU computing power, the MCCS algorithm is modified to match the GPU hardware architecture. The performance of the authors' GPU-based implementation on an Nvidia GTX260 card is compared to a multithreaded software implementation on a quad-core system. A speedup in the range of 6.7-11.4x is observed for the clinical cases used. The less than 2% statistical fluctuation also indicates that the accuracy of the authors' GPU-based implementation is in good agreement with the results from the quad-core CPU implementation. This work shows that GPU is a feasible and cost-efficient solution compared to other alternatives such as using cluster machines or field-programmable gate arrays for satisfying the increasing demands on computation speed and accuracy of dose calculation. But there are also inherent limitations of using GPU for accelerating MC-type applications, which are also analyzed in detail in this article.
Monte Carlo methods and applications in nuclear physics
International Nuclear Information System (INIS)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs
Monte Carlo methods and applications in nuclear physics
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Molecular dynamics algorithms for quantum Monte Carlo methods
Miura, Shinichi
2009-11-01
In the present Letter, novel molecular dynamics methods compatible with corresponding quantum Monte Carlo methods are developed. One is a variational molecular dynamics method that is a molecular dynamics analog of quantum variational Monte Carlo method. The other is a variational path integral molecular dynamics method, which is based on the path integral molecular dynamics method for finite temperature systems by Tuckerman et al. [M. Tuckerman, B.J. Berne, G.J. Martyna, M.L. Klein, J. Chem. Phys. 99 (1993) 2796]. These methods are applied to model systems including the liquid helium-4, demonstrated to work satisfactorily for the tested ground state calculations.
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.)
Simulation and the Monte Carlo Method, Student Solutions Manual
Rubinstein, Reuven Y
2012-01-01
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second 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 twenty-five years 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, suc
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.
Combinatorial nuclear level density by a Monte Carlo method
International Nuclear Information System (INIS)
Cerf, N.
1994-01-01
We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations
A threaded Java concurrent implementation of the Monte-Carlo Metropolis Ising model
Castañeda-Marroquín, Carlos; de la Puente, Alfonso Ortega; Alfonseca, Manuel; Glazier, James A.; Swat, Maciej
2010-01-01
This paper describes a concurrent Java implementation of the Metropolis Monte-Carlo algorithm that is used in 2D Ising model simulations. The presented method uses threads, monitors, shared variables and high level concurrent constructs that hide the low level details. In our algorithm we assign one thread to handle one spin flip attempt at a time. We use special lattice site selection algorithm to avoid two or more threads working concurently in the region of the lattice that “belongs” to two or more different spins undergoing spin-flip transformation. Our approach does not depend on the current platform and maximizes concurrent use of the available resources. PMID:21814633
Monte Carlo methods for the self-avoiding walk
International Nuclear Information System (INIS)
Janse van Rensburg, E J
2009-01-01
The numerical simulation of self-avoiding walks remains a significant component in the study of random objects in lattices. In this review, I give a comprehensive overview of the current state of Monte Carlo simulations of models of self-avoiding walks. The self-avoiding walk model is revisited, and the motivations for Monte Carlo simulations of this model are discussed. Efficient sampling of self-avoiding walks remains an elusive objective, but significant progress has been made over the last three decades. The model still poses challenging numerical questions however, and I review specific Monte Carlo methods for improved sampling including general Monte Carlo techniques such as Metropolis sampling, umbrella sampling and multiple Markov Chain sampling. In addition, specific static and dynamic algorithms for walks are presented, and I give an overview of recent innovations in this field, including algorithms such as flatPERM, flatGARM and flatGAS. (topical review)
Energy Technology Data Exchange (ETDEWEB)
Perfetti, Christopher M [ORNL; Martin, William R [University of Michigan; Rearden, Bradley T [ORNL; Williams, Mark L [ORNL
2012-01-01
Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the SHIFT Monte Carlo code within the Scale code package. The methods were used for several simple test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods.
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.
Directory of Open Access Journals (Sweden)
Hammou Amine Bouziane
2013-03-01
Full Text Available We study the thermodynamic and structural properties of a flexible homopolymer chain using both multi canonical Monte Carlo method and Wang-Landau method. In this work, we focus on the coil-globule transition. Starting from a completely random chain, we have obtained a globule for different sizes of the chain. The implementation of these advanced Monte Carlo methods allowed us to obtain a flat histogram in energy space and calculate various thermodynamic quantities such as the density of states, the free energy and the specific heat. Structural quantities such as the radius of gyration where also calculated.
Markov chain Monte Carlo methods: an introductory example
Klauenberg, Katy; Elster, Clemens
2016-02-01
When the Guide to the Expression of Uncertainty in Measurement (GUM) and methods from its supplements are not applicable, the Bayesian approach may be a valid and welcome alternative. Evaluating the posterior distribution, estimates or uncertainties involved in Bayesian inferences often requires numerical methods to avoid high-dimensional integrations. Markov chain Monte Carlo (MCMC) sampling is such a method—powerful, flexible and widely applied. Here, a concise introduction is given, illustrated by a simple, typical example from metrology. The Metropolis-Hastings algorithm is the most basic and yet flexible MCMC method. Its underlying concepts are explained and the algorithm is given step by step. The few lines of software code required for its implementation invite interested readers to get started. Diagnostics to evaluate the performance and common algorithmic choices are illustrated to calibrate the Metropolis-Hastings algorithm for efficiency. Routine application of MCMC algorithms may be hindered currently by the difficulty to assess the convergence of MCMC output and thus to assure the validity of results. An example points to the importance of convergence and initiates discussion about advantages as well as areas of research. Available software tools are mentioned throughout.
Introduction to Monte Carlo methods: sampling techniques and random numbers
International Nuclear Information System (INIS)
Bhati, Sharda; Patni, H.K.
2009-01-01
The Monte Carlo method describes a very broad area of science, in which many processes, physical systems and phenomena that are statistical in nature and are difficult to solve analytically are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions. As the number of individual events (called histories) is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. Assuming that the behavior of physical system can be described by probability density functions, then the Monte Carlo simulation can proceed by sampling from these probability density functions, which necessitates a fast and effective way to generate random numbers uniformly distributed on the interval (0,1). Particles are generated within the source region and are transported by sampling from probability density functions through the scattering media until they are absorbed or escaped the volume of interest. The outcomes of these random samplings or trials, must be accumulated or tallied in an appropriate manner to produce the desired result, but the essential characteristic of Monte Carlo is the use of random sampling techniques to arrive at a solution of the physical problem. The major components of Monte Carlo methods for random sampling for a given event are described in the paper
LISA data analysis using Markov chain Monte Carlo methods
International Nuclear Information System (INIS)
Cornish, Neil J.; Crowder, Jeff
2005-01-01
The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low-frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50 000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analysis, and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we supercool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions
Application of Monte Carlo Method to Steady State Heat Conduction ...
African Journals Online (AJOL)
The Monte Carlo method was used in modelling steady state heat conduction problems. The method uses the fixed and the floating random walks to determine temperature in the domain of the definition of the heat conduction equation, at a single point directly. A heat conduction problem with an irregular shaped geometry ...
A Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
P Zakian
2017-10-10
Oct 10, 2017 ... simulations are proposed. Various comparisons are examined to illustrate the capability of both methods for random simulation of faults. Keywords. Monte Carlo simulation; stochastic modeling; split node technique; finite element method; earthquake fault dislocation. 1. Introduction. In material science, a ...
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.
TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging
International Nuclear Information System (INIS)
Badal, A; Zbijewski, W; Bolch, W; Sechopoulos, I
2014-01-01
Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10 7 xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual
Selection of Investment Projects by Monte Carlo Method in Risk Condition
Directory of Open Access Journals (Sweden)
M. E.
2017-12-01
Full Text Available The Monte Carlo method (also known as the Monte Carlo simulation was proposed by Nicholas Metropolis, S. Ulam and Jhon Von Neiman in 50-th years of the past century. The method can be widely applied to analysis of investment projects due to the advantages recognized both by practitioners and the academic community. The balance model of a project with discounted financial flows has been implemented for Microsoft Excel and Google Docs spread-sheet solutions. The Monte Carlo method for project with low and high correlated net present value (NPV parameters in the environment of the electronic tables of MS Excel/Google Docs. A distinct graduation of risk was identified. A necessity of account of correlation effects and the use of multivariate imitation during the project selection has been demonstrated.
Latent uncertainties of the precalculated track Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Renaud, Marc-André; Seuntjens, Jan [Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4 (Canada); Roberge, David [Département de radio-oncologie, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec H2L 4M1 (Canada)
2015-01-15
Purpose: 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. Methods: 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 D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: 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
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
International Nuclear Information System (INIS)
Stapleton, S; Zavgorodni, S; Popescu, I A; Beckham, W A
2005-01-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
Stapleton, S.; Zavgorodni, S.; Popescu, I. A.; Beckham, W. A.
2005-02-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.
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.
Improved Monte Carlo methods for fermions
International Nuclear Information System (INIS)
DeGrand, T.A.; Dreitlein, J.; Toms, D.J.
1983-01-01
We describe an improved version of the Kuti-Von Neumann-Ulam algorithm useful for fermion contributions in lattice field theories. This is done by sampling the Neumann series for the propagator, which may be thought of as a sum over a set of weighted paths between two points on the lattice. Rather than selecting paths by a locally determined random walk, we average over sets of paths globally preselected for their importance in evaluating the few needed elements of the inverse. We also describe a method for the calculation of ratios of fermion determinants which is considerably less time consuming than the conventional one. (orig.)
International Nuclear Information System (INIS)
Han Jingru; Chen Yixue; Yuan Longjun
2013-01-01
The Monte Carlo (MC) and discrete ordinates (SN) are the commonly used methods in the design of radiation shielding. Monte Carlo method is able to treat the geometry exactly, but time-consuming in dealing with the deep penetration problem. The discrete ordinate method has great computational efficiency, but it is quite costly in computer memory and it suffers from ray effect. Single discrete ordinates method or single Monte Carlo method has limitation in shielding calculation for large complex nuclear facilities. In order to solve the problem, the Monte Carlo and discrete ordinates bidirectional coupling method is developed. The bidirectional coupling method is implemented in the interface program to transfer the particle probability distribution of MC and angular flux of discrete ordinates. The coupling method combines the advantages of MC and SN. The test problems of cartesian and cylindrical coordinate have been calculated by the coupling methods. The calculation results are performed with comparison to MCNP and TORT and satisfactory agreements are obtained. The correctness of the program is proved. (authors)
Parallelism in continuous energy Monte Carlo method for neutron transport
Energy Technology Data Exchange (ETDEWEB)
Uenohara, Yuji (Nuclear Engineering Lab., Toshiba Corp. (Japan))
1993-04-01
The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)
Parallelism in continuous energy Monte Carlo method for neutron transport
International Nuclear Information System (INIS)
Uenohara, Yuji
1993-01-01
The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)
International Nuclear Information System (INIS)
Li, Zeguang; Wang, Kan; Zhang, Xisi
2011-01-01
In traditional Monte Carlo method, the material properties in a certain cell are assumed to be constant, but this is no longer applicable in continuous varying materials where the material's nuclear cross-sections vary over the particle's flight path. So, three Monte Carlo methods, including sub stepping method, delta-tracking method and direct sampling method, are discussed in this paper to solve the problems with continuously varying materials. After the verification and comparison of these methods in 1-D models, the basic specialties of these methods are discussed and then we choose the delta-tracking method as the main method to solve the problems with continuously varying materials, especially 3-D problems. To overcome the drawbacks of the original delta-tracking method, an improved delta-tracking method is proposed in this paper to make this method more efficient in solving problems where the material's cross-sections vary sharply over the particle's flight path. To use this method in practical calculation, we implemented the improved delta-tracking method into the 3-D Monte Carlo code RMC developed by Department of Engineering Physics, Tsinghua University. Two problems based on Godiva system were constructed and calculations were made using both improved delta-tracking method and the sub stepping method, and the results proved the effects of improved delta-tracking method. (author)
A separable shadow Hamiltonian hybrid Monte Carlo method
Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.
2009-11-01
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
Present status of transport code development based on Monte Carlo method
International Nuclear Information System (INIS)
Nakagawa, Masayuki
1985-01-01
The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)
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.
Energy Technology Data Exchange (ETDEWEB)
Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C., E-mail: jaime.esquivel@fi.uaemex.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2011-11-15
The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)
Monte Carlo Methods in ICF (LIRPP Vol. 13)
Zimmerman, George B.
2016-10-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved SOX in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
Difficult Sudoku Puzzles Created by Replica Exchange Monte Carlo Method
Watanabe, Hiroshi
2013-01-01
An algorithm to create difficult Sudoku puzzles is proposed. An Ising spin-glass like Hamiltonian describing difficulty of puzzles is defined, and difficult puzzles are created by minimizing the energy of the Hamiltonian. We adopt the replica exchange Monte Carlo method with simultaneous temperature adjustments to search lower energy states efficiently, and we succeed in creating a puzzle which is the world hardest ever created in our definition, to our best knowledge. (Added on Mar. 11, the ...
Comparison of deterministic and Monte Carlo methods in shielding design.
Oliveira, A D; Oliveira, C
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions.
Comparison of deterministic and Monte Carlo methods in shielding design
International Nuclear Information System (INIS)
Oliveira, A. D.; Oliveira, C.
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions. (authors)
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.
Diagrammatic Monte Carlo method as applied to the polaron problem
International Nuclear Information System (INIS)
Mishchenko, A.S.
2005-01-01
Exact numerical solution methods for the problem of a few particles interacting with one another and with several bosonic excitation modes are presented. The diagrammatic Monte Carlo method allows the exact calculation of the Green function, and the stochastic optimization technique provides an analytic continuation. Results unobtainable by conventional methods are discussed, including the properties of excited states in the self-trapping phenomenon, the optical spectra of polarons in all coupling regimes, the validity analysis of the exciton models, and the photoemission spectra of a phonon-coupled hole [ru
International Nuclear Information System (INIS)
Perfetti, C.; Martin, W.; Rearden, B.; Williams, M.
2012-01-01
Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the Shift Monte Carlo code within the SCALE code package. The methods were used for two small-scale test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods. (authors)
Energy Technology Data Exchange (ETDEWEB)
Perfetti, C.; Martin, W. [Univ. of Michigan, Dept. of Nuclear Engineering and Radiological Sciences, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109-2104 (United States); Rearden, B.; Williams, M. [Oak Ridge National Laboratory, Reactor and Nuclear Systems Div., Bldg. 5700, P.O. Box 2008, Oak Ridge, TN 37831-6170 (United States)
2012-07-01
Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the Shift Monte Carlo code within the SCALE code package. The methods were used for two small-scale test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods. (authors)
Probability-neighbor method of accelerating geometry treatment in reactor Monte Carlo code RMC
International Nuclear Information System (INIS)
She, Ding; Li, Zeguang; Xu, Qi; Wang, Kan; Yu, Ganglin
2011-01-01
Probability neighbor method (PNM) is proposed in this paper to accelerate geometry treatment of Monte Carlo (MC) simulation and validated in self-developed reactor Monte Carlo code RMC. During MC simulation by either ray-tracking or delta-tracking method, large amounts of time are spent in finding out which cell one particle is located in. The traditional way is to search cells one by one with certain sequence defined previously. However, this procedure becomes very time-consuming when the system contains a large number of cells. Considering that particles have different probability to enter different cells, PNM method optimizes the searching sequence, i.e., the cells with larger probability are searched preferentially. The PNM method is implemented in RMC code and the numerical results show that the considerable time of geometry treatment in MC calculation for complicated systems is saved, especially effective in delta-tracking simulation. (author)
Directory of Open Access Journals (Sweden)
José Luiz Ferreira Martins
2011-09-01
. From these data was taken at random samples with, respectively, 10, 15 and 20 elements and were performed simulations by Monte Carlo method. Comparing the results of the sample with 160 elements and the data generated by simulation is observed that good results can be obtained by using Monte Carlo method in estimating productivity of industrial welding. On the other hand in Brazilian construction industry the value of productivity average is normally used as a productivity indicator and is based on historical data from other projects collected and measured only after project completion, which is a limitation. This article presents a tool for evaluation of the implementation in real time, enabling adjustments in estimates and monitoring productivity during the project. Similarly, in biddings, budgets and schedule estimations, the use of this tool could enable the adoption of other estimative different from of the average productivity, which is commonly used and as an alternative are suggested three criteria: optimistic, average and pessimistic productivity.
Maucec, M
2005-01-01
Monte Carlo simulations for nuclear logging applications are considered to be highly demanding transport problems. In this paper, the implementation of weight-window variance reduction schemes in a 'manual' fashion to improve the efficiency of calculations for a neutron logging tool is presented.
Comparison of Monte Carlo method and deterministic method for neutron transport calculation
International Nuclear Information System (INIS)
Mori, Takamasa; Nakagawa, Masayuki
1987-01-01
The report outlines major features of the Monte Carlo method by citing various applications of the method and techniques used for Monte Carlo codes. Major areas of its application include analysis of measurements on fast critical assemblies, nuclear fusion reactor neutronics analysis, criticality safety analysis, evaluation by VIM code, and calculation for shielding. Major techniques used for Monte Carlo codes include the random walk method, geometric expression method (combinatorial geometry, 1, 2, 4-th degree surface and lattice geometry), nuclear data expression, evaluation method (track length, collision, analog (absorption), surface crossing, point), and dispersion reduction (Russian roulette, splitting, exponential transform, importance sampling, corrected sampling). Major features of the Monte Carlo method are as follows: 1) neutron source distribution and systems of complex geometry can be simulated accurately, 2) physical quantities such as neutron flux in a place, on a surface or at a point can be evaluated, and 3) calculation requires less time. (Nogami, K.)
Monte Carlo methods in electron transport problems. Pt. 1
International Nuclear Information System (INIS)
Cleri, F.
1989-01-01
The condensed-history Monte Carlo method for charged particles transport is reviewed and discussed starting from a general form of the Boltzmann equation (Part I). The physics of the electronic interactions, together with some pedagogic example will be introduced in the part II. The lecture is directed to potential users of the method, for which it can be a useful introduction to the subject matter, and wants to establish the basis of the work on the computer code RECORD, which is at present in a developing stage
TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging
Energy Technology Data Exchange (ETDEWEB)
Badal, A [U.S. Food and Drug Administration (CDRH/OSEL), Silver Spring, MD (United States); Zbijewski, W [Johns Hopkins University, Baltimore, MD (United States); Bolch, W [University of Florida, Gainesville, FL (United States); Sechopoulos, I [Emory University, Atlanta, GA (United States)
2014-06-15
Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the
International Nuclear Information System (INIS)
Cacais, F.L.; Delgado, J.U.; Loayza, V.M.
2016-01-01
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)
Radial-based tail methods for Monte Carlo simulations of cylindrical interfaces
Goujon, Florent; Bêche, Bruno; Malfreyt, Patrice; Ghoufi, Aziz
2018-03-01
In this work, we implement for the first time the radial-based tail methods for Monte Carlo simulations of cylindrical interfaces. The efficiency of this method is then evaluated through the calculation of surface tension and coexisting properties. We show that the inclusion of tail corrections during the course of the Monte Carlo simulation impacts the coexisting and the interfacial properties. We establish that the long range corrections to the surface tension are the same order of magnitude as those obtained from planar interface. We show that the slab-based tail method does not amend the localization of the Gibbs equimolar dividing surface. Additionally, a non-monotonic behavior of surface tension is exhibited as a function of the radius of the equimolar dividing surface.
International Nuclear Information System (INIS)
Chen, Zhenping; Song, Jing; Zheng, Huaqing; Wu, Bin; Hu, Liqin
2015-01-01
Highlights: • The subdivision combines both advantages of uniform and non-uniform schemes. • The grid models were proved to be more efficient than traditional CSG models. • Monte Carlo simulation performance was enhanced by Optimal Spatial Subdivision. • Efficiency gains were obtained for realistic whole reactor core models. - Abstract: Geometry navigation is one of the key aspects of dominating Monte Carlo particle transport simulation performance for large-scale whole reactor models. In such cases, spatial subdivision is an easily-established and high-potential method to improve the run-time performance. In this study, a dedicated method, named Optimal Spatial Subdivision, is proposed for generating numerically optimal spatial grid models, which are demonstrated to be more efficient for geometry navigation than traditional Constructive Solid Geometry (CSG) models. The method uses a recursive subdivision algorithm to subdivide a CSG model into non-overlapping grids, which are labeled as totally or partially occupied, or not occupied at all, by CSG objects. The most important point is that, at each stage of subdivision, a conception of quality factor based on a cost estimation function is derived to evaluate the qualities of the subdivision schemes. Only the scheme with optimal quality factor will be chosen as the final subdivision strategy for generating the grid model. Eventually, the model built with the optimal quality factor will be efficient for Monte Carlo particle transport simulation. The method has been implemented and integrated into the Super Monte Carlo program SuperMC developed by FDS Team. Testing cases were used to highlight the performance gains that could be achieved. Results showed that Monte Carlo simulation runtime could be reduced significantly when using the new method, even as cases reached whole reactor core model sizes
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.
Condensed history Monte Carlo methods for photon transport problems
International Nuclear Information System (INIS)
Bhan, Katherine; Spanier, Jerome
2007-01-01
We study methods for accelerating Monte Carlo simulations that retain most of the accuracy of conventional Monte Carlo algorithms. These methods - called Condensed History (CH) methods - have been very successfully used to model the transport of ionizing radiation in turbid systems. Our primary objective is to determine whether or not such methods might apply equally well to the transport of photons in biological tissue. In an attempt to unify the derivations, we invoke results obtained first by Lewis, Goudsmit and Saunderson and later improved by Larsen and Tolar. We outline how two of the most promising of the CH models - one based on satisfying certain similarity relations and the second making use of a scattering phase function that permits only discrete directional changes - can be developed using these approaches. The main idea is to exploit the connection between the space-angle moments of the radiance and the angular moments of the scattering phase function. We compare the results obtained when the two CH models studied are used to simulate an idealized tissue transport problem. The numerical results support our findings based on the theoretical derivations and suggest that CH models should play a useful role in modeling light-tissue interactions
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.
DCA opacity results computed by Monte Carlo Methods
International Nuclear Information System (INIS)
Wilson, B.G.; Albritton, J.R.; Liberman, D.A.
1991-01-01
The authors present the Monte Carlo methods employed by the code ENRICO for obtaining detailed configuration accounting calculations of LTE opacity. Sample calculations of some mid Z elements, all at experimentally accessible conditions 60ev temperature and one-one hundredth solid density, are presented to illustrate the phenomena of transition array breakup. The prediction of systematic trends in transition array breakup is proposed as a means of testing the ion stage balance produced by codes. The importance of including detailed level transitions in arrays, at least on the level of the UTA approximation, is presented, and a novel approximation for explicitly incorporating the individual transitions between configuration is discussed
Entropic sampling in the path integral Monte Carlo method
International Nuclear Information System (INIS)
Vorontsov-Velyaminov, P N; Lyubartsev, A P
2003-01-01
We have extended the entropic sampling Monte Carlo method to the case of path integral representation of a quantum system. A two-dimensional density of states is introduced into path integral form of the quantum canonical partition function. Entropic sampling technique within the algorithm suggested recently by Wang and Landau (Wang F and Landau D P 2001 Phys. Rev. Lett. 86 2050) is then applied to calculate the corresponding entropy distribution. A three-dimensional quantum oscillator is considered as an example. Canonical distributions for a wide range of temperatures are obtained in a single simulation run, and exact data for the energy are reproduced
'Odontologic dosimetric card' experiments and simulations using Monte Carlo methods
International Nuclear Information System (INIS)
Menezes, C.J.M.; Lima, R. de A.; Peixoto, J.E.; Vieira, J.W.
2008-01-01
The techniques for data processing, combined with the development of fast and more powerful computers, makes the Monte Carlo methods one of the most widely used tools in the radiation transport simulation. For applications in diagnostic radiology, this method generally uses anthropomorphic phantoms to evaluate the absorbed dose to patients during exposure. In this paper, some Monte Carlo techniques were used to simulation of a testing device designed for intra-oral X-ray equipment performance evaluation called Odontologic Dosimetric Card (CDO of 'Cartao Dosimetrico Odontologico' in Portuguese) for different thermoluminescent detectors. This paper used two computational models of exposition RXD/EGS4 and CDO/EGS4. In the first model, the simulation results are compared with experimental data obtained in the similar conditions. The second model, it presents the same characteristics of the testing device studied (CDO). For the irradiations, the X-ray spectra were generated by the IPEM report number 78, spectrum processor. The attenuated spectrum was obtained for IEC 61267 qualities and various additional filters for a Pantak 320 X-ray industrial equipment. The results obtained for the study of the copper filters used in the determination of the kVp were compared with experimental data, validating the model proposed for the characterization of the CDO. The results shower of the CDO will be utilized in quality assurance programs in order to guarantee that the equipment fulfill the requirements of the Norm SVS No. 453/98 MS (Brazil) 'Directives of Radiation Protection in Medical and Dental Radiodiagnostic'. We conclude that the EGS4 is a suitable code Monte Carlo to simulate thermoluminescent dosimeters and experimental procedures employed in the routine of the quality control laboratory in diagnostic radiology. (author)
Research on Monte Carlo simulation method of industry CT system
International Nuclear Information System (INIS)
Li Junli; Zeng Zhi; Qui Rui; Wu Zhen; Li Chunyan
2010-01-01
There are a series of radiation physical problems in the design and production of industry CT system (ICTS), including limit quality index analysis; the effect of scattering, efficiency of detectors and crosstalk to the system. Usually the Monte Carlo (MC) Method is applied to resolve these problems. Most of them are of little probability, so direct simulation is very difficult, and existing MC methods and programs can't meet the needs. To resolve these difficulties, particle flux point auto-important sampling (PFPAIS) is given on the basis of auto-important sampling. Then, on the basis of PFPAIS, a particular ICTS simulation method: MCCT is realized. Compared with existing MC methods, MCCT is proved to be able to simulate the ICTS more exactly and effectively. Furthermore, the effects of all kinds of disturbances of ICTS are simulated and analyzed by MCCT. To some extent, MCCT can guide the research of the radiation physical problems in ICTS. (author)
Diagrammatic Monte Carlo method as applied to the polaron problems
International Nuclear Information System (INIS)
Mishchenko, Andrei S
2005-01-01
Numerical methods whereby exact solutions to the problem of a few particles interacting with one another and with several bosonic excitation branches are presented. The diagrammatic Monte Carlo method allows the exact calculation of the Matsubara Green function, and the stochastic optimization technique provides an approximation-free analytic continuation. In this review, results unobtainable by conventional methods are discussed, including the properties of excited states in the self-trapping phenomenon, the optical spectra of polarons in all coupling regimes, the validity range analysis of the Frenkel and Wannier approximations relevant to the exciton, and the peculiarities of photoemission spectra of a lattice-coupled hole in a Mott insulator. (reviews of topical problems)
Hybrid Monte-Carlo method for ICF calculations
Energy Technology Data Exchange (ETDEWEB)
Clouet, J.F.; Samba, G. [CEA Bruyeres-le-Chatel, 91 (France)
2003-07-01
) conduction and ray-tracing for laser description. Radiation transport is usually solved by a Monte-Carlo method. In coupling diffusion approximation and transport description, the difficult part comes from the need for an implicit discretization of the emission-absorption terms: this problem was solved by using the symbolic Monte-Carlo method. This means that at each step of the simulation a matrix is computed by a Monte-Carlo method which accounts for the radiation energy exchange between the cells. Because of time step limitation by hydrodynamic motion, energy exchange is limited to a small number of cells and the matrix remains sparse. This matrix is added to usual diffusion matrix for thermal and radiative conductions: finally we arrive at a non-symmetric linear system to invert. A generalized Marshak condition describe the coupling between transport and diffusion. In this paper we will present the principles of the method and numerical simulation of an ICF hohlraum. We shall illustrate the benefits of the method by comparing the results with full implicit Monte-Carlo calculations. In particular we shall show how the spectral cut-off evolves during the propagation of the radiative front in the gold wall. Several issues are still to be addressed (robust algorithm for spectral cut- off calculation, coupling with ALE capabilities): we shall briefly discuss these problems. (authors)
Hybrid Monte-Carlo method for ICF calculations
International Nuclear Information System (INIS)
Clouet, J.F.; Samba, G.
2003-01-01
) conduction and ray-tracing for laser description. Radiation transport is usually solved by a Monte-Carlo method. In coupling diffusion approximation and transport description, the difficult part comes from the need for an implicit discretization of the emission-absorption terms: this problem was solved by using the symbolic Monte-Carlo method. This means that at each step of the simulation a matrix is computed by a Monte-Carlo method which accounts for the radiation energy exchange between the cells. Because of time step limitation by hydrodynamic motion, energy exchange is limited to a small number of cells and the matrix remains sparse. This matrix is added to usual diffusion matrix for thermal and radiative conductions: finally we arrive at a non-symmetric linear system to invert. A generalized Marshak condition describe the coupling between transport and diffusion. In this paper we will present the principles of the method and numerical simulation of an ICF hohlraum. We shall illustrate the benefits of the method by comparing the results with full implicit Monte-Carlo calculations. In particular we shall show how the spectral cut-off evolves during the propagation of the radiative front in the gold wall. Several issues are still to be addressed (robust algorithm for spectral cut- off calculation, coupling with ALE capabilities): we shall briefly discuss these problems. (authors)
Convergence Studies on Monte Carlo Methods for Pricing Mortgage-Backed Securities
Directory of Open Access Journals (Sweden)
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.
Application of Macro Response Monte Carlo method for electron spectrum simulation
International Nuclear Information System (INIS)
Perles, L.A.; Almeida, A. de
2007-01-01
During the past years several variance reduction techniques for Monte Carlo electron transport have been developed in order to reduce the electron computation time transport for absorbed dose distribution. We have implemented the Macro Response Monte Carlo (MRMC) method to evaluate the electron spectrum which can be used as a phase space input for others simulation programs. Such technique uses probability distributions for electron histories previously simulated in spheres (called kugels). These probabilities are used to sample the primary electron final state, as well as the creation secondary electrons and photons. We have compared the MRMC electron spectra simulated in homogeneous phantom against the Geant4 spectra. The results showed an agreement better than 6% in the spectra peak energies and that MRMC code is up to 12 time faster than Geant4 simulations
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
Directory of Open Access Journals (Sweden)
Juan A Martínez-Velasco
2008-06-01
Full Text Available An accurate calculation of lightning overvoltages is an important issue for the analysis and design of overhead transmission lines. The different parts of a transmission line that are involved in lightning calculations must be represented taking into account the frequency ranges of transients associated to lightning. In addition, the procedures to be used in these calculations must be developed considering the random nature of lightning phenomena. Several simulation tools have been used to estimate the lightning performance of transmission lines. The most popular approaches are those based on a time-domain simulation technique for which adequate procedures and transmission line models have to be developed. This paper presents a summary of the computational efforts made by the authors for the development and implementation in an EMTP-like tool of a Monte Carlo procedure, as well as the models of some transmission line components, aimed at analyzing the lightning performance of transmission lines. An actual test line is used to illustrate the scope of this procedure and the type of studies that can be performed.El cálculo riguroso de sobretensiones de origen atmosférico es un aspecto importante en el análisis y diseño de líneas aéreas de transmisión. Las diferentes partes de una línea que están involucradas en las sobretensiones causadas por el rayo deben ser representadas teniendo en cuenta el rango de frecuencia de los transientes causados por el impacto de una descarga atmosférica. Por otro lado, los procedimientos a emplear en el cálculo de sobretensiones deben ser desarrollados teniendo en cuenta la naturaleza aleatoria del rayo. Varias herramientas de cálculo han sido empleadas hasta la fecha para estimar el comportamiento de líneas aéreas de transmisión frente al rayo. Los procedimientos más utilizados emplean una técnica basada en el dominio del tiempo para la que se han de desarrollar y aplicar modelos adecuados de las
Multi-pass Monte Carlo simulation method in nuclear transmutations.
Mateescu, Liviu; Kadambi, N Prasad; Ravindra, Nuggehalli M
2016-12-01
Monte Carlo methods, in their direct brute simulation incarnation, bring realistic results if the involved probabilities, be they geometrical or otherwise, remain constant for the duration of the simulation. However, there are physical setups where the evolution of the simulation represents a modification of the simulated system itself. Chief among such evolving simulated systems are the activation/transmutation setups. That is, the simulation starts with a given set of probabilities, which are determined by the geometry of the system, the components and by the microscopic interaction cross-sections. However, the relative weight of the components of the system changes along with the steps of the simulation. A natural measure would be adjusting probabilities after every step of the simulation. On the other hand, the physical system has typically a number of components of the order of Avogadro's number, usually 10 25 or 10 26 members. A simulation step changes the characteristics for just a few of these members; a probability will therefore shift by a quantity of 1/10 25 . Such a change cannot be accounted for within a simulation, because then the simulation should have then a number of at least 10 28 steps in order to have some significance. This is not feasible, of course. For our computing devices, a simulation of one million steps is comfortable, but a further order of magnitude becomes too big a stretch for the computing resources. We propose here a method of dealing with the changing probabilities, leading to the increasing of the precision. This method is intended as a fast approximating approach, and also as a simple introduction (for the benefit of students) in the very branched subject of Monte Carlo simulations vis-à-vis nuclear reactors. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
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...
Quantum Monte Carlo method for models of molecular nanodevices
Arrachea, Liliana; Rozenberg, Marcelo J.
2005-07-01
We introduce a quantum Monte Carlo technique to calculate exactly at finite temperatures the Green function of a fermionic quantum impurity coupled to a bosonic field. While the algorithm is general, we focus on the single impurity Anderson model coupled to a Holstein phonon as a schematic model for a molecular transistor. We compute the density of states at the impurity in a large range of parameters, to demonstrate the accuracy and efficiency of the method. We also obtain the conductance of the impurity model and analyze different regimes. The results show that even in the case when the effective attractive phonon interaction is larger than the Coulomb repulsion, a Kondo-like conductance behavior might be observed.
Recursive Monte Carlo method for deep-penetration problems
International Nuclear Information System (INIS)
Goldstein, M.; Greenspan, E.
1980-01-01
The Recursive Monte Carlo (RMC) method developed for estimating importance function distributions in deep-penetration problems is described. Unique features of the method, including the ability to infer the importance function distribution pertaining to many detectors from, essentially, a single M.C. run and the ability to use the history tape created for a representative region to calculate the importance function in identical regions, are illustrated. The RMC method is applied to the solution of two realistic deep-penetration problems - a concrete shield problem and a Tokamak major penetration problem. It is found that the RMC method can provide the importance function distributions, required for importance sampling, with accuracy that is suitable for an efficient solution of the deep-penetration problems considered. The use of the RMC method improved, by one to three orders of magnitude, the solution efficiency of the two deep-penetration problems considered: a concrete shield problem and a Tokamak major penetration problem. 8 figures, 4 tables
Simulation of Rossi-α method with analog Monte-Carlo method
International Nuclear Information System (INIS)
Lu Yuzhao; Xie Qilin; Song Lingli; Liu Hangang
2012-01-01
The analog Monte-Carlo code for simulating Rossi-α method based on Geant4 was developed. The prompt neutron decay constant α of six metal uranium configurations in Oak Ridge National Laboratory were calculated. α was also calculated by Burst-Neutron method and the result was consistent with the result of Rossi-α method. There is the difference between results of analog Monte-Carlo simulation and experiment, and the reasons for the difference is the gaps between uranium layers. The influence of gaps decrease as the sub-criticality deepens. The relative difference between results of analog Monte-Carlo simulation and experiment changes from 19% to 0.19%. (authors)
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
On the Markov Chain Monte Carlo (MCMC) method
Indian Academy of Sciences (India)
In this article, we give an introduction to Monte Carlo techniques with special emphasis on. Markov Chain Monte Carlo (MCMC). Since the latter needs Markov chains with state space that is R or Rd and most text books on Markov chains do not discuss such chains, we have included a short appendix that gives basic ...
The Linked Neighbour List (LNL) method for fast off-lattice Monte Carlo simulations of fluids
Mazzeo, M. D.; Ricci, M.; Zannoni, C.
2010-03-01
We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.
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…
Monte Carlo methods for flux expansion solutions of transport problems
International Nuclear Information System (INIS)
Spanier, J.
1999-01-01
Adaptive Monte Carlo methods, based on the use of either correlated sampling or importance sampling, to obtain global solutions to certain transport problems have recently been described. The resulting learning algorithms are capable of achieving geometric convergence when applied to the estimation of a finite number of coefficients in a flux expansion representation of the global solution. However, because of the nonphysical nature of the random walk simulations needed to perform importance sampling, conventional transport estimators and source sampling techniques require modification to be used successfully in conjunction with such flux expansion methods. It is shown how these problems can be overcome. First, the traditional path length estimators in wide use in particle transport simulations are generalized to include rather general detector functions (which, in this application, are the individual basis functions chosen for the flus expansion). Second, it is shown how to sample from the signed probabilities that arise as source density functions in these applications, without destroying the zero variance property needed to ensure geometric convergence to zero error
Seriation in paleontological data using markov chain Monte Carlo methods.
Directory of Open Access Journals (Sweden)
Kai Puolamäki
2006-02-01
Full Text Available Given a collection of fossil sites with data about the taxa that occur in each site, the task in biochronology is to find good estimates for the ages or ordering of sites. We describe a full probabilistic model for fossil data. The parameters of the model are natural: the ordering of the sites, the origination and extinction times for each taxon, and the probabilities of different types of errors. We show that the posterior distributions of these parameters can be estimated reliably by using Markov chain Monte Carlo techniques. The posterior distributions of the model parameters can be used to answer many different questions about the data, including seriation (finding the best ordering of the sites and outlier detection. We demonstrate the usefulness of the model and estimation method on synthetic data and on real data on large late Cenozoic mammals. As an example, for the sites with large number of occurrences of common genera, our methods give orderings, whose correlation with geochronologic ages is 0.95.
Tyagi, Neelam; Bose, Abhijit; Chetty, Indrin J
2004-09-01
We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1 x 10(8) or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8 x 10(8) histories. For a smaller number of histories (1 x 10(8)) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1 x 10(8) histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy.
International Nuclear Information System (INIS)
Tyagi, Neelam; Bose, Abhijit; Chetty, Indrin J.
2004-01-01
We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1x10 8 or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8x10 8 histories. For a smaller number of histories (1x10 8 ) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1x10 8 histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy
Usefulness of the Monte Carlo method in reliability calculations
International Nuclear Information System (INIS)
Lanore, J.M.; Kalli, H.
1977-01-01
Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels
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.
Research of pulse formation neutron detector efficiency by Monte Carlo method
International Nuclear Information System (INIS)
Zhang Jianmin; Deng Li; Xie Zhongsheng; Yu Weidong; Zhong Zhenqian
2001-01-01
A study on detection efficiency of the neutron detector used in oil logging by Monte Carlo method is presented. Detection efficiency of the thermal and epithermal neutron detectors used in oil logging was calculated by Monte Carlo method using the MCNP code. The calculation results were satisfactory
Safety assessment of infrastructures using a new Bayesian Monte Carlo method
Rajabali Nejad, Mohammadreza; Demirbilek, Z.
2011-01-01
A recently developed Bayesian Monte Carlo (BMC) method and its application to safety assessment of structures are described in this paper. We use a one-dimensional BMC method that was proposed in 2009 by Rajabalinejad in order to develop a weighted logical dependence between successive Monte Carlo
Directory of Open Access Journals (Sweden)
Timothy J Kyng
2014-03-01
Full Text Available The economic valuation of complex financial contracts is often done using Monte-Carlo simulation. We show how to implement this approach using Excel. We discuss Monte-Carlo evaluation for standard single asset European options and then demonstrate how the basic ideas may be extended to evaluate options with exotic multi-asset multi-period features. Single asset option evaluation becomes a special case. We use a typical Executive Stock Option to motivate the discussion, which we analyse using novel theory developed in our previous works. We demonstrate the simulation of the multivariate normal distribution and the multivariate Log-Normal distribution using the Cholesky Square Root of a covariance matrix for replicating the correlation structure in the multi-asset, multi period simulation required for estimating the economic value of the contract. We do this in the standard Black Scholes framework with constant parameters. Excel implementation provides many pedagogical merits due to its relative transparency and simplicity for students. This approach also has relevance to industry due to the widespread use of Excel by practitioners and for graduates who may desire to work in the finance industry. This allows students to be able to price complex financial contracts for which an analytic approach is intractable.
Implementation of mathematical phantom of hand and forearm in GEANT4 Monte Carlo code
International Nuclear Information System (INIS)
Pessanha, Paula Rocha; Queiroz Filho, Pedro Pacheco de; Santos, Denison de Souza
2014-01-01
In this work, the implementation of a hand and forearm Geant4 phantom code, for further evaluation of occupational exposure of ends of the radionuclides decay manipulated during procedures involving the use of injection syringe. The simulation model offered by Geant4 includes a full set of features, with the reconstruction of trajectories, geometries and physical models. For this work, the values calculated in the simulation are compared with the measurements rates by thermoluminescent dosimeters (TLDs) in physical phantom REMAB®. From the analysis of the data obtained through simulation and experimentation, of the 14 points studied, there was a discrepancy of only 8.2% of kerma values found, and these figures are considered compatible. The geometric phantom implemented in Geant4 Monte Carlo code was validated and can be used later for the evaluation of doses at ends
Doerner, Edgardo; Caprile, Paola
2017-12-01
To present the implementation of a new option for parallel processing of the EGSnrc Monte Carlo system using the OpenMP API, as an alternative to the provided method based on the use of a batch queuing system (BQS). The parallel solution presented, called OMP_EGS, makes use of OpenMP features to control the workload distribution between the compute units. These features were inserted into the original EGSnrc source code through properly defined macros. In order to validate the platform, the possibility of producing results in exact agreement with the serial implementation was assessed. The performance of OMP_EGS was evaluated against the BQS method, in terms of parallel speedup and efficiency. As the OpenMP features can be activated or deactivated depending on the compilation options, the implementation of the platform allowed the direct recovery of the original serial implementation. The validation tests showed that OMP_EGS was able to reproduce the exact same results as the serial implementation. The performance and scalability tests showed that OMP_EGS is a better alternative than the EGSnrc BQS parallel implementation, both in terms of runtime and parallel efficiency. The presented solution has several advantages over the BQS-based parallel implementation available for the EGSnrc system. One of the main advantages is that, in contrast to the BQS alternative, it can be implemented using different compilers and operative systems, which turns it into a compact and portable solution that can be used on a wide range of working environments. It does not introduce artifacts on the simulated distributions, as it only handles the distribution of work among the available computing resources and it proved to have a better performance. © 2017 American Association of Physicists in Medicine.
Implementation of GPU accelerated SPECT reconstruction with Monte Carlo-based scatter correction.
Bexelius, Tobias; Sohlberg, Antti
2018-03-21
Statistical SPECT reconstruction can be very time-consuming especially when compensations for collimator and detector response, attenuation, and scatter are included in the reconstruction. This work proposes an accelerated SPECT reconstruction algorithm based on graphics processing unit (GPU) processing. Ordered subset expectation maximization (OSEM) algorithm with CT-based attenuation modelling, depth-dependent Gaussian convolution-based collimator-detector response modelling, and Monte Carlo-based scatter compensation was implemented using OpenCL. The OpenCL implementation was compared against the existing multi-threaded OSEM implementation running on a central processing unit (CPU) in terms of scatter-to-primary ratios, standardized uptake values (SUVs), and processing speed using mathematical phantoms and clinical multi-bed bone SPECT/CT studies. The difference in scatter-to-primary ratios, visual appearance, and SUVs between GPU and CPU implementations was minor. On the other hand, at its best, the GPU implementation was noticed to be 24 times faster than the multi-threaded CPU version on a normal 128 × 128 matrix size 3 bed bone SPECT/CT data set when compensations for collimator and detector response, attenuation, and scatter were included. GPU SPECT reconstructions show great promise as an every day clinical reconstruction tool.
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...
DEFF Research Database (Denmark)
Hey, Jody; Nielsen, Rasmus
2007-01-01
Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint...
A Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
Mean and standard deviation values, as well as probability density function of ground surface responses due to the dislocation are computed. Based on analytical and numerical calculation of dislocation, two approaches of Monte Carlo simulations are proposed. Various comparisons are examined to illustrate the capability ...
A Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
Dislocation modelling of an earthquake fault is of great importance due to the fact that ground surface response may be predicted by the model. 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 ...
International Nuclear Information System (INIS)
Wagner, John C.; Mosher, Scott W.; Evans, Thomas M.; Peplow, Douglas E.; Turner, John A.
2010-01-01
This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform real commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the gold standard for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method, which
International Nuclear Information System (INIS)
Wagner, J.C.; Mosher, S.W.; Evans, T.M.; Peplow, D.E.; Turner, J.A.
2010-01-01
This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method
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.
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.
Theory and applications of the fission matrix method for continuous-energy Monte Carlo
International Nuclear Information System (INIS)
Carney, Sean; Brown, Forrest; Kiedrowski, Brian; Martin, William
2014-01-01
Highlights: • The fission matrix method is implemented into the MCNP Monte Carlo code. • Eigenfunctions and eigenvalues of power distributions are shown and studied. • Source convergence acceleration is demonstrated for a fuel storage vault problem. • Forward flux eigenmodes and relative uncertainties are shown for a reactor problem. • Eigenmodes expansions are performed during source convergence for a reactor problem. - Abstract: The fission matrix method can be used to provide estimates of the fundamental mode fission distribution, the dominance ratio, the eigenvalue spectrum, and higher mode forward and adjoint eigenfunctions of the fission distribution. It can also be used to accelerate the convergence of power method iterations and to provide basis functions for higher-order perturbation theory. The higher-mode fission sources can be used to determine higher-mode forward fluxes and tallies, and work is underway to provide higher-mode adjoint-weighted fluxes and tallies. These aspects of the method are here both theoretically justified and demonstrated, and then used to investigate fundamental properties of the transport equation for a continuous-energy physics treatment. Implementation into the MCNP6 Monte Carlo code is also discussed, including a sparse representation of the fission matrix, which permits much larger and more accurate representations. Properties of the calculated eigenvalue spectrum of a 2D PWR problem are discussed: for a fine enough mesh and a sufficient degree of sampling, the spectrum both converges and has a negligible imaginary component. Calculation of the fundamental mode of the fission matrix for a fuel storage vault problem shows how convergence can be accelerated by over a factor of ten given a flat initial distribution. Forward fluxes and the relative uncertainties for a 2D PWR are shown, both of which qualitatively agree with expectation. Lastly, eigenmode expansions are performed during source convergence of the 2D PWR
Energy Technology Data Exchange (ETDEWEB)
Martin-Bragado, Ignacio, E-mail: ignacio.martin@imdea.org [IMDEA Materials Institute, C/ Eric Kandel 2, 28906 Getafe, Madrid (Spain); Abujas, J.; Galindo, P.L.; Pizarro, J. [Departamento de Ingeniería Informática, Universidad de Cádiz, Puerto Real, Cádiz (Spain)
2015-06-01
An adaptation of the synchronous parallel Kinetic Monte Carlo (spKMC) algorithm developed by Martinez et al. (2008) to the existing KMC code MMonCa (Martin-Bragado et al. 2013) is presented in this work. Two cases, general enough to provide an idea of the current state-of-the-art in parallel KMC, are presented: Object KMC simulations of the evolution of damage in irradiated iron, and Lattice KMC simulations of epitaxial regrowth of amorphized silicon. The results allow us to state that (a) the parallel overhead is critical, and severely degrades the performance of the simulator when it is comparable to the CPU time consumed per event, (b) the balance between domains is important, but not critical, (c) the algorithm and its implementation are correct and (d) further improvements are needed for spKMC to become a general, all-working solution for KMC simulations.
Gamma ray energy loss spectra simulation in NaI detectors with the Monte Carlo method
International Nuclear Information System (INIS)
Vieira, W.J.
1982-01-01
With the aim of studying and applying the Monte Carlo method, a computer code was developed to calculate the pulse height spectra and detector efficiencies for gamma rays incident on NaI (Tl) crystals. The basic detector processes in NaI (Tl) detectors are given together with an outline of Monte Carlo methods and a general review of relevant published works. A detailed description of the application of Monte Carlo methods to ν-ray detection in NaI (Tl) detectors is given. Comparisons are made with published, calculated and experimental, data. (Author) [pt
Directory of Open Access Journals (Sweden)
Jia-Cheng Yu
2018-02-01
Full Text Available A three-dimensional topography simulation of deep reactive ion etching (DRIE is developed based on the narrow band level set method for surface evolution and Monte Carlo method for flux distribution. The advanced level set method is implemented to simulate the time-related movements of etched surface. In the meanwhile, accelerated by ray tracing algorithm, the Monte Carlo method incorporates all dominant physical and chemical mechanisms such as ion-enhanced etching, ballistic transport, ion scattering, and sidewall passivation. The modified models of charged particles and neutral particles are epitomized to determine the contributions of etching rate. The effects such as scalloping effect and lag effect are investigated in simulations and experiments. Besides, the quantitative analyses are conducted to measure the simulation error. Finally, this simulator will be served as an accurate prediction tool for some MEMS fabrications.
International Nuclear Information System (INIS)
Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William
2013-01-01
Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC-Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC-Chem has been shown to be capable of running at the peta scale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exa scale platforms with a comparable level of efficiency is expected to be feasible. (authors)
Strings, Projected Entangled Pair States, and variational Monte Carlo methods
Schuch, Norbert; Wolf, Michael M.; Verstraete, Frank; Cirac, J. Ignacio
2007-01-01
We introduce string-bond states, a class of states obtained by placing strings of operators on a lattice, which encompasses the relevant states in Quantum Information. For string-bond states, expectation values of local observables can be computed efficiently using Monte Carlo sampling, making them suitable for a variational abgorithm which extends DMRG to higher dimensional and irregular systems. Numerical results demonstrate the applicability of these states to the simulation of many-body s...
Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.
2010-10-01
Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.
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...
The Calculation of Thermal Conductivities by Three Dimensional Direct Simulation Monte Carlo Method.
Zhao, Xin-Peng; Li, Zeng-Yao; Liu, He; Tao, Wen-Quan
2015-04-01
Three dimensional direct simulation Monte Carlo (DSMC) method with the variable soft sphere (VSS) collision model is implemented to solve the Boltzmann equation and to acquire the heat flux between two parallel plates (Fourier Flow). The gaseous thermal conductivity of nitrogen is derived based on the Fourier's law under local equilibrium condition at temperature from 270 to 1800 K and pressure from 0.5 to 100,000 Pa and compared with the experimental data and Eucken relation from Chapman and Enskog (CE) theory. It is concluded that the present results are consistent with the experimental data but much higher than those by Eucken relation especially at high temperature. The contribution of internal energy of molecule to the gaseous thermal conductivity becomes significant as increasing the temperature.
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.
Numerical solution of DGLAP equations using Laguerre polynomials expansion and Monte Carlo method.
Ghasempour Nesheli, A; Mirjalili, A; Yazdanpanah, M M
2016-01-01
We investigate the numerical solutions of the DGLAP evolution equations at the LO and NLO approximations, using the Laguerre polynomials expansion. The theoretical framework is based on Furmanski et al.'s articles. What makes the content of this paper different from other works, is that all calculations in the whole stages to extract the evolved parton distributions, are done numerically. The employed techniques to do the numerical solutions, based on Monte Carlo method, has this feature that all the results are obtained in a proper wall clock time by computer. The algorithms are implemented in FORTRAN and the employed coding ideas can be used in other numerical computations as well. Our results for the evolved parton densities are in good agreement with some phenomenological models. They also indicate better behavior with respect to the results of similar numerical calculations.
Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues
International Nuclear Information System (INIS)
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
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.
A. Zellner (Arnold); L. Bauwens (Luc); H.K. van Dijk (Herman)
1988-01-01
textabstractBayesian procedures for specification analysis or diagnostic checking of modeling assumptions for structural equations of econometric models are developed and applied using Monte Carlo numerical methods. Checks on the validity of identifying restrictions, exogeneity assumptions and other
Petersen, Jeremy; Tichy, Jason; Wawrzyniak, Geoffrey; Richon, Karen
2014-01-01
The James Webb Space Telescope will be launched into a highly elliptical orbit that does not possess sufficient energy to achieve a proper Sun-Earth L2 libration point orbit. Three mid-course correction (MCC) maneuvers are planned to rectify the energy deficit: MCC-1a, MCC-1b, and MCC-2. To validate the propellant budget and trajectory design methods, a set of Monte Carlo analyses that incorporate MCC maneuver modeling and execution are employed. The first analysis focuses on the effects of launch vehicle injection errors on the magnitude of MCC-1a. The second on the spread of potential V based on the performance of the propulsion system as applied to all three MCC maneuvers. The final highlights the slight, but notable, contribution of the attitude thrusters during each MCC maneuver. Given the possible variations in these three scenarios, the trajectory design methods are determined to be robust to errors in the modeling of the flight system.
Review of Monte Carlo methods for particle multiplicity evaluation
International Nuclear Information System (INIS)
Armesto, Nestor
2005-01-01
I present a brief review of the existing models for particle multiplicity evaluation in heavy ion collisions which are at our disposal in the form of Monte Carlo simulators. Models are classified according to the physical mechanisms with which they try to describe the different stages of a high-energy collision between heavy nuclei. A comparison of predictions, as available at the beginning of year 2000, for multiplicities in central AuAu collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and PbPb collisions at the CERN Large Hadron Collider (LHC) is provided
International Nuclear Information System (INIS)
Ramos M, D.; Yera S, Y.; Lopez B, G. M.; Acosta R, N.; Vergara G, A.
2014-08-01
This work is based on the determination of the detection efficiency of 125 I and 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 131 I and 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)
International Nuclear Information System (INIS)
Yamamoto, Toshihiro
2014-01-01
Highlights: • The cross power spectral density in ADS has correlated and uncorrelated components. • A frequency domain Monte Carlo method to calculate the uncorrelated one is developed. • The method solves the Fourier transformed transport equation. • The method uses complex-valued weights to solve the equation. • The new method reproduces well the CPSDs calculated with time domain MC method. - Abstract: In an accelerator driven system (ADS), pulsed spallation neutrons are injected at a constant frequency. The cross power spectral density (CPSD), which can be used for monitoring the subcriticality of the ADS, is composed of the correlated and uncorrelated components. The uncorrelated component is described by a series of the Dirac delta functions that occur at the integer multiples of the pulse repetition frequency. In the present paper, a Monte Carlo method to solve the Fourier transformed neutron transport equation with a periodically pulsed neutron source term has been developed to obtain the CPSD in ADSs. Since the Fourier transformed flux is a complex-valued quantity, the Monte Carlo method introduces complex-valued weights to solve the Fourier transformed equation. The Monte Carlo algorithm used in this paper is similar to the one that was developed by the author of this paper to calculate the neutron noise caused by cross section perturbations. The newly-developed Monte Carlo algorithm is benchmarked to the conventional time domain Monte Carlo simulation technique. The CPSDs are obtained both with the newly-developed frequency domain Monte Carlo method and the conventional time domain Monte Carlo method for a one-dimensional infinite slab. The CPSDs obtained with the frequency domain Monte Carlo method agree well with those with the time domain method. The higher order mode effects on the CPSD in an ADS with a periodically pulsed neutron source are discussed
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.
International Nuclear Information System (INIS)
Ureba, A.; Palma, B. A.; Leal, A.
2011-01-01
Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.
Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement
Directory of Open Access Journals (Sweden)
Joko Siswantoro
2014-01-01
Full Text Available Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.
Siswantoro, Joko; Prabuwono, Anton Satria; Abdullah, Azizi; Idrus, Bahari
2014-01-01
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
Parallel implementation of the Monte Carlo transport code EGS4 on the hypercube
International Nuclear Information System (INIS)
Kirk, B.L.; Azmy, Y.Y.; Gabriel, T.A.; Fu, C.Y.
1991-01-01
Monte Carlo transport codes are commonly used in the study of particle interactions. The CALOR89 code system is a combination of several Monte Carlo transport and analysis programs. In order to produce good results, a typical Monte Carlo run will have to produce many particle histories. On a single processor computer, the transport calculation can take a huge amount of time. However, if the transport of particles were divided among several processors in a multiprocessor machine, the time can be drastically reduced
The calculation of neutron flux using Monte Carlo method
Günay, Mehtap; Bardakçı, Hilal
2017-09-01
In this study, a hybrid reactor system was designed by using 99-95% Li20Sn80 + 1-5% RG-Pu, 99-95% Li20Sn80 + 1-5% RG-PuF4, and 99-95% Li20Sn80 + 1-5% RG-PuO2 fluids, ENDF/B-VII.0 evaluated nuclear data library and 9Cr2WVTa structural material. The fluids were used in the liquid first wall, liquid second wall (blanket) and shield zones of a fusion-fission hybrid reactor system. The neutron flux was calculated according to the mixture components, radial, energy spectrum in the designed hybrid reactor system for the selected fluids, library and structural material. Three-dimensional nucleonic calculations were performed using the most recent version MCNPX-2.7.0 the Monte Carlo code.
Simulation of thermochromotographic processes by the Monte-Carlo method
International Nuclear Information System (INIS)
Zvara, I.
1983-01-01
A simplified microscopic model is proposed for the gas adsorption thermochromatography in open columns with laminar flow of the carrier gas. This model describes the downstream migration of a sample molecule as a rather small number of some effective random displacements and sequences of adsorption-desorption events that occur without changing the coordinates. The relevant probability density distributions are thereby derived. Based on this model, a computer program has been developed for simulating thermochromatographic zone profiles by employing the Monte-Carlo technique. The program is versatile in accounting for a wide range of experimental conditions and for treating various properties of the species to be separated. Some results of these simulations are given to demonstrate the influence of several parameters on the zone profile
International Nuclear Information System (INIS)
Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.
2009-01-01
In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)
International Nuclear Information System (INIS)
Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.
2008-01-01
In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)
Markov chain Monte Carlo methods for state-space models with point process observations.
Yuan, Ke; Girolami, Mark; Niranjan, Mahesan
2012-06-01
This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations. We quantified the efficiencies of these MCMC methods on synthetic data, and our results suggest that the Reimannian manifold Hamiltonian Monte Carlo method offers the best performance. We further compared such a method with a previously tested variational Bayes method on two experimental data sets. Results indicate similar performance on the large data sets and superior performance on small ones. The work offers an extensive suite of MCMC algorithms evaluated on an important class of models for physiological signal analysis.
Implementation of the P barANDA Planar-GEM tracking detector in Monte Carlo simulations
Divani Veis, Nazila; Ehret, Andre; Firoozabadi, Mohammad M.; Karabowicz, Radoslaw; Maas, Frank; Saito, Nami; Saito, Takehiko R.; Voss, Bernd; PANDA Gem-Tracker Subgroup
2018-02-01
The P barANDA experiment at FAIR will be performed to investigate different aspects of hadron physics using anti-proton beams interacting with a fixed nuclear target. The experimental setup consists of a complex series of detector components covering a large solid angle. A detector with a gaseous active media equipped with gas electron multiplier (GEM) technique will be employed to measure tracks of charged particles at forward direction in order to achieve a high momentum resolution. In this work, a full setup of the GEM tracking detector has been implemented in the P barANDA Monte Carlo simulation package (PandaRoot) based on the current technical and conceptual design, and the expected performance of the P barANDA GEM-tracking detector has been investigated. Furthermore, material-budget studies in terms of the radiation length of the P barANDA GEM-tracking detector have been made in order to investigate the effect of the detector materials and its associated structures to particle measurements.
Zaidi, H; Morel, Christian
1998-01-01
This paper describes the implementation of the Eidolon Monte Carlo program designed to simulate fully three-dimensional (3D) cylindrical positron tomographs on a MIMD parallel architecture. The original code was written in Objective-C and developed under the NeXTSTEP development environment. Different steps involved in porting the software on a parallel architecture based on PowerPC 604 processors running under AIX 4.1 are presented. Basic aspects and strategies of running Monte Carlo calculations on parallel computers are described. A linear decrease of the computing time was achieved with the number of computing nodes. The improved time performances resulting from parallelisation of the Monte Carlo calculations makes it an attractive tool for modelling photon transport in 3D positron tomography. The parallelisation paradigm used in this work is independent from the chosen parallel architecture
SU-E-T-277: Raystation Electron Monte Carlo Commissioning and Clinical Implementation
Energy Technology Data Exchange (ETDEWEB)
Allen, C; Sansourekidou, P; Pavord, D [Health-quest, Poughkeepsie, NY (United States)
2014-06-01
Purpose: To evaluate the Raystation v4.0 Electron Monte Carlo algorithm for an Elekta Infinity linear accelerator and commission for clinical use. Methods: A total of 199 tests were performed (75 Export and Documentation, 20 PDD, 30 Profiles, 4 Obliquity, 10 Inhomogeneity, 55 MU Accuracy, and 5 Grid and Particle History). Export and documentation tests were performed with respect to MOSAIQ (Elekta AB) and RadCalc (Lifeline Software Inc). Mechanical jaw parameters and cutout magnifications were verified. PDD and profiles for open cones and cutouts were extracted and compared with water tank measurements. Obliquity and inhomogeneity for bone and air calculations were compared to film dosimetry. MU calculations for open cones and cutouts were performed and compared to both RadCalc and simple hand calculations. Grid size and particle histories were evaluated per energy for statistical uncertainty performance. Acceptability was categorized as follows: performs as expected, negligible impact on workflow, marginal impact, critical impact or safety concern, and catastrophic impact of safety concern. Results: Overall results are: 88.8% perform as expected, 10.2% negligible, 2.0% marginal, 0% critical and 0% catastrophic. Results per test category are as follows: Export and Documentation: 100% perform as expected, PDD: 100% perform as expected, Profiles: 66.7% perform as expected, 33.3% negligible, Obliquity: 100% marginal, Inhomogeneity 50% perform as expected, 50% negligible, MU Accuracy: 100% perform as expected, Grid and particle histories: 100% negligible. To achieve distributions with satisfactory smoothness level, 5,000,000 particle histories were used. Calculation time was approximately 1 hour. Conclusion: Raystation electron Monte Carlo is acceptable for clinical use. All of the issues encountered have acceptable workarounds. Known issues were reported to Raysearch and will be resolved in upcoming releases.
SU-E-T-277: Raystation Electron Monte Carlo Commissioning and Clinical Implementation
International Nuclear Information System (INIS)
Allen, C; Sansourekidou, P; Pavord, D
2014-01-01
Purpose: To evaluate the Raystation v4.0 Electron Monte Carlo algorithm for an Elekta Infinity linear accelerator and commission for clinical use. Methods: A total of 199 tests were performed (75 Export and Documentation, 20 PDD, 30 Profiles, 4 Obliquity, 10 Inhomogeneity, 55 MU Accuracy, and 5 Grid and Particle History). Export and documentation tests were performed with respect to MOSAIQ (Elekta AB) and RadCalc (Lifeline Software Inc). Mechanical jaw parameters and cutout magnifications were verified. PDD and profiles for open cones and cutouts were extracted and compared with water tank measurements. Obliquity and inhomogeneity for bone and air calculations were compared to film dosimetry. MU calculations for open cones and cutouts were performed and compared to both RadCalc and simple hand calculations. Grid size and particle histories were evaluated per energy for statistical uncertainty performance. Acceptability was categorized as follows: performs as expected, negligible impact on workflow, marginal impact, critical impact or safety concern, and catastrophic impact of safety concern. Results: Overall results are: 88.8% perform as expected, 10.2% negligible, 2.0% marginal, 0% critical and 0% catastrophic. Results per test category are as follows: Export and Documentation: 100% perform as expected, PDD: 100% perform as expected, Profiles: 66.7% perform as expected, 33.3% negligible, Obliquity: 100% marginal, Inhomogeneity 50% perform as expected, 50% negligible, MU Accuracy: 100% perform as expected, Grid and particle histories: 100% negligible. To achieve distributions with satisfactory smoothness level, 5,000,000 particle histories were used. Calculation time was approximately 1 hour. Conclusion: Raystation electron Monte Carlo is acceptable for clinical use. All of the issues encountered have acceptable workarounds. Known issues were reported to Raysearch and will be resolved in upcoming releases
Directory of Open Access Journals (Sweden)
M. J. Werner
2011-02-01
Full Text Available Data assimilation is routinely employed in meteorology, engineering and computer sciences to optimally combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts, than achieved by ignoring data uncertainties. Earthquake forecasting, too, suffers from measurement errors and partial model information and may thus gain significantly from data assimilation. We present perhaps the first fully implementable data assimilation method for earthquake forecasts generated by a point-process model of seismicity. We test the method on a synthetic and pedagogical example of a renewal process observed in noise, which is relevant for the seismic gap hypothesis, models of characteristic earthquakes and recurrence statistics of large quakes inferred from paleoseismic data records. To address the non-Gaussian statistics of earthquakes, we use sequential Monte Carlo methods, a set of flexible simulation-based methods for recursively estimating arbitrary posterior distributions. We perform extensive numerical simulations to demonstrate the feasibility and benefits of forecasting earthquakes based on data assimilation.
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.
Implementation of a Monte Carlo algorithm for neutron transport on a massively parallel SIMD machine
International Nuclear Information System (INIS)
Baker, R.S.
1993-01-01
We present some results from the recent adaptation of a vectorized Monte Carlo algorithm to a massively parallel architecture. The performance of the algorithm on a single processor Cray Y-MP and a Thinking Machine Corporations CM-2 and CM-200 is compared for several test problems. The results show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when the algorithms are applied to realistic problems which require extensive variance reduction. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well. (orig.)
Automating methods to improve precision in Monte-Carlo event generation for particle colliders
Energy Technology Data Exchange (ETDEWEB)
Gleisberg, Tanju
2008-07-01
The subject of this thesis was the development of tools for the automated calculation of exact matrix elements, which are a key for the systematic improvement of precision and confidence for theoretical predictions. Part I of this thesis concentrates on the calculations of cross sections at tree level. A number of extensions have been implemented in the matrix element generator AMEGIC++, namely new interaction models such as effective loop-induced couplings of the Higgs boson with massless gauge bosons, required for a number of channels for the Higgs boson search at LHC and anomalous gauge couplings, parameterizing a number of models beyond th SM. Further a special treatment to deal with complicated decay chains of heavy particles has been constructed. A significant effort went into the implementation of methods to push the limits on particle multiplicities. Two recursive methods have been implemented, the Cachazo-Svrcek-Witten recursion and the colour dressed Berends-Giele recursion. For the latter the new module COMIX has been added to the SHERPA framework. The Monte-Carlo phase space integration techniques have been completely revised, which led to significantly reduced statistical error estimates when calculating cross sections and a greatly improved unweighting efficiency for the event generation. Special integration methods have been developed to cope with the newly accessible final states. The event generation framework SHERPA directly benefits from those new developments, improving the precision and the efficiency. Part II was addressed to the automation of QCD calculations at next-to-leading order. A code has been developed, that, for the first time fully automates the real correction part of a NLO calculation. To calculate the correction for a m-parton process obeying the Catani-Seymour dipole subtraction method the following components are provided: 1. the corresponding m+1-parton tree level matrix elements, 2. a number dipole subtraction terms to remove
Application of Monte Carlo methods for dead time calculations for counting measurements
International Nuclear Information System (INIS)
Henniger, Juergen; Jakobi, Christoph
2015-01-01
From a mathematical point of view Monte Carlo methods are the numerical solution of certain integrals and integral equations using a random experiment. There are several advantages compared to the classical stepwise integration. The time required for computing increases for multi-dimensional problems only moderately with increasing dimension. The only requirements for the integral kernel are its capability of being integrated in the considered integration area and the possibility of an algorithmic representation. These are the important properties of Monte Carlo methods that allow the application in every scientific area. Besides that Monte Carlo algorithms are often more intuitive than conventional numerical integration methods. The contribution demonstrates these facts using the example of dead time corrections for counting measurements.
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
Revisiting the hybrid quantum Monte Carlo method for Hubbard and electron-phonon models
Beyl, Stefan; Goth, Florian; Assaad, Fakher F.
2018-02-01
A unique feature of the hybrid quantum Monte Carlo (HQMC) method is the potential to simulate negative sign free lattice fermion models with subcubic scaling in system size. Here we will revisit the algorithm for various models. We will show that for the Hubbard model the HQMC suffers from ergodicity issues and unbounded forces in the effective action. Solutions to these issues can be found in terms of a complexification of the auxiliary fields. This implementation of the HQMC that does not attempt to regularize the fermionic matrix so as to circumvent the aforementioned singularities does not outperform single spin flip determinantal methods with cubic scaling. On the other hand we will argue that there is a set of models for which the HQMC is very efficient. This class is characterized by effective actions free of singularities. Using the Majorana representation, we show that models such as the Su-Schrieffer-Heeger Hamiltonian at half filling and on a bipartite lattice belong to this class. For this specific model subcubic scaling is achieved.
Energy Technology Data Exchange (ETDEWEB)
Kiedrowski, Brian C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-03-11
The goals of this project are to develop Monte Carlo radiation transport methods and simulation software for engineering analysis that are robust, efficient and easy to use; and provide computational resources to assess and improve the predictive capability of radiation transport methods and nuclear data.
International Nuclear Information System (INIS)
Androsenko, A.A.; Androsenko, P.A.; Kagalenko, I.Eh.; Mironovich, Yu.N.
1992-01-01
Consideration is given of a technique and algorithms of constructing neutron trajectories in the Monte-Carlo method taking into account the data on adjoint transport equation solution. When simulating the transport part of transfer kernel the use is made of piecewise-linear approximation of free path length density along the particle motion direction. The approach has been implemented in programs within the framework of the BRAND code system. The importance is calculated in the multigroup P 1 -approximation within the framework of the DD-30 code system. The efficiency of the developed computation technique is demonstrated by means of solution of two model problems. 4 refs.; 2 tabs
External individual monitoring: experiments and simulations using Monte Carlo Method
International Nuclear Information System (INIS)
Guimaraes, Carla da Costa
2005-01-01
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 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 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 2 :NaCl compound estimated by simulation to be 2,20(25) mm -1 was introduced. Conversion coefficients C 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 constructed with low
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.
Quasi-Monte Carlo methods: applications to modeling of light transport in tissue
Schafer, Steven A.
1996-05-01
Monte Carlo modeling of light propagation can accurately predict the distribution of light in scattering materials. A drawback of Monte Carlo methods is that they converge inversely with the square root of the number of iterations. Theoretical considerations suggest that convergence which scales inversely with the first power of the number of iterations is possible. We have previously shown that one can obtain at least a portion of that improvement by using van der Corput sequences in place of a conventional pseudo-random number generator. Here, we present our further analysis, and show that quasi-Monte Carlo methods do have limited applicability to light scattering problems. We also discuss potential improvements which may increase the applicability.
A new method to assess the statistical convergence of monte carlo solutions
International Nuclear Information System (INIS)
Forster, R.A.
1991-01-01
Accurate Monte Carlo confidence intervals (CIs), which are formed with an estimated mean and an estimated standard deviation, can only be created when the number of particle histories N becomes large enough so that the central limit theorem can be applied. The Monte Carlo user has a limited number of marginal methods to assess the fulfillment of this condition, such as statistical error reduction proportional to 1/√N with error magnitude guidelines and third and fourth moment estimators. A new method is presented here to assess the statistical convergence of Monte Carlo solutions by analyzing the shape of the empirical probability density function (PDF) of history scores. Related work in this area includes the derivation of analytic score distributions for a two-state Monte Carlo problem. Score distribution histograms have been generated to determine when a small number of histories accounts for a large fraction of the result. This summary describes initial studies of empirical Monte Carlo history score PDFs created from score histograms of particle transport simulations. 7 refs., 1 fig
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.
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Larsen, Edward W.
2004-01-01
The equations of nonlinear, time-dependent radiative transfer are known to yield the equilibrium diffusion equation as the leading-order solution of an asymptotic analysis when the mean-free path and mean-free time of a photon become small. We apply this same analysis to the Fleck-Cummings, Carter-Forest, and N'kaoua Monte Carlo approximations for grey (frequency-independent) radiative transfer. Although Monte Carlo simulation usually does not require the discretizations found in deterministic transport techniques, Monte Carlo methods for radiative transfer require a time discretization due to the nonlinearities of the problem. If an asymptotic analysis of the equations used by a particular Monte Carlo method yields an accurate time-discretized version of the equilibrium diffusion equation, the method should generate accurate solutions if a time discretization is chosen that resolves temperature changes, even if the time steps are much larger than the mean-free time of a photon. This analysis is of interest because in many radiative transfer problems, it is a practical necessity to use time steps that are large compared to a mean-free time. Our asymptotic analysis shows that: (i) the N'kaoua method has the equilibrium diffusion limit, (ii) the Carter-Forest method has the equilibrium diffusion limit if the material temperature change during a time step is small, and (iii) the Fleck-Cummings method does not have the equilibrium diffusion limit. We include numerical results that verify our theoretical predictions
The codes WAV3BDY and WAV4BDY and the variational Monte Carlo method
International Nuclear Information System (INIS)
Schiavilla, R.
1987-01-01
A description of the codes WAV3BDY and WAV4BDY, which generate the variational ground state wave functions of the A=3 and 4 nuclei, is given, followed by a discussion of the Monte Carlo integration technique, which is used to calculate expectation values and transition amplitudes of operators, and for whose implementation WAV3BDY and WAV4BDY are well suited
Numerical solution to the problem of criticality by Monte Carlo method
International Nuclear Information System (INIS)
Kyncl, J.
1989-04-01
A new method of numerical solution of the criticality problem is proposed. The method is based on the results of the Krein and Rutman theory. Monte Carlo method is used and the random process is chosen in such a way that the differences between results obtained and exact ones would be arbitrarily small. The method can be applied for both analogous and nonanalogous random processes. (author). 8 refs
Research on reactor physics analysis method based on Monte Carlo homogenization
International Nuclear Information System (INIS)
Ye Zhimin; Zhang Peng
2014-01-01
In order to meet the demand of nuclear energy market in the future, many new concepts of nuclear energy systems has been put forward. The traditional deterministic neutronics analysis method has been challenged in two aspects: one is the ability of generic geometry processing; the other is the multi-spectrum applicability of the multigroup cross section libraries. Due to its strong geometry modeling capability and the application of continuous energy cross section libraries, the Monte Carlo method has been widely used in reactor physics calculations, and more and more researches on Monte Carlo method has been carried out. Neutronics-thermal hydraulics coupling analysis based on Monte Carlo method has been realized. However, it still faces the problems of long computation time and slow convergence which make it not applicable to the reactor core fuel management simulations. Drawn from the deterministic core analysis method, a new two-step core analysis scheme is proposed in this work. Firstly, Monte Carlo simulations are performed for assembly, and the assembly homogenized multi-group cross sections are tallied at the same time. Secondly, the core diffusion calculations can be done with these multigroup cross sections. The new scheme can achieve high efficiency while maintain acceptable precision, so it can be used as an effective tool for the design and analysis of innovative nuclear energy systems. Numeric tests have been done in this work to verify the new scheme. (authors)
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.
Directory of Open Access Journals (Sweden)
D. Lu
2017-09-01
Full Text Available 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.
A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions
Liang, Yihao; Xing, Xiangjun; Li, Yaohang
2017-06-01
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures, and adopts the sequential updating scheme of Metropolis algorithm. It makes no approximation in the computation of energy, and reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We further use this method to simulate primitive model electrolytes, and measure very precisely all ion-ion pair correlation functions at high concentrations. From these data, we extract the renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.
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...... a tendency to foetal loss is heritable. The data possess a complicated dependence structure due to replicate pregnancies for the same woman, and a given family pattern. We conclude that a tendency to foetal loss is heritable. The model is of great interest in genetic epidemiology, because it considers both...
Power Analysis for Complex Mediational Designs Using Monte Carlo Methods
Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.
2010-01-01
Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…
A variance-reduced electrothermal Monte Carlo method for semiconductor device simulation
Energy Technology Data Exchange (ETDEWEB)
Muscato, Orazio; Di Stefano, Vincenza [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) Leibniz-Institut im Forschungsverbund Berlin e.V., Berlin (Germany)
2012-11-01
This paper is concerned with electron transport and heat generation in semiconductor devices. An improved version of the electrothermal Monte Carlo method is presented. This modification has better approximation properties due to reduced statistical fluctuations. The corresponding transport equations are provided and results of numerical experiments are presented.
Tarim, Urkiye Akar; Ozmutlu, Emin N.; Yalcin, Sezai; Gundogdu, Ozcan; Bradley, D. A.; Gurler, Orhan
2017-11-01
A Monte Carlo method was developed to investigate radiation shielding properties of bismuth borate glass. The mass attenuation coefficients and half-value layer parameters were determined for different fractional amounts of Bi2O3 in the glass samples for the 356, 662, 1173 and 1332 keV photon energies. A comparison of the theoretical and experimental attenuation coefficients is presented.
Generation of triangulated random surfaces by the Monte Carlo method in the grand canonical ensemble
International Nuclear Information System (INIS)
Zmushko, V.V.; Migdal, A.A.
1987-01-01
A model of triangulated random surfaces which is the discrete analog of the Polyakov string is considered. An algorithm is proposed which enables one to study the model by the Monte Carlo method in the grand canonical ensemble. Preliminary results on the determination of the critical index γ are presented
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"…
Analysis of the distribution of X-ray characteristic production using the Monte Carlo methods
International Nuclear Information System (INIS)
Del Giorgio, Marcelo; Brizuela, Horacio; Riveros, J.A.
1987-01-01
The Monte Carlo method has been applied for the simulation of electron trajectories in a bulk sample, and therefore for the distribution of signals produced in an electron microprobe. Results for the function φ(ρz) are compared with experimental data. Some conclusions are drawn with respect to the parameters involved in the gaussian model. (Author) [es
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...
Thomas B. Lynch; Jeffrey H. Gove
2014-01-01
The typical "double counting" application of the mirage method of boundary correction cannot be applied to sampling systems such as critical height sampling (CHS) that are based on a Monte Carlo sample of a tree (or debris) attribute because the critical height (or other random attribute) sampled from a mirage point is generally not equal to the critical...
User's guide to Monte Carlo methods for evaluating path integrals
Westbroek, Marise J. E.; King, Peter R.; Vvedensky, Dimitri D.; Dürr, Stephan
2018-04-01
We give an introduction to the calculation of path integrals on a lattice, with the quantum harmonic oscillator as an example. In addition to providing an explicit computational setup and corresponding pseudocode, we pay particular attention to the existence of autocorrelations and the calculation of reliable errors. The over-relaxation technique is presented as a way to counter strong autocorrelations. The simulation methods can be extended to compute observables for path integrals in other settings.
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...
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)
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
Energy Technology Data Exchange (ETDEWEB)
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)
A hybrid transport-diffusion method for Monte Carlo radiative-transfer simulations
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Urbatsch, Todd J.; Evans, Thomas M.; Buksas, Michael W.
2007-01-01
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Monte Carlo particle-transport simulations in diffusive media. If standard Monte Carlo is used in such media, particle histories will consist of many small steps, resulting in a computationally expensive calculation. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many small Monte Carlo steps, thus increasing the efficiency of the simulation. In addition, given that DDMC is based on a diffusion equation, it should produce accurate solutions if used judiciously. In practice, DDMC is combined with standard Monte Carlo to form a hybrid transport-diffusion method that can accurately simulate problems with both diffusive and non-diffusive regions. In this paper, we extend previously developed DDMC techniques in several ways that improve the accuracy and utility of DDMC for nonlinear, time-dependent, radiative-transfer calculations. The use of DDMC in these types of problems is advantageous since, due to the underlying linearizations, optically thick regions appear to be diffusive. First, we employ a diffusion equation that is discretized in space but is continuous in time. Not only is this methodology theoretically more accurate than temporally discretized DDMC techniques, but it also has the benefit that a particle's time is always known. Thus, there is no ambiguity regarding what time to assign a particle that leaves an optically thick region (where DDMC is used) and begins transporting by standard Monte Carlo in an optically thin region. Also, we treat the interface between optically thick and optically thin regions with an improved method, based on the asymptotic diffusion-limit boundary condition, that can produce accurate results regardless of the angular distribution of the incident Monte Carlo particles. Finally, we develop a technique for estimating radiation momentum deposition during the
CAD-based Monte Carlo automatic modeling method based on primitive solid
International Nuclear Information System (INIS)
Wang, Dong; Song, Jing; Yu, Shengpeng; Long, Pengcheng; Wang, Yongliang
2016-01-01
Highlights: • We develop a method which bi-convert between CAD model and primitive solid. • This method was improved from convert method between CAD model and half space. • This method was test by ITER model and validated the correctness and efficiency. • This method was integrated in SuperMC which could model for SuperMC and Geant4. - Abstract: Monte Carlo method has been widely used in nuclear design and analysis, where geometries are described with primitive solids. However, it is time consuming and error prone to describe a primitive solid geometry, especially for a complicated model. To reuse the abundant existed CAD models and conveniently model with CAD modeling tools, an automatic modeling method for accurate prompt modeling between CAD model and primitive solid is needed. An automatic modeling method for Monte Carlo geometry described by primitive solid was developed which could bi-convert between CAD model and Monte Carlo geometry represented by primitive solids. While converting from CAD model to primitive solid model, the CAD model was decomposed into several convex solid sets, and then corresponding primitive solids were generated and exported. While converting from primitive solid model to the CAD model, the basic primitive solids were created and related operation was done. This method was integrated in the SuperMC and was benchmarked with ITER benchmark model. The correctness and efficiency of this method were demonstrated.
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.
Acceptance and implementation of a system of planning computerized based on Monte Carlo
International Nuclear Information System (INIS)
Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.
2013-01-01
It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)
TMD PDFs. A Monte Carlo implementation for the sea quark distribution
Energy Technology Data Exchange (ETDEWEB)
Hautmann, F. [Oxford Univ. (United Kingdom). Dept. of Theoretical Physics; Hentschinski, M. [Univ. Autonoma de Madrid (Spain). Dept. Fisica Teorica UAM/CSIC; Jung, H. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); European Organization for Nuclear Research (CERN), Geneva (Switzerland)
2012-05-15
This article gives an introduction to transverse momentum dependent (TMD) parton distribution functions and their use in shower Monte Carlo event generators for high-energy hadron collisions, and describes recent progress in the treatment of sea quark effects within a TMD parton-shower framework.
Evaluation of Investment Risks in CBA with Monte Carlo Method
Directory of Open Access Journals (Sweden)
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.
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.
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.
Using Monte Carlo Methods for the Valuation of Intangible Assets in Sports Economics
Directory of Open Access Journals (Sweden)
Majewski Sebastian
2017-12-01
Full Text Available This paper indicates the possibilities of using Monte Carlo simulations methods in players’ performance rights value monitoring. The authors have formulated a hypothesis that connects Monte Carlo methods (MC and econometric models of the player’s life cycle that could give club managers another source of information for the decision process. The MC method in finance is usually used to value the option price on the basis of assumed distribution of price changes. In this approach, the method was used to determine future the hypothetical value of footballers’ performance rights. Using econometric models of the player’s life cycle we could observe and analyse the phase in the life cycle of a football player and determine volatility.
Investigation of Compton scattering correction methods in cardiac SPECT by Monte Carlo simulations
International Nuclear Information System (INIS)
Silva, A.M. Marques da; Furlan, A.M.; Robilotta, C.C.
2001-01-01
The goal of this work was the use of Monte Carlo simulations to investigate the effects of two scattering correction methods: dual energy window (DEW) and dual photopeak window (DPW), in quantitative cardiac SPECT reconstruction. MCAT torso-cardiac phantom, with 99m Tc and non-uniform attenuation map was simulated. Two different photopeak windows were evaluated in DEW method: 15% and 20%. Two 10% wide subwindows centered symmetrically within the photopeak were used in DPW method. Iterative ML-EM reconstruction with modified projector-backprojector for attenuation correction was applied. Results indicated that the choice of the scattering and photopeak windows determines the correction accuracy. For the 15% window, fitted scatter fraction gives better results than k = 0.5. For the 20% window, DPW is the best method, but it requires parameters estimation using Monte Carlo simulations. (author)
A recursive Monte Carlo method for estimating importance functions in deep penetration problems
International Nuclear Information System (INIS)
Goldstein, M.
1980-04-01
A pratical recursive Monte Carlo method for estimating the importance function distribution, aimed at importance sampling for the solution of deep penetration problems in three-dimensional systems, was developed. The efficiency of the recursive method was investigated for sample problems including one- and two-dimensional, monoenergetic and and multigroup problems, as well as for a practical deep-penetration problem with streaming. The results of the recursive Monte Carlo calculations agree fairly well with Ssub(n) results. It is concluded that the recursive Monte Carlo method promises to become a universal method for estimating the importance function distribution for the solution of deep-penetration problems, in all kinds of systems: for many systems the recursive method is likely to be more efficient than previously existing methods; for three-dimensional systems it is the first method that can estimate the importance function with the accuracy required for an efficient solution based on importance sampling of neutron deep-penetration problems in those systems
Makai, Mihály; Szatmáry, Zoltán
2013-01-01
In the Monte Carlo (MC) method statistical noise is usually present. Statistical noise may become dominant in the calculation of a distribution, usually by iteration, but is less Important in calculating integrals. The subject of the present work is the role of statistical noise in iterations involving stochastic simulation (MC method). Convergence is checked by comparing two consecutive solutions in the iteration. The statistical noise may randomize or pervert the convergence. We study the p...
Generation of gamma-ray streaming kernels through cylindrical ducts via Monte Carlo method
International Nuclear Information System (INIS)
Kim, Dong Su
1992-02-01
Since radiation streaming through penetrations is often the critical consideration in protection against exposure of personnel in a nuclear facility, it has been of great concern in radiation shielding design and analysis. Several methods have been developed and applied to the analysis of the radiation streaming in the past such as ray analysis method, single scattering method, albedo method, and Monte Carlo method. But they may be used for order-of-magnitude calculations and where sufficient margin is available, except for the Monte Carlo method which is accurate but requires a lot of computing time. This study developed a Monte Carlo method and constructed a data library of solutions using the Monte Carlo method for radiation streaming through a straight cylindrical duct in concrete walls of a broad, mono-directional, monoenergetic gamma-ray beam of unit intensity. The solution named as plane streaming kernel is the average dose rate at duct outlet and was evaluated for 20 source energies from 0 to 10 MeV, 36 source incident angles from 0 to 70 degrees, 5 duct radii from 10 to 30 cm, and 16 wall thicknesses from 0 to 100 cm. It was demonstrated that average dose rate due to an isotropic point source at arbitrary positions can be well approximated using the plane streaming kernel with acceptable error. Thus, the library of the plane streaming kernels can be used for the accurate and efficient analysis of radiation streaming through a straight cylindrical duct in concrete walls due to arbitrary distributions of gamma-ray sources
Protocol design and implementation using formal methods
van Sinderen, Marten J.; Ferreira Pires, Luis; Pires, L.F.; Vissers, C.A.
1992-01-01
This paper reports on a number of formal methods that support correct protocol design and implementation. These methods are placed in the framework of a design methodology for distributed systems that was studied and developed within the ESPRIT II Lotosphere project (2304). The paper focuses on
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
equivalent problems nevertheless requires the possibility to modify the macroscopic cross-sections, and we use the work of Kuijper, van der Marck and Hogenbirk to define group-wise macroscopic cross-sections in MCNP [1]. The method is illustrated in this paper at a frequency of 1 Hz, for which only the real......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...... stationary dynamic calculations, the presented method does not require any modification of the Monte Carlo code....
A computer programme for perturbation calculations by correlated sampling Monte Carlo method
International Nuclear Information System (INIS)
Nakagawa, Masayuki; Asaoka, Takumi
1979-11-01
The perturbation calculation method by the Monte Carlo approach has been improved with use of correlated sampling technique and incorporated into the general purpose Monte Carlo code MORSE. The two methods, similar flight path and identical flight path methods have been adopted for evaluating the reactivity change. In the conventional perturbation method, only the first order term of the perturbation formula was taken into account but the present method can estimate up to the second order term. Through the Monte Carlo games, neutrons passing through perturbed regions in both unperturbed and perturbed systems are followed in a way to have a strong correlation for not only the first but the second generation. In this article, the perturbation formula is derived from the integral transport equation to estimate the reactivity change. The calculation flow and input/output format are explained for the user of the present computer programme. In Appendices, the FORTRAN list of main subroutines modified from the original code is shown in addition to an output example. (author)
Energy Technology Data Exchange (ETDEWEB)
Zychor, I. [Soltan Inst. for Nuclear Studies, Otwock-Swierk (Poland)
1994-12-31
The application of a Monte Carlo method to study a transport in matter of electron and photon beams is presented, especially for electrons with energies up to 18 MeV. The SHOWME Monte Carlo code, a modified version of GEANT3 code, was used on the CONVEX C3210 computer at Swierk. It was assumed that an electron beam is mono directional and monoenergetic. Arbitrary user-defined, complex geometries made of any element or material can be used in calculation. All principal phenomena occurring when electron beam penetrates the matter are taken into account. The use of calculation for a therapeutic electron beam collimation is presented. (author). 20 refs, 29 figs.
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
Spectral method and its high performance implementation
Wu, Zedong
2014-01-01
We have presented a new method that can be dispersion free and unconditionally stable. Thus the computational cost and memory requirement will be reduced a lot. Based on this feature, we have implemented this algorithm on GPU based CUDA for the anisotropic Reverse time migration. There is almost no communication between CPU and GPU. For the prestack wavefield extrapolation, it can combine all the shots together to migration. However, it requires to solve a bigger dimensional problem and more meory which can\\'t fit into one GPU cards. In this situation, we implement it based on domain decomposition method and MPI for distributed memory system.
An improved method for storing and retrieving tabulated data in a scalar Monte Carlo code
International Nuclear Information System (INIS)
Hollenbach, D.F.; Reynolds, K.H.; Dodds, H.L.; Landers, N.F.; Petrie, L.M.
1990-01-01
The KENO-Va code is a production-level criticality safety code used to calculate the k eff of a system. The code is stochastic in nature, using a Monte Carlo algorithm to track individual particles one at a time through the system. The advent of computers with vector processors has generated an interest in improving KENO-Va to take advantage of the potential speed-up associated with these new processors. Unfortunately, the original Monte Carlo algorithm and method of storing and retrieving cross-section data is not adaptable to vector processing. This paper discusses an alternate method for storing and retrieving data that not only is readily vectorizable but also improves the efficiency of the current scalar code
Sink strength simulations using the Monte Carlo method: Applied to spherical traps
Ahlgren, T.; Bukonte, L.
2017-12-01
The sink strength is an important parameter for the mean-field rate equations to simulate temporal changes in the micro-structure of materials. However, there are noteworthy discrepancies between sink strengths obtained by the Monte Carlo and analytical methods. In this study, we show the reasons for these differences. We present the equations to estimate the statistical error for sink strength calculations and show the way to determine the sink strengths for multiple traps. We develop a novel, very fast Monte Carlo method to obtain sink strengths. The results show that, in addition to the well-known sink strength dependence of the trap concentration, trap radius and the total sink strength, the sink strength also depends on the defect diffusion jump length and the total trap volume fraction. Taking these factors into account, allows us to obtain a very accurate analytic expression for the sink strength of spherical traps.
Calculation of the Feynman integrals by means of the Monte Carlo method
International Nuclear Information System (INIS)
Filinov, V.S.
1986-01-01
The Monte Carlo method (the Metropolis algorithm), which is employed extensively in lattice gauge theories and quantum mechanics, was applicable only to the euclidean version of the Feynman path integrals, i.e. it was valid for evaluating the integrals of real functions. In the present work the Monte Carlo method is extended to the evaluation of the integrals of complex-valued functions. The Feynman path integrals representing the time-dependent Green function of the one-dimensional non-stationary Schroedinger equation have been calculated for the harmonic oscillator and the particle motion in barrier- and well-type potential fields. The numerical results are in reasonable agreement with the analytical estimates, in spite of the presence of singularities in the Green functions. (orig.)
Implicit Monte Carlo methods and non-equilibrium Marshak wave radiative transport
International Nuclear Information System (INIS)
Lynch, J.E.
1985-01-01
Two enhancements to the Fleck implicit Monte Carlo method for radiative transport are described, for use in transparent and opaque media respectively. The first introduces a spectral mean cross section, which applies to pseudoscattering in transparent regions with a high frequency incident spectrum. The second provides a simple Monte Carlo random walk method for opaque regions, without the need for a supplementary diffusion equation formulation. A time-dependent transport Marshak wave problem of radiative transfer, in which a non-equilibrium condition exists between the radiation and material energy fields, is then solved. These results are compared to published benchmark solutions and to new discrete ordinate S-N results, for both spatially integrated radiation-material energies versus time and to new spatially dependent temperature profiles. Multigroup opacities, which are independent of both temperature and frequency, are used in addition to a material specific heat which is proportional to the cube of the temperature. 7 refs., 4 figs
Path-integral Monte Carlo method for the local Z2 Berry phase.
Motoyama, Yuichi; Todo, Synge
2013-02-01
We present a loop cluster algorithm Monte Carlo method for calculating the local Z(2) Berry phase of the quantum spin models. The Berry connection, which is given as the inner product of two ground states with different local twist angles, is expressed as a Monte Carlo average on the worldlines with fixed spin configurations at the imaginary-time boundaries. The "complex weight problem" caused by the local twist is solved by adopting the meron cluster algorithm. We present the results of simulation on the antiferromagnetic Heisenberg model on an out-of-phase bond-alternating ladder to demonstrate that our method successfully detects the change in the valence bond pattern at the quantum phase transition point. We also propose that the gauge-fixed local Berry connection can be an effective tool to estimate precisely the quantum critical point.
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.
Evaluation of equivalent doses in 18F PET/CT using the Monte Carlo method with MCNPX code
International Nuclear Information System (INIS)
Belinato, Walmir; Santos, William Souza; Perini, Ana Paula; Neves, Lucio Pereira; Souza, Divanizia N.
2017-01-01
The present work used the Monte Carlo method (MMC), specifically the Monte Carlo NParticle - MCNPX, to simulate the interaction of radiation involving photons and particles, such as positrons and electrons, with virtual adult anthropomorphic simulators on PET / CT scans and to determine absorbed and equivalent doses in adult male and female patients
Efficient data management techniques implemented in the Karlsruhe Monte Carlo code KAMCCO
International Nuclear Information System (INIS)
Arnecke, G.; Borgwaldt, H.; Brandl, V.; Lalovic, M.
1974-01-01
The Karlsruhe Monte Carlo Code KAMCCO is a forward neutron transport code with an eigenfunction and a fixed source option, including time-dependence. A continuous energy model is combined with a detailed representation of neutron cross sections, based on linear interpolation, Breit-Wigner resonances and probability tables. All input is processed into densely packed, dynamically addressed parameter fields and networks of pointers (addresses). Estimation routines are decoupled from random walk and analyze a storage region with sample records. This technique leads to fast execution with moderate storage requirements and without any I/O-operations except in the input and output stages. 7 references. (U.S.)
Application of Monte Carlo method in determination of secondary characteristic X radiation in XFA
International Nuclear Information System (INIS)
Roubicek, P.
1982-01-01
Secondary characteristic radiation is excited by primary radiation from the X-ray tube and by secondary radiation of other elements so that excitations of several orders result. The Monte Carlo method was used to consider all these possibilities and the resulting flux of characteristic radiation was simulated for samples of silicate raw materials. A comparison of the results of these computations with experiments allows to determine the effect of sample preparation on the characteristic radiation flux. (M.D.)
BRAND program complex for neutron-physical experiment simulation by the Monte-Carlo method
International Nuclear Information System (INIS)
Androsenko, A.A.; Androsenko, P.A.
1984-01-01
Possibilities of the BRAND program complex for neutron and γ-radiation transport simulation by the Monte-Carlo method are described in short. The complex includes the following modules: geometric module, source module, detector module, modules of simulation of a vector of particle motion direction after interaction and a free path. The complex is written in the FORTRAN langauage and realized by the BESM-6 computer
Calculation of ion stopping in dense plasma by the Monte-Carlo method
Kodanova, S. K.; Ramazanov, T. S.; Issanova, M. K.; Bastykova, N. Kh; Golyatina, R. I.; Maiorov, S. A.
2018-01-01
In this paper, the Monte-Carlo method was used to simulate ion trajectories in dense plasma of inertial confinement fusion. The results of computer simulation are numerical data on the dynamic characteristics, such as energy loss, penetration depth, the effective range of particles, stopping and straggling. By the results of the work the program of three-dimensional visualization of ion trajectories in dense plasma of inertial confinement fusion was developed.
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.
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.
R and D on automatic modeling methods for Monte Carlo codes FLUKA
International Nuclear Information System (INIS)
Wang Dianxi; Hu Liqin; Wang Guozhong; Zhao Zijia; Nie Fanzhi; Wu Yican; Long Pengcheng
2013-01-01
FLUKA is a fully integrated particle physics Monte Carlo simulation package. It is necessary to create the geometry models before calculation. However, it is time- consuming and error-prone to describe the geometry models manually. This study developed an automatic modeling method which could automatically convert computer-aided design (CAD) geometry models into FLUKA models. The conversion program was integrated into CAD/image-based automatic modeling program for nuclear and radiation transport simulation (MCAM). Its correctness has been demonstrated. (authors)
Investigation of Multicritical Phenomena in ANNNI Model by Monte Carlo Methods
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
Heath, Emily; Seuntjens, Jan; Sheikh-Bagheri, Daryoush
2004-01-01
In this work we dosimetrically evaluated the clinical implementation of a commercial Monte Carlo treatment planning software (PEREGRINE, North American Scientific, Cranberry Township, PA) intended for quality assurance (QA) of intensity modulated radiation therapy treatment plans. Dose profiles calculated in homogeneous and heterogeneous phantoms using this system were compared to both measurements and simulations using the EGSnrc Monte Carlo code for the 6 MV beam of a Varian CL21EX linear accelerator. For simple jaw-defined fields, calculations agree within 2% of the dose at d max with measurements in homogeneous phantoms with the exception of the buildup region where the calculations overestimate the dose by up to 8%. In heterogeneous lung and bone phantoms the agreement is within 3%, on average, up to 5% for a 1x1 cm 2 field. We tested two consecutive implementations of the MLC model. After matching the calculated and measured MLC leakage, simulations of static and dynamic MLC-defined fields using the most recent MLC model agreed to within 2% with measurements
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.
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.
An Implementation of the Frequency Matching Method
DEFF Research Database (Denmark)
Lange, Katrine; Frydendall, Jan; Hansen, Thomas Mejer
During the last decade multiple-point statistics has become in-creasingly popular as a tool for incorporating complex prior infor-mation when solving inverse problems in geosciences. A variety of methods have been proposed but often the implementation of these is not straightforward. One of these......During the last decade multiple-point statistics has become in-creasingly popular as a tool for incorporating complex prior infor-mation when solving inverse problems in geosciences. A variety of methods have been proposed but often the implementation of these is not straightforward. One...... of these methods is the recently proposed Frequency Matching method to compute the maximum a posteriori model of an inverse problem where multiple-point statistics, learned from a training image, is used to formulate a closed form expression for an a priori probability density function. This paper discusses...... aspects of the implementation of the Fre-quency Matching method and the techniques adopted to make it com-putationally feasible also for large-scale inverse problems. The source code is publicly available at GitHub and this paper also provides an example of how to apply the Frequency Matching method...
International Nuclear Information System (INIS)
Balos, Y.; Timurtuerkan, E. B.; Yorulmaz, N.; Bozkurt, A.
2009-01-01
In determining the radiation background of a region, it is important to carry out environmental radioactivity measurements in soil, water and air, to determine their contribution to the dose rate in air. This study aims to determine the dose conversion coefficients (in {nGy/h}/{Bq/kg}) that are used to convert radionuclide activity concentration in soil (in Bq/kg) to dose rate in air (in nGy/h) using the Monte Carlo method. An isotropic source which emits monoenergetic photons is assumed to be uniformly distributed in soil. The doses released by photons in organs and tissues of a mathematical phantom are determined by the Monte Carlo package MCNP. The organ doses are then used, together with radiation weighting factors and organ weighting factors, to obtain effective doses for the energy range of 100 keV-3 MeV, which in turn are used to determine the dose rates in air per unit of specific activity.
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
Implementation and the choice of evaluation methods
DEFF Research Database (Denmark)
Flyvbjerg, Bent
1984-01-01
with an approach founded more in phenomenology and social science. The role of analytical methods is viewed very differently in the two paradigms as in the conception of the policy process in general. Allthough analytical methods have come to play a prominent (and often dominant) role in transportation evaluation...... the programmed paradigm. By emphasizing the importance of the process of social interaction and subordinating analysis to this process, the adaptive paradigm reduces the likelihood of analytical methods narrowing and biasing implementation. To fulfil this subordinate role and to aid social interaction...
International Nuclear Information System (INIS)
Sharma, Anupam; Long, Lyle N.
2004-01-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented
Sharma, Anupam; Long, Lyle N.
2004-10-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.
On computing efficiency of Monte-Carlo methods in solving Dirichlet's problem
International Nuclear Information System (INIS)
Androsenko, P.A.; Lomtev, V.L.
1990-01-01
Algorithms of Monte-Carlo method based on boundary random walks, application of Fredholm's series and intended for the solution of stationary and non-stationary boundary value Dirichlet's problem for the Laplace's equation are presented. Description is made of the code systems BRANDB, BRANDBT and BRANDF realizing the above algorithms and allowing the calculation of values of solution and its derivatives for three-dimensional geometrical systems. The results of computing experiments on solving a number of problems in the system with convex and non-convex geometries are presented, conclusions are made on the computing efficiency of the methods involved. 13 refs.; 4 figs.; 2 tabs
International Nuclear Information System (INIS)
David, Mariano Gazineu; Salata, Camila; Almeida, Carlos Eduardo
2014-01-01
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 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)
International Nuclear Information System (INIS)
Noack, K.
1982-01-01
The perturbation source method may be a powerful Monte-Carlo means to calculate small effects in a particle field. In a preceding paper we have formulated this methos in inhomogeneous linear particle transport problems describing the particle fields by solutions of Fredholm integral equations and have derived formulae for the second moment of the difference event point estimator. In the present paper we analyse the general structure of its variance, point out the variance peculiarities, discuss the dependence on certain transport games and on generation procedures of the auxiliary particles and draw conclusions to improve this method
Geant4 based Monte Carlo simulation for verifying the modified sum-peak method.
Aso, Tsukasa; Ogata, Yoshimune; Makino, Ryuta
2018-04-01
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 60 Co 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.
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.
Shield calculation of research reactor IAN-R1 by Monte Carlo method
International Nuclear Information System (INIS)
Puerta, J.; Buritica, D.A.; Cardenas, H.F.
1993-01-01
Using the Monte Carlo Method a computer program has been developed to simulate the neutron radiation transport and determine the basic parameters in shielding calculations. The program has been tested comparing dose conversion factors with kerma factors issued by the international commission on radiation units and measurements (ICRU) on its report (No 26 of 1987) giving errors less than ten percent showing the goodness of the method. The program computer transmitted backscattered and absorbed flux on energy less on each collision. when neutrons are produced by region source with knowing energy; results are given like conversion factors and reliability of this program allows a wide application on radiological and medical physics
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.
Subtraction method for NLO corrections in Monte-Carlo event generators for leptoproduction
International Nuclear Information System (INIS)
Collins, J.
2000-01-01
In the case of the gluon-fusion process in deep-inelastic leptoproduction, I explicitly show how to incorporate NLO corrections in a Monte-Carlo event generator by a subtraction method. I calculate the parton densities to be used by the event generator in terms of MS-bar densities. The method is generalizable. A particular motivation for treating the gluon-fusion process is to treat diffractive deep-inelastic scattering properly, since in diffractive scattering the gluon density dominates the quark densities. I also propose a modified algorithm for treating parton kinematics in event generators; the new algorithm results in much simpler formulae for the NLO corrections. (author)
The adaptation method in the Monte Carlo simulation for computed tomography
Energy Technology Data Exchange (ETDEWEB)
Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)
2015-06-15
The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
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.
The adaptation method in the Monte Carlo simulation for computed tomography
Directory of Open Access Journals (Sweden)
Hyounggun Lee
2015-06-01
Full Text Available The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT. To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA and a human-like voxel phantom (KTMAN-2 (Los Alamos National Laboratory, Los Alamos, NM, USA. For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations—assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
Simulação do equilíbrio: o método de Monte Carlo Equilibrium simulation: Monte Carlo method
Directory of Open Access Journals (Sweden)
Alejandro López-Castillo
2007-01-01
Full Text Available We make several simulations using the Monte Carlo method in order to obtain the chemical equilibrium for several first-order reactions and one second-order reaction. We study several direct, reverse and consecutive reactions. These simulations show the fluctuations and relaxation time and help to understand the solution of the corresponding differential equations of chemical kinetics. This work was done in an undergraduate physical chemistry course at UNIFIEO.
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...
Vectorization of continuous energy Monte Carlo method for neutron transport calculation
International Nuclear Information System (INIS)
Mori, Takamasa; Nakagawa, Masayuki; Sasaki, Makoto
1992-01-01
The vectorization method was studied to achieve a high efficiency for the precise physics model used in the continuous energy Monte Carlo method. The collision analysis task was reconstructed on the basis of the event based algorithm, and the stack-driven zone-selection method was applied to the vectorization of random walk simulation. These methods were installed into the vectorized continuous energy MVP code for general purpose uses. Performance of the present method was evaluated by comparison with conventional scalar codes VIM and MCNP for two typical problems. The MVP code achieved a vectorization ratio of more than 95% and a computation speed faster by a factor of 8∼22 on the FACOM VP-2600 vector supercomputer compared with the conventional scalar codes. (author)
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.
A Monte-Carlo study of landmines detection by neutron backscattering method
International Nuclear Information System (INIS)
Maucec, M.; De Meijer, R.J.
2000-01-01
The use of Monte-Carlo simulations for modelling a simplified landmine detector system with a 252 Cf- neutron source is presented in this contribution. Different aspects and variety of external conditions, affecting the localisation and identification of a buried suspicious object (such as landmine) have been tested. Results of sensitivity calculations confirm that the landmine detection methods, based on the analysis of the backscattered neutron radiation can be applicable in higher density formations, with the mass fraction of present pore-water <15 %. (author)
Determination of partial structure factors by reverse Monte Carlo modelling—a test of the method
Gruner, S.; Akinlade, O.; Hoyer, W.
2006-05-01
The reverse Monte Carlo modelling technique is commonly applied for the analysis of the atomic structure of liquid and amorphous substances. In particular, partial structure factors of multi-component alloys can be determined using this method. In the present study we use the example of the liquid Ni33Ge67 alloy to investigate the impact of different input data on the result of RMC modelling. It was found that even two experimental structure factors might be sufficient to obtain reliable partial structure factors if the contrast between them is high enough.
Reliability analysis of PWR thermohydraulic design by the Monte Carlo method
International Nuclear Information System (INIS)
Silva Junior, H.C. da; Berthoud, J.S.; Carajilescov, P.
1977-01-01
The operating power level of a PWR is limited by the occurence of DNB. Without affecting the safety and performance of the reactor, it is possible to admit failure of a certain number of core channels. The thermohydraulic design, however, is affect by a great number of uncertainties of deterministic or statistical nature. In the present work, the Monte Carlo method is applied to yield the probability that a number F of channels submitted to boiling crises will not exceed a number F* previously given. This probability is obtained as function of the reactor power level. (Author) [pt
The future of new calculation concepts in dosimetry based on the Monte Carlo Methods
International Nuclear Information System (INIS)
Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M.
2009-01-01
Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)
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.
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...
Application of direct simulation Monte Carlo method for analysis of AVLIS evaporation process
International Nuclear Information System (INIS)
Nishimura, Akihiko
1995-01-01
The computation code of the direct simulation Monte Carlo (DSMC) method was developed in order to analyze the atomic vapor evaporation in atomic vapor laser isotope separation (AVLIS). The atomic excitation temperatures of gadolinium atom were calculated for the model with five low lying states. Calculation results were compared with the experiments obtained by laser absorption spectroscopy. Two types of DSMC simulations which were different in inelastic collision procedure were carried out. It was concluded that the energy transfer was forbidden unless the total energy of the colliding atoms exceeds a threshold value. (author)
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...... equivalent problems nevertheless requires the possibility to modify the macroscopic cross-sections, and we use the work of Kuijper, van der Marck and Hogenbirk to define group-wise macroscopic cross-sections in MCNP [1]. The method is illustrated in this paper at a frequency of 1 Hz, for which only the real...
Monte-Carlo Method Python Library for dose distribution Calculation in Brachytherapy
International Nuclear Information System (INIS)
Randriantsizafy, R.D.; Ramanandraibe, M.J.; Raboanary, R.
2007-01-01
The Cs-137 Brachytherapy treatment is performed in Madagascar since 2005. Time treatment calculation for prescribed dose is made manually. Monte-Carlo Method Python library written at Madagascar INSTN is experimentally used to calculate the dose distribution on the tumour and around it. The first validation of the code was done by comparing the library curves with the Nucletron company curves. To reduce the duration of the calculation, a Grid of PC's is set up with listner patch run on each PC. The library will be used to modelize the dose distribution in the CT scan patient picture for individual and better accuracy time calculation for a prescribed dose.
Energy Technology Data Exchange (ETDEWEB)
Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.
2013-07-01
It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)
Monte Carlo method for polarized radiative transfer in gradient-index media
International Nuclear Information System (INIS)
Zhao, J.M.; Tan, J.Y.; Liu, L.H.
2015-01-01
Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer. - Highlights: • A Monte Carlo method for polarized radiative transfer in gradient index media. • Effect of curved ray paths on polarized radiative transfer is considered. • Importance of atmospheric refraction for polarized light transfer is demonstrated
Determination of the spatial response of neutron based analysers using a Monte Carlo based method
Tickner
2000-10-01
One of the principal advantages of using thermal neutron capture (TNC, also called prompt gamma neutron activation analysis or PGNAA) or neutron inelastic scattering (NIS) techniques for measuring elemental composition is the high penetrating power of both the incident neutrons and the resultant gamma-rays, which means that large sample volumes can be interrogated. Gauges based on these techniques are widely used in the mineral industry for on-line determination of the composition of bulk samples. However, attenuation of both neutrons and gamma-rays in the sample and geometric (source/detector distance) effects typically result in certain parts of the sample contributing more to the measured composition than others. In turn, this introduces errors in the determination of the composition of inhomogeneous samples. This paper discusses a combined Monte Carlo/analytical method for estimating the spatial response of a neutron gauge. Neutron propagation is handled using a Monte Carlo technique which allows an arbitrarily complex neutron source and gauge geometry to be specified. Gamma-ray production and detection is calculated analytically which leads to a dramatic increase in the efficiency of the method. As an example, the method is used to study ways of reducing the spatial sensitivity of on-belt composition measurements of cement raw meal.
Dosimetry of Beta-Emitting Radionuclides at the Tissular Level Using Monte Carlo Methods
International Nuclear Information System (INIS)
Coulot, J.; Lavielle, F.; Faggiano, A.; Bellon, N.; Aubert, B.; Schlumberger, M.; Ricard, M.
2005-01-01
Standard macroscopic methods used to assess the dose in nuclear medicine are limited to cases of homogeneous radionuclide distributions and provide dose estimations at the organ level. In a few applications, like radioimmunotherapy, the mean dose to an organ is not suitable to explain clinical observations, and knowledge of the dose at the tissular level is mandatory. Therefore, one must determine how particles lose their energy and what is the best way to represent tissues. The Monte Carlo method is appropriate to solve the problem of particle transport, but the question of the geometric representation of biology remains. In this paper, we describe a software (CLUSTER3D) that is able to build randomly biologically representative sphere cluster geometries using a statistical description of tissues. These geometries are then used by our Monte Carlo code called DOSE3D to perform particle transport. First results obtained on thyroid models highlight the need of cellular and tissular data to take into account actual radionuclide distributions in tissues. The flexibility and reliability of the method makes it a useful tool to study the energy deposition at various cellular and tissular levels in any configuration
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.
On solution to the problem of criticality by alternative Monte Carlo method
International Nuclear Information System (INIS)
Kyncl, J.
2005-03-01
The problem of criticality for the neutron transport equation is analyzed. The problem is transformed into an equivalent problem in a suitable set of complex functions, and the existence and uniqueness of its solution is demonstrated. The source iteration method is discussed. It is shown that the final result of the iterative process is strongly affected by the insufficient accuracy of the individual iterations. A modified method is suggested to circumvent this problem based on the theory of positive operators; the criticality problem is solved by the Monte Carlo method constructing special random process and variable so that the difference between the result and the true value can be arbitrarily small. The efficiency of this alternative method is analysed
On solution to the problem of criticality by alternative MONTE CARLO method
International Nuclear Information System (INIS)
Kyncl, J.
2005-01-01
The contribution deals with solution to the problem of criticality for neutron transport equation. The problem is transformed to equivalent one in a suitable set of complex functions and existence and uniqueness of its solution is shown. Then the source iteration method of the solution is discussed. It is pointed out that final result of iterative process is strongly affected by the fact that individual iterations are not computed with sufficient accuracy. To avoid this problem a modified method of the solution is suggested and presented. The modification is based on results of the theory of positive operators and problem of criticality is solved by Monte Carlo method constructing special random process and variable so that differences between results obtained and the exact ones would be arbitrarily small. Efficiency of this alternative method is analysed as well (Author)
International Nuclear Information System (INIS)
Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M.
2010-01-01
Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within ∼3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.
Energy Technology Data Exchange (ETDEWEB)
Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' ' Carlos Haya' ' , Avda. Carlos Haya s/n, E-29010 Malaga (Spain); Unidad de Radiofisica Hospitalaria, Hospital Xanit Internacional, Avda. de los Argonautas s/n, E-29630 Benalmadena (Malaga) (Spain); NCTeam, Strahlenklinik, Universitaetsklinikum Essen, Hufelandstr. 55, D-45122 Essen (Germany); Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)
2010-07-15
Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within {approx}3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.
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.
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...
Charged-particle thermonuclear reaction rates: I. Monte Carlo method and statistical distributions
International Nuclear Information System (INIS)
Longland, R.; Iliadis, C.; Champagne, A.E.; Newton, J.R.; Ugalde, C.; Coc, A.; Fitzgerald, R.
2010-01-01
A method based on Monte Carlo techniques is presented for evaluating thermonuclear reaction rates. We begin by reviewing commonly applied procedures and point out that reaction rates that have been reported up to now in the literature have no rigorous statistical meaning. Subsequently, we associate each nuclear physics quantity entering in the calculation of reaction rates with a specific probability density function, including Gaussian, lognormal and chi-squared distributions. Based on these probability density functions the total reaction rate is randomly sampled many times until the required statistical precision is achieved. This procedure results in a median (Monte Carlo) rate which agrees under certain conditions with the commonly reported recommended 'classical' rate. In addition, we present at each temperature a low rate and a high rate, corresponding to the 0.16 and 0.84 quantiles of the cumulative reaction rate distribution. These quantities are in general different from the statistically meaningless 'minimum' (or 'lower limit') and 'maximum' (or 'upper limit') reaction rates which are commonly reported. Furthermore, we approximate the output reaction rate probability density function by a lognormal distribution and present, at each temperature, the lognormal parameters μ and σ. The values of these quantities will be crucial for future Monte Carlo nucleosynthesis studies. Our new reaction rates, appropriate for bare nuclei in the laboratory, are tabulated in the second paper of this issue (Paper II). The nuclear physics input used to derive our reaction rates is presented in the third paper of this issue (Paper III). In the fourth paper of this issue (Paper IV) we compare our new reaction rates to previous results.
Implementation of SMED method in wood processing
Directory of Open Access Journals (Sweden)
Vukićević Milan R.
2007-01-01
Full Text Available The solution of problems in production is mainly tackled by the management based on the hardware component, i.e. by the introduction of work centres of recent generation. In this way, it ensures the continuity of quality reduced consumption of energy, humanization of work, etc. However, the interaction between technical-technological and organizational-economic aspects of production is neglected. This means that the new-generation equipment requires a modern approach to planning, organization, and management of production, as well as to economy of production. Consequently it is very important to ensure the implementation of modern organizational methods in wood processing. This paper deals with the problem of implementation of SMED method (SMED - Single Digit Minute Exchange of Die in the aim of rationalization of set-up-end-up operations. It is known that in the conditions of discontinuous production, set-up-end-up time is a significant limiting factor in the increase of flexibility of production systems.
Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Brown, F.
2007-01-01
Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)
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
Application of Monte Carlo method for dose calculation in thyroid follicle
International Nuclear Information System (INIS)
Silva, Frank Sinatra Gomes da
2008-02-01
The Monte Carlo method is an important tool to simulate radioactive particles interaction with biologic medium. The principal advantage of the method when compared with deterministic methods is the ability to simulate a complex geometry. Several computational codes use the Monte Carlo method to simulate the particles transport and they have the capacity to simulate energy deposition in models of organs and/or tissues, as well models of cells of human body. Thus, the calculation of the absorbed dose to thyroid's follicles (compound of colloid and follicles' cells) have a fundamental importance to dosimetry, because these cells are radiosensitive due to ionizing radiation exposition, in particular, exposition due to radioisotopes of iodine, because a great amount of radioiodine may be released into the environment in case of a nuclear accidents. In this case, the goal of this work was use the code of particles transport MNCP4C to calculate absorbed doses in models of thyroid's follicles, for Auger electrons, internal conversion electrons and beta particles, by iodine-131 and short-lived iodines (131, 132, 133, 134 e 135), with diameters varying from 30 to 500 μm. The results obtained from simulation with the MCNP4C code shown an average percentage of the 25% of total absorbed dose by colloid to iodine- 131 and 75% to short-lived iodine's. For follicular cells, this percentage was of 13% to iodine-131 and 87% to short-lived iodine's. The contributions from particles with low energies, like Auger and internal conversion electrons should not be neglected, to assessment the absorbed dose in cellular level. Agglomerative hierarchical clustering was used to compare doses obtained by codes MCNP4C, EPOTRAN, EGS4 and by deterministic methods. (author)
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.
Directory of Open Access Journals (Sweden)
Xingchu Gong
Full Text Available 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.
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.
International Nuclear Information System (INIS)
Meschede, Henning; Dunkelberg, Heiko; Stöhr, Fabian; Peesel, Ron-Hendrik; Hesselbach, Jens
2017-01-01
This paper investigates the use of renewable energies to supply hotels in island regions. The aim is to evaluate the effect of weather and occupancy fluctuations on the sensitivity of investment criteria. The sensitivity of the chosen energy system is examined using a Monte Carlo simulation considering stochastic weather data, occupancy rates and energy needs. For this purpose, algorithms based on measured data are developed and applied to a case study on the Canary Islands. The results underline that electricity use in hotels is by far the largest contributor to their overall energy cost. For the invested hotel on the Canary Islands, the optimal share of renewable electricity generation is found to be 63%, split into 67% photovoltaic and 33% wind power. Furthermore, a battery is used to balance the differences between day and night. It is found, that the results are sensitive to weather fluctuations as well as economic parameters to about the same degree. The results underline the risk caused by using reference time series for designing energy systems. The Monte Carlo method helps to define the mean of the annuity more precisely and to rate the risk of fluctuating weather and occupancy better. - Highlights: • An approach to generate synthetic weather data was pointed out. • A methodology to create synthetic energy demand data for hotels was developed. • The influence to the sensitivity of renewable energy systems was analysed. • Fluctuations in weather data have a greater impact on the economy than occupancy.
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.
Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot
International Nuclear Information System (INIS)
Wang Yongbo; Wu Huapeng; Handroos, Heikki
2011-01-01
This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has ten degrees of freedom (DOF), among which six DOF are contributed by the parallel mechanism and the rest are from the serial mechanism. In this paper, a kinematic error model which involves 54 unknown geometrical error parameters is developed for the proposed robot. Based on this error model, the mean values of the unknown parameters are statistically analyzed and estimated by means of Markov Chain Monte Carlo (MCMC) approach. The computer simulation is conducted by introducing random geometric errors and measurement poses which represent the corresponding real physical behaviors. The simulation results of the marginal posterior distributions of the estimated model parameters indicate that our method is reliable and robust.
Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot
Energy Technology Data Exchange (ETDEWEB)
Wang Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machine, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu Huapeng; Handroos, Heikki [Laboratory of Intelligent Machine, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)
2011-10-15
This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has ten degrees of freedom (DOF), among which six DOF are contributed by the parallel mechanism and the rest are from the serial mechanism. In this paper, a kinematic error model which involves 54 unknown geometrical error parameters is developed for the proposed robot. Based on this error model, the mean values of the unknown parameters are statistically analyzed and estimated by means of Markov Chain Monte Carlo (MCMC) approach. The computer simulation is conducted by introducing random geometric errors and measurement poses which represent the corresponding real physical behaviors. The simulation results of the marginal posterior distributions of the estimated model parameters indicate that our method is reliable and robust.
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.
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.
New one-flavor hybrid Monte Carlo simulation method for lattice fermions with γ5 hermiticity
International Nuclear Information System (INIS)
Ogawa, Kenji
2011-01-01
We propose a new method for Hybrid Monte Carlo (HMC) simulations with odd numbers of dynamical fermions on the lattice. It employs a different approach from polynomial or rational HMC. In this method, γ 5 hermiticity of the lattice Dirac operators is crucial and it can be applied to Wilson, domain-wall, and overlap fermions. We compare HMC simulations with two degenerate flavors and (1+1) degenerate flavors using optimal domain-wall fermions. The ratio of the efficiency, (number of accepted trajectories)/(simulation time), is about 3:2. The relation between pseudofermion action of chirally symmetric lattice fermions in four-dimensional (overlap) and five-dimensional (domain-wall) representation are also analyzed.
Reproduction of the coincidence effect in gamma ray spectrometry by using Monte Carlo method
International Nuclear Information System (INIS)
Park, S. H.; Kim, J. K.; Lee, S. H.
2001-01-01
Scintillation detector such as NaI(TI), or semiconductor detector, such as HPGe, are used for Measurement/Assessment of the radiation type and radiation activity. The measured energy spectrum are used for measuring the radiation type and activity. Corrections for true coincidence due to emit more than 2 photons at the same time and random coincidence due to measuring system when increasing of the radiation intensity. For accurate assessment, measurement with adequate measure system is performed, and corrections for coincidence are performed in the hardware aspect and software aspect. In general, there are limitations or difficulties in measurement of radiation assessment, computational simulation is instead used. In simulation, it has much advantages than measurement in technically, timely, and financially, it is widely used instead of measurement. In this study, the method to reproduce of the coincidence effect was proposed by using monte carlo method
Radiation dose performance in the triple-source CT based on a Monte Carlo method
Yang, Zhenyu; Zhao, Jun
2012-10-01
Multiple-source structure is promising in the development of computed tomography, for it could effectively eliminate motion artifacts in the cardiac scanning and other time-critical implementations with high temporal resolution. However, concerns about the dose performance shade this technique, as few reports on the evaluation of dose performance of multiple-source CT have been proposed for judgment. Our experiments focus on the dose performance of one specific multiple-source CT geometry, the triple-source CT scanner, whose theories and implementations have already been well-established and testified by our previous work. We have modeled the triple-source CT geometry with the help of EGSnrc Monte Carlo radiation transport code system, and simulated the CT examinations of a digital chest phantom with our modified version of the software, using x-ray spectrum according to the data of physical tube. Single-source CT geometry is also estimated and tested for evaluation and comparison. Absorbed dose of each organ is calculated according to its real physics characteristics. Results show that the absorbed radiation dose of organs with the triple-source CT is almost equal to that with the single-source CT system. As the advantage of temporal resolution, the triple-source CT would be a better choice in the x-ray cardiac examination.
Directory of Open Access Journals (Sweden)
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.
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.
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.
International Nuclear Information System (INIS)
Lee, Choonsik; Nagaoka, Tomoaki; Lee, Jai-Ki
2006-01-01
Japanese male and female tomographic phantoms, which have been developed for radio-frequency electromagnetic-field dosimetry, were implemented into multi-particle Monte Carlo transport code to evaluate realistic dose distribution in human body exposed to radiation field. Japanese tomographic phantoms, which were developed from the whole body magnetic resonance images of Japanese average adult male and female, were processed as follows to be implemented into general purpose multi-particle Monte Carlo code, MCNPX2.5. Original array size of Japanese male and female phantoms, 320 x 160 x 866 voxels and 320 x 160 x 804 voxels, respectively, were reduced into 320 x 160 x 433 voxels and 320 x 160 x 402 voxels due to the limitation of memory use in MCNPX2.5. The 3D voxel array of the phantoms were processed by using the built-in repeated structure algorithm, where the human anatomy was described by the repeated lattice of tiny cube containing the information of material composition and organ index number. Original phantom data were converted into ASCII file, which can be directly ported into the lattice card of MCNPX2.5 input deck by using in-house code. A total of 30 material compositions obtained from International Commission on Radiation Units and Measurement (ICRU) report 46 were assigned to 54 and 55 organs and tissues in the male and female phantoms, respectively, and imported into the material card of MCNPX2.5 along with the corresponding cross section data. Illustrative calculation of absorbed doses for 26 internal organs and effective dose were performed for idealized broad parallel photon and neutron beams in anterior-posterior irradiation geometry, which is typical for workers at nuclear power plant. The results were compared with the data from other Japanese and Caucasian tomographic phantom, and International Commission on Radiological Protection (ICRP) report 74. The further investigation of the difference in organ dose and effective dose among tomographic
Coherent-wave Monte Carlo method for simulating light propagation in tissue
Kraszewski, Maciej; Pluciński, Jerzy
2016-03-01
Simulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative transfer equation, allows to simulate only propagation of light averaged over the ensemble of turbid medium realizations. This makes them unuseful for simulating phenomena connected to coherence properties of light. We propose a new method for simulating propagation of coherent light (e.g. laser beam) in biological tissue, that we called Coherent-Wave Monte Carlo method. This method is based on direct computation of optical interaction between scatterers inside the random medium, what allows to reduce amount of memory and computation time required for simulation. We present the theoretical basis of the proposed method and its comparison with finite-difference methods for simulating light propagation in scattering media in Rayleigh approximation regime.
Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method
Directory of Open Access Journals (Sweden)
Muneki Yasuda
2018-04-01
Full Text Available The machine learning techniques for Markov random fields are fundamental in various fields involving pattern recognition, image processing, sparse modeling, and earth science, and a Boltzmann machine is one of the most important models in Markov random fields. However, the inference and learning problems in the Boltzmann machine are NP-hard. The investigation of an effective learning algorithm for the Boltzmann machine is one of the most important challenges in the field of statistical machine learning. In this paper, we study Boltzmann machine learning based on the (first-order spatial Monte Carlo integration method, referred to as the 1-SMCI learning method, which was proposed in the author’s previous paper. In the first part of this paper, we compare the method with the maximum pseudo-likelihood estimation (MPLE method using a theoretical and a numerical approaches, and show the 1-SMCI learning method is more effective than the MPLE. In the latter part, we compare the 1-SMCI learning method with other effective methods, ratio matching and minimum probability flow, using a numerical experiment, and show the 1-SMCI learning method outperforms them.
International Nuclear Information System (INIS)
Nagaya, Yasunobu; Okumura, Keisuke; Sakurai, Takeshi; Mori, Takamasa
2017-03-01
In order to realize fast and accurate Monte Carlo simulation of neutron and photon transport problems, two Monte Carlo codes MVP (continuous-energy method) and GMVP (multigroup method) have been developed at Japan Atomic Energy Agency. The codes have adopted a vectorized algorithm and have been developed for vector-type supercomputers. They also support parallel processing with a standard parallelization library MPI and thus a speed-up of Monte Carlo calculations can be achieved on general computing platforms. The first and second versions of the codes were released in 1994 and 2005, respectively. They have been extensively improved and new capabilities have been implemented. The major improvements and new capabilities are as follows: (1) perturbation calculation for effective multiplication factor, (2) exact resonant elastic scattering model, (3) calculation of reactor kinetics parameters, (4) photo-nuclear model, (5) simulation of delayed neutrons, (6) generation of group constants. This report describes the physical model, geometry description method used in the codes, new capabilities and input instructions. (author)
Forwards and Backwards Modelling of Ashfall Hazards in New Zealand by Monte Carlo Methods
Hurst, T.; Smith, W. D.; Bibby, H. M.
2003-12-01
We have developed a technique for quantifying the probability of particular thicknesses of airfall ash from a volcanic eruption at any given site, using Monte Carlo methods, for hazards planning and insurance purposes. We use an established program (ASHFALL) to model individual eruptions, where the likely thickness of ash deposited at selected sites depends on the location of the volcano, eruptive volume, column height and ash size, and the wind conditions. A Monte Carlo formulation then allows us to simulate the variations in eruptive volume and in wind conditions by analysing repeat eruptions, each time allowing the parameters to vary randomly according to known or assumed distributions. Actual wind velocity profiles are used, with randomness included by selection of a starting date. We show how this method can handle the effects of multiple volcanic sources by aggregation, each source with its own characteristics. This follows a similar procedure which we have used for earthquake hazard assessment. The result is estimates of the frequency with which any given depth of ash is likely to be deposited at the selected site, accounting for all volcanoes that might affect it. These numbers are expressed as annual probabilities or as mean return periods. We can also use this method for obtaining an estimate of how often and how large the eruptions from a particular volcano have been. Results from ash cores in Auckland can give useful bounds for the likely total volumes erupted from the volcano Mt Egmont/Mt Taranaki, 280 km away, during the last 140,000 years, information difficult to obtain from local tephra stratigraphy.
O'Keeffe, C J; Ren, Ruichao; Orkoulas, G
2007-11-21
Spatial updating grand canonical Monte Carlo algorithms are generalizations of random and sequential updating algorithms for lattice systems to continuum fluid models. The elementary steps, insertions or removals, are constructed by generating points in space either at random (random updating) or in a prescribed order (sequential updating). These algorithms have previously been developed only for systems of impenetrable spheres for which no particle overlap occurs. In this work, spatial updating grand canonical algorithms are generalized to continuous, soft-core potentials to account for overlapping configurations. Results on two- and three-dimensional Lennard-Jones fluids indicate that spatial updating grand canonical algorithms, both random and sequential, converge faster than standard grand canonical algorithms. Spatial algorithms based on sequential updating not only exhibit the fastest convergence but also are ideal for parallel implementation due to the absence of strict detailed balance and the nature of the updating that minimizes interprocessor communication. Parallel simulation results for three-dimensional Lennard-Jones fluids show a substantial reduction of simulation time for systems of moderate and large size. The efficiency improvement by parallel processing through domain decomposition is always in addition to the efficiency improvement by sequential updating.
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.
Investigation of a V15 magnetic molecular nanocluster by the Monte Carlo method
International Nuclear Information System (INIS)
Khizriev, K. Sh.; Dzhamalutdinova, I. S.; Taaev, T. A.
2013-01-01
Exchange interactions in a V 15 magnetic molecular nanocluster are considered, and the process of magnetization reversal for various values of the set of exchange constants is analyzed by the Monte Carlo method. It is shown that the best agreement between the field dependence of susceptibility and experimental results is observed for the following set of exchange interaction constants in a V 15 magnetic molecular nanocluster: J = 500 K, J′ = 150 K, J″ = 225 K, J 1 = 50 K, and J 2 = 50 K. It is observed for the first time that, in a strong magnetic field, for each of the three transitions from low-spin to high-spin states, the heat capacity exhibits two closely spaced maxima
Generation of organic scintillators response function for fast neutrons using the Monte Carlo method
International Nuclear Information System (INIS)
Mazzaro, A.C.
1979-01-01
A computer program (DALP) in Fortran-4-G language, has been developed using the Monte Carlo method to simulate the experimental techniques leading to the distribution of pulse heights due to monoenergetic neutrons reaching an organic scintillator. The calculation of the pulse height distribution has been done for two different systems: 1) Monoenergetic neutrons from a punctual source reaching the flat face of a cylindrical organic scintillator; 2) Environmental monoenergetic neutrons randomly reaching either the flat or curved face of the cylindrical organic scintillator. The computer program has been developed in order to be applied to the NE-213 liquid organic scintillator, but can be easily adapted to any other kind of organic scintillator. With this program one can determine the pulse height distribution for neutron energies ranging from 15 KeV to 10 MeV. (Author) [pt
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.
International Nuclear Information System (INIS)
Levitan, Iu.L.; Sobol, I.M.; Khlopov, M.Iu.; Chechetkin, V.M.
1982-01-01
The variation of the hard part of the neutrino emission spectra of collapsing degenerate stellar cores with matter having a small optical depth to neutrinos is analyzed. The interaction of neutrinos with the degenerate matter is determined by processes of neutrino scattering on nuclei (without a change in neutrino energy) and neutrino scattering on degenerate electrons, in which the neutrino energy can only decrease. The neutrino emission spectrum of a collapsing stellar core in the initial stage of the onset of opacity is calculated by the Monte Carlo method: using a central density of 10 trillion g/cu cm and, in the stage of deep collapse, for a central density of 60 trillion g/cu cm. In the latter case the calculation of the spectrum without allowance for effects of neutrino degeneration in the central part of the collapsing stellar core corresponds to the maximum possible suppression of the hard part of the neutrino emission spectrum
Absorbed dose measurements in mammography using Monte Carlo method and ZrO2+PTFE dosemeters
International Nuclear Information System (INIS)
Duran M, H. A.; Hernandez O, M.; Salas L, M. A.; Hernandez D, V. M.; Vega C, H. R.; Pinedo S, A.; Ventura M, J.; Chacon, F.; Rivera M, T.
2009-10-01
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 2 +PTFE thermoluminescent dosemeters, this calculation was completed with calculating the absorbed dose. (author)
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.
Investigation of physical regularities in gamma gamma logging of oil wells by Monte Carlo method
International Nuclear Information System (INIS)
Gulin, Yu.A.
1973-01-01
Some results are given of calculations by the Monte Carlo method of specific problems of gamma-gamma density logging. The paper considers the influence of probe length and volume density of the rocks; the angular distribution of the scattered radiation incident on the instrument; the spectra of the radiation being recorded and of the source radiation; depths of surveys, the effect of the mud cake, the possibility of collimating the source radiation; the choice of source, initial collimation angles, the optimum angle of recording scattered gamma-radiation and the radiation discrimination threshold; and the possibility of determining the mineralogical composition of rocks in sections of oil wells and of identifying once-scattered radiation. (author)
Calibration of lung counter using a CT model of Torso phantom and Monte Carlo method
International Nuclear Information System (INIS)
Zhang Binquan; Ma Jizeng; Yang Duanjie; Liu Liye; Cheng Jianping
2006-01-01
Tomography image of a Torso phantom was obtained from CT-Scan. The Torso phantom represents the trunk of an adult man that is 170 cm high and weight of 65 kg. After these images were segmented, cropped, and resized, a 3-dimension voxel phantom was created. The voxel phantom includes more than 2 million voxels, which size was 2.73 mm x 2.73 mm x 3 mm. This model could be used for the calibration of lung counter with Monte Carlo method. On the assumption that radioactive material was homogeneously distributed throughout the lung, counting efficiencies of a HPGe detector in different positions were calculated as Adipose Mass fraction (AMF) was different in the soft tissue in chest. The results showed that counting efficiencies of the lung counter changed up to 67% for 17.5 keV γ ray and 20% for 25 keV γ ray when AMF changed from 0 to 40%. (authors)
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.
Finite-Temperature Variational Monte Carlo Method for Strongly Correlated Electron Systems
Takai, Kensaku; Ido, Kota; Misawa, Takahiro; Yamaji, Youhei; Imada, Masatoshi
2016-03-01
A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in the imaginary-time formulation, starting from the infinite-temperature state that is well approximated by a small number of certain random initial states. Lower temperatures are progressively reached by the imaginary-time evolution. The algorithm follows the framework of the quantum transfer matrix and finite-temperature Lanczos methods, but we extend them to treat much larger system sizes without the negative sign problem by optimizing the truncated Hilbert space on the basis of the time-dependent variational principle (TDVP). This optimization algorithm is equivalent to the stochastic reconfiguration (SR) method that has been frequently used for the ground state to optimally truncate the Hilbert space. The obtained finite-temperature states allow an interpretation based on the thermal pure quantum (TPQ) state instead of the conventional canonical-ensemble average. Our method is tested for the one- and two-dimensional Hubbard models and its accuracy and efficiency are demonstrated.
Variational Monte Carlo Technique
Indian Academy of Sciences (India)
ias
RESONANCE ⎜ August 2014. GENERAL ⎜ ARTICLE. Variational Monte Carlo Technique. Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. Keywords. Variational methods, Monte. Carlo techniques, harmonic os- cillators, quantum mechanical systems. Sukanta Deb is an. Assistant Professor in the.
Indian Academy of Sciences (India)
. Keywords. Gibbs sampling, Markov Chain. Monte Carlo, Bayesian inference, stationary distribution, conver- gence, image restoration. Arnab Chakraborty. We describe the mathematics behind the Markov. Chain Monte Carlo method of ...
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
Bahadori, Amir Alexander
Astronauts are exposed to a unique radiation environment in space. United States terrestrial radiation worker limits, derived from guidelines produced by scientific panels, do not apply to astronauts. Limits for astronauts have changed throughout the Space Age, eventually reaching the current National Aeronautics and Space Administration limit of 3% risk of exposure induced death, with an administrative stipulation that the risk be assured to the upper 95% confidence limit. Much effort has been spent on reducing the uncertainty associated with evaluating astronaut risk for radiogenic cancer mortality, while tools that affect the accuracy of the calculations have largely remained unchanged. In the present study, the impacts of using more realistic computational phantoms with size variability to represent astronauts with simplified deterministic radiation transport were evaluated. Next, the impacts of microgravity-induced body changes on space radiation dosimetry using the same transport method were investigated. Finally, dosimetry and risk calculations resulting from Monte Carlo radiation transport were compared with results obtained using simplified deterministic radiation transport. The results of the present study indicated that the use of phantoms that more accurately represent human anatomy can substantially improve space radiation dose estimates, most notably for exposures from solar particle events under light shielding conditions. Microgravity-induced changes were less important, but results showed that flexible phantoms could assist in optimizing astronaut body position for reducing exposures during solar particle events. Finally, little overall differences in risk calculations using simplified deterministic radiation transport and 3D Monte Carlo radiation transport were found; however, for the galactic cosmic ray ion spectra, compensating errors were observed for the constituent ions, thus exhibiting the need to perform evaluations on a particle
International Nuclear Information System (INIS)
Mercier, B.; Meurant, G.; Tassart, J.
1985-04-01
The description of the equations in the fluid frame has been done recently. A simplification of the collision term is obtained, but the streaming term now has to include angular deviation and the Doppler shift. We choose the latter description which is more convenient for our purpose. We introduce some notations and recall some facts about stochastic kernels and the Monte-Carlo method. We show how to apply the Monte-Carlo method to a transport equation with an arbitrary streaming term; in particular we show that the track length estimator is unbiased. We review some properties of the radiation hydrodynamics equations, and show how energy conservation is obtained. Then, we apply the Monte-Carlo method explained in section 2 to the particular case of the transfer equation in the fluid frame. Finally, we describe a physical example and give some numerical results
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.
Lysak, Y. V.; Klimanov, V. A.; Narkevich, B. Ya
2017-01-01
One of the most difficult problems of modern radionuclide therapy (RNT) is control of the absorbed dose in pathological volume. This research presents new approach based on estimation of radiopharmaceutical (RP) accumulated activity value in tumor volume, based on planar scintigraphic images of the patient and calculated radiation transport using Monte Carlo method, including absorption and scattering in biological tissues of the patient, and elements of gamma camera itself. In our research, to obtain the data, we performed modeling scintigraphy of the vial with administered to the patient activity of RP in gamma camera, the vial was placed at the certain distance from the collimator, and the similar study was performed in identical geometry, with the same values of activity of radiopharmaceuticals in the pathological target in the body of the patient. For correct calculation results, adapted Fisher-Snyder human phantom was simulated in MCNP program. In the context of our technique, calculations were performed for different sizes of pathological targets and various tumors deeps inside patient’s body, using radiopharmaceuticals based on a mixed β-γ-radiating (131I, 177Lu), and clear β- emitting (89Sr, 90Y) therapeutic radionuclides. Presented method can be used for adequate implementing in clinical practice estimation of absorbed doses in the regions of interest on the basis of planar scintigraphy of the patient with sufficient accuracy.
Accelerated kinetics of amorphous silicon using an on-the-fly off-lattice kinetic Monte-Carlo method
Joly, Jean-Francois; El-Mellouhi, Fedwa; Beland, Laurent Karim; Mousseau, Normand
2011-03-01
The time evolution of a series of well relaxed amorphous silicon models was simulated using the kinetic Activation-RelaxationTechnique (kART), an on-the-fly off-lattice kinetic Monte Carlo method. This novel algorithm uses the ART nouveau algorithm to generate activated events and links them with local topologies. It was shown to work well for crystals with few defects but this is the first time it is used to study an amorphous material. A parallel implementation allows us to increase the speed of the event generation phase. After each KMC step, new searches are initiated for each new topology encountered. Well relaxed amorphous silicon models of 1000 atoms described by a modified version of the empirical Stillinger-Weber potential were used as a starting point for the simulations. Initial results show that the method is faster by orders of magnitude compared to conventional MD simulations up to temperatures of 500 K. Vacancy-type defects were also introduced in this system and their stability and lifetimes are calculated.
International Nuclear Information System (INIS)
Truchet, G.; Leconte, P.; Peneliau, Y.; Santamarina, A.
2013-01-01
The first goal of this paper is to present an exact method able to precisely evaluate very small reactivity effects with a Monte Carlo code (<10 pcm). it has been decided to implement the exact perturbation theory in TRIPOLI-4 and, consequently, to calculate a continuous-energy adjoint flux. The Iterated Fission Probability (IFP) method was chosen because it has shown great results in some other Monte Carlo codes. The IFP method uses a forward calculation to compute the adjoint flux, and consequently, it does not rely on complex code modifications but on the physical definition of the adjoint flux as a phase-space neutron importance. In the first part of this paper, the IFP method implemented in TRIPOLI-4 is described. To illustrate the efficiency of the method, several adjoint fluxes are calculated and compared with their equivalent obtained by the deterministic code APOLLO-2. The new implementation can calculate angular adjoint flux. In the second part, a procedure to carry out an exact perturbation calculation is described. A single cell benchmark has been used to test the accuracy of the method, compared with the 'direct' estimation of the perturbation. Once again the method based on the IFP shows good agreement for a calculation time far more inferior to the 'direct' method. The main advantage of the method is that the relative accuracy of the reactivity variation does not depend on the magnitude of the variation itself, which allows us to calculate very small reactivity perturbations with high precision. It offers the possibility to split reactivity contributions on both isotopes and reactions. Other applications of this perturbation method are presented and tested like the calculation of exact kinetic parameters (βeff, Λeff) or sensitivity parameters
Calculation of neutron importance function in fissionable assemblies using Monte Carlo method
International Nuclear Information System (INIS)
Feghhi, S.A.H.; Shahriari, M.; Afarideh, H.
2007-01-01
The purpose of the present work is to develop an efficient solution method for the calculation of neutron importance function in fissionable assemblies for all criticality conditions, based on Monte Carlo calculations. The neutron importance function has an important role in perturbation theory and reactor dynamic calculations. Usually this function can be determined by calculating the adjoint flux while solving the adjoint weighted transport equation based on deterministic methods. However, in complex geometries these calculations are very complicated. In this article, considering the capabilities of MCNP code in solving problems with complex geometries and its closeness to physical concepts, a comprehensive method based on the physical concept of neutron importance has been introduced for calculating the neutron importance function in sub-critical, critical and super-critical conditions. For this propose a computer program has been developed. The results of the method have been benchmarked with ANISN code calculations in 1 and 2 group modes for simple geometries. The correctness of these results has been confirmed for all three criticality conditions. Finally, the efficiency of the method for complex geometries has been shown by the calculation of neutron importance in Miniature Neutron Source Reactor (MNSR) research reactor
Applications of Monte Carlo method to nonlinear regression of rheological data
Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo
2018-02-01
In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.
Energy Technology Data Exchange (ETDEWEB)
Trias, Miquel [Departament de Fisica, Universitat de les Illes Balears, Cra. Valldemossa Km. 7.5, E-07122 Palma de Mallorca (Spain); Vecchio, Alberto; Veitch, John, E-mail: miquel.trias@uib.e, E-mail: av@star.sr.bham.ac.u, E-mail: jveitch@star.sr.bham.ac.u [School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT (United Kingdom)
2009-10-21
Bayesian analysis of Laser Interferometer Space Antenna (LISA) data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that dramatically reduces the efficiency of the sampling techniques. Here we introduce a new fully Markovian algorithm, a delayed rejection Metropolis-Hastings Markov chain Monte Carlo method, to efficiently explore these kind of structures and we demonstrate its performance on selected LISA data sets containing a known number of stellar-mass binary signals embedded in Gaussian stationary noise.
Lu, D.; Ricciuto, D. M.; Evans, K. J.
2017-12-01
Data-worth analysis plays an essential role in improving the understanding of the subsurface system, in developing and refining subsurface models, and in supporting rational water resources management. However, data-worth analysis is computationally expensive as it requires quantifying parameter uncertainty, prediction uncertainty, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface simulations using standard Monte Carlo (MC) sampling or advanced surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose efficient Bayesian analysis of data-worth using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce the computational cost with the use of multifidelity approximations. As the data-worth analysis involves a great deal of expectation estimations, the cost savings from MLMC in the assessment can be very outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it to a highly heterogeneous oil reservoir simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the estimation obtained from the standard MC. But compared to the standard MC, the MLMC greatly reduces the computational costs in the uncertainty reduction estimation, with up to 600 days cost savings when one processor is used.
An efficient Bayesian data-worth analysis using a multilevel Monte Carlo method
Lu, Dan; Ricciuto, Daniel; Evans, Katherine
2018-03-01
Improving the understanding of subsurface systems and thus reducing prediction uncertainty requires collection of data. As the collection of subsurface data is costly, it is important that the data collection scheme is cost-effective. Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface hydrological model simulations using standard Monte Carlo (MC) sampling or surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose an efficient Bayesian data-worth analysis using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce computational costs using multifidelity approximations. Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it for a highly heterogeneous two-phase subsurface flow simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the standard MC estimation. But compared to the standard MC, the MLMC greatly reduces the computational costs.
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.
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.
Application of Monte Carlo Method to Design a Delayed Neutron Counting System
International Nuclear Information System (INIS)
Ahn, Gil Hoon; Park, Il Jin; Kim, Jung Soo; Min, Gyung Sik
2006-01-01
The quantitative determination of fissile materials in environmental samples is becoming more and more important because of the increasing demand for nuclear nonproliferation. A number of methods have been proposed for screening environmental samples to measure fissile material content. Among them, delayed neutron counting (DNC) that is a nondestructive neutron activation analysis (NAA) method without chemical preparation has numerous advantages over other screening techniques. Fissile materials such as 239 Pu and 235 U can be made to undergo fission in the intense neutron field. Some of the fission products emit neutrons referred to as 'delayed neutrons' because they are emitted after a brief decay period following irradiation. Counting these delayed neutrons provides a simple method for determining the total fissile content in the sample. In delayed neutron counting, the chemical bonding environment of a fissile atom has no effect on the measurement process. Therefore, NAA is virtually immune to the 'matrix' effects that complicate other methods. The present study aims at design of a DNC system. In advance, neutron detector, gamma ray shielding material, and neutron thermalizing material should be selected. Next, investigation should be done to optimize the thickness of gamma ray shielding material and neutron thermalizing material using the MCNPX that is a well-known and widely-used Monte Carlo radiation transport code to find the following
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.
Estimation of the Thermal Process in the Honeycomb Panel by a Monte Carlo Method
Gusev, S. A.; Nikolaev, V. N.
2018-01-01
A new Monte Carlo method for estimating the thermal state of the heat insulation containing honeycomb panels is proposed in the paper. The heat transfer in the honeycomb panel is described by a boundary value problem for a parabolic equation with discontinuous diffusion coefficient and boundary conditions of the third kind. To obtain an approximate solution, it is proposed to use the smoothing of the diffusion coefficient. After that, the obtained problem is solved on the basis of the probability representation. The probability representation is the expectation of the functional of the diffusion process corresponding to the boundary value problem. The process of solving the problem is reduced to numerical statistical modelling of a large number of trajectories of the diffusion process corresponding to the parabolic problem. It was used earlier the Euler method for this object, but that requires a large computational effort. In this paper the method is modified by using combination of the Euler and the random walk on moving spheres methods. The new approach allows us to significantly reduce the computation costs.
Energy Technology Data Exchange (ETDEWEB)
Silva, Frank Sinatra Gomes da
2008-02-15
The Monte Carlo method is an important tool to simulate radioactive particles interaction with biologic medium. The principal advantage of the method when compared with deterministic methods is the ability to simulate a complex geometry. Several computational codes use the Monte Carlo method to simulate the particles transport and they have the capacity to simulate energy deposition in models of organs and/or tissues, as well models of cells of human body. Thus, the calculation of the absorbed dose to thyroid's follicles (compound of colloid and follicles' cells) have a fundamental importance to dosimetry, because these cells are radiosensitive due to ionizing radiation exposition, in particular, exposition due to radioisotopes of iodine, because a great amount of radioiodine may be released into the environment in case of a nuclear accidents. In this case, the goal of this work was use the code of particles transport MNCP4C to calculate absorbed doses in models of thyroid's follicles, for Auger electrons, internal conversion electrons and beta particles, by iodine-131 and short-lived iodines (131, 132, 133, 134 e 135), with diameters varying from 30 to 500 {mu}m. The results obtained from simulation with the MCNP4C code shown an average percentage of the 25% of total absorbed dose by colloid to iodine- 131 and 75% to short-lived iodine's. For follicular cells, this percentage was of 13% to iodine-131 and 87% to short-lived iodine's. The contributions from particles with low energies, like Auger and internal conversion electrons should not be neglected, to assessment the absorbed dose in cellular level. Agglomerative hierarchical clustering was used to compare doses obtained by codes MCNP4C, EPOTRAN, EGS4 and by deterministic methods. (author)
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
Simulation of neutral gas flow in a tokamak divertor using the Direct Simulation Monte Carlo method
International Nuclear Information System (INIS)
Gleason-González, Cristian; Varoutis, Stylianos; Hauer, Volker; Day, Christian
2014-01-01
Highlights: • Subdivertor gas flows calculations in tokamaks by coupling the B2-EIRENE and DSMC method. • The results include pressure, temperature, bulk velocity and particle fluxes in the subdivertor. • Gas recirculation effect towards the plasma chamber through the vertical targets is found. • Comparison between DSMC and the ITERVAC code reveals a very good agreement. - Abstract: This paper presents a new innovative scientific and engineering approach for describing sub-divertor gas flows of fusion devices by coupling the B2-EIRENE (SOLPS) code and the Direct Simulation Monte Carlo (DSMC) method. The present study exemplifies this with a computational investigation of neutral gas flow in the ITER's sub-divertor region. The numerical results include the flow fields and contours of the overall quantities of practical interest such as the pressure, the temperature and the bulk velocity assuming helium as model gas. Moreover, the study unravels the gas recirculation effect located behind the vertical targets, viz. neutral particles flowing towards the plasma chamber. Comparison between calculations performed by the DSMC method and the ITERVAC code reveals a very good agreement along the main sub-divertor ducts
The EURADOS-KIT training course on Monte Carlo methods for the calibration of body counters
International Nuclear Information System (INIS)
Breustedt, B.; Broggio, D.; Gomez-Ros, J.M.; Lopez, M.A.; Leone, D.; Poelz, S.; Marzocchi, O.; Shutt, A.
2016-01-01
Monte Carlo (MC) methods are numerical simulation techniques that can be used to extend the scope of calibrations performed in in vivo monitoring laboratories. These methods allow calibrations to be carried out for a much wider range of body shapes and sizes than would be feasible using physical phantoms. Unfortunately, nowadays, this powerful technique is still used mainly in research institutions only. In 2013, EURADOS and the in vivo monitoring laboratory of Karlsruhe Institute of Technology (KIT) organized a 3-d training course to disseminate knowledge on the application of MC methods for in vivo monitoring. It was intended as a hands-on course centered around an exercise which guided the participants step by step through the calibration process using a simplified version of KIT's equipment. Only introductory lectures on in vivo monitoring and voxel models were given. The course was based on MC codes of the MCNP family, widespread in the community. The strong involvement of the participants and the working atmosphere in the classroom as well as the formal evaluation of the course showed that the approach chosen was appropriate. Participants liked the hands-on approach and the extensive course materials on the exercise. (authors)
Bridging the gap between quantum Monte Carlo and F12-methods
Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André
2012-06-01
Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.
Bridging the gap between quantum Monte Carlo and F12-methods
International Nuclear Information System (INIS)
Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André
2012-01-01
Graphical abstract: Tensor product approximation of pair-correlation functions: τ(x,y)≈∑ κ=1 κ u k (1) (x 1 ,y 1 )u k (2) (x 2 ,y 2 )u k (3) (x 3 ,y 3 ) Pair-correlation function τ(x,y)∣ ∣x·y∣=∣x∣∣y∣ of the He atom and corresponding tensor product approximation errors. Display Omitted - Abstract: Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.
Louis Leon Thurstone in Monte Carlo: creating error bars for the method of paired comparison
Montag, Ethan D.
2003-12-01
The method of paired comparison is often used in experiments where perceptual scale values for a collection of stimuli are desired, such as in experiments analyzing image quality. Thurstone's Case V of his Law of Comparative Judgments is often used as the basis for analyzing data produced in paired comparison experiments. However, methods for determining confidence intervals and critical distances for significant differences based on Thurstone's Law have been elusive leading some to abandon the simple analysis provided by Thurstone's formulation. In order to provide insight into this problem of determining error, Monte Carlo simulations of paired comparison experiments were performed based on the assumptions of uniformly normal, independent, and uncorrelated responses from stimulus pair presentations. The results from these multiple simulations show that the variation in the distribution of experimental results of paired comparison experiments can be well predicted as a function of stimulus number and the number of observations. Using these results, confidence intervals and critical values for comparisons can be made using traditional statistical methods. In addition the results from simulations can be used to analyze goodness-of-fit techniques.
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).
Mass change distribution inverted from space-borne gravimetric data using a Monte Carlo method
Zhou, X.; Sun, X.; Wu, Y.; Sun, W.
2017-12-01
Mass estimate plays a key role in using temporally satellite gravimetric data to quantify the terrestrial water storage change. GRACE (Gravity Recovery and Climate Experiment) only observes the low degree gravity field changes, which can be used to estimate the total surface density or equivalent water height (EWH) variation, with a limited spatial resolution of 300 km. There are several methods to estimate the mass variation in an arbitrary region, such as averaging kernel, forward modelling and mass concentration (mascon). Mascon method can isolate the local mass from the gravity change at a large scale through solving the observation equation (objective function) which represents the relationship between unknown masses and the measurements. To avoid the unreasonable local mass inverted from smoothed gravity change map, regularization has to be used in the inversion. We herein give a Markov chain Monte Carlo (MCMC) method to objectively determine the regularization parameter for the non-negative mass inversion problem. We first apply this approach to the mass inversion from synthetic data. Result show MCMC can effectively reproduce the local mass variation taking GRACE measurement error into consideration. We then use MCMC to estimate the ground water change rate of North China Plain from GRACE gravity change rate from 2003 to 2014 under a supposition of the continuous ground water loss in this region. Inversion result show that the ground water loss rate in North China Plain is 7.6±0.2Gt/yr during past 12 years which is coincident with that from previous researches.
International Nuclear Information System (INIS)
Ganjaei, A. A.; Nourazar, S. S.
2009-01-01
A new algorithm, the modified direct simulation Monte-Carlo (MDSMC) method, for the simulation of Couette- Taylor gas flow problem is developed. The Taylor series expansion is used to obtain the modified equation of the first order time discretization of the collision equation and the new algorithm, MDSMC, is implemented to simulate the collision equation in the Boltzmann equation. In the new algorithm (MDSMC) there exists a new extra term which takes in to account the effect of the second order collision. This new extra term has the effect of enhancing the appearance of the first Taylor instabilities of vortices streamlines. In the new algorithm (MDSMC) there also exists a second order term in time step in the probabilistic coefficients which has the effect of simulation with higher accuracy than the previous DSMC algorithm. The appearance of the first Taylor instabilities of vortices streamlines using the MDSMC algorithm at different ratios of ω/ν (experimental data of Taylor) occurred at less time-step than using the DSMC algorithm. The results of the torque developed on the stationary cylinder using the MDSMC algorithm show better agreement in comparison with the experimental data of Kuhlthau than the results of the torque developed on the stationary cylinder using the DSMC algorithm
Directory of Open Access Journals (Sweden)
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.
Energy Technology Data Exchange (ETDEWEB)
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.
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.
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...... to predict the structure of a functional amyloid protein, by using intramolecular evolutionary restrains in Monte Carlo simulations....... 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...
International Nuclear Information System (INIS)
Jinaphanh, A.
2012-01-01
Monte Carlo criticality calculation allows to estimate the effective multiplication factor as well as local quantities such as local reaction rates. Some configurations presenting weak neutronic coupling (high burn up profile, complete reactor core,...) may induce biased estimations for k eff or reaction rates. In order to improve robustness of the iterative Monte Carlo methods, a coupling with a deterministic code was studied. An adjoint flux is obtained by a deterministic calculation and then used in the Monte Carlo. The initial guess is then automated, the sampling of fission sites is modified and the random walk of neutrons is modified using splitting and russian roulette strategies. An automated convergence detection method has been developed. It locates and suppresses the transient due to the initialization in an output series, applied here to k eff and Shannon entropy. It relies on modeling stationary series by an order 1 auto regressive process and applying statistical tests based on a Student Bridge statistics. This method can easily be extended to every output of an iterative Monte Carlo. Methods developed in this thesis are tested on different test cases. (author)
International Nuclear Information System (INIS)
Zmushko, V.V.; Migdal, A.A.
1987-01-01
A model of triangulated random surfaces which is the discrete analogue of the Polyakov string is considered in the work. An algorithm is proposed which enables one to study the model by means of the Monte Carlo method in the grand canonical ensemble. Preliminary results are presented on the evaluation of the critical index γ
Czech Academy of Sciences Publication Activity Database
Zapoměl, Jaroslav; Ferfecki, Petr; Kozánek, Jan
2014-01-01
Roč. 8, č. 1 (2014), s. 129-138 ISSN 1802-680X Institutional support: RVO:61388998 Keywords : uncertain parameters of rigid motors * magnetorheological dampers * force transmission * Monte Carlo method Subject RIV: BI - Acoustics http://www.kme.zcu.cz/acm/acm/article/view/247/275
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.
Application of Monte Carlo Method to Test Fingerprinting System for Dry Storage Canister
International Nuclear Information System (INIS)
Ahn, Gil Hoon; Park, Il-Jin; Min, Gyung Sik
2006-01-01
From 1992, dry storage canisters have been used for long-term disposition of the CANDU spent fuel bundles at Wolsong. Periodic inspection of the dual seals is currently the only measure that exists to verify that the contents have not been altered. So, verification for spent nuclear fuel in the dry storage is one of the important safeguarding tasks because the spent fuel contains significant quantities of fissile material. Although traditional non-destructive analysis and assay techniques to verify contents are ineffective due to shielding of spent fuel and canister wall, straggling position of detector, etc., Manual measurement of the radiation levels present in the reverification tubes that run along the length of the canister to enable the radiation profile within the canister is presently the most reliable method for ensuring that the stored materials are still present. So, gamma-ray fingerprinting method has been used after a canister is sealed in Korea to provide a continuity of knowledge that canister contents remain as loaded. The present study aims at test of current fingerprinting system using the MCNPX that is a well known and widely-used Monte Carlo radiation transport code, which may be useful in the verification measures of the spent fuel subject with final disposal guidance criterion(4kg of Pu, 0.5 SQ)
Systematic hierarchical coarse-graining with the inverse Monte Carlo method
International Nuclear Information System (INIS)
Lyubartsev, Alexander P.; Naômé, Aymeric; Vercauteren, Daniel P.; Laaksonen, Aatto
2015-01-01
We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730–3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile
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).
Tubman, Norm; Whaley, Birgitta
The development of exponential scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, allows exact diagonalization through stochastically sampling of determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, together with a stochastic projected wave function, which are used to explore the important parts of Hilbert space. However, a stochastic representation of the wave function is not required to search Hilbert space efficiently and new deterministic approaches have recently been shown to efficiently find the important parts of determinant space. We shall discuss the technique of Adaptive Sampling Configuration Interaction (ASCI) and the related heat-bath Configuration Interaction approach for ground state and excited state simulations. We will present several applications for strongly correlated Hamiltonians. This work was supported through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences.
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.
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.
Directory of Open Access Journals (Sweden)
Joko Siswantoro
2014-11-01
Full Text Available Volume is one of important issues in the production and processing of food product. Traditionally, volume measurement can be performed using water displacement method based on Archimedes’ principle. Water displacement method is inaccurate and considered as destructive method. Computer vision offers an accurate and nondestructive method in measuring volume of food product. This paper proposes algorithm for volume measurement of irregular shape food product using computer vision based on Monte Carlo method. Five images of object were acquired from five different views and then processed to obtain the silhouettes of object. From the silhouettes of object, Monte Carlo method was performed to approximate the volume of object. The simulation result shows that the algorithm produced high accuracy and precision for volume measurement.
International Nuclear Information System (INIS)
Yeh, C.Y.; Lee, C.C.; Chao, T.C.; Lin, M.H.; Lai, P.A.; Liu, F.H.; Tung, C.J.
2014-01-01
This study aims to utilize a measurement-based Monte Carlo (MBMC) method to evaluate the accuracy of dose distributions calculated using the Eclipse radiotherapy treatment planning system (TPS) based on the anisotropic analytical algorithm. Dose distributions were calculated for the nasopharyngeal carcinoma (NPC) patients treated with the intensity modulated radiotherapy (IMRT). Ten NPC IMRT plans were evaluated by comparing their dose distributions with those obtained from the in-house MBMC programs for the same CT images and beam geometry. To reconstruct the fluence distribution of the IMRT field, an efficiency map was obtained by dividing the energy fluence of the intensity modulated field by that of the open field, both acquired from an aS1000 electronic portal imaging device. The integrated image of the non-gated mode was used to acquire the full dose distribution delivered during the IMRT treatment. This efficiency map redistributed the particle weightings of the open field phase-space file for IMRT applications. Dose differences were observed in the tumor and air cavity boundary. The mean difference between MBMC and TPS in terms of the planning target volume coverage was 0.6% (range: 0.0–2.3%). The mean difference for the conformity index was 0.01 (range: 0.0–0.01). In conclusion, the MBMC method serves as an independent IMRT dose verification tool in a clinical setting. - Highlights: ► The patient-based Monte Carlo method serves as a reference standard to verify IMRT doses. ► 3D Dose distributions for NPC patients have been verified by the Monte Carlo method. ► Doses predicted by the Monte Carlo method matched closely with those by the TPS. ► The Monte Carlo method predicted a higher mean dose to the middle ears than the TPS. ► Critical organ doses should be confirmed to avoid overdose to normal organs
The Calculation Of Titanium Buildup Factor Based On Monte Carlo Method
International Nuclear Information System (INIS)
Has, Hengky Istianto; Achmad, Balza; Harto, Andang Widi
2001-01-01
The objective of radioactive-waste container is to reduce radiation emission to the environment. For that purpose, we need material with ability to shield that radiation and last for 10.000 years. Titanium is one of the materials that can be used to make containers. Unfortunately, its buildup factor, which is an importance factor in setting up radiation shielding, has not been calculated. Therefore, the calculations of titanium buildup factor as a function of other parameters is needed. Buildup factor can be determined either experimentally or by simulation. The purpose of this study is to determine titanium buildup factor using simulation program based on Monte Carlo method. Monte Carlo is a stochastic method, therefore is proper to calculate nuclear radiation which naturally has random characteristic. Simulation program also able to give result while experiments can not be performed, because of their limitations.The result of the simulation is, that by increasing titanium thickness the buildup factor number and dosage increase. In contrary If photon energy is higher, then buildup factor number and dosage are lower. The photon energy used in the simulation was ranged from 0.2 MeV to 2.0 MeV with 0.2 MeV step size, while the thickness was ranged from 0.2 cm to 3.0 cm with step size of 0.2 cm. The highest buildup factor number is β = 1.4540 ± 0.047229 at 0.2 MeV photon energy with titanium thickness of 3.0 cm. The lowest is β = 1.0123 ± 0.000650 at 2.0 MeV photon energy with 0.2 cm thickness of titanium. For the dosage buildup factor, the highest dose is β D = 1.3991 ± 0.013999 at 0.2 MeV of the photon energy with a titanium thickness of 3.0 cm and the lowest is β D = 1.0042 ± 0.000597 at 2.0 MeV with titanium thickness of 0.2 cm. For the photon energy and the thickness of titanium used in simulation, buildup factor and dosage buildup factor as a function of photon energy and titanium thickness can be formulated as follow β = 1.1264 e - 0.0855 E e 0 .0584 T
Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.
Ballnus, Benjamin; Hug, Sabine; Hatz, Kathrin; Görlitz, Linus; Hasenauer, Jan; Theis, Fabian J
2017-06-24
In quantitative biology, mathematical models are used to describe and analyze biological processes. The parameters of these models are usually unknown and need to be estimated from experimental data using statistical methods. In particular, Markov chain Monte Carlo (MCMC) methods have become increasingly popular as they allow for a rigorous analysis of parameter and prediction uncertainties without the need for assuming parameter identifiability or removing non-identifiable parameters. A broad spectrum of MCMC algorithms have been proposed, including single- and multi-chain approaches. However, selecting and tuning sampling algorithms suited for a given problem remains challenging and a comprehensive comparison of different methods is so far not available. We present the results of a thorough benchmarking of state-of-the-art single- and multi-chain sampling methods, including Adaptive Metropolis, Delayed Rejection Adaptive Metropolis, Metropolis adjusted Langevin algorithm, Parallel Tempering and Parallel Hierarchical Sampling. Different initialization and adaptation schemes are considered. To ensure a comprehensive and fair comparison, we consider problems with a range of features such as bifurcations, periodical orbits, multistability of steady-state solutions and chaotic regimes. These problem properties give rise to various posterior distributions including uni- and multi-modal distributions and non-normally distributed mode tails. For an objective comparison, we developed a pipeline for the semi-automatic comparison of sampling results. The comparison of MCMC algorithms, initialization and adaptation schemes revealed that overall multi-chain algorithms perform better than single-chain algorithms. In some cases this performance can be further increased by using a preceding multi-start local optimization scheme. These results can inform the selection of sampling methods and the benchmark collection can serve for the evaluation of new algorithms. Furthermore, our
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.
International Nuclear Information System (INIS)
Yamamoto, K.; Hashizume, K.; Wada, T.; Ohta, M.; Suda, T.; Nishimura, T.; Fujimoto, M. Y.; Kato, K.; Aikawa, M.
2006-01-01
We propose a Monte Carlo method to study the reaction paths in nucleosynthesis during stellar evolution. Determination of reaction paths is important to obtain the physical picture of stellar evolution. The combination of network calculation and our method gives us a better understanding of physical picture. We apply our method to the case of the helium shell flash model in the extremely metal poor star
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.
Bécares, V.; Pérez Martín, S.; Vázquez Antolín, Miriam; Villamarín, D.; Martín Fuertes, Francisco; González Romero, E.M.; Merino Rodríguez, Iván
2014-01-01
The calculation of the effective delayed neutron fraction, beff , with Monte Carlo codes is a complex task due to the requirement of properly considering the adjoint weighting of delayed neutrons. Nevertheless, several techniques have been proposed to circumvent this difficulty and obtain accurate Monte Carlo results for beff without the need of explicitly determining the adjoint flux. In this paper, we make a review of some of these techniques; namely we have analyzed two variants of what we...
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
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.
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
Sustainable Queuing-Network Design for Airport Security Based on the Monte Carlo Method
Directory of Open Access Journals (Sweden)
Xiangqian Xu
2018-01-01
Full Text Available The design of airport queuing networks is a significant research field currently for researchers. Many factors must to be considered in order to achieve the optimized strategies, including the passenger flow volume, boarding time, and boarding order of passengers. Optimizing these factors lead to the sustainable development of the queuing network, which currently faces a few difficulties. In particular, the high variance in checkpoint lines can be extremely costly to passengers as they arrive unduly early or possibly miss their scheduled flights. In this article, the Monte Carlo method is used to design the queuing network so as to achieve sustainable development. Thereafter, a network diagram is used to determine the critical working point, and design a structurally and functionally sustainable network. Finally, a case study for a sustainable queuing-network design in the airport is conducted to verify the efficiency of the proposed model. Specifically, three sustainable queuing-network design solutions are proposed, all of which not only maintain the same standards of security, but also increase checkpoint throughput and reduce passenger waiting time variance.
Absorbed dose calculations using mesh-based human phantoms and Monte Carlo methods
International Nuclear Information System (INIS)
Kramer, Richard
2010-01-01
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)
Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods
International Nuclear Information System (INIS)
Kramer, Richard
2011-01-01
Health risks attributable to the exposure to ionizing radiation are considered to be a function of the absorbed or equivalent dose to radiosensitive organs and tissues. However, as human tissue cannot express itself in terms of equivalent dose, exposure models have to be used to determine the distribution of equivalent dose throughout the human body. An exposure model, be it physical or computational, 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 equivalent dose to organ and tissues of interest. The FASH2 (Female Adult meSH) and the MASH2 (Male Adult meSH) computational phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools and anatomical atlases. Representing standing adults, FASH2 and MASH2 have organ and tissue masses, body height and body 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 can transport photons, electrons and positrons through arbitrary media. This paper reviews the development of the FASH2 and the MASH2 phantoms and presents dosimetric applications for X-ray diagnosis and for prostate brachytherapy.
Dose rate evaluation of body phantom behind ITER bio-shield wall using Monte Carlo method
International Nuclear Information System (INIS)
Beheshti, A.; Jabbari, I.; Karimian, A.; Abdi, M.
2012-01-01
One of the most critical risks to humans in reactors environment is radiation exposure. Around the tokamak hall personnel are exposed to a wide range of particles, including neutrons and photons. International Thermonuclear Experimental Reactor (ITER) is a nuclear fusion research and engineering project, which is the most advanced experimental tokamak nuclear fusion reactor. Dose rates assessment and photon radiation due to the neutron activation of the solid structures in ITER is important from the radiological point of view. Therefore, the dosimetry considered in this case is based on the Deuterium-Tritium (DT) plasma burning with neutrons production rate at 14.1 MeV. The aim of this study is assessment the amount of radiation behind bio-shield wall that a human received during normal operation of ITER by considering neutron activation and delay gammas. To achieve the aim, the ITER system and its components were simulated by Monte Carlo method. Also to increase the accuracy and precision of the absorbed dose assessment a body phantom were considered in the simulation. The results of this research showed that total dose rates level near the outside of bio-shield wall of the tokamak hall is less than ten percent of the annual occupational dose limits during normal operation of ITER and It is possible to learn how long human beings can remain in that environment before the body absorbs dangerous levels of radiation. (authors)
Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods
Kramer, Richard
2011-08-01
Health risks attributable to the exposure to ionizing radiation are considered to be a function of the absorbed or equivalent dose to radiosensitive organs and tissues. However, as human tissue cannot express itself in terms of equivalent dose, exposure models have to be used to determine the distribution of equivalent dose throughout the human body. An exposure model, be it physical or computational, 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 equivalent dose to organ and tissues of interest. The FASH2 (Female Adult meSH) and the MASH2 (Male Adult meSH) computational phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools and anatomical atlases. Representing standing adults, FASH2 and MASH2 have organ and tissue masses, body height and body 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 can transport photons, electrons and positrons through arbitrary media. This paper reviews the development of the FASH2 and the MASH2 phantoms and presents dosimetric applications for X-ray diagnosis and for prostate brachytherapy.
Evaluation of functioning of an extrapolation chamber using Monte Carlo method
International Nuclear Information System (INIS)
Oramas Polo, I.; Alfonso Laguardia, R.
2015-01-01
The extrapolation chamber is a parallel plate chamber and variable volume based on the Braff-Gray theory. It determines in absolute mode, with high accuracy the dose absorbed by the extrapolation of the ionization current measured for a null distance between the electrodes. This camera is used for dosimetry of external beta rays for radiation protection. This paper presents a simulation for evaluating the functioning of an extrapolation chamber type 23392 of PTW, using the MCNPX Monte Carlo method. In the simulation, the fluence in the air collector cavity of the chamber was obtained. The influence of the materials that compose the camera on its response against beta radiation beam was also analysed. A comparison of the contribution of primary and secondary radiation was performed. The energy deposition in the air collector cavity for different depths was calculated. The component with the higher energy deposition is the Polymethyl methacrylate block. The energy deposition in the air collector cavity for chamber depth 2500 μm is greater with a value of 9.708E-07 MeV. The fluence in the air collector cavity decreases with depth. It's value is 1.758E-04 1/cm 2 for chamber depth 500 μm. The values reported are for individual electron and photon histories. The graphics of simulated parameters are presented in the paper. (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)
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
International Nuclear Information System (INIS)
Hall, Howard L.
2012-01-01
Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation.
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
International Nuclear Information System (INIS)
Garrison, J.R.; Hanson, D.E.; Hall, H.L.
2012-01-01
Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation. (author)
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.
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)
Deterministic flows of order-parameters in stochastic processes of quantum Monte Carlo method
International Nuclear Information System (INIS)
Inoue, Jun-ichi
2010-01-01
In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range (d(= ∞)-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding (d + 1)-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some 'non-monotonic' behaviour in its time evolution.
Application of the Monte Carlo method to estimate doses in a radioactive waste drum environment
International Nuclear Information System (INIS)
Rodenas, J.; Garcia, T.; Burgos, M.C.; Felipe, A.; Sanchez-Mayoral, M.L.
2002-01-01
During refuelling operation in a Nuclear Power Plant, filtration is used to remove non-soluble radionuclides contained in the water from reactor pool. Filter cartridges accumulate a high radioactivity, so that they are usually placed into a drum. When the operation ends up, the drum is filled with concrete and stored along with other drums containing radioactive wastes. Operators working in the refuelling plant near these radwaste drums can receive high dose rates. Therefore, it is convenient to estimate those doses to prevent risks in order to apply ALARA criterion for dose reduction to workers. The Monte Carlo method has been applied, using MCNP 4B code, to simulate the drum containing contaminated filters and estimate doses produced in the drum environment. In the paper, an analysis of the results obtained with the MCNP code has been performed. Thus, the influence on the evaluated doses of distance from drum and interposed shielding barriers has been studied. The source term has also been analysed to check the importance of the isotope composition. Two different geometric models have been considered in order to simplify calculations. Results have been compared with dose measurements in plant in order to validate the calculation procedure. This work has been developed at the Nuclear Engineering Department of the Polytechnic University of Valencia in collaboration with IBERINCO in the frame of an RD project sponsored by IBERINCO
Velazquez, L.; Castro-Palacio, J. C.
2015-03-01
Velazquez and Curilef [J. Stat. Mech. (2010) P02002, 10.1088/1742-5468/2010/02/P02002; J. Stat. Mech. (2010) P04026, 10.1088/1742-5468/2010/04/P04026] have proposed a methodology to extend Monte Carlo algorithms that are based on canonical ensemble. According to our previous study, their proposal allows us to overcome slow sampling problems in systems that undergo any type of temperature-driven phase transition. After a comprehensive review about ideas and connections of this framework, we discuss the application of a reweighting technique to improve the accuracy of microcanonical calculations, specifically, the well-known multihistograms method of Ferrenberg and Swendsen [Phys. Rev. Lett. 63, 1195 (1989), 10.1103/PhysRevLett.63.1195]. As an example of application, we reconsider the study of the four-state Potts model on the square lattice L ×L with periodic boundary conditions. This analysis allows us to detect the existence of a very small latent heat per site qL during the occurrence of temperature-driven phase transition of this model, whose size dependence seems to follow a power law qL(L ) ∝(1/L ) z with exponent z ≃0 .26 ±0 .02. Discussed is the compatibility of these results with the continuous character of temperature-driven phase transition when L →+∞ .
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.
Importance iteration in MORSE Monte Carlo calculations
International Nuclear Information System (INIS)
Kloosterman, J.L.; Hoogenboom, J.E.
1994-02-01
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)
Tracer diffusion in an ordered alloy: application of the path probability and Monte Carlo methods
International Nuclear Information System (INIS)
Sato, Hiroshi; Akbar, S.A.; Murch, G.E.
1984-01-01
Tracer diffusion technique has been extensively utilized to investigate diffusion phenomena and has contributed a great deal to the understanding of the phenomena. However, except for self diffusion and impurity diffusion, the meaning of tracer diffusion is not yet satisfactorily understood. Here we try to extend the understanding to concentrated alloys. Our major interest here is directed towards understanding the physical factors which control diffusion through the comparison of results obtained by the Path Probability Method (PPM) and those by the Monte Carlo simulation method (MCSM). Both the PPM and the MCSM are basically in the same category of statistical mechanical approaches applicable to random processes. The advantage of the Path Probability method in dealing with phenomena which occur in crystalline systems has been well established. However, the approximations which are inevitably introduced to make the analytical treatment tractable, although their meaning may be well-established in equilibrium statistical mechanics, sometimes introduce unwarranted consequences the origin of which is often hard to trace. On the other hand, the MCSM which can be carried out in a parallel fashion to the PPM provides, with care, numerically exact results. Thus a side-by-side comparison can give insight into the effect of approximations in the PPM. It was found that in the pair approximation of the CVM, the distribution in the completely random state is regarded as homogeneous (without fluctuations), and hence, the fluctuation in distribution is not well represented in the PPM. These examples thus show clearly how the comparison of analytical results with carefully carried out calculations by the MCSM guides the progress of theoretical treatments and gives insights into the mechanism of diffusion
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.
International Nuclear Information System (INIS)
Dupre, Corinne.
1982-10-01
The Monte Carlo method was applied to simulate the transport of a photon beam in an organic liquid scintillation detector. The interactions of secondary gamma rays and electrons with the detector and its peripheral materials components such as the pyrex glass container are included. The pulse height spectra and the detectors efficiency are compared with calculated and measured results. Calculations and programmation methods are presented in the same way as results concerning cobalt and cesium sources [fr
Energy Technology Data Exchange (ETDEWEB)
Martínez-Rovira, I., E-mail: immamartinez@gmail.com; Jouvie, C.; Jan, S. [Service Hospitalier Frédéric Joliot, Commissariat à l’énergie atomique et aux énergies alternatives (CEA/DSV/I2BM/SHFJ), 4 place du général Leclerc, 91401 Orsay Cedex (France)
2015-04-15
Purpose: The imaging of positron emitting isotopes produced during patient irradiation is the only in vivo method used for hadrontherapy dose monitoring in clinics nowadays. However, the accuracy of this method is limited by the loss of signal due to the metabolic decay processes (biological washout). In this work, a generic modeling of washout was incorporated into the GATE simulation platform. Additionally, the influence of the washout on the β{sup +} activity distributions in terms of absolute quantification and spatial distribution was studied. Methods: First, the irradiation of a human head phantom with a {sup 12}C beam, so that a homogeneous dose distribution was achieved in the tumor, was simulated. The generated {sup 11}C and {sup 15}O distribution maps were used as β{sup +} sources in a second simulation, where the PET scanner was modeled following a detailed Monte Carlo approach. The activity distributions obtained in the presence and absence of washout processes for several clinical situations were compared. Results: Results show that activity values are highly reduced (by a factor of 2) in the presence of washout. These processes have a significant influence on the shape of the PET distributions. Differences in the distal activity falloff position of 4 mm are observed for a tumor dose deposition of 1 Gy (T{sub ini} = 0 min). However, in the case of high doses (3 Gy), the washout processes do not have a large effect on the position of the distal activity falloff (differences lower than 1 mm). The important role of the tumor washout parameters on the activity quantification was also evaluated. Conclusions: With this implementation, GATE/GEANT 4 is the only open-source code able to simulate the full chain from the hadrontherapy irradiation to the PET dose monitoring including biological effects. Results show the strong impact of the washout processes, indicating that the development of better models and measurement of biological washout data are
Fix, Michael K; Cygler, Joanna; Frei, Daniel; Volken, Werner; Neuenschwander, Hans; Born, Ernst J; Manser, Peter
2013-05-07
The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.
Waldmann, Patrik; Hallander, Jon; Hoti, Fabian; Sillanpää, Mikko J
2008-06-01
Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler.
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
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.
International Nuclear Information System (INIS)
Chetty, Indrin J.; Curran, Bruce; Cygler, Joanna E.; DeMarco, John J.; Ezzell, Gary; Faddegon, Bruce A.; Kawrakow, Iwan; Keall, Paul J.; Liu, Helen; Ma, C.-M. Charlie; Rogers, D. W. O.; Seuntjens, Jan; Sheikh-Bagheri, Daryoush; Siebers, Jeffrey V.
2007-01-01
The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and
International Nuclear Information System (INIS)
White, Morgan C.
2000-01-01
The fundamental motivation for the research presented in this dissertation was the need to development a more accurate prediction method for characterization of mixed radiation fields around medical electron accelerators (MEAs). Specifically, a model is developed for simulation of neutron and other particle production from photonuclear reactions and incorporated in the Monte Carlo N-Particle (MCNP) radiation transport code. This extension of the capability within the MCNP code provides for the more accurate assessment of the mixed radiation fields. The Nuclear Theory and Applications group of the Los Alamos National Laboratory has recently provided first-of-a-kind evaluated photonuclear data for a select group of isotopes. These data provide the reaction probabilities as functions of incident photon energy with angular and energy distribution information for all reaction products. The availability of these data is the cornerstone of the new methodology for state-of-the-art mutually coupled photon-neutron transport simulations. The dissertation includes details of the model development and implementation necessary to use the new photonuclear data within MCNP simulations. A new data format has been developed to include tabular photonuclear data. Data are processed from the Evaluated Nuclear Data Format (ENDF) to the new class ''u'' A Compact ENDF (ACE) format using a standalone processing code. MCNP modifications have been completed to enable Monte Carlo sampling of photonuclear reactions. Note that both neutron and gamma production are included in the present model. The new capability has been subjected to extensive verification and validation (V and V) testing. Verification testing has established the expected basic functionality. Two validation projects were undertaken. First, comparisons were made to benchmark data from literature. These calculations demonstrate the accuracy of the new data and transport routines to better than 25 percent. Second, the ability to
Energy Technology Data Exchange (ETDEWEB)
White, Morgan C. [Univ. of Florida, Gainesville, FL (United States)
2000-07-01
The fundamental motivation for the research presented in this dissertation was the need to development a more accurate prediction method for characterization of mixed radiation fields around medical electron accelerators (MEAs). Specifically, a model is developed for simulation of neutron and other particle production from photonuclear reactions and incorporated in the Monte Carlo N-Particle (MCNP) radiation transport code. This extension of the capability within the MCNP code provides for the more accurate assessment of the mixed radiation fields. The Nuclear Theory and Applications group of the Los Alamos National Laboratory has recently provided first-of-a-kind evaluated photonuclear data for a select group of isotopes. These data provide the reaction probabilities as functions of incident photon energy with angular and energy distribution information for all reaction products. The availability of these data is the cornerstone of the new methodology for state-of-the-art mutually coupled photon-neutron transport simulations. The dissertation includes details of the model development and implementation necessary to use the new photonuclear data within MCNP simulations. A new data format has been developed to include tabular photonuclear data. Data are processed from the Evaluated Nuclear Data Format (ENDF) to the new class ''u'' A Compact ENDF (ACE) format using a standalone processing code. MCNP modifications have been completed to enable Monte Carlo sampling of photonuclear reactions. Note that both neutron and gamma production are included in the present model. The new capability has been subjected to extensive verification and validation (V&V) testing. Verification testing has established the expected basic functionality. Two validation projects were undertaken. First, comparisons were made to benchmark data from literature. These calculations demonstrate the accuracy of the new data and transport routines to better than 25 percent. Second
Energy Technology Data Exchange (ETDEWEB)
Clouet, J.F.; Samba, G. [CEA Bruyeres-le-Chatel, 91 (France)
2005-07-01
We use asymptotic analysis to study the diffusion limit of the Symbolic Implicit Monte-Carlo (SIMC) method for the transport equation. For standard SIMC with piecewise constant basis functions, we demonstrate mathematically that the solution converges to the solution of a wrong diffusion equation. Nevertheless a simple extension to piecewise linear basis functions enables to obtain the correct solution. This improvement allows the calculation in opaque medium on a mesh resolving the diffusion scale much larger than the transport scale. Anyway, the huge number of particles which is necessary to get a correct answer makes this computation time consuming. Thus, we have derived from this asymptotic study an hybrid method coupling deterministic calculation in the opaque medium and Monte-Carlo calculation in the transparent medium. This method gives exactly the same results as the previous one but at a much lower price. We present numerical examples which illustrate the analysis. (authors)
International Nuclear Information System (INIS)
Karriem, Z.; Ivanov, K.; Zamonsky, O.
2011-01-01
This paper presents work that has been performed to develop an integrated Monte Carlo- Deterministic transport methodology in which the two methods make use of exactly the same general geometry and multigroup nuclear data. The envisioned application of this methodology is in reactor lattice physics methods development and shielding calculations. The methodology will be based on the Method of Long Characteristics (MOC) and the Monte Carlo N-Particle Transport code MCNP5. Important initial developments pertaining to ray tracing and the development of an MOC flux solver for the proposed methodology are described. Results showing the viability of the methodology are presented for two 2-D general geometry transport problems. The essential developments presented is the use of MCNP as geometry construction and ray tracing tool for the MOC, verification of the ray tracing indexing scheme that was developed to represent the MCNP geometry in the MOC and the verification of the prototype 2-D MOC flux solver. (author)
International Nuclear Information System (INIS)
Bacchetta, Alessandro; Jung, Hannes; Kutak, Krzysztof
2010-02-01
A method for tuning parameters in Monte Carlo generators is described and applied to a specific case. The method works in the following way: each observable is generated several times using different values of the parameters to be tuned. The output is then approximated by some analytic form to describe the dependence of the observables on the parameters. This approximation is used to find the values of the parameter that give the best description of the experimental data. This results in significantly faster fitting compared to an approach in which the generator is called iteratively. As an application, we employ this method to fit the parameters of the unintegrated gluon density used in the Cascade Monte Carlo generator, using inclusive deep inelastic data measured by the H1 Collaboration. We discuss the results of the fit, its limitations, and its strong points. (orig.)
International Nuclear Information System (INIS)
Kim, Hyeong Heon
2000-02-01
The equivalence theorem providing a relation between a homogeneous and a heterogeneous medium has been used in the resonance calculation for the heterogeneous system. The accuracy of the resonance calculation based on the equivalence theorem depends on how accurately the fuel collision probability is expressed by the rational terms. The fuel collision probability is related to the Dancoff factor in closely packed lattices. The calculation of the Dancoff factor is one of the most difficult problems in the core analysis because the actual configuration of fuel elements in the lattice is very complex. Most reactor physics codes currently used are based on the roughly calculated black Dancoff factor, where total cross section of the fuel is assumed to be infinite. Even the black Dancoff factors have not been calculated accurately though many methods have been proposed. The equivalence theorem based on the black Dancoff factor causes some errors inevitably due to the approximations involved in the Dancoff factor calculation and the derivation of the fuel collision probability, but they have not been evaluated seriously before. In this study, a Monte Carlo program - G-DANCOFF - was developed to calculate not only the traditional black Dancoff factor but also grey Dancoff factor where the medium is described realistically. G-DANCOFF calculates the Dancoff factor based on its collision probability definition in an arbitrary arrangement of cylindrical fuel pins in full three-dimensional fashion. G-DANCOFF was verified by comparing the black Dancoff factors calculated for the geometries where accurate solutions are available. With 100,000 neutron histories, the calculated results by G-DANCOFF were matched within maximum 1% and in most cases less than 0.2% with previous results. G-DANCOFF also provides graphical information on particle tracks which makes it possible to calculate the Dancoff factor independently. The effects of the Dancoff factor on the criticality calculation
Monte Carlo method for neutron transport calculations in graphics processing units (GPUs)
International Nuclear Information System (INIS)
Pellegrino, Esteban
2011-01-01
Monte Carlo simulation is well suited for solving the Boltzmann neutron transport equation in an inhomogeneous media for complicated geometries. However, routine applications require the computation time to be reduced to hours and even minutes in a desktop PC. The interest in adopting Graphics Processing Units (GPUs) for Monte Carlo acceleration is rapidly growing. This is due to the massive parallelism provided by the latest GPU technologies which is the most promising solution to the challenge of performing full-size reactor core analysis on a routine basis. In this study, Monte Carlo codes for a fixed-source neutron transport problem were developed for GPU environments in order to evaluate issues associated with computational speedup using GPUs. Results obtained in this work suggest that a speedup of several orders of magnitude is possible using the state-of-the-art GPU technologies. (author) [es
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.
International Nuclear Information System (INIS)
Capote, Roberto; Smith, Donald L.
2008-01-01
The Unified Monte Carlo method (UMC) has been suggested to avoid certain limitations and approximations inherent to the well-known Generalized Least Squares (GLS) method of nuclear data evaluation. This contribution reports on an investigation of the performance of the UMC method in comparison with the GLS method. This is accomplished by applying both methods to simple examples with few input values that were selected to explore various features of the evaluation process that impact upon the quality of an evaluation. Among the issues explored are: i) convergence of UMC results with the number of Monte Carlo histories and the ranges of sampled values; ii) a comparison of Monte Carlo sampling using the Metropolis scheme and a brute force approach; iii) the effects of large data discrepancies; iv) the effects of large data uncertainties; v) the effects of strong or weak model or experimental data correlations; and vi) the impact of ratio data and integral data. Comparisons are also made of the evaluated results for these examples when the input values are first transformed to comparable logarithmic values prior to performing the evaluation. Some general conclusions that are applicable to more realistic evaluation exercises are offered
Palmer, Grant; Prabhu, Dinesh; Cruden, Brett A.
2013-01-01
The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While
Green, Carla A; Duan, Naihua; Gibbons, Robert D; Hoagwood, Kimberly E; Palinkas, Lawrence A; Wisdom, Jennifer P
2015-09-01
Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings.
Dosimetry of 252Cf medical sources using Monte-Carlo methods
International Nuclear Information System (INIS)
Wierzbicki, J.G.; Roberts, W.; Rivard, M.J.; Fontanesi, J.
1996-01-01
Dosimetric measurements are the only way to calibrate radioactive sources. Dose distribution around sources have also been determined experimentally, but in recent years, dramatic technological developments have made computer simulations an attractive method for dose distribution studies. Monte Carlo simulations are especially useful if the radiation field has several components with different biological properties. The dose in the vicinity of 252 Cf source has five components: primary fast neutron, primary photon, secondary 2.2 MeV photon from the H(n,γ) reaction, protons from the 14 N(n,p) reaction, and products of the boron neutron capture reaction if the tumor is augmented by 10 B. The RBE values for these components are different, and their independent determination is essential for 252 Cf brachytherapy. We used MCNP, neutron-photon transport code to calculate all five components of the total dose. The 252 Cf medical source is 2.3 cm long and has diameter 2.8 mm. To construct along-away tables, we divided the volume into cells using concentric cylinders with the source length and planes perpendicular to the source. The computer simulated both neutron and photon histories using cross sections provided by the code library. The neutron/photon energy spectrum and kerma values for particular components were made based on the most recent data available. Results of neutron/photon flux and dose rates were obtained for all cells. Based on these data, along-away tables were constructed for all components of the total dose which will be entered into the treatment planning computer and used for total dose calculations with the appropriate RBE multipliers. Similar calculations may also be done for 252 Cf source of any design
Davis, A. D.; Heimbach, P.; Marzouk, Y.
2017-12-01
We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice
Directory of Open Access Journals (Sweden)
T. A. Mikhailova
2016-01-01
Full Text Available In the paper the algorithm of modeling of continuous low-temperature free-radical butadiene-styrene copolymerization process in emulsion based on the Monte-Carlo method is offered. This process is the cornerstone of industrial production butadiene – styrene synthetic rubber which is the most widespread large-capacity rubber of general purpose. Imitation of growth of each macromolecule of the formed copolymer and tracking of the processes happening to it is the basis of algorithm of modeling. Modeling is carried out taking into account residence-time distribution of particles in system that gives the chance to research the process proceeding in the battery of consistently connected polymerization reactors. At the same time each polymerization reactor represents the continuous stirred tank reactor. Since the process is continuous, it is considered continuous addition of portions to the reaction mixture in the first reactor of battery. The constructed model allows to research molecular-weight and viscous characteristics of the formed copolymerization product, to predict the mass content of butadiene and styrene in copolymer, to carry out calculation of molecular-weight distribution of the received product at any moment of conducting process. According to the results of computational experiments analyzed the influence of mode of the process of the regulator introduced during the maintaining on change of characteristics of the formed butadiene-styrene copolymer. As the considered process takes place with participation of monomers of two types, besides listed the model allows to research compositional heterogeneity of the received product that is to carry out calculation of composite distribution and distribution of macromolecules for the size and structure. On the basis of the proposed algorithm created the software tool that allows you to keep track of changes in the characteristics of the resulting product in the dynamics.
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.
Implementation of TDCR method in KRISS
International Nuclear Information System (INIS)
Lee, K.B.; Man Lee, Jong; Soon Park, Tae; Hwang, HanYull
2004-01-01
Among the LSC techniques used for the standardization of radionuclides, the TDCR method is the only absolute measurement technique. This method consists of the theoretical calculations of counting efficiencies and the experimental data obtained using a special liquid scintillation equipment. Design, construction and characteristics of the KRISS TDCR systems are reported. Also presented are the preliminary results of the activity measurements for the pure-beta emitting nuclides of H3 and C14
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.
International Nuclear Information System (INIS)
Rodrigues, Leticia Jenisch; Bogado, Sergio; Vilhena, Marco T.
2008-01-01
The WIMS code is a well known and one of the most used codes to handle nuclear core physics calculations. Recently, the PIJM module of the WIMS code was modified in order to allow the calculation of Grey Dancoff factors, for partially absorbing materials, using the alternative definition in terms of escape and collision probabilities. Grey Dancoff factors for the Canadian CANDU-37 and CANFLEX assemblies were calculated with PIJM at five symmetrically distinct fuel pin positions. The results, obtained via Direct Method, i.e., by direct calculation of escape and collision probabilities, were satisfactory when compared with the ones of literature. On the other hand, the PIJMC module was developed to calculate escape and collision probabilities using Monte Carlo method. Modifications in this module were performed to determine Black Dancoff factors, considering perfectly absorbing fuel rods. In this work, we proceed further in the task of validating the Direct Method by the Monte Carlo approach. To this end, the PIJMC routine is modified to compute Grey Dancoff factors using the cited alternative definition. Results are reported for the mentioned CANDU-37 and CANFLEX assemblies obtained with PIJMC, at the same fuel pin positions as with PIJM. A good agreement is observed between the results from the Monte Carlo and Direct methods
Evaluation of Monte Carlo Codes Regarding the Calculated Detector Response Function in NDP Method
Energy Technology Data Exchange (ETDEWEB)
Tuan, Hoang Sy Minh; Sun, Gwang Min; Park, Byung Gun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-10-15
The basis of the NDP is the irradiation of a sample with a thermal or cold neutron beam and the subsequent release of charged particles due to neutron-induced exoergic charged particle reactions. Neutrons interact with the nuclei of elements and release mono-energetic charged particles, e.g. alpha particles or protons, and recoil atoms. Depth profile of the analyzed element can be obtained by making a linear transformation of the measured energy spectrum by using the stopping power of the sample material. A few micrometer of the material can be analyzed nondestructively, and on the order of 10nm depth resolution can be obtained depending on the material type with NDP method. In the NDP method, the one first steps of the analytical process is a channel-energy calibration. This calibration is normally made with the experimental measurement of NIST Standard Reference Material sample (SRM-93a). In this study, some Monte Carlo (MC) codes were tried to calculate the Si detector response function when this detector accounted the energy charges particles emitting from an analytical sample. In addition, these MC codes were also tried to calculate the depth distributions of some light elements ({sup 10}B, {sup 3}He, {sup 6}Li, etc.) in SRM-93a and SRM-2137 samples. These calculated profiles were compared with the experimental profiles and SIMS profiles. In this study, some popular MC neutron transport codes are tried and tested to calculate the detector response function in the NDP method. The simulations were modeled based on the real CN-NDP system which is a part of Cold Neutron Activation Station (CONAS) at HANARO (KAERI). The MC simulations are very successful at predicting the alpha peaks in the measured energy spectrum. The net area difference between the measured and predicted alpha peaks are less than 1%. A possible explanation might be bad cross section data set usage in the MC codes for the transport of low energetic lithium atoms inside the silicon substrate.
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
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
International Nuclear Information System (INIS)
Gereben, O; Pusztai, L; McGreevy, R L
2010-01-01
A new reverse Monte Carlo (RMC) method has been developed for creating three-dimensional structures in agreement with small angle scattering data. Extensive tests, using computer generated quasi-experimental data for aggregation processes via constrained RMC and Langevin molecular dynamics, were performed. The software is capable of fitting several consecutive time frames of scattering data, and movie-like visualization of the structure (and its evolution) either during or after the simulation is also possible.
Augmented reality implementation methods in mainstream applications
Directory of Open Access Journals (Sweden)
David Procházka
2011-01-01
Full Text Available Augmented reality has became an useful tool in many areas from space exploration to military applications. Although used theoretical principles are well known for almost a decade, the augmented reality is almost exclusively used in high budget solutions with a special hardware. However, in last few years we could see rising popularity of many projects focused on deployment of the augmented reality on different mobile devices. Our article is aimed on developers who consider development of an augmented reality application for the mainstream market. Such developers will be forced to keep the application price, therefore also the development price, at reasonable level. Usage of existing image processing software library could bring a signiﬁcant cut-down of the development costs. In the theoretical part of the article is presented an overview of the augmented reality application structure. Further, an approach for selection appropriate library as well as the review of the existing software libraries focused in this area is described. The last part of the article outlines our implementation of key parts of the augmented reality application using the OpenCV library.
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.
Energy Technology Data Exchange (ETDEWEB)
Del Nero, Renata Aline; Yoriyaz, Hélio [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Nakandakari, Marcos Vinicius Nakaoka, E-mail: hyoriyaz@ipen.br, E-mail: marcos.sake@gmail.com [Hospital Beneficência Portuguesa de São Paulo, SP (Brazil)
2017-07-01
The Monte Carlo method for radiation transport data has been adapted for medical physics application. More specifically, it has received more attention in clinical treatment planning with the development of more efficient computer simulation techniques. In linear accelerator modeling by the Monte Carlo method, the phase space data file (phsp) is used a lot. However, to obtain precision in the results, it is necessary detailed information about the accelerator's head and commonly the supplier does not provide all the necessary data. An alternative to the phsp is the Virtual Source Model (VSM). This alternative approach presents many advantages for the clinical Monte Carlo application. This is the most efficient method for particle generation and can provide an accuracy similar when the phsp is used. This research propose a VSM simulation with the use of a Virtual Flattening Filter (VFF) for profiles and percent deep doses calculation. Two different sizes of open fields (40 x 40 cm² and 40√2 x 40√2 cm²) were used and two different source to surface distance (SSD) were applied: the standard 100 cm and custom SSD of 370 cm, which is applied in radiotherapy treatments of total body irradiation. The data generated by the simulation was analyzed and compared with experimental data to validate the VSM. This current model is easy to build and test. (author)
Modeling dose-rate on/over the surface of cylindrical radio-models using Monte Carlo methods
International Nuclear Information System (INIS)
Xiao Xuefu; Ma Guoxue; Wen Fuping; Wang Zhongqi; Wang Chaohui; Zhang Jiyun; Huang Qingbo; Zhang Jiaqiu; Wang Xinxing; Wang Jun
2004-01-01
Objective: To determine the dose-rates on/over the surface of 10 cylindrical radio-models, which belong to the Metrology Station of Radio-Geological Survey of CNNC. Methods: The dose-rates on/over the surface of 10 cylindrical radio-models were modeled using the famous Monte Carlo code-MCNP. The dose-rates on/over the surface of 10 cylindrical radio-models were measured by a high gas pressurized ionization chamber dose-rate meter, respectively. The values of dose-rate modeled using MCNP code were compared with those obtained by authors in the present experimental measurement, and with those obtained by other workers previously. Some factors causing the discrepancy between the data obtained by authors using MCNP code and the data obtained using other methods are discussed in this paper. Results: The data of dose-rates on/over the surface of 10 cylindrical radio-models, obtained using MCNP code, were in good agreement with those obtained by other workers using the theoretical method. They were within the discrepancy of ±5% in general, and the maximum discrepancy was less than 10%. Conclusions: As if each factor needed for the Monte Carlo code is correct, the dose-rates on/over the surface of cylindrical radio-models modeled using the Monte Carlo code are correct with an uncertainty of 3%
Implementing Assessment Methods in Plastic Surgery.
Gosman, Amanda; Mann, Karen; Reid, Christopher M; Vedder, Nicholas B; Janis, Jeffrey E
2016-03-01
Principles of effective assessment have become increasingly popular topics in graduate medical education. Changes in the structure of plastic surgery training demand a thorough understanding of the state-of-the-art in assessing surgical trainees. Moreover, the authors' understanding of different domains and methods of assessment and the available tools continues to grow. The authors reviewed the available literature regarding assessment in graduate medical education, specifically as it pertains to plastic surgery. In addition, the authors present principles of effective assessment and report on the currently available assessment methods. Assessment is multifaceted and impacts everyone, not just the individual learner. For assessments to be useful, they need to possess validity and reliability. Moreover, there is a necessary pragmatism limiting different methods and tools for assessing learners. Some types of assessment are universally familiar and include examples such as written examinations and procedural logs. Other emerging areas that are actively being researched involve simulation, nontechnical skills, and procedure-specific technical assessments. Updating the thoroughness and multidimensionality with which plastic surgery trainees are assessed is an evolving area and one that is ripe for continued research.
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2010-01-01
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...... might be prohibitive long. In such cases the property mentioned above for the FORM reliability index can be assumed valid in the Monte Carlo simulations making it possible to increase the out-crossing rates and thus reduced the necessary length of the time domain simulations by applying a larger......-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...
Monte-Carlo method simulation of the Bremsstrahlung mirror reflection experiment
International Nuclear Information System (INIS)
Aliev, F.K.; Muminov, A.T.; Skvortsov, V.V.; Osmanov, B.S.
2004-01-01
Full text: To detect gamma-ray mirror reflection on macroscopic smooth surface a search experiment at microtron MT-22S with 330 meter flying distance is in progress. Measured slip angles (i.e. angles between incident ray and reflector surface) don't exceed tens of micro-radian. Under such angles an effect of the reflection could be easily veiled due to negative background conditions. That is why the process needed to be simulated by Monte-Carlo method as accurate as possible and corresponding computer program was developed. A first operating mode of the MT-22S generates 13 MeV electrons that are incident on a Bremsstrahlung target. So energies of gamma-rays were simulated to be in the range of 0.01†12.5 MeV and be distributed by known Shift formula. When any gamma-quantum was incident on the reflector it resulted in following two cases. If its slip angle was more than the critical one, gamma-quantum was to be absorbed by the reflector and the program started to simulate next event. In the other case the program replaced incident gamma-quantum trajectory parameters by the reflected ones. The gamma-quantum trajectory behind the reflector was traced till its detector. Any gamma-quantum that got the detector was to be registered. As any simulated gamma-quantum was of random energy the critical slip angle of every simulated event was evaluated by the following formula: α crit = eh/E √ZN A ρ/πAm. Table values of the absorption coefficients were used for random simulation of gamma-quanta absorption in the air. And it was assumed that any gamma-quantum interaction with air resulted in its disappearance. Dependence of different flying distances (120 and 330 m), gap heights (10, 20 and 50 μ) of the gap collimator and inclinations (20 and 40 μrad) of the reflector's plane on detected gamma-quanta energy distribution and vertical angle one was studied with a help of the developed program
A calibration method for whole-body counters, using Monte Carlo simulation
International Nuclear Information System (INIS)
Ishikawa, T.; Matsumoto, M.; Uchiyama, M.
1996-01-01
A Monte Carlo simulation code was developed to estimate the counting efficiencies in whole-body counting for various body sizes. The code consists of mathematical models and parameters which are categorised into three groups: a geometrical model for phantom and detectors, a photon transport model, and a detection system model. Photon histories were simulated with these models. The counting efficiencies for five 137 Cs block phantoms of different sizes were calculated by the code and compared with those measured with a whole-body counter at NIRS (Japan). The phantoms corresponded to a newborn, a 5 month old, a 6 year old, and 11 year old and an adult. The differences between the measured and calculated values were within 6%. For the adult phantom, the difference was 0.5%. The results suggest that the Monte Carlo simulation code can be used to estimate the counting efficiencies for various body sizes. (Author)
A calibration method for whole-body counters, using Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Ishikawa, T.; Matsumoto, M.; Uchiyama, M. [National Inst. of Radiological Sciences, Chiba (Japan)
1996-11-01
A Monte Carlo simulation code was developed to estimate the counting efficiencies in whole-body counting for various body sizes. The code consists of mathematical models and parameters which are categorised into three groups: a geometrical model for phantom and detectors, a photon transport model, and a detection system model. Photon histories were simulated with these models. The counting efficiencies for five {sup 137}Cs block phantoms of different sizes were calculated by the code and compared with those measured with a whole-body counter at NIRS (Japan). The phantoms corresponded to a newborn, a 5 month old, a 6 year old, and 11 year old and an adult. The differences between the measured and calculated values were within 6%. For the adult phantom, the difference was 0.5%. The results suggest that the Monte Carlo simulation code can be used to estimate the counting efficiencies for various body sizes. (Author).
International Nuclear Information System (INIS)
Momennezhad, Mehdi; Nasseri, Shahrokh; Zakavi, Seyed Rasoul; Parach, Ali Asghar; Ghorbani, Mahdi; Asl, Ruhollah Ghahraman
2016-01-01
Single-photon emission computed tomography (SPECT)-based tracers are easily available and more widely used than positron emission tomography (PET)-based tracers, and SPECT imaging still remains the most prevalent nuclear medicine imaging modality worldwide. The aim of this study is to implement an image-based Monte Carlo method for patient-specific three-dimensional (3D) absorbed dose calculation in patients after injection of 99m Tc-hydrazinonicotinamide (hynic)-Tyr 3 -octreotide as a SPECT radiotracer. 99m Tc patient-speci@@@@@@c S values and the absorbed doses were calculated with GATE code for each source-target organ pair in four patients who were imaged for suspected neuroendocrine tumors. Each patient underwent multiple whole-body planar scans as well as SPECT imaging over a period of 1-24 h after intravenous injection of 99m hynic-Tyr 3 -octreotide. The patient-specific S values calculated by GATE Monte Carlo code and the corresponding S values obtained by MIRDOSE program differed within 4.3% on an average for self-irradiation, and differed within 69.6% on an average for cross-irradiation. However, the agreement between total organ doses calculated by GATE code and MIRDOSE program for all patients was reasonably well (percentage difference was about 4.6% on an average). Normal and tumor absorbed doses calculated with GATE were slightly higher than those calculated with MIRDOSE program. The average ratio of GATE absorbed doses to MIRDOSE was 1.07 ± 0.11 (ranging from 0.94 to 1.36). According to the results, it is proposed that when cross-organ irradiation is dominant, a comprehensive approach such as GATE Monte Carlo dosimetry be used since it provides more reliable dosimetric results
Simulation based sequential Monte Carlo methods for discretely observed Markov processes
Neal, Peter
2014-01-01
Parameter estimation for discretely observed Markov processes is a challenging problem. However, simulation of Markov processes is straightforward using the Gillespie algorithm. We exploit this ease of simulation to develop an effective sequential Monte Carlo (SMC) algorithm for obtaining samples from the posterior distribution of the parameters. In particular, we introduce two key innovations, coupled simulations, which allow us to study multiple parameter values on the basis of a single sim...
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 222 Rn decay products was developed. The distributions of the relevant factors, including air sampling and radionuclide collection, are propagated using Monte Carlo simulation to the final distribution of the measurement results. The uncertainties of the 222 Rn decay products concentrations in the air are realistically evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.
A highly heterogeneous 3D PWR core benchmark: deterministic and Monte Carlo method comparison
Jaboulay, J.-C.; Damian, F.; Douce, S.; Lopez, F.; Guenaut, C.; Aggery, A.; Poinot-Salanon, C.
2014-06-01
Physical analyses of the LWR potential performances with regards to the fuel utilization require an important part of the work dedicated to the validation of the deterministic models used for theses analyses. Advances in both codes and computer technology give the opportunity to perform the validation of these models on complex 3D core configurations closed to the physical situations encountered (both steady-state and transient configurations). In this paper, we used the Monte Carlo Transport code TRIPOLI-4®; to describe a whole 3D large-scale and highly-heterogeneous LWR core. The aim of this study is to validate the deterministic CRONOS2 code to Monte Carlo code TRIPOLI-4®; in a relevant PWR core configuration. As a consequence, a 3D pin by pin model with a consistent number of volumes (4.3 millions) and media (around 23,000) is established to precisely characterize the core at equilibrium cycle, namely using a refined burn-up and moderator density maps. The configuration selected for this analysis is a very heterogeneous PWR high conversion core with fissile (MOX fuel) and fertile zones (depleted uranium). Furthermore, a tight pitch lattice is selcted (to increase conversion of 238U in 239Pu) that leads to harder neutron spectrum compared to standard PWR assembly. In these conditions two main subjects will be discussed: the Monte Carlo variance calculation and the assessment of the diffusion operator with two energy groups for the core calculation.
International Nuclear Information System (INIS)
Nagaya, Yasunobu; Okumura, Keisuke; Mori, Takamasa; Nakagawa, Masayuki
2005-06-01
In order to realize fast and accurate Monte Carlo simulation of neutron and photon transport problems, two vectorized Monte Carlo codes MVP and GMVP have been developed at JAERI. MVP is based on the continuous energy model and GMVP is on the multigroup model. Compared with conventional scalar codes, these codes achieve higher computation speed by a factor of 10 or more on vector super-computers. Both codes have sufficient functions for production use by adopting accurate physics model, geometry description capability and variance reduction techniques. The first version of the codes was released in 1994. They have been extensively improved and new functions have been implemented. The major improvements and new functions are (1) capability to treat the scattering model expressed with File 6 of the ENDF-6 format, (2) time-dependent tallies, (3) reaction rate calculation with the pointwise response function, (4) flexible source specification, (5) continuous-energy calculation at arbitrary temperatures, (6) estimation of real variances in eigenvalue problems, (7) point detector and surface crossing estimators, (8) statistical geometry model, (9) function of reactor noise analysis (simulation of the Feynman-α experiment), (10) arbitrary shaped lattice boundary, (11) periodic boundary condition, (12) parallelization with standard libraries (MPI, PVM), (13) supporting many platforms, etc. This report describes the physical model, geometry description method used in the codes, new functions and how to use them. (author)
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.
A Model Based Security Testing Method for Protocol Implementation
Directory of Open Access Journals (Sweden)
Yu Long Fu
2014-01-01
Full Text Available The security of protocol implementation is important and hard to be verified. Since the penetration testing is usually based on the experience of the security tester and the specific protocol specifications, a formal and automatic verification method is always required. In this paper, we propose an extended model of IOLTS to describe the legal roles and intruders of security protocol implementations, and then combine them together to generate the suitable test cases to verify the security of protocol implementation.
Formalization and Implementation of Algebraic Methods in Geometry
Directory of Open Access Journals (Sweden)
Filip Marić
2012-02-01
Full Text Available We describe our ongoing project of formalization of algebraic methods for geometry theorem proving (Wu's method and the Groebner bases method, their implementation and integration in educational tools. The project includes formal verification of the algebraic methods within Isabelle/HOL proof assistant and development of a new, open-source Java implementation of the algebraic methods. The project should fill-in some gaps still existing in this area (e.g., the lack of formal links between algebraic methods and synthetic geometry and the lack of self-contained implementations of algebraic methods suitable for integration with dynamic geometry tools and should enable new applications of theorem proving in education.
Energy Technology Data Exchange (ETDEWEB)
Grant, Carlos; Marconi, Javier; Serra, Oscar [Comision Nacional de Energia Atomica, Buenos Aires (Argentina)]. E-mail: grant@cnea.gov.ar; Mollerach, Ricardo; Fink, Jose [Nucleoelectrica Argentina S.A., Buenos Aires (Argentina)]. E-mail: RMollerach@na-sa.com.ar; JFink@na-sa.com.ar
2005-07-01
Nowadays, the increased calculation capacity of modern computers allows us to evaluate the 2D and 3D flux and power distribution of nuclear reactor in a reasonable amount of time using a Monte Carlo method. This method gives results that can be considered the most reliable evaluation of flux and power distribution with a great amount of detail. This is the reason why these results can be considered as benchmark cases that can be used for the validation of other methods. For this purpose, idealized models were calculated using Monte Carlo (code MCNP5) for the ATUCHA I reactor. 2D and 3D cases with and without control rods and channels without fuel element were analyzed. All of them were modeled using a finite element code (DELFIN) and a finite difference code (PUMA). In both cases two energy groups were use. (author)
Energy Technology Data Exchange (ETDEWEB)
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.
Implementing Adaptive Educational Methods with IMS Learning Design
Specht, Marcus; Burgos, Daniel
2006-01-01
Please, cite this publication as: Specht, M. & Burgos, D. (2006). Implementing Adaptive Educational Methods with IMS Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org
Efficient and effective implementation of alternative project delivery methods.
2017-05-01
Over the past decade, the Maryland Department of Transportation State Highway : Administration (MDOT SHA) has implemented Alternative Project Delivery (APD) methods : in a number of transportation projects. While these innovative practices have produ...
Use of Monte Carlo Methods for determination of isodose curves in brachytherapy
International Nuclear Information System (INIS)
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)
Application of voxel phantoms and Monte Carlo methods to internal and external dosimetry
International Nuclear Information System (INIS)
Hunt, J.G.; Santos, D. de S.; Silva, F.C. da; Dantas, B.M.; Azeredo, A.; Malatova, I.; Foltanova, S.
2000-01-01
Voxel phantoms and the Monte Carlo technique are applied to the areas of calibration of in vivo measurement systems, Specific Effective Energy calculations, and dose calculations due to external sources of radiation. The main advantages of the use of voxel phantoms is their high level of detail of body structures, and the ease with which their physical dimensions can be changed. For the simulation of in vivo measurement systems for calibration purposes, a voxel phantom with a format of 871 'slices' each of 277 x 148 picture elements was used. The Monte Carlo technique is used to simulate the tissue contamination, to transport the photons through the tissues and to simulate the detection of the radiation. For benchmarking, the program was applied to obtain calibration factors for the in vivo measurement of 241 Am, U nat and 137 Cs deposited in various tissues or in the whole body, as measured with a NaI or Gernlanium detector. The calculated and real activities in all cases were found to be in good agreement. For the calculation of Specific Effective Energies (SEEs) and the calculation of dose received from external sources, the Yale voxel phantom with a format of 493 slices' each of 87 x 147 picture elements was used. The Monte Carlo program was developed to calculate external doses due to environmental, occupational or accidental exposures. The program calculates tissue and effective dose for the following geometries: cloud immersion, ground contamination, X-ray irradiation, point source irradiation or others. The benchmarking results for the external source are in good agreement with the measured values. The results obtained for the SEEs are compatible with the ICRP values. (author)
東條, 匡志; tojo, masashi
2007-01-01
In this study, a BWR core calculation method is developed. The continuous energy Monte Carlo burn-up calculation code is newly applied to BWR assembly calculations of production level. The applicability of the present new calculation method is verified through the tracking-calculation of commercial BWR.The mechanism and quantitative effects of the error propagations, the spatial discretization and of the temperature distribution in fuel pellet on the Monte Carlo burn-up calculations are clari...
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.
Energy Technology Data Exchange (ETDEWEB)
Ureba, A.; Palma, B. A.; Leal, A.
2011-07-01
Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.
Evaluation of occupational exposure in interventionist procedures using Monte Carlo Method
International Nuclear Information System (INIS)
Santos, William S.; Neves, Lucio P.; Perini, Ana P.; Caldas, Linda V.E.; Belinato, Walmir; Maia, Ana F.
2014-01-01
This study presents a computational model of exposure for a patient, cardiologist and nurse in a typical scenario of cardiac interventional procedures. In this case a set of conversion coefficient (CC) for effective dose (E) in terms of kerma-area product (KAP) for all individuals involved using seven different energy spectra and eight beam projections. The CC was also calculated for the entrance skin dose (ESD) normalized to the PKA for the patient. All individuals were represented by anthropomorphic phantoms incorporated in a radiation transport code based on Monte Carlo simulation. (author)
International Nuclear Information System (INIS)
Voter, A.F.
1985-01-01
We present a new Monte Carlo procedure for determining the Helmholtz free-energy difference between two systems that are separated in configuration space. Unlike most standard approaches, no integration over intermediate potentials is required. A Metropolis walk is performed for each system, and the average Metropolis acceptance probability for a hypothetical step along a probe vector into the other system is accumulated. Either classical or quantum free energies may be computed, and the procedure is also ideally suited for evaluating generalized transition state theory rate constants. As an application we determine the relative free energies of three configurations of a tungsten dimer on the W(110) surface
Effective dose in individuals from exposure the patients treated with 131I using Monte Carlo method
International Nuclear Information System (INIS)
Carvalho Junior, Alberico B. de; Silva, Ademir X.
2007-01-01
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 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)
A hybrid method for evaluating enterprise architecture implementation.
Nikpay, Fatemeh; Ahmad, Rodina; Yin Kia, Chiam
2017-02-01
Enterprise Architecture (EA) implementation evaluation provides a set of methods and practices for evaluating the EA implementation artefacts within an EA implementation project. There are insufficient practices in existing EA evaluation models in terms of considering all EA functions and processes, using structured methods in developing EA implementation, employing matured practices, and using appropriate metrics to achieve proper evaluation. The aim of this research is to develop a hybrid evaluation method that supports achieving the objectives of EA implementation. To attain this aim, the first step is to identify EA implementation evaluation practices. To this end, a Systematic Literature Review (SLR) was conducted. Second, the proposed hybrid method was developed based on the foundation and information extracted from the SLR, semi-structured interviews with EA practitioners, program theory evaluation and Information Systems (ISs) evaluation. Finally, the proposed method was validated by means of a case study and expert reviews. This research provides a suitable foundation for researchers who wish to extend and continue this research topic with further analysis and exploration, and for practitioners who would like to employ an effective and lightweight evaluation method for EA projects. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
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.
International Nuclear Information System (INIS)
Yang, M.; Liu, F.; Smallwood, G.J.
2004-01-01
Laser-Induced Incandescence (LII) technique has been widely used to measure soot volume fraction and primary particle size in flames and engine exhaust. Currently there is lack of quantitative understanding of the shielding effect of aggregated soot particles on its conduction heat loss rate to the surrounding gas. The conventional approach for this problem would be the application of the Monte Carlo (MC) method. This method is based on simulation of the trajectories of individual molecules and calculation of the heat transfer at each of the molecule/molecule collisions and the molecule/particle collisions. As the first step toward calculating the heat transfer between a soot aggregate and the surrounding gas, the Direct Simulation Monte Carlo (DSMC) method was used in this study to calculate the heat transfer rate between a single spherical aerosol particle and its cooler surrounding gas under different conditions of temperature, pressure, and the accommodation coefficient. A well-defined and simple hard sphere model was adopted to describe molecule/molecule elastic collisions. A combination of the specular reflection and completely diffuse reflection model was used to consider molecule/particle collisions. The results obtained by DSMC are in good agreement with the known analytical solution of heat transfer rate for an isolated, motionless sphere in the free-molecular regime. Further the DSMC method was applied to calculate the heat transfer in the transition regime. Our present DSMC results agree very well with published DSMC data. (author)
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.
Palenčár, Rudolf; Sopkuliak, Peter; Palenčár, Jakub; Ďuriš, Stanislav; Suroviak, Emil; Halaj, Martin
2017-06-01
Evaluation of uncertainties of the temperature measurement by standard platinum resistance thermometer calibrated at the defining fixed points according to ITS-90 is a problem that can be solved in different ways. The paper presents a procedure based on the propagation of distributions using the Monte Carlo method. The procedure employs generation of pseudo-random numbers for the input variables of resistances at the defining fixed points, supposing the multivariate Gaussian distribution for input quantities. This allows taking into account the correlations among resistances at the defining fixed points. Assumption of Gaussian probability density function is acceptable, with respect to the several sources of uncertainties of resistances. In the case of uncorrelated resistances at the defining fixed points, the method is applicable to any probability density function. Validation of the law of propagation of uncertainty using the Monte Carlo method is presented on the example of specific data for 25 Ω standard platinum resistance thermometer in the temperature range from 0 to 660 °C. Using this example, we demonstrate suitability of the method by validation of its results.
Czech Academy of Sciences Publication Activity Database
Moučka, F.; Nezbeda, Ivo
2010-01-01
Roč. 36, 7-8 (2010), s. 526-534 ISSN 0892-7022 Institutional research plan: CEZ:AV0Z40720504 Keywords : multi-particle move MC * graphics processing unit * polarisable model Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.215, year: 2010
Evaluation of high packing density powder X-ray screens by Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Liaparinos, P. [Department of Medical Physics, Medical School, University of Patras, 26500 Patras (Greece); Kandarakis, I.; Cavouras, D. [Department of Medical Instruments Technology, Technological Educational Institution of Athens, Ag. Spyridonos Street, Aigaleo, 12210 Athens (Greece); Kalivas, N. [Greek Atomic Energy Commission, 15310 Athens (Greece); Delis, H. [Department of Medical Physics, Medical School, University of Patras, 26500 Patras (Greece); Panayiotakis, G. [Department of Medical Physics, Medical School, University of Patras, 26500 Patras (Greece)], E-mail: panayiot@upatras.gr
2007-09-21
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{sub 2}O{sub 2}S:Tb phosphor material with packing density of 70% and grain size of 7 {mu}m and (c) phosphor thickness ranging between 30 and 70 mg/cm{sup 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{sup 2} phosphor thickness. It was found that high packing density screens may be appropriate for use in medical radiographic systems.
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.
Gudjonson, Herman; Kats, Mikhail A.; Liu, Kun; Nie, Zhihong; Kumacheva, Eugenia; Capasso, Federico
2014-01-01
Many experimental systems consist of large ensembles of uncoupled or weakly interacting elements operating as a single whole; this is particularly the case for applications in nano-optics and plasmonics, including colloidal solutions, plasmonic or dielectric nanoparticles on a substrate, antenna arrays, and others. In such experiments, measurements of the optical spectra of ensembles will differ from measurements of the independent elements as a result of small variations from element to element (also known as polydispersity) even if these elements are designed to be identical. In particular, sharp spectral features arising from narrow-band resonances will tend to appear broader and can even be washed out completely. Here, we explore this effect of inhomogeneous broadening as it occurs in colloidal nanopolymers comprising self-assembled nanorod chains in solution. Using a technique combining finite-difference time-domain simulations and Monte Carlo sampling, we predict the inhomogeneously broadened optical spectra of these colloidal nanopolymers and observe significant qualitative differences compared with the unbroadened spectra. The approach combining an electromagnetic simulation technique with Monte Carlo sampling is widely applicable for quantifying the effects of inhomogeneous broadening in a variety of physical systems, including those with many degrees of freedom that are otherwise computationally intractable. PMID:24469797
Evaluation of high packing density powder X-ray screens by Monte Carlo methods
International Nuclear Information System (INIS)
Liaparinos, P.; Kandarakis, I.; Cavouras, D.; Kalivas, N.; Delis, H.; Panayiotakis, G.
2007-01-01
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 2 O 2 S: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
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.
Sun, Hai-Feng; Sun, Feng-Xian; Xia, Xin-Lin
2018-01-01
A hybrid method combing the unstructured finite volume method and the Monte Carlo method and incorporating the line-by-line model has been developed to simulate the radiative transfer in highly spectral and inhomogeneous medium. In this method, the unstructured finite volume method is adopted to solve the spectral radiative transfer equation at wave numbers or spectral locations determined by the Monte Carlo method. The Monte Carlo method takes effects by firstly defining the monotonic random number relations corresponding to the spectral emitted power density of every discretized element of the concerning medium, and then by reversing the spectral location through comparison of these relations with predefined random numbers. Through this Monte Carlo method, the actual number of spectral locations on which the spectral radiative transfer equations are solved may be reduced: only the spectral locations that have higher spectral emissive powers would be more possibly selected. To increase the performance of the presented method, the total variation diminishing scheme on unstructured grids is adopted in treating the spectral radiative intensity at interface between control volumes. And, the discretized radiative transfer equation is implicitly and iteratively solved by an algebraic multi-grid solution approach to accelerate the convergence of the equation. The presented method was applied to 3D homogeneous and inhomogeneous cases for the validation and performance studies. Results show that for both cases, the presented method agree well with pure Monte Carlo benchmark solutions with acceptable number of spectral locations and computing time.
International Nuclear Information System (INIS)
Harris, S.; Dave Dunn, D.
2009-01-01
The sensitivity of two specific types of radionuclide detectors for conducting an on-board search in the maritime environment was evaluated using Monte Carlo simulation implemented in AVERT(reg s ign). AVERT(reg s ign), short for the Automated Vulnerability Evaluation for Risk of Terrorism, is personal computer based vulnerability assessment software developed by the ARES Corporation. The sensitivity of two specific types of radionuclide detectors for conducting an on-board search in the maritime environment was evaluated using Monte Carlo simulation. The detectors, a RadPack and also a Personal Radiation Detector (PRD), were chosen from the class of Human Portable Radiation Detection Systems (HPRDS). Human Portable Radiation Detection Systems (HPRDS) serve multiple purposes. In the maritime environment, there is a need to detect, localize, characterize, and identify radiological/nuclear (RN) material or weapons. The RadPack is a commercially available broad-area search device used for gamma and also for neutron detection. The PRD is chiefly used as a personal radiation protection device. It is also used to detect contraband radionuclides and to localize radionuclide sources. Neither device has the capacity to characterize or identify radionuclides. The principal aim of this study was to investigate the sensitivity of both the RadPack and the PRD while being used under controlled conditions in a simulated maritime environment for detecting hidden RN contraband. The detection distance varies by the source strength and the shielding present. The characterization parameters of the source are not indicated in this report so the results summarized are relative. The Monte Carlo simulation results indicate the probability of detection of the RN source at certain distances from the detector which is a function of transverse speed and instrument sensitivity for the specified RN source
Energy Technology Data Exchange (ETDEWEB)
Kim, Chan Hyeong; Jeong, Jong Hwi [Department of Nuclear Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791 (Korea, Republic of); Bolch, Wesley E [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Cho, Kun-Woo [Korea Institute of Nuclear Safety, 19 Guseong-dong, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Hwang, Sung Bae, E-mail: chkim@hanyang.ac.kr [Department of Physical Therapy, Kyungbuk College, Hyucheon 2-dong, Yeongju-si, Gyeongbuk 750-712 (Korea, Republic of)
2011-05-21
Even though the hybrid phantom embodies both the anatomic reality of voxel phantoms and the deformability of stylized phantoms, it must be voxelized to be used in a Monte Carlo code for dose calculation or some imaging simulation, which incurs the inherent limitations of voxel phantoms. In the present study, a voxel phantom named VKH-Man (Visible Korean Human-Man), was converted to a polygon-surface phantom (PSRK-Man, Polygon-Surface Reference Korean-Man), which was then adjusted to the Reference Korean data. Subsequently, the PSRK-Man polygon phantom was directly, without any voxelization process, implemented in the Geant4 Monte Carlo code for dose calculations. The calculated dose values and computation time were then compared with those of HDRK-Man (High Definition Reference Korean-Man), a corresponding voxel phantom adjusted to the same Reference Korean data from the same VKH-Man voxel phantom. Our results showed that the calculated dose values of the PSRK-Man surface phantom agreed well with those of the HDRK-Man voxel phantom. The calculation speed for the PSRK-Man polygon phantom though was 70-150 times slower than that of the HDRK-Man voxel phantom; that speed, however, could be acceptable in some applications, in that direct use of the surface phantom PSRK-Man in Geant4 does not require a separate voxelization process. Computing speed can be enhanced, in future, either by optimizing the Monte Carlo transport kernel for the polygon surfaces or by using modern computing technologies such as grid computing and general-purpose computing on graphics processing units programming.