Bayesian Monte Carlo method

International Nuclear Information System (INIS)

Rajabalinejad, M.

2010-01-01

To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

Science.gov (United States)

Höök, L. J.; Johnson, T.; Hellsten, T.

2012-01-01

This work investigates the applicability of the randomized quasi-Monte Carlo method for simulation of fast-ion thermalization processes in fusion plasmas, e.g. for simulation of neutral beam injection and radio frequency heating. In contrast to the standard Monte Carlo method, the quasi-Monte Carlo method uses deterministic numbers instead of pseudo-random numbers and has a statistical weak convergence close to {O}(N^{-1}) , where N is the number of markers. We have compared different quasi-Monte Carlo methods for a neutral beam injection scenario, which is solved by many realizations of the associated stochastic differential equation, discretized with the Euler-Maruyama scheme. The statistical convergence of the methods is measured for time steps up to 214.

Monte Carlo simulation for IRRMA

International Nuclear Information System (INIS)

Gardner, R.P.; Liu Lianyan

2000-01-01

Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors

Monte Carlo methods

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.

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

International Nuclear Information System (INIS)

Höök, L J; Johnson, T; Hellsten, T

2012-01-01

This work investigates the applicability of the randomized quasi-Monte Carlo method for simulation of fast-ion thermalization processes in fusion plasmas, e.g. for simulation of neutral beam injection and radio frequency heating. In contrast to the standard Monte Carlo method, the quasi-Monte Carlo method uses deterministic numbers instead of pseudo-random numbers and has a statistical weak convergence close to O(N -1 ), where N is the number of markers. We have compared different quasi-Monte Carlo methods for a neutral beam injection scenario, which is solved by many realizations of the associated stochastic differential equation, discretized with the Euler-Maruyama scheme. The statistical convergence of the methods is measured for time steps up to 2 14 . (paper)

Methods for Monte Carlo simulations of biomacromolecules.

Science.gov (United States)

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.

Monte Carlo simulation applied to alpha spectrometry

International Nuclear Information System (INIS)

Baccouche, S.; Gharbi, F.; Trabelsi, A.

2007-01-01

Alpha particle spectrometry is a widely-used analytical method, in particular when we deal with pure alpha emitting radionuclides. Monte Carlo simulation is an adequate tool to investigate the influence of various phenomena on this analytical method. We performed an investigation of those phenomena using the simulation code GEANT of CERN. The results concerning the geometrical detection efficiency in different measurement geometries agree with analytical calculations. This work confirms that Monte Carlo simulation of solid angle of detection is a very useful tool to determine with very good accuracy the detection efficiency.

Monte Carlo simulation in statistical physics an introduction

CERN Document Server

Binder, Kurt

1992-01-01

The Monte Carlo method is a computer simulation method which uses random numbers to simulate statistical fluctuations The method is used to model complex systems with many degrees of freedom Probability distributions for these systems are generated numerically and the method then yields numerically exact information on the models Such simulations may be used tosee how well a model system approximates a real one or to see how valid the assumptions are in an analyical theory A short and systematic theoretical introduction to the method forms the first part of this book The second part is a practical guide with plenty of examples and exercises for the student Problems treated by simple sampling (random and self-avoiding walks, percolation clusters, etc) are included, along with such topics as finite-size effects and guidelines for the analysis of Monte Carlo simulations The two parts together provide an excellent introduction to the theory and practice of Monte Carlo simulations

Study of the quantitative analysis approach of maintenance by the Monte Carlo simulation method

International Nuclear Information System (INIS)

Shimizu, Takashi

2007-01-01

This study is examination of the quantitative valuation by Monte Carlo simulation method of maintenance activities of a nuclear power plant. Therefore, the concept of the quantitative valuation of maintenance that examination was advanced in the Japan Society of Maintenology and International Institute of Universality (IUU) was arranged. Basis examination for quantitative valuation of maintenance was carried out at simple feed water system, by Monte Carlo simulation method. (author)

Crop canopy BRDF simulation and analysis using Monte Carlo method

NARCIS (Netherlands)

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

Frequency domain Monte Carlo simulation method for cross power spectral density driven by periodically pulsed spallation neutron source using complex-valued weight Monte Carlo

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

Multiple histogram method and static Monte Carlo sampling

NARCIS (Netherlands)

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

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.

Monte Carlo Methods in ICF

Science.gov (United States)

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.

Monte Carlo methods in ICF

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

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

Monte Carlo simulation of experiments

International Nuclear Information System (INIS)

Opat, G.I.

1977-07-01

An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)

Monte Carlo simulation of continuous-space crystal growth

International Nuclear Information System (INIS)

Dodson, B.W.; Taylor, P.A.

1986-01-01

We describe a method, based on Monte Carlo techniques, of simulating the atomic growth of crystals without the discrete lattice space assumed by conventional Monte Carlo growth simulations. Since no lattice space is assumed, problems involving epitaxial growth, heteroepitaxy, phonon-driven mechanisms, surface reconstruction, and many other phenomena incompatible with the lattice-space approximation can be studied. Also, use of the Monte Carlo method circumvents to some extent the extreme limitations on simulated timescale inherent in crystal-growth techniques which might be proposed using molecular dynamics. The implementation of the new method is illustrated by studying the growth of strained-layer superlattice (SLS) interfaces in two-dimensional Lennard-Jones atomic systems. Despite the extreme simplicity of such systems, the qualitative features of SLS growth seen here are similar to those observed experimentally in real semiconductor systems

Transport methods: general. 1. The Analytical Monte Carlo Method for Radiation Transport Calculations

International Nuclear Information System (INIS)

Martin, William R.; Brown, Forrest B.

2001-01-01

We present an alternative Monte Carlo method for solving the coupled equations of radiation transport and material energy. This method is based on incorporating the analytical solution to the material energy equation directly into the Monte Carlo simulation for the radiation intensity. This method, which we call the Analytical Monte Carlo (AMC) method, differs from the well known Implicit Monte Carlo (IMC) method of Fleck and Cummings because there is no discretization of the material energy equation since it is solved as a by-product of the Monte Carlo simulation of the transport equation. Our method also differs from the method recently proposed by Ahrens and Larsen since they use Monte Carlo to solve both equations, while we are solving only the radiation transport equation with Monte Carlo, albeit with effective sources and cross sections to represent the emission sources. Our method bears some similarity to a method developed and implemented by Carter and Forest nearly three decades ago, but there are substantive differences. We have implemented our method in a simple zero-dimensional Monte Carlo code to test the feasibility of the method, and the preliminary results are very promising, justifying further extension to more realistic geometries. (authors)

Coded aperture optimization using Monte Carlo simulations

International Nuclear Information System (INIS)

Martineau, A.; Rocchisani, J.M.; Moretti, J.L.

2010-01-01

Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.

Exploring Monte Carlo methods

CERN Document Server

Dunn, William L

2012-01-01

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble

Monte Carlo simulations of neutron scattering instruments

International Nuclear Information System (INIS)

Aestrand, Per-Olof; Copenhagen Univ.; Lefmann, K.; Nielsen, K.

2001-01-01

A Monte Carlo simulation is an important computational tool used in many areas of science and engineering. The use of Monte Carlo techniques for simulating neutron scattering instruments is discussed. The basic ideas, techniques and approximations are presented. Since the construction of a neutron scattering instrument is very expensive, Monte Carlo software used for design of instruments have to be validated and tested extensively. The McStas software was designed with these aspects in mind and some of the basic principles of the McStas software will be discussed. Finally, some future prospects are discussed for using Monte Carlo simulations in optimizing neutron scattering experiments. (R.P.)

Monte Carlo methods in ICF

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

Stock Price Simulation Using Bootstrap and Monte Carlo

Directory of Open Access Journals (Sweden)

Pažický Martin

2017-06-01

Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.

Monte Carlo method for array criticality calculations

International Nuclear Information System (INIS)

Dickinson, D.; Whitesides, G.E.

1976-01-01

The Monte Carlo method for solving neutron transport problems consists of mathematically tracing paths of individual neutrons collision by collision until they are lost by absorption or leakage. The fate of the neutron after each collision is determined by the probability distribution functions that are formed from the neutron cross-section data. These distributions are sampled statistically to establish the successive steps in the neutron's path. The resulting data, accumulated from following a large number of batches, are analyzed to give estimates of k/sub eff/ and other collision-related quantities. The use of electronic computers to produce the simulated neutron histories, initiated at Los Alamos Scientific Laboratory, made the use of the Monte Carlo method practical for many applications. In analog Monte Carlo simulation, the calculation follows the physical events of neutron scattering, absorption, and leakage. To increase calculational efficiency, modifications such as the use of statistical weights are introduced. The Monte Carlo method permits the use of a three-dimensional geometry description and a detailed cross-section representation. Some of the problems in using the method are the selection of the spatial distribution for the initial batch, the preparation of the geometry description for complex units, and the calculation of error estimates for region-dependent quantities such as fluxes. The Monte Carlo method is especially appropriate for criticality safety calculations since it permits an accurate representation of interacting units of fissile material. Dissimilar units, units of complex shape, moderators between units, and reflected arrays may be calculated. Monte Carlo results must be correlated with relevant experimental data, and caution must be used to ensure that a representative set of neutron histories is produced

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

Science.gov (United States)

Chen, Jundong

2018-03-01

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

Packing simulation code to calculate distribution function of hard spheres by Monte Carlo method : MCRDF

International Nuclear Information System (INIS)

Murata, Isao; Mori, Takamasa; Nakagawa, Masayuki; Shirai, Hiroshi.

1996-03-01

High Temperature Gas-cooled Reactors (HTGRs) employ spherical fuels named coated fuel particles (CFPs) consisting of a microsphere of low enriched UO 2 with coating layers in order to prevent FP release. There exist many spherical fuels distributed randomly in the cores. Therefore, the nuclear design of HTGRs is generally performed on the basis of the multigroup approximation using a diffusion code, S N transport code or group-wise Monte Carlo code. This report summarizes a Monte Carlo hard sphere packing simulation code to simulate the packing of equal hard spheres and evaluate the necessary probability distribution of them, which is used for the application of the new Monte Carlo calculation method developed to treat randomly distributed spherical fuels with the continuous energy Monte Carlo method. By using this code, obtained are the various statistical values, namely Radial Distribution Function (RDF), Nearest Neighbor Distribution (NND), 2-dimensional RDF and so on, for random packing as well as ordered close packing of FCC and BCC. (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.

'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)

Odd-flavor Simulations by the Hybrid Monte Carlo

CERN Document Server

Takaishi, Tetsuya; Takaishi, Tetsuya; De Forcrand, Philippe

2001-01-01

The standard hybrid Monte Carlo algorithm is known to simulate even flavors QCD only. Simulations of odd flavors QCD, however, can be also performed in the framework of the hybrid Monte Carlo algorithm where the inverse of the fermion matrix is approximated by a polynomial. In this exploratory study we perform three flavors QCD simulations. We make a comparison of the hybrid Monte Carlo algorithm and the R-algorithm which also simulates odd flavors systems but has step-size errors. We find that results from our hybrid Monte Carlo algorithm are in agreement with those from the R-algorithm obtained at very small step-size.

Dynamic bounds coupled with Monte Carlo simulations

NARCIS (Netherlands)

Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.

2011-01-01

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper

Monte Carlo Simulation in Statistical Physics An Introduction

CERN Document Server

Binder, Kurt

2010-01-01

Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...

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)

Monte Carlo simulated dynamical magnetization of single-chain magnets

Energy Technology Data Exchange (ETDEWEB)

Li, Jun; Liu, Bang-Gui, E-mail: bgliu@iphy.ac.cn

2015-03-15

Here, a dynamical Monte-Carlo (DMC) method is used to study temperature-dependent dynamical magnetization of famous Mn{sub 2}Ni system as typical example of single-chain magnets with strong magnetic anisotropy. Simulated magnetization curves are in good agreement with experimental results under typical temperatures and sweeping rates, and simulated coercive fields as functions of temperature are also consistent with experimental curves. Further analysis indicates that the magnetization reversal is determined by both thermal-activated effects and quantum spin tunnelings. These can help explore basic properties and applications of such important magnetic systems. - Highlights: • Monte Carlo simulated magnetization curves are in good agreement with experimental results. • Simulated coercive fields as functions of temperature are consistent with experimental results. • The magnetization reversal is understood in terms of the Monte Carlo simulations.

A hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition

International Nuclear Information System (INIS)

Zheng Zheming; Stephens, Ryan M.; Braatz, Richard D.; Alkire, Richard C.; Petzold, Linda R.

2008-01-01

A hybrid multiscale kinetic Monte Carlo (HMKMC) method for speeding up the simulation of copper electrodeposition is presented. The fast diffusion events are simulated deterministically with a heterogeneous diffusion model which considers site-blocking effects of additives. Chemical reactions are simulated by an accelerated (tau-leaping) method for discrete stochastic simulation which adaptively selects exact discrete stochastic simulation for the appropriate reaction whenever that is necessary. The HMKMC method is seen to be accurate and highly efficient

Monte Carlo and analytic simulations in nanoparticle-enhanced radiation therapy

Directory of Open Access Journals (Sweden)

Paro AD

2016-09-01

Full Text Available Autumn D Paro,1 Mainul Hossain,2 Thomas J Webster,1,3,4 Ming Su1,4 1Department of Chemical Engineering, Northeastern University, Boston, MA, USA; 2NanoScience Technology Center and School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida, USA; 3Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, Saudi Arabia; 4Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Science, Wenzhou Medical University, Zhejiang, People’s Republic of China Abstract: Analytical and Monte Carlo simulations have been used to predict dose enhancement factors in nanoparticle-enhanced X-ray radiation therapy. Both simulations predict an increase in dose enhancement in the presence of nanoparticles, but the two methods predict different levels of enhancement over the studied energy, nanoparticle materials, and concentration regime for several reasons. The Monte Carlo simulation calculates energy deposited by electrons and photons, while the analytical one only calculates energy deposited by source photons and photoelectrons; the Monte Carlo simulation accounts for electron–hole recombination, while the analytical one does not; and the Monte Carlo simulation randomly samples photon or electron path and accounts for particle interactions, while the analytical simulation assumes a linear trajectory. This study demonstrates that the Monte Carlo simulation will be a better choice to evaluate dose enhancement with nanoparticles in radiation therapy. Keywords: nanoparticle, dose enhancement, Monte Carlo simulation, analytical simulation, radiation therapy, tumor cell, X-ray 

Optimal Spatial Subdivision method for improving geometry navigation performance in Monte Carlo particle transport simulation

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

Monte Carlo simulation of Markov unreliability models

International Nuclear Information System (INIS)

Lewis, E.E.; Boehm, F.

1984-01-01

A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)

Lattice gauge theories and Monte Carlo simulations

International Nuclear Information System (INIS)

Rebbi, C.

1981-11-01

After some preliminary considerations, the discussion of quantum gauge theories on a Euclidean lattice takes up the definition of Euclidean quantum theory and treatment of the continuum limit; analogy is made with statistical mechanics. Perturbative methods can produce useful results for strong or weak coupling. In the attempts to investigate the properties of the systems for intermediate coupling, numerical methods known as Monte Carlo simulations have proved valuable. The bulk of this paper illustrates the basic ideas underlying the Monte Carlo numerical techniques and the major results achieved with them according to the following program: Monte Carlo simulations (general theory, practical considerations), phase structure of Abelian and non-Abelian models, the observables (coefficient of the linear term in the potential between two static sources at large separation, mass of the lowest excited state with the quantum numbers of the vacuum (the so-called glueball), the potential between two static sources at very small distance, the critical temperature at which sources become deconfined), gauge fields coupled to basonic matter (Higgs) fields, and systems with fermions

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

Flat-histogram methods in quantum Monte Carlo simulations: Application to the t-J model

International Nuclear Information System (INIS)

Diamantis, Nikolaos G.; Manousakis, Efstratios

2016-01-01

We discuss that flat-histogram techniques can be appropriately applied in the sampling of quantum Monte Carlo simulation in order to improve the statistical quality of the results at long imaginary time or low excitation energy. Typical imaginary-time correlation functions calculated in quantum Monte Carlo are subject to exponentially growing errors as the range of imaginary time grows and this smears the information on the low energy excitations. We show that we can extract the low energy physics by modifying the Monte Carlo sampling technique to one in which configurations which contribute to making the histogram of certain quantities flat are promoted. We apply the diagrammatic Monte Carlo (diag-MC) method to the motion of a single hole in the t-J model and we show that the implementation of flat-histogram techniques allows us to calculate the Green's function in a wide range of imaginary-time. In addition, we show that applying the flat-histogram technique alleviates the “sign”-problem associated with the simulation of the single-hole Green's function at long imaginary time. (paper)

Reliability analysis of neutron transport simulation using Monte Carlo method

International Nuclear Information System (INIS)

Souza, Bismarck A. de; Borges, Jose C.

1995-01-01

This work presents a statistical and reliability analysis covering data obtained by computer simulation of neutron transport process, using the Monte Carlo method. A general description of the method and its applications is presented. Several simulations, corresponding to slowing down and shielding problems have been accomplished. The influence of the physical dimensions of the materials and of the sample size on the reliability level of results was investigated. The objective was to optimize the sample size, in order to obtain reliable results, optimizing computation time. (author). 5 refs, 8 figs

Monte Carlo simulation of grain growth

Directory of Open Access Journals (Sweden)

Paulo Blikstein

1999-07-01

Full Text Available Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical behavior of the atoms is properly reproduced; microstructural evolution depends only on the real topology of the grains and not on any kind of geometric simplification. Computer simulation has the advantage of allowing the user to visualize graphically the procedures, even dynamically and in three dimensions. Single-phase alloy grain growth simulation was carried out by calculating the free energy of each atom in the lattice (with its present crystallographic orientation and comparing this value to another one calculated with a different random orientation. When the resulting free energy is lower or equal to the initial value, the new orientation replaces the former. The measure of time is the Monte Carlo Step (MCS, which involves a series of trials throughout the lattice. A very close relationship between experimental and theoretical values for the grain growth exponent (n was observed.

A virtual source method for Monte Carlo simulation of Gamma Knife Model C

Energy Technology Data Exchange (ETDEWEB)

Kim, Tae Hoon; Kim, Yong Kyun [Hanyang University, Seoul (Korea, Republic of); Chung, Hyun Tai [Seoul National University College of Medicine, Seoul (Korea, Republic of)

2016-05-15

The Monte Carlo simulation method has been used for dosimetry of radiation treatment. Monte Carlo simulation is the method that determines paths and dosimetry of particles using random number. Recently, owing to the ability of fast processing of the computers, it is possible to treat a patient more precisely. However, it is necessary to increase the simulation time to improve the efficiency of accuracy uncertainty. When generating the particles from the cobalt source in a simulation, there are many particles cut off. So it takes time to simulate more accurately. For the efficiency, we generated the virtual source that has the phase space distribution which acquired a single gamma knife channel. We performed the simulation using the virtual sources on the 201 channel and compared the measurement with the simulation using virtual sources and real sources. A virtual source file was generated to reduce the simulation time of a Gamma Knife Model C. Simulations with a virtual source executed about 50 times faster than the original source code and there was no statistically significant difference in simulated results.

A virtual source method for Monte Carlo simulation of Gamma Knife Model C

International Nuclear Information System (INIS)

Kim, Tae Hoon; Kim, Yong Kyun; Chung, Hyun Tai

2016-01-01

The Monte Carlo simulation method has been used for dosimetry of radiation treatment. Monte Carlo simulation is the method that determines paths and dosimetry of particles using random number. Recently, owing to the ability of fast processing of the computers, it is possible to treat a patient more precisely. However, it is necessary to increase the simulation time to improve the efficiency of accuracy uncertainty. When generating the particles from the cobalt source in a simulation, there are many particles cut off. So it takes time to simulate more accurately. For the efficiency, we generated the virtual source that has the phase space distribution which acquired a single gamma knife channel. We performed the simulation using the virtual sources on the 201 channel and compared the measurement with the simulation using virtual sources and real sources. A virtual source file was generated to reduce the simulation time of a Gamma Knife Model C. Simulations with a virtual source executed about 50 times faster than the original source code and there was no statistically significant difference in simulated results

Direct Monte Carlo simulation of nanoscale mixed gas bearings

Directory of Open Access Journals (Sweden)

Kyaw Sett Myo

2015-06-01

Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.

Recommender engine for continuous-time quantum Monte Carlo methods

Science.gov (United States)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

A contribution Monte Carlo method

International Nuclear Information System (INIS)

Aboughantous, C.H.

1994-01-01

A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time

Monte Carlo molecular simulation of phase-coexistence for oil production and processing

KAUST Repository

Li, Jun

2011-01-01

The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components, the Gibbs-NPT ensemble Monte Carlo method is employed in the simulation while the mole fraction of each component in each phase is modeled as a Leonard-Jones fluid. As the results of Monte Carlo simulations usually contain huge statistical error, the blocking method is used to estimate the variance of the simulation results. Additionally, in order to improve the simulation efficiency, the step sizes of different trial moves is adjusted automatically so that their acceptance probabilities can approach to the preset values.

(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.

Track 4: basic nuclear science variance reduction for Monte Carlo criticality simulations. 6. Variational Variance Reduction for Monte Carlo Criticality Calculations

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Larsen, Edward W.

2001-01-01

Recently, it has been shown that the figure of merit (FOM) of Monte Carlo source-detector problems can be enhanced by using a variational rather than a direct functional to estimate the detector response. The direct functional, which is traditionally employed in Monte Carlo simulations, requires an estimate of the solution of the forward problem within the detector region. The variational functional is theoretically more accurate than the direct functional, but it requires estimates of the solutions of the forward and adjoint source-detector problems over the entire phase-space of the problem. In recent work, we have performed Monte Carlo simulations using the variational functional by (a) approximating the adjoint solution deterministically and representing this solution as a function in phase-space and (b) estimating the forward solution using Monte Carlo. We have called this general procedure variational variance reduction (VVR). The VVR method is more computationally expensive per history than traditional Monte Carlo because extra information must be tallied and processed. However, the variational functional yields a more accurate estimate of the detector response. Our simulations have shown that the VVR reduction in variance usually outweighs the increase in cost, resulting in an increased FOM. In recent work on source-detector problems, we have calculated the adjoint solution deterministically and represented this solution as a linear-in-angle, histogram-in-space function. This procedure has several advantages over previous implementations: (a) it requires much less adjoint information to be stored and (b) it is highly efficient for diffusive problems, due to the accurate linear-in-angle representation of the adjoint solution. (Traditional variance-reduction methods perform poorly for diffusive problems.) Here, we extend this VVR method to Monte Carlo criticality calculations, which are often diffusive and difficult for traditional variance-reduction methods

Monte Carlo simulation for theoretical calculations of damage and sputtering processes

International Nuclear Information System (INIS)

Yamamura, Yasunori

1984-01-01

The radiation damage accompanying ion irradiation and the various problems caused with it should be determined in principle by resolving Boltzmann's equations. However, in reality, those for a semi-infinite system cannot be generally resolved. Moreover, the effect of crystals, oblique incidence and so on make the situation more difficult. The analysis of the complicated phenomena of the collision in solids and the problems of radiation damage and sputtering accompanying them is possible in most cases only by computer simulation. At present, the methods of simulating the atomic collision phenomena in solids are roughly classified into molecular dynamics method and Monte Carlo method. In the molecular dynamics, Newton's equations are numerically calculated time-dependently as they are, and it has large merits that many body effect and nonlinear effect can be taken in consideration, but much computing time is required. The features and problems of the Monte Carlo simulation and nonlinear Monte Carlo simulation are described. The comparison of the Monte Carlo simulation codes calculating on the basis of two-body collision approximation, MARLOWE, TRIM and ACAT, was carried out through the calculation of the backscattering spectra of light ions. (Kako, I.)

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

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

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

Research of Monte Carlo method used in simulation of different maintenance processes

International Nuclear Information System (INIS)

Zhao Siqiao; Liu Jingquan

2011-01-01

The paper introduces two kinds of Monte Carlo methods used in equipment life process simulation under the least maintenance: condition: method of producing the interval of lifetime, method of time scale conversion. The paper also analyzes the characteristics and the using scope of the two methods. By using the conception of service age reduction factor, the model of equipment's life process under incomplete maintenance condition is established, and also the life process simulation method applicable to this situation is invented. (authors)

Multiple-time-stepping generalized hybrid Monte Carlo methods

Energy Technology Data Exchange (ETDEWEB)

Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)

2015-01-01

Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.

The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature

CERN Document Server

Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

2010-01-01

A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.

Profit Forecast Model Using Monte Carlo Simulation in Excel

Directory of Open Access Journals (Sweden)

Petru BALOGH

2014-01-01

Full Text Available Profit forecast is very important for any company. The purpose of this study is to provide a method to estimate the profit and the probability of obtaining the expected profit. Monte Carlo methods are stochastic techniques–meaning they are based on the use of random numbers and probability statistics to investigate problems. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. Our example of Monte Carlo simulation in Excel will be a simplified profit forecast model. Each step of the analysis will be described in detail. The input data for the case presented: the number of leads per month, the percentage of leads that result in sales, , the cost of a single lead, the profit per sale and fixed cost, allow obtaining profit and associated probabilities of achieving.

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.

Monte Carlo burnup codes acceleration using the correlated sampling method

International Nuclear Information System (INIS)

Dieudonne, C.

2013-01-01

For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this document we present an original methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time we develop a theoretical model to study the features of the correlated sampling method to understand its effects on depletion calculations. In a third time the implementation of this method in the TRIPOLI-4 code will be discussed, as well as the precise calculation scheme used to bring important speed-up of the depletion calculation. We will begin to validate and optimize the perturbed depletion scheme with the calculation of a REP-like fuel cell depletion. Then this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes. (author) [fr

Qualitative Simulation of Photon Transport in Free Space Based on Monte Carlo Method and Its Parallel Implementation

Directory of Open Access Journals (Sweden)

Xueli Chen

2010-01-01

Full Text Available During the past decade, Monte Carlo method has obtained wide applications in optical imaging to simulate photon transport process inside tissues. However, this method has not been effectively extended to the simulation of free-space photon transport at present. In this paper, a uniform framework for noncontact optical imaging is proposed based on Monte Carlo method, which consists of the simulation of photon transport both in tissues and in free space. Specifically, the simplification theory of lens system is utilized to model the camera lens equipped in the optical imaging system, and Monte Carlo method is employed to describe the energy transformation from the tissue surface to the CCD camera. Also, the focusing effect of camera lens is considered to establish the relationship of corresponding points between tissue surface and CCD camera. Furthermore, a parallel version of the framework is realized, making the simulation much more convenient and effective. The feasibility of the uniform framework and the effectiveness of the parallel version are demonstrated with a cylindrical phantom based on real experimental results.

Monte Carlo techniques in radiation therapy

CERN Document Server

Verhaegen, Frank

2013-01-01

Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...

Rare event simulation using Monte Carlo methods

CERN Document Server

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. ...

11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

CERN Document Server

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.

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)

2013-07-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

International Nuclear Information System (INIS)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.

2013-01-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Research on Monte Carlo improved quasi-static method for reactor space-time dynamics

International Nuclear Information System (INIS)

Xu Qi; Wang Kan; Li Shirui; Yu Ganglin

2013-01-01

With large time steps, improved quasi-static (IQS) method can improve the calculation speed for reactor dynamic simulations. The Monte Carlo IQS method was proposed in this paper, combining the advantages of both the IQS method and MC method. Thus, the Monte Carlo IQS method is beneficial for solving space-time dynamics problems of new concept reactors. Based on the theory of IQS, Monte Carlo algorithms for calculating adjoint neutron flux, reactor kinetic parameters and shape function were designed and realized. A simple Monte Carlo IQS code and a corresponding diffusion IQS code were developed, which were used for verification of the Monte Carlo IQS method. (authors)

Monte Carlo simulation with the Gate software using grid computing

International Nuclear Information System (INIS)

Reuillon, R.; Hill, D.R.C.; Gouinaud, C.; El Bitar, Z.; Breton, V.; Buvat, I.

2009-03-01

Monte Carlo simulations are widely used in emission tomography, for protocol optimization, design of processing or data analysis methods, tomographic reconstruction, or tomograph design optimization. Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the 'Multiple Replications In Parallel' approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-science), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses. (authors)

Advanced Multilevel Monte Carlo Methods

KAUST Repository

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.

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay; Law, Kody; Suciu, Carina

2017-01-01

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.

Monte Carlo simulations for plasma physics

International Nuclear Information System (INIS)

Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X.

2000-07-01

Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)

Analysis of Monte Carlo methods for the simulation of photon transport

International Nuclear Information System (INIS)

Carlsson, G.A.; Kusoffsky, L.

1975-01-01

In connection with the transport of low-energy photons (30 - 140 keV) through layers of water of different thicknesses, various aspects of Monte Carlo methods are examined in order to improve their effectivity (to produce statistically more reliable results with shorter computer times) and to bridge the gap between more physical methods and more mathematical ones. The calculations are compared with results of experiments involving the simulation of photon transport, using direct methods and collision density ones (J.S.)

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.)

Simplified monte carlo simulation for Beijing spectrometer

International Nuclear Information System (INIS)

Wang Taijie; Wang Shuqin; Yan Wuguang; Huang Yinzhi; Huang Deqiang; Lang Pengfei

1986-01-01

The Monte Carlo method based on the functionization of the performance of detectors and the transformation of values of kinematical variables into ''measured'' ones by means of smearing has been used to program the Monte Carlo simulation of the performance of the Beijing Spectrometer (BES) in FORTRAN language named BESMC. It can be used to investigate the multiplicity, the particle type, and the distribution of four-momentum of the final states of electron-positron collision, and also the response of the BES to these final states. Thus, it provides a measure to examine whether the overall design of the BES is reasonable and to decide the physical topics of the BES

Detailed balance method for chemical potential determination in Monte Carlo and molecular dynamics simulations

International Nuclear Information System (INIS)

Fay, P.J.; Ray, J.R.; Wolf, R.J.

1994-01-01

We present a new, nondestructive, method for determining chemical potentials in Monte Carlo and molecular dynamics simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials in which the Monte Carlo method is used to determine success or failure of the creation/destruction attempts; we thus call the method a detailed balance method. The method allows one to obtain estimates of the chemical potential for a given species in any closed ensemble simulation; the closed ensemble is paired with a ''natural'' open ensemble for the purpose of obtaining creation and destruction probabilities. We present results for the Lennard-Jones system and also for an embedded atom model of liquid palladium, and compare to previous results in the literature for these two systems. We are able to obtain an accurate estimate of the chemical potential for the Lennard-Jones system at higher densities than reported in the literature

Autocorrelations in hybrid Monte Carlo simulations

International Nuclear Information System (INIS)

Schaefer, Stefan; Virotta, Francesco

2010-11-01

Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)

Monte Carlo Methods in ICF (LIRPP Vol. 13)

Science.gov (United States)

Zimmerman, George B.

2016-10-01

Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved SOX in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.

Monte Carlo simulation of the microcanonical ensemble

International Nuclear Information System (INIS)

Creutz, M.

1984-01-01

We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references

Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....

Monte Carlo method to characterize radioactive waste drums

International Nuclear Information System (INIS)

Lima, Josenilson B.; Dellamano, Jose C.; Potiens Junior, Ademar J.

2013-01-01

Non-destructive methods for radioactive waste drums characterization have being developed in the Waste Management Department (GRR) at Nuclear and Energy Research Institute IPEN. This study was conducted as part of the radioactive wastes characterization program in order to meet specifications and acceptance criteria for final disposal imposed by regulatory control by gamma spectrometry. One of the main difficulties in the detectors calibration process is to obtain the counting efficiencies that can be solved by the use of mathematical techniques. The aim of this work was to develop a methodology to characterize drums using gamma spectrometry and Monte Carlo method. Monte Carlo is a widely used mathematical technique, which simulates the radiation transport in the medium, thus obtaining the efficiencies calibration of the detector. The equipment used in this work is a heavily shielded Hyperpure Germanium (HPGe) detector coupled with an electronic setup composed of high voltage source, amplifier and multiport multichannel analyzer and MCNP software for Monte Carlo simulation. The developing of this methodology will allow the characterization of solid radioactive wastes packed in drums and stored at GRR. (author)

Simulation of quantum systems by the tomography Monte Carlo method

International Nuclear Information System (INIS)

Bogdanov, Yu I

2007-01-01

A new method of statistical simulation of quantum systems is presented which is based on the generation of data by the Monte Carlo method and their purposeful tomography with the energy minimisation. The numerical solution of the problem is based on the optimisation of the target functional providing a compromise between the maximisation of the statistical likelihood function and the energy minimisation. The method does not involve complicated and ill-posed multidimensional computational procedures and can be used to calculate the wave functions and energies of the ground and excited stationary sates of complex quantum systems. The applications of the method are illustrated. (fifth seminar in memory of d.n. klyshko)

Sink strength simulations using the Monte Carlo method: Applied to spherical traps

Science.gov (United States)

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.

Monte Carlo theory and practice

International Nuclear Information System (INIS)

James, F.

1987-01-01

Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem

Monte Carlo and Quasi-Monte Carlo Sampling

CERN Document Server

Lemieux, Christiane

2009-01-01

Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.

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)

Monte Carlo Simulation for Particle Detectors

CERN Document Server

Pia, Maria Grazia

2012-01-01

Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...

Monte Carlo Simulation of Influence of Input Parameters Uncertainty on Output Data

International Nuclear Information System (INIS)

Sobek, Lukas

2010-01-01

Input parameters of a complex system in the probabilistic simulation are treated by means of probability density function (PDF). The result of the simulation have also probabilistic character. Monte Carlo simulation is widely used to obtain predictions concerning the probability of the risk. The Monte Carlo method was performed to calculate histograms of PDF for release rate given by uncertainty in distribution coefficient of radionuclides 135 Cs and 235 U.

PRELIMINARY COUPLING OF THE MONTE CARLO CODE OPENMC AND THE MULTIPHYSICS OBJECT-ORIENTED SIMULATION ENVIRONMENT (MOOSE) FOR ANALYZING DOPPLER FEEDBACK IN MONTE CARLO SIMULATIONS

Energy Technology Data Exchange (ETDEWEB)

Matthew Ellis; Derek Gaston; Benoit Forget; Kord Smith

2011-07-01

In recent years the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open source Monte Carlo code OpenMC with the open source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes. An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two dimensional 17x17 PWR fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes Functional Expansion Tallies to accurately and efficiently transfer pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two dimensional PWR fuel assembly case also demonstrates that for a simplified model the pin-by-pin doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.

Three-Dimensional Simulation of DRIE Process Based on the Narrow Band Level Set and Monte Carlo Method

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.

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

Fast sequential Monte Carlo methods for counting and optimization

CERN Document Server

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

A study on the shielding element using Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Kim, Ki Jeong [Dept. of Radiology, Konkuk University Medical Center, Seoul (Korea, Republic of); Shim, Jae Goo [Dept. of Radiologic Technology, Daegu Health College, Daegu (Korea, Republic of)

2017-06-15

In this research, we simulated the elementary star shielding ability using Monte Carlo simulation to apply medical radiation shielding sheet which can replace existing lead. In the selection of elements, mainly elements and metal elements having a large atomic number, which are known to have high shielding performance, recently, various composite materials have improved shielding performance, so that weight reduction, processability, In consideration of activity etc., 21 elements were selected. The simulation tools were utilized Monte Carlo method. As a result of simulating the shielding performance by each element, it was estimated that the shielding ratio is the highest at 98.82% and 98.44% for tungsten and gold.

Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

International Nuclear Information System (INIS)

Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

2000-01-01

Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency

A micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations

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...

Quasi-Monte Carlo methods for lattice systems. A first look

International Nuclear Information System (INIS)

Jansen, K.; Cyprus Univ., Nicosia; Leovey, H.; Griewank, A.; Nube, A.; Humboldt-Universitaet, Berlin; Mueller-Preussker, M.

2013-02-01

We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N -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 -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 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.

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

2010-01-01

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

Monte Carlo methods of PageRank computation

NARCIS (Netherlands)

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 simulation of neutron counters for safeguards applications

International Nuclear Information System (INIS)

Looman, Marc; Peerani, Paolo; Tagziria, Hamid

2009-01-01

MCNP-PTA is a new Monte Carlo code for the simulation of neutron counters for nuclear safeguards applications developed at the Joint Research Centre (JRC) in Ispra (Italy). After some preliminary considerations outlining the general aspects involved in the computational modelling of neutron counters, this paper describes the specific details and approximations which make up the basis of the model implemented in the code. One of the major improvements allowed by the use of Monte Carlo simulation is a considerable reduction in both the experimental work and in the reference materials required for the calibration of the instruments. This new approach to the calibration of counters using Monte Carlo simulation techniques is also discussed.

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

Becker, T.L.; Larsen, E.W.

2011-01-01

This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)

Burnup calculations using Monte Carlo method

International Nuclear Information System (INIS)

Ghosh, Biplab; Degweker, S.B.

2009-01-01

In the recent years, interest in burnup calculations using Monte Carlo methods has gained momentum. Previous burn up codes have used multigroup transport theory based calculations followed by diffusion theory based core calculations for the neutronic portion of codes. The transport theory methods invariably make approximations with regard to treatment of the energy and angle variables involved in scattering, besides approximations related to geometry simplification. Cell homogenisation to produce diffusion, theory parameters adds to these approximations. Moreover, while diffusion theory works for most reactors, it does not produce accurate results in systems that have strong gradients, strong absorbers or large voids. Also, diffusion theory codes are geometry limited (rectangular, hexagonal, cylindrical, and spherical coordinates). Monte Carlo methods are ideal to solve very heterogeneous reactors and/or lattices/assemblies in which considerable burnable poisons are used. The key feature of this approach is that Monte Carlo methods permit essentially 'exact' modeling of all geometrical detail, without resort to ene and spatial homogenization of neutron cross sections. Monte Carlo method would also be better for in Accelerator Driven Systems (ADS) which could have strong gradients due to the external source and a sub-critical assembly. To meet the demand for an accurate burnup code, we have developed a Monte Carlo burnup calculation code system in which Monte Carlo neutron transport code is coupled with a versatile code (McBurn) for calculating the buildup and decay of nuclides in nuclear materials. McBurn is developed from scratch by the authors. In this article we will discuss our effort in developing the continuous energy Monte Carlo burn-up code, McBurn. McBurn is intended for entire reactor core as well as for unit cells and assemblies. Generally, McBurn can do burnup of any geometrical system which can be handled by the underlying Monte Carlo transport code

On an efficient multiple time step Monte Carlo simulation of the SABR model

NARCIS (Netherlands)

Leitao Rodriguez, A.; Grzelak, L.A.; Oosterlee, C.W.

2017-01-01

In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math.

Random Numbers and Monte Carlo Methods

Science.gov (United States)

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.

LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events

CERN Document Server

Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V

2008-01-01

In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.

Monte Carlo Simulation of stepping source in afterloading intracavitary brachytherapy for GZP6 unit

International Nuclear Information System (INIS)

Toossi, M.T.B.; Abdollahi, M.; Ghorbani, M.

2010-01-01

Full text: Stepping source in brachytherapy systems is used to treat a target lesion longer than the effective treatment length of the source. Dose calculation accuracy plays a vital role in the outcome of brachytherapy treatment. In this study, the stepping source (channel 6) of GZP6 brachytherapy unit was simulated by Monte Carlo simulation and matrix shift method. The stepping source of GZP6 was simulated by Monte Carlo MCNPX code. The Mesh tally (type I) was employed for absorbed dose calculation in a cylindrical water phantom. 5 x 108 photon histories were scored and a 0.2% statistical uncertainty was obtained by Monte Carlo calculations. Dose distributions were obtained by our matrix shift method for esophageal cancer tumor lengths of 8 and 10 cm. Isodose curves produced by simulation and TPS were superimposed to estimate the differences. Results Comparison of Monte Carlo and TPS dose distributions show that in longitudinal direction (source movement direction) Monte Carlo and TPS dose distributions are comparable. [n transverse direction, the dose differences of 7 and 5% were observed for esophageal tumor lengths of 8 and 10 cm respectively. Conclusions Although, the results show that the maximum difference between Monte Carlo and TPS calculations is about 7%, but considering that the certified activity is given with ± I 0%, uncertainty, then an error of the order of 20% for Monte Carlo calculation would be reasonable. It can be suggested that accuracy of the dose distribution produced by TPS is acceptable for clinical applications. (author)

Direct Simulation Monte Carlo Application of the Three Dimensional Forced Harmonic Oscillator Model

Science.gov (United States)

2017-12-07

NUMBER (Include area code) 07 December 2017 Journal Article 24 February 2017 - 31 December 2017 Direct Simulation Monte Carlo Application of the...is proposed. The implementation employs precalculated lookup tables for transition probabilities and is suitable for the direct simulation Monte Carlo...method. It takes into account the microscopic reversibility between the excitation and deexcitation processes , and it satisfies the detailed balance

Application of Monte Carlo method to solving boundary value problem of differential equations

International Nuclear Information System (INIS)

Zuo Yinghong; Wang Jianguo

2012-01-01

This paper introduces the foundation of the Monte Carlo method and the way how to generate the random numbers. Based on the basic thought of the Monte Carlo method and finite differential method, the stochastic model for solving the boundary value problem of differential equations is built. To investigate the application of the Monte Carlo method to solving the boundary value problem of differential equations, the model is used to solve Laplace's equations with the first boundary condition and the unsteady heat transfer equation with initial values and boundary conditions. The results show that the boundary value problem of differential equations can be effectively solved with the Monte Carlo method, and the differential equations with initial condition can also be calculated by using a stochastic probability model which is based on the time-domain finite differential equations. Both the simulation results and theoretical analyses show that the errors of numerical results are lowered as the number of simulation particles is increased. (authors)

Monte Carlo simulation experiments on box-type radon dosimeter

International Nuclear Information System (INIS)

Jamil, Khalid; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-01-01

Epidemiological studies show that inhalation of radon gas ( 222 Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the 222 Rn concentrations (Bq/m 3 ) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η int ) and alpha hit efficiency (η hit ). The η int depends upon only on the dimensions of the dosimeter and η hit depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper explains that how radon

Monte Carlo simulation experiments on box-type radon dosimeter

Energy Technology Data Exchange (ETDEWEB)

Jamil, Khalid, E-mail: kjamil@comsats.edu.pk; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-11-11

Epidemiological studies show that inhalation of radon gas ({sup 222}Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the {sup 222}Rn concentrations (Bq/m{sup 3}) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η{sub int}) and alpha hit efficiency (η{sub hit}). The η{sub int} depends upon only on the dimensions of the dosimeter and η{sub hit} depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper

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

The Monte Carlo method the method of statistical trials

CERN Document Server

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

Alternative implementations of the Monte Carlo power method

International Nuclear Information System (INIS)

Blomquist, R.N.; Gelbard, E.M.

2002-01-01

We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency

Sequential Monte Carlo simulation of collision risk in free flight air traffic

NARCIS (Netherlands)

Blom, H.A.P.; Bakker, G.; Krystul, J.; Everdij, M.H.C.; Klein Obbink, B.; Klompstra, M.B.

2005-01-01

Within HYBRIDGE a novel approach in speeding up Monte Carlo simulation of rare events has been developed. In the current report this method is extended for application to simulating collisions with a stochastic dynamical model of an air traffic operational concept. Subsequently this extended Monte

Adaptive Multilevel Monte Carlo Simulation

KAUST Repository

Hoel, H

2011-08-23

This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).

Closed-shell variational quantum Monte Carlo simulation for the ...

African Journals Online (AJOL)

Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.

A Monte Carlo method using octree structure in photon and electron transport

International Nuclear Information System (INIS)

Ogawa, K.; Maeda, S.

1995-01-01

Most of the early Monte Carlo calculations in medical physics were used to calculate absorbed dose distributions, and detector responses and efficiencies. Recently, data acquisition in Single Photon Emission CT (SPECT) has been simulated by a Monte Carlo method to evaluate scatter photons generated in a human body and a collimator. Monte Carlo simulations in SPECT data acquisition are generally based on the transport of photons only because the photons being simulated are low energy, and therefore the bremsstrahlung productions by the electrons generated are negligible. Since the transport calculation of photons without electrons is much simpler than that with electrons, it is possible to accomplish the high-speed simulation in a simple object with one medium. Here, object description is important in performing the photon and/or electron transport using a Monte Carlo method efficiently. The authors propose a new description method using an octree representation of an object. Thus even if the boundaries of each medium are represented accurately, high-speed calculation of photon transport can be accomplished because the number of voxels is much fewer than that of the voxel-based approach which represents an object by a union of the voxels of the same size. This Monte Carlo code using the octree representation of an object first establishes the simulation geometry by reading octree string, which is produced by forming an octree structure from a set of serial sections for the object before the simulation; then it transports photons in the geometry. Using the code, if the user just prepares a set of serial sections for the object in which he or she wants to simulate photon trajectories, he or she can perform the simulation automatically using the suboptimal geometry simplified by the octree representation without forming the optimal geometry by handwriting

Microcanonical Monte Carlo approach for computing melting curves by atomistic simulations

OpenAIRE

Davis, Sergio; Gutiérrez, Gonzalo

2017-01-01

We report microcanonical Monte Carlo simulations of melting and superheating of a generic, Lennard-Jones system starting from the crystalline phase. The isochoric curve, the melting temperature $T_m$ and the critical superheating temperature $T_{LS}$ obtained are in close agreement (well within the microcanonical temperature fluctuations) with standard molecular dynamics one-phase and two-phase methods. These results validate the use of microcanonical Monte Carlo to compute melting points, a ...

Monte Carlo Molecular Simulation with Isobaric-Isothermal and Gibbs-NPT Ensembles

KAUST Repository

Du, Shouhong

2012-01-01

This thesis presents Monte Carlo methods for simulations of phase behaviors of Lennard-Jones fluids. The isobaric-isothermal (NPT) ensemble and Gibbs-NPT ensemble are introduced in detail. NPT ensemble is employed to determine the phase diagram of pure component. The reduced simulation results are verified by comparison with the equation of state by by Johnson et al. and results with L-J parameters of methane agree considerably with the experiment measurements. We adopt the blocking method for variance estimation and error analysis of the simulation results. The relationship between variance and number of Monte Carlo cycles, error propagation and Random Number Generator performance are also investigated. We review the Gibbs-NPT ensemble employed for phase equilibrium of binary mixture. The phase equilibrium is achieved by performing three types of trial move: particle displacement, volume rearrangement and particle transfer. The simulation models and the simulation details are introduced. The simulation results of phase coexistence for methane and ethane are reported with comparison of the experimental data. Good agreement is found for a wide range of pressures. The contribution of this thesis work lies in the study of the error analysis with respect to the Monte Carlo cycles and number of particles in some interesting aspects.

Monte Carlo Molecular Simulation with Isobaric-Isothermal and Gibbs-NPT Ensembles

KAUST Repository

Du, Shouhong

2012-05-01

This thesis presents Monte Carlo methods for simulations of phase behaviors of Lennard-Jones fluids. The isobaric-isothermal (NPT) ensemble and Gibbs-NPT ensemble are introduced in detail. NPT ensemble is employed to determine the phase diagram of pure component. The reduced simulation results are verified by comparison with the equation of state by by Johnson et al. and results with L-J parameters of methane agree considerably with the experiment measurements. We adopt the blocking method for variance estimation and error analysis of the simulation results. The relationship between variance and number of Monte Carlo cycles, error propagation and Random Number Generator performance are also investigated. We review the Gibbs-NPT ensemble employed for phase equilibrium of binary mixture. The phase equilibrium is achieved by performing three types of trial move: particle displacement, volume rearrangement and particle transfer. The simulation models and the simulation details are introduced. The simulation results of phase coexistence for methane and ethane are reported with comparison of the experimental data. Good agreement is found for a wide range of pressures. The contribution of this thesis work lies in the study of the error analysis with respect to the Monte Carlo cycles and number of particles in some interesting aspects.

Multilevel Monte Carlo methods using ensemble level mixed MsFEM for two-phase flow and transport simulations

KAUST Repository

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

Simulation based sequential Monte Carlo methods for discretely observed Markov processes

OpenAIRE

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...

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)

Monte Carlo simulation of Touschek effect

Directory of Open Access Journals (Sweden)

Aimin Xiao

2010-07-01

Full Text Available We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian-distributed beam or for a general beam whose distribution function is given. In addition, scattered electrons can be tracked through the beam line and the local beam-loss rate and beam halo information recorded.

Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Suman, Vitisha [Health Physics Division, Bhabha Atomic Research Centre, Mumbai 400085 (India); Sarkar, P.K., E-mail: pksarkar02@gmail.com [Manipal Centre for Natural Sciences, Manipal University, Manipal 576104 (India)

2014-02-11

A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra.

Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation

International Nuclear Information System (INIS)

Suman, Vitisha; Sarkar, P.K.

2014-01-01

A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra

Power distribution system reliability evaluation using dagger-sampling Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Hu, Y.; Zhao, S.; Ma, Y. [North China Electric Power Univ., Hebei (China). Dept. of Electrical Engineering

2009-03-11

A dagger-sampling Monte Carlo simulation method was used to evaluate power distribution system reliability. The dagger-sampling technique was used to record the failure of a component as an incident and to determine its occurrence probability by generating incident samples using random numbers. The dagger sampling technique was combined with the direct sequential Monte Carlo method to calculate average values of load point indices and system indices. Results of the 2 methods with simulation times of up to 100,000 years were then compared. The comparative evaluation showed that less computing time was required using the dagger-sampling technique due to its higher convergence speed. When simulation times were 1000 years, the dagger-sampling method required 0.05 seconds to accomplish an evaluation, while the direct method required 0.27 seconds. 12 refs., 3 tabs., 4 figs.

Monte Carlo 2000 Conference : Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications

CERN Document Server

Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro

2001-01-01

This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.

Application of Monte Carlo method in forward simulation of azimuthal gamma imaging while drilling

International Nuclear Information System (INIS)

Yuan Chao; Zhou Cancan; Zhang Feng; Chen Zhi

2014-01-01

Monte Carlo simulation is one of the most important numerical simulation methods in nuclear logging. Formation models can be conveniently built with MCNP code, which provides a simple and effective approach for fundamental study of nuclear logging. Monte Carlo method is employed to set up formation models under logging while drilling condition, and the characteristic of azimuthal gamma imaging is simulated. The results present that the azimuthal gamma imaging shows a sinusoidal curve features. The imaging can be used to accurately calculate the relative dip angle of borehole and thickness of radioactive formation. The larger relative dip angle of borehole and the thicker radioactive formation lead to the larger height of the sinusoidal curve in the imaging. The borehole size has no affect for the calculation of the relative dip angle, but largely affects the determination of formation thickness. The standoff of logging tool has great influence for the calculation of the relative dip angle and formation thickness. If the gamma ray counts meet the demand of counting statistics in nuclear logging, the effect of borehole fluid on the imaging can be ignored. (authors)

Applications of the Monte Carlo simulation in dosimetry and medical physics problems

International Nuclear Information System (INIS)

Rojas C, E. L.

2010-01-01

At the present time the computers use to solve important problems extends to all the areas. These areas can be of social, economic, of engineering, of basic and applied science, etc. With and appropriate handling of computation programs and information can be carried out calculations and simulations of real models, to study them and to solve theoretical or application problems. The processes that contain random variables are susceptible of being approached with the Monte Carlo method. This is a numeric method that, thanks to the improvements in the processors of the computers, it can apply in many tasks more than what was made in the principles of their practical application (at the beginning of the decade of 1950). In this work the application of the Monte Carlo method will be approached in the simulation of the radiation interaction with the matter, to investigate dosimetric aspects of some problems that exist in the medical physics area. Also, contain an introduction about some historical data and some general concepts related with the Monte Carlo simulation are revised. (Author)

MC 93 - Proceedings of the International Conference on Monte Carlo Simulation in High Energy and Nuclear Physics

Science.gov (United States)

Dragovitsch, Peter; Linn, Stephan L.; Burbank, Mimi

1994-01-01

The Table of Contents for the book is as follows: * Preface * Heavy Fragment Production for Hadronic Cascade Codes * Monte Carlo Simulations of Space Radiation Environments * Merging Parton Showers with Higher Order QCD Monte Carlos * An Order-αs Two-Photon Background Study for the Intermediate Mass Higgs Boson * GEANT Simulation of Hall C Detector at CEBAF * Monte Carlo Simulations in Radioecology: Chernobyl Experience * UNIMOD2: Monte Carlo Code for Simulation of High Energy Physics Experiments; Some Special Features * Geometrical Efficiency Analysis for the Gamma-Neutron and Gamma-Proton Reactions * GISMO: An Object-Oriented Approach to Particle Transport and Detector Modeling * Role of MPP Granularity in Optimizing Monte Carlo Programming * Status and Future Trends of the GEANT System * The Binary Sectioning Geometry for Monte Carlo Detector Simulation * A Combined HETC-FLUKA Intranuclear Cascade Event Generator * The HARP Nucleon Polarimeter * Simulation and Data Analysis Software for CLAS * TRAP -- An Optical Ray Tracing Program * Solutions of Inverse and Optimization Problems in High Energy and Nuclear Physics Using Inverse Monte Carlo * FLUKA: Hadronic Benchmarks and Applications * Electron-Photon Transport: Always so Good as We Think? Experience with FLUKA * Simulation of Nuclear Effects in High Energy Hadron-Nucleus Collisions * Monte Carlo Simulations of Medium Energy Detectors at COSY Jülich * Complex-Valued Monte Carlo Method and Path Integrals in the Quantum Theory of Localization in Disordered Systems of Scatterers * Radiation Levels at the SSCL Experimental Halls as Obtained Using the CLOR89 Code System * Overview of Matrix Element Methods in Event Generation * Fast Electromagnetic Showers * GEANT Simulation of the RMC Detector at TRIUMF and Neutrino Beams for KAON * Event Display for the CLAS Detector * Monte Carlo Simulation of High Energy Electrons in Toroidal Geometry * GEANT 3.14 vs. EGS4: A Comparison Using the DØ Uranium/Liquid Argon

Study of the Transition Flow Regime using Monte Carlo Methods

Science.gov (United States)

Hassan, H. A.

1999-01-01

This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.

Prospect on general software of Monte Carlo method

International Nuclear Information System (INIS)

Pei Lucheng

1992-01-01

This is a short paper on the prospect of Monte Carlo general software. The content consists of cluster sampling method, zero variance technique, self-improved method, and vectorized Monte Carlo method

A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

NARCIS (Netherlands)

MIKOSCH, T; WANG, QA

We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.

Modern analysis of ion channeling data by Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)

2005-10-15

Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.

Improved local lattice Monte Carlo simulation for charged systems

Science.gov (United States)

Jiang, Jian; Wang, Zhen-Gang

2018-03-01

Maggs and Rossetto [Phys. Rev. Lett. 88, 196402 (2002)] proposed a local lattice Monte Carlo algorithm for simulating charged systems based on Gauss's law, which scales with the particle number N as O(N). This method includes two degrees of freedom: the configuration of the mobile charged particles and the electric field. In this work, we consider two important issues in the implementation of the method, the acceptance rate of configurational change (particle move) and the ergodicity in the phase space sampled by the electric field. We propose a simple method to improve the acceptance rate of particle moves based on the superposition principle for electric field. Furthermore, we introduce an additional updating step for the field, named "open-circuit update," to ensure that the system is fully ergodic under periodic boundary conditions. We apply this improved local Monte Carlo simulation to an electrolyte solution confined between two low dielectric plates. The results show excellent agreement with previous theoretical work.

Applications of Monte Carlo method in Medical Physics

International Nuclear Information System (INIS)

Diez Rios, A.; Labajos, M.

1989-01-01

The basic ideas of Monte Carlo techniques are presented. Random numbers and their generation by congruential methods, which underlie Monte Carlo calculations are shown. Monte Carlo techniques to solve integrals are discussed. The evaluation of a simple monodimensional integral with a known answer, by means of two different Monte Carlo approaches are discussed. The basic principles to simualate on a computer photon histories reduce variance and the current applications in Medical Physics are commented. (Author)

Study of TXRF experimental system by Monte Carlo simulation

International Nuclear Information System (INIS)

Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T.; Anjos, Marcelino J.; Conti, Claudio C.

2011-01-01

The Total-Reflection X-ray Fluorescence (TXRF) technique offers unique possibilities to study the concentrations of a wide range of trace elements in various types of samples. Besides that, the TXRF technique is widely used to study the trace elements in biological, medical and environmental samples due to its multielemental character as well as simplicity of sample preparation and quantification methods used. In general the TXRF experimental setup is not simple and might require substantial experimental efforts. On the other hand, in recent years, experimental TXRF portable systems have been developed. It has motivated us to develop our own TXRF portable system. In this work we presented a first step in order to optimize a TXRF experimental setup using Monte Carlo simulation by MCNP code. The results found show that the Monte Carlo simulation method can be used to investigate the development of a TXRF experimental system before its assembly. (author)

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.

A New Approach to Monte Carlo Simulations in Statistical Physics

Science.gov (United States)

Landau, David P.

2002-08-01

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

Monte Carlo simulation of VHTR particle fuel with chord length sampling

International Nuclear Information System (INIS)

Ji, W.; Martin, W. R.

2007-01-01

The Very High Temperature Gas-Cooled Reactor (VHTR) poses a problem for neutronic analysis due to the double heterogeneity posed by the particle fuel and either the fuel compacts in the case of the prismatic block reactor or the fuel pebbles in the case of the pebble bed reactor. Direct Monte Carlo simulation has been used in recent years to analyze these VHTR configurations but is computationally challenged when space dependent phenomena are considered such as depletion or temperature feedback. As an alternative approach, we have considered chord length sampling to reduce the computational burden of the Monte Carlo simulation. We have improved on an existing method called 'limited chord length sampling' and have used it to analyze stochastic media representative of either pebble bed or prismatic VHTR fuel geometries. Based on the assumption that the PDF had an exponential form, a theoretical chord length distribution is derived and shown to be an excellent model for a wide range of packing fractions. This chord length PDF was then used to analyze a stochastic medium that was constructed using the RSA (Random Sequential Addition) algorithm and the results were compared to a benchmark Monte Carlo simulation of the actual stochastic geometry. The results are promising and suggest that the theoretical chord length PDF can be used instead of a full Monte Carlo random walk simulation in the stochastic medium, saving orders of magnitude in computational time (and memory demand) to perform the simulation. (authors)

Simulation of neutron transport equation using parallel Monte Carlo for deep penetration problems

International Nuclear Information System (INIS)

Bekar, K. K.; Tombakoglu, M.; Soekmen, C. N.

2001-01-01

Neutron transport equation is simulated using parallel Monte Carlo method for deep penetration neutron transport problem. Monte Carlo simulation is parallelized by using three different techniques; direct parallelization, domain decomposition and domain decomposition with load balancing, which are used with PVM (Parallel Virtual Machine) software on LAN (Local Area Network). The results of parallel simulation are given for various model problems. The performances of the parallelization techniques are compared with each other. Moreover, the effects of variance reduction techniques on parallelization are discussed

Radiotherapy Monte Carlo simulation using cloud computing technology.

Science.gov (United States)

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

2012-12-01

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

Radiotherapy Monte Carlo simulation using cloud computing technology

International Nuclear Information System (INIS)

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

2012-01-01

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

Multilevel Monte Carlo methods using ensemble level mixed MsFEM for two-phase flow and transport simulations

KAUST Repository

Efendiev, Yalchin R.; Iliev, Oleg; Kronsbein, C.

2013-01-01

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

Monte Carlo Simulation for Statistical Decay of Compound Nucleus

Directory of Open Access Journals (Sweden)

Chadwick M.B.

2012-02-01

Full Text Available We perform Monte Carlo simulations for neutron and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory. This Monte Carlo Hauser-Feshbach (MCHF method calculation, which gives us correlated information between emitted particles and γ-rays. It will be a powerful tool in many applications, as nuclear reactions can be probed in a more microscopic way. We have been developing the MCHF code, CGM, which solves the Hauser-Feshbach theory with the Monte Carlo method. The code includes all the standard models that used in a standard Hauser-Feshbach code, namely the particle transmission generator, the level density module, interface to the discrete level database, and so on. CGM can emit multiple neutrons, as long as the excitation energy of the compound nucleus is larger than the neutron separation energy. The γ-ray competition is always included at each compound decay stage, and the angular momentum and parity are conserved. Some calculations for a fission fragment 140Xe are shown as examples of the MCHF method, and the correlation between the neutron and γ-ray is discussed.

Global Monte Carlo Simulation with High Order Polynomial Expansions

International Nuclear Information System (INIS)

William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin

2007-01-01

The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as 'local' piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi's method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source convergence

A modular method to handle multiple time-dependent quantities in Monte Carlo simulations

International Nuclear Information System (INIS)

Shin, J; Faddegon, B A; Perl, J; Schümann, J; Paganetti, H

2012-01-01

A general method for handling time-dependent quantities in Monte Carlo simulations was developed to make such simulations more accessible to the medical community for a wide range of applications in radiotherapy, including fluence and dose calculation. To describe time-dependent changes in the most general way, we developed a grammar of functions that we call ‘Time Features’. When a simulation quantity, such as the position of a geometrical object, an angle, a magnetic field, a current, etc, takes its value from a Time Feature, that quantity varies over time. The operation of time-dependent simulation was separated into distinct parts: the Sequence samples time values either sequentially at equal increments or randomly from a uniform distribution (allowing quantities to vary continuously in time), and then each time-dependent quantity is calculated according to its Time Feature. Due to this modular structure, time-dependent simulations, even in the presence of multiple time-dependent quantities, can be efficiently performed in a single simulation with any given time resolution. This approach has been implemented in TOPAS (TOol for PArticle Simulation), designed to make Monte Carlo simulations with Geant4 more accessible to both clinical and research physicists. To demonstrate the method, three clinical situations were simulated: a variable water column used to verify constancy of the Bragg peak of the Crocker Lab eye treatment facility of the University of California, the double-scattering treatment mode of the passive beam scattering system at Massachusetts General Hospital (MGH), where a spinning range modulator wheel accompanied by beam current modulation produces a spread-out Bragg peak, and the scanning mode at MGH, where time-dependent pulse shape, energy distribution and magnetic fields control Bragg peak positions. Results confirm the clinical applicability of the method. (paper)

Adjoint electron Monte Carlo calculations

International Nuclear Information System (INIS)

Jordan, T.M.

1986-01-01

Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment

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

Monte-Carlo Simulation for PDC-Based Optical CDMA System

Directory of Open Access Journals (Sweden)

FAHIM AZIZ UMRANI

2010-10-01

Full Text Available This paper presents the Monte-Carlo simulation of Optical CDMA (Code Division Multiple Access systems, and analyse its performance in terms of the BER (Bit Error Rate. The spreading sequence chosen for CDMA is Perfect Difference Codes. Furthermore, this paper derives the expressions of noise variances from first principles to calibrate the noise for both bipolar (electrical domain and unipolar (optical domain signalling required for Monte-Carlo simulation. The simulated results conform to the theory and show that the receiver gain mismatch and splitter loss at the transceiver degrades the system performance.

GEANT Monte Carlo simulations for the GREAT spectrometer

International Nuclear Information System (INIS)

Andreyev, A.N.; Butler, P.A.; Page, R.D.; Appelbe, D.E.; Jones, G.D.; Joss, D.T.; Herzberg, R.-D.; Regan, P.H.; Simpson, J.; Wadsworth, R.

2004-01-01

GEANT Monte Carlo simulations for the recently developed GREAT spectrometer are presented. Some novel applications of the spectrometer for γ-ray, conversion-electron and β-decay spectroscopy are discussed. The conversion-electron spectroscopy of heavy nuclei with strongly converted transitions and the extension of the recoil decay tagging method to β-decaying nuclei are considered in detail

Specialized Monte Carlo codes versus general-purpose Monte Carlo codes

International Nuclear Information System (INIS)

Moskvin, Vadim; DesRosiers, Colleen; Papiez, Lech; Lu, Xiaoyi

2002-01-01

The possibilities of Monte Carlo modeling for dose calculations and optimization treatment are quite limited in radiation oncology applications. The main reason is that the Monte Carlo technique for dose calculations is time consuming while treatment planning may require hundreds of possible cases of dose simulations to be evaluated for dose optimization. The second reason is that general-purpose codes widely used in practice, require an experienced user to customize them for calculations. This paper discusses the concept of Monte Carlo code design that can avoid the main problems that are preventing wide spread use of this simulation technique in medical physics. (authors)

Monte Carlo simulation for radiographic applications

International Nuclear Information System (INIS)

Tillack, G.R.; Bellon, C.

2003-01-01

Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de

Suppression of the initial transient in Monte Carlo criticality simulations; Suppression du regime transitoire initial des simulations Monte-Carlo de criticite

Energy Technology Data Exchange (ETDEWEB)

Richet, Y

2006-12-15

Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)

Monte Carlo simulations in skin radiotherapy

International Nuclear Information System (INIS)

Sarvari, A.; Jeraj, R.; Kron, T.

2000-01-01

The primary goal of this work was to develop a procedure for calculation the appropriate filter shape for a brachytherapy applicator used for skin radiotherapy. In the applicator a radioactive source is positioned close to the skin. Without a filter, the resultant dose distribution would be highly nonuniform.High uniformity is usually required however. This can be achieved using an appropriately shaped filter, which flattens the dose profile. Because of the complexity of the transport and geometry, Monte Carlo simulations had to be used. An 192 Ir high dose rate photon source was used. All necessary transport parameters were simulated with the MCNP4B Monte Carlo code. A highly efficient iterative procedure was developed, which enabled calculation of the optimal filter shape in only few iterations. The initially non-uniform dose distributions became uniform within a percent when applying the filter calculated by this procedure. (author)

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.

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

Monte Carlo method for calculating the radiation skyshine produced by electron accelerators

Energy Technology Data Exchange (ETDEWEB)

Kong Chaocheng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China)]. E-mail: kongchaocheng@tsinghua.org.cn; Li Quanfeng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Chen Huaibi [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Du Taibin [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Cheng Cheng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Tang Chuanxiang [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Zhu Li [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Zhang Hui [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Pei Zhigang [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Ming Shenjin [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China)

2005-06-01

Using the MCNP4C Monte Carlo code, the X-ray skyshine produced by 9 MeV, 15 MeV and 21 MeV electron linear accelerators were calculated respectively with a new two-step method combined with the split and roulette variance reduction technique. Results of the Monte Carlo simulation, the empirical formulas used for skyshine calculation and the dose measurements were analyzed and compared. In conclusion, the skyshine dose measurements agreed reasonably with the results computed by the Monte Carlo method, but deviated from computational results given by empirical formulas. The effect on skyshine dose caused by different structures of accelerator head is also discussed in this paper.

Monte Carlo simulations on a 9-node PC cluster

International Nuclear Information System (INIS)

Gouriou, J.

2001-01-01

Monte Carlo simulation methods are frequently used in the fields of medical physics, dosimetry and metrology of ionising radiation. Nevertheless, the main drawback of this technique is to be computationally slow, because the statistical uncertainty of the result improves only as the square root of the computational time. We present a method, which allows to reduce by a factor 10 to 20 the used effective running time. In practice, the aim was to reduce the calculation time in the LNHB metrological applications from several weeks to a few days. This approach includes the use of a PC-cluster, under Linux operating system and PVM parallel library (version 3.4). The Monte Carlo codes EGS4, MCNP and PENELOPE have been implemented on this platform and for the two last ones adapted for running under the PVM environment. The maximum observed speedup is ranging from a factor 13 to 18 according to the codes and the problems to be simulated. (orig.)

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)

Monte Carlo simulation: tool for the calibration in analytical determination of radionuclides

International Nuclear Information System (INIS)

Gonzalez, Jorge A. Carrazana; Ferrera, Eduardo A. Capote; Gomez, Isis M. Fernandez; Castro, Gloria V. Rodriguez; Ricardo, Niury Martinez

2013-01-01

This work shows how is established the traceability of the analytical determinations using this calibration method. Highlights the advantages offered by Monte Carlo simulation for the application of corrections by differences in chemical composition, density and height of the samples analyzed. Likewise, the results obtained by the LVRA in two exercises organized by the International Agency for Atomic Energy (IAEA) are presented. In these exercises (an intercomparison and a proficiency test) all reported analytical results were obtained based on calibrations in efficiency by Monte Carlo simulation using the DETEFF program

Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...

On Monte Carlo Simulation and Analysis of Electricity Markets

International Nuclear Information System (INIS)

Amelin, Mikael

2004-07-01

This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models

Applications of the Monte Carlo simulation in dosimetry and medical physics problems; Aplicaciones de la simulacion Monte Carlo en dosimetria y problemas de fisica medica

Energy Technology Data Exchange (ETDEWEB)

Rojas C, E. L., E-mail: leticia.rojas@inin.gob.m [ININ, Gerencia de Ciencias Ambientales, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

2010-07-01

At the present time the computers use to solve important problems extends to all the areas. These areas can be of social, economic, of engineering, of basic and applied science, etc. With and appropriate handling of computation programs and information can be carried out calculations and simulations of real models, to study them and to solve theoretical or application problems. The processes that contain random variables are susceptible of being approached with the Monte Carlo method. This is a numeric method that, thanks to the improvements in the processors of the computers, it can apply in many tasks more than what was made in the principles of their practical application (at the beginning of the decade of 1950). In this work the application of the Monte Carlo method will be approached in the simulation of the radiation interaction with the matter, to investigate dosimetric aspects of some problems that exist in the medical physics area. Also, contain an introduction about some historical data and some general concepts related with the Monte Carlo simulation are revised. (Author)

Shell model Monte Carlo methods

International Nuclear Information System (INIS)

Koonin, S.E.; Dean, D.J.; Langanke, K.

1997-01-01

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; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) 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, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)

The Monte Carlo simulation of the Ladon photon beam facility

International Nuclear Information System (INIS)

Strangio, C.

1976-01-01

The backward compton scattering of laser light against high energy electrons has been simulated with a Monte Carlo method. The main features of the produced photon beam are reported as well as a careful description of the numerical calculation

Cluster monte carlo method for nuclear criticality safety calculation

International Nuclear Information System (INIS)

Pei Lucheng

1984-01-01

One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further

Monte Carlo simulation and experimental verification of radiotherapy electron beams

International Nuclear Information System (INIS)

Griffin, J.; Deloar, H. M.

2007-01-01

Full text: Based on fundamental physics and statistics, the Monte Carlo technique is generally accepted as the accurate method for modelling radiation therapy treatments. A Monte Carlo simulation system has been installed, and models of linear accelerators in the more commonly used electron beam modes have been built and commissioned. A novel technique for radiation dosimetry is also being investigated. Combining the advantages of both water tank and solid phantom dosimetry, a hollow, thin walled shell or mask is filled with water and then raised above the natural water surface to produce a volume of water with the desired irregular shape.

Applications of the Monte Carlo method in radiation protection

International Nuclear Information System (INIS)

Kulkarni, R.N.; Prasad, M.A.

1999-01-01

This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)

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

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)

Monte Carlo simulation for the design of industrial gamma-ray transmission tomography

International Nuclear Information System (INIS)

Kim, Jongbum; Jung, Sunghee; Moon, Jinho; Kwon, Taekyong; Cho, Gyuseong

2011-01-01

The Monte Carlo simulation and experiment were carried out for a large-scale industrial gamma ray tomographic scanning geometry. The geometry of the tomographic system has a moving source with 16 stationary detectors. This geometry is advantageous for the diagnosis of a large-scale industrial plant. The simulation data was carried out for the phantom with 32 views, 16 detectors, and a different energy bin. The simulation data was processed to be used for image reconstruction. Image reconstruction was performed by a Diagonally-Scaled Gradient-Ascent algorithm for simulation data. Experiments were conducted in a 78 cm diameter column filled with polypropylene grains. Sixteen 0.5-inch-thick and 1 inch long NaI(Tl) cylindrical detectors, and 20 mCi of 137 Cs radioactive source were used. The experimental results were compared to the simulation data. The experimental results were similar to Monte Carlo simulation results. This result showed that the Monte Carlo simulation is useful for predicting the result of the industrial gamma tomographic scan method And it can also give a solution for designing the industrial gamma tomography system and preparing the field experiment. (author)

Monte Carlo simulation: tool for the calibration in analytical determination of radionuclides; Simulacion Monte Carlo: herramienta para la calibracion en determinaciones analiticas de radionucleidos

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, Jorge A. Carrazana; Ferrera, Eduardo A. Capote; Gomez, Isis M. Fernandez; Castro, Gloria V. Rodriguez; Ricardo, Niury Martinez, E-mail: cphr@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones (CPHR), La Habana (Cuba)

2013-07-01

This work shows how is established the traceability of the analytical determinations using this calibration method. Highlights the advantages offered by Monte Carlo simulation for the application of corrections by differences in chemical composition, density and height of the samples analyzed. Likewise, the results obtained by the LVRA in two exercises organized by the International Agency for Atomic Energy (IAEA) are presented. In these exercises (an intercomparison and a proficiency test) all reported analytical results were obtained based on calibrations in efficiency by Monte Carlo simulation using the DETEFF program.

Scouting the feasibility of Monte Carlo reactor dynamics simulations

International Nuclear Information System (INIS)

Legrady, David; Hoogenboom, J. Eduard

2008-01-01

In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

Scouting the feasibility of Monte Carlo reactor dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)

2008-07-01

In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses

Energy Technology Data Exchange (ETDEWEB)

ALAM,TODD M.

1999-12-21

Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

A Monte Carlo simulation model for stationary non-Gaussian processes

DEFF Research Database (Denmark)

Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.

2003-01-01

includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...

Monte Carlo simulation on kinetics of batch and semi-batch free radical polymerization

KAUST Repository

Shao, Jing

2015-10-27

Based on Monte Carlo simulation technology, we proposed a hybrid routine which combines reaction mechanism together with coarse-grained molecular simulation to study the kinetics of free radical polymerization. By comparing with previous experimental and simulation studies, we showed the capability of our Monte Carlo scheme on representing polymerization kinetics in batch and semi-batch processes. Various kinetics information, such as instant monomer conversion, molecular weight, and polydispersity etc. are readily calculated from Monte Carlo simulation. The kinetic constants such as polymerization rate k p is determined in the simulation without of “steady-state” hypothesis. We explored the mechanism for the variation of polymerization kinetics those observed in previous studies, as well as polymerization-induced phase separation. Our Monte Carlo simulation scheme is versatile on studying polymerization kinetics in batch and semi-batch processes.

CloudMC: a cloud computing application for Monte Carlo simulation

International Nuclear Information System (INIS)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-01-01

This work presents CloudMC, a cloud computing application—developed in Windows Azure®, the platform of the Microsoft® cloud—for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based—the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice. (note)

CloudMC: a cloud computing application for Monte Carlo simulation.

Science.gov (United States)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

Variational variance reduction for particle transport eigenvalue calculations using Monte Carlo adjoint simulation

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Larsen, Edward W.

2003-01-01

The Variational Variance Reduction (VVR) method is an effective technique for increasing the efficiency of Monte Carlo simulations [Ann. Nucl. Energy 28 (2001) 457; Nucl. Sci. Eng., in press]. This method uses a variational functional, which employs first-order estimates of forward and adjoint fluxes, to yield a second-order estimate of a desired system characteristic - which, in this paper, is the criticality eigenvalue k. If Monte Carlo estimates of the forward and adjoint fluxes are used, each having global 'first-order' errors of O(1/√N), where N is the number of histories used in the Monte Carlo simulation, then the statistical error in the VVR estimation of k will in principle be O(1/N). In this paper, we develop this theoretical possibility and demonstrate with numerical examples that implementations of the VVR method for criticality problems can approximate O(1/N) convergence for significantly large values of N

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

Science.gov (United States)

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

2012-11-01

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

Quantum statistical Monte Carlo methods and applications to spin systems

International Nuclear Information System (INIS)

Suzuki, M.

1986-01-01

A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures

Monte-Carlo simulation of electromagnetic showers

International Nuclear Information System (INIS)

Amatuni, Ts.A.

1984-01-01

The universal ELSS-1 program for Monte Carlo simulation of high energy electromagnetic showers in homogeneous absorbers of arbitrary geometry is written. The major processes and effects of electron and photon interaction with matter, particularly the Landau-Pomeranchuk-Migdal effect, are taken into account in the simulation procedures. The simulation results are compared with experimental data. Some characteristics of shower detectors and electromagnetic showers for energies up 1 TeV are calculated

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

Energy Technology Data Exchange (ETDEWEB)

Souris, Kevin, E-mail: kevin.souris@uclouvain.be; Lee, John Aldo [Center for Molecular Imaging and Experimental Radiotherapy, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Avenue Hippocrate 54, 1200 Brussels, Belgium and ICTEAM Institute, Université catholique de Louvain, Louvain-la-Neuve 1348 (Belgium); Sterpin, Edmond [Center for Molecular Imaging and Experimental Radiotherapy, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Avenue Hippocrate 54, 1200 Brussels, Belgium and Department of Oncology, Katholieke Universiteit Leuven, O& N I Herestraat 49, 3000 Leuven (Belgium)

2016-04-15

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2011-10-11

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

DNA strand breaks induced by electrons simulated with nanodosimetry Monte Carlo simulation code: NASIC

International Nuclear Information System (INIS)

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

2015-01-01

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

Monte Carlo simulations of neutron-scattering instruments using McStas

DEFF Research Database (Denmark)

Nielsen, K.; Lefmann, K.

2000-01-01

Monte Carlo simulations have become an essential tool for improving the performance of neutron-scattering instruments, since the level of sophistication in the design of instruments is defeating purely analytical methods. The program McStas, being developed at Rise National Laboratory, includes...

EGS4, Electron Photon Shower Simulation by Monte-Carlo

International Nuclear Information System (INIS)

1998-01-01

1 - Description of program or function: The EGS code system is one of a chain of three codes designed to solve the electromagnetic shower problem by Monte Carlo simulation. This chain makes possible simulation of almost any electron-photon transport problem conceivable. The structure of the system, with its global features, modular form, and structured programming, is readily adaptable to virtually any interfacing scheme that is desired on the part of the user. EGS4 is a package of subroutines plus block data with a flexible user interface. This allows for greater flexibility without requiring the user to be overly familiar with the internal details of the code. Combining this with the macro facility capabilities of the Mortran3 language, this reduces the likelihood that user edits will introduce bugs into the code. EGS4 uses material cross section and branching ratio data created and fit by the companion code, PEGS4. EGS4 allows for the implementation of importance sampling and other variance reduction techniques such as leading particle biasing, splitting, path length biasing, Russian roulette, etc. 2 - Method of solution: EGS employs the Monte Carlo method of solution. It allows all of the fundamental processes to be included and arbitrary geometries can be treated, also. Other minor processes, such as photoneutron production, can be added as a further generalization. Since showers develop randomly according to the quantum laws of probability, each shower is different. We again are led to the Monte Carlo method. 3 - Restrictions on the complexity of the problem: None noted

Determinantal and worldline quantum Monte Carlo methods for many-body systems

International Nuclear Information System (INIS)

Vekic, M.; White, S.R.

1993-01-01

We examine three different quantum Monte Carlo methods for studying systems of interacting particles. The determinantal quantum Monte Carlo method is compared to two different worldline simulations. The first worldline method consists of a simulation carried out in the real-space basis, while the second method is implemented using as basis the eigenstates of the Hamiltonian on blocks of the two-dimensional lattice. We look, in particular, at the Hubbard model on a 4x4 lattice with periodic boundary conditions. The block method is superior to the real-space method in terms of the computational cost of the simulation, but shows a much worse negative sign problem. For larger values of U and away from half-filling it is found that the real-space method can provide results at lower temperatures than the determinantal method. We show that the sign problem in the block method can be slightly improved by an appropriate choice of basis

Monte Carlo simulation of a mammographic test phantom

International Nuclear Information System (INIS)

Hunt, R. A.; Dance, D. R.; Pachoud, M.; Carlsson, G. A.; Sandborg, M.; Ullman, G.

2005-01-01

A test phantom, including a wide range of mammographic tissue equivalent materials and test details, was imaged on a digital mammographic system. In order to quantify the effect of scatter on the contrast obtained for the test details, calculations of the scatter-to-primary ratio (S/P) have been made using a Monte Carlo simulation of the digital mammographic imaging chain, grid and test phantom. The results show that the S/P values corresponding to the imaging conditions used were in the range 0.084-0.126. Calculated and measured pixel values in different regions of the image were compared as a validation of the model and showed excellent agreement. The results indicate the potential of Monte Carlo methods in the image quality-patient dose process optimisation, especially in the assessment of imaging conditions not available on standard mammographic units. (authors)

Monte Carlo simulation of radiative processes in electron-positron scattering

International Nuclear Information System (INIS)

Kleiss, R.H.P.

1982-01-01

The Monte Carlo simulation of scattering processes has turned out to be one of the most successful methods of translating theoretical predictions into experimentally meaningful quantities. It is the purpose of this thesis to describe how this approach can be applied to higher-order QED corrections to several fundamental processes. In chapter II a very brief overview of the currently interesting phenomena in e +- scattering is given. It is argued that accurate information on higher-order QED corrections is very important and that the Monte Carlo approach is one of the most flexible and general methods to obtain this information. In chapter III the author describes various techniques which are useful in this context, and makes a few remarks on the numerical aspects of the proposed method. In the following three chapters he applies this to the processes e + e - → μ + μ - (γ) and e + e - → qanti q(sigma). In chapter IV he motivates his choice of these processes in view of their experimental and theoretical relevance. The formulae necessary for a computer simulation of all quantities of interest, up to order α 3 , is given. Chapters V and VI describe how this simulation can be performed using the techniques mentioned in chapter III. In chapter VII it is shown how additional dynamical quantities, namely the polarization of the incoming and outgoing particles, can be incorporated in our treatment, and the relevant formulae for the example processes mentioned above are given. Finally, in chapter VIII the author presents some examples of the comparison between theoretical predictions based on Monte Carlo simulations as outlined here, and the results from actual experiments. (Auth.)

Monte Carlo simulation of the ARGO

International Nuclear Information System (INIS)

Depaola, G.O.

1997-01-01

We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)

Stabilization effect of fission source in coupled Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Olsen, Borge; Dufek, Jan [Div. of Nuclear Reactor Technology, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm (Sweden)

2017-08-15

A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

Stabilization effect of fission source in coupled Monte Carlo simulations

Directory of Open Access Journals (Sweden)

Börge Olsen

2017-08-01

Full Text Available A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

International Nuclear Information System (INIS)

Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM

2016-01-01

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

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

Energy Technology Data Exchange (ETDEWEB)

Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.

2016-11-29

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

Comparative evaluations of the Monte Carlo-based light propagation simulation packages for optical imaging

Directory of Open Access Journals (Sweden)

Lin Wang

2018-01-01

Full Text Available Monte Carlo simulation of light propagation in turbid medium has been studied for years. A number of software packages have been developed to handle with such issue. However, it is hard to compare these simulation packages, especially for tissues with complex heterogeneous structures. Here, we first designed a group of mesh datasets generated by Iso2Mesh software, and used them to cross-validate the accuracy and to evaluate the performance of four Monte Carlo-based simulation packages, including Monte Carlo model of steady-state light transport in multi-layered tissues (MCML, tetrahedron-based inhomogeneous Monte Carlo optical simulator (TIMOS, Molecular Optical Simulation Environment (MOSE, and Mesh-based Monte Carlo (MMC. The performance of each package was evaluated based on the designed mesh datasets. The merits and demerits of each package were also discussed. Comparative results showed that the TIMOS package provided the best performance, which proved to be a reliable, efficient, and stable MC simulation package for users.

Continuous energy Monte Carlo method based homogenization multi-group constants calculation

International Nuclear Information System (INIS)

Li Mancang; Wang Kan; Yao Dong

2012-01-01

The efficiency of the standard two-step reactor physics calculation relies on the accuracy of multi-group constants from the assembly-level homogenization process. In contrast to the traditional deterministic methods, generating the homogenization cross sections 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 bank can be used for a wide range of applications, resulting in the versatility using Monte Carlo codes for homogenization. As the first stage to realize Monte Carlo based lattice homogenization, the track length scheme is used as the foundation of cross section generation, which is straight forward. The scattering matrix and Legendre components, however, require special techniques. The Scattering Event method was proposed to solve the problem. There are no continuous energy counterparts in the Monte Carlo calculation for neutron diffusion coefficients. P 1 cross sections were used to calculate the diffusion coefficients for diffusion reactor simulator codes. B N theory is applied to take the leakage effect into account when the infinite lattice of identical symmetric motives is assumed. The MCMC code was developed and the code was applied in four assembly configurations to assess the accuracy and the applicability. At core-level, A PWR prototype core is examined. The results show that the Monte Carlo based multi-group constants behave well in average. The method could be applied to complicated configuration nuclear reactor core to gain higher accuracy. (authors)

Monte Carlo molecular simulation of phase-coexistence for oil production and processing

KAUST Repository

Li, Jun; Sun, Shuyu; Calo, Victor M.

2011-01-01

The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components

Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

KAUST Repository

Moraes, Alvaro

2015-01-01

even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.

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

Science.gov (United States)

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

2016-04-01

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

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung

2009-11-01

Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.

Statistics of Monte Carlo methods used in radiation transport calculation

International Nuclear Information System (INIS)

Datta, D.

2009-01-01

Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

Non-Boltzmann Ensembles and Monte Carlo Simulations

International Nuclear Information System (INIS)

Murthy, K. P. N.

2016-01-01

Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc . This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g ( E , M ), as a function of both energy E , and order parameter M . This is carried out in two stages. We estimate g ( E ) in the first stage

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.

Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

International Nuclear Information System (INIS)

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

Off-diagonal expansion quantum Monte Carlo.

Science.gov (United States)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Investigating the impossible: Monte Carlo simulations

International Nuclear Information System (INIS)

Kramer, Gary H.; Crowley, Paul; Burns, Linda C.

2000-01-01

Designing and testing new equipment can be an expensive and time consuming process or the desired performance characteristics may preclude its construction due to technological shortcomings. Cost may also prevent equipment being purchased for other scenarios to be tested. An alternative is to use Monte Carlo simulations to make the investigations. This presentation exemplifies how Monte Carlo code calculations can be used to fill the gap. An example is given for the investigation of two sizes of germanium detector (70 mm and 80 mm diameter) at four different crystal thicknesses (15, 20, 25, and 30 mm) and makes predictions on how the size affects the counting efficiency and the Minimum Detectable Activity (MDA). The Monte Carlo simulations have shown that detector efficiencies can be adequately modelled using photon transport if the data is used to investigate trends. The investigation of the effect of detector thickness on the counting efficiency has shown that thickness for a fixed diameter detector of either 70 mm or 80 mm is unimportant up to 60 keV. At higher photon energies, the counting efficiency begins to decrease as the thickness decreases as expected. The simulations predict that the MDA of either the 70 mm or 80 mm diameter detectors does not differ by more than a factor of 1.15 at 17 keV or 1.2 at 60 keV when comparing detectors of equivalent thicknesses. The MDA is slightly increased at 17 keV, and rises by about 52% at 660 keV, when the thickness is decreased from 30 mm to 15 mm. One could conclude from this information that the extra cost associated with the larger area Ge detectors may not be justified for the slight improvement predicted in the MDA. (author)

Monte Carlo simulation of mixed neutron-gamma radiation fields and dosimetry devices

International Nuclear Information System (INIS)

Zhang, Guoqing

2011-01-01

Monte Carlo methods based on random sampling are widely used in different fields for the capability of solving problems with a large number of coupled degrees of freedom. In this work, Monte Carlos methods are successfully applied for the simulation of the mixed neutron-gamma field in an interim storage facility and neutron dosimeters of different types. Details are discussed in two parts: In the first part, the method of simulating an interim storage facility loaded with CASTORs is presented. The size of a CASTOR is rather large (several meters) and the CASTOR wall is very thick (tens of centimeters). Obtaining the results of dose rates outside a CASTOR with reasonable errors costs usually hours or even days. For the simulation of a large amount of CASTORs in an interim storage facility, it needs weeks or even months to finish a calculation. Variance reduction techniques were used to reduce the calculation time and to achieve reasonable relative errors. Source clones were applied to avoid unnecessary repeated calculations. In addition, the simulations were performed on a cluster system. With the calculation techniques discussed above, the efficiencies of calculations can be improved evidently. In the second part, the methods of simulating the response of neutron dosimeters are presented. An Alnor albedo dosimeter was modelled in MCNP, and it has been simulated in the facility to calculate the calibration factor to get the evaluated response to a Cf-252 source. The angular response of Makrofol detectors to fast neutrons has also been investigated. As a kind of SSNTD, Makrofol can detect fast neutrons by recording the neutron induced heavy charged recoils. To obtain the information of charged recoils, general-purpose Monte Carlo codes were used for transporting incident neutrons. The response of Makrofol to fast neutrons is dependent on several factors. Based on the parameters which affect the track revealing, the formation of visible tracks was determined. For

Monte Carlo simulation of mixed neutron-gamma radiation fields and dosimetry devices

Energy Technology Data Exchange (ETDEWEB)

Zhang, Guoqing

2011-12-22

Monte Carlo methods based on random sampling are widely used in different fields for the capability of solving problems with a large number of coupled degrees of freedom. In this work, Monte Carlos methods are successfully applied for the simulation of the mixed neutron-gamma field in an interim storage facility and neutron dosimeters of different types. Details are discussed in two parts: In the first part, the method of simulating an interim storage facility loaded with CASTORs is presented. The size of a CASTOR is rather large (several meters) and the CASTOR wall is very thick (tens of centimeters). Obtaining the results of dose rates outside a CASTOR with reasonable errors costs usually hours or even days. For the simulation of a large amount of CASTORs in an interim storage facility, it needs weeks or even months to finish a calculation. Variance reduction techniques were used to reduce the calculation time and to achieve reasonable relative errors. Source clones were applied to avoid unnecessary repeated calculations. In addition, the simulations were performed on a cluster system. With the calculation techniques discussed above, the efficiencies of calculations can be improved evidently. In the second part, the methods of simulating the response of neutron dosimeters are presented. An Alnor albedo dosimeter was modelled in MCNP, and it has been simulated in the facility to calculate the calibration factor to get the evaluated response to a Cf-252 source. The angular response of Makrofol detectors to fast neutrons has also been investigated. As a kind of SSNTD, Makrofol can detect fast neutrons by recording the neutron induced heavy charged recoils. To obtain the information of charged recoils, general-purpose Monte Carlo codes were used for transporting incident neutrons. The response of Makrofol to fast neutrons is dependent on several factors. Based on the parameters which affect the track revealing, the formation of visible tracks was determined. For

Direct simulation Monte Carlo method for the Uehling-Uhlenbeck-Boltzmann equation.

Science.gov (United States)

Garcia, Alejandro L; Wagner, Wolfgang

2003-11-01

In this paper we describe a direct simulation Monte Carlo algorithm for the Uehling-Uhlenbeck-Boltzmann equation in terms of Markov processes. This provides a unifying framework for both the classical Boltzmann case as well as the Fermi-Dirac and Bose-Einstein cases. We establish the foundation of the algorithm by demonstrating its link to the kinetic equation. By numerical experiments we study its sensitivity to the number of simulation particles and to the discretization of the velocity space, when approximating the steady-state distribution.

Monte Carlo computation in the applied research of nuclear technology

International Nuclear Information System (INIS)

Xu Shuyan; Liu Baojie; Li Qin

2007-01-01

This article briefly introduces Monte Carlo Methods and their properties. It narrates the Monte Carlo methods with emphasis in their applications to several domains of nuclear technology. Monte Carlo simulation methods and several commonly used computer software to implement them are also introduced. The proposed methods are demonstrated by a real example. (authors)

PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO

Directory of Open Access Journals (Sweden)

WAYAN ARTHINI

2012-09-01

Full Text Available Value at Risk (VaR is the maximum potential loss on a portfolio based on the probability at a certain time.  In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data. Historical data is processed so as to obtain stock returns, variance, correlation coefficient, and variance-covariance matrix, then the method of Markowitz sought proportion of each stock fund, and portfolio risk and return portfolio. The data was then simulated by Monte Carlo simulation, Exact Monte Carlo Simulation and Expected Monte Carlo Simulation. Exact Monte Carlo simulation have same returns and standard deviation  with historical data, while the Expected Monte Carlo Simulation satistic calculation similar to historical data. The results of this research is the portfolio VaR  with time horizon T=1, T=10, T=22 and the confidence level of 95 %, values obtained VaR between historical data and Monte Carlo simulation data with the method exact and expected. Value of VaR from both Monte Carlo simulation is greater than VaR historical data.

Evaluation of cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Woo, Sang Keun; Kim, Wook; Park, Yong Sung; Kang, Joo Hyun; Lee, Yong Jin [Korea Institute of Radiological and Medical Sciences, KIRAMS, Seoul (Korea, Republic of); Cho, Doo Wan; Lee, Hong Soo; Han, Su Cheol [Jeonbuk Department of Inhalation Research, Korea Institute of toxicology, KRICT, Jeongeup (Korea, Republic of)

2016-12-15

These absorbed dose can calculated using the Monte Carlo transport code MCNP (Monte Carlo N-particle transport code). Internal radiotherapy absorbed dose was calculated using conventional software, such as OLINDA/EXM or Monte Carlo simulation. However, the OLINDA/EXM does not calculate individual absorbed dose and non-standard organ, such as tumor. While the Monte Carlo simulation can calculated non-standard organ and specific absorbed dose using individual CT image. External radiotherapy, absorbed dose can calculated by specific absorbed energy in specific organs using Monte Carlo simulation. The specific absorbed energy in each organ was difference between species or even if the same species. Since they have difference organ sizes, position, and density of organs. The aim of this study was to individually evaluated cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation. We evaluation of cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation. The absorbed energy in each organ compared with mouse heart was 54.6 fold higher than monkey absorbed energy in heart. Likewise lung was 88.4, liver was 16.0, urinary bladder was 29.4 fold higher than monkey. It means that the distance of each organs and organ mass was effects of the absorbed energy. This result may help to can calculated absorbed dose and more accuracy plan for external radiation beam therapy and internal radiotherapy.

Evaluation of cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation

International Nuclear Information System (INIS)

Woo, Sang Keun; Kim, Wook; Park, Yong Sung; Kang, Joo Hyun; Lee, Yong Jin; Cho, Doo Wan; Lee, Hong Soo; Han, Su Cheol

2016-01-01

These absorbed dose can calculated using the Monte Carlo transport code MCNP (Monte Carlo N-particle transport code). Internal radiotherapy absorbed dose was calculated using conventional software, such as OLINDA/EXM or Monte Carlo simulation. However, the OLINDA/EXM does not calculate individual absorbed dose and non-standard organ, such as tumor. While the Monte Carlo simulation can calculated non-standard organ and specific absorbed dose using individual CT image. External radiotherapy, absorbed dose can calculated by specific absorbed energy in specific organs using Monte Carlo simulation. The specific absorbed energy in each organ was difference between species or even if the same species. Since they have difference organ sizes, position, and density of organs. The aim of this study was to individually evaluated cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation. We evaluation of cobalt-60 energy deposit in mouse and monkey using Monte Carlo simulation. The absorbed energy in each organ compared with mouse heart was 54.6 fold higher than monkey absorbed energy in heart. Likewise lung was 88.4, liver was 16.0, urinary bladder was 29.4 fold higher than monkey. It means that the distance of each organs and organ mass was effects of the absorbed energy. This result may help to can calculated absorbed dose and more accuracy plan for external radiation beam therapy and internal radiotherapy.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

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

Determination of the optical properties of turbid media from a single Monte Carlo simulation

International Nuclear Information System (INIS)

Kienle, A.; Patterson, M.S.

1996-01-01

We describe a fast, accurate method for determination of the optical coefficients of 'semi-infinite' and 'infinite' turbid media. For the particular case of time-resolved reflectance from a biological medium, we show that a single Monte Carlo simulation can be used to fit the data and to derive the absorption and reduced scattering coefficients. Tests with independent Monte Carlo simulations showed that the errors in the deduced absorption and reduced scattering coefficients are smaller than 1% and 2%, respectively. (author)

Multi-level Monte Carlo Methods for Efficient Simulation of Coulomb Collisions

Science.gov (United States)

Ricketson, Lee

2013-10-01

We discuss the use of multi-level Monte Carlo (MLMC) schemes--originally introduced by Giles for financial applications--for the efficient simulation of Coulomb collisions in the Fokker-Planck limit. The scheme is based on a Langevin treatment of collisions, and reduces the computational cost of achieving a RMS error scaling as ɛ from O (ɛ-3) --for standard Langevin methods and binary collision algorithms--to the theoretically optimal scaling O (ɛ-2) for the Milstein discretization, and to O (ɛ-2 (logɛ)2) with the simpler Euler-Maruyama discretization. In practice, this speeds up simulation by factors up to 100. We summarize standard MLMC schemes, describe some tricks for achieving the optimal scaling, present results from a test problem, and discuss the method's range of applicability. This work was performed under the auspices of the U.S. DOE by the University of California, Los Angeles, under grant DE-FG02-05ER25710, and by LLNL under contract DE-AC52-07NA27344.

TITAN: a computer program for accident occurrence frequency analyses by component Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Nomura, Yasushi [Department of Fuel Cycle Safety Research, Nuclear Safety Research Center, Tokai Research Establishment, Japan Atomic Energy Research Institute, Tokai, Ibaraki (Japan); Tamaki, Hitoshi [Department of Safety Research Technical Support, Tokai Research Establishment, Japan Atomic Energy Research Institute, Tokai, Ibaraki (Japan); Kanai, Shigeru [Fuji Research Institute Corporation, Tokyo (Japan)

2000-04-01

In a plant system consisting of complex equipments and components for a reprocessing facility, there might be grace time between an initiating event and a resultant serious accident, allowing operating personnel to take remedial actions, thus, terminating the ongoing accident sequence. A component Monte Carlo simulation computer program TITAN has been developed to analyze such a complex reliability model including the grace time without any difficulty to obtain an accident occurrence frequency. Firstly, basic methods for the component Monte Carlo simulation is introduced to obtain an accident occurrence frequency, and then, the basic performance such as precision, convergence, and parallelization of calculation, is shown through calculation of a prototype accident sequence model. As an example to illustrate applicability to a real scale plant model, a red oil explosion in a German reprocessing plant model is simulated to show that TITAN can give an accident occurrence frequency with relatively good accuracy. Moreover, results of uncertainty analyses by TITAN are rendered to show another performance, and a proposal is made for introducing of a new input-data format to adapt the component Monte Carlo simulation. The present paper describes the calculational method, performance, applicability to a real scale, and new proposal for the TITAN code. In the Appendixes, a conventional analytical method is shown to avoid complex and laborious calculation to obtain a strict solution of accident occurrence frequency, compared with Monte Carlo method. The user's manual and the list/structure of program are also contained in the Appendixes to facilitate TITAN computer program usage. (author)

TITAN: a computer program for accident occurrence frequency analyses by component Monte Carlo simulation

International Nuclear Information System (INIS)

Nomura, Yasushi; Tamaki, Hitoshi; Kanai, Shigeru

2000-04-01

In a plant system consisting of complex equipments and components for a reprocessing facility, there might be grace time between an initiating event and a resultant serious accident, allowing operating personnel to take remedial actions, thus, terminating the ongoing accident sequence. A component Monte Carlo simulation computer program TITAN has been developed to analyze such a complex reliability model including the grace time without any difficulty to obtain an accident occurrence frequency. Firstly, basic methods for the component Monte Carlo simulation is introduced to obtain an accident occurrence frequency, and then, the basic performance such as precision, convergence, and parallelization of calculation, is shown through calculation of a prototype accident sequence model. As an example to illustrate applicability to a real scale plant model, a red oil explosion in a German reprocessing plant model is simulated to show that TITAN can give an accident occurrence frequency with relatively good accuracy. Moreover, results of uncertainty analyses by TITAN are rendered to show another performance, and a proposal is made for introducing of a new input-data format to adapt the component Monte Carlo simulation. The present paper describes the calculational method, performance, applicability to a real scale, and new proposal for the TITAN code. In the Appendixes, a conventional analytical method is shown to avoid complex and laborious calculation to obtain a strict solution of accident occurrence frequency, compared with Monte Carlo method. The user's manual and the list/structure of program are also contained in the Appendixes to facilitate TITAN computer program usage. (author)

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)

Problems in radiation shielding calculations with Monte Carlo methods

International Nuclear Information System (INIS)

Ueki, Kohtaro

1985-01-01

The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)

Parallel Monte Carlo simulations on an ARC-enabled computing grid

International Nuclear Information System (INIS)

Nilsen, Jon K; Samset, Bjørn H

2011-01-01

Grid computing opens new possibilities for running heavy Monte Carlo simulations of physical systems in parallel. The presentation gives an overview of GaMPI, a system for running an MPI-based random walker simulation on grid resources. Integrating the ARC middleware and the new storage system Chelonia with the Ganga grid job submission and control system, we show that MPI jobs can be run on a world-wide computing grid with good performance and promising scaling properties. Results for relatively communication-heavy Monte Carlo simulations run on multiple heterogeneous, ARC-enabled computing clusters in several countries are presented.

A Monte Carlo method and finite volume method coupled optical simulation method for parabolic trough solar collectors

International Nuclear Information System (INIS)

Liang, Hongbo; Fan, Man; You, Shijun; Zheng, Wandong; Zhang, Huan; Ye, Tianzhen; Zheng, Xuejing

2017-01-01

Highlights: •Four optical models for parabolic trough solar collectors were compared in detail. •Characteristics of Monte Carlo Method and Finite Volume Method were discussed. •A novel method was presented combining advantages of different models. •The method was suited to optical analysis of collectors with different geometries. •A new kind of cavity receiver was simulated depending on the novel method. -- Abstract: The PTC (parabolic trough solar collector) is widely used for space heating, heat-driven refrigeration, solar power, etc. The concentrated solar radiation is the only energy source for a PTC, thus its optical performance significantly affects the collector efficiency. In this study, four different optical models were constructed, validated and compared in detail. On this basis, a novel coupled method was presented by combining advantages of these models, which was suited to carry out a mass of optical simulations of collectors with different geometrical parameters rapidly and accurately. Based on these simulation results, the optimal configuration of a collector with highest efficiency can be determined. Thus, this method was useful for collector optimization and design. In the four models, MCM (Monte Carlo Method) and FVM (Finite Volume Method) were used to initialize photons distribution, as well as CPEM (Change Photon Energy Method) and MCM were adopted to describe the process of reflecting, transmitting and absorbing. For simulating reflection, transmission and absorption, CPEM was more efficient than MCM, so it was utilized in the coupled method. For photons distribution initialization, FVM saved running time and computation effort, whereas it needed suitable grid configuration. MCM only required a total number of rays for simulation, whereas it needed higher computing cost and its results fluctuated in multiple runs. In the novel coupled method, the grid configuration for FVM was optimized according to the “true values” from MCM of

A residual Monte Carlo method for discrete thermal radiative diffusion

International Nuclear Information System (INIS)

Evans, T.M.; Urbatsch, T.J.; Lichtenstein, H.; Morel, J.E.

2003-01-01

Residual Monte Carlo methods reduce statistical error at a rate of exp(-bN), where b is a positive constant and N is the number of particle histories. Contrast this convergence rate with 1/√N, which is the rate of statistical error reduction for conventional Monte Carlo methods. Thus, residual Monte Carlo methods hold great promise for increased efficiency relative to conventional Monte Carlo methods. Previous research has shown that the application of residual Monte Carlo methods to the solution of continuum equations, such as the radiation transport equation, is problematic for all but the simplest of cases. However, the residual method readily applies to discrete systems as long as those systems are monotone, i.e., they produce positive solutions given positive sources. We develop a residual Monte Carlo method for solving a discrete 1D non-linear thermal radiative equilibrium diffusion equation, and we compare its performance with that of the discrete conventional Monte Carlo method upon which it is based. We find that the residual method provides efficiency gains of many orders of magnitude. Part of the residual gain is due to the fact that we begin each timestep with an initial guess equal to the solution from the previous timestep. Moreover, fully consistent non-linear solutions can be obtained in a reasonable amount of time because of the effective lack of statistical noise. We conclude that the residual approach has great potential and that further research into such methods should be pursued for more general discrete and continuum systems

Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model

Science.gov (United States)

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

2018-04-01

While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.

Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation

International Nuclear Information System (INIS)

Marseguerra, M.; Zio, E.

2000-01-01

In this paper we present an optimization approach based on the combination of a Genetic Algorithms maximization procedure with a Monte Carlo simulation. The approach is applied within the context of plant logistic management for what concerns the choice of maintenance and repair strategies. A stochastic model of plant operation is developed from the standpoint of its reliability/availability behavior, i.e. of the failure/repair/maintenance processes of its components. The model is evaluated by Monte Carlo simulation in terms of economic costs and revenues of operation. The flexibility of the Monte Carlo method allows us to include several practical aspects such as stand-by operation modes, deteriorating repairs, aging, sequences of periodic maintenances, number of repair teams available for different kinds of repair interventions (mechanical, electronic, hydraulic, etc.), components priority rankings. A genetic algorithm is then utilized to optimize the components maintenance periods and number of repair teams. The fitness function object of the optimization is a profit function which inherently accounts for the safety and economic performance of the plant and whose value is computed by the above Monte Carlo simulation model. For an efficient combination of Genetic Algorithms and Monte Carlo simulation, only few hundreds Monte Carlo histories are performed for each potential solution proposed by the genetic algorithm. Statistical significance of the results of the solutions of interest (i.e. the best ones) is then attained exploiting the fact that during the population evolution the fit chromosomes appear repeatedly many times. The proposed optimization approach is applied on two case studies of increasing complexity

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung; Liang, Faming

2009-01-01

in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method

Importance estimation in Monte Carlo modelling of neutron and photon transport

International Nuclear Information System (INIS)

Mickael, M.W.

1992-01-01

The estimation of neutron and photon importance in a three-dimensional geometry is achieved using a coupled Monte Carlo and diffusion theory calculation. The parameters required for the solution of the multigroup adjoint diffusion equation are estimated from an analog Monte Carlo simulation of the system under investigation. The solution of the adjoint diffusion equation is then used as an estimate of the particle importance in the actual simulation. This approach provides an automated and efficient variance reduction method for Monte Carlo simulations. The technique has been successfully applied to Monte Carlo simulation of neutron and coupled neutron-photon transport in the nuclear well-logging field. The results show that the importance maps obtained in a few minutes of computer time using this technique are in good agreement with Monte Carlo generated importance maps that require prohibitive computing times. The application of this method to Monte Carlo modelling of the response of neutron porosity and pulsed neutron instruments has resulted in major reductions in computation time. (Author)

Understanding quantum tunneling using diffusion Monte Carlo simulations

Science.gov (United States)

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

2018-03-01

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

Monte Carlo simulations of plutonium gamma-ray spectra

International Nuclear Information System (INIS)

Koenig, Z.M.; Carlson, J.B.; Wang, Tzu-Fang; Ruhter, W.D.

1993-01-01

Monte Carlo calculations were investigated as a means of simulating the gamma-ray spectra of Pu. These simulated spectra will be used to develop and evaluate gamma-ray analysis techniques for various nondestructive measurements. Simulated spectra of calculational standards can be used for code intercomparisons, to understand systematic biases and to estimate minimum detection levels of existing and proposed nondestructive analysis instruments. The capability to simulate gamma-ray spectra from HPGe detectors could significantly reduce the costs of preparing large numbers of real reference materials. MCNP was used for the Monte Carlo transport of the photons. Results from the MCNP calculations were folded in with a detector response function for a realistic spectrum. Plutonium spectrum peaks were produced with Lorentzian shapes, for the x-rays, and Gaussian distributions. The MGA code determined the Pu isotopes and specific power of this calculated spectrum and compared it to a similar analysis on a measured spectrum

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.

Monte Carlo applications to radiation shielding problems

International Nuclear Information System (INIS)

Subbaiah, K.V.

2009-01-01

Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling of physical and mathematical systems to compute their results. However, basic concepts of MC are both simple and straightforward and can be learned by using a personal computer. Uses of Monte Carlo methods require large amounts of random numbers, and it was their use that spurred the development of pseudorandom number generators, which were far quicker to use than the tables of random numbers which had been previously used for statistical sampling. In Monte Carlo simulation of radiation transport, the history (track) of a particle is viewed as a random sequence of free flights that end with an interaction event where the particle changes its direction of movement, loses energy and, occasionally, produces secondary particles. The Monte Carlo simulation of a given experimental arrangement (e.g., an electron beam, coming from an accelerator and impinging on a water phantom) consists of the numerical generation of random histories. To simulate these histories we need an interaction model, i.e., a set of differential cross sections (DCS) for the relevant interaction mechanisms. The DCSs determine the probability distribution functions (pdf) of the random variables that characterize a track; 1) free path between successive interaction events, 2) type of interaction taking place and 3) energy loss and angular deflection in a particular event (and initial state of emitted secondary particles, if any). Once these pdfs are known, random histories can be generated by using appropriate sampling methods. If the number of generated histories is large enough, quantitative information on the transport process may be obtained by simply averaging over the simulated histories. The Monte Carlo method yields the same information as the solution of the Boltzmann transport equation, with the same interaction model, but is easier to implement. In particular, the simulation of radiation

Automatic variance reduction for Monte Carlo simulations via the local importance function transform

International Nuclear Information System (INIS)

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ''real'' particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ''black box''. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases

Gamma irradiation of cultural artifacts for disinfection using Monte Carlo simulations

International Nuclear Information System (INIS)

Choi, Jong-il; Yoon, Minchul; Kim, Dongho

2012-01-01

In this study, it has been investigated the disinfection of Korean cultural artifacts by gamma irradiation, simulating the absorbed dose distribution on the object with the Monte Carlo methodology. Fungal contamination was identified on two traditional Korean agricultural tools, Hongdukkae and Holtae, which had been stored in a museum. Nine primary species were identified from these items: Bjerkandera adusta, Dothideomycetes sp., Penicillium sp., Cladosporium tenuissimum, Aspergillus versicolor, Penicillium sp., Entrophospora sp., Aspergillus sydowii, and Corynascus sepedonium. However, these fungi were completely inactivated by gamma irradiation at an absorbed dose of 20 kGy on the front side. Monte Carlo N Particle Transport Code was used to simulate the doses applied to these cultural artifacts, and the measured dose distributions were well predicted by the simulations. These results show that irradiation is effective for the disinfection of cultural artifacts and that dose distribution can be predicted with Monte Carlo simulations, allowing the optimization of the radiation treatment. - Highlights: ► Radiation was applied for the disinfection of Korean cultural artifacts. ► Fungi on the artifacts were completely inactivated by the irradiation. ► Monte Carlo N Particle Transport Code was used to predict the dose distribution. ► This study is applicable for the preservation of cultural artifacts by irradiation.

Methods for coupling radiation, ion, and electron energies in grey Implicit Monte Carlo

International Nuclear Information System (INIS)

Evans, T.M.; Densmore, J.D.

2007-01-01

We present three methods for extending the Implicit Monte Carlo (IMC) method to treat the time-evolution of coupled radiation, electron, and ion energies. The first method splits the ion and electron coupling and conduction from the standard IMC radiation-transport process. The second method recasts the IMC equations such that part of the coupling is treated during the Monte Carlo calculation. The third method treats all of the coupling and conduction in the Monte Carlo simulation. We apply modified equation analysis (MEA) to simplified forms of each method that neglects the errors in the conduction terms. Through MEA we show that the third method is theoretically the most accurate. We demonstrate the effectiveness of each method on a series of 0-dimensional, nonlinear benchmark problems where the accuracy of the third method is shown to be up to ten times greater than the other coupling methods for selected calculations

Monte Carlo simulations of adsorption-induced segregation

DEFF Research Database (Denmark)

Christoffersen, Ebbe; Stoltze, Per; Nørskov, Jens Kehlet

2002-01-01

Through the use of Monte Carlo simulations we study the effect of adsorption-induced segregation. From the bulk composition, degree of dispersion and the partial pressure of the gas phase species we calculate the surface composition of bimetallic alloys. We show that both segregation and adsorption...

Neutron shielding calculations in a proton therapy facility based on Monte Carlo simulations and analytical models: Criterion for selecting the method of choice

International Nuclear Information System (INIS)

Titt, U.; Newhauser, W. D.

2005-01-01

Proton therapy facilities are shielded to limit the amount of secondary radiation to which patients, occupational workers and members of the general public are exposed. The most commonly applied shielding design methods for proton therapy facilities comprise semi-empirical and analytical methods to estimate the neutron dose equivalent. This study compares the results of these methods with a detailed simulation of a proton therapy facility by using the Monte Carlo technique. A comparison of neutron dose equivalent values predicted by the various methods reveals the superior accuracy of the Monte Carlo predictions in locations where the calculations converge. However, the reliability of the overall shielding design increases if simulation results, for which solutions have not converged, e.g. owing to too few particle histories, can be excluded, and deterministic models are being used at these locations. Criteria to accept or reject Monte Carlo calculations in such complex structures are not well understood. An optimum rejection criterion would allow all converging solutions of Monte Carlo simulation to be taken into account, and reject all solutions with uncertainties larger than the design safety margins. In this study, the optimum rejection criterion of 10% was found. The mean ratio was 26, 62% of all receptor locations showed a ratio between 0.9 and 10, and 92% were between 1 and 100. (authors)

Genetic algorithms and Monte Carlo simulation for optimal plant design

International Nuclear Information System (INIS)

Cantoni, M.; Marseguerra, M.; Zio, E.

2000-01-01

We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown-Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance

Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation

Energy Technology Data Exchange (ETDEWEB)

Nilmeier, J. P.; Crooks, G. E.; Minh, D. D. L.; Chodera, J. D.

2011-10-24

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Here, we introduce a new class of moves based on nonequilibrium dynamics: candidate configurations are generated through a finite-time process in which a system is actively driven out of equilibrium, and accepted with criteria that preserve the equilibrium distribution. The acceptance rule is similar to the Metropolis acceptance probability, but related to the nonequilibrium work rather than the instantaneous energy difference. Our method is applicable to sampling from both a single thermodynamic state or a mixture of thermodynamic states, and allows both coordinates and thermodynamic parameters to be driven in nonequilibrium proposals. While generating finite-time switching trajectories incurs an additional cost, driving some degrees of freedom while allowing others to evolve naturally can lead to large enhancements in acceptance probabilities, greatly reducing structural correlation times. Using nonequilibrium driven processes vastly expands the repertoire of useful Monte Carlo proposals in simulations of dense solvated systems.

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)

Acceleration of monte Carlo solution by conjugate gradient method

International Nuclear Information System (INIS)

Toshihisa, Yamamoto

2005-01-01

The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)

Meaningful timescales from Monte Carlo simulations of particle systems with hard-core interactions

Energy Technology Data Exchange (ETDEWEB)

Costa, Liborio I., E-mail: liborio78@gmail.com

2016-12-01

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.

Monte Carlo simulations in theoretical physic

International Nuclear Information System (INIS)

Billoire, A.

1991-01-01

After a presentation of the MONTE CARLO method principle, the method is applied, first to the critical exponents calculations in the three dimensions ISING model, and secondly to the discrete quantum chromodynamic with calculation times in function of computer power. 28 refs., 4 tabs

Development of ray tracing visualization program by Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro

1997-09-01

Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)

Simulation and study on the γ response spectrum of BGO detector by the application of monte carlo code MOCA

International Nuclear Information System (INIS)

Jia Wenbao; Chen Xiaowen; Xu Aiguo; Li Anmin

2010-01-01

Application of Monte Carlo method to build spectra library is useful to reduce experiment workload in Prompt Gamma Neutron Activation Analysis (PGNAA). The new Monte Carlo Code MOCA was used to simulate the response spectra of BGO detector for gamma rays from 137 Cs, 60 Co and neutron induced gamma rays from S and Ti. The results were compared with general code MCNP, show that the agreement of MOCA between simulation and experiment is better than MCNP. This research indicates that building spectra library by Monte Carlo method is feasible. (authors)

Quantum Mechanical Single Molecule Partition Function from PathIntegral Monte Carlo Simulations

Energy Technology Data Exchange (ETDEWEB)

Chempath, Shaji; Bell, Alexis T.; Predescu, Cristian

2006-10-01

An algorithm for calculating the partition function of a molecule with the path integral Monte Carlo method is presented. Staged thermodynamic perturbation with respect to a reference harmonic potential is utilized to evaluate the ratio of partition functions. Parallel tempering and a new Monte Carlo estimator for the ratio of partition functions are implemented here to achieve well converged simulations that give an accuracy of 0.04 kcal/mol in the reported free energies. The method is applied to various test systems, including a catalytic system composed of 18 atoms. Absolute free energies calculated by this method lead to corrections as large as 2.6 kcal/mol at 300 K for some of the examples presented.

The Hybrid Monte Carlo (HMC) method and dynamic fermions

International Nuclear Information System (INIS)

Amaral, Marcia G. do

1994-01-01

Nevertheless the Monte Carlo method has been extensively used in the simulation of many types of theories, the successful application has been established only for models containing boson fields. With the present computer generation, the development of faster and efficient algorithms became necessary and urgent. This paper studies the HMC and the dynamic fermions

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

Science.gov (United States)

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

2015-01-01

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

Monte Carlo 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.

A Monte Carlo simulation study of associated liquid crystals

Science.gov (United States)

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

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

Introduction to the simulation with MCNP Monte Carlo code and its applications in Medical Physics

International Nuclear Information System (INIS)

Parreno Z, F.; Paucar J, R.; Picon C, C.

1998-01-01

The simulation by Monte Carlo is tool which Medical Physics counts with it for the development of its research, the interest by this tool is growing, as we may observe in the main scientific journals for the years 1995-1997 where more than 27 % of the papers treat over Monte Carlo and/or its applications in the radiation transport.In the Peruvian Institute of Nuclear Energy we are implementing and making use of the MCNP4 and EGS4 codes. In this work are presented the general features of the Monte Carlo method and its more useful applications in Medical Physics. Likewise, it is made a simulation of the calculation of isodose curves in an interstitial treatment with Ir-192 wires in a mammary gland carcinoma. (Author)

Monte Carlo particle simulation and finite-element techniques for tandem mirror transport

International Nuclear Information System (INIS)

Rognlien, T.D.; Cohen, B.I.; Matsuda, Y.; Stewart, J.J. Jr.

1987-01-01

A description is given of numerical methods used in the study of axial transport in tandem mirrors owing to Coulomb collisions and rf diffusion. The methods are Monte Carlo particle simulations and direct solution to the Fokker-Planck equations by finite-element expansion. (author)

Monte Carlo particle simulation and finite-element techniques for tandem mirror transport

International Nuclear Information System (INIS)

Rognlien, T.D.; Cohen, B.I.; Matsuda, Y.; Stewart, J.J. Jr.

1985-12-01

A description is given of numerical methods used in the study of axial transport in tandem mirrors owing to Coulomb collisions and rf diffusion. The methods are Monte Carlo particle simulations and direct solution to the Fokker-Planck equations by finite-element expansion. 11 refs

Suppression of the initial transient in Monte Carlo criticality simulations

International Nuclear Information System (INIS)

Richet, Y.

2006-12-01

Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)

Monte Carlo Simulations of Neutron Oil well Logging Tools

International Nuclear Information System (INIS)

Azcurra, Mario

2002-01-01

Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented.The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively.The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation.The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B.Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation.In particular, the ratio C/O was analyzed as an indicator of oil saturation.Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition

Monte Carlo simulations of neutron oil well logging tools

International Nuclear Information System (INIS)

Azcurra, Mario O.; Zamonsky, Oscar M.

2003-01-01

Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented. The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively. The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation. The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B. Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation. In particular, the ratio C/O was analyzed as an indicator of oil saturation. Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition. (author)

Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications

CERN Document Server

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.

Exploring Various Monte Carlo Simulations for Geoscience Applications

Science.gov (United States)

Blais, R.

2010-12-01

Computer simulations are increasingly important in geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN), or chaotic random number (CRN) generators. Equidistributed quasi-random numbers (QRNs) can also be used in Monte Carlo simulations. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as Importance Sampling and Stratified Sampling can be implemented to significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on examples of geodetic applications of gravimetric terrain corrections and gravity inversion, conclusions and recommendations concerning their performance and general applicability are included.

Exploring pseudo- and chaotic random Monte Carlo simulations

Science.gov (United States)

Blais, J. A. Rod; Zhang, Zhan

2011-07-01

Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer-generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as importance sampling and stratified sampling can be applied in most Monte Carlo simulations and significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on some practical examples of geodetic direct and inverse problems, conclusions and recommendations concerning their performance and general applicability are included.

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.

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

Multi-Subband Ensemble Monte Carlo simulations of scaled GAA MOSFETs

Science.gov (United States)

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

2018-05-01

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

Monte Carlo method applied to medical physics

International Nuclear Information System (INIS)

Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.

2000-01-01

The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)

Neutron flux calculation by means of Monte Carlo methods

International Nuclear Information System (INIS)

Barz, H.U.; Eichhorn, M.

1988-01-01

In this report a survey of modern neutron flux calculation procedures by means of Monte Carlo methods is given. Due to the progress in the development of variance reduction techniques and the improvements of computational techniques this method is of increasing importance. The basic ideas in application of Monte Carlo methods are briefly outlined. In more detail various possibilities of non-analog games and estimation procedures are presented, problems in the field of optimizing the variance reduction techniques are discussed. In the last part some important international Monte Carlo codes and own codes of the authors are listed and special applications are described. (author)

Topological zero modes in Monte Carlo simulations

International Nuclear Information System (INIS)

Dilger, H.

1994-08-01

We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)

Numerical integration of the Langevin equation: Monte Carlo simulation

International Nuclear Information System (INIS)

Ermak, D.L.; Buckholz, H.

1980-01-01

Monte Carlo simulation techniques are derived for solving the ordinary Langevin equation of motion for a Brownian particle in the presence of an external force. These methods allow considerable freedom in selecting the size of the time step, which is restricted only by the rate of change in the external force. This approach is extended to the generalized Langevin equation which uses a memory function in the friction force term. General simulation techniques are derived which are independent of the form of the memory function. A special method requiring less storage space is presented for the case of the exponential memory function

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 simulation of a gas-sampled hadron calorimeter

Energy Technology Data Exchange (ETDEWEB)

Chang, C Y; Kunori, S; Rapp, P; Talaga, R; Steinberg, P; Tylka, A J; Wang, Z M

1988-02-15

A prototype of the OPAL barrel hadron calorimeter, which is a gas-sampled calorimeter using plastic streamer tubes, was exposed to pions at energies between 1 and 7 GeV. The response of the detector was simulated using the CERN GEANT3 Monte Carlo program. By using the observed high energy muon signals to deduce details of the streamer formation, the Monte Carlo program was able to reproduce the observed calorimeter response. The behavior of the hadron calorimeter when placed behind a lead glass electromagnetic calorimeter was also investigated.

CORPORATE VALUATION USING TWO-DIMENSIONAL MONTE CARLO SIMULATION

Directory of Open Access Journals (Sweden)

Toth Reka

2010-12-01

Full Text Available In this paper, we have presented a corporate valuation model. The model combine several valuation methods in order to get more accurate results. To determine the corporate asset value we have used the Gordon-like two-stage asset valuation model based on the calculation of the free cash flow to the firm. We have used the free cash flow to the firm to determine the corporate market value, which was calculated with use of the Black-Scholes option pricing model in frame of the two-dimensional Monte Carlo simulation method. The combined model and the use of the two-dimensional simulation model provides a better opportunity for the corporate value estimation.

Monte Carlo simulation of asymmetrical growth of cube-shaped nanoparticles

International Nuclear Information System (INIS)

Wang Yuanyuan; Xie Huaqing; Wu Zihua; Xing Jiaojiao

2016-01-01

We simulated the asymmetrical growth of cube-shaped nanoparticles by applying the Monte Carlo method. The influence of the specific mechanisms on the crystal growth of nanoparticles has been phenomenologically described by efficient growth possibilities along different directions (or crystal faces). The roles of the thermodynamic and kinetic factors have been evaluated in three phenomenological models. The simulation results would benefit the understanding about the cause and manner of the asymmetrical growth of nanoparticles. (paper)

SPQR: a Monte Carlo reactor kinetics code

International Nuclear Information System (INIS)

Cramer, S.N.; Dodds, H.L.

1980-02-01

The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations

Monte Carlo methods for the reliability analysis of Markov systems

International Nuclear Information System (INIS)

Buslik, A.J.

1985-01-01

This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator

Monte Carlo-molecular dynamics simulations for two-dimensional magnets

International Nuclear Information System (INIS)

Kawabata, C.; takeuchi, M.; Bishop, A.R.

1985-01-01

A combined Monte Carlo-molecular dynamics simulation technique is used to study the dynamic structure factor on a square lattice for isotropic Heisenberg and planar classical ferromagnetic spin Hamiltonians

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)

Data decomposition of Monte Carlo particle transport simulations via tally servers

International Nuclear Information System (INIS)

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit; Smith, Kord

2013-01-01

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations

Kontrola tačnosti rezultata u simulacijama Monte Karlo / Accuracy control in Monte Carlo simulations

Directory of Open Access Journals (Sweden)

Nebojša V. Nikolić

2010-04-01

Full Text Available U radu je demonstrirana primena metode automatizovanog ponavljanja nezavisnih simulacionih eksperimenata sa prikupljanjem statistike slučajnih procesa, u dostizanju i kontroli tačnosti simulacionih rezultata u simulaciji sistema masovnog opsluživanja Monte Karlo. Metoda se zasniva na primeni osnovnih stavova i teorema matematičke statistike i teorije verovatnoće. Tačnost simulacionih rezultata dovedena je u direktnu vezu sa brojem ponavljanja simulacionih eksperimenata. / The paper presents an application of the Automated Independent Replication with Gathering Statistics of the Stochastic Processes Method in achieving and controlling the accuracy of simulation results in the Monte Carlo queuing simulations. The method is based on the application of the basic theorems of the theory of probability and mathematical statistics. The accuracy of the simulation results is linked with a number of independent replications of simulation experiments.

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

Science.gov (United States)

Good, Brian

2013-01-01

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

Auxiliary-Field Quantum Monte Carlo Simulations of Strongly-Correlated Molecules and Solids

Energy Technology Data Exchange (ETDEWEB)

Chang, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Morales, M. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-11-10

We propose a method of implementing projected wave functions for second-quantized auxiliary-field quantum Monte Carlo (AFQMC) techniques. The method is based on expressing the two-body projector as one-body terms coupled to binary Ising fields. To benchmark the method, we choose to study the two-dimensional (2D) one-band Hubbard model with repulsive interactions using the constrained-path MC (CPMC). The CPMC uses a trial wave function to guide the random walks so that the so-called fermion sign problem can be eliminated. The trial wave function also serves as the importance function in Monte Carlo sampling. As such, the quality of the trial wave function has a direct impact to the efficiency and accuracy of the simulations.

Auxiliary-Field Quantum Monte Carlo Simulations of Strongly-Correlated Molecules and Solids

International Nuclear Information System (INIS)

Chang, C.; Morales, M. A.

2016-01-01

We propose a method of implementing projected wave functions for second-quantized auxiliary-field quantum Monte Carlo (AFQMC) techniques. The method is based on expressing the two-body projector as one-body terms coupled to binary Ising fields. To benchmark the method, we choose to study the two-dimensional (2D) one-band Hubbard model with repulsive interactions using the constrained-path MC (CPMC). The CPMC uses a trial wave function to guide the random walks so that the so-called fermion sign problem can be eliminated. The trial wave function also serves as the importance function in Monte Carlo sampling. As such, the quality of the trial wave function has a direct impact to the efficiency and accuracy of the simulations.

Lecture 1. Monte Carlo basics. Lecture 2. Adjoint Monte Carlo. Lecture 3. Coupled Forward-Adjoint calculations

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J.E. [Delft University of Technology, Interfaculty Reactor Institute, Delft (Netherlands)

2000-07-01

The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)

Lecture 1. Monte Carlo basics. Lecture 2. Adjoint Monte Carlo. Lecture 3. Coupled Forward-Adjoint calculations

International Nuclear Information System (INIS)

Hoogenboom, J.E.

2000-01-01

The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)

Numerical simulation of logging-while-drilling density image by Monte-Carlo method

International Nuclear Information System (INIS)

Yue Aizhong; He Biao; Zhang Jianmin; Wang Lijuan

2010-01-01

Logging-while-drilling system is researched by Monte Carlo Method. Model of Logging-while-drilling system is built, tool response and azimuth density image are acquired, methods dealing with azimuth density data is discussed. This outcome lay foundation for optimizing tool, developing new tool and logging explanation. (authors)

Microcanonical Monte Carlo

International Nuclear Information System (INIS)

Creutz, M.

1986-01-01

The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena

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.

On the inclusion of macroscopic theory in Monte Carlo simulation using game theory

International Nuclear Information System (INIS)

Tatarkiewicz, J.

1980-01-01

This paper presents the inclusion of macroscopic damage theory into Monte Carlo particle-range simulation using game theory. A new computer code called RADDI was developed on the basis of this inclusion. Results of Monte Carlo damage simulation after 6.3 MeV proton bombardment of silicon are compared with experimental data of Bulgakov et al. (orig.)

Monte-Carlo simulation of heavy-ion collisions

International Nuclear Information System (INIS)

Schenke, Bjoern; Jeon, Sangyong; Gale, Charles

2011-01-01

We present Monte-Carlo simulations for heavy-ion collisions combining PYTHIA and the McGill-AMY formalism to describe the evolution of hard partons in a soft background, modelled using hydrodynamic simulations. MARTINI generates full event configurations in the high p T region that take into account thermal QCD and QED effects as well as effects of the evolving medium. This way it is possible to perform detailed quantitative comparisons with experimental observables.

Simulating the reactions of CO2 in aqueous monoethanolamine solution by reaction ensemble Monte Carlo using the continuous fractional component method

NARCIS (Netherlands)

Balaji, S.P.; Gangarapu, S.; Ramdin, M.; Torres-Knoop, A.; Zuilhof, H.; Goetheer, E.L.V.; Dubbeldam, D.; Vlugt, T.J.H.

2015-01-01

Molecular simulations were used to compute the equilibrium concentrations of the different species in CO2/monoethanolamine solutions for different CO2 loadings. Simulations were performed in the Reaction Ensemble using the continuous fractional component Monte Carlo method at temperatures of 293,

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

Science.gov (United States)

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

Science.gov (United States)

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.