WorldWideScience

Sample records for carlo simulation method

  1. Metropolis Methods for Quantum Monte Carlo Simulations

    OpenAIRE

    Ceperley, D. M.

    2003-01-01

    Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...

  2. Simulation and the Monte Carlo method

    CERN Document Server

    Rubinstein, Reuven Y

    2016-01-01

    Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...

  3. 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.

  4. 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. ...

  5. Forest canopy BRDF simulation using Monte Carlo method

    NARCIS (Netherlands)

    Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.

    2006-01-01

    Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.

  6. Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)

    2011-07-01

    This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)

  7. Simulation and the Monte Carlo Method, Student Solutions Manual

    CERN Document Server

    Rubinstein, Reuven Y

    2012-01-01

    This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, suc

  8. Multi-pass Monte Carlo simulation method in nuclear transmutations.

    Science.gov (United States)

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

    2016-12-01

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

  9. 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)

  10. '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)

  11. 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

  12. Simulation of Rossi-α method with analog Monte-Carlo method

    International Nuclear Information System (INIS)

    Lu Yuzhao; Xie Qilin; Song Lingli; Liu Hangang

    2012-01-01

    The analog Monte-Carlo code for simulating Rossi-α method based on Geant4 was developed. The prompt neutron decay constant α of six metal uranium configurations in Oak Ridge National Laboratory were calculated. α was also calculated by Burst-Neutron method and the result was consistent with the result of Rossi-α method. There is the difference between results of analog Monte-Carlo simulation and experiment, and the reasons for the difference is the gaps between uranium layers. The influence of gaps decrease as the sub-criticality deepens. The relative difference between results of analog Monte-Carlo simulation and experiment changes from 19% to 0.19%. (authors)

  13. The Monte Carlo Simulation Method for System Reliability and Risk Analysis

    CERN Document Server

    Zio, Enrico

    2013-01-01

    Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.   Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.   This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...

  14. Simulation of thermochromotographic processes by the Monte-Carlo method

    International Nuclear Information System (INIS)

    Zvara, I.

    1983-01-01

    A simplified microscopic model is proposed for the gas adsorption thermochromatography in open columns with laminar flow of the carrier gas. This model describes the downstream migration of a sample molecule as a rather small number of some effective random displacements and sequences of adsorption-desorption events that occur without changing the coordinates. The relevant probability density distributions are thereby derived. Based on this model, a computer program has been developed for simulating thermochromatographic zone profiles by employing the Monte-Carlo technique. The program is versatile in accounting for a wide range of experimental conditions and for treating various properties of the species to be separated. Some results of these simulations are given to demonstrate the influence of several parameters on the zone profile

  15. Numerical simulation of the blast impact problem using the Direct Simulation Monte Carlo (DSMC) method

    International Nuclear Information System (INIS)

    Sharma, Anupam; Long, Lyle N.

    2004-01-01

    A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented

  16. Numerical simulation of the blast impact problem using the Direct Simulation Monte Carlo (DSMC) method

    Science.gov (United States)

    Sharma, Anupam; Long, Lyle N.

    2004-10-01

    A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.

  17. External individual monitoring: experiments and simulations using Monte Carlo Method

    International Nuclear Information System (INIS)

    Guimaraes, Carla da Costa

    2005-01-01

    In this work, we have evaluated the possibility of applying the Monte Carlo simulation technique in photon dosimetry of external individual monitoring. The GEANT4 toolkit was employed to simulate experiments with radiation monitors containing TLD-100 and CaF 2 :NaCl thermoluminescent detectors. As a first step, X ray spectra were generated impinging electrons on a tungsten target. Then, the produced photon beam was filtered in a beryllium window and additional filters to obtain the radiation with desired qualities. This procedure, used to simulate radiation fields produced by a X ray tube, was validated by comparing characteristics such as half value layer, which was also experimentally measured, mean photon energy and the spectral resolution of simulated spectra with that of reference spectra established by international standards. In the construction of thermoluminescent dosimeter, two approaches for improvements have. been introduced. The first one was the inclusion of 6% of air in the composition of the CaF 2 :NaCl detector due to the difference between measured and calculated values of its density. Also, comparison between simulated and experimental results showed that the self-attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account. Then, in the second approach, the light attenuation coefficient of CaF 2 :NaCl compound estimated by simulation to be 2,20(25) mm -1 was introduced. Conversion coefficients C p from air kerma to personal dose equivalent were calculated using a slab water phantom with polymethyl-metacrilate (PMMA) walls, for reference narrow and wide X ray spectrum series [ISO 4037-1], and also for the wide spectra implanted and used in routine at Laboratorio de Dosimetria. Simulations of backscattered radiations by PMMA slab water phantom and slab phantom of ICRU tissue-equivalent material produced very similar results. Therefore, the PMMA slab water phantom that can be easily constructed with low

  18. MONTE CARLO METHOD AND APPLICATION IN @RISK SIMULATION SYSTEM

    Directory of Open Access Journals (Sweden)

    Gabriela Ižaríková

    2015-12-01

    Full Text Available The article is an example of using the software simulation @Risk designed for simulation in Microsoft Excel spread sheet, demonstrated the possibility of its usage in order to show a universal method of solving problems. The simulation is experimenting with computer models based on the real production process in order to optimize the production processes or the system. The simulation model allows performing a number of experiments, analysing them, evaluating, optimizing and afterwards applying the results to the real system. A simulation model in general is presenting modelling system by using mathematical formulations and logical relations. In the model is possible to distinguish controlled inputs (for instance investment costs and random outputs (for instance demand, which are by using a model transformed into outputs (for instance mean value of profit. In case of a simulation experiment at the beginning are chosen controlled inputs and random (stochastic outputs are generated randomly. Simulations belong into quantitative tools, which can be used as a support for a decision making.

  19. Non-analogue Monte Carlo method, application to neutron simulation; Methode de Monte Carlo non analogue, application a la simulation des neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Morillon, B.

    1996-12-31

    With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.

  20. Adjoint Weighting Methods Applied to Monte Carlo Simulations of Applications and Experiments in Nuclear Criticality

    Energy Technology Data Exchange (ETDEWEB)

    Kiedrowski, Brian C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-03-11

    The goals of this project are to develop Monte Carlo radiation transport methods and simulation software for engineering analysis that are robust, efficient and easy to use; and provide computational resources to assess and improve the predictive capability of radiation transport methods and nuclear data.

  1. Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

    Science.gov (United States)

    Gergely, John Robert

    2009-01-01

    Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…

  2. 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...

  3. 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)

  4. 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

  5. Simulation of neutral gas flow in a tokamak divertor using the Direct Simulation Monte Carlo method

    International Nuclear Information System (INIS)

    Gleason-González, Cristian; Varoutis, Stylianos; Hauer, Volker; Day, Christian

    2014-01-01

    Highlights: • Subdivertor gas flows calculations in tokamaks by coupling the B2-EIRENE and DSMC method. • The results include pressure, temperature, bulk velocity and particle fluxes in the subdivertor. • Gas recirculation effect towards the plasma chamber through the vertical targets is found. • Comparison between DSMC and the ITERVAC code reveals a very good agreement. - Abstract: This paper presents a new innovative scientific and engineering approach for describing sub-divertor gas flows of fusion devices by coupling the B2-EIRENE (SOLPS) code and the Direct Simulation Monte Carlo (DSMC) method. The present study exemplifies this with a computational investigation of neutral gas flow in the ITER's sub-divertor region. The numerical results include the flow fields and contours of the overall quantities of practical interest such as the pressure, the temperature and the bulk velocity assuming helium as model gas. Moreover, the study unravels the gas recirculation effect located behind the vertical targets, viz. neutral particles flowing towards the plasma chamber. Comparison between calculations performed by the DSMC method and the ITERVAC code reveals a very good agreement along the main sub-divertor ducts

  6. 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

  7. 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

  8. 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.

  9. Geant4 based Monte Carlo simulation for verifying the modified sum-peak method.

    Science.gov (United States)

    Aso, Tsukasa; Ogata, Yoshimune; Makino, Ryuta

    2018-04-01

    The modified sum-peak method can practically estimate radioactivity by using solely the peak and the sum peak count rate. In order to efficiently verify the method in various experimental conditions, a Geant4 based Monte Carlo simulation for a high-purity germanium detector system was applied. The energy spectra in the detector were simulated for a 60 Co point source in various source to detector distances. The calculated radioactivity shows good agreement with the number of decays in the simulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. A hybrid transport-diffusion method for Monte Carlo radiative-transfer simulations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Urbatsch, Todd J.; Evans, Thomas M.; Buksas, Michael W.

    2007-01-01

    Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Monte Carlo particle-transport simulations in diffusive media. If standard Monte Carlo is used in such media, particle histories will consist of many small steps, resulting in a computationally expensive calculation. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many small Monte Carlo steps, thus increasing the efficiency of the simulation. In addition, given that DDMC is based on a diffusion equation, it should produce accurate solutions if used judiciously. In practice, DDMC is combined with standard Monte Carlo to form a hybrid transport-diffusion method that can accurately simulate problems with both diffusive and non-diffusive regions. In this paper, we extend previously developed DDMC techniques in several ways that improve the accuracy and utility of DDMC for nonlinear, time-dependent, radiative-transfer calculations. The use of DDMC in these types of problems is advantageous since, due to the underlying linearizations, optically thick regions appear to be diffusive. First, we employ a diffusion equation that is discretized in space but is continuous in time. Not only is this methodology theoretically more accurate than temporally discretized DDMC techniques, but it also has the benefit that a particle's time is always known. Thus, there is no ambiguity regarding what time to assign a particle that leaves an optically thick region (where DDMC is used) and begins transporting by standard Monte Carlo in an optically thin region. Also, we treat the interface between optically thick and optically thin regions with an improved method, based on the asymptotic diffusion-limit boundary condition, that can produce accurate results regardless of the angular distribution of the incident Monte Carlo particles. Finally, we develop a technique for estimating radiation momentum deposition during the

  11. 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.

  12. The adaptation method in the Monte Carlo simulation for computed tomography

    Directory of Open Access Journals (Sweden)

    Hyounggun Lee

    2015-06-01

    Full Text Available The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT. To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA and a human-like voxel phantom (KTMAN-2 (Los Alamos National Laboratory, Los Alamos, NM, USA. For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations—assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.

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

    Science.gov (United States)

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

    2018-03-01

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

  14. Improving Power System Risk Evaluation Method Using Monte Carlo Simulation and Gaussian Mixture Method

    Directory of Open Access Journals (Sweden)

    GHAREHPETIAN, G. B.

    2009-06-01

    Full Text Available The analysis of the risk of partial and total blackouts has a crucial role to determine safe limits in power system design, operation and upgrade. Due to huge cost of blackouts, it is very important to improve risk assessment methods. In this paper, Monte Carlo simulation (MCS was used to analyze the risk and Gaussian Mixture Method (GMM has been used to estimate the probability density function (PDF of the load curtailment, in order to improve the power system risk assessment method. In this improved method, PDF and a suggested index have been used to analyze the risk of loss of load. The effect of considering the number of generation units of power plants in the risk analysis has been studied too. The improved risk assessment method has been applied to IEEE 118 bus and the network of Khorasan Regional Electric Company (KREC and the PDF of the load curtailment has been determined for both systems. The effect of various network loadings, transmission unavailability, transmission capacity and generation unavailability conditions on blackout risk has been investigated too.

  15. Experimental results and Monte Carlo simulations of a landmine localization device using the neutron backscattering method

    CERN Document Server

    Datema, C P; Eijk, C W E

    2002-01-01

    Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.

  16. Shuttle vertical fin flowfield by the direct simulation Monte Carlo method

    Science.gov (United States)

    Hueser, J. E.; Brock, F. J.; Melfi, L. T.

    1985-01-01

    The flow properties in a model flowfield, simulating the shuttle vertical fin, determined using the Direct Simulation Monte Carlo method. The case analyzed corresponds to an orbit height of 225 km with the freestream velocity vector orthogonal to the fin surface. Contour plots of the flowfield distributions of density, temperature, velocity and flow angle are presented. The results also include mean molecular collision frequency (which reaches 1/60 sec near the surface), collision frequency density (approaches 7 x 10 to the 18/cu m sec at the surface) and the mean free path (19 m at the surface).

  17. Three-dimensional hypersonic rarefied flow calculations using direct simulation Monte Carlo method

    Science.gov (United States)

    Celenligil, M. Cevdet; Moss, James N.

    1993-01-01

    A summary of three-dimensional simulations on the hypersonic rarefied flows in an effort to understand the highly nonequilibrium flows about space vehicles entering the Earth's atmosphere for a realistic estimation of the aerothermal loads is presented. Calculations are performed using the direct simulation Monte Carlo method with a five-species reacting gas model, which accounts for rotational and vibrational internal energies. Results are obtained for the external flows about various bodies in the transitional flow regime. For the cases considered, convective heating, flowfield structure and overall aerodynamic coefficients are presented and comparisons are made with the available experimental data. The agreement between the calculated and measured results are very good.

  18. 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)

  19. Coherent-wave Monte Carlo method for simulating light propagation in tissue

    Science.gov (United States)

    Kraszewski, Maciej; Pluciński, Jerzy

    2016-03-01

    Simulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative transfer equation, allows to simulate only propagation of light averaged over the ensemble of turbid medium realizations. This makes them unuseful for simulating phenomena connected to coherence properties of light. We propose a new method for simulating propagation of coherent light (e.g. laser beam) in biological tissue, that we called Coherent-Wave Monte Carlo method. This method is based on direct computation of optical interaction between scatterers inside the random medium, what allows to reduce amount of memory and computation time required for simulation. We present the theoretical basis of the proposed method and its comparison with finite-difference methods for simulating light propagation in scattering media in Rayleigh approximation regime.

  20. Methods for Monte Carlo simulation of the exospheres of the moon and Mercury

    Science.gov (United States)

    Hodges, R. R., Jr.

    1980-01-01

    A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.

  1. 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.

  2. 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

  3. DSMC calculations for the double ellipse. [direct simulation Monte Carlo method

    Science.gov (United States)

    Moss, James N.; Price, Joseph M.; Celenligil, M. Cevdet

    1990-01-01

    The direct simulation Monte Carlo (DSMC) method involves the simultaneous computation of the trajectories of thousands of simulated molecules in simulated physical space. Rarefied flow about the double ellipse for test case 6.4.1 has been calculated with the DSMC method of Bird. The gas is assumed to be nonreacting nitrogen flowing at a 30 degree incidence with respect to the body axis, and for the surface boundary conditions, the wall is assumed to be diffuse with full thermal accommodation and at a constant wall temperature of 620 K. A parametric study is presented that considers the effect of variations of computational domain, gas model, cell size, and freestream density on surface quantities.

  4. 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.

  5. Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method

    Science.gov (United States)

    Cave, H. M.; Tseng, K.-C.; Wu, J.-S.; Jermy, M. C.; Huang, J.-C.; Krumdieck, S. P.

    2008-06-01

    An unsteady sampling routine for a general parallel direct simulation Monte Carlo method called PDSC is introduced, allowing the simulation of time-dependent flow problems in the near continuum range. A post-processing procedure called DSMC rapid ensemble averaging method (DREAM) is developed to improve the statistical scatter in the results while minimising both memory and simulation time. This method builds an ensemble average of repeated runs over small number of sampling intervals prior to the sampling point of interest by restarting the flow using either a Maxwellian distribution based on macroscopic properties for near equilibrium flows (DREAM-I) or output instantaneous particle data obtained by the original unsteady sampling of PDSC for strongly non-equilibrium flows (DREAM-II). The method is validated by simulating shock tube flow and the development of simple Couette flow. Unsteady PDSC is found to accurately predict the flow field in both cases with significantly reduced run-times over single processor code and DREAM greatly reduces the statistical scatter in the results while maintaining accurate particle velocity distributions. Simulations are then conducted of two applications involving the interaction of shocks over wedges. The results of these simulations are compared to experimental data and simulations from the literature where there these are available. In general, it was found that 10 ensembled runs of DREAM processing could reduce the statistical uncertainty in the raw PDSC data by 2.5-3.3 times, based on the limited number of cases in the present study.

  6. Design space development for the extraction process of Danhong injection using a Monte Carlo simulation method.

    Directory of Open Access Journals (Sweden)

    Xingchu Gong

    Full Text Available A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs. Extraction number, extraction time, and the mass ratio of water and material (W/M ratio were selected as critical process parameters (CPPs. Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10,000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.

  7. Design space development for the extraction process of Danhong injection using a Monte Carlo simulation method.

    Science.gov (United States)

    Gong, Xingchu; Li, Yao; Chen, Huali; Qu, Haibin

    2015-01-01

    A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10,000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.

  8. Application of the direct simulation Monte Carlo method to the full shuttle geometry

    Science.gov (United States)

    Bird, G. A.

    1990-01-01

    A new set of programs has been developed for the application of the direct simulation Monte Carlo (or DSMC) method to rarefied gas flows with complex three-dimensional boundaries. The programs are efficient in terms of the computational load and also in terms of the effort required to set up particular cases. This efficiency is illustrated through computations of the flow about the Shuttle Orbiter. The general flow features are illustrated for altitudes from 170 to 100 km. Also, the computed lift-drag ratio during re-entry is compared with flight measurements.

  9. A numerical study of rays in random media. [Monte Carlo method simulation

    Science.gov (United States)

    Youakim, M. Y.; Liu, C. H.; Yeh, K. C.

    1973-01-01

    Statistics of electromagnetic rays in a random medium are studied numerically by the Monte Carlo method. Two dimensional random surfaces with prescribed correlation functions are used to simulate the random media. Rays are then traced in these sample media. Statistics of the ray properties such as the ray positions and directions are computed. Histograms showing the distributions of the ray positions and directions at different points along the ray path as well as at given points in space are given. The numerical experiment is repeated for different cases corresponding to weakly and strongly random media with isotropic and anisotropic irregularities. Results are compared with those derived from theoretical investigations whenever possible.

  10. The Linked Neighbour List (LNL) method for fast off-lattice Monte Carlo simulations of fluids

    Science.gov (United States)

    Mazzeo, M. D.; Ricci, M.; Zannoni, C.

    2010-03-01

    We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.

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

    Science.gov (United States)

    Boyd, Iain D.

    1991-01-01

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

  12. Adaptive Splitting Integrators for Enhancing Sampling Efficiency of Modified Hamiltonian Monte Carlo Methods in Molecular Simulation.

    Science.gov (United States)

    Akhmatskaya, Elena; Fernández-Pendás, Mario; Radivojević, Tijana; Sanz-Serna, J M

    2017-10-24

    The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modified Hamiltonians within a Hybrid Monte Carlo (HMC) framework, often outperform in sampling efficiency standard techniques such as molecular dynamics (MD) and HMC. The performance of MHMC may be enhanced further through the rational choice of the simulation parameters and by replacing the standard Verlet integrator with more sophisticated splitting algorithms. Unfortunately, it is not easy to identify the appropriate values of the parameters that appear in those algorithms. We propose a technique, that we call MAIA (Modified Adaptive Integration Approach), which, for a given simulation system and a given time step, automatically selects the optimal integrator within a useful family of two-stage splitting formulas. Extended MAIA (or e-MAIA) is an enhanced version of MAIA, which additionally supplies a value of the method-specific parameter that, for the problem under consideration, keeps the momentum acceptance rate at a user-desired level. The MAIA and e-MAIA algorithms have been implemented, with no computational overhead during simulations, in MultiHMC-GROMACS, a modified version of the popular software package GROMACS. Tests performed on well-known molecular models demonstrate the superiority of the suggested approaches over a range of integrators (both standard and recently developed), as well as their capacity to improve the sampling efficiency of GSHMC, a noticeable method for molecular simulation in the MHMC family. GSHMC combined with e-MAIA shows a remarkably good performance when compared to MD and HMC coupled with the appropriate adaptive integrators.

  13. Study of Monte Carlo Simulation Method for Methane Phase Diagram Prediction using Two Different Potential Models

    KAUST Repository

    Kadoura, Ahmad

    2011-06-06

    Lennard‐Jones (L‐J) and Buckingham exponential‐6 (exp‐6) potential models were used to produce isotherms for methane at temperatures below and above critical one. Molecular simulation approach, particularly Monte Carlo simulations, were employed to create these isotherms working with both canonical and Gibbs ensembles. Experiments in canonical ensemble with each model were conducted to estimate pressures at a range of temperatures above methane critical temperature. Results were collected and compared to experimental data existing in literature; both models showed an elegant agreement with the experimental data. In parallel, experiments below critical temperature were run in Gibbs ensemble using L‐J model only. Upon comparing results with experimental ones, a good fit was obtained with small deviations. The work was further developed by adding some statistical studies in order to achieve better understanding and interpretation to the estimated quantities by the simulation. Methane phase diagrams were successfully reproduced by an efficient molecular simulation technique with different potential models. This relatively simple demonstration shows how powerful molecular simulation methods could be, hence further applications on more complicated systems are considered. Prediction of phase behavior of elemental sulfur in sour natural gases has been an interesting and challenging field in oil and gas industry. Determination of elemental sulfur solubility conditions helps avoiding all kinds of problems caused by its dissolution in gas production and transportation processes. For this purpose, further enhancement to the methods used is to be considered in order to successfully simulate elemental sulfur phase behavior in sour natural gases mixtures.

  14. A method based on Monte Carlo simulation for the determination of the G(E) function.

    Science.gov (United States)

    Chen, Wei; Feng, Tiancheng; Liu, Jun; Su, Chuanying; Tian, Yanjie

    2015-02-01

    The G(E) function method is a spectrometric method for the exposure dose estimation; this paper describes a method based on Monte Carlo method to determine the G(E) function of a 4″ × 4″ × 16″ NaI(Tl) detector. Simulated spectrums of various monoenergetic gamma rays in the region of 40 -3200 keV and the corresponding deposited energy in an air ball in the energy region of full-energy peak were obtained using Monte Carlo N-particle Transport Code. Absorbed dose rate in air was obtained according to the deposited energy and divided by counts of corresponding full-energy peak to get the G(E) function value at energy E in spectra. Curve-fitting software 1st0pt was used to determine coefficients of the G(E) function. Experimental results show that the calculated dose rates using the G(E) function determined by the authors' method are accordant well with those values obtained by ionisation chamber, with a maximum deviation of 6.31 %. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  15. Lectures on Monte Carlo methods

    CERN Document Server

    Madras, Neal

    2001-01-01

    Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati

  16. Numerical investigation of turbomolecular pumps using the direct simulation Monte Carlo method with moving surfaces

    NARCIS (Netherlands)

    Versluis, R.; Dorsman, R.; Thielen, L.; Roos, M.E.

    2009-01-01

    A new approach for performing numerical direct simulation Monte Carlo (DSMC) simulations on turbomolecular pumps in the free molecular and transitional flow regimes is described. The chosen approach is to use surfaces that move relative to the grid to model the effect of rotors and stators on a gas

  17. 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

  18. Simulação do equilíbrio: o método de Monte Carlo Equilibrium simulation: Monte Carlo method

    Directory of Open Access Journals (Sweden)

    Alejandro López-Castillo

    2007-01-01

    Full Text Available We make several simulations using the Monte Carlo method in order to obtain the chemical equilibrium for several first-order reactions and one second-order reaction. We study several direct, reverse and consecutive reactions. These simulations show the fluctuations and relaxation time and help to understand the solution of the corresponding differential equations of chemical kinetics. This work was done in an undergraduate physical chemistry course at UNIFIEO.

  19. 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

  20. 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.

  1. The Calculation of Thermal Conductivities by Three Dimensional Direct Simulation Monte Carlo Method.

    Science.gov (United States)

    Zhao, Xin-Peng; Li, Zeng-Yao; Liu, He; Tao, Wen-Quan

    2015-04-01

    Three dimensional direct simulation Monte Carlo (DSMC) method with the variable soft sphere (VSS) collision model is implemented to solve the Boltzmann equation and to acquire the heat flux between two parallel plates (Fourier Flow). The gaseous thermal conductivity of nitrogen is derived based on the Fourier's law under local equilibrium condition at temperature from 270 to 1800 K and pressure from 0.5 to 100,000 Pa and compared with the experimental data and Eucken relation from Chapman and Enskog (CE) theory. It is concluded that the present results are consistent with the experimental data but much higher than those by Eucken relation especially at high temperature. The contribution of internal energy of molecule to the gaseous thermal conductivity becomes significant as increasing the temperature.

  2. Investigation of Reliabilities of Bolt Distances for Bolted Structural Steel Connections by Monte Carlo Simulation Method

    Directory of Open Access Journals (Sweden)

    Ertekin Öztekin Öztekin

    2015-12-01

    Full Text Available Design of the distance of bolts to each other and design of the distance of bolts to the edge of connection plates are made based on minimum and maximum boundary values proposed by structural codes. In this study, reliabilities of those distances were investigated. For this purpose, loading types, bolt types and plate thicknesses were taken as variable parameters. Monte Carlo Simulation (MCS method was used in the reliability computations performed for all combination of those parameters. At the end of study, all reliability index values for all those distances were presented in graphics and tables. Results obtained from this study compared with the values proposed by some structural codes and finally some evaluations were made about those comparisons. Finally, It was emphasized in the end of study that, it would be incorrect of the usage of the same bolt distances in the both traditional designs and the higher reliability level designs.

  3. 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...

  4. Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

    Science.gov (United States)

    Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.

    1994-01-01

    Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

  5. Monte Carlo simulation in nuclear medicine

    International Nuclear Information System (INIS)

    Morel, Ch.

    2007-01-01

    The Monte Carlo method allows for simulating random processes by using series of pseudo-random numbers. It became an important tool in nuclear medicine to assist in the design of new medical imaging devices, optimise their use and analyse their data. Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes. The availability to simulate time dependent processes opens up new horizons for Monte Carlo simulation in nuclear medicine. In a near future, these developments will allow to tackle simultaneously imaging and dosimetry issues and soon, case system Monte Carlo simulations may become part of the nuclear medicine diagnostic process. This paper describes some Monte Carlo method basics and the sampling methods that were developed for it. It gives a referenced list of different simulation software used in nuclear medicine and enumerates some of their present and prospective applications. (author)

  6. Efficient Data-Worth Analysis Using a Multilevel Monte Carlo Method Applied in Oil Reservoir Simulations

    Science.gov (United States)

    Lu, D.; Ricciuto, D. M.; Evans, K. J.

    2017-12-01

    Data-worth analysis plays an essential role in improving the understanding of the subsurface system, in developing and refining subsurface models, and in supporting rational water resources management. However, data-worth analysis is computationally expensive as it requires quantifying parameter uncertainty, prediction uncertainty, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface simulations using standard Monte Carlo (MC) sampling or advanced surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose efficient Bayesian analysis of data-worth using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce the computational cost with the use of multifidelity approximations. As the data-worth analysis involves a great deal of expectation estimations, the cost savings from MLMC in the assessment can be very outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it to a highly heterogeneous oil reservoir simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the estimation obtained from the standard MC. But compared to the standard MC, the MLMC greatly reduces the computational costs in the uncertainty reduction estimation, with up to 600 days cost savings when one processor is used.

  7. 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.

  8. Grid generation and adaptation for the Direct Simulation Monte Carlo Method. [for complex flows past wedges and cones

    Science.gov (United States)

    Olynick, David P.; Hassan, H. A.; Moss, James N.

    1988-01-01

    A grid generation and adaptation procedure based on the method of transfinite interpolation is incorporated into the Direct Simulation Monte Carlo Method of Bird. In addition, time is advanced based on a local criterion. The resulting procedure is used to calculate steady flows past wedges and cones. Five chemical species are considered. In general, the modifications result in a reduced computational effort. Moreover, preliminary results suggest that the simulation method is time step dependent if requirements on cell sizes are not met.

  9. Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods

    Energy Technology Data Exchange (ETDEWEB)

    Godfrey, Andrew T [ORNL; Gehin, Jess C [ORNL; Bekar, Kursat B [ORNL; Celik, Cihangir [ORNL

    2014-01-01

    The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.

  10. Constant-pH Hybrid Nonequilibrium Molecular Dynamics–Monte Carlo Simulation Method

    Science.gov (United States)

    2016-01-01

    A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys.2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD–MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD–MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems. PMID:26300709

  11. Constant-pH Hybrid Nonequilibrium Molecular Dynamics-Monte Carlo Simulation Method.

    Science.gov (United States)

    Chen, Yunjie; Roux, Benoît

    2015-08-11

    A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys. 2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD-MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD-MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems.

  12. Mean field simulation for Monte Carlo integration

    CERN Document Server

    Del Moral, Pierre

    2013-01-01

    In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko

  13. Comparison of Monte Carlo and fuzzy math simulation methods for quantitative microbial risk assessment.

    Science.gov (United States)

    Davidson, Valerie J; Ryks, Joanne

    2003-10-01

    The objective of food safety risk assessment is to quantify levels of risk for consumers as well as to design improved processing, distribution, and preparation systems that reduce exposure to acceptable limits. Monte Carlo simulation tools have been used to deal with the inherent variability in food systems, but these tools require substantial data for estimates of probability distributions. The objective of this study was to evaluate the use of fuzzy values to represent uncertainty. Fuzzy mathematics and Monte Carlo simulations were compared to analyze the propagation of uncertainty through a number of sequential calculations in two different applications: estimation of biological impacts and economic cost in a general framework and survival of Campylobacter jejuni in a sequence of five poultry processing operations. Estimates of the proportion of a population requiring hospitalization were comparable, but using fuzzy values and interval arithmetic resulted in more conservative estimates of mortality and cost, in terms of the intervals of possible values and mean values, compared to Monte Carlo calculations. In the second application, the two approaches predicted the same reduction in mean concentration (-4 log CFU/ ml of rinse), but the limits of the final concentration distribution were wider for the fuzzy estimate (-3.3 to 5.6 log CFU/ml of rinse) compared to the probability estimate (-2.2 to 4.3 log CFU/ml of rinse). Interval arithmetic with fuzzy values considered all possible combinations in calculations and maximum membership grade for each possible result. Consequently, fuzzy results fully included distributions estimated by Monte Carlo simulations but extended to broader limits. When limited data defines probability distributions for all inputs, fuzzy mathematics is a more conservative approach for risk assessment than Monte Carlo simulations.

  14. A calibration method for whole-body counters, using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Ishikawa, T.; Matsumoto, M.; Uchiyama, M.

    1996-01-01

    A Monte Carlo simulation code was developed to estimate the counting efficiencies in whole-body counting for various body sizes. The code consists of mathematical models and parameters which are categorised into three groups: a geometrical model for phantom and detectors, a photon transport model, and a detection system model. Photon histories were simulated with these models. The counting efficiencies for five 137 Cs block phantoms of different sizes were calculated by the code and compared with those measured with a whole-body counter at NIRS (Japan). The phantoms corresponded to a newborn, a 5 month old, a 6 year old, and 11 year old and an adult. The differences between the measured and calculated values were within 6%. For the adult phantom, the difference was 0.5%. The results suggest that the Monte Carlo simulation code can be used to estimate the counting efficiencies for various body sizes. (Author)

  15. A calibration method for whole-body counters, using Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Ishikawa, T.; Matsumoto, M.; Uchiyama, M. [National Inst. of Radiological Sciences, Chiba (Japan)

    1996-11-01

    A Monte Carlo simulation code was developed to estimate the counting efficiencies in whole-body counting for various body sizes. The code consists of mathematical models and parameters which are categorised into three groups: a geometrical model for phantom and detectors, a photon transport model, and a detection system model. Photon histories were simulated with these models. The counting efficiencies for five {sup 137}Cs block phantoms of different sizes were calculated by the code and compared with those measured with a whole-body counter at NIRS (Japan). The phantoms corresponded to a newborn, a 5 month old, a 6 year old, and 11 year old and an adult. The differences between the measured and calculated values were within 6%. For the adult phantom, the difference was 0.5%. The results suggest that the Monte Carlo simulation code can be used to estimate the counting efficiencies for various body sizes. (Author).

  16. Analysis of large solid propellant rocket engine exhaust plumes using the direct simulation Monte Carlo method

    Science.gov (United States)

    Hueser, J. E.; Brock, F. J.; Melfi, L. T., Jr.; Bird, G. A.

    1984-01-01

    A new solution procedure has been developed to analyze the flowfield properties in the vicinity of the Inertial Upper Stage/Spacecraft during the 1st stage (SRMI) burn. Continuum methods are used to compute the nozzle flow and the exhaust plume flowfield as far as the boundary where the breakdown of translational equilibrium leaves these methods invalid. The Direct Simulation Monte Carlo (DSMC) method is applied everywhere beyond this breakdown boundary. The flowfield distributions of density, velocity, temperature, relative abundance, surface flux density, and pressure are discussed for each species for 2 sets of boundary conditions: vacuum and freestream. The interaction of the exhaust plume and the freestream with the spacecraft and the 2-stream direct interaction are discussed. The results show that the low density, high velocity, counter flowing free-stream substantially modifies the flowfield properties and the flux density incident on the spacecraft. A freestream bow shock is observed in the data, located forward of the high density region of the exhaust plume into which the freestream gas does not penetrate. The total flux density incident on the spacecraft, integrated over the SRM1 burn interval is estimated to be of the order of 10 to the 22nd per sq m (about 1000 atomic layers).

  17. A new algorithm for the simulation of the Boltzmann equation using the direct simulation monte-carlo method

    International Nuclear Information System (INIS)

    Ganjaei, A. A.; Nourazar, S. S.

    2009-01-01

    A new algorithm, the modified direct simulation Monte-Carlo (MDSMC) method, for the simulation of Couette- Taylor gas flow problem is developed. The Taylor series expansion is used to obtain the modified equation of the first order time discretization of the collision equation and the new algorithm, MDSMC, is implemented to simulate the collision equation in the Boltzmann equation. In the new algorithm (MDSMC) there exists a new extra term which takes in to account the effect of the second order collision. This new extra term has the effect of enhancing the appearance of the first Taylor instabilities of vortices streamlines. In the new algorithm (MDSMC) there also exists a second order term in time step in the probabilistic coefficients which has the effect of simulation with higher accuracy than the previous DSMC algorithm. The appearance of the first Taylor instabilities of vortices streamlines using the MDSMC algorithm at different ratios of ω/ν (experimental data of Taylor) occurred at less time-step than using the DSMC algorithm. The results of the torque developed on the stationary cylinder using the MDSMC algorithm show better agreement in comparison with the experimental data of Kuhlthau than the results of the torque developed on the stationary cylinder using the DSMC algorithm

  18. Hybrid method for fast Monte Carlo simulation of diffuse reflectance from a multilayered tissue model with tumor-like heterogeneities.

    Science.gov (United States)

    Zhu, Caigang; Liu, Quan

    2012-01-01

    We present a hybrid method that combines a multilayered scaling method and a perturbation method to speed up the Monte Carlo simulation of diffuse reflectance from a multilayered tissue model with finite-size tumor-like heterogeneities. The proposed method consists of two steps. In the first step, a set of photon trajectory information generated from a baseline Monte Carlo simulation is utilized to scale the exit weight and exit distance of survival photons for the multilayered tissue model. In the second step, another set of photon trajectory information, including the locations of all collision events from the baseline simulation and the scaling result obtained from the first step, is employed by the perturbation Monte Carlo method to estimate diffuse reflectance from the multilayered tissue model with tumor-like heterogeneities. Our method is demonstrated to shorten simulation time by several orders of magnitude. Moreover, this hybrid method works for a larger range of probe configurations and tumor models than the scaling method or the perturbation method alone.

  19. Monte-Carlo method simulation of the Bremsstrahlung mirror reflection experiment

    International Nuclear Information System (INIS)

    Aliev, F.K.; Muminov, A.T.; Skvortsov, V.V.; Osmanov, B.S.

    2004-01-01

    Full text: To detect gamma-ray mirror reflection on macroscopic smooth surface a search experiment at microtron MT-22S with 330 meter flying distance is in progress. Measured slip angles (i.e. angles between incident ray and reflector surface) don't exceed tens of micro-radian. Under such angles an effect of the reflection could be easily veiled due to negative background conditions. That is why the process needed to be simulated by Monte-Carlo method as accurate as possible and corresponding computer program was developed. A first operating mode of the MT-22S generates 13 MeV electrons that are incident on a Bremsstrahlung target. So energies of gamma-rays were simulated to be in the range of 0.01†12.5 MeV and be distributed by known Shift formula. When any gamma-quantum was incident on the reflector it resulted in following two cases. If its slip angle was more than the critical one, gamma-quantum was to be absorbed by the reflector and the program started to simulate next event. In the other case the program replaced incident gamma-quantum trajectory parameters by the reflected ones. The gamma-quantum trajectory behind the reflector was traced till its detector. Any gamma-quantum that got the detector was to be registered. As any simulated gamma-quantum was of random energy the critical slip angle of every simulated event was evaluated by the following formula: α crit = eh/E √ZN A ρ/πAm. Table values of the absorption coefficients were used for random simulation of gamma-quanta absorption in the air. And it was assumed that any gamma-quantum interaction with air resulted in its disappearance. Dependence of different flying distances (120 and 330 m), gap heights (10, 20 and 50 μ) of the gap collimator and inclinations (20 and 40 μrad) of the reflector's plane on detected gamma-quanta energy distribution and vertical angle one was studied with a help of the developed program

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

    Science.gov (United States)

    Sima, Octavian; Luca, Aurelian; Sahagia, Maria

    2017-08-01

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

  1. 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.

  2. Simulation of Jack-Up Overturning Using the Monte Carlo Method with Artificially Increased Significant Wave Height

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2010-01-01

    wave height irrespectively of the non-linearity in the system. However, the FORM analysis only gives an approximation to the mean out-crossing rate. A more exact result can be obtained by Monte Carlo simulations, but the necessary length of the time domain simulations for very low out-crossing rates...... might be prohibitive long. In such cases the property mentioned above for the FORM reliability index can be assumed valid in the Monte Carlo simulations making it possible to increase the out-crossing rates and thus reduced the necessary length of the time domain simulations by applying a larger......-linear processes the mean out-crossing rate depends non-linearly on the response level r and a good estimate can be found using the First Order Reliability Method (FORM), see e.g. Jensen and Capul (2006). The FORM analysis also shows that the reliability index is strictly inversely proportional to the significant...

  3. Monte Carlo Simulation of Phase Transitions

    OpenAIRE

    村井, 信行; N., MURAI; 中京大学教養部

    1983-01-01

    In the Monte Carlo simulation of phase transition, a simple heat bath method is applied to the classical Heisenberg model in two dimensions. It reproduces the correlation length predicted by the Monte Carlo renor-malization group and also computed in the non-linear σ model

  4. 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)

  5. 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

  6. Monte carlo simulation for soot dynamics

    KAUST Repository

    Zhou, Kun

    2012-01-01

    A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

  7. 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

  8. Monte Carlo methods

    CERN Document Server

    Kalos, Melvin H

    2008-01-01

    This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application. Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research.The book focuses on two basic themes: The first is the importance of random walks as they occur both in natural stochastic systems and in their relationship to integral and differential equations. The second theme is that of variance reduction in general and importance sampling in particular as a technique for efficient use of the methods. Random walks are introduced with an elementary example in which the modeling of radiation transport arises directly from a schematic probabilistic description of the interaction of radiation with matter. Building on this example, the relationship between random walks and integral equations is outlined

  9. 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

  10. 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.

  11. 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

  12. 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

  13. Simulation of diffuse photon migration in tissue by a Monte Carlo method derived from the optical scattering of spheroids.

    Science.gov (United States)

    Hart, Vern P; Doyle, Timothy E

    2013-09-01

    A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.

  14. A Monte Carlo simulation method for assessing biotransformation effects on groundwater fuel hydrocarbon plume lengths

    International Nuclear Information System (INIS)

    McNab, W.W. Jr.

    2000-01-01

    Biotransformation of dissolved groundwater hydrocarbon plumes emanating from leaking underground fuel tanks should, in principle, result in plume length stabilization over relatively short distances, thus diminishing the environmental risk. However, because the behavior of hydrocarbon plumes is usually poorly constrained at most leaking underground fuel tank sites in terms of release history, groundwater velocity, dispersion, as well as the biotransformation rate, demonstrating such a limitation in plume length is problematic. Biotransformation signatures in the aquifer geochemistry, most notably elevated bicarbonate, may offer a means of constraining the relationship between plume length and the mean biotransformation rate. In this study, modeled plume lengths and spatial bicarbonate differences among a population of synthetic hydrocarbon plumes, generated through Monte Carlo simulation of an analytical solute transport model, are compared to field observations from six underground storage tank (UST) sites at military bases in California. Simulation results indicate that the relationship between plume length and the distribution of bicarbonate is best explained by biotransformation rates that are consistent with ranges commonly reported in the literature. This finding suggests that bicarbonate can indeed provide an independent means for evaluating limitations in hydrocarbon plume length resulting from biotransformation. (Author)

  15. DSMC calculations for the delta wing. [Direct Simulation Monte Carlo method

    Science.gov (United States)

    Celenligil, M. Cevdet; Moss, James N.

    1990-01-01

    Results are reported from three-dimensional direct simulation Monte Carlo (DSMC) computations, using a variable-hard-sphere molecular model, of hypersonic flow on a delta wing. The body-fitted grid is made up of deformed hexahedral cells divided into six tetrahedral subcells with well defined triangular faces; the simulation is carried out for 9000 time steps using 150,000 molecules. The uniform freestream conditions include M = 20.2, T = 13.32 K, rho = 0.00001729 kg/cu m, and T(wall) = 620 K, corresponding to lambda = 0.00153 m and Re = 14,000. The results are presented in graphs and briefly discussed. It is found that, as the flow expands supersonically around the leading edge, an attached leeside flow develops around the wing, and the near-surface density distribution has a maximum downstream from the stagnation point. Coefficients calculated include C(H) = 0.067, C(DP) = 0.178, C(DF) = 0.110, C(L) = 0.714, and C(D) = 1.089. The calculations required 56 h of CPU time on the NASA Langley Voyager CRAY-2 supercomputer.

  16. Monte Carlo codes and Monte Carlo simulator program

    International Nuclear Information System (INIS)

    Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.

    1990-03-01

    Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)

  17. 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

  18. 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....

  19. Monte Carlo simulation studies of spatial resolution in magnification mammography using the edge method

    Science.gov (United States)

    Koutalonis, M.; Delis, H.; Spyrou, G.; Costaridou, L.; Tzanakos, G.; Panayiotakis, G.

    2009-05-01

    Small sized focal spots are very essential when magnification is performed in mammography, as they represent the only way to reduce the geometrical unsharpness. The effect of focal spot size on spatial resolution in contact mammography or under magnification has been experimentally investigated but, due to construction limitations, only a small range of focal spot sizes has been studied. In this study, a Monte Carlo simulation model is utilized in order to examine the effect of a wide range of focal spots on spatial resolution under magnification conditions. A thick sharp edge consisted of lead was imaged under various conditions and the corresponding spatial resolution was calculated through the Modulation Transfer Function. Results demonstrate that increasing the degree of magnification from 1.0 to 2.0 induces degradation on spatial resolution which varies from 49% for a 0.04 mm focal spot to 53.2% for a 0.14 mm one. Larger focal spots cause higher degradation even for low magnification. Focal spots larger than 0.10 mm are considered appropriate only for low degrees of magnification according to the IAEA regulations that designate spatial resolution for mammography higher than 12 lp/mm. However, for high degrees of magnification the focal spot size should be even smaller. The construction of a microfocus of 0.04 mm would result in acceptable values of spatial resolution even for degrees of magnification up to 1.9.

  20. Monte Carlo simulation studies of spatial resolution in magnification mammography using the edge method

    Energy Technology Data Exchange (ETDEWEB)

    Koutalonis, M; Delis, H; Costaridou, L; Panayiotakis, G [University of Patras, Department of Medical Physics, 26500 Rio-Patras (Greece); Spyrou, G [Academy of Athens, Biomedical Research Foundation, 11527 Athens (Greece); Tzanakos, G [University of Athens, Department of Physics, 15771 Athens (Greece)], E-mail: mkoutalonis@med.upatras.gr

    2009-05-15

    Small sized focal spots are very essential when magnification is performed in mammography, as they represent the only way to reduce the geometrical unsharpness. The effect of focal spot size on spatial resolution in contact mammography or under magnification has been experimentally investigated but, due to construction limitations, only a small range of focal spot sizes has been studied. In this study, a Monte Carlo simulation model is utilized in order to examine the effect of a wide range of focal spots on spatial resolution under magnification conditions. A thick sharp edge consisted of lead was imaged under various conditions and the corresponding spatial resolution was calculated through the Modulation Transfer Function. Results demonstrate that increasing the degree of magnification from 1.0 to 2.0 induces degradation on spatial resolution which varies from 49% for a 0.04 mm focal spot to 53.2% for a 0.14 mm one. Larger focal spots cause higher degradation even for low magnification. Focal spots larger than 0.10 mm are considered appropriate only for low degrees of magnification according to the IAEA regulations that designate spatial resolution for mammography higher than 12 lp/mm. However, for high degrees of magnification the focal spot size should be even smaller. The construction of a microfocus of 0.04 mm would result in acceptable values of spatial resolution even for degrees of magnification up to 1.9.

  1. Simulation of the functioning of a gamma camera using Monte Carlo method; Simulacion del funcionamiento de una camara gamma mediante metodo Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Oramas Polo, I.

    2014-07-01

    This paper presents the simulation of the gamma camera Park Isocam II by Monte Carlo code SIMIND. This simulation allows detailed assessment of the functioning of the gamma camera. The parameters evaluated by means of the simulation are: the intrinsic uniformity with different window amplitudes, the system uniformity, the extrinsic spatial resolution, the maximum rate of counts, the intrinsic sensitivity, the system sensitivity, the energy resolution and the pixel size. The results of the simulation are compared and evaluated against the specifications of the manufacturer of the gamma camera and taking into account the National Protocol for Quality Control of Nuclear Medicine Instruments of the Cuban Medical Equipment Control Center. The simulation reported here demonstrates the validity of the SIMIND Monte Carlo code to evaluate the performance of the gamma camera Park Isocam II and as result a computational model of the camera has been obtained. (Author)

  2. Application of the direct simulation Monte Carlo method to nanoscale heat transfer between a soot particle and the surrounding gas

    International Nuclear Information System (INIS)

    Yang, M.; Liu, F.; Smallwood, G.J.

    2004-01-01

    Laser-Induced Incandescence (LII) technique has been widely used to measure soot volume fraction and primary particle size in flames and engine exhaust. Currently there is lack of quantitative understanding of the shielding effect of aggregated soot particles on its conduction heat loss rate to the surrounding gas. The conventional approach for this problem would be the application of the Monte Carlo (MC) method. This method is based on simulation of the trajectories of individual molecules and calculation of the heat transfer at each of the molecule/molecule collisions and the molecule/particle collisions. As the first step toward calculating the heat transfer between a soot aggregate and the surrounding gas, the Direct Simulation Monte Carlo (DSMC) method was used in this study to calculate the heat transfer rate between a single spherical aerosol particle and its cooler surrounding gas under different conditions of temperature, pressure, and the accommodation coefficient. A well-defined and simple hard sphere model was adopted to describe molecule/molecule elastic collisions. A combination of the specular reflection and completely diffuse reflection model was used to consider molecule/particle collisions. The results obtained by DSMC are in good agreement with the known analytical solution of heat transfer rate for an isolated, motionless sphere in the free-molecular regime. Further the DSMC method was applied to calculate the heat transfer in the transition regime. Our present DSMC results agree very well with published DSMC data. (author)

  3. The effect of carrier gas flow rate and source cell temperature on low pressure organic vapor phase deposition simulation by direct simulation Monte Carlo method

    Science.gov (United States)

    Wada, Takao; Ueda, Noriaki

    2013-04-01

    The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature.

  4. Cu-Au Alloys Using Monte Carlo Simulations and the BFS Method for Alloys

    Science.gov (United States)

    Bozzolo, Guillermo; Good, Brian; Ferrante, John

    1996-01-01

    Semi empirical methods have shown considerable promise in aiding in the calculation of many properties of materials. Materials used in engineering applications have defects that occur for various reasons including processing. In this work we present the first application of the BFS method for alloys to describe some aspects of microstructure due to processing for the Cu-Au system (Cu-Au, CuAu3, and Cu3Au). We use finite temperature Monte Carlo calculations, in order to show the influence of 'heat treatment' in the low-temperature phase of the alloy. Although relatively simple, it has enough features that could be used as a first test of the reliability of the technique. The main questions to be answered in this work relate to the existence of low temperature ordered structures for specific concentrations, for example, the ability to distinguish between rather similar phases for equiatomic alloys (CuAu I and CuAu II, the latter characterized by an antiphase boundary separating two identical phases).

  5. A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions

    Science.gov (United States)

    Liang, Yihao; Xing, Xiangjun; Li, Yaohang

    2017-06-01

    In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures, and adopts the sequential updating scheme of Metropolis algorithm. It makes no approximation in the computation of energy, and reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We further use this method to simulate primitive model electrolytes, and measure very precisely all ion-ion pair correlation functions at high concentrations. From these data, we extract the renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.

  6. Study on method to simulate light propagation on tissue with characteristics of radial-beam LED based on Monte-Carlo method.

    Science.gov (United States)

    Song, Sangha; Elgezua, Inko; Kobayashi, Yo; Fujie, Masakatsu G

    2013-01-01

    In biomedical, Monte-carlo simulation is commonly used for simulation of light diffusion in tissue. But, most of previous studies did not consider a radial beam LED as light source. Therefore, we considered characteristics of a radial beam LED and applied them on MC simulation as light source. In this paper, we consider 3 characteristics of radial beam LED. The first is an initial launch area of photons. The second is an incident angle of a photon at an initial photon launching area. The third is the refraction effect according to contact area between LED and a turbid medium. For the verification of the MC simulation, we compared simulation and experimental results. The average of the correlation coefficient between simulation and experimental results is 0.9954. Through this study, we show an effective method to simulate light diffusion on tissue with characteristics for radial beam LED based on MC simulation.

  7. Simulation of the Interaction of X-rays with a Gas in an Ionization Chamber by the Monte Carlo Method

    International Nuclear Information System (INIS)

    Grau Carles, A.; Garcia Gomez-Tejedor, G.

    2001-01-01

    The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs

  8. A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations

    International Nuclear Information System (INIS)

    Turner, Adam C.; Zhang Di; Kim, Hyun J.; DeMarco, John J.; Cagnon, Chris H.; Angel, Erin; Cody, Dianna D.; Stevens, Donna M.; Primak, Andrew N.; McCollough, Cynthia H.; McNitt-Gray, Michael F.

    2009-01-01

    The purpose of this study was to present a method for generating x-ray source models for performing Monte Carlo (MC) radiation dosimetry simulations of multidetector row CT (MDCT) scanners. These so-called ''equivalent'' source models consist of an energy spectrum and filtration description that are generated based wholly on the measured values and can be used in place of proprietary manufacturer's data for scanner-specific MDCT MC simulations. Required measurements include the half value layers (HVL 1 and HVL 2 ) and the bowtie profile (exposure values across the fan beam) for the MDCT scanner of interest. Using these measured values, a method was described (a) to numerically construct a spectrum with the calculated HVLs approximately equal to those measured (equivalent spectrum) and then (b) to determine a filtration scheme (equivalent filter) that attenuates the equivalent spectrum in a similar fashion as the actual filtration attenuates the actual x-ray beam, as measured by the bowtie profile measurements. Using this method, two types of equivalent source models were generated: One using a spectrum based on both HVL 1 and HVL 2 measurements and its corresponding filtration scheme and the second consisting of a spectrum based only on the measured HVL 1 and its corresponding filtration scheme. Finally, a third type of source model was built based on the spectrum and filtration data provided by the scanner's manufacturer. MC simulations using each of these three source model types were evaluated by comparing the accuracy of multiple CT dose index (CTDI) simulations to measured CTDI values for 64-slice scanners from the four major MDCT manufacturers. Comprehensive evaluations were carried out for each scanner using each kVp and bowtie filter combination available. CTDI experiments were performed for both head (16 cm in diameter) and body (32 cm in diameter) CTDI phantoms using both central and peripheral measurement positions. Both equivalent source model types

  9. A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations

    Science.gov (United States)

    Turner, Adam C.; Zhang, Di; Kim, Hyun J.; DeMarco, John J.; Cagnon, Chris H.; Angel, Erin; Cody, Dianna D.; Stevens, Donna M.; Primak, Andrew N.; McCollough, Cynthia H.; McNitt-Gray, Michael F.

    2009-01-01

    The purpose of this study was to present a method for generating x-ray source models for performing Monte Carlo (MC) radiation dosimetry simulations of multidetector row CT (MDCT) scanners. These so-called “equivalent” source models consist of an energy spectrum and filtration description that are generated based wholly on the measured values and can be used in place of proprietary manufacturer’s data for scanner-specific MDCT MC simulations. Required measurements include the half value layers (HVL1 and HVL2) and the bowtie profile (exposure values across the fan beam) for the MDCT scanner of interest. Using these measured values, a method was described (a) to numerically construct a spectrum with the calculated HVLs approximately equal to those measured (equivalent spectrum) and then (b) to determine a filtration scheme (equivalent filter) that attenuates the equivalent spectrum in a similar fashion as the actual filtration attenuates the actual x-ray beam, as measured by the bowtie profile measurements. Using this method, two types of equivalent source models were generated: One using a spectrum based on both HVL1 and HVL2 measurements and its corresponding filtration scheme and the second consisting of a spectrum based only on the measured HVL1 and its corresponding filtration scheme. Finally, a third type of source model was built based on the spectrum and filtration data provided by the scanner’s manufacturer. MC simulations using each of these three source model types were evaluated by comparing the accuracy of multiple CT dose index (CTDI) simulations to measured CTDI values for 64-slice scanners from the four major MDCT manufacturers. Comprehensive evaluations were carried out for each scanner using each kVp and bowtie filter combination available. CTDI experiments were performed for both head (16 cm in diameter) and body (32 cm in diameter) CTDI phantoms using both central and peripheral measurement positions. Both equivalent source model types

  10. A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations.

    Science.gov (United States)

    Turner, Adam C; Zhang, Di; Kim, Hyun J; DeMarco, John J; Cagnon, Chris H; Angel, Erin; Cody, Dianna D; Stevens, Donna M; Primak, Andrew N; McCollough, Cynthia H; McNitt-Gray, Michael F

    2009-06-01

    The purpose of this study was to present a method for generating x-ray source models for performing Monte Carlo (MC) radiation dosimetry simulations of multidetector row CT (MDCT) scanners. These so-called "equivalent" source models consist of an energy spectrum and filtration description that are generated based wholly on the measured values and can be used in place of proprietary manufacturer's data for scanner-specific MDCT MC simulations. Required measurements include the half value layers (HVL1 and HVL2) and the bowtie profile (exposure values across the fan beam) for the MDCT scanner of interest. Using these measured values, a method was described (a) to numerically construct a spectrum with the calculated HVLs approximately equal to those measured (equivalent spectrum) and then (b) to determine a filtration scheme (equivalent filter) that attenuates the equivalent spectrum in a similar fashion as the actual filtration attenuates the actual x-ray beam, as measured by the bowtie profile measurements. Using this method, two types of equivalent source models were generated: One using a spectrum based on both HVL1 and HVL2 measurements and its corresponding filtration scheme and the second consisting of a spectrum based only on the measured HVL1 and its corresponding filtration scheme. Finally, a third type of source model was built based on the spectrum and filtration data provided by the scanner's manufacturer. MC simulations using each of these three source model types were evaluated by comparing the accuracy of multiple CT dose index (CTDI) simulations to measured CTDI values for 64-slice scanners from the four major MDCT manufacturers. Comprehensive evaluations were carried out for each scanner using each kVp and bowtie filter combination available. CTDI experiments were performed for both head (16 cm in diameter) and body (32 cm in diameter) CTDI phantoms using both central and peripheral measurement positions. Both equivalent source model types result in

  11. Monte Carlo simulation methods in moment-based scale-bridging algorithms for thermal radiative-transfer problems

    International Nuclear Information System (INIS)

    Densmore, J.D.; Park, H.; Wollaber, A.B.; Rauenzahn, R.M.; Knoll, D.A.

    2015-01-01

    We present a moment-based acceleration algorithm applied to Monte Carlo simulation of thermal radiative-transfer problems. Our acceleration algorithm employs a continuum system of moments to accelerate convergence of stiff absorption–emission physics. The combination of energy-conserving tallies and the use of an asymptotic approximation in optically thick regions remedy the difficulties of local energy conservation and mitigation of statistical noise in such regions. We demonstrate the efficiency and accuracy of the developed method. We also compare directly to the standard linearization-based method of Fleck and Cummings [1]. A factor of 40 reduction in total computational time is achieved with the new algorithm for an equivalent (or more accurate) solution as compared with the Fleck–Cummings algorithm

  12. Computer Simulation of the E.C.C.S. Buckling Curve using a Monte-Carlo Method

    NARCIS (Netherlands)

    Strating, J.; Vos, H.

    1973-01-01

    The application of a Monte-Carlo simulation procedure to obtain the distribution function of the maximum load of a hinged column with imperfections is discussed. Buckling tests carried out by the E.C.C.S. on IPE 160 sections have been simulated. Information concerning the column variables is

  13. 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.)

  14. Turbulent flow and temperature noise simulation by a multiparticle Monte Carlo method

    International Nuclear Information System (INIS)

    Hughes, G.; Overton, R.S.

    1980-10-01

    A statistical method of simulating real-time temperature fluctuations in liquid sodium pipe flow, for potential application to the estimation of temperature signals generated by subassembly blockages in LMFBRs is described. The method is based on the empirical characterisation of the flow by turbulence intensity and macroscale, radial velocity correlations and spectral form. These are used to produce realisations of the correlated motion of successive batches of representative 'marker particles' released at discrete time intervals into the flow. Temperature noise is generated by the radial mixing of the particles as they move downstream from an assumed mean temperature profile, where they acquire defined temperatures. By employing multi-particle batches, it is possible to perform radial heat transfer calculations, resulting in axial dissipation of the temperature noise levels. A simulated temperature-time signal is built up by recording the temperature at a given point in the flow as each batch of particles reaches the radial measurement plane. This is an advantage over conventional techniques which can usually only predict time-averaged parameters. (U.K.)

  15. 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.)

  16. A proposal on alternative sampling-based modeling method of spherical particles in stochastic media for Monte Carlo simulation

    Directory of Open Access Journals (Sweden)

    Song Hyun Kim

    2015-08-01

    Full Text Available Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

  17. Thermodynamics and simulation of hard-sphere fluid and solid: Kinetic Monte Carlo method versus standard Metropolis scheme.

    Science.gov (United States)

    Ustinov, E A

    2017-01-21

    The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.

  18. 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

  19. A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

    Science.gov (United States)

    Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

    2017-10-01

    Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.

  20. AN APPLICATION OF VALUE AT RISK BY MONTE CARLO SIMULATION METHOD IN PORTFOLIOS OF ISE30 INDEX AND GOVERNMENT SECURITIES

    Directory of Open Access Journals (Sweden)

    OKTAY TAŞ

    2013-06-01

    Full Text Available As a result of the rapid development of information technologies and globalization, growing trading volumes and variety of securities have increased the exposure of economic units on risk. Therefore, the topics with respect to risk management have drawn substantial attention from both in academic and practitioners. In recent years , Value at Risk “VaR” approach, one of the methods used for evaluating risk , has gained widespread acceptance. In the first part of this study , the types of risk , the definition and historical development of the Value at Risk Approach , its methods and differences among these methods are explained. At the next section , VaR’s of the portfolios of ISE 30 index and goverment securities are estimated at the %99 and %95 confidence level and for 1 day and 10-day periods by the Monte Carlo simulation method which is one of the nonparametric estimation approaches of VaR. For each portfolio, simulations are performed based on the normal and Student–t distributions and results are compared. In the last section, the study is evaluated as a whole and emprical results are commented.

  1. 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.

  2. Antitwilight II: Monte Carlo simulations.

    Science.gov (United States)

    Richtsmeier, Steven C; Lynch, David K; Dearborn, David S P

    2017-07-01

    For this paper, we employ the Monte Carlo scene (MCScene) radiative transfer code to elucidate the underlying physics giving rise to the structure and colors of the antitwilight, i.e., twilight opposite the Sun. MCScene calculations successfully reproduce colors and spatial features observed in videos and still photos of the antitwilight taken under clear, aerosol-free sky conditions. Through simulations, we examine the effects of solar elevation angle, Rayleigh scattering, molecular absorption, aerosol scattering, multiple scattering, and surface reflectance on the appearance of the antitwilight. We also compare MCScene calculations with predictions made by the MODTRAN radiative transfer code for a solar elevation angle of +1°.

  3. 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).

  4. Monte Carlo Simulation of Alloy Design Techniques: Fracture and Welding Studied Using the BFS Method for Alloys

    Science.gov (United States)

    Bozzolo, Guillermo H.; Good, Brian; Noebe, Ronald D.; Honecy, Frank; Abel, Phillip

    1999-01-01

    Large-scale simulations of dynamic processes at the atomic level have developed into one of the main areas of work in computational materials science. Until recently, severe computational restrictions, as well as the lack of accurate methods for calculating the energetics, resulted in slower growth in the area than that required by current alloy design programs. The Computational Materials Group at the NASA Lewis Research Center is devoted to the development of powerful, accurate, economical tools to aid in alloy design. These include the BFS (Bozzolo, Ferrante, and Smith) method for alloys (ref. 1) and the development of dedicated software for large-scale simulations based on Monte Carlo- Metropolis numerical techniques, as well as state-of-the-art visualization methods. Our previous effort linking theoretical and computational modeling resulted in the successful prediction of the microstructure of a five-element intermetallic alloy, in excellent agreement with experimental results (refs. 2 and 3). This effort also produced a complete description of the role of alloying additions in intermetallic binary, ternary, and higher order alloys (ref. 4).

  5. A Kinetic Monte Carlo method for the simulation of heteroepitaxial growth

    NARCIS (Netherlands)

    Much, F.; Ahr, M.; Biehl, M.; Kinzel, W.

    2002-01-01

    We introduce a simulation algorithm which allows the off-lattice simulation of various phenomena observed in heteroepitaxial growth like a critical layer thickness for the appearance of misfit dislocations, or self-assembled island formation in 1 + 1 dimensions. The only parameters of the model are

  6. Application of the extended boundary condition method to Monte Carlo simulations of scattering of waves by two-dimensional random rough surfaces

    Science.gov (United States)

    Tsang, L.; Lou, S. H.; Chan, C. H.

    1991-01-01

    The extended boundary condition method is applied to Monte Carlo simulations of two-dimensional random rough surface scattering. The numerical results are compared with one-dimensional random rough surfaces obtained from the finite-element method. It is found that the mean scattered intensity from two-dimensional rough surfaces differs from that of one dimension for rough surfaces with large slopes.

  7. Digitized Onondaga Lake Dissolved Oxygen Concentrations and Model Simulated Values using Bayesian Monte Carlo Methods

    Data.gov (United States)

    U.S. Environmental Protection Agency — The dataset is lake dissolved oxygen concentrations obtained form plots published by Gelda et al. (1996) and lake reaeration model simulated values using Bayesian...

  8. Simulation of neutron transport process, photons and charged particles within the Monte Carlo method

    International Nuclear Information System (INIS)

    Androsenko, A.A.; Androsenko, P.A.; Artamonov, S.N.; Bolonkina, G.V.; Lomtev, V.L.; Pupko, S.V.

    1991-01-01

    Description is given to the program system BRAND designed for the accurate solution of non-stationary transport equation of neutrons, photons and charged particles in the conditions of real three-dimensional geometry. An extensive set of local and non-local estimates provides an opportunity of calculating a great set of linear functionals normally being of interest in the calculation of reactors, radiation protection and experiment simulation. The process of particle interaction with substance is simulated on the basis of individual non-group data on each isotope of the composition. 24 refs

  9. 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.

  10. Simulation of x-rays in refractive structure by the Monte Carlo method using the supercomputer SKIF

    International Nuclear Information System (INIS)

    Yaskevich, Yu.R.; Kravchenko, O.I.; Soroka, I.I.; Chembrovskij, A.G.; Kolesnik, A.S.; Serikova, N.V.; Petrov, P.V.; Kol'chevskij, N.N.

    2013-01-01

    Software 'Xray-SKIF' for the simulation of the X-rays in refractive structures by the Monte-Carlo method using the supercomputer SKIF BSU are developed. The program generates a large number of rays propagated from a source to the refractive structure. The ray trajectory under assumption of geometrical optics is calculated. Absorption is calculated for each ray inside of refractive structure. Dynamic arrays are used for results of calculation rays parameters, its restore the X-ray field distributions very fast at different position of detector. It was found that increasing the number of processors leads to proportional decreasing of calculation time: simulation of 10 8 X-rays using supercomputer with the number of processors from 1 to 30 run-times equal 3 hours and 6 minutes, respectively. 10 9 X-rays are calculated by software 'Xray-SKIF' which allows to reconstruct the X-ray field after refractive structure with a special resolution of 1 micron. (authors)

  11. Assessment of the effectiveness of attenuation of leaded aprons through TLD dosimetry and Monte Carlo simulation method

    Energy Technology Data Exchange (ETDEWEB)

    Olaya D, H.; Diaz M, J. A.; Martinez O, S. A. [Universidad Pedagogica y Tecnologica de Colombia, Grupo de Fisica Nuclear Aplicada y Simulacion, 150003 Tunja, Boyaca (Colombia); Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas, Zac. (Mexico)

    2016-10-15

    Were performed experimental setups using an X-ray equipment continuous emission Pantak DXT-3000 and three types of leaded aprons with thickness of 0.25, 0.5 and 0.75 mm coated with Mylar Fiber coated Mylar on its surface. Apron was located at a distance of 2.5 m with respect focus in order to cover a radiation field size of a meter in diameter. At the beam output were added aluminum filtration in order to reproduce qualities of narrow beams N-40 (E{sub efective} = 33 keV), N-80 (E{sub efective} = 65 keV) and N-100 (E{sub efective} = 83 keV) according to the ISO standard 4037 (1-3). Each lead apron were fixed 10 TLD dosimeters over its surface, 5 dosimeters before and 5 dosimeters after with respect to X-ray beam and were calibrated for Harshaw 4500 thermoluminescent reader system order to assess the attenuation of each apron. Were performed dosimeters readings and were calculated the attenuation coefficients for each effective energy of X-ray quality. In order to confirm the method of effective energy of ISO-4037 and evaluate effectiveness of lead aprons based on energy range for each medical practice was made a Monte Carlo simulation using code GEANT-4, calculating the fluence and absorbed dose in each one of the dosimeters Monte Carlo, then coefficients of linear attenuation were calculated and compared with the experimental data and reported by the National Institute of Standards and Technology (Nist). Finally, results are consistent between theoretical calculation and experimental measures. This work will serve to make assessments for other personalized leaded protections. (Author)

  12. 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.

  13. Adiabatic optimization versus diffusion Monte Carlo methods

    Science.gov (United States)

    Jarret, Michael; Jordan, Stephen P.; Lackey, Brad

    2016-10-01

    Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .

  14. Simulation of Chemical Reaction Equilibria by the Reaction Ensemble Monte Carlo Method:

    Czech Academy of Sciences Publication Activity Database

    Turner, C.H.; Brennan, J.K.; Lísal, Martin; Smith, W.R.; Johnson, J. K.; Gubbins, K.E.

    2008-01-01

    Roč. 34, č. 2 (2008), s. 119-146 ISSN 0892-7022 R&D Projects: GA AV ČR KAN400720701; GA ČR GA203/05/0725; GA AV ČR IAA400720710; GA AV ČR 1ET400720507 Grant - others:NRCC(CA) OGP1041 Institutional research plan: CEZ:AV0Z40720504 Keywords : simulation * review * reaction equilibria Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.325, year: 2008

  15. 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.

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

    Science.gov (United States)

    Kotalczyk, G.; Kruis, F. E.

    2017-07-01

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

  17. Can You Repeat That Please?: Using Monte Carlo Simulation in Graduate Quantitative Research Methods Classes

    Science.gov (United States)

    Carsey, Thomas M.; Harden, Jeffrey J.

    2015-01-01

    Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…

  18. Development of modern approach to absorbed dose assessment in radionuclide therapy, based on Monte Carlo method simulation of patient scintigraphy

    Science.gov (United States)

    Lysak, Y. V.; Klimanov, V. A.; Narkevich, B. Ya

    2017-01-01

    One of the most difficult problems of modern radionuclide therapy (RNT) is control of the absorbed dose in pathological volume. This research presents new approach based on estimation of radiopharmaceutical (RP) accumulated activity value in tumor volume, based on planar scintigraphic images of the patient and calculated radiation transport using Monte Carlo method, including absorption and scattering in biological tissues of the patient, and elements of gamma camera itself. In our research, to obtain the data, we performed modeling scintigraphy of the vial with administered to the patient activity of RP in gamma camera, the vial was placed at the certain distance from the collimator, and the similar study was performed in identical geometry, with the same values of activity of radiopharmaceuticals in the pathological target in the body of the patient. For correct calculation results, adapted Fisher-Snyder human phantom was simulated in MCNP program. In the context of our technique, calculations were performed for different sizes of pathological targets and various tumors deeps inside patient’s body, using radiopharmaceuticals based on a mixed β-γ-radiating (131I, 177Lu), and clear β- emitting (89Sr, 90Y) therapeutic radionuclides. Presented method can be used for adequate implementing in clinical practice estimation of absorbed doses in the regions of interest on the basis of planar scintigraphy of the patient with sufficient accuracy.

  19. 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.)

  20. Estimating the impact of various pathway parameters on tenderness, flavour and juiciness of pork using Monte Carlo simulation methods.

    Science.gov (United States)

    Channon, H A; Hamilton, A J; D'Souza, D N; Dunshea, F R

    2016-06-01

    Monte Carlo simulation was investigated as a potential methodology to estimate sensory tenderness, flavour and juiciness scores of pork following the implementation of key pathway interventions known to influence eating quality. Correction factors were established using mean data from published studies investigating key production, processing and cooking parameters. Probability distributions of correction factors were developed for single pathway parameters only, due to lack of interaction data. Except for moisture infusion, ageing period, aitchbone hanging and cooking pork to an internal temperature of >74°C, only small shifts in the mean of the probability distributions of correction factors were observed for the majority of pathway parameters investigated in this study. Output distributions of sensory scores, generated from Monte Carlo simulations of input distributions of correction factors and for individual pigs, indicated that this methodology may be useful in estimating both the shift and variability in pork eating traits when different pathway interventions are applied. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. 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...

  2. Simulation of the build-up phase of a high voltage low pressure gas discharge using Monte-Carlo-methods

    International Nuclear Information System (INIS)

    Niessen, W.

    1990-02-01

    In this report the simulation of a Pseudospark predischarge between anode and cathode using Monte-Carlo-Methods is described. In the early phase of the discharge electric and magnetic self-fields can be neglected. The model is based on a discharge between two infinitely extended capacitor plates. Eleven different collision reactions and two electrode surface effects are taken into account. A Fortran program was developed that computes the built-up of the discharge in time and space. A specially of the code is, that not only electrons and ions are taken into account, but also fast neutral atoms and molecules. Three pairs of diode-length and voltage were investigated at different pressures: 350 kV/5.0 cm, 30 kV/10.0 cm and 6.9 kV/0.7 cm. The working gas was hydrogen. The computations included: The Paschen-curve, the time evolution of the current densities of the electrons at the anode and the ions at the cathode, the space- and time-dependent particle densities, the time-dependent energy distributions of the different particle species, the relative number of the different collision reactions. (orig./HSI) [de

  3. 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)

  4. Integrated Building Energy Design of a Danish Office Building Based on Monte Carlo Simulation Method

    DEFF Research Database (Denmark)

    Sørensen, Mathias Juul; Myhre, Sindre Hammer; Hansen, Kasper Kingo

    2017-01-01

    The focus on reducing buildings energy consumption is gradually increasing, and the optimization of a building’s performance and maximizing its potential leads to great challenges between architects and engineers. In this study, we collaborate with a group of architects on a design project of a new...... office building located in Aarhus, Denmark. Building geometry, floor plans and employee schedules were obtained from the architects which is the basis for this study. This study aims to simplify the iterative design process that is based on the traditional trial and error method in the late design phases...

  5. Monte carlo methods and models in finance and insurance

    CERN Document Server

    Korn, Ralf; Kroisandt, Gerald

    2010-01-01

    Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...

  6. Monte Carlo methods and models in finance and insurance

    CERN Document Server

    Korn, Ralf; Kroisandt, Gerald

    2010-01-01

    Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...

  7. Improving the Ar I and II branching ratio calibration method: Monte Carlo simulations of effects from photon scattering/reflecting in hollow cathodes

    Science.gov (United States)

    Lawler, J. E.; Den Hartog, E. A.

    2018-03-01

    The Ar I and II branching ratio calibration method is discussed with the goal of improving the technique. This method of establishing a relative radiometric calibration is important in ongoing research to improve atomic transition probabilities for quantitative spectroscopy in astrophysics and other fields. Specific suggestions are presented along with Monte Carlo simulations of wavelength dependent effects from scattering/reflecting of photons in a hollow cathode.

  8. Multilevel Monte Carlo simulation of Coulomb collisions

    Energy Technology Data Exchange (ETDEWEB)

    Rosin, M.S., E-mail: msr35@math.ucla.edu [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Department of Mathematics and Science, Pratt Institute, Brooklyn, NY 11205 (United States); Ricketson, L.F. [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Dimits, A.M. [Lawrence Livermore National Laboratory, L-637, P.O. Box 808, Livermore, CA 94511-0808 (United States); Caflisch, R.E. [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Institute for Pure and Applied Mathematics, University of California at Los Angeles, Los Angeles, CA 90095 (United States); Cohen, B.I. [Lawrence Livermore National Laboratory, L-637, P.O. Box 808, Livermore, CA 94511-0808 (United States)

    2014-10-01

    We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε, the computational cost of the method is O(ε{sup −2}) or O(ε{sup −2}(lnε){sup 2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε{sup −3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10{sup −5}. We discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.

  9. 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

  10. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    Markov Chain Monte Carlo Methods. 2. The Markov Chain Case. K B Athreya, Mohan Delampady and T Krishnan. K B Athreya is a Professor at. Cornell University. His research interests include mathematical analysis, probability theory and its application and statistics. He enjoys writing for Resonance. His spare time is ...

  11. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    GENERAL ! ARTICLE. Markov Chain Monte Carlo Methods. 3. Statistical Concepts. K B Athreya, Mohan Delampady and T Krishnan. K B Athreya is a Professor at. Cornell University. His research interests include mathematical analysis, probability theory and its application and statistics. He enjoys writing for Resonance.

  12. Phase-coexistence simulations of fluid mixtures by the Markov Chain Monte Carlo method using single-particle models

    KAUST Repository

    Li, Jun

    2013-09-01

    We present a single-particle Lennard-Jones (L-J) model for CO2 and N2. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO2 and N2 agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH4, CO2 and N2 are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. Since the single-particle model reduces the particle number and avoids the time-consuming Ewald summation used to evaluate Coulomb interactions, the proposed model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available. © 2013 Elsevier Inc.

  13. An Evaluation of the Plant Density Estimator the Point-Centred Quarter Method (PCQM) Using Monte Carlo Simulation.

    Science.gov (United States)

    Khan, Md Nabiul Islam; Hijbeek, Renske; Berger, Uta; Koedam, Nico; Grueters, Uwe; Islam, S M Zahirul; Hasan, Md Asadul; Dahdouh-Guebas, Farid

    2016-01-01

    In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns) plant populations and empirical ones. PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N - 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N - 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published. If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process

  14. An Evaluation of the Plant Density Estimator the Point-Centred Quarter Method (PCQM Using Monte Carlo Simulation.

    Directory of Open Access Journals (Sweden)

    Md Nabiul Islam Khan

    Full Text Available In the Point-Centred Quarter Method (PCQM, the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1 and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns plant populations and empirical ones.PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3 show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition. If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1/(π ∑ R2 but not 12N/(π ∑ R2, of PCQM2 is 4(8N - 1/(π ∑ R2 but not 28N/(π ∑ R2 and of PCQM3 is 4(12N - 1/(π ∑ R2 but not 44N/(π ∑ R2 as published.If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process

  15. External individual monitoring: experiments and simulations using Monte Carlo Method; Monitoracao individual externa: experimentos e simulacoes com o metodo de Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Guimaraes, Carla da Costa

    2005-07-01

    In this work, we have evaluated the possibility of applying the Monte Carlo simulation technique in photon dosimetry of external individual monitoring. The GEANT4 toolkit was employed to simulate experiments with radiation monitors containing TLD-100 and CaF{sub 2}:NaCl thermoluminescent detectors. As a first step, X ray spectra were generated impinging electrons on a tungsten target. Then, the produced photon beam was filtered in a beryllium window and additional filters to obtain the radiation with desired qualities. This procedure, used to simulate radiation fields produced by a X ray tube, was validated by comparing characteristics such as half value layer, which was also experimentally measured, mean photon energy and the spectral resolution of simulated spectra with that of reference spectra established by international standards. In the construction of thermoluminescent dosimeter, two approaches for improvements have. been introduced. The first one was the inclusion of 6% of air in the composition of the CaF{sub 2}:NaCl detector due to the difference between measured and calculated values of its density. Also, comparison between simulated and experimental results showed that the self-attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account. Then, in the second approach, the light attenuation coefficient of CaF{sub 2}:NaCl compound estimated by simulation to be 2,20(25) mm{sup -1} was introduced. Conversion coefficients C{sub p} from air kerma to personal dose equivalent were calculated using a slab water phantom with polymethyl-metacrilate (PMMA) walls, for reference narrow and wide X ray spectrum series [ISO 4037-1], and also for the wide spectra implanted and used in routine at Laboratorio de Dosimetria. Simulations of backscattered radiations by PMMA slab water phantom and slab phantom of ICRU tissue-equivalent material produced very similar results. Therefore, the PMMA slab water phantom that can be easily

  16. Monte Carlo simulations of medical imaging modalities

    Energy Technology Data Exchange (ETDEWEB)

    Estes, G.P. [Los Alamos National Lab., NM (United States)

    1998-09-01

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

  17. 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.)

  18. [Simulation of dose distribution in bone medium of125I photon emitting source with Monte Carlo method].

    Science.gov (United States)

    Ye, K Q; Huang, M W; Li, J L; Tang, J T; Zhang, J G

    2018-02-18

    To present a theoretical analysis of how the presence of bone in interstitial brachytherapy affects dose rate distributions with MCNP4C Monte Carlo code and to prepare for the next clinical study on the dose distribution of interstitial brachytherapy in head and neck neoplasm. Type 6711, 125 I brachytherapy source was simulated with MCNP4C Monte Carlo code whose cross section library was DLC-200. The dose distribution along the transverse axis in water and dose constant were compared with the American Association of Physicists in Medicine (AAPM) TG43UI update dosimetry formalism and current literature. The validated computer code was then applied to simple homogeneous bone tissue model to determine the affected different bone tissue had on dose distribution from 125 I interstitial implant. 125 I brachytherapy source simulated with MCNP4C Monte Carlo code met the requirements of TG43UI report. Dose rate constant, 0.977 78 cGy/(h×U), was in agreement within 1.32% compared with the recommended value of TG43UI. There was a good agreement between TG43UI about the dosimetric parameters at distances of 1 to 10 cm along the transverse axis of the 125 I source established by MCNP4C and current published data. And the dose distribution of 125 I photon emitting source in different bone tissue was calculated. Dose-deposition capacity of photons was in decreasing order: cortical bone, spongy bone, cartilage, yellow bone marrow, red bone marrow in the same medium depth. Photons deposited significantly in traversal axis among the phantom material of cortical bone and sponge bone relevant to the dose to water. In the medium depth of 0.01 cm, 0.1 cm, and 1 cm, the dose in the cortical bone was 12.90 times, 9.72 times, and 0.30 times of water respectively. This study build a 125 I source model with MCNP4C Monte Carlo code, which is validated, and could be used in subsequent study. Dose distribution of photons in different bone medium is not the same as water, and its main energy

  19. 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

  20. 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

  1. Extending canonical Monte Carlo methods

    International Nuclear Information System (INIS)

    Velazquez, L; Curilef, S

    2010-01-01

    In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model

  2. (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.

  3. Monte Carlo and detector simulation in OOP

    International Nuclear Information System (INIS)

    Atwood, W.B.; Blankenbecler, R.; Kunz, P.; Burnett, T.; Storr, K.M.

    1990-01-01

    Object-Oriented Programming techniques are explored with an eye towards applications in High Energy Physics codes. Two prototype examples are given: MCOOP (a particle Monte Carlo generator) and GISMO (a detector simulation/analysis package). The OOP programmer does no explicit or detailed memory management nor other bookkeeping chores; hence, the writing, modification, and extension of the code is considerably simplified. Inheritance can be used to simplify the class definitions as well as the instance variables and action methods of each class; thus the work required to add new classes, parameters, or new methods is minimal. The software industry is moving rapidly to OOP since it has been proven to improve programmer productivity, and promises even more for the future by providing truly reusable software. The High Energy Physics community clearly needs to follow this trend

  4. 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.

  5. Atomistic Monte Carlo Simulation of Lipid Membranes

    Directory of Open Access Journals (Sweden)

    Daniel Wüstner

    2014-01-01

    Full Text Available Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA for the phospholipid dipalmitoylphosphatidylcholine (DPPC. We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.

  6. Numerical simulations of a coupled radiative?conductive heat transfer model using a modified Monte Carlo method

    KAUST Repository

    Kovtanyuk, Andrey E.

    2012-01-01

    Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.

  7. [Reference value for micronucleus frequency of peripheral blood lymphocytes in general Chinese population: a method of Monte Carlo simulation].

    Science.gov (United States)

    Teng, Jingjing; Duan, Huawei; Zheng, Yuxin

    2015-12-01

    To estimate the reference value for micronucleus frequency of peripheral blood lymphocytes in general Chinese population, and to guide the genotoxicity evaluation and risk analysis for populations exposed to environmental or occupational chemicals. A fulltext search was performed in CNKI with the key words of "micronucleus" and "human", and PubMed was searched with "cytokinesis-block micronucleus","CBMN","humans", and "adults", to obtain the articles published at home and abroad from 2001 to 2014 in which cytokinesis-block micronucleus (CBMN)assay was applied for micronucleus detection and populations not exposed to genotoxins were established as a control. Monte Carlo simulation was performed based on the micronucleus frequency, standard deviation, and sample size provided in these articles to calculate the micronucleus frequency for general population and to analyze the influence of sex, smoking, and drinking on micronucleus frequency. A total of 23 articles were included in the final analysis. The minimum mean micronucleus frequency was 0.39‰, and the maximum mean micronucleus frequency was 25.3‰. There were 1623 subjects in the control group in total (range 22~178, mean 70.6). Monte Carlo simulation was performed 100 times, and the mode of micronucleus frequency was 0 or 1‰; the values of P0, P25, P50 , P75, and P95 were 0‰, 1‰, 2‰~3‰, 5‰~6‰, and 14‰~19‰, respectively; the mean value was 4.36‰(range 4.22‰~4.57‰). With the application of one-sided 95% range(x±1.64 s), the upper limit of the range of reference value was calculated to be 13.46‰~14.75‰. The micronucleus frequency of peripheral blood lymphocytes in general Chinese population is 4.36‰, the interquartile range is 1‰~5‰ or 1‰~6‰, and the upper limit of reference value is 14.17‰. The factors of living area, sex, smoking, and drinking may influence micronucleus frequency.

  8. Parallel Monte Carlo Simulation of Aerosol Dynamics

    Directory of Open Access Journals (Sweden)

    Kun Zhou

    2014-02-01

    Full Text Available A highly efficient Monte Carlo (MC algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process. Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI. The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles.

  9. Parallel Monte Carlo simulation of aerosol dynamics

    KAUST Repository

    Zhou, K.

    2014-01-01

    A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.

  10. 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

  11. Numerical integration of detector response functions via Monte Carlo simulations

    Science.gov (United States)

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

    2017-09-01

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

  12. Direct determination of liquid phase coexistence by Monte Carlo simulations

    NARCIS (Netherlands)

    Zweistra, H.J.A.; Besseling, N.A.M.

    2006-01-01

    A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase.

  13. K-Antithetic Variates in Monte Carlo Simulation | Nasroallah | Afrika ...

    African Journals Online (AJOL)

    Abstract. Standard Monte Carlo simulation needs prohibitive time to achieve reasonable estimations. for untractable integrals (i.e. multidimensional integrals and/or intergals with complex integrand forms). Several statistical technique, called variance reduction methods, are used to reduce the simulation time. In this note ...

  14. 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.

  15. A high-quality multilayer structure characterization method based on X-ray fluorescence and Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Brunetti, Antonio; Golosio, Bruno [Universita degli Studi di Sassari, Dipartimento di Scienze Politiche, Scienze della Comunicazione e Ingegneria dell' Informazione, Sassari (Italy); Melis, Maria Grazia [Universita degli Studi di Sassari, Dipartimento di Storia, Scienze dell' Uomo e della Formazione, Sassari (Italy); Mura, Stefania [Universita degli Studi di Sassari, Dipartimento di Agraria e Nucleo di Ricerca sulla Desertificazione, Sassari (Italy)

    2014-11-08

    X-ray fluorescence (XRF) is a well known nondestructive technique. It is also applied to multilayer characterization, due to its possibility of estimating both composition and thickness of the layers. Several kinds of cultural heritage samples can be considered as a complex multilayer, such as paintings or decorated objects or some types of metallic samples. Furthermore, they often have rough surfaces and this makes a precise determination of the structure and composition harder. The standard quantitative XRF approach does not take into account this aspect. In this paper, we propose a novel approach based on a combined use of X-ray measurements performed with a polychromatic beam and Monte Carlo simulations. All the information contained in an X-ray spectrum is used. This approach allows obtaining a very good estimation of the sample contents both in terms of chemical elements and material thickness, and in this sense, represents an improvement of the possibility of XRF measurements. Some examples will be examined and discussed. (orig.)

  16. Study of Atom Transfer Radical Polymerization of Styrene and Its Gel Effect by Monte Carlo Simulation Method

    Directory of Open Access Journals (Sweden)

    M. Najafi

    2009-12-01

    Full Text Available Atom transfer radical polymerization (ATRP of styrene was carried out at 105°C and a Monte Carlo simulation was employed to model the system. The variations of monomer conversion, the initiator concentration, average molecular weight, and molecular weight distribution were evaluated as the reaction proceeded. According to the results obtained, for similar reaction time, monomer conversion is higher when gel effect is taken into account. Also, the concentration of initiator suddenly drops at the initial stages of polymerization, and finally reaches zero. In addition, in the presence of gel effect, bimolecular termination rate constant decreases during the polymerization. Moreover, number- and weight-average molecular weights linearly rise as the polymerization progresses; this also is a confirmation to the living nature of the polymerization. Finally, the molecular weight distribution of polymers synthesized narrows at high monomer conversion. In effect, polydispersity index decreases from about 2 (at the onset of polymerization to around 1.3 (towards the end of polymerization.

  17. Post-DFT methods for Earth materials: Quantum Monte Carlo simulations of (Mg,Fe)O (Invited)

    Science.gov (United States)

    Driver, K. P.; Militzer, B.; Cohen, R. E.

    2013-12-01

    (Mg,Fe)O is a major mineral phase in Earth's lower mantle that plays a key role in determining the structural and dynamical properties of deep Earth. A pressure-induced spin-pairing transition of Fe has been the subject of numerous theoretical and experimental studies due to the consequential effects on lower mantle physics. The standard density functional theory (DFT) method does not treat strongly correlated electrons properly and results can have dependence on the choice of exchange-correlation functional. DFT+U, offers significant improvement over standard DFT for treating strongly correlated electrons. Indeed, DFT+U calculations and experiments have narrowed the ambient spin-transition between 40-60 GPa in (Mg,Fe)O. However, DFT+U, is not an ideal method due to dependence on Hubbard U parameter among other approximations. In order to further clarify details of the spin transition, it is necessary to use methods that explicitly treat effects of electron exchange and correlation, such as quantum Monte Carlo (QMC). Here, we will discuss methods of going beyond standard DFT and present QMC results on the (Mg,Fe)O elastic properties and spin-transition pressure in order to benchmark DFT+U results.

  18. 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)

  19. Quantum Monte Carlo method for attractive Coulomb potentials

    NARCIS (Netherlands)

    Kole, J.S.; Raedt, H. De

    2001-01-01

    Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quantum Monte Carlo method that can handle singular attractive potentials. We illustrate the basic ideas of this quantum Monte Carlo algorithm by simulating the ground state of hydrogen and helium.

  20. Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method

    CERN Document Server

    Jadach, S.

    2017-01-01

    We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...

  1. 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

  2. A third generation tomography system with fifteen detectors and a gamma-ray source in fan beam geometry simulated by Monte Carlo Method

    International Nuclear Information System (INIS)

    Velo, A.F.; Alvarez, A.G.; Carvalho, D.V.S.; Fernandez, V.; Somessari, S.; Sprenger, F.F.; Hamada, M.M.; Mesquita, C.H.

    2017-01-01

    This paper describes the Monte Carlo simulation, using MCNP4C, of a multichannel third generation tomography system containing a two radioactive sources, 192 Ir (316.5 - 468 KeV) and 137 Cs (662 KeV), and a set of fifteen NaI(Tl) detectors, with dimensions of 1 inch diameter and 2 inches thick, in fan beam geometry, positioned diametrically opposite. Each detector moves 10 steps of 0,24 deg , totalizing 150 virtual detectors per projection, and then the system rotate 2 degrees. The Monte Carlo simulation was performed to evaluate the viability of this configuration. For this, a multiphase phantom containing polymethyl methacrylate (PMMA ((ρ ≅ 1.19 g/cm 3 )), iron (ρ ≅ 7.874 g/cm 3 ), aluminum (ρ ≅ 2.6989 g/cm 3 ) and air (ρ ≅ 1.20479E-03 g/cm 3 ) was simulated. The simulated number of histories was 1.1E+09 per projection and the tally used were the F8, which gives the pulse height of each detector. The data obtained by the simulation was used to reconstruct the simulated phantom using the statistical iterative Maximum Likelihood Estimation Method Technique (ML-EM) algorithm. Each detector provides a gamma spectrum of the sources, and a pulse height analyzer (PHA) of 10% on the 316.5 KeV and 662 KeV photopeaks was performed. This technique provides two reconstructed images of the simulated phantom. The reconstructed images provided high spatial resolution, and it is supposed that the temporal resolution (spending time for one complete revolution) is about 2.5 hours. (author)

  3. A third generation tomography system with fifteen detectors and a gamma-ray source in fan beam geometry simulated by Monte Carlo Method

    Energy Technology Data Exchange (ETDEWEB)

    Velo, A.F.; Alvarez, A.G.; Carvalho, D.V.S.; Fernandez, V.; Somessari, S.; Sprenger, F.F.; Hamada, M.M.; Mesquita, C.H., E-mail: chmesqui@usp.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    This paper describes the Monte Carlo simulation, using MCNP4C, of a multichannel third generation tomography system containing a two radioactive sources, {sup 192}Ir (316.5 - 468 KeV) and {sup 137}Cs (662 KeV), and a set of fifteen NaI(Tl) detectors, with dimensions of 1 inch diameter and 2 inches thick, in fan beam geometry, positioned diametrically opposite. Each detector moves 10 steps of 0,24 deg , totalizing 150 virtual detectors per projection, and then the system rotate 2 degrees. The Monte Carlo simulation was performed to evaluate the viability of this configuration. For this, a multiphase phantom containing polymethyl methacrylate (PMMA ((ρ ≅ 1.19 g/cm{sup 3})), iron (ρ ≅ 7.874 g/cm{sup 3}), aluminum (ρ ≅ 2.6989 g/cm{sup 3}) and air (ρ ≅ 1.20479E-03 g/cm{sup 3}) was simulated. The simulated number of histories was 1.1E+09 per projection and the tally used were the F8, which gives the pulse height of each detector. The data obtained by the simulation was used to reconstruct the simulated phantom using the statistical iterative Maximum Likelihood Estimation Method Technique (ML-EM) algorithm. Each detector provides a gamma spectrum of the sources, and a pulse height analyzer (PHA) of 10% on the 316.5 KeV and 662 KeV photopeaks was performed. This technique provides two reconstructed images of the simulated phantom. The reconstructed images provided high spatial resolution, and it is supposed that the temporal resolution (spending time for one complete revolution) is about 2.5 hours. (author)

  4. Simulation of the Interaction of X-rays with a Gas in an Ionization Chamber by the Monte Carlo Method; Simulacion Monte Carlo de la Interaccion de Rays X con el Gas de una Camara de Ionizacion

    Energy Technology Data Exchange (ETDEWEB)

    Grau Carles, A.; Garcia Gomez-Tejedor, G.

    2001-07-01

    The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs.

  5. A Monte Carlo adapted finite element method for dislocation ...

    Indian Academy of Sciences (India)

    P Zakian

    2017-10-10

    Oct 10, 2017 ... simulations are proposed. Various comparisons are examined to illustrate the capability of both methods for random simulation of faults. Keywords. Monte Carlo simulation; stochastic modeling; split node technique; finite element method; earthquake fault dislocation. 1. Introduction. In material science, a ...

  6. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2007-09-21

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  7. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Vilches, M.; Lallena, A.M.

    2007-01-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool

  8. General purpose code for Monte Carlo simulations

    International Nuclear Information System (INIS)

    Wilcke, W.W.

    1983-01-01

    A general-purpose computer called MONTHY has been written to perform Monte Carlo simulations of physical systems. To achieve a high degree of flexibility the code is organized like a general purpose computer, operating on a vector describing the time dependent state of the system under simulation. The instruction set of the computer is defined by the user and is therefore adaptable to the particular problem studied. The organization of MONTHY allows iterative and conditional execution of operations

  9. 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.)

  10. Monte Carlo simulation code modernization

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    The continual development of sophisticated transport simulation algorithms allows increasingly accurate description of the effect of the passage of particles through matter. This modelling capability finds applications in a large spectrum of fields from medicine to astrophysics, and of course HEP. These new capabilities however come at the cost of a greater computational intensity of the new models, which has the effect of increasing the demands of computing resources. This is particularly true for HEP, where the demand for more simulation are driven by the need of both more accuracy and more precision, i.e. better models and more events. Usually HEP has relied on the "Moore's law" evolution, but since almost ten years the increase in clock speed has withered and computing capacity comes in the form of hardware architectures of many-core or accelerated processors. To harness these opportunities we need to adapt our code to concurrent programming models taking advantages of both SIMD and SIMT architectures. Th...

  11. Fixed forced detection for fast SPECT Monte-Carlo simulation

    Science.gov (United States)

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

    2018-03-01

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

  12. 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 ...

  13. Monte Carlo method in radiation transport problems

    International Nuclear Information System (INIS)

    Dejonghe, G.; Nimal, J.C.; Vergnaud, T.

    1986-11-01

    In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media [fr

  14. An Efficient Method of Reweighting and Reconstructing Monte Carlo Molecular Simulation Data for Extrapolation to Different Temperature and Density Conditions

    KAUST Repository

    Sun, Shuyu

    2013-06-01

    This paper introduces an efficient technique to generate new molecular simulation Markov chains for different temperature and density conditions, which allow for rapid extrapolation of canonical ensemble averages at a range of temperatures and densities different from the original conditions where a single simulation is conducted. Obtained information from the original simulation are reweighted and even reconstructed in order to extrapolate our knowledge to the new conditions. Our technique allows not only the extrapolation to a new temperature or density, but also the double extrapolation to both new temperature and density. The method was implemented for Lennard-Jones fluid with structureless particles in single-gas phase region. Extrapolation behaviors as functions of extrapolation ranges were studied. Limits of extrapolation ranges showed a remarkable capability especially along isochors where only reweighting is required. Various factors that could affect the limits of extrapolation ranges were investigated and compared. In particular, these limits were shown to be sensitive to the number of particles used and starting point where the simulation was originally conducted.

  15. 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.

  16. Prediction of the number of 14 MeV neutron elastically scattered from large sample of aluminium using Monte Carlo simulation method

    International Nuclear Information System (INIS)

    Husin Wagiran; Wan Mohd Nasir Wan Kadir

    1997-01-01

    In neutron scattering processes, the effect of multiple scattering is to cause an effective increase in the measured cross-sections due to increase on the probability of neutron scattering interactions in the sample. Analysis of how the effective cross-section varies with thickness is very complicated due to complicated sample geometries and the variations of scattering cross-section with energy. Monte Carlo method is one of the possible method for treating the multiple scattering processes in the extended sample. In this method a lot of approximations have to be made and the accurate data of microscopic cross-sections are needed at various angles. In the present work, a Monte Carlo simulation programme suitable for a small computer was developed. The programme was capable to predict the number of neutrons scattered from various thickness of aluminium samples at all possible angles between 00 to 36011 with 100 increments. In order to make the the programme not too complicated and capable of being run on microcomputer with reasonable time, the calculations was done in two dimension coordinate system. The number of neutrons predicted from this model show in good agreement with previous experimental results

  17. A kinetic Monte Carlo simulation method of van der Waals epitaxy for atomistic nucleation-growth processes of transition metal dichalcogenides.

    Science.gov (United States)

    Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae

    2017-06-07

    Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

  18. Handbook of Monte Carlo methods

    National Research Council Canada - National Science Library

    Kroese, Dirk P; Taimre, Thomas; Botev, Zdravko I

    2011-01-01

    ... in rapid succession, the staggering number of related techniques, ideas, concepts and algorithms makes it difficult to maintain an overall picture of the Monte Carlo approach. This book attempts to encapsulate the emerging dynamics of this field of study"--

  19. Replica Exchange for Reactive Monte Carlo Simulations

    Czech Academy of Sciences Publication Activity Database

    Turner, C.H.; Brennan, J.K.; Lísal, Martin

    2007-01-01

    Roč. 111, č. 43 (2007), s. 15706-15715 ISSN 1932-7447 R&D Projects: GA ČR GA203/05/0725; GA AV ČR 1ET400720409; GA AV ČR 1ET400720507 Institutional research plan: CEZ:AV0Z40720504 Keywords : monte carlo * simulation * reactive system Subject RIV: CF - Physical ; Theoretical Chemistry

  20. Monte Carlo simulation of quantum statistical lattice models

    NARCIS (Netherlands)

    Raedt, Hans De; Lagendijk, Ad

    1985-01-01

    In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used

  1. 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. ... From our result, though the VQMC method showed much fluctuation, the technique calculated the electric dipole moment of hydrazine molecule as 2.0 D, which is in closer ...

  2. Fatigue damage estimation in non-linear systems using a combination of Monte Carlo simulation and the First Order Reliability Method

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2015-01-01

    For non-linear systems the estimation of fatigue damage under stochastic loadings can be rather time-consuming. Usually Monte Carlo simulation (MCS) is applied, but the coefficient-of-variation (COV) can be large if only a small set of simulations can be done due to otherwise excessive CPU time. ...

  3. 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.

  4. MBR Monte Carlo Simulation in PYTHIA8

    Science.gov (United States)

    Ciesielski, R.

    We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.

  5. 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.

  6. 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.

  7. Simulation Monte Carlo as a method of verification of the characterization of fountains in ophthalmic brachytherapy; Simulacion Monte Carlo como metodo de verificacion de la caracterizacion de fuentes en braquiterapia oftalmica

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz Lora, A.; Miras del Rio, H.; Terron Leon, J. A.

    2013-07-01

    Following the recommendations of the IAEA, and as a further check, they have been Monte Carlo simulation of each one of the plates that are arranged at the Hospital. The objective of the work is the verification of the certificates of calibration and intends to establish criteria of action for its acceptance. (Author)

  8. Monte Carlo methods for the self-avoiding walk

    International Nuclear Information System (INIS)

    Janse van Rensburg, E J

    2009-01-01

    The numerical simulation of self-avoiding walks remains a significant component in the study of random objects in lattices. In this review, I give a comprehensive overview of the current state of Monte Carlo simulations of models of self-avoiding walks. The self-avoiding walk model is revisited, and the motivations for Monte Carlo simulations of this model are discussed. Efficient sampling of self-avoiding walks remains an elusive objective, but significant progress has been made over the last three decades. The model still poses challenging numerical questions however, and I review specific Monte Carlo methods for improved sampling including general Monte Carlo techniques such as Metropolis sampling, umbrella sampling and multiple Markov Chain sampling. In addition, specific static and dynamic algorithms for walks are presented, and I give an overview of recent innovations in this field, including algorithms such as flatPERM, flatGARM and flatGAS. (topical review)

  9. 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.

  10. Hybrid Monte Carlo methods in computational finance

    NARCIS (Netherlands)

    Leitao Rodriguez, A.

    2017-01-01

    Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the

  11. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    time Technical Consultant to. Systat Software Asia-Pacific. (P) Ltd., in Bangalore, where the technical work for the development of the statistical software Systat takes place. His research interests have been in statistical pattern recognition and biostatistics. Keywords. Markov chain, Monte Carlo sampling, Markov chain Monte.

  12. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    ter of the 20th century, due to rapid developments in computing technology ... early part of this development saw a host of Monte ... These iterative. Monte Carlo procedures typically generate a random se- quence with the Markov property such that the Markov chain is ergodic with a limiting distribution coinciding with the ...

  13. Accelerated GPU based SPECT Monte Carlo simulations.

    Science.gov (United States)

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-07

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational

  14. Accelerated GPU based SPECT Monte Carlo simulations

    Science.gov (United States)

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-01

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency

  15. Monte Carlo methods for particle transport

    CERN Document Server

    Haghighat, Alireza

    2015-01-01

    The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...

  16. 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)

  17. Monte Carlo simulation of a CZT detector

    International Nuclear Information System (INIS)

    Chun, Sung Dae; Park, Se Hwan; Ha, Jang Ho; Kim, Han Soo; Cho, Yoon Ho; Kang, Sang Mook; Kim, Yong Kyun; Hong, Duk Geun

    2008-01-01

    CZT detector is one of the most promising radiation detectors for hard X-ray and γ-ray measurement. The energy spectrum of CZT detector has to be simulated to optimize the detector design. A CZT detector was fabricated with dimensions of 5x5x2 mm 3 . A Peltier cooler with a size of 40x40 mm 2 was installed below the fabricated CZT detector to reduce the operation temperature of the detector. Energy spectra of were measured with 59.5 keV γ-ray from 241 Am. A Monte Carlo code was developed to simulate the CZT energy spectrum, which was measured with a planar-type CZT detector, and the result was compared with the measured one. The simulation was extended to the CZT detector with strip electrodes. (author)

  18. 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)

  19. Quantification of rat brain SPECT with 123I-ioflupane: evaluation of different reconstruction methods and image degradation compensations using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Roé-Vellvé, N; Pino, F; Cot, A; Ros, D; Falcon, C; Gispert, J D; Pavía, J; Marin, C

    2014-01-01

    SPECT studies with 123 I-ioflupane facilitate the diagnosis of Parkinson’s disease (PD). The effect on quantification of image degradations has been extensively evaluated in human studies but their impact on studies of experimental PD models is still unclear. The aim of this work was to assess the effect of compensating for the degrading phenomena on the quantification of small animal SPECT studies using 123 I-ioflupane. This assessment enabled us to evaluate the feasibility of quantitatively detecting small pathological changes using different reconstruction methods and levels of compensation for the image degrading phenomena. Monte Carlo simulated studies of a rat phantom were reconstructed and quantified. Compensations for point spread function (PSF), scattering, attenuation and partial volume effect were progressively included in the quantification protocol. A linear relationship was found between calculated and simulated specific uptake ratio (SUR) in all cases. In order to significantly distinguish disease stages, noise-reduction during the reconstruction process was the most relevant factor, followed by PSF compensation. The smallest detectable SUR interval was determined by biological variability rather than by image degradations or coregistration errors. The quantification methods that gave the best results allowed us to distinguish PD stages with SUR values that are as close as 0.5 using groups of six rats to represent each stage. (paper)

  20. 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.

  1. Dosimetric references for low and medium energy X rays at the LNE-LHB: X ray spectrum simulation and calculation of corrective factors using the Monte Carlo method

    International Nuclear Information System (INIS)

    Ksouri, W.; Gouriou, J.; Denoziere, M.

    2010-01-01

    As the LNHB (Laboratoire National Henri Becquerel) has set dosimetric references for low and medium energy X rays in medical and industrial applications, the authors report the determination of different corrective factors: those related to the mechanical realization of the ionization chamber, and those related to physical phenomena in this room (electron loss or Ke, and photon diffusion or Ksc). These factors are computed using the Monte Carlo PENELOPE code. As the determination of Ke and Ksc requires the knowledge of the energy spectral distribution of impinging photons, and as spectrum measurement exhibit ambiguities, spectra are determined through a Monte Carlo simulation using PENELOPE and EGS codes, by modelling the X ray tube

  2. Monte Carlo simulations for instrumentation at SINQ

    International Nuclear Information System (INIS)

    Filges, U.; Ronnow, H.M.; Zsigmond, G.

    2006-01-01

    The Paul Scherrer Institut (PSI) operates a spallation source SINQ equipped with 11 different neutron scattering instruments. Beside the optimization of the existing instruments, the extension with new instruments and devices are continuously done at PSI. For design and performance studies different Monte Carlo packages are used. Presently two major projects are in an advanced stage of planning. These are the new thermal neutron triple-axis spectrometer Enhanced Intensity and Greater Energy Range (EIGER) and the ultra-cold neutron source (UCN-PSI). The EIGER instrument design is focused on an optimal signal-to-background ratio. A very important design part was to realize a monochromator shielding which covers best shielding characteristic, low background production and high instrument functionality. The Monte Carlo package MCNPX was used to find the best choice. Due to the sharp energy distribution of ultra-cold neutrons (UCN) which can be Doppler-shifted towards cold neutron energies, a UCN phase space transformation (PST) device could produce highly monochromatic cold and very cold neutrons (VCN). The UCN-PST instrumentation project running at PSI is very timely since a new-generation superthermal spallation source of UCN is under construction at PSI with a UCN density of 3000-4000 n cm -3 . Detailed numerical simulations have been carried out to optimize the UCN density and flux. Recent results on numerical simulations of an UCN-PST-based source of highly monochromatic cold neutrons and VCN are presented

  3. Direct Monte Carlo Simulation Methods for Nonreacting and Reacting Systems at Fixed Total Internal Energy or Enthalpy

    Czech Academy of Sciences Publication Activity Database

    Smith, W.; Lísal, Martin

    2002-01-01

    Roč. 66, č. 1 (2002), s. 011104-1 - 011104-1 ISSN 1063-651X R&D Projects: GA ČR GA203/02/0805 Grant - others:NSERC(CA) OGP1041 Keywords : MC * simulation * reaction Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.397, year: 2002

  4. 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

  5. Accurate Vapour-Liquid Equilibrium Calculations for Complex Systems Using the Reaction Gibbs Ensemble Monte Carlo Simulation Method

    Czech Academy of Sciences Publication Activity Database

    Lísal, Martin; Smith, W. R.; Nezbeda, Ivo

    2001-01-01

    Roč. 181, 1-2 (2001), s. 127-146 ISSN 0378-3812 R&D Projects: GA ČR GA203/98/1446; GA AV ČR IAA4072712 Grant - others:NSERC(Ca) OGP1041 Institutional research plan: CEZ:AV0Z4072921 Keywords : computer simulations * mixtures * water Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.217, year: 2001

  6. 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.)

  7. Study of TXRF experimental system by Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T., E-mail: ricardo@lin.ufrj.br [Nuclear Instrumentation Laboratory, Nuclear Engineering Program/COPPE Federal University of Rio de Janeiro (UFRJ), RJ (Brazil); Anjos, Marcelino J., E-mail: marcelin@uerj.br [State University of Rio de Janeiro (UERJ/IFADT/DFAT), RJ (Brazil); Conti, Claudio C., E-mail: ccconti@ird.gov.br [Instituto de Radioprotecao e Dosimetria, (IRD/CNEN-RJ), Rio de janeiro, RJ (Brazil)

    2011-07-01

    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)

  8. 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

  9. A novel method combining Monte Carlo-FEM simulations and experiments for simultaneous evaluation of the ultrathin film mass density and Young's modulus

    Czech Academy of Sciences Publication Activity Database

    Zapoměl, Jaroslav; Stachiv, Ivo; Ferfecki, P.

    66-67, January (2016), s. 223-231 ISSN 0888-3270 R&D Projects: GA ČR GAP107/12/0800 Institutional support: RVO:61388998 ; RVO:68378271 Keywords : film measurement * finite element method * Monte Carlo probabilistic method * resonance frequency Subject RIV: BI - Acoustics; BI - Acoustics (FZU-D) Impact factor: 4.116, year: 2016

  10. Bayesian statistics and Monte Carlo methods

    Science.gov (United States)

    Koch, K. R.

    2018-03-01

    The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

  11. Image reconstruction using Monte Carlo simulation and artificial neural networks

    International Nuclear Information System (INIS)

    Emert, F.; Missimner, J.; Blass, W.; Rodriguez, A.

    1997-01-01

    PET data sets are subject to two types of distortions during acquisition: the imperfect response of the scanner and attenuation and scattering in the active distribution. In addition, the reconstruction of voxel images from the line projections composing a data set can introduce artifacts. Monte Carlo simulation provides a means for modeling the distortions and artificial neural networks a method for correcting for them as well as minimizing artifacts. (author) figs., tab., refs

  12. Applications of Monte Carlo simulations of gamma-ray spectra

    International Nuclear Information System (INIS)

    Clark, D.D.

    1995-01-01

    A short, convenient computer program based on the Monte Carlo method that was developed to generate simulated gamma-ray spectra has been found to have useful applications in research and teaching. In research, we use it to predict spectra in neutron activation analysis (NAA), particularly in prompt gamma-ray NAA (PGNAA). In teaching, it is used to illustrate the dependence of detector response functions on the nature of gamma-ray interactions, the incident gamma-ray energy, and detector geometry

  13. 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.

  14. An evaluation of the plant density estimator the point-centred quarter method (PCQM) using monte carlo simulation

    NARCIS (Netherlands)

    Khan, M.N.I.; Hijbeek, Renske; Berger, Uta; Koedam, Nico; Grueters, Uwe; Islam, S.M.Z.; Hasan, M.A.; Dahdouh-Guebas, Farid

    2016-01-01

    Background In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM

  15. Keno-Nr a Monte Carlo Code Simulating the Californium -252-SOURCE-DRIVEN Noise Analysis Experimental Method for Determining Subcriticality

    Science.gov (United States)

    Ficaro, Edward Patrick

    The ^{252}Cf -source-driven noise analysis (CSDNA) requires the measurement of the cross power spectral density (CPSD) G_ {23}(omega), between a pair of neutron detectors (subscripts 2 and 3) located in or near the fissile assembly, and the CPSDs, G_{12}( omega) and G_{13}( omega), between the neutron detectors and an ionization chamber 1 containing ^{252}Cf also located in or near the fissile assembly. The key advantage of this method is that the subcriticality of the assembly can be obtained from the ratio of spectral densities,{G _sp{12}{*}(omega)G_ {13}(omega)over G_{11 }(omega)G_{23}(omega) },using a point kinetic model formulation which is independent of the detector's properties and a reference measurement. The multigroup, Monte Carlo code, KENO-NR, was developed to eliminate the dependence of the measurement on the point kinetic formulation. This code utilizes time dependent, analog neutron tracking to simulate the experimental method, in addition to the underlying nuclear physics, as closely as possible. From a direct comparison of simulated and measured data, the calculational model and cross sections are validated for the calculation, and KENO-NR can then be rerun to provide a distributed source k_ {eff} calculation. Depending on the fissile assembly, a few hours to a couple of days of computation time are needed for a typical simulation executed on a desktop workstation. In this work, KENO-NR demonstrated the ability to accurately estimate the measured ratio of spectral densities from experiments using capture detectors performed on uranium metal cylinders, a cylindrical tank filled with aqueous uranyl nitrate, and arrays of safe storage bottles filled with uranyl nitrate. Good agreement was also seen between simulated and measured values of the prompt neutron decay constant from the fitted CPSDs. Poor agreement was seen between simulated and measured results using composite ^6Li-glass-plastic scintillators at large subcriticalities for the tank of

  16. A method based on Monte Carlo simulations and voxelized anatomical atlases to evaluate and correct uncertainties on radiotracer accumulation quantitation in beta microprobe studies in the rat brain

    Science.gov (United States)

    Pain, F.; Dhenain, M.; Gurden, H.; Routier, A. L.; Lefebvre, F.; Mastrippolito, R.; Lanièce, P.

    2008-10-01

    The β-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using 18F, 11C and 15O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous β-microprobe reports. In the context of realistic experiments (binding of 11C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with 18F-FDG and H2O15 blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed β-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the different sources of beta signal. Finally, since stereotaxic accuracy is

  17. A method based on Monte Carlo simulations and voxelized anatomical atlases to evaluate and correct uncertainties on radiotracer accumulation quantitation in beta microprobe studies in the rat brain

    Energy Technology Data Exchange (ETDEWEB)

    Pain, F; Dhenain, M; Gurden, H; Routier, A L; Lefebvre, F; Mastrippolito, R; Laniece, P [UMR8165 Imagerie et Modelisation en Cancerologie et Neurobiologie, Universites Paris 11/Paris 7, Campus d' Orsay Bat 104/440 91406 Orsay Cedex (France)

    2008-10-07

    The {beta}-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using {sup 18}F, {sup 11}C and {sup 15}O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous {beta}-microprobe reports. In the context of realistic experiments (binding of {sup 11}C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with {sup 18}F-FDG and H{sub 2}O{sup 15} blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed {beta}-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the

  18. 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.

  19. A Simple Scatter Reduction Method in Cone-Beam Computed Tomography for Dental and Maxillofacial Applications Based on Monte Carlo Simulation

    Directory of Open Access Journals (Sweden)

    Chalinee Thanasupsombat

    2018-01-01

    Full Text Available The quality of images obtained from cone-beam computed tomography (CBCT is important in diagnosis and treatment planning for dental and maxillofacial applications. However, X-ray scattering inside a human head is one of the main factors that cause a drop in image quality, especially in the CBCT system with a wide-angle cone-beam X-ray source and a large area detector. In this study, the X-ray scattering distribution within a standard head phantom was estimated using the Monte Carlo method based on Geant4. Due to small variation of low-frequency scattering signals, the scattering signals from the head phantom can be represented as the simple predetermined scattering signals from a patient’s head and subtracted the projection data for scatter reduction. The results showed higher contrast and less cupping artifacts on the reconstructed images of the head phantom and real patients. Furthermore, the same simulated scattering signals can also be applied to process with higher-resolution projection data.

  20. 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

  1. Monte Carlo simulation of the standardization of {sup 22}Na using scintillation detector arrays

    Energy Technology Data Exchange (ETDEWEB)

    Sato, Y., E-mail: yss.sato@aist.go.j [National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan); Murayama, H. [National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage, Chiba 263-8555 (Japan); Yamada, T. [Japan Radioisotope Association, 2-28-45, Hon-komagome, Bunkyo, Tokyo 113-8941 (Japan); National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan); Tohoku University, 6-6, Aoba, Aramaki, Aoba, Sendai 980-8579 (Japan); Hasegawa, T. [Kitasato University, 1-15-1, Kitasato, Sagamihara, Kanagawa 228-8555 (Japan); Oda, K. [Tokyo Metropolitan Institute of Gerontology, 1-1 Nakacho, Itabashi-ku, Tokyo 173-0022 (Japan); Unno, Y.; Yunoki, A. [National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, Quantum Radiation Division, Radioactivity and Neutron Section, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568 (Japan)

    2010-07-15

    In order to calibrate PET devices by a sealed point source, we contrived an absolute activity measurement method for the sealed point source using scintillation detector arrays. This new method was verified by EGS5 Monte Carlo simulation.

  2. Spatial distribution sampling and Monte Carlo simulation of radioactive isotopes

    CERN Document Server

    Krainer, Alexander Michael

    2015-01-01

    This work focuses on the implementation of a program for random sampling of uniformly spatially distributed isotopes for Monte Carlo particle simulations and in specific FLUKA. With FLUKA it is possible to calculate the radio nuclide production in high energy fields. The decay of these nuclide, and therefore the resulting radiation field, however can only be simulated in the same geometry. This works gives the tool to simulate the decay of the produced nuclide in other geometries. With that the radiation field from an irradiated object can be simulated in arbitrary environments. The sampling of isotope mixtures was tested by simulating a 50/50 mixture of $Cs^{137}$ and $Co^{60}$. These isotopes are both well known and provide therefore a first reliable benchmark in that respect. The sampling of uniformly distributed coordinates was tested using the histogram test for various spatial distributions. The advantages and disadvantages of the program compared to standard methods are demonstrated in the real life ca...

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

    NARCIS (Netherlands)

    A. Leitao Rodriguez (Álvaro); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractIn 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.

  4. 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.

  5. Introduction to Monte Carlo methods: sampling techniques and random numbers

    International Nuclear Information System (INIS)

    Bhati, Sharda; Patni, H.K.

    2009-01-01

    The Monte Carlo method describes a very broad area of science, in which many processes, physical systems and phenomena that are statistical in nature and are difficult to solve analytically are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions. As the number of individual events (called histories) is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. Assuming that the behavior of physical system can be described by probability density functions, then the Monte Carlo simulation can proceed by sampling from these probability density functions, which necessitates a fast and effective way to generate random numbers uniformly distributed on the interval (0,1). Particles are generated within the source region and are transported by sampling from probability density functions through the scattering media until they are absorbed or escaped the volume of interest. The outcomes of these random samplings or trials, must be accumulated or tallied in an appropriate manner to produce the desired result, but the essential characteristic of Monte Carlo is the use of random sampling techniques to arrive at a solution of the physical problem. The major components of Monte Carlo methods for random sampling for a given event are described in the paper

  6. 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

  7. Coupling an analytical description of anti-scatter grids with simulation software of radiographic systems using Monte Carlo code; Couplage d'une methode de description analytique de grilles anti diffusantes avec un logiciel de simulation de systemes radiographiques base sur un code Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Rinkel, J.; Dinten, J.M.; Tabary, J

    2004-07-01

    The use of focused anti-scatter grids on digital radiographic systems with two-dimensional detectors produces acquisitions with a decreased scatter to primary ratio and thus improved contrast and resolution. Simulation software is of great interest in optimizing grid configuration according to a specific application. Classical simulators are based on complete detailed geometric descriptions of the grid. They are accurate but very time consuming since they use Monte Carlo code to simulate scatter within the high-frequency grids. We propose a new practical method which couples an analytical simulation of the grid interaction with a radiographic system simulation program. First, a two dimensional matrix of probability depending on the grid is created offline, in which the first dimension represents the angle of impact with respect to the normal to the grid lines and the other the energy of the photon. This matrix of probability is then used by the Monte Carlo simulation software in order to provide the final scattered flux image. To evaluate the gain of CPU time, we define the increasing factor as the increase of CPU time of the simulation with as opposed to without the grid. Increasing factors were calculated with the new model and with classical methods representing the grid with its CAD model as part of the object. With the new method, increasing factors are shorter by one to two orders of magnitude compared with the second one. These results were obtained with a difference in calculated scatter of less than five percent between the new and the classical method. (authors)

  8. Monte Carlo simulations on SIMD computer architectures

    International Nuclear Information System (INIS)

    Burmester, C.P.; Gronsky, R.; Wille, L.T.

    1992-01-01

    In this paper algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SIMD) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carl updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures

  9. 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

  10. A keff calculation method by Monte Carlo

    International Nuclear Information System (INIS)

    Shen, H; Wang, K.

    2008-01-01

    The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)

  11. Monte Carlo method in neutron activation analysis

    International Nuclear Information System (INIS)

    Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.

    2009-01-01

    Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA

  12. Monte Carlo method for random surfaces

    International Nuclear Information System (INIS)

    Berg, B.

    1985-01-01

    Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)

  13. The MCLIB library: Monte Carlo simulation of neutron scattering instruments

    International Nuclear Information System (INIS)

    Seeger, P.A.

    1995-01-01

    Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC RUN) which use the library are shown as an example

  14. The MCLIB library: Monte Carlo simulation of neutron scattering instruments

    Energy Technology Data Exchange (ETDEWEB)

    Seeger, P.A.

    1995-09-01

    Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC{_}RUN) which use the library are shown as an example.

  15. Simulation of clinical X-ray tube using the Monte Carlo Method - PENELOPE code; Simulacao de um tubo de raios X clinico atraves do Metodo de Monte Carlo usando codigo PENELOPE

    Energy Technology Data Exchange (ETDEWEB)

    Albuquerque, M.A.G.; David, M.G.; Almeida, C.E. de; Magalhaes, L.A.G., E-mail: malbuqueque@hotmail.com [Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ (Brazil). Lab. de Ciencias Radiologicas; Bernal, M. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil); Braz, D. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

    2015-07-01

    Breast cancer is the most common type of cancer among women. The main strategy to increase the long-term survival of patients with this disease is the early detection of the tumor, and mammography is the most appropriate method for this purpose. Despite the reduction of cancer deaths, there is a big concern about the damage caused by the ionizing radiation to the breast tissue. To evaluate these measures it was modeled a mammography equipment, and obtained the depth spectra using the Monte Carlo method - PENELOPE code. The average energies of the spectra in depth and the half value layer of the mammography output spectrum. (author)

  16. Introduction to the Monte Carlo methods

    International Nuclear Information System (INIS)

    Uzhinskij, V.V.

    1993-01-01

    Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab

  17. Monte Carlo methods for shield design calculations

    International Nuclear Information System (INIS)

    Grimstone, M.J.

    1974-01-01

    A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)

  18. Monte Carlo simulations for heavy ion dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Geithner, O.

    2006-07-26

    Water-to-air stopping power ratio (s{sub w,air}) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)

  19. Monte Carlo simulations for heavy ion dosimetry

    International Nuclear Information System (INIS)

    Geithner, O.

    2006-01-01

    Water-to-air stopping power ratio (s w,air ) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s w,air , the influence of fragments and I-values on s w,air for carbon ion beams was investigated. The value of s w,air deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)

  20. Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

    International Nuclear Information System (INIS)

    Chatterjee, Abhijit; Vlachos, Dionisios G.

    2006-01-01

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

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. A zero-variance based scheme for Monte Carlo criticality simulations

    NARCIS (Netherlands)

    Christoforou, S.

    2010-01-01

    The ability of the Monte Carlo method to solve particle transport problems by simulating the particle behaviour makes it a very useful technique in nuclear reactor physics. However, the statistical nature of Monte Carlo implies that there will always be a variance associated with the estimate

  6. 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...... are well-described within the method. It is shown that adsorption of CO and O(2), on a PtRu alloy increases the concentration of Ru in the surface. Furthermore we present a database of CO adsorption energies collected from the literature. (C) 2002 Elsevier Science B.V. All rights reserved....

  7. Monte Carlo simulations of the randomly forced Burgers equation

    International Nuclear Information System (INIS)

    Dueben, P.; Homeier, D.; Muenster, G.; Jansen, K.; Mesterhazy, D.; Urbach, C.

    2008-10-01

    The behaviour of the one-dimensional random-forced Burgers equation is investigated in the path integral formalism, using a discrete space-time lattice. We show that by means of Monte Carlo methods one may evaluate observables, such as structure functions, as ensemble averages over different field realizations. The regularization of shock solutions to the zero-viscosity limit (Hopf-eq.) eventually leads to constraints on lattice parameters, required for the stability of the simulations. Insight into the formation of localized structures (shocks) and their dynamics is obtained. (orig.)

  8. Resolution and intensity in neutron spectrometry determined by Monte Carlo simulation

    DEFF Research Database (Denmark)

    Dietrich, O.W.

    1968-01-01

    The Monte Carlo simulation technique was applied to the propagation of Bragg-reflected neutrons in mosaic single crystals. The method proved to be very useful for the determination of resolution and intensity in neutron spectrometers.......The Monte Carlo simulation technique was applied to the propagation of Bragg-reflected neutrons in mosaic single crystals. The method proved to be very useful for the determination of resolution and intensity in neutron spectrometers....

  9. Monte Carlo methods for preference learning

    DEFF Research Database (Denmark)

    Viappiani, P.

    2012-01-01

    Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....

  10. 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.

  11. Markov chain Monte Carlo simulation for Bayesian Hidden Markov Models

    Science.gov (United States)

    Chan, Lay Guat; Ibrahim, Adriana Irawati Nur Binti

    2016-10-01

    A hidden Markov model (HMM) is a mixture model which has a Markov chain with finite states as its mixing distribution. HMMs have been applied to a variety of fields, such as speech and face recognitions. The main purpose of this study is to investigate the Bayesian approach to HMMs. Using this approach, we can simulate from the parameters' posterior distribution using some Markov chain Monte Carlo (MCMC) sampling methods. HMMs seem to be useful, but there are some limitations. Therefore, by using the Mixture of Dirichlet processes Hidden Markov Model (MDPHMM) based on Yau et. al (2011), we hope to overcome these limitations. We shall conduct a simulation study using MCMC methods to investigate the performance of this model.

  12. Direct Simulation Monte Carlo (DSMC) on the Connection Machine

    International Nuclear Information System (INIS)

    Wong, B.C.; Long, L.N.

    1992-01-01

    The massively parallel computer Connection Machine is utilized to map an improved version of the direct simulation Monte Carlo (DSMC) method for solving flows with the Boltzmann equation. The kinetic theory is required for analyzing hypersonic aerospace applications, and the features and capabilities of the DSMC particle-simulation technique are discussed. The DSMC is shown to be inherently massively parallel and data parallel, and the algorithm is based on molecule movements, cross-referencing their locations, locating collisions within cells, and sampling macroscopic quantities in each cell. The serial DSMC code is compared to the present parallel DSMC code, and timing results show that the speedup of the parallel version is approximately linear. The correct physics can be resolved from the results of the complete DSMC method implemented on the connection machine using the data-parallel approach. 41 refs

  13. 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.)

  14. Simulation of ventilation efficiency, and pre-closure temperatures in emplacement drifts at Yucca Mountain, Nevada, using Monte Carlo and composite thermal-pulse methods

    Science.gov (United States)

    Case, J.B.; Buesch, D.C.

    2004-01-01

    Predictions of waste canister and repository driftwall temperatures as functions of space and time are important to evaluate pre-closure performance of the proposed repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain, Nevada. Variations in the lithostratigraphic features in densely welded and crystallized rocks of the 12.8-million-year-old Topopah Spring Tuff, especially the porosity resulting from lithophysal cavities, affect thermal properties. A simulated emplacement drift is based on projecting lithophysal cavity porosity values 50 to 800 m from the Enhanced Characterization of the Repository Block cross drift. Lithophysal cavity porosity varies from 0.00 to 0.05 cm3/cm3 in the middle nonlithophysal zone and from 0.03 to 0.28 cm3/cm3 in the lower lithophysal zone. A ventilation model and computer program titled "Monte Carlo Simulation of Ventilation" (MCSIMVENT), which is based on a composite thermal-pulse calculation, simulates statistical variability and uncertainty of rock-mass thermal properties and ventilation performance along a simulated emplacement drift for a pre-closure period of 50 years. Although ventilation efficiency is relatively insensitive to thermal properties, variations in lithophysal porosity along the drift can result in a range of peak driftwall temperatures can range from 40 to 85??C for the preclosure period. Copyright ?? 2004 by ASME.

  15. 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.

  16. Markov Chain Monte Carlo Methods-Simple Monte Carlo

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 4. Markov Chain Monte Carlo ... New York 14853, USA. Indian Statistical Institute 8th Mile, Mysore Road Bangalore 560 059, India. Systat Software Asia-Pacific (PI Ltd., Floor 5, 'C' Tower Golden Enclave, Airport Road Bangalore 560017, India.

  17. 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

  18. by means of FLUKA Monte Carlo method

    Directory of Open Access Journals (Sweden)

    Ermis Elif Ebru

    2015-01-01

    Full Text Available Calculations of gamma-ray mass attenuation coefficients of various detector materials (crystals were carried out by means of FLUKA Monte Carlo (MC method at different gamma-ray energies. NaI, PVT, GSO, GaAs and CdWO4 detector materials were chosen in the calculations. Calculated coefficients were also compared with the National Institute of Standards and Technology (NIST values. Obtained results through this method were highly in accordance with those of the NIST values. It was concluded from the study that FLUKA MC method can be an alternative way to calculate the gamma-ray mass attenuation coefficients of the detector materials.

  19. 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 

  20. Simulation of transport equations with Monte Carlo

    International Nuclear Information System (INIS)

    Matthes, W.

    1975-09-01

    The main purpose of the report is to explain the relation between the transport equation and the Monte Carlo game used for its solution. The introduction of artificial particles carrying a weight provides one with high flexibility in constructing many different games for the solution of the same equation. This flexibility opens a way to construct a Monte Carlo game for the solution of the adjoint transport equation. Emphasis is laid mostly on giving a clear understanding of what to do and not on the details of how to do a specific game

  1. 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.

  2. Vector Monte Carlo simulations on atmospheric scattering of polarization qubits.

    Science.gov (United States)

    Li, Ming; Lu, Pengfei; Yu, Zhongyuan; Yan, Lei; Chen, Zhihui; Yang, Chuanghua; Luo, Xiao

    2013-03-01

    In this paper, a vector Monte Carlo (MC) method is proposed to study the influence of atmospheric scattering on polarization qubits for satellite-based quantum communication. The vector MC method utilizes a transmittance method to solve the photon free path for an inhomogeneous atmosphere and random number sampling to determine whether the type of scattering is aerosol scattering or molecule scattering. Simulations are performed for downlink and uplink. The degrees and the rotations of polarization are qualitatively and quantitatively obtained, which agree well with the measured results in the previous experiments. The results show that polarization qubits are well preserved in the downlink and uplink, while the number of received single photons is less than half of the total transmitted single photons for both links. Moreover, our vector MC method can be applied for the scattering of polarized light in other inhomogeneous random media.

  3. A new approach for radiosynoviorthesis: A dose-optimized planning method based on Monte Carlo simulation and synovial measurement using 3D slicer and MRI.

    Science.gov (United States)

    Torres Berdeguez, Mirta Bárbara; Thomas, Sylvia; Rafful, Patricia; Arruda Sanchez, Tiago; Medeiros Oliveira Ramos, Susie; Souza Albernaz, Marta; Vasconcellos de Sá, Lidia; Lopes de Souza, Sergio Augusto; Mas Milian, Felix; Silva, Ademir Xavier da

    2017-07-01

    Recently, there has been a growing interest in a methodology for dose planning in radiosynoviorthesis to substitute fixed activity. Clinical practice based on fixed activity frequently does not embrace radiopharmaceutical dose optimization in patients. The aim of this paper is to propose and discuss a dose planning methodology considering the radiological findings of interest obtained by three-dimensional magnetic resonance imaging combined with Monte Carlo simulation in radiosynoviorthesis treatment applied to hemophilic arthropathy. The parameters analyzed were: surface area of the synovial membrane (synovial size), synovial thickness and joint effusion obtained by 3D MRI of nine knees from nine patients on a SIEMENS AVANTO 1.5 T scanner using a knee coil. The 3D Slicer software performed both the semiautomatic segmentation and quantitation of these radiological findings. A Lucite phantom 3D MRI validated the quantitation methodology. The study used Monte Carlo N-Particle eXtended code version 2.6 for calculating the S-values required to set up the injected activity to deliver a 100 Gy absorbed dose at a determined synovial thickness. The radionuclides assessed were: 90Y, 32P, 188Re, 186Re, 153Sm, and 177Lu, and the present study shows their effective treatment ranges. The quantitation methodology was successfully tested, with an error below 5% for different materials. S-values calculated could provide data on the activity to be injected into the joint, considering no extra-articular leakage from joint cavity. Calculation of effective treatment range could assist with the therapeutic decision, with an optimized protocol for dose prescription in RSO. Using 3D Slicer software, this study focused on segmentation and quantitation of radiological features such as joint effusion, synovial size, and thickness, all obtained by 3D MRI in patients' knees with hemophilic arthropathy. The combination of synovial size and thickness with the parameters obtained by Monte Carlo

  4. Risk-based determination of design pressure of LNG fuel storage tanks based on dynamic process simulation combined with Monte Carlo method

    International Nuclear Information System (INIS)

    Noh, Yeelyong; Chang, Kwangpil; Seo, Yutaek; Chang, Daejun

    2014-01-01

    This study proposes a new methodology that combines dynamic process simulation (DPS) and Monte Carlo simulation (MCS) to determine the design pressure of fuel storage tanks on LNG-fueled ships. Because the pressure of such tanks varies with time, DPS is employed to predict the pressure profile. Though equipment failure and subsequent repair affect transient pressure development, it is difficult to implement these features directly in the process simulation due to the randomness of the failure. To predict the pressure behavior realistically, MCS is combined with DPS. In MCS, discrete events are generated to create a lifetime scenario for a system. The combination of MCS with long-term DPS reveals the frequency of the exceedance pressure. The exceedance curve of the pressure provides risk-based information for determining the design pressure based on risk acceptance criteria, which may vary with different points of view. - Highlights: • The realistic operation scenario of the LNG FGS system is estimated by MCS. • In repeated MCS trials, the availability of the FGS system is evaluated. • The realistic pressure profile is obtained by the proposed methodology. • The exceedance curve provides risk-based information for determining design pressure

  5. 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)

  6. 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.

  7. Optimization of reconstruction algorithms using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Hanson, K.M.

    1989-01-01

    A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by an iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a non-negativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. (author)

  8. Monte Carlo field-theoretic simulations of a homopolymer blend

    Science.gov (United States)

    Spencer, Russell; Matsen, Mark

    Fluctuation corrections to the macrophase segregation transition (MST) in a symmetric homopolymer blend are examined using Monte Carlo field-theoretic simulations (MC-FTS). This technique involves treating interactions between unlike monomers using standard Monte-Carlo techniques, while enforcing incompressibility as is done in mean-field theory. When using MC-FTS, we need to account for a UV divergence. This is done by renormalizing the Flory-Huggins interaction parameter to incorporate the divergent part of the Hamiltonian. We compare different ways of calculating this effective interaction parameter. Near the MST, the length scale of compositional fluctuations becomes large, however, the high computational requirements of MC-FTS restrict us to small system sizes. We account for these finite size effects using the method of Binder cumulants, allowing us to locate the MST with high precision. We examine fluctuation corrections to the mean field MST, χN = 2 , as they vary with the invariant degree of polymerization, N =ρ2a6 N . These results are compared with particle-based simulations as well as analytical calculations using the renormalized one loop theory. This research was funded by the Center for Sustainable Polymers.

  9. Monte Carlo simulation of gas Cerenkov detectors

    International Nuclear Information System (INIS)

    Mack, J.M.; Jain, M.; Jordan, T.M.

    1984-01-01

    Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier

  10. 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

  11. 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.

  12. Monte Carlo simulation of light fluence calculation during pleural PDT

    Science.gov (United States)

    Meo, Julia L.; Zhu, Timothy

    2013-03-01

    A thorough understanding of light distribution in the desired tissue is necessary for accurate light dosimetry in PDT. Solving the problem of light dose depends, in part, on the geometry of the tissue to be treated. When considering PDT in the thoracic cavity for treatment of malignant, localized tumors such as those observed in malignant pleural mesothelioma (MPM), changes in light dose caused by the cavity geometry should be accounted for in order to improve treatment efficacy. Cavity-like geometries demonstrate what is known as the "integrating sphere effect" where multiple light scattering off the cavity walls induces an overall increase in light dose in the cavity. We present a Monte Carlo simulation of light fluence based on a spherical and an elliptical cavity geometry with various dimensions. The tissue optical properties as well as the non-scattering medium (air and water) varies. We have also introduced small absorption inside the cavity to simulate the effect of blood absorption. We expand the MC simulation to track photons both within the cavity and in the surrounding cavity walls. Simulations are run for a variety of cavity optical properties determined using spectroscopic methods. We concluded from the MC simulation that the light fluence inside the cavity is inversely proportional to the surface area.

  13. Advanced Markov chain Monte Carlo methods learning from past samples

    CERN Document Server

    Liang, Faming; Carrol, Raymond J

    2010-01-01

    This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem have been developed include, the modified Gibbs sampler, the methods based on auxiliary variables and the methods making use of past samples. The focus of this book is on the algorithms that make use of past samples. This book includes the multicanonical algorithm, dynamic weighting, dynamically weight

  14. Efficient configurational-bias Monte-Carlo simulations of chain molecules with `swarms' of trial configurations

    OpenAIRE

    Boon, Niels

    2017-01-01

    Proposed here is a dynamic Monte-Carlo algorithm that is efficient in simulating dense systems of long flexible chain molecules. It expands on the configurational-bias Monte-Carlo method through the simultaneous generation of a large set of trial configurations. This process is directed by attempting to terminate unfinished chains with a low statistical weight, and replacing these chains with clones (enrichments) of stronger chains. The efficiency of the resulting method is explored by simula...

  15. Monte Carlo simulation of virtual compton scattering at MAMI

    International Nuclear Information System (INIS)

    D'Hose, N.; Ducret, J.E.; Gousset, TH.; Guichon, P.A.M.; Kerhoas, S.; Lhuillier, D.; Marchand, C.; Marchand, D.; Martino, J.; Mougey, J.; Roche, J.; Vanderhaeghen, M.; Vernin, P.; Bohm, H.; Distler, M.; Edelhoff, R.; Friedrich, J.M.; Geiges, R.; Jennewein, P.; Kahrau, M.; Korn, M.; Kramer, H.; Krygier, K.W.; Kunde, V.; Liesenfeld, A.; Merkel, H.; Merle, K.; Neuhausen, R.; Pospischil, TH.; Rosner, G.; Sauer, P.; Schmieden, H.; Schardt, S.; Tamas, G.; Wagner, A.; Walcher, TH.; Wolf, S.; Hyde-Wright, CH.; Boeglin, W.U.; Van de Wiele, J.

    1996-01-01

    The Monte Carlo simulation developed specially for the VCS experiments taking place at MAMI in fully described. This simulation can generate events according to the Bethe-Heitler + Born cross section behaviour and takes into account resolution deteriorating effects. It is used to determine solid angles for the various experimental settings. (authors)

  16. Coupled Monte Carlo simulation and Copula theory for uncertainty analysis of multiphase flow simulation models.

    Science.gov (United States)

    Jiang, Xue; Na, Jin; Lu, Wenxi; Zhang, Yu

    2017-11-01

    Simulation-optimization techniques are effective in identifying an optimal remediation strategy. Simulation models with uncertainty, primarily in the form of parameter uncertainty with different degrees of correlation, influence the reliability of the optimal remediation strategy. In this study, a coupled Monte Carlo simulation and Copula theory is proposed for uncertainty analysis of a simulation model when parameters are correlated. Using the self-adaptive weight particle swarm optimization Kriging method, a surrogate model was constructed to replace the simulation model and reduce the computational burden and time consumption resulting from repeated and multiple Monte Carlo simulations. The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were employed to identify whether the t Copula function or the Gaussian Copula is the optimal Copula function to match the relevant structure of the parameters. The results show that both the AIC and BIC values of the t Copula function are less than those of the Gaussian Copula function. This indicates that the t Copula function is the optimal function for matching the relevant structure of the parameters. The outputs of the simulation model when parameter correlation was considered and when it was ignored were compared. The results show that the amplitude of the fluctuation interval when parameter correlation was considered is less than the corresponding amplitude when parameter estimation was ignored. Moreover, it was demonstrated that considering the correlation among parameters is essential for uncertainty analysis of a simulation model, and the results of uncertainty analysis should be incorporated into the remediation strategy optimization process.

  17. Improving computational efficiency of Monte Carlo simulations with variance reduction

    International Nuclear Information System (INIS)

    Turner, A.; Davis, A.

    2013-01-01

    CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)

  18. Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

    DEFF Research Database (Denmark)

    Hey, Jody; Nielsen, Rasmus

    2007-01-01

    Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint...

  19. 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)

  20. 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.

  1. Self-test Monte Carlo method

    International Nuclear Information System (INIS)

    Ohta, Shigemi

    1996-01-01

    The Self-Test Monte Carlo (STMC) method resolves the main problems in using algebraic pseudo-random numbers for Monte Carlo (MC) calculations: that they can interfere with MC algorithms and lead to erroneous results, and that such an error often cannot be detected without known exact solution. STMC is based on good randomness of about 10 10 bits available from physical noise or transcendental numbers like π = 3.14---. Various bit modifiers are available to get more bits for applications that demands more than 10 10 random bits such as lattice quantum chromodynamics (QCD). These modifiers are designed so that a) each of them gives a bit sequence comparable in randomness as the original if used separately from each other, and b) their mutual interference when used jointly in a single MC calculation is adjustable. Intermediate data of the MC calculation itself are used to quantitatively test and adjust the mutual interference of the modifiers in respect of the MC algorithm. STMC is free of systematic error and gives reliable statistical error. Also it can be easily implemented on vector and parallel supercomputers. (author)

  2. MONTE CARLO SIMULATION OF MULTIFOCAL STOCHASTIC SCANNING SYSTEM

    Directory of Open Access Journals (Sweden)

    LIXIN LIU

    2014-01-01

    Full Text Available Multifocal multiphoton microscopy (MMM has greatly improved the utilization of excitation light and imaging speed due to parallel multiphoton excitation of the samples and simultaneous detection of the signals, which allows it to perform three-dimensional fast fluorescence imaging. Stochastic scanning can provide continuous, uniform and high-speed excitation of the sample, which makes it a suitable scanning scheme for MMM. In this paper, the graphical programming language — LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanners by using white noise signals to control the x and y mirrors independently. Moreover, the stochastic scanning process is simulated by using Monte Carlo method. Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N × N foci array. Therefore, continuous and uniform scanning in the whole field of view is implemented.

  3. 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.

  4. Copper precipitation in iron: a comparison between metropolis Monte Carlo and lattice kinetic Monte Carlo methods

    CERN Document Server

    Khrushcheva, O; Malerba, L; Becquart, C S; Domain, C; Hou, M

    2003-01-01

    Several variants are possible in the suite of programs forming multiscale predictive tools to estimate the yield strength increase caused by irradiation in RPV steels. For instance, at the atomic scale, both the Metropolis and the lattice kinetic Monte Carlo methods (MMC and LKMC respectively) allow predicting copper precipitation under irradiation conditions. Since these methods are based on different physical models, the present contribution discusses their consistency on the basis of a realistic case study. A cascade debris in iron containing 0.2% of copper was modelled by molecular dynamics with the DYMOKA code, which is part of the REVE suite. We use this debris as input for both the MMC and the LKMC simulations. Thermal motion and lattice relaxation can be avoided in the MMC, making the model closer to the LKMC (LMMC method). The predictions and the complementarity of the three methods for modelling the same phenomenon are then discussed.

  5. Construction of the quantitative analysis environment using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Shirakawa, Seiji; Ushiroda, Tomoya; Hashimoto, Hiroshi; Tadokoro, Masanori; Uno, Masaki; Tsujimoto, Masakazu; Ishiguro, Masanobu; Toyama, Hiroshi

    2013-01-01

    The thoracic phantom image was acquisitioned of the axial section to construct maps of the source and density with Monte Carlo (MC) simulation. The phantom was Heart/Liver Type HL (Kyoto Kagaku Co., Ltd.) single photon emission CT (SPECT)/CT machine was Symbia T6 (Siemence) with the collimator LMEGP (low-medium energy general purpose). Maps were constructed from CT images with an in-house software using Visual studio C Sharp (Microsoft). The code simulation of imaging nuclear detectors (SIMIND) was used for MC simulation, Prominence processor (Nihon Medi-Physics) for filter processing and image reconstruction, and the environment DELL Precision T7400 for all image processes. For the actual experiment, the phantom was given 15 MBq of 99m Tc assuming the uptake 2% at the dose of 740 MBq in its myocardial portion and SPECT image was acquisitioned and reconstructed with Butter-worth filter and filter back projection method. CT images were similarly obtained in 0.3 mm thick slices, which were filed in one formatted with digital imaging and communication in medicine (DICOM), and then processed for application to SIMIND for mapping the source and density. Physical and mensuration factors were examined in ideal images by sequential exclusion and simulation of those factors as attenuation, scattering, spatial resolution deterioration and statistical fluctuation. Gamma energy spectrum, SPECT projection and reconstructed images given by the simulation were found to well agree with the actual data, and the precision of MC simulation was confirmed. Physical and mensuration factors were found to be evaluable individually, suggesting the usefulness of the simulation for assessing the precision of their correction. (T.T.)

  6. Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Stochastic reaction networks (SRNs) is a class of continuous-time Markov chains intended to describe, from the kinetic point of view, the time-evolution of chemical systems in which molecules of different chemical species undergo a finite set of reaction channels. This talk is based on articles [4, 5, 6], where we are interested in the following problem: given a SRN, X, defined though its set of reaction channels, and its initial state, x0, estimate E (g(X(T))); that is, the expected value of a scalar observable, g, of the process, X, at a fixed time, T. This problem lead us to define a series of Monte Carlo estimators, M, such that, with high probability can produce values close to the quantity of interest, E (g(X(T))). More specifically, given a user-selected tolerance, TOL, and a small confidence level, η, find an estimator, M, based on approximate sampled paths of X, such that, P (|E (g(X(T))) − M| ≤ TOL) ≥ 1 − η; even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.

  7. Utilising Monte Carlo Simulation for the Valuation of Mining Concessions

    Directory of Open Access Journals (Sweden)

    Rosli Said

    2005-12-01

    Full Text Available Valuation involves the analyses of various input data to produce an estimated value. Since each input is itself often an estimate, there is an element of uncertainty in the input. This leads to uncertainty in the resultant output value. It is argued that a valuation must also convey information on the uncertainty, so as to be more meaningful and informative to the user. The Monte Carlo simulation technique can generate the information on uncertainty and is therefore potentially useful to valuation. This paper reports on the investigation that has been conducted to apply Monte Carlo simulation technique in mineral valuation, more specifically, in the valuation of a quarry concession.

  8. THE APPLICATION OF MONTE CARLO SIMULATION FOR A DECISION PROBLEM

    Directory of Open Access Journals (Sweden)

    Çiğdem ALABAŞ

    2001-01-01

    Full Text Available The ultimate goal of the standard decision tree approach is to calculate the expected value of a selected performance measure. In the real-world situations, the decision problems become very complex as the uncertainty factors increase. In such cases, decision analysis using standard decision tree approach is not useful. One way of overcoming this difficulty is the Monte Carlo simulation. In this study, a Monte Carlo simulation model is developed for a complex problem and statistical analysis is performed to make the best decision.

  9. Monte Carlo simulation of the Leksell Gamma Knife: I. Source modelling and calculations in homogeneous media

    Energy Technology Data Exchange (ETDEWEB)

    Moskvin, Vadim [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN (United States)]. E-mail: vmoskvin@iupui.edu; DesRosiers, Colleen; Papiez, Lech; Timmerman, Robert; Randall, Marcus; DesRosiers, Paul [Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN (United States)

    2002-06-21

    The Monte Carlo code PENELOPE has been used to simulate photon flux from the Leksell Gamma Knife, a precision method for treating intracranial lesions. Radiation from a single {sup 60}Co assembly traversing the collimator system was simulated, and phase space distributions at the output surface of the helmet for photons and electrons were calculated. The characteristics describing the emitted final beam were used to build a two-stage Monte Carlo simulation of irradiation of a target. A dose field inside a standard spherical polystyrene phantom, usually used for Gamma Knife dosimetry, has been computed and compared with experimental results, with calculations performed by other authors with the use of the EGS4 Monte Carlo code, and data provided by the treatment planning system Gamma Plan. Good agreement was found between these data and results of simulations in homogeneous media. Owing to this established accuracy, PENELOPE is suitable for simulating problems relevant to stereotactic radiosurgery. (author)

  10. Monte Carlo simulations of lattice gauge theories

    International Nuclear Information System (INIS)

    Forcrand, P. de; Minnesota Univ., Minneapolis, MN

    1989-01-01

    Lattice gauge simulations are presented in layman's terms. The need for large computer resources is justified. The main aspects of implementations on vector and parallel machines are explained. An overview of state of the art simulations and dedicated hardware projects is presented. 8 refs.; 1 figure; 1 table

  11. 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.

  12. 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

  13. Entropic sampling in the path integral Monte Carlo method

    International Nuclear Information System (INIS)

    Vorontsov-Velyaminov, P N; Lyubartsev, A P

    2003-01-01

    We have extended the entropic sampling Monte Carlo method to the case of path integral representation of a quantum system. A two-dimensional density of states is introduced into path integral form of the quantum canonical partition function. Entropic sampling technique within the algorithm suggested recently by Wang and Landau (Wang F and Landau D P 2001 Phys. Rev. Lett. 86 2050) is then applied to calculate the corresponding entropy distribution. A three-dimensional quantum oscillator is considered as an example. Canonical distributions for a wide range of temperatures are obtained in a single simulation run, and exact data for the energy are reproduced

  14. Monte Carlo Simulation of Partially Confined Flexible Polymers

    NARCIS (Netherlands)

    Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias

    2002-01-01

    We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the

  15. Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations

    DEFF Research Database (Denmark)

    Kamran, Faisal; Andersen, Peter E.

    2015-01-01

    profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...

  16. Monte Carlo simulation models of breeding-population advancement.

    Science.gov (United States)

    J.N. King; G.R. Johnson

    1993-01-01

    Five generations of population improvement were modeled using Monte Carlo simulations. The model was designed to address questions that are important to the development of an advanced generation breeding population. Specifically we addressed the effects on both gain and effective population size of different mating schemes when creating a recombinant population for...

  17. Condensed history Monte Carlo methods for photon transport problems

    International Nuclear Information System (INIS)

    Bhan, Katherine; Spanier, Jerome

    2007-01-01

    We study methods for accelerating Monte Carlo simulations that retain most of the accuracy of conventional Monte Carlo algorithms. These methods - called Condensed History (CH) methods - have been very successfully used to model the transport of ionizing radiation in turbid systems. Our primary objective is to determine whether or not such methods might apply equally well to the transport of photons in biological tissue. In an attempt to unify the derivations, we invoke results obtained first by Lewis, Goudsmit and Saunderson and later improved by Larsen and Tolar. We outline how two of the most promising of the CH models - one based on satisfying certain similarity relations and the second making use of a scattering phase function that permits only discrete directional changes - can be developed using these approaches. The main idea is to exploit the connection between the space-angle moments of the radiance and the angular moments of the scattering phase function. We compare the results obtained when the two CH models studied are used to simulate an idealized tissue transport problem. The numerical results support our findings based on the theoretical derivations and suggest that CH models should play a useful role in modeling light-tissue interactions

  18. REVIEW: Fifty years of Monte Carlo simulations for medical physics

    Science.gov (United States)

    Rogers, D. W. O.

    2006-07-01

    Monte Carlo techniques have become ubiquitous in medical physics over the last 50 years with a doubling of papers on the subject every 5 years between the first PMB paper in 1967 and 2000 when the numbers levelled off. While recognizing the many other roles that Monte Carlo techniques have played in medical physics, this review emphasizes techniques for electron-photon transport simulations. The broad range of codes available is mentioned but there is special emphasis on the EGS4/EGSnrc code system which the author has helped develop for 25 years. The importance of the 1987 Erice Summer School on Monte Carlo techniques is highlighted. As an illustrative example of the role Monte Carlo techniques have played, the history of the correction for wall attenuation and scatter in an ion chamber is presented as it demonstrates the interplay between a specific problem and the development of tools to solve the problem which in turn leads to applications in other areas. This paper is dedicated to W Ralph Nelson and to the memory of Martin J Berger, two men who have left indelible marks on the field of Monte Carlo simulation of electron-photon transport.

  19. Monte Carlo simulation of tomography techniques using the platform Gate

    International Nuclear Information System (INIS)

    Barbouchi, Asma

    2007-01-01

    Simulations play a key role in functional imaging, with applications ranging from scanner design, scatter correction, protocol optimisation. GATE (Geant4 for Application Tomography Emission) is a platform for Monte Carlo Simulation. It is based on Geant4 to generate and track particles, to model geometry and physics process. Explicit modelling of time includes detector motion, time of flight, tracer kinetics. Interfaces to voxellised models and image reconstruction packages improve the integration of GATE in the global modelling cycle. In this work Monte Carlo simulations are used to understand and optimise the gamma camera's performances. We study the effect of the distance between source and collimator, the diameter of the holes and the thick of the collimator on the spatial resolution, energy resolution and efficiency of the gamma camera. We also study the reduction of simulation's time and implement a model of left ventricle in GATE. (Author). 7 refs

  20. Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations

    OpenAIRE

    Roberto S. Flowers-Cano; Ruperto Ortiz-Gómez; Jesús Enrique León-Jiménez; Raúl López Rivera; Luis A. Perera Cruz

    2018-01-01

    Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP), bias-corrected bootstrap (BC), accelerated bias-corrected bootstrap (BCA) and a modified version of the standard bootstrap (MSB). Different simulation scenarios were analyzed. In some cases, the mother distributi...

  1. A general purpose code for Monte Carlo simulations

    International Nuclear Information System (INIS)

    Wilcke, W.W.; Rochester Univ., NY

    1984-01-01

    A general-purpose computer code MONTHY has been written to perform Monte Carlo simulations of physical systems. To achieve a high degree of flexibility the code is organized like a general purpose computer, operating on a vector describing the time dependent state of the system under simulation. The instruction set of the 'computer' is defined by the user and is therefore adaptable to the particular problem studied. The organization of MONTHY allows iterative and conditional execution of operations. (orig.)

  2. Monte Carlo simulation of hybrid systems: An example

    International Nuclear Information System (INIS)

    Bacha, F.; D'Alencon, H.; Grivelet, J.; Jullien, E.; Jejcic, A.; Maillard, J.; Silva, J.; Zukanovich, R.; Vergnes, J.

    1997-01-01

    Simulation of hybrid systems needs tracking of particles from the GeV (incident proton beam) range down to a fraction of eV (thermic neutrons). We show how a GEANT based Monte-Carlo program can achieve this, with a realistic computer time and accompanying tools. An example of a dedicated original actinide burner is simulated with this chain. 8 refs., 5 figs

  3. Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia

    Energy Technology Data Exchange (ETDEWEB)

    Granero Cabanero, D.

    2015-07-01

    The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)

  4. 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

  5. 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

  6. Monte Carlo simulations of lattice models for single polymer systems

    International Nuclear Information System (INIS)

    Hsu, Hsiao-Ping

    2014-01-01

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

  7. Direct Simulation Monte Carlo Investigation of Noncontinuum Couette Flow

    Science.gov (United States)

    Torczynski, J. R.; Gallis, M. A.

    2009-11-01

    The Direct Simulation Monte Carlo (DSMC) method of molecular gas dynamics is used to study noncontinuum effects in Couette flow. The walls have equal temperatures and equal accommodation coefficients but unequal tangential velocities. Simulations are performed for near-free-molecular to near-continuum gas pressures with accommodation coefficients of 0.25, 0.5, and 1. Ten gases are examined: argon, helium, nitrogen, sea-level air, and six Inverse-Power-Law (IPL) gases with viscosity temperature exponents of 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0, as represented by the Variable Soft Sphere (VSS) interaction. In all cases, the wall shear stress is proportional to the slip velocity. The momentum transfer coefficient relating these two quantities can be accurately correlated in terms of the Knudsen number based on the wall separation. The two dimensionless parameters in the correlation are similar for all gases examined. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  8. Optimizing the HLT Buffer Strategy with Monte Carlo Simulations

    CERN Document Server

    AUTHOR|(CDS)2266763

    2017-01-01

    This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.

  9. 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)

  10. 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.

  11. 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.

  12. 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

  13. A Monte Carlo simulation technique to determine the optimal portfolio

    Directory of Open Access Journals (Sweden)

    Hassan Ghodrati

    2014-03-01

    Full Text Available During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR, which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.

  14. Optimization of reconstruction algorithms using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Hanson, K.M.

    1989-01-01

    A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by a iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a nonnegativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. 11 refs., 6 figs., 2 tabs

  15. Monte Carlo methods for pricing financial options

    Indian Academy of Sciences (India)

    Monte Carlo methods have increasingly become a popular computational tool to price complex financial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the 'curse of dimensionality'. However, even Monte-Carlo ...

  16. Approximating Sievert Integrals to Monte Carlo Methods to calculate ...

    African Journals Online (AJOL)

    Radiation dose rates along the transverse axis of a miniature P192PIr source were calculated using Sievert Integral (considered simple and inaccurate), and by the sophisticated and accurate Monte Carlo method. Using data obt-ained by the Monte Carlo method as benchmark and applying least squares regression curve ...

  17. A preliminary study of in-house Monte Carlo simulations: an integrated Monte Carlo verification system.

    Science.gov (United States)

    Mukumoto, Nobutaka; Tsujii, Katsutomo; Saito, Susumu; Yasunaga, Masayoshi; Takegawa, Hideki; Yamamoto, Tokihiro; Numasaki, Hodaka; Teshima, Teruki

    2009-10-01

    To develop an infrastructure for the integrated Monte Carlo verification system (MCVS) to verify the accuracy of conventional dose calculations, which often fail to accurately predict dose distributions, mainly due to inhomogeneities in the patient's anatomy, for example, in lung and bone. The MCVS consists of the graphical user interface (GUI) based on a computational environment for radiotherapy research (CERR) with MATLAB language. The MCVS GUI acts as an interface between the MCVS and a commercial treatment planning system to import the treatment plan, create MC input files, and analyze MC output dose files. The MCVS consists of the EGSnrc MC codes, which include EGSnrc/BEAMnrc to simulate the treatment head and EGSnrc/DOSXYZnrc to calculate the dose distributions in the patient/phantom. In order to improve computation time without approximations, an in-house cluster system was constructed. The phase-space data of a 6-MV photon beam from a Varian Clinac unit was developed and used to establish several benchmarks under homogeneous conditions. The MC results agreed with the ionization chamber measurements to within 1%. The MCVS GUI could import and display the radiotherapy treatment plan created by the MC method and various treatment planning systems, such as RTOG and DICOM-RT formats. Dose distributions could be analyzed by using dose profiles and dose volume histograms and compared on the same platform. With the cluster system, calculation time was improved in line with the increase in the number of central processing units (CPUs) at a computation efficiency of more than 98%. Development of the MCVS was successful for performing MC simulations and analyzing dose distributions.

  18. Fault Risk Assessment of Underwater Vehicle Steering System Based on Virtual Prototyping and Monte Carlo Simulation

    Directory of Open Access Journals (Sweden)

    He Deyu

    2016-09-01

    Full Text Available Assessing the risks of steering system faults in underwater vehicles is a human-machine-environment (HME systematic safety field that studies faults in the steering system itself, the driver’s human reliability (HR and various environmental conditions. This paper proposed a fault risk assessment method for an underwater vehicle steering system based on virtual prototyping and Monte Carlo simulation. A virtual steering system prototype was established and validated to rectify a lack of historic fault data. Fault injection and simulation were conducted to acquire fault simulation data. A Monte Carlo simulation was adopted that integrated randomness due to the human operator and environment. Randomness and uncertainty of the human, machine and environment were integrated in the method to obtain a probabilistic risk indicator. To verify the proposed method, a case of stuck rudder fault (SRF risk assessment was studied. This method may provide a novel solution for fault risk assessment of a vehicle or other general HME system.

  19. Monte Carlo simulations of the stability of delta-Pu

    DEFF Research Database (Denmark)

    Landa, A.; Soderlind, P.; Ruban, Andrei

    2003-01-01

    The transition temperature (T-c) for delta-Pu has been calculated for the first time. A Monte Carlo method is employed for this purpose and the effective cluster interactions are obtained from first-principles calculations incorporated with the Connolly-Williams and generalized perturbation methods...

  20. 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

  1. Anybody can do Value at Risk: A Teaching Study using Parametric Computation and Monte Carlo Simulation

    Directory of Open Access Journals (Sweden)

    Yun Hsing Cheung

    2012-12-01

    Full Text Available The three main Value at Risk (VaR methodologies are historical, parametric and Monte Carlo Simulation.Cheung & Powell (2012, using a step-by-step teaching study, showed how a nonparametric historical VaRmodel could be constructed using Excel, thus benefitting teachers and researchers by providing them with areadily useable teaching study and an inexpensive and flexible VaR modelling option. This article extends thatwork by demonstrating how parametric and Monte Carlo Simulation VaR models can also be constructed inExcel, thus providing a total Excel modelling package encompassing all three VaR methods.

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

    Science.gov (United States)

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

    2017-11-01

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

  3. Monte Carlo simulations of multiple scattering effects in ERD measurements

    International Nuclear Information System (INIS)

    Doyle, Barney Lee; Arstila, Kai.; Nordlumd, K.; Knapp, James Arthur

    2003-01-01

    Multiple scattering effects in ERD measurements are studied by comparing two Monte Carlo simulation codes, representing different approaches to obtain acceptable statistics, to experimental spectra measured from a HfO 2 sample with a time-of-flight-ERD setup. The results show that both codes can reproduce the absolute detection yields and the energy distributions in an adequate way. The effect of the choice of the interatomic potential in multiple scattering effects is also studied. Finally the capabilities of the MC simulations in the design of new measurement setups are demonstrated by simulating the recoil energy spectra from a WC x N y sample with a low energy heavy ion beam.

  4. Computed radiography simulation using the Monte Carlo code MCNPX

    International Nuclear Information System (INIS)

    Correa, S.C.A.; Souza, E.M.; Silva, A.X.; Lopes, R.T.

    2009-01-01

    Simulating x-ray images has been of great interest in recent years as it makes possible an analysis of how x-ray images are affected owing to relevant operating parameters. In this paper, a procedure for simulating computed radiographic images using the Monte Carlo code MCNPX is proposed. The sensitivity curve of the BaFBr image plate detector as well as the characteristic noise of a 16-bit computed radiography system were considered during the methodology's development. The results obtained confirm that the proposed procedure for simulating computed radiographic images is satisfactory, as it allows obtaining results comparable with experimental data. (author)

  5. Monte Carlo simulation of a prototype photodetector used in radiotherapy

    CERN Document Server

    Kausch, C; Albers, D; Schmidt, R; Schreiber, B

    2000-01-01

    The imaging performance of prototype electronic portal imaging devices (EPID) has been investigated. Monte Carlo simulations have been applied to calculate the modulation transfer function (MTF( f )), the noise power spectrum (NPS( f )) and the detective quantum efficiency (DQE( f )) for different new type of EPIDs, which consist of a detector combination of metal or polyethylene (PE), a phosphor layer of Gd sub 2 O sub 2 S and a flat array of photodiodes. The simulated results agree well with measurements. Based on simulated results, possible optimization of these devices is discussed.

  6. Computed radiography simulation using the Monte Carlo code MCNPX

    Energy Technology Data Exchange (ETDEWEB)

    Correa, S.C.A. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Centro Universitario Estadual da Zona Oeste (CCMAT)/UEZO, Av. Manuel Caldeira de Alvarenga, 1203, Campo Grande, 23070-200, Rio de Janeiro, RJ (Brazil); Souza, E.M. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Silva, A.X., E-mail: ademir@con.ufrj.b [PEN/COPPE-DNC/Poli CT, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Cassiano, D.H. [Instituto de Radioprotecao e Dosimetria/CNEN Av. Salvador Allende, s/n, Recreio, 22780-160, Rio de Janeiro, RJ (Brazil); Lopes, R.T. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil)

    2010-09-15

    Simulating X-ray images has been of great interest in recent years as it makes possible an analysis of how X-ray images are affected owing to relevant operating parameters. In this paper, a procedure for simulating computed radiographic images using the Monte Carlo code MCNPX is proposed. The sensitivity curve of the BaFBr image plate detector as well as the characteristic noise of a 16-bit computed radiography system were considered during the methodology's development. The results obtained confirm that the proposed procedure for simulating computed radiographic images is satisfactory, as it allows obtaining results comparable with experimental data.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules

    CERN Document Server

    Lester, William A; Reynolds, PJ

    1994-01-01

    This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n

  13. 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

  14. Monte Carlo simulation of PET images for injection doseoptimization

    Czech Academy of Sciences Publication Activity Database

    Boldyš, Jiří; Dvořák, Jiří; Skopalová, M.; Bělohlávek, O.

    2013-01-01

    Roč. 29, č. 9 (2013), s. 988-999 ISSN 2040-7939 R&D Projects: GA MŠk 1M0572 Institutional support: RVO:67985556 Keywords : positron emission tomography * Monte Carlo simulation * biological system modeling * image quality Subject RIV: FD - Oncology ; Hematology Impact factor: 1.542, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/boldys-0397175.pdf

  15. Quantum Monte Carlo simulations for high-Tc superconductors

    International Nuclear Information System (INIS)

    Muramatsu, A.; Dopf, G.; Wagner, J.; Dieterich, P.; Hanke, W.

    1992-01-01

    Quantum Monte Carlo simulations for a multi-band model of high-Tc superconductors are reviewed with special emphasis on the comparison of different observabels with experiments. It is shown that a give parameter set of the three-band Hubbard model leads to a consistent description of normal-state propteries as well as pairing correlation function for the copper-oxide superconductors as a function of doping and temperature. (orig.)

  16. Simulating Polymorphic Phase Behavior Using Reaction Ensemble Monte Carlo

    Czech Academy of Sciences Publication Activity Database

    Brennan, J.K.; Rice, B.M.; Lísal, Martin

    2007-01-01

    Roč. 111, č. 1 (2007), s. 365-373 ISSN 1932-7447 R&D Projects: GA ČR(CZ) GA203/05/0725; GA AV ČR(CZ) 1ET400720507; GA AV ČR(CZ) 1ET400720409 Institutional research plan: CEZ:AV0Z40720504 Keywords : simulation * monte carlo * phase transition Subject RIV: CF - Physical ; Theoretical Chemistry

  17. Molecular-level Monte Carlo Simulation at Fixed Entropy

    Czech Academy of Sciences Publication Activity Database

    Smith, W.R.; Lísal, Martin; Nezbeda, Ivo

    2006-01-01

    Roč. 426, 4-6 (2006), s. 436-440 ISSN 0009-2614 R&D Projects: GA AV ČR(CZ) 1ET400720507; GA AV ČR 1ET400720409 Grant - others:NRCC(CA) OGP1041 Institutional research plan: CEZ:AV0Z40720504 Keywords : simulation * entropy * Monte Carlo Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.462, year: 2006

  18. 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)

  19. A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

    Science.gov (United States)

    S. Healey; P. Patterson; S. Urbanski

    2014-01-01

    Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

  20. Advanced Monte Carlo for radiation physics, particle transport simulation and applications. Proceedings

    International Nuclear Information System (INIS)

    Kling, A.; Barao, F.J.C.; Nakagawa, M.; Tavora, L.

    2001-01-01

    The following topics were dealt with: Electron and photon interactions and transport mechanisms, random number generation, applications in medical physisc, microdosimetry, track structure, radiobiological modeling, Monte Carlo method in radiotherapy, dosimetry, and medical accelerator simulation, neutron transport, high-energy hadron transport. (HSI)

  1. Generation of Random Numbers and Parallel Random Number Streams for Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    L. Yu. Barash

    2012-01-01

    Full Text Available Modern methods and libraries for high quality pseudorandom number generation and for generation of parallel random number streams for Monte Carlo simulations are considered. The probability equidistribution property and the parameters when the property holds at dimensions up to logarithm of mesh size are considered for Multiple Recursive Generators.

  2. 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.

  3. Enhancement of high-energy distribution tail in Monte Carlo semiconductor simulations using a Variance Reduction Scheme

    Directory of Open Access Journals (Sweden)

    Vincenza Di Stefano

    2009-11-01

    Full Text Available The Multicomb variance reduction technique has been introduced in the Direct Monte Carlo Simulation for submicrometric semiconductor devices. The method has been implemented in bulk silicon. The simulations show that the statistical variance of hot electrons is reduced with some computational cost. The method is efficient and easy to implement in existing device simulators.

  4. Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

    Science.gov (United States)

    Pratx, Guillem; Xing, Lei

    2011-01-01

    Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes. PMID:22191916

  5. 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

  6. On the Markov Chain Monte Carlo (MCMC) method

    Indian Academy of Sciences (India)

    Abstract. Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be specified indirectly. In this article, we give an introduction to this method along with some examples.

  7. Monte Carlo simulation for radiation dose in children radiology

    International Nuclear Information System (INIS)

    Mendes, Hitalo R.; Tomal, Alessandra

    2016-01-01

    The dosimetry in pediatric radiology is essential due to the higher risk that children have in comparison to adults. The focus of this study is to present how the dose varies depending on the depth in a 10 year old and a newborn, for this purpose simulations are made using the Monte Carlo method. Potential differences were considered 70 and 90 kVp for the 10 year old and 70 and 80 kVp for the newborn. The results show that in both cases, the dose at the skin surface is larger for smaller potential value, however, it decreases faster for larger potential values. Another observation made is that because the newborn is less thick the ratio between the initial dose and the final is lower compared to the case of a 10 year old, showing that it is possible to make an image using a smaller entrance dose in the skin, keeping the same level of exposure at the detector. (author)

  8. Monte Carlo simulation techniques for predicting annual power production

    International Nuclear Information System (INIS)

    Cross, J.P.; Bulandr, P.J.

    1991-01-01

    As the owner and operator of a number of small to mid-sized hydroelectric sites, STS HydroPower has been faced with the need to accurately predict anticipated hydroelectric revenues over a period of years. The typical approach to this problem has been to look at each site from a mathematical deterministic perspective and evaluate the annual production from historic streamflows. Average annual production is simply taken to be the area under the flow duration curve defined by the operating and design characteristics of the selected turbines. Minimum annual production is taken to be a historic dry year scenario and maximum production is viewed as power generated under the most ideal of conditions. Such an approach creates two problems. First, in viewing the characteristics of a single site, it does not take into account the probability of such an event occurring. Second, in viewing all sites in a single organization's portfolio together, it does not reflect the varying flow conditions at the different sites. This paper attempts to address the first of these two concerns, that being the creation of a simulation model utilizing the Monte Carlo method at a single site. The result of the analysis is a picture of the production at the site that is both a better representation of anticipated conditions and defined probabilistically

  9. Monte Carlo simulation of the seed germination process

    International Nuclear Information System (INIS)

    Gladyszewska, B.; Koper, R.

    2000-01-01

    Paper presented a mathematical model of seed germination process based on the Monte Carlo method and theoretical premises resulted from the physiology of seed germination suggesting three consecutive stages: physical, biochemical and physiological. The model was experimentally verified by determination of germination characteristics for seeds of ground tomatoes, Promyk cultivar, within broad range of temperatures (from 15 to 30 deg C)

  10. Monte Carlo simulations of ionization potential depression in dense plasmas

    Czech Academy of Sciences Publication Activity Database

    Stránský, Michal

    2016-01-01

    Roč. 23, č. 1 (2016), 1-5, č. článku 012708. ISSN 1070-664X R&D Projects: GA MŠk LG15013 Institutional support: RVO:68378271 Keywords : Monte Carlo methods * aluminium * plasma temperature * computer modeling * ionization Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 2.115, year: 2016

  11. Hybrid Monte-Carlo method for ICF calculations

    Energy Technology Data Exchange (ETDEWEB)

    Clouet, J.F.; Samba, G. [CEA Bruyeres-le-Chatel, 91 (France)

    2003-07-01

    ) conduction and ray-tracing for laser description. Radiation transport is usually solved by a Monte-Carlo method. In coupling diffusion approximation and transport description, the difficult part comes from the need for an implicit discretization of the emission-absorption terms: this problem was solved by using the symbolic Monte-Carlo method. This means that at each step of the simulation a matrix is computed by a Monte-Carlo method which accounts for the radiation energy exchange between the cells. Because of time step limitation by hydrodynamic motion, energy exchange is limited to a small number of cells and the matrix remains sparse. This matrix is added to usual diffusion matrix for thermal and radiative conductions: finally we arrive at a non-symmetric linear system to invert. A generalized Marshak condition describe the coupling between transport and diffusion. In this paper we will present the principles of the method and numerical simulation of an ICF hohlraum. We shall illustrate the benefits of the method by comparing the results with full implicit Monte-Carlo calculations. In particular we shall show how the spectral cut-off evolves during the propagation of the radiative front in the gold wall. Several issues are still to be addressed (robust algorithm for spectral cut- off calculation, coupling with ALE capabilities): we shall briefly discuss these problems. (authors)

  12. 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)

  13. SIMIND Monte Carlo simulation of a single photon emission CT

    International Nuclear Information System (INIS)

    Bahreyni Toossi, M.T.; Pirayesh Islamian, J.; Naseri, S.H.; Momennezhad, M.; Ljungberg, M.

    2010-01-01

    In this study, we simulated a Siemens E.CAM SPECT system using SIMIND Monte Carlo program to acquire its experimental characterization in terms of energy resolution, sensitivity, spatial resolution and imaging of phantoms using 99m Tc. The experimental and simulation data for SPECT imaging was acquired from a point source and Jaszczak phantom. Verification of the simulation was done by comparing two sets of images and related data obtained from the actual and simulated systems. Image quality was assessed by comparing image contrast and resolution. Simulated and measured energy spectra (with or without a collimator) and spatial resolution from point sources in air were compared. The resulted energy spectra present similar peaks for the gamma energy of 99m Tc at 140 KeV. FWHM for the simulation calculated to 14.01 KeV and 13.80 KeV for experimental data, corresponding to energy resolution of 10.01 and 9.86% compared to defined 9.9% for both systems, respectively. Sensitivities of the real and virtual gamma cameras were calculated to 85.11 and 85.39 cps/MBq, respectively. The energy spectra of both simulated and real gamma cameras were matched. Images obtained from Jaszczak phantom, experimentally and by simulation, showed similarly in contrast and resolution. SIMIND Monte Carlo could successfully simulate the Siemens E.CAM gamma camera. The results validate the use of the simulated system for further investigation, including modification, planning, and developing a SPECT system to improve the quality of images. (author)

  14. 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)

  15. Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

    Science.gov (United States)

    Restrepo, Carolina; Hurtado, John E.

    2011-01-01

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

  16. 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)

  17. Stacking fault growth of FCC crystal: The Monte-Carlo simulation approach

    International Nuclear Information System (INIS)

    Jian Jianmin; Ming Naiben

    1988-03-01

    The Monte-Carlo method has been used to simulate the growth of the FCC (111) crystal surface, on which is presented the outcrop of a stacking fault. The comparison of the growth rates has been made between the stacking fault containing surface and the perfect surface. The successive growth stages have been simulated. It is concluded that the outcrop of stacking fault on the crystal surface can act as a self-perpetuating step generating source. (author). 7 refs, 3 figs

  18. 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)

  19. Monte Carlo simulation of breast imaging using synchrotron radiation

    Energy Technology Data Exchange (ETDEWEB)

    Fitousi, N. T.; Delis, H.; Panayiotakis, G. [Department of Medical Physics, Faculty of Medicine, University of Patras, 26504 Patras (Greece)

    2012-04-15

    Purpose: Synchrotron radiation (SR), being the brightest artificial source of x-rays with a very promising geometry, has raised the scientific expectations that it could be used for breast imaging with optimized results. The ''in situ'' evaluation of this technique is difficult to perform, mostly due to the limited available SR facilities worldwide. In this study, a simulation model for SR breast imaging was developed, based on Monte Carlo simulation techniques, and validated using data acquired in the SYRMEP beamline of the Elettra facility in Trieste, Italy. Furthermore, primary results concerning the performance of SR were derived. Methods: The developed model includes the exact setup of the SR beamline, considering that the x-ray source is located at almost 23 m from the slit, while the photon energy was considered to originate from a very narrow Gaussian spectrum. Breast phantoms, made of Perspex and filled with air cavities, were irradiated with energies in the range of 16-28 keV. The model included a Gd{sub 2}O{sub 2}S detector with the same characteristics as the one available in the SYRMEP beamline. Following the development and validation of the model, experiments were performed in order to evaluate the contrast resolution of SR. A phantom made of adipose tissue and filled with inhomogeneities of several compositions and sizes was designed and utilized to simulate the irradiation under conventional mammography and SR conditions. Results: The validation results of the model showed an excellent agreement with the experimental data, with the correlation for contrast being 0.996. Significant differences only appeared at the edges of the phantom, where phase effects occur. The initial evaluation experiments revealed that SR shows very good performance in terms of the image quality indices utilized, namely subject contrast and contrast to noise ratio. The response of subject contrast to energy is monotonic; however, this does not stand for

  20. Monte Carlo-based simulation of dynamic jaws tomotherapy

    International Nuclear Information System (INIS)

    Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S.

    2011-01-01

    Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis

  1. Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models

    Science.gov (United States)

    Sato, Toshihiro; Assaad, Fakher F.; Grover, Tarun

    2018-03-01

    The absence of the negative sign problem in quantum Monte Carlo simulations of spin and fermion systems has different origins. World-line based algorithms for spins require positivity of matrix elements whereas auxiliary field approaches for fermions depend on symmetries such as particle-hole symmetry. For negative-sign-free spin and fermionic systems, we show that one can formulate a negative-sign-free auxiliary field quantum Monte Carlo algorithm that allows Kondo coupling of fermions with the spins. Using this general approach, we study a half-filled Kondo lattice model on the honeycomb lattice with geometric frustration. In addition to the conventional Kondo insulator and antiferromagnetically ordered phases, we find a partial Kondo screened state where spins are selectively screened so as to alleviate frustration, and the lattice rotation symmetry is broken nematically.

  2. Monte-Carlo simulations in a gas centrifuge

    International Nuclear Information System (INIS)

    Roblin, Ph.; Doneddu, F.

    2000-01-01

    This paper is associated with the centrifugation process for isotope separation, using the principle of a cylinder rotating at high speed in a vacuum casing. As in the most widely used configuration, the gas containing the isotope mixture is introduced by a fixed axial feed pipe and expands in the cylinder. It is subjected to high centrifugal acceleration, undergoes rigid body rotation and stratifies radially according to a barometric-type pressure law. By pressure diffusion, the heavier isotopes migrate to the cylinder wall and the lighter to the center. A temperature gradient on the wall and the presence of a scoop in the fluid, produce a vertical countercurrent which transforms the radial separation effect into an axial effect. The scoop extracts the gas depleted in light isotopes, called W, and another is used to recover the gas enriched in light isotopes, called P. Practically all the gas is governed by the Navier-Stokes equations in 2D axial symmetry. Due to the strong pressure stratification, continuous fluid equations are not valid in the whole cylinder, with or without linearization of the model. Consequently, an internal boundary separates the continuum domain from a rarefied domain in which the feed gas expands. The radial position of this cut-off then approaches the cylinder wall with increasing rotation speeds. In the rarefied domain, the Boltzmann equation is solved and a well suited numerical method is the Monte-Carlo method. A complete simulation of feed gas expansion and interaction with rotating gas, presented here with the DSMC (Direct Simulation Monte-Carlo) code, provides realistic boundary conditions for fluid flow calculations. The reference centrifuge is a hypothetical machine enabling the scientific community to compare results obtained for the optimization of separation performance. Its radius a is 6 cm, and its peripheral speed a is 600 m/s. The selected gas, containing the isotopes, is UF 6 . The gas pressure p(a) at the cylinder wall is

  3. Partial multicanonical algorithm for molecular dynamics and Monte Carlo simulations.

    Science.gov (United States)

    Okumura, Hisashi

    2008-09-28

    Partial multicanonical algorithm is proposed for molecular dynamics and Monte Carlo simulations. The partial multicanonical simulation samples a wide range of a part of the potential-energy terms, which is necessary to sample the conformational space widely, whereas a wide range of total potential energy is sampled in the multicanonical algorithm. Thus, one can concentrate the effort to determine the weight factor only on the important energy terms in the partial multicanonical simulation. The partial multicanonical, multicanonical, and canonical molecular dynamics algorithms were applied to an alanine dipeptide in explicit water solvent. The canonical simulation sampled the states of P(II), C(5), alpha(R), and alpha(P). The multicanonical simulation covered the alpha(L) state as well as these states. The partial multicanonical simulation also sampled the C(7) (ax) state in addition to the states that were sampled by the multicanonical simulation. In the partial multicanonical simulation, furthermore, backbone dihedral angles phi and psi rotated more frequently than those in the multicanonical and canonical simulations. These results mean that the partial multicanonical algorithm has a higher sampling efficiency than the multicanonical and canonical algorithms.

  4. Efficient Monte Carlo Simulations of Gas Molecules Inside Porous Materials.

    Science.gov (United States)

    Kim, Jihan; Smit, Berend

    2012-07-10

    Monte Carlo (MC) simulations are commonly used to obtain adsorption properties of gas molecules inside porous materials. In this work, we discuss various optimization strategies that lead to faster MC simulations with CO2 gas molecules inside host zeolite structures used as a test system. The reciprocal space contribution of the gas-gas Ewald summation and both the direct and the reciprocal gas-host potential energy interactions are stored inside energy grids to reduce the wall time in the MC simulations. Additional speedup can be obtained by selectively calling the routine that computes the gas-gas Ewald summation, which does not impact the accuracy of the zeolite's adsorption characteristics. We utilize two-level density-biased sampling technique in the grand canonical Monte Carlo (GCMC) algorithm to restrict CO2 insertion moves into low-energy regions within the zeolite materials to accelerate convergence. Finally, we make use of the graphics processing units (GPUs) hardware to conduct multiple MC simulations in parallel via judiciously mapping the GPU threads to available workload. As a result, we can obtain a CO2 adsorption isotherm curve with 14 pressure values (up to 10 atm) for a zeolite structure within a minute of total compute wall time.

  5. Optimal mesh hierarchies in Multilevel Monte Carlo methods

    KAUST Repository

    Von Schwerin, Erik

    2016-01-08

    I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.

  6. Interacting multiagent systems kinetic equations and Monte Carlo methods

    CERN Document Server

    Pareschi, Lorenzo

    2014-01-01

    The description of emerging collective phenomena and self-organization in systems composed of large numbers of individuals has gained increasing interest from various research communities in biology, ecology, robotics and control theory, as well as sociology and economics. Applied mathematics is concerned with the construction, analysis and interpretation of mathematical models that can shed light on significant problems of the natural sciences as well as our daily lives. To this set of problems belongs the description of the collective behaviours of complex systems composed by a large enough number of individuals. Examples of such systems are interacting agents in a financial market, potential voters during political elections, or groups of animals with a tendency to flock or herd. Among other possible approaches, this book provides a step-by-step introduction to the mathematical modelling based on a mesoscopic description and the construction of efficient simulation algorithms by Monte Carlo methods. The ar...

  7. Extreme Value Predictions using Monte Carlo Simulations with Artificially Increased Wave Height

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2010-01-01

    accurate result can be obtained by Monte Carlo simulations, but the necessary length of the time domain simulations for very low out-crossing rates might be prohibitively long. The present paper investigates whether the FORM property regarding the dependency of the reliability index on the significant wave...... height can be used in Monte Carlo simulations to increase the out-crossing rates and thus reduce the necessary length of the time domain simulations by applying a larger significant wave height than actually required for design. The mean out-crossing rate thus obtained can then afterwards be scaled down......-linear processes the reliability index depends non-linearly on the response level r, and a good estimate can be found using the First Order Reliability Method (FORM). The reliability index from the FORM analysis is still strictly inversely proportional to the severity of the sea state, i.e. ß=c(r)/Hs. A more...

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations

    Science.gov (United States)

    Hatch, Harold W.; Jiao, Sally; Mahynski, Nathan A.; Blanco, Marco A.; Shen, Vincent K.

    2017-12-01

    Virial coefficients are predicted over a large range of both temperatures and model parameter values (i.e., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayer-sampling Monte Carlo simulation of the SPC/E (extended simple point charge) water model quantitatively predicted the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicted the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% down to zero charge. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid.

  14. Monte Carlo simulations for design of the KFUPM PGNAA facility

    CERN Document Server

    Naqvi, A A; Maslehuddin, M; Kidwai, S

    2003-01-01

    Monte Carlo simulations were carried out to design a 2.8 MeV neutron-based prompt gamma ray neutron activation analysis (PGNAA) setup for elemental analysis of cement samples. The elemental analysis was carried out using prompt gamma rays produced through capture of thermal neutrons in sample nuclei. The basic design of the PGNAA setup consists of a cylindrical cement sample enclosed in a cylindrical high-density polyethylene moderator placed between a neutron source and a gamma ray detector. In these simulations the predominant geometrical parameters of the PGNAA setup were optimized, including moderator size, sample size and shielding of the detector. Using the results of the simulations, an experimental PGNAA setup was then fabricated at the 350 kV Accelerator Laboratory of this University. The design calculations were checked experimentally through thermal neutron flux measurements inside the PGNAA moderator. A test prompt gamma ray spectrum of the PGNAA setup was also acquired from a Portland cement samp...

  15. Molecular dynamics algorithms for quantum Monte Carlo methods

    Science.gov (United States)

    Miura, Shinichi

    2009-11-01

    In the present Letter, novel molecular dynamics methods compatible with corresponding quantum Monte Carlo methods are developed. One is a variational molecular dynamics method that is a molecular dynamics analog of quantum variational Monte Carlo method. The other is a variational path integral molecular dynamics method, which is based on the path integral molecular dynamics method for finite temperature systems by Tuckerman et al. [M. Tuckerman, B.J. Berne, G.J. Martyna, M.L. Klein, J. Chem. Phys. 99 (1993) 2796]. These methods are applied to model systems including the liquid helium-4, demonstrated to work satisfactorily for the tested ground state calculations.

  16. A Monte Carlo simulation of the packing and segregation of spheres in cylinders

    Directory of Open Access Journals (Sweden)

    C. R. A. ABREU

    1999-12-01

    Full Text Available In this work, the Monte Carlo method (MC was extended to simulate the packing and segregation of particles subjected to a gravitational field and confined inside rigid walls. The method was used in systems containing spheres inside cylinders. The calculation of void fraction profiles in both the axial and radial directions was formulated, and some results are presented. In agreement with experimental data, the simulations show that the packed beds present structural ordering near the cylindrical walls up to a distance of about 4 particle diameters. The simulations also indicate that the presence of the cylindrical wall does not seem to have a strong effect on the gravitational segregation phenomenon.

  17. Estimation of beryllium ground state energy by Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)

    2015-05-15

    Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.

  18. Monte Carlo Simulations Validation Study: Vascular Brachytherapy Beta Sources

    International Nuclear Information System (INIS)

    Orion, I.; Koren, K.

    2004-01-01

    During the last decade many versions of angioplasty irradiation treatments have been proposed. The purpose of this unique brachytherapy is to administer a sufficient radiation dose into the vein walls in order to prevent restonosis, a clinical sequel to balloon angioplasty. The most suitable sources for this vascular brachytherapy are the β - emitters such as Re-188, P-32, and Sr-90/Y-90, with a maximum energy range of up to 2.1 MeV [1,2,3]. The radioactive catheters configurations offered for these treatments can be a simple wire [4], a fluid filled balloon or a coated stent. Each source is differently positioned inside the blood vessel, and the emitted electrons ranges therefore vary. Many types of sources and configurations were studied either experimentally or with the use of the Monte Carlo calculation technique, while most of the Monte Carlo simulations were carried out using EGS4 [5] or MCNP [6]. In this study we compared the beta-source absorbed-dose versus radial-distance of two treatment configurations using MCNP and EGS4 simulations. This comparison was aimed to discover the differences between the MCNP and the EGS4 simulation code systems in intermediate energies electron transport

  19. Monte-Carlo Tree Search for Simulated Car Racing

    DEFF Research Database (Denmark)

    Fischer, Jacob; Falsted, Nikolaj; Vielwerth, Mathias

    2015-01-01

    might play well, and how it can be modified to achieve this. In this paper, we investigate the application of MCTS to simulated car racing, in particular the open-source racing game TORCS. The presented approach is based on the development of an efficient forward model and the discretization......Monte Carlo Tree Search (MCTS) has recently seen considerable success in playing certain types of games, most of which are discrete, fully observable zero-sum games. Consequently there is currently considerable interest within the research community in investigating what other games this algorithm...

  20. Monte Carlo Simulations of Thin Internal Target Scattering In CELSIUS

    CERN Document Server

    Rao, Yi-Nong

    2005-01-01

    In the practical operation of the storage ring CELSIUS with the hydrogen pellet target, we simetimes observe a cooling phenomenon in the longitudinal phase space, that is, the circulating beam's phase space gets shrunk instead of blown up. This phenomenon occurs independently on the electron cooling. In this paper, we aim to investigate and interpret this phenomenon as well as the beam lifetime in the presence of hydrogen pellet target with and without rf and with and without electron cooling in CELSIUS using Monte Carlo simulations.

  1. Proceedings of the first symposium on Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-01-01

    The first symposium on Monte Carlo simulation was held at Mitsubishi Research Institute, Otemachi, Tokyo, on 10th and 11st of September, 1998. This symposium was organized by Nuclear Code Research Committee at Japan Atomic Energy Research Institute. In the sessions, were presented orally 21 papers on code development, parallel calculation, reactor physics, burn-up, criticality, shielding safety, dose evaluation, nuclear fusion reactor, thermonuclear fusion plasma, nuclear transmutation, electromagnetic cascade, fuel cycle facility. Those presented papers are compiled in this proceedings. The 21 of the presented papers are indexed individually. (J.P.N.)

  2. New electron multiple scattering distributions for Monte Carlo transport simulation

    Energy Technology Data Exchange (ETDEWEB)

    Chibani, Omar (Haut Commissariat a la Recherche (C.R.S.), 2 Boulevard Franz Fanon, Alger B.P. 1017, Alger-Gare (Algeria)); Patau, Jean Paul (Laboratoire de Biophysique et Biomathematiques, Faculte des Sciences Pharmaceutiques, Universite Paul Sabatier, 35 Chemin des Maraichers, 31062 Toulouse cedex (France))

    1994-10-01

    New forms of electron (positron) multiple scattering distributions are proposed. The first is intended for use in the conditions of validity of the Moliere theory. The second distribution takes place when the electron path is so short that only few elastic collisions occur. These distributions are adjustable formulas. The introduction of some parameters allows impositions of the correct value of the first moment. Only positive and analytic functions were used in constructing the present expressions. This makes sampling procedures easier. Systematic tests are presented and some Monte Carlo simulations, as benchmarks, are carried out. ((orig.))

  3. 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

  4. Monte Carlo Simulation of Random-Anisotropy Amorphous Magnets

    Science.gov (United States)

    Bondarev, A. V.; Bataronov, I. L.

    2018-01-01

    Using the Monte Carlo method, within the frame of the Heisenberg model, we studies the magnetic properties of amorphous Tb. The relaxation of magnetization of the model of amorphous Tb was studied. We stablished that the relaxation goes in two stages. On the first stage the magnetization sharply decreases by some amount ΔMz , on the second stage the magnetization decreases with time according to the logarithmic law. The possible mechanisms of relaxation is discussed.

  5. 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

  6. Application of biasing techniques to the contributon Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Dubi, A.; Gerstl, S.A.W.

    1980-01-01

    Recently, a new Monte Carlo Method called the Contribution Monte Carlo Method was developed. The method is based on the theory of contributions, and uses a new receipe for estimating target responses by a volume integral over the contribution current. The analog features of the new method were discussed in previous publications. The application of some biasing methods to the new contribution scheme is examined here. A theoretical model is developed that enables an analytic prediction of the benefit to be expected when these biasing schemes are applied to both the contribution method and regular Monte Carlo. This model is verified by a variety of numerical experiments and is shown to yield satisfying results, especially for deep-penetration problems. Other considerations regarding the efficient use of the new method are also discussed, and remarks are made as to the application of other biasing methods. 14 figures, 1 tables.

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

    Science.gov (United States)

    2017-12-07

    challenges of implementing the full array of VV transitions mentioned earlier. Note here that an account of VV processes is not expected to influence the...method. It takes into account the microscopic reversibility between the excitation and deexcitation processes, and it satisfies the detailed balance...probabilities and is suitable for the direct simulation Monte Carlo method. It takes into account the microscopic reversibility between the excitation

  8. Vapor-Liquid Equilibria of Alternative Refrigerants and Their Binaries by Molecular Simulations Employing the Reaction Gibbs Ensemble Monte Carlo Method

    Czech Academy of Sciences Publication Activity Database

    Budinský, R.; Vacek, V.; Lísal, Martin

    222-223, - (2004), s. 213-220 ISSN 0378-3812 R&D Projects: GA AV ČR IAA4072301 Institutional research plan: CEZ:AV0Z4072921 Keywords : refrigerant * simulation * phase equilibria Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.356, year: 2004

  9. Exploring fluctuations and phase equilibria in fluid mixtures via Monte Carlo simulation

    Science.gov (United States)

    Denton, Alan R.; Schmidt, Michael P.

    2013-03-01

    Monte Carlo simulation provides a powerful tool for understanding and exploring thermodynamic phase equilibria in many-particle interacting systems. Among the most physically intuitive simulation methods is Gibbs ensemble Monte Carlo (GEMC), which allows direct computation of phase coexistence curves of model fluids by assigning each phase to its own simulation cell. When one or both of the phases can be modelled virtually via an analytic free energy function (Mehta and Kofke 1993 Mol. Phys. 79 39), the GEMC method takes on new pedagogical significance as an efficient means of analysing fluctuations and illuminating the statistical foundation of phase behaviour in finite systems. Here we extend this virtual GEMC method to binary fluid mixtures and demonstrate its implementation and instructional value with two applications: (1) a lattice model of simple mixtures and polymer blends and (2) a free-volume model of a complex mixture of colloids and polymers. We present algorithms for performing Monte Carlo trial moves in the virtual Gibbs ensemble, validate the method by computing fluid demixing phase diagrams, and analyse the dependence of fluctuations on system size. Our open-source simulation programs, coded in the platform-independent Java language, are suitable for use in classroom, tutorial, or computational laboratory settings.

  10. Observation of Jet Photoproduction and Comparison to Monte Carlo Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Lincoln, Donald W. [Rice Univ., Houston, TX (United States)

    1994-01-01

    The photon is the carrier of the electromagnetic force. However in addition to its well known nature, the theories of QCD and quantum mechanics would indicate that the photon can also for brief periods of time split into a $q\\bar{q}$ pair (an extended photon.) How these constituents share energy and momentum is an interesting question and such a measurement was investigated by scattering photons off protons. The post collision kinematics should reveal pre-collision information. Unfortunately, when these constituents exit the collision point, they undergo subsequent interactions (gluon radiation, fragmentation, etc.) which scramble their kinematics. An algorithm was explored which was shown via Monte Carlo techniques to partially disentangle these post collision interactions and reveal the collision kinematics. The presence or absence of large transverse momenta internal ($k_\\perp$) to the photon has a significant impact on the ability to reconstruct the kinematics of the leading order calculation hard scatter system. Reconstruction of the next to leading order high $E_\\perp$ partons is more straightforward. Since the photon exhibits this unusual behavior only part of the time, many of the collisions recorded will be with a non-extended (or direct) photon. Unless a method for culling only the extended photons out can be invented, this contamination of direct photons must be accounted for. No such culling method is currently known, and so any measurement will necessarily contain both photon types. Theoretical predictions using Monte Carlo methods are compared with the data and are found to reproduce many experimentally measured distributions quite well. Overall the LUND Monte Carlo reproduces the data better than the HERWIG Monte Carlo. As expected at low jet $E_\\perp$, the data set seems to be dominated by extended photons, with the mix becoming nearly equal at jet $E_\\perp > 4$ GeV. The existence of a large photon $k_\\perp$ appears to be favored.

  11. Coarse-grained Monte Carlo simulations of non-equilibrium systems.

    Science.gov (United States)

    Liu, Xiao; Crocker, John C; Sinno, Talid

    2013-06-28

    We extend the scope of a recent method for generating coarse-grained lattice Metropolis Monte Carlo simulations [X. Liu, W. D. Seider, and T. Sinno, Phys. Rev. E 86, 026708 (2012); and J. Chem. Phys. 138, 114104 (2013)] from continuous interaction potentials to non-equilibrium situations. The original method has been shown to satisfy detailed balance at the coarse scale and to provide a good representation of various equilibrium properties in both atomic and molecular systems. However, we show here that the original method is inconsistent with non-equilibrium trajectories generated by full-resolution Monte Carlo simulations, which, under certain conditions, have been shown to correspond to Langevin dynamics. The modified coarse-grained method is generated by simultaneously biasing the forward and backward transition probability for every possible move, thereby preserving the detailed balance of the original method. The resulting coarse-grained Monte Carlo simulations are shown to provide trajectories that are consistent with overdamped Langevin (Smoluchowski) dynamics using a sequence of simple non-equilibrium examples. We first consider the purely diffusional spreading of a Gaussian pulse of ideal-gas particles and then include an external potential to study the influence of drift. Finally, we validate the method using a more general situation in which the particles interact via a Lennard-Jones interparticle potential.

  12. Optimal placement of wind turbines in a wind park using Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Marmidis, Grigorios; Lazarou, Stavros; Pyrgioti, Eleftheria [High Voltage Laboratory, Department of Electrical and Computer Engineering, University of Patras, 26500 Rio, Patras (Greece)

    2008-07-15

    In the present study, a novel procedure is introduced for the optimal placement and arrangement of wind turbines in a wind park. In this approach a statistical and mathematical method is used, which is called 'Monte Carlo simulation method'. The optimization is made by the mean of maximum energy production and minimum cost installation criteria. As a test case, a square site is subdivided into 100 square cells that can be possible turbine locations and as a result, the program presents us the optimal arrangement of the wind turbines in the wind park, based on the Monte Carlo simulation method. The results of this study are compared to the results of previous studies that handle the same issue. (author)

  13. Monte Carlo based simulation of LIAC intraoperative radiotherapy accelerator along with beam shaper applicator

    Directory of Open Access Journals (Sweden)

    N Heidarloo

    2017-08-01

    Full Text Available Intraoperative electron radiotherapy is one of the radiotherapy methods that delivers a high single fraction of radiation dose to the patient in one session during the surgery. Beam shaper applicator is one of the applicators that is recently employed with this radiotherapy method. This applicator has a considerable application in treatment of large tumors. In this study, the dosimetric characteristics of the electron beam produced by LIAC intraoperative radiotherapy accelerator in conjunction with this applicator have been evaluated through Monte Carlo simulation by MCNP code. The results showed that the electron beam produced by the beam shaper applicator would have the desirable dosimetric characteristics, so that the mentioned applicator can be considered for clinical purposes. Furthermore, the good agreement between the results of simulation and practical dosimetry, confirms the applicability of Monte Carlo method in determining the dosimetric parameters of electron beam  intraoperative radiotherapy

  14. Dosimetric references for low and medium energy X rays at the LNE-LHB: X ray spectrum simulation and calculation of corrective factors using the Monte Carlo method; References dosimetriques pour les rayons X de basses et moyennes energies au LNE-LNHB: simulation de spectre de rayons X et calcul des facteurs de correction a l'aide de la methode monte carlo

    Energy Technology Data Exchange (ETDEWEB)

    Ksouri, W.; Gouriou, J.; Denoziere, M. [CEA Saclay, LIST, Laboratoire National Henri Becquerel (LNE-LNHB), 91 - Gif-sur-Yvette (France)

    2010-07-01

    As the LNHB (Laboratoire National Henri Becquerel) has set dosimetric references for low and medium energy X rays in medical and industrial applications, the authors report the determination of different corrective factors: those related to the mechanical realization of the ionization chamber, and those related to physical phenomena in this room (electron loss or Ke, and photon diffusion or Ksc). These factors are computed using the Monte Carlo PENELOPE code. As the determination of Ke and Ksc requires the knowledge of the energy spectral distribution of impinging photons, and as spectrum measurement exhibit ambiguities, spectra are determined through a Monte Carlo simulation using PENELOPE and EGS codes, by modelling the X ray tube

  15. A Monte Carlo adapted finite element method for dislocation ...

    Indian Academy of Sciences (India)

    Mean and standard deviation values, as well as probability density function of ground surface responses due to the dislocation are computed. Based on analytical and numerical calculation of dislocation, two approaches of Monte Carlo simulations are proposed. Various comparisons are examined to illustrate the capability ...

  16. A Monte Carlo approach for simulating the propagation of partially coherent x-ray beams

    DEFF Research Database (Denmark)

    Prodi, A.; Bergbäck Knudsen, Erik; Willendrup, Peter Kjær

    2011-01-01

    by sampling Huygens-Fresnel waves with Monte Carlo methods and is used to propagate each source realization to the detector plane. The sampling is implemented with a modified Monte Carlo ray tracing scheme where the optical path of each generated ray is stored. Such information is then used in the summation...... coherence function (MCF) are propagated to the exit plane. Here we present an approach based on Monte Carlo sampling of the Green function. A Gauss-Shell Stochastic Source with arbitrary spatial coherence is synthesized by means of the Gaussian copula statistical tool. The Green function is obtained......Advances at SR sources in the generation of nanofocused beams with a high degree of transverse coherence call for effective techniques to simulate the propagation of partially coherent X-ray beams through complex optical systems in order to characterize how coherence properties such as the mutual...

  17. Monte Carlo methods for flux expansion solutions of transport problems

    International Nuclear Information System (INIS)

    Spanier, J.

    1999-01-01

    Adaptive Monte Carlo methods, based on the use of either correlated sampling or importance sampling, to obtain global solutions to certain transport problems have recently been described. The resulting learning algorithms are capable of achieving geometric convergence when applied to the estimation of a finite number of coefficients in a flux expansion representation of the global solution. However, because of the nonphysical nature of the random walk simulations needed to perform importance sampling, conventional transport estimators and source sampling techniques require modification to be used successfully in conjunction with such flux expansion methods. It is shown how these problems can be overcome. First, the traditional path length estimators in wide use in particle transport simulations are generalized to include rather general detector functions (which, in this application, are the individual basis functions chosen for the flus expansion). Second, it is shown how to sample from the signed probabilities that arise as source density functions in these applications, without destroying the zero variance property needed to ensure geometric convergence to zero error

  18. LISA data analysis using Markov chain Monte Carlo methods

    International Nuclear Information System (INIS)

    Cornish, Neil J.; Crowder, Jeff

    2005-01-01

    The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low-frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50 000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analysis, and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we supercool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions

  19. Monte Carlo computer simulation of sedimentation of charged hard spherocylinders

    Energy Technology Data Exchange (ETDEWEB)

    Viveros-Méndez, P. X., E-mail: xviveros@fisica.uaz.edu.mx; Aranda-Espinoza, S. [Unidad Académica de Física, Universidad Autónoma de Zacatecas, Calzada Solidaridad esq. Paseo, La Bufa s/n, 98060 Zacatecas, Zacatecas, México (Mexico); Gil-Villegas, Alejandro [Departamento de Ingeniería Física, División de Ciencias e Ingenierías, Campus León, Universidad de Guanajuato, Loma del Bosque 103, Lomas del Campestre, 37150 León, Guanajuato, México (Mexico)

    2014-07-28

    In this article we present a NVT Monte Carlo computer simulation study of sedimentation of an electroneutral mixture of oppositely charged hard spherocylinders (CHSC) with aspect ratio L/σ = 5, where L and σ are the length and diameter of the cylinder and hemispherical caps, respectively, for each particle. This system is an extension of the restricted primitive model for spherical particles, where L/σ = 0, and it is assumed that the ions are immersed in an structureless solvent, i.e., a continuum with dielectric constant D. The system consisted of N = 2000 particles and the Wolf method was implemented to handle the coulombic interactions of the inhomogeneous system. Results are presented for different values of the strength ratio between the gravitational and electrostatic interactions, Γ = (mgσ)/(e{sup 2}/Dσ), where m is the mass per particle, e is the electron's charge and g is the gravitational acceleration value. A semi-infinite simulation cell was used with dimensions L{sub x} ≈ L{sub y} and L{sub z} = 5L{sub x}, where L{sub x}, L{sub y}, and L{sub z} are the box dimensions in Cartesian coordinates, and the gravitational force acts along the z-direction. Sedimentation effects were studied by looking at every layer formed by the CHSC along the gravitational field. By increasing Γ, particles tend to get more packed at each layer and to arrange in local domains with an orientational ordering along two perpendicular axis, a feature not observed in the uncharged system with the same hard-body geometry. This type of arrangement, known as tetratic phase, has been observed in two-dimensional systems of hard-rectangles and rounded hard-squares. In this way, the coupling of gravitational and electric interactions in the CHSC system induces the arrangement of particles in layers, with the formation of quasi-two dimensional tetratic phases near the surface.

  20. The Monte Carlo simulation of the Borexino detector

    Science.gov (United States)

    Agostini, M.; Altenmüller, K.; Appel, S.; Atroshchenko, V.; Bagdasarian, Z.; Basilico, D.; Bellini, G.; Benziger, J.; Bick, D.; Bonfini, G.; Borodikhina, L.; Bravo, D.; Caccianiga, B.; Calaprice, F.; Caminata, A.; Canepa, M.; Caprioli, S.; Carlini, M.; Cavalcante, P.; Chepurnov, A.; Choi, K.; D'Angelo, D.; Davini, S.; Derbin, A.; Ding, X. F.; Di Noto, L.; Drachnev, I.; Fomenko, K.; Formozov, A.; Franco, D.; Froborg, F.; Gabriele, F.; Galbiati, C.; Ghiano, C.; Giammarchi, M.; Goeger-Neff, M.; Goretti, A.; Gromov, M.; Hagner, C.; Houdy, T.; Hungerford, E.; Ianni, Aldo; Ianni, Andrea; Jany, A.; Jeschke, D.; Kobychev, V.; Korablev, D.; Korga, G.; Kryn, D.; Laubenstein, M.; Litvinovich, E.; Lombardi, F.; Lombardi, P.; Ludhova, L.; Lukyanchenko, G.; Machulin, I.; Magnozzi, M.; Manuzio, G.; Marcocci, S.; Martyn, J.; Meroni, E.; Meyer, M.; Miramonti, L.; Misiaszek, M.; Muratova, V.; Neumair, B.; Oberauer, L.; Opitz, B.; Ortica, F.; Pallavicini, M.; Papp, L.; Pocar, A.; Ranucci, G.; Razeto, A.; Re, A.; Romani, A.; Roncin, R.; Rossi, N.; Schönert, S.; Semenov, D.; Shakina, P.; Skorokhvatov, M.; Smirnov, O.; Sotnikov, A.; Stokes, L. F. F.; Suvorov, Y.; Tartaglia, R.; Testera, G.; Thurn, J.; Toropova, M.; Unzhakov, E.; Vishneva, A.; Vogelaar, R. B.; von Feilitzsch, F.; Wang, H.; Weinz, S.; Wojcik, M.; Wurm, M.; Yokley, Z.; Zaimidoroga, O.; Zavatarelli, S.; Zuber, K.; Zuzel, G.

    2018-01-01

    We describe the Monte Carlo (MC) simulation of the Borexino detector and the agreement of its output with data. The Borexino MC "ab initio" simulates the energy loss of particles in all detector components and generates the resulting scintillation photons and their propagation within the liquid scintillator volume. The simulation accounts for absorption, reemission, and scattering of the optical photons and tracks them until they either are absorbed or reach the photocathode of one of the photomultiplier tubes. Photon detection is followed by a comprehensive simulation of the readout electronics response. The MC is tuned using data collected with radioactive calibration sources deployed inside and around the scintillator volume. The simulation reproduces the energy response of the detector, its uniformity within the fiducial scintillator volume relevant to neutrino physics, and the time distribution of detected photons to better than 1% between 100 keV and several MeV. The techniques developed to simulate the Borexino detector and their level of refinement are of possible interest to the neutrino community, especially for current and future large-volume liquid scintillator experiments such as Kamland-Zen, SNO+, and Juno.

  1. PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment.

    Science.gov (United States)

    Sipos, Botond; Massingham, Tim; Jordan, Gregory E; Goldman, Nick

    2011-04-19

    The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity. PhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, PhyloSim can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing PhyloSim to be adapted to specific needs. Close integration with R and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that PhyloSim will be useful to future studies involving simulated alignments.

  2. PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

    Directory of Open Access Journals (Sweden)

    Massingham Tim

    2011-04-01

    Full Text Available Abstract Background The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity. Results PhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, PhyloSim can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing PhyloSim to be adapted to specific needs. Conclusions Close integration with R and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that PhyloSim will be useful to future studies involving simulated alignments.

  3. Monte Carlo simulation of zinc protoporphyrin fluorescence in the retina

    Science.gov (United States)

    Chen, Xiaoyan; Lane, Stephen

    2010-02-01

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

  4. Treatment planning in radiosurgery: parallel Monte Carlo simulation software

    Energy Technology Data Exchange (ETDEWEB)

    Scielzo, G. [Galliera Hospitals, Genova (Italy). Dept. of Hospital Physics; Grillo Ruggieri, F. [Galliera Hospitals, Genova (Italy) Dept. for Radiation Therapy; Modesti, M.; Felici, R. [Electronic Data System, Rome (Italy); Surridge, M. [University of South Hampton (United Kingdom). Parallel Apllication Centre

    1995-12-01

    The main objective of this research was to evaluate the possibility of direct Monte Carlo simulation for accurate dosimetry with short computation time. We made us of: graphics workstation, linear accelerator, water, PMMA and anthropomorphic phantoms, for validation purposes; ionometric, film and thermo-luminescent techniques, for dosimetry; treatment planning system for comparison. Benchmarking results suggest that short computing times can be obtained with use of the parallel version of EGS4 that was developed. Parallelism was obtained assigning simulation incident photons to separate processors, and the development of a parallel random number generator was necessary. Validation consisted in: phantom irradiation, comparison of predicted and measured values good agreement in PDD and dose profiles. Experiments on anthropomorphic phantoms (with inhomogeneities) were carried out, and these values are being compared with results obtained with the conventional treatment planning system.

  5. Monte Carlo simulations of radioactive waste embedded into polymer

    International Nuclear Information System (INIS)

    Ozdemir, Tonguc; Usanmaz, Ali

    2009-01-01

    Radioactive waste is generated from the nuclear applications and it should properly be managed according to the regulations set by the regulatory authority. Poly(carbonate urethane) and poly(bisphenol a-co-epichlorohydrin) are radiation-resistant polymers and they are possible candidate materials that can be used in the radioactive waste management. In this study, maximum allowable waste activity that can be embedded into these polymers and dose rate distribution of the waste drum (containing waste and the polymer matrix) were found via Monte Carlo simulations. The change of mechanical properties of above-mentioned polymers was simulated and their variations within the waste drum were determined for 15, 30 and 300 years after embedding.

  6. Pluto++ - A Monte Carlo simulation tool for hadronic physics

    International Nuclear Information System (INIS)

    Kagarlis, M.A.

    2000-07-01

    A versatile package for Monte Carlo simulations of hadronic interactions in C++ is presented, designed for compatibility with the ROOT analysis environment. Realistic models of resonance production, hadronic, and electromagnetic decays are implemented, motivated by the physics program of HADES. Empirical angular-distribution parametrizations for selected processes are utilized as well, such as resonance excitation in hadronic interactions, and nucleon-nucleon elastic scattering. The code comprises a self-contained framework for stand-alone principle simulations, including an extensive database of elementary particles and properties with support for additional user-input data, as well as utilities for the implementation of elementary detector setups and acceptance cuts. A standard interface for further on- and off-line processing of generated events with GEANT is also supplied. User-defined tasks via macros and derived classes are facilitated by the flexible design of the code, which in analysis mode may be employed for on-line fitting of experimental spectra. (orig.)

  7. Monte Carlo simulation of electron swarms in H2

    International Nuclear Information System (INIS)

    Hunter, S.R.

    1977-01-01

    A Monte Carlo simulation of the motion of an electron swarm in molecular hydrogen has been studied in the range E/N 1.4-170 Td. The simulation was performed for 400-600 electrons at several values of E/N for two different sets of inelastic collision cross sections at high E/N. Results were obtained for the longitudinal diffusion coefficient Dsub(L), lateral diffusion coefficient D, swarm drift velocity W, average swarm energy and ionization and excitation production coefficients, and these were compared with experimental data where available. It is found that the results differ significantly from the experimental values and this is attributed to the isotropic scattering model used in this work. However, the results lend support to the experimental technique used recently by Blevin et al. to determine these transport parameters, and in particular confirm their results that Dsub(L) > D at high values of E/N. (Author)

  8. Exploring Monte Carlo Simulation Strategies for Geoscience Applications

    Science.gov (United States)

    Blais, J.; Grebenitcharsky, R.; Zhang, Z.

    2008-12-01

    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), quasi-random number (QRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the expected error variances are generally of different orders for the same number of random numbers. A comparative analysis of these three strategies has been carried out for geodetic and related applications in planar and spherical contexts. Based on these computational experiments, conclusions and recommendations concerning their performance and error variances are included.

  9. Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Roberto S. Flowers-Cano

    2018-02-01

    Full Text Available Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP, bias-corrected bootstrap (BC, accelerated bias-corrected bootstrap (BCA and a modified version of the standard bootstrap (MSB. Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.

  10. Monte Carlo simulation on teaching of luminescence and excited states decay kinetics; Simulacao Monte Carlo no ensino de luminescencia e cinetica de decaimento de estado excitado

    Energy Technology Data Exchange (ETDEWEB)

    Winnischofer, Herbert; Araujo, Marcio Peres de; Dias Junior, Lauro Camargo; Novo, Joao Batista Marques [Universidade Federal do Parana (UFPR), Curitiba, PR (Brazil)

    2010-07-01

    A software based in the Monte Carlo method have been developed aiming the teaching of important cases of mechanisms found in luminescence and in excited states decay kinetics, including: multiple decays, consecutive decays and coupled systems decays. The Monte Carlo Method allows the student to easily simulate and visualize the luminescence mechanisms, focusing on the probabilities of the related steps. The software CINESTEX was written for FreeBASIC compiler; it assumes first-order kinetics and any number of excited states, where the pathways are allowed with probabilities assigned by the user. (author)

  11. An Investigation of Ion-Pairing of Alkali Metal Halides in Aqueous Solutions Using the Electrical Conductivity and the Monte Carlo Computer Simulation Methods.

    Science.gov (United States)

    Gujt, Jure; Bešter-Rogač, Marija; Hribar-Lee, Barbara

    2014-02-01

    The ion pairing is, in very dilute aqueous solutions, of rather small importance for solutions' properties, which renders its precise quantification quite a laborious task. Here we studied the ion pairing of alkali halides in water by using the precise electric conductivity measurements in dilute solutions, and in a wide temperature range. The low-concentration chemical model was used to analyze the results, and to estimate the association constant of different alkali halide salts. It has been shown that the association constant is related to the solubility of salts in water and produces a 'volcano relationship', when plotted against the difference between the free energy of hydration of the corresponding individual ions. The computer simulation, using the simple MB+dipole water model, were used to interprete the results, to find a microscopic basis for Collins' law of matching water affinities.

  12. 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

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

    Science.gov (United States)

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

    2017-10-01

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

  14. A Multivariate Time Series Method for Monte Carlo Reactor Analysis

    International Nuclear Information System (INIS)

    Taro Ueki

    2008-01-01

    A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor

  15. Monte Carlo simulation of nanowires of different metals and two-metal alloys.

    Science.gov (United States)

    Giménez, M C; Schmicker, Wolfgang

    2011-02-14

    Nanowires of different metals and two-metal alloys have been studied by means of canonical Monte Carlo simulations and the embedded atom method for the interatomic potentials. For nanowires of gold, a relatively stable three-atom-wide chain was observed. The presence of one-atom-wide linear atomic chains is not stable in any case. For two-metal alloy nanowires, the metal with a higher surface energy tends to locate in the inner region of the nanowire.

  16. TU-H-CAMPUS-IeP1-03: Comparison of Monte Carlo Simulation and Conversion Factor Based Method On Estimation of Effective Dose in Pediatric Patients Undergoing Interventional Cardiac Procedures

    International Nuclear Information System (INIS)

    Leung, K; Wong, M; Ng, Y; Lee, S; Ming Chun Chau, R; Lee, F

    2016-01-01

    Purpose: Interventional cardiac procedures utilize frequent fluoroscopy and cineangiography, which impose considerable radiation risk to patients, especially pediatric patients. Accurate calculation of effective dose is important in order to estimate cancer risk over the rest of their lifetime. This study evaluates the difference in effective dose calculated by Monte Carlo simulation with those estimated by locally-derived conversion factors (CF-local) and by commonly quoted conversion factors from Karambatsakidou et al (CF-K). Methods: Effective dose (E),of 12 pediatric patients, age between 2.5–19 years old, who had undergone interventional cardiac procedures, were calculated using PCXMC-2.0 software. Tube spectrum, irradiation geometry, exposure parameters and dose-area product (DAP) of each projection were included in the software calculation. Effective doses for each patient were also estimated by two Methods: 1) CF-local: conversion factor derived locally by generalizing results of 12 patients, multiplied by DAP of each patient gives E-local. 2) CF-K: selected factor from above-mentioned literature, multiplied by DAP of each patient gives E-K. Results: Mean of E, E-local and E-K were 16.01 mSv, 16.80 mSv and 22.25 mSv respectively. A deviation of −29.35% to +34.85% between E and E-local, while a greater deviation of −28.96% to +60.86% between E and EK were observed. E-K overestimated the effective dose for patients at age 7.5–19. Conclusion: Effective dose obtained by conversion factors is simple and quick to estimate radiation risk of pediatric patients. This study showed that estimation by CF-local may bear an error of 35% when compared with Monte Carlo calculation. If using conversion factors derived by other studies may result in an even greater error, of up to 60%, due to factors that are not catered for in the estimation, including patient size, projection angles, exposure parameters, tube filtration, etc. Users must be aware of these potential

  17. Analysis of the distribution of X-ray characteristic production using the Monte Carlo methods

    International Nuclear Information System (INIS)

    Del Giorgio, Marcelo; Brizuela, Horacio; Riveros, J.A.

    1987-01-01

    The Monte Carlo method has been applied for the simulation of electron trajectories in a bulk sample, and therefore for the distribution of signals produced in an electron microprobe. Results for the function φ(ρz) are compared with experimental data. Some conclusions are drawn with respect to the parameters involved in the gaussian model. (Author) [es

  18. A Hybrid Approach to Simulate X-Ray Imaging Techniques, Combining Monte Carlo and Deterministic Algorithms

    Science.gov (United States)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-10-01

    In this paper, we propose a hybrid approach to simulate multiple scattering of photons in objects under X-ray inspection, without recourse to parallel computing and without any approximation sacrificing accuracy. Photon scattering is considered from two points of view: it contributes to X-ray imaging and to the dose absorbed by the patient. The proposed hybrid approach consists of a Monte Carlo stage followed by a deterministic phase, thus taking advantage of the complementarity between these two methods. In the first stage, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Then this set of scattering events is used to compute the energy imparted to the detector, with a deterministic algorithm based on a "forced detection" scheme. Regarding dose evaluation, we propose to assess separately the energy deposited by direct radiation (using a deterministic algorithm) and by scattered radiation (using our hybrid approach). The results obtained in a test case are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the required detector resolution and statistics). It is possible to simulate radiographic images virtually free from photon noise. In the case of dose evaluation, the hybrid approach appears particularly suitable to calculate the dose absorbed by regions of interest (rather than the entire irradiated organ) with computation time and statistical fluctuations considerably reduced in comparison with conventional Monte Carlo simulation.

  19. Low cloud investigations for project FIRE: Island studies of cloud properties, surface radiation, and boundary layer dynamics. A simulation of the reflectivity over a stratocumulus cloud deck by the Monte Carlo method. M.S. Thesis Final Report

    Science.gov (United States)

    Ackerman, Thomas P.; Lin, Ruei-Fong

    1993-01-01

    The radiation field over a broken stratocumulus cloud deck is simulated by the Monte Carlo method. We conducted four experiments to investigate the main factor for the observed shortwave reflectively over the FIRE flight 2 leg 5, in which reflectivity decreases almost linearly from the cloud center to cloud edge while the cloud top height and the brightness temperature remain almost constant through out the clouds. From our results, the geometry effect, however, did not contribute significantly to what has been observed. We found that the variation of the volume extinction coefficient as a function of its relative position in the cloud affects the reflectivity efficiently. Additional check of the brightness temperature of each experiment also confirms this conclusion. The cloud microphysical data showed some interesting features. We found that the cloud droplet spectrum is nearly log-normal distributed when the clouds were solid. However, whether the shift of cloud droplet spectrum toward the larger end is not certain. The decrease of number density from cloud center to cloud edges seems to have more significant effects on the optical properties.

  20. Treatment planning for a small animal using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Chow, James C. L.; Leung, Michael K. K.

    2007-01-01

    The development of a small animal model for radiotherapy research requires a complete setup of customized imaging equipment, irradiators, and planning software that matches the sizes of the subjects. The purpose of this study is to develop and demonstrate the use of a flexible in-house research environment for treatment planning on small animals. The software package, called DOSCTP, provides a user-friendly platform for DICOM computed tomography-based Monte Carlo dose calculation using the EGSnrcMP-based DOSXYZnrc code. Validation of the treatment planning was performed by comparing the dose distributions for simple photon beam geometries calculated through the Pinnacle3 treatment planning system and measurements. A treatment plan for a mouse based on a CT image set by a 360-deg photon arc is demonstrated. It is shown that it is possible to create 3D conformal treatment plans for small animals with consideration of inhomogeneities using small photon beam field sizes in the diameter range of 0.5-5 cm, with conformal dose covering the target volume while sparing the surrounding critical tissue. It is also found that Monte Carlo simulation is suitable to carry out treatment planning dose calculation for small animal anatomy with voxel size about one order of magnitude smaller than that of the human

  1. 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)

  2. Pipeline integrity management using Monte Carlo simulation; A aplicacao do metodo de Monte Carlo no gerenciamento da integridade de dutos

    Energy Technology Data Exchange (ETDEWEB)

    Garcia, Claudio; Costa, Artur; Bittencourt, Euclides [TRANSPETRO - PETROBRAS Transporte, Rio de Janeiro, RJ (Brazil)

    2005-07-01

    Due to the growing relevance of safety and environmental protection policies in PETROBRAS and its subsidiaries, as well as official regulatory agencies and population requirements, integrity management of oil and gas pipelines became a priority activity in TRANSPETRO, involving several sectors of the company's Support Management Department. Inspection activities using intelligent PIGs, field correlations and replacement of pipeline segments are known as high cost operations and request complex logistics. Thus, it is imperative the adoption of management tools that optimize the available resources. This study presents Monte Carlo simulation method as an additional tool for evaluation and management of pipeline structural integrity. The method consists in foreseeing future physical conditions of most significant defects found in intelligent PIG In Line Inspections based on a probabilistic approach. Through Monte Carlo simulation, probability functions of failure for each defect are produced, helping managers to decide which repairs should be executed in order to reach the desired or accepted risk level. The case that illustrates this study refers to the reconditioning of ORSOL 14'' (35,56 mm) pipeline. This pipeline was constructed to transfer petroleum from Urucu's production fields to Solimoes port, in Coari, city in Brazilian Amazon Region. The result of this analysis indicated critical points for repair, in addition to the results obtained by the conventional evaluation (deterministic ASME B-31G method). Due to the difficulties to mobilize staff and execute necessary repairs in remote areas like Amazon forest, the probabilistic tool was extremely useful, improving pipeline integrity level and avoiding future additional costs. (author)

  3. A new method for studying the transport of gamma photons in various geological materials by combining the SSNTD technique with Monte Carlo simulations

    International Nuclear Information System (INIS)

    Misdaq, M.A.; Merzouki, A.; Bourzik, W.; Sfairi, T.

    2000-01-01

    The gamma dose rate due to the uranium and thorium series as well as the potassium 40 nuclei represents a large fraction of the total dose rate from the natural background. Natural gamma-activities of rock and soil samples collected from volcanic areas have been determined using gamma-ray spectrometry. The corresponding gamma dose rates in air have been measured by means of thermoluminescence (TL) dosimeters. Annual absorbed gamma dose rates have been evaluated in different soil samples belonging to an archaeological site by using experimental and calculational methods. Uranium and thorium contents in different geological samples have been determined by using CR-39 and LR-115 type II solid state nuclear track detectors (SSNTD) and calculating the probabilities for alpha particles emitted by the uranium and thorium series to reach and be registered on the SSNTD films. A new method has been developed based on calculating the self-absorption and transmission coefficients of the gamma photons emitted by the uranium and thorium families as well as the potassium 40 isotope for evaluating the gamma dose rate in the considered geological samples. Transport of gamma-photons across parallelepipedic blocks of the geological materials studied has been investigated. Gamma dose rates have been evaluated in the atmosphere of different geological deposits. (author)

  4. Monte Carlo simulation of lattice bosons in three dimensions

    International Nuclear Information System (INIS)

    Blaer, A.; Han, J.

    1992-01-01

    We present an algorithm for calculating the thermodynamic properties of a system of nonrelativistic bosons on a three-dimensional spatial lattice. The method, which maps the three-dimensional quantum system onto a four-dimensional classical system, uses Monte Carlo sampling of configurations in either the canonical or the grand canonical ensemble. Our procedure is applicable to any system of lattice bosons with arbitrary short-range interactions. We test the algorithm by computing the temperature dependence of the energy, the heat capacity, and the condensate fraction of the free Bose gas

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

    Energy Technology Data Exchange (ETDEWEB)

    Mahady, Kyle [Univ. of Tennessee, Knoxville, TN (United States); Tan, Shida [Intel Corp., Santa Clara, CA (United States); Greenzweig, Yuval [Intel Israel Ltd., Haifa (Israel); Livengood, Richard [Intel Corp., Santa Clara, CA (United States); Raveh, Amir [Intel Israel Ltd., Haifa (Israel); Fowlkes, Jason D. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rack, Philip [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-07-01

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

  6. Monte Carlo simulations for angular and spatial distributions in therapeutic-energy proton beams

    Science.gov (United States)

    Lin, Yi-Chun; Pan, C. Y.; Chiang, K. J.; Yuan, M. C.; Chu, C. H.; Tsai, Y. W.; Teng, P. K.; Lin, C. H.; Chao, T. C.; Lee, C. C.; Tung, C. J.; Chen, A. E.

    2017-11-01

    The purpose of this study is to compare the angular and spatial distributions of therapeutic-energy proton beams obtained from the FLUKA, GEANT4 and MCNP6 Monte Carlo codes. The Monte Carlo simulations of proton beams passing through two thin targets and a water phantom were investigated to compare the primary and secondary proton fluence distributions and dosimetric differences among these codes. The angular fluence distributions, central axis depth-dose profiles, and lateral distributions of the Bragg peak cross-field were calculated to compare the proton angular and spatial distributions and energy deposition. Benchmark verifications from three different Monte Carlo simulations could be used to evaluate the residual proton fluence for the mean range and to estimate the depth and lateral dose distributions and the characteristic depths and lengths along the central axis as the physical indices corresponding to the evaluation of treatment effectiveness. The results showed a general agreement among codes, except that some deviations were found in the penumbra region. These calculated results are also particularly helpful for understanding primary and secondary proton components for stray radiation calculation and reference proton standard determination, as well as for determining lateral dose distribution performance in proton small-field dosimetry. By demonstrating these calculations, this work could serve as a guide to the recent field of Monte Carlo methods for therapeutic-energy protons.

  7. Lattice gauge theory and Monte Carlo methods

    International Nuclear Information System (INIS)

    Creutz, M.

    1988-11-01

    Lattice gauge theory is now the primary non-perturbative technique for quantum field theory. The lattice represents an ultraviolet cutoff, and renormalization group arguments show how the bare coupling must be varied to obtain the continuum limit. Expansions in the inverse of the coupling constant demonstrate quark confinement in the strong coupling limit. Numerical simulation has become the approach to calculating hadronic properties. The basic algorithms for obtaining appropriately weighted gauge field configurations are discussed. Algorithms for treating fermionic fields, which still require considerably more computer time than needed for purely bosonic simulations, are also discussed. Some particularly promising recent approaches are based on global accept-reject steps and should display a rather favorable dependence of computer time on the system volume. 39 refs

  8. Monte Carlo methods for pricing financial options

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Now we discuss the antithetic variate method. Like the control variate method, it is very easy to implement in fairly general situations. It also combines well with other variance reduction techniques. The essential idea behind this method is straightforward. Consider two continuous random variables X1 and X2. The variance ...

  9. Application of Monte Carlo Method to Steady State Heat Conduction ...

    African Journals Online (AJOL)

    The Monte Carlo method was used in modelling steady state heat conduction problems. The method uses the fixed and the floating random walks to determine temperature in the domain of the definition of the heat conduction equation, at a single point directly. A heat conduction problem with an irregular shaped geometry ...

  10. Characterization of a cylindrical plastic β-detector with Monte Carlo simulations of optical photons

    Energy Technology Data Exchange (ETDEWEB)

    Guadilla, V., E-mail: victor.guadilla@ific.uv.es [Instituto de Física Corpuscular, CSIC-Universidad de Valencia, E-46071 Valencia (Spain); Algora, A. [Instituto de Física Corpuscular, CSIC-Universidad de Valencia, E-46071 Valencia (Spain); Institute of Nuclear Research of the Hungarian Academy of Sciences, Debrecen H-4026 (Hungary); Tain, J.L.; Agramunt, J. [Instituto de Física Corpuscular, CSIC-Universidad de Valencia, E-46071 Valencia (Spain); Äystö, J. [University of Jyvaskyla, Department of Physics, P.O. Box 35, FI-40014 (Finland); Briz, J.A.; Cucoanes, A. [Subatech, CNRS/IN2P3, Nantes, EMN, F-44307 Nantes (France); Eronen, T. [University of Jyvaskyla, Department of Physics, P.O. Box 35, FI-40014 (Finland); Estienne, M.; Fallot, M. [Subatech, CNRS/IN2P3, Nantes, EMN, F-44307 Nantes (France); Fraile, L.M. [Universidad Complutense, Grupo de Física Nuclear, CEI Moncloa, E-28040 Madrid (Spain); Ganioğlu, E. [Department of Physics, Istanbul University, 34134 Istanbul (Turkey); Gelletly, W. [Instituto de Física Corpuscular, CSIC-Universidad de Valencia, E-46071 Valencia (Spain); Department of Physics, University of Surrey, GU2 7XH Guildford (United Kingdom); Gorelov, D.; Hakala, J.; Jokinen, A. [University of Jyvaskyla, Department of Physics, P.O. Box 35, FI-40014 (Finland); Jordan, D. [Instituto de Física Corpuscular, CSIC-Universidad de Valencia, E-46071 Valencia (Spain); Kankainen, A.; Kolhinen, V.; Koponen, J. [University of Jyvaskyla, Department of Physics, P.O. Box 35, FI-40014 (Finland); and others

    2017-05-11

    In this work we report on the Monte Carlo study performed to understand and reproduce experimental measurements of a new plastic β-detector with cylindrical geometry. Since energy deposition simulations differ from the experimental measurements for such a geometry, we show how the simulation of production and transport of optical photons does allow one to obtain the shapes of the experimental spectra. Moreover, taking into account the computational effort associated with this kind of simulation, we develop a method to convert the simulations of energy deposited into light collected, depending only on the interaction point in the detector. This method represents a useful solution when extensive simulations have to be done, as in the case of the calculation of the response function of the spectrometer in a total absorption γ-ray spectroscopy analysis.

  11. Monte Carlo simulations of solid-state photoswitches

    Energy Technology Data Exchange (ETDEWEB)

    Rambo, P.W.; Denavit, J.

    1995-09-01

    Large increases in conductivity induced in GaAs and other semiconductors by photoionization allow fast switching by laser light with applications to pulse-power technology and microwave generation. Experiments have shown that under high-field conditions (10 to 50 kV/cm), conductivity may occur either in the linear mode where it is proportional to the absorbed light, in the {open_quotes}lock-on{close_quotes} mode, where it persists after termination of the laser pulse or in the avalanche mode where multiple carriers are generated. We have assembled a self-consistent Monte Carlo code to study these phenomena and in particular to model hot electron effects, which are expected to be important at high field strengths. This project has also brought our expertise acquired in advanced particle simulation of plasmas to bear on the modeling of semiconductor devices, which has broad industrial applications.

  12. Monte Carlo simulation to analyze the performance of CPV modules

    Science.gov (United States)

    Herrero, Rebeca; Antón, Ignacio; Sala, Gabriel; De Nardis, Davide; Araki, Kenji; Yamaguchi, Masafumi

    2017-09-01

    A model to evaluate the performance of high concentrator photovoltaics (HCPV) modules (that generates current-voltage curves) has been applied together with a Monte Carlo approach to obtain a distribution of modules with a given set of characteristics (e.g., receivers electrical properties and misalignments within elementary units in modules) related to a manufacturing scenario. In this paper, the performance of CPV systems (tracker and inverter) that contain the set of simulated modules is evaluated depending on different system characteristics: inverter configuration, sorting of modules and bending of the tracker frame. Thus, the study of the HCPV technology regarding its angular constrains is fully covered by analyzing all the possible elements affecting the generated electrical power.

  13. Monte Carlo simulation of ionization in a magnetron plasma

    International Nuclear Information System (INIS)

    Miranda, J.E.; Goeckner, M.J.; Goree, J.; Sheridan, T.E.

    1990-01-01

    A Monte Carlo simulation of electrons emitted from the cathode of a planar magnetron is tested against experiments that were reported by Wendt, Lieberman, and Meuth [J. Vac. Sci. Technol. A 6, 1827 (1988)] and by Gu and Lieberman [J. Vac. Sci. Technol. A 6, 2960 (1988)]. Comparing their measurements of the radial profile of current and the axial profile of optical emission to the ionization profiles predicted by the model, we find good agreement for a typical magnetic field strength of 456 G. We also find that at 456 G the product of the average number of ionizations left-angle N i right-angle and the secondary electron emission coefficient γ is ∼1. This indicates that secondary emission contributes significantly to the ionization that sustains the discharge. At 171 G, however, left-angle N i right-angle γ much-lt 1, revealing that cathode emission is inadequate to sustain a discharge at a low magnetic field

  14. Monte Carlo simulation of magnetic multi-core nanoparticles

    International Nuclear Information System (INIS)

    Schaller, Vincent; Wahnstroem, Goeran; Sanz-Velasco, Anke; Enoksson, Peter; Johansson, Christer

    2009-01-01

    In this paper, a Monte Carlo simulation is carried out to evaluate the equilibrium magnetization of magnetic multi-core nanoparticles in a liquid and subjected to a static magnetic field. The particles contain a magnetic multi-core consisting of a cluster of magnetic single-domains of magnetite. We show that the magnetization of multi-core nanoparticles cannot be fully described by a Langevin model. Inter-domain dipolar interactions and domain magnetic anisotropy contribute to decrease the magnetization of the particles, whereas the single-domain size distribution yields an increase in magnetization. Also, we show that the interactions affect the effective magnetic moment of the multi-core nanoparticles.

  15. Monte Carlo Simulations of Background Spectra in Integral Imager Detectors

    Science.gov (United States)

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

    1998-01-01

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

  16. Monte Carlo Form-Finding Method for Tensegrity Structures

    Science.gov (United States)

    Li, Yue; Feng, Xi-Qiao; Cao, Yan-Ping

    2010-05-01

    In this paper, we propose a Monte Carlo-based approach to solve tensegrity form-finding problems. It uses a stochastic procedure to find the deterministic equilibrium configuration of a tensegrity structure. The suggested Monte Carlo form-finding (MCFF) method is highly efficient because it does not involve complicated matrix operations and symmetry analysis and it works for arbitrary initial configurations. Both regular and non-regular tensegrity problems of large scale can be solved. Some representative examples are presented to demonstrate the efficiency and accuracy of this versatile method.

  17. Characterization of parallel-hole collimator using Monte Carlo Simulation

    International Nuclear Information System (INIS)

    Pandey, Anil Kumar; Sharma, Sanjay Kumar; Karunanithi, Sellam; Kumar, Praveen; Bal, Chandrasekhar; Kumar, Rakesh

    2015-01-01

    Accuracy of in vivo activity quantification improves after the correction of penetrated and scattered photons. However, accurate assessment is not possible with physical experiment. We have used Monte Carlo Simulation to accurately assess the contribution of penetrated and scattered photons in the photopeak window. Simulations were performed with Simulation of Imaging Nuclear Detectors Monte Carlo Code. The simulations were set up in such a way that it provides geometric, penetration, and scatter components after each simulation and writes binary images to a data file. These components were analyzed graphically using Microsoft Excel (Microsoft Corporation, USA). Each binary image was imported in software (ImageJ) and logarithmic transformation was applied for visual assessment of image quality, plotting profile across the center of the images and calculating full width at half maximum (FWHM) in horizontal and vertical directions. The geometric, penetration, and scatter at 140 keV for low-energy general-purpose were 93.20%, 4.13%, 2.67% respectively. Similarly, geometric, penetration, and scatter at 140 keV for low-energy high-resolution (LEHR), medium-energy general-purpose (MEGP), and high-energy general-purpose (HEGP) collimator were (94.06%, 3.39%, 2.55%), (96.42%, 1.52%, 2.06%), and (96.70%, 1.45%, 1.85%), respectively. For MEGP collimator at 245 keV photon and for HEGP collimator at 364 keV were 89.10%, 7.08%, 3.82% and 67.78%, 18.63%, 13.59%, respectively. Low-energy general-purpose and LEHR collimator is best to image 140 keV photon. HEGP can be used for 245 keV and 364 keV; however, correction for penetration and scatter must be applied if one is interested to quantify the in vivo activity of energy 364 keV. Due to heavy penetration and scattering, 511 keV photons should not be imaged with HEGP collimator

  18. Monte Carlo radiative transfer simulation of a cavity solar reactor for the reduction of cerium oxide

    Energy Technology Data Exchange (ETDEWEB)

    Villafan-Vidales, H.I.; Arancibia-Bulnes, C.A.; Dehesa-Carrasco, U. [Centro de Investigacion en Energia, Universidad Nacional Autonoma de Mexico, Privada Xochicalco s/n, Col. Centro, A.P. 34, Temixco, Morelos 62580 (Mexico); Romero-Paredes, H. [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco No.186, Col. Vicentina, A.P. 55-534, Mexico D.F 09340 (Mexico)

    2009-01-15

    Radiative heat transfer in a solar thermochemical reactor for the thermal reduction of cerium oxide is simulated with the Monte Carlo method. The directional characteristics and the power distribution of the concentrated solar radiation that enters the cavity is obtained by carrying out a Monte Carlo ray tracing of a paraboloidal concentrator. It is considered that the reactor contains a gas/particle suspension directly exposed to concentrated solar radiation. The suspension is treated as a non-isothermal, non-gray, absorbing, emitting, and anisotropically scattering medium. The transport coefficients of the particles are obtained from Mie-scattering theory by using the optical properties of cerium oxide. From the simulations, the aperture radius and the particle concentration were optimized to match the characteristics of the considered concentrator. (author)

  19. 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)

  20. Probability-neighbor method of accelerating geometry treatment in reactor Monte Carlo code RMC

    International Nuclear Information System (INIS)

    She, Ding; Li, Zeguang; Xu, Qi; Wang, Kan; Yu, Ganglin

    2011-01-01

    Probability neighbor method (PNM) is proposed in this paper to accelerate geometry treatment of Monte Carlo (MC) simulation and validated in self-developed reactor Monte Carlo code RMC. During MC simulation by either ray-tracking or delta-tracking method, large amounts of time are spent in finding out which cell one particle is located in. The traditional way is to search cells one by one with certain sequence defined previously. However, this procedure becomes very time-consuming when the system contains a large number of cells. Considering that particles have different probability to enter different cells, PNM method optimizes the searching sequence, i.e., the cells with larger probability are searched preferentially. The PNM method is implemented in RMC code and the numerical results show that the considerable time of geometry treatment in MC calculation for complicated systems is saved, especially effective in delta-tracking simulation. (author)

  1. Monte carlo simulation of carboxylic acid phase equilibria.

    Science.gov (United States)

    Clifford, Scott; Bolton, Kim; Ramjugernath, Deresh

    2006-11-02

    Configurational-bias Monte Carlo simulations were carried out in the Gibbs ensemble to generate phase equilibrium data for several carboxylic acids. Pure component coexistence densities and saturated vapor pressures were determined for acetic acid, propanoic acid, 2-methylpropanoic acid, and pentanoic acid, and binary vapor-liquid equilibrium (VLE) data for the propanoic acid + pentanoic acid and 2-methylpropanoic acid + pentanoic acid systems. The TraPPE-UA force field was used, as it has recently been extended to include parameters for carboxylic acids. To simulate the branched compound 2-methylpropanoic acid, certain minor assumptions were necessary regarding angle and torsion terms involving the -CH- pseudo-atom, since parameters for these terms do not exist in the TraPPE-UA force field. The pure component data showed good agreement with the available experimental data, particularly with regard to the saturated liquid densities (mean absolute errors were less than 1.1%). On average, the predicted critical temperature and density were within 1% of the experimental values. All of the binary simulations showed good agreement with the experimental x-y data. However, the TraPPE-UA force field predicts saturated vapor pressures of pure components that are larger than the experimental values, and consequently the P-x-y and T-x-y data of the binary systems also deviate from the measured data.

  2. Fast Monte Carlo for ion beam analysis simulations

    International Nuclear Information System (INIS)

    Schiettekatte, Francois

    2008-01-01

    A Monte Carlo program for the simulation of ion beam analysis data is presented. It combines mainly four features: (i) ion slowdown is computed separately from the main scattering/recoil event, which is directed towards the detector. (ii) A virtual detector, that is, a detector larger than the actual one can be used, followed by trajectory correction. (iii) For each collision during ion slowdown, scattering angle components are extracted form tables. (iv) Tables of scattering angle components, stopping power and energy straggling are indexed using the binary representation of floating point numbers, which allows logarithmic distribution of these tables without the computation of logarithms to access them. Tables are sufficiently fine-grained that interpolation is not necessary. Ion slowdown computation thus avoids trigonometric, inverse and transcendental function calls and, as much as possible, divisions. All these improvements make possible the computation of 10 7 collisions/s on current PCs. Results for transmitted ions of several masses in various substrates are well comparable to those obtained using SRIM-2006 in terms of both angular and energy distributions, as long as a sufficiently large number of collisions is considered for each ion. Examples of simulated spectrum show good agreement with experimental data, although a large detector rather than the virtual detector has to be used to properly simulate background signals that are due to plural collisions. The program, written in standard C, is open-source and distributed under the terms of the GNU General Public License

  3. 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.

  4. Monte-Carlo simulation of a stochastic differential equation

    Science.gov (United States)

    Arif, ULLAH; Majid, KHAN; M, KAMRAN; R, KHAN; Zhengmao, SHENG

    2017-12-01

    For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient, Monte Carlo (MC) techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem. Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

  5. Calculation of ion stopping in dense plasma by the Monte-Carlo method

    Science.gov (United States)

    Kodanova, S. K.; Ramazanov, T. S.; Issanova, M. K.; Bastykova, N. Kh; Golyatina, R. I.; Maiorov, S. A.

    2018-01-01

    In this paper, the Monte-Carlo method was used to simulate ion trajectories in dense plasma of inertial confinement fusion. The results of computer simulation are numerical data on the dynamic characteristics, such as energy loss, penetration depth, the effective range of particles, stopping and straggling. By the results of the work the program of three-dimensional visualization of ion trajectories in dense plasma of inertial confinement fusion was developed.

  6. R and D on automatic modeling methods for Monte Carlo codes FLUKA

    International Nuclear Information System (INIS)

    Wang Dianxi; Hu Liqin; Wang Guozhong; Zhao Zijia; Nie Fanzhi; Wu Yican; Long Pengcheng

    2013-01-01

    FLUKA is a fully integrated particle physics Monte Carlo simulation package. It is necessary to create the geometry models before calculation. However, it is time- consuming and error-prone to describe the geometry models manually. This study developed an automatic modeling method which could automatically convert computer-aided design (CAD) geometry models into FLUKA models. The conversion program was integrated into CAD/image-based automatic modeling program for nuclear and radiation transport simulation (MCAM). Its correctness has been demonstrated. (authors)

  7. Strings, Projected Entangled Pair States, and variational Monte Carlo methods

    OpenAIRE

    Schuch, Norbert; Wolf, Michael M.; Verstraete, Frank; Cirac, J. Ignacio

    2007-01-01

    We introduce string-bond states, a class of states obtained by placing strings of operators on a lattice, which encompasses the relevant states in Quantum Information. For string-bond states, expectation values of local observables can be computed efficiently using Monte Carlo sampling, making them suitable for a variational abgorithm which extends DMRG to higher dimensional and irregular systems. Numerical results demonstrate the applicability of these states to the simulation of many-body s...

  8. CAD-based Monte Carlo Program for Integrated Simulation of Nuclear System SuperMC

    Science.gov (United States)

    Wu, Yican; Song, Jing; Zheng, Huaqing; Sun, Guangyao; Hao, Lijuan; Long, Pengcheng; Hu, Liqin

    2014-06-01

    Monte Carlo (MC) method has distinct advantages to simulate complicated nuclear systems and is envisioned as routine method for nuclear design and analysis in the future. High fidelity simulation with MC method coupled with multi-physical phenomenon simulation has significant impact on safety, economy and sustainability of nuclear systems. However, great challenges to current MC methods and codes prevent its application in real engineering project. SuperMC is a CAD-based Monte Carlo program for integrated simulation of nuclear system developed by FDS Team, China, making use of hybrid MC-deterministic method and advanced computer technologies. The design aim, architecture and main methodology of SuperMC were presented in this paper. SuperMC2.1, the latest version for neutron, photon and coupled neutron and photon transport calculation, has been developed and validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model. SuperMC is still in its evolution process toward a general and routine tool for nuclear system. Warning, no authors found for 2014snam.conf06023.

  9. 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.

  10. Kinetic Monte Carlo simulation of formation of microstructures in liquid droplets

    International Nuclear Information System (INIS)

    Block, M; Kunert, R; Schoell, E; Boeck, T; Teubner, Th

    2004-01-01

    We study the deposition of indium droplets on a glass surface and the subsequent formation of silicon microcrystals inside these droplets. Kinetic Monte Carlo methods are used to analyse the influence of growth temperature, flux of incoming particles, surface coverage, and in particular an energy parameter simulating the surface tension, upon the morphology of growth. According to the experimental conditions of crystallization, a temperature gradient and diffusion in spherical droplets are included. The simulations explain the formation of silicon crystal structures in good agreement with the experiment. The dependence of their shape and the conditions of formation on the growth parameters are investigated in detail

  11. Monte Carlo simulation of radiative heat transfer in coarse fibrous media

    Energy Technology Data Exchange (ETDEWEB)

    Nisipeanu, E.; Jones, P.D.

    1999-07-01

    Radiative transfer through a medium made up of a multitude of randomly oriented opaque cylindrical fibers is examined using Monte Carlo simulation of multiple surface radiative exchange for energy bundles interacting with each fiber in their path. The method is termed Monte Carlo Discontinuous Medium (MCDM). As compared to radiative continuum methods, the present approach does not require specification of extinction coefficient, scattering albedo, or scattering phase function. Instead, only volume fraction, fiber diameter, and fiber material complex index of refraction are required as parameters. Although the MCDM method is only strictly valid for the geometric limit, comparison with previous experiments on the edge of this limit (5 {lt} x {lt} 11) is qualitatively good. For the low (solid) volume fractions considered here, comparison is excellent between MCDM results and radiative continuum results, the later being solved by both Monte Carlo simulation and by exact integral solution of the Radiative Transfer Equation (RTE). MCDM results show a sensitivity to directional bias of the fibers in the medium, suggesting that bias parameters are necessary to solve radiative transfer in media with non-random fiber orientations. MCDM results for fibrous media are very similar to those for spherical suspensions at the same volume fraction and scatterer diameter, suggesting that the precise shape of a scattering particle may be relatively less important for radiation heat transfer through randomly oriented solid matrix materials.

  12. Spatial distribution of reflected gamma rays by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Jehouani, A.; Merzouki, A.; Boutadghart, F.; Ghassoun, J.

    2007-01-01

    In nuclear facilities, the reflection of gamma rays of the walls and metals constitutes an unknown origin of radiation. These reflected gamma rays must be estimated and determined. This study concerns reflected gamma rays on metal slabs. We evaluated the spatial distribution of the reflected gamma rays spectra by using the Monte Carlo method. An appropriate estimator for the double differential albedo is used to determine the energy spectra and the angular distribution of reflected gamma rays by slabs of iron and aluminium. We took into the account the principal interactions of gamma rays with matter: photoelectric, coherent scattering (Rayleigh), incoherent scattering (Compton) and pair creation. The Klein-Nishina differential cross section was used to select direction and energy of scattered photons after each Compton scattering. The obtained spectra show peaks at 0.511 * MeV for higher source energy. The Results are in good agreement with those obtained by the TRIPOLI code [J.C. Nimal et al., TRIPOLI02: Programme de Monte Carlo Polycinsetique a Trois dimensions, CEA Rapport, Commissariat a l'Energie Atomique.

  13. An Overview of the Monte Carlo Methods, Codes, & Applications Group

    Energy Technology Data Exchange (ETDEWEB)

    Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-08-30

    This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.

  14. 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

  15. 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

  16. 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.)

  17. Monte Carlo simulation for dual head gamma camera

    International Nuclear Information System (INIS)

    Osman, Yousif Bashir Soliman

    2015-12-01

    Monte Carlo (MC) simulation technique was used widely in medical physics applications. In nuclear medicine MC was used to design new medical imaging devices such as positron emission tomography (PET), gamma camera and single photon emission computed tomography (SPECT). Also it can be used to study the factors affecting image quality and internal dosimetry, Gate is on of monte Carlo code that has a number of advantages for simulation of SPECT and PET. There is a limit accessibilities in machines which are used in clinics because of the work load of machines. This makes it hard to evaluate some factors effecting machine performance which must be evaluated routinely. Also because of difficulties of carrying out scientific research and training of students, MC model can be optimum solution for the problem. The aim of this study was to use gate monte Carlo code to model Nucline spirit, medico dual head gamma camera hosted in radiation and isotopes center of Khartoum which is equipped with low energy general purpose LEGP collimators. This was used model to evaluate spatial resolution and sensitivity which is important factor affecting image quality and to demonstrate the validity of gate by comparing experimental results with simulation results on spatial resolution. The gate model of Nuclide spirit, medico dual head gamma camera was developed by applying manufacturer specifications. Then simulation was run. In evaluation of spatial resolution the FWHM was calculated from image profile of line source of Tc 99m gammas emitter of energy 140 KeV at different distances from modeled camera head at 5,10,15,20,22,27,32,37 cm and for these distances the spatial resolution was founded to be 5.76, 7.73, 10.7, 13.8, 14.01,16.91, 19.75 and 21.9 mm, respectively. These results showed a decrement of spatial resolution with increase of the distance between object (line source) and collimator in linear manner. FWHM calculated at 10 cm was compared with experimental results. The

  18. Monte Carlo simulation of beta particle-induced bremsstrahlung doses.

    Science.gov (United States)

    Mrdja, D; Bikit, K; Bikit, I; Slivka, J; Forkapic, S; Knezevic, J

    2018-03-01

    It is well known that protection from the external irradiation produced by beta emitters is simpler than the corresponding shielding of radioactive sources that emit gamma radiation. This is caused by the relatively strong absorption (i.e. short range) of electrons in different materials. However, for strong beta sources specific attention should be paid to the bremsstrahlung radiation induced in the source encapsulation (matrix), especially for emitters with relatively high beta-endpoint energy (1 MeV) that are frequently used in nuclear medicine. In the present work, the bremsstrahlung spectra produced in various materials by the following beta emitters, Sr-90 (together with its daughter Y-90), P-32 and Bi-210, were investigated by Monte Carlo simulations using Geant4 software. In these simulations, it is supposed that the point radioactive sources are surrounded by cylindrically shaped capsules made from different materials: Pb, Cu, Al, glass and plastic. For the case of Y-90(Sr-90) in cylindrical lead and aluminum capsules, the dimensions of these capsules have also been varied. The absorbed dose rates from bremsstrahlung radiation were calculated for cases where the encapsulated point source is placed at a distance of 30 mm from the surface of a water cylinder with a mass of 75 kg (approximately representing the human body). The bremsstrahlung dose rate and bremsstrahlung spectrum from the Y-90(Sr-90) point source encapsulated in an Al capsule were also measured experimentally and compared with the corresponding simulation results. In addition, the bremsstrahlung radiation risk for medical staff in therapies using Y-90 was considered in simulations, relating to finger dose as well as whole-body dose during preparation and injection of this radioisotope. The corresponding annual doses were obtained for medical workers for specified numbers of Y-90 applications to patients.

  19. Electric field Monte Carlo simulation of polarized light propagation in turbid media.

    Science.gov (United States)

    Xu, Min

    2004-12-27

    A Monte Carlo method based on tracing the multiply scattered electric field is presented to simulate the propagation of polarized light in turbid media. Multiple scattering of light comprises a series of updates of the parallel and perpendicular components of the complex electric field with respect to the scattering plane by the amplitude scattering matrix and rotations of the local coordinate system spanned by the unit vectors in the directions of the parallel and perpendicular electric field components and the propagation direction of light. The backscattering speckle pattern and the backscattering Mueller matrix of an aqueous suspension of polystyrene spheres in a slab geometry are computed using this Electric Field Monte Carlo (EMC) method. An efficient algorithm computing the Mueller matrix in the pure backscattering direction is detailed in the paper.

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

    Science.gov (United States)

    Baes, M.; Camps, P.

    2015-09-01

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

  1. Improved Monte Carlo methods for fermions

    International Nuclear Information System (INIS)

    DeGrand, T.A.; Dreitlein, J.; Toms, D.J.

    1983-01-01

    We describe an improved version of the Kuti-Von Neumann-Ulam algorithm useful for fermion contributions in lattice field theories. This is done by sampling the Neumann series for the propagator, which may be thought of as a sum over a set of weighted paths between two points on the lattice. Rather than selecting paths by a locally determined random walk, we average over sets of paths globally preselected for their importance in evaluating the few needed elements of the inverse. We also describe a method for the calculation of ratios of fermion determinants which is considerably less time consuming than the conventional one. (orig.)

  2. Parallelization of a Monte Carlo particle transport simulation code

    Science.gov (United States)

    Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.

    2010-05-01

    We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.

  3. Monte Carlo dose simulation of 192IR wires in tissue inhomogeneites

    International Nuclear Information System (INIS)

    Sanchez-Reyes, A.; Salvat, F.; Rovirosa, A.; Varea, JM Fernandez

    1996-01-01

    AIM: Study of the effect of tissue inhomogeneities on the dose delivered by 192 Ir wire using Monte Carlo simulation. MATERIAL AND METHODS: The Monte Carlo code PENELOPE is used to calculate radial dose distributions (scored on the symetry plane) produced by straight 192 Ir wires of different lengths (from 2 to 10 cm). PENELOPE is a self-contained simulation package for electron-photon transport, developed at the University of Barcelona. It is written in standard FORTRAN 77 and runs on virtually every computer. The present simulation have been performed on a 100 MHz PENTIUM. Typical running times were of the order of two days and involved the generation of about 7 million photon histories. Such large population were generated to ensure high statistical accuracy. Firstly, simulations were performed for water, and the results were compared with data available in the bibliography. Subsequently, the program was run for various tissues (bone, lung), and the effect of inhomogeneities was studied for geometries consisting of separate regions with different compositions (tissues, water and air). RESULTS: Good agreement between our simulation in water and data reported in the literature is found. Radial doses for water and lung not differ significantly. Separate regions with different compositions produce significant differences with simulation in water

  4. Monte-Carlo simulation and microdosimetry analysis of an α-particle source for cell irradiation

    International Nuclear Information System (INIS)

    Belchior, A.; Teles, P.; Vaz, P.; Peralta, L.; Almeida, P.

    2010-01-01

    The application of Monte Carlo methods to microdosimetry is an open issue. We used the MCNPX Monte Carlo code for the assessment of several physical parameters of relevance in microdosimetry. These parameters, such as dose distribution and linear energy transfer are evaluated through the irradiation of a cell-monolayer. In this work, we report on the computational results obtained for energy and linear energy and transfer (LET) spectra in a monolayer. These results were obtained using MCNPX and compared to the results obtained with the Stopping and Range of Ions in Matter (SRIM), a computational tool that solves the transport equation of alpha particles using analytical methods. The simulation results were compared to experimental data. In order to do this, we used an experimental setup consisting of an α-particle irradiator using a 210 Po radioactive source was calibrated using a barrier surface detector of Si(Li) under specific conditions, for cell irradiation. A Monte-Carlo model of the experimental setup was implemented using MCNPX. In order to perform a detailed and realistic simulation, all the experimental conditions were taken into account. The main challenges of this simulation arise from the geometry of the experimental setup which involves different layers of materials with micrometric thickness, imposing stringent requirements on the tracking of the α-particles at the micrometer level. Also, the use of biological material means that many additional parameters, such as tissue non-homogeneity, must be taken into account. Monte-Carlo results are in good agreement with experimental data. Sources of discrepancy between the computational results and measurements are analyzed. (author)

  5. 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.

  6. 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)

  7. Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

    Science.gov (United States)

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

    2018-02-01

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

  8. Dosimetry in radiotherapy and brachytherapy by Monte-Carlo GATE simulation on computing grid; Dosimetrie en radiotherapie et curietherapie par simulation Monte-Carlo GATE sur grille informatique

    Energy Technology Data Exchange (ETDEWEB)

    Thiam, Ch.O

    2007-10-15

    Accurate radiotherapy treatment requires the delivery of a precise dose to the tumour volume and a good knowledge of the dose deposit to the neighbouring zones. Computation of the treatments is usually carried out by a Treatment Planning System (T.P.S.) which needs to be precise and fast. The G.A.T.E. platform for Monte-Carlo simulation based on G.E.A.N.T.4 is an emerging tool for nuclear medicine application that provides functionalities for fast and reliable dosimetric calculations. In this thesis, we studied in parallel a validation of the G.A.T.E. platform for the modelling of electrons and photons low energy sources and the optimized use of grid infrastructures to reduce simulations computing time. G.A.T.E. was validated for the dose calculation of point kernels for mono-energetic electrons and compared with the results of other Monte-Carlo studies. A detailed study was made on the energy deposit during electrons transport in G.E.A.N.T.4. In order to validate G.A.T.E. for very low energy photons (<35 keV), three models of radioactive sources used in brachytherapy and containing iodine 125 (2301 of Best Medical International; Symmetra of Uro- Med/Bebig and 6711 of Amersham) were simulated. Our results were analyzed according to the recommendations of task group No43 of American Association of Physicists in Medicine (A.A.P.M.). They show a good agreement between G.A.T.E., the reference studies and A.A.P.M. recommended values. The use of Monte-Carlo simulations for a better definition of the dose deposited in the tumour volumes requires long computing time. In order to reduce it, we exploited E.G.E.E. grid infrastructure where simulations are distributed using innovative technologies taking into account the grid status. Time necessary for the computing of a radiotherapy planning simulation using electrons was reduced by a factor 30. A Web platform based on G.E.N.I.U.S. portal was developed to make easily available all the methods to submit and manage G

  9. High-speed evaluation of track-structure Monte Carlo electron transport simulations.

    Science.gov (United States)

    Pasciak, A S; Ford, J R

    2008-10-07

    There are many instances where Monte Carlo simulation using the track-structure method for electron transport is necessary for the accurate analytical computation and estimation of dose and other tally data. Because of the large electron interaction cross-sections and highly anisotropic scattering behavior, the track-structure method requires an enormous amount of computation time. For microdosimetry, radiation biology and other applications involving small site and tally sizes, low electron energies or high-Z/low-Z material interfaces where the track-structure method is preferred, a computational device called a field-programmable gate array (FPGA) is capable of executing track-structure Monte Carlo electron-transport simulations as fast as or faster than a standard computer can complete an identical simulation using the condensed history (CH) technique. In this paper, data from FPGA-based track-structure electron-transport computations are presented for five test cases, from simple slab-style geometries to radiation biology applications involving electrons incident on endosteal bone surface cells. For the most complex test case presented, an FPGA is capable of evaluating track-structure electron-transport problems more than 500 times faster than a standard computer can perform the same track-structure simulation and with comparable accuracy.

  10. Latent uncertainties of the precalculated track Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Renaud, Marc-André; Seuntjens, Jan [Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4 (Canada); Roberge, David [Département de radio-oncologie, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec H2L 4M1 (Canada)

    2015-01-15

    Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of

  11. Determination of in-process limits during parenteral solution manufacturing using Monte Carlo Simulation.

    Science.gov (United States)

    Kuu, Wei Y; Chilamkurti, Rao

    2003-01-01

    The purpose of this study is to utilize Monte Carlo Simulation methodology to determine the in-process limits for the parenteral solution manufacturing process. The Monte Carlo Simulation predicts the distribution of a dependable variable (such as drug concentration) in a naturally occurring process through random value generation considering the variability associated with the depended variable. The propagation of variation in drug concentration from batch to batch is cascading in nature during the following four formulation steps: 1) determination of drug raw material potency (or purity), 2) weighing of drug raw material, 3) measurement of batch volume, and 4) determination of drug concentration in the mix tank. The coefficients of variation for these four steps are denoted as CV1, CV2, CV3, and CV4, respectively. The Monte Carlo Simulation was performed for each of the above four cascading steps. The results of the simulation demonstrate that the in-process limits of the drug can be successfully determined using the Monte Carlo Simulation. Once the specification limits are determined, the Monte Carlo Simulation can be used to study the effect of each variability on the percent out of specification limits (OOL) for the in-process testing. Demonstrations were performed using the acceptance criterion of less than 5% of OOL batches, and the typical values of CV2 and CV3 being equal to 0.03% and 0.5%, respectively. The results show that for the in-process limits of +/- 1%, the values of CV1 and CV4 should not be greater than 0.1%. These assay requirements appear to be difficult to achieve for a given chemical analytical method. By comparison, for the In-process limits of +/- 4%, the requirements are much easier to achieve. The values of CV1 and CV4 should not be greater than 1.38%. In addition, the relationship between the percent OOL versus CV1 or CV4 is nonlinear per se. The number of OOL batches increases rapidly with increasing variability of CV1 or CV4.

  12. 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.

  13. A separable shadow Hamiltonian hybrid Monte Carlo method

    Science.gov (United States)

    Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.

    2009-11-01

    Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).

  14. Parallelism in continuous energy Monte Carlo method for neutron transport

    Energy Technology Data Exchange (ETDEWEB)

    Uenohara, Yuji (Nuclear Engineering Lab., Toshiba Corp. (Japan))

    1993-04-01

    The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)

  15. Parallelism in continuous energy Monte Carlo method for neutron transport

    International Nuclear Information System (INIS)

    Uenohara, Yuji

    1993-01-01

    The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)

  16. GATE Monte Carlo simulation of dose distribution using MapReduce in a cloud computing environment.

    Science.gov (United States)

    Liu, Yangchuan; Tang, Yuguo; Gao, Xin

    2017-12-01

    The GATE Monte Carlo simulation platform has good application prospects of treatment planning and quality assurance. However, accurate dose calculation using GATE is time consuming. The purpose of this study is to implement a novel cloud computing method for accurate GATE Monte Carlo simulation of dose distribution using MapReduce. An Amazon Machine Image installed with Hadoop and GATE is created to set up Hadoop clusters on Amazon Elastic Compute Cloud (EC2). Macros, the input files for GATE, are split into a number of self-contained sub-macros. Through Hadoop Streaming, the sub-macros are executed by GATE in Map tasks and the sub-results are aggregated into final outputs in Reduce tasks. As an evaluation, GATE simulations were performed in a cubical water phantom for X-ray photons of 6 and 18 MeV. The parallel simulation on the cloud computing platform is as accurate as the single-threaded simulation on a local server and the simulation correctness is not affected by the failure of some worker nodes. The cloud-based simulation time is approximately inversely proportional to the number of worker nodes. For the simulation of 10 million photons on a cluster with 64 worker nodes, time decreases of 41× and 32× were achieved compared to the single worker node case and the single-threaded case, respectively. The test of Hadoop's fault tolerance showed that the simulation correctness was not affected by the failure of some worker nodes. The results verify that the proposed method provides a feasible cloud computing solution for GATE.

  17. Modelling of an industrial environment, part 1.: Monte Carlo simulations of photon transport

    International Nuclear Information System (INIS)

    Kis, Z.; Eged, K.; Meckbach, R.; Voigt, G.

    2002-01-01

    After a nuclear accident releasing radioactive material into the environment the external exposures may contribute significantly to the radiation exposure of the population (UNSCEAR 1988, 2000). For urban populations the external gamma exposure from radionuclides deposited on the surfaces of the urban-industrial environments yields the dominant contributions to the total dose to the public (Kelly 1987; Jacob and Meckbach 1990). The radiation field is naturally influenced by the environment around the sources. For calculations of the shielding effect of the structures in complex and realistic urban environments Monte Carlo methods turned out to be useful tools (Jacob and Meckbach 1987; Meckbach et al. 1988). Using these methods a complex environment can be set up in which the photon transport can be solved on a reliable way. The accuracy of the methods is in principle limited only by the knowledge of the atomic cross sections and the computational time. Several papers using Monte Carlo results for calculating doses from the external gamma exposures were published (Jacob and Meckbach 1987, 1990; Meckbach et al. 1988; Rochedo et al. 1996). In these papers the Monte Carlo simulations were run in urban environments and for different photon energies. The industrial environment can be defined as such an area where productive and/or commercial activity is carried out. A good example can be a factory or a supermarket. An industrial environment can rather be different from the urban ones as for the types and structures of the buildings and their dimensions. These variations will affect the radiation field of this environment. Hence there is a need to run new Monte Carlo simulations designed specially for the industrial environments

  18. PENELOPE-2008 Monte Carlo simulation of gamma exposure induced by 60Co and NORM-radionuclides in closed geometries

    International Nuclear Information System (INIS)

    Merk, R.; Kröger, H.; Edelhäuser-Hornung, L.; Hoffmann, B.

    2013-01-01

    We present Monte Carlo simulations of the gamma exposure in closed rooms made of steel or concrete and contaminated by 60 Co or NORM radionuclides. The computer code PENELOPE-2008 (Salvat et al., 2009) was used. Our simulations for 60 Co suggest considering detailed Monte Carlo simulations in future recommendations on clearance and exemption of materials with low radioactivity. For NORM nuclides our calculations suggest that Monte Carlo simulations are a possible alternative in case a material fails the dose rate criteria by using the RP 112 screening method. - Highlights: • PENELOPE-2008 was used for Monte Carlo simulations of gamma exposure in closed rooms made of steel or concrete. • Findings support introducing IAEA SR 44 activity concentration value of 0.1 Bq/g as exemption value for 60 Co. • PENELOPE-2008 calculations show good agreement with a density corrected Berger model for dose rate calculations concerning NORM building materials. • Monte Carlo calculations or a density corrected Berger model could be used to modify the model suggested in RP 112

  19. Iterative Determination of Distributions by the Monte Carlo Method in Problems with an External Source

    OpenAIRE

    Makai, Mihály; Szatmáry, Zoltán

    2013-01-01

    In the Monte Carlo (MC) method statistical noise is usually present. Statistical noise may become dominant in the calculation of a distribution, usually by iteration, but is less Important in calculating integrals. The subject of the present work is the role of statistical noise in iterations involving stochastic simulation (MC method). Convergence is checked by comparing two consecutive solutions in the iteration. The statistical noise may randomize or pervert the convergence. We study the p...

  20. Integrated logistic support studies using behavioral Monte Carlo simulation, supported by Generalized Stochastic Petri Nets

    International Nuclear Information System (INIS)

    Garnier, Robert; Chevalier, Marcel

    2000-01-01

    Studying large and complex industrial sites, requires more and more accuracy in modeling. In particular, when considering Spares, Maintenance and Repair / Replacement processes, determining optimal Integrated Logistic Support policies requires a high level modeling formalism, in order to make the model as close as possible to the real considered processes. Generally, numerical methods are used to process this kind of study. In this paper, we propose an alternate way to process optimal Integrated Logistic Support policy determination when dealing with large, complex and distributed multi-policies industrial sites. This method is based on the use of behavioral Monte Carlo simulation, supported by Generalized Stochastic Petri Nets. (author)