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Sample records for carlo method implemented

  1. Alternative implementations of the Monte Carlo power method

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  2. Alternative Implementations of the Monte Carlo Power Method

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  3. A Monte Carlo implementation of the predictor-corrector Quasi-Static method

    International Nuclear Information System (INIS)

    Hackemack, M. W.; Ragusa, J. C.; Griesheimer, D. P.; Pounders, J. M.

    2013-01-01

    The Quasi-Static method (QS) is a useful tool for solving reactor transients since it allows for larger time steps when updating neutron distributions. Because of the beneficial attributes of Monte Carlo (MC) methods (exact geometries and continuous energy treatment), it is desirable to develop a MC implementation for the QS method. In this work, the latest version of the QS method known as the Predictor-Corrector Quasi-Static method is implemented. Experiments utilizing two energy-groups provide results that show good agreement with analytical and reference solutions. The method as presented can easily be implemented in any continuous energy, arbitrary geometry, MC code. (authors)

  4. Monte Carlo method implementation on IPSC 860 for the resolution of the Boltzmann equation

    International Nuclear Information System (INIS)

    AloUGES, Francois

    1993-01-01

    This note deals with the implementation on a massively parallel machine (IPSC-860) of a Monte-Carlo method aiming at resolving the Boltzmann equation. The parallelism of the machine incites to consider a multi-domain approach and poses the problem of the automatic generation of local meshes from a non-structured 3-D global mesh [fr

  5. A computationally efficient moment-preserving Monte Carlo electron transport method with implementation in Geant4

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, D.A., E-mail: ddixon@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663, MS P365, Los Alamos, NM 87545 (United States); Prinja, A.K., E-mail: prinja@unm.edu [Department of Nuclear Engineering, MSC01 1120, 1 University of New Mexico, Albuquerque, NM 87131-0001 (United States); Franke, B.C., E-mail: bcfrank@sandia.gov [Sandia National Laboratories, Albuquerque, NM 87123 (United States)

    2015-09-15

    This paper presents the theoretical development and numerical demonstration of a moment-preserving Monte Carlo electron transport method. Foremost, a full implementation of the moment-preserving (MP) method within the Geant4 particle simulation toolkit is demonstrated. Beyond implementation details, it is shown that the MP method is a viable alternative to the condensed history (CH) method for inclusion in current and future generation transport codes through demonstration of the key features of the method including: systematically controllable accuracy, computational efficiency, mathematical robustness, and versatility. A wide variety of results common to electron transport are presented illustrating the key features of the MP method. In particular, it is possible to achieve accuracy that is statistically indistinguishable from analog Monte Carlo, while remaining up to three orders of magnitude more efficient than analog Monte Carlo simulations. Finally, it is shown that the MP method can be generalized to any applicable analog scattering DCS model by extending previous work on the MP method beyond analytical DCSs to the partial-wave (PW) elastic tabulated DCS data.

  6. Implementation of the dynamic Monte Carlo method for transient analysis in the general purpose code Tripoli

    Energy Technology Data Exchange (ETDEWEB)

    Sjenitzer, Bart L.; Hoogenboom, J. Eduard, E-mail: B.L.Sjenitzer@TUDelft.nl, E-mail: J.E.Hoogenboom@TUDelft.nl [Delft University of Technology (Netherlands)

    2011-07-01

    A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)

  7. Implementation of the dynamic Monte Carlo method for transient analysis in the general purpose code Tripoli

    International Nuclear Information System (INIS)

    Sjenitzer, Bart L.; Hoogenboom, J. Eduard

    2011-01-01

    A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)

  8. Implementation of the probability table method in a continuous-energy Monte Carlo code system

    International Nuclear Information System (INIS)

    Sutton, T.M.; Brown, F.B.

    1998-10-01

    RACER is a particle-transport Monte Carlo code that utilizes a continuous-energy treatment for neutrons and neutron cross section data. Until recently, neutron cross sections in the unresolved resonance range (URR) have been treated in RACER using smooth, dilute-average representations. This paper describes how RACER has been modified to use probability tables to treat cross sections in the URR, and the computer codes that have been developed to compute the tables from the unresolved resonance parameters contained in ENDF/B data files. A companion paper presents results of Monte Carlo calculations that demonstrate the effect of the use of probability tables versus the use of dilute-average cross sections for the URR. The next section provides a brief review of the probability table method as implemented in the RACER system. The production of the probability tables for use by RACER takes place in two steps. The first step is the generation of probability tables from the nuclear parameters contained in the ENDF/B data files. This step, and the code written to perform it, are described in Section 3. The tables produced are at energy points determined by the ENDF/B parameters and/or accuracy considerations. The tables actually used in the RACER calculations are obtained in the second step from those produced in the first. These tables are generated at energy points specific to the RACER calculation. Section 4 describes this step and the code written to implement it, as well as modifications made to RACER to enable it to use the tables. Finally, some results and conclusions are presented in Section 5

  9. Implementation of a Monte Carlo method to model photon conversion for solar cells

    International Nuclear Information System (INIS)

    Canizo, C. del; Tobias, I.; Perez-Bedmar, J.; Pan, A.C.; Luque, A.

    2008-01-01

    A physical model describing different photon conversion mechanisms is presented in the context of photovoltaic applications. To solve the resulting system of equations, a Monte Carlo ray-tracing model is implemented, which takes into account the coupling of the photon transport phenomena to the non-linear rate equations describing luminescence. It also separates the generation of rays from the two very different sources of photons involved (the sun and the luminescence centers). The Monte Carlo simulator presented in this paper is proposed as a tool to help in the evaluation of candidate materials for up- and down-conversion. Some application examples are presented, exploring the range of values that the most relevant parameters describing the converter should have in order to give significant gain in photocurrent

  10. 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

  11. 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.

  12. Bayesian Monte Carlo method

    International Nuclear Information System (INIS)

    Rajabalinejad, M.

    2010-01-01

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

  13. Monte Carlo method implemented in a finite element code with application to dynamic vacuum in particle accelerators

    CERN Document Server

    Garion, C

    2009-01-01

    Modern particle accelerators require UHV conditions during their operation. In the accelerating cavities, breakdowns can occur, releasing large amount of gas into the vacuum chamber. To determine the pressure profile along the cavity as a function of time, the time-dependent behaviour of the gas has to be simulated. To do that, it is useful to apply accurate three-dimensional method, such as Test Particles Monte Carlo. In this paper, a time-dependent Test Particles Monte Carlo is used. It has been implemented in a Finite Element code, CASTEM. The principle is to track a sample of molecules during time. The complex geometry of the cavities can be created either in the FE code or in a CAD software (CATIA in our case). The interface between the two softwares to export the geometry from CATIA to CASTEM is given. The algorithm of particle tracking for collisionless flow in the FE code is shown. Thermal outgassing, pumping surfaces and electron and/or ion stimulated desorption can all be generated as well as differ...

  14. 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

  15. Shell model Monte Carlo methods

    International Nuclear Information System (INIS)

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

    1997-01-01

    We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)

  16. 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

  17. 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.

  18. Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy

    International Nuclear Information System (INIS)

    Kohno, R; Hotta, K; Nishioka, S; Matsubara, K; Tansho, R; Suzuki, T

    2011-01-01

    We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30–16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9–67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning. (note)

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

    Directory of Open Access Journals (Sweden)

    Xueli Chen

    2010-01-01

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

  20. 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

  1. 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

  2. Analysis of the uranium price predicted to 24 months, implementing neural networks and the Monte Carlo method like predictive tools

    International Nuclear Information System (INIS)

    Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C.

    2011-11-01

    The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)

  3. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay; Law, Kody; Suciu, Carina

    2017-01-01

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  4. 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.

  5. 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.)

  6. A contribution Monte Carlo method

    International Nuclear Information System (INIS)

    Aboughantous, C.H.

    1994-01-01

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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. Criticality calculations on pebble-bed HTR-PROTEUS configuration as a validation for the pseudo-scattering tracking method implemented in the MORET 5 Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Forestier, Benoit; Miss, Joachim; Bernard, Franck; Dorval, Aurelien [Institut de Radioprotection et Surete Nucleaire, Fontenay aux Roses (France); Jacquet, Olivier [Independent consultant (France); Verboomen, Bernard [Belgian Nuclear Research Center - SCK-CEN (Belgium)

    2008-07-01

    The MORET code is a three dimensional Monte Carlo criticality code. It is designed to calculate the effective multiplication factor (k{sub eff}) of any geometrical configuration as well as the reaction rates in the various volumes and the neutron leakage out of the system. A recent development for the MORET code consists of the implementation of an alternate neutron tracking method, known as the pseudo-scattering tracking method. This method has been successfully implemented in the MORET code and its performances have been tested by mean of an extensive parametric study on very simple geometrical configurations. In this context, the goal of the present work is to validate the pseudo-scattering method against realistic configurations. In this perspective, pebble-bed cores are particularly well-adapted cases to model, as they exhibit large amount of volumes stochastically arranged on two different levels (the pebbles in the core and the TRISO particles inside each pebble). This paper will introduce the techniques and methods used to model pebble-bed cores in a realistic way. The results of the criticality calculations, as well as the pseudo-scattering tracking method performance in terms of computation time, will also be presented. (authors)

  12. Efficient implementation of the Monte Carlo method for lattice gauge theory calculations on the floating point systems FPS-164

    International Nuclear Information System (INIS)

    Moriarty, K.J.M.; Blackshaw, J.E.

    1983-01-01

    The computer program calculates the average action per plaquette for SU(6)/Z 6 lattice gauge theory. By considering quantum field theory on a space-time lattice, the ultraviolet divergences of the theory are regulated through the finite lattice spacing. The continuum theory results can be obtained by a renormalization group procedure. Making use of the FPS Mathematics Library (MATHLIB), we are able to generate an efficient code for the Monte Carlo algorithm for lattice gauge theory calculations which compares favourably with the performance of the CDC 7600. (orig.)

  13. (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.

  14. Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

    International Nuclear Information System (INIS)

    Urbatsch, T.J.

    1995-11-01

    If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors

  15. 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.

  16. 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.

  17. TH-A-19A-04: Latent Uncertainties and Performance of a GPU-Implemented Pre-Calculated Track Monte Carlo Method

    International Nuclear Information System (INIS)

    Renaud, M; Seuntjens, J; Roberge, D

    2014-01-01

    Purpose: Assessing the performance and uncertainty of a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport running on graphics processing units (GPU). While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from recycling a limited number of tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pre-generated track bank size can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pre-generated for electrons and protons using EGSnrc and GEANT4, respectively. The PMC algorithm for track transport was implemented on the CUDA programming framework. GPU-PMC dose distributions were compared to benchmark dose distributions simulated using general-purpose MC codes in the same conditions. A latent uncertainty analysis was performed by comparing GPUPMC dose values to a “ground truth” benchmark while varying the track bank size and primary particle histories. Results: GPU-PMC dose distributions and benchmark doses were within 1% of each other in voxels with dose greater than 50% of Dmax. In proton calculations, a submillimeter distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty followed a Poisson distribution with the number of tracks per energy (TPE) and a track bank of 20,000 TPE produced a latent uncertainty of approximately 1%. Efficiency analysis showed a 937× and 508× gain over a single processor core running DOSXYZnrc for 16 MeV electrons in water and bone, respectively. Conclusion: The GPU-PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty below 1%. The track bank size necessary to achieve an optimal efficiency can be tuned based on the desired uncertainty. Coupled with a model to calculate dose contributions from uncharged particles, GPU-PMC is a candidate for inverse planning of modulated electron radiotherapy

  18. 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)

  19. Experience with the Monte Carlo Method

    Energy Technology Data Exchange (ETDEWEB)

    Hussein, E M.A. [Department of Mechanical Engineering University of New Brunswick, Fredericton, N.B., (Canada)

    2007-06-15

    Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed.

  20. Experience with the Monte Carlo Method

    International Nuclear Information System (INIS)

    Hussein, E.M.A.

    2007-01-01

    Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed

  1. 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...

  2. Monte Carlo method applied to medical physics

    International Nuclear Information System (INIS)

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

    2000-01-01

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

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

    International Nuclear Information System (INIS)

    Martin, William R.; Brown, Forrest B.

    2001-01-01

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

  4. Some problems on Monte Carlo method development

    International Nuclear Information System (INIS)

    Pei Lucheng

    1992-01-01

    This is a short paper on some problems of Monte Carlo method development. The content consists of deep-penetration problems, unbounded estimate problems, limitation of Mdtropolis' method, dependency problem in Metropolis' method, random error interference problems and random equations, intellectualisation and vectorization problems of general software

  5. 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.

  6. 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

  7. Monte Carlo method for array criticality calculations

    International Nuclear Information System (INIS)

    Dickinson, D.; Whitesides, G.E.

    1976-01-01

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

  8. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    Systat Software Asia-Pacific. Ltd., in Bangalore, where the technical work for the development of the statistica' software ... concepts that are relevant for the application of MCMC methods and ... joint distribution of the vector N of the numbers of.

  9. Monte Carlo method for neutron transport problems

    International Nuclear Information System (INIS)

    Asaoka, Takumi

    1977-01-01

    Some methods for decreasing variances in Monte Carlo neutron transport calculations are presented together with the results of sample calculations. A general purpose neutron transport Monte Carlo code ''MORSE'' was used for the purpose. The first method discussed in this report is the method of statistical estimation. As an example of this method, the application of the coarse-mesh rebalance acceleration method to the criticality calculation of a cylindrical fast reactor is presented. Effective multiplication factor and its standard deviation are presented as a function of the number of histories and comparisons are made between the coarse-mesh rebalance method and the standard method. Five-group neutron fluxes at core center are also compared with the result of S4 calculation. The second method is the method of correlated sampling. This method was applied to the perturbation calculation of control rod worths in a fast critical assembly (FCA-V-3) Two methods of sampling (similar flight paths and identical flight paths) are tested and compared with experimental results. For every cases the experimental value lies within the standard deviation of the Monte Carlo calculations. The third method is the importance sampling. In this report a biased selection of particle flight directions discussed. This method was applied to the flux calculation in a spherical fast neutron system surrounded by a 10.16 cm iron reflector. Result-direction biasing, path-length stretching, and no biasing are compared with S8 calculation. (Aoki, K.)

  10. Burnup calculations using Monte Carlo method

    International Nuclear Information System (INIS)

    Ghosh, Biplab; Degweker, S.B.

    2009-01-01

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

  11. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    levels. This is based on the famous Laws of Large Num- bers {LLN}: Let XI,X2,X3, ... of the volume of Ai nD to the volume of D (here volume ... This method depends on being able to generate' a sarnple ... casinos offering games of chance.

  12. 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)

  13. 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

  14. Monte Carlo methods beyond detailed balance

    NARCIS (Netherlands)

    Schram, Raoul D.; Barkema, Gerard T.|info:eu-repo/dai/nl/101275080

    2015-01-01

    Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying

  15. 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.)

  16. Variance Reduction Techniques in Monte Carlo Methods

    NARCIS (Netherlands)

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

    2010-01-01

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

  17. 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

  18. 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

  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. Prospect on general software of Monte Carlo method

    International Nuclear Information System (INIS)

    Pei Lucheng

    1992-01-01

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

  1. Monte Carlo burnup codes acceleration using the correlated sampling method

    International Nuclear Information System (INIS)

    Dieudonne, C.

    2013-01-01

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

  2. Clinical implementation of full Monte Carlo dose calculation in proton beam therapy

    International Nuclear Information System (INIS)

    Paganetti, Harald; Jiang, Hongyu; Parodi, Katia; Slopsema, Roelf; Engelsman, Martijn

    2008-01-01

    The goal of this work was to facilitate the clinical use of Monte Carlo proton dose calculation to support routine treatment planning and delivery. The Monte Carlo code Geant4 was used to simulate the treatment head setup, including a time-dependent simulation of modulator wheels (for broad beam modulation) and magnetic field settings (for beam scanning). Any patient-field-specific setup can be modeled according to the treatment control system of the facility. The code was benchmarked against phantom measurements. Using a simulation of the ionization chamber reading in the treatment head allows the Monte Carlo dose to be specified in absolute units (Gy per ionization chamber reading). Next, the capability of reading CT data information was implemented into the Monte Carlo code to model patient anatomy. To allow time-efficient dose calculation, the standard Geant4 tracking algorithm was modified. Finally, a software link of the Monte Carlo dose engine to the patient database and the commercial planning system was established to allow data exchange, thus completing the implementation of the proton Monte Carlo dose calculation engine ('DoC++'). Monte Carlo re-calculated plans are a valuable tool to revisit decisions in the planning process. Identification of clinically significant differences between Monte Carlo and pencil-beam-based dose calculations may also drive improvements of current pencil-beam methods. As an example, four patients (29 fields in total) with tumors in the head and neck regions were analyzed. Differences between the pencil-beam algorithm and Monte Carlo were identified in particular near the end of range, both due to dose degradation and overall differences in range prediction due to bony anatomy in the beam path. Further, the Monte Carlo reports dose-to-tissue as compared to dose-to-water by the planning system. Our implementation is tailored to a specific Monte Carlo code and the treatment planning system XiO (Computerized Medical Systems Inc

  3. Multiple-time-stepping generalized hybrid Monte Carlo methods

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-01-01

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

  4. 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....

  5. 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

  6. Monte Carlo methods to calculate impact probabilities

    Science.gov (United States)

    Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.

    2014-09-01

    Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward

  7. Reactor perturbation calculations by Monte Carlo methods

    International Nuclear Information System (INIS)

    Gubbins, M.E.

    1965-09-01

    Whilst Monte Carlo methods are useful for reactor calculations involving complicated geometry, it is difficult to apply them to the calculation of perturbation worths because of the large amount of computing time needed to obtain good accuracy. Various ways of overcoming these difficulties are investigated in this report, with the problem of estimating absorbing control rod worths particularly in mind. As a basis for discussion a method of carrying out multigroup reactor calculations by Monte Carlo methods is described. Two methods of estimating a perturbation worth directly, without differencing two quantities of like magnitude, are examined closely but are passed over in favour of a third method based on a correlation technique. This correlation method is described, and demonstrated by a limited range of calculations for absorbing control rods in a fast reactor. In these calculations control rod worths of between 1% and 7% in reactivity are estimated to an accuracy better than 10% (3 standard errors) in about one hour's computing time on the English Electric KDF.9 digital computer. (author)

  8. 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

  9. A general framework for implementing NLO calculations in shower Monte Carlo programs. The POWHEG BOX

    Energy Technology Data Exchange (ETDEWEB)

    Alioli, Simone [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Nason, Paolo [INFN, Milano-Bicocca (Italy); Oleari, Carlo [INFN, Milano-Bicocca (Italy); Milano-Bicocca Univ. (Italy); Re, Emanuele [Durham Univ. (United Kingdom). Inst. for Particle Physics Phenomenology

    2010-02-15

    In this work we illustrate the POWHEG BOX, a general computer code framework for implementing NLO calculations in shower Monte Carlo programs according to the POWHEG method. Aim of this work is to provide an illustration of the needed theoretical ingredients, a view of how the code is organized and a description of what a user should provide in order to use it. (orig.)

  10. A general framework for implementing NLO calculations in shower Monte Carlo programs. The POWHEG BOX

    International Nuclear Information System (INIS)

    Alioli, Simone; Nason, Paolo; Oleari, Carlo; Re, Emanuele

    2010-02-01

    In this work we illustrate the POWHEG BOX, a general computer code framework for implementing NLO calculations in shower Monte Carlo programs according to the POWHEG method. Aim of this work is to provide an illustration of the needed theoretical ingredients, a view of how the code is organized and a description of what a user should provide in order to use it. (orig.)

  11. 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...

  12. 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.

  13. 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)

  14. Applications of Monte Carlo method in Medical Physics

    International Nuclear Information System (INIS)

    Diez Rios, A.; Labajos, M.

    1989-01-01

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

  15. 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.

  16. Optimization of sequential decisions by least squares Monte Carlo method

    DEFF Research Database (Denmark)

    Nishijima, Kazuyoshi; Anders, Annett

    change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...... is proposed by Longstaff and Schwartz (2001) for pricing of American options. The present paper formulates the decision problem in a more general manner and explains how the solution scheme proposed by Anders and Nishijima (2011) is implemented for the optimization of the formulated decision problem...

  17. Implementation of a Monte Carlo based inverse planning model for clinical IMRT with MCNP code

    International Nuclear Information System (INIS)

    He, Tongming Tony

    2003-01-01

    Inaccurate dose calculations and limitations of optimization algorithms in inverse planning introduce systematic and convergence errors to treatment plans. This work was to implement a Monte Carlo based inverse planning model for clinical IMRT aiming to minimize the aforementioned errors. The strategy was to precalculate the dose matrices of beamlets in a Monte Carlo based method followed by the optimization of beamlet intensities. The MCNP 4B (Monte Carlo N-Particle version 4B) code was modified to implement selective particle transport and dose tallying in voxels and efficient estimation of statistical uncertainties. The resulting performance gain was over eleven thousand times. Due to concurrent calculation of multiple beamlets of individual ports, hundreds of beamlets in an IMRT plan could be calculated within a practical length of time. A finite-sized point source model provided a simple and accurate modeling of treatment beams. The dose matrix calculations were validated through measurements in phantoms. Agreements were better than 1.5% or 0.2 cm. The beamlet intensities were optimized using a parallel platform based optimization algorithm that was capable of escape from local minima and preventing premature convergence. The Monte Carlo based inverse planning model was applied to clinical cases. The feasibility and capability of Monte Carlo based inverse planning for clinical IMRT was demonstrated. Systematic errors in treatment plans of a commercial inverse planning system were assessed in comparison with the Monte Carlo based calculations. Discrepancies in tumor doses and critical structure doses were up to 12% and 17%, respectively. The clinical importance of Monte Carlo based inverse planning for IMRT was demonstrated

  18. Quantum statistical Monte Carlo methods and applications to spin systems

    International Nuclear Information System (INIS)

    Suzuki, M.

    1986-01-01

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

  19. Applications of the Monte Carlo method in radiation protection

    International Nuclear Information System (INIS)

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

    1999-01-01

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

  20. 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.

  1. Reliable method for fission source convergence of Monte Carlo criticality calculation with Wielandt's method

    International Nuclear Information System (INIS)

    Yamamoto, Toshihiro; Miyoshi, Yoshinori

    2004-01-01

    A new algorithm of Monte Carlo criticality calculations for implementing Wielandt's method, which is one of acceleration techniques for deterministic source iteration methods, is developed, and the algorithm can be successfully implemented into MCNP code. In this algorithm, part of fission neutrons emitted during random walk processes are tracked within the current cycle, and thus a fission source distribution used in the next cycle spread more widely. Applying this method intensifies a neutron interaction effect even in a loosely-coupled array where conventional Monte Carlo criticality methods have difficulties, and a converged fission source distribution can be obtained with fewer cycles. Computing time spent for one cycle, however, increases because of tracking fission neutrons within the current cycle, which eventually results in an increase of total computing time up to convergence. In addition, statistical fluctuations of a fission source distribution in a cycle are worsened by applying Wielandt's method to Monte Carlo criticality calculations. However, since a fission source convergence is attained with fewer source iterations, a reliable determination of convergence can easily be made even in a system with a slow convergence. This acceleration method is expected to contribute to prevention of incorrect Monte Carlo criticality calculations. (author)

  2. 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. ...

  3. Implementation and analysis of an adaptive multilevel Monte Carlo algorithm

    KAUST Repository

    Hoel, Hakon; Von Schwerin, Erik; Szepessy, Anders; Tempone, Raul

    2014-01-01

    We present an adaptive multilevel Monte Carlo (MLMC) method for weak approximations of solutions to Itô stochastic dierential equations (SDE). The work [11] proposed and analyzed an MLMC method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a single level Euler-Maruyama Monte Carlo method from O(TOL-3) to O(TOL-2 log(TOL-1)2) for a mean square error of O(TOL2). Later, the work [17] presented an MLMC method using a hierarchy of adaptively re ned, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform time discretizationMLMC method. This work improves the adaptiveMLMC algorithms presented in [17] and it also provides mathematical analysis of the improved algorithms. In particular, we show that under some assumptions our adaptive MLMC algorithms are asymptotically accurate and essentially have the correct complexity but with improved control of the complexity constant factor in the asymptotic analysis. Numerical tests include one case with singular drift and one with stopped diusion, where the complexity of a uniform single level method is O(TOL-4). For both these cases the results con rm the theory, exhibiting savings in the computational cost for achieving the accuracy O(TOL) from O(TOL-3) for the adaptive single level algorithm to essentially O(TOL-2 log(TOL-1)2) for the adaptive MLMC algorithm. © 2014 by Walter de Gruyter Berlin/Boston 2014.

  4. Cluster monte carlo method for nuclear criticality safety calculation

    International Nuclear Information System (INIS)

    Pei Lucheng

    1984-01-01

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

  5. 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.

  6. Statistics of Monte Carlo methods used in radiation transport calculation

    International Nuclear Information System (INIS)

    Datta, D.

    2009-01-01

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

  7. A functional method for estimating DPA tallies in Monte Carlo calculations of Light Water Reactors

    International Nuclear Information System (INIS)

    Read, Edward A.; Oliveira, Cassiano R.E. de

    2011-01-01

    There has been a growing need in recent years for the development of methodology to calculate radiation damage factors, namely displacements per atom (dpa), of structural components for Light Water Reactors (LWRs). The aim of this paper is to discuss the development and implementation of a dpa method using Monte Carlo method for transport calculations. The capabilities of the Monte Carlo code Serpent such as Woodcock tracking and fuel depletion are assessed for radiation damage calculations and its capability demonstrated and compared to those of the Monte Carlo code MCNP for radiation damage calculations of a typical LWR configuration. (author)

  8. 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

  9. A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

    NARCIS (Netherlands)

    MIKOSCH, T; WANG, QA

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

  10. Problems in radiation shielding calculations with Monte Carlo methods

    International Nuclear Information System (INIS)

    Ueki, Kohtaro

    1985-01-01

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

  11. Neutron flux calculation by means of Monte Carlo methods

    International Nuclear Information System (INIS)

    Barz, H.U.; Eichhorn, M.

    1988-01-01

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

  12. Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

    Science.gov (United States)

    Sharma, Sanjib

    2017-08-01

    Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, efficient Monte Carlo based methods are continuously being developed and explored. In this review, we first explain the basics of Bayesian theory and discuss how to set up data analysis problems within this framework. Next, we provide an overview of various Monte Carlo based methods for performing Bayesian data analysis. Finally, we discuss advanced ideas that enable us to tackle complex problems and thus hold great promise for the future. We also distribute downloadable computer software (available at https://github.com/sanjibs/bmcmc/ ) that implements some of the algorithms and examples discussed here.

  13. 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

  14. 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.

  15. Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code

    International Nuclear Information System (INIS)

    Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.

    2015-01-01

    This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Some specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000 ® problems. These benchmark and scaling studies show promising results

  16. A NEW MONTE CARLO METHOD FOR TIME-DEPENDENT NEUTRINO RADIATION TRANSPORT

    International Nuclear Information System (INIS)

    Abdikamalov, Ernazar; Ott, Christian D.; O'Connor, Evan; Burrows, Adam; Dolence, Joshua C.; Löffler, Frank; Schnetter, Erik

    2012-01-01

    Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck and Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

  17. A NEW MONTE CARLO METHOD FOR TIME-DEPENDENT NEUTRINO RADIATION TRANSPORT

    Energy Technology Data Exchange (ETDEWEB)

    Abdikamalov, Ernazar; Ott, Christian D.; O' Connor, Evan [TAPIR, California Institute of Technology, MC 350-17, 1200 E California Blvd., Pasadena, CA 91125 (United States); Burrows, Adam; Dolence, Joshua C. [Department of Astrophysical Sciences, Princeton University, Peyton Hall, Ivy Lane, Princeton, NJ 08544 (United States); Loeffler, Frank; Schnetter, Erik, E-mail: abdik@tapir.caltech.edu [Center for Computation and Technology, Louisiana State University, 216 Johnston Hall, Baton Rouge, LA 70803 (United States)

    2012-08-20

    Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck and Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

  18. Recommender engine for continuous-time quantum Monte Carlo methods

    Science.gov (United States)

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

    2017-03-01

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

  19. A residual Monte Carlo method for discrete thermal radiative diffusion

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  20. 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

  1. Study of the Transition Flow Regime using Monte Carlo Methods

    Science.gov (United States)

    Hassan, H. A.

    1999-01-01

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

  2. Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method

    CERN Document Server

    2002-01-01

    This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.

  3. An algorithm of α-and γ-mode eigenvalue calculations by Monte Carlo method

    International Nuclear Information System (INIS)

    Yamamoto, Toshihiro; Miyoshi, Yoshinori

    2003-01-01

    A new algorithm for Monte Carlo calculation was developed to obtain α- and γ-mode eigenvalues. The α is a prompt neutron time decay constant measured in subcritical experiments, and the γ is a spatial decay constant measured in an exponential method for determining the subcriticality. This algorithm can be implemented into existing Monte Carlo eigenvalue calculation codes with minimum modifications. The algorithm was implemented into MCNP code and the performance of calculating the both mode eigenvalues were verified through comparison of the calculated eigenvalues with the ones obtained by fixed source calculations. (author)

  4. Study of thermodynamic and structural properties of a flexible homopolymer chain using advanced Monte Carlo methods

    Directory of Open Access Journals (Sweden)

    Hammou Amine Bouziane

    2013-03-01

    Full Text Available We study the thermodynamic and structural properties of a flexible homopolymer chain using both multi canonical Monte Carlo method and Wang-Landau method. In this work, we focus on the coil-globule transition. Starting from a completely random chain, we have obtained a globule for different sizes of the chain. The implementation of these advanced Monte Carlo methods allowed us to obtain a flat histogram in energy space and calculate various thermodynamic quantities such as the density of states, the free energy and the specific heat. Structural quantities such as the radius of gyration where also calculated.

  5. Quantum Monte Carlo diagonalization method as a variational calculation

    International Nuclear Information System (INIS)

    Mizusaki, Takahiro; Otsuka, Takaharu; Honma, Michio.

    1997-01-01

    A stochastic method for performing large-scale shell model calculations is presented, which utilizes the auxiliary field Monte Carlo technique and diagonalization method. This method overcomes the limitation of the conventional shell model diagonalization and can extremely widen the feasibility of shell model calculations with realistic interactions for spectroscopic study of nuclear structure. (author)

  6. Acceleration of monte Carlo solution by conjugate gradient method

    International Nuclear Information System (INIS)

    Toshihisa, Yamamoto

    2005-01-01

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

  7. Monte Carlo methods for the reliability analysis of Markov systems

    International Nuclear Information System (INIS)

    Buslik, A.J.

    1985-01-01

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

  8. 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

  9. 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

  10. Particle-transport simulation with the Monte Carlo method

    International Nuclear Information System (INIS)

    Carter, L.L.; Cashwell, E.D.

    1975-01-01

    Attention is focused on the application of the Monte Carlo method to particle transport problems, with emphasis on neutron and photon transport. Topics covered include sampling methods, mathematical prescriptions for simulating particle transport, mechanics of simulating particle transport, neutron transport, and photon transport. A literature survey of 204 references is included. (GMT)

  11. A midway forward-adjoint coupling method for neutron and photon Monte Carlo transport

    International Nuclear Information System (INIS)

    Serov, I.V.; John, T.M.; Hoogenboom, J.E.

    1999-01-01

    The midway Monte Carlo method for calculating detector responses combines a forward and an adjoint Monte Carlo calculation. In both calculations, particle scores are registered at a surface to be chosen by the user somewhere between the source and detector domains. The theory of the midway response determination is developed within the framework of transport theory for external sources and for criticality theory. The theory is also developed for photons, which are generated at inelastic scattering or capture of neutrons. In either the forward or the adjoint calculation a so-called black absorber technique can be applied; i.e., particles need not be followed after passing the midway surface. The midway Monte Carlo method is implemented in the general-purpose MCNP Monte Carlo code. The midway Monte Carlo method is demonstrated to be very efficient in problems with deep penetration, small source and detector domains, and complicated streaming paths. All the problems considered pose difficult variance reduction challenges. Calculations were performed using existing variance reduction methods of normal MCNP runs and using the midway method. The performed comparative analyses show that the midway method appears to be much more efficient than the standard techniques in an overwhelming majority of cases and can be recommended for use in many difficult variance reduction problems of neutral particle transport

  12. 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

  13. 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

  14. 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.

  15. Latent uncertainties of the precalculated track Monte Carlo method

    International Nuclear Information System (INIS)

    Renaud, Marc-André; Seuntjens, Jan; Roberge, David

    2015-01-01

    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 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 the

  16. 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

  17. Extending the alias Monte Carlo sampling method to general distributions

    International Nuclear Information System (INIS)

    Edwards, A.L.; Rathkopf, J.A.; Smidt, R.K.

    1991-01-01

    The alias method is a Monte Carlo sampling technique that offers significant advantages over more traditional methods. It equals the accuracy of table lookup and the speed of equal probable bins. The original formulation of this method sampled from discrete distributions and was easily extended to histogram distributions. We have extended the method further to applications more germane to Monte Carlo particle transport codes: continuous distributions. This paper presents the alias method as originally derived and our extensions to simple continuous distributions represented by piecewise linear functions. We also present a method to interpolate accurately between distributions tabulated at points other than the point of interest. We present timing studies that demonstrate the method's increased efficiency over table lookup and show further speedup achieved through vectorization. 6 refs., 12 figs., 2 tabs

  18. Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans

    International Nuclear Information System (INIS)

    Stapleton, S; Zavgorodni, S; Popescu, I A; Beckham, W A

    2005-01-01

    The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot

  19. Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans

    Science.gov (United States)

    Stapleton, S.; Zavgorodni, S.; Popescu, I. A.; Beckham, W. A.

    2005-02-01

    The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.

  20. Proton therapy analysis using the Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Noshad, Houshyar [Center for Theoretical Physics and Mathematics, AEOI, P.O. Box 14155-1339, Tehran (Iran, Islamic Republic of)]. E-mail: hnoshad@aeoi.org.ir; Givechi, Nasim [Islamic Azad University, Science and Research Branch, Tehran (Iran, Islamic Republic of)

    2005-10-01

    The range and straggling data obtained from the transport of ions in matter (TRIM) computer program were used to determine the trajectories of monoenergetic 60 MeV protons in muscle tissue by using the Monte Carlo technique. The appropriate profile for the shape of a proton pencil beam in proton therapy as well as the dose deposited in the tissue were computed. The good agreements between our results as compared with the corresponding experimental values are presented here to show the reliability of our Monte Carlo method.

  1. Improved Monte Carlo Method for PSA Uncertainty Analysis

    International Nuclear Information System (INIS)

    Choi, Jongsoo

    2016-01-01

    The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard

  2. Improved Monte Carlo Method for PSA Uncertainty Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Jongsoo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2016-10-15

    The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard.

  3. The Hybrid Monte Carlo (HMC) method and dynamic fermions

    International Nuclear Information System (INIS)

    Amaral, Marcia G. do

    1994-01-01

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

  4. Monte Carlo method for magnetic impurities in metals

    Science.gov (United States)

    Hirsch, J. E.; Fye, R. M.

    1986-01-01

    The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.

  5. Markov chain Monte Carlo methods in radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Hugtenburg, R.P.

    2001-01-01

    The Markov chain method can be used to incorporate measured data in Monte Carlo based radiotherapy treatment planning. This paper shows that convergence to the measured data, within the target precision, is achievable. Relative output factors for blocked fields and oblique beams are shown to compare well with independent measurements according to the same criterion. (orig.)

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

    International Nuclear Information System (INIS)

    Vekic, M.; White, S.R.

    1993-01-01

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

  7. Development of three-dimensional program based on Monte Carlo and discrete ordinates bidirectional coupling method

    International Nuclear Information System (INIS)

    Han Jingru; Chen Yixue; Yuan Longjun

    2013-01-01

    The Monte Carlo (MC) and discrete ordinates (SN) are the commonly used methods in the design of radiation shielding. Monte Carlo method is able to treat the geometry exactly, but time-consuming in dealing with the deep penetration problem. The discrete ordinate method has great computational efficiency, but it is quite costly in computer memory and it suffers from ray effect. Single discrete ordinates method or single Monte Carlo method has limitation in shielding calculation for large complex nuclear facilities. In order to solve the problem, the Monte Carlo and discrete ordinates bidirectional coupling method is developed. The bidirectional coupling method is implemented in the interface program to transfer the particle probability distribution of MC and angular flux of discrete ordinates. The coupling method combines the advantages of MC and SN. The test problems of cartesian and cylindrical coordinate have been calculated by the coupling methods. The calculation results are performed with comparison to MCNP and TORT and satisfactory agreements are obtained. The correctness of the program is proved. (authors)

  8. Improvement of correlated sampling Monte Carlo methods for reactivity calculations

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki; Asaoka, Takumi

    1978-01-01

    Two correlated Monte Carlo methods, the similar flight path and the identical flight path methods, have been improved to evaluate up to the second order change of the reactivity perturbation. Secondary fission neutrons produced by neutrons having passed through perturbed regions in both unperturbed and perturbed systems are followed in a way to have a strong correlation between secondary neutrons in both the systems. These techniques are incorporated into the general purpose Monte Carlo code MORSE, so as to be able to estimate also the statistical error of the calculated reactivity change. The control rod worths measured in the FCA V-3 assembly are analyzed with the present techniques, which are shown to predict the measured values within the standard deviations. The identical flight path method has revealed itself more useful than the similar flight path method for the analysis of the control rod worth. (auth.)

  9. The Monte Carlo method in mining nuclear geophysics: Pt. 1

    International Nuclear Information System (INIS)

    Burmistenko, Yu.N.; Lukhminsky, B.E.

    1990-01-01

    Prospects for using a new generation of neutron generators in mining geophysics are discussed. For their evaluation we use Monte Carlo computational methods with a special package of FORTRAN programs code-named MOK. Among the methods of pulsed neutron logging we discuss the method of time-dependent slowing down for the measurement of resonance neutron absorbers (mercury, tungsten, silver, gold, gadolinium, etc.) and time dependent spectral analysis of capture γ-rays (mercury). Among the neutron activation methods, we discuss the two source methods ( 252 Cf + neutron generator) and the method of spectral activation ratio for bauxites ( 27 Al/ 27 Mg or 27 Al/ 24m Na). (author)

  10. Superalloy design - A Monte Carlo constrained optimization method

    CSIR Research Space (South Africa)

    Stander, CM

    1996-01-01

    Full Text Available optimization method C. M. Stander Division of Materials Science and Technology, CSIR, PO Box 395, Pretoria, Republic of South Africa Received 74 March 1996; accepted 24 June 1996 A method, based on Monte Carlo constrained... successful hit, i.e. when Liow < LMP,,, < Lhiph, and for all the properties, Pj?, < P, < Pi@?. If successful this hit falls within the ROA. Repeat steps 4 and 5 to find at least ten (or more) successful hits with values...

  11. A comparison of generalized hybrid Monte Carlo methods with and without momentum flip

    International Nuclear Information System (INIS)

    Akhmatskaya, Elena; Bou-Rabee, Nawaf; Reich, Sebastian

    2009-01-01

    The generalized hybrid Monte Carlo (GHMC) method combines Metropolis corrected constant energy simulations with a partial random refreshment step in the particle momenta. The standard detailed balance condition requires that momenta are negated upon rejection of a molecular dynamics proposal step. The implication is a trajectory reversal upon rejection, which is undesirable when interpreting GHMC as thermostated molecular dynamics. We show that a modified detailed balance condition can be used to implement GHMC without momentum flips. The same modification can be applied to the generalized shadow hybrid Monte Carlo (GSHMC) method. Numerical results indicate that GHMC/GSHMC implementations with momentum flip display a favorable behavior in terms of sampling efficiency, i.e., the traditional GHMC/GSHMC implementations with momentum flip got the advantage of a higher acceptance rate and faster decorrelation of Monte Carlo samples. The difference is more pronounced for GHMC. We also numerically investigate the behavior of the GHMC method as a Langevin-type thermostat. We find that the GHMC method without momentum flip interferes less with the underlying stochastic molecular dynamics in terms of autocorrelation functions and it to be preferred over the GHMC method with momentum flip. The same finding applies to GSHMC

  12. A new effective Monte Carlo Midway coupling method in MCNP applied to a well logging problem

    Energy Technology Data Exchange (ETDEWEB)

    Serov, I.V.; John, T.M.; Hoogenboom, J.E

    1998-12-01

    The background of the Midway forward-adjoint coupling method including the black absorber technique for efficient Monte Carlo determination of radiation detector responses is described. The method is implemented in the general purpose MCNP Monte Carlo code. The utilization of the method is fairly straightforward and does not require any substantial extra expertise. The method was applied to a standard neutron well logging porosity tool problem. The results exhibit reliability and high efficiency of the Midway method. For the studied problem the efficiency gain is considerably higher than for a normal forward calculation, which is already strongly optimized by weight-windows. No additional effort is required to adjust the Midway model if the position of the detector or the porosity of the formation is changed. Additionally, the Midway method can be used with other variance reduction techniques if extra gain in efficiency is desired.

  13. Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method

    Science.gov (United States)

    Gilbreth, C. N.; Alhassid, Y.

    2015-03-01

    Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.

  14. Analysis of the uranium price predicted to 24 months, implementing neural networks and the Monte Carlo method like predictive tools; Analisis del precio del uranio pronosticado a 24 meses, implementando redes neuronales y el metodo de Monte Carlo como herramientas predictivas

    Energy Technology Data Exchange (ETDEWEB)

    Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C., E-mail: jaime.esquivel@fi.uaemex.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

    2011-11-15

    The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)

  15. Present status of transport code development based on Monte Carlo method

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki

    1985-01-01

    The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)

  16. 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.

  17. Development of ray tracing visualization program by Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-09-01

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

  18. Simulation of quantum systems by the tomography Monte Carlo method

    International Nuclear Information System (INIS)

    Bogdanov, Yu I

    2007-01-01

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

  19. Review and comparison of effective delayed neutron fraction calculation methods with Monte Carlo codes

    International Nuclear Information System (INIS)

    Bécares, V.; Pérez-Martín, S.; Vázquez-Antolín, M.; Villamarín, D.; Martín-Fuertes, F.; González-Romero, E.M.; Merino, I.

    2014-01-01

    Highlights: • Review of several Monte Carlo effective delayed neutron fraction calculation methods. • These methods have been implemented with the Monte Carlo code MCNPX. • They have been benchmarked against against some critical and subcritical systems. • Several nuclear data libraries have been used. - Abstract: The calculation of the effective delayed neutron fraction, β eff , with Monte Carlo codes is a complex task due to the requirement of properly considering the adjoint weighting of delayed neutrons. Nevertheless, several techniques have been proposed to circumvent this difficulty and obtain accurate Monte Carlo results for β eff without the need of explicitly determining the adjoint flux. In this paper, we make a review of some of these techniques; namely we have analyzed two variants of what we call the k-eigenvalue technique and other techniques based on different interpretations of the physical meaning of the adjoint weighting. To test the validity of all these techniques we have implemented them with the MCNPX code and we have benchmarked them against a range of critical and subcritical systems for which either experimental or deterministic values of β eff are available. Furthermore, several nuclear data libraries have been used in order to assess the impact of the uncertainty in nuclear data in the calculated value of β eff

  20. Calculations of pair production by Monte Carlo methods

    International Nuclear Information System (INIS)

    Bottcher, C.; Strayer, M.R.

    1991-01-01

    We describe some of the technical design issues associated with the production of particle-antiparticle pairs in very large accelerators. To answer these questions requires extensive calculation of Feynman diagrams, in effect multi-dimensional integrals, which we evaluate by Monte Carlo methods on a variety of supercomputers. We present some portable algorithms for generating random numbers on vector and parallel architecture machines. 12 refs., 14 figs

  1. Difficult Sudoku Puzzles Created by Replica Exchange Monte Carlo Method

    OpenAIRE

    Watanabe, Hiroshi

    2013-01-01

    An algorithm to create difficult Sudoku puzzles is proposed. An Ising spin-glass like Hamiltonian describing difficulty of puzzles is defined, and difficult puzzles are created by minimizing the energy of the Hamiltonian. We adopt the replica exchange Monte Carlo method with simultaneous temperature adjustments to search lower energy states efficiently, and we succeed in creating a puzzle which is the world hardest ever created in our definition, to our best knowledge. (Added on Mar. 11, the ...

  2. POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS

    OpenAIRE

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power...

  3. Many-body optimization using an ab initio monte carlo method.

    Science.gov (United States)

    Haubein, Ned C; McMillan, Scott A; Broadbelt, Linda J

    2003-01-01

    Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.

  4. Comparison of deterministic and Monte Carlo methods in shielding design.

    Science.gov (United States)

    Oliveira, A D; Oliveira, C

    2005-01-01

    In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions.

  5. Comparison of deterministic and Monte Carlo methods in shielding design

    International Nuclear Information System (INIS)

    Oliveira, A. D.; Oliveira, C.

    2005-01-01

    In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions. (authors)

  6. Monte Carlo methods for medical physics a practical introduction

    CERN Document Server

    Schuemann, Jan; Paganetti, Harald

    2018-01-01

    The Monte Carlo (MC) method, established as the gold standard to predict results of physical processes, is now fast becoming a routine clinical tool for applications that range from quality control to treatment verification. This book provides a basic understanding of the fundamental principles and limitations of the MC method in the interpretation and validation of results for various scenarios. It shows how user-friendly and speed optimized MC codes can achieve online image processing or dose calculations in a clinical setting. It introduces this essential method with emphasis on applications in hardware design and testing, radiological imaging, radiation therapy, and radiobiology.

  7. 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

  8. Novel extrapolation method in the Monte Carlo shell model

    International Nuclear Information System (INIS)

    Shimizu, Noritaka; Abe, Takashi; Utsuno, Yutaka; Mizusaki, Takahiro; Otsuka, Takaharu; Honma, Michio

    2010-01-01

    We propose an extrapolation method utilizing energy variance in the Monte Carlo shell model to estimate the energy eigenvalue and observables accurately. We derive a formula for the energy variance with deformed Slater determinants, which enables us to calculate the energy variance efficiently. The feasibility of the method is demonstrated for the full pf-shell calculation of 56 Ni, and the applicability of the method to a system beyond the current limit of exact diagonalization is shown for the pf+g 9/2 -shell calculation of 64 Ge.

  9. Monte Carlo method to characterize radioactive waste drums

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  10. 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)

  11. Implementation of variance-reduction techniques for Monte Carlo nuclear logging calculations with neutron sources

    NARCIS (Netherlands)

    Maucec, M

    2005-01-01

    Monte Carlo simulations for nuclear logging applications are considered to be highly demanding transport problems. In this paper, the implementation of weight-window variance reduction schemes in a 'manual' fashion to improve the efficiency of calculations for a neutron logging tool is presented.

  12. Estimativa da produtividade em soldagem pelo Método de Monte Carlo Productivity estimation in welding by Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    José Luiz Ferreira Martins

    2011-09-01

    . From these data was taken at random samples with, respectively, 10, 15 and 20 elements and were performed simulations by Monte Carlo method. Comparing the results of the sample with 160 elements and the data generated by simulation is observed that good results can be obtained by using Monte Carlo method in estimating productivity of industrial welding. On the other hand in Brazilian construction industry the value of productivity average is normally used as a productivity indicator and is based on historical data from other projects collected and measured only after project completion, which is a limitation. This article presents a tool for evaluation of the implementation in real time, enabling adjustments in estimates and monitoring productivity during the project. Similarly, in biddings, budgets and schedule estimations, the use of this tool could enable the adoption of other estimative different from of the average productivity, which is commonly used and as an alternative are suggested three criteria: optimistic, average and pessimistic productivity.

  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. A Hamiltonian Monte–Carlo method for Bayesian inference of supermassive black hole binaries

    International Nuclear Information System (INIS)

    Porter, Edward K; Carré, Jérôme

    2014-01-01

    We investigate the use of a Hamiltonian Monte–Carlo to map out the posterior density function for supermassive black hole binaries. While previous Markov Chain Monte–Carlo (MCMC) methods, such as Metropolis–Hastings MCMC, have been successfully employed for a number of different gravitational wave sources, these methods are essentially random walk algorithms. The Hamiltonian Monte–Carlo treats the inverse likelihood surface as a ‘gravitational potential’ and by introducing canonical positions and momenta, dynamically evolves the Markov chain by solving Hamilton's equations of motion. This method is not as widely used as other MCMC algorithms due to the necessity of calculating gradients of the log-likelihood, which for most applications results in a bottleneck that makes the algorithm computationally prohibitive. We circumvent this problem by using accepted initial phase-space trajectory points to analytically fit for each of the individual gradients. Eliminating the waveform generation needed for the numerical derivatives reduces the total number of required templates for a 10 6 iteration chain from ∼10 9 to ∼10 6 . The result is in an implementation of the Hamiltonian Monte–Carlo that is faster, and more efficient by a factor of approximately the dimension of the parameter space, than a Hessian MCMC. (paper)

  15. Monte Carlo methods in electron transport problems. Pt. 1

    International Nuclear Information System (INIS)

    Cleri, F.

    1989-01-01

    The condensed-history Monte Carlo method for charged particles transport is reviewed and discussed starting from a general form of the Boltzmann equation (Part I). The physics of the electronic interactions, together with some pedagogic example will be introduced in the part II. The lecture is directed to potential users of the method, for which it can be a useful introduction to the subject matter, and wants to establish the basis of the work on the computer code RECORD, which is at present in a developing stage

  16. Reliability analysis of neutron transport simulation using Monte Carlo method

    International Nuclear Information System (INIS)

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

    1995-01-01

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

  17. Applications to shielding design and others of monte carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Ito, Daiichiro [Mitsui Engineering and Shipbuiding Co., Ltd., Tokyo (Japan)

    2001-01-01

    One-dimensional or two-dimensional Sn computer code (ANISN, DOT3.5, etc.) and a point attenuation kernel integral code (QAD, etc.) have been used widely for shielding design. Application examples of monte carlo method which could follow precisely the three-dimensional configuration of shielding structure are shown as follow: (1) CASTER cask has a complex structure which consists of a large number of fuel baskets (stainless steel), neutron moderators (polyethylene rods), the body (cast iron), and cooling fin. The R-{theta} model of Sn code DOT3.5 cannot follow closely the complex form of polyethylene rods and fuel baskets. A monte carlo code MORSE is used to ascertain the calculation results of DOT3.5. The discrepancy between the calculation results of DOT3.5 and MORSE was in 10% for dose rate at distance of 1 m from the cask surface. (2) The dose rates of an iron cell at 10 cm above the floor are calculated by the code QAD and the MORSE. The reflected components of gamma ray caused by the auxiliary floor shield (lead) are analyzed by the MORSE. (3) A monte carlo code MCNP4A is used for skyshine evaluation of spent fuel carrier ship 'ROKUEIMARU'. The direct and skyshine components of gamma ray and neutron flux are estimated at each center of engine room and wheel house. The skyshine dose rate of neutron flux is 5-15 times larger than the gamma ray. (M. Suetake)

  18. Validation of uncertainty of weighing in the preparation of radionuclide standards by Monte Carlo Method

    International Nuclear Information System (INIS)

    Cacais, F.L.; Delgado, J.U.; Loayza, V.M.

    2016-01-01

    In preparing solutions for the production of radionuclide metrology standards is necessary measuring the quantity Activity by mass. The gravimetric method by elimination is applied to perform weighing with smaller uncertainties. At this work is carried out the validation, by the Monte Carlo method, of the uncertainty calculation approach implemented by Lourenco and Bobin according to ISO GUM for the method by elimination. The results obtained by both uncertainty calculation methods were consistent indicating that were fulfilled the conditions for the application of ISO GUM in the preparation of radioactive standards. (author)

  19. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures

    Directory of Open Access Journals (Sweden)

    Mahdi Shadab Far

    2016-01-01

    Full Text Available Structural load types, on the one hand, and structural capacity to withstand these loads, on the other hand, are of a probabilistic nature as they cannot be calculated and presented in a fully deterministic way. As such, the past few decades have witnessed the development of numerous probabilistic approaches towards the analysis and design of structures. Among the conventional methods used to assess structural reliability, the Monte Carlo sampling method has proved to be very convenient and efficient. However, it does suffer from certain disadvantages, the biggest one being the requirement of a very large number of samples to handle small probabilities, leading to a high computational cost. In this paper, a simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method. This revised approach was then presented in a step-by-step flowchart, for the purpose of easy programming and implementation.

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

    International Nuclear Information System (INIS)

    Xu Qi; Wang Kan; Li Shirui; Yu Ganglin

    2013-01-01

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

  1. 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

  2. A simple eigenfunction convergence acceleration method for Monte Carlo

    International Nuclear Information System (INIS)

    Booth, Thomas E.

    2011-01-01

    Monte Carlo transport codes typically use a power iteration method to obtain the fundamental eigenfunction. The standard convergence rate for the power iteration method is the ratio of the first two eigenvalues, that is, k_2/k_1. Modifications to the power method have accelerated the convergence by explicitly calculating the subdominant eigenfunctions as well as the fundamental. Calculating the subdominant eigenfunctions requires using particles of negative and positive weights and appropriately canceling the negative and positive weight particles. Incorporating both negative weights and a ± weight cancellation requires a significant change to current transport codes. This paper presents an alternative convergence acceleration method that does not require modifying the transport codes to deal with the problems associated with tracking and cancelling particles of ± weights. Instead, only positive weights are used in the acceleration method. (author)

  3. Analytic continuation of quantum Monte Carlo data. Stochastic sampling method

    Energy Technology Data Exchange (ETDEWEB)

    Ghanem, Khaldoon; Koch, Erik [Institute for Advanced Simulation, Forschungszentrum Juelich, 52425 Juelich (Germany)

    2016-07-01

    We apply Bayesian inference to the analytic continuation of quantum Monte Carlo (QMC) data from the imaginary axis to the real axis. Demanding a proper functional Bayesian formulation of any analytic continuation method leads naturally to the stochastic sampling method (StochS) as the Bayesian method with the simplest prior, while it excludes the maximum entropy method and Tikhonov regularization. We present a new efficient algorithm for performing StochS that reduces computational times by orders of magnitude in comparison to earlier StochS methods. We apply the new algorithm to a wide variety of typical test cases: spectral functions and susceptibilities from DMFT and lattice QMC calculations. Results show that StochS performs well and is able to resolve sharp features in the spectrum.

  4. 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

  5. Parallelization and implementation of approximate root isolation for nonlinear system by Monte Carlo

    Science.gov (United States)

    Khosravi, Ebrahim

    1998-12-01

    This dissertation solves a fundamental problem of isolating the real roots of nonlinear systems of equations by Monte-Carlo that were published by Bush Jones. This algorithm requires only function values and can be applied readily to complicated systems of transcendental functions. The implementation of this sequential algorithm provides scientists with the means to utilize function analysis in mathematics or other fields of science. The algorithm, however, is so computationally intensive that the system is limited to a very small set of variables, and this will make it unfeasible for large systems of equations. Also a computational technique was needed for investigating a metrology of preventing the algorithm structure from converging to the same root along different paths of computation. The research provides techniques for improving the efficiency and correctness of the algorithm. The sequential algorithm for this technique was corrected and a parallel algorithm is presented. This parallel method has been formally analyzed and is compared with other known methods of root isolation. The effectiveness, efficiency, enhanced overall performance of the parallel processing of the program in comparison to sequential processing is discussed. The message passing model was used for this parallel processing, and it is presented and implemented on Intel/860 MIMD architecture. The parallel processing proposed in this research has been implemented in an ongoing high energy physics experiment: this algorithm has been used to track neutrinoes in a super K detector. This experiment is located in Japan, and data can be processed on-line or off-line locally or remotely.

  6. 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

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

    CERN Document Server

    Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne

    2014-01-01

    The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.

  8. 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)

  9. '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)

  10. Stability analysis and time-step limits for a Monte Carlo Compton-scattering method

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Warsa, James S.; Lowrie, Robert B.

    2010-01-01

    A Monte Carlo method for simulating Compton scattering in high energy density applications has been presented that models the photon-electron collision kinematics exactly [E. Canfield, W.M. Howard, E.P. Liang, Inverse Comptonization by one-dimensional relativistic electrons, Astrophys. J. 323 (1987) 565]. However, implementing this technique typically requires an explicit evaluation of the material temperature, which can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and develop two time-step limits that avoid undesirable behavior. The first time-step limit prevents instabilities, while the second, more restrictive time-step limit avoids both instabilities and nonphysical oscillations. With a set of numerical examples, we demonstrate the efficacy of these time-step limits.

  11. New sampling method in continuous energy Monte Carlo calculation for pebble bed reactors

    International Nuclear Information System (INIS)

    Murata, Isao; Takahashi, Akito; Mori, Takamasa; Nakagawa, Masayuki.

    1997-01-01

    A pebble bed reactor generally has double heterogeneity consisting of two kinds of spherical fuel element. In the core, there exist many fuel balls piled up randomly in a high packing fraction. And each fuel ball contains a lot of small fuel particles which are also distributed randomly. In this study, to realize precise neutron transport calculation of such reactors with the continuous energy Monte Carlo method, a new sampling method has been developed. The new method has been implemented in the general purpose Monte Carlo code MCNP to develop a modified version MCNP-BALL. This method was validated by calculating inventory of spherical fuel elements arranged successively by sampling during transport calculation and also by performing criticality calculations in ordered packing models. From the results, it was confirmed that the inventory of spherical fuel elements could be reproduced using MCNP-BALL within a sufficient accuracy of 0.2%. And the comparison of criticality calculations in ordered packing models between MCNP-BALL and the reference method shows excellent agreement in neutron spectrum as well as multiplication factor. MCNP-BALL enables us to analyze pebble bed type cores such as PROTEUS precisely with the continuous energy Monte Carlo method. (author)

  12. Forward-weighted CADIS method for variance reduction of Monte Carlo calculations of distributions and multiple localized quantities

    International Nuclear Information System (INIS)

    Wagner, J. C.; Blakeman, E. D.; Peplow, D. E.

    2009-01-01

    This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is a variation on the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for some time to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain approximately uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented in the ADVANTG/MCNP framework and has been fully automated within the MAVRIC sequence of SCALE 6. Results of the application of the method to enabling the calculation of dose rates throughout an entire full-scale pressurized-water reactor facility are presented and discussed. (authors)

  13. Advanced Monte Carlo methods for thermal radiation transport

    Science.gov (United States)

    Wollaber, Allan B.

    During the past 35 years, the Implicit Monte Carlo (IMC) method proposed by Fleck and Cummings has been the standard Monte Carlo approach to solving the thermal radiative transfer (TRT) equations. However, the IMC equations are known to have accuracy limitations that can produce unphysical solutions. In this thesis, we explicitly provide the IMC equations with a Monte Carlo interpretation by including particle weight as one of its arguments. We also develop and test a stability theory for the 1-D, gray IMC equations applied to a nonlinear problem. We demonstrate that the worst case occurs for 0-D problems, and we extend the results to a stability algorithm that may be used for general linearizations of the TRT equations. We derive gray, Quasidiffusion equations that may be deterministically solved in conjunction with IMC to obtain an inexpensive, accurate estimate of the temperature at the end of the time step. We then define an average temperature T* to evaluate the temperature-dependent problem data in IMC, and we demonstrate that using T* is more accurate than using the (traditional) beginning-of-time-step temperature. We also propose an accuracy enhancement to the IMC equations: the use of a time-dependent "Fleck factor". This Fleck factor can be considered an automatic tuning of the traditionally defined user parameter alpha, which generally provides more accurate solutions at an increased cost relative to traditional IMC. We also introduce a global weight window that is proportional to the forward scalar intensity calculated by the Quasidiffusion method. This weight window improves the efficiency of the IMC calculation while conserving energy. All of the proposed enhancements are tested in 1-D gray and frequency-dependent problems. These enhancements do not unconditionally eliminate the unphysical behavior that can be seen in the IMC calculations. However, for fixed spatial and temporal grids, they suppress them and clearly work to make the solution more

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

    International Nuclear Information System (INIS)

    Diamantis, Nikolaos G.; Manousakis, Efstratios

    2016-01-01

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

  15. 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)

  16. A study of potential energy curves from the model space quantum Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Ohtsuka, Yuhki; Ten-no, Seiichiro, E-mail: tenno@cs.kobe-u.ac.jp [Department of Computational Sciences, Graduate School of System Informatics, Kobe University, Nada-ku, Kobe 657-8501 (Japan)

    2015-12-07

    We report on the first application of the model space quantum Monte Carlo (MSQMC) to potential energy curves (PECs) for the excited states of C{sub 2}, N{sub 2}, and O{sub 2} to validate the applicability of the method. A parallel MSQMC code is implemented with the initiator approximation to enable efficient sampling. The PECs of MSQMC for various excited and ionized states are compared with those from the Rydberg-Klein-Rees and full configuration interaction methods. The results indicate the usefulness of MSQMC for precise PECs in a wide range obviating problems concerning quasi-degeneracy.

  17. Modelling a gamma irradiation process using the Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Soares, Gabriela A.; Pereira, Marcio T., E-mail: gas@cdtn.br, E-mail: mtp@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

    2011-07-01

    In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)

  18. Radiative heat transfer by the Monte Carlo method

    CERN Document Server

    Hartnett †, James P; Cho, Young I; Greene, George A; Taniguchi, Hiroshi; Yang, Wen-Jei; Kudo, Kazuhiko

    1995-01-01

    This book presents the basic principles and applications of radiative heat transfer used in energy, space, and geo-environmental engineering, and can serve as a reference book for engineers and scientists in researchand development. A PC disk containing software for numerical analyses by the Monte Carlo method is included to provide hands-on practice in analyzing actual radiative heat transfer problems.Advances in Heat Transfer is designed to fill the information gap between regularly scheduled journals and university level textbooks by providing in-depth review articles over a broader scope than journals or texts usually allow.Key Features* Offers solution methods for integro-differential formulation to help avoid difficulties* Includes a computer disk for numerical analyses by PC* Discusses energy absorption by gas and scattering effects by particles* Treats non-gray radiative gases* Provides example problems for direct applications in energy, space, and geo-environmental engineering

  19. Modelling a gamma irradiation process using the Monte Carlo method

    International Nuclear Information System (INIS)

    Soares, Gabriela A.; Pereira, Marcio T.

    2011-01-01

    In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)

  20. 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

  1. Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

    Science.gov (United States)

    Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

    2014-12-01

    Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

  2. Kinetics of electron-positron pair plasmas using an adaptive Monte Carlo method

    International Nuclear Information System (INIS)

    Pilla, R.P.; Shaham, J.

    1997-01-01

    A new algorithm for implementing the adaptive Monte Carlo method is given. It is used to solve the Boltzmann equations that describe the time evolution of a nonequilibrium electron-positron pair plasma containing high-energy photons. These are coupled nonlinear integro-differential equations. The collision kernels for the photons as well as pairs are evaluated for Compton scattering, pair annihilation and creation, bremsstrahlung, and Coulomb collisions. They are given as multidimensional integrals which are valid for all energies. For an homogeneous and isotropic plasma with no particle escape, the equilibrium solution is expressed analytically in terms of the initial conditions. For two specific cases, for which the photon and the pair spectra are initially constant or have a power-law distribution within the given limits, the time evolution of the plasma is analyzed using the new method. The final spectra are found to be in a good agreement with the analytical solutions. The new algorithm is faster than the Monte Carlo scheme based on uniform sampling and more flexible than the numerical methods used in the past, which do not involve Monte Carlo sampling. It is also found to be very stable. Some astrophysical applications of this technique are discussed. copyright 1997 The American Astronomical Society

  3. SU-E-T-467: Implementation of Monte Carlo Dose Calculation for a Multileaf Collimator Equipped Robotic Radiotherapy System

    Energy Technology Data Exchange (ETDEWEB)

    Li, JS; Fan, J; Ma, C-M [Fox Chase Cancer Center, Philadelphia, PA (United States)

    2015-06-15

    Purpose: To improve the treatment efficiency and capabilities for full-body treatment, a robotic radiosurgery system has equipped with a multileaf collimator (MLC) to extend its accuracy and precision to radiation therapy. To model the MLC and include it in the Monte Carlo patient dose calculation is the goal of this work. Methods: The radiation source and the MLC were carefully modeled to consider the effects of the source size, collimator scattering, leaf transmission and leaf end shape. A source model was built based on the output factors, percentage depth dose curves and lateral dose profiles measured in a water phantom. MLC leaf shape, leaf end design and leaf tilt for minimizing the interleaf leakage and their effects on beam fluence and energy spectrum were all considered in the calculation. Transmission/leakage was added to the fluence based on the transmission factors of the leaf and the leaf end. The transmitted photon energy was tuned to consider the beam hardening effects. The calculated results with the Monte Carlo implementation was compared with measurements in homogeneous water phantom and inhomogeneous phantoms with slab lung or bone material for 4 square fields and 9 irregularly shaped fields. Results: The calculated output factors are compared with the measured ones and the difference is within 1% for different field sizes. The calculated dose distributions in the phantoms show good agreement with measurements using diode detector and films. The dose difference is within 2% inside the field and the distance to agreement is within 2mm in the penumbra region. The gamma passing rate is more than 95% with 2%/2mm criteria for all the test cases. Conclusion: Implementation of Monte Carlo dose calculation for a MLC equipped robotic radiosurgery system is completed successfully. The accuracy of Monte Carlo dose calculation with MLC is clinically acceptable. This work was supported by Accuray Inc.

  4. SU-E-T-467: Implementation of Monte Carlo Dose Calculation for a Multileaf Collimator Equipped Robotic Radiotherapy System

    International Nuclear Information System (INIS)

    Li, JS; Fan, J; Ma, C-M

    2015-01-01

    Purpose: To improve the treatment efficiency and capabilities for full-body treatment, a robotic radiosurgery system has equipped with a multileaf collimator (MLC) to extend its accuracy and precision to radiation therapy. To model the MLC and include it in the Monte Carlo patient dose calculation is the goal of this work. Methods: The radiation source and the MLC were carefully modeled to consider the effects of the source size, collimator scattering, leaf transmission and leaf end shape. A source model was built based on the output factors, percentage depth dose curves and lateral dose profiles measured in a water phantom. MLC leaf shape, leaf end design and leaf tilt for minimizing the interleaf leakage and their effects on beam fluence and energy spectrum were all considered in the calculation. Transmission/leakage was added to the fluence based on the transmission factors of the leaf and the leaf end. The transmitted photon energy was tuned to consider the beam hardening effects. The calculated results with the Monte Carlo implementation was compared with measurements in homogeneous water phantom and inhomogeneous phantoms with slab lung or bone material for 4 square fields and 9 irregularly shaped fields. Results: The calculated output factors are compared with the measured ones and the difference is within 1% for different field sizes. The calculated dose distributions in the phantoms show good agreement with measurements using diode detector and films. The dose difference is within 2% inside the field and the distance to agreement is within 2mm in the penumbra region. The gamma passing rate is more than 95% with 2%/2mm criteria for all the test cases. Conclusion: Implementation of Monte Carlo dose calculation for a MLC equipped robotic radiosurgery system is completed successfully. The accuracy of Monte Carlo dose calculation with MLC is clinically acceptable. This work was supported by Accuray Inc

  5. 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...

  6. 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.

  7. Optimal mesh hierarchies in Multilevel Monte Carlo methods

    KAUST Repository

    Von Schwerin, Erik

    2016-01-01

    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.

  8. Recursive Monte Carlo method for deep-penetration problems

    International Nuclear Information System (INIS)

    Goldstein, M.; Greenspan, E.

    1980-01-01

    The Recursive Monte Carlo (RMC) method developed for estimating importance function distributions in deep-penetration problems is described. Unique features of the method, including the ability to infer the importance function distribution pertaining to many detectors from, essentially, a single M.C. run and the ability to use the history tape created for a representative region to calculate the importance function in identical regions, are illustrated. The RMC method is applied to the solution of two realistic deep-penetration problems - a concrete shield problem and a Tokamak major penetration problem. It is found that the RMC method can provide the importance function distributions, required for importance sampling, with accuracy that is suitable for an efficient solution of the deep-penetration problems considered. The use of the RMC method improved, by one to three orders of magnitude, the solution efficiency of the two deep-penetration problems considered: a concrete shield problem and a Tokamak major penetration problem. 8 figures, 4 tables

  9. 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)

  10. Modeling granular phosphor screens by Monte Carlo methods

    International Nuclear Information System (INIS)

    Liaparinos, Panagiotis F.; Kandarakis, Ioannis S.; Cavouras, Dionisis A.; Delis, Harry B.; Panayiotakis, George S.

    2006-01-01

    The intrinsic phosphor properties are of significant importance for the performance of phosphor screens used in medical imaging systems. In previous analytical-theoretical and Monte Carlo studies on granular phosphor materials, values of optical properties, and light interaction cross sections were found by fitting to experimental data. These values were then employed for the assessment of phosphor screen imaging performance. However, it was found that, depending on the experimental technique and fitting methodology, the optical parameters of a specific phosphor material varied within a wide range of values, i.e., variations of light scattering with respect to light absorption coefficients were often observed for the same phosphor material. In this study, x-ray and light transport within granular phosphor materials was studied by developing a computational model using Monte Carlo methods. The model was based on the intrinsic physical characteristics of the phosphor. Input values required to feed the model can be easily obtained from tabulated data. The complex refractive index was introduced and microscopic probabilities for light interactions were produced, using Mie scattering theory. Model validation was carried out by comparing model results on x-ray and light parameters (x-ray absorption, statistical fluctuations in the x-ray to light conversion process, number of emitted light photons, output light spatial distribution) with previous published experimental data on Gd 2 O 2 S:Tb phosphor material (Kodak Min-R screen). Results showed the dependence of the modulation transfer function (MTF) on phosphor grain size and material packing density. It was predicted that granular Gd 2 O 2 S:Tb screens of high packing density and small grain size may exhibit considerably better resolution and light emission properties than the conventional Gd 2 O 2 S:Tb screens, under similar conditions (x-ray incident energy, screen thickness)

  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. 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.

  13. Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

    Science.gov (United States)

    Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

    2017-01-01

    The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

  14. Application to risk analysis of Monte Carlo method

    International Nuclear Information System (INIS)

    Mihara, Takashi

    2001-01-01

    Phased mission analysis code, PHAMMON by means of monte carlo method is developed for reliability assessment of decay heat removal system in LMFBR. Success criteria and grace periods of the decay heat removal system which has long mission times (∼1 week or ∼1 month) change as a function of time. It is necessary to divide mission time into some phases. In probability safety assessment (PSA) of real systems, it usually happens that the mean time to component failure (MTTF) is considerably long (1000-10 6 hours) and the mean time to component repair (MTTR) is short (∼10 hours). The failure probability of the systems, therefore, is extremely small (10 -6 -10 -9 ). Suitable variance reduction techniques are needed. The PHAMMON code involved two kinds of variance reduction techniques: (1) forced time transitions, and (2) failure biasing. For further reducing the variance of the result from the PHAMMON code execution, a biasing method of the transitions towards the closest cut set incorporating a new distance concept is introduced to the PHAMMON code. Failure probability and it's fractional standard deviation for the decay heat removal system are calculated by the PHAMMON code under the conditions of various success criteria over 168hrs after reactor shutdown. The biasing of the transition towards the closet cut set is an effective means of reducing the variance. (M. Suetake)

  15. 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

  16. Implementation of a Markov Chain Monte Carlo method to inorganic aerosol modeling of observations from the MCMA-2003 campaign – Part II: Model application to the CENICA, Pedregal and Santa Ana sites

    Directory of Open Access Journals (Sweden)

    F. M. San Martini

    2006-01-01

    Full Text Available A Markov Chain Monte Carlo model for integrating the observations of inorganic species with a thermodynamic equilibrium model was presented in Part I of this series. Using observations taken at three ground sites, i.e. a residential, industrial and rural site, during the MCMA-2003 campaign in Mexico City, the model is used to analyze the inorganic particle and ammonia data and to predict gas phase concentrations of nitric and hydrochloric acid. In general, the model is able to accurately predict the observed inorganic particle concentrations at all three sites. The agreement between the predicted and observed gas phase ammonia concentration is excellent. The NOz concentration calculated from the NOy, NO and NO2 observations is of limited use in constraining the gas phase nitric acid concentration given the large uncertainties in this measure of nitric acid and additional reactive nitrogen species. Focusing on the acidic period of 9–11 April identified by Salcedo et al. (2006, the model accurately predicts the particle phase observations during this period with the exception of the nitrate predictions after 10:00 a.m. (Central Daylight Time, CDT on 9 April, where the model underpredicts the observations by, on average, 20%. This period had a low planetary boundary layer, very high particle concentrations, and higher than expected nitrogen dioxide concentrations. For periods when the particle chloride observations are consistently above the detection limit, the model is able to both accurately predict the particle chloride mass concentrations and provide well-constrained HCl (g concentrations. The availability of gas-phase ammonia observations helps constrain the predicted HCl (g concentrations. When the particles are aqueous, the most likely concentrations of HCl (g are in the sub-ppbv range. The most likely predicted concentration of HCl (g was found to reach concentrations of order 10 ppbv if the particles are dry. Finally, the

  17. Implementation of the DPM Monte Carlo code on a parallel architecture for treatment planning applications.

    Science.gov (United States)

    Tyagi, Neelam; Bose, Abhijit; Chetty, Indrin J

    2004-09-01

    We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1 x 10(8) or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8 x 10(8) histories. For a smaller number of histories (1 x 10(8)) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1 x 10(8) histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy.

  18. Implementation of the DPM Monte Carlo code on a parallel architecture for treatment planning applications

    International Nuclear Information System (INIS)

    Tyagi, Neelam; Bose, Abhijit; Chetty, Indrin J.

    2004-01-01

    We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1x10 8 or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8x10 8 histories. For a smaller number of histories (1x10 8 ) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1x10 8 histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy

  19. 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

  20. New Hybrid Monte Carlo methods for efficient sampling. From physics to biology and statistics

    International Nuclear Information System (INIS)

    Akhmatskaya, Elena; Reich, Sebastian

    2011-01-01

    We introduce a class of novel hybrid methods for detailed simulations of large complex systems in physics, biology, materials science and statistics. These generalized shadow Hybrid Monte Carlo (GSHMC) methods combine the advantages of stochastic and deterministic simulation techniques. They utilize a partial momentum update to retain some of the dynamical information, employ modified Hamiltonians to overcome exponential performance degradation with the system’s size and make use of multi-scale nature of complex systems. Variants of GSHMCs were developed for atomistic simulation, particle simulation and statistics: GSHMC (thermodynamically consistent implementation of constant-temperature molecular dynamics), MTS-GSHMC (multiple-time-stepping GSHMC), meso-GSHMC (Metropolis corrected dissipative particle dynamics (DPD) method), and a generalized shadow Hamiltonian Monte Carlo, GSHmMC (a GSHMC for statistical simulations). All of these are compatible with other enhanced sampling techniques and suitable for massively parallel computing allowing for a range of multi-level parallel strategies. A brief description of the GSHMC approach, examples of its application on high performance computers and comparison with other existing techniques are given. Our approach is shown to resolve such problems as resonance instabilities of the MTS methods and non-preservation of thermodynamic equilibrium properties in DPD, and to outperform known methods in sampling efficiency by an order of magnitude. (author)

  1. Medical Imaging Image Quality Assessment with Monte Carlo Methods

    International Nuclear Information System (INIS)

    Michail, C M; Fountos, G P; Kalyvas, N I; Valais, I G; Kandarakis, I S; Karpetas, G E; Martini, Niki; Koukou, Vaia

    2015-01-01

    The aim of the present study was to assess image quality of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction, with cluster computing. The PET scanner simulated in this study was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the Modulation Transfer Function (MTF). MTF curves were estimated from transverse reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL algorithm. OSMAPOSL reconstruction was assessed by using various subsets (3 to 21) and iterations (1 to 20), as well as by using various beta (hyper) parameter values. MTF values were found to increase up to the 12th iteration whereas remain almost constant thereafter. MTF improves by using lower beta values. The simulated PET evaluation method based on the TLC plane source can be also useful in research for the further development of PET and SPECT scanners though GATE simulations. (paper)

  2. Safety assessment of infrastructures using a new Bayesian Monte Carlo method

    NARCIS (Netherlands)

    Rajabali Nejad, Mohammadreza; Demirbilek, Z.

    2011-01-01

    A recently developed Bayesian Monte Carlo (BMC) method and its application to safety assessment of structures are described in this paper. We use a one-dimensional BMC method that was proposed in 2009 by Rajabalinejad in order to develop a weighted logical dependence between successive Monte Carlo

  3. A new Monte Carlo method for neutron noise calculations in the frequency domain

    International Nuclear Information System (INIS)

    Rouchon, Amélie; Zoia, Andrea; Sanchez, Richard

    2017-01-01

    Neutron noise equations, which are obtained by assuming small perturbations of macroscopic cross sections around a steady-state neutron field and by subsequently taking the Fourier transform in the frequency domain, have been usually solved by analytical techniques or by resorting to diffusion theory. A stochastic approach has been recently proposed in the literature by using particles with complex-valued weights and by applying a weight cancellation technique. We develop a new Monte Carlo algorithm that solves the transport neutron noise equations in the frequency domain. The stochastic method presented here relies on a modified collision operator and does not need any weight cancellation technique. In this paper, both Monte Carlo methods are compared with deterministic methods (diffusion in a slab geometry and transport in a simplified rod model) for several noise frequencies and for isotropic and anisotropic noise sources. Our stochastic method shows better performances in the frequency region of interest and is easier to implement because it relies upon the conventional algorithm for fixed-source problems.

  4. Implementation of mathematical phantom of hand and forearm in GEANT4 Monte Carlo code

    International Nuclear Information System (INIS)

    Pessanha, Paula Rocha; Queiroz Filho, Pedro Pacheco de; Santos, Denison de Souza

    2014-01-01

    In this work, the implementation of a hand and forearm Geant4 phantom code, for further evaluation of occupational exposure of ends of the radionuclides decay manipulated during procedures involving the use of injection syringe. The simulation model offered by Geant4 includes a full set of features, with the reconstruction of trajectories, geometries and physical models. For this work, the values calculated in the simulation are compared with the measurements rates by thermoluminescent dosimeters (TLDs) in physical phantom REMAB®. From the analysis of the data obtained through simulation and experimentation, of the 14 points studied, there was a discrepancy of only 8.2% of kerma values found, and these figures are considered compatible. The geometric phantom implemented in Geant4 Monte Carlo code was validated and can be used later for the evaluation of doses at ends

  5. Enhanced least squares Monte Carlo method for real-time decision optimizations for evolving natural hazards

    DEFF Research Database (Denmark)

    Anders, Annett; Nishijima, Kazuyoshi

    The present paper aims at enhancing a solution approach proposed by Anders & Nishijima (2011) to real-time decision problems in civil engineering. The approach takes basis in the Least Squares Monte Carlo method (LSM) originally proposed by Longstaff & Schwartz (2001) for computing American option...... prices. In Anders & Nishijima (2011) the LSM is adapted for a real-time operational decision problem; however it is found that further improvement is required in regard to the computational efficiency, in order to facilitate it for practice. This is the focus in the present paper. The idea behind...... the improvement of the computational efficiency is to “best utilize” the least squares method; i.e. least squares method is applied for estimating the expected utility for terminal decisions, conditional on realizations of underlying random phenomena at respective times in a parametric way. The implementation...

  6. BACKWARD AND FORWARD MONTE CARLO METHOD IN POLARIZED RADIATIVE TRANSFER

    Energy Technology Data Exchange (ETDEWEB)

    Yong, Huang; Guo-Dong, Shi; Ke-Yong, Zhu, E-mail: huangy_zl@263.net [School of Aeronautical Science and Engineering, Beihang University, Beijing 100191 (China)

    2016-03-20

    In general, the Stocks vector cannot be calculated in reverse in the vector radiative transfer. This paper presents a novel backward and forward Monte Carlo simulation strategy to study the vector radiative transfer in the participated medium. A backward Monte Carlo process is used to calculate the ray trajectory and the endpoint of the ray. The Stocks vector is carried out by a forward Monte Carlo process. A one-dimensional graded index semi-transparent medium was presented as the physical model and the thermal emission consideration of polarization was studied in the medium. The solution process to non-scattering, isotropic scattering, and the anisotropic scattering medium, respectively, is discussed. The influence of the optical thickness and albedo on the Stocks vector are studied. The results show that the U, V-components of the apparent Stocks vector are very small, but the Q-component of the apparent Stocks vector is relatively larger, which cannot be ignored.

  7. Fourier path-integral Monte Carlo methods: Partial averaging

    International Nuclear Information System (INIS)

    Doll, J.D.; Coalson, R.D.; Freeman, D.L.

    1985-01-01

    Monte Carlo Fourier path-integral techniques are explored. It is shown that fluctuation renormalization techniques provide an effective means for treating the effects of high-order Fourier contributions. The resulting formalism is rapidly convergent, is computationally convenient, and has potentially useful variational aspects

  8. 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...

  9. Review of quantum Monte Carlo methods and results for Coulombic systems

    International Nuclear Information System (INIS)

    Ceperley, D.

    1983-01-01

    The various Monte Carlo methods for calculating ground state energies are briefly reviewed. Then a summary of the charged systems that have been studied with Monte Carlo is given. These include the electron gas, small molecules, a metal slab and many-body hydrogen

  10. Multilevel and Multi-index Monte Carlo methods for the McKean–Vlasov equation

    KAUST Repository

    Haji Ali, Abdul Lateef; Tempone, Raul

    2017-01-01

    of particles. Based on these two parameters, we consider different variants of the Monte Carlo and Multilevel Monte Carlo (MLMC) methods and show that, in the best case, the optimal work complexity of MLMC, to estimate the functional in one typical setting

  11. Hybrid and Parallel Domain-Decomposition Methods Development to Enable Monte Carlo for Reactor Analyses

    International Nuclear Information System (INIS)

    Wagner, John C.; Mosher, Scott W.; Evans, Thomas M.; Peplow, Douglas E.; Turner, John A.

    2010-01-01

    This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform real commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the gold standard for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method, which

  12. Hybrid and parallel domain-decomposition methods development to enable Monte Carlo for reactor analyses

    International Nuclear Information System (INIS)

    Wagner, J.C.; Mosher, S.W.; Evans, T.M.; Peplow, D.E.; Turner, J.A.

    2010-01-01

    This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method

  13. Contribution to the solution of the multigroup Boltzmann equation by the determinist methods and the Monte Carlo method; Contribution a la resolution de l`equation de Bolztmann en multigroupe par les methodes deterministes et Monte-Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Li, M

    1998-08-01

    In this thesis, two methods for solving the multigroup Boltzmann equation have been studied: the interface-current method and the Monte Carlo method. A new version of interface-current (IC) method has been develop in the TDT code at SERMA, where the currents of interface are represented by piecewise constant functions in the solid angle space. The convergence of this method to the collision probability (CP) method has been tested. Since the tracking technique is used for both the IC and CP methods, it is necessary to normalize he collision probabilities obtained by this technique. Several methods for this object have been studied and implemented in our code, we have compared their performances and chosen the best one as the standard choice. The transfer matrix treatment has been a long-standing difficulty for the multigroup Monte Carlo method: when the cross-sections are converted into multigroup form, important negative parts will appear in the angular transfer laws represented by low-order Legendre polynomials. Several methods based on the preservation of the first moments, such as the discrete angles methods and the equally-probable step function method, have been studied and implemented in the TRIMARAN-II code. Since none of these codes has been satisfactory, a new method, the non equally-probably step function method, has been proposed and realized in our code. The comparisons for these methods have been done in several aspects: the preservation of the moments required, the calculation of a criticality problem and the calculation of a neutron-transfer in water problem. The results have showed that the new method is the best one in all these comparisons, and we have proposed that it should be a standard choice for the multigroup transfer matrix. (author) 76 refs.

  14. A contribution to the Monte Carlo method in the reactor theory

    International Nuclear Information System (INIS)

    Lieberoth, J.

    1976-01-01

    The report gives a contribution to the further development of the Monte-Carlo Method to solve the neutron transport problem. The necessary fundamentals, mainly of statistical nature, are collected and partly derived, such as the statistical weight, the use of random numbers or the Monte-Carlo integration method. Special emphasis is put on the so-called team-method, which will help to reduce the statistical error of Monte-Carlo estimates, and on the path-method, which can be used to calculate the neutron fluxes in pre-defined local points

  15. 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

  16. Quantum Monte Carlo for large chemical systems: implementing efficient strategies for peta scale platforms and beyond

    International Nuclear Information System (INIS)

    Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

    2013-01-01

    Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC-Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC-Chem has been shown to be capable of running at the peta scale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exa scale platforms with a comparable level of efficiency is expected to be feasible. (authors)

  17. 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.

  18. A study of certain Monte Carlo search and optimisation methods

    International Nuclear Information System (INIS)

    Budd, C.

    1984-11-01

    Studies are described which might lead to the development of a search and optimisation facility for the Monte Carlo criticality code MONK. The facility envisaged could be used to maximise a function of k-effective with respect to certain parameters of the system or, alternatively, to find the system (in a given range of systems) for which that function takes a given value. (UK)

  19. Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

    Science.gov (United States)

    Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

    2010-10-01

    Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

  20. The FLUKA code for application of Monte Carlo methods to promote high precision ion beam therapy

    CERN Document Server

    Parodi, K; Cerutti, F; Ferrari, A; Mairani, A; Paganetti, H; Sommerer, F

    2010-01-01

    Monte Carlo (MC) methods are increasingly being utilized to support several aspects of commissioning and clinical operation of ion beam therapy facilities. In this contribution two emerging areas of MC applications are outlined. The value of MC modeling to promote accurate treatment planning is addressed via examples of application of the FLUKA code to proton and carbon ion therapy at the Heidelberg Ion Beam Therapy Center in Heidelberg, Germany, and at the Proton Therapy Center of Massachusetts General Hospital (MGH) Boston, USA. These include generation of basic data for input into the treatment planning system (TPS) and validation of the TPS analytical pencil-beam dose computations. Moreover, we review the implementation of PET/CT (Positron-Emission-Tomography / Computed- Tomography) imaging for in-vivo verification of proton therapy at MGH. Here, MC is used to calculate irradiation-induced positron-emitter production in tissue for comparison with the +-activity measurement in order to infer indirect infor...

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

    International Nuclear Information System (INIS)

    Zuo Yinghong; Wang Jianguo

    2012-01-01

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

  2. Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues

    International Nuclear Information System (INIS)

    Harris, G.; Van Horn, R.

    1996-06-01

    The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL

  3. Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues

    Energy Technology Data Exchange (ETDEWEB)

    Harris, G.; Van Horn, R.

    1996-06-01

    The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL.

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

    International Nuclear Information System (INIS)

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

    2013-02-01

    We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N -1/2 , where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to N -1 . We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.

  5. A perturbation-based susbtep method for coupled depletion Monte-Carlo codes

    International Nuclear Information System (INIS)

    Kotlyar, Dan; Aufiero, Manuele; Shwageraus, Eugene; Fratoni, Massimiliano

    2017-01-01

    Highlights: • The GPT method allows to calculate the sensitivity coefficients to any perturbation. • Full Jacobian of sensitivities, cross sections (XS) to concentrations, may be obtained. • The time dependent XS is obtained by combining the GPT and substep methods. • The proposed GPT substep method considerably reduces the time discretization error. • No additional MC transport solutions are required within the time step. - Abstract: Coupled Monte Carlo (MC) methods are becoming widely used in reactor physics analysis and design. Many research groups therefore, developed their own coupled MC depletion codes. Typically, in such coupled code systems, neutron fluxes and cross sections are provided to the depletion module by solving a static neutron transport problem. These fluxes and cross sections are representative only of a specific time-point. In reality however, both quantities would change through the depletion time interval. Recently, Generalized Perturbation Theory (GPT) equivalent method that relies on collision history approach was implemented in Serpent MC code. This method was used here to calculate the sensitivity of each nuclide and reaction cross section due to the change in concentration of every isotope in the system. The coupling method proposed in this study also uses the substep approach, which incorporates these sensitivity coefficients to account for temporal changes in cross sections. As a result, a notable improvement in time dependent cross section behavior was obtained. The method was implemented in a wrapper script that couples Serpent with an external depletion solver. The performance of this method was compared with other existing methods. The results indicate that the proposed method requires substantially less MC transport solutions to achieve the same accuracy.

  6. Multilevel markov chain monte carlo method for high-contrast single-phase flow problems

    KAUST Repository

    Efendiev, Yalchin R.; Jin, Bangti; Michael, Presho; Tan, Xiaosi

    2014-01-01

    Carlo (MLMC) methods. The former provides a hierarchy of approximations of different resolution, whereas the latter gives an efficient way to estimate quantities of interest using samples on different levels. The number of basis functions in the online

  7. Review of Monte Carlo methods for particle multiplicity evaluation

    CERN Document Server

    Armesto-Pérez, Nestor

    2005-01-01

    I present a brief review of the existing models for particle multiplicity evaluation in heavy ion collisions which are at our disposal in the form of Monte Carlo simulators. Models are classified according to the physical mechanisms with which they try to describe the different stages of a high-energy collision between heavy nuclei. A comparison of predictions, as available at the beginning of year 2000, for multiplicities in central AuAu collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and PbPb collisions at the CERN Large Hadron Collider (LHC) is provided.

  8. Review of Monte Carlo methods for particle multiplicity evaluation

    International Nuclear Information System (INIS)

    Armesto, Nestor

    2005-01-01

    I present a brief review of the existing models for particle multiplicity evaluation in heavy ion collisions which are at our disposal in the form of Monte Carlo simulators. Models are classified according to the physical mechanisms with which they try to describe the different stages of a high-energy collision between heavy nuclei. A comparison of predictions, as available at the beginning of year 2000, for multiplicities in central AuAu collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and PbPb collisions at the CERN Large Hadron Collider (LHC) is provided

  9. Dose optimization based on linear programming implemented in a system for treatment planning in Monte Carlo

    International Nuclear Information System (INIS)

    Ureba, A.; Palma, B. A.; Leal, A.

    2011-01-01

    Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    International Nuclear Information System (INIS)

    Shimizu, Takashi

    2007-01-01

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

  12. Calibration of the identiFINDER detector for the iodine measurement in thyroid using the Monte Carlo method

    International Nuclear Information System (INIS)

    Ramos M, D.; Yera S, Y.; Lopez B, G. M.; Acosta R, N.; Vergara G, A.

    2014-08-01

    This work is based on the determination of the detection efficiency of 125 I and 131 I in thyroid of the identiFINDER detector using the Monte Carlo method. The suitability of the calibration method is analyzed, when comparing the results of the direct Monte Carlo method with the corrected, choosing the latter because the differences with the real efficiency stayed below 10%. To simulate the detector their geometric parameters were optimized using a tomographic study, what allowed the uncertainties minimization of the estimates. Finally were obtained the simulations of the detector geometry-point source to find the correction factors to 5 cm, 15 cm and 25 cm, and those corresponding to the detector-simulator arrangement for the method validation and final calculation of the efficiency, demonstrating that in the Monte Carlo method implementation if simulates at a greater distance than the used in the Laboratory measurements an efficiency overestimation can be obtained, while if simulates at a shorter distance this will be underestimated, so should be simulated at the same distance to which will be measured in the reality. Also, is achieved the obtaining of the efficiency curves and minimum detectable activity for the measurement of 131 I and 125 I. In general is achieved the implementation of the Monte Carlo methodology for the identiFINDER calibration with the purpose of estimating the measured activity of iodine in thyroid. This method represents an ideal way to replace the lack of patterns solutions and simulators assuring the capacities of the Internal Contamination Laboratory of the Centro de Proteccion e Higiene de las Radiaciones are always calibrated for the iodine measurement in thyroid. (author)

  13. 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

  14. Application of the Monte Carlo method to diagnostic radiology

    International Nuclear Information System (INIS)

    Persliden, J.

    1986-01-01

    A Monte Carlo program for photon transport is developed. The program is used to investigate the energy imparted to water slabs (simulating patients), and the related backscattered and transmitted energies as functions of primary photon energy and water slab thickness. The accuracy of the results depends on the cross-section data for the probabilities of the various interactions in the slab and on the physical quantity calculated. Backscattered energy fractions can vary by as much as 10-20 %, using different sets of published data for the photoelectric cross section while imparted fractions are only slightly affected. The results are used to calculate improved conversion factors for determining the energy imparted to the patient in X-ray diagnostic examinations from measurements of the air collision kerma integrated over beam area. The small angle distribution of scattered photons transmitted through a water slab, relevant to problems of image quality, is calculated taking into account the diffraction phenomena of liquid water. The calculations are performed with a collision density estimator. This estimator makes it possible to calculate important physical quantities which are virtually impracticable to assess with the Monte Carlo codes commonly used in medical physics or in experiments. With the collision density estimator, the influence of air gaps on the reduction of scattered radiation is investigated for different detectors, field areas and primary X-ray spectra. Contrast degradation and contrast improvement factors are given as functions of field area for various air gaps. (With 105 refs.) (author)

  15. Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

    Directory of Open Access Journals (Sweden)

    Joko Siswantoro

    2014-01-01

    Full Text Available Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.

  16. Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.

    Science.gov (United States)

    Siswantoro, Joko; Prabuwono, Anton Satria; Abdullah, Azizi; Idrus, Bahari

    2014-01-01

    Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  18. The calculation of neutron flux using Monte Carlo method

    Science.gov (United States)

    Günay, Mehtap; Bardakçı, Hilal

    2017-09-01

    In this study, a hybrid reactor system was designed by using 99-95% Li20Sn80 + 1-5% RG-Pu, 99-95% Li20Sn80 + 1-5% RG-PuF4, and 99-95% Li20Sn80 + 1-5% RG-PuO2 fluids, ENDF/B-VII.0 evaluated nuclear data library and 9Cr2WVTa structural material. The fluids were used in the liquid first wall, liquid second wall (blanket) and shield zones of a fusion-fission hybrid reactor system. The neutron flux was calculated according to the mixture components, radial, energy spectrum in the designed hybrid reactor system for the selected fluids, library and structural material. Three-dimensional nucleonic calculations were performed using the most recent version MCNPX-2.7.0 the Monte Carlo code.

  19. Whole core calculations of power reactors by Monte Carlo method

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki; Mori, Takamasa

    1993-01-01

    Whole core calculations have been performed for a commercial size PWR and a prototype LMFBR by using vectorized Monte Carlo codes. Geometries of cores were precisely represented in a pin by pin model. The calculated parameters were k eff , control rod worth, power distribution and so on. Both multigroup and continuous energy models were used and the accuracy of multigroup approximation was evaluated through the comparison of both results. One million neutron histories were tracked to considerably reduce variances. It was demonstrated that the high speed vectorized codes could calculate k eff , assembly power and some reactivity worths within practical computation time. For pin power and small reactivity worth calculations, the order of 10 million histories would be necessary. Required number of histories to achieve target design accuracy were estimated for those neutronic parameters. (orig.)

  20. A hybrid transport-diffusion Monte Carlo method for frequency-dependent radiative-transfer simulations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Thompson, Kelly G.; Urbatsch, Todd J.

    2012-01-01

    Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations in optically thick media. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many smaller Monte Carlo steps, thus improving the efficiency of the simulation. In this paper, we present an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold, as optical thickness is typically a decreasing function of frequency. Above this threshold we employ standard Monte Carlo, which results in a hybrid transport-diffusion scheme. With a set of frequency-dependent test problems, we confirm the accuracy and increased efficiency of our new DDMC method.

  1. Buildup factors for multilayer shieldings in deterministic methods and their comparison with Monte Carlo

    International Nuclear Information System (INIS)

    Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.

    2008-01-01

    In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)

  2. Buildup factors for multilayer shieldings in deterministic methods and their comparison with Monte Carlo

    International Nuclear Information System (INIS)

    Listjak, M.; Slavik, O.; Kubovcova, D.; Vermeersch, F.

    2009-01-01

    In general there are two ways how to calculate effective doses. The first way is by use of deterministic methods like point kernel method which is implemented in Visiplan or Microshield. These kind of calculations are very fast, but they are not very convenient for a complex geometry with shielding composed of more then one material in meaning of result precision. In spite of this that programs are sufficient for ALARA optimisation calculations. On other side there are Monte Carlo methods which can be used for calculations. This way of calculation is quite precise in comparison with reality but calculation time is usually very large. Deterministic method like programs have one disadvantage -usually there is option to choose buildup factor (BUF) only for one material in multilayer stratified slabs shielding calculation problems even if shielding is composed from different materials. In literature there are proposed different formulas for multilayer BUF approximation. Aim of this paper was to examine these different formulas and their comparison with MCNP calculations. At first ware compared results of Visiplan and Microshield. Simple geometry was modelled - point source behind single and double slab shielding. For Build-up calculations was chosen Geometric Progression method (feature of the newest version of Visiplan) because there are lower deviations in comparison with Taylor fitting. (authors)

  3. Analysis of possibility to apply new mathematical methods (R-function theory) in Monte Carlo simulation of complex geometry

    International Nuclear Information System (INIS)

    Altiparmakov, D.

    1988-12-01

    This analysis is part of the report on ' Implementation of geometry module of 05R code in another Monte Carlo code', chapter 6.0: establishment of future activity related to geometry in Monte Carlo method. The introduction points out some problems in solving complex three-dimensional models which induce the need for developing more efficient geometry modules in Monte Carlo calculations. Second part include formulation of the problem and geometry module. Two fundamental questions to be solved are defined: (1) for a given point, it is necessary to determine material region or boundary where it belongs, and (2) for a given direction, all cross section points with material regions should be determined. Third part deals with possible connection with Monte Carlo calculations for computer simulation of geometry objects. R-function theory enables creation of geometry module base on the same logic (complex regions are constructed by elementary regions sets operations) as well as construction geometry codes. R-functions can efficiently replace functions of three-value logic in all significant models. They are even more appropriate for application since three-value logic is not typical for digital computers which operate in two-value logic. This shows that there is a need for work in this field. It is shown that there is a possibility to develop interactive code for computer modeling of geometry objects in parallel with development of geometry module [sr

  4. Implementation of the P barANDA Planar-GEM tracking detector in Monte Carlo simulations

    Science.gov (United States)

    Divani Veis, Nazila; Ehret, Andre; Firoozabadi, Mohammad M.; Karabowicz, Radoslaw; Maas, Frank; Saito, Nami; Saito, Takehiko R.; Voss, Bernd; PANDA Gem-Tracker Subgroup

    2018-02-01

    The P barANDA experiment at FAIR will be performed to investigate different aspects of hadron physics using anti-proton beams interacting with a fixed nuclear target. The experimental setup consists of a complex series of detector components covering a large solid angle. A detector with a gaseous active media equipped with gas electron multiplier (GEM) technique will be employed to measure tracks of charged particles at forward direction in order to achieve a high momentum resolution. In this work, a full setup of the GEM tracking detector has been implemented in the P barANDA Monte Carlo simulation package (PandaRoot) based on the current technical and conceptual design, and the expected performance of the P barANDA GEM-tracking detector has been investigated. Furthermore, material-budget studies in terms of the radiation length of the P barANDA GEM-tracking detector have been made in order to investigate the effect of the detector materials and its associated structures to particle measurements.

  5. BREESE-II: auxiliary routines for implementing the albedo option in the MORSE Monte Carlo code

    International Nuclear Information System (INIS)

    Cain, V.R.; Emmett, M.B.

    1979-07-01

    The routines in the BREESE package implement the albedo option in the MORSE Monte Carlo Code by providing (1) replacements for the default routines ALBIN and ALBDO in the MORSE Code, (2) an estimating routine ALBDOE compatible with the SAMBO package in MORSE, and (3) a separate program that writes a tape of albedo data in the proper format for ALBIN. These extensions of the package initially reported in 1974 were performed jointly by ORNL, Bechtel Power Corporation, and Science Applications, Inc. The first version of BREESE had a fixed number of outgoing polar angles and the number of outgoing azimuthal angles was a function of the value of the outgoing polar angle only. An examination of differential albedo data led to this modified version which allows the number of outgoing polar angles to be dependent upon the value of the incoming polar angle and the number of outgoing azimuthal angles to be a function of the value of both incoming and outgoing polar angles

  6. Implementation of 3D models in the Monte Carlo code MCNP

    International Nuclear Information System (INIS)

    Lopes, Vivaldo; Millian, Felix M.; Guevara, Maria Victoria M.; Garcia, Fermin; Sena, Isaac; Menezes, Hugo

    2009-01-01

    On the area of numerical dosimetry Applied to medical physics, the scientific community focuses on the elaboration of new hybrids models based on 3D models. But different steps of the process of simulation with 3D models needed improvement and optimization in order to expedite the calculations and accuracy using this methodology. This project was developed with the aim of optimize the process of introduction of 3D models within the simulation code of radiation transport by Monte Carlo (MCNP). The fast implementation of these models on the simulation code allows the estimation of the dose deposited on the patient organs on a more personalized way, increasing the accuracy with this on the estimates and reducing the risks to health, caused by ionizing radiations. The introduction o these models within the MCNP was made through a input file, that was constructed through a sequence of images, bi-dimensional in the 3D model, generated using the program '3DSMAX', imported by the program 'TOMO M C' and thus, introduced as INPUT FILE of the MCNP code. (author)

  7. SU-E-T-277: Raystation Electron Monte Carlo Commissioning and Clinical Implementation

    International Nuclear Information System (INIS)

    Allen, C; Sansourekidou, P; Pavord, D

    2014-01-01

    Purpose: To evaluate the Raystation v4.0 Electron Monte Carlo algorithm for an Elekta Infinity linear accelerator and commission for clinical use. Methods: A total of 199 tests were performed (75 Export and Documentation, 20 PDD, 30 Profiles, 4 Obliquity, 10 Inhomogeneity, 55 MU Accuracy, and 5 Grid and Particle History). Export and documentation tests were performed with respect to MOSAIQ (Elekta AB) and RadCalc (Lifeline Software Inc). Mechanical jaw parameters and cutout magnifications were verified. PDD and profiles for open cones and cutouts were extracted and compared with water tank measurements. Obliquity and inhomogeneity for bone and air calculations were compared to film dosimetry. MU calculations for open cones and cutouts were performed and compared to both RadCalc and simple hand calculations. Grid size and particle histories were evaluated per energy for statistical uncertainty performance. Acceptability was categorized as follows: performs as expected, negligible impact on workflow, marginal impact, critical impact or safety concern, and catastrophic impact of safety concern. Results: Overall results are: 88.8% perform as expected, 10.2% negligible, 2.0% marginal, 0% critical and 0% catastrophic. Results per test category are as follows: Export and Documentation: 100% perform as expected, PDD: 100% perform as expected, Profiles: 66.7% perform as expected, 33.3% negligible, Obliquity: 100% marginal, Inhomogeneity 50% perform as expected, 50% negligible, MU Accuracy: 100% perform as expected, Grid and particle histories: 100% negligible. To achieve distributions with satisfactory smoothness level, 5,000,000 particle histories were used. Calculation time was approximately 1 hour. Conclusion: Raystation electron Monte Carlo is acceptable for clinical use. All of the issues encountered have acceptable workarounds. Known issues were reported to Raysearch and will be resolved in upcoming releases

  8. SU-E-T-277: Raystation Electron Monte Carlo Commissioning and Clinical Implementation

    Energy Technology Data Exchange (ETDEWEB)

    Allen, C; Sansourekidou, P; Pavord, D [Health-quest, Poughkeepsie, NY (United States)

    2014-06-01

    Purpose: To evaluate the Raystation v4.0 Electron Monte Carlo algorithm for an Elekta Infinity linear accelerator and commission for clinical use. Methods: A total of 199 tests were performed (75 Export and Documentation, 20 PDD, 30 Profiles, 4 Obliquity, 10 Inhomogeneity, 55 MU Accuracy, and 5 Grid and Particle History). Export and documentation tests were performed with respect to MOSAIQ (Elekta AB) and RadCalc (Lifeline Software Inc). Mechanical jaw parameters and cutout magnifications were verified. PDD and profiles for open cones and cutouts were extracted and compared with water tank measurements. Obliquity and inhomogeneity for bone and air calculations were compared to film dosimetry. MU calculations for open cones and cutouts were performed and compared to both RadCalc and simple hand calculations. Grid size and particle histories were evaluated per energy for statistical uncertainty performance. Acceptability was categorized as follows: performs as expected, negligible impact on workflow, marginal impact, critical impact or safety concern, and catastrophic impact of safety concern. Results: Overall results are: 88.8% perform as expected, 10.2% negligible, 2.0% marginal, 0% critical and 0% catastrophic. Results per test category are as follows: Export and Documentation: 100% perform as expected, PDD: 100% perform as expected, Profiles: 66.7% perform as expected, 33.3% negligible, Obliquity: 100% marginal, Inhomogeneity 50% perform as expected, 50% negligible, MU Accuracy: 100% perform as expected, Grid and particle histories: 100% negligible. To achieve distributions with satisfactory smoothness level, 5,000,000 particle histories were used. Calculation time was approximately 1 hour. Conclusion: Raystation electron Monte Carlo is acceptable for clinical use. All of the issues encountered have acceptable workarounds. Known issues were reported to Raysearch and will be resolved in upcoming releases.

  9. Implementation of a Monte Carlo simulation environment for fully 3D PET on a high-performance parallel platform

    CERN Document Server

    Zaidi, H; Morel, Christian

    1998-01-01

    This paper describes the implementation of the Eidolon Monte Carlo program designed to simulate fully three-dimensional (3D) cylindrical positron tomographs on a MIMD parallel architecture. The original code was written in Objective-C and developed under the NeXTSTEP development environment. Different steps involved in porting the software on a parallel architecture based on PowerPC 604 processors running under AIX 4.1 are presented. Basic aspects and strategies of running Monte Carlo calculations on parallel computers are described. A linear decrease of the computing time was achieved with the number of computing nodes. The improved time performances resulting from parallelisation of the Monte Carlo calculations makes it an attractive tool for modelling photon transport in 3D positron tomography. The parallelisation paradigm used in this work is independent from the chosen parallel architecture

  10. Convex-based void filling method for CAD-based Monte Carlo geometry modeling

    International Nuclear Information System (INIS)

    Yu, Shengpeng; Cheng, Mengyun; Song, Jing; Long, Pengcheng; Hu, Liqin

    2015-01-01

    Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time

  11. Memory-efficient calculations of adjoint-weighted tallies by the Monte Carlo Wielandt method

    International Nuclear Information System (INIS)

    Choi, Sung Hoon; Shim, Hyung Jin

    2016-01-01

    Highlights: • The MC Wielandt method is applied to reduce memory for the adjoint estimation. • The adjoint-weighted kinetics parameters are estimated in the MC Wielandt calculations. • The MC S/U analyses are conducted in the MC Wielandt calculations. - Abstract: The current Monte Carlo (MC) adjoint-weighted tally techniques based on the iterated fission probability (IFP) concept require a memory amount which is proportional to the numbers of the adjoint-weighted tallies and histories per cycle to store history-wise tally estimates during the convergence of the adjoint flux. Especially the conventional MC adjoint-weighted perturbation (AWP) calculations for the nuclear data sensitivity and uncertainty (S/U) analysis suffer from the huge memory consumption to realize the IFP concept. In order to reduce the memory requirement drastically, we present a new adjoint estimation method in which the memory usage is irrelevant to the numbers of histories per cycle by applying the IFP concept for the MC Wielandt calculations. The new algorithms for the adjoint-weighted kinetics parameter estimation and the AWP calculations in the MC Wielandt method are implemented in a Seoul National University MC code, McCARD and its validity is demonstrated in critical facility problems. From the comparison of the nuclear data S/U analyses, it is demonstrated that the memory amounts to store the sensitivity estimates in the proposed method become negligibly small.

  12. Monte Carlo computation in the applied research of nuclear technology

    International Nuclear Information System (INIS)

    Xu Shuyan; Liu Baojie; Li Qin

    2007-01-01

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

  13. 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.

  14. Analysis of inconsistent source sampling in monte carlo weight-window variance reduction methods

    Directory of Open Access Journals (Sweden)

    David P. Griesheimer

    2017-09-01

    Full Text Available The application of Monte Carlo (MC to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

  15. Implementation of a Monte Carlo algorithm for neutron transport on a massively parallel SIMD machine

    International Nuclear Information System (INIS)

    Baker, R.S.

    1992-01-01

    We present some results from the recent adaptation of a vectorized Monte Carlo algorithm to a massively parallel architecture. The performance of the algorithm on a single processor Cray Y-MP and a Thinking Machine Corporations CM-2 and CM-200 is compared for several test problems. The results show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when the algorithms are applied to realistic problems which require extensive variance reduction. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well

  16. Implementation of a Monte Carlo algorithm for neutron transport on a massively parallel SIMD machine

    International Nuclear Information System (INIS)

    Baker, R.S.

    1993-01-01

    We present some results from the recent adaptation of a vectorized Monte Carlo algorithm to a massively parallel architecture. The performance of the algorithm on a single processor Cray Y-MP and a Thinking Machine Corporations CM-2 and CM-200 is compared for several test problems. The results show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when the algorithms are applied to realistic problems which require extensive variance reduction. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well. (orig.)

  17. Calculation Aspects of the European Rebalanced Basket Option using Monte Carlo Methods: Valuation

    Directory of Open Access Journals (Sweden)

    CJ van der Merwe

    2012-06-01

    Full Text Available Extra premiums can be charged to a client to guarantee a minimum payout of a contract on a portfolio that gets rebalanced on a regular basis back to fixed proportions. The valuation of this premium can be changed to that of the pricing of a European put option with underlying rebalanced portfolio. This article finds the most efficient estimators for the value of this path-dependant multi-asset put option using different Monte Carlo methods. With the help of a refined method, computing time of the value decreased significantly. Furthermore, Variance Reduction Techniques and Quasi-Monte Carlo methods delivered more accurate and faster converging estimates as well.

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

    International Nuclear Information System (INIS)

    Li Mancang; Wang Kan; Yao Dong

    2012-01-01

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

  19. Automating methods to improve precision in Monte-Carlo event generation for particle colliders

    International Nuclear Information System (INIS)

    Gleisberg, Tanju

    2008-01-01

    The subject of this thesis was the development of tools for the automated calculation of exact matrix elements, which are a key for the systematic improvement of precision and confidence for theoretical predictions. Part I of this thesis concentrates on the calculations of cross sections at tree level. A number of extensions have been implemented in the matrix element generator AMEGIC++, namely new interaction models such as effective loop-induced couplings of the Higgs boson with massless gauge bosons, required for a number of channels for the Higgs boson search at LHC and anomalous gauge couplings, parameterizing a number of models beyond th SM. Further a special treatment to deal with complicated decay chains of heavy particles has been constructed. A significant effort went into the implementation of methods to push the limits on particle multiplicities. Two recursive methods have been implemented, the Cachazo-Svrcek-Witten recursion and the colour dressed Berends-Giele recursion. For the latter the new module COMIX has been added to the SHERPA framework. The Monte-Carlo phase space integration techniques have been completely revised, which led to significantly reduced statistical error estimates when calculating cross sections and a greatly improved unweighting efficiency for the event generation. Special integration methods have been developed to cope with the newly accessible final states. The event generation framework SHERPA directly benefits from those new developments, improving the precision and the efficiency. Part II was addressed to the automation of QCD calculations at next-to-leading order. A code has been developed, that, for the first time fully automates the real correction part of a NLO calculation. To calculate the correction for a m-parton process obeying the Catani-Seymour dipole subtraction method the following components are provided: 1. the corresponding m+1-parton tree level matrix elements, 2. a number dipole subtraction terms to remove

  20. Automating methods to improve precision in Monte-Carlo event generation for particle colliders

    Energy Technology Data Exchange (ETDEWEB)

    Gleisberg, Tanju

    2008-07-01

    The subject of this thesis was the development of tools for the automated calculation of exact matrix elements, which are a key for the systematic improvement of precision and confidence for theoretical predictions. Part I of this thesis concentrates on the calculations of cross sections at tree level. A number of extensions have been implemented in the matrix element generator AMEGIC++, namely new interaction models such as effective loop-induced couplings of the Higgs boson with massless gauge bosons, required for a number of channels for the Higgs boson search at LHC and anomalous gauge couplings, parameterizing a number of models beyond th SM. Further a special treatment to deal with complicated decay chains of heavy particles has been constructed. A significant effort went into the implementation of methods to push the limits on particle multiplicities. Two recursive methods have been implemented, the Cachazo-Svrcek-Witten recursion and the colour dressed Berends-Giele recursion. For the latter the new module COMIX has been added to the SHERPA framework. The Monte-Carlo phase space integration techniques have been completely revised, which led to significantly reduced statistical error estimates when calculating cross sections and a greatly improved unweighting efficiency for the event generation. Special integration methods have been developed to cope with the newly accessible final states. The event generation framework SHERPA directly benefits from those new developments, improving the precision and the efficiency. Part II was addressed to the automation of QCD calculations at next-to-leading order. A code has been developed, that, for the first time fully automates the real correction part of a NLO calculation. To calculate the correction for a m-parton process obeying the Catani-Seymour dipole subtraction method the following components are provided: 1. the corresponding m+1-parton tree level matrix elements, 2. a number dipole subtraction terms to remove

  1. Development of burnup methods and capabilities in Monte Carlo code RMC

    International Nuclear Information System (INIS)

    She, Ding; Liu, Yuxuan; Wang, Kan; Yu, Ganglin; Forget, Benoit; Romano, Paul K.; Smith, Kord

    2013-01-01

    Highlights: ► The RMC code has been developed aiming at large-scale burnup calculations. ► Matrix exponential methods are employed to solve the depletion equations. ► The Energy-Bin method reduces the time expense of treating ACE libraries. ► The Cell-Mapping method is efficient to handle massive amounts of tally cells. ► Parallelized depletion is necessary for massive amounts of burnup regions. -- Abstract: The Monte Carlo burnup calculation has always been a challenging problem because of its large time consumption when applied to full-scale assembly or core calculations, and thus its application in routine analysis is limited. Most existing MC burnup codes are usually external wrappers between a MC code, e.g. MCNP, and a depletion code, e.g. ORIGEN. The code RMC is a newly developed MC code with an embedded depletion module aimed at performing burnup calculations of large-scale problems with high efficiency. Several measures have been taken to strengthen the burnup capabilities of RMC. Firstly, an accurate and efficient depletion module called DEPTH has been developed and built in, which employs the rational approximation and polynomial approximation methods. Secondly, the Energy-Bin method and the Cell-Mapping method are implemented to speed up the transport calculations with large numbers of nuclides and tally cells. Thirdly, the batch tally method and the parallelized depletion module have been utilized to better handle cases with massive amounts of burnup regions in parallel calculations. Burnup cases including a PWR pin and a 5 × 5 assembly group are calculated, thereby demonstrating the burnup capabilities of the RMC code. In addition, the computational time and memory requirements of RMC are compared with other MC burnup codes.

  2. Numerical methods design, analysis, and computer implementation of algorithms

    CERN Document Server

    Greenbaum, Anne

    2012-01-01

    Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book a...

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

    International Nuclear Information System (INIS)

    Yue Aizhong; He Biao; Zhang Jianmin; Wang Lijuan

    2010-01-01

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

  4. Calculation of extended shields in the Monte Carlo method using importance function (BRAND and DD code systems)

    International Nuclear Information System (INIS)

    Androsenko, A.A.; Androsenko, P.A.; Kagalenko, I.Eh.; Mironovich, Yu.N.

    1992-01-01

    Consideration is given of a technique and algorithms of constructing neutron trajectories in the Monte-Carlo method taking into account the data on adjoint transport equation solution. When simulating the transport part of transfer kernel the use is made of piecewise-linear approximation of free path length density along the particle motion direction. The approach has been implemented in programs within the framework of the BRAND code system. The importance is calculated in the multigroup P 1 -approximation within the framework of the DD-30 code system. The efficiency of the developed computation technique is demonstrated by means of solution of two model problems. 4 refs.; 2 tabs

  5. 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

  6. Advantages of Analytical Transformations in Monte Carlo Methods for Radiation Transport

    International Nuclear Information System (INIS)

    McKinley, M S; Brooks III, E D; Daffin, F

    2004-01-01

    Monte Carlo methods for radiation transport typically attempt to solve an integral by directly sampling analog or weighted particles, which are treated as physical entities. Improvements to the methods involve better sampling, probability games or physical intuition about the problem. We show that significant improvements can be achieved by recasting the equations with an analytical transform to solve for new, non-physical entities or fields. This paper looks at one such transform, the difference formulation for thermal photon transport, showing a significant advantage for Monte Carlo solution of the equations for time dependent transport. Other related areas are discussed that may also realize significant benefits from similar analytical transformations

  7. Interface methods for hybrid Monte Carlo-diffusion radiation-transport simulations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2006-01-01

    Discrete diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Monte Carlo simulations in diffusive media. An important aspect of DDMC is the treatment of interfaces between diffusive regions, where DDMC is used, and transport regions, where standard Monte Carlo is employed. Three previously developed methods exist for treating transport-diffusion interfaces: the Marshak interface method, based on the Marshak boundary condition, the asymptotic interface method, based on the asymptotic diffusion-limit boundary condition, and the Nth-collided source technique, a scheme that allows Monte Carlo particles to undergo several collisions in a diffusive region before DDMC is used. Numerical calculations have shown that each of these interface methods gives reasonable results as part of larger radiation-transport simulations. In this paper, we use both analytic and numerical examples to compare the ability of these three interface techniques to treat simpler, transport-diffusion interface problems outside of a more complex radiation-transport calculation. We find that the asymptotic interface method is accurate regardless of the angular distribution of Monte Carlo particles incident on the interface surface. In contrast, the Marshak boundary condition only produces correct solutions if the incident particles are isotropic. We also show that the Nth-collided source technique has the capacity to yield accurate results if spatial cells are optically small and Monte Carlo particles are allowed to undergo many collisions within a diffusive region before DDMC is employed. These requirements make the Nth-collided source technique impractical for realistic radiation-transport calculations

  8. Speed-Up of the Monte Carlo Method by Using a Physical Model of the Dempster-Shafer Theory

    NARCIS (Netherlands)

    Resconi, G.; Wal, A.J. van der; Ruan, D.

    1998-01-01

    By using the Monte Carlo method, we can obtain the minimum value of a function V(r) that is generally associated with the potential energy. In this paper we present a method that makes it possible to speed up the classical Monte Carlo method. The new method is based on the observation that the

  9. Quasi-Monte Carlo methods: applications to modeling of light transport in tissue

    Science.gov (United States)

    Schafer, Steven A.

    1996-05-01

    Monte Carlo modeling of light propagation can accurately predict the distribution of light in scattering materials. A drawback of Monte Carlo methods is that they converge inversely with the square root of the number of iterations. Theoretical considerations suggest that convergence which scales inversely with the first power of the number of iterations is possible. We have previously shown that one can obtain at least a portion of that improvement by using van der Corput sequences in place of a conventional pseudo-random number generator. Here, we present our further analysis, and show that quasi-Monte Carlo methods do have limited applicability to light scattering problems. We also discuss potential improvements which may increase the applicability.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-06-01

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

  11. 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.

  12. A new method to assess the statistical convergence of monte carlo solutions

    International Nuclear Information System (INIS)

    Forster, R.A.

    1991-01-01

    Accurate Monte Carlo confidence intervals (CIs), which are formed with an estimated mean and an estimated standard deviation, can only be created when the number of particle histories N becomes large enough so that the central limit theorem can be applied. The Monte Carlo user has a limited number of marginal methods to assess the fulfillment of this condition, such as statistical error reduction proportional to 1/√N with error magnitude guidelines and third and fourth moment estimators. A new method is presented here to assess the statistical convergence of Monte Carlo solutions by analyzing the shape of the empirical probability density function (PDF) of history scores. Related work in this area includes the derivation of analytic score distributions for a two-state Monte Carlo problem. Score distribution histograms have been generated to determine when a small number of histories accounts for a large fraction of the result. This summary describes initial studies of empirical Monte Carlo history score PDFs created from score histograms of particle transport simulations. 7 refs., 1 fig

  13. The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

    Energy Technology Data Exchange (ETDEWEB)

    Hall, Clifford [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); Ji, Weixiao [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); Blaisten-Barojas, Estela, E-mail: blaisten@gmu.edu [Computational Materials Science Center, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States); School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030 (United States)

    2014-02-01

    We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm, which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.

  14. The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

    International Nuclear Information System (INIS)

    Hall, Clifford; Ji, Weixiao; Blaisten-Barojas, Estela

    2014-01-01

    We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm, which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.

  15. The codes WAV3BDY and WAV4BDY and the variational Monte Carlo method

    International Nuclear Information System (INIS)

    Schiavilla, R.

    1987-01-01

    A description of the codes WAV3BDY and WAV4BDY, which generate the variational ground state wave functions of the A=3 and 4 nuclei, is given, followed by a discussion of the Monte Carlo integration technique, which is used to calculate expectation values and transition amplitudes of operators, and for whose implementation WAV3BDY and WAV4BDY are well suited

  16. Asymptotic equilibrium diffusion analysis of time-dependent Monte Carlo methods for grey radiative transfer

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2004-01-01

    The equations of nonlinear, time-dependent radiative transfer are known to yield the equilibrium diffusion equation as the leading-order solution of an asymptotic analysis when the mean-free path and mean-free time of a photon become small. We apply this same analysis to the Fleck-Cummings, Carter-Forest, and N'kaoua Monte Carlo approximations for grey (frequency-independent) radiative transfer. Although Monte Carlo simulation usually does not require the discretizations found in deterministic transport techniques, Monte Carlo methods for radiative transfer require a time discretization due to the nonlinearities of the problem. If an asymptotic analysis of the equations used by a particular Monte Carlo method yields an accurate time-discretized version of the equilibrium diffusion equation, the method should generate accurate solutions if a time discretization is chosen that resolves temperature changes, even if the time steps are much larger than the mean-free time of a photon. This analysis is of interest because in many radiative transfer problems, it is a practical necessity to use time steps that are large compared to a mean-free time. Our asymptotic analysis shows that: (i) the N'kaoua method has the equilibrium diffusion limit, (ii) the Carter-Forest method has the equilibrium diffusion limit if the material temperature change during a time step is small, and (iii) the Fleck-Cummings method does not have the equilibrium diffusion limit. We include numerical results that verify our theoretical predictions

  17. Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

    Science.gov (United States)

    Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William

    2017-09-01

    Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

  18. 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)

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

    Indian Academy of Sciences (India)

    included a short appendix that gives basic definitions and results in this case. ... Moreover, the central limit theorem gives the order of error; the error here is ... Indeed, the common method to generate samples from N(0,1) also uses the idea of ...

  20. Power Analysis for Complex Mediational Designs Using Monte Carlo Methods

    Science.gov (United States)

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…

  1. Markov chain Monte Carlo methods in directed graphical models

    DEFF Research Database (Denmark)

    Højbjerre, Malene

    Directed graphical models present data possessing a complex dependence structure, and MCMC methods are computer-intensive simulation techniques to approximate high-dimensional intractable integrals, which emerge in such models with incomplete data. MCMC computations in directed graphical models h...

  2. 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.

  3. Validation of uncertainty of weighing in the preparation of radionuclide standards by Monte Carlo Method; Validacao da incerteza de pesagens no preparo de padroes de radionuclideos por Metodo de Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Cacais, F.L.; Delgado, J.U., E-mail: facacais@gmail.com [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Loayza, V.M. [Instituto Nacional de Metrologia (INMETRO), Rio de Janeiro, RJ (Brazil). Qualidade e Tecnologia

    2016-07-01

    In preparing solutions for the production of radionuclide metrology standards is necessary measuring the quantity Activity by mass. The gravimetric method by elimination is applied to perform weighing with smaller uncertainties. At this work is carried out the validation, by the Monte Carlo method, of the uncertainty calculation approach implemented by Lourenco and Bobin according to ISO GUM for the method by elimination. The results obtained by both uncertainty calculation methods were consistent indicating that were fulfilled the conditions for the application of ISO GUM in the preparation of radioactive standards. (author)

  4. Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Wagner, John C.; Peplow, Douglas E.; Mosher, Scott W.; Evans, Thomas M.

    2010-01-01

    This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10 2-4 ), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.

  5. Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Wagner, John C.; Peplow, Douglas E.; Mosher, Scott W.; Evans, Thomas M.

    2010-01-01

    This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(102-4), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.

  6. Review of hybrid (deterministic/Monte Carlo) radiation transport methods, codes, and applications at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Wagner, J.C.; Peplow, D.E.; Mosher, S.W.; Evans, T.M.

    2010-01-01

    This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10 2-4 ), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications. (author)

  7. Algorithm simulating the atom displacement processes induced by the gamma rays on the base of Monte Carlo method

    International Nuclear Information System (INIS)

    Cruz, C. M.; Pinera, I; Abreu, Y.; Leyva, A.

    2007-01-01

    Present work concerns with the implementation of a Monte Carlo based calculation algorithm describing particularly the occurrence of Atom Displacements induced by the Gamma Radiation interactions at a given target material. The Atom Displacement processes were considered only on the basis of single elastic scattering interactions among fast secondary electrons with matrix atoms, which are ejected from their crystalline sites at recoil energies higher than a given threshold energy. The secondary electron transport was described assuming typical approaches on this matter, where consecutive small angle scattering and very low energy transfer events behave as a continuously cuasi-classical electron state changes along a given path length delimited by two discrete high scattering angle and electron energy losses events happening on a random way. A limiting scattering angle was introduced and calculated according Moliere-Bethe-Goudsmit-Saunderson Electron Multiple Scattering, which allows splitting away secondary electrons single scattering processes from multiple one, according which a modified McKinley-Feshbach electron elastic scattering cross section arises. This distribution was statistically sampled and simulated in the framework of the Monte Carlo Method to perform discrete single electron scattering processes, particularly those leading to Atom Displacement events. The possibility of adding this algorithm to present existing open Monte Carlo code systems is analyze, in order to improve their capabilities. (Author)

  8. User's guide to Monte Carlo methods for evaluating path integrals

    Science.gov (United States)

    Westbroek, Marise J. E.; King, Peter R.; Vvedensky, Dimitri D.; Dürr, Stephan

    2018-04-01

    We give an introduction to the calculation of path integrals on a lattice, with the quantum harmonic oscillator as an example. In addition to providing an explicit computational setup and corresponding pseudocode, we pay particular attention to the existence of autocorrelations and the calculation of reliable errors. The over-relaxation technique is presented as a way to counter strong autocorrelations. The simulation methods can be extended to compute observables for path integrals in other settings.

  9. Proton recoil spectra in spherical proportional counters calculated with finite element and Monte Carlo methods

    Energy Technology Data Exchange (ETDEWEB)

    Benmosbah, M. [Laboratoire de Chimie Physique et Rayonnement Alain Chambaudet, UMR CEA E4, Universite de Franche-Comte, 16 route de Gray, 25030 Besancon Cedex (France); Groetz, J.E. [Laboratoire de Chimie Physique et Rayonnement Alain Chambaudet, UMR CEA E4, Universite de Franche-Comte, 16 route de Gray, 25030 Besancon Cedex (France)], E-mail: jegroetz@univ-fcomte.fr; Crovisier, P. [Service de Protection contre les Rayonnements, CEA Valduc, 21120 Is/Tille (France); Asselineau, B. [Laboratoire de Metrologie et de Dosimetrie des Neutrons, IRSN, Cadarache BP3, 13115 St Paul-lez-Durance (France); Truffert, H.; Cadiou, A. [AREVA NC, Etablissement de la Hague, DQSSE/PR/E/D, 50444 Beaumont-Hague Cedex (France)

    2008-08-11

    Proton recoil spectra were calculated for various spherical proportional counters using Monte Carlo simulation combined with the finite element method. Electric field lines and strength were calculated by defining an appropriate mesh and solving the Laplace equation with the associated boundary conditions, taking into account the geometry of every counter. Thus, different regions were defined in the counter with various coefficients for the energy deposition in the Monte Carlo transport code MCNPX. Results from the calculations are in good agreement with measurements for three different gas pressures at various neutron energies.

  10. A Monte Carlo Green's function method for three-dimensional neutron transport

    International Nuclear Information System (INIS)

    Gamino, R.G.; Brown, F.B.; Mendelson, M.R.

    1992-01-01

    This paper describes a Monte Carlo transport kernel capability, which has recently been incorporated into the RACER continuous-energy Monte Carlo code. The kernels represent a Green's function method for neutron transport from a fixed-source volume out to a particular volume of interest. This method is very powerful transport technique. Also, since kernels are evaluated numerically by Monte Carlo, the problem geometry can be arbitrarily complex, yet exact. This method is intended for problems where an ex-core neutron response must be determined for a variety of reactor conditions. Two examples are ex-core neutron detector response and vessel critical weld fast flux. The response is expressed in terms of neutron transport kernels weighted by a core fission source distribution. In these types of calculations, the response must be computed for hundreds of source distributions, but the kernels only need to be calculated once. The advance described in this paper is that the kernels are generated with a highly accurate three-dimensional Monte Carlo transport calculation instead of an approximate method such as line-of-sight attenuation theory or a synthesized three-dimensional discrete ordinates solution

  11. Application of the perturbation series expansion quantum Monte Carlo method to multiorbital systems having Hund's coupling

    International Nuclear Information System (INIS)

    Sakai, Shiro; Arita, Ryotaro; Aoki, Hideo

    2006-01-01

    We propose a new quantum Monte Carlo method especially intended to couple with the dynamical mean-field theory. The algorithm is not only much more efficient than the conventional Hirsch-Fye algorithm, but is applicable to multiorbital systems having an SU(2)-symmetric Hund's coupling as well

  12. 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...

  13. 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.

  14. Application of monte-carlo method in definition of key categories of most radioactive polluted soil

    Energy Technology Data Exchange (ETDEWEB)

    Mahmudov, H M; Valibeyova, G; Jafarov, Y D; Musaeva, Sh Z [Institute of Radiation Problems, Azerbaijan National Academy of Sciences, Baku (Azerbaijan); others, and

    2006-10-15

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capasites of radiation and data on activity within the boundaries of their individual density of frequency distribution of exposition doses capacities.The analysis using Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainly in reports.Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report.Relative uncertainly of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of resources available for preparation and to prepare possible estimations for the most significant categories of sources.Usage of the notion {sup u}ncertainty{sup i}n reports also allows to set threshold value for a key category of sources, if it necessary, for exact reflection of 90 per cent uncertainty in reports.According to radiation safety norms level of radiation backgrounds exceeding 33 mkR/hour is considered dangerous.By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of polluted soil.

  15. Application of monte-carlo method in definition of key categories of most radioactive polluted soil

    International Nuclear Information System (INIS)

    Mahmudov, H.M; Valibeyova, G.; Jafarov, Y.D; Musaeva, Sh.Z

    2006-01-01

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capasites of radiation and data on activity within the boundaries of their individual density of frequency distribution of exposition doses capacities.The analysis using Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainly in reports.Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report.Relative uncertainly of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of resources available for preparation and to prepare possible estimations for the most significant categories of sources.Usage of the notion u ncertainty i n reports also allows to set threshold value for a key category of sources, if it necessary, for exact reflection of 90 per cent uncertainty in reports.According to radiation safety norms level of radiation backgrounds exceeding 33 mkR/hour is considered dangerous.By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of polluted soil.

  16. Some aspects of Trim-algorithm modernization for Monte-Carlo method

    International Nuclear Information System (INIS)

    Dovnar, S.V.; Grigor'ev, V.V.; Kamyshan, M.A.; Leont'ev, A.V.; Yanusko, S.V.

    2001-01-01

    Some aspects of Trim-algorithm modernization in Monte-Carlo method are discussed. This modification permits to raise the universality of program work with various potentials of ion-atom interactions and to improve the calculation precision for scattering angle θ c

  17. Derivation of a Monte Carlo method for modeling heterodyne detection in optical coherence tomography systems

    DEFF Research Database (Denmark)

    Tycho, Andreas; Jørgensen, Thomas Martini; Andersen, Peter E.

    2002-01-01

    A Monte Carlo (MC) method for modeling optical coherence tomography (OCT) measurements of a diffusely reflecting discontinuity emb edded in a scattering medium is presented. For the first time to the authors' knowledge it is shown analytically that the applicability of an MC approach to this opti...

  18. Markov chain Monte Carlo methods for statistical analysis of RF photonic devices

    DEFF Research Database (Denmark)

    Piels, Molly; Zibar, Darko

    2016-01-01

    uncertainty is shown to give unsatisfactory and incorrect results due to the nonlinear relationship between the circuit parameters and the measured data. Markov chain Monte Carlo methods are shown to provide superior results, both for individual devices and for assessing within-die variation...

  19. 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

  20. The unbiasedness of a generalized mirage boundary correction method for Monte Carlo integration estimators of volume

    Science.gov (United States)

    Thomas B. Lynch; Jeffrey H. Gove

    2014-01-01

    The typical "double counting" application of the mirage method of boundary correction cannot be applied to sampling systems such as critical height sampling (CHS) that are based on a Monte Carlo sample of a tree (or debris) attribute because the critical height (or other random attribute) sampled from a mirage point is generally not equal to the critical...

  1. Generation of triangulated random surfaces by the Monte Carlo method in the grand canonical ensemble

    International Nuclear Information System (INIS)

    Zmushko, V.V.; Migdal, A.A.

    1987-01-01

    A model of triangulated random surfaces which is the discrete analog of the Polyakov string is considered. An algorithm is proposed which enables one to study the model by the Monte Carlo method in the grand canonical ensemble. Preliminary results on the determination of the critical index γ are presented

  2. Evaluation of gamma-ray attenuation properties of bismuth borate glass systems using Monte Carlo method

    Science.gov (United States)

    Tarim, Urkiye Akar; Ozmutlu, Emin N.; Yalcin, Sezai; Gundogdu, Ozcan; Bradley, D. A.; Gurler, Orhan

    2017-11-01

    A Monte Carlo method was developed to investigate radiation shielding properties of bismuth borate glass. The mass attenuation coefficients and half-value layer parameters were determined for different fractional amounts of Bi2O3 in the glass samples for the 356, 662, 1173 and 1332 keV photon energies. A comparison of the theoretical and experimental attenuation coefficients is presented.

  3. A Research and Study Course for learning the concept of discrete randomvariable using Monte Carlo methods

    Directory of Open Access Journals (Sweden)

    Vicente D. Estruch

    2017-08-01

    Full Text Available The concept of random variable is a mathematical construct that presents some theoretical complexity. However, learning  this  concept  can  be  facilitated  if  it  is  presented  as  the  end  of  a  sequential  process  of  modeling  of  a  real event. More specifically, to learn the concept of discrete random variable, the Monte Carlo simulation can provide an extremely useful tool because in the process of modeling / simulation one can approach the theoretical concept of random variable, while the random variable is observed \\in action". This paper presents a Research and Study Course  (RSC  based  on  series  of  activities  related  to  random  variables  such  as  training  and  introduction  of  simulation  elements,  then  the  construction  of  the  model  is  presented,  which  is  the  substantial  part  of  the  activity, generating a random variable and its probability function. Starting from a simple situation related to reproduction and  survival  of  the  litter  of  a  rodent,  with  random  components,  step  by  step,  the  model  that  represents  the  real raised situation is built obtaining an \\original" random variable. In the intermediate stages of the construction of the model have a fundamental role the uniform discrete and binomial distributions. The trajectory of these stages allows reinforcing the concept of random variable while exploring the possibilities offered by Monte Carlo methods to  simulate  real  cases  and  the  simplicity  of  implementing  these  methods  by  means  of  the  Matlab© programming language.

  4. Correlation between vacancies and magnetoresistance changes in FM manganites using the Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Agudelo-Giraldo, J.D. [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo-Parra, E., E-mail: erestrepopa@unal.edu.co [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo, J. [Grupo de Magnetismo y Simulación, Instituto de Física, Universidad de Antioquia, A.A. 1226, Medellín (Colombia)

    2015-10-01

    The Metropolis algorithm and the classical Heisenberg approximation were implemented by the Monte Carlo method to design a computational approach to the magnetization and resistivity of La{sub 2/3}Ca{sub 1/3}MnO{sub 3}, which depends on the Mn ion vacancies as the external magnetic field increases. This compound is ferromagnetic, and it exhibits the colossal magnetoresistance (CMR) effect. The monolayer was built with L×L×d dimensions, and it had L=30 umc (units of magnetic cells) for its dimension in the x–y plane and was d=12 umc in thickness. The Hamiltonian that was used contains interactions between first neighbors, the magnetocrystalline anisotropy effect and the external applied magnetic field response. The system that was considered contains mixed-valence bonds: Mn{sup 3+eg’}–O–Mn{sup 3+eg}, Mn{sup 3+eg}–O–Mn{sup 4+d3} and Mn{sup 3+eg’}–O–Mn{sup 4+d3}. The vacancies were placed randomly in the sample, replacing any type of Mn ion. The main result shows that without vacancies, the transitions T{sub C} (Curie temperature) and T{sub MI} (metal–insulator temperature) are similar, whereas with the increase in the vacancy percentage, T{sub MI} presented lower values than T{sub C}. This situation is caused by the competition between the external magnetic field, the vacancy percentage and the magnetocrystalline anisotropy, which favors the magnetoresistive effect at temperatures below T{sub MI}. Resistivity loops were also observed, which shows a direct correlation with the hysteresis loops of magnetization at temperatures below T{sub C}. - Highlights: • Changes in the resistivity of FM materials as a function of the temperature and external magnetic field can be obtained by the Monte Carlo method, Metropolis algorithm, classical Heisenberg and Kronig–Penney approximation for magnetic clusters. • Increases in the magnetoresistive effect were observed at temperatures below T{sub MI} by the vacancies effect. • The resistive hysteresis

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

    International Nuclear Information System (INIS)

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

    1994-01-01

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

  6. CAD-based Monte Carlo automatic modeling method based on primitive solid

    International Nuclear Information System (INIS)

    Wang, Dong; Song, Jing; Yu, Shengpeng; Long, Pengcheng; Wang, Yongliang

    2016-01-01

    Highlights: • We develop a method which bi-convert between CAD model and primitive solid. • This method was improved from convert method between CAD model and half space. • This method was test by ITER model and validated the correctness and efficiency. • This method was integrated in SuperMC which could model for SuperMC and Geant4. - Abstract: Monte Carlo method has been widely used in nuclear design and analysis, where geometries are described with primitive solids. However, it is time consuming and error prone to describe a primitive solid geometry, especially for a complicated model. To reuse the abundant existed CAD models and conveniently model with CAD modeling tools, an automatic modeling method for accurate prompt modeling between CAD model and primitive solid is needed. An automatic modeling method for Monte Carlo geometry described by primitive solid was developed which could bi-convert between CAD model and Monte Carlo geometry represented by primitive solids. While converting from CAD model to primitive solid model, the CAD model was decomposed into several convex solid sets, and then corresponding primitive solids were generated and exported. While converting from primitive solid model to the CAD model, the basic primitive solids were created and related operation was done. This method was integrated in the SuperMC and was benchmarked with ITER benchmark model. The correctness and efficiency of this method were demonstrated.

  7. 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

  8. Calibration of the identiFINDER detector for the iodine measurement in thyroid using the Monte Carlo method; Calibracion del detector identiFINDER para la medicion de yodo en tiroides utilizando el metodo Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Ramos M, D.; Yera S, Y.; Lopez B, G. M.; Acosta R, N.; Vergara G, A., E-mail: dayana@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones, Calle 20 No. 4113 e/ 41 y 47, Playa, 10600 La Habana (Cuba)

    2014-08-15

    This work is based on the determination of the detection efficiency of {sup 125}I and {sup 131}I in thyroid of the identiFINDER detector using the Monte Carlo method. The suitability of the calibration method is analyzed, when comparing the results of the direct Monte Carlo method with the corrected, choosing the latter because the differences with the real efficiency stayed below 10%. To simulate the detector their geometric parameters were optimized using a tomographic study, what allowed the uncertainties minimization of the estimates. Finally were obtained the simulations of the detector geometry-point source to find the correction factors to 5 cm, 15 cm and 25 cm, and those corresponding to the detector-simulator arrangement for the method validation and final calculation of the efficiency, demonstrating that in the Monte Carlo method implementation if simulates at a greater distance than the used in the Laboratory measurements an efficiency overestimation can be obtained, while if simulates at a shorter distance this will be underestimated, so should be simulated at the same distance to which will be measured in the reality. Also, is achieved the obtaining of the efficiency curves and minimum detectable activity for the measurement of {sup 131}I and {sup 125}I. In general is achieved the implementation of the Monte Carlo methodology for the identiFINDER calibration with the purpose of estimating the measured activity of iodine in thyroid. This method represents an ideal way to replace the lack of patterns solutions and simulators assuring the capacities of the Internal Contamination Laboratory of the Centro de Proteccion e Higiene de las Radiaciones are always calibrated for the iodine measurement in thyroid. (author)

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  10. Analysis of Monte Carlo methods for the simulation of photon transport

    International Nuclear Information System (INIS)

    Carlsson, G.A.; Kusoffsky, L.

    1975-01-01

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

  11. Determination of axial diffusion coefficients by the Monte-Carlo method

    International Nuclear Information System (INIS)

    Milgram, M.

    1994-01-01

    A simple method to calculate the homogenized diffusion coefficient for a lattice cell using Monte-Carlo techniques is demonstrated. The method relies on modelling a finite reactor volume to induce a curvature in the flux distribution, and then follows a large number of histories to obtain sufficient statistics for a meaningful result. The goal is to determine the diffusion coefficient with sufficient accuracy to test approximate methods built into deterministic lattice codes. Numerical results are given. (author). 4 refs., 8 figs

  12. Comments on the use of the Monte Carlo method for criticality calculations

    International Nuclear Information System (INIS)

    Whitesides, G.E.

    1975-01-01

    As evidenced by recent papers given at Nuclear Criticality Safety Division meetings, the use of the Monte Carlo method has become a very popular computational tool. The ease of use has undoubtably been a primary reason for this popularity. This ease of use, however, may lead to a false sense of security when using the method. Guidance on the effective use of the method and some suggestions on how to avoid some of the pitfalls that can occur are presented

  13. TMD PDFs. A Monte Carlo implementation for the sea quark distribution

    International Nuclear Information System (INIS)

    Hautmann, F.

    2012-05-01

    This article gives an introduction to transverse momentum dependent (TMD) parton distribution functions and their use in shower Monte Carlo event generators for high-energy hadron collisions, and describes recent progress in the treatment of sea quark effects within a TMD parton-shower framework.

  14. Acceptance and implementation of a system of planning computerized based on Monte Carlo

    International Nuclear Information System (INIS)

    Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.

    2013-01-01

    It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)

  15. Application of Monte-Carlo method in definition of key categories of most radioactive polluted soil

    International Nuclear Information System (INIS)

    Mahmudov, H.M.; Valibeyova, G.; Jafarov, Y.D.; Musaeva, Sh.Z.

    2006-01-01

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capacities of radiation and data on activity within the boundaries of their individual density of frequency distribution upon corresponding sizes of exposition doses capacities. This procedure repeats for many times using computer and results of each round of calculations create universal density of frequency distribution of exposition doses capacities. The analysis using Monte Carlo method can be carried out at the level of radiation polluted soil categories. The analysis by Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainty in reports. Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report. Relative uncertainty of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of a confidential interval are asymmetric. It is important to determine key categories of radiation polluted soil to establish priorities to use reports of resources available for preparation and to prepare possible estimations for the most significant categories of sources. Usage of the notion u ncertainty i n reports also allows to set threshold value for a key category of sources, if it is necessary, for exact reflection of 90 percent uncertainty in reports. According to radiation safety norms level of radiation background exceeding 33 mkR/hour is considered dangerous. By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of

  16. Application of Monte-Carlo method in definition of key categories of most radioactive polluted soil

    Energy Technology Data Exchange (ETDEWEB)

    Mahmudov, H M; Valibeyova, G; Jafarov, Y D; Musaeva, Sh Z [Institute of Radiation Problems, Azerbaijan National Academy of Sciences, Baku (Azerbaijan)

    2006-11-15

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capacities of radiation and data on activity within the boundaries of their individual density of frequency distribution upon corresponding sizes of exposition doses capacities. This procedure repeats for many times using computer and results of each round of calculations create universal density of frequency distribution of exposition doses capacities. The analysis using Monte Carlo method can be carried out at the level of radiation polluted soil categories. The analysis by Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainty in reports. Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report. Relative uncertainty of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of a confidential interval are asymmetric. It is important to determine key categories of radiation polluted soil to establish priorities to use reports of resources available for preparation and to prepare possible estimations for the most significant categories of sources. Usage of the notion {sup u}ncertainty{sup i}n reports also allows to set threshold value for a key category of sources, if it is necessary, for exact reflection of 90 percent uncertainty in reports. According to radiation safety norms level of radiation background exceeding 33 mkR/hour is considered dangerous. By calted Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of

  17. The future of new calculation concepts in dosimetry based on the Monte Carlo Methods; Avenir des nouveaux concepts des calculs dosimetriques bases sur les methodes de Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J. [Universite de Franche-Comte, Equipe IRMA/ENISYS/FEMTO-ST, UMR6174 CNRS, 25 - Montbeliard (France); Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M. [Universite de Franche-Comte, Equipe AND/LIFC, 90 - Belfort (France)

    2009-01-15

    Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)

  18. Evaluation of Investment Risks in CBA with Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    Jana Korytárová

    2015-01-01

    Full Text Available Investment decisions are at the core of any development strategy. Economic growth and welfare depend on productive capital, infrastructure, human capital, knowledge, total factor productivity and the quality of institutions. Decision-making process on the selection of suitable projects in the public sector is in some aspects more difficult than in the private sector. Evaluating projects on the basis of their financial profitability, where the basic parameter is the value of the potential profit, can be misleading in these cases. One of the basic objectives of the allocation of public resources is respecting of the 3E principle (Economy, Effectiveness, Efficiency in their whole life cycle. The life cycle of the investment projects consists of four main phases. The first pre-investment phase is very important for decision-making process whether to accept or reject a public project for its realization. A well-designed feasibility study as well as cost-benefit analysis (CBA in this phase are important assumptions for future success of the project. A future financial and economical CF which represent the fundamental basis for calculation of economic effectiveness indicators are formed and modelled in these documents. This paper deals with the possibility to calculate the financial and economic efficiency of the public investment projects more accurately by simulation methods used.

  19. 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.

  20. Improved Monte Carlo-perturbation method for estimation of control rod worths in a research reactor

    International Nuclear Information System (INIS)

    Kalcheva, Silva; Koonen, Edgar

    2009-01-01

    A hybrid method dedicated to improve the experimental technique for estimation of control rod worths in a research reactor is presented. The method uses a combination of Monte Carlo technique and perturbation theory. Perturbation method is used to obtain the equation for the relative efficiency of control rod insertion. A series of coefficients, describing the axial absorption profile are used to correct the equation for a composite rod, having a complicated burn-up irradiation history. These coefficients have to be determined - by experiment or by using some theoretical/numerical method. In the present paper they are derived from the macroscopic absorption cross-sections, obtained from detailed Monte Carlo calculations by MCNPX 2.6.F of the axial burn-up profile during control rod life. The method is validated on measurements of control rod worths at the BR2 reactor. Comparison with direct MCNPX evaluations of control rod worths is also presented

  1. Protocol design and implementation using formal methods

    NARCIS (Netherlands)

    van Sinderen, Marten J.; Ferreira Pires, Luis; Pires, L.F.; Vissers, C.A.

    1992-01-01

    This paper reports on a number of formal methods that support correct protocol design and implementation. These methods are placed in the framework of a design methodology for distributed systems that was studied and developed within the ESPRIT II Lotosphere project (2304). The paper focuses on

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

    International Nuclear Information System (INIS)

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

    1996-03-01

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

  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. A recursive Monte Carlo method for estimating importance functions in deep penetration problems

    International Nuclear Information System (INIS)

    Goldstein, M.

    1980-04-01

    A pratical recursive Monte Carlo method for estimating the importance function distribution, aimed at importance sampling for the solution of deep penetration problems in three-dimensional systems, was developed. The efficiency of the recursive method was investigated for sample problems including one- and two-dimensional, monoenergetic and and multigroup problems, as well as for a practical deep-penetration problem with streaming. The results of the recursive Monte Carlo calculations agree fairly well with Ssub(n) results. It is concluded that the recursive Monte Carlo method promises to become a universal method for estimating the importance function distribution for the solution of deep-penetration problems, in all kinds of systems: for many systems the recursive method is likely to be more efficient than previously existing methods; for three-dimensional systems it is the first method that can estimate the importance function with the accuracy required for an efficient solution based on importance sampling of neutron deep-penetration problems in those systems

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

    International Nuclear Information System (INIS)

    Ogawa, K.; Maeda, S.

    1995-01-01

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

  6. Generation of gamma-ray streaming kernels through cylindrical ducts via Monte Carlo method

    International Nuclear Information System (INIS)

    Kim, Dong Su

    1992-02-01

    Since radiation streaming through penetrations is often the critical consideration in protection against exposure of personnel in a nuclear facility, it has been of great concern in radiation shielding design and analysis. Several methods have been developed and applied to the analysis of the radiation streaming in the past such as ray analysis method, single scattering method, albedo method, and Monte Carlo method. But they may be used for order-of-magnitude calculations and where sufficient margin is available, except for the Monte Carlo method which is accurate but requires a lot of computing time. This study developed a Monte Carlo method and constructed a data library of solutions using the Monte Carlo method for radiation streaming through a straight cylindrical duct in concrete walls of a broad, mono-directional, monoenergetic gamma-ray beam of unit intensity. The solution named as plane streaming kernel is the average dose rate at duct outlet and was evaluated for 20 source energies from 0 to 10 MeV, 36 source incident angles from 0 to 70 degrees, 5 duct radii from 10 to 30 cm, and 16 wall thicknesses from 0 to 100 cm. It was demonstrated that average dose rate due to an isotropic point source at arbitrary positions can be well approximated using the plane streaming kernel with acceptable error. Thus, the library of the plane streaming kernels can be used for the accurate and efficient analysis of radiation streaming through a straight cylindrical duct in concrete walls due to arbitrary distributions of gamma-ray sources

  7. Extrapolation method in the Monte Carlo Shell Model and its applications

    International Nuclear Information System (INIS)

    Shimizu, Noritaka; Abe, Takashi; Utsuno, Yutaka; Mizusaki, Takahiro; Otsuka, Takaharu; Honma, Michio

    2011-01-01

    We demonstrate how the energy-variance extrapolation method works using the sequence of the approximated wave functions obtained by the Monte Carlo Shell Model (MCSM), taking 56 Ni with pf-shell as an example. The extrapolation method is shown to work well even in the case that the MCSM shows slow convergence, such as 72 Ge with f5pg9-shell. The structure of 72 Se is also studied including the discussion of the shape-coexistence phenomenon.

  8. Study of cold neutron sources: Implementation and validation of a complete computation scheme for research reactor using Monte Carlo codes TRIPOLI-4.4 and McStas

    International Nuclear Information System (INIS)

    Campioni, Guillaume; Mounier, Claude

    2006-01-01

    The main goal of the thesis about studies of cold neutrons sources (CNS) in research reactors was to create a complete set of tools to design efficiently CNS. The work raises the problem to run accurate simulations of experimental devices inside reactor reflector valid for parametric studies. On one hand, deterministic codes have reasonable computation times but introduce problems for geometrical description. On the other hand, Monte Carlo codes give the possibility to compute on precise geometry, but need computation times so important that parametric studies are impossible. To decrease this computation time, several developments were made in the Monte Carlo code TRIPOLI-4.4. An uncoupling technique is used to isolate a study zone in the complete reactor geometry. By recording boundary conditions (incoming flux), further simulations can be launched for parametric studies with a computation time reduced by a factor 60 (case of the cold neutron source of the Orphee reactor). The short response time allows to lead parametric studies using Monte Carlo code. Moreover, using biasing methods, the flux can be recorded on the surface of neutrons guides entries (low solid angle) with a further gain of running time. Finally, the implementation of a coupling module between TRIPOLI- 4.4 and the Monte Carlo code McStas for research in condensed matter field gives the possibility to obtain fluxes after transmission through neutrons guides, thus to have the neutron flux received by samples studied by scientists of condensed matter. This set of developments, involving TRIPOLI-4.4 and McStas, represent a complete computation scheme for research reactors: from nuclear core, where neutrons are created, to the exit of neutrons guides, on samples of matter. This complete calculation scheme is tested against ILL4 measurements of flux in cold neutron guides. (authors)

  9. Spectral method and its high performance implementation

    KAUST Repository

    Wu, Zedong

    2014-01-01

    We have presented a new method that can be dispersion free and unconditionally stable. Thus the computational cost and memory requirement will be reduced a lot. Based on this feature, we have implemented this algorithm on GPU based CUDA for the anisotropic Reverse time migration. There is almost no communication between CPU and GPU. For the prestack wavefield extrapolation, it can combine all the shots together to migration. However, it requires to solve a bigger dimensional problem and more meory which can\\'t fit into one GPU cards. In this situation, we implement it based on domain decomposition method and MPI for distributed memory system.

  10. About the use of the Monte-Carlo code based tracing algorithm and the volume fraction method for S n full core calculations

    Energy Technology Data Exchange (ETDEWEB)

    Gurevich, M. I.; Oleynik, D. S. [RRC Kurchatov Inst., Kurchatov Sq., 1, 123182, Moscow (Russian Federation); Russkov, A. A.; Voloschenko, A. M. [Keldysh Inst. of Applied Mathematics, Miusskaya Sq., 4, 125047, Moscow (Russian Federation)

    2006-07-01

    The tracing algorithm that is implemented in the geometrical module of Monte-Carlo transport code MCU is applied to calculate the volume fractions of original materials by spatial cells of the mesh that overlays problem geometry. In this way the 3D combinatorial geometry presentation of the problem geometry, used by MCU code, is transformed to the user defined 2D or 3D bit-mapped ones. Next, these data are used in the volume fraction (VF) method to approximate problem geometry by introducing additional mixtures for spatial cells, where a few original materials are included. We have found that in solving realistic 2D and 3D core problems a sufficiently fast convergence of the VF method takes place if the spatial mesh is refined. Virtually, the proposed variant of implementation of the VF method seems as a suitable geometry interface between Monte-Carlo and S{sub n} transport codes. (authors)

  11. Estimation of magnetocaloric properties by using Monte Carlo method for AMRR cycle

    International Nuclear Information System (INIS)

    Arai, R; Fukuda, H; Numazawa, T; Tamura, R; Li, J; Saito, A T; Nakagome, H; Kaji, S

    2015-01-01

    In order to achieve a wide refrigerating temperature range in magnetic refrigeration, it is effective to layer multiple materials with different Curie temperatures. It is crucial to have a detailed understanding of physical properties of materials to optimize the material selection and the layered structure. In the present study, we discuss methods for estimating a change in physical properties, particularly the Curie temperature when some of the Gd atoms are substituted for non-magnetic elements for material design, based on Gd as a ferromagnetic material which is a typical magnetocaloric material. For this purpose, whilst making calculations using the S=7/2 Ising model and the Monte Carlo method, we made a specific heat measurement and a magnetization measurement of Gd-R alloy (R = Y, Zr) to compare experimental values and calculated ones. The results showed that the magnetic entropy change, specific heat, and Curie temperature can be estimated with good accuracy using the Monte Carlo method. (paper)

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

    International Nuclear Information System (INIS)

    Zhao Siqiao; Liu Jingquan

    2011-01-01

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

  13. Analysis of subgrid scale mixing using a hybrid LES-Monte-Carlo PDF method

    International Nuclear Information System (INIS)

    Olbricht, C.; Hahn, F.; Sadiki, A.; Janicka, J.

    2007-01-01

    This contribution introduces a hybrid LES-Monte-Carlo method for a coupled solution of the flow and the multi-dimensional scalar joint pdf in two complex mixing devices. For this purpose an Eulerian Monte-Carlo method is used. First, a complex mixing device (jet-in-crossflow, JIC) is presented in which the stochastic convergence and the coherency between the scalar field solution obtained via finite-volume methods and that from the stochastic solution of the pdf for the hybrid method are evaluated. Results are compared to experimental data. Secondly, an extensive investigation of the micromixing on the basis of assumed shape and transported SGS-pdfs in a configuration with practical relevance is carried out. This consists of a mixing chamber with two opposite rows of jets penetrating a crossflow (multi-jet-in-crossflow, MJIC). Some numerical results are compared to available experimental data and to RANS based results. It turns out that the hybrid LES-Monte-Carlo method could achieve a detailed analysis of the mixing at the subgrid level

  14. Improved Monte Carlo - Perturbation Method For Estimation Of Control Rod Worths In A Research Reactor

    International Nuclear Information System (INIS)

    Kalcheva, Silva; Koonen, Edgar

    2008-01-01

    A hybrid method dedicated to improve the experimental technique for estimation of control rod worths in a research reactor is presented. The method uses a combination of Monte Carlo technique and perturbation theory. The perturbation theory is used to obtain the relation between the relative rod efficiency and the buckling of the reactor with partially inserted rod. A series of coefficients, describing the axial absorption profile are used to correct the buckling for an arbitrary composite rod, having complicated burn up irradiation history. These coefficients have to be determined - by experiment or by using some theoretical/numerical method. In the present paper they are derived from the macroscopic absorption cross sections, obtained from detailed Monte Carlo calculations by MCNPX 2.6.F of the axial burn up profile during control rod life. The method is validated on measurements of control rod worths at the BR2 reactor. Comparison with direct Monte Carlo evaluations of control rod worths is also presented. The uncertainties, arising from the used approximations in the presented hybrid method are discussed. (authors)

  15. [Study of Determination of Oil Mixture Components Content Based on Quasi-Monte Carlo Method].

    Science.gov (United States)

    Wang, Yu-tian; Xu, Jing; Liu, Xiao-fei; Chen, Meng-han; Wang, Shi-tao

    2015-05-01

    Gasoline, kerosene, diesel is processed by crude oil with different distillation range. The boiling range of gasoline is 35 ~205 °C. The boiling range of kerosene is 140~250 °C. And the boiling range of diesel is 180~370 °C. At the same time, the carbon chain length of differentmineral oil is different. The carbon chain-length of gasoline is within the scope of C7 to C11. The carbon chain length of kerosene is within the scope of C12 to C15. And the carbon chain length of diesel is within the scope of C15 to C18. The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics. Mineral oil pollution occurs frequently, so monitoring mineral oil content in the ocean is very important. A new method of components content determination of spectra overlapping mineral oil mixture is proposed, with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method, combined with optimal algorithm solving optimum number of characteristic peak and range of integral region, solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter, Boyden, Fletcher, Goldfarb and Shanno) method. Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line, so the measurement of small changes of component content is sensitive. At the same time, compared with the single point measurement, measurement sensitivity is improved by the decrease influence of random error due to the selection of points. Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene, diesel and gasoline as research objects, with a single mineral oil regarded whole, not considered each mineral oil components. Six characteristic peaks are

  16. The application of Monte Carlo method to electron and photon beams transport; Zastosowanie metody Monte Carlo do analizy transportu elektronow i fotonow

    Energy Technology Data Exchange (ETDEWEB)

    Zychor, I. [Soltan Inst. for Nuclear Studies, Otwock-Swierk (Poland)

    1994-12-31

    The application of a Monte Carlo method to study a transport in matter of electron and photon beams is presented, especially for electrons with energies up to 18 MeV. The SHOWME Monte Carlo code, a modified version of GEANT3 code, was used on the CONVEX C3210 computer at Swierk. It was assumed that an electron beam is mono directional and monoenergetic. Arbitrary user-defined, complex geometries made of any element or material can be used in calculation. All principal phenomena occurring when electron beam penetrates the matter are taken into account. The use of calculation for a therapeutic electron beam collimation is presented. (author). 20 refs, 29 figs.

  17. Implementation and verification of nuclear interactions in a Monte-Carlo code for the Procom-ProGam proton therapy planning system

    Science.gov (United States)

    Kostyuchenko, V. I.; Makarova, A. S.; Ryazantsev, O. B.; Samarin, S. I.; Uglov, A. S.

    2014-06-01

    A great breakthrough in proton therapy has happened in the new century: several tens of dedicated centers are now operated throughout the world and their number increases every year. An important component of proton therapy is a treatment planning system. To make calculations faster, these systems usually use analytical methods whose reliability and accuracy do not allow the advantages of this method of treatment to implement to the full extent. Predictions by the Monte Carlo (MC) method are a "gold" standard for the verification of calculations with these systems. At the Institute of Experimental and Theoretical Physics (ITEP) which is one of the eldest proton therapy centers in the world, an MC code is an integral part of their treatment planning system. This code which is called IThMC was developed by scientists from RFNC-VNIITF (Snezhinsk) under ISTC Project 3563.

  18. Solution of charged particle transport equation by Monte-Carlo method in the BRANDZ code system

    International Nuclear Information System (INIS)

    Artamonov, S.N.; Androsenko, P.A.; Androsenko, A.A.

    1992-01-01

    Consideration is given to the issues of Monte-Carlo employment for the solution of charged particle transport equation and its implementation in the BRANDZ code system under the conditions of real 3D geometry and all the data available on radiation-to-matter interaction in multicomponent and multilayer targets. For the solution of implantation problem the results of BRANDZ data comparison with the experiments and calculations by other codes in complexes systems are presented. The results of direct nuclear pumping process simulation for laser-active media by a proton beam are also included. 4 refs.; 7 figs

  19. Study on critical effect in lattice homogenization via Monte Carlo method

    International Nuclear Information System (INIS)

    Li Mancang; Wang Kan; Yao Dong

    2012-01-01

    In contrast to the traditional deterministic lattice codes, generating the homogenization multigroup constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum. thus provides more accuracy parameters. An infinite lattice of identical symmetric motives is usually assumed when performing the homogenization. However, the finite size of a reactor is reality and it should influence the lattice calculation. In practice of the homogenization with Monte Carlo method, B N theory is applied to take the leakage effect into account. The fundamental mode with the buckling B is used as a measure of the finite size. The critical spectrum in the solution of 0-dimensional fine-group B 1 equations is used to correct the weighted spectrum for homogenization. A PWR prototype core is examined to verify that the presented method indeed generates few group constants effectively. In addition, a zero power physical experiment verification is performed. The results show that B N theory is adequate for leakage correction in the multigroup constants generation via Monte Carlo method. (authors)

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  1. An Implementation of the Frequency Matching Method

    DEFF Research Database (Denmark)

    Lange, Katrine; Frydendall, Jan; Hansen, Thomas Mejer

    During the last decade multiple-point statistics has become in-creasingly popular as a tool for incorporating complex prior infor-mation when solving inverse problems in geosciences. A variety of methods have been proposed but often the implementation of these is not straightforward. One of these......During the last decade multiple-point statistics has become in-creasingly popular as a tool for incorporating complex prior infor-mation when solving inverse problems in geosciences. A variety of methods have been proposed but often the implementation of these is not straightforward. One...... of these methods is the recently proposed Frequency Matching method to compute the maximum a posteriori model of an inverse problem where multiple-point statistics, learned from a training image, is used to formulate a closed form expression for an a priori probability density function. This paper discusses...... aspects of the implementation of the Fre-quency Matching method and the techniques adopted to make it com-putationally feasible also for large-scale inverse problems. The source code is publicly available at GitHub and this paper also provides an example of how to apply the Frequency Matching method...

  2. An improved method for storing and retrieving tabulated data in a scalar Monte Carlo code

    International Nuclear Information System (INIS)

    Hollenbach, D.F.; Reynolds, K.H.; Dodds, H.L.; Landers, N.F.; Petrie, L.M.

    1990-01-01

    The KENO-Va code is a production-level criticality safety code used to calculate the k eff of a system. The code is stochastic in nature, using a Monte Carlo algorithm to track individual particles one at a time through the system. The advent of computers with vector processors has generated an interest in improving KENO-Va to take advantage of the potential speed-up associated with these new processors. Unfortunately, the original Monte Carlo algorithm and method of storing and retrieving cross-section data is not adaptable to vector processing. This paper discusses an alternate method for storing and retrieving data that not only is readily vectorizable but also improves the efficiency of the current scalar code

  3. High-order Path Integral Monte Carlo methods for solving strongly correlated fermion problems

    Science.gov (United States)

    Chin, Siu A.

    2015-03-01

    In solving for the ground state of a strongly correlated many-fermion system, the conventional second-order Path Integral Monte Carlo method is plagued with the sign problem. This is due to the large number of anti-symmetric free fermion propagators that are needed to extract the square of the ground state wave function at large imaginary time. In this work, I show that optimized fourth-order Path Integral Monte Carlo methods, which uses no more than 5 free-fermion propagators, in conjunction with the use of the Hamiltonian energy estimator, can yield accurate ground state energies for quantum dots with up to 20 polarized electrons. The correlations are directly built-in and no explicit wave functions are needed. This work is supported by the Qatar National Research Fund NPRP GRANT #5-674-1-114.

  4. 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.

  5. Implicit Monte Carlo methods and non-equilibrium Marshak wave radiative transport

    International Nuclear Information System (INIS)

    Lynch, J.E.

    1985-01-01

    Two enhancements to the Fleck implicit Monte Carlo method for radiative transport are described, for use in transparent and opaque media respectively. The first introduces a spectral mean cross section, which applies to pseudoscattering in transparent regions with a high frequency incident spectrum. The second provides a simple Monte Carlo random walk method for opaque regions, without the need for a supplementary diffusion equation formulation. A time-dependent transport Marshak wave problem of radiative transfer, in which a non-equilibrium condition exists between the radiation and material energy fields, is then solved. These results are compared to published benchmark solutions and to new discrete ordinate S-N results, for both spatially integrated radiation-material energies versus time and to new spatially dependent temperature profiles. Multigroup opacities, which are independent of both temperature and frequency, are used in addition to a material specific heat which is proportional to the cube of the temperature. 7 refs., 4 figs

  6. Efficient data management techniques implemented in the Karlsruhe Monte Carlo code KAMCCO

    International Nuclear Information System (INIS)

    Arnecke, G.; Borgwaldt, H.; Brandl, V.; Lalovic, M.

    1974-01-01

    The Karlsruhe Monte Carlo Code KAMCCO is a forward neutron transport code with an eigenfunction and a fixed source option, including time-dependence. A continuous energy model is combined with a detailed representation of neutron cross sections, based on linear interpolation, Breit-Wigner resonances and probability tables. All input is processed into densely packed, dynamically addressed parameter fields and networks of pointers (addresses). Estimation routines are decoupled from random walk and analyze a storage region with sample records. This technique leads to fast execution with moderate storage requirements and without any I/O-operations except in the input and output stages. 7 references. (U.S.)

  7. 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.

  8. 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.

  9. Contributon Monte Carlo

    International Nuclear Information System (INIS)

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

    1979-05-01

    The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables

  10. 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

  11. Multilevel markov chain monte carlo method for high-contrast single-phase flow problems

    KAUST Repository

    Efendiev, Yalchin R.

    2014-12-19

    In this paper we propose a general framework for the uncertainty quantification of quantities of interest for high-contrast single-phase flow problems. It is based on the generalized multiscale finite element method (GMsFEM) and multilevel Monte Carlo (MLMC) methods. The former provides a hierarchy of approximations of different resolution, whereas the latter gives an efficient way to estimate quantities of interest using samples on different levels. The number of basis functions in the online GMsFEM stage can be varied to determine the solution resolution and the computational cost, and to efficiently generate samples at different levels. In particular, it is cheap to generate samples on coarse grids but with low resolution, and it is expensive to generate samples on fine grids with high accuracy. By suitably choosing the number of samples at different levels, one can leverage the expensive computation in larger fine-grid spaces toward smaller coarse-grid spaces, while retaining the accuracy of the final Monte Carlo estimate. Further, we describe a multilevel Markov chain Monte Carlo method, which sequentially screens the proposal with different levels of approximations and reduces the number of evaluations required on fine grids, while combining the samples at different levels to arrive at an accurate estimate. The framework seamlessly integrates the multiscale features of the GMsFEM with the multilevel feature of the MLMC methods following the work in [26], and our numerical experiments illustrate its efficiency and accuracy in comparison with standard Monte Carlo estimates. © Global Science Press Limited 2015.

  12. 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

  13. Multiquark masses and wave functions through modified Green's function Monte Carlo method

    International Nuclear Information System (INIS)

    Kerbikov, B.O.; Polikarpov, M.I.; Shevchenko, L.V.

    1987-01-01

    The Modified Green's function Monte Carlo method (MGFMC) is used to calculate the masses and ground-state wave functions of multiquark systems in the potential model. The previously developed MGFMC is generalized in order to treat systems containing quarks with inequal masses. The obtained results are presented with the Cornell potential for the masses and the wave functions of light and heavy flavoured baryons and multiquark states (N=6, 9, 12) made of light quarks

  14. Study of the multiple scattering effect in TEBENE using the Monte Carlo method

    International Nuclear Information System (INIS)

    Singkarat, Somsorn.

    1990-01-01

    The neutron time-of-flight and energy spectra, from the TEBENE set-up, have been calculated by a computer program using the Monte Carlo method. The neutron multiple scattering within the polyethylene scatterer ring is closely investigated. The results show that multiple scattering has a significant effect on the detected neutron yield. They also indicate that the thickness of the scatterer ring has to be carefully chosen. (author)

  15. Application of Monte Carlo method in determination of secondary characteristic X radiation in XFA

    International Nuclear Information System (INIS)

    Roubicek, P.

    1982-01-01

    Secondary characteristic radiation is excited by primary radiation from the X-ray tube and by secondary radiation of other elements so that excitations of several orders result. The Monte Carlo method was used to consider all these possibilities and the resulting flux of characteristic radiation was simulated for samples of silicate raw materials. A comparison of the results of these computations with experiments allows to determine the effect of sample preparation on the characteristic radiation flux. (M.D.)

  16. Efficiency determination of whole-body counters by Monte Carlo method, using a microcomputer

    International Nuclear Information System (INIS)

    Fernandes Neto, J.M.

    1987-01-01

    A computing program using Monte Carlo method for calculate the whole efficiency of distributed radiation counters in human body is developed. A simulater of human proportions was used, of which was filled with a known and uniform solution containing a quantity of radioisopes. The 99m Tc, 131 I and 42 K were used in this experience, and theirs activities compared by a liquid scintillator. (C.G.C.) [pt

  17. A study of orientational disorder in ND4Cl by the reverse Monte Carlo method

    International Nuclear Information System (INIS)

    Belushkin, A.V.; Kozlenko, D.P.; Savenko, B.N.; McGreevy, R.L.; Zetterstroem, P.

    1998-01-01

    The total structure factor for deuterated ammonium chloride measured by neutron diffraction has been modeled using the reverse Monte Carlo method. The results show that the orientational disorder of the ammonium ions consists of a local librational motion with an average angular amplitude α = 17 deg and reorientations of ammonium ions by 90 deg jumps around two-fold axes. Reorientations around three-fold axes have a very low probability

  18. Linewidth of Cyclotron Absorption in Band-Gap Graphene: Relaxation Time Approximation vs. Monte Carlo Method

    OpenAIRE

    S.V. Kryuchkov; E.I. Kukhar’; D.V. Zav’yalov

    2015-01-01

    The power of the elliptically polarized electromagnetic radiation absorbed by band-gap graphene in presence of constant magnetic field is calculated. The linewidth of cyclotron absorption is shown to be non-zero even if the scattering is absent. The calculations are performed analytically with the Boltzmann kinetic equation and confirmed numerically with the Monte Carlo method. The dependence of the linewidth of the cyclotron absorption on temperature applicable for a band-gap graphene in the...

  19. A new fuzzy Monte Carlo method for solving SLAE with ergodic fuzzy Markov chains

    Directory of Open Access Journals (Sweden)

    Maryam Gharehdaghi

    2015-05-01

    Full Text Available In this paper we introduce a new fuzzy Monte Carlo method for solving system of linear algebraic equations (SLAE over the possibility theory and max-min algebra. To solve the SLAE, we first define a fuzzy estimator and prove that this is an unbiased estimator of the solution. To prove unbiasedness, we apply the ergodic fuzzy Markov chains. This new approach works even for cases with coefficients matrix with a norm greater than one.

  20. 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)

  1. Atmosphere Re-Entry Simulation Using Direct Simulation Monte Carlo (DSMC Method

    Directory of Open Access Journals (Sweden)

    Francesco Pellicani

    2016-05-01

    Full Text Available Hypersonic re-entry vehicles aerothermodynamic investigations provide fundamental information to other important disciplines like materials and structures, assisting the development of thermal protection systems (TPS efficient and with a low weight. In the transitional flow regime, where thermal and chemical equilibrium is almost absent, a new numerical method for such studies has been introduced, the direct simulation Monte Carlo (DSMC numerical technique. The acceptance and applicability of the DSMC method have increased significantly in the 50 years since its invention thanks to the increase in computer speed and to the parallel computing. Anyway, further verification and validation efforts are needed to lead to its greater acceptance. In this study, the Monte Carlo simulator OpenFOAM and Sparta have been studied and benchmarked against numerical and theoretical data for inert and chemically reactive flows and the same will be done against experimental data in the near future. The results show the validity of the data found with the DSMC. The best setting of the fundamental parameters used by a DSMC simulator are presented for each software and they are compared with the guidelines deriving from the theory behind the Monte Carlo method. In particular, the number of particles per cell was found to be the most relevant parameter to achieve valid and optimized results. It is shown how a simulation with a mean value of one particle per cell gives sufficiently good results with very low computational resources. This achievement aims to reconsider the correct investigation method in the transitional regime where both the direct simulation Monte Carlo (DSMC and the computational fluid-dynamics (CFD can work, but with a different computational effort.

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

    KAUST Repository

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

    2013-01-01

    In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed

  3. TH-A-19A-08: Intel Xeon Phi Implementation of a Fast Multi-Purpose Monte Carlo Simulation for Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Souris, K; Lee, J; Sterpin, E [Universite catholique de Louvain, Brussels (Belgium)

    2014-06-15

    Purpose: Recent studies have demonstrated the capability of graphics processing units (GPUs) to compute dose distributions using Monte Carlo (MC) methods within clinical time constraints. However, GPUs have a rigid vectorial architecture that favors the implementation of simplified particle transport algorithms, adapted to specific tasks. Our new, fast, and multipurpose MC code, named MCsquare, runs on Intel Xeon Phi coprocessors. This technology offers 60 independent cores, and therefore more flexibility to implement fast and yet generic MC functionalities, such as prompt gamma simulations. Methods: MCsquare implements several models and hence allows users to make their own tradeoff between speed and accuracy. A 200 MeV proton beam is simulated in a heterogeneous phantom using Geant4 and two configurations of MCsquare. The first one is the most conservative and accurate. The method of fictitious interactions handles the interfaces and secondary charged particles emitted in nuclear interactions are fully simulated. The second, faster configuration simplifies interface crossings and simulates only secondary protons after nuclear interaction events. Integral depth-dose and transversal profiles are compared to those of Geant4. Moreover, the production profile of prompt gammas is compared to PENH results. Results: Integral depth dose and transversal profiles computed by MCsquare and Geant4 are within 3%. The production of secondaries from nuclear interactions is slightly inaccurate at interfaces for the fastest configuration of MCsquare but this is unlikely to have any clinical impact. The computation time varies between 90 seconds for the most conservative settings to merely 59 seconds in the fastest configuration. Finally prompt gamma profiles are also in very good agreement with PENH results. Conclusion: Our new, fast, and multi-purpose Monte Carlo code simulates prompt gammas and calculates dose distributions in less than a minute, which complies with clinical time

  4. TH-A-19A-08: Intel Xeon Phi Implementation of a Fast Multi-Purpose Monte Carlo Simulation for Proton Therapy

    International Nuclear Information System (INIS)

    Souris, K; Lee, J; Sterpin, E

    2014-01-01

    Purpose: Recent studies have demonstrated the capability of graphics processing units (GPUs) to compute dose distributions using Monte Carlo (MC) methods within clinical time constraints. However, GPUs have a rigid vectorial architecture that favors the implementation of simplified particle transport algorithms, adapted to specific tasks. Our new, fast, and multipurpose MC code, named MCsquare, runs on Intel Xeon Phi coprocessors. This technology offers 60 independent cores, and therefore more flexibility to implement fast and yet generic MC functionalities, such as prompt gamma simulations. Methods: MCsquare implements several models and hence allows users to make their own tradeoff between speed and accuracy. A 200 MeV proton beam is simulated in a heterogeneous phantom using Geant4 and two configurations of MCsquare. The first one is the most conservative and accurate. The method of fictitious interactions handles the interfaces and secondary charged particles emitted in nuclear interactions are fully simulated. The second, faster configuration simplifies interface crossings and simulates only secondary protons after nuclear interaction events. Integral depth-dose and transversal profiles are compared to those of Geant4. Moreover, the production profile of prompt gammas is compared to PENH results. Results: Integral depth dose and transversal profiles computed by MCsquare and Geant4 are within 3%. The production of secondaries from nuclear interactions is slightly inaccurate at interfaces for the fastest configuration of MCsquare but this is unlikely to have any clinical impact. The computation time varies between 90 seconds for the most conservative settings to merely 59 seconds in the fastest configuration. Finally prompt gamma profiles are also in very good agreement with PENH results. Conclusion: Our new, fast, and multi-purpose Monte Carlo code simulates prompt gammas and calculates dose distributions in less than a minute, which complies with clinical time

  5. Multilevel and Multi-index Monte Carlo methods for the McKean–Vlasov equation

    KAUST Repository

    Haji-Ali, Abdul-Lateef

    2017-09-12

    We address the approximation of functionals depending on a system of particles, described by stochastic differential equations (SDEs), in the mean-field limit when the number of particles approaches infinity. This problem is equivalent to estimating the weak solution of the limiting McKean–Vlasov SDE. To that end, our approach uses systems with finite numbers of particles and a time-stepping scheme. In this case, there are two discretization parameters: the number of time steps and the number of particles. Based on these two parameters, we consider different variants of the Monte Carlo and Multilevel Monte Carlo (MLMC) methods and show that, in the best case, the optimal work complexity of MLMC, to estimate the functional in one typical setting with an error tolerance of $$\\\\mathrm {TOL}$$TOL, is when using the partitioning estimator and the Milstein time-stepping scheme. We also consider a method that uses the recent Multi-index Monte Carlo method and show an improved work complexity in the same typical setting of . Our numerical experiments are carried out on the so-called Kuramoto model, a system of coupled oscillators.

  6. Response matrix of regular moderator volumes with 3He detector using Monte Carlo methods

    International Nuclear Information System (INIS)

    Baltazar R, A.; Vega C, H. R.; Ortiz R, J. M.; Solis S, L. O.; Castaneda M, R.; Soto B, T. G.; Medina C, D.

    2017-10-01

    In the last three decades the uses of Monte Carlo methods, for the estimation of physical phenomena associated with the interaction of radiation with matter, have increased considerably. The reason is due to the increase in computing capabilities and the reduction of computer prices. Monte Carlo methods allow modeling and simulating real systems before their construction, saving time and costs. The interaction mechanisms between neutrons and matter are diverse and range from elastic dispersion to nuclear fission; to facilitate the neutrons detection, is necessary to moderate them until reaching electronic equilibrium with the medium at standard conditions of pressure and temperature, in this state the total cross section of the 3 He is large. The objective of the present work was to estimate the response matrix of a proportional detector of 3 He using regular volumes of moderator through Monte Carlo methods. Neutron monoenergetic sources with energies of 10 -9 to 20 MeV and polyethylene moderators of different sizes were used. The calculations were made with the MCNP5 code; the number of stories for each detector-moderator combination was large enough to obtain errors less than 1.5%. We found that for small moderators the highest response is obtained for lower energy neutrons, when increasing the moderator dimension we observe that the response decreases for neutrons of lower energy and increases for higher energy neutrons. The total sum of the responses of each moderator allows obtaining a response close to a constant function. (Author)

  7. Implementation of an approximate zero-variance scheme in the TRIPOLI Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Dumonteil, E.; Petit, O.; Diop, C. [Commissariat a l' Energie Atomique CEA, Gif-sur-Yvette (France)

    2006-07-01

    In an accompanying paper it is shown that theoretically a zero-variance Monte Carlo scheme can be devised for criticality calculations if the space, energy and direction dependent adjoint function is exactly known. This requires biasing of the transition and collision kernels with the appropriate adjoint function. In this paper it is discussed how an existing general purpose Monte Carlo code like TRIPOLI can be modified to approach the zero-variance scheme. This requires modifications for reading in the adjoint function obtained from a separate deterministic calculation for a number of space intervals, energy groups and discrete directions. Furthermore, a function has to be added to supply the direction dependent and the averaged adjoint function at a specific position in the system by interpolation. The initial particle weights of a certain batch must be set inversely proportional to the averaged adjoint function and proper normalization of the initial weights must be secured. The sampling of the biased transition kernel requires cumulative integrals of the biased kernel along the flight path until a certain value, depending on a selected random number is reached to determine a new collision site. The weight of the particle must be adapted accordingly. The sampling of the biased collision kernel (in a multigroup treatment) is much more like the normal sampling procedure. A numerical example is given for a 3-group calculation with a simplified transport model (two-direction model), demonstrating that the zero-variance scheme can be approximated quite well for this simplified case. (authors)

  8. Imitation Monte Carlo methods for problems of the Boltzmann equation with small Knudsen numbers, parallelizing algorithms with splitting

    International Nuclear Information System (INIS)

    Khisamutdinov, A I; Velker, N N

    2014-01-01

    The talk examines a system of pairwise interaction particles, which models a rarefied gas in accordance with the nonlinear Boltzmann equation, the master equations of Markov evolution of this system and corresponding numerical Monte Carlo methods. Selection of some optimal method for simulation of rarefied gas dynamics depends on the spatial size of the gas flow domain. For problems with the Knudsen number K n of order unity 'imitation', or 'continuous time', Monte Carlo methods ([2]) are quite adequate and competitive. However if K n ≤ 0.1 (the large sizes), excessive punctuality, namely, the need to see all the pairs of particles in the latter, leads to a significant increase in computational cost(complexity). We are interested in to construct the optimal methods for Boltzmann equation problems with large enough spatial sizes of the flow. Speaking of the optimal, we mean that we are talking about algorithms for parallel computation to be implemented on high-performance multi-processor computers. The characteristic property of large systems is the weak dependence of sub-parts of each other at a sufficiently small time intervals. This property is taken into account in the approximate methods using various splittings of operator of corresponding master equations. In the paper, we develop the approximate method based on the splitting of the operator of master equations system 'over groups of particles' ([7]). The essence of the method is that the system of particles is divided into spatial subparts which are modeled independently for small intervals of time, using the precise 'imitation' method. The type of splitting used is different from other well-known type 'over collisions and displacements', which is an attribute of the known Direct simulation Monte Carlo methods. The second attribute of the last ones is the grid of the 'interaction cells', which is completely absent in the imitation methods. The

  9. Use of the Monte Carlo uncertainty combination method in nuclear reactor setpoint evaluation

    International Nuclear Information System (INIS)

    Berte, Frank J.

    2004-01-01

    This paper provides an overview of an alternate method for the performance of instrument uncertainty calculation and instrument setpoint determination, when a setpoint analysis requires application of techniques beyond that provided by the widely used 'Root Sum Squares' approach. The paper will address, when the application of the Monte Carlo (MC) method should be considered, application of the MC method when independent and/or dependent uncertainties are involved, and finally interpretation of results obtained. Both single module as well as instrument string sample applications will be presented. (author)

  10. Hamiltonian Markov Chain Monte Carlo Methods for the CUORE Neutrinoless Double Beta Decay Sensitivity

    Science.gov (United States)

    Graham, Eleanor; Cuore Collaboration

    2017-09-01

    The CUORE experiment is a large-scale bolometric detector seeking to observe the never-before-seen process of neutrinoless double beta decay. Predictions for CUORE's sensitivity to neutrinoless double beta decay allow for an understanding of the half-life ranges that the detector can probe, and also to evaluate the relative importance of different detector parameters. Currently, CUORE uses a Bayesian analysis based in BAT, which uses Metropolis-Hastings Markov Chain Monte Carlo, for its sensitivity studies. My work evaluates the viability and potential improvements of switching the Bayesian analysis to Hamiltonian Monte Carlo, realized through the program Stan and its Morpho interface. I demonstrate that the BAT study can be successfully recreated in Stan, and perform a detailed comparison between the results and computation times of the two methods.

  11. Visual improvement for bad handwriting based on Monte-Carlo method

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

    2014-03-01

    A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

  12. Development and evaluation of attenuation and scatter correction techniques for SPECT using the Monte Carlo method

    International Nuclear Information System (INIS)

    Ljungberg, M.

    1990-05-01

    Quantitative scintigrafic images, obtained by NaI(Tl) scintillation cameras, are limited by photon attenuation and contribution from scattered photons. A Monte Carlo program was developed in order to evaluate these effects. Simple source-phantom geometries and more complex nonhomogeneous cases can be simulated. Comparisons with experimental data for both homogeneous and nonhomogeneous regions and with published results have shown good agreement. The usefulness for simulation of parameters in scintillation camera systems, stationary as well as in SPECT systems, has also been demonstrated. An attenuation correction method based on density maps and build-up functions has been developed. The maps were obtained from a transmission measurement using an external 57 Co flood source and the build-up was simulated by the Monte Carlo code. Two scatter correction methods, the dual-window method and the convolution-subtraction method, have been compared using the Monte Carlo method. The aim was to compare the estimated scatter with the true scatter in the photo-peak window. It was concluded that accurate depth-dependent scatter functions are essential for a proper scatter correction. A new scatter and attenuation correction method has been developed based on scatter line-spread functions (SLSF) obtained for different depths and lateral positions in the phantom. An emission image is used to determine the source location in order to estimate the scatter in the photo-peak window. Simulation studies of a clinically realistic source in different positions in cylindrical water phantoms were made for three photon energies. The SLSF-correction method was also evaluated by simulation studies for 1. a myocardial source, 2. uniform source in the lungs and 3. a tumour located in the lungs in a realistic, nonhomogeneous computer phantom. The results showed that quantitative images could be obtained in nonhomogeneous regions. (67 refs.)

  13. Simulation of clinical X-ray tube using the Monte Carlo Method - PENELOPE code

    International Nuclear Information System (INIS)

    Albuquerque, M.A.G.; David, M.G.; Almeida, C.E. de; Magalhaes, L.A.G.; Braz, D.

    2015-01-01

    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)

  14. Variance analysis of the Monte-Carlo perturbation source method in inhomogeneous linear particle transport problems

    International Nuclear Information System (INIS)

    Noack, K.

    1982-01-01

    The perturbation source method may be a powerful Monte-Carlo means to calculate small effects in a particle field. In a preceding paper we have formulated this methos in inhomogeneous linear particle transport problems describing the particle fields by solutions of Fredholm integral equations and have derived formulae for the second moment of the difference event point estimator. In the present paper we analyse the general structure of its variance, point out the variance peculiarities, discuss the dependence on certain transport games and on generation procedures of the auxiliary particles and draw conclusions to improve this method

  15. Binocular optical axis parallelism detection precision analysis based on Monte Carlo method

    Science.gov (United States)

    Ying, Jiaju; Liu, Bingqi

    2018-02-01

    According to the working principle of the binocular photoelectric instrument optical axis parallelism digital calibration instrument, and in view of all components of the instrument, the various factors affect the system precision is analyzed, and then precision analysis model is established. Based on the error distribution, Monte Carlo method is used to analyze the relationship between the comprehensive error and the change of the center coordinate of the circle target image. The method can further guide the error distribution, optimize control the factors which have greater influence on the comprehensive error, and improve the measurement accuracy of the optical axis parallelism digital calibration instrument.

  16. A Monte Carlo method for nuclear evaporation and fission at intermediate energies

    International Nuclear Information System (INIS)

    Deppman, A.; Likhachev, V.P.; Mesa, J.; Pina, S.R. de; Arruda-Neto, J.D.T.; Goncalves, M.; Rodriguez, O.

    2003-04-01

    We describe a Monte Carlo method to calculate the characteristics of the competition between particle evaporation and nuclear fission processes taking place in the compound nucleus formed after the intranuclear cascade following the absorption of intermediate energy photons by the nucleus. In this version we include not only neutrons, but also protons and alphas as possible evaporating particles. However, this method allows an ease inclusion of other evaporating particles, as deuteron or heavier clusters. Some results for 237 Np, 238 U, and 232 Th are shown. (author)

  17. A Monte Carlo method for nuclear evaporation and fission at intermediate energies

    International Nuclear Information System (INIS)

    Deppman, A.; Tavares, O.A.P.; Duarte, S.B.; Arruda-Neto, J.D.T.; Goncalves, M.; Likhachev, V.P.; Mesa, J.; Oliveira, E.C. de; Pina, S.R. de; Rodriguez, O.

    2003-01-01

    We describe a Monte Carlo method to calculate the characteristics of the competition between particle evaporation and nuclear fission processes taking place in the compound nucleus formed after the intranuclear cascade following the absorption of intermediate energy photons by the nucleus. In this version we include not only neutrons, but also protons and alphas as possible evaporating particles. The present method allows the easy inclusion of other evaporating particles, such as deuteron or heavier clusters. Some fissility results are discussed for the target nuclei 237 Np, 238 U and 232 Th

  18. An efficient search method for finding the critical slip surface using the compositional Monte Carlo technique

    International Nuclear Information System (INIS)

    Goshtasbi, K.; Ahmadi, M; Naeimi, Y.

    2008-01-01

    Locating the critical slip surface and the associated minimum factor of safety are two complementary parts in a slope stability analysis. A large number of computer programs exist to solve slope stability problems. Most of these programs, however, have used inefficient and unreliable search procedures to locate the global minimum factor of safety. This paper presents an efficient and reliable method to determine the global minimum factor of safety coupled with a modified version of the Monte Carlo technique. Examples arc presented to illustrate the reliability of the proposed method

  19. Plasma flow to a surface using the iterative Monte Carlo method

    International Nuclear Information System (INIS)

    Pitcher, C.S.

    1994-01-01

    The iterative Monte Carlo (IMC) method is applied to a number of one-dimensional plasma flow problems, which encompass a wide range of conditions typical of those present in the boundary of magnetic fusion devices. The kinetic IMC method of solving plasma flow to a surface consists of launching and following particles within a grid of 'bins' into which weights are left according to the time a particle spends within a bin. The density and potential distributions within the plasma are iterated until the final solution is arrived at. The IMC results are compared with analytical treatments of these problems and, in general, good agreement is obtained. (author)

  20. Determination of factors through Monte Carlo method for Fricke dosimetry from 192Ir sources for brachytherapy

    International Nuclear Information System (INIS)

    David, Mariano Gazineu; Salata, Camila; Almeida, Carlos Eduardo

    2014-01-01

    The Laboratorio de Ciencias Radiologicas develops a methodology for the determination of the absorbed dose to water by Fricke chemical dosimetry method for brachytherapy sources of 192 Ir high dose rate and have compared their results with the laboratory of the National Research Council Canada. This paper describes the determination of the correction factors by Monte Carlo method, with the Penelope code. Values for all factors are presented, with a maximum difference of 0.22% for their determination by an alternative way. (author)

  1. Remarks on a financial inverse problem by means of Monte Carlo Methods

    Science.gov (United States)

    Cuomo, Salvatore; Di Somma, Vittorio; Sica, Federica

    2017-10-01

    Estimating the price of a barrier option is a typical inverse problem. In this paper we present a numerical and statistical framework for a market with risk-free interest rate and a risk asset, described by a Geometric Brownian Motion (GBM). After approximating the risk asset with a numerical method, we find the final option price by following an approach based on sequential Monte Carlo methods. All theoretical results are applied to the case of an option whose underlying is a real stock.

  2. A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT.

    Science.gov (United States)

    Dewaraja, Yuni K; Ljungberg, Michael; Majumdar, Amitava; Bose, Abhijit; Koral, Kenneth F

    2002-02-01

    This paper reports the implementation of the SIMIND Monte Carlo code on an IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. Our parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For (131)I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.

  3. Application of Monte Carlo filtering method in regional sensitivity analysis of AASHTOWare Pavement ME design

    Directory of Open Access Journals (Sweden)

    Zhong Wu

    2017-04-01

    Full Text Available Since AASHTO released the Mechanistic-Empirical Pavement Design Guide (MEPDG for public review in 2004, many highway research agencies have performed sensitivity analyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering (MCF, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed.

  4. Effective implementation of wavelet Galerkin method

    Science.gov (United States)

    Finěk, Václav; Šimunková, Martina

    2012-11-01

    It was proved by W. Dahmen et al. that an adaptive wavelet scheme is asymptotically optimal for a wide class of elliptic equations. This scheme approximates the solution u by a linear combination of N wavelets and a benchmark for its performance is the best N-term approximation, which is obtained by retaining the N largest wavelet coefficients of the unknown solution. Moreover, the number of arithmetic operations needed to compute the approximate solution is proportional to N. The most time consuming part of this scheme is the approximate matrix-vector multiplication. In this contribution, we will introduce our implementation of wavelet Galerkin method for Poisson equation -Δu = f on hypercube with homogeneous Dirichlet boundary conditions. In our implementation, we identified nonzero elements of stiffness matrix corresponding to the above problem and we perform matrix-vector multiplication only with these nonzero elements.

  5. Time-dependent integral equations of neutron transport for calculating the kinetics of nuclear reactors by the Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Davidenko, V. D., E-mail: Davidenko-VD@nrcki.ru; Zinchenko, A. S., E-mail: zin-sn@mail.ru; Harchenko, I. K. [National Research Centre Kurchatov Institute (Russian Federation)

    2016-12-15

    Integral equations for the shape functions in the adiabatic, quasi-static, and improved quasi-static approximations are presented. The approach to solving these equations by the Monte Carlo method is described.

  6. 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.

  7. Softcopy quality ruler method: implementation and validation

    Science.gov (United States)

    Jin, Elaine W.; Keelan, Brian W.; Chen, Junqing; Phillips, Jonathan B.; Chen, Ying

    2009-01-01

    A softcopy quality ruler method was implemented for the International Imaging Industry Association (I3A) Camera Phone Image Quality (CPIQ) Initiative. This work extends ISO 20462 Part 3 by virtue of creating reference digital images of known subjective image quality, complimenting the hardcopy Standard Reference Stimuli (SRS). The softcopy ruler method was developed using images from a Canon EOS 1Ds Mark II D-SLR digital still camera (DSC) and a Kodak P880 point-and-shoot DSC. Images were viewed on an Apple 30in Cinema Display at a viewing distance of 34 inches. Ruler images were made for 16 scenes. Thirty ruler images were generated for each scene, representing ISO 20462 Standard Quality Scale (SQS) values of approximately 2 to 31 at an increment of one just noticeable difference (JND) by adjusting the system modulation transfer function (MTF). A Matlab GUI was developed to display the ruler and test images side-by-side with a user-adjustable ruler level controlled by a slider. A validation study was performed at Kodak, Vista Point Technology, and Aptina Imaging in which all three companies set up a similar viewing lab to run the softcopy ruler method. The results show that the three sets of data are in reasonable agreement with each other, with the differences within the range expected from observer variability. Compared to previous implementations of the quality ruler, the slider-based user interface allows approximately 2x faster assessments with 21.6% better precision.

  8. A graphics-card implementation of Monte-Carlo simulations for cosmic-ray transport

    Science.gov (United States)

    Tautz, R. C.

    2016-05-01

    A graphics card implementation of a test-particle simulation code is presented that is based on the CUDA extension of the C/C++ programming language. The original CPU version has been developed for the calculation of cosmic-ray diffusion coefficients in artificial Kolmogorov-type turbulence. In the new implementation, the magnetic turbulence generation, which is the most time-consuming part, is separated from the particle transport and is performed on a graphics card. In this article, the modification of the basic approach of integrating test particle trajectories to employ the SIMD (single instruction, multiple data) model is presented and verified. The efficiency of the new code is tested and several language-specific accelerating factors are discussed. For the example of isotropic magnetostatic turbulence, sample results are shown and a comparison to the results of the CPU implementation is performed.

  9. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    Jadach, S.; Skrzypek, M. [Polish Academy of Sciences, Institute of Nuclear Physics, Krakow (Poland); Nail, G. [University of Manchester, Particle Physics Group, School of Physics and Astronomy, Manchester (United Kingdom); Karlsruhe Institute of Technology, Institute for Theoretical Physics, Karlsruhe (Germany); Placzek, W. [Jagiellonian University, Marian Smoluchowski Institute of Physics, Krakow (Poland); Sapeta, S.; Siodmok, A. [Polish Academy of Sciences, Institute of Nuclear Physics, Krakow (Poland); Theoretical Physics Department, CERN, Geneva (Switzerland)

    2017-03-15

    We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton-shower Monte Carlo generators (NLO+PS). This method was described in detail in our previous publications, where it was also compared with other NLO+PS matching approaches (MC rate at NLO and POWHEG) as well as fixed-order NLO and NNLO calculations. Here we concentrate on presenting some numerical results (cross sections and distributions) for Z/γ* (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell-Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then we present the first results of the KrkNLO method for Higgs production in gluon-gluon fusion at the LHC and compare them with MC rate at NLO and POWHEG predictions from Herwig 7, fixed-order results from HNNLO and a resummed calculation from HqT, as well as with experimental data from the ATLAS collaboration. (orig.)

  11. Analysis and modeling of localized heat generation by tumor-targeted nanoparticles (Monte Carlo methods)

    Science.gov (United States)

    Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan

    2016-04-01

    We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.

  12. Monte Carlo Finite Volume Element Methods for the Convection-Diffusion Equation with a Random Diffusion Coefficient

    Directory of Open Access Journals (Sweden)

    Qian Zhang

    2014-01-01

    Full Text Available The paper presents a framework for the construction of Monte Carlo finite volume element method (MCFVEM for the convection-diffusion equation with a random diffusion coefficient, which is described as a random field. We first approximate the continuous stochastic field by a finite number of random variables via the Karhunen-Loève expansion and transform the initial stochastic problem into a deterministic one with a parameter in high dimensions. Then we generate independent identically distributed approximations of the solution by sampling the coefficient of the equation and employing finite volume element variational formulation. Finally the Monte Carlo (MC method is used to compute corresponding sample averages. Statistic error is estimated analytically and experimentally. A quasi-Monte Carlo (QMC technique with Sobol sequences is also used to accelerate convergence, and experiments indicate that it can improve the efficiency of the Monte Carlo method.

  13. Calculating Relativistic Transition Matrix Elements for Hydrogenic Atoms Using Monte Carlo Methods

    Science.gov (United States)

    Alexander, Steven; Coldwell, R. L.

    2015-03-01

    The nonrelativistic transition matrix elements for hydrogen atoms can be computed exactly and these expressions are given in a number of classic textbooks. The relativistic counterparts of these equations can also be computed exactly but these expressions have been described in only a few places in the literature. In part, this is because the relativistic equations lack the elegant simplicity of the nonrelativistic equations. In this poster I will describe how variational Monte Carlo methods can be used to calculate the energy and properties of relativistic hydrogen atoms and how the wavefunctions for these systems can be used to calculate transition matrix elements.

  14. 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)

  15. 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.

  16. A Monte-Carlo study of landmines detection by neutron backscattering method

    International Nuclear Information System (INIS)

    Maucec, M.; De Meijer, R.J.

    2000-01-01

    The use of Monte-Carlo simulations for modelling a simplified landmine detector system with a 252 Cf- neutron source is presented in this contribution. Different aspects and variety of external conditions, affecting the localisation and identification of a buried suspicious object (such as landmine) have been tested. Results of sensitivity calculations confirm that the landmine detection methods, based on the analysis of the backscattered neutron radiation can be applicable in higher density formations, with the mass fraction of present pore-water <15 %. (author)

  17. Evaluation of gamma-ray attenuation properties of bismuth borate glass systems using Monte Carlo method

    International Nuclear Information System (INIS)

    Tarim, Urkiye Akar; Ozmutlu, Emin N.; Yalcin, Sezai; Gundogdu, Ozcan; Bradley, D.A.; Gurler, Orhan

    2017-01-01

    A Monte Carlo method was developed to investigate radiation shielding properties of bismuth borate glass. The mass attenuation coefficients and half-value layer parameters were determined for different fractional amounts of Bi 2 O 3 in the glass samples for the 356, 662, 1173 and 1332 keV photon energies. A comparison of the theoretical and experimental attenuation coefficients is presented. - Highlights: • Radiation shielding properties of bismuth borate glass systems have been reported. • Mass attenuation coefficients increase linearly with increase in Bi concentration. • Half-value layer decreases with increasing concentration of Bi. • Half-value layer decreases with the increase in the sample density.

  18. Monte-Carlo Method Python Library for dose distribution Calculation in Brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Randriantsizafy, R D; Ramanandraibe, M J [Madagascar Institut National des Sciences et Techniques Nucleaires, Antananarivo (Madagascar); Raboanary, R [Institut of astro and High-Energy Physics Madagascar, University of Antananarivo, Antananarivo (Madagascar)

    2007-07-01

    The Cs-137 Brachytherapy treatment is performed in Madagascar since 2005. Time treatment calculation for prescribed dose is made manually. Monte-Carlo Method Python library written at Madagascar INSTN is experimentally used to calculate the dose distribution on the tumour and around it. The first validation of the code was done by comparing the library curves with the Nucletron company curves. To reduce the duration of the calculation, a Grid of PC's is set up with listner patch run on each PC. The library will be used to modelize the dose distribution in the CT scan patient picture for individual and better accuracy time calculation for a prescribed dose.

  19. Monte-Carlo Method Python Library for dose distribution Calculation in Brachytherapy

    International Nuclear Information System (INIS)

    Randriantsizafy, R.D.; Ramanandraibe, M.J.; Raboanary, R.

    2007-01-01

    The Cs-137 Brachytherapy treatment is performed in Madagascar since 2005. Time treatment calculation for prescribed dose is made manually. Monte-Carlo Method Python library written at Madagascar INSTN is experimentally used to calculate the dose distribution on the tumour and around it. The first validation of the code was done by comparing the library curves with the Nucletron company curves. To reduce the duration of the calculation, a Grid of PC's is set up with listner patch run on each PC. The library will be used to modelize the dose distribution in the CT scan patient picture for individual and better accuracy time calculation for a prescribed dose.

  20. The future of new calculation concepts in dosimetry based on the Monte Carlo Methods

    International Nuclear Information System (INIS)

    Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M.

    2009-01-01

    Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)

  1. Reliability analysis of PWR thermohydraulic design by the Monte Carlo method

    International Nuclear Information System (INIS)

    Silva Junior, H.C. da; Berthoud, J.S.; Carajilescov, P.

    1977-01-01

    The operating power level of a PWR is limited by the occurence of DNB. Without affecting the safety and performance of the reactor, it is possible to admit failure of a certain number of core channels. The thermohydraulic design, however, is affect by a great number of uncertainties of deterministic or statistical nature. In the present work, the Monte Carlo method is applied to yield the probability that a number F of channels submitted to boiling crises will not exceed a number F* previously given. This probability is obtained as function of the reactor power level. (Author) [pt

  2. Determination of the spatial response of neutron based analysers using a Monte Carlo based method

    International Nuclear Information System (INIS)

    Tickner, James

    2000-01-01

    One of the principal advantages of using thermal neutron capture (TNC, also called prompt gamma neutron activation analysis or PGNAA) or neutron inelastic scattering (NIS) techniques for measuring elemental composition is the high penetrating power of both the incident neutrons and the resultant gamma-rays, which means that large sample volumes can be interrogated. Gauges based on these techniques are widely used in the mineral industry for on-line determination of the composition of bulk samples. However, attenuation of both neutrons and gamma-rays in the sample and geometric (source/detector distance) effects typically result in certain parts of the sample contributing more to the measured composition than others. In turn, this introduces errors in the determination of the composition of inhomogeneous samples. This paper discusses a combined Monte Carlo/analytical method for estimating the spatial response of a neutron gauge. Neutron propagation is handled using a Monte Carlo technique which allows an arbitrarily complex neutron source and gauge geometry to be specified. Gamma-ray production and detection is calculated analytically which leads to a dramatic increase in the efficiency of the method. As an example, the method is used to study ways of reducing the spatial sensitivity of on-belt composition measurements of cement raw meal

  3. Monte Carlo method for polarized radiative transfer in gradient-index media

    International Nuclear Information System (INIS)

    Zhao, J.M.; Tan, J.Y.; Liu, L.H.

    2015-01-01

    Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer. - Highlights: • A Monte Carlo method for polarized radiative transfer in gradient index media. • Effect of curved ray paths on polarized radiative transfer is considered. • Importance of atmospheric refraction for polarized light transfer is demonstrated

  4. On solution to the problem of criticality by alternative Monte Carlo method

    International Nuclear Information System (INIS)

    Kyncl, J.

    2005-03-01

    The problem of criticality for the neutron transport equation is analyzed. The problem is transformed into an equivalent problem in a suitable set of complex functions, and the existence and uniqueness of its solution is demonstrated. The source iteration method is discussed. It is shown that the final result of the iterative process is strongly affected by the insufficient accuracy of the individual iterations. A modified method is suggested to circumvent this problem based on the theory of positive operators; the criticality problem is solved by the Monte Carlo method constructing special random process and variable so that the difference between the result and the true value can be arbitrarily small. The efficiency of this alternative method is analysed

  5. Scattering theory on the lattice and with a Monte Carlo method

    International Nuclear Information System (INIS)

    Kroeger, H.; Moriarty, K.J.M.; Potvin, J.

    1990-01-01

    We present an alternative time-dependent method of calculating the S matrix in quantum systems governed by a Hamiltonian. In the first step one constructs a new Hamiltonian that describes the physics of scattering at energy E with a reduced number of degrees of freedom. Its matrix elements are computed with a Monte Carlo projector method. In the second step the scattering matrix is computed algebraically via diagonalization and exponentiation of the new Hamiltonian. Although we have in mind applications in many-body systems and quantum field theory, the method should be applicable and useful in such diverse areas as atomic and molecular physics, nuclear physics, high-energy physics and solid-state physics. As an illustration of the method, we compute s-wave scattering of two nucleons in a nonrelativistic potential model (Yamaguchi potential), for which the S matrix is known exactly

  6. An adaptive Monte Carlo method under emission point as sampling station for deep penetration calculation

    International Nuclear Information System (INIS)

    Wang, Ruihong; Yang, Shulin; Pei, Lucheng

    2011-01-01

    Deep penetration problem has been one of the difficult problems in shielding calculation with Monte Carlo method for several decades. In this paper, an adaptive technique under the emission point as a sampling station is presented. The main advantage is to choose the most suitable sampling number from the emission point station to get the minimum value of the total cost in the process of the random walk. Further, the related importance sampling method is also derived. The main principle is to define the importance function of the response due to the particle state and ensure the sampling number of the emission particle is proportional to the importance function. The numerical results show that the adaptive method under the emission point as a station could overcome the difficulty of underestimation to the result in some degree, and the related importance sampling method gets satisfied results as well. (author)

  7. Acceptance and implementation of a system of planning computerized based on Monte Carlo; Aceptacion y puesta en marcha de un sistema de planificacion comutarizada basado en Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.

    2013-07-01

    It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)

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

    International Nuclear Information System (INIS)

    Yuan Chao; Zhou Cancan; Zhang Feng; Chen Zhi

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-05-15

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  11. Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.

    Science.gov (United States)

    Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong

    2017-02-28

    The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.

  12. Monteray Mark-I: Computer program (PC-version) for shielding calculation with Monte Carlo method

    International Nuclear Information System (INIS)

    Pudjijanto, M.S.; Akhmad, Y.R.

    1998-01-01

    A computer program for gamma ray shielding calculation using Monte Carlo method has been developed. The program is written in WATFOR77 language. The MONTERAY MARH-1 is originally developed by James Wood. The program was modified by the authors that the modified version is easily executed. Applying Monte Carlo method the program observe photon gamma transport in an infinity planar shielding with various thick. A photon gamma is observed till escape from the shielding or when its energy less than the cut off energy. Pair production process is treated as pure absorption process that annihilation photons generated in the process are neglected in the calculation. The out put data calculated by the program are total albedo, build-up factor, and photon spectra. The calculation result for build-up factor of a slab lead and water media with 6 MeV parallel beam gamma source shows that they are in agreement with published data. Hence the program is adequate as a shielding design tool for observing gamma radiation transport in various media

  13. Uncertainty analysis using Monte Carlo method in the measurement of phase by ESPI

    International Nuclear Information System (INIS)

    Anguiano Morales, Marcelino; Martinez, Amalia; Rayas, J. A.; Cordero, Raul R.

    2008-01-01

    A method for simultaneously measuring whole field in-plane displacements by using optical fiber and based on the dual-beam illumination principle electronic speckle pattern interferometry (ESPI) is presented in this paper. A set of single mode optical fibers and beamsplitter are employed to split the laser beam into four beams of equal intensity.One pair of fibers is utilized to illuminate the sample in the horizontal plane so it is sensitive only to horizontal in-plane displacement. Another pair of optical fibers is set to be sensitive only to vertical in-plane displacement. Each pair of optical fibers differs in longitude to avoid unwanted interference. By means of a Fourier-transform method of fringe-pattern analysis (Takeda method), we can obtain the quantitative data of whole field displacements. We found the uncertainty associated with the phases by mean of Monte Carlo-based technique

  14. Monte Carlo based statistical power analysis for mediation models: methods and software.

    Science.gov (United States)

    Zhang, Zhiyong

    2014-12-01

    The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

  15. Multi-chain Markov chain Monte Carlo methods for computationally expensive models

    Science.gov (United States)

    Huang, M.; Ray, J.; Ren, H.; Hou, Z.; Bao, J.

    2017-12-01

    Markov chain Monte Carlo (MCMC) methods are used to infer model parameters from observational data. The parameters are inferred as probability densities, thus capturing estimation error due to sparsity of the data, and the shortcomings of the model. Multiple communicating chains executing the MCMC method have the potential to explore the parameter space better, and conceivably accelerate the convergence to the final distribution. We present results from tests conducted with the multi-chain method to show how the acceleration occurs i.e., for loose convergence tolerances, the multiple chains do not make much of a difference. The ensemble of chains also seems to have the ability to accelerate the convergence of a few chains that might start from suboptimal starting points. Finally, we show the performance of the chains in the estimation of O(10) parameters using computationally expensive forward models such as the Community Land Model, where the sampling burden is distributed over multiple chains.

  16. Ant colony algorithm implementation in electron and photon Monte Carlo transport: Application to the commissioning of radiosurgery photon beams

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' ' Carlos Haya' ' , Avda. Carlos Haya s/n, E-29010 Malaga (Spain); Unidad de Radiofisica Hospitalaria, Hospital Xanit Internacional, Avda. de los Argonautas s/n, E-29630 Benalmadena (Malaga) (Spain); NCTeam, Strahlenklinik, Universitaetsklinikum Essen, Hufelandstr. 55, D-45122 Essen (Germany); Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2010-07-15

    Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within {approx}3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

  17. Ant colony algorithm implementation in electron and photon Monte Carlo transport: Application to the commissioning of radiosurgery photon beams

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M.

    2010-01-01

    Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within ∼3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

  18. Charged-particle thermonuclear reaction rates: I. Monte Carlo method and statistical distributions

    International Nuclear Information System (INIS)

    Longland, R.; Iliadis, C.; Champagne, A.E.; Newton, J.R.; Ugalde, C.; Coc, A.; Fitzgerald, R.

    2010-01-01

    A method based on Monte Carlo techniques is presented for evaluating thermonuclear reaction rates. We begin by reviewing commonly applied procedures and point out that reaction rates that have been reported up to now in the literature have no rigorous statistical meaning. Subsequently, we associate each nuclear physics quantity entering in the calculation of reaction rates with a specific probability density function, including Gaussian, lognormal and chi-squared distributions. Based on these probability density functions the total reaction rate is randomly sampled many times until the required statistical precision is achieved. This procedure results in a median (Monte Carlo) rate which agrees under certain conditions with the commonly reported recommended 'classical' rate. In addition, we present at each temperature a low rate and a high rate, corresponding to the 0.16 and 0.84 quantiles of the cumulative reaction rate distribution. These quantities are in general different from the statistically meaningless 'minimum' (or 'lower limit') and 'maximum' (or 'upper limit') reaction rates which are commonly reported. Furthermore, we approximate the output reaction rate probability density function by a lognormal distribution and present, at each temperature, the lognormal parameters μ and σ. The values of these quantities will be crucial for future Monte Carlo nucleosynthesis studies. Our new reaction rates, appropriate for bare nuclei in the laboratory, are tabulated in the second paper of this issue (Paper II). The nuclear physics input used to derive our reaction rates is presented in the third paper of this issue (Paper III). In the fourth paper of this issue (Paper IV) we compare our new reaction rates to previous results.

  19. Quantum Monte Carlo methods and strongly correlated electrons on honeycomb structures

    Energy Technology Data Exchange (ETDEWEB)

    Lang, Thomas C.

    2010-12-16

    In this thesis we apply recently developed, as well as sophisticated quantum Monte Carlo methods to numerically investigate models of strongly correlated electron systems on honeycomb structures. The latter are of particular interest owing to their unique properties when simulating electrons on them, like the relativistic dispersion, strong quantum fluctuations and their resistance against instabilities. This work covers several projects including the advancement of the weak-coupling continuous time quantum Monte Carlo and its application to zero temperature and phonons, quantum phase transitions of valence bond solids in spin-1/2 Heisenberg systems using projector quantum Monte Carlo in the valence bond basis, and the magnetic field induced transition to a canted antiferromagnet of the Hubbard model on the honeycomb lattice. The emphasis lies on two projects investigating the phase diagram of the SU(2) and the SU(N)-symmetric Hubbard model on the hexagonal lattice. At sufficiently low temperatures, condensed-matter systems tend to develop order. An exception are quantum spin-liquids, where fluctuations prevent a transition to an ordered state down to the lowest temperatures. Previously elusive in experimentally relevant microscopic two-dimensional models, we show by means of large-scale quantum Monte Carlo simulations of the SU(2) Hubbard model on the honeycomb lattice, that a quantum spin-liquid emerges between the state described by massless Dirac fermions and an antiferromagnetically ordered Mott insulator. This unexpected quantum-disordered state is found to be a short-range resonating valence bond liquid, akin to the one proposed for high temperature superconductors. Inspired by the rich phase diagrams of SU(N) models we study the SU(N)-symmetric Hubbard Heisenberg quantum antiferromagnet on the honeycomb lattice to investigate the reliability of 1/N corrections to large-N results by means of numerically exact QMC simulations. We study the melting of phases

  20. Application of Monte Carlo method for dose calculation in thyroid follicle

    International Nuclear Information System (INIS)

    Silva, Frank Sinatra Gomes da

    2008-02-01

    The Monte Carlo method is an important tool to simulate radioactive particles interaction with biologic medium. The principal advantage of the method when compared with deterministic methods is the ability to simulate a complex geometry. Several computational codes use the Monte Carlo method to simulate the particles transport and they have the capacity to simulate energy deposition in models of organs and/or tissues, as well models of cells of human body. Thus, the calculation of the absorbed dose to thyroid's follicles (compound of colloid and follicles' cells) have a fundamental importance to dosimetry, because these cells are radiosensitive due to ionizing radiation exposition, in particular, exposition due to radioisotopes of iodine, because a great amount of radioiodine may be released into the environment in case of a nuclear accidents. In this case, the goal of this work was use the code of particles transport MNCP4C to calculate absorbed doses in models of thyroid's follicles, for Auger electrons, internal conversion electrons and beta particles, by iodine-131 and short-lived iodines (131, 132, 133, 134 e 135), with diameters varying from 30 to 500 μm. The results obtained from simulation with the MCNP4C code shown an average percentage of the 25% of total absorbed dose by colloid to iodine- 131 and 75% to short-lived iodine's. For follicular cells, this percentage was of 13% to iodine-131 and 87% to short-lived iodine's. The contributions from particles with low energies, like Auger and internal conversion electrons should not be neglected, to assessment the absorbed dose in cellular level. Agglomerative hierarchical clustering was used to compare doses obtained by codes MCNP4C, EPOTRAN, EGS4 and by deterministic methods. (author)

  1. Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations

    International Nuclear Information System (INIS)

    Brown, F.

    2007-01-01

    Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)

  2. Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

    Science.gov (United States)

    Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

    2005-01-01

    The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

  3. Application of the Monte Carlo integration method in calculations of dose distributions in HDR-Brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Baltas, D; Geramani, K N; Ioannidis, G T; Kolotas, C; Zamboglou, N [Strahlenklinik, Stadtische Kliniken Offenbach, Offenbach (Germany); Giannouli, S [Department of Electrical and Computer Engineering, National Technical University of Athens, Athens (Greece)

    1999-12-31

    Source anisotropy is a very important factor in brachytherapy quality assurance of high dose rate HDR Ir 192 afterloading stepping sources. If anisotropy is not taken into account then doses received by a brachytherapy patient in certain directions can be in error by a clinically significant amount. Experimental measurements of anisotropy are very labour intensive. We have shown that within acceptable limits of accuracy, Monte Carlo integration (MCI) of a modified Sievert integral (3D generalisation) can provide the necessary data within a much shorter time scale than can experiments. Hence MCI can be used for routine quality assurance schedules whenever a new design of HDR or PDR Ir 192 is used for brachytherapy afterloading. Our MCI calculation results are comparable with published experimental data and Monte Carlo simulation data for microSelectron and VariSource Ir 192 sources. We have shown not only that MCI offers advantages over alternative numerical integration methods, but also that treating filtration coefficients as radial distance-dependent functions improves Sievert integral accuracy at low energies. This paper also provides anisotropy data for three new Ir 192 sources, one for microSelectron-HDR and two for the microSelectron-PDR, for which data currently is not available. The information we have obtained in this study can be incorporated into clinical practice.

  4. Improvement of the neutron flux calculations in thick shield by conditional Monte Carlo and deterministic methods

    International Nuclear Information System (INIS)

    Ghassoun, Jillali; Jehoauni, Abdellatif

    2000-01-01

    In practice, the estimation of the flux obtained by Fredholm integral equation needs a truncation of the Neuman series. The order N of the truncation must be large in order to get a good estimation. But a large N induces a very large computation time. So the conditional Monte Carlo method is used to reduce time without affecting the estimation quality. In a previous works, in order to have rapid convergence of calculations it was considered only weakly diffusing media so that has permitted to truncate the Neuman series after an order of 20 terms. But in the most practical shields, such as water, graphite and beryllium the scattering probability is high and if we truncate the series at 20 terms we get bad estimation of flux, so it becomes useful to use high orders in order to have good estimation. We suggest two simple techniques based on the conditional Monte Carlo. We have proposed a simple density of sampling the steps for the random walk. Also a modified stretching factor density depending on a biasing parameter which affects the sample vector by stretching or shrinking the original random walk in order to have a chain that ends at a given point of interest. Also we obtained a simple empirical formula which gives the neutron flux for a medium characterized by only their scattering probabilities. The results are compared to the exact analytic solution, we have got a good agreement of results with a good acceleration of convergence calculations. (author)

  5. TREEDE, Point Fluxes and Currents Based on Track Rotation Estimator by Monte-Carlo Method

    International Nuclear Information System (INIS)

    Dubi, A.

    1985-01-01

    1 - Description of problem or function: TREEDE is a Monte Carlo transport code based on the Track Rotation estimator, used, in general, to calculate fluxes and currents at a point. This code served as a test code in the development of the concept of the Track Rotation estimator, and therefore analogue Monte Carlo is used (i.e. no importance biasing). 2 - Method of solution: The basic idea is to follow the particle's track in the medium and then to rotate it such that it passes through the detector point. That is, rotational symmetry considerations (even in non-spherically symmetric configurations) are applied to every history, so that a very large fraction of the track histories can be rotated and made to pass through the point of interest; in this manner the 1/r 2 singularity in the un-collided flux estimator (next event estimator) is avoided. TREEDE, being a test code, is used to estimate leakage or in-medium fluxes at given points in a 3-dimensional finite box, where the source is an isotropic point source at the centre of the z = 0 surface. However, many of the constraints of geometry and source can be easily removed. The medium is assumed homogeneous with isotropic scattering, and one energy group only is considered. 3 - Restrictions on the complexity of the problem: One energy group, a homogeneous medium, isotropic scattering

  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. On stochastic error and computational efficiency of the Markov Chain Monte Carlo method

    KAUST Repository

    Li, Jun

    2014-01-01

    In Markov Chain Monte Carlo (MCMC) simulations, thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. These samples are selected in accordance with the probability distribution function, known from the partition function of equilibrium state. As the stochastic error of the simulation results is significant, it is desirable to understand the variance of the estimation by ensemble average, which depends on the sample size (i.e., the total number of samples in the set) and the sampling interval (i.e., cycle number between two consecutive samples). Although large sample sizes reduce the variance, they increase the computational cost of the simulation. For a given CPU time, the sample size can be reduced greatly by increasing the sampling interval, while having the corresponding increase in variance be negligible if the original sampling interval is very small. In this work, we report a few general rules that relate the variance with the sample size and the sampling interval. These results are observed and confirmed numerically. These variance rules are derived for theMCMCmethod but are also valid for the correlated samples obtained using other Monte Carlo methods. The main contribution of this work includes the theoretical proof of these numerical observations and the set of assumptions that lead to them. © 2014 Global-Science Press.

  8. Assessment of probabilistic distributed factors influencing renewable energy supply for hotels using Monte-Carlo methods

    International Nuclear Information System (INIS)

    Meschede, Henning; Dunkelberg, Heiko; Stöhr, Fabian; Peesel, Ron-Hendrik; Hesselbach, Jens

    2017-01-01

    This paper investigates the use of renewable energies to supply hotels in island regions. The aim is to evaluate the effect of weather and occupancy fluctuations on the sensitivity of investment criteria. The sensitivity of the chosen energy system is examined using a Monte Carlo simulation considering stochastic weather data, occupancy rates and energy needs. For this purpose, algorithms based on measured data are developed and applied to a case study on the Canary Islands. The results underline that electricity use in hotels is by far the largest contributor to their overall energy cost. For the invested hotel on the Canary Islands, the optimal share of renewable electricity generation is found to be 63%, split into 67% photovoltaic and 33% wind power. Furthermore, a battery is used to balance the differences between day and night. It is found, that the results are sensitive to weather fluctuations as well as economic parameters to about the same degree. The results underline the risk caused by using reference time series for designing energy systems. The Monte Carlo method helps to define the mean of the annuity more precisely and to rate the risk of fluctuating weather and occupancy better. - Highlights: • An approach to generate synthetic weather data was pointed out. • A methodology to create synthetic energy demand data for hotels was developed. • The influence to the sensitivity of renewable energy systems was analysed. • Fluctuations in weather data have a greater impact on the economy than occupancy.

  9. Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot

    International Nuclear Information System (INIS)

    Wang Yongbo; Wu Huapeng; Handroos, Heikki

    2011-01-01

    This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has ten degrees of freedom (DOF), among which six DOF are contributed by the parallel mechanism and the rest are from the serial mechanism. In this paper, a kinematic error model which involves 54 unknown geometrical error parameters is developed for the proposed robot. Based on this error model, the mean values of the unknown parameters are statistically analyzed and estimated by means of Markov Chain Monte Carlo (MCMC) approach. The computer simulation is conducted by introducing random geometric errors and measurement poses which represent the corresponding real physical behaviors. The simulation results of the marginal posterior distributions of the estimated model parameters indicate that our method is reliable and robust.

  10. Reproduction of the coincidence effect in gamma ray spectrometry by using Monte Carlo method

    International Nuclear Information System (INIS)

    Park, S. H.; Kim, J. K.; Lee, S. H.

    2001-01-01

    Scintillation detector such as NaI(TI), or semiconductor detector, such as HPGe, are used for Measurement/Assessment of the radiation type and radiation activity. The measured energy spectrum are used for measuring the radiation type and activity. Corrections for true coincidence due to emit more than 2 photons at the same time and random coincidence due to measuring system when increasing of the radiation intensity. For accurate assessment, measurement with adequate measure system is performed, and corrections for coincidence are performed in the hardware aspect and software aspect. In general, there are limitations or difficulties in measurement of radiation assessment, computational simulation is instead used. In simulation, it has much advantages than measurement in technically, timely, and financially, it is widely used instead of measurement. In this study, the method to reproduce of the coincidence effect was proposed by using monte carlo method

  11. Transport calculation of medium-energy protons and neutrons by Monte Carlo method

    International Nuclear Information System (INIS)

    Ban, Syuuichi; Hirayama, Hideo; Katoh, Kazuaki.

    1978-09-01

    A Monte Carlo transport code, ARIES, has been developed for protons and neutrons at medium energy (25 -- 500 MeV). Nuclear data provided by R.G. Alsmiller, Jr. were used for the calculation. To simulate the cascade development in the medium, each generation was represented by a single weighted particle and an average number of emitted particles was used as the weight. Neutron fluxes were stored by the collisions density method. The cutoff energy was set to 25 MeV. Neutrons below the cutoff were stored to be used as the source for the low energy neutron transport calculation upon the discrete ordinates method. Then transport calculations were performed for both low energy neutrons (thermal -- 25 MeV) and secondary gamma-rays. Energy spectra of emitted neutrons were calculated and compared with those of published experimental and calculated results. The agreement was good for the incident particles of energy between 100 and 500 MeV. (author)

  12. Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

    Science.gov (United States)

    Schwarz, Karsten; Rieger, Heiko

    2013-03-01

    We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

  13. Thermal studies of a superconducting current limiter using Monte-Carlo method

    International Nuclear Information System (INIS)

    Leveque, J.; Rezzoug, A.

    1999-01-01

    Considering the increase of the fault current level in electrical network, the current limiters become very interesting. The superconducting limiters are based on the quasi-instantaneous intrinsic transition from superconducting state to normal resistive one. Without detection of default or given order, they reduce the constraints supported by electrical installations above the fault. To avoid the destruction of the superconducting coil, the temperature must not exceed a certain value. Therefore the design of a superconducting coil needs the simultaneous resolution of an electrical equation and a thermal one. This papers deals with a resolution of this coupled problem by the method of Monte-Carlo. This method allows us to calculate the evolution of the resistance of the coil as well as the current of limitation. Experimental results are compared with theoretical ones. (orig.)

  14. 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.

  15. Employing a Monte Carlo algorithm in Newton-type methods for restricted maximum likelihood estimation of genetic parameters.

    Directory of Open Access Journals (Sweden)

    Kaarina Matilainen

    Full Text Available Estimation of variance components by Monte Carlo (MC expectation maximization (EM restricted maximum likelihood (REML is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR, where the information matrix was generated via sampling; MC average information(AI, where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.

  16. Implementation of Japanese male and female tomographic phantoms to multi-particle Monte Carlo code for ionizing radiation dosimetry

    International Nuclear Information System (INIS)

    Lee, Choonsik; Nagaoka, Tomoaki; Lee, Jai-Ki

    2006-01-01

    Japanese male and female tomographic phantoms, which have been developed for radio-frequency electromagnetic-field dosimetry, were implemented into multi-particle Monte Carlo transport code to evaluate realistic dose distribution in human body exposed to radiation field. Japanese tomographic phantoms, which were developed from the whole body magnetic resonance images of Japanese average adult male and female, were processed as follows to be implemented into general purpose multi-particle Monte Carlo code, MCNPX2.5. Original array size of Japanese male and female phantoms, 320 x 160 x 866 voxels and 320 x 160 x 804 voxels, respectively, were reduced into 320 x 160 x 433 voxels and 320 x 160 x 402 voxels due to the limitation of memory use in MCNPX2.5. The 3D voxel array of the phantoms were processed by using the built-in repeated structure algorithm, where the human anatomy was described by the repeated lattice of tiny cube containing the information of material composition and organ index number. Original phantom data were converted into ASCII file, which can be directly ported into the lattice card of MCNPX2.5 input deck by using in-house code. A total of 30 material compositions obtained from International Commission on Radiation Units and Measurement (ICRU) report 46 were assigned to 54 and 55 organs and tissues in the male and female phantoms, respectively, and imported into the material card of MCNPX2.5 along with the corresponding cross section data. Illustrative calculation of absorbed doses for 26 internal organs and effective dose were performed for idealized broad parallel photon and neutron beams in anterior-posterior irradiation geometry, which is typical for workers at nuclear power plant. The results were compared with the data from other Japanese and Caucasian tomographic phantom, and International Commission on Radiological Protection (ICRP) report 74. The further investigation of the difference in organ dose and effective dose among tomographic

  17. Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method

    Directory of Open Access Journals (Sweden)

    Muneki Yasuda

    2018-04-01

    Full Text Available The machine learning techniques for Markov random fields are fundamental in various fields involving pattern recognition, image processing, sparse modeling, and earth science, and a Boltzmann machine is one of the most important models in Markov random fields. However, the inference and learning problems in the Boltzmann machine are NP-hard. The investigation of an effective learning algorithm for the Boltzmann machine is one of the most important challenges in the field of statistical machine learning. In this paper, we study Boltzmann machine learning based on the (first-order spatial Monte Carlo integration method, referred to as the 1-SMCI learning method, which was proposed in the author’s previous paper. In the first part of this paper, we compare the method with the maximum pseudo-likelihood estimation (MPLE method using a theoretical and a numerical approaches, and show the 1-SMCI learning method is more effective than the MPLE. In the latter part, we compare the 1-SMCI learning method with other effective methods, ratio matching and minimum probability flow, using a numerical experiment, and show the 1-SMCI learning method outperforms them.

  18. Quasi Monte Carlo methods for optimization models of the energy industry with pricing and load processes; Quasi-Monte Carlo Methoden fuer Optimierungsmodelle der Energiewirtschaft mit Preis- und Last-Prozessen

    Energy Technology Data Exchange (ETDEWEB)

    Leoevey, H.; Roemisch, W. [Humboldt-Univ., Berlin (Germany)

    2015-07-01

    We discuss progress in quasi Monte Carlo methods for numerical calculation integrals or expected values and justify why these methods are more efficient than the classic Monte Carlo methods. Quasi Monte Carlo methods are found to be particularly efficient if the integrands have a low effective dimension. That's why We also discuss the concept of effective dimension and prove on the example of a stochastic Optimization model of the energy industry that such models can posses a low effective dimension. Modern quasi Monte Carlo methods are therefore for such models very promising. [German] Wir diskutieren Fortschritte bei Quasi-Monte Carlo Methoden zur numerischen Berechnung von Integralen bzw. Erwartungswerten und begruenden warum diese Methoden effizienter sind als die klassischen Monte Carlo Methoden. Quasi-Monte Carlo Methoden erweisen sich als besonders effizient, falls die Integranden eine geringe effektive Dimension besitzen. Deshalb diskutieren wir auch den Begriff effektive Dimension und weisen am Beispiel eines stochastischen Optimierungsmodell aus der Energiewirtschaft nach, dass solche Modelle eine niedrige effektive Dimension besitzen koennen. Moderne Quasi-Monte Carlo Methoden sind deshalb fuer solche Modelle sehr erfolgversprechend.

  19. MVP/GMVP Version 3. General purpose Monte Carlo codes for neutron and photon transport calculations based on continuous energy and multigroup methods (Translated document)

    International Nuclear Information System (INIS)

    Nagaya, Yasunobu; Okumura, Keisuke; Sakurai, Takeshi; Mori, Takamasa

    2017-03-01

    In order to realize fast and accurate Monte Carlo simulation of neutron and photon transport problems, two Monte Carlo codes MVP (continuous-energy method) and GMVP (multigroup method) have been developed at Japan Atomic Energy Agency. The codes have adopted a vectorized algorithm and have been developed for vector-type supercomputers. They also support parallel processing with a standard parallelization library MPI and thus a speed-up of Monte Carlo calculations can be achieved on general computing platforms. The first and second versions of the codes were released in 1994 and 2005, respectively. They have been extensively improved and new capabilities have been implemented. The major improvements and new capabilities are as follows: (1) perturbation calculation for effective multiplication factor, (2) exact resonant elastic scattering model, (3) calculation of reactor kinetics parameters, (4) photo-nuclear model, (5) simulation of delayed neutrons, (6) generation of group constants. This report describes the physical model, geometry description method used in the codes, new capabilities and input instructions. (author)

  20. MVP/GMVP version 3. General purpose Monte Carlo codes for neutron and photon transport calculations based on continuous energy and multigroup methods

    International Nuclear Information System (INIS)

    Nagaya, Yasunobu; Okumura, Keisuke; Sakurai, Takeshi; Mori, Takamasa

    2017-03-01

    In order to realize fast and accurate Monte Carlo simulation of neutron and photon transport problems, two Monte Carlo codes MVP (continuous-energy method) and GMVP (multigroup method) have been developed at Japan Atomic Energy Agency. The codes have adopted a vectorized algorithm and have been developed for vector-type supercomputers. They also support parallel processing with a standard parallelization library MPI and thus a speed-up of Monte Carlo calculations can be achieved on general computing platforms. The first and second versions of the codes were released in 1994 and 2005, respectively. They have been extensively improved and new capabilities have been implemented. The major improvements and new capabilities are as follows: (1) perturbation calculation for effective multiplication factor, (2) exact resonant elastic scattering model, (3) calculation of reactor kinetics parameters, (4) photo-nuclear model, (5) simulation of delayed neutrons, (6) generation of group constants. This report describes the physical model, geometry description method used in the codes, new capabilities and input instructions. (author)

  1. Spatial updating grand canonical Monte Carlo algorithms for fluid simulation: generalization to continuous potentials and parallel implementation.

    Science.gov (United States)

    O'Keeffe, C J; Ren, Ruichao; Orkoulas, G

    2007-11-21

    Spatial updating grand canonical Monte Carlo algorithms are generalizations of random and sequential updating algorithms for lattice systems to continuum fluid models. The elementary steps, insertions or removals, are constructed by generating points in space either at random (random updating) or in a prescribed order (sequential updating). These algorithms have previously been developed only for systems of impenetrable spheres for which no particle overlap occurs. In this work, spatial updating grand canonical algorithms are generalized to continuous, soft-core potentials to account for overlapping configurations. Results on two- and three-dimensional Lennard-Jones fluids indicate that spatial updating grand canonical algorithms, both random and sequential, converge faster than standard grand canonical algorithms. Spatial algorithms based on sequential updating not only exhibit the fastest convergence but also are ideal for parallel implementation due to the absence of strict detailed balance and the nature of the updating that minimizes interprocessor communication. Parallel simulation results for three-dimensional Lennard-Jones fluids show a substantial reduction of simulation time for systems of moderate and large size. The efficiency improvement by parallel processing through domain decomposition is always in addition to the efficiency improvement by sequential updating.

  2. Calculation of neutron importance function in fissionable assemblies using Monte Carlo method

    International Nuclear Information System (INIS)

    Feghhi, S. A. H.; Afarideh, H.; Shahriari, M.

    2007-01-01

    The purpose of the present work is to develop an efficient solution method to calculate neutron importance function in fissionable assemblies for all criticality conditions, using Monte Carlo Method. The neutron importance function has a well important role in perturbation theory and reactor dynamic calculations. Usually this function can be determined by calculating adjoint flux through out solving the Adjoint weighted transport equation with deterministic methods. However, in complex geometries these calculations are very difficult. In this article, considering the capabilities of MCNP code in solving problems with complex geometries and its closeness to physical concepts, a comprehensive method based on physical concept of neutron importance has been introduced for calculating neutron importance function in sub-critical, critical and supercritical conditions. For this means a computer program has been developed. The results of the method has been benchmarked with ANISN code calculations in 1 and 2 group modes for simple geometries and their correctness has been approved for all three criticality conditions. Ultimately, the efficiency of the method for complex geometries has been shown by calculation of neutron importance in MNSR research reactor

  3. Finite-Temperature Variational Monte Carlo Method for Strongly Correlated Electron Systems

    Science.gov (United States)

    Takai, Kensaku; Ido, Kota; Misawa, Takahiro; Yamaji, Youhei; Imada, Masatoshi

    2016-03-01

    A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in the imaginary-time formulation, starting from the infinite-temperature state that is well approximated by a small number of certain random initial states. Lower temperatures are progressively reached by the imaginary-time evolution. The algorithm follows the framework of the quantum transfer matrix and finite-temperature Lanczos methods, but we extend them to treat much larger system sizes without the negative sign problem by optimizing the truncated Hilbert space on the basis of the time-dependent variational principle (TDVP). This optimization algorithm is equivalent to the stochastic reconfiguration (SR) method that has been frequently used for the ground state to optimally truncate the Hilbert space. The obtained finite-temperature states allow an interpretation based on the thermal pure quantum (TPQ) state instead of the conventional canonical-ensemble average. Our method is tested for the one- and two-dimensional Hubbard models and its accuracy and efficiency are demonstrated.

  4. Monte Carlo method for critical systems in infinite volume: The planar Ising model.

    Science.gov (United States)

    Herdeiro, Victor; Doyon, Benjamin

    2016-10-01

    In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three-, and four-point of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.

  5. Neutrino emission spectra of collapsing degenerate stellar cores - Calculations by the Monte Carlo method

    International Nuclear Information System (INIS)

    Levitan, Iu.L.; Sobol, I.M.; Khlopov, M.Iu.; Chechetkin, V.M.

    1982-01-01

    The variation of the hard part of the neutrino emission spectra of collapsing degenerate stellar cores with matter having a small optical depth to neutrinos is analyzed. The interaction of neutrinos with the degenerate matter is determined by processes of neutrino scattering on nuclei (without a change in neutrino energy) and neutrino scattering on degenerate electrons, in which the neutrino energy can only decrease. The neutrino emission spectrum of a collapsing stellar core in the initial stage of the onset of opacity is calculated by the Monte Carlo method: using a central density of 10 trillion g/cu cm and, in the stage of deep collapse, for a central density of 60 trillion g/cu cm. In the latter case the calculation of the spectrum without allowance for effects of neutrino degeneration in the central part of the collapsing stellar core corresponds to the maximum possible suppression of the hard part of the neutrino emission spectrum

  6. The study of thin film growth by using Monte Carlo method

    International Nuclear Information System (INIS)

    Tandogan, M.; Aktas, S.

    2010-01-01

    Thin film growth was studied by using Monte Carlo simulation method. Three basic models were used in this study. Model A, the gas particles used for the formation of film were under no external effects until they stick on the surface or to another particle which already stickled on the surface to form the film. Model B, gases were drifted towards the surface by an external agent. Model C, where the gas particles in the closed container were always distributed uniformly throughout the container while they are in gas state. The simulations revealed the fact that for an ideal thin film growth Model C gave the best result to prepare a thin film while a thicker but a better quality could be obtained by Model B.

  7. Absorbed dose measurements in mammography using Monte Carlo method and ZrO2+PTFE dosemeters

    International Nuclear Information System (INIS)

    Duran M, H. A.; Hernandez O, M.; Salas L, M. A.; Hernandez D, V. M.; Vega C, H. R.; Pinedo S, A.; Ventura M, J.; Chacon, F.; Rivera M, T.

    2009-10-01

    Mammography test is a central tool for breast cancer diagnostic. In addition, programs are conducted periodically to detect the asymptomatic women in certain age groups; these programs have shown a reduction on breast cancer mortality. Early detection of breast cancer is achieved through a mammography, which contrasts the glandular and adipose tissue with a probable calcification. The parameters used for mammography are based on the thickness and density of the breast, their values depend on the voltage, current, focal spot and anode-filter combination. To achieve an image clear and a minimum dose must be chosen appropriate irradiation conditions. Risk associated with mammography should not be ignored. This study was performed in the General Hospital No. 1 IMSS in Zacatecas. Was used a glucose phantom and measured air Kerma at the entrance of the breast that was calculated using Monte Carlo methods and ZrO 2 +PTFE thermoluminescent dosemeters, this calculation was completed with calculating the absorbed dose. (author)

  8. Generation of organic scintillators response function for fast neutrons using the Monte Carlo method

    International Nuclear Information System (INIS)

    Mazzaro, A.C.

    1979-01-01

    A computer program (DALP) in Fortran-4-G language, has been developed using the Monte Carlo method to simulate the experimental techniques leading to the distribution of pulse heights due to monoenergetic neutrons reaching an organic scintillator. The calculation of the pulse height distribution has been done for two different systems: 1) Monoenergetic neutrons from a punctual source reaching the flat face of a cylindrical organic scintillator; 2) Environmental monoenergetic neutrons randomly reaching either the flat or curved face of the cylindrical organic scintillator. The computer program has been developed in order to be applied to the NE-213 liquid organic scintillator, but can be easily adapted to any other kind of organic scintillator. With this program one can determine the pulse height distribution for neutron energies ranging from 15 KeV to 10 MeV. (Author) [pt

  9. Pairing in Cold Atoms and other Applications for Quantum Monte Carlo methods

    International Nuclear Information System (INIS)

    Bajdich, Michal; Kolorenc, Jindrich; Mitas, Lubos; Reynolds, P.J.

    2010-01-01

    We discuss the importance of the fermion nodes for the quantum Monte Carlo (QMC) methods and find two cases of the exact nodes. We describe the structure of the generalized pairing wave functions in Pfaffian antisymmetric form and demonstrate their equivalency with certain class of configuration interaction wave functions. We present the QMC calculations of a model fermion system at unitary limit. We find the system to have the energy of E = 0.425Efree and the condensate fraction of = 0.48. Further we also perform the QMC calculations of the potential energy surface and the electric dipole moment along that surface of the LiSr molecule. We estimate the vibrationally averaged dipole moment to be D =0 = 0.4(2).

  10. Radiation shielding design for DECY-13 cyclotron using Monte Carlo method

    International Nuclear Information System (INIS)

    Rasito T; Bunawas; Taufik; Sunardi; Hari Suryanto

    2016-01-01

    DECY-13 is a 13 MeV proton cyclotron with target H_2"1"8O. The bombarding of 13 MeV protons on target H_2"1"8O produce large amounts of neutrons and gamma radiation. It needs the efficient radiation shielding to reduce the level of neutrons and gamma rays to ensure safety for workers and public. Modeling and calculations have been carried out using Monte Carlo method with MCNPX code to optimize the thickness for the radiation shielding. The calculations were done for radiation shielding of rectangular space room type with the size of 5.5 m x 5 m x 3 m and thickness of 170 cm made from lightweight concrete types of portland. It was shown that with this shielding the dose rate outside the wall was reduced to 1 μSv/h. (author)

  11. A spectral analysis of the domain decomposed Monte Carlo method for linear systems

    Energy Technology Data Exchange (ETDEWEB)

    Slattery, S. R.; Wilson, P. P. H. [Engineering Physics Department, University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Evans, T. M. [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 (United States)

    2013-07-01

    The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)

  12. A spectral analysis of the domain decomposed Monte Carlo method for linear systems

    International Nuclear Information System (INIS)

    Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.

    2013-01-01

    The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)

  13. Use of Monte Carlo method in low-energy gamma radiation applications

    International Nuclear Information System (INIS)

    Sulc, J.

    1982-01-01

    Modelling based on the Monte Carlo method is described in detail of the interaction of low-energy gamma radiation resulting in characteristic radiation of the K series of a pure element. The modelled system corresponds to the usual configuration of the measuring part of a radionuclide X-ray fluorescence analyzer. The accuracy of determination of the mean probability of impingement of characteristic radiation on the detector increases with the number of events. The number of events was selected with regard to the required accuracy, the demand on computer time and the accuracy of input parameters. The results of a comparison of computation and experiment are yet to be published. (M.D.)

  14. Efficiency determination of whole-body counter by Monte Carlo method, using a microcomputer

    International Nuclear Information System (INIS)

    Fernandes Neto, Jose Maria

    1986-01-01

    The purpose of this investigation was the development of an analytical microcomputer model to evaluate a whole body counter efficiency. The model is based on a modified Sryder's model. A stretcher type geometry along with the Monte Carlo method and a Synclair type microcomputer were used. Experimental measurements were performed using two phantoms, one as an adult and the other as a 5 year old child. The phantoms were made in acrylic and and 99m Tc, 131 I and 42 K were the radioisotopes utilized. Results showed a close relationship between experimental and predicted data for energies ranging from 250 keV to 2 MeV, but some discrepancies were found for lower energies. (author)

  15. 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.

  16. A Monte-Carlo method for ex-core neutron response

    International Nuclear Information System (INIS)

    Gamino, R.G.; Ward, J.T.; Hughes, J.C.

    1997-10-01

    A Monte Carlo neutron transport kernel capability primarily for ex-core neutron response is described. The capability consists of the generation of a set of response kernels, which represent the neutron transport from the core to a specific ex-core volume. This is accomplished by tagging individual neutron histories from their initial source sites and tracking them throughout the problem geometry, tallying those that interact in the geometric regions of interest. These transport kernels can subsequently be combined with any number of core power distributions to determine detector response for a variety of reactor Thus, the transport kernels are analogous to an integrated adjoint response. Examples of pressure vessel response and ex-core neutron detector response are provided to illustrate the method

  17. Calibration of lung counter using a CT model of Torso phantom and Monte Carlo method

    International Nuclear Information System (INIS)

    Zhang Binquan; Ma Jizeng; Yang Duanjie; Liu Liye; Cheng Jianping

    2006-01-01

    Tomography image of a Torso phantom was obtained from CT-Scan. The Torso phantom represents the trunk of an adult man that is 170 cm high and weight of 65 kg. After these images were segmented, cropped, and resized, a 3-dimension voxel phantom was created. The voxel phantom includes more than 2 million voxels, which size was 2.73 mm x 2.73 mm x 3 mm. This model could be used for the calibration of lung counter with Monte Carlo method. On the assumption that radioactive material was homogeneously distributed throughout the lung, counting efficiencies of a HPGe detector in different positions were calculated as Adipose Mass fraction (AMF) was different in the soft tissue in chest. The results showed that counting efficiencies of the lung counter changed up to 67% for 17.5 keV γ ray and 20% for 25 keV γ ray when AMF changed from 0 to 40%. (authors)

  18. Application of variance reduction techniques of Monte-Carlo method to deep penetration shielding problems

    International Nuclear Information System (INIS)

    Rawat, K.K.; Subbaiah, K.V.

    1996-01-01

    General purpose Monte Carlo code MCNP is being widely employed for solving deep penetration problems by applying variance reduction techniques. These techniques depend on the nature and type of the problem being solved. Application of geometry splitting and implicit capture method are examined to study the deep penetration problems of neutron, gamma and coupled neutron-gamma in thick shielding materials. The typical problems chosen are: i) point isotropic monoenergetic gamma ray source of 1 MeV energy in nearly infinite water medium, ii) 252 Cf spontaneous source at the centre of 140 cm thick water and concrete and iii) 14 MeV fast neutrons incident on the axis of 100 cm thick concrete disk. (author). 7 refs., 5 figs

  19. Application of Gumbel I and Monte Carlo methods to assess seismic hazard in and around Pakistan

    Science.gov (United States)

    Rehman, Khaista; Burton, Paul W.; Weatherill, Graeme A.

    2018-05-01

    A proper assessment of seismic hazard is of considerable importance in order to achieve suitable building construction criteria. This paper presents probabilistic seismic hazard assessment in and around Pakistan (23° N-39° N; 59° E-80° E) in terms of peak ground acceleration (PGA). Ground motion is calculated in terms of PGA for a return period of 475 years using a seismogenic-free zone method of Gumbel's first asymptotic distribution of extreme values and Monte Carlo simulation. Appropriate attenuation relations of universal and local types have been used in this study. The results show that for many parts of Pakistan, the expected seismic hazard is relatively comparable with the level specified in the existing PGA maps.

  20. Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

    KAUST Repository

    Nobile, Fabio

    2016-01-09

    In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

  1. Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

    KAUST Repository

    Nobile, Fabio; Haji Ali, Abdul Lateef; Tamellini, Lorenzo; Tempone, Raul

    2016-01-01

    In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

  2. Development of a software package for solid-angle calculations using the Monte Carlo method

    International Nuclear Information System (INIS)

    Zhang, Jie; Chen, Xiulian; Zhang, Changsheng; Li, Gang; Xu, Jiayun; Sun, Guangai

    2014-01-01

    Solid-angle calculations play an important role in the absolute calibration of radioactivity measurement systems and in the determination of the activity of radioactive sources, which are often complicated. In the present paper, a software package is developed to provide a convenient tool for solid-angle calculations in nuclear physics. The proposed software calculates solid angles using the Monte Carlo method, in which a new type of variance reduction technique was integrated. The package, developed under the environment of Microsoft Foundation Classes (MFC) in Microsoft Visual C ++ , has a graphical user interface, in which, the visualization function is integrated in conjunction with OpenGL. One advantage of the proposed software package is that it can calculate the solid angle subtended by a detector with different geometric shapes (e.g., cylinder, square prism, regular triangular prism or regular hexagonal prism) to a point, circular or cylindrical source without any difficulty. The results obtained from the proposed software package were compared with those obtained from previous studies and calculated using Geant4. It shows that the proposed software package can produce accurate solid-angle values with a greater computation speed than Geant4. -- Highlights: • This software package (SAC) can give accurate solid-angle values. • SAC calculate solid angles using the Monte Carlo method and it has higher computation speed than Geant4. • A simple but effective variance reduction technique which was put forward by the authors has been applied in SAC. • A visualization function and a graphical user interface are also integrated in SAC

  3. Internet security information system implement method

    International Nuclear Information System (INIS)

    Liu Baoxu; Mei Jie; Xu Rongsheng; An Dehai; Yu Mingjian; Chen Xiangyang; Zheng Peng

    1999-01-01

    On the basis of analysis of the key elements that will affect the Internet Security Information System, the author takes UNIX Operating System as an example, and provides the important stages that must be considered when implementing the Internet Security Information System. An implemental model of the Internet Security Information System is given

  4. Calculation of dose distribution for 252Cf fission neutron source in tissue equivalent phantoms using Monte Carlo method

    International Nuclear Information System (INIS)

    Ji Gang; Guo Yong; Luo Yisheng; Zhang Wenzhong

    2001-01-01

    Objective: To provide useful parameters for neutron radiotherapy, the author presents results of a Monte Carlo simulation study investigating the dosimetric characteristics of linear 252 Cf fission neutron sources. Methods: A 252 Cf fission source and tissue equivalent phantom were modeled. The dose of neutron and gamma radiations were calculated using Monte Carlo Code. Results: The dose of neutron and gamma at several positions for 252 Cf in the phantom made of equivalent materials to water, blood, muscle, skin, bone and lung were calculated. Conclusion: The results by Monte Carlo methods were compared with the data by measurement and references. According to the calculation, the method using water phantom to simulate local tissues such as muscle, blood and skin is reasonable for the calculation and measurements of dose distribution for 252 Cf

  5. A deterministic alternative to the full configuration interaction quantum Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Tubman, Norm M.; Lee, Joonho; Takeshita, Tyler Y.; Head-Gordon, Martin; Whaley, K. Birgitta [University of California, Berkeley, Berkeley, California 94720 (United States)

    2016-07-28

    Development of exponentially scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, is a useful algorithm that allows exact diagonalization through stochastically sampling determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, along with a stochastic projected wave function, to find the important parts of Hilbert space. However, the stochastic representation of the wave function is not required to search Hilbert space efficiently, and here we describe a highly efficient deterministic method that can achieve chemical accuracy for a wide range of systems, including the difficult Cr{sub 2} molecule. We demonstrate for systems like Cr{sub 2} that such calculations can be performed in just a few cpu hours which makes it one of the most efficient and accurate methods that can attain chemical accuracy for strongly correlated systems. In addition our method also allows efficient calculation of excited state energies, which we illustrate with benchmark results for the excited states of C{sub 2}.

  6. Applications of Monte Carlo method to nonlinear regression of rheological data

    Science.gov (United States)

    Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

    2018-02-01

    In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

  7. Calculation of neutron importance function in fissionable assemblies using Monte Carlo method

    International Nuclear Information System (INIS)

    Feghhi, S.A.H.; Shahriari, M.; Afarideh, H.

    2007-01-01

    The purpose of the present work is to develop an efficient solution method for the calculation of neutron importance function in fissionable assemblies for all criticality conditions, based on Monte Carlo calculations. The neutron importance function has an important role in perturbation theory and reactor dynamic calculations. Usually this function can be determined by calculating the adjoint flux while solving the adjoint weighted transport equation based on deterministic methods. However, in complex geometries these calculations are very complicated. In this article, considering the capabilities of MCNP code in solving problems with complex geometries and its closeness to physical concepts, a comprehensive method based on the physical concept of neutron importance has been introduced for calculating the neutron importance function in sub-critical, critical and super-critical conditions. For this propose a computer program has been developed. The results of the method have been benchmarked with ANISN code calculations in 1 and 2 group modes for simple geometries. The correctness of these results has been confirmed for all three criticality conditions. Finally, the efficiency of the method for complex geometries has been shown by the calculation of neutron importance in Miniature Neutron Source Reactor (MNSR) research reactor

  8. Continuous-energy adjoint flux and perturbation calculation using the iterated fission probability method in Monte-Carlo code TRIPOLI-4 and underlying applications

    International Nuclear Information System (INIS)

    Truchet, G.; Leconte, P.; Peneliau, Y.; Santamarina, A.

    2013-01-01

    The first goal of this paper is to present an exact method able to precisely evaluate very small reactivity effects with a Monte Carlo code (<10 pcm). it has been decided to implement the exact perturbation theory in TRIPOLI-4 and, consequently, to calculate a continuous-energy adjoint flux. The Iterated Fission Probability (IFP) method was chosen because it has shown great results in some other Monte Carlo codes. The IFP method uses a forward calculation to compute the adjoint flux, and consequently, it does not rely on complex code modifications but on the physical definition of the adjoint flux as a phase-space neutron importance. In the first part of this paper, the IFP method implemented in TRIPOLI-4 is described. To illustrate the efficiency of the method, several adjoint fluxes are calculated and compared with their equivalent obtained by the deterministic code APOLLO-2. The new implementation can calculate angular adjoint flux. In the second part, a procedure to carry out an exact perturbation calculation is described. A single cell benchmark has been used to test the accuracy of the method, compared with the 'direct' estimation of the perturbation. Once again the method based on the IFP shows good agreement for a calculation time far more inferior to the 'direct' method. The main advantage of the method is that the relative accuracy of the reactivity variation does not depend on the magnitude of the variation itself, which allows us to calculate very small reactivity perturbations with high precision. It offers the possibility to split reactivity contributions on both isotopes and reactions. Other applications of this perturbation method are presented and tested like the calculation of exact kinetic parameters (βeff, Λeff) or sensitivity parameters

  9. Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

    Science.gov (United States)

    Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

    2015-06-01

    A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

  10. Studying stellar binary systems with the Laser Interferometer Space Antenna using delayed rejection Markov chain Monte Carlo methods

    International Nuclear Information System (INIS)

    Trias, Miquel; Vecchio, Alberto; Veitch, John

    2009-01-01

    Bayesian analysis of Laser Interferometer Space Antenna (LISA) data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that dramatically reduces the efficiency of the sampling techniques. Here we introduce a new fully Markovian algorithm, a delayed rejection Metropolis-Hastings Markov chain Monte Carlo method, to efficiently explore these kind of structures and we demonstrate its performance on selected LISA data sets containing a known number of stellar-mass binary signals embedded in Gaussian stationary noise.

  11. Criticality analysis of thermal reactors for two energy groups applying Monte Carlo and neutron Albedo method

    International Nuclear Information System (INIS)

    Terra, Andre Miguel Barge Pontes Torres

    2005-01-01

    The Albedo method applied to criticality calculations to nuclear reactors is characterized by following the neutron currents, allowing to make detailed analyses of the physics phenomena about interactions of the neutrons with the core-reflector set, by the determination of the probabilities of reflection, absorption, and transmission. Then, allowing to make detailed appreciations of the variation of the effective neutron multiplication factor, keff. In the present work, motivated for excellent results presented in dissertations applied to thermal reactors and shieldings, was described the methodology to Albedo method for the analysis criticality of thermal reactors by using two energy groups admitting variable core coefficients to each re-entrant current. By using the Monte Carlo KENO IV code was analyzed relation between the total fraction of neutrons absorbed in the core reactor and the fraction of neutrons that never have stayed into the reflector but were absorbed into the core. As parameters of comparison and analysis of the results obtained by the Albedo method were used one dimensional deterministic code ANISN (ANIsotropic SN transport code) and Diffusion method. The keff results determined by the Albedo method, to the type of analyzed reactor, showed excellent agreement. Thus were obtained relative errors of keff values smaller than 0,78% between the Albedo method and code ANISN. In relation to the Diffusion method were obtained errors smaller than 0,35%, showing the effectiveness of the Albedo method applied to criticality analysis. The easiness of application, simplicity and clarity of the Albedo method constitute a valuable instrument to neutronic calculations applied to nonmultiplying and multiplying media. (author)

  12. On the solution of a few problems of multiple scattering by Monte Carlo method

    International Nuclear Information System (INIS)

    Bluet, J.C.

    1966-02-01

    Three problems of multiple scattering arising from neutron cross sections experiments, are reported here. The common hypothesis are: - Elastic scattering is the only possible process - Angular distributions are isotropic - Losses of particle energy are negligible in successive collisions. In the three cases practical results, corresponding to actual experiments are given. Moreover the results are shown in more general way, using dimensionless variable such as the ratio of geometrical dimensions to neutron mean free path. The FORTRAN codes are given together with to the corresponding flow charts, and lexicons of symbols. First problem: Measurement of sodium capture cross-section. A sodium sample of given geometry is submitted to a neutron flux. Induced activity is then measured by means of a sodium iodide cristal. The distribution of active nuclei in the sample, and the counter efficiency are calculated by Monte-Carlo method taking multiple scattering into account. Second problem: absolute measurement of a neutron flux using a glass scintillator. The scintillator is a use of lithium 6 loaded glass, submitted to neutron flux perpendicular to its plane faces. If the glass thickness is not negligible compared with scattering mean free path λ, the mean path e' of neutrons in the glass is different from the thickness. Monte-Carlo calculation are made to compute this path and a relative correction to efficiency equal to (e' - e)/e. Third problem: study of a neutron collimator. A neutron detector is placed at the bottom of a cylinder surrounded with water. A neutron source is placed on the cylinder axis, in front of the water shield. The number of neutron tracks going directly and indirectly through the water from the source to the detector are counted. (author) [fr

  13. Study on quantification method based on Monte Carlo sampling for multiunit probabilistic safety assessment models

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Kye Min [KHNP Central Research Institute, Daejeon (Korea, Republic of); Han, Sang Hoon; Park, Jin Hee; Lim, Ho Gon; Yang, Joon Yang [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of)

    2017-06-15

    In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.

  14. Report on some methods of determining the state of convergence of Monte Carlo risk estimates

    International Nuclear Information System (INIS)

    Orford, J.L.; Hufton, D.; Johnson, K.

    1991-05-01

    The Department of the Environment is developing a methodology for assessing potential sites for the disposal of low and intermediate level radioactive wastes. Computer models are used to simulate the groundwater transport of radioactive materials from a disposal facility back to man. Monte Carlo methods are being employed to conduct a probabilistic risk assessment (pra) of potential sites. The models calculate time histories of annual radiation dose to the critical group population. The annual radiation dose to the critical group in turn specifies the annual individual risk. The distribution of dose is generally highly skewed and many simulation runs are required to predict the level of confidence in the risk estimate i.e. to determine whether the risk estimate is converged. This report describes some statistical methods for determining the state of convergence of the risk estimate. The methods described include the Shapiro-Wilk test, calculation of skewness and kurtosis and normal probability plots. A method for forecasting the number of samples needed before the risk estimate is converged is presented. Three case studies were conducted to examine the performance of some of these techniques. (author)

  15. Monte Carlo evaluation of scattering correction methods in 131I studies using pinhole collimator

    International Nuclear Information System (INIS)

    López Díaz, Adlin; San Pedro, Aley Palau; Martín Escuela, Juan Miguel; Rodríguez Pérez, Sunay; Díaz García, Angelina

    2017-01-01

    Scattering is quite important for image activity quantification. In order to study the scattering factors and the efficacy of 3 multiple window energy scatter correction methods during 131 I thyroid studies with a pinhole collimator (5 mm hole) a Monte Carlo simulation (MC) was developed. The GAMOS MC code was used to model the gamma camera and the thyroid source geometry. First, to validate the MC gamma camera pinhole-source model, sensibility in air and water of the simulated and measured thyroid phantom geometries were compared. Next, simulations to investigate scattering and the result of triple energy (TEW), Double energy (DW) and Reduced double (RDW) energy windows correction methods were performed for different thyroid sizes and depth thicknesses. The relative discrepancies to MC real event were evaluated. Results: The accuracy of the GAMOS MC model was verified and validated. The image’s scattering contribution was significant, between 27-40 %. The discrepancies between 3 multiple window energy correction method results were significant (between 9-86 %). The Reduce Double Window methods (15%) provide discrepancies of 9-16 %. Conclusions: For the simulated thyroid geometry with pinhole, the RDW (15 %) was the most effective. (author)

  16. Estimation of the Thermal Process in the Honeycomb Panel by a Monte Carlo Method

    Science.gov (United States)

    Gusev, S. A.; Nikolaev, V. N.

    2018-01-01

    A new Monte Carlo method for estimating the thermal state of the heat insulation containing honeycomb panels is proposed in the paper. The heat transfer in the honeycomb panel is described by a boundary value problem for a parabolic equation with discontinuous diffusion coefficient and boundary conditions of the third kind. To obtain an approximate solution, it is proposed to use the smoothing of the diffusion coefficient. After that, the obtained problem is solved on the basis of the probability representation. The probability representation is the expectation of the functional of the diffusion process corresponding to the boundary value problem. The process of solving the problem is reduced to numerical statistical modelling of a large number of trajectories of the diffusion process corresponding to the parabolic problem. It was used earlier the Euler method for this object, but that requires a large computational effort. In this paper the method is modified by using combination of the Euler and the random walk on moving spheres methods. The new approach allows us to significantly reduce the computation costs.

  17. Analysis of communication costs for domain decomposed Monte Carlo methods in nuclear reactor analysis

    International Nuclear Information System (INIS)

    Siegel, A.; Smith, K.; Fischer, P.; Mahadevan, V.

    2012-01-01

    A domain decomposed Monte Carlo communication kernel is used to carry out performance tests to establish the feasibility of using Monte Carlo techniques for practical Light Water Reactor (LWR) core analyses. The results of the prototype code are interpreted in the context of simplified performance models which elucidate key scaling regimes of the parallel algorithm.

  18. Hybrid Monte Carlo-Diffusion Method For Light Propagation in Tissue With a Low-Scattering Region

    Science.gov (United States)

    Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

    2003-06-01

    The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

  19. A study of Monte Carlo methods for weak approximations of stochastic particle systems in the mean-field?

    KAUST Repository

    Haji Ali, Abdul Lateef

    2016-01-01

    I discuss using single level and multilevel Monte Carlo methods to compute quantities of interests of a stochastic particle system in the mean-field. In this context, the stochastic particles follow a coupled system of Ito stochastic differential equations (SDEs). Moreover, this stochastic particle system converges to a stochastic mean-field limit as the number of particles tends to infinity. I start by recalling the results of applying different versions of Multilevel Monte Carlo (MLMC) for particle systems, both with respect to time steps and the number of particles and using a partitioning estimator. Next, I expand on these results by proposing the use of our recent Multi-index Monte Carlo method to obtain improved convergence rates.

  20. A study of Monte Carlo methods for weak approximations of stochastic particle systems in the mean-field?

    KAUST Repository

    Haji Ali, Abdul Lateef

    2016-01-08

    I discuss using single level and multilevel Monte Carlo methods to compute quantities of interests of a stochastic particle system in the mean-field. In this context, the stochastic particles follow a coupled system of Ito stochastic differential equations (SDEs). Moreover, this stochastic particle system converges to a stochastic mean-field limit as the number of particles tends to infinity. I start by recalling the results of applying different versions of Multilevel Monte Carlo (MLMC) for particle systems, both with respect to time steps and the number of particles and using a partitioning estimator. Next, I expand on these results by proposing the use of our recent Multi-index Monte Carlo method to obtain improved convergence rates.

  1. Spiral computed tomography phase-space source model in the BEAMnrc/EGSnrc Monte Carlo system: implementation and validation

    International Nuclear Information System (INIS)

    Kim, Sangroh; Yoshizumi, Terry T; Yin Fangfang; Chetty, Indrin J

    2013-01-01

    Currently, the BEAMnrc/EGSnrc Monte Carlo (MC) system does not provide a spiral CT source model for the simulation of spiral CT scanning. We developed and validated a spiral CT phase-space source model in the BEAMnrc/EGSnrc system. The spiral phase-space source model was implemented in the DOSXYZnrc user code of the BEAMnrc/EGSnrc system by analyzing the geometry of spiral CT scan—scan range, initial angle, rotational direction, pitch, slice thickness, etc. Table movement was simulated by changing the coordinates of the isocenter as a function of beam angles. Some parameters such as pitch, slice thickness and translation per rotation were also incorporated into the model to make the new phase-space source model, designed specifically for spiral CT scan simulations. The source model was hard-coded by modifying the ‘ISource = 8: Phase-Space Source Incident from Multiple Directions’ in the srcxyznrc.mortran and dosxyznrc.mortran files in the DOSXYZnrc user code. In order to verify the implementation, spiral CT scans were simulated in a CT dose index phantom using the validated x-ray tube model of a commercial CT simulator for both the original multi-direction source (ISOURCE = 8) and the new phase-space source model in the DOSXYZnrc system. Then the acquired 2D and 3D dose distributions were analyzed with respect to the input parameters for various pitch values. In addition, surface-dose profiles were also measured for a patient CT scan protocol using radiochromic film and were compared with the MC simulations. The new phase-space source model was found to simulate the spiral CT scanning in a single simulation run accurately. It also produced the equivalent dose distribution of the ISOURCE = 8 model for the same CT scan parameters. The MC-simulated surface profiles were well matched to the film measurement overall within 10%. The new spiral CT phase-space source model was implemented in the BEAMnrc/EGSnrc system. This work will be beneficial in estimating the

  2. Spiral computed tomography phase-space source model in the BEAMnrc/EGSnrc Monte Carlo system: implementation and validation.

    Science.gov (United States)

    Kim, Sangroh; Yoshizumi, Terry T; Yin, Fang-Fang; Chetty, Indrin J

    2013-04-21

    Currently, the BEAMnrc/EGSnrc Monte Carlo (MC) system does not provide a spiral CT source model for the simulation of spiral CT scanning. We developed and validated a spiral CT phase-space source model in the BEAMnrc/EGSnrc system. The spiral phase-space source model was implemented in the DOSXYZnrc user code of the BEAMnrc/EGSnrc system by analyzing the geometry of spiral CT scan-scan range, initial angle, rotational direction, pitch, slice thickness, etc. Table movement was simulated by changing the coordinates of the isocenter as a function of beam angles. Some parameters such as pitch, slice thickness and translation per rotation were also incorporated into the model to make the new phase-space source model, designed specifically for spiral CT scan simulations. The source model was hard-coded by modifying the 'ISource = 8: Phase-Space Source Incident from Multiple Directions' in the srcxyznrc.mortran and dosxyznrc.mortran files in the DOSXYZnrc user code. In order to verify the implementation, spiral CT scans were simulated in a CT dose index phantom using the validated x-ray tube model of a commercial CT simulator for both the original multi-direction source (ISOURCE = 8) and the new phase-space source model in the DOSXYZnrc system. Then the acquired 2D and 3D dose distributions were analyzed with respect to the input parameters for various pitch values. In addition, surface-dose profiles were also measured for a patient CT scan protocol using radiochromic film and were compared with the MC simulations. The new phase-space source model was found to simulate the spiral CT scanning in a single simulation run accurately. It also produced the equivalent dose distribution of the ISOURCE = 8 model for the same CT scan parameters. The MC-simulated surface profiles were well matched to the film measurement overall within 10%. The new spiral CT phase-space source model was implemented in the BEAMnrc/EGSnrc system. This work will be beneficial in estimating the spiral

  3. Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

    Science.gov (United States)

    Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

    2011-12-01

    Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion

  4. Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks

    KAUST Repository

    Ben Hammouda, Chiheb

    2015-05-12

    In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for

  5. The EURADOS-KIT training course on Monte Carlo methods for the calibration of body counters

    International Nuclear Information System (INIS)

    Breustedt, B.; Broggio, D.; Gomez-Ros, J.M.; Lopez, M.A.; Leone, D.; Poelz, S.; Marzocchi, O.; Shutt, A.

    2016-01-01

    Monte Carlo (MC) methods are numerical simulation techniques that can be used to extend the scope of calibrations performed in in vivo monitoring laboratories. These methods allow calibrations to be carried out for a much wider range of body shapes and sizes than would be feasible using physical phantoms. Unfortunately, nowadays, this powerful technique is still used mainly in research institutions only. In 2013, EURADOS and the in vivo monitoring laboratory of Karlsruhe Institute of Technology (KIT) organized a 3-d training course to disseminate knowledge on the application of MC methods for in vivo monitoring. It was intended as a hands-on course centered around an exercise which guided the participants step by step through the calibration process using a simplified version of KIT's equipment. Only introductory lectures on in vivo monitoring and voxel models were given. The course was based on MC codes of the MCNP family, widespread in the community. The strong involvement of the participants and the working atmosphere in the classroom as well as the formal evaluation of the course showed that the approach chosen was appropriate. Participants liked the hands-on approach and the extensive course materials on the exercise. (authors)

  6. 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

  7. Comparison of ISO-GUM and Monte Carlo Method for Evaluation of Measurement Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Young-Cheol; Her, Jae-Young; Lee, Seung-Jun; Lee, Kang-Jin [Korea Gas Corporation, Daegu (Korea, Republic of)

    2014-07-15

    To supplement the ISO-GUM method for the evaluation of measurement uncertainty, a simulation program using the Monte Carlo method (MCM) was developed, and the MCM and GUM methods were compared. The results are as follows: (1) Even under a non-normal probability distribution of the measurement, MCM provides an accurate coverage interval; (2) Even if a probability distribution that emerged from combining a few non-normal distributions looks as normal, there are cases in which the actual distribution is not normal and the non-normality can be determined by the probability distribution of the combined variance; and (3) If type-A standard uncertainties are involved in the evaluation of measurement uncertainty, GUM generally offers an under-valued coverage interval. However, this problem can be solved by the Bayesian evaluation of type-A standard uncertainty. In this case, the effective degree of freedom for the combined variance is not required in the evaluation of expanded uncertainty, and the appropriate coverage factor for 95% level of confidence was determined to be 1.96.

  8. Mass change distribution inverted from space-borne gravimetric data using a Monte Carlo method

    Science.gov (United States)

    Zhou, X.; Sun, X.; Wu, Y.; Sun, W.

    2017-12-01

    Mass estimate plays a key role in using temporally satellite gravimetric data to quantify the terrestrial water storage change. GRACE (Gravity Recovery and Climate Experiment) only observes the low degree gravity field changes, which can be used to estimate the total surface density or equivalent water height (EWH) variation, with a limited spatial resolution of 300 km. There are several methods to estimate the mass variation in an arbitrary region, such as averaging kernel, forward modelling and mass concentration (mascon). Mascon method can isolate the local mass from the gravity change at a large scale through solving the observation equation (objective function) which represents the relationship between unknown masses and the measurements. To avoid the unreasonable local mass inverted from smoothed gravity change map, regularization has to be used in the inversion. We herein give a Markov chain Monte Carlo (MCMC) method to objectively determine the regularization parameter for the non-negative mass inversion problem. We first apply this approach to the mass inversion from synthetic data. Result show MCMC can effectively reproduce the local mass variation taking GRACE measurement error into consideration. We then use MCMC to estimate the ground water change rate of North China Plain from GRACE gravity change rate from 2003 to 2014 under a supposition of the continuous ground water loss in this region. Inversion result show that the ground water loss rate in North China Plain is 7.6±0.2Gt/yr during past 12 years which is coincident with that from previous researches.

  9. Bridging the gap between quantum Monte Carlo and F12-methods

    Science.gov (United States)

    Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André

    2012-06-01

    Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.

  10. Bridging the gap between quantum Monte Carlo and F12-methods

    International Nuclear Information System (INIS)

    Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André

    2012-01-01

    Graphical abstract: Tensor product approximation of pair-correlation functions: τ(x,y)≈∑ κ=1 κ u k (1) (x 1 ,y 1 )u k (2) (x 2 ,y 2 )u k (3) (x 3 ,y 3 ) Pair-correlation function τ(x,y)∣ ∣x·y∣=∣x∣∣y∣ of the He atom and corresponding tensor product approximation errors. Display Omitted - Abstract: Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.

  11. 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

  12. Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency Offset Estimation in Multicarrier Systems

    Directory of Open Access Journals (Sweden)

    Christelle Garnier

    2008-05-01

    Full Text Available We address the problem of phase noise (PHN and carrier frequency offset (CFO mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE and the intercarrier interference (ICI which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER and mean square error (MSE to illustrate the efficiency and the robustness of the proposed algorithm.

  13. Study of the applicability of Markov chain Monte Carlo methods to the statistical separation of electron sources via the impact parameter for ALICE

    Energy Technology Data Exchange (ETDEWEB)

    Wittner, Manuel [Physikalisches Institut, Universitaet Heidelberg, Heidelberg (Germany); Collaboration: ALICE-Collaboration

    2015-07-01

    One particularly interesting measurement detected by the ALICE set-up at the LHC are electrons from charm and beauty hadron decays. Heavy quarks originate from initial hard scattering processes and thus experience the whole history of a heavy ion collision. Therefore, they are valuable probes to study the mechanisms of energy loss and hadronization in the hot and dense state of matter, that is expected to be formed in a heavy-ion collision at LHC. One important task is the distinction of the different electron sources, for which a method was developed. Hereby, the impact parameter distribution of the measurement data is compared with impact parameter distributions for the individual sources, which are created through Monte Carlo simulations. Afterwards, a maximum likelihood fit is applied. However, creating a posterior distribution of the likelihood according to Bayes' theorem and sampling it with Markov Chain Monte Carlo algorithms provides several advantages, e.g. a mathematically correct estimation of the uncertainties or the usage of prior knowledge. Hence for the first time in this particular problem, a Markov Chain Monte Carlo algorithm, namely the Metropolis algorithm, was implemented and investigated for its applicability in heavy flavor physics. First studies indicate its great usefulness in this field of physics.

  14. Efficiency of rejection-free methods for dynamic Monte Carlo studies of off-lattice interacting particles

    KAUST Repository

    Guerra, Marta L.; Novotny, M. A.; Watanabe, Hiroshi; Ito, Nobuyasu

    2009-01-01

    We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.

  15. Efficiency of rejection-free methods for dynamic Monte Carlo studies of off-lattice interacting particles

    KAUST Repository

    Guerra, Marta L.

    2009-02-23

    We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.

  16. A task parallel implementation of fast multipole methods

    KAUST Repository

    Taura, Kenjiro; Nakashima, Jun; Yokota, Rio; Maruyama, Naoya

    2012-01-01

    This paper describes a task parallel implementation of ExaFMM, an open source implementation of fast multipole methods (FMM), using a lightweight task parallel library MassiveThreads. Although there have been many attempts on parallelizing FMM

  17. A discussion on validity of the diffusion theory by Monte Carlo method

    Science.gov (United States)

    Peng, Dong-qing; Li, Hui; Xie, Shusen

    2008-12-01

    Diffusion theory was widely used as a basis of the experiments and methods in determining the optical properties of biological tissues. A simple analytical solution could be obtained easily from the diffusion equation after a series of approximations. Thus, a misinterpret of analytical solution would be made: while the effective attenuation coefficient of several semi-infinite bio-tissues were the same, the distribution of light fluence in the tissues would be the same. In order to assess the validity of knowledge above, depth resolved internal fluence of several semi-infinite biological tissues which have the same effective attenuation coefficient were simulated with wide collimated beam in the paper by using Monte Carlo method in different condition. Also, the influence of bio-tissue refractive index on the distribution of light fluence was discussed in detail. Our results showed that, when the refractive index of several bio-tissues which had the same effective attenuation coefficient were the same, the depth resolved internal fluence would be the same; otherwise, the depth resolved internal fluence would be not the same. The change of refractive index of tissue would have affection on the light depth distribution in tissue. Therefore, the refractive index is an important optical property of tissue, and should be taken in account while using the diffusion approximation theory.

  18. Deterministic alternatives to the full configuration interaction quantum Monte Carlo method for strongly correlated systems

    Science.gov (United States)

    Tubman, Norm; Whaley, Birgitta

    The development of exponential scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, allows exact diagonalization through stochastically sampling of determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, together with a stochastic projected wave function, which are used to explore the important parts of Hilbert space. However, a stochastic representation of the wave function is not required to search Hilbert space efficiently and new deterministic approaches have recently been shown to efficiently find the important parts of determinant space. We shall discuss the technique of Adaptive Sampling Configuration Interaction (ASCI) and the related heat-bath Configuration Interaction approach for ground state and excited state simulations. We will present several applications for strongly correlated Hamiltonians. This work was supported through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences.

  19. Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods

    Directory of Open Access Journals (Sweden)

    Qian Liu

    2015-01-01

    Full Text Available Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.

  20. Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data

    International Nuclear Information System (INIS)

    Silva, A. N. C. da; Amaral, R. S.; Araujo Santos Jr, J.; Wilson Vieira, J.; Lima, F. R. de A.

    2015-01-01

    There are operational difficulties in obtaining samples for radioecological studies. Population data may no longer be available during the study and obtaining new samples may not be possible. These problems do the researcher sometimes work with a small number of data. Therefore, it is difficult to know whether the number of samples will be sufficient to estimate the desired parameter. Hence, it is critical do the analysis of sample sufficiency. It is not interesting uses the classical methods of statistic to analyze sample sufficiency in Radioecology, because naturally occurring radionuclides have a random distribution in soil, usually arise outliers and gaps with missing values. The present work was developed aiming to apply the Monte Carlo Bootstrap method in the analysis of sample sufficiency with quantitative estimation of a single variable such as specific activity of a natural radioisotope present in plants. The pseudo population was a small sample with 14 values of specific activity of 226 Ra in forage palm (Opuntia spp.). Using the R software was performed a computational procedure to calculate the number of the sample values. The re sampling process with replacement took the 14 values of original sample and produced 10,000 bootstrap samples for each round. Then was calculated the estimated average θ for samples with 2, 5, 8, 11 and 14 values randomly selected. The results showed that if the researcher work with only 11 sample values, the average parameter will be within a confidence interval with 90% probability . (Author)