WorldWideScience

Sample records for carlo method implemented

  1. 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)

  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 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

  3. 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.

  4. 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)

  5. 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

  6. 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

  7. 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.)

  8. 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

  9. 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.

  10. 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.

  11. 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)

  12. 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

  13. 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.

  14. 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)

  15. 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

  16. 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)

  17. 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)

  18. 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.

  19. 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

  20. 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.)

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. (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.

  11. 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.

  12. 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...

  13. 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

  14. 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)

  15. 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.

  16. 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.

  17. 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.

  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. 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.

  20. 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)

  1. 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

  2. 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.

  3. 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

  4. 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.

  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. 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)

  7. 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

  8. 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

  9. 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...

  10. 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.

  11. 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)

  12. 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

  13. 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.

  14. 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)

  15. 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

  16. 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

  17. 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.

  18. 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)

  19. 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.

  20. 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

  1. 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

  2. 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)

  3. 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...

  4. 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)

  5. Forest canopy BRDF simulation using Monte Carlo method

    NARCIS (Netherlands)

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

    2006-01-01

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

  6. 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

  7. 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

  8. 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)

  9. 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

  10. 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)

  11. 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.

  12. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, George B.

    1997-01-01

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials

  13. 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.

  14. 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.)

  15. 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

  16. 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.)

  17. 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.)

  18. 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.

  19. 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)

  20. 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

  1. 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)

  2. 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)

  3. 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.

  4. 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

  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. 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

  7. 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

  8. 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

  9. 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

  10. 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...

  11. 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)

  12. 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)

  13. 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.)

  14. 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)

  15. 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

  16. 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

  17. 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)

  18. 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)

  19. 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)

  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. 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)

  2. 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.

  3. 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.

  4. 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)

  5. 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.

  6. 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.

  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. 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.

  9. 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.

  10. 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.

  11. 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)

  12. 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

  13. 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.

  14. 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

  15. 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)

  16. 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)

  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. 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

  19. 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

  20. 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

  1. 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)

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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)

  7. 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...

  8. 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)

  9. 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.)

  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. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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)

  18. 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.

  19. 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

  20. 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.

  1. General purpose dynamic Monte Carlo with continuous energy for transient analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sjenitzer, B. L.; Hoogenboom, J. E. [Delft Univ. of Technology, Dept. of Radiation, Radionuclide and Reactors, Mekelweg 15, 2629JB Delft (Netherlands)

    2012-07-01

    For safety assessments transient analysis is an important tool. It can predict maximum temperatures during regular reactor operation or during an accident scenario. Despite the fact that this kind of analysis is very important, the state of the art still uses rather crude methods, like diffusion theory and point-kinetics. For reference calculations it is preferable to use the Monte Carlo method. In this paper the dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli4. Also, the method is extended for use with continuous energy. The first results of Dynamic Tripoli demonstrate that this kind of calculation is indeed accurate and the results are achieved in a reasonable amount of time. With the method implemented in Tripoli it is now possible to do an exact transient calculation in arbitrary geometry. (authors)

  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. 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.

  4. 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)

  5. 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.

  6. 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.

  7. Monte Carlo and Quasi-Monte Carlo Sampling

    CERN Document Server

    Lemieux, Christiane

    2009-01-01

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

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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)

  13. 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.

  14. Final Report: 06-LW-013, Nuclear Physics the Monte Carlo Way

    International Nuclear Information System (INIS)

    Ormand, W.E.

    2009-01-01

    This is document reports the progress and accomplishments achieved in 2006-2007 with LDRD funding under the proposal 06-LW-013, 'Nuclear Physics the Monte Carlo Way'. The project was a theoretical study to explore a novel approach to dealing with a persistent problem in Monte Carlo approaches to quantum many-body systems. The goal was to implement a solution to the notorious 'sign-problem', which if successful, would permit, for the first time, exact solutions to quantum many-body systems that cannot be addressed with other methods. In this document, we outline the progress and accomplishments achieved during FY2006-2007 with LDRD funding in the proposal 06-LW-013, 'Nuclear Physics the Monte Carlo Way'. This project was funded under the Lab Wide LDRD competition at Lawrence Livermore National Laboratory. The primary objective of this project was to test the feasibility of implementing a novel approach to solving the generic quantum many-body problem, which is one of the most important problems being addressed in theoretical physics today. Instead of traditional methods based matrix diagonalization, this proposal focused a Monte Carlo method. The principal difficulty with Monte Carlo methods, is the so-called 'sign problem'. The sign problem, which will discussed in some detail later, is endemic to Monte Carlo approaches to the quantum many-body problem, and is the principal reason that they have not been completely successful in the past. Here, we outline our research in the 'shifted-contour method' applied the Auxiliary Field Monte Carlo (AFMC) method

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-07-01

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

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

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.

    2000-01-01

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

  4. 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

  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(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.

  6. 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.

  7. 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)

  8. Importance iteration in MORSE Monte Carlo calculations

    International Nuclear Information System (INIS)

    Kloosterman, J.L.; Hoogenboom, J.E.

    1994-01-01

    An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation

  9. Importance iteration in MORSE Monte Carlo calculations

    International Nuclear Information System (INIS)

    Kloosterman, J.L.; Hoogenboom, J.E.

    1994-02-01

    An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)

  10. 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.

  11. 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)

  12. 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)

  13. 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)

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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)

  20. 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

  1. 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)

  2. 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.

  3. 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)

  4. 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)

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

    Science.gov (United States)

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

    2011-10-11

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

  7. 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

  8. 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

  9. 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.

  10. Perturbation based Monte Carlo criticality search in density, enrichment and concentration

    International Nuclear Information System (INIS)

    Li, Zeguang; Wang, Kan; Deng, Jingkang

    2015-01-01

    Highlights: • A new perturbation based Monte Carlo criticality search method is proposed. • The method could get accurate results with only one individual criticality run. • The method is used to solve density, enrichment and concentration search problems. • Results show the feasibility and good performances of this method. • The relationship between results’ accuracy and perturbation order is discussed. - Abstract: Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods

  11. 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....

  12. 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

  13. 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

  14. 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)

  15. 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)

  16. 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

  17. Parallel MCNP Monte Carlo transport calculations with MPI

    International Nuclear Information System (INIS)

    Wagner, J.C.; Haghighat, A.

    1996-01-01

    The steady increase in computational performance has made Monte Carlo calculations for large/complex systems possible. However, in order to make these calculations practical, order of magnitude increases in performance are necessary. The Monte Carlo method is inherently parallel (particles are simulated independently) and thus has the potential for near-linear speedup with respect to the number of processors. Further, the ever-increasing accessibility of parallel computers, such as workstation clusters, facilitates the practical use of parallel Monte Carlo. Recognizing the nature of the Monte Carlo method and the trends in available computing, the code developers at Los Alamos National Laboratory implemented the message-passing general-purpose Monte Carlo radiation transport code MCNP (version 4A). The PVM package was chosen by the MCNP code developers because it supports a variety of communication networks, several UNIX platforms, and heterogeneous computer systems. This PVM version of MCNP has been shown to produce speedups that approach the number of processors and thus, is a very useful tool for transport analysis. Due to software incompatibilities on the local IBM SP2, PVM has not been available, and thus it is not possible to take advantage of this useful tool. Hence, it became necessary to implement an alternative message-passing library package into MCNP. Because the message-passing interface (MPI) is supported on the local system, takes advantage of the high-speed communication switches in the SP2, and is considered to be the emerging standard, it was selected

  18. 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.

  19. Monte Carlo simulation of continuous-space crystal growth

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  20. 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)

  1. 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.

  2. 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)

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. 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)

  10. 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.)

  11. 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

  12. 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...

  13. Reflections on early Monte Carlo calculations

    International Nuclear Information System (INIS)

    Spanier, J.

    1992-01-01

    Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances

  14. 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

  15. 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...

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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

  2. Sampling from a polytope and hard-disk Monte Carlo

    International Nuclear Information System (INIS)

    Kapfer, Sebastian C; Krauth, Werner

    2013-01-01

    The hard-disk problem, the statics and the dynamics of equal two-dimensional hard spheres in a periodic box, has had a profound influence on statistical and computational physics. Markov-chain Monte Carlo and molecular dynamics were first discussed for this model. Here we reformulate hard-disk Monte Carlo algorithms in terms of another classic problem, namely the sampling from a polytope. Local Markov-chain Monte Carlo, as proposed by Metropolis et al. in 1953, appears as a sequence of random walks in high-dimensional polytopes, while the moves of the more powerful event-chain algorithm correspond to molecular dynamics evolution. We determine the convergence properties of Monte Carlo methods in a special invariant polytope associated with hard-disk configurations, and the implications for convergence of hard-disk sampling. Finally, we discuss parallelization strategies for event-chain Monte Carlo and present results for a multicore implementation

  3. Continuum variational and diffusion quantum Monte Carlo calculations

    International Nuclear Information System (INIS)

    Needs, R J; Towler, M D; Drummond, N D; Lopez RIos, P

    2010-01-01

    This topical review describes the methodology of continuum variational and diffusion quantum Monte Carlo calculations. These stochastic methods are based on many-body wavefunctions and are capable of achieving very high accuracy. The algorithms are intrinsically parallel and well suited to implementation on petascale computers, and the computational cost scales as a polynomial in the number of particles. A guide to the systems and topics which have been investigated using these methods is given. The bulk of the article is devoted to an overview of the basic quantum Monte Carlo methods, the forms and optimization of wavefunctions, performing calculations under periodic boundary conditions, using pseudopotentials, excited-state calculations, sources of calculational inaccuracy, and calculating energy differences and forces. (topical review)

  4. 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

  5. Current and future applications of Monte Carlo

    International Nuclear Information System (INIS)

    Zaidi, H.

    2003-01-01

    Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions (pdfs). As the number of individual events (called 'histories') is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic

  6. 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.

  7. 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

  8. 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.

  9. 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...

  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. 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

  12. 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

  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. Probability of initiation and extinction in the Mercury Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    McKinley, M. S.; Brantley, P. S. [Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94551 (United States)

    2013-07-01

    A Monte Carlo method for computing the probability of initiation has previously been implemented in Mercury. Recently, a new method based on the probability of extinction has been implemented as well. The methods have similarities from counting progeny to cycling in time, but they also have differences such as population control and statistical uncertainty reporting. The two methods agree very well for several test problems. Since each method has advantages and disadvantages, we currently recommend that both methods are used to compute the probability of criticality. (authors)

  15. 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

  16. How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

    Science.gov (United States)

    Lecca, Paola

    2018-01-01

    We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of

  17. Condensed history Monte Carlo methods for photon transport problems

    International Nuclear Information System (INIS)

    Bhan, Katherine; Spanier, Jerome

    2007-01-01

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

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

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2001-01-01

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

  19. 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

  20. 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

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

    Science.gov (United States)

    2017-12-07

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

  2. 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…

  3. 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)

  4. 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.

  5. 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

  6. Monte Carlo evaluation of derivative-based global sensitivity measures

    International Nuclear Information System (INIS)

    Kucherenko, S.; Rodriguez-Fernandez, M.; Pantelides, C.; Shah, N.

    2009-01-01

    A novel approach for evaluation of derivative-based global sensitivity measures (DGSM) is presented. It is compared with the Morris and the Sobol' sensitivity indices methods. It is shown that there is a link between DGSM and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is many orders of magnitude lower than that for estimation of the Sobol' sensitivity indices. It is also lower than that for the Morris method. Efficiencies of Monte Carlo (MC) and quasi-Monte Carlo (QMC) sampling methods for calculation of DGSM are compared. It is shown that the superiority of QMC over MC depends on the problem's effective dimension, which can also be estimated using DGSM.

  7. 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)

  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. 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)

  10. IMPLEMENTASI METODE MARKOV CHAIN MONTE CARLO DALAM PENENTUAN HARGA KONTRAK BERJANGKA KOMODITAS

    Directory of Open Access Journals (Sweden)

    PUTU AMANDA SETIAWANI

    2015-06-01

    Full Text Available The aim of the research is to implement Markov Chain Monte Carlo (MCMC simulation method to price the futures contract of cocoa commodities. The result shows that MCMC is more flexible than Standard Monte Carlo (SMC simulation method because MCMC method uses hit-and-run sampler algorithm to generate proposal movements that are subsequently accepted or rejected with a probability that depends on the distribution of the target that we want to be achieved. This research shows that MCMC method is suitable to be used to simulate the model of cocoa commodity price movement. The result of this research is a simulation of future contract prices for the next three months and future contract prices that must be paid at the time the contract expires. Pricing future contract by using MCMC method will produce the cheaper contract price if it compares to Standard Monte Carlo simulation.

  11. 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.)

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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)

  17. Atomistic Monte Carlo simulation of lipid membranes

    DEFF Research Database (Denmark)

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

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

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

    Science.gov (United States)

    Kim, Jeongnim; Baczewski, Andrew D.; Beaudet, Todd D.; Benali, Anouar; Chandler Bennett, M.; Berrill, Mark A.; Blunt, Nick S.; Josué Landinez Borda, Edgar; Casula, Michele; Ceperley, David M.; Chiesa, Simone; Clark, Bryan K.; Clay, Raymond C., III; Delaney, Kris T.; Dewing, Mark; Esler, Kenneth P.; Hao, Hongxia; Heinonen, Olle; Kent, Paul R. C.; Krogel, Jaron T.; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M. Graham; Luo, Ye; Malone, Fionn D.; Martin, Richard M.; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A.; Mitas, Lubos; Morales, Miguel A.; Neuscamman, Eric; Parker, William D.; Pineda Flores, Sergio D.; Romero, Nichols A.; Rubenstein, Brenda M.; Shea, Jacqueline A. R.; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F.; Townsend, Joshua P.; Tubman, Norm M.; Van Der Goetz, Brett; Vincent, Jordan E.; ChangMo Yang, D.; Yang, Yubo; Zhang, Shuai; Zhao, Luning

    2018-05-01

    QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater–Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

  3. 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.

  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. Monte Carlo applications to radiation shielding problems

    International Nuclear Information System (INIS)

    Subbaiah, K.V.

    2009-01-01

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

  6. 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.

  7. Monte Carlo evaluation of derivative-based global sensitivity measures

    Energy Technology Data Exchange (ETDEWEB)

    Kucherenko, S. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)], E-mail: s.kucherenko@ic.ac.uk; Rodriguez-Fernandez, M. [Process Engineering Group, Instituto de Investigaciones Marinas, Spanish Council for Scientific Research (C.S.I.C.), C/ Eduardo Cabello, 6, 36208 Vigo (Spain); Pantelides, C.; Shah, N. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)

    2009-07-15

    A novel approach for evaluation of derivative-based global sensitivity measures (DGSM) is presented. It is compared with the Morris and the Sobol' sensitivity indices methods. It is shown that there is a link between DGSM and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is many orders of magnitude lower than that for estimation of the Sobol' sensitivity indices. It is also lower than that for the Morris method. Efficiencies of Monte Carlo (MC) and quasi-Monte Carlo (QMC) sampling methods for calculation of DGSM are compared. It is shown that the superiority of QMC over MC depends on the problem's effective dimension, which can also be estimated using DGSM.

  8. 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.

  9. 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

  10. 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.

  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. Continuous-time quantum Monte Carlo impurity solvers

    Science.gov (United States)

    Gull, Emanuel; Werner, Philipp; Fuchs, Sebastian; Surer, Brigitte; Pruschke, Thomas; Troyer, Matthias

    2011-04-01

    Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states. Program summaryProgram title: dmft Catalogue identifier: AEIL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: ALPS LIBRARY LICENSE version 1.1 No. of lines in distributed program, including test data, etc.: 899 806 No. of bytes in distributed program, including test data, etc.: 32 153 916 Distribution format: tar.gz Programming language: C++ Operating system: The ALPS libraries have been tested on the following platforms and compilers: Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher) MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0) IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers Compaq Tru64 UNIX with Compq C++ Compiler (cxx) SGI IRIX with MIPSpro C++ Compiler (CC) HP-UX with HP C++ Compiler (aCC) Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher) RAM: 10 MB-1 GB Classification: 7.3 External routines: ALPS [1], BLAS/LAPACK, HDF5 Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as

  13. 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.

  14. Monte Carlo principles and applications

    Energy Technology Data Exchange (ETDEWEB)

    Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center

    1976-03-01

    The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.

  15. 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)

  16. 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

  17. Adaptive time-stepping Monte Carlo integration of Coulomb collisions

    Science.gov (United States)

    Särkimäki, K.; Hirvijoki, E.; Terävä, J.

    2018-01-01

    We report an accessible and robust tool for evaluating the effects of Coulomb collisions on a test particle in a plasma that obeys Maxwell-Jüttner statistics. The implementation is based on the Beliaev-Budker collision integral which allows both the test particle and the background plasma to be relativistic. The integration method supports adaptive time stepping, which is shown to greatly improve the computational efficiency. The Monte Carlo method is implemented for both the three-dimensional particle momentum space and the five-dimensional guiding center phase space. Detailed description is provided for both the physics and implementation of the operator. The focus is in adaptive integration of stochastic differential equations, which is an overlooked aspect among existing Monte Carlo implementations of Coulomb collision operators. We verify that our operator converges to known analytical results and demonstrate that careless implementation of the adaptive time step can lead to severely erroneous results. The operator is provided as a self-contained Fortran 95 module and can be included into existing orbit-following tools that trace either the full Larmor motion or the guiding center dynamics. The adaptive time-stepping algorithm is expected to be useful in situations where the collision frequencies vary greatly over the course of a simulation. Examples include the slowing-down of fusion products or other fast ions, and the Dreicer generation of runaway electrons as well as the generation of fast ions or electrons with ion or electron cyclotron resonance heating.

  18. 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.

  19. Handbook of Markov chain Monte Carlo

    CERN Document Server

    Brooks, Steve

    2011-01-01

    ""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.

  20. Monte Carlo simulation of Touschek effect

    Directory of Open Access Journals (Sweden)

    Aimin Xiao

    2010-07-01

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

  1. Mesh-based weight window approach for Monte Carlo simulation

    International Nuclear Information System (INIS)

    Liu, L.; Gardner, R.P.

    1997-01-01

    The Monte Carlo method has been increasingly used to solve particle transport problems. Statistical fluctuation from random sampling is the major limiting factor of its application. To obtain the desired precision, variance reduction techniques are indispensable for most practical problems. Among various variance reduction techniques, the weight window method proves to be one of the most general, powerful, and robust. The method is implemented in the current MCNP code. An importance map is estimated during a regular Monte Carlo run, and then the map is used in the subsequent run for splitting and Russian roulette games. The major drawback of this weight window method is lack of user-friendliness. It normally requires that users divide the large geometric cells into smaller ones by introducing additional surfaces to ensure an acceptable spatial resolution of the importance map. In this paper, we present a new weight window approach to overcome this drawback

  2. 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)

  3. 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.

  4. 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

  5. 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)

  6. 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)

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

    Directory of Open Access Journals (Sweden)

    Vincenza Di Stefano

    2009-11-01

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

  8. 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)

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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)

  14. Quantum Mechanical Single Molecule Partition Function from PathIntegral Monte Carlo Simulations

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-10-01

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

  15. 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

  16. 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

  17. 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

  18. Transforming high-dimensional potential energy surfaces into sum-of-products form using Monte Carlo methods

    Science.gov (United States)

    Schröder, Markus; Meyer, Hans-Dieter

    2017-08-01

    We propose a Monte Carlo method, "Monte Carlo Potfit," for transforming high-dimensional potential energy surfaces evaluated on discrete grid points into a sum-of-products form, more precisely into a Tucker form. To this end we use a variational ansatz in which we replace numerically exact integrals with Monte Carlo integrals. This largely reduces the numerical cost by avoiding the evaluation of the potential on all grid points and allows a treatment of surfaces up to 15-18 degrees of freedom. We furthermore show that the error made with this ansatz can be controlled and vanishes in certain limits. We present calculations on the potential of HFCO to demonstrate the features of the algorithm. To demonstrate the power of the method, we transformed a 15D potential of the protonated water dimer (Zundel cation) in a sum-of-products form and calculated the ground and lowest 26 vibrationally excited states of the Zundel cation with the multi-configuration time-dependent Hartree method.

  19. 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)

  20. 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)

  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.

    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)

  2. A positive-weight next-to-leading-order Monte Carlo for Z pair hadroproduction

    International Nuclear Information System (INIS)

    Nason, Paolo; Ridolfi, Giovanni

    2006-01-01

    We present a first application of a previously published method for the computation of QCD processes that is accurate at next-to-leading order, and that can be interfaced consistently to standard shower Monte Carlo programs. We have considered Z pair production in hadron-hadron collisions, a process whose complexity is sufficient to test the general applicability of the method. We have interfaced our result to the HERWIG and PYTHIA shower Monte Carlo programs. Previous work on next-to-leading order corrections in a shower Monte Carlo (the MC-NLO program) may involve the generation of events with negative weights, that are avoided with the present method. We have compared our results with those obtained with MC-NLO, and found remarkable consistency. Our method can also be used as a standalone, alternative implementation of QCD corrections, with the advantage of positivity, improved convergence, and next-to-leading logarithmic accuracy in the region of small transverse momentum of the radiated parton

  3. GPU implementation of Bayesian neural network construction for data-intensive applications

    International Nuclear Information System (INIS)

    Perry, Michelle; Meyer-Baese, Anke; Prosper, Harrison B

    2014-01-01

    We describe a graphical processing unit (GPU) implementation of the Hybrid Markov Chain Monte Carlo (HMC) method for training Bayesian Neural Networks (BNN). Our implementation uses NVIDIA's parallel computing architecture, CUDA. We briefly review BNNs and the HMC method and we describe our implementations and give preliminary results.

  4. 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.

  5. 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)

  6. 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.)

  7. SU-E-J-60: Efficient Monte Carlo Dose Calculation On CPU-GPU Heterogeneous Systems

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, K; Chen, D. Z; Hu, X. S [University of Notre Dame, Notre Dame, IN (United States); Zhou, B [Altera Corp., San Jose, CA (United States)

    2014-06-01

    Purpose: It is well-known that the performance of GPU-based Monte Carlo dose calculation implementations is bounded by memory bandwidth. One major cause of this bottleneck is the random memory writing patterns in dose deposition, which leads to several memory efficiency issues on GPU such as un-coalesced writing and atomic operations. We propose a new method to alleviate such issues on CPU-GPU heterogeneous systems, which achieves overall performance improvement for Monte Carlo dose calculation. Methods: Dose deposition is to accumulate dose into the voxels of a dose volume along the trajectories of radiation rays. Our idea is to partition this procedure into the following three steps, which are fine-tuned for CPU or GPU: (1) each GPU thread writes dose results with location information to a buffer on GPU memory, which achieves fully-coalesced and atomic-free memory transactions; (2) the dose results in the buffer are transferred to CPU memory; (3) the dose volume is constructed from the dose buffer on CPU. We organize the processing of all radiation rays into streams. Since the steps within a stream use different hardware resources (i.e., GPU, DMA, CPU), we can overlap the execution of these steps for different streams by pipelining. Results: We evaluated our method using a Monte Carlo Convolution Superposition (MCCS) program and tested our implementation for various clinical cases on a heterogeneous system containing an Intel i7 quad-core CPU and an NVIDIA TITAN GPU. Comparing with a straightforward MCCS implementation on the same system (using both CPU and GPU for radiation ray tracing), our method gained 2-5X speedup without losing dose calculation accuracy. Conclusion: The results show that our new method improves the effective memory bandwidth and overall performance for MCCS on the CPU-GPU systems. Our proposed method can also be applied to accelerate other Monte Carlo dose calculation approaches. This research was supported in part by NSF under Grants CCF

  8. Hybrid SN/Monte Carlo research and results

    International Nuclear Information System (INIS)

    Baker, R.S.

    1993-01-01

    The neutral particle transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S N ) and stochastic (Monte Carlo) methods are applied. The Monte Carlo and S N regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid Monte Carlo/S N method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S N is well suited for by themselves. The hybrid method has been successfully applied to realistic shielding problems. The vectorized Monte Carlo algorithm in the hybrid method has been ported to the massively parallel architecture of the Connection Machine. Comparisons of performance on a vector machine (Cray Y-MP) and the Connection Machine (CM-2) show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when realistic problems requiring variance reduction are considered. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Monte Carlo theory and practice

    International Nuclear Information System (INIS)

    James, F.

    1987-01-01

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

  14. 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)

  15. 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.

  16. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-10

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

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

    International Nuclear Information System (INIS)

    Chang, C.; Morales, M. A.

    2016-01-01

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

  19. 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

  20. 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)

  1. 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

  2. Testing results of Monte Carlo sampling processes in MCSAD

    International Nuclear Information System (INIS)

    Pinnera, I.; Cruz, C.; Abreu, Y.; Leyva, A.; Correa, C.; Demydenko, C.

    2009-01-01

    The Monte Carlo Simulation of Atom Displacements (MCSAD) is a code implemented by the authors to simulate the complete process of atom displacement (AD) formation. This code makes use of the Monte Carlo (MC) method to sample all the processes involved in the gamma and electronic radiation transport through matter. The kernel of the calculations applied to this code relies on a model based on an algorithm developed by the authors, which firstly splits out multiple electron elastic scattering events from those single ones at higher scattering angles and then, from the last one, sampling those leading to AD at high transferred atomic recoil energies. Some tests have been developed to check the sampling algorithms with the help of the corresponding theoretical distribution functions. Satisfactory results have been obtained, which indicate the strength of the methods and subroutines used in the code. (Author)

  3. 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...

  4. 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

  5. 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.

  6. 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

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

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2003-01-01

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

  8. Homogenized group cross sections by Monte Carlo

    International Nuclear Information System (INIS)

    Van Der Marck, S. C.; Kuijper, J. C.; Oppe, J.

    2006-01-01

    Homogenized group cross sections play a large role in making reactor calculations efficient. Because of this significance, many codes exist that can calculate these cross sections based on certain assumptions. However, the application to the High Flux Reactor (HFR) in Petten, the Netherlands, the limitations of such codes imply that the core calculations would become less accurate when using homogenized group cross sections (HGCS). Therefore we developed a method to calculate HGCS based on a Monte Carlo program, for which we chose MCNP. The implementation involves an addition to MCNP, and a set of small executables to perform suitable averaging after the MCNP run(s) have completed. Here we briefly describe the details of the method, and we report on two tests we performed to show the accuracy of the method and its implementation. By now, this method is routinely used in preparation of the cycle to cycle core calculations for HFR. (authors)

  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. Improved local lattice Monte Carlo simulation for charged systems

    Science.gov (United States)

    Jiang, Jian; Wang, Zhen-Gang

    2018-03-01

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

  11. 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.

  12. 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.

  13. Domain Decomposition strategy for pin-wise full-core Monte Carlo depletion calculation with the reactor Monte Carlo Code

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Jingang; Wang, Kan; Qiu, Yishu [Dept. of Engineering Physics, LiuQing Building, Tsinghua University, Beijing (China); Chai, Xiao Ming; Qiang, Sheng Long [Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu (China)

    2016-06-15

    Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions.

  14. 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.

  15. 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)

  16. Monte Carlo techniques in radiation therapy

    CERN Document Server

    Verhaegen, Frank

    2013-01-01

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

  17. 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.

  18. 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.

  19. 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.

  20. Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

    International Nuclear Information System (INIS)

    Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

    2000-01-01

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

  1. Application of the measurement-based Monte Carlo method in nasopharyngeal cancer patients for intensity modulated radiation therapy

    International Nuclear Information System (INIS)

    Yeh, C.Y.; Lee, C.C.; Chao, T.C.; Lin, M.H.; Lai, P.A.; Liu, F.H.; Tung, C.J.

    2014-01-01

    This study aims to utilize a measurement-based Monte Carlo (MBMC) method to evaluate the accuracy of dose distributions calculated using the Eclipse radiotherapy treatment planning system (TPS) based on the anisotropic analytical algorithm. Dose distributions were calculated for the nasopharyngeal carcinoma (NPC) patients treated with the intensity modulated radiotherapy (IMRT). Ten NPC IMRT plans were evaluated by comparing their dose distributions with those obtained from the in-house MBMC programs for the same CT images and beam geometry. To reconstruct the fluence distribution of the IMRT field, an efficiency map was obtained by dividing the energy fluence of the intensity modulated field by that of the open field, both acquired from an aS1000 electronic portal imaging device. The integrated image of the non-gated mode was used to acquire the full dose distribution delivered during the IMRT treatment. This efficiency map redistributed the particle weightings of the open field phase-space file for IMRT applications. Dose differences were observed in the tumor and air cavity boundary. The mean difference between MBMC and TPS in terms of the planning target volume coverage was 0.6% (range: 0.0–2.3%). The mean difference for the conformity index was 0.01 (range: 0.0–0.01). In conclusion, the MBMC method serves as an independent IMRT dose verification tool in a clinical setting. - Highlights: ► The patient-based Monte Carlo method serves as a reference standard to verify IMRT doses. ► 3D Dose distributions for NPC patients have been verified by the Monte Carlo method. ► Doses predicted by the Monte Carlo method matched closely with those by the TPS. ► The Monte Carlo method predicted a higher mean dose to the middle ears than the TPS. ► Critical organ doses should be confirmed to avoid overdose to normal organs

  2. 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

  3. 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

  4. 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

  5. Nested Sampling with Constrained Hamiltonian Monte Carlo

    OpenAIRE

    Betancourt, M. J.

    2010-01-01

    Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.

  6. Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function

    International Nuclear Information System (INIS)

    Wagner, J.C.; Haghighat, A.

    1998-01-01

    Although the Monte Carlo method is considered to be the most accurate method available for solving radiation transport problems, its applicability is limited by its computational expense. Thus, biasing techniques, which require intuition, guesswork, and iterations involving manual adjustments, are employed to make reactor shielding calculations feasible. To overcome this difficulty, the authors have developed a method for using the S N adjoint function for automated variance reduction of Monte Carlo calculations through source biasing and consistent transport biasing with the weight window technique. They describe the implementation of this method into the standard production Monte Carlo code MCNP and its application to a realistic calculation, namely, the reactor cavity dosimetry calculation. The computational effectiveness of the method, as demonstrated through the increase in calculational efficiency, is demonstrated and quantified. Important issues associated with this method and its efficient use are addressed and analyzed. Additional benefits in terms of the reduction in time and effort required of the user are difficult to quantify but are possibly as important as the computational efficiency. In general, the automated variance reduction method presented is capable of increases in computational performance on the order of thousands, while at the same time significantly reducing the current requirements for user experience, time, and effort. Therefore, this method can substantially increase the applicability and reliability of Monte Carlo for large, real-world shielding applications

  7. Vectorized Monte Carlo

    International Nuclear Information System (INIS)

    Brown, F.B.

    1981-01-01

    Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes

  8. Comparison of MCB and MONTEBURNS Monte Carlo burnup codes on a one-pass deep burn

    International Nuclear Information System (INIS)

    Talamo, Alberto; Ji, Wei; Cetnar, Jerzy; Gudowski, Waclaw

    2006-01-01

    Numerical applications implemented on the Monte Carlo method have developed in line with the increase of computer power; nowadays, in the field of nuclear reactor physics, it is possible to perform burnup simulations in a detailed 3D geometry and a continuous energy description by the Monte Carlo method; moreover, the required computing time can be abundantly reduced by taking advantage of a computer cluster. In this paper we focused on comparing the results of the two major Monte Carlo burnup codes, MONTEBURNS and MCB, when they share the same MCNP geometry, nuclear data library, core thermal power, and they apply the same refueling and shuffling schedule. While simulating a total operation time of the Gas Turbine-Modular Helium Reactor of 2100 effective full power days and a one-pass deep burn in-core fuel management schedule, we have found that the two Monte Carlo codes produce very similar results both on the criticality value of the core and the transmutation of the key actinides

  9. Comparison of MCB and MONTEBURNS Monte Carlo burnup codes on a one-pass deep burn

    Energy Technology Data Exchange (ETDEWEB)

    Talamo, Alberto [Royal Institute of Technology (KTH), Roslagstullsbacken 21, Stockholm S-10691 (Sweden)]. E-mail: alby@anl.gov; Ji, Wei [University of Michigan, Bonisteel Boulevard 2355, Ann Arbor, MI 48109-2104 (United States); Cetnar, Jerzy [AGH-University of Science and Technology, Al. Mickiewicza 30 Cracow (Poland); Gudowski, Waclaw [Royal Institute of Technology (KTH), Roslagstullsbacken 21, Stockholm S-10691 (Sweden)

    2006-09-15

    Numerical applications implemented on the Monte Carlo method have developed in line with the increase of computer power; nowadays, in the field of nuclear reactor physics, it is possible to perform burnup simulations in a detailed 3D geometry and a continuous energy description by the Monte Carlo method; moreover, the required computing time can be abundantly reduced by taking advantage of a computer cluster. In this paper we focused on comparing the results of the two major Monte Carlo burnup codes, MONTEBURNS and MCB, when they share the same MCNP geometry, nuclear data library, core thermal power, and they apply the same refueling and shuffling schedule. While simulating a total operation time of the Gas Turbine-Modular Helium Reactor of 2100 effective full power days and a one-pass deep burn in-core fuel management schedule, we have found that the two Monte Carlo codes produce very similar results both on the criticality value of the core and the transmutation of the key actinides.

  10. 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)

  11. NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media

    Science.gov (United States)

    Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique

    2017-08-01

    NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.

  12. Studies of criticality Monte Carlo method convergence: use of a deterministic calculation and automated detection of the transient

    International Nuclear Information System (INIS)

    Jinaphanh, A.

    2012-01-01

    Monte Carlo criticality calculation allows to estimate the effective multiplication factor as well as local quantities such as local reaction rates. Some configurations presenting weak neutronic coupling (high burn up profile, complete reactor core,...) may induce biased estimations for k eff or reaction rates. In order to improve robustness of the iterative Monte Carlo methods, a coupling with a deterministic code was studied. An adjoint flux is obtained by a deterministic calculation and then used in the Monte Carlo. The initial guess is then automated, the sampling of fission sites is modified and the random walk of neutrons is modified using splitting and russian roulette strategies. An automated convergence detection method has been developed. It locates and suppresses the transient due to the initialization in an output series, applied here to k eff and Shannon entropy. It relies on modeling stationary series by an order 1 auto regressive process and applying statistical tests based on a Student Bridge statistics. This method can easily be extended to every output of an iterative Monte Carlo. Methods developed in this thesis are tested on different test cases. (author)

  13. 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

  14. 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

  15. Recent developments of JAEA's Monte Carlo Code MVP for reactor physics applications

    International Nuclear Information System (INIS)

    Nagaya, Y.; Okumura, K.; Mori, T.

    2013-01-01

    MVP is a general-purpose continuous-energy Monte Carlo code for neutron and photon transport calculations that has been developed since the late 1980's at Japan Atomic Energy Agency (JAEA, formerly JAERI). The MVP code is designed for nuclear reactor applications such as reactor core design/analysis, criticality safety and reactor shielding. This paper describes the MVP code and present its latest developments. Among the new capabilities of MVP we find: -) the perturbation method has been implemented for the change in k(eff); -) the eigenvalue calculations can be performed with an explicit treatment of delayed neutrons in which their fission spectra are taken into account; -) the capability of tallying the scattering matrix (group-to-group scattering cross sections); -) the implementation of an exact model for resonance elastic scattering; and -) a Monte Carlo perturbation technique is used to calculate reactor kinetics parameters

  16. 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

  17. 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

  18. Monte Carlo Transport for Electron Thermal Transport

    Science.gov (United States)

    Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

    2015-11-01

    The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

  19. Reactor physics simulations with coupled Monte Carlo calculation and computational fluid dynamics

    International Nuclear Information System (INIS)

    Seker, V.; Thomas, J.W.; Downar, T.J.

    2007-01-01

    A computational code system based on coupling the Monte Carlo code MCNP5 and the Computational Fluid Dynamics (CFD) code STAR-CD was developed as an audit tool for lower order nuclear reactor calculations. This paper presents the methodology of the developed computer program 'McSTAR'. McSTAR is written in FORTRAN90 programming language and couples MCNP5 and the commercial CFD code STAR-CD. MCNP uses a continuous energy cross section library produced by the NJOY code system from the raw ENDF/B data. A major part of the work was to develop and implement methods to update the cross section library with the temperature distribution calculated by STARCD for every region. Three different methods were investigated and implemented in McSTAR. The user subroutines in STAR-CD are modified to read the power density data and assign them to the appropriate variables in the program and to write an output data file containing the temperature, density and indexing information to perform the mapping between MCNP and STAR-CD cells. Preliminary testing of the code was performed using a 3x3 PWR pin-cell problem. The preliminary results are compared with those obtained from a STAR-CD coupled calculation with the deterministic transport code DeCART. Good agreement in the k eff and the power profile was observed. Increased computational capabilities and improvements in computational methods have accelerated interest in high fidelity modeling of nuclear reactor cores during the last several years. High-fidelity has been achieved by utilizing full core neutron transport solutions for the neutronics calculation and computational fluid dynamics solutions for the thermal-hydraulics calculation. Previous researchers have reported the coupling of 3D deterministic neutron transport method to CFD and their application to practical reactor analysis problems. One of the principal motivations of the work here was to utilize Monte Carlo methods to validate the coupled deterministic neutron transport

  20. 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 ...

  1. 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...

  2. Monte Carlo simulations to advance characterisation of landmines by pulsed fast/thermal neutron analysis

    NARCIS (Netherlands)

    Maucec, M.; Rigollet, C.

    The performance of a detection system based on the pulsed fast/thermal neutron analysis technique was assessed using Monte Carlo simulations. The aim was to develop and implement simulation methods, to support and advance the data analysis techniques of the characteristic gamma-ray spectra,

  3. Monte Carlo - Advances and Challenges

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.

    2008-01-01

    Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature

  4. 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

  5. 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

  6. A study of parallelizing O(N) Green-function-based Monte Carlo method for many fermions coupled with classical degrees of freedom

    International Nuclear Information System (INIS)

    Zhang Shixun; Yamagia, Shinichi; Yunoki, Seiji

    2013-01-01

    Models of fermions interacting with classical degrees of freedom are applied to a large variety of systems in condensed matter physics. For this class of models, Weiße [Phys. Rev. Lett. 102, 150604 (2009)] has recently proposed a very efficient numerical method, called O(N) Green-Function-Based Monte Carlo (GFMC) method, where a kernel polynomial expansion technique is used to avoid the full numerical diagonalization of the fermion Hamiltonian matrix of size N, which usually costs O(N 3 ) computational complexity. Motivated by this background, in this paper we apply the GFMC method to the double exchange model in three spatial dimensions. We mainly focus on the implementation of GFMC method using both MPI on a CPU-based cluster and Nvidia's Compute Unified Device Architecture (CUDA) programming techniques on a GPU-based (Graphics Processing Unit based) cluster. The time complexity of the algorithm and the parallel implementation details on the clusters are discussed. We also show the performance scaling for increasing Hamiltonian matrix size and increasing number of nodes, respectively. The performance evaluation indicates that for a 32 3 Hamiltonian a single GPU shows higher performance equivalent to more than 30 CPU cores parallelized using MPI

  7. Estimation of ex-core detector responses by adjoint Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

    2006-07-01

    Ex-core detector responses can be efficiently calculated by combining an adjoint Monte Carlo calculation with the converged source distribution of a forward Monte Carlo calculation. As the fission source distribution from a Monte Carlo calculation is given only as a collection of discrete space positions, the coupling requires a point flux estimator for each collision in the adjoint calculation. To avoid the infinite variance problems of the point flux estimator, a next-event finite-variance point flux estimator has been applied, witch is an energy dependent form for heterogeneous media of a finite-variance estimator known from the literature. To test the effects of this combined adjoint-forward calculation a simple geometry of a homogeneous core with a reflector was adopted with a small detector in the reflector. To demonstrate the potential of the method the continuous-energy adjoint Monte Carlo technique with anisotropic scattering was implemented with energy dependent absorption and fission cross sections and constant scattering cross section. A gain in efficiency over a completely forward calculation of the detector response was obtained, which is strongly dependent on the specific system and especially the size and position of the ex-core detector and the energy range considered. Further improvements are possible. The method works without problems for small detectors, even for a point detector and a small or even zero energy range. (authors)

  8. 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

  9. Monte-Carlo method - codes for the study of criticality problems (on IBM 7094); Methode de Monte- Carlo - codes pour l'etude des problemes de criticite (IBM 7094)

    Energy Technology Data Exchange (ETDEWEB)

    Moreau, J; Rabot, H; Robin, C [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1965-07-01

    The two codes presented here allow to determine the multiplication constant of media containing fissionable materials under numerous and divided forms; they are based on the Monte-Carlo method. The first code apply to x, y, z, geometries. The volume to be studied ought to be divisible in parallelepipeds, the media within each parallelepiped being limited by non-secant surfaces. The second code is intended for r, 0, z geometries. The results include an analysis of collisions in each medium. Applications and examples with informations on time and accuracy are given. (authors) [French] Les deux codes presentes dans ce rapport permettent la determination des coefficients de multiplication de milieux contenant des matieres fissiles sous des formes tres variees et divisees, ils reposent sur la methode de Monte-Carlo. Le premier code s'applique aux geometries x, y, z, le volume a etudier doit pouvoir etre decompose en parallelepipedes, les milieux a l'interieur de chaque parallelepipede etant limites par des surfaces non secantes. Le deuxieme code s'applique aux geometries r, 0, z. Les resultats comportent une analyse des collisions dans chaque milieu. Des applications et des exemples avec les indications de temps et de precision sont fournis. (auteurs)

  10. Monte Carlo evaluation of path integral for the nuclear shell model

    International Nuclear Information System (INIS)

    Lang, G.H.

    1993-01-01

    The authors present a path-integral formulation of the nuclear shell model using auxillary fields; the path-integral is evaluated by Monte Carlo methods. The method scales favorably with valence-nucleon number and shell-model basis: full-basis calculations are demonstrated up to the rare-earth region, which cannot be treated by other methods. Observables are calculated for the ground state and in a thermal ensemble. Dynamical correlations are obtained, from which strength functions are extracted through the Maximum Entropy method. Examples in the s-d shell, where exact diagonalization can be carried out, compared well with exact results. The open-quotes sign problemclose quotes generic to quantum Monte Carlo calculations is found to be absent in the attractive pairing-plus-multipole interactions. The formulation is general for interacting fermion systems and is well suited for parallel computation. The authors have implemented it on the Intel Touchstone Delta System, achieving better than 99% parallelization

  11. Adjoint electron Monte Carlo calculations

    International Nuclear Information System (INIS)

    Jordan, T.M.

    1986-01-01

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

  12. MORET: Version 4.B. A multigroup Monte Carlo criticality code

    International Nuclear Information System (INIS)

    Jacquet, Olivier; Miss, Joachim; Courtois, Gerard

    2003-01-01

    MORET 4 is a three dimensional multigroup Monte Carlo code which calculates the effective multiplication factor (keff) of any configurations more or less complex as well as reaction rates in the different volumes of the geometry and the leakage out of the system. MORET 4 is the Monte Carlo code of the APOLLO2-MORET 4 standard route of CRISTAL, the French criticality package. It is the most commonly used Monte Carlo code for French criticality calculations. During the last four years, the MORET 4 team has developed or improved the following major points: modernization of the geometry, implementation of perturbation algorithms, source distribution convergence, statistical detection of stationarity, unbiased variance estimation and creation of pre-processing and post-processing tools. The purpose of this paper is not only to present the new features of MORET but also to detail clearly the physical models and the mathematical methods used in the code. (author)

  13. A fully coupled Monte Carlo/discrete ordinates solution to the neutron transport equation. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Randal Scott [Univ. of Arizona, Tucson, AZ (United States)

    1990-01-01

    The neutron transport equation is solved by a hybrid method that iteratively couples regions where deterministic (SN) and stochastic (Monte Carlo) methods are applied. Unlike previous hybrid methods, the Monte Carlo and SN regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor SN is well suited for by themselves. The fully coupled Monte Carlo/SN technique consists of defining spatial and/or energy regions of a problem in which either a Monte Carlo calculation or an SN calculation is to be performed. The Monte Carlo region may comprise the entire spatial region for selected energy groups, or may consist of a rectangular area that is either completely or partially embedded in an arbitrary SN region. The Monte Carlo and SN regions are then connected through the common angular boundary fluxes, which are determined iteratively using the response matrix technique, and volumetric sources. The hybrid method has been implemented in the SN code TWODANT by adding special-purpose Monte Carlo subroutines to calculate the response matrices and volumetric sources, and linkage subrountines to carry out the interface flux iterations. The common angular boundary fluxes are included in the SN code as interior boundary sources, leaving the logic for the solution of the transport flux unchanged, while, with minor modifications, the diffusion synthetic accelerator remains effective in accelerating SN calculations. The special-purpose Monte Carlo routines used are essentially analog, with few variance reduction techniques employed. However, the routines have been successfully vectorized, with approximately a factor of five increase in speed over the non-vectorized version.

  14. Monte Carlo simulation in nuclear medicine

    International Nuclear Information System (INIS)

    Morel, Ch.

    2007-01-01

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

  15. Transport methods: general. 2. Monte Carlo Particle Transport in Media with Exponentially Varying Time-Dependent Cross Sections

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Martin, William R.

    2001-01-01

    We have investigated Monte Carlo schemes for analyzing particle transport through media with exponentially varying time-dependent cross sections. For such media, the cross sections are represented in the form Σ(t) = Σ 0 e -at (1) or equivalently as Σ(x) = Σ 0 e -bx (2) where b = av and v is the particle speed. For the following discussion, the parameters a and b may be either positive, for exponentially decreasing cross sections, or negative, for exponentially increasing cross sections. For most time-dependent Monte Carlo applications, the time and spatial variations of the cross-section data are handled by means of a stepwise procedure, holding the cross sections constant for each region over a small time interval Δt, performing the Monte Carlo random walk over the interval Δt, updating the cross sections, and then repeating for a series of time intervals. Continuously varying spatial- or time-dependent cross sections can be treated in a rigorous Monte Carlo fashion using delta-tracking, but inefficiencies may arise if the range of cross-section variation is large. In this paper, we present a new method for sampling collision distances directly for cross sections that vary exponentially in space or time. The method is exact and efficient and has direct application to Monte Carlo radiation transport methods. To verify that the probability density function (PDF) is correct and that the random-sampling procedure yields correct results, numerical experiments were performed using a one-dimensional Monte Carlo code. The physical problem consisted of a beam source impinging on a purely absorbing infinite slab, with a slab thickness of 1 cm and Σ 0 = 1 cm -1 . Monte Carlo calculations with 10 000 particles were run for a range of the exponential parameter b from -5 to +20 cm -1 . Two separate Monte Carlo calculations were run for each choice of b, a continuously varying case using the random-sampling procedures described earlier, and a 'conventional' case where the

  16. Introduction to the simulation with MCNP Monte Carlo code and its applications in Medical Physics; Introduccion a la simulacion con el codigo de Monte Carlo MCNP y sus aplicaciones en Fisica Medica

    Energy Technology Data Exchange (ETDEWEB)

    Parreno Z, F.; Paucar J, R.; Picon C, C. [Instituto Peruano de Energia Nuclear, Av. Canada 1470, San Borja, Lima 41 (Peru)

    1998-12-31

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

  17. Monte Carlo simulations on a 9-node PC cluster

    International Nuclear Information System (INIS)

    Gouriou, J.

    2001-01-01

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

  18. Volume Measurement Algorithm for Food Product with Irregular Shape using Computer Vision based on Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    Joko Siswantoro

    2014-11-01

    Full Text Available Volume is one of important issues in the production and processing of food product. Traditionally, volume measurement can be performed using water displacement method based on Archimedes’ principle. Water displacement method is inaccurate and considered as destructive method. Computer vision offers an accurate and nondestructive method in measuring volume of food product. This paper proposes algorithm for volume measurement of irregular shape food product using computer vision based on Monte Carlo method. Five images of object were acquired from five different views and then processed to obtain the silhouettes of object. From the silhouettes of object, Monte Carlo method was performed to approximate the volume of object. The simulation result shows that the algorithm produced high accuracy and precision for volume measurement.

  19. 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

  20. Movable geometry and eigenvalue search capability in the MC21 Monte Carlo code

    International Nuclear Information System (INIS)

    Gill, D. F.; Nease, B. R.; Griesheimer, D. P.

    2013-01-01

    A description of a robust and flexible movable geometry implementation in the Monte Carlo code MC21 is described along with a search algorithm that can be used in conjunction with the movable geometry capability to perform eigenvalue searches based on the position of some geometric component. The natural use of the combined movement and search capability is searching to critical through variation of control rod (or control drum) position. The movable geometry discussion provides the mathematical framework for moving surfaces in the MC21 combinatorial solid geometry description. A discussion of the interface between the movable geometry system and the user is also described, particularly the ability to create a hierarchy of movable groups. Combined with the hierarchical geometry description in MC21 the movable group framework provides a very powerful system for inline geometry modification. The eigenvalue search algorithm implemented in MC21 is also described. The foundations of this algorithm are a regula falsi search though several considerations are made in an effort to increase the efficiency of the algorithm for use with Monte Carlo. Specifically, criteria are developed to determine after each batch whether the Monte Carlo calculation should be continued, the search iteration can be rejected, or the search iteration has converged. These criteria seek to minimize the amount of time spent per iteration. Results for the regula falsi method are shown, illustrating that the method as implemented is indeed convergent and that the optimizations made ultimately reduce the total computational expense. (authors)

  1. Movable geometry and eigenvalue search capability in the MC21 Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Gill, D. F.; Nease, B. R.; Griesheimer, D. P. [Bettis Atomic Power Laboratory, PO Box 79, West Mifflin, PA 15122 (United States)

    2013-07-01

    A description of a robust and flexible movable geometry implementation in the Monte Carlo code MC21 is described along with a search algorithm that can be used in conjunction with the movable geometry capability to perform eigenvalue searches based on the position of some geometric component. The natural use of the combined movement and search capability is searching to critical through variation of control rod (or control drum) position. The movable geometry discussion provides the mathematical framework for moving surfaces in the MC21 combinatorial solid geometry description. A discussion of the interface between the movable geometry system and the user is also described, particularly the ability to create a hierarchy of movable groups. Combined with the hierarchical geometry description in MC21 the movable group framework provides a very powerful system for inline geometry modification. The eigenvalue search algorithm implemented in MC21 is also described. The foundations of this algorithm are a regula falsi search though several considerations are made in an effort to increase the efficiency of the algorithm for use with Monte Carlo. Specifically, criteria are developed to determine after each batch whether the Monte Carlo calculation should be continued, the search iteration can be rejected, or the search iteration has converged. These criteria seek to minimize the amount of time spent per iteration. Results for the regula falsi method are shown, illustrating that the method as implemented is indeed convergent and that the optimizations made ultimately reduce the total computational expense. (authors)

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

    KAUST Repository

    Efendiev, Yalchin R.

    2013-08-21

    In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate

  3. Monte Carlo based diffusion coefficients for LMFBR analysis

    International Nuclear Information System (INIS)

    Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

    2010-01-01

    A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

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

    International Nuclear Information System (INIS)

    Turner, S.A.

    1996-02-01

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

  10. 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.

  11. 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)

  12. 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.

  13. 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.

  14. A reverse Monte Carlo method for deriving optical constants of solids from reflection electron energy-loss spectroscopy spectra

    International Nuclear Information System (INIS)

    Da, B.; Sun, Y.; Ding, Z. J.; Mao, S. F.; Zhang, Z. M.; Jin, H.; Yoshikawa, H.; Tanuma, S.

    2013-01-01

    A reverse Monte Carlo (RMC) method is developed to obtain the energy loss function (ELF) and optical constants from a measured reflection electron energy-loss spectroscopy (REELS) spectrum by an iterative Monte Carlo (MC) simulation procedure. The method combines the simulated annealing method, i.e., a Markov chain Monte Carlo (MCMC) sampling of oscillator parameters, surface and bulk excitation weighting factors, and band gap energy, with a conventional MC simulation of electron interaction with solids, which acts as a single step of MCMC sampling in this RMC method. To examine the reliability of this method, we have verified that the output data of the dielectric function are essentially independent of the initial values of the trial parameters, which is a basic property of a MCMC method. The optical constants derived for SiO 2 in the energy loss range of 8-90 eV are in good agreement with other available data, and relevant bulk ELFs are checked by oscillator strength-sum and perfect-screening-sum rules. Our results show that the dielectric function can be obtained by the RMC method even with a wide range of initial trial parameters. The RMC method is thus a general and effective method for determining the optical properties of solids from REELS measurements.

  15. Progress on RMC: a Monte Carlo neutron transport code for reactor analysis

    International Nuclear Information System (INIS)

    Wang, Kan; Li, Zeguang; She, Ding; Liu, Yuxuan; Xu, Qi; Shen, Huayun; Yu, Ganglin

    2011-01-01

    This paper presents a new 3-D Monte Carlo neutron transport code named RMC (Reactor Monte Carlo code), specifically intended for reactor physics analysis. This code is being developed by Department of Engineering Physics in Tsinghua University and written in C++ and Fortran 90 language with the latest version of RMC 2.5.0. The RMC code uses the method known as the delta-tracking method to simulate neutron transport, the advantages of which include fast simulation in complex geometries and relatively simple handling of complicated geometrical objects. Some other techniques such as computational-expense oriented method and hash-table method have been developed and implemented in RMC to speedup the calculation. To meet the requirements of reactor analysis, the RMC code has the calculational functions including criticality calculation, burnup calculation and also kinetics simulation. In this paper, comparison calculations of criticality problems, burnup problems and transient problems are carried out using RMC code and other Monte Carlo codes, and the results show that RMC performs quite well in these kinds of problems. Based on MPI, RMC succeeds in parallel computation and represents a high speed-up. This code is still under intensive development and the further work directions are mentioned at the end of this paper. (author)

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Monte Carlo simulations on SIMD computer architectures

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  1. 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)

  2. Modeling dose-rate on/over the surface of cylindrical radio-models using Monte Carlo methods

    International Nuclear Information System (INIS)

    Xiao Xuefu; Ma Guoxue; Wen Fuping; Wang Zhongqi; Wang Chaohui; Zhang Jiyun; Huang Qingbo; Zhang Jiaqiu; Wang Xinxing; Wang Jun

    2004-01-01

    Objective: To determine the dose-rates on/over the surface of 10 cylindrical radio-models, which belong to the Metrology Station of Radio-Geological Survey of CNNC. Methods: The dose-rates on/over the surface of 10 cylindrical radio-models were modeled using the famous Monte Carlo code-MCNP. The dose-rates on/over the surface of 10 cylindrical radio-models were measured by a high gas pressurized ionization chamber dose-rate meter, respectively. The values of dose-rate modeled using MCNP code were compared with those obtained by authors in the present experimental measurement, and with those obtained by other workers previously. Some factors causing the discrepancy between the data obtained by authors using MCNP code and the data obtained using other methods are discussed in this paper. Results: The data of dose-rates on/over the surface of 10 cylindrical radio-models, obtained using MCNP code, were in good agreement with those obtained by other workers using the theoretical method. They were within the discrepancy of ±5% in general, and the maximum discrepancy was less than 10%. Conclusions: As if each factor needed for the Monte Carlo code is correct, the dose-rates on/over the surface of cylindrical radio-models modeled using the Monte Carlo code are correct with an uncertainty of 3%

  3. Mean field simulation for Monte Carlo integration

    CERN Document Server

    Del Moral, Pierre

    2013-01-01

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

  4. Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

    KAUST Repository

    Martinez, Josue G.

    2010-06-01

    The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.

  5. 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. ...

  6. Testing random number generators for Monte Carlo applications

    International Nuclear Information System (INIS)

    Sim, L.H.

    1992-01-01

    Central to any system for modelling radiation transport phenomena using Monte Carlo techniques is the method by which pseudo random numbers are generated. This method is commonly referred to as the Random Number Generator (RNG). It is usually a computer implemented mathematical algorithm which produces a series of numbers uniformly distributed on the interval [0,1]. If this series satisfies certain statistical tests for randomness, then for practical purposes the pseudo random numbers in the series can be considered to be random. Tests of this nature are important not only for new RNGs but also to test the implementation of known RNG algorithms in different computer environments. Six RNGs have been tested using six statistical tests and one visual test. The statistical tests are the moments, frequency (digit and number), serial, gap, and poker tests. The visual test is a simple two dimensional ordered pair display. In addition the RNGs have been tested in a specific Monte Carlo application. This type of test is often overlooked, however it is important that in addition to satisfactory performance in statistical tests, the RNG be able to perform effectively in the applications of interest. The RNGs tested here are based on a variety of algorithms, including multiplicative and linear congruential, lagged Fibonacci, and combination arithmetic and lagged Fibonacci. The effect of the Bays-Durham shuffling algorithm on the output of a known bad RNG has also been investigated. 18 refs., 11 tabs., 4 figs. of

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  8. A Study on Efficiency Improvement of the Hybrid Monte Carlo/Deterministic Method for Global Transport Problems

    International Nuclear Information System (INIS)

    Kim, Jong Woo; Woo, Myeong Hyeon; Kim, Jae Hyun; Kim, Do Hyun; Shin, Chang Ho; Kim, Jong Kyung

    2017-01-01

    In this study hybrid Monte Carlo/Deterministic method is explained for radiation transport analysis in global system. FW-CADIS methodology construct the weight window parameter and it useful at most global MC calculation. However, Due to the assumption that a particle is scored at a tally, less particles are transported to the periphery of mesh tallies. For compensation this space-dependency, we modified the module in the ADVANTG code to add the proposed method. We solved the simple test problem for comparing with result from FW-CADIS methodology, it was confirmed that a uniform statistical error was secured as intended. In the future, it will be added more practical problems. It might be useful to perform radiation transport analysis using the Hybrid Monte Carlo/Deterministic method in global transport problems.

  9. 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...

  10. 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

  11. 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)

  12. 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)

  13. A radiating shock evaluated using Implicit Monte Carlo Diffusion

    International Nuclear Information System (INIS)

    Cleveland, M.; Gentile, N.

    2013-01-01

    Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)

  14. Measurement and Monte Carlo modeling of the spatial response of scintillation screens

    Energy Technology Data Exchange (ETDEWEB)

    Pistrui-Maximean, S.A. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)], E-mail: spistrui@gmail.com; Letang, J.M. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)], E-mail: jean-michel.letang@insa-lyon.fr; Freud, N. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France); Koch, A. [Thales Electron Devices, 38430 Moirans (France); Walenta, A.H. [Detectors and Electronics Department, FB Physik, Siegen University, 57068 Siegen (Germany); Montarou, G. [Corpuscular Physics Laboratory, Blaise Pascal University, 63177 Aubiere (France); Babot, D. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)

    2007-11-01

    In this article, we propose a detailed protocol to carry out measurements of the spatial response of scintillation screens and to assess the agreement with simulated results. The experimental measurements have been carried out using a practical implementation of the slit method. A Monte Carlo simulation model of scintillator screens, implemented with the toolkit Geant4, has been used to study the influence of the acquisition setup parameters and to compare with the experimental results. An algorithm of global stochastic optimization based on a localized random search method has been implemented to adjust the optical parameters (optical scattering and absorption coefficients). The algorithm has been tested for different X-ray tube voltages (40, 70 and 100 kV). A satisfactory convergence between the results simulated with the optimized model and the experimental measurements is obtained.

  15. Modeling the reflectance of the lunar regolith by a new method combining Monte Carlo Ray tracing and Hapke's model with application to Chang'E-1 IIM data.

    Science.gov (United States)

    Wong, Un-Hong; Wu, Yunzhao; Wong, Hon-Cheng; Liang, Yanyan; Tang, Zesheng

    2014-01-01

    In this paper, we model the reflectance of the lunar regolith by a new method combining Monte Carlo ray tracing and Hapke's model. The existing modeling methods exploit either a radiative transfer model or a geometric optical model. However, the measured data from an Interference Imaging spectrometer (IIM) on an orbiter were affected not only by the composition of minerals but also by the environmental factors. These factors cannot be well addressed by a single model alone. Our method implemented Monte Carlo ray tracing for simulating the large-scale effects such as the reflection of topography of the lunar soil and Hapke's model for calculating the reflection intensity of the internal scattering effects of particles of the lunar soil. Therefore, both the large-scale and microscale effects are considered in our method, providing a more accurate modeling of the reflectance of the lunar regolith. Simulation results using the Lunar Soil Characterization Consortium (LSCC) data and Chang'E-1 elevation map show that our method is effective and useful. We have also applied our method to Chang'E-1 IIM data for removing the influence of lunar topography to the reflectance of the lunar soil and to generate more realistic visualizations of the lunar surface.

  16. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

    2016-01-01

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  17. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  18. Variational Variance Reduction for Monte Carlo Criticality Calculations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2001-01-01

    A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions

  19. Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

    International Nuclear Information System (INIS)

    Shaukata, Nadeem; Shim, Hyung Jin

    2015-01-01

    In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

  20. Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Shaukata, Nadeem; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of)

    2015-10-15

    In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

  1. 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...

  2. 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

  3. 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)

  4. Continuous energy Monte Carlo calculations for randomly distributed spherical fuels based on statistical geometry model

    Energy Technology Data Exchange (ETDEWEB)

    Murata, Isao [Osaka Univ., Suita (Japan); Mori, Takamasa; Nakagawa, Masayuki; Itakura, Hirofumi

    1996-03-01

    The method to calculate neutronics parameters of a core composed of randomly distributed spherical fuels has been developed based on a statistical geometry model with a continuous energy Monte Carlo method. This method was implemented in a general purpose Monte Carlo code MCNP, and a new code MCNP-CFP had been developed. This paper describes the model and method how to use it and the validation results. In the Monte Carlo calculation, the location of a spherical fuel is sampled probabilistically along the particle flight path from the spatial probability distribution of spherical fuels, called nearest neighbor distribution (NND). This sampling method was validated through the following two comparisons: (1) Calculations of inventory of coated fuel particles (CFPs) in a fuel compact by both track length estimator and direct evaluation method, and (2) Criticality calculations for ordered packed geometries. This method was also confined by applying to an analysis of the critical assembly experiment at VHTRC. The method established in the present study is quite unique so as to a probabilistic model of the geometry with a great number of spherical fuels distributed randomly. Realizing the speed-up by vector or parallel computations in future, it is expected to be widely used in calculation of a nuclear reactor core, especially HTGR cores. (author).

  5. Monte Carlo simulations for plasma physics

    International Nuclear Information System (INIS)

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

    2000-07-01

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

  6. 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.

  7. 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

  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. Statistical implications in Monte Carlo depletions - 051

    International Nuclear Information System (INIS)

    Zhiwen, Xu; Rhodes, J.; Smith, K.

    2010-01-01

    As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)

  10. Non statistical Monte-Carlo

    International Nuclear Information System (INIS)

    Mercier, B.

    1985-04-01

    We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems

  11. 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

  12. Discrete Diffusion Monte Carlo for Electron Thermal Transport

    Science.gov (United States)

    Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

    2014-10-01

    The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

  13. 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)

  14. 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)

  15. Monte Carlo codes and Monte Carlo simulator program

    International Nuclear Information System (INIS)

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

    1990-03-01

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

  16. Automatic modeling for the Monte Carlo transport code Geant4

    International Nuclear Information System (INIS)

    Nie Fanzhi; Hu Liqin; Wang Guozhong; Wang Dianxi; Wu Yican; Wang Dong; Long Pengcheng; FDS Team

    2015-01-01

    Geant4 is a widely used Monte Carlo transport simulation package. Its geometry models could be described in Geometry Description Markup Language (GDML), but it is time-consuming and error-prone to describe the geometry models manually. This study implemented the conversion between computer-aided design (CAD) geometry models and GDML models. This method has been Studied based on Multi-Physics Coupling Analysis Modeling Program (MCAM). The tests, including FDS-Ⅱ model, demonstrated its accuracy and feasibility. (authors)

  17. Massively parallel Monte Carlo for many-particle simulations on GPUs

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Joshua A.; Jankowski, Eric [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Grubb, Thomas L. [Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Engel, Michael [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Glotzer, Sharon C., E-mail: sglotzer@umich.edu [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States)

    2013-12-01

    Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little attention because of the inherent serial nature of the statistical sampling. In this paper, we present a massively parallel method that obeys detailed balance and implement it for a system of hard disks on the GPU. We reproduce results of serial high-precision Monte Carlo runs to verify the method. This is a good test case because the hard disk equation of state over the range where the liquid transforms into the solid is particularly sensitive to small deviations away from the balance conditions. On a Tesla K20, our GPU implementation executes over one billion trial moves per second, which is 148 times faster than on a single Intel Xeon E5540 CPU core, enables 27 times better performance per dollar, and cuts energy usage by a factor of 13. With this improved performance we are able to calculate the equation of state for systems of up to one million hard disks. These large system sizes are required in order to probe the nature of the melting transition, which has been debated for the last forty years. In this paper we present the details of our computational method, and discuss the thermodynamics of hard disks separately in a companion paper.

  18. Research on perturbation based Monte Carlo reactor criticality search

    International Nuclear Information System (INIS)

    Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

    2013-01-01

    Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)

  19. 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)

  20. Improving multivariate Horner schemes with Monte Carlo tree search

    Science.gov (United States)

    Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

    2013-11-01

    Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

  1. Monte Carlo techniques in diagnostic and therapeutic nuclear medicine

    International Nuclear Information System (INIS)

    Zaidi, H.

    2002-01-01

    Monte Carlo techniques have become one of the most popular tools in different areas of medical radiation physics following the development and subsequent implementation of powerful computing systems for clinical use. In particular, they have been extensively applied to simulate processes involving random behaviour and to quantify physical parameters that are difficult or even impossible to calculate analytically or to determine by experimental measurements. The use of the Monte Carlo method to simulate radiation transport turned out to be the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides. There is broad consensus in accepting that the earliest Monte Carlo calculations in medical radiation physics were made in the area of nuclear medicine, where the technique was used for dosimetry modelling and computations. Formalism and data based on Monte Carlo calculations, developed by the Medical Internal Radiation Dose (MIRD) committee of the Society of Nuclear Medicine, were published in a series of supplements to the Journal of Nuclear Medicine, the first one being released in 1968. Some of these pamphlets made extensive use of Monte Carlo calculations to derive specific absorbed fractions for electron and photon sources uniformly distributed in organs of mathematical phantoms. Interest in Monte Carlo-based dose calculations with β-emitters has been revived with the application of radiolabelled monoclonal antibodies to radioimmunotherapy. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the medical physics

  2. 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

  3. Fast CPU-based Monte Carlo simulation for radiotherapy dose calculation

    Science.gov (United States)

    Ziegenhein, Peter; Pirner, Sven; Kamerling, Cornelis Ph; Oelfke, Uwe

    2015-08-01

    Monte-Carlo (MC) simulations are considered to be the most accurate method for calculating dose distributions in radiotherapy. Its clinical application, however, still is limited by the long runtimes conventional implementations of MC algorithms require to deliver sufficiently accurate results on high resolution imaging data. In order to overcome this obstacle we developed the software-package PhiMC, which is capable of computing precise dose distributions in a sub-minute time-frame by leveraging the potential of modern many- and multi-core CPU-based computers. PhiMC is based on the well verified dose planning method (DPM). We could demonstrate that PhiMC delivers dose distributions which are in excellent agreement to DPM. The multi-core implementation of PhiMC scales well between different computer architectures and achieves a speed-up of up to 37× compared to the original DPM code executed on a modern system. Furthermore, we could show that our CPU-based implementation on a modern workstation is between 1.25× and 1.95× faster than a well-known GPU implementation of the same simulation method on a NVIDIA Tesla C2050. Since CPUs work on several hundreds of GB RAM the typical GPU memory limitation does not apply for our implementation and high resolution clinical plans can be calculated.

  4. Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

    Energy Technology Data Exchange (ETDEWEB)

    Bates, Cameron Russell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mckigney, Edward Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-01-09

    The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

  5. 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.

  6. Monte Carlo approaches to light nuclei

    International Nuclear Information System (INIS)

    Carlson, J.

    1990-01-01

    Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of 16 O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs

  7. Monte Carlo approaches to light nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Carlson, J.

    1990-01-01

    Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.

  8. Kohn-Sham orbitals and potentials from quantum Monte Carlo molecular densities

    International Nuclear Information System (INIS)

    Varsano, Daniele; Barborini, Matteo; Guidoni, Leonardo

    2014-01-01

    In this work we show the possibility to extract Kohn-Sham orbitals, orbital energies, and exchange correlation potentials from accurate Quantum Monte Carlo (QMC) densities for atoms (He, Be, Ne) and molecules (H 2 , Be 2 , H 2 O, and C 2 H 4 ). The Variational Monte Carlo (VMC) densities based on accurate Jastrow Antisymmetrised Geminal Power wave functions are calculated through different estimators. Using these reference densities, we extract the Kohn-Sham quantities with the method developed by Zhao, Morrison, and Parr (ZMP) [Phys. Rev. A 50, 2138 (1994)]. We compare these extracted quantities with those obtained form CISD densities and with other data reported in the literature, finding a good agreement between VMC and other high-level quantum chemistry methods. Our results demonstrate the applicability of the ZMP procedure to QMC molecular densities, that can be used for the testing and development of improved functionals and for the implementation of embedding schemes based on QMC and Density Functional Theory

  9. 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

  10. 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.

  11. Monte Carlo Techniques for the Comprehensive Modeling of Isotopic Inventories in Future Nuclear Systems and Fuel Cycles. Final Report

    International Nuclear Information System (INIS)

    Paul P.H. Wilson

    2005-01-01

    The development of Monte Carlo techniques for isotopic inventory analysis has been explored in order to facilitate the modeling of systems with flowing streams of material through varying neutron irradiation environments. This represents a novel application of Monte Carlo methods to a field that has traditionally relied on deterministic solutions to systems of first-order differential equations. The Monte Carlo techniques were based largely on the known modeling techniques of Monte Carlo radiation transport, but with important differences, particularly in the area of variance reduction and efficiency measurement. The software that was developed to implement and test these methods now provides a basis for validating approximate modeling techniques that are available to deterministic methodologies. The Monte Carlo methods have been shown to be effective in reproducing the solutions of simple problems that are possible using both stochastic and deterministic methods. The Monte Carlo methods are also effective for tracking flows of materials through complex systems including the ability to model removal of individual elements or isotopes in the system. Computational performance is best for flows that have characteristic times that are large fractions of the system lifetime. As the characteristic times become short, leading to thousands or millions of passes through the system, the computational performance drops significantly. Further research is underway to determine modeling techniques to improve performance within this range of problems. This report describes the technical development of Monte Carlo techniques for isotopic inventory analysis. The primary motivation for this solution methodology is the ability to model systems of flowing material being exposed to varying and stochastically varying radiation environments. The methodology was developed in three stages: analog methods which model each atom with true reaction probabilities (Section 2), non-analog methods

  12. EGS4, Electron Photon Shower Simulation by Monte-Carlo

    International Nuclear Information System (INIS)

    1998-01-01

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

  13. Randomized quasi-Monte Carlo simulation of fast-ion thermalization

    Science.gov (United States)

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

    2012-01-01

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

  14. 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.

  15. 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

  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. Evaluation of six scatter correction methods based on spectral analysis in 99m Tc SPECT imaging using SIMIND Monte Carlo simulation

    Directory of Open Access Journals (Sweden)

    Mahsa Noori Asl

    2013-01-01

    Full Text Available Compton-scattered photons included within the photopeak pulse-height window result in the degradation of SPECT images both qualitatively and quantitatively. The purpose of this study is to evaluate and compare six scatter correction methods based on setting the energy windows in 99m Tc spectrum. SIMIND Monte Carlo simulation is used to generate the projection images from a cold-sphere hot-background phantom. For evaluation of different scatter correction methods, three assessment criteria including image contrast, signal-to-noise ratio (SNR and relative noise of the background (RNB are considered. Except for the dual-photopeak window (DPW method, the image contrast of the five cold spheres is improved in the range of 2.7-26%. Among methods considered, two methods show a nonuniform correction performance. The RNB for all of the scatter correction methods is ranged from minimum 0.03 for DPW method to maximum 0.0727 for the three energy window (TEW method using trapezoidal approximation. The TEW method using triangular approximation because of ease of implementation, good improvement of the image contrast and the SNR for the five cold spheres, and the low noise level is proposed as most appropriate correction method.

  18. 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.

  19. 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)

  20. 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.)

  1. SPQR: a Monte Carlo reactor kinetics code

    International Nuclear Information System (INIS)

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

    1980-02-01

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

  2. Shell model the Monte Carlo way

    International Nuclear Information System (INIS)

    Ormand, W.E.

    1995-01-01

    The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined

  3. Shell model the Monte Carlo way

    Energy Technology Data Exchange (ETDEWEB)

    Ormand, W.E.

    1995-03-01

    The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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)

  9. 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)

  10. Randomized quasi-Monte Carlo simulation of fast-ion thermalization

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  11. Temperature variance study in Monte-Carlo photon transport theory

    International Nuclear Information System (INIS)

    Giorla, J.

    1985-10-01

    We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

  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. 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.

  14. A polygon-surface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chan Hyeong; Jeong, Jong Hwi [Department of Nuclear Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791 (Korea, Republic of); Bolch, Wesley E [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Cho, Kun-Woo [Korea Institute of Nuclear Safety, 19 Guseong-dong, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Hwang, Sung Bae, E-mail: chkim@hanyang.ac.kr [Department of Physical Therapy, Kyungbuk College, Hyucheon 2-dong, Yeongju-si, Gyeongbuk 750-712 (Korea, Republic of)

    2011-05-21

    Even though the hybrid phantom embodies both the anatomic reality of voxel phantoms and the deformability of stylized phantoms, it must be voxelized to be used in a Monte Carlo code for dose calculation or some imaging simulation, which incurs the inherent limitations of voxel phantoms. In the present study, a voxel phantom named VKH-Man (Visible Korean Human-Man), was converted to a polygon-surface phantom (PSRK-Man, Polygon-Surface Reference Korean-Man), which was then adjusted to the Reference Korean data. Subsequently, the PSRK-Man polygon phantom was directly, without any voxelization process, implemented in the Geant4 Monte Carlo code for dose calculations. The calculated dose values and computation time were then compared with those of HDRK-Man (High Definition Reference Korean-Man), a corresponding voxel phantom adjusted to the same Reference Korean data from the same VKH-Man voxel phantom. Our results showed that the calculated dose values of the PSRK-Man surface phantom agreed well with those of the HDRK-Man voxel phantom. The calculation speed for the PSRK-Man polygon phantom though was 70-150 times slower than that of the HDRK-Man voxel phantom; that speed, however, could be acceptable in some applications, in that direct use of the surface phantom PSRK-Man in Geant4 does not require a separate voxelization process. Computing speed can be enhanced, in future, either by optimizing the Monte Carlo transport kernel for the polygon surfaces or by using modern computing technologies such as grid computing and general-purpose computing on graphics processing units programming.

  15. A polygon-surface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation

    International Nuclear Information System (INIS)

    Kim, Chan Hyeong; Jeong, Jong Hwi; Bolch, Wesley E; Cho, Kun-Woo; Hwang, Sung Bae

    2011-01-01

    Even though the hybrid phantom embodies both the anatomic reality of voxel phantoms and the deformability of stylized phantoms, it must be voxelized to be used in a Monte Carlo code for dose calculation or some imaging simulation, which incurs the inherent limitations of voxel phantoms. In the present study, a voxel phantom named VKH-Man (Visible Korean Human-Man), was converted to a polygon-surface phantom (PSRK-Man, Polygon-Surface Reference Korean-Man), which was then adjusted to the Reference Korean data. Subsequently, the PSRK-Man polygon phantom was directly, without any voxelization process, implemented in the Geant4 Monte Carlo code for dose calculations. The calculated dose values and computation time were then compared with those of HDRK-Man (High Definition Reference Korean-Man), a corresponding voxel phantom adjusted to the same Reference Korean data from the same VKH-Man voxel phantom. Our results showed that the calculated dose values of the PSRK-Man surface phantom agreed well with those of the HDRK-Man voxel phantom. The calculation speed for the PSRK-Man polygon phantom though was 70-150 times slower than that of the HDRK-Man voxel phantom; that speed, however, could be acceptable in some applications, in that direct use of the surface phantom PSRK-Man in Geant4 does not require a separate voxelization process. Computing speed can be enhanced, in future, either by optimizing the Monte Carlo transport kernel for the polygon surfaces or by using modern computing technologies such as grid computing and general-purpose computing on graphics processing units programming.

  16. 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

  17. Isotopic depletion with Monte Carlo

    International Nuclear Information System (INIS)

    Martin, W.R.; Rathkopf, J.A.

    1996-06-01

    This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation

  18. 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.

  19. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung

    2009-11-01

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

  20. 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.

  1. Present status and future prospects of neutronics Monte Carlo

    International Nuclear Information System (INIS)

    Gelbard, E.M.

    1990-01-01

    It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)

  2. 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

  3. A method for tuning parameters of Monte Carlo generators and a determination of the unintegrated gluon density

    International Nuclear Information System (INIS)

    Bacchetta, Alessandro; Jung, Hannes; Kutak, Krzysztof

    2010-02-01

    A method for tuning parameters in Monte Carlo generators is described and applied to a specific case. The method works in the following way: each observable is generated several times using different values of the parameters to be tuned. The output is then approximated by some analytic form to describe the dependence of the observables on the parameters. This approximation is used to find the values of the parameter that give the best description of the experimental data. This results in significantly faster fitting compared to an approach in which the generator is called iteratively. As an application, we employ this method to fit the parameters of the unintegrated gluon density used in the Cascade Monte Carlo generator, using inclusive deep inelastic data measured by the H1 Collaboration. We discuss the results of the fit, its limitations, and its strong points. (orig.)

  4. 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

  5. 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.)

  6. 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.

  7. 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...

  8. 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

  9. Approaches to Mixed Methods Dissemination and Implementation Research: Methods, Strengths, Caveats, and Opportunities.

    Science.gov (United States)

    Green, Carla A; Duan, Naihua; Gibbons, Robert D; Hoagwood, Kimberly E; Palinkas, Lawrence A; Wisdom, Jennifer P

    2015-09-01

    Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings.

  10. RMCgui: a new interface for the workflow associated with running Reverse Monte Carlo simulations

    International Nuclear Information System (INIS)

    Dove, Martin T; Rigg, Gary

    2013-01-01

    The Reverse Monte Carlo method enables construction and refinement of large atomic models of materials that are tuned to give best agreement with experimental data such as neutron and x-ray total scattering data, capturing both the average structure and fluctuations. The practical drawback with the current implementations of this approach is the relatively complex workflow required, from setting up the configuration and simulation details through to checking the final outputs and analysing the resultant configurations. In order to make this workflow more accessible to users, we have developed an end-to-end workflow wrapped within a graphical user interface—RMCgui—designed to make the Reverse Monte Carlo more widely accessible. (paper)

  11. Igo - A Monte Carlo Code For Radiotherapy Planning

    International Nuclear Information System (INIS)

    Goldstein, M.; Regev, D.

    1999-01-01

    The goal of radiation therapy is to deliver a lethal dose to the tumor, while minimizing the dose to normal tissues and vital organs. To carry out this task, it is critical to calculate correctly the 3-D dose delivered. Monte Carlo transport methods (especially the Adjoint Monte Carlo have the potential to provide more accurate predictions of the 3-D dose the currently used methods. IG0 is a Monte Carlo code derived from the general Monte Carlo Program - MCNP, tailored specifically for calculating the effects of radiation therapy. This paper describes the IG0 transport code, the PIG0 interface and some preliminary results

  12. Monte Carlo techniques for analyzing deep-penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

    1986-01-01

    Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications

  13. Uncertainty analysis in Monte Carlo criticality computations

    International Nuclear Information System (INIS)

    Qi Ao

    2011-01-01

    Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.

  14. 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.

  15. 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)

  16. 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.

  17. Contributions to the Monte-Carlo methods development for the criticality studies: the anisotropy diffusion representation, the perturbations study; Contributions au developpement des methodes de Monte-Carlo pour les etudes de criticite: representation de l'anisotropie de la diffusion, etude des perturbations

    Energy Technology Data Exchange (ETDEWEB)

    Le Cocq, A

    1998-11-23

    The aim of this work is the performances improvement of the Monte-Carlo codes for the criticality studies. MORET IV is especially concerned. With multigroup approximations, the anisotropy equations are very irregular and show quick variations. In a Monte-Carlo codes, they are estimated only by the first coefficients of Legendre polynomials development. Many methods have been characterised using variable number of these coefficients, allowing their reconstruction. So reference representations were defined. Thus they showed that the approximation by only one Dirac could lead to a reactivity under-evaluations. Referring to these representations, new methods have been introduced in MORET IV and instructions have been proposed. Two methods (the correlated samples method and the derivatives sampling method) have been studied to define the divergence between two closely configurations result. A few variance formula of the collision density variation for an infinite medium to an energy group, have been established. These formula have been perfected by simulation for a finite medium. (A.L.B.)

  18. 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

  19. 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)

  20. Burnup calculation methodology in the serpent 2 Monte Carlo code

    International Nuclear Information System (INIS)

    Leppaenen, J.; Isotalo, A.

    2012-01-01

    This paper presents two topics related to the burnup calculation capabilities in the Serpent 2 Monte Carlo code: advanced time-integration methods and improved memory management, accomplished by the use of different optimization modes. The development of the introduced methods is an important part of re-writing the Serpent source code, carried out for the purpose of extending the burnup calculation capabilities from 2D assembly-level calculations to large 3D reactor-scale problems. The progress is demonstrated by repeating a PWR test case, originally carried out in 2009 for the validation of the newly-implemented burnup calculation routines in Serpent 1. (authors)