Vectorizing and macrotasking Monte Carlo neutral particle algorithms

International Nuclear Information System (INIS)

Heifetz, D.B.

1987-04-01

Monte Carlo algorithms for computing neutral particle transport in plasmas have been vectorized and macrotasked. The techniques used are directly applicable to Monte Carlo calculations of neutron and photon transport, and Monte Carlo integration schemes in general. A highly vectorized code was achieved by calculating test flight trajectories in loops over arrays of flight data, isolating the conditional branches to as few a number of loops as possible. A number of solutions are discussed to the problem of gaps appearing in the arrays due to completed flights, which impede vectorization. A simple and effective implementation of macrotasking is achieved by dividing the calculation of the test flight profile among several processors. A tree of random numbers is used to ensure reproducible results. The additional memory required for each task may preclude using a larger number of tasks. In future machines, the limit of macrotasking may be possible, with each test flight, and split test flight, being a separate task

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

CERN Document Server

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

2001-01-01

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

Efficiencies of dynamic Monte Carlo algorithms for off-lattice particle systems with a single impurity

KAUST Repository

Novotny, M.A.; Watanabe, Hiroshi; Ito, Nobuyasu

2010-01-01

The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing

Monte Carlo simulations of the Galileo energetic particle detector

CERN Document Server

Jun, I; Garrett, H B; McEntire, R W

2002-01-01

Monte Carlo radiation transport studies have been performed for the Galileo spacecraft energetic particle detector (EPD) in order to study its response to energetic electrons and protons. Three-dimensional Monte Carlo radiation transport codes, MCNP version 4B (for electrons) and MCNPX version 2.2.3 (for protons), were used throughout the study. The results are presented in the form of 'geometric factors' for the high-energy channels studied in this paper: B1, DC2, and DC3 for electrons and B0, DC0, and DC1 for protons. The geometric factor is the energy-dependent detector response function that relates the incident particle fluxes to instrument count rates. The trend of actual data measured by the EPD was successfully reproduced using the geometric factors obtained in this study.

Monte Carlo simulations of the Galileo energetic particle detector

International Nuclear Information System (INIS)

Jun, I.; Ratliff, J.M.; Garrett, H.B.; McEntire, R.W.

2002-01-01

Monte Carlo radiation transport studies have been performed for the Galileo spacecraft energetic particle detector (EPD) in order to study its response to energetic electrons and protons. Three-dimensional Monte Carlo radiation transport codes, MCNP version 4B (for electrons) and MCNPX version 2.2.3 (for protons), were used throughout the study. The results are presented in the form of 'geometric factors' for the high-energy channels studied in this paper: B1, DC2, and DC3 for electrons and B0, DC0, and DC1 for protons. The geometric factor is the energy-dependent detector response function that relates the incident particle fluxes to instrument count rates. The trend of actual data measured by the EPD was successfully reproduced using the geometric factors obtained in this study

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)

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

PEREGRINE: An all-particle Monte Carlo code for radiation therapy

International Nuclear Information System (INIS)

Hartmann Siantar, C.L.; Chandler, W.P.; Rathkopf, J.A.; Svatos, M.M.; White, R.M.

1994-09-01

The goal of radiation therapy is to deliver a lethal dose to the tumor while minimizing the dose to normal tissues. To carry out this task, it is critical to calculate correctly the distribution of dose delivered. Monte Carlo transport methods have the potential to provide more accurate prediction of dose distributions than currently-used methods. PEREGRINE is a new Monte Carlo transport code developed at Lawrence Livermore National Laboratory for the specific purpose of modeling the effects of radiation therapy. PEREGRINE transports neutrons, photons, electrons, positrons, and heavy charged-particles, including protons, deuterons, tritons, helium-3, and alpha particles. This paper describes the PEREGRINE transport code and some preliminary results for clinically relevant materials and radiation sources

Data decomposition of Monte Carlo particle transport simulations via tally servers

International Nuclear Information System (INIS)

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

2013-01-01

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

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

Chain segmentation for the Monte Carlo solution of particle transport problems

International Nuclear Information System (INIS)

Ragheb, M.M.H.

1984-01-01

A Monte Carlo approach is proposed where the random walk chains generated in particle transport simulations are segmented. Forward and adjoint-mode estimators are then used in conjunction with the firstevent source density on the segmented chains to obtain multiple estimates of the individual terms of the Neumann series solution at each collision point. The solution is then constructed by summation of the series. The approach is compared to the exact analytical and to the Monte Carlo nonabsorption weighting method results for two representative slowing down and deep penetration problems. Application of the proposed approach leads to unbiased estimates for limited numbers of particle simulations and is useful in suppressing an effective bias problem observed in some cases of deep penetration particle transport problems

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...

Efficiencies of dynamic Monte Carlo algorithms for off-lattice particle systems with a single impurity

KAUST Repository

Novotny, M.A.

2010-02-01

The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing Markov Chains method are given. Simulation results are presented to confirm the theoretical efficiencies. © 2010.

(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.

Monte Carlo simulation of particle-induced bit upsets

Science.gov (United States)

Wrobel, Frédéric; Touboul, Antoine; Vaillé, Jean-Roch; Boch, Jérôme; Saigné, Frédéric

2017-09-01

We investigate the issue of radiation-induced failures in electronic devices by developing a Monte Carlo tool called MC-Oracle. It is able to transport the particles in device, to calculate the energy deposited in the sensitive region of the device and to calculate the transient current induced by the primary particle and the secondary particles produced during nuclear reactions. We compare our simulation results with SRAM experiments irradiated with neutrons, protons and ions. The agreement is very good and shows that it is possible to predict the soft error rate (SER) for a given device in a given environment.

Monte Carlo simulation of particle-induced bit upsets

Directory of Open Access Journals (Sweden)

Wrobel Frédéric

2017-01-01

Full Text Available We investigate the issue of radiation-induced failures in electronic devices by developing a Monte Carlo tool called MC-Oracle. It is able to transport the particles in device, to calculate the energy deposited in the sensitive region of the device and to calculate the transient current induced by the primary particle and the secondary particles produced during nuclear reactions. We compare our simulation results with SRAM experiments irradiated with neutrons, protons and ions. The agreement is very good and shows that it is possible to predict the soft error rate (SER for a given device in a given environment.

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

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

Monte carlo simulation for soot dynamics

KAUST Repository

Zhou, Kun

2012-01-01

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

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)

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)

The OpenMC Monte Carlo particle transport code

International Nuclear Information System (INIS)

Romano, Paul K.; Forget, Benoit

2013-01-01

Highlights: ► An open source Monte Carlo particle transport code, OpenMC, has been developed. ► Solid geometry and continuous-energy physics allow high-fidelity simulations. ► Development has focused on high performance and modern I/O techniques. ► OpenMC is capable of scaling up to hundreds of thousands of processors. ► Results on a variety of benchmark problems agree with MCNP5. -- Abstract: A new Monte Carlo code called OpenMC is currently under development at the Massachusetts Institute of Technology as a tool for simulation on high-performance computing platforms. Given that many legacy codes do not scale well on existing and future parallel computer architectures, OpenMC has been developed from scratch with a focus on high performance scalable algorithms as well as modern software design practices. The present work describes the methods used in the OpenMC code and demonstrates the performance and accuracy of the code on a variety of problems.

A Monte Carlo Sampling Technique for Multi-phonon Processes

Energy Technology Data Exchange (ETDEWEB)

Hoegberg, Thure

1961-12-15

A sampling technique for selecting scattering angle and energy gain in Monte Carlo calculations of neutron thermalization is described. It is supposed that the scattering is separated into processes involving different numbers of phonons. The number of phonons involved is first determined. Scattering angle and energy gain are then chosen by using special properties of the multi-phonon term.

Randomly dispersed particle fuel model in the PSG Monte Carlo neutron transport code

International Nuclear Information System (INIS)

Leppaenen, J.

2007-01-01

High-temperature gas-cooled reactor fuels are composed of thousands of microscopic fuel particles, randomly dispersed in a graphite matrix. The modelling of such geometry is complicated, especially using continuous-energy Monte Carlo codes, which are unable to apply any deterministic corrections in the calculation. This paper presents the geometry routine developed for modelling randomly dispersed particle fuels using the PSG Monte Carlo reactor physics code. The model is based on the delta-tracking method, and it takes into account the spatial self-shielding effects and the random dispersion of the fuel particles. The calculation routine is validated by comparing the results to reference MCNP4C calculations using uranium and plutonium based fuels. (authors)

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

Energy Technology Data Exchange (ETDEWEB)

O' Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2²¹ = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.

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.

Modified Monte Carlo procedure for particle transport problems

International Nuclear Information System (INIS)

Matthes, W.

1978-01-01

The simulation of photon transport in the atmosphere with the Monte Carlo method forms part of the EURASEP-programme. The specifications for the problems posed for a solution were such, that the direct application of the analogue Monte Carlo method was not feasible. For this reason the standard Monte Carlo procedure was modified in the sense that additional properly weighted branchings at each collision and transport process in a photon history were introduced. This modified Monte Carlo procedure leads to a clear and logical separation of the essential parts of a problem and offers a large flexibility for variance reducing techniques. More complex problems, as foreseen in the EURASEP-programme (e.g. clouds in the atmosphere, rough ocean-surface and chlorophyl-distribution in the ocean) can be handled by recoding some subroutines. This collision- and transport-splitting procedure can of course be performed differently in different space- and energy regions. It is applied here only for a homogeneous problem

Parallel processing of Monte Carlo code MCNP for particle transport problem

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Kenji; Kawasaki, Takuji

1996-06-01

It is possible to vectorize or parallelize Monte Carlo codes (MC code) for photon and neutron transport problem, making use of independency of the calculation for each particle. Applicability of existing MC code to parallel processing is mentioned. As for parallel computer, we have used both vector-parallel processor and scalar-parallel processor in performance evaluation. We have made (i) vector-parallel processing of MCNP code on Monte Carlo machine Monte-4 with four vector processors, (ii) parallel processing on Paragon XP/S with 256 processors. In this report we describe the methodology and results for parallel processing on two types of parallel or distributed memory computers. In addition, we mention the evaluation of parallel programming environments for parallel computers used in the present work as a part of the work developing STA (Seamless Thinking Aid) Basic Software. (author)

Design of tallying function for general purpose Monte Carlo particle transport code JMCT

International Nuclear Information System (INIS)

Shangguan Danhua; Li Gang; Deng Li; Zhang Baoyin

2013-01-01

A new postponed accumulation algorithm was proposed. Based on JCOGIN (J combinatorial geometry Monte Carlo transport infrastructure) framework and the postponed accumulation algorithm, the tallying function of the general purpose Monte Carlo neutron-photon transport code JMCT was improved markedly. JMCT gets a higher tallying efficiency than MCNP 4C by 28% for simple geometry model, and JMCT is faster than MCNP 4C by two orders of magnitude for complicated repeated structure model. The available ability of tallying function for JMCT makes firm foundation for reactor analysis and multi-step burnup calculation. (authors)

Implementation of Japanese male and female tomographic phantoms to multi-particle Monte Carlo code for ionizing radiation dosimetry

International Nuclear Information System (INIS)

Lee, Choonsik; Nagaoka, Tomoaki; Lee, Jai-Ki

2006-01-01

Japanese male and female tomographic phantoms, which have been developed for radio-frequency electromagnetic-field dosimetry, were implemented into multi-particle Monte Carlo transport code to evaluate realistic dose distribution in human body exposed to radiation field. Japanese tomographic phantoms, which were developed from the whole body magnetic resonance images of Japanese average adult male and female, were processed as follows to be implemented into general purpose multi-particle Monte Carlo code, MCNPX2.5. Original array size of Japanese male and female phantoms, 320 x 160 x 866 voxels and 320 x 160 x 804 voxels, respectively, were reduced into 320 x 160 x 433 voxels and 320 x 160 x 402 voxels due to the limitation of memory use in MCNPX2.5. The 3D voxel array of the phantoms were processed by using the built-in repeated structure algorithm, where the human anatomy was described by the repeated lattice of tiny cube containing the information of material composition and organ index number. Original phantom data were converted into ASCII file, which can be directly ported into the lattice card of MCNPX2.5 input deck by using in-house code. A total of 30 material compositions obtained from International Commission on Radiation Units and Measurement (ICRU) report 46 were assigned to 54 and 55 organs and tissues in the male and female phantoms, respectively, and imported into the material card of MCNPX2.5 along with the corresponding cross section data. Illustrative calculation of absorbed doses for 26 internal organs and effective dose were performed for idealized broad parallel photon and neutron beams in anterior-posterior irradiation geometry, which is typical for workers at nuclear power plant. The results were compared with the data from other Japanese and Caucasian tomographic phantom, and International Commission on Radiological Protection (ICRP) report 74. The further investigation of the difference in organ dose and effective dose among tomographic

Investigation of pattern recognition techniques for the indentification of splitting surfaces in Monte Carlo particle transport calculations

International Nuclear Information System (INIS)

Macdonald, J.L.

1975-08-01

Statistical and deterministic pattern recognition systems are designed to classify the state space of a Monte Carlo transport problem into importance regions. The surfaces separating the regions can be used for particle splitting and Russian roulette in state space in order to reduce the variance of the Monte Carlo tally. Computer experiments are performed to evaluate the performance of the technique using one and two dimensional Monte Carlo problems. Additional experiments are performed to determine the sensitivity of the technique to various pattern recognition and Monte Carlo problem dependent parameters. A system for applying the technique to a general purpose Monte Carlo code is described. An estimate of the computer time required by the technique is made in order to determine its effectiveness as a variance reduction device. It is recommended that the technique be further investigated in a general purpose Monte Carlo code. (auth)

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.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2000-07-01

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

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

International Nuclear Information System (INIS)

Hoogenboom, J.E.

2000-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-12-01

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

Monte Carlo event generator MCMHA for high energy hadron-nucleus collisions and intranuclear cascade interactions

International Nuclear Information System (INIS)

Iga, Y.; Hamatsu, R.; Yamazaki, S.

1988-01-01

The Monte Carlo event generator for high energy hadron-nucleus (h-A) collisions has been developed which is based on the multi-chain model. The concept of formation zone and the cascade interactions of secondary particles are properly taken into account in this Monte Carlo code. Comparing the results of this code with experimental data, the importance of intranuclear cascade interactions becomes very clear. (orig.)

Monte Carlo simulation of VHTR particle fuel with chord length sampling

International Nuclear Information System (INIS)

Ji, W.; Martin, W. R.

2007-01-01

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

Monte Carlo variance reduction approaches for non-Boltzmann tallies

International Nuclear Information System (INIS)

Booth, T.E.

1992-12-01

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

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

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

International Nuclear Information System (INIS)

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

2016-01-01

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

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-29

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

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

Monte Carlo Methods in ICF

Science.gov (United States)

Zimmerman, George B.

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

Monte Carlo methods in ICF

International Nuclear Information System (INIS)

Zimmerman, George B.

1997-01-01

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

Spot: a new Monte Carlo solver for fast alpha particles

International Nuclear Information System (INIS)

Schneider, M.; Eriksson, L.G.; Basiuk, V.; Imbeaux, F.

2004-01-01

The predictive transport code CRONOS has been augmented by an orbit following Monte Carlo code, SPOT (Simulation of Particle Orbits in a Tokamak). The SPOT code simulates the dynamics of nonthermal particles, and takes into account effects of finite orbit width and collisional transport of fast ions. Recent developments indicate that it might be difficult to avoid, at least transiently, current holes in a reactor. They occur already on existing tokamaks during advanced tokamak scenarios. The SPOT code has been used to study the alpha particle behaviour in the presence of current holes for both JET and ITER relevant parameters. (authors)

Study on Quantification for Multi-unit Seismic PSA Model using Monte Carlo Sampling

International Nuclear Information System (INIS)

Oh, Kyemin; Han, Sang Hoon; Jang, Seung-cheol; Park, Jin Hee; Lim, Ho-Gon; Yang, Joon Eon; Heo, Gyunyoung

2015-01-01

In existing PSA, frequency for accident sequences occurred in single-unit has been estimated. While multi-unit PSA has to consider various combinations because accident sequence in each units can be different. However, it is difficult to quantify all of combination between inter-units using traditional method such as Minimal Cut Upper Bound (MCUB). For this reason, we used Monte Carlo sampling as a method to quantify multi-unit PSA model. In this paper, Monte Carlo method was used to quantify multi-unit PSA model. The advantage of this method is to consider all of combinations by the increase of number of unit and to calculate nearly exact value compared to other method. However, it is difficult to get detailed information such as minimal cut sets and accident sequence. To solve partially this problem, FTeMC was modified. In multi-unit PSA, quantification for both internal and external multi-unit accidents is the significant issue. Although our result above mentioned was one of the case studies to check application of method suggested in this paper, it is expected that this method can be used in practical assessment for multi-unit risk

Monte Carlo simulations of interacting particle mixtures in ratchet potentials

International Nuclear Information System (INIS)

Fendrik, A J; Romanelli, L

2012-01-01

There are different models of devices for achieving a separation of mixtures of particles by using the ratchet effect. On the other hand, it has been proposed that one could also control the separation by means of appropriate interactions. Through Monte Carlo simulations, we show that inclusion of simple interactions leads to a decrease of the ratchet effect and therefore also a separation of the mixtures.

Successful vectorization - reactor physics Monte Carlo code

International Nuclear Information System (INIS)

Martin, W.R.

1989-01-01

Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)

Monte Carlo parametric importance sampling with particle tracks scaling

International Nuclear Information System (INIS)

Ragheb, M.M.H.

1981-01-01

A method for Monte Carlo importance sampling with parametric dependence is proposed. It depends upon obtaining over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adopted and others rejected. The proposed method is applied to the finite slab penetration problem. When the exponential transformation is used, our method involves scaling of the generated particle tracks, and is a new application of Morton's method of similar trajectories. The method constitutes a generalization of Spanier's multistage importance sampling method, obtained by proper weighting over a single stage the curves he obtains over several stages, and preserves the statistical correlations between histories. It represents an extension of a theory by Frolov and Chentsov on Monte Carlo calculations of smooth curves to surfaces and to importance sampling calculations. By the proposed method, it seems possible to systematically arrive at minimum variance results and to avoid the infinite variances and effective biases sometimes observed in this type of calculation. (orig.) [de

New features of the mercury Monte Carlo particle transport code

International Nuclear Information System (INIS)

Procassini, Richard; Brantley, Patrick; Dawson, Shawn

2010-01-01

Several new capabilities have been added to the Mercury Monte Carlo transport code over the past four years. The most important algorithmic enhancement is a general, extensible infrastructure to support source, tally and variance reduction actions. For each action, the user defines a phase space, as well as any number of responses that are applied to a specified event. Tallies are accumulated into a correlated, multi-dimensional. Cartesian-product result phase space. Our approach employs a common user interface to specify the data sets and distributions that define the phase, response and result for each action. Modifications to the particle trackers include the use of facet halos (instead of extrapolative fuzz) for robust tracking, and material interface reconstruction for use in shape overlaid meshes. Support for expected-value criticality eigenvalue calculations has also been implemented. Computer science enhancements include an in-line Python interface for user customization of problem setup and output. (author)

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

International Nuclear Information System (INIS)

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

1987-01-01

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

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

International Nuclear Information System (INIS)

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

1985-12-01

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

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

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.

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

Science.gov (United States)

Crevillén-García, D; Power, H

2017-08-01

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

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

Science.gov (United States)

Crevillén-García, D.; Power, H.

2017-08-01

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

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

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

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

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

2013-07-01

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

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

International Nuclear Information System (INIS)

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

2013-01-01

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

Research on GPU acceleration for Monte Carlo criticality calculation

International Nuclear Information System (INIS)

Xu, Q.; Yu, G.; Wang, K.

2013-01-01

The Monte Carlo (MC) neutron transport method can be naturally parallelized by multi-core architectures due to the dependency between particles during the simulation. The GPU+CPU heterogeneous parallel mode has become an increasingly popular way of parallelism in the field of scientific supercomputing. Thus, this work focuses on the GPU acceleration method for the Monte Carlo criticality simulation, as well as the computational efficiency that GPUs can bring. The 'neutron transport step' is introduced to increase the GPU thread occupancy. In order to test the sensitivity of the MC code's complexity, a 1D one-group code and a 3D multi-group general purpose code are respectively transplanted to GPUs, and the acceleration effects are compared. The result of numerical experiments shows considerable acceleration effect of the 'neutron transport step' strategy. However, the performance comparison between the 1D code and the 3D code indicates the poor scalability of MC codes on GPUs. (authors)

Monte Carlo modeling of Standard Model multi-boson production processes for √s = 13 TeV ATLAS analyses

CERN Document Server

Li, Shu; The ATLAS collaboration

2017-01-01

We present the Monte Carlo(MC) setup used by ATLAS to model multi-boson processes in √s = 13 TeV proton-proton collisions. The baseline Monte Carlo generators are compared with each other in key kinematic distributions of the processes under study. Sample normalization and systematic uncertainties are discussed.

Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

Science.gov (United States)

Buyukada, Musa

2016-09-01

Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached by ANN61 multi-layer perception model with a R(2) of 0.99994. Blend ratio of 90 to 10 (PH to coal, wt%), temperature of 305°C, and heating rate of 49°Cmin(-1) were determined as the optimum input values and yield of 87.4% was obtained under PSO optimized conditions. The validation experiments resulted in yields of 87.5%±0.2 after three replications. Monte Carlo simulations were used for the probabilistic assessments of stochastic variability and uncertainty associated with explanatory variables of co-combustion process. Copyright © 2016 Elsevier Ltd. All rights reserved.

A unified Monte Carlo interpretation of particle simulations and applications to nonneutral plasmas

International Nuclear Information System (INIS)

Aydemir, A.Y.

1993-09-01

Using a ''Monte Carlo interpretation'' a particle simulations, a general description of low-noise techniques is developed in terms well-known Monte Carlo variance reduction methods. Some of these techniques then are applied to linear and nonlinear studies of pure electron plasmas in cylindrical geometry, with emphasis on the generation and nonlinear evolution of electron vortices. Long-lived l = 1 and l and l = 2 vortices, and others produced by unstable diocotron modes in hollow profiles, are studies. It is shown that low-noise techniques make it possible to follow the linear evolution and saturation of even the very weakly unstable resonant diocotron modes

Simple formalism for efficient derivatives and multi-determinant expansions in quantum Monte Carlo

NARCIS (Netherlands)

Filippi, Claudia; Assaraf, R.; Moroni, S.

2016-01-01

We present a simple and general formalism to compute efficiently the derivatives of a multi-determinant Jastrow-Slater wave function, the local energy, the interatomic forces, and similar quantities needed in quantum Monte Carlo. Through a straightforward manipulation of matrices evaluated on the

Characterization of an Ar/O2 magnetron plasma by a multi-species Monte Carlo model

International Nuclear Information System (INIS)

Bultinck, E; Bogaerts, A

2011-01-01

A combined Monte Carlo (MC)/analytical surface model is developed to study the plasma processes occurring during the reactive sputter deposition of TiO x thin films. This model describes the important plasma species with a MC approach (i.e. electrons, Ar + ions, O 2 + ions, fast Ar atoms and sputtered Ti atoms). The deposition of the TiO x film is treated by an analytical surface model. The implementation of our so-called multi-species MC model is presented, and some typical calculation results are shown, such as densities, fluxes, energies and collision rates. The advantages and disadvantages of the multi-species MC model are illustrated by a comparison with a particle-in-cell/Monte Carlo collisions (PIC/MCC) model. Disadvantages include the fact that certain input values and assumptions are needed. However, when these are accounted for, the results are in good agreement with the PIC/MCC simulations, and the calculation time has drastically decreased, which enables us to simulate large and complicated reactor geometries. To illustrate this, the effect of larger target-substrate distances on the film properties is investigated. It is shown that a stoichiometric film is deposited at all investigated target-substrate distances (24, 40, 60 and 80 mm). Moreover, a larger target-substrate distance promotes film uniformity, but the deposition rate is much lower.

A Monte Carlo algorithm for the Vavilov distribution

International Nuclear Information System (INIS)

Yi, Chul-Young; Han, Hyon-Soo

1999-01-01

Using the convolution property of the inverse Laplace transform, an improved Monte Carlo algorithm for the Vavilov energy-loss straggling distribution of the charged particle is developed, which is relatively simple and gives enough accuracy to be used for most Monte Carlo applications

Adaptive multilevel splitting for Monte Carlo particle transport

Directory of Open Access Journals (Sweden)

Louvin Henri

2017-01-01

Full Text Available In the Monte Carlo simulation of particle transport, and especially for shielding applications, variance reduction techniques are widely used to help simulate realisations of rare events and reduce the relative errors on the estimated scores for a given computation time. Adaptive Multilevel Splitting (AMS is one of these variance reduction techniques that has recently appeared in the literature. In the present paper, we propose an alternative version of the AMS algorithm, adapted for the first time to the field of particle transport. Within this context, it can be used to build an unbiased estimator of any quantity associated with particle tracks, such as flux, reaction rates or even non-Boltzmann tallies like pulse-height tallies and other spectra. Furthermore, the efficiency of the AMS algorithm is shown not to be very sensitive to variations of its input parameters, which makes it capable of significant variance reduction without requiring extended user effort.

Review of Monte Carlo methods for particle multiplicity evaluation

CERN Document Server

Armesto-Pérez, Nestor

2005-01-01

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

Review of Monte Carlo methods for particle multiplicity evaluation

International Nuclear Information System (INIS)

Armesto, Nestor

2005-01-01

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

Development of general-purpose particle and heavy ion transport monte carlo code

International Nuclear Information System (INIS)

Iwase, Hiroshi; Nakamura, Takashi; Niita, Koji

2002-01-01

The high-energy particle transport code NMTC/JAM, which has been developed at JAERI, was improved for the high-energy heavy ion transport calculation by incorporating the JQMD code, the SPAR code and the Shen formula. The new NMTC/JAM named PHITS (Particle and Heavy-Ion Transport code System) is the first general-purpose heavy ion transport Monte Carlo code over the incident energies from several MeV/nucleon to several GeV/nucleon. (author)

McSnow: A Monte-Carlo Particle Model for Riming and Aggregation of Ice Particles in a Multidimensional Microphysical Phase Space

Science.gov (United States)

Brdar, S.; Seifert, A.

2018-01-01

We present a novel Monte-Carlo ice microphysics model, McSnow, to simulate the evolution of ice particles due to deposition, aggregation, riming, and sedimentation. The model is an application and extension of the super-droplet method of Shima et al. (2009) to the more complex problem of rimed ice particles and aggregates. For each individual super-particle, the ice mass, rime mass, rime volume, and the number of monomers are predicted establishing a four-dimensional particle-size distribution. The sensitivity of the model to various assumptions is discussed based on box model and one-dimensional simulations. We show that the Monte-Carlo method provides a feasible approach to tackle this high-dimensional problem. The largest uncertainty seems to be related to the treatment of the riming processes. This calls for additional field and laboratory measurements of partially rimed snowflakes.

Monte Carlo techniques for analyzing deep penetration problems

International Nuclear Information System (INIS)

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

1985-01-01

A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. 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 multi-group 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

Monte Carlo techniques for analyzing deep penetration problems

International Nuclear Information System (INIS)

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

1985-01-01

A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. 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 multi-group 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. 29 refs

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.

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

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

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

2011-01-01

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

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

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

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.)

Monte Carlo electron/photon transport

International Nuclear Information System (INIS)

Mack, J.M.; Morel, J.E.; Hughes, H.G.

1985-01-01

A review of nonplasma coupled electron/photon transport using Monte Carlo method is presented. Remarks are mainly restricted to linerarized formalisms at electron energies from 1 keV to 1000 MeV. Applications involving pulse-height estimation, transport in external magnetic fields, and optical Cerenkov production are discussed to underscore the importance of this branch of computational physics. Advances in electron multigroup cross-section generation is reported, and its impact on future code development assessed. Progress toward the transformation of MCNP into a generalized neutral/charged-particle Monte Carlo code is described. 48 refs

Multi-Subband Ensemble Monte Carlo simulations of scaled GAA MOSFETs

Science.gov (United States)

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

2018-05-01

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

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

A Monte Carlo simulation study of associated liquid crystals

Science.gov (United States)

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

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

A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

OpenAIRE

Mendenhall, Marcus H.; Weller, Robert A.

2011-01-01

In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This makes it possible t...

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

Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.

Science.gov (United States)

Florin, Charles; Paragios, Nikos; Williams, Jim

2005-01-01

In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.

Design of sampling tools for Monte Carlo particle transport code JMCT

International Nuclear Information System (INIS)

Shangguan Danhua; Li Gang; Zhang Baoyin; Deng Li

2012-01-01

A class of sampling tools for general Monte Carlo particle transport code JMCT is designed. Two ways are provided to sample from distributions. One is the utilization of special sampling methods for special distribution; the other is the utilization of general sampling methods for arbitrary discrete distribution and one-dimensional continuous distribution on a finite interval. Some open source codes are included in the general sampling method for the maximum convenience of users. The sampling results show sampling correctly from distribution which are popular in particle transport can be achieved with these tools, and the user's convenience can be assured. (authors)

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)

A measure for isotropy-equilibrium degree of a multi-particle system

International Nuclear Information System (INIS)

Liu Zhiqing; Li Runze; Xu Mingmei; Liu Lianshou

2008-01-01

Aiming at using sphericity as a tool to study the isotropy-equilibrium property of a multi-particle system, in particular the hadronic final state IFS produced in instanton-induced DIS events, we discuss in detail the dependence is sphericity on multiplicity and the multiplicity distribution, as well as on the isotropy degree of the system. A rotational symmetric model with a fluctuating isotropy-degree is constructed, which can fit the mean and width of sphericity of the Monte Carlo IFS-results simultaneously. The IFS from the Monte Carlo simulation is found to be not ideally isotropic but has a probability of 4.7% to be isotropic within error of 5%. The results provide us a description of how far the IFS departs from equilibrium. The method developed is applicable to any Monte Carlo generated multi-particle system, for which the isotropy-equilibrium property is significant. (authors)

Monte Carlo methods

Directory of Open Access Journals (Sweden)

Bardenet Rémi

2013-07-01

Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.

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

Automated Monte Carlo biasing for photon-generated electrons near surfaces.

Energy Technology Data Exchange (ETDEWEB)

Franke, Brian Claude; Crawford, Martin James; Kensek, Ronald Patrick

2009-09-01

This report describes efforts to automate the biasing of coupled electron-photon Monte Carlo particle transport calculations. The approach was based on weight-windows biasing. Weight-window settings were determined using adjoint-flux Monte Carlo calculations. A variety of algorithms were investigated for adaptivity of the Monte Carlo tallies. Tree data structures were used to investigate spatial partitioning. Functional-expansion tallies were used to investigate higher-order spatial representations.

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

Verification and Validation of Monte Carlo n-Particle Code 6 (MCNP6) with Neutron Protection Factor Measurements of an Iron Box

Science.gov (United States)

2014-03-27

Vehicle Code System (VCS), the Monte Carlo Adjoint SHielding (MASH), and the Monte Carlo n- Particle ( MCNP ) code. Of the three, the oldest and still most...widely utilized radiation transport code is MCNP . First created at Los Alamos National Laboratory (LANL) in 1957, the code simulated neutral...particle types, and previous versions of MCNP were repeatedly validated using both simple and complex 10 geometries [12, 13]. Much greater discussion and

A 3D particle Monte Carlo approach to studying nucleation

DEFF Research Database (Denmark)

Köhn, Christoph; Bødker Enghoff, Martin; Svensmark, Henrik

2018-01-01

The nucleation of sulphuric acid molecules plays a key role in the formation of aerosols. We here present a three dimensional particle Monte Carlo model to study the growth of sulphuric acid clusters as well as its dependence on the ambient temperature and the initial particle density. We initiate...... a swarm of sulphuric acid–water clusters with a size of 0.329 nm with densities between 107 and and 108 cm-3 at temperatures between 200 and 300 K and a relative humidity of 50%. After every time step, we update the position of particles as a function of size-dependent diffusion coefficients. If two...... particles encounter, we merge them and add their volumes and masses. Inversely, we check after every time step whether a polymer evaporates liberating a molecule. We present the spatial distribution as well as the size distribution calculated from individual clusters. We also calculate the nucleation rate...

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)

Monte Carlo dose distributions for radiosurgery

International Nuclear Information System (INIS)

Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E.

2001-01-01

The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)

A continuation multilevel Monte Carlo algorithm

KAUST Repository

Collier, Nathan; Haji Ali, Abdul Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul

2014-01-01

We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

Science.gov (United States)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

An Overview of the Monte Carlo Application ToolKit (MCATK)

Energy Technology Data Exchange (ETDEWEB)

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

2016-01-07

MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library designed to build specialized applications and designed to provide new functionality in existing general-purpose Monte Carlo codes like MCNP; it was developed with Agile software engineering methodologies under the motivation to reduce costs. The characteristics of MCATK can be summarized as follows: MCATK physics – continuous energy neutron-gamma transport with multi-temperature treatment, static eigenvalue (k and α) algorithms, time-dependent algorithm, fission chain algorithms; MCATK geometry – mesh geometries, solid body geometries. MCATK provides verified, unit-tested Monte Carlo components, flexibility in Monte Carlo applications development, and numerous tools such as geometry and cross section plotters. Recent work has involved deterministic and Monte Carlo analysis of stochastic systems. Static and dynamic analysis is discussed, and the results of a dynamic test problem are given.

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

Modification to the Monte Carlo N-Particle (MCNP) Visual Editor (MCNPVised) to Read in Computer Aided Design (CAD) Files

International Nuclear Information System (INIS)

Randolph Schwarz; Leland L. Carter; Alysia Schwarz

2005-01-01

Monte Carlo N-Particle Transport Code (MCNP) is the code of choice for doing complex neutron/photon/electron transport calculations for the nuclear industry and research institutions. The Visual Editor for Monte Carlo N-Particle is internationally recognized as the best code for visually creating and graphically displaying input files for MCNP. The work performed in this grant was used to enhance the capabilities of the MCNP Visual Editor to allow it to read in both 2D and 3D Computer Aided Design (CAD) files, allowing the user to electronically generate a valid MCNP input geometry

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

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

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

Specialized Monte Carlo codes versus general-purpose Monte Carlo codes

International Nuclear Information System (INIS)

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

2002-01-01

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

Performance of quantum Monte Carlo for calculating molecular bond lengths

Energy Technology Data Exchange (ETDEWEB)

Cleland, Deidre M., E-mail: deidre.cleland@csiro.au; Per, Manolo C., E-mail: manolo.per@csiro.au [CSIRO Virtual Nanoscience Laboratory, 343 Royal Parade, Parkville, Victoria 3052 (Australia)

2016-03-28

This work investigates the accuracy of real-space quantum Monte Carlo (QMC) methods for calculating molecular geometries. We present the equilibrium bond lengths of a test set of 30 diatomic molecules calculated using variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods. The effect of different trial wavefunctions is investigated using single determinants constructed from Hartree-Fock (HF) and Density Functional Theory (DFT) orbitals with LDA, PBE, and B3LYP functionals, as well as small multi-configurational self-consistent field (MCSCF) multi-determinant expansions. When compared to experimental geometries, all DMC methods exhibit smaller mean-absolute deviations (MADs) than those given by HF, DFT, and MCSCF. The most accurate MAD of 3 ± 2 × 10{sup −3} Å is achieved using DMC with a small multi-determinant expansion. However, the more computationally efficient multi-determinant VMC method has a similar MAD of only 4.0 ± 0.9 × 10{sup −3} Å, suggesting that QMC forces calculated from the relatively simple VMC algorithm may often be sufficient for accurate molecular geometries.

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.

Particle-In-Cell/Monte Carlo Simulation of Ion Back Bombardment in Photoinjectors

International Nuclear Information System (INIS)

Qiang, Ji; Corlett, John; Staples, John

2009-01-01

In this paper, we report on studies of ion back bombardment in high average current dc and rf photoinjectors using a particle-in-cell/Monte Carlo method. Using H 2 ion as an example, we observed that the ion density and energy deposition on the photocathode in rf guns are order of magnitude lower than that in a dc gun. A higher rf frequency helps mitigate the ion back bombardment of the cathode in rf guns

Introduction to the Latest Version of the Test-Particle Monte Carlo Code Molflow+

CERN Document Server

Ady, M

2014-01-01

The Test-Particle Monte Carlo code Molflow+ is getting more and more attention from the scientific community needing detailed 3D calculations of vacuum in the molecular flow regime mainly, but not limited to, the particle accelerator field. Substantial changes, bug fixes, geometry-editing and modelling features, and computational speed improvements have been made to the code in the last couple of years. This paper will outline some of these new features, and show examples of applications to the design and analysis of vacuum systems at CERN and elsewhere.

Antiproton annihilation physics annihilation physics in the Monte Carlo particle transport code particle transport code SHIELD-HIT12A

DEFF Research Database (Denmark)

Taasti, Vicki Trier; Knudsen, Helge; Holzscheiter, Michael

2015-01-01

The Monte Carlo particle transport code SHIELD-HIT12A is designed to simulate therapeutic beams for cancer radiotherapy with fast ions. SHIELD-HIT12A allows creation of antiproton beam kernels for the treatment planning system TRiP98, but first it must be benchmarked against experimental data. An...

Monte Carlo simulation based reliability evaluation in a multi-bilateral contracts market

International Nuclear Information System (INIS)

Goel, L.; Viswanath, P.A.; Wang, P.

2004-01-01

This paper presents a time sequential Monte Carlo simulation technique to evaluate customer load point reliability in multi-bilateral contracts market. The effects of bilateral transactions, reserve agreements, and the priority commitments of generating companies on customer load point reliability have been investigated. A generating company with bilateral contracts is modelled as an equivalent time varying multi-state generation (ETMG). A procedure to determine load point reliability based on ETMG has been developed. The developed procedure is applied to a reliability test system to illustrate the technique. Representing each bilateral contract by an ETMG provides flexibility in determining the reliability at various customer load points. (authors)

Initial Assessment of Parallelization of Monte Carlo Calculation using Graphics Processing Units

International Nuclear Information System (INIS)

Choi, Sung Hoon; Joo, Han Gyu

2009-01-01

Monte Carlo (MC) simulation is an effective tool for calculating neutron transports in complex geometry. However, because Monte Carlo simulates each neutron behavior one by one, it takes a very long computing time if enough neutrons are used for high precision of calculation. Accordingly, methods that reduce the computing time are required. In a Monte Carlo code, parallel calculation is well-suited since it simulates the behavior of each neutron independently and thus parallel computation is natural. The parallelization of the Monte Carlo codes, however, was done using multi CPUs. By the global demand for high quality 3D graphics, the Graphics Processing Unit (GPU) has developed into a highly parallel, multi-core processor. This parallel processing capability of GPUs can be available to engineering computing once a suitable interface is provided. Recently, NVIDIA introduced CUDATM, a general purpose parallel computing architecture. CUDA is a software environment that allows developers to manage GPU using C/C++ or other languages. In this work, a GPU-based Monte Carlo is developed and the initial assessment of it parallel performance is investigated

Monte Carlo simulations of the particle transport in semiconductor detectors of fast neutrons

International Nuclear Information System (INIS)

Sedlačková, Katarína; Zaťko, Bohumír; Šagátová, Andrea; Nečas, Vladimír

2013-01-01

Several Monte Carlo all-particle transport codes are under active development around the world. In this paper we focused on the capabilities of the MCNPX code (Monte Carlo N-Particle eXtended) to follow the particle transport in semiconductor detector of fast neutrons. Semiconductor detector based on semi-insulating GaAs was the object of our investigation. As converter material capable to produce charged particles from the (n, p) interaction, a high-density polyethylene (HDPE) was employed. As the source of fast neutrons, the 239 Pu–Be neutron source was used in the model. The simulations were performed using the MCNPX code which makes possible to track not only neutrons but also recoiled protons at all interesting energies. Hence, the MCNPX code enables seamless particle transport and no other computer program is needed to process the particle transport. The determination of the optimal thickness of the conversion layer and the minimum thickness of the active region of semiconductor detector as well as the energy spectra simulation were the principal goals of the computer modeling. Theoretical detector responses showed that the best detection efficiency can be achieved for 500 μm thick HDPE converter layer. The minimum detector active region thickness has been estimated to be about 400 μm. -- Highlights: ► Application of the MCNPX code for fast neutron detector design is demonstrated. ► Simulations of the particle transport through conversion film of HDPE are presented. ► Simulations of the particle transport through detector active region are presented. ► The optimal thickness of the HDPE conversion film has been calculated. ► Detection efficiency of 0.135% was reached for 500 μm thick HDPE conversion film

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.

Monte Carlo simulation applied to alpha spectrometry

International Nuclear Information System (INIS)

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

2007-01-01

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

Simulation of transport equations with Monte Carlo

International Nuclear Information System (INIS)

Matthes, W.

1975-09-01

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

Creating and using a type of free-form geometry in Monte Carlo particle transport

International Nuclear Information System (INIS)

Wessol, D.E.; Wheeler, F.J.

1993-01-01

While the reactor physicists were fine-tuning the Monte Carlo paradigm for particle transport in regular geometries, the computer scientists were developing rendering algorithms to display extremely realistic renditions of irregular objects ranging from the ubiquitous teakettle to dynamic Jell-O. Even though the modeling methods share a common basis, the initial strategies each discipline developed for variance reduction were remarkably different. Initially, the reactor physicist used Russian roulette, importance sampling, particle splitting, and rejection techniques. In the early stages of development, the computer scientist relied primarily on rejection techniques, including a very elegant hierarchical construction and sampling method. This sampling method allowed the computer scientist to viably track particles through irregular geometries in three-dimensional space, while the initial methods developed by the reactor physicists would only allow for efficient searches through analytical surfaces or objects. As time goes by, it appears there has been some merging of the variance reduction strategies between the two disciplines. This is an early (possibly first) incorporation of geometric hierarchical construction and sampling into the reactor physicists' Monte Carlo transport model that permits efficient tracking through nonuniform rational B-spline surfaces in three-dimensional space. After some discussion, the results from this model are compared with experiments and the model employing implicit (analytical) geometric representation

Self-learning Monte Carlo (dynamical biasing)

International Nuclear Information System (INIS)

Matthes, W.

1981-01-01

In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)

A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

Energy Technology Data Exchange (ETDEWEB)

Mendenhall, Marcus H., E-mail: marcus.h.mendenhall@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States); Weller, Robert A., E-mail: robert.a.weller@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States)

2012-03-01

In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10{sup 4} (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).

A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

International Nuclear Information System (INIS)

Mendenhall, Marcus H.; Weller, Robert A.

2012-01-01

In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10 4 (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

Science.gov (United States)

Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric

2017-12-01

This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-04-15

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-04-01

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

Importance estimation in Monte Carlo modelling of neutron and photon transport

International Nuclear Information System (INIS)

Mickael, M.W.

1992-01-01

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

Development of Monte Carlo decay gamma-ray transport calculation system

Energy Technology Data Exchange (ETDEWEB)

Sato, Satoshi [Japan Atomic Energy Research Inst., Naka, Ibaraki (Japan). Naka Fusion Research Establishment; Kawasaki, Nobuo [Fujitsu Ltd., Tokyo (Japan); Kume, Etsuo [Japan Atomic Energy Research Inst., Center for Promotion of Computational Science and Engineering, Tokai, Ibaraki (Japan)

2001-06-01

In the DT fusion reactor, it is critical concern to evaluate the decay gamma-ray biological dose rates after the reactor shutdown exactly. In order to evaluate the decay gamma-ray biological dose rates exactly, three dimensional Monte Carlo decay gamma-ray transport calculation system have been developed by connecting the three dimensional Monte Carlo particle transport calculation code and the induced activity calculation code. The developed calculation system consists of the following four functions. (1) The operational neutron flux distribution is calculated by the three dimensional Monte Carlo particle transport calculation code. (2) The induced activities are calculated by the induced activity calculation code. (3) The decay gamma-ray source distribution is obtained from the induced activities. (4) The decay gamma-rays are generated by using the decay gamma-ray source distribution, and the decay gamma-ray transport calculation is conducted by the three dimensional Monte Carlo particle transport calculation code. In order to reduce the calculation time drastically, a biasing system for the decay gamma-ray source distribution has been developed, and the function is also included in the present system. In this paper, the outline and the detail of the system, and the execution example are reported. The evaluation for the effect of the biasing system is also reported. (author)

A kinetic theory for nonanalog Monte Carlo particle transport algorithms: Exponential transform with angular biasing in planar-geometry anisotropically scattering media

International Nuclear Information System (INIS)

Ueki, T.; Larsen, E.W.

1998-01-01

The authors show that Monte Carlo simulations of neutral particle transport in planargeometry anisotropically scattering media, using the exponential transform with angular biasing as a variance reduction device, are governed by a new Boltzman Monte Carlo (BMC) equation, which includes particle weight as an extra independent variable. The weight moments of the solution of the BMC equation determine the moments of the score and the mean number of collisions per history in the nonanalog Monte Carlo simulations. Therefore, the solution of the BMC equation predicts the variance of the score and the figure of merit in the simulation. Also, by (1) using an angular biasing function that is closely related to the ''asymptotic'' solution of the linear Boltzman equation and (2) requiring isotropic weight changes as collisions, they derive a new angular biasing scheme. Using the BMC equation, they propose a universal ''safe'' upper limit of the transform parameter, valid for any type of exponential transform. In numerical calculations, they demonstrate that the behavior of the Monte Carlo simulations and the performance predicted by deterministically solving the BMC equation agree well, and that the new angular biasing scheme is always advantageous

Calculation of absorbed fractions to human skeletal tissues due to alpha particles using the Monte Carlo and 3-d chord-based transport techniques

Energy Technology Data Exchange (ETDEWEB)

Hunt, J.G. [Institute of Radiation Protection and Dosimetry, Av. Salvador Allende s/n, Recreio, Rio de Janeiro, CEP 22780-160 (Brazil); Watchman, C.J. [Department of Radiation Oncology, University of Arizona, Tucson, AZ, 85721 (United States); Bolch, W.E. [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL, 32611 (United States); Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611 (United States)

2007-07-01

Absorbed fraction (AF) calculations to the human skeletal tissues due to alpha particles are of interest to the internal dosimetry of occupationally exposed workers and members of the public. The transport of alpha particles through the skeletal tissue is complicated by the detailed and complex microscopic histology of the skeleton. In this study, both Monte Carlo and chord-based techniques were applied to the transport of alpha particles through 3-D micro-CT images of the skeletal microstructure of trabecular spongiosa. The Monte Carlo program used was 'Visual Monte Carlo-VMC'. VMC simulates the emission of the alpha particles and their subsequent energy deposition track. The second method applied to alpha transport is the chord-based technique, which randomly generates chord lengths across bone trabeculae and the marrow cavities via alternate and uniform sampling of their cumulative density functions. This paper compares the AF of energy to two radiosensitive skeletal tissues, active marrow and shallow active marrow, obtained with these two techniques. (authors)

Decomposition of a laser-Doppler spectrum for estimation of speed distribution of particles moving in an optically turbid medium: Monte Carlo validation study

International Nuclear Information System (INIS)

Liebert, A; Zolek, N; Maniewski, R

2006-01-01

A method for measurement of distribution of speed of particles moving in an optically turbid medium is presented. The technique is based on decomposition of the laser-Doppler spectrum. The theoretical background is shown together with the results of Monte Carlo simulations, which were performed to validate the proposed method. The laser-Doppler spectra were obtained by Monte Carlo simulations for assumed uniform and Gaussian speed distributions of particles moving in the turbid medium. The Doppler shift probability distributions were calculated by Monte Carlo simulations for several anisotropy factors of the medium, assuming the Hanyey-Greenstein phase function. The results of the spectra decomposition show that the calculated speed distribution of moving particles match well the distribution assumed for Monte Carlo simulations. This result was obtained for the spectra simulated in optical conditions, in which the photon is scattered with the Doppler shift not more than once during its travel between the source and detector. Influence of multiple scattering of the photon is analysed and a perspective of spectrum decomposition under such conditions is considered. Potential applications and limitations of the method are discussed

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...

The application of weight windows to 'Global' Monte Carlo problems

International Nuclear Information System (INIS)

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

2009-01-01

This paper describes two basic types of global deep-penetration (shielding) problems-the global flux problem and the global response problem. For each of these, two methods for generating weight windows are presented. The first approach, developed by the authors of this paper and referred to generally as the Global Weight Window, constructs a weight window that distributes Monte Carlo particles according to a user-specified distribution. The second approach, developed at Oak Ridge National Laboratory and referred to as FW-CADIS, constructs a weight window based on intuitively extending the concept of the source-detector problem to global problems. The numerical results confirm that the theory used to describe the Monte Carlo particle distribution for a given weight window is valid and that the figure of merit is strongly correlated to the Monte Carlo particle distribution. Furthermore, they illustrate that, while both methods are capable of obtaining the correct solution, the Global Weight Window distributes particles much more uniformly than FW-CADIS. As a result, the figure of merit is higher for the Global Weight Window. (authors)

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

Unbiased estimators of coincidence and correlation in non-analogous Monte Carlo particle transport

International Nuclear Information System (INIS)

Szieberth, M.; Kloosterman, J.L.

2014-01-01

Highlights: • The history splitting method was developed for non-Boltzmann Monte Carlo estimators. • The method allows variance reduction for pulse-height and higher moment estimators. • It works in highly multiplicative problems but Russian roulette has to be replaced. • Estimation of higher moments allows the simulation of neutron noise measurements. • Biased sampling of fission helps the effective simulation of neutron noise methods. - Abstract: The conventional non-analogous Monte Carlo methods are optimized to preserve the mean value of the distributions. Therefore, they are not suited to non-Boltzmann problems such as the estimation of coincidences or correlations. This paper presents a general method called history splitting for the non-analogous estimation of such quantities. The basic principle of the method is that a non-analogous particle history can be interpreted as a collection of analogous histories with different weights according to the probability of their realization. Calculations with a simple Monte Carlo program for a pulse-height-type estimator prove that the method is feasible and provides unbiased estimation. Different variance reduction techniques have been tried with the method and Russian roulette turned out to be ineffective in high multiplicity systems. An alternative history control method is applied instead. Simulation results of an auto-correlation (Rossi-α) measurement show that even the reconstruction of the higher moments is possible with the history splitting method, which makes the simulation of neutron noise measurements feasible

Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox

DEFF Research Database (Denmark)

Nonejad, Nima

This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast...... and efficient framework for estimation. These advantages are used to for instance estimate stochastic volatility models with leverage effect or with Student-t distributed errors. We also model changing time series characteristics of the US inflation rate by considering a heteroskedastic ARFIMA model where...

Monte Carlo simulation of experiments

International Nuclear Information System (INIS)

Opat, G.I.

1977-07-01

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

Monte Carlo Numerical Models for Nuclear Logging Applications

Directory of Open Access Journals (Sweden)

Fusheng Li

2012-06-01

Full Text Available Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting. Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models

Analysis of error in Monte Carlo transport calculations

International Nuclear Information System (INIS)

Booth, T.E.

1979-01-01

The Monte Carlo method for neutron transport calculations suffers, in part, because of the inherent statistical errors associated with the method. Without an estimate of these errors in advance of the calculation, it is difficult to decide what estimator and biasing scheme to use. Recently, integral equations have been derived that, when solved, predicted errors in Monte Carlo calculations in nonmultiplying media. The present work allows error prediction in nonanalog Monte Carlo calculations of multiplying systems, even when supercritical. Nonanalog techniques such as biased kernels, particle splitting, and Russian Roulette are incorporated. Equations derived here allow prediction of how much a specific variance reduction technique reduces the number of histories required, to be weighed against the change in time required for calculation of each history. 1 figure, 1 table

Fundamentals of Monte Carlo

International Nuclear Information System (INIS)

Wollaber, Allan Benton

2016-01-01

This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

Fundamentals of Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-16

This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

Novel hybrid Monte Carlo/deterministic technique for shutdown dose rate analyses of fusion energy systems

International Nuclear Information System (INIS)

Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; Grove, Robert E.

2014-01-01

Highlights: •Develop the novel Multi-Step CADIS (MS-CADIS) hybrid Monte Carlo/deterministic method for multi-step shielding analyses. •Accurately calculate shutdown dose rates using full-scale Monte Carlo models of fusion energy systems. •Demonstrate the dramatic efficiency improvement of the MS-CADIS method for the rigorous two step calculations of the shutdown dose rate in fusion reactors. -- Abstract: The rigorous 2-step (R2S) computational system uses three-dimensional Monte Carlo transport simulations to calculate the shutdown dose rate (SDDR) in fusion reactors. Accurate full-scale R2S calculations are impractical in fusion reactors because they require calculating space- and energy-dependent neutron fluxes everywhere inside the reactor. The use of global Monte Carlo variance reduction techniques was suggested for accelerating the R2S neutron transport calculation. However, the prohibitive computational costs of these approaches, which increase with the problem size and amount of shielding materials, inhibit their ability to accurately predict the SDDR in fusion energy systems using full-scale modeling of an entire fusion plant. This paper describes a novel hybrid Monte Carlo/deterministic methodology that uses the Consistent Adjoint Driven Importance Sampling (CADIS) method but focuses on multi-step shielding calculations. The Multi-Step CADIS (MS-CADIS) methodology speeds up the R2S neutron Monte Carlo calculation using an importance function that represents the neutron importance to the final SDDR. Using a simplified example, preliminary results showed that the use of MS-CADIS enhanced the efficiency of the neutron Monte Carlo simulation of an SDDR calculation by a factor of 550 compared to standard global variance reduction techniques, and that the efficiency enhancement compared to analog Monte Carlo is higher than a factor of 10,000

Systematic vacuum study of the ITER model cryopump by test particle Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Luo, Xueli; Haas, Horst; Day, Christian [Institute for Technical Physics, Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe (Germany)

2011-07-01

The primary pumping systems on the ITER torus are based on eight tailor-made cryogenic pumps because not any standard commercial vacuum pump can meet the ITER working criteria. This kind of cryopump can provide high pumping speed, especially for light gases, by the cryosorption on activated charcoal at 4.5 K. In this paper we will present the systematic Monte Carlo simulation results of the model pump in a reduced scale by ProVac3D, a new Test Particle Monte Carlo simulation program developed by KIT. The simulation model has included the most important mechanical structures such as sixteen cryogenic panels working at 4.5 K, the 80 K radiation shield envelope with baffles, the pump housing, inlet valve and the TIMO (Test facility for the ITER Model Pump) test facility. Three typical gas species, i.e., deuterium, protium and helium are simulated. The pumping characteristics have been obtained. The result is in good agreement with the experiment data up to the gas throughput of 1000 sccm, which marks the limit for free molecular flow. This means that ProVac3D is a useful tool in the design of the prototype cryopump of ITER. Meanwhile, the capture factors at different critical positions are calculated. They can be used as the important input parameters for a follow-up Direct Simulation Monte Carlo (DSMC) simulation for higher gas throughput.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

Science.gov (United States)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with

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

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

International Nuclear Information System (INIS)

Noack, K.

1982-01-01

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

Study on random number generator in Monte Carlo code

International Nuclear Information System (INIS)

Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi

2011-01-01

The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)

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.

On the use of stochastic approximation Monte Carlo for Monte Carlo integration

KAUST Repository

Liang, Faming

2009-03-01

The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.

On the use of stochastic approximation Monte Carlo for Monte Carlo integration

KAUST Repository

Liang, Faming

2009-01-01

The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration

Simple formalism for efficient derivatives and multi-determinant expansions in quantum Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Filippi, Claudia, E-mail: c.filippi@utwente.nl [MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Assaraf, Roland, E-mail: assaraf@lct.jussieu.fr [Sorbonne Universités, UPMC Univ Paris 06, CNRS, Laboratoire de Chimie Théorique CC 137-4, place Jussieu F-75252 Paris Cedex 05 (France); Moroni, Saverio, E-mail: moroni@democritos.it [CNR-IOM DEMOCRITOS, Istituto Officina dei Materiali, and SISSA Scuola Internazionale Superiore di Studi Avanzati, Via Bonomea 265, I-34136 Trieste (Italy)

2016-05-21

We present a simple and general formalism to compute efficiently the derivatives of a multi-determinant Jastrow-Slater wave function, the local energy, the interatomic forces, and similar quantities needed in quantum Monte Carlo. Through a straightforward manipulation of matrices evaluated on the occupied and virtual orbitals, we obtain an efficiency equivalent to algorithmic differentiation in the computation of the interatomic forces and the optimization of the orbital parameters. Furthermore, for a large multi-determinant expansion, the significant computational gain afforded by a recently introduced table method is here extended to the local value of any one-body operator and to its derivatives, in both all-electron and pseudopotential calculations.

Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

KAUST Repository

Nobile, Fabio; Haji Ali, Abdul Lateef; Tamellini, Lorenzo; Tempone, Raul

2016-01-01

In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

Multi-Index Monte Carlo and stochastic collocation methods for random PDEs

KAUST Repository

Nobile, Fabio

2016-01-09

In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.

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

Estimation of coincidence and correlation in non-analogous Monte Carlo particle transport - 159

International Nuclear Information System (INIS)

Szieberth, M.; Leen Kloosterman, J.

2010-01-01

The conventional non-analogous Monte Carlo methods are optimized to preserve the mean value of the distributions and therefore they are not suited for non-Boltzmann problems like the estimation of coincidences or correlations. This paper presents a general method called history splitting for the non-analogous estimation of such quantities. The basic principle of the method is that a non-analogous particle history can be interpreted as a collection of analogous histories with different weights according to the probability of their realization. Calculations with a simple Monte Carlo program for a pulse-height-type estimator prove that the method is feasible and provides unbiased estimation. Different variance reduction techniques have been tried with the method and Russian roulette turned out to be ineffective in high multiplicity systems. An alternative history control method is applied instead. Simulation results of a Feynman-α measurement shows that even the reconstruction of the higher moments is possible with the history splitting method, which makes the simulation of neutron noise measurements feasible. (authors)

Classical trajectory Monte Carlo simulations of particle confinement using dual levitated coils

Directory of Open Access Journals (Sweden)

R. A. Lane

2014-07-01

Full Text Available The particle confinement properties of plasma confinement systems that employ dual levitated magnetic coils are investigated using classical trajectory Monte Carlo simulations. Two model systems are examined. In one, two identical current-carrying loops are coaxial and separated axially. In the second, two concentric and coplanar loops have different radii and carry equal currents. In both systems, a magnetic null circle is present between the current loops. Simulations are carried out for seven current loop separations for each system and at numerous values of magnetic field strength. Particle confinement is investigated at three locations between the loops at different distances from the magnetic null circle. Each simulated particle that did not escape the system exhibited one of four modes of confinement. Reduced results are given for both systems as the lowest magnetic field strength that exhibits complete confinement of all simulated particles for a particular loop separation.

Monte Carlo codes use in neutron therapy; Application de codes Monte Carlo en neutrontherapie

Energy Technology Data Exchange (ETDEWEB)

Paquis, P.; Mokhtari, F.; Karamanoukian, D. [Hopital Pasteur, 06 - Nice (France); Pignol, J.P. [Hopital du Hasenrain, 68 - Mulhouse (France); Cuendet, P. [CEA Centre d' Etudes de Saclay, 91 - Gif-sur-Yvette (France). Direction des Reacteurs Nucleaires; Fares, G.; Hachem, A. [Faculte des Sciences, 06 - Nice (France); Iborra, N. [Centre Antoine-Lacassagne, 06 - Nice (France)

1998-04-01

Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)

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.

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.

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

A 3D particle Monte Carlo approach to studying nucleation

Science.gov (United States)

Köhn, Christoph; Enghoff, Martin Bødker; Svensmark, Henrik

2018-06-01

The nucleation of sulphuric acid molecules plays a key role in the formation of aerosols. We here present a three dimensional particle Monte Carlo model to study the growth of sulphuric acid clusters as well as its dependence on the ambient temperature and the initial particle density. We initiate a swarm of sulphuric acid-water clusters with a size of 0.329 nm with densities between 107 and 108 cm-3 at temperatures between 200 and 300 K and a relative humidity of 50%. After every time step, we update the position of particles as a function of size-dependent diffusion coefficients. If two particles encounter, we merge them and add their volumes and masses. Inversely, we check after every time step whether a polymer evaporates liberating a molecule. We present the spatial distribution as well as the size distribution calculated from individual clusters. We also calculate the nucleation rate of clusters with a radius of 0.85 nm as a function of time, initial particle density and temperature. The nucleation rates obtained from the presented model agree well with experimentally obtained values and those of a numerical model which serves as a benchmark of our code. In contrast to previous nucleation models, we here present for the first time a code capable of tracing individual particles and thus of capturing the physics related to the discrete nature of particles.

Simplified monte carlo simulation for Beijing spectrometer

International Nuclear Information System (INIS)

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

1986-01-01

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

Monte Carlo: Basics

OpenAIRE

Murthy, K. P. N.

2001-01-01

An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...

MORSE Monte Carlo code

International Nuclear Information System (INIS)

Cramer, S.N.

1984-01-01

The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

Science.gov (United States)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

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

Multi-Index Monte Carlo (MIMC) When sparsity meets sampling

KAUST Repository

Tempone, Raul

2015-01-01

This talk focuses into our newest method: Multi Index Monte Carlo (MIMC). The MIMC method uses a stochastic combination technique to solve the given approximation problem, generalizing the notion of standard MLMC levels into a set of multi indices that should be properly chosen to exploit the available regularity. Indeed, instead of using first-order differences as in standard MLMC, MIMC uses high-order differences to reduce the variance of the hierarchical differences dramatically. This in turn gives a new improved complexity result that increases the domain of the problem parameters for which the method achieves the optimal convergence rate, O(TOL-2). Using optimal index sets that we determined, MIMC achieves a better rate for the computational complexity does not depend on the dimensionality of the underlying problem, up to logarithmic factors. We present numerical results related to a three dimensional PDE with random coefficients to substantiate some of the derived computational complexity rates. Finally, using the Lindeberg-Feller theorem, we also show the asymptotic normality of the statistical error in the MIMC estimator and justify in this way our error estimate that allows prescribing both the required accuracy and confidence in the final result

Multi-Index Monte Carlo (MIMC) When sparsity meets sampling

KAUST Repository

Tempone, Raul

2015-01-07

This talk focuses into our newest method: Multi Index Monte Carlo (MIMC). The MIMC method uses a stochastic combination technique to solve the given approximation problem, generalizing the notion of standard MLMC levels into a set of multi indices that should be properly chosen to exploit the available regularity. Indeed, instead of using first-order differences as in standard MLMC, MIMC uses high-order differences to reduce the variance of the hierarchical differences dramatically. This in turn gives a new improved complexity result that increases the domain of the problem parameters for which the method achieves the optimal convergence rate, O(TOL-2). Using optimal index sets that we determined, MIMC achieves a better rate for the computational complexity does not depend on the dimensionality of the underlying problem, up to logarithmic factors. We present numerical results related to a three dimensional PDE with random coefficients to substantiate some of the derived computational complexity rates. Finally, using the Lindeberg-Feller theorem, we also show the asymptotic normality of the statistical error in the MIMC estimator and justify in this way our error estimate that allows prescribing both the required accuracy and confidence in the final result

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

Comparison of analytical and Monte Carlo calculations of multi-photon effects in bremsstrahlung emission by high-energy electrons

DEFF Research Database (Denmark)

Mangiarotti, Alessio; Sona, Pietro; Ballestrero, Sergio

2012-01-01

Approximate analytical calculations of multi-photon effects in the spectrum of total radiated energy by high-energy electrons crossing thin targets are compared to the results of Monte Carlo type simulations. The limits of validity of the analytical expressions found in the literature are establi...

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

Weak second-order splitting schemes for Lagrangian Monte Carlo particle methods for the composition PDF/FDF transport equations

International Nuclear Information System (INIS)

Wang Haifeng; Popov, Pavel P.; Pope, Stephen B.

2010-01-01

We study a class of methods for the numerical solution of the system of stochastic differential equations (SDEs) that arises in the modeling of turbulent combustion, specifically in the Monte Carlo particle method for the solution of the model equations for the composition probability density function (PDF) and the filtered density function (FDF). This system consists of an SDE for particle position and a random differential equation for particle composition. The numerical methods considered advance the solution in time with (weak) second-order accuracy with respect to the time step size. The four primary contributions of the paper are: (i) establishing that the coefficients in the particle equations can be frozen at the mid-time (while preserving second-order accuracy), (ii) examining the performance of three existing schemes for integrating the SDEs, (iii) developing and evaluating different splitting schemes (which treat particle motion, reaction and mixing on different sub-steps), and (iv) developing the method of manufactured solutions (MMS) to assess the convergence of Monte Carlo particle methods. Tests using MMS confirm the second-order accuracy of the schemes. In general, the use of frozen coefficients reduces the numerical errors. Otherwise no significant differences are observed in the performance of the different SDE schemes and splitting schemes.

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

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)

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)

Monte Carlo simulation for IRRMA

International Nuclear Information System (INIS)

Gardner, R.P.; Liu Lianyan

2000-01-01

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

Alpha particle density and energy distributions in tandem mirrors using Monte-Carlo techniques

International Nuclear Information System (INIS)

Kerns, J.A.

1986-05-01

We have simulated the alpha thermalization process using a Monte-Carlo technique, in which the alpha guiding center is followed between simulated collisions and Spitzer's collision model is used for the alpha-plasma interaction. Monte-Carlo techniques are used to determine the alpha radial birth position, the alpha particle position at a collision, and the angle scatter and dispersion at a collision. The plasma is modeled as a hot reacting core, surrounded by a cold halo plasma (T approx.50 eV). Alpha orbits that intersect the halo lose 90% of their energy to the halo electrons because of the halo drag, which is ten times greater than the drag in the core. The uneven drag across the alpha orbit also produces an outward, radial, guiding center drift. This drag drift is dependent on the plasma density and temperature radial profiles. We have modeled these profiles and have specifically studied a single-scale-length model, in which the density scale length (r/sub pD/) equals the temperature scale length (r/sub pT/), and a two-scale-length model, in which r/sub pD//r/sub pT/ = 1.1

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

Variation in computer time with geometry prescription in monte carlo code KENO-IV

International Nuclear Information System (INIS)

Gopalakrishnan, C.R.

1988-01-01

In most studies, the Monte Carlo criticality code KENO-IV has been compared with other Monte Carlo codes, but evaluation of its performance with different box descriptions has not been done so far. In Monte Carlo computations, any fractional savings of computing time is highly desirable. Variation in computation time with box description in KENO for two different fast reactor fuel subassemblies of FBTR and PFBR is studied. The K eff of an infinite array of fuel subassemblies is calculated by modelling the subassemblies in two different ways (i) multi-region, (ii) multi-box. In addition to these two cases, excess reactivity calculations of FBTR are also performed in two ways to study this effect in a complex geometry. It is observed that the K eff values calculated by multi-region and multi-box models agree very well. However the increase in computation time from the multi-box to the multi-region is considerable, while the difference in computer storage requirements for the two models is negligible. This variation in computing time arises from the way the neutron is tracked in the two cases. (author)

Monte Carlo modeling of Standard Model multi-boson production processes for $\\sqrt{s} = 13$ TeV ATLAS analyses

CERN Document Server

Li, Shu; The ATLAS collaboration

2017-01-01

Proceeding for the poster presentation at LHCP2017, Shanghai, China on the topic of "Monte Carlo modeling of Standard Model multi-boson production processes for $\\sqrt{s} = 13$ TeV ATLAS analyses" (ATL-PHYS-SLIDE-2017-265 https://cds.cern.ch/record/2265389) Deadline: 01/09/2017

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.

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.

Monte Carlo Simulation for Statistical Decay of Compound Nucleus

Directory of Open Access Journals (Sweden)

Chadwick M.B.

2012-02-01

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

Monte Carlo surface flux tallies

International Nuclear Information System (INIS)

Favorite, Jeffrey A.

2010-01-01

Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.

Green's function Monte Carlo calculations of /sup 4/He

Energy Technology Data Exchange (ETDEWEB)

Carlson, J.A.

1988-01-01

Green's Function Monte Carlo methods have been developed to study the ground state properties of light nuclei. These methods are shown to reproduce results of Faddeev calculations for A = 3, and are then used to calculate ground state energies, one- and two-body distribution functions, and the D-state probability for the alpha particle. Results are compared to variational Monte Carlo calculations for several nuclear interaction models. 31 refs.

A multi-microcomputer system for Monte Carlo calculations

International Nuclear Information System (INIS)

Hertzberger, L.O.; Berg, B.; Krasemann, H.

1981-01-01

We propose a microcomputer system which allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and presumably many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 68000 microprocessor. One attraction if this processor is that it allows up to 16 M Byte random access memory. (orig.)

Monte Carlo and analytic simulations in nanoparticle-enhanced radiation therapy

Directory of Open Access Journals (Sweden)

Paro AD

2016-09-01

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

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1997-08-01

Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems

Gamma irradiation of cultural artifacts for disinfection using Monte Carlo simulations

International Nuclear Information System (INIS)

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

2012-01-01

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

Methodology of Continuous-Energy Adjoint Monte Carlo for Neutron, Photon, and Coupled Neutron-Photon Transport

International Nuclear Information System (INIS)

Hoogenboom, J. Eduard

2003-01-01

Adjoint Monte Carlo may be a useful alternative to regular Monte Carlo calculations in cases where a small detector inhibits an efficient Monte Carlo calculation as only very few particle histories will cross the detector. However, in general purpose Monte Carlo codes, normally only the multigroup form of adjoint Monte Carlo is implemented. In this article the general methodology for continuous-energy adjoint Monte Carlo neutron transport is reviewed and extended for photon and coupled neutron-photon transport. In the latter cases the discrete photons generated by annihilation or by neutron capture or inelastic scattering prevent a direct application of the general methodology. Two successive reaction events must be combined in the selection process to accommodate the adjoint analog of a reaction resulting in a photon with a discrete energy. Numerical examples illustrate the application of the theory for some simplified problems

Monte Carlo Simulations of Neutron Oil well Logging Tools

International Nuclear Information System (INIS)

Azcurra, Mario

2002-01-01

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

Monte Carlo simulations of neutron oil well logging tools

International Nuclear Information System (INIS)

Azcurra, Mario O.; Zamonsky, Oscar M.

2003-01-01

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

Monte Carlo calculation of secondary electron emission from carbon-surface by obliquely incident particles

International Nuclear Information System (INIS)

Ohya, Kaoru; Kawata, Jun; Mori, Ichiro

1990-01-01

Incidence angle dependences of secondary electron emission from a carbon surface by low energy electron and hydrogen atom are calculated using Monte Carlo simulations on the kinetic emission model. The calculation shows very small increase or rather decrease of the secondary electron yield with oblique incidence. It is explained in terms of not only multiple elastic collisions of incident particles with the carbon atoms but also small penetration depth of the particles comparable with the escape depth of secondary electrons. In addition, the two types of secondary electron emission are distinguished by using the secondary electron yield statistics; one is the emission due to trapped particles in the carbon, and the other is that due to backscattered particles. The high-yield component of the statistics on oblique incidence is more suppressed than those on normal incidence. (author)

Multi-index Monte Carlo: when sparsity meets sampling

KAUST Repository

Haji Ali, Abdul Lateef

2015-06-27

We propose and analyze a novel multi-index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, we use in MIMC high-order mixed differences instead of using first-order differences as in MLMC to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis and which increase the domain of the problem parameters for which we achieve the optimal convergence, O(TOL−2). Moreover, in MIMC, the rate of increase of required memory with respect to TOL is independent of the number of directions up to a logarithmic term which allows far more accurate solutions to be calculated for higher dimensions than what is possible when using MLMC. We motivate the setting of MIMC by first focusing on a simple full tensor index set. We then propose a systematic construction of optimal sets of indices for MIMC based on properly defined profits that in turn depend on the average cost per sample and the corresponding weak error and variance. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be the total degree type. In some cases, using optimal index sets, MIMC achieves a better rate for the computational complexity than the corresponding rate when using full tensor index sets. We also show the asymptotic normality of the statistical error in the resulting MIMC estimator and justify in this way our error estimate, which allows both the required accuracy and the confidence level in our computational

Monte Carlo: in the beginning and some great expectations

International Nuclear Information System (INIS)

Metropolis, N.

1985-01-01

The central theme will be on the historical setting and origins of the Monte Carlo Method. The scene was post-war Los Alamos Scientific Laboratory. There was an inevitability about the Monte Carlo Event: the ENIAC had recently enjoyed its meteoric rise (on a classified Los Alamos problem); Stan Ulam had returned to Los Alamos; John von Neumann was a frequent visitor. Techniques, algorithms, and applications developed rapidly at Los Alamos. Soon, the fascination of the Method reached wider horizons. The first paper was submitted for publication in the spring of 1949. In the summer of 1949, the first open conference was held at the University of California at Los Angeles. Of some interst perhaps is an account of Fermi's earlier, independent application in neutron moderation studies while at the University of Rome. The quantum leap expected with the advent of massively parallel processors will provide stimuli for very ambitious applications of the Monte Carlo Method in disciplines ranging from field theories to cosmology, including more realistic models in the neurosciences. A structure of multi-instruction sets for parallel processing is ideally suited for the Monte Carlo approach. One may even hope for a modest hardening of the soft sciences

Parallel Monte Carlo Particle Transport and the Quality of Random Number Generators: How Good is Good Enough?

International Nuclear Information System (INIS)

Procassini, R J; Beck, B R

2004-01-01

It might be assumed that use of a ''high-quality'' random number generator (RNG), producing a sequence of ''pseudo random'' numbers with a ''long'' repetition period, is crucial for producing unbiased results in Monte Carlo particle transport simulations. While several theoretical and empirical tests have been devised to check the quality (randomness and period) of an RNG, for many applications it is not clear what level of RNG quality is required to produce unbiased results. This paper explores the issue of RNG quality in the context of parallel, Monte Carlo transport simulations in order to determine how ''good'' is ''good enough''. This study employs the MERCURY Monte Carlo code, which incorporates the CNPRNG library for the generation of pseudo-random numbers via linear congruential generator (LCG) algorithms. The paper outlines the usage of random numbers during parallel MERCURY simulations, and then describes the source and criticality transport simulations which comprise the empirical basis of this study. A series of calculations for each test problem in which the quality of the RNG (period of the LCG) is varied provides the empirical basis for determining the minimum repetition period which may be employed without producing a bias in the mean integrated results

Monte Carlo radiation transport: A revolution in science

International Nuclear Information System (INIS)

Hendricks, J.

1993-01-01

When Enrico Fermi, Stan Ulam, Nicholas Metropolis, John von Neuman, and Robert Richtmyer invented the Monte Carlo method fifty years ago, little could they imagine the far-flung consequences, the international applications, and the revolution in science epitomized by their abstract mathematical method. The Monte Carlo method is used in a wide variety of fields to solve exact computational models approximately by statistical sampling. It is an alternative to traditional physics modeling methods which solve approximate computational models exactly by deterministic methods. Modern computers and improved methods, such as variance reduction, have enhanced the method to the point of enabling a true predictive capability in areas such as radiation or particle transport. This predictive capability has contributed to a radical change in the way science is done: design and understanding come from computations built upon experiments rather than being limited to experiments, and the computer codes doing the computations have become the repository for physics knowledge. The MCNP Monte Carlo computer code effort at Los Alamos is an example of this revolution. Physicians unfamiliar with physics details can design cancer treatments using physics buried in the MCNP computer code. Hazardous environments and hypothetical accidents can be explored. Many other fields, from underground oil well exploration to aerospace, from physics research to energy production, from safety to bulk materials processing, benefit from MCNP, the Monte Carlo method, and the revolution in science

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

WE-DE-BRA-05: Monte Carlo Simulation of a Novel Multi-Layer MV Imager

Energy Technology Data Exchange (ETDEWEB)

Myronakis, M; Rottmann, J; Berbeco, R [Brigham and Women’s Hospital, Boston, MA (United States); Hu, Y [Dana Farber Cancer Institute, Boston, MA (United States); Wang, A; Shedlock, D; Star-Lack, J [Varian Medical Systems, Palo Alto, CA (United States); Morf, D [Varian Medical Systems, Dattwil, Aargau (Switzerland)

2016-06-15

Purpose: To develop and validate a Monte Carlo (MC) model of a novel multi-layer imager (MLI) for megavolt (MV) energy beams. The MC model will enable performance optimization of the MLI design for clinical applications including patient setup verification, tumor tracking and MVCBCT. Methods: The MLI is composed of four layers of converter, scintillator and light detector, each layer similar to the current clinical AS1200 detector (Varian Medical Systems, Inc). The MLI model was constructed using the Geant4 Application for Tomographic Emission (GATE v7.1) and includes interactions for x-ray photons, charged particles and optical photons. Computational experiments were performed to assess Modulation Transfer Function (MTF), Detective Quantum Efficiency (DQE) and Noise Power Spectrum normalized by photon fluence and average detector signal (qNNPS). Results were compared with experimental measurements. The current work incorporates, in one model, the complete chain of events occurring in the imager; i.e. starting from x-ray interaction to charged particle transport and energy deposition to subsequent generation, interactions and detection of optical photons. Results: There is good agreement between measured and simulated MTF, qNNPS and DQE values. Normalized root mean squared error (NRMSE) between measured and simulated values over all four layers was 2.18%, 2.43% and 6.05% for MTF, qNNPS and DQE respectively. The relative difference between simulated and measured values for qNNPS(0) was 1.68% and 1.57% for DQE(0). Current results were obtained using a 6MV Varian Truebeam™ spectrum. Conclusion: A comprehensive Monte Carlo model of the MLI prototype was developed to allow optimization of detector components. The model was assessed in terms of imaging performance using standard metrics (i.e. MTF, qNNPS, DQE). Good agreement was found between simulated and measured values. The model will be used to assess alternative detector constructions to facilitate advanced

Parallelization of a Monte Carlo particle transport simulation code

Science.gov (United States)

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

2010-05-01

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

Monte Carlo simulation of the spectral response of beta-particle emitters in LSC systems

International Nuclear Information System (INIS)

Ortiz, F.; Los Arcos, J.M.; Grau, A.; Rodriguez, L.

1992-01-01

This paper presents a new method to evaluate the counting efficiency and the effective spectra at the output of any dynodic stage, for any pure beta-particle emitter, measured in a liquid scintillation counting system with two photomultipliers working in sum-coincidence mode. The process is carried out by a Monte Carlo simulation procedure that gives the electron distribution, and consequently the counting efficiency, at any dynode, in response to the beta particles emitted, as a function of the figure of merit of the system and the dynodic gains. The spectral outputs for 3 H and 14 C have been computed and compared with experimental data obtained with two sets of quenched radioactive standards of these nuclides. (orig.)

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

International Nuclear Information System (INIS)

Tatarkiewicz, J.

1980-01-01

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

The effect of load imbalances on the performance of Monte Carlo algorithms in LWR analysis

International Nuclear Information System (INIS)

Siegel, A.R.; Smith, K.; Romano, P.K.; Forget, B.; Felker, K.

2013-01-01

A model is developed to predict the impact of particle load imbalances on the performance of domain-decomposed Monte Carlo neutron transport algorithms. Expressions for upper bound performance “penalties” are derived in terms of simple machine characteristics, material characterizations and initial particle distributions. The hope is that these relations can be used to evaluate tradeoffs among different memory decomposition strategies in next generation Monte Carlo codes, and perhaps as a metric for triggering particle redistribution in production codes

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)

Monte Carlo perturbation theory in neutron transport calculations

International Nuclear Information System (INIS)

Hall, M.C.G.

1980-01-01

The need to obtain sensitivities in complicated geometrical configurations has resulted in the development of Monte Carlo sensitivity estimation. A new method has been developed to calculate energy-dependent sensitivities of any number of responses in a single Monte Carlo calculation with a very small time penalty. This estimation typically increases the tracking time per source particle by about 30%. The method of estimation is explained. Sensitivities obtained are compared with those calculated by discrete ordinates methods. Further theoretical developments, such as second-order perturbation theory and application to k/sub eff/ calculations, are discussed. The application of the method to uncertainty analysis and to the analysis of benchmark experiments is illustrated. 5 figures

Multilevel parallel strategy on Monte Carlo particle transport for the large-scale full-core pin-by-pin simulations

International Nuclear Information System (INIS)

Zhang, B.; Li, G.; Wang, W.; Shangguan, D.; Deng, L.

2015-01-01

This paper introduces the Strategy of multilevel hybrid parallelism of JCOGIN Infrastructure on Monte Carlo Particle Transport for the large-scale full-core pin-by-pin simulations. The particle parallelism, domain decomposition parallelism and MPI/OpenMP parallelism are designed and implemented. By the testing, JMCT presents the parallel scalability of JCOGIN, which reaches the parallel efficiency 80% on 120,000 cores for the pin-by-pin computation of the BEAVRS benchmark. (author)

Minimum variance Monte Carlo importance sampling with parametric dependence

International Nuclear Information System (INIS)

Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

1981-01-01

An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

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.

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

Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

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

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.

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

Collision of Physics and Software in the Monte Carlo Application Toolkit (MCATK)

Energy Technology Data Exchange (ETDEWEB)

Sweezy, Jeremy Ed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-01-21

The topic is presented in a series of slides organized as follows: MCATK overview, development strategy, available algorithms, problem modeling (sources, geometry, data, tallies), parallelism, miscellaneous tools/features, example MCATK application, recent areas of research, and summary and future work. MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library with continuous energy neutron and photon transport. Designed to build specialized applications and to provide new functionality in existing general-purpose Monte Carlo codes like MCNP, it reads ACE formatted nuclear data generated by NJOY. The motivation behind MCATK was to reduce costs. MCATK physics involves continuous energy neutron & gamma transport with multi-temperature treatment, static eigenvalue (k_eff and α) algorithms, time-dependent algorithm, and fission chain algorithms. MCATK geometry includes mesh geometries and solid body geometries. MCATK provides verified, unit-test Monte Carlo components, flexibility in Monte Carlo application development, and numerous tools such as geometry and cross section plotters.

Monte Carlo studies of nuclei and quantum liquid drops

International Nuclear Information System (INIS)

Pandharipande, V.R.; Pieper, S.C.

1989-01-01

The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs

Monte Carlo studies of nuclei and quantum liquid drops

Energy Technology Data Exchange (ETDEWEB)

Pandharipande, V.R.; Pieper, S.C.

1989-01-01

The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs.

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

Directory of Open Access Journals (Sweden)

Lin Wang

2018-01-01

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

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay

2017-04-24

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

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay; Law, Kody; Suciu, Carina

2017-01-01

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

Quantum Monte Carlo for vibrating molecules

International Nuclear Information System (INIS)

Brown, W.R.; Lawrence Berkeley National Lab., CA

1996-08-01

Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H 2 O and C 3 vibrational states, using 7 PES's, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H 2 O and C 3 . In order to construct accurate trial wavefunctions for C 3 , the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C 3 the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C 3 PES's suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies

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)

Vectorization of Monte Carlo particle transport

International Nuclear Information System (INIS)

Burns, P.J.; Christon, M.; Schweitzer, R.; Lubeck, O.M.; Wasserman, H.J.; Simmons, M.L.; Pryor, D.V.

1989-01-01

This paper reports that fully vectorized versions of the Los Alamos National Laboratory benchmark code Gamteb, a Monte Carlo photon transport algorithm, were developed for the Cyber 205/ETA-10 and Cray X-MP/Y-MP architectures. Single-processor performance measurements of the vector and scalar implementations were modeled in a modified Amdahl's Law that accounts for additional data motion in the vector code. The performance and implementation strategy of the vector codes are related to architectural features of each machine. Speedups between fifteen and eighteen for Cyber 205/ETA-10 architectures, and about nine for CRAY X-MP/Y-MP architectures are observed. The best single processor execution time for the problem was 0.33 seconds on the ETA-10G, and 0.42 seconds on the CRAY Y-MP

Load balancing in highly parallel processing of Monte Carlo code for particle transport

International Nuclear Information System (INIS)

Higuchi, Kenji; Takemiya, Hiroshi; Kawasaki, Takuji

1998-01-01

In parallel processing of Monte Carlo (MC) codes for neutron, photon and electron transport problems, particle histories are assigned to processors making use of independency of the calculation for each particle. Although we can easily parallelize main part of a MC code by this method, it is necessary and practically difficult to optimize the code concerning load balancing in order to attain high speedup ratio in highly parallel processing. In fact, the speedup ratio in the case of 128 processors remains in nearly one hundred times when using the test bed for the performance evaluation. Through the parallel processing of the MCNP code, which is widely used in the nuclear field, it is shown that it is difficult to attain high performance by static load balancing in especially neutron transport problems, and a load balancing method, which dynamically changes the number of assigned particles minimizing the sum of the computational and communication costs, overcomes the difficulty, resulting in nearly fifteen percentage of reduction for execution time. (author)

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

Monte Carlo assessment of the dose rates produced by spent fuel from CANDU reactors

International Nuclear Information System (INIS)

Pantazi, Doina; Mateescu, Silvia; Stanciu, Marcela

2003-01-01

One of the technical measures considered for biological protection is radiation shielding. The implementation process of a spent fuel intermediate storage system at Cernavoda NPP includes an evolution in computation methods related to shielding evaluation: from using simpler computer codes, like MicroShield and QAD, to systems of codes, like SCALE (which contains few independent modules) and the multipurpose and multi-particles transport code MCNP, based on Monte Carlo method. The Monte Carlo assessment of the dose rates produced by CANDU type spent fuel, during its handling for the intermediate storage, is the main objective of this paper. The work had two main features: -establishing of geometrical models according to description mode used in code MCNP, capable to account for the specific characteristics of CANDU nuclear fuel; - confirming the correctness of proposed models, by comparing MCNP results and the related results obtained with other computer codes for shielding evaluation and dose rates calculations. (authors)

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

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)

Measurements and Monte-Carlo simulations of the particle self-shielding effect of B4C grains in neutron shielding concrete

Science.gov (United States)

DiJulio, D. D.; Cooper-Jensen, C. P.; Llamas-Jansa, I.; Kazi, S.; Bentley, P. M.

2018-06-01

A combined measurement and Monte-Carlo simulation study was carried out in order to characterize the particle self-shielding effect of B4C grains in neutron shielding concrete. Several batches of a specialized neutron shielding concrete, with varying B4C grain sizes, were exposed to a 2 Å neutron beam at the R2D2 test beamline at the Institute for Energy Technology located in Kjeller, Norway. The direct and scattered neutrons were detected with a neutron detector placed behind the concrete blocks and the results were compared to Geant4 simulations. The particle self-shielding effect was included in the Geant4 simulations by calculating effective neutron cross-sections during the Monte-Carlo simulation process. It is shown that this method well reproduces the measured results. Our results show that shielding calculations for low-energy neutrons using such materials would lead to an underestimate of the shielding required for a certain design scenario if the particle self-shielding effect is not included in the calculations.

Monte Carlo simulation experiments on box-type radon dosimeter

International Nuclear Information System (INIS)

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

2014-01-01

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

Monte Carlo simulation experiments on box-type radon dosimeter

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-11

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

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

KAUST Repository

Du, Shouhong

2012-01-01

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

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

KAUST Repository

Du, Shouhong

2012-05-01

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

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

The MC21 Monte Carlo Transport Code

International Nuclear Information System (INIS)

Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H

2007-01-01

MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities

Monte Carlo Treatment Planning for Advanced Radiotherapy

DEFF Research Database (Denmark)

Cronholm, Rickard

This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...... and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...

The effects of particle recycling on the divertor plasma: A particle-in-cell with Monte Carlo collision simulation

Science.gov (United States)

Chang, Mingyu; Sang, Chaofeng; Sun, Zhenyue; Hu, Wanpeng; Wang, Dezhen

2018-05-01

A Particle-In-Cell (PIC) with Monte Carlo Collision (MCC) model is applied to study the effects of particle recycling on divertor plasma in the present work. The simulation domain is the scrape-off layer of the tokamak in one-dimension along the magnetic field line. At the divertor plate, the reflected deuterium atoms (D) and thermally released deuterium molecules (D2) are considered. The collisions between the plasma particles (e and D+) and recycled neutral particles (D and D2) are described by the MCC method. It is found that the recycled neutral particles have a great impact on divertor plasma. The effects of different collisions on the plasma are simulated and discussed. Moreover, the impacts of target materials on the plasma are simulated by comparing the divertor with Carbon (C) and Tungsten (W) targets. The simulation results show that the energy and momentum losses of the C target are larger than those of the W target in the divertor region even without considering the impurity particles, whereas the W target has a more remarkable influence on the core plasma.

Monte Carlo and detector simulation in OOP [Object-Oriented Programming

International Nuclear Information System (INIS)

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

1990-10-01

Object-Oriented Programming techniques are explored with an eye toward applications in High Energy Physics codes. Two prototype examples are given: McOOP (a particle Monte Carlo generator) and GISMO (a detector simulation/analysis package)

Improved Monte Carlo modelling of multi-energy a-rays penetration through thick stratified shielding slabs

International Nuclear Information System (INIS)

Bakos, G.C.

2001-01-01

This paper deals with the application of Monte Carlo method for the calculation of dose build up factor of, mixed 1.37 and 2.75 MeV, a-rays penetration through stratified shielding slabs. Six double layer shielding slabs namely, 12 A l+Fe, 12 A l+Pb, 6 F e+Al, 6 F e+Pb, 4 P b+Al, 4 P b+Fe were examined. Furthermore, experimental and theoretical results are also presented. The experimental results were taken from the experimental facility installed at the Universities Research reactor Center (Risley, UK). Activated Na2SO3 solution provided a uniform Na-24 disc source of a-rays at both energies (1.37 and 2.75 MeV) with equal intensity. The theoretical results were calculated using the Bowman and Trubey formula. This formula takes into account an exponentially decaying function of the shield thickness (in mfp) to the end point of the multi-layer slab. The experimental and theoretical results were used to evaluate the simulation results produced from a Monte Carlo program (DUTMONCA code) which was developed in Democritus University of Thrace (Xanthi, Greece). The DUTMONCA code was written in Pascal language and run on an Intel PIII-800 microprocessor. The developed code (which is an improved version of an existing Monte Carlo program) has the ability to produce good results for thick shielding slabs overcoming the problems encountered in older version program. The simulation results are compared with experimental and theoretical results. Good agreement can be observed, even for thick layer shielding slabs, although there are some wayward experimental values which are due to sources of error associated with the experimental procedure

A benchmark study of the Signed-particle Monte Carlo algorithm for the Wigner equation

Directory of Open Access Journals (Sweden)

Muscato Orazio

2017-12-01

Full Text Available The Wigner equation represents a promising model for the simulation of electronic nanodevices, which allows the comprehension and prediction of quantum mechanical phenomena in terms of quasi-distribution functions. During these years, a Monte Carlo technique for the solution of this kinetic equation has been developed, based on the generation and annihilation of signed particles. This technique can be deeply understood in terms of the theory of pure jump processes with a general state space, producing a class of stochastic algorithms. One of these algorithms has been validated successfully by numerical experiments on a benchmark test case.

Comparison of experimental and Monte-Carlo simulation of MeV particle transport through tapered/straight glass capillaries and circular collimators

Energy Technology Data Exchange (ETDEWEB)

Hespeels, F., E-mail: felicien.hespeels@unamur.be [University of Namur, PMR, 61 rue de Bruxelles, 5000 Namur (Belgium); Tonneau, R. [University of Namur, PMR, 61 rue de Bruxelles, 5000 Namur (Belgium); Ikeda, T. [RIKEN Nishina Center, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Lucas, S. [University of Namur, PMR, 61 rue de Bruxelles, 5000 Namur (Belgium)

2015-11-01

Highlights: • Monte-Carlo simulation for beam transportation through collimations devices. • We confirm the focusing effect of tapered glass capillary. • We confirm the feasibility of using passive collimation devices for ion beam analysis application. - Abstract: This study compares the capabilities of three different passive collimation devices to produce micrometer-sized beams for proton and alpha particle beams (1.7 MeV and 5.3 MeV respectively): classical platinum TEM-like collimators, straight glass capillaries and tapered glass capillaries. In addition, we developed a Monte-Carlo code, based on the Rutherford scattering theory, which simulates particle transportation through collimating devices. The simulation results match the experimental observations of beam transportation through collimators both in air and vacuum. This research shows the focusing effects of tapered capillaries which clearly enable higher transmission flux. Nevertheless, the capillaries alignment with an incident beam is a prerequisite but is tedious, which makes the TEM collimator the easiest way to produce a 50 μm microbeam.

Development of M3C code for Monte Carlo reactor physics criticality calculations

International Nuclear Information System (INIS)

Kumar, Anek; Kannan, Umasankari; Krishanani, P.D.

2015-06-01

The development of Monte Carlo code (M3C) for reactor design entails use of continuous energy nuclear data and Monte Carlo simulations for each of the neutron interaction processes. BARC has started a concentrated effort for developing a new general geometry continuous energy Monte Carlo code for reactor physics calculation indigenously. The code development required a comprehensive understanding of the basic continuous energy cross section sets. The important features of this code are treatment of heterogeneous lattices by general geometry, use of point cross sections along with unionized energy grid approach, thermal scattering model for low energy treatment, capability of handling the microscopic fuel particles dispersed randomly. The capability of handling the randomly dispersed microscopic fuel particles which is very useful for the modeling of High-Temperature Gas-Cooled reactor fuels which are composed of thousands of microscopic fuel particle (TRISO fuel particle), randomly dispersed in a graphite matrix. The Monte Carlo code for criticality calculation is a pioneering effort and has been used to study several types of lattices including cluster geometries. The code has been verified for its accuracy against more than 60 sample problems covering a wide range from simple (like spherical) to complex geometry (like PHWR lattice). Benchmark results show that the code performs quite well for the criticality calculation of the system. In this report, the current status of the code, features of the code, some of the benchmark results for the testing of the code and input preparation etc. are discussed. (author)

DUST, Albedo Monte-Carlo Simulation of Neutron Streaming in Multi-legged Square Concrete Ducts

International Nuclear Information System (INIS)

1993-01-01

1 - Description of program or function: DUST simulates the thermal neutron streaming through multi-legged square concrete ducts. 2 - Method of solution: DUST uses the albedo Monte Carlo method. The albedo data used are in the form of empirical formulae based on the measured doubly differential albedo data. Sampling of the reflected polar and azimuthal angles is done by the rejection method. Variance reduction devices such as Russian Roulette are used. 3 - Restrictions on the complexity of the problem: - The albedo data and the subroutines for sampling the reflected polar and azimuthal angles are specific for concrete ducts. The maximum number of legs (as specified by dimension statements) is 5 and the maximum number of dose points is 50. The dose points considered are only in the last leg of the multi-legged duct

Optimization of FIBMOS Through 2D Silvaco ATLAS and 2D Monte Carlo Particle-based Device Simulations

OpenAIRE

Kang, J.; He, X.; Vasileska, D.; Schroder, D. K.

2001-01-01

Focused Ion Beam MOSFETs (FIBMOS) demonstrate large enhancements in core device performance areas such as output resistance, hot electron reliability and voltage stability upon channel length or drain voltage variation. In this work, we describe an optimization technique for FIBMOS threshold voltage characterization using the 2D Silvaco ATLAS simulator. Both ATLAS and 2D Monte Carlo particle-based simulations were used to show that FIBMOS devices exhibit enhanced current drive ...

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

Science.gov (United States)

McDaniel, T.; D'Azevedo, E. F.; Li, Y. W.; Wong, K.; Kent, P. R. C.

2017-11-01

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Assessment study for multi-barrier system used in radioactive borate waste isolation based on Monte Carlo simulations.

Science.gov (United States)

Bayoumi, T A; Reda, S M; Saleh, H M

2012-01-01

Radioactive waste generated from the nuclear applications should be properly isolated by a suitable containment system such as, multi-barrier container. The present study aims to evaluate the isolation capacity of a new multi-barrier container made from cement and clay and including borate waste materials. These wastes were spiked by (137)Cs and (60)Co radionuclides to simulate that waste generated from the primary cooling circuit of pressurized water reactors. Leaching of both radionuclides in ground water was followed and calculated during ten years. Monte Carlo (MCNP5) simulations computed the photon flux distribution of the multi-barrier container, including radioactive borate waste of specific activity 11.22KBq/g and 4.18KBq/g for (137)Cs and (60)Co, respectively, at different periods of 0, 15.1, 30.2 and 302 years. The average total flux for 100cm radius of spherical cell was 0.192photon/cm(2) at initial time and 2.73×10(-4)photon/cm(2) after 302 years. Maximum waste activity keeping the surface radiation dose within the permissible level was calculated and found to be 56KBq/g with attenuation factors of 0.73cm(-1) and 0.6cm(-1) for cement and clay, respectively. The average total flux was 1.37×10(-3)photon/cm(2) after 302 years. Monte Carlo simulations revealed that the proposed multi-barrier container is safe enough during transportation, evacuation or rearrangement in the disposal site for more than 300 years. Copyright © 2011 Elsevier Ltd. All rights reserved.

A multi-agent quantum Monte Carlo model for charge transport: Application to organic field-effect transistors

International Nuclear Information System (INIS)

Bauer, Thilo; Jäger, Christof M.; Jordan, Meredith J. T.; Clark, Timothy

2015-01-01

We have developed a multi-agent quantum Monte Carlo model to describe the spatial dynamics of multiple majority charge carriers during conduction of electric current in the channel of organic field-effect transistors. The charge carriers are treated by a neglect of diatomic differential overlap Hamiltonian using a lattice of hydrogen-like basis functions. The local ionization energy and local electron affinity defined previously map the bulk structure of the transistor channel to external potentials for the simulations of electron- and hole-conduction, respectively. The model is designed without a specific charge-transport mechanism like hopping- or band-transport in mind and does not arbitrarily localize charge. An electrode model allows dynamic injection and depletion of charge carriers according to source-drain voltage. The field-effect is modeled by using the source-gate voltage in a Metropolis-like acceptance criterion. Although the current cannot be calculated because the simulations have no time axis, using the number of Monte Carlo moves as pseudo-time gives results that resemble experimental I/V curves

A multi-agent quantum Monte Carlo model for charge transport: Application to organic field-effect transistors

Energy Technology Data Exchange (ETDEWEB)

Bauer, Thilo; Jäger, Christof M. [Department of Chemistry and Pharmacy, Computer-Chemistry-Center and Interdisciplinary Center for Molecular Materials, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nägelsbachstrasse 25, 91052 Erlangen (Germany); Jordan, Meredith J. T. [School of Chemistry, University of Sydney, Sydney, NSW 2006 (Australia); Clark, Timothy, E-mail: tim.clark@fau.de [Department of Chemistry and Pharmacy, Computer-Chemistry-Center and Interdisciplinary Center for Molecular Materials, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nägelsbachstrasse 25, 91052 Erlangen (Germany); Centre for Molecular Design, University of Portsmouth, Portsmouth PO1 2DY (United Kingdom)

2015-07-28

We have developed a multi-agent quantum Monte Carlo model to describe the spatial dynamics of multiple majority charge carriers during conduction of electric current in the channel of organic field-effect transistors. The charge carriers are treated by a neglect of diatomic differential overlap Hamiltonian using a lattice of hydrogen-like basis functions. The local ionization energy and local electron affinity defined previously map the bulk structure of the transistor channel to external potentials for the simulations of electron- and hole-conduction, respectively. The model is designed without a specific charge-transport mechanism like hopping- or band-transport in mind and does not arbitrarily localize charge. An electrode model allows dynamic injection and depletion of charge carriers according to source-drain voltage. The field-effect is modeled by using the source-gate voltage in a Metropolis-like acceptance criterion. Although the current cannot be calculated because the simulations have no time axis, using the number of Monte Carlo moves as pseudo-time gives results that resemble experimental I/V curves.

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

Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

Science.gov (United States)

Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang

2017-07-10

In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

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.

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.

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)

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.

MCNP-REN a Monte Carlo tool for neutron detector design

CERN Document Server

Abhold, M E

2002-01-01

The development of neutron detectors makes extensive use of the predictions of detector response through the use of Monte Carlo techniques in conjunction with the point reactor model. Unfortunately, the point reactor model fails to accurately predict detector response in common applications. For this reason, the general Monte Carlo code developed at Los Alamos National Laboratory, Monte Carlo N-Particle (MCNP), was modified to simulate the pulse streams that would be generated by a neutron detector and normally analyzed by a shift register. This modified code, MCNP-Random Exponentially Distributed Neutron Source (MCNP-REN), along with the Time Analysis Program, predicts neutron detector response without using the point reactor model, making it unnecessary for the user to decide whether or not the assumptions of the point model are met for their application. MCNP-REN is capable of simulating standard neutron coincidence counting as well as neutron multiplicity counting. Measurements of mixed oxide fresh fuel w...

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

Science.gov (United States)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

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.

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

Tripoli-4, a three-dimensional poly-kinetic particle transport Monte-Carlo code

International Nuclear Information System (INIS)

Both, J.P.; Lee, Y.K.; Mazzolo, A.; Peneliau, Y.; Petit, O.; Roesslinger, B.; Soldevila, M.

2003-01-01

In this updated of the Monte-Carlo transport code Tripoli-4, we list and describe its current main features. The code computes coupled neutron-photon propagation as well as the electron-photon cascade shower. While providing the user with common biasing techniques, it also implements an automatic weighting scheme. Tripoli-4 enables the user to compute the following physical quantities: a flux, a multiplication factor, a current, a reaction rate, a dose equivalent rate as well as deposit of energy and recoil energies. For each interesting physical quantity, a Monte-Carlo simulation offers different types of estimators. Tripoli-4 has support for execution in parallel mode. Special features and applications are also presented

Tripoli-4, a three-dimensional poly-kinetic particle transport Monte-Carlo code

Energy Technology Data Exchange (ETDEWEB)

Both, J P; Lee, Y K; Mazzolo, A; Peneliau, Y; Petit, O; Roesslinger, B; Soldevila, M [CEA Saclay, Dir. de l' Energie Nucleaire (DEN/DM2S/SERMA/LEPP), 91 - Gif sur Yvette (France)

2003-07-01

In this updated of the Monte-Carlo transport code Tripoli-4, we list and describe its current main features. The code computes coupled neutron-photon propagation as well as the electron-photon cascade shower. While providing the user with common biasing techniques, it also implements an automatic weighting scheme. Tripoli-4 enables the user to compute the following physical quantities: a flux, a multiplication factor, a current, a reaction rate, a dose equivalent rate as well as deposit of energy and recoil energies. For each interesting physical quantity, a Monte-Carlo simulation offers different types of estimators. Tripoli-4 has support for execution in parallel mode. Special features and applications are also presented.

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

International Nuclear Information System (INIS)

Noack, K.

1981-01-01

The perturbation source method is used in the Monte Carlo method in calculating small effects in a particle field. It offers primising possibilities for introducing positive correlation between subtracting estimates even in the cases where other methods fail, in the case of geometrical variations of a given arrangement. The perturbation source method is formulated on the basis of integral equations for the particle fields. The formulae for the second moment of the difference of events are derived. Explicity a certain class of transport games and different procedures for generating the so-called perturbation particles are considered [ru

Monte Carlo codes use in neutron therapy

International Nuclear Information System (INIS)

Paquis, P.; Mokhtari, F.; Karamanoukian, D.; Pignol, J.P.; Cuendet, P.; Iborra, N.

1998-01-01

Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)

Monte Carlo alpha calculation

Energy Technology Data Exchange (ETDEWEB)

Brockway, D.; Soran, P.; Whalen, P.

1985-01-01

A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.

Monte Carlo simulations of neutron scattering instruments

International Nuclear Information System (INIS)

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

2001-01-01

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

Considerations of MCNP Monte Carlo code to be used as a radiotherapy treatment planning tool.

Science.gov (United States)

Juste, B; Miro, R; Gallardo, S; Verdu, G; Santos, A

2005-01-01

The present work has simulated the photon and electron transport in a Theratron 780® (MDS Nordion)60Co radiotherapy unit, using the Monte Carlo transport code, MCNP (Monte Carlo N-Particle). This project explains mainly the different methodologies carried out to speedup calculations in order to apply this code efficiently in radiotherapy treatment planning.

Tackling the premature convergence problem in Monte-Carlo localization

NARCIS (Netherlands)

Kootstra, Gert; de Boer, Bart

Monte-Carlo localization uses particle filtering to estimate the position of the robot. The method is known to suffer from the loss of potential positions when there is ambiguity present in the environment. Since many indoor environments are highly symmetric, this problem of premature convergence is

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

Science.gov (United States)

Chen, Jundong

2018-03-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-12-15

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Linear filtering applied to Monte Carlo criticality calculations

International Nuclear Information System (INIS)

Morrison, G.W.; Pike, D.H.; Petrie, L.M.

1975-01-01

A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed

Monte Carlo study of the multiquark systems

International Nuclear Information System (INIS)

Kerbikov, B.O.; Polikarpov, M.I.; Zamolodchikov, A.B.

1986-01-01

Random walks have been used to calculate the energies of the ground states in systems of N=3, 6, 9, 12 quarks. Multiquark states with N>3 are unstable with respect to the spontaneous dissociation into color singlet hadrons. The modified Green's function Monte Carlo algorithm which proved to be more simple and much accurate than the conventional few body methods have been employed. In contrast to other techniques, the same equations are used for any number of particles, while the computer time increases only linearly V, S the number of particles

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

Load Balancing of Parallel Monte Carlo Transport Calculations

International Nuclear Information System (INIS)

Procassini, R J; O'Brien, M J; Taylor, J M

2005-01-01

The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since he particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations

Numerical computation of discrete differential scattering cross sections for Monte Carlo charged particle transport

International Nuclear Information System (INIS)

Walsh, Jonathan A.; Palmer, Todd S.; Urbatsch, Todd J.

2015-01-01

Highlights: • Generation of discrete differential scattering angle and energy loss cross sections. • Gauss–Radau quadrature utilizing numerically computed cross section moments. • Development of a charged particle transport capability in the Milagro IMC code. • Integration of cross section generation and charged particle transport capabilities. - Abstract: We investigate a method for numerically generating discrete scattering cross sections for use in charged particle transport simulations. We describe the cross section generation procedure and compare it to existing methods used to obtain discrete cross sections. The numerical approach presented here is generalized to allow greater flexibility in choosing a cross section model from which to derive discrete values. Cross section data computed with this method compare favorably with discrete data generated with an existing method. Additionally, a charged particle transport capability is demonstrated in the time-dependent Implicit Monte Carlo radiative transfer code, Milagro. We verify the implementation of charged particle transport in Milagro with analytic test problems and we compare calculated electron depth–dose profiles with another particle transport code that has a validated electron transport capability. Finally, we investigate the integration of the new discrete cross section generation method with the charged particle transport capability in Milagro.

A Fast Monte Carlo Simulation for the International Linear Collider Detector

International Nuclear Information System (INIS)

Furse, D.

2005-01-01

The following paper contains details concerning the motivation for, implementation and performance of a Java-based fast Monte Carlo simulation for a detector designed to be used in the International Linear Collider. This simulation, presently included in the SLAC ILC group's org.lcsim package, reads in standard model or SUSY events in STDHEP file format, stochastically simulates the blurring in physics measurements caused by intrinsic detector error, and writes out an LCIO format file containing a set of final particles statistically similar to those that would have found by a full Monte Carlo simulation. In addition to the reconstructed particles themselves, descriptions of the calorimeter hit clusters and tracks that these particles would have produced are also included in the LCIO output. These output files can then be put through various analysis codes in order to characterize the effectiveness of a hypothetical detector at extracting relevant physical information about an event. Such a tool is extremely useful in preliminary detector research and development, as full simulations are extremely cumbersome and taxing on processor resources; a fast, efficient Monte Carlo can facilitate and even make possible detector physics studies that would be very impractical with the full simulation by sacrificing what is in many cases inappropriate attention to detail for valuable gains in time required for results

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)

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

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...

Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine

International Nuclear Information System (INIS)

Coulot, J

2003-01-01

Monte Carlo techniques are involved in many applications in medical physics, and the field of nuclear medicine has seen a great development in the past ten years due to their wider use. Thus, it is of great interest to look at the state of the art in this domain, when improving computer performances allow one to obtain improved results in a dramatically reduced time. The goal of this book is to make, in 15 chapters, an exhaustive review of the use of Monte Carlo techniques in nuclear medicine, also giving key features which are not necessary directly related to the Monte Carlo method, but mandatory for its practical application. As the book deals with therapeutic' nuclear medicine, it focuses on internal dosimetry. After a general introduction on Monte Carlo techniques and their applications in nuclear medicine (dosimetry, imaging and radiation protection), the authors give an overview of internal dosimetry methods (formalism, mathematical phantoms, quantities of interest). Then, some of the more widely used Monte Carlo codes are described, as well as some treatment planning softwares. Some original techniques are also mentioned, such as dosimetry for boron neutron capture synovectomy. It is generally well written, clearly presented, and very well documented. Each chapter gives an overview of each subject, and it is up to the reader to investigate it further using the extensive bibliography provided. Each topic is discussed from a practical point of view, which is of great help for non-experienced readers. For instance, the chapter about mathematical aspects of Monte Carlo particle transport is very clear and helps one to apprehend the philosophy of the method, which is often a difficulty with a more theoretical approach. Each chapter is put in the general (clinical) context, and this allows the reader to keep in mind the intrinsic limitation of each technique involved in dosimetry (for instance activity quantitation). Nevertheless, there are some minor remarks to

Monte Carlo simulation of a medical linear accelerator for radiotherapy use

International Nuclear Information System (INIS)

Serrano, B.; Hachem, A.; Franchisseur, E.; Herault, J.; Marcie, S.; Costa, A.; Bensadoun, R. J.; Barthe, J.; Gerard, J. P.

2006-01-01

A Monte Carlo code MCNPX (Monte Carlo N-particle) was used to model a 25 MV photon beam from a PRIMUS (KD2-Siemens) medical linear electron accelerator at the Centre Antoine Lacassagne in Nice. The entire geometry including the accelerator head and the water phantom was simulated to calculate the dose profile and the relative depth-dose distribution. The measurements were done using an ionisation chamber in water for different square field ranges. The first results show that the mean electron beam energy is not 19 MeV as mentioned by Siemens. The adjustment between the Monte Carlo calculated and measured data is obtained when the mean electron beam energy is ∼15 MeV. These encouraging results will permit to check calculation data given by the treatment planning system, especially for small fields in high gradient heterogeneous zones, typical for intensity modulated radiation therapy technique. (authors)

VIP-Man: An image-based whole-body adult male model constructed from color photographs of the visible human project for multi-particle Monte Carlo calculations

International Nuclear Information System (INIS)

Xu, X.G.; Chao, T.C.; Bozkurt, A.

2000-01-01

Human anatomical models have been indispensable to radiation protection dosimetry using Monte Carlo calculations. Existing MIRD-based mathematical models are easy to compute and standardize, but they are simplified and crude compared to human anatomy. This article describes the development of an image-based whole-body model, called VIP-Man, using transversal color photographic images obtained from the National Library of Medicine's Visible Human Project for Monte Carlo organ dose calculations involving photons, electron, neutrons, and protons. As the first of a series of papers on dose calculations based on VIP-Man, this article provides detailed information about how to construct an image-based model, as well as how to adopt it into well-tested Monte Carlo codes, EGS4, MCNP4B, and MCNPX

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.

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...

Effects of changing the random number stride in Monte Carlo calculations

International Nuclear Information System (INIS)

Hendricks, J.S.

1991-01-01

This paper reports on a common practice in Monte Carlo radiation transport codes which is to start each random walk a specified number of steps up the random number sequence from the previous one. This is called the stride in the random number sequence between source particles. It is used for correlated sampling or to provide tree-structured random numbers. A new random number generator algorithm for the major Monte Carlo code MCNP has been written to allow adjustment of the random number stride. This random number generator is machine portable. The effects of varying the stride for several sample problems are examined

A New Monte Carlo Neutron Transport Code at UNIST

International Nuclear Information System (INIS)

Lee, Hyunsuk; Kong, Chidong; Lee, Deokjung

2014-01-01

Monte Carlo neutron transport code named MCS is under development at UNIST for the advanced reactor design and research purpose. This MC code can be used for fixed source calculation and criticality calculation. Continuous energy neutron cross section data and multi-group cross section data can be used for the MC calculation. This paper presents the overview of developed MC code and its calculation results. The real time fixed source calculation ability is also tested in this paper. The calculation results show good agreement with commercial code and experiment. A new Monte Carlo neutron transport code is being developed at UNIST. The MC codes are tested with several benchmark problems: ICSBEP, VENUS-2, and Hoogenboom-Martin benchmark. These benchmarks covers pin geometry to 3-dimensional whole core, and results shows good agreement with reference results

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.

Geometric allocation approaches in Markov chain Monte Carlo

International Nuclear Information System (INIS)

Todo, S; Suwa, H

2013-01-01

The Markov chain Monte Carlo method is a versatile tool in statistical physics to evaluate multi-dimensional integrals numerically. For the method to work effectively, we must consider the following key issues: the choice of ensemble, the selection of candidate states, the optimization of transition kernel, algorithm for choosing a configuration according to the transition probabilities. We show that the unconventional approaches based on the geometric allocation of probabilities or weights can improve the dynamics and scaling of the Monte Carlo simulation in several aspects. Particularly, the approach using the irreversible kernel can reduce or sometimes completely eliminate the rejection of trial move in the Markov chain. We also discuss how the space-time interchange technique together with Walker's method of aliases can reduce the computational time especially for the case where the number of candidates is large, such as models with long-range interactions

Generalized hybrid Monte Carlo - CMFD methods for fission source convergence

International Nuclear Information System (INIS)

Wolters, Emily R.; Larsen, Edward W.; Martin, William R.

2011-01-01

In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)

Monte Carlo analysis of a control technique for a tunable white lighting system

DEFF Research Database (Denmark)

Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

2017-01-01

A simulated colour control mechanism for a multi-coloured LED lighting system is presented. The system achieves adjustable and stable white light output and allows for system-to-system reproducibility after application of the control mechanism. The control unit works using a pre-calibrated lookup...... table for an experimentally realized system, with a calibrated tristimulus colour sensor. A Monte Carlo simulation is used to examine the system performance concerning the variation of luminous flux and chromaticity of the light output. The inputs to the Monte Carlo simulation, are variations of the LED...... peak wavelength, the LED rated luminous flux bin, the influence of the operating conditions, ambient temperature, driving current, and the spectral response of the colour sensor. The system performance is investigated by evaluating the outputs from the Monte Carlo simulation. The outputs show...

Monte Carlo simulation of hybrid systems: An example

International Nuclear Information System (INIS)

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

1997-01-01

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

Is Monte Carlo embarrassingly parallel?

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

2012-07-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

Is Monte Carlo embarrassingly parallel?

International Nuclear Information System (INIS)

Hoogenboom, J. E.

2012-01-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

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

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

Science.gov (United States)

Ricketson, Lee

2013-10-01

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

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

Science.gov (United States)

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

2017-12-01

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

A 3D Monte Carlo code for plasma transport in island divertors

International Nuclear Information System (INIS)

Feng, Y.; Sardei, F.; Kisslinger, J.; Grigull, P.

1997-01-01

A fully 3D self-consistent Monte Carlo code EMC3 (edge Monte Carlo 3D) for modelling the plasma transport in island divertors has been developed. In a first step, the code solves a simplified version of the 3D time-independent plasma fluid equations. Coupled to the neutral transport code EIRENE, the EMC3 code has been used to study the particle, energy and neutral transport in W7-AS island divertor configurations. First results are compared with data from different diagnostics (Langmuir probes, H α cameras and thermography). (orig.)

The proton therapy nozzles at Samsung Medical Center: A Monte Carlo simulation study using TOPAS

Science.gov (United States)

Chung, Kwangzoo; Kim, Jinsung; Kim, Dae-Hyun; Ahn, Sunghwan; Han, Youngyih

2015-07-01

To expedite the commissioning process of the proton therapy system at Samsung Medical Center (SMC), we have developed a Monte Carlo simulation model of the proton therapy nozzles by using TOol for PArticle Simulation (TOPAS). At SMC proton therapy center, we have two gantry rooms with different types of nozzles: a multi-purpose nozzle and a dedicated scanning nozzle. Each nozzle has been modeled in detail following the geometry information provided by the manufacturer, Sumitomo Heavy Industries, Ltd. For this purpose, the novel features of TOPAS, such as the time feature or the ridge filter class, have been used, and the appropriate physics models for proton nozzle simulation have been defined. Dosimetric properties, like percent depth dose curve, spreadout Bragg peak (SOBP), and beam spot size, have been simulated and verified against measured beam data. Beyond the Monte Carlo nozzle modeling, we have developed an interface between TOPAS and the treatment planning system (TPS), RayStation. An exported radiotherapy (RT) plan from the TPS is interpreted by using an interface and is then translated into the TOPAS input text. The developed Monte Carlo nozzle model can be used to estimate the non-beam performance, such as the neutron background, of the nozzles. Furthermore, the nozzle model can be used to study the mechanical optimization of the design of the nozzle.

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.)

Monte Carlo simulation for the estimation of iron in human whole ...

Indian Academy of Sciences (India)

2017-02-10

Feb 10, 2017 ... Monte Carlo N-particle (MCNP) code has been used to simulate the transport of gamma photon rays ... experimental data, and better than the theoretical XCOM values. ... tions in the materials, according to probability density.

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

Sequential Monte Carlo with Highly Informative Observations

OpenAIRE

Del Moral, Pierre; Murray, Lawrence M.

2014-01-01

We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...

Monte Carlo Solutions for Blind Phase Noise Estimation

Directory of Open Access Journals (Sweden)

Çırpan Hakan

2009-01-01

Full Text Available This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN channels. The main contributions of the paper are (i the development of a Monte Carlo framework for phase noise estimation, with special attention to sequential importance sampling and Rao-Blackwellization, (ii the interpretation of existing Monte Carlo solutions within this generic framework, and (iii the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past, the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that, on one hand, the Monte Carlo phase noise estimators outperform the existing estimators and, on the other hand, our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions.

Monte Carlo advances for the Eolus Asci Project

International Nuclear Information System (INIS)

Hendrick, J. S.; McKinney, G. W.; Cox, L. J.

2000-01-01

The Eolus ASCI project includes parallel, 3-D transport simulation for various nuclear applications. The codes developed within this project provide neutral and charged particle transport, detailed interaction physics, numerous source and tally capabilities, and general geometry packages. One such code is MCNPW which is a general purpose, 3-dimensional, time-dependent, continuous-energy Monte Carlo fully-coupled N-Particle transport code. Significant advances are also being made in the areas of modern software engineering and parallel computing. These advances are described in detail

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)

Modelling of a general purpose irradiation chamber using a Monte Carlo particle transport code

International Nuclear Information System (INIS)

Dhiyauddin Ahmad Fauzi; Sheik, F.O.A.; Nurul Fadzlin Hasbullah

2013-01-01

Full-text: The aim of this research is to stimulate the effectiveness use of a general purpose irradiation chamber to contain pure neutron particles obtained from a research reactor. The secondary neutron and gamma particles dose discharge from the chamber layers will be used as a platform to estimate the safe dimension of the chamber. The chamber, made up of layers of lead (Pb), shielding, polyethylene (PE), moderator and commercial grade aluminium (Al) cladding is proposed for the use of interacting samples with pure neutron particles in a nuclear reactor environment. The estimation was accomplished through simulation based on general Monte Carlo N-Particle transport code using Los Alamos MCNPX software. Simulations were performed on the model of the chamber subjected to high neutron flux radiation and its gamma radiation product. The model of neutron particle used is based on the neutron source found in PUSPATI TRIGA MARK II research reactor which holds a maximum flux value of 1 x 10 12 neutron/ cm 2 s. The expected outcomes of this research are zero gamma dose in the core of the chamber and neutron dose rate of less than 10 μSv/ day discharge from the chamber system. (author)

SPHERE: a spherical-geometry multimaterial electron/photon Monte Carlo transport code

International Nuclear Information System (INIS)

Halbleib, J.A. Sr.

1977-06-01

SPHERE provides experimenters and theorists with a method for the routine solution of coupled electron/photon transport through multimaterial configurations possessing spherical symmetry. Emphasis is placed upon operational simplicity without sacrificing the rigor of the model. SPHERE combines condensed-history electron Monte Carlo with conventional single-scattering photon Monte Carlo in order to describe the transport of all generations of particles from several MeV down to 1.0 and 10.0 keV for electrons and photons, respectively. The model is more accurate at the higher energies, with a less rigorous description of the particle cascade at energies where the shell structure of the transport media becomes important. Flexibility of construction permits the user to tailor the model to specific applications and to extend the capabilities of the model to more sophisticated applications through relatively simple update procedures. 8 figs., 3 tables

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

Science.gov (United States)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models

Science.gov (United States)

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

2018-03-01

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

Computer system for Monte Carlo experimentation

International Nuclear Information System (INIS)

Grier, D.A.

1986-01-01

A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language

Quantum Monte Carlo simulations for high-Tc superconductors

International Nuclear Information System (INIS)

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

1992-01-01

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

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.

A Monte Carlo study of the two-dimensional melting mechanism

NARCIS (Netherlands)

Allen, M.P.; Frenkel, D.; Gignac, W.; Mctaque, J.P.

1983-01-01

We report here a Monte Carlo study of the thermodynamic and structural properties of a two-dimensional system of 2500 particles interacting by a repulsive inverse sixth power potential. Particular effort was made in the melting region, both to identify the defect structures and to ascertain the

LCG Monte-Carlo Data Base

CERN Document Server

Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.

2004-01-01

We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.

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

New Monte Carlo approach to the adjoint Boltzmann equation

International Nuclear Information System (INIS)

De Matteis, A.; Simonini, R.

1978-01-01

A class of stochastic models for the Monte Carlo integration of the adjoint neutron transport equation is described. Some current general methods are brought within this class, thus preparing the ground for subsequent comparisons. Monte Carlo integration of the adjoint Boltzmann equation can be seen as a simulation of the transport of mathematical particles with reaction kernels not normalized to unity. This last feature is a source of difficulty: It can influence the variance of the result negatively and also often leads to preparation of special ''libraries'' consisting of tables of normalization factors as functions of energy, presently used by several methods. These are the two main points that are discussed and that are taken into account to devise a nonmultigroup method of solution for a certain class of problems. Reactions considered in detail are radiative capture, elastic scattering, discrete levels and continuum inelastic scattering, for which the need for tables has been almost completely eliminated. The basic policy pursued to avoid a source of statistical fluctuations is to try to make the statistical weight of the traveling particle dependent only on its starting and current energies, at least in simple cases. The effectiveness of the sampling schemes proposed is supported by numerical comparison with other more general adjoint Monte Carlo methods. Computation of neutron flux at a point by means of an adjoint formulation is the problem taken as a test for numerical experiments. Very good results have been obtained in the difficult case of resonant cross sections

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

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

Odd-flavor Simulations by the Hybrid Monte Carlo

CERN Document Server

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

2001-01-01

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

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

Quantum Monte Carlo approaches for correlated systems

CERN Document Server

Becca, Federico

2017-01-01

Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...

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

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

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

International Nuclear Information System (INIS)

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

2004-01-01

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

Dynamic Load Balancing of Parallel Monte Carlo Transport Calculations

International Nuclear Information System (INIS)

O'Brien, M; Taylor, J; Procassini, R

2004-01-01

The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since the particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations

Criticality assessment for prismatic high temperature reactors by fuel stochastic Monte Carlo modeling

Energy Technology Data Exchange (ETDEWEB)

Zakova, Jitka [Department of Nuclear and Reactor Physics, Royal Institute of Technology, KTH, Roslagstullsbacken 21, S-10691 Stockholm (Sweden)], E-mail: jitka.zakova@neutron.kth.se; Talamo, Alberto [Nuclear Engineering Division, Argonne National Laboratory, ANL, 9700 South Cass Avenue, Argonne, IL 60439 (United States)], E-mail: alby@anl.gov

2008-05-15

Modeling of prismatic high temperature reactors requires a high precision description due to the triple heterogeneity of the core and also to the random distribution of fuel particles inside the fuel pins. On the latter issue, even with the most advanced Monte Carlo techniques, some approximation often arises while assessing the criticality level: first, a regular lattice of TRISO particles inside the fuel pins and, second, the cutting of TRISO particles by the fuel boundaries. We utilized two of the most accurate Monte Codes: MONK and MCNP, which are both used for licensing nuclear power plants in United Kingdom and in the USA, respectively, to evaluate the influence of the two previous approximations on estimating the criticality level of the Gas Turbine Modular Helium Reactor. The two codes exactly shared the same geometry and nuclear data library, ENDF/B, and only modeled different lattices of TRISO particles inside the fuel pins. More precisely, we investigated the difference between a regular lattice that cuts TRISO particles and a random lattice that axially repeats a region containing over 3000 non-cut particles. We have found that both Monte Carlo codes provide similar excesses of reactivity, provided that they share the same approximations.

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)

The lund Monte Carlo for jet fragmentation

International Nuclear Information System (INIS)

Sjoestrand, T.

1982-03-01

We present a Monte Carlo program based on the Lund model for jet fragmentation. Quark, gluon, diquark and hadron jets are considered. Special emphasis is put on the fragmentation of colour singlet jet systems, for which energy, momentum and flavour are conserved explicitly. The model for decays of unstable particles, in particular the weak decay of heavy hadrons, is described. The central part of the paper is a detailed description on how to use the FORTRAN 77 program. (Author)

A New Approach to Monte Carlo Simulations in Statistical Physics

Science.gov (United States)

Landau, David P.

2002-08-01

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

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.

Crossing the mesoscale no-mans land via parallel kinetic Monte Carlo.

Energy Technology Data Exchange (ETDEWEB)

Garcia Cardona, Cristina (San Diego State University); Webb, Edmund Blackburn, III; Wagner, Gregory John; Tikare, Veena; Holm, Elizabeth Ann; Plimpton, Steven James; Thompson, Aidan Patrick; Slepoy, Alexander (U. S. Department of Energy, NNSA); Zhou, Xiao Wang; Battaile, Corbett Chandler; Chandross, Michael Evan

2009-10-01

The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution.

Application of MCAM in generating Monte Carlo model for ITER port limiter

International Nuclear Information System (INIS)

Lu Lei; Li Ying; Ding Aiping; Zeng Qin; Huang Chenyu; Wu Yican

2007-01-01

On the basis of the pre-processing and conversion functions supplied by MCAM (Monte-Carlo Particle Transport Calculated Automatic Modeling System), this paper performed the generation of ITER Port Limiter MC (Monte-Carlo) calculation model from the CAD engineering model. The result was validated by using reverse function of MCAM and MCNP PLOT 2D cross-section drawing program. the successful application of MCAM to ITER Port Limiter demonstrates that MCAM is capable of dramatically increasing the efficiency and accuracy to generate MC calculation models from CAD engineering models with complex geometry comparing with the traditional manual modeling method. (authors)

Enhancing hydrologic data assimilation by evolutionary Particle Filter and Markov Chain Monte Carlo

Science.gov (United States)

Abbaszadeh, Peyman; Moradkhani, Hamid; Yan, Hongxiang

2018-01-01

Particle Filters (PFs) have received increasing attention by researchers from different disciplines including the hydro-geosciences, as an effective tool to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation using the PFs in hydrology has evolved since 2005 from the PF-SIR (sampling importance resampling) to PF-MCMC (Markov Chain Monte Carlo), and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and MCMC, the so-called EPFM. In this framework, the prior distribution undergoes an evolutionary process based on the designed mutation and crossover operators of GA. The merit of this approach is that the particles move to an appropriate position by using the GA optimization and then the number of effective particles is increased by means of MCMC, whereby the particle degeneracy is avoided and the particle diversity is improved. In this study, the usefulness and effectiveness of the proposed EPFM is investigated by applying the technique on a conceptual and highly nonlinear hydrologic model over four river basins located in different climate and geographical regions of the United States. Both synthetic and real case studies demonstrate that the EPFM improves both the state and parameter estimation more effectively and reliably as compared with the PF-MCMC.

Selection of important Monte Carlo histories

International Nuclear Information System (INIS)

Egbert, Stephen D.

1987-01-01

The 1986 Dosimetry System (DS86) for Japanese A-bomb survivors uses information describing the behavior of individual radiation particles, simulated by Monte Carlo methods, to calculate the transmission of radiation into structures and, thence, into humans. However, there are practical constraints on the number of such particle 'histories' that may be used. First, the number must be sufficiently high to provide adequate statistical precision fir any calculated quantity of interest. For integral quantities, such as dose or kerma, statistical precision of approximately 5% (standard deviation) is required to ensure that statistical uncertainties are not a major contributor to the overall uncertainty of the transmitted value. For differential quantities, such as scalar fluence spectra, 10 to 15% standard deviation on individual energy groups is adequate. Second, the number of histories cannot be so large as to require an unacceptably large amount of computer time to process the entire survivor data base. Given that there are approx. 30,000 survivors, each having 13 or 14 organs of interest, the number of histories per organ must be constrained to less than several ten's of thousands at the very most. Selection and use of the most important Monte Carlo leakage histories from among all those calculated allows the creation of an efficient house and organ radiation transmission system for use at RERF. While attempts have been made during the adjoint Monte Carlo calculation to bias the histories toward an efficient dose estimate, this effort has been far from satisfactory. Many of the adjoint histories on a typical leakage tape are either starting in an energy group in which there is very little kerma or dose or leaking into an energy group with very little free-field couple with. By knowing the typical free-field fluence and the fluence-to-dose factors with which the leaking histories will be used, one can select histories rom a leakage tape that will contribute to dose

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

International Nuclear Information System (INIS)

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

2001-01-01

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

Free energy and phase equilibria for the restricted primitive model of ionic fluids from Monte Carlo simulations

International Nuclear Information System (INIS)

Orkoulas, G.; Panagiotopoulos, A.Z.

1994-01-01

In this work, we investigate the liquid--vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T * c =0.053, ρ * c =0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids

Biases in Monte Carlo eigenvalue calculations

Energy Technology Data Exchange (ETDEWEB)

Gelbard, E.M.

1992-12-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

Biases in Monte Carlo eigenvalue calculations

Energy Technology Data Exchange (ETDEWEB)

Gelbard, E.M.

1992-01-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

Biases in Monte Carlo eigenvalue calculations

International Nuclear Information System (INIS)

Gelbard, E.M.

1992-01-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ''fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (''replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here

Overview of the MCU Monte Carlo software package

International Nuclear Information System (INIS)

Kalugin, M.A.; Oleynik, D.S.; Shkarovsky, D.A.

2013-01-01

MCU (Monte Carlo Universal) is a project on development and practical use of a universal computer code for simulation of particle transport (neutrons, photons, electrons, positrons) in three-dimensional systems by means of the Monte Carlo method. This paper provides the information on the current state of the project. The developed libraries of constants are briefly described, and the potentialities of the MCU-5 package modules and the executable codes compiled from them are characterized. Examples of important problems of reactor physics solved with the code are presented. It is shown that the MCU constructor tool is able to assemble a full-scale 3D model from templates describing single components using simple and intuitive graphic user interface. The templates are prepared by a skilled user and stored in constructor's templates library. Ordinary user works with the graphic user interface and does not deal with MCU input data directly. At the present moment there are template libraries for several types of reactors

Multi-step magnetization of the Ising model on a Shastry-Sutherland lattice: a Monte Carlo simulation

International Nuclear Information System (INIS)

Huang, W C; Huo, L; Tian, G; Qian, H R; Gao, X S; Qin, M H; Liu, J-M

2012-01-01

The magnetization behaviors and spin configurations of the classical Ising model on a Shastry-Sutherland lattice are investigated using Monte Carlo simulations, in order to understand the fascinating magnetization plateaus observed in TmB 4 and other rare-earth tetraborides. The simulations reproduce the 1/2 magnetization plateau by taking into account the dipole-dipole interaction. In addition, a narrow 2/3 magnetization step at low temperature is predicted in our simulation. The multi-step magnetization can be understood as the consequence of the competitions among the spin-exchange interaction, the dipole-dipole interaction, and the static magnetic energy.

Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model

International Nuclear Information System (INIS)

Stotler, D.P.

2005-01-01

The components of the neutral- and plasma-surface interaction model used in the Monte Carlo neutral transport code DEGAS 2 are reviewed. The idealized surfaces and processes handled by that model are inadequate for accurately simulating neutral transport behavior in present day and future fusion devices. We identify some of the physical processes missing from the model, such as mixed materials and implanted hydrogen, and make some suggestions for improving the model

A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle

Science.gov (United States)

Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi

2017-10-01

This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

Application of OMEGA Monte Carlo codes for radiation therapy treatment planning

International Nuclear Information System (INIS)

Ayyangar, Komanduri M.; Jiang, Steve B.

1998-01-01

The accuracy of conventional dose algorithms for radiosurgery treatment planning is limited, due to the inadequate consideration of the lateral radiation transport and the difficulty of acquiring accurate dosimetric data for very small beams. In the present paper, some initial work on the application of Monte Carlo method in radiation treatment planning in general, and in radiosurgery treatment planning in particular, has been presented. Two OMEGA Monte Carlo codes, BEAM and DOSXYZ, are used. The BEAM code is used to simulate the transport of particles in the linac treatment head and radiosurgery collimator. A phase space file is obtained from the BEAM simulation for each collimator size. The DOSXYZ code is used to calculate the dose distribution in the patient's body reconstructed from CT slices using the phase space file as input. The accuracy of OMEGA Monte Carlo simulation for radiosurgery dose calculation is verified by comparing the calculated and measured basic dosimetric data for several radiosurgery beams and a 4 x 4 cm 2 conventional beam. The dose distributions for three clinical cases are calculated using OMEGA codes as the dose engine for an in-house developed radiosurgery treatment planning system. The verification using basic dosimetric data and the dose calculation for clinical cases demonstrate the feasibility of applying OMEGA Monte Carlo code system to radiosurgery treatment planning. (author)

Optimization of Monte Carlo algorithms and ray tracing on GPUs

International Nuclear Information System (INIS)

Bergmann, R.M.; Vujic, J.L.

2013-01-01

To take advantage of the computational power of GPUs (Graphical Processing Units), algorithms that work well on CPUs must be modified to conform to the GPU execution model. In this study, typical task-parallel Monte Carlo algorithms have been reformulated in a data-parallel way, and the benefits of doing so are examined. We were able to show that the data-parallel approach greatly improves thread coherency and keeps thread blocks busy, improving GPU utilization compared to the task-parallel approach. Data-parallel does not, however, outperform the task-parallel approach in regards to speedup over CPU. Regarding the ray-tracing acceleration, OptiX shows promise for providing enough ray tracing speed to be used in a full 3D Monte Carlo neutron transport code for reactor calculations. It is important to note that it is necessary to operate on large datasets of particle histories in order to have good performance in both OptiX and the data-parallel algorithm since this reduces the impact of latency. Our paper also shows the need to rewrite standard Monte Carlo algorithms in order to take full advantage of these new, powerful processor architectures

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.

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

Strategije drevesnega preiskovanja Monte Carlo

OpenAIRE

VODOPIVEC, TOM

2018-01-01

Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...

Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study.

Science.gov (United States)

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.

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)

CAD-based Monte Carlo program for integrated simulation of nuclear system SuperMC

International Nuclear Information System (INIS)

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

2015-01-01

Highlights: • The new developed CAD-based Monte Carlo program named SuperMC for integrated simulation of nuclear system makes use of hybrid MC-deterministic method and advanced computer technologies. SuperMC is designed to perform transport calculation of various types of particles, depletion and activation calculation including isotope burn-up, material activation and shutdown dose, and multi-physics coupling calculation including thermo-hydraulics, fuel performance and structural mechanics. The bi-directional automatic conversion between general CAD models and physical settings and calculation models can be well performed. Results and process of simulation can be visualized with dynamical 3D dataset and geometry model. Continuous-energy cross section, burnup, activation, irradiation damage and material data etc. are used to support the multi-process simulation. Advanced cloud computing framework makes the computation and storage extremely intensive simulation more attractive just as a network service to support design optimization and assessment. The modular design and generic interface promotes its flexible manipulation and coupling of external solvers. • The new developed and incorporated advanced methods in SuperMC was introduced including hybrid MC-deterministic transport method, particle physical interaction treatment method, multi-physics coupling calculation method, geometry automatic modeling and processing method, intelligent data analysis and visualization method, elastic cloud computing technology and parallel calculation method. • The functions of SuperMC2.1 integrating automatic modeling, neutron and photon transport calculation, results and process visualization was introduced. It has been validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model. - Abstract: Monte Carlo (MC) method has distinct advantages to simulate complicated nuclear systems and is envisioned as a routine

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

Validation of cross sections for Monte Carlo simulation of the photoelectric effect

CERN Document Server

Han, Min Cheol; Pia, Maria Grazia; Basaglia, Tullio; Batic, Matej; Hoff, Gabriela; Kim, Chan Hyeong; Saracco, Paolo

2016-01-01

Several total and partial photoionization cross section calculations, based on both theoretical and empirical approaches, are quantitatively evaluated with statistical analyses using a large collection of experimental data retrieved from the literature to identify the state of the art for modeling the photoelectric effect in Monte Carlo particle transport. Some of the examined cross section models are available in general purpose Monte Carlo systems, while others have been implemented and subjected to validation tests for the first time to estimate whether they could improve the accuracy of particle transport codes. The validation process identifies Scofield's 1973 non-relativistic calculations, tabulated in the Evaluated Photon Data Library(EPDL), as the one best reproducing experimental measurements of total cross sections. Specialized total cross section models, some of which derive from more recent calculations, do not provide significant improvements. Scofield's non-relativistic calculations are not surp...

The structure of liquid water by polarized neutron diffraction and reverse Monte Carlo modelling.

Science.gov (United States)

Temleitner, László; Pusztai, László; Schweika, Werner

2007-08-22

The coherent static structure factor of water has been investigated by polarized neutron diffraction. Polarization analysis allows us to separate the huge incoherent scattering background from hydrogen and to obtain high quality data of the coherent scattering from four different mixtures of liquid H(2)O and D(2)O. The information obtained by the variation of the scattering contrast confines the configurational space of water and is used by the reverse Monte Carlo technique to model the total structure factors. Structural characteristics have been calculated directly from the resulting sets of particle coordinates. Consistency with existing partial pair correlation functions, derived without the application of polarized neutrons, was checked by incorporating them into our reverse Monte Carlo calculations. We also performed Monte Carlo simulations of a hard sphere system, which provides an accurate estimate of the information content of the measured data. It is shown that the present combination of polarized neutron scattering and reverse Monte Carlo structural modelling is a promising approach towards a detailed understanding of the microscopic structure of water.

Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul

2015-01-01

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.

Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki

2015-01-07

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.

Two-dimensional Monte Carlo simulations of structures of a suspension comprised of magnetic and nonmagnetic particles in uniform magnetic fields

International Nuclear Information System (INIS)

Peng Xiaoling; Min Yong; Ma Tianyu; Luo Wei; Yan Mi

2009-01-01

The structures of suspensions comprised of magnetic and nonmagnetic particles in magnetic fields are studied using two-dimensional Monte Carlo simulations. The magnetic interaction among magnetic particles, magnetic field strength, and concentrations of both magnetic and nonmagnetic particles are considered as key influencing factors in the present work. The results show that chain-like clusters of magnetic particles are formed along the field direction. The size of the clusters increases with increasing magnetic interaction between magnetic particles, while it keeps nearly unchanged as the field strength increases. As the concentration of magnetic particles increases, both the number and size of the clusters increase. Moreover, nonmagnetic particles are found to hinder the migration of magnetic ones. As the concentration of nonmagnetic particles increases, the hindrance on migration of magnetic particles is enhanced

Steady-State Electrodiffusion from the Nernst-Planck Equation Coupled to Local Equilibrium Monte Carlo Simulations.

Science.gov (United States)

Boda, Dezső; Gillespie, Dirk

2012-03-13

We propose a procedure to compute the steady-state transport of charged particles based on the Nernst-Planck (NP) equation of electrodiffusion. To close the NP equation and to establish a relation between the concentration and electrochemical potential profiles, we introduce the Local Equilibrium Monte Carlo (LEMC) method. In this method, Grand Canonical Monte Carlo simulations are performed using the electrochemical potential specified for the distinct volume elements. An iteration procedure that self-consistently solves the NP and flux continuity equations with LEMC is shown to converge quickly. This NP+LEMC technique can be used in systems with diffusion of charged or uncharged particles in complex three-dimensional geometries, including systems with low concentrations and small applied voltages that are difficult for other particle simulation techniques.

Nonlinear Monte Carlo model of superdiffusive shock acceleration with magnetic field amplification

Science.gov (United States)

Bykov, Andrei M.; Ellison, Donald C.; Osipov, Sergei M.

2017-03-01

Fast collisionless shocks in cosmic plasmas convert their kinetic energy flow into the hot downstream thermal plasma with a substantial fraction of energy going into a broad spectrum of superthermal charged particles and magnetic fluctuations. The superthermal particles can penetrate into the shock upstream region producing an extended shock precursor. The cold upstream plasma flow is decelerated by the force provided by the superthermal particle pressure gradient. In high Mach number collisionless shocks, efficient particle acceleration is likely coupled with turbulent magnetic field amplification (MFA) generated by the anisotropic distribution of accelerated particles. This anisotropy is determined by fast particle transport, making the problem strongly nonlinear and multiscale. Here, we present a nonlinear Monte Carlo model of collisionless shock structure with superdiffusive propagation of high-energy Fermi accelerated particles coupled to particle acceleration and MFA, which affords a consistent description of strong shocks. A distinctive feature of the Monte Carlo technique is that it includes the full angular anisotropy of the particle distribution at all precursor positions. The model reveals that the superdiffusive transport of energetic particles (i.e., Lévy-walk propagation) generates a strong quadruple anisotropy in the precursor particle distribution. The resultant pressure anisotropy of the high-energy particles produces a nonresonant mirror-type instability that amplifies compressible wave modes with wavelengths longer than the gyroradii of the highest-energy protons produced by the shock.

Evaluation and comparison of SN and Monte-Carlo charged particle transport calculations

International Nuclear Information System (INIS)

Hadad, K.

2000-01-01

A study was done to evaluate a 3-D S N charged particle transport code called SMARTEPANTS 1 and another 3-D Monte Carlo code called Integrated Tiger Series, ITS 2 . The evaluation study of SMARTEPANTS code was based on angular discretization and reflected boundary sensitivity whilst the evaluation of ITS was based on CPU time and variance reduction. The comparison of the two code was based on energy and charge deposition calculation in block of Gallium Arsenide with embedded gold cylinders. The result of evaluation tests shows that an S 8 calculation maintains both accuracy and speed and calculations with reflected boundaries geometry produces full symmetrical results. As expected for ITS evaluation, the CPU time and variance reduction are opposite to a point beyond which the history augmentation while increasing the CPU time do not result in variance reduction. The comparison test problem showed excellent agreement in total energy deposition calculations

Present status of transport code development based on Monte Carlo method