A study of Monte Carlo methods for weak approximations of stochastic particle systems in the mean-field?

KAUST Repository

Haji Ali, Abdul Lateef

2016-01-08

I discuss using single level and multilevel Monte Carlo methods to compute quantities of interests of a stochastic particle system in the mean-field. In this context, the stochastic particles follow a coupled system of Ito stochastic differential equations (SDEs). Moreover, this stochastic particle system converges to a stochastic mean-field limit as the number of particles tends to infinity. I start by recalling the results of applying different versions of Multilevel Monte Carlo (MLMC) for particle systems, both with respect to time steps and the number of particles and using a partitioning estimator. Next, I expand on these results by proposing the use of our recent Multi-index Monte Carlo method to obtain improved convergence rates.

A study of Monte Carlo methods for weak approximations of stochastic particle systems in the mean-field?

KAUST Repository

Haji Ali, Abdul Lateef

2016-01-01

I discuss using single level and multilevel Monte Carlo methods to compute quantities of interests of a stochastic particle system in the mean-field. In this context, the stochastic particles follow a coupled system of Ito stochastic differential equations (SDEs). Moreover, this stochastic particle system converges to a stochastic mean-field limit as the number of particles tends to infinity. I start by recalling the results of applying different versions of Multilevel Monte Carlo (MLMC) for particle systems, both with respect to time steps and the number of particles and using a partitioning estimator. Next, I expand on these results by proposing the use of our recent Multi-index Monte Carlo method to obtain improved convergence rates.

(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.

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)

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)

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 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

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)

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

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

The vector and parallel processing of MORSE code on Monte Carlo Machine

International Nuclear Information System (INIS)

Hasegawa, Yukihiro; Higuchi, Kenji.

1995-11-01

Multi-group Monte Carlo Code for particle transport, MORSE is modified for high performance computing on Monte Carlo Machine Monte-4. The method and the results are described. Monte-4 was specially developed to realize high performance computing of Monte Carlo codes for particle transport, which have been difficult to obtain high performance in vector processing on conventional vector processors. Monte-4 has four vector processor units with the special hardware called Monte Carlo pipelines. The vectorization and parallelization of MORSE code and the performance evaluation on Monte-4 are described. (author)

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)

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

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.

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

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)

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.

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...

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.)

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.

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)

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 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.

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.

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

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)

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

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

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

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

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

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

Memory bottlenecks and memory contention in multi-core Monte Carlo transport codes

International Nuclear Information System (INIS)

Tramm, J.R.; Siegel, A.R.

2013-01-01

The simulation of whole nuclear cores through the use of Monte Carlo codes requires an impracticably long time-to-solution. We have extracted a kernel that executes only the most computationally expensive steps of the Monte Carlo particle transport algorithm - the calculation of macroscopic cross sections - in an effort to expose bottlenecks within multi-core, shared memory architectures. (authors)

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.

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)

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

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

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

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 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.

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay

2017-04-24

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

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay; Law, Kody; Suciu, Carina

2017-01-01

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

Monte Carlo - 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

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

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

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)

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...

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

KAUST Repository

Haji-Ali, Abdul-Lateef

2017-09-12

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

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)

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)

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)

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 ...

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

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...

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)

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)

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.

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

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.

Generalized hybrid Monte Carlo - CMFD methods for fission source convergence

International Nuclear Information System (INIS)

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

2011-01-01

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

Monte Carlo simulation of 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

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.)

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)

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.)

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

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

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

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

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)

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)

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

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

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

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)

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

International Nuclear Information System (INIS)

Nakagawa, Masayuki

1985-01-01

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

Enhancements to the Combinatorial Geometry Particle Tracker in the Mercury Monte Carlo Transport Code: Embedded Meshes and Domain Decomposition

International Nuclear Information System (INIS)

Greenman, G.M.; O'Brien, M.J.; Procassini, R.J.; Joy, K.I.

2009-01-01

Two enhancements to the combinatorial geometry (CG) particle tracker in the Mercury Monte Carlo transport code are presented. The first enhancement is a hybrid particle tracker wherein a mesh region is embedded within a CG region. This method permits efficient calculations of problems with contain both large-scale heterogeneous and homogeneous regions. The second enhancement relates to the addition of parallelism within the CG tracker via spatial domain decomposition. This permits calculations of problems with a large degree of geometric complexity, which are not possible through particle parallelism alone. In this method, the cells are decomposed across processors and a particles is communicated to an adjacent processor when it tracks to an interprocessor boundary. Applications that demonstrate the efficacy of these new methods are presented

Extending the alias Monte Carlo sampling method to general distributions

International Nuclear Information System (INIS)

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

1991-01-01

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

Applications of FLUKA Monte Carlo code for nuclear and accelerator physics

CERN Document Server

Battistoni, Giuseppe; Brugger, Markus; Campanella, Mauro; Carboni, Massimo; Empl, Anton; Fasso, Alberto; Gadioli, Ettore; Cerutti, Francesco; Ferrari, Alfredo; Ferrari, Anna; Lantz, Matthias; Mairani, Andrea; Margiotta, M; Morone, Christina; Muraro, Silvia; Parodi, Katerina; Patera, Vincenzo; Pelliccioni, Maurizio; Pinsky, Lawrence; Ranft, Johannes; Roesler, Stefan; Rollet, Sofia; Sala, Paola R; Santana, Mario; Sarchiapone, Lucia; Sioli, Maximiliano; Smirnov, George; Sommerer, Florian; Theis, Christian; Trovati, Stefania; Villari, R; Vincke, Heinz; Vincke, Helmut; Vlachoudis, Vasilis; Vollaire, Joachim; Zapp, Neil

2011-01-01

FLUKA is a general purpose Monte Carlo code capable of handling all radiation components from thermal energies (for neutrons) or 1keV (for all other particles) to cosmic ray energies and can be applied in many different fields. Presently the code is maintained on Linux. The validity of the physical models implemented in FLUKA has been benchmarked against a variety of experimental data over a wide energy range, from accelerator data to cosmic ray showers in the Earth atmosphere. FLUKA is widely used for studies related both to basic research and to applications in particle accelerators, radiation protection and dosimetry, including the specific issue of radiation damage in space missions, radiobiology (including radiotherapy) and cosmic ray calculations. After a short description of the main features that make FLUKA valuable for these topics, the present paper summarizes some of the recent applications of the FLUKA Monte Carlo code in the nuclear as well high energy physics. In particular it addresses such top...

Neoclassical toroidal viscosity calculations in tokamaks using a δf Monte Carlo simulation and their verifications.

Science.gov (United States)

Satake, S; Park, J-K; Sugama, H; Kanno, R

2011-07-29

Neoclassical toroidal viscosities (NTVs) in tokamaks are investigated using a δf Monte Carlo simulation, and are successfully verified with a combined analytic theory over a wide range of collisionality. A Monte Carlo simulation has been required in the study of NTV since the complexities in guiding-center orbits of particles and their collisions cannot be fully investigated by any means of analytic theories alone. Results yielded the details of the complex NTV dependency on particle precessions and collisions, which were predicted roughly in a combined analytic theory. Both numerical and analytic methods can be utilized and extended based on these successful verifications.

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung; Liang, Faming

2009-01-01

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

Mesh-based weight window approach for Monte Carlo simulation

International Nuclear Information System (INIS)

Liu, L.; Gardner, R.P.

1997-01-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Evaluation of equivalent doses in {sup 18}F PET/CT using the Monte Carlo method with MCNPX code; Avaliação de doses equivalentes em PET/CT com {sup 18}F utilizando o Método Monte Carlo com código MCNPX

Energy Technology Data Exchange (ETDEWEB)

Belinato, Walmir [Instituto Federal de Bahia (IFBA), Vitória da Conquista, BA (Brazil); Santos, William Souza; Perini, Ana Paula; Neves, Lucio Pereira [Universidade Federal de Uberlândia (UFU), Uberlândia, MG (Brazil). Instituto de Física; Caldas, Linda V. E. [Instituto de Pesquisas Energéticas e Nucleares (IPEN-CNEN/SP), São Paulo, SP (Brazil); Souza, Divanizia N. [Universidade Federal de Sergipe (UFS), São Cristóvão, SE (Brazil)

2017-07-01

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.

Reconstruction of Monte Carlo replicas from Hessian parton distributions

Energy Technology Data Exchange (ETDEWEB)

Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)

2017-03-20

We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

Sampling from a polytope and hard-disk Monte Carlo

International Nuclear Information System (INIS)

Kapfer, Sebastian C; Krauth, Werner

2013-01-01

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

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)

Cluster monte carlo method for nuclear criticality safety calculation

International Nuclear Information System (INIS)

Pei Lucheng

1984-01-01

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

Automatic modeling for the monte carlo transport TRIPOLI code

International Nuclear Information System (INIS)

Zhang Junjun; Zeng Qin; Wu Yican; Wang Guozhong; FDS Team

2010-01-01

TRIPOLI, developed by CEA, France, is Monte Carlo particle transport simulation code. It has been widely applied to nuclear physics, shielding design, evaluation of nuclear safety. However, it is time-consuming and error-prone to manually describe the TRIPOLI input file. This paper implemented bi-directional conversion between CAD model and TRIPOLI model. Its feasibility and efficiency have been demonstrated by several benchmarking examples. (authors)

Weight window/importance generator for Monte Carlo streaming problems

International Nuclear Information System (INIS)

Booth, T.E.

1983-01-01

A Monte Carlo method for solving highly angle dependent streaming problems is described. The method uses a DXTRAN-like angle biasing scheme, a space-angle weight window to reduce weight fluctuations introduced by the angle biasing, and a space-angle importance generator to set parameters for the space-angle weight window. Particle leakage through a doubly-bent duct is calculated to demonstrate the method's use

Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations

International Nuclear Information System (INIS)

Brown, F.

2007-01-01

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

Monte Carlo shielding analyses using an automated biasing procedure

International Nuclear Information System (INIS)

Tang, J.S.; Hoffman, T.J.

1988-01-01

A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost

Applications of the Monte Carlo method in radiation protection

International Nuclear Information System (INIS)

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

1999-01-01

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

Pore-scale uncertainty quantification with multilevel Monte Carlo

KAUST Repository

Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul

2014-01-01

. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost

Current and future applications of Monte Carlo

International Nuclear Information System (INIS)

Zaidi, H.

2003-01-01

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

Quantum statistical Monte Carlo methods and applications to spin systems

International Nuclear Information System (INIS)

Suzuki, M.

1986-01-01

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

SPQR: a Monte Carlo reactor kinetics code

International Nuclear Information System (INIS)

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

1980-02-01

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

Optix: A Monte Carlo scintillation light transport code

Energy Technology Data Exchange (ETDEWEB)

Safari, M.J., E-mail: mjsafari@aut.ac.ir [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Afarideh, H. [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Ghal-Eh, N. [School of Physics, Damghan University, PO Box 36716-41167, Damghan (Iran, Islamic Republic of); Davani, F. Abbasi [Nuclear Engineering Department, Shahid Beheshti University, PO Box 1983963113, Tehran (Iran, Islamic Republic of)

2014-02-11

The paper reports on the capabilities of Monte Carlo scintillation light transport code Optix, which is an extended version of previously introduced code Optics. Optix provides the user a variety of both numerical and graphical outputs with a very simple and user-friendly input structure. A benchmarking strategy has been adopted based on the comparison with experimental results, semi-analytical solutions, and other Monte Carlo simulation codes to verify various aspects of the developed code. Besides, some extensive comparisons have been made against the tracking abilities of general-purpose MCNPX and FLUKA codes. The presented benchmark results for the Optix code exhibit promising agreements. -- Highlights: • Monte Carlo simulation of scintillation light transport in 3D geometry. • Evaluation of angular distribution of detected photons. • Benchmark studies to check the accuracy of Monte Carlo simulations.

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung

2009-11-01

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

Present status and future prospects of neutronics Monte Carlo

International Nuclear Information System (INIS)

Gelbard, E.M.

1990-01-01

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

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

Science.gov (United States)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Advanced Monte Carlo methods for thermal radiation transport

Science.gov (United States)

Wollaber, Allan B.

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

An improved Monte Carlo (MC) dose simulation for charged particle cancer therapy

Energy Technology Data Exchange (ETDEWEB)

Ying, C. K. [Advanced Medical and Dental Institute, AMDI, Universiti Sains Malaysia, Penang, Malaysia and School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu (Malaysia); Kamil, W. A. [Advanced Medical and Dental Institute, AMDI, Universiti Sains Malaysia, Penang, Malaysia and Radiology Department, Hospital USM, Kota Bharu (Malaysia); Shuaib, I. L. [Advanced Medical and Dental Institute, AMDI, Universiti Sains Malaysia, Penang (Malaysia); Matsufuji, Naruhiro [Research Centre of Charged Particle Therapy, National Institute of Radiological Sciences, NIRS, Chiba (Japan)

2014-02-12

Heavy-particle therapy such as carbon ion therapy are more popular nowadays because of the nature characteristics of charged particle and almost no side effect to patients. An effective treatment is achieved with high precision of dose calculation, in this research work, Geant4 based Monte Carlo simulation method has been used to calculate the radiation transport and dose distribution. The simulation have the same setting with the treatment room in Heavy Ion Medical Accelerator, HIMAC. The carbon ion beam at the isocentric gantry nozzle for the therapeutic energy of 290 MeV/u was simulated, experimental work was carried out in National Institute of Radiological Sciences, NIRS, Chiba, Japan by using the HIMAC to confirm the accuracy and qualities dose distribution by MC methods. The Geant4 based simulated dose distribution were verified with measurements for Bragg peak and spread out Bragg peak (SOBP) respectively. The verification of results shows that the Bragg peak depth-dose and SOBP distributions in simulation has good agreement with measurements. In overall, the study showed that Geant4 based can be fully applied in the heavy-ion therapy field for simulation, further works need to be carry on to refine and improve the Geant4 MC simulations.

An improved Monte Carlo (MC) dose simulation for charged particle cancer therapy

International Nuclear Information System (INIS)

Ying, C. K.; Kamil, W. A.; Shuaib, I. L.; Matsufuji, Naruhiro

2014-01-01

Heavy-particle therapy such as carbon ion therapy are more popular nowadays because of the nature characteristics of charged particle and almost no side effect to patients. An effective treatment is achieved with high precision of dose calculation, in this research work, Geant4 based Monte Carlo simulation method has been used to calculate the radiation transport and dose distribution. The simulation have the same setting with the treatment room in Heavy Ion Medical Accelerator, HIMAC. The carbon ion beam at the isocentric gantry nozzle for the therapeutic energy of 290 MeV/u was simulated, experimental work was carried out in National Institute of Radiological Sciences, NIRS, Chiba, Japan by using the HIMAC to confirm the accuracy and qualities dose distribution by MC methods. The Geant4 based simulated dose distribution were verified with measurements for Bragg peak and spread out Bragg peak (SOBP) respectively. The verification of results shows that the Bragg peak depth-dose and SOBP distributions in simulation has good agreement with measurements. In overall, the study showed that Geant4 based can be fully applied in the heavy-ion therapy field for simulation, further works need to be carry on to refine and improve the Geant4 MC simulations

An improved Monte Carlo (MC) dose simulation for charged particle cancer therapy

International Nuclear Information System (INIS)

Ying, C.K.; Kamil, W.A.; Shuaib, I.L.; Ying, C.K.; Kamil, W.A.

2013-01-01

Full-text: Heavy-particle therapy such as carbon ion therapy are more popular nowadays because of the nature characteristics of charged particle and almost no side effect to patients. An effective treatment is achieved with high precision of dose calculation, in this research work, Geant4 based Monte Carlo simulation method has been used to calculate the radiation transport and dose distribution. The simulation have the same setting with the treatment room in Heavy Ion Medical Accelerator, HIMAC. The carbon ion beam at the isocentric gantry nozzle for the therapeutic energy of 290 MeV/u was simulated, experimental work was carried out in National Institute of Radiological Sciences, NIRS, Chiba, Japan by using the HIMAC to confirm the accuracy and qualities dose distribution by MC methods. The Geant4 based simulated dose distribution were verified with measurements for Bragg peak and spread out Bragg peak (SOBP) respectively. The verification of results shows that the Bragg peak depth-dose and SOBP distributions in simulation has good agreement with measurements. In overall, the study showed that Geant4 based can be fully applied in the heavy ion therapy field for simulation, further works need to be carry on to refine and improve the Geant4 MC simulations. (author)

Neutron point-flux calculation by Monte Carlo

International Nuclear Information System (INIS)

Eichhorn, M.

1986-04-01

A survey of the usual methods for estimating flux at a point is given. The associated variance-reducing techniques in direct Monte Carlo games are explained. The multigroup Monte Carlo codes MC for critical systems and PUNKT for point source-point detector-systems are represented, and problems in applying the codes to practical tasks are discussed. (author)

Proton therapy Monte Carlo SRNA-VOX code

Directory of Open Access Journals (Sweden)

Ilić Radovan D.

2012-01-01

Full Text Available The most powerful feature of the Monte Carlo method is the possibility of simulating all individual particle interactions in three dimensions and performing numerical experiments with a preset error. These facts were the motivation behind the development of a general-purpose Monte Carlo SRNA program for proton transport simulation in technical systems described by standard geometrical forms (plane, sphere, cone, cylinder, cube. Some of the possible applications of the SRNA program are: (a a general code for proton transport modeling, (b design of accelerator-driven systems, (c simulation of proton scattering and degrading shapes and composition, (d research on proton detectors; and (e radiation protection at accelerator installations. This wide range of possible applications of the program demands the development of various versions of SRNA-VOX codes for proton transport modeling in voxelized geometries and has, finally, resulted in the ISTAR package for the calculation of deposited energy distribution in patients on the basis of CT data in radiotherapy. All of the said codes are capable of using 3-D proton sources with an arbitrary energy spectrum in an interval of 100 keV to 250 MeV.

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

International Nuclear Information System (INIS)

Yamamoto, Toshihiro

2014-01-01

Highlights: • The cross power spectral density in ADS has correlated and uncorrelated components. • A frequency domain Monte Carlo method to calculate the uncorrelated one is developed. • The method solves the Fourier transformed transport equation. • The method uses complex-valued weights to solve the equation. • The new method reproduces well the CPSDs calculated with time domain MC method. - Abstract: In an accelerator driven system (ADS), pulsed spallation neutrons are injected at a constant frequency. The cross power spectral density (CPSD), which can be used for monitoring the subcriticality of the ADS, is composed of the correlated and uncorrelated components. The uncorrelated component is described by a series of the Dirac delta functions that occur at the integer multiples of the pulse repetition frequency. In the present paper, a Monte Carlo method to solve the Fourier transformed neutron transport equation with a periodically pulsed neutron source term has been developed to obtain the CPSD in ADSs. Since the Fourier transformed flux is a complex-valued quantity, the Monte Carlo method introduces complex-valued weights to solve the Fourier transformed equation. The Monte Carlo algorithm used in this paper is similar to the one that was developed by the author of this paper to calculate the neutron noise caused by cross section perturbations. The newly-developed Monte Carlo algorithm is benchmarked to the conventional time domain Monte Carlo simulation technique. The CPSDs are obtained both with the newly-developed frequency domain Monte Carlo method and the conventional time domain Monte Carlo method for a one-dimensional infinite slab. The CPSDs obtained with the frequency domain Monte Carlo method agree well with those with the time domain method. The higher order mode effects on the CPSD in an ADS with a periodically pulsed neutron source are discussed

Shell model the Monte Carlo way

International Nuclear Information System (INIS)

Ormand, W.E.

1995-01-01

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

Shell model the Monte Carlo way

Energy Technology Data Exchange (ETDEWEB)

Ormand, W.E.

1995-03-01

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

Research on perturbation based Monte Carlo reactor criticality search

International Nuclear Information System (INIS)

Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

2013-01-01

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

Monte Carlo learning/biasing experiment with intelligent random numbers

International Nuclear Information System (INIS)

Booth, T.E.

1985-01-01

A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs

Temperature variance study in Monte-Carlo photon transport theory

International Nuclear Information System (INIS)

Giorla, J.

1985-10-01

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

Monte Carlo simulation for the transport beamline

Energy Technology Data Exchange (ETDEWEB)

Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)

2013-07-26

In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.

Monte Carlo simulation for the transport beamline

International Nuclear Information System (INIS)

Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.; Tramontana, A.

2013-01-01

In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

Science.gov (United States)

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

2012-01-01

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

Application of Monte Carlo codes to neutron dosimetry

International Nuclear Information System (INIS)

Prevo, C.T.

1982-01-01

In neutron dosimetry, calculations enable one to predict the response of a proposed dosimeter before effort is expended to design and fabricate the neutron instrument or dosimeter. The nature of these calculations requires the use of computer programs that implement mathematical models representing the transport of radiation through attenuating media. Numerical, and in some cases analytical, solutions of these models can be obtained by one of several calculational techniques. All of these techniques are either approximate solutions to the well-known Boltzmann equation or are based on kernels obtained from solutions to the equation. The Boltzmann equation is a precise mathematical description of neutron behavior in terms of position, energy, direction, and time. The solution of the transport equation represents the average value of the particle flux density. Integral forms of the transport equation are generally regarded as the formal basis for the Monte Carlo method, the results of which can in principle be made to approach the exact solution. This paper focuses on the Monte Carlo technique

An introduction to applied quantum mechanics in the Wigner Monte Carlo formalism

International Nuclear Information System (INIS)

Sellier, J.M.; Nedjalkov, M.; Dimov, I.

2015-01-01

The Wigner formulation of quantum mechanics is a very intuitive approach which allows the comprehension and prediction of quantum mechanical phenomena in terms of quasi-distribution functions. In this review, our aim is to provide a detailed introduction to this theory along with a Monte Carlo method for the simulation of time-dependent quantum systems evolving in a phase-space. This work consists of three main parts. First, we introduce the Wigner formalism, then we discuss in detail the Wigner Monte Carlo method and, finally, we present practical applications. In particular, the Wigner model is first derived from the Schrödinger equation. Then a generalization of the formalism due to Moyal is provided, which allows to recover important mathematical properties of the model. Next, the Wigner equation is further generalized to the case of many-body quantum systems. Finally, a physical interpretation of the negative part of a quasi-distribution function is suggested. In the second part, the Wigner Monte Carlo method, based on the concept of signed (virtual) particles, is introduced in detail for the single-body problem. Two extensions of the Wigner Monte Carlo method to quantum many-body problems are introduced, in the frameworks of time-dependent density functional theory and ab-initio methods. Finally, in the third and last part of this paper, applications to single- and many-body problems are performed in the context of quantum physics and quantum chemistry, specifically focusing on the hydrogen, lithium and boron atoms, the H 2 molecule and a system of two identical Fermions. We conclude this work with a discussion on the still unexplored directions the Wigner Monte Carlo method could take in the next future

Gamma irradiator dose mapping: a Monte Carlo simulation and experimental measurements

International Nuclear Information System (INIS)

Rodrigues, Rogerio R.; Ribeiro, Mariana A.; Grynberg, Suely E.; Ferreira, Andrea V.; Meira-Belo, Luiz Claudio; Sousa, Romulo V.; Sebastiao, Rita de C.O.

2009-01-01

Gamma irradiator facilities can be used in a wide range of applications such as biological and chemical researches, food treatment and sterilization of medical devices and products. Dose mapping must be performed in these equipment in order to establish plant operational parameters, as dose uniformity, source utilization efficiency and maximum and minimum dose positions. The isodoses curves are generally measured using dosimeters distributed throughout the device, and this procedure often consume a large amount of dosimeters, irradiation time and manpower. However, a detailed curve doses identification of the irradiation facility can be performed using Monte Carlo simulation, which reduces significantly the monitoring with dosimeters. The present work evaluates the absorbed dose in the CDTN/CNEN Gammacell Irradiation Facility, using the Monte Carlo N-particles (MCNP) code. The Gammacell 220, serial number 39, was produced by Atomic Energy of Canada Limited and was loaded with sources of 60 Co. Dose measurements using TLD and Fricke dosimeters were also performed to validate the calculations. The good agreement of the results shows that Monte Carlo simulations can be used as a predictive tool of irradiation planning for the CDTN/CNEN Gamma Cell Irradiator. (author)

Adaptive Multilevel Monte Carlo Simulation

KAUST Repository

Hoel, H

2011-08-23

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-01-15

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

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

International Nuclear Information System (INIS)

Han Jingru; Chen Yixue; Yuan Longjun

2013-01-01

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

Nested Sampling with Constrained Hamiltonian Monte Carlo

OpenAIRE

Betancourt, M. J.

2010-01-01

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

Clinical dosimetry in photon radiotherapy. A Monte Carlo based investigation

International Nuclear Information System (INIS)

Wulff, Joerg

2010-01-01

. The efficiency of ionization chamber calculations could be improved by several orders of magnitude. Using the developed methods, current clinical dosimetry protocols for the determination of absorbed dose to water under reference conditions in photon beams were reviewed. Calculations of correction factors were performed and compared to the currently existing data. It could be shown that the calculated values are in agreement with recent data, mainly based on calorimetric measurements, but partially deviate from currently used data in dosimetry protocols by ∝1%. Reason for these discrepancies are outdated theories and measurements for the single underlying perturbations. Sources of uncertainties in the calculated results based on Monte Carlo simulations were investigated, also considering uncertainties in underlying cross sections as input for these calculations. It could be shown that following a conservative estimation, systematic uncertainties of ≤1% might be adherent to the calculated results, a fact that is barely considered in recent works. Ion chambers under non-reference conditions were investigated with the use of a virtual model of a clinical linear accelerator. Besides developing a procedure for commissioning the model i.e. adapting it to measurements with respect to primary electron characteristics, these calculations aimed at answering the question how ionization chambers behave in non-reference geometrical conditions. It turned out that commonly used ionization chambers show only small changes in response under non-reference conditions when fulfilling the condition of charged particle equilibrium. In contrast, whenever charged particle disequilibrium and high dose gradients exists, i.e. in the penumbra of a small radiation field, a strong change in detector response might occur. The applicability of the Spencer-Attix theory under these severe conditions was tested. It could be shown that, within a 1% uncertainty, the application of the Spencer

A Monte Carlo program for generating hadronic final states

International Nuclear Information System (INIS)

Angelini, L.; Pellicoro, M.; Nitti, L.; Preparata, G.; Valenti, G.

1991-01-01

FIRST is a computer program to generate final states from high energy hadronic interactions using the Monte Carlo technique. It is based on a theoretical model in which the high degree of universality in such interactions is related with the existence of highly excited quark-antiquark bound states, called fire-strings. The program handles the decay of both fire-strings and unstable particles produced in the intermediate states. (orig.)

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 computation in the applied research of nuclear technology

International Nuclear Information System (INIS)

Xu Shuyan; Liu Baojie; Li Qin

2007-01-01

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

Shell model Monte Carlo methods

International Nuclear Information System (INIS)

Koonin, S.E.

1996-01-01

We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs

Multiple histogram method and static Monte Carlo sampling

NARCIS (Netherlands)

Inda, M.A.; Frenkel, D.

2004-01-01

We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From

Forest canopy BRDF simulation using Monte Carlo method

NARCIS (Netherlands)

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

2006-01-01

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

Monte Carlo simulation of magnetic multi-core nanoparticles

International Nuclear Information System (INIS)

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

2009-01-01

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

Discrete Diffusion Monte Carlo for Electron Thermal Transport

Science.gov (United States)

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

2014-10-01

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

Monte Carlo techniques in diagnostic and therapeutic nuclear medicine

International Nuclear Information System (INIS)

Zaidi, H.

2002-01-01

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

Monte Carlo strategies in scientific computing

CERN Document Server

Liu, Jun S

2008-01-01

This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...

Off-diagonal expansion quantum Monte Carlo.

Science.gov (United States)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

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

Dynamic bounds coupled with Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)

2011-02-15

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.

Coded aperture optimization using Monte Carlo simulations

International Nuclear Information System (INIS)

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

2010-01-01

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

Variational Monte Carlo Technique

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...

Application of adjoint Monte Carlo to accelerate simulations of mono-directional beams in treatment planning for Boron Neutron Capture Therapy

International Nuclear Information System (INIS)

Nievaart, V. A.; Legrady, D.; Moss, R. L.; Kloosterman, J. L.; Hagen, T. H. J. J. van der; Dam, H. van

2007-01-01

This paper deals with the application of the adjoint transport theory in order to optimize Monte Carlo based radiotherapy treatment planning. The technique is applied to Boron Neutron Capture Therapy where most often mixed beams of neutrons and gammas are involved. In normal forward Monte Carlo simulations the particles start at a source and lose energy as they travel towards the region of interest, i.e., the designated point of detection. Conversely, with adjoint Monte Carlo simulations, the so-called adjoint particles start at the region of interest and gain energy as they travel towards the source where they are detected. In this respect, the particles travel backwards and the real source and real detector become the adjoint detector and adjoint source, respectively. At the adjoint detector, an adjoint function is obtained with which numerically the same result, e.g., dose or flux in the tumor, can be derived as with forward Monte Carlo. In many cases, the adjoint method is more efficient and by that is much quicker when, for example, the response in the tumor or organ at risk for many locations and orientations of the treatment beam around the patient is required. However, a problem occurs when the treatment beam is mono-directional as the probability of detecting adjoint Monte Carlo particles traversing the beam exit (detector plane in adjoint mode) in the negative direction of the incident beam is zero. This problem is addressed here and solved first with the use of next event estimators and second with the application of a Legendre expansion technique of the angular adjoint function. In the first approach, adjoint particles are tracked deterministically through a tube to a (adjoint) point detector far away from the geometric model. The adjoint particles will traverse the disk shaped entrance of this tube (the beam exit in the actual geometry) perpendicularly. This method is slow whenever many events are involved that are not contributing to the point

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

International Nuclear Information System (INIS)

Höök, L J; Johnson, T; Hellsten, T

2012-01-01

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

Usefulness of the Monte Carlo method in reliability calculations

International Nuclear Information System (INIS)

Lanore, J.M.; Kalli, H.

1977-01-01

Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels

Combinatorial nuclear level density by a Monte Carlo method

International Nuclear Information System (INIS)

Cerf, N.

1994-01-01

We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations

Discrete diffusion Monte Carlo for frequency-dependent radiative transfer

International Nuclear Information System (INIS)

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

2011-01-01

Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop 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. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique. (author)

Uncertainty analysis in Monte Carlo criticality computations

International Nuclear Information System (INIS)

Qi Ao

2011-01-01

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

MONTE CARLO SIMULATION MODEL OF ENERGETIC PROTON TRANSPORT THROUGH SELF-GENERATED ALFVEN WAVES

Energy Technology Data Exchange (ETDEWEB)

Afanasiev, A.; Vainio, R., E-mail: alexandr.afanasiev@helsinki.fi [Department of Physics, University of Helsinki (Finland)

2013-08-15

A new Monte Carlo simulation model for the transport of energetic protons through self-generated Alfven waves is presented. The key point of the model is that, unlike the previous ones, it employs the full form (i.e., includes the dependence on the pitch-angle cosine) of the resonance condition governing the scattering of particles off Alfven waves-the process that approximates the wave-particle interactions in the framework of quasilinear theory. This allows us to model the wave-particle interactions in weak turbulence more adequately, in particular, to implement anisotropic particle scattering instead of isotropic scattering, which the previous Monte Carlo models were based on. The developed model is applied to study the transport of flare-accelerated protons in an open magnetic flux tube. Simulation results for the transport of monoenergetic protons through the spectrum of Alfven waves reveal that the anisotropic scattering leads to spatially more distributed wave growth than isotropic scattering. This result can have important implications for diffusive shock acceleration, e.g., affect the scattering mean free path of the accelerated particles in and the size of the foreshock region.

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.

Efficiency and accuracy of Monte Carlo (importance) sampling

NARCIS (Netherlands)

Waarts, P.H.

2003-01-01

Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed

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

Energy Technology Data Exchange (ETDEWEB)

Richet, Y

2006-12-15

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

Monte Carlo criticality analysis for dissolvers with neutron poison

International Nuclear Information System (INIS)

Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.

1987-01-01

Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)

Numerical heating in Particle-In-Cell simulations with Monte Carlo binary collisions

Science.gov (United States)

Alves, E. Paulo; Mori, Warren; Fiuza, Frederico

2017-10-01

The binary Monte Carlo collision (BMCC) algorithm is a robust and popular method to include Coulomb collision effects in Particle-in-Cell (PIC) simulations of plasmas. While a number of works have focused on extending the validity of the model to different physical regimes of temperature and density, little attention has been given to the fundamental coupling between PIC and BMCC algorithms. Here, we show that the coupling between PIC and BMCC algorithms can give rise to (nonphysical) numerical heating of the system, that can be far greater than that observed when these algorithms operate independently. This deleterious numerical heating effect can significantly impact the evolution of the simulated system particularly for long simulation times. In this work, we describe the source of this numerical heating, and derive scaling laws for the numerical heating rates based on the numerical parameters of PIC-BMCC simulations. We compare our theoretical scalings with PIC-BMCC numerical experiments, and discuss strategies to minimize this parasitic effect. This work is supported by DOE FES under FWP 100237 and 100182.