Monte Carlo Simulation in Statistical Physics An Introduction

CERN Document Server

Binder, Kurt

2010-01-01

Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...

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 molecular simulation of phase-coexistence for oil production and processing

KAUST Repository

Li, Jun

2011-01-01

The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components, the Gibbs-NPT ensemble Monte Carlo method is employed in the simulation while the mole fraction of each component in each phase is modeled as a Leonard-Jones fluid. As the results of Monte Carlo simulations usually contain huge statistical error, the blocking method is used to estimate the variance of the simulation results. Additionally, in order to improve the simulation efficiency, the step sizes of different trial moves is adjusted automatically so that their acceptance probabilities can approach to the preset values.

Estimation of absorbed doses from paediatric cone-beam CT scans: MOSFET measurements and Monte Carlo simulations.

Science.gov (United States)

Kim, Sangroh; Yoshizumi, Terry T; Toncheva, Greta; Frush, Donald P; Yin, Fang-Fang

2010-03-01

The purpose of this study was to establish a dose estimation tool with Monte Carlo (MC) simulations. A 5-y-old paediatric anthropomorphic phantom was computed tomography (CT) scanned to create a voxelised phantom and used as an input for the abdominal cone-beam CT in a BEAMnrc/EGSnrc MC system. An X-ray tube model of the Varian On-Board Imager((R)) was built in the MC system. To validate the model, the absorbed doses at each organ location for standard-dose and low-dose modes were measured in the physical phantom with MOSFET detectors; effective doses were also calculated. In the results, the MC simulations were comparable to the MOSFET measurements. This voxelised phantom approach could produce a more accurate dose estimation than the stylised phantom method. This model can be easily applied to multi-detector CT dosimetry.

A study on the shielding element using Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Kim, Ki Jeong [Dept. of Radiology, Konkuk University Medical Center, Seoul (Korea, Republic of); Shim, Jae Goo [Dept. of Radiologic Technology, Daegu Health College, Daegu (Korea, Republic of)

2017-06-15

In this research, we simulated the elementary star shielding ability using Monte Carlo simulation to apply medical radiation shielding sheet which can replace existing lead. In the selection of elements, mainly elements and metal elements having a large atomic number, which are known to have high shielding performance, recently, various composite materials have improved shielding performance, so that weight reduction, processability, In consideration of activity etc., 21 elements were selected. The simulation tools were utilized Monte Carlo method. As a result of simulating the shielding performance by each element, it was estimated that the shielding ratio is the highest at 98.82% and 98.44% for tungsten and gold.

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

First Passage Probability Estimation of Wind Turbines by Markov Chain Monte Carlo

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Nielsen, Søren R.K.

2013-01-01

Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events...... of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal...... to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of the accuracy of the first passage probability estimation by the SS methods....

Suppression of the initial transient in Monte Carlo criticality simulations

International Nuclear Information System (INIS)

Richet, Y.

2006-12-01

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 Simulation of an American Option

Directory of Open Access Journals (Sweden)

Gikiri Thuo

2007-04-01

Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.

Monte Carlo simulations of plutonium gamma-ray spectra

International Nuclear Information System (INIS)

Koenig, Z.M.; Carlson, J.B.; Wang, Tzu-Fang; Ruhter, W.D.

1993-01-01

Monte Carlo calculations were investigated as a means of simulating the gamma-ray spectra of Pu. These simulated spectra will be used to develop and evaluate gamma-ray analysis techniques for various nondestructive measurements. Simulated spectra of calculational standards can be used for code intercomparisons, to understand systematic biases and to estimate minimum detection levels of existing and proposed nondestructive analysis instruments. The capability to simulate gamma-ray spectra from HPGe detectors could significantly reduce the costs of preparing large numbers of real reference materials. MCNP was used for the Monte Carlo transport of the photons. Results from the MCNP calculations were folded in with a detector response function for a realistic spectrum. Plutonium spectrum peaks were produced with Lorentzian shapes, for the x-rays, and Gaussian distributions. The MGA code determined the Pu isotopes and specific power of this calculated spectrum and compared it to a similar analysis on a measured spectrum

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

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

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.

Profit Forecast Model Using Monte Carlo Simulation in Excel

Directory of Open Access Journals (Sweden)

Petru BALOGH

2014-01-01

Full Text Available Profit forecast is very important for any company. The purpose of this study is to provide a method to estimate the profit and the probability of obtaining the expected profit. Monte Carlo methods are stochastic techniques–meaning they are based on the use of random numbers and probability statistics to investigate problems. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. Our example of Monte Carlo simulation in Excel will be a simplified profit forecast model. Each step of the analysis will be described in detail. The input data for the case presented: the number of leads per month, the percentage of leads that result in sales, , the cost of a single lead, the profit per sale and fixed cost, allow obtaining profit and associated probabilities of achieving.

Monte Carlo simulation for ion-molecule collisions at intermediate velocity

International Nuclear Information System (INIS)

Kadhane, U R; Mishra, P M; Rajput, J; Safvan, C P; Vig, S

2015-01-01

Electronic energy loss distribution estimation is done under local density distribution using Monte Carlo simulations. These results are used to compare the experimental results of proton-polycyclic aromatic hydrocarbons (PAHs) and proton-nucleobase interactions at intermediate velocity collisions. (paper)

Photon dose estimation from ultraintense laser–solid interactions and shielding calculation with Monte Carlo simulation

International Nuclear Information System (INIS)

Yang, Bo; Qiu, Rui; Li, JunLi; Lu, Wei; Wu, Zhen; Li, Chunyan

2017-01-01

When a strong laser beam irradiates a solid target, a hot plasma is produced and high-energy electrons are usually generated (the so-called “hot electrons”). These energetic electrons subsequently generate hard X-rays in the solid target through the Bremsstrahlung process. To date, only limited studies have been conducted on this laser-induced radiological protection issue. In this study, extensive literature reviews on the physics and properties of hot electrons have been conducted. On the basis of these information, the photon dose generated by the interaction between hot electrons and a solid target was simulated with the Monte Carlo code FLUKA. With some reasonable assumptions, the calculated dose can be regarded as the upper boundary of the experimental results over the laser intensity ranging from 10 19 to 10 21 W/cm 2 . Furthermore, an equation to estimate the photon dose generated from ultraintense laser–solid interactions based on the normalized laser intensity is derived. The shielding effects of common materials including concrete and lead were also studied for the laser-driven X-ray source. The dose transmission curves and tenth-value layers (TVLs) in concrete and lead were calculated through Monte Carlo simulations. These results could be used to perform a preliminary and fast radiation safety assessment for the X-rays generated from ultraintense laser–solid interactions. - Highlights: • The laser–driven X-ray ionizing radiation source was analyzed in this study. • An equation to estimate the photon dose based on the laser intensity is given. • The shielding effects of concrete and lead were studied for this new X-ray source. • The aim of this study is to analyze and mitigate the laser–driven X-ray hazard.

Oxygen transport properties estimation by classical trajectory–direct simulation Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Bruno, Domenico, E-mail: domenico.bruno@cnr.it [Istituto di Metodologie Inorganiche e dei Plasmi, Consiglio Nazionale delle Ricerche– Via G. Amendola 122, 70125 Bari (Italy); Frezzotti, Aldo, E-mail: aldo.frezzotti@polimi.it; Ghiroldi, Gian Pietro, E-mail: gpghiro@gmail.com [Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano–Via La Masa 34, 20156 Milano (Italy)

2015-05-15

Coupling direct simulation Monte Carlo (DSMC) simulations with classical trajectory calculations is a powerful tool to improve predictive capabilities of computational dilute gas dynamics. The considerable increase in computational effort outlined in early applications of the method can be compensated by running simulations on massively parallel computers. In particular, Graphics Processing Unit acceleration has been found quite effective in reducing computing time of classical trajectory (CT)-DSMC simulations. The aim of the present work is to study dilute molecular oxygen flows by modeling binary collisions, in the rigid rotor approximation, through an accurate Potential Energy Surface (PES), obtained by molecular beams scattering. The PES accuracy is assessed by calculating molecular oxygen transport properties by different equilibrium and non-equilibrium CT-DSMC based simulations that provide close values of the transport properties. Comparisons with available experimental data are presented and discussed in the temperature range 300–900 K, where vibrational degrees of freedom are expected to play a limited (but not always negligible) role.

Probabilistic approach of resource assessment in Kerinci geothermal field using numerical simulation coupling with monte carlo simulation

Science.gov (United States)

Hidayat, Iki; Sutopo; Pratama, Heru Berian

2017-12-01

The Kerinci geothermal field is one phase liquid reservoir system in the Kerinci District, western part of Jambi Province. In this field, there are geothermal prospects that identified by the heat source up flow inside a National Park area. Kerinci field was planned to develop 1×55 MWe by Pertamina Geothermal Energy. To define reservoir characterization, the numerical simulation of Kerinci field is developed by using TOUGH2 software with information from conceptual model. The pressure and temperature profile well data of KRC-B1 are validated with simulation data to reach natural state condition. The result of the validation is suitable matching. Based on natural state simulation, the resource assessment of Kerinci geothermal field is estimated by using Monte Carlo simulation with the result P10-P50-P90 are 49.4 MW, 64.3 MW and 82.4 MW respectively. This paper is the first study of resource assessment that has been estimated successfully in Kerinci Geothermal Field using numerical simulation coupling with Monte carlo simulation.

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.)

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.

Global Monte Carlo Simulation with High Order Polynomial Expansions

International Nuclear Information System (INIS)

William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin

2007-01-01

The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as 'local' piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi's method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source convergence

Estimation of crosstalk in LED fNIRS by photon propagation Monte Carlo simulation

Science.gov (United States)

Iwano, Takayuki; Umeyama, Shinji

2015-12-01

fNIRS (functional near-Infrared spectroscopy) can measure brain activity non-invasively and has advantages such as low cost and portability. While the conventional fNIRS has used laser light, LED light fNIRS is recently becoming common in use. Using LED for fNIRS, equipment can be more inexpensive and more portable. LED light, however, has a wider illumination spectrum than laser light, which may change crosstalk between the calculated concentration change of oxygenated and deoxygenated hemoglobins. The crosstalk is caused by difference in light path length in the head tissues depending on wavelengths used. We conducted Monte Carlo simulations of photon propagation in the tissue layers of head (scalp, skull, CSF, gray matter, and white matter) to estimate the light path length in each layers. Based on the estimated path lengths, the crosstalk in fNIRS using LED light was calculated. Our results showed that LED light more increases the crosstalk than laser light does when certain combinations of wavelengths were adopted. Even in such cases, the crosstalk increased by using LED light can be effectively suppressed by replacing the value of extinction coefficients used in the hemoglobin calculation to their weighted average over illumination spectrum.

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.

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

Science.gov (United States)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Gradient angle estimation by uniform directional simulation on a cone

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager

1997-01-01

approximation to a locally most central limit state point. Moreover, the estimated angle can be used to correct the geometric reliability index.\\bfseries Keywords: Directional simulation, effectivity factor, gradient angle estimation, maximum likelihood, model-correction-factor method, Monte Carlo simulation...

Simulation based sequential Monte Carlo methods for discretely observed Markov processes

OpenAIRE

Neal, Peter

2014-01-01

Parameter estimation for discretely observed Markov processes is a challenging problem. However, simulation of Markov processes is straightforward using the Gillespie algorithm. We exploit this ease of simulation to develop an effective sequential Monte Carlo (SMC) algorithm for obtaining samples from the posterior distribution of the parameters. In particular, we introduce two key innovations, coupled simulations, which allow us to study multiple parameter values on the basis of a single sim...

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

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.

On the predictivity of pore-scale simulations: estimating uncertainties with multilevel Monte Carlo

KAUST Repository

Icardi, Matteo

2016-02-08

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another “equivalent” sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [2015. https://bitbucket.org/micardi/porescalemc.], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers

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)

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

Energy Technology Data Exchange (ETDEWEB)

Lai, Chao-Jen, E-mail: cjlai3711@gmail.com; Zhong, Yuncheng; Yi, Ying; Wang, Tianpeng; Shaw, Chris C. [Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030-4009 (United States)

2015-06-15

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm{sup 2} field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical

Non-Boltzmann Ensembles and Monte Carlo Simulations

International Nuclear Information System (INIS)

Murthy, K. P. N.

2016-01-01

Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc . This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g ( E , M ), as a function of both energy E , and order parameter M . This is carried out in two stages. We estimate g ( E ) in the first stage

On the use of Monte Carlo-derived dosimetric data in the estimation of patient dose from CT examinations

International Nuclear Information System (INIS)

Perisinakis, Kostas; Tzedakis, Antonis; Damilakis, John

2008-01-01

The purpose of this work was to investigate the applicability and appropriateness of Monte Carlo-derived normalized data to provide accurate estimations of patient dose from computed tomography (CT) exposures. Monte Carlo methodology and mathematical anthropomorphic phantoms were used to simulate standard patient CT examinations of the head, thorax, abdomen, and trunk performed on a multislice CT scanner. Phantoms were generated to simulate the average adult individual and two individuals with different body sizes. Normalized dose values for all radiosensitive organs and normalized effective dose values were calculated for standard axial and spiral CT examinations. Discrepancies in CT dosimetry using Monte Carlo-derived coefficients originating from the use of: (a) Conversion coefficients derived for axial CT exposures, (b) a mathematical anthropomorphic phantom of standard body size to derive conversion coefficients, and (c) data derived for a specific CT scanner to estimate patient dose from CT examinations performed on a different scanner, were separately evaluated. The percentage differences between the normalized organ dose values derived for contiguous axial scans and the corresponding values derived for spiral scans with pitch=1 and the same total scanning length were up to 10%, while the corresponding percentage differences in normalized effective dose values were less than 0.7% for all standard CT examinations. The normalized organ dose values for standard spiral CT examinations with pitch 0.5-1.5 were found to differ from the corresponding values derived for contiguous axial scans divided by the pitch, by less than 14% while the corresponding percentage differences in normalized effective dose values were less than 1% for all standard CT examinations. Normalized effective dose values for the standard contiguous axial CT examinations derived by Monte Carlo simulation were found to considerably decrease with increasing body size of the mathematical phantom

Non-analog Monte Carlo estimators for radiation momentum deposition

International Nuclear Information System (INIS)

Hykes, Joshua M.; Densmore, Jeffery D.

2009-01-01

The standard method for calculating radiation momentum deposition in Monte Carlo simulations is the analog estimator, which tallies the change in a particle's momentum at each interaction with the matter. Unfortunately, the analog estimator can suffer from large amounts of statistical error. In this paper, we present three new non-analog techniques for estimating momentum deposition. Specifically, we use absorption, collision, and track-length estimators to evaluate a simple integral expression for momentum deposition that does not contain terms that can cause large amounts of statistical error in the analog scheme. We compare our new non-analog estimators to the analog estimator with a set of test problems that encompass a wide range of material properties and both isotropic and anisotropic scattering. In nearly all cases, the new non-analog estimators outperform the analog estimator. The track-length estimator consistently yields the highest performance gains, improving upon the analog-estimator figure of merit by factors of up to two orders of magnitude.

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...

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.

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)

Exploring the use of a deterministic adjoint flux calculation in criticality Monte Carlo simulations

International Nuclear Information System (INIS)

Jinaphanh, A.; Miss, J.; Richet, Y.; Martin, N.; Hebert, A.

2011-01-01

The paper presents a preliminary study on the use of a deterministic adjoint flux calculation to improve source convergence issues by reducing the number of iterations needed to reach the converged distribution in criticality Monte Carlo calculations. Slow source convergence in Monte Carlo eigenvalue calculations may lead to underestimate the effective multiplication factor or reaction rates. The convergence speed depends on the initial distribution and the dominance ratio. We propose using an adjoint flux estimation to modify the transition kernel according to the Importance Sampling technique. This adjoint flux is also used as the initial guess of the first generation distribution for the Monte Carlo simulation. Calculated Variance of a local estimator of current is being checked. (author)

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.

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

Indian Academy of Sciences (India)

The simulation shows that theobtained results are in good agreement with experimental data, and better than the theoretical XCOM values. The study indicates that MCNP simulation is an excellent tool to estimate the iron concentration in the blood samples. The MCNP code can also be utilized to estimate other trace ...

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

Monte Carlo Simulation for Particle Detectors

CERN Document Server

Pia, Maria Grazia

2012-01-01

Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

Energy Technology Data Exchange (ETDEWEB)

Grimes, Joshua, E-mail: grimes.joshua@mayo.edu [Department of Physics and Astronomy, University of British Columbia, Vancouver V5Z 1L8 (Canada); Celler, Anna [Department of Radiology, University of British Columbia, Vancouver V5Z 1L8 (Canada)

2014-09-15

Purpose: The authors’ objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate. Methods: Six patients injected with{sup 99m}Tc-hydrazinonicotinamide-Tyr{sup 3}-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate {sup 99m}Tc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for {sup 131}I, {sup 177}Lu, and {sup 90}Y assuming the same biological half-lives as the {sup 99m}Tc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for {sup 99m}Tc, {sup 131}I, {sup 177}Lu, and {sup 90}Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique. Results: The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume (D90

Monte Carlo Simulation of stepping source in afterloading intracavitary brachytherapy for GZP6 unit

International Nuclear Information System (INIS)

Toossi, M.T.B.; Abdollahi, M.; Ghorbani, M.

2010-01-01

Full text: Stepping source in brachytherapy systems is used to treat a target lesion longer than the effective treatment length of the source. Dose calculation accuracy plays a vital role in the outcome of brachytherapy treatment. In this study, the stepping source (channel 6) of GZP6 brachytherapy unit was simulated by Monte Carlo simulation and matrix shift method. The stepping source of GZP6 was simulated by Monte Carlo MCNPX code. The Mesh tally (type I) was employed for absorbed dose calculation in a cylindrical water phantom. 5 x 108 photon histories were scored and a 0.2% statistical uncertainty was obtained by Monte Carlo calculations. Dose distributions were obtained by our matrix shift method for esophageal cancer tumor lengths of 8 and 10 cm. Isodose curves produced by simulation and TPS were superimposed to estimate the differences. Results Comparison of Monte Carlo and TPS dose distributions show that in longitudinal direction (source movement direction) Monte Carlo and TPS dose distributions are comparable. [n transverse direction, the dose differences of 7 and 5% were observed for esophageal tumor lengths of 8 and 10 cm respectively. Conclusions Although, the results show that the maximum difference between Monte Carlo and TPS calculations is about 7%, but considering that the certified activity is given with ± I 0%, uncertainty, then an error of the order of 20% for Monte Carlo calculation would be reasonable. It can be suggested that accuracy of the dose distribution produced by TPS is acceptable for clinical applications. (author)

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

Science.gov (United States)

Kanjilal, Oindrila; Manohar, C. S.

2017-07-01

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.

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.

CORPORATE VALUATION USING TWO-DIMENSIONAL MONTE CARLO SIMULATION

Directory of Open Access Journals (Sweden)

Toth Reka

2010-12-01

Full Text Available In this paper, we have presented a corporate valuation model. The model combine several valuation methods in order to get more accurate results. To determine the corporate asset value we have used the Gordon-like two-stage asset valuation model based on the calculation of the free cash flow to the firm. We have used the free cash flow to the firm to determine the corporate market value, which was calculated with use of the Black-Scholes option pricing model in frame of the two-dimensional Monte Carlo simulation method. The combined model and the use of the two-dimensional simulation model provides a better opportunity for the corporate value estimation.

Monte Carlo simulation study of the muon-induced neutron flux at LNGS

International Nuclear Information System (INIS)

Persiani, R.; Garbini, M.; Massoli, F.; Sartorelli, G; Selvi, M.

2011-01-01

Muon-induced neutrons are ultimate background for all the experiments searching for rare events in underground laboratories. Several measurements and simulations were performed concerning the neutron production and propagation but there are disagreements between experimental data and simulations. In this work we present our Monte-Carlo simulation study, based on Geant4, to estimate the muon-induced neutron flux at LNGS. The obtained integral flux of neutrons above 1 MeV is 2.31 x 10 -10 n/cm 2 /s.

Monte-Carlo estimation of the inflight performance of the GEMS satellite x-ray polarimeter

Science.gov (United States)

Kitaguchi, Takao; Tamagawa, Toru; Hayato, Asami; Enoto, Teruaki; Yoshikawa, Akifumi; Kaneko, Kenta; Takeuchi, Yoko; Black, Kevin; Hill, Joanne; Jahoda, Keith; Krizmanic, John; Sturner, Steven; Griffiths, Scott; Kaaret, Philip; Marlowe, Hannah

2014-07-01

We report a Monte-Carlo estimation of the in-orbit performance of a cosmic X-ray polarimeter designed to be installed on the focal plane of a small satellite. The simulation uses GEANT for the transport of photons and energetic particles and results from Magboltz for the transport of secondary electrons in the detector gas. We validated the simulation by comparing spectra and modulation curves with actual data taken with radioactive sources and an X-ray generator. We also estimated the in-orbit background induced by cosmic radiation in low Earth orbit.

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

International Nuclear Information System (INIS)

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

1994-01-01

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

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 

Dynamic Monte Carlo Simulations of Phase Ordering in Br Electrosorption on Ag(100)

Science.gov (United States)

Mitchell, S. J.; Brown, G.; Rikvold, P. A.

2000-03-01

We study the dynamics of Br electrosorption on single-crystal Ag(100) by Monte Carlo simulation. The system has a second-order phase transition from a low-coverage disordered phase at more negative potentials to a doubly degenerate c(2× 2) ordered phase at more positive potentials.(B.M. Ocko, et al.), Phys. Rev. Lett. 79, 1511 (1997). Effective lateral interactions were estimated by fitting equilibrium Monte Carlo isotherms to experiments. These are well described by nearest-neighbor exclusion and repulsive 1/r^3 interactions.(M.T.M. Koper, J. Electroanal. Chem. 450), 189 (1997). Considering adsorption/desorption and diffusion with barriers estimated from ab-initio calculations,(A. Ignaczak and J.A.N.F. Gomes, J. Electroanal. Chem. 420), 71 (1997). we simulate the time dependent Br coverage, order parameter, and x-ray scattering intensity following sudden potential steps across the phase boundary. For steps far into the ordered phase, dynamical scaling is observed. For smaller steps, the dynamics are more complicated. We also analyze hysteresis in a simulated cyclic-voltammetry experiment. Movies at http://www.scri.fsu.edu/ ~mitchell/.

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.

Reducing uncertainty of Monte Carlo estimated fatigue damage in offshore wind turbines using FORM

DEFF Research Database (Denmark)

H. Horn, Jan-Tore; Jensen, Jørgen Juncher

2016-01-01

Uncertainties related to fatigue damage estimation of non-linear systems are highly dependent on the tail behaviour and extreme values of the stress range distribution. By using a combination of the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), the accuracy of the fatigue...

Monte Carlo simulation for slip rate sensitivity analysis in Cimandiri fault area

Energy Technology Data Exchange (ETDEWEB)

Pratama, Cecep, E-mail: great.pratama@gmail.com [Graduate Program of Earth Science, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Meilano, Irwan [Geodesy Research Division, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Nugraha, Andri Dian [Global Geophysical Group, Faculty of Mining and Petroleum Engineering, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia)

2015-04-24

Slip rate is used to estimate earthquake recurrence relationship which is the most influence for hazard level. We examine slip rate contribution of Peak Ground Acceleration (PGA), in probabilistic seismic hazard maps (10% probability of exceedance in 50 years or 500 years return period). Hazard curve of PGA have been investigated for Sukabumi using a PSHA (Probabilistic Seismic Hazard Analysis). We observe that the most influence in the hazard estimate is crustal fault. Monte Carlo approach has been developed to assess the sensitivity. Then, Monte Carlo simulations properties have been assessed. Uncertainty and coefficient of variation from slip rate for Cimandiri Fault area has been calculated. We observe that seismic hazard estimates is sensitive to fault slip rate with seismic hazard uncertainty result about 0.25 g. For specific site, we found seismic hazard estimate for Sukabumi is between 0.4904 – 0.8465 g with uncertainty between 0.0847 – 0.2389 g and COV between 17.7% – 29.8%.

Monte Carlo simulation in statistical physics an introduction

CERN Document Server

Binder, Kurt

1992-01-01

The Monte Carlo method is a computer simulation method which uses random numbers to simulate statistical fluctuations The method is used to model complex systems with many degrees of freedom Probability distributions for these systems are generated numerically and the method then yields numerically exact information on the models Such simulations may be used tosee how well a model system approximates a real one or to see how valid the assumptions are in an analyical theory A short and systematic theoretical introduction to the method forms the first part of this book The second part is a practical guide with plenty of examples and exercises for the student Problems treated by simple sampling (random and self-avoiding walks, percolation clusters, etc) are included, along with such topics as finite-size effects and guidelines for the analysis of Monte Carlo simulations The two parts together provide an excellent introduction to the theory and practice of Monte Carlo simulations

IVF cycle cost estimation using Activity Based Costing and Monte Carlo simulation.

Science.gov (United States)

Cassettari, Lucia; Mosca, Marco; Mosca, Roberto; Rolando, Fabio; Costa, Mauro; Pisaturo, Valerio

2016-03-01

The Authors present a new methodological approach in stochastic regime to determine the actual costs of an healthcare process. The paper specifically shows the application of the methodology for the determination of the cost of an Assisted reproductive technology (ART) treatment in Italy. The reason of this research comes from the fact that deterministic regime is inadequate to implement an accurate estimate of the cost of this particular treatment. In fact the durations of the different activities involved are unfixed and described by means of frequency distributions. Hence the need to determine in addition to the mean value of the cost, the interval within which it is intended to vary with a known confidence level. Consequently the cost obtained for each type of cycle investigated (in vitro fertilization and embryo transfer with or without intracytoplasmic sperm injection), shows tolerance intervals around the mean value sufficiently restricted as to make the data obtained statistically robust and therefore usable also as reference for any benchmark with other Countries. It should be noted that under a methodological point of view the approach was rigorous. In fact it was used both the technique of Activity Based Costing for determining the cost of individual activities of the process both the Monte Carlo simulation, with control of experimental error, for the construction of the tolerance intervals on the final result.

Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

KAUST Repository

Moraes, Alvaro

2015-01-07

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

Propagation of uncertainty in nasal spray in vitro performance models using Monte Carlo simulation: Part II. Error propagation during product performance modeling.

Science.gov (United States)

Guo, Changning; Doub, William H; Kauffman, John F

2010-08-01

Monte Carlo simulations were applied to investigate the propagation of uncertainty in both input variables and response measurements on model prediction for nasal spray product performance design of experiment (DOE) models in the first part of this study, with an initial assumption that the models perfectly represent the relationship between input variables and the measured responses. In this article, we discard the initial assumption, and extended the Monte Carlo simulation study to examine the influence of both input variable variation and product performance measurement variation on the uncertainty in DOE model coefficients. The Monte Carlo simulations presented in this article illustrate the importance of careful error propagation during product performance modeling. Our results show that the error estimates based on Monte Carlo simulation result in smaller model coefficient standard deviations than those from regression methods. This suggests that the estimated standard deviations from regression may overestimate the uncertainties in the model coefficients. Monte Carlo simulations provide a simple software solution to understand the propagation of uncertainty in complex DOE models so that design space can be specified with statistically meaningful confidence levels. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Monte Carlo simulated dynamical magnetization of single-chain magnets

Energy Technology Data Exchange (ETDEWEB)

Li, Jun; Liu, Bang-Gui, E-mail: bgliu@iphy.ac.cn

2015-03-15

Here, a dynamical Monte-Carlo (DMC) method is used to study temperature-dependent dynamical magnetization of famous Mn{sub 2}Ni system as typical example of single-chain magnets with strong magnetic anisotropy. Simulated magnetization curves are in good agreement with experimental results under typical temperatures and sweeping rates, and simulated coercive fields as functions of temperature are also consistent with experimental curves. Further analysis indicates that the magnetization reversal is determined by both thermal-activated effects and quantum spin tunnelings. These can help explore basic properties and applications of such important magnetic systems. - Highlights: • Monte Carlo simulated magnetization curves are in good agreement with experimental results. • Simulated coercive fields as functions of temperature are consistent with experimental results. • The magnetization reversal is understood in terms of the Monte Carlo simulations.

Direct Monte Carlo simulation of nanoscale mixed gas bearings

Directory of Open Access Journals (Sweden)

Kyaw Sett Myo

2015-06-01

Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.

Investigation of Compton scattering correction methods in cardiac SPECT by Monte Carlo simulations

International Nuclear Information System (INIS)

Silva, A.M. Marques da; Furlan, A.M.; Robilotta, C.C.

2001-01-01

The goal of this work was the use of Monte Carlo simulations to investigate the effects of two scattering correction methods: dual energy window (DEW) and dual photopeak window (DPW), in quantitative cardiac SPECT reconstruction. MCAT torso-cardiac phantom, with 99m Tc and non-uniform attenuation map was simulated. Two different photopeak windows were evaluated in DEW method: 15% and 20%. Two 10% wide subwindows centered symmetrically within the photopeak were used in DPW method. Iterative ML-EM reconstruction with modified projector-backprojector for attenuation correction was applied. Results indicated that the choice of the scattering and photopeak windows determines the correction accuracy. For the 15% window, fitted scatter fraction gives better results than k = 0.5. For the 20% window, DPW is the best method, but it requires parameters estimation using Monte Carlo simulations. (author)

Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2014-01-01

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model

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

Monte-Carlo background simulations of present and future detectors in x-ray astronomy

Science.gov (United States)

Tenzer, C.; Kendziorra, E.; Santangelo, A.

2008-07-01

Reaching a low-level and well understood internal instrumental background is crucial for the scientific performance of an X-ray detector and, therefore, a main objective of the instrument designers. Monte-Carlo simulations of the physics processes and interactions taking place in a space-based X-ray detector as a result of its orbital environment can be applied to explain the measured background of existing missions. They are thus an excellent tool to predict and optimize the background of future observatories. Weak points of a design and the main sources of the background can be identified and methods to reduce them can be implemented and studied within the simulations. Using the Geant4 Monte-Carlo toolkit, we have created a simulation environment for space-based detectors and we present results of such background simulations for XMM-Newton's EPIC pn-CCD camera. The environment is also currently used to estimate and optimize the background of the future instruments Simbol-X and eRosita.

Monte Carlo simulation for the estimation of the glandular breast dose for a digital breast tomosynthesis system

International Nuclear Information System (INIS)

Rodrigues, Leonardo; Braz, Delson; Goncalves Magalhaes, Luis Alexandre

2015-01-01

Digital breast tomosynthesis (DBT) is a screening and diagnostic modality that acquires images of the breast at multiple angles during a short scan. The Selenia Dimensions (Hologic, Bedford, Mass) DBT system can perform both full-field digital mammography and DBT. The system acquires 15 projections over a 15 deg. angular range (from -7.5 deg. to +7.5 deg.). An important factor in determining the optimal imaging technique for breast tomosynthesis is the radiation dose. In breast imaging, the radiation dose of concern is that deposited in the glandular tissue of the breast because this is the tissue that has a risk of developing cancer. The concept of the normalised mean glandular dose (DgN) has been introduced as the metric for the dose in breast imaging. The DgN is difficult to measure. The Monte Carlo techniques offer an alternative method for a realistic estimation of the radiation dose. The purpose of this work was to use the Monte Carlo code MCNPX technique to generate monoenergetic glandular dose data for estimating the breast tissue dose in tomosynthesis for arbitrary spectra as well as to observe the deposited radiation dose by projection on the glandular portion of the breast in a Selenia Dimensions DBT system. A Monte Carlo simulation of the system was developed to compute the DgN in a craniocaudal view. Monoenergetic X-ray beams from 10 to 49 keV in 1-keV increments were used. The simulation utilised the assumption of a homogeneous breast composition and three compositions (0 % glandular, 50 % glandular and 100 % glandular). The glandular and adipose tissue compositions were specified according ICRU Report 44. A skin layer of 4 mm was assumed to encapsulate the breast on all surfaces. The breast size was varied using the chest wall-to-nipple distance (CND) and compressed breast thickness (t). In this work, the authors assumed a CND of 5 cm and the thicknesses ranged from 2 to 8 cm, in steps of 2 cm. The fractional energy absorption increases (up to 44

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

Directory of Open Access Journals (Sweden)

José Luiz Ferreira Martins

2011-09-01

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

Monte Carlo simulation of continuous-space crystal growth

International Nuclear Information System (INIS)

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

1986-01-01

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

LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events

CERN Document Server

Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V

2008-01-01

In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.

The Monte Carlo Simulation Method for System Reliability and Risk Analysis

CERN Document Server

Zio, Enrico

2013-01-01

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

The adaptation method in the Monte Carlo simulation for computed tomography

Energy Technology Data Exchange (ETDEWEB)

Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)

2015-06-15

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

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.

Monte Carlo simulation of neutron counters for safeguards applications

International Nuclear Information System (INIS)

Looman, Marc; Peerani, Paolo; Tagziria, Hamid

2009-01-01

MCNP-PTA is a new Monte Carlo code for the simulation of neutron counters for nuclear safeguards applications developed at the Joint Research Centre (JRC) in Ispra (Italy). After some preliminary considerations outlining the general aspects involved in the computational modelling of neutron counters, this paper describes the specific details and approximations which make up the basis of the model implemented in the code. One of the major improvements allowed by the use of Monte Carlo simulation is a considerable reduction in both the experimental work and in the reference materials required for the calibration of the instruments. This new approach to the calibration of counters using Monte Carlo simulation techniques is also discussed.

MC 93 - Proceedings of the International Conference on Monte Carlo Simulation in High Energy and Nuclear Physics

Science.gov (United States)

Dragovitsch, Peter; Linn, Stephan L.; Burbank, Mimi

1994-01-01

Calorimeter Geometry * Simulations with EGS4/PRESTA for Thin Si Sampling Calorimeter * SIBERIA -- Monte Carlo Code for Simulation of Hadron-Nuclei Interactions * CALOR89 Predictions for the Hanging File Test Configurations * Estimation of the Multiple Coulomb Scattering Error for Various Numbers of Radiation Lengths * Monte Carlo Generator for Nuclear Fragmentation Induced by Pion Capture * Calculation and Randomization of Hadron-Nucleus Reaction Cross Section * Developments in GEANT Physics * Status of the MC++ Event Generator Toolkit * Theoretical Overview of QCD Event Generators * Random Numbers? * Simulation of the GEM LKr Barrel Calorimeter Using CALOR89 * Recent Improvement of the EGS4 Code, Implementation of Linearly Polarized Photon Scattering * Interior-Flux Simulation in Enclosures with Electron-Emitting Walls * Some Recent Developments in Global Determinations of Parton Distributions * Summary of the Workshop on Simulating Accelerator Radiation Environments * Simulating the SDC Radiation Background and Activation * Applications of Cluster Monte Carlo Method to Lattice Spin Models * PDFLIB: A Library of All Available Parton Density Functions of the Nucleon, the Pion and the Photon and the Corresponding αs Calculations * DTUJET92: Sampling Hadron Production at Supercolliders * A New Model for Hadronic Interactions at Intermediate Energies for the FLUKA Code * Matrix Generator of Pseudo-Random Numbers * The OPAL Monte Carlo Production System * Monte Carlo Simulation of the Microstrip Gas Counter * Inner Detector Simulations in ATLAS * Simulation and Reconstruction in H1 Liquid Argon Calorimetry * Polarization Decomposition of Fluxes and Kinematics in ep Reactions * Towards Object-Oriented GEANT -- ProdiG Project * Parallel Processing of AMY Detector Simulation on Fujitsu AP1000 * Enigma: An Event Generator for Electron-Photon- or Pion-Induced Events in the ~1 GeV Region * SSCSIM: Development and Use by the Fermilab SDC Group * The GEANT-CALOR Interface

Estimation of Adjoint-Weighted Kinetics Parameters in Monte Carlo Wieland Calculations

International Nuclear Information System (INIS)

Choi, Sung Hoon; Shim, Hyung Jin

2013-01-01

The effective delayed neutron fraction, β eff , and the prompt neutron generation time, Λ, in the point kinetics equation are weighted by the adjoint flux to improve the accuracy of the reactivity estimate. Recently the Monte Carlo (MC) kinetics parameter estimation methods by using the self-consistent adjoint flux calculated in the MC forward simulations have been developed and successfully applied for the research reactor analyses. However these adjoint estimation methods based on the cycle-by-cycle genealogical table require a huge memory size to store the pedigree hierarchy. In this paper, we present a new adjoint estimation in which the pedigree of a single history is utilized by applying the MC Wielandt method. The effectiveness of the new method is demonstrated in the kinetics parameter estimations for infinite homogeneous two-group problems and the Godiva critical facility

Radiotherapy Monte Carlo simulation using cloud computing technology.

Science.gov (United States)

Poole, C M; Cornelius, I; Trapp, J V; Langton, C M

2012-12-01

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

Radiotherapy Monte Carlo simulation using cloud computing technology

International Nuclear Information System (INIS)

Poole, C.M.; Cornelius, I.; Trapp, J.V.; Langton, C.M.

2012-01-01

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

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.

Monte Carlo simulation of grain growth

Directory of Open Access Journals (Sweden)

Paulo Blikstein

1999-07-01

Full Text Available Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical behavior of the atoms is properly reproduced; microstructural evolution depends only on the real topology of the grains and not on any kind of geometric simplification. Computer simulation has the advantage of allowing the user to visualize graphically the procedures, even dynamically and in three dimensions. Single-phase alloy grain growth simulation was carried out by calculating the free energy of each atom in the lattice (with its present crystallographic orientation and comparing this value to another one calculated with a different random orientation. When the resulting free energy is lower or equal to the initial value, the new orientation replaces the former. The measure of time is the Monte Carlo Step (MCS, which involves a series of trials throughout the lattice. A very close relationship between experimental and theoretical values for the grain growth exponent (n was observed.

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.

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)

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

Science.gov (United States)

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model

Science.gov (United States)

Ferrenberg, Alan M.; Xu, Jiahao; Landau, David P.

2018-04-01

While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.

Estimation of computed tomography dose index in cone beam computed tomography: MOSFET measurements and Monte Carlo simulations.

Science.gov (United States)

Kim, Sangroh; Yoshizumi, Terry; Toncheva, Greta; Yoo, Sua; Yin, Fang-Fang; Frush, Donald

2010-05-01

To address the lack of accurate dose estimation method in cone beam computed tomography (CBCT), we performed point dose metal oxide semiconductor field-effect transistor (MOSFET) measurements and Monte Carlo (MC) simulations. A Varian On-Board Imager (OBI) was employed to measure point doses in the polymethyl methacrylate (PMMA) CT phantoms with MOSFETs for standard and low dose modes. A MC model of the OBI x-ray tube was developed using BEAMnrc/EGSnrc MC system and validated by the half value layer, x-ray spectrum and lateral and depth dose profiles. We compared the weighted computed tomography dose index (CTDIw) between MOSFET measurements and MC simulations. The CTDIw was found to be 8.39 cGy for the head scan and 4.58 cGy for the body scan from the MOSFET measurements in standard dose mode, and 1.89 cGy for the head and 1.11 cGy for the body in low dose mode, respectively. The CTDIw from MC compared well to the MOSFET measurements within 5% differences. In conclusion, a MC model for Varian CBCT has been established and this approach may be easily extended from the CBCT geometry to multi-detector CT geometry.

Monte-Carlo simulation of electromagnetic showers

International Nuclear Information System (INIS)

Amatuni, Ts.A.

1984-01-01

The universal ELSS-1 program for Monte Carlo simulation of high energy electromagnetic showers in homogeneous absorbers of arbitrary geometry is written. The major processes and effects of electron and photon interaction with matter, particularly the Landau-Pomeranchuk-Migdal effect, are taken into account in the simulation procedures. The simulation results are compared with experimental data. Some characteristics of shower detectors and electromagnetic showers for energies up 1 TeV are calculated

Modern analysis of ion channeling data by Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)

2005-10-15

Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.

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

International Nuclear Information System (INIS)

Lu Yuzhao; Xie Qilin; Song Lingli; Liu Hangang

2012-01-01

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

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

Dynamic bounds coupled with Monte Carlo simulations

NARCIS (Netherlands)

Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.

2011-01-01

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper

A new Monte Carlo code for simulation of the effect of irregular surfaces on X-ray spectra

Energy Technology Data Exchange (ETDEWEB)

Brunetti, Antonio, E-mail: brunetti@uniss.it; Golosio, Bruno

2014-04-01

Generally, quantitative X-ray fluorescence (XRF) analysis estimates the content of chemical elements in a sample based on the areas of the fluorescence peaks in the energy spectrum. Besides the concentration of the elements, the peak areas depend also on the geometrical conditions. In fact, the estimate of the peak areas is simple if the sample surface is smooth and if the spectrum shows a good statistic (large-area peaks). For this reason often the sample is prepared as a pellet. However, this approach is not always feasible, for instance when cultural heritage or valuable samples must be analyzed. In this case, the sample surface cannot be smoothed. In order to address this problem, several works have been reported in the literature, based on experimental measurements on a few sets of specific samples or on Monte Carlo simulations. The results obtained with the first approach are limited by the specific class of samples analyzed, while the second approach cannot be applied to arbitrarily irregular surfaces. The present work describes a more general analysis tool based on a new fast Monte Carlo algorithm, which is virtually able to simulate any kind of surface. At the best of our knowledge, it is the first Monte Carlo code with this option. A study of the influence of surface irregularities on the measured spectrum is performed and some results reported. - Highlights: • We present a fast Monte Carlo code with the possibility to simulate any irregularly rough surfaces. • We show applications to multilayer measurements. • Real time simulations are available.

Quantum Mechanical Single Molecule Partition Function from PathIntegral Monte Carlo Simulations

Energy Technology Data Exchange (ETDEWEB)

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

2006-10-01

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

Stock Price Simulation Using Bootstrap and Monte Carlo

Directory of Open Access Journals (Sweden)

Pažický Martin

2017-06-01

Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.

Monte-Carlo Simulation for PDC-Based Optical CDMA System

Directory of Open Access Journals (Sweden)

FAHIM AZIZ UMRANI

2010-10-01

Full Text Available This paper presents the Monte-Carlo simulation of Optical CDMA (Code Division Multiple Access systems, and analyse its performance in terms of the BER (Bit Error Rate. The spreading sequence chosen for CDMA is Perfect Difference Codes. Furthermore, this paper derives the expressions of noise variances from first principles to calibrate the noise for both bipolar (electrical domain and unipolar (optical domain signalling required for Monte-Carlo simulation. The simulated results conform to the theory and show that the receiver gain mismatch and splitter loss at the transceiver degrades the system performance.

Using Monte Carlo Simulation To Improve Cargo Mass Estimates For International Space Station Commercial Resupply Flights

Science.gov (United States)

2016-12-01

The Challenges of ISS Resupply .......................................... 23 F. THE IMPORTANCE OF MASS PROPERTIES IN SPACECRAFT AND MISSION DESIGN...Transportation System TBA trundle bearing assembly VLC verification loads cycle xv EXECUTIVE SUMMARY Resupplying the International Space Station...management priorities. This study addresses those challenges by developing Monte Carlo simulations based on over 13 years of as- flownSS resupply

Monte Carlo simulation of medical linear accelerator using primo code

International Nuclear Information System (INIS)

Omer, Mohamed Osman Mohamed Elhasan

2014-12-01

The use of monte Carlo simulation has become very important in the medical field and especially in calculation in radiotherapy. Various Monte Carlo codes were developed simulating interactions of particles and photons with matter. One of these codes is PRIMO that performs simulation of radiation transport from the primary electron source of a linac to estimate the absorbed dose in a water phantom or computerized tomography (CT). PRIMO is based on Penelope Monte Carlo code. Measurements of 6 MV photon beam PDD and profile were done for Elekta precise linear accelerator at Radiation and Isotopes Center Khartoum using computerized Blue water phantom and CC13 Ionization Chamber. accept Software was used to control the phantom to measure and verify dose distribution. Elektalinac from the list of available linacs in PRIMO was tuned to model Elekta precise linear accelerator. Beam parameter of 6.0 MeV initial electron energy, 0.20 MeV FWHM, and 0.20 cm focal spot FWHM were used, and an error of 4% between calculated and measured curves was found. The buildup region Z max was 1.40 cm and homogenous profile in cross line and in line were acquired. A number of studies were done to verily the model usability one of them is the effect of the number of histories on accuracy of the simulation and the resulted profile for the same beam parameters. The effect was noticeable and inaccuracies in the profile were reduced by increasing the number of histories. Another study was the effect of Side-step errors on the calculated dose which was compared with the measured dose for the same setting.It was in range of 2% for 5 cm shift, but it was higher in the calculated dose because of the small difference between the tuned model and measured dose curves. Future developments include simulating asymmetrical fields, calculating the dose distribution in computerized tomographic (CT) volume, studying the effect of beam modifiers on beam profile for both electron and photon beams.(Author)

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)

Cross talk in the Lambert-Beer calculation for near-infrared wavelengths estimated by Monte Carlo simulations.

Science.gov (United States)

Uludag, K; Kohl, M; Steinbrink, J; Obrig, H; Villringer, A

2002-01-01

Using the modified Lambert-Beer law to analyze attenuation changes measured noninvasively during functional activation of the brain might result in an insufficient separation of chromophore changes ("cross talk") due to the wavelength dependence of the partial path length of photons in the activated volume of the head. The partial path length was estimated by performing Monte Carlo simulations on layered head models. When assuming cortical activation (e.g., in the depth of 8-12 mm), we determine negligible cross talk when considering changes in oxygenated and deoxygenated hemoglobin. But additionally taking changes in the redox state of cytochrome-c-oxidase into account, this analysis results in significant artifacts. An analysis developed for changes in mean time of flight--instead of changes in attenuation--reduces the cross talk for the layers of cortical activation. These results were validated for different oxygen saturations, wavelength combinations and scattering coefficients. For the analysis of changes in oxygenated and deoxygenated hemoglobin only, low cross talk was also found when the activated volume was assumed to be a 4-mm-diam sphere.

Monte Carlo simulations of the radiation environment for the CMS experiment

Energy Technology Data Exchange (ETDEWEB)

Mallows, S., E-mail: sophie.mallows@cern.ch [KIT, Karlsruhe (Germany); Azhgirey, I.; Bayshev, I. [IHEP, Protvino (Russian Federation); Bergstrom, I.; Cooijmans, T.; Dabrowski, A.; Glöggler, L.; Guthoff, M. [CERN, Geneva (Switzerland); Kurochkin, I. [IHEP, Protvino (Russian Federation); Vincke, H.; Tajeda, S. [CERN, Geneva (Switzerland)

2016-07-11

Monte Carlo radiation transport codes are used by the CMS Beam Radiation Instrumentation and Luminosity (BRIL) project to estimate the radiation levels due to proton–proton collisions and machine induced background. Results are used by the CMS collaboration for various applications: comparison with detector hit rates, pile-up studies, predictions of radiation damage based on various models (Dose, NIEL, DPA), shielding design, estimations of residual dose environment. Simulation parameters, and the maintenance of the input files are summarized, and key results are presented. Furthermore, an overview of additional programs developed by the BRIL project to meet the specific needs of CMS community is given.

Monte Carlo simulations of the radiation environment for the CMS Experiment

CERN Document Server

AUTHOR|(CDS)2068566; Bayshev, I.; Bergstrom, I.; Cooijmans, T.; Dabrowski, A.; Glöggler, L.; Guthoff, M.; Kurochkin, I.; Vincke, H.; Tajeda, S.

2016-01-01

Monte Carlo radiation transport codes are used by the CMS Beam Radiation Instrumentation and Luminosity (BRIL) project to estimate the radiation levels due to proton-proton collisions and machine induced background. Results are used by the CMS collaboration for various applications: comparison with detector hit rates, pile-up studies, predictions of radiation damage based on various models (Dose, NIEL, DPA), shielding design, estimations of residual dose environment. Simulation parameters, and the maintenance of the input files are summarised, and key results are presented. Furthermore, an overview of additional programs developed by the BRIL project to meet the specific needs of CMS community is given.

Scouting the feasibility of Monte Carlo reactor dynamics simulations

International Nuclear Information System (INIS)

Legrady, David; Hoogenboom, J. Eduard

2008-01-01

In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

Scouting the feasibility of Monte Carlo reactor dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)

2008-07-01

In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses

Energy Technology Data Exchange (ETDEWEB)

ALAM,TODD M.

1999-12-21

Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

Lattice gauge theories and Monte Carlo simulations

International Nuclear Information System (INIS)

Rebbi, C.

1981-11-01

After some preliminary considerations, the discussion of quantum gauge theories on a Euclidean lattice takes up the definition of Euclidean quantum theory and treatment of the continuum limit; analogy is made with statistical mechanics. Perturbative methods can produce useful results for strong or weak coupling. In the attempts to investigate the properties of the systems for intermediate coupling, numerical methods known as Monte Carlo simulations have proved valuable. The bulk of this paper illustrates the basic ideas underlying the Monte Carlo numerical techniques and the major results achieved with them according to the following program: Monte Carlo simulations (general theory, practical considerations), phase structure of Abelian and non-Abelian models, the observables (coefficient of the linear term in the potential between two static sources at large separation, mass of the lowest excited state with the quantum numbers of the vacuum (the so-called glueball), the potential between two static sources at very small distance, the critical temperature at which sources become deconfined), gauge fields coupled to basonic matter (Higgs) fields, and systems with fermions

Monte Carlo simulations in skin radiotherapy

International Nuclear Information System (INIS)

Sarvari, A.; Jeraj, R.; Kron, T.

2000-01-01

The primary goal of this work was to develop a procedure for calculation the appropriate filter shape for a brachytherapy applicator used for skin radiotherapy. In the applicator a radioactive source is positioned close to the skin. Without a filter, the resultant dose distribution would be highly nonuniform.High uniformity is usually required however. This can be achieved using an appropriately shaped filter, which flattens the dose profile. Because of the complexity of the transport and geometry, Monte Carlo simulations had to be used. An 192 Ir high dose rate photon source was used. All necessary transport parameters were simulated with the MCNP4B Monte Carlo code. A highly efficient iterative procedure was developed, which enabled calculation of the optimal filter shape in only few iterations. The initially non-uniform dose distributions became uniform within a percent when applying the filter calculated by this procedure. (author)

Closed-shell variational quantum Monte Carlo simulation for the ...

African Journals Online (AJOL)

Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.

CloudMC: a cloud computing application for Monte Carlo simulation

International Nuclear Information System (INIS)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-01-01

This work presents CloudMC, a cloud computing application—developed in Windows Azure®, the platform of the Microsoft® cloud—for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based—the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice. (note)

CloudMC: a cloud computing application for Monte Carlo simulation.

Science.gov (United States)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

Monte Carlo simulation for pixel detectors: a feasibility study for X radiation applications

International Nuclear Information System (INIS)

Marinho, F.; Akiba, K.

2014-01-01

In this paper we analyze the feasibility of a Monte Carlo simulation for the description of pixel semiconductor detectors as a tool for research and development of such devices and their applications for X-rays. We present as a result the technical aspects and main characteristics of a set of algorithms recently developed which allows one to estimate the energy spectrum and cluster classification. (author)

Monte Carlo simulation with the Gate software using grid computing

International Nuclear Information System (INIS)

Reuillon, R.; Hill, D.R.C.; Gouinaud, C.; El Bitar, Z.; Breton, V.; Buvat, I.

2009-03-01

Monte Carlo simulations are widely used in emission tomography, for protocol optimization, design of processing or data analysis methods, tomographic reconstruction, or tomograph design optimization. Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the 'Multiple Replications In Parallel' approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-science), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses. (authors)

Monte Carlo simulation on kinetics of batch and semi-batch free radical polymerization

KAUST Repository

Shao, Jing

2015-10-27

Based on Monte Carlo simulation technology, we proposed a hybrid routine which combines reaction mechanism together with coarse-grained molecular simulation to study the kinetics of free radical polymerization. By comparing with previous experimental and simulation studies, we showed the capability of our Monte Carlo scheme on representing polymerization kinetics in batch and semi-batch processes. Various kinetics information, such as instant monomer conversion, molecular weight, and polydispersity etc. are readily calculated from Monte Carlo simulation. The kinetic constants such as polymerization rate k p is determined in the simulation without of “steady-state” hypothesis. We explored the mechanism for the variation of polymerization kinetics those observed in previous studies, as well as polymerization-induced phase separation. Our Monte Carlo simulation scheme is versatile on studying polymerization kinetics in batch and semi-batch processes.

Experimental validation of a rapid Monte Carlo based micro-CT simulator

International Nuclear Information System (INIS)

Colijn, A P; Zbijewski, W; Sasov, A; Beekman, F J

2004-01-01

We describe a newly developed, accelerated Monte Carlo simulator of a small animal micro-CT scanner. Transmission measurements using aluminium slabs are employed to estimate the spectrum of the x-ray source. The simulator incorporating this spectrum is validated with micro-CT scans of physical water phantoms of various diameters, some containing stainless steel and Teflon rods. Good agreement is found between simulated and real data: normalized error of simulated projections, as compared to the real ones, is typically smaller than 0.05. Also the reconstructions obtained from simulated and real data are found to be similar. Thereafter, effects of scatter are studied using a voxelized software phantom representing a rat body. It is shown that the scatter fraction can reach tens of per cents in specific areas of the body and therefore scatter can significantly affect quantitative accuracy in small animal CT imaging

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans.

Science.gov (United States)

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2017-03-07

The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients' CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

Science.gov (United States)

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2017-03-01

The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.

Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

Science.gov (United States)

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...

Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations

Directory of Open Access Journals (Sweden)

Roberto S. Flowers-Cano

2018-02-01

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

Clinical trial optimization: Monte Carlo simulation Markov model for planning clinical trials recruitment.

Science.gov (United States)

Abbas, Ismail; Rovira, Joan; Casanovas, Josep

2007-05-01

The patient recruitment process of clinical trials is an essential element which needs to be designed properly. In this paper we describe different simulation models under continuous and discrete time assumptions for the design of recruitment in clinical trials. The results of hypothetical examples of clinical trial recruitments are presented. The recruitment time is calculated and the number of recruited patients is quantified for a given time and probability of recruitment. The expected delay and the effective recruitment durations are estimated using both continuous and discrete time modeling. The proposed type of Monte Carlo simulation Markov models will enable optimization of the recruitment process and the estimation and the calibration of its parameters to aid the proposed clinical trials. A continuous time simulation may minimize the duration of the recruitment and, consequently, the total duration of the trial.

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.

Monte Carlo simulation of scatter in non-uniform symmetrical attenuating media for point and distributed sources

International Nuclear Information System (INIS)

Henry, L.J.; Rosenthal, M.S.

1992-01-01

We report results of scatter simulations for both point and distributed sources of 99m Tc in symmetrical non-uniform attenuating media. The simulations utilized Monte Carlo techniques and were tested against experimental phantoms. Both point and ring sources were used inside a 10.5 cm radius acrylic phantom. Attenuating media consisted of combinations of water, ground beef (to simulate muscle mass), air and bone meal (to simulate bone mass). We estimated/measured energy spectra, detector efficiencies and peak height ratios for all cases. In all cases, the simulated spectra agree with the experimentally measured spectra within 2 SD. Detector efficiencies and peak height ratios also are in agreement. The Monte Carlo code is able to properly model the non-uniform attenuating media used in this project. With verification of the simulations, it is possible to perform initial evaluation studies of scatter correction algorithms by evaluating the mechanisms of action of the correction algorithm on the simulated spectra where the magnitude and sources of scatter are known. (author)

Monte Carlo simulation of prompt γ-ray emission in proton therapy using a specific track length estimator

International Nuclear Information System (INIS)

El Kanawati, W; Létang, J M; Sarrut, D; Freud, N; Dauvergne, D; Pinto, M; Testa, É

2015-01-01

A Monte Carlo (MC) variance reduction technique is developed for prompt-γ emitters calculations in proton therapy. Prompt-γ emitted through nuclear fragmentation reactions and exiting the patient during proton therapy could play an important role to help monitoring the treatment. However, the estimation of the number and the energy of emitted prompt-γ per primary proton with MC simulations is a slow process. In order to estimate the local distribution of prompt-γ emission in a volume of interest for a given proton beam of the treatment plan, a MC variance reduction technique based on a specific track length estimator (TLE) has been developed. First an elemental database of prompt-γ emission spectra is established in the clinical energy range of incident protons for all elements in the composition of human tissues. This database of the prompt-γ spectra is built offline with high statistics. Regarding the implementation of the prompt-γ TLE MC tally, each proton deposits along its track the expectation of the prompt-γ spectra from the database according to the proton kinetic energy and the local material composition. A detailed statistical study shows that the relative efficiency mainly depends on the geometrical distribution of the track length. Benchmarking of the proposed prompt-γ TLE MC technique with respect to an analogous MC technique is carried out. A large relative efficiency gain is reported, ca. 10 5 . (paper)

Estimation of functional failure probability of passive systems based on subset simulation method

International Nuclear Information System (INIS)

Wang Dongqing; Wang Baosheng; Zhang Jianmin; Jiang Jing

2012-01-01

In order to solve the problem of multi-dimensional epistemic uncertainties and small functional failure probability of passive systems, an innovative reliability analysis algorithm called subset simulation based on Markov chain Monte Carlo was presented. The method is found on the idea that a small failure probability can be expressed as a product of larger conditional failure probabilities by introducing a proper choice of intermediate failure events. Markov chain Monte Carlo simulation was implemented to efficiently generate conditional samples for estimating the conditional failure probabilities. Taking the AP1000 passive residual heat removal system, for example, the uncertainties related to the model of a passive system and the numerical values of its input parameters were considered in this paper. And then the probability of functional failure was estimated with subset simulation method. The numerical results demonstrate that subset simulation method has the high computing efficiency and excellent computing accuracy compared with traditional probability analysis methods. (authors)

Stabilization effect of fission source in coupled Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Olsen, Borge; Dufek, Jan [Div. of Nuclear Reactor Technology, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm (Sweden)

2017-08-15

A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

Stabilization effect of fission source in coupled Monte Carlo simulations

Directory of Open Access Journals (Sweden)

Börge Olsen

2017-08-01

Full Text Available A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

Estimation of ex-core detector responses by adjoint Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

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

2006-07-01

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

Probability Density Estimation Using Neural Networks in Monte Carlo Calculations

International Nuclear Information System (INIS)

Shim, Hyung Jin; Cho, Jin Young; Song, Jae Seung; Kim, Chang Hyo

2008-01-01

The Monte Carlo neutronics analysis requires the capability for a tally distribution estimation like an axial power distribution or a flux gradient in a fuel rod, etc. This problem can be regarded as a probability density function estimation from an observation set. We apply the neural network based density estimation method to an observation and sampling weight set produced by the Monte Carlo calculations. The neural network method is compared with the histogram and the functional expansion tally method for estimating a non-smooth density, a fission source distribution, and an absorption rate's gradient in a burnable absorber rod. The application results shows that the neural network method can approximate a tally distribution quite well. (authors)

Monte Carlo simulation for theoretical calculations of damage and sputtering processes

International Nuclear Information System (INIS)

Yamamura, Yasunori

1984-01-01

The radiation damage accompanying ion irradiation and the various problems caused with it should be determined in principle by resolving Boltzmann's equations. However, in reality, those for a semi-infinite system cannot be generally resolved. Moreover, the effect of crystals, oblique incidence and so on make the situation more difficult. The analysis of the complicated phenomena of the collision in solids and the problems of radiation damage and sputtering accompanying them is possible in most cases only by computer simulation. At present, the methods of simulating the atomic collision phenomena in solids are roughly classified into molecular dynamics method and Monte Carlo method. In the molecular dynamics, Newton's equations are numerically calculated time-dependently as they are, and it has large merits that many body effect and nonlinear effect can be taken in consideration, but much computing time is required. The features and problems of the Monte Carlo simulation and nonlinear Monte Carlo simulation are described. The comparison of the Monte Carlo simulation codes calculating on the basis of two-body collision approximation, MARLOWE, TRIM and ACAT, was carried out through the calculation of the backscattering spectra of light ions. (Kako, I.)

Monte Carlo simulation of the microcanonical ensemble

International Nuclear Information System (INIS)

Creutz, M.

1984-01-01

We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references

Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

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

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

Estimation of Compton Imager Using Single 3D Position-Sensitive LYSO Scintillator: Monte Carlo Simulation

Energy Technology Data Exchange (ETDEWEB)

Lee, Taewoong; Lee, Hyounggun; Kim, Younghak; Lee, Wonho [Korea University, Seoul (Korea, Republic of)

2017-07-15

The performance of a Compton imager using a single three-dimensional position-sensitive LYSO scintillator detector was estimated using a Monte Carlo simulation. The Compton imager consisted of a single LYSO scintillator with a pixelized structure. The size of the scintillator and each pixel were 1.3 × 1.3 × 1.3 cm{sup 3} and 0.3 × 0.3 × 0.3 cm{sup 3}, respectively. The order of γ-ray interactions was determined based on the deposited energies in each detector. After the determination of the interaction sequence, various types of reconstruction algorithms such as simple back-projection, filtered back-projection, and list-mode maximum-likelihood expectation maximization (LM-MLEM) were applied and compared with each other in terms of their angular resolution and signal-tonoise ratio (SNR) for several γ-ray energies. The LM-MLEM reconstruction algorithm exhibited the best performance for Compton imaging in maintaining high angular resolution and SNR. The two sources of {sup 137}Cs (662 keV) could be distinguishable if they were more than 17 ◦ apart. The reconstructed Compton images showed the precise position and distribution of various radiation isotopes, which demonstrated the feasibility of the monitoring of nuclear materials in homeland security and radioactive waste management applications.

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

Directory of Open Access Journals (Sweden)

Lin Wang

2018-01-01

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

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

Science.gov (United States)

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

2015-07-01

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

A Monte Carlo simulation model for stationary non-Gaussian processes

DEFF Research Database (Denmark)

Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.

2003-01-01

includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...

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

Directory of Open Access Journals (Sweden)

Md Nabiul Islam Khan

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

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

Energy Technology Data Exchange (ETDEWEB)

Kanjilal, Oindrila, E-mail: oindrila@civil.iisc.ernet.in; Manohar, C.S., E-mail: manohar@civil.iisc.ernet.in

2017-07-15

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.

Recovery of Graded Response Model Parameters: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation

Science.gov (United States)

Kieftenbeld, Vincent; Natesan, Prathiba

2012-01-01

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

Parallel Monte Carlo simulations on an ARC-enabled computing grid

International Nuclear Information System (INIS)

Nilsen, Jon K; Samset, Bjørn H

2011-01-01

Grid computing opens new possibilities for running heavy Monte Carlo simulations of physical systems in parallel. The presentation gives an overview of GaMPI, a system for running an MPI-based random walker simulation on grid resources. Integrating the ARC middleware and the new storage system Chelonia with the Ganga grid job submission and control system, we show that MPI jobs can be run on a world-wide computing grid with good performance and promising scaling properties. Results for relatively communication-heavy Monte Carlo simulations run on multiple heterogeneous, ARC-enabled computing clusters in several countries are presented.

Evaluation and characterization of X-ray scattering in tissues and mammographic simulators using Monte Carlo simulation

International Nuclear Information System (INIS)

Oliveira, Monica G. Nunes; Braz, Delson; Silva, Regina Cely B. da S.

2005-01-01

The computer simulation has been widely used in physical researches by both the viability of the codes and the growth of the power of computers in the last decades. The Monte Carlo simulation program, EGS4 code is a simulation program used in the area of radiation transport. The simulators, surrogate tissues, phantoms are objects used to perform studies on dosimetric quantities and quality testing of images. The simulators have characteristics of scattering and absorption of radiation similar to tissues that make up the body. The aim of this work is to translate the effects of radiation interactions in a real healthy breast tissues, sick and on simulators using the EGS4 Monte Carlo simulation code

Investigating the impossible: Monte Carlo simulations

International Nuclear Information System (INIS)

Kramer, Gary H.; Crowley, Paul; Burns, Linda C.

2000-01-01

Designing and testing new equipment can be an expensive and time consuming process or the desired performance characteristics may preclude its construction due to technological shortcomings. Cost may also prevent equipment being purchased for other scenarios to be tested. An alternative is to use Monte Carlo simulations to make the investigations. This presentation exemplifies how Monte Carlo code calculations can be used to fill the gap. An example is given for the investigation of two sizes of germanium detector (70 mm and 80 mm diameter) at four different crystal thicknesses (15, 20, 25, and 30 mm) and makes predictions on how the size affects the counting efficiency and the Minimum Detectable Activity (MDA). The Monte Carlo simulations have shown that detector efficiencies can be adequately modelled using photon transport if the data is used to investigate trends. The investigation of the effect of detector thickness on the counting efficiency has shown that thickness for a fixed diameter detector of either 70 mm or 80 mm is unimportant up to 60 keV. At higher photon energies, the counting efficiency begins to decrease as the thickness decreases as expected. The simulations predict that the MDA of either the 70 mm or 80 mm diameter detectors does not differ by more than a factor of 1.15 at 17 keV or 1.2 at 60 keV when comparing detectors of equivalent thicknesses. The MDA is slightly increased at 17 keV, and rises by about 52% at 660 keV, when the thickness is decreased from 30 mm to 15 mm. One could conclude from this information that the extra cost associated with the larger area Ge detectors may not be justified for the slight improvement predicted in the MDA. (author)

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

Energy Technology Data Exchange (ETDEWEB)

Jennings, E.; Madigan, M.

2017-04-01

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrain high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC

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

Science.gov (United States)

Wada, Takao; Ueda, Noriaki

2013-01-01

The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature. PMID:23674843

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

Science.gov (United States)

Wada, Takao; Ueda, Noriaki

2013-04-01

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

Particle-transport simulation with the Monte Carlo method

International Nuclear Information System (INIS)

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

1975-01-01

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

Topological zero modes in Monte Carlo simulations

International Nuclear Information System (INIS)

Dilger, H.

1994-08-01

We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)

Crop canopy BRDF simulation and analysis using Monte Carlo method

NARCIS (Netherlands)

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

2006-01-01

This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and

The determination of beam quality correction factors: Monte Carlo simulations and measurements.

Science.gov (United States)

González-Castaño, D M; Hartmann, G H; Sánchez-Doblado, F; Gómez, F; Kapsch, R-P; Pena, J; Capote, R

2009-08-07

Modern dosimetry protocols are based on the use of ionization chambers provided with a calibration factor in terms of absorbed dose to water. The basic formula to determine the absorbed dose at a user's beam contains the well-known beam quality correction factor that is required whenever the quality of radiation used at calibration differs from that of the user's radiation. The dosimetry protocols describe the whole ionization chamber calibration procedure and include tabulated beam quality correction factors which refer to 60Co gamma radiation used as calibration quality. They have been calculated for a series of ionization chambers and radiation qualities based on formulae, which are also described in the protocols. In the case of high-energy photon beams, the relative standard uncertainty of the beam quality correction factor is estimated to amount to 1%. In the present work, two alternative methods to determine beam quality correction factors are prescribed-Monte Carlo simulation using the EGSnrc system and an experimental method based on a comparison with a reference chamber. Both Monte Carlo calculations and ratio measurements were carried out for nine chambers at several radiation beams. Four chamber types are not included in the current dosimetry protocols. Beam quality corrections for the reference chamber at two beam qualities were also measured using a calorimeter at a PTB Primary Standards Dosimetry Laboratory. Good agreement between the Monte Carlo calculated (1% uncertainty) and measured (0.5% uncertainty) beam quality correction factors was obtained. Based on these results we propose that beam quality correction factors can be generated both by measurements and by the Monte Carlo simulations with an uncertainty at least comparable to that given in current dosimetry protocols.

Shielding evaluation of neutron generator hall by Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Pujala, U.; Selvakumaran, T.S.; Baskaran, R.; Venkatraman, B. [Radiological Safety Division, Indira Gandhi Center for Atomic Research, Kalpakkam (India); Thilagam, L.; Mohapatra, D.K., E-mail: swathythila2@yahoo.com [Safety Research Institute, Atomic Energy Regulatory Board, Kalpakkam (India)

2017-04-01

A shielded hall was constructed for accommodating a D-D, D-T or D-Be based pulsed neutron generator (NG) with 4π yield of 10{sup 9} n/s. The neutron shield design of the facility was optimized using NCRP-51 methodology such that the total dose rates outside the hall areas are well below the regulatory limit for full occupancy criterion (1 μSv/h). However, the total dose rates at roof top, cooling room trench exit and labyrinth exit were found to be above this limit for the optimized design. Hence, additional neutron shielding arrangements were proposed for cooling room trench and labyrinth exits. The roof top was made inaccessible. The present study is an attempt to evaluate the neutron and associated capture gamma transport through the bulk shields for the complete geometry and materials of the NG-Hall using Monte Carlo (MC) codes MCNP and FLUKA. The neutron source terms of D-D, D-T and D-Be reactions are considered in the simulations. The effect of additional shielding proposed has been demonstrated through the simulations carried out with the consideration of the additional shielding for D-Be neutron source term. The results MC simulations using two different codes are found to be consistent with each other for neutron dose rate estimates. However, deviation up to 28% is noted between these two codes at few locations for capture gamma dose rate estimates. Overall, the dose rates estimated by MC simulations including additional shields shows that all the locations surrounding the hall satisfy the full occupancy criteria for all three types of sources. Additionally, the dose rates due to direct transmission of primary neutrons estimated by FLUKA are compared with the values calculated using the formula given in NCRP-51 which shows deviations up to 50% with each other. The details of MC simulations and NCRP-51 methodology for the estimation of primary neutron dose rate along with the results are presented in this paper. (author)

Monte Carlo Simulation of Influence of Input Parameters Uncertainty on Output Data

International Nuclear Information System (INIS)

Sobek, Lukas

2010-01-01

Input parameters of a complex system in the probabilistic simulation are treated by means of probability density function (PDF). The result of the simulation have also probabilistic character. Monte Carlo simulation is widely used to obtain predictions concerning the probability of the risk. The Monte Carlo method was performed to calculate histograms of PDF for release rate given by uncertainty in distribution coefficient of radionuclides 135 Cs and 235 U.

Organ doses for reference pediatric and adolescent patients undergoing computed tomography estimated by Monte Carlo simulation

International Nuclear Information System (INIS)

Lee, Choonsik; Kim, Kwang Pyo; Long, Daniel J.; Bolch, Wesley E.

2012-01-01

Purpose: To establish an organ dose database for pediatric and adolescent reference individuals undergoing computed tomography (CT) examinations by using Monte Carlo simulation. The data will permit rapid estimates of organ and effective doses for patients of different age, gender, examination type, and CT scanner model. Methods: The Monte Carlo simulation model of a Siemens Sensation 16 CT scanner previously published was employed as a base CT scanner model. A set of absorbed doses for 33 organs/tissues normalized to the product of 100 mAs and CTDI vol (mGy/100 mAs mGy) was established by coupling the CT scanner model with age-dependent reference pediatric hybrid phantoms. A series of single axial scans from the top of head to the feet of the phantoms was performed at a slice thickness of 10 mm, and at tube potentials of 80, 100, and 120 kVp. Using the established CTDI vol - and 100 mAs-normalized dose matrix, organ doses for different pediatric phantoms undergoing head, chest, abdomen-pelvis, and chest-abdomen-pelvis (CAP) scans with the Siemens Sensation 16 scanner were estimated and analyzed. The results were then compared with the values obtained from three independent published methods: CT-Expo software, organ dose for abdominal CT scan derived empirically from patient abdominal circumference, and effective dose per dose-length product (DLP). Results: Organ and effective doses were calculated and normalized to 100 mAs and CTDI vol for different CT examinations. At the same technical setting, dose to the organs, which were entirely included in the CT beam coverage, were higher by from 40 to 80% for newborn phantoms compared to those of 15-year phantoms. An increase of tube potential from 80 to 120 kVp resulted in 2.5-2.9-fold greater brain dose for head scans. The results from this study were compared with three different published studies and/or techniques. First, organ doses were compared to those given by CT-Expo which revealed dose differences up to

Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

International Nuclear Information System (INIS)

Shaukata, Nadeem; Shim, Hyung Jin

2015-01-01

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

Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-15

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

Monte-Carlo simulation of heavy-ion collisions

International Nuclear Information System (INIS)

Schenke, Bjoern; Jeon, Sangyong; Gale, Charles

2011-01-01

We present Monte-Carlo simulations for heavy-ion collisions combining PYTHIA and the McGill-AMY formalism to describe the evolution of hard partons in a soft background, modelled using hydrodynamic simulations. MARTINI generates full event configurations in the high p T region that take into account thermal QCD and QED effects as well as effects of the evolving medium. This way it is possible to perform detailed quantitative comparisons with experimental observables.

Exploring Various Monte Carlo Simulations for Geoscience Applications

Science.gov (United States)

Blais, R.

2010-12-01

Computer simulations are increasingly important in geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN), or chaotic random number (CRN) generators. Equidistributed quasi-random numbers (QRNs) can also be used in Monte Carlo simulations. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as Importance Sampling and Stratified Sampling can be implemented to significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on examples of geodetic applications of gravimetric terrain corrections and gravity inversion, conclusions and recommendations concerning their performance and general applicability are included.

Exploring pseudo- and chaotic random Monte Carlo simulations

Science.gov (United States)

Blais, J. A. Rod; Zhang, Zhan

2011-07-01

Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer-generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as importance sampling and stratified sampling can be applied in most Monte Carlo simulations and significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on some practical examples of geodetic direct and inverse problems, conclusions and recommendations concerning their performance and general applicability are included.

Understanding quantum tunneling using diffusion Monte Carlo simulations

Science.gov (United States)

Inack, E. M.; Giudici, G.; Parolini, T.; Santoro, G.; Pilati, S.

2018-03-01

In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1 /Δ2 , where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1 /Δ , i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.

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)

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.

Monte Carlo simulation of Markov unreliability models

International Nuclear Information System (INIS)

Lewis, E.E.; Boehm, F.

1984-01-01

A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)

Monte Carlo simulations of adsorption-induced segregation

DEFF Research Database (Denmark)

Christoffersen, Ebbe; Stoltze, Per; Nørskov, Jens Kehlet

2002-01-01

Through the use of Monte Carlo simulations we study the effect of adsorption-induced segregation. From the bulk composition, degree of dispersion and the partial pressure of the gas phase species we calculate the surface composition of bimetallic alloys. We show that both segregation and adsorption...

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.

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.

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

General purpose code for Monte Carlo simulations

International Nuclear Information System (INIS)

Wilcke, W.W.

1983-01-01

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

A Monte Carlo-based model for simulation of digital chest tomo-synthesis

International Nuclear Information System (INIS)

Ullman, G.; Dance, D. R.; Sandborg, M.; Carlsson, G. A.; Svalkvist, A.; Baath, M.

2010-01-01

The aim of this work was to calculate synthetic digital chest tomo-synthesis projections using a computer simulation model based on the Monte Carlo method. An anthropomorphic chest phantom was scanned in a computed tomography scanner, segmented and included in the computer model to allow for simulation of realistic high-resolution X-ray images. The input parameters to the model were adapted to correspond to the VolumeRAD chest tomo-synthesis system from GE Healthcare. Sixty tomo-synthesis projections were calculated with projection angles ranging from + 15 to -15 deg. The images from primary photons were calculated using an analytical model of the anti-scatter grid and a pre-calculated detector response function. The contributions from scattered photons were calculated using an in-house Monte Carlo-based model employing a number of variance reduction techniques such as the collision density estimator. Tomographic section images were reconstructed by transferring the simulated projections into the VolumeRAD system. The reconstruction was performed for three types of images using: (i) noise-free primary projections, (ii) primary projections including contributions from scattered photons and (iii) projections as in (ii) with added correlated noise. The simulated section images were compared with corresponding section images from projections taken with the real, anthropomorphic phantom from which the digital voxel phantom was originally created. The present article describes a work in progress aiming towards developing a model intended for optimisation of chest tomo-synthesis, allowing for simulation of both existing and future chest tomo-synthesis systems. (authors)

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

Sink strength simulations using the Monte Carlo method: Applied to spherical traps

Science.gov (United States)

Ahlgren, T.; Bukonte, L.

2017-12-01

The sink strength is an important parameter for the mean-field rate equations to simulate temporal changes in the micro-structure of materials. However, there are noteworthy discrepancies between sink strengths obtained by the Monte Carlo and analytical methods. In this study, we show the reasons for these differences. We present the equations to estimate the statistical error for sink strength calculations and show the way to determine the sink strengths for multiple traps. We develop a novel, very fast Monte Carlo method to obtain sink strengths. The results show that, in addition to the well-known sink strength dependence of the trap concentration, trap radius and the total sink strength, the sink strength also depends on the defect diffusion jump length and the total trap volume fraction. Taking these factors into account, allows us to obtain a very accurate analytic expression for the sink strength of spherical traps.

Deficiency in Monte Carlo simulations of coupled neutron-gamma-ray fields

NARCIS (Netherlands)

Maleka, Peane P.; Maucec, Marko; de Meijer, Robert J.

2011-01-01

The deficiency in Monte Carlo simulations of coupled neutron-gamma-ray field was investigated by benchmarking two simulation codes with experimental data. Simulations showed better correspondence with the experimental data for gamma-ray transport only. In simulations, the neutron interactions with

Primary study of Monte Carlo simulation on CdZnTe nuclear detector

International Nuclear Information System (INIS)

Ren Shaojun; Sang Wenbin; Jin Wei; Li Wanwan; Zhang Qi; Min Jiahua

2004-01-01

The Monte Carlo simulation software is developed based on the operating principle of CdZnTe detector, the randomicity of γ ray reaction in the detector and the statistic rule of the amount of electron-hole pairs produced. First, the reaction depth of photons is calculated based on the disintegration rule. Secondly, the reaction section of every reaction is estimated and the reaction probability of the three atoms in CZT and the probability of every reaction of every atom are calculated. Based on these probabilities, the category of atoms and the type of reactions of a photon reacting with the detector are determined and the amount of electron-hole pairs produced by the photon is obtained. From the reaction depth and the amount of electron-hole pairs produced, the amount of charge collected can be calculated. The response energy spectra of γ ray in the CdZnTe detector are simulated by using the Monte Carlo software developed. The simulation results are well comparable with the data of the real CdZnTe devices. In addition, the ideal thickness of the device, which is of maximum detecting efficiency, is also obtained based on the analysis over the relationship between the thickness and the efficiency, assuming the device to be under the radiation of 57 Co source

The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature

CERN Document Server

Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

2010-01-01

A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.

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)

Genetic algorithms and Monte Carlo simulation for optimal plant design

International Nuclear Information System (INIS)

Cantoni, M.; Marseguerra, M.; Zio, E.

2000-01-01

We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown-Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance

Monte Carlo simulation of virtual compton scattering at MAMI

International Nuclear Information System (INIS)

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

1996-01-01

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

Confidence interval procedures for Monte Carlo transport simulations

International Nuclear Information System (INIS)

Pederson, S.P.

1997-01-01

The problem of obtaining valid confidence intervals based on estimates from sampled distributions using Monte Carlo particle transport simulation codes such as MCNP is examined. Such intervals can cover the true parameter of interest at a lower than nominal rate if the sampled distribution is extremely right-skewed by large tallies. Modifications to the standard theory of confidence intervals are discussed and compared with some existing heuristics, including batched means normality tests. Two new types of diagnostics are introduced to assess whether the conditions of central limit theorem-type results are satisfied: the relative variance of the variance determines whether the sample size is sufficiently large, and estimators of the slope of the right tail of the distribution are used to indicate the number of moments that exist. A simulation study is conducted to quantify the relationship between various diagnostics and coverage rates and to find sample-based quantities useful in indicating when intervals are expected to be valid. Simulated tally distributions are chosen to emulate behavior seen in difficult particle transport problems. Measures of variation in the sample variance s 2 are found to be much more effective than existing methods in predicting when coverage will be near nominal rates. Batched means tests are found to be overly conservative in this regard. A simple but pathological MCNP problem is presented as an example of false convergence using existing heuristics. The new methods readily detect the false convergence and show that the results of the problem, which are a factor of 4 too small, should not be used. Recommendations are made for applying these techniques in practice, using the statistical output currently produced by MCNP

Clustering and traveling waves in the Monte Carlo criticality simulation of decoupled and confined media

Directory of Open Access Journals (Sweden)

Eric Dumonteil

2017-09-01

Full Text Available The Monte Carlo criticality simulation of decoupled systems, as for instance in large reactor cores, has been a challenging issue for a long time. In particular, due to limited computer time resources, the number of neutrons simulated per generation is still many order of magnitudes below realistic statistics, even during the start-up phases of reactors. This limited number of neutrons triggers a strong clustering effect of the neutron population that affects Monte Carlo tallies. Below a certain threshold, not only is the variance affected but also the estimation of the eigenvectors. In this paper we will build a time-dependent diffusion equation that takes into account both spatial correlations and population control (fixed number of neutrons along generations. We will show that its solution obeys a traveling wave dynamic, and we will discuss the mechanism that explains this biasing of local tallies whenever leakage boundary conditions are applied to the system.

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)

Monte Carlo simulation of radiation streaming from a radioactive material shipping cask

International Nuclear Information System (INIS)

Liu, Y.Y.; Schwarz, R.A.; Tang, J.S.

1996-01-01

Simulated detection of gamma radiation streaming from a radioactive material shipping cask have been performed with the Monte Carlo codes MCNP4A and MORSE-SGC/S. Despite inherent difficulties in simulating deep penetration of radiation and streaming, the simulations have yielded results that agree within one order of magnitude with the radiation survey data, with reasonable statistics. These simulations have also provided insight into modeling radiation detection, notably on location and orientation of the radiation detector with respect to photon streaming paths, and on techniques used to reduce variance in the Monte Carlo calculations. 13 refs., 4 figs., 2 tabs

Monte Carlo simulation for the design of industrial gamma-ray transmission tomography

International Nuclear Information System (INIS)

Kim, Jongbum; Jung, Sunghee; Moon, Jinho; Kwon, Taekyong; Cho, Gyuseong

2011-01-01

The Monte Carlo simulation and experiment were carried out for a large-scale industrial gamma ray tomographic scanning geometry. The geometry of the tomographic system has a moving source with 16 stationary detectors. This geometry is advantageous for the diagnosis of a large-scale industrial plant. The simulation data was carried out for the phantom with 32 views, 16 detectors, and a different energy bin. The simulation data was processed to be used for image reconstruction. Image reconstruction was performed by a Diagonally-Scaled Gradient-Ascent algorithm for simulation data. Experiments were conducted in a 78 cm diameter column filled with polypropylene grains. Sixteen 0.5-inch-thick and 1 inch long NaI(Tl) cylindrical detectors, and 20 mCi of 137 Cs radioactive source were used. The experimental results were compared to the simulation data. The experimental results were similar to Monte Carlo simulation results. This result showed that the Monte Carlo simulation is useful for predicting the result of the industrial gamma tomographic scan method And it can also give a solution for designing the industrial gamma tomography system and preparing the field experiment. (author)

Estimation variance bounds of importance sampling simulations in digital communication systems

Science.gov (United States)

Lu, D.; Yao, K.

1991-01-01

In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.

DNA strand breaks induced by electrons simulated with nanodosimetry Monte Carlo simulation code: NASIC

International Nuclear Information System (INIS)

Li, Junli; Qiu, Rui; Yan, Congchong; Xie, Wenzhang; Zeng, Zhi; Li, Chunyan; Wu, Zhen; Tung, Chuanjong

2015-01-01

The method of Monte Carlo simulation is a powerful tool to investigate the details of radiation biological damage at the molecular level. In this paper, a Monte Carlo code called NASIC (Nanodosimetry Monte Carlo Simulation Code) was developed. It includes physical module, pre-chemical module, chemical module, geometric module and DNA damage module. The physical module can simulate physical tracks of low-energy electrons in the liquid water event-by-event. More than one set of inelastic cross sections were calculated by applying the dielectric function method of Emfietzoglou's optical-data treatments, with different optical data sets and dispersion models. In the pre-chemical module, the ionised and excited water molecules undergo dissociation processes. In the chemical module, the produced radiolytic chemical species diffuse and react. In the geometric module, an atomic model of 46 chromatin fibres in a spherical nucleus of human lymphocyte was established. In the DNA damage module, the direct damages induced by the energy depositions of the electrons and the indirect damages induced by the radiolytic chemical species were calculated. The parameters should be adjusted to make the simulation results be agreed with the experimental results. In this paper, the influence study of the inelastic cross sections and vibrational excitation reaction on the parameters and the DNA strand break yields were studied. Further work of NASIC is underway (authors)

Monte Carlo-molecular dynamics simulations for two-dimensional magnets

International Nuclear Information System (INIS)

Kawabata, C.; takeuchi, M.; Bishop, A.R.

1985-01-01

A combined Monte Carlo-molecular dynamics simulation technique is used to study the dynamic structure factor on a square lattice for isotropic Heisenberg and planar classical ferromagnetic spin Hamiltonians

Monte-Carlo simulation on the cold neutron guides at CARR

International Nuclear Information System (INIS)

Guo Liping; Wang Hongli; Yang Tonghua; Cheng Zhixu; Liu Yi

2003-01-01

The designs of the two cold neutron guides to be built at China Advanced Research Reactor (CARR) are simulated with Monte-Carlo simulation software VITESS. Various parameters of the guides, e.g. transmission efficiency, neutron flux, divergence, etc., are obtained. (author)

Data decomposition of Monte Carlo particle transport simulations via tally servers

International Nuclear Information System (INIS)

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

2013-01-01

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

SIMULACIÓN DE MONTE CARLO APLICADA A LA ESTIMACIÓN DE DEPRESIONES RÁPIDAS DE LA TENSIÓN EN REDES ELÉCTRICAS MONTE CARLO SIMULATION APPLIED TO THE ESTIMATION OF VOLTAGE DIPS IN ELECTRIC NETWORKS

Directory of Open Access Journals (Sweden)

Miguel Arias Albornoz

2008-09-01

Full Text Available En este trabajo se aplica el método de simulación de Monte Carlo (MC para estimar el número de depresiones rápidas de tensión (dips esperados en barras de una red eléctrica. Las estimaciones obtenidas a través de MC se comparan con los resultados de otro método de cálculo conocido como Método de Posiciones de Falla (MPF. Entre los resultados se muestra tanto la convergencia del algoritmo MC a los valores de largo plazo del método MPF como la distribución completa de frecuencias para diferentes eventos, lo cual representa información valiosa para apoyar la toma de decisiones sobre el empleo de equipos sensibles a este tipo de perturbación.In this work, the Monte Carlo simulation method (MC is applied to estimate the number of expected voltage dips in the nodes of an electric network. The estimations obtained through MC are compared with the results of another method of calculation, known as Failure Position Method (MPF. In the results, both the convergence of the algorithm with the long-term values of the MPF method and the complete distribution of frequencies for different events are shown. This represents valuable information to support the decision-making process for equipment that is sensitive to this type of perturbation.

A Monte Carlo-shear lag simulation of tensile fracture behaviour of Bi2223 filament

International Nuclear Information System (INIS)

Ochiai, S; Ishida, T; Doko, D; Morishita, K; Okuda, H; Oh, S S; Ha, D W; Hojo, M; Tanaka, M; Sugano, M; Osamura, K

2005-01-01

The damage evolution in Bi2223 filaments and its influence on critical current was described by a Monte Carlo-shear lag simulation method. The experimentally observed zigzag crack propagation across aligned Bi2223 grains under tensile strain was effectively modelled by including transverse and longitudinal failure modes for individual grains. From the simulated stress-strain curve, the survival parameter (slope of the stress-strain curve normalized with respect to the original Young's modulus) was estimated with increasing applied strain. With this parameter combined with the strain sensitivity of the critical current, the measured change of critical current of the composite tape with applied strain could be described well

An NPT Monte Carlo Molecular Simulation-Based Approach to Investigate Solid-Vapor Equilibrium: Application to Elemental Sulfur-H2S System

KAUST Repository

Kadoura, Ahmad Salim; Salama, Amgad; Sun, Shuyu; Sherik, Abdelmounam

2013-01-01

In this work, a method to estimate solid elemental sulfur solubility in pure and gas mixtures using Monte Carlo (MC) molecular simulation is proposed. This method is based on Isobaric-Isothermal (NPT) ensemble and the Widom insertion technique

Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations

Science.gov (United States)

Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias

2015-01-01

Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.

Testing Lorentz Invariance Emergence in the Ising Model using Monte Carlo simulations

CERN Document Server

Dias Astros, Maria Isabel

2017-01-01

In the context of the Lorentz invariance as an emergent phenomenon at low energy scales to study quantum gravity a system composed by two 3D interacting Ising models (one with an anisotropy in one direction) was proposed. Two Monte Carlo simulations were run: one for the 2D Ising model and one for the target model. In both cases the observables (energy, magnetization, heat capacity and magnetic susceptibility) were computed for different lattice sizes and a Binder cumulant introduced in order to estimate the critical temperature of the systems. Moreover, the correlation function was calculated for the 2D Ising model.

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.)

Monte Carlo simulation of tomography techniques using the platform Gate

International Nuclear Information System (INIS)

Barbouchi, Asma

2007-01-01

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

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

Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

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

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

Premar-2: a Monte Carlo code for radiative transport simulation in atmospheric environments

International Nuclear Information System (INIS)

Cupini, E.

1999-01-01

The peculiarities of the PREMAR-2 code, aimed at radiation transport Monte Carlo simulation in atmospheric environments in the infrared-ultraviolet frequency range, are described. With respect to the previously developed PREMAR code, besides plane multilayers, spherical multilayers and finite sequences of vertical layers, each one with its own atmospheric behaviour, are foreseen in the new code, together with the refraction phenomenon, so that long range, highly slanted paths can now be more faithfully taken into account. A zenithal angular dependence of the albedo coefficient has moreover been introduced. Lidar systems, with spatially independent source and telescope, are allowed again to be simulated, and, in this latest version of the code, sensitivity analyses to be performed. According to this last feasibility, consequences on radiation transport of small perturbations in physical components of the atmospheric environment may be analyze and the related effects on searched results estimated. The availability of a library of physical data (reaction coefficients, phase functions and refraction indexes) is required by the code, providing the essential features of the environment of interest needed of the Monte Carlo simulation. Variance reducing techniques have been enhanced in the Premar-2 code, by introducing, for instance, a local forced collision technique, especially apt to be used in Lidar system simulations. Encouraging comparisons between code and experimental results carried out at the Brasimone Centre of ENEA, have so far been obtained, even if further checks of the code are to be performed [it

Reducing Monte Carlo error in the Bayesian estimation of risk ratios using log-binomial regression models.

Science.gov (United States)

Salmerón, Diego; Cano, Juan A; Chirlaque, María D

2015-08-30

In cohort studies, binary outcomes are very often analyzed by logistic regression. However, it is well known that when the goal is to estimate a risk ratio, the logistic regression is inappropriate if the outcome is common. In these cases, a log-binomial regression model is preferable. On the other hand, the estimation of the regression coefficients of the log-binomial model is difficult owing to the constraints that must be imposed on these coefficients. Bayesian methods allow a straightforward approach for log-binomial regression models and produce smaller mean squared errors in the estimation of risk ratios than the frequentist methods, and the posterior inferences can be obtained using the software WinBUGS. However, Markov chain Monte Carlo methods implemented in WinBUGS can lead to large Monte Carlo errors in the approximations to the posterior inferences because they produce correlated simulations, and the accuracy of the approximations are inversely related to this correlation. To reduce correlation and to improve accuracy, we propose a reparameterization based on a Poisson model and a sampling algorithm coded in R. Copyright © 2015 John Wiley & Sons, Ltd.

A computer code package for electron transport Monte Carlo simulation

International Nuclear Information System (INIS)

Popescu, Lucretiu M.

1999-01-01

A computer code package was developed for solving various electron transport problems by Monte Carlo simulation. It is based on condensed history Monte Carlo algorithm. In order to get reliable results over wide ranges of electron energies and target atomic numbers, specific techniques of electron transport were implemented such as: Moliere multiscatter angular distributions, Blunck-Leisegang multiscatter energy distribution, sampling of electron-electron and Bremsstrahlung individual interactions. Path-length and lateral displacement corrections algorithms and the module for computing collision, radiative and total restricted stopping powers and ranges of electrons are also included. Comparisons of simulation results with experimental measurements are finally presented. (author)

PRELIMINARY COUPLING OF THE MONTE CARLO CODE OPENMC AND THE MULTIPHYSICS OBJECT-ORIENTED SIMULATION ENVIRONMENT (MOOSE) FOR ANALYZING DOPPLER FEEDBACK IN MONTE CARLO SIMULATIONS

Energy Technology Data Exchange (ETDEWEB)

Matthew Ellis; Derek Gaston; Benoit Forget; Kord Smith

2011-07-01

In recent years the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open source Monte Carlo code OpenMC with the open source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes. An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two dimensional 17x17 PWR fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes Functional Expansion Tallies to accurately and efficiently transfer pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two dimensional PWR fuel assembly case also demonstrates that for a simplified model the pin-by-pin doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

Energy Technology Data Exchange (ETDEWEB)

Badal, A [U.S. Food and Drug Administration (CDRH/OSEL), Silver Spring, MD (United States); Zbijewski, W [Johns Hopkins University, Baltimore, MD (United States); Bolch, W [University of Florida, Gainesville, FL (United States); Sechopoulos, I [Emory University, Atlanta, GA (United States)

2014-06-15

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

International Nuclear Information System (INIS)

Badal, A; Zbijewski, W; Bolch, W; Sechopoulos, I

2014-01-01

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10 7 xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual

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

Assessing the convergence of LHS Monte Carlo simulations of wastewater treatment models.

Science.gov (United States)

Benedetti, Lorenzo; Claeys, Filip; Nopens, Ingmar; Vanrolleghem, Peter A

2011-01-01

Monte Carlo (MC) simulation appears to be the only currently adopted tool to estimate global sensitivities and uncertainties in wastewater treatment modelling. Such models are highly complex, dynamic and non-linear, requiring long computation times, especially in the scope of MC simulation, due to the large number of simulations usually required. However, no stopping rule to decide on the number of simulations required to achieve a given confidence in the MC simulation results has been adopted so far in the field. In this work, a pragmatic method is proposed to minimize the computation time by using a combination of several criteria. It makes no use of prior knowledge about the model, is very simple, intuitive and can be automated: all convenient features in engineering applications. A case study is used to show an application of the method, and the results indicate that the required number of simulations strongly depends on the model output(s) selected, and on the type and desired accuracy of the analysis conducted. Hence, no prior indication is available regarding the necessary number of MC simulations, but the proposed method is capable of dealing with these variations and stopping the calculations after convergence is reached.

Monte Carlo Simulations of Compressible Ising Models: Do We Understand Them?

Science.gov (United States)

Landau, D. P.; Dünweg, B.; Laradji, M.; Tavazza, F.; Adler, J.; Cannavaccioulo, L.; Zhu, X.

Extensive Monte Carlo simulations have begun to shed light on our understanding of phase transitions and universality classes for compressible Ising models. A comprehensive analysis of a Landau-Ginsburg-Wilson hamiltonian for systems with elastic degrees of freedom resulted in the prediction that there should be four distinct cases that would have different behavior, depending upon symmetries and thermodynamic constraints. We shall provide an account of the results of careful Monte Carlo simulations for a simple compressible Ising model that can be suitably modified so as to replicate all four cases.

On Monte Carlo Simulation and Analysis of Electricity Markets

International Nuclear Information System (INIS)

Amelin, Mikael

2004-07-01

This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models

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

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

Science.gov (United States)

2017-12-07

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

Methods for Monte Carlo simulations of biomacromolecules.

Science.gov (United States)

Vitalis, Andreas; Pappu, Rohit V

2009-01-01

The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.

Application of Macro Response Monte Carlo method for electron spectrum simulation

International Nuclear Information System (INIS)

Perles, L.A.; Almeida, A. de

2007-01-01

During the past years several variance reduction techniques for Monte Carlo electron transport have been developed in order to reduce the electron computation time transport for absorbed dose distribution. We have implemented the Macro Response Monte Carlo (MRMC) method to evaluate the electron spectrum which can be used as a phase space input for others simulation programs. Such technique uses probability distributions for electron histories previously simulated in spheres (called kugels). These probabilities are used to sample the primary electron final state, as well as the creation secondary electrons and photons. We have compared the MRMC electron spectra simulated in homogeneous phantom against the Geant4 spectra. The results showed an agreement better than 6% in the spectra peak energies and that MRMC code is up to 12 time faster than Geant4 simulations

Monte Carlo simulation of Touschek effect

Directory of Open Access Journals (Sweden)

Aimin Xiao

2010-07-01

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

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.

PC-based process distribution to solve iterative Monte Carlo simulations in physical dosimetry

International Nuclear Information System (INIS)

Leal, A.; Sanchez-Doblado, F.; Perucha, M.; Rincon, M.; Carrasco, E.; Bernal, C.

2001-01-01

A distribution model to simulate physical dosimetry measurements with Monte Carlo (MC) techniques has been developed. This approach is indicated to solve the simulations where there are continuous changes of measurement conditions (and hence of the input parameters) such as a TPR curve or the estimation of the resolution limit of an optimal densitometer in the case of small field profiles. As a comparison, a high resolution scan for narrow beams with no iterative process is presented. The model has been installed on a network PCs without any resident software. The only requirement for these PCs has been a small and temporal Linux partition in the hard disks and to be connecting by the net with our server PC. (orig.)

A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.

Science.gov (United States)

Nestler, Steffen

2013-02-01

We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecified. The results showed that when the model was correctly specified, PIV produced estimates that were as accurate as ULS and DWLS. Furthermore, the simulation showed that PIV was more robust to structural misspecifications than ULS and DWLS. © 2012 The British Psychological Society.

Simulation of neutron transport equation using parallel Monte Carlo for deep penetration problems

International Nuclear Information System (INIS)

Bekar, K. K.; Tombakoglu, M.; Soekmen, C. N.

2001-01-01

Neutron transport equation is simulated using parallel Monte Carlo method for deep penetration neutron transport problem. Monte Carlo simulation is parallelized by using three different techniques; direct parallelization, domain decomposition and domain decomposition with load balancing, which are used with PVM (Parallel Virtual Machine) software on LAN (Local Area Network). The results of parallel simulation are given for various model problems. The performances of the parallelization techniques are compared with each other. Moreover, the effects of variance reduction techniques on parallelization are discussed

A Proposal on the Geometry Splitting Strategy to Enhance the Calculation Efficiency in Monte Carlo Simulation

Energy Technology Data Exchange (ETDEWEB)

Han, Gi Yeong; Kim, Song Hyun; Kim, Do Hyun; Shin, Chang Ho; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of)

2014-05-15

In this study, how the geometry splitting strategy affects the calculation efficiency was analyzed. In this study, a geometry splitting method was proposed to increase the calculation efficiency in Monte Carlo simulation. First, the analysis of the neutron distribution characteristics in a deep penetration problem was performed. Then, considering the neutron population distribution, a geometry splitting method was devised. Using the proposed method, the FOMs with benchmark problems were estimated and compared with the conventional geometry splitting strategy. The results show that the proposed method can considerably increase the calculation efficiency in using geometry splitting method. It is expected that the proposed method will contribute to optimizing the computational cost as well as reducing the human errors in Monte Carlo simulation. Geometry splitting in Monte Carlo (MC) calculation is one of the most popular variance reduction techniques due to its simplicity, reliability and efficiency. For the use of the geometry splitting, the user should determine locations of geometry splitting and assign the relative importance of each region. Generally, the splitting parameters are decided by the user's experience. However, in this process, the splitting parameters can ineffectively or erroneously be selected. In order to prevent it, there is a recommendation to help the user eliminate guesswork, which is to split the geometry evenly. And then, the importance is estimated by a few iterations for preserving population of particle penetrating each region. However, evenly geometry splitting method can make the calculation inefficient due to the change in mean free path (MFP) of particles.

A Proposal on the Geometry Splitting Strategy to Enhance the Calculation Efficiency in Monte Carlo Simulation

International Nuclear Information System (INIS)

Han, Gi Yeong; Kim, Song Hyun; Kim, Do Hyun; Shin, Chang Ho; Kim, Jong Kyung

2014-01-01

In this study, how the geometry splitting strategy affects the calculation efficiency was analyzed. In this study, a geometry splitting method was proposed to increase the calculation efficiency in Monte Carlo simulation. First, the analysis of the neutron distribution characteristics in a deep penetration problem was performed. Then, considering the neutron population distribution, a geometry splitting method was devised. Using the proposed method, the FOMs with benchmark problems were estimated and compared with the conventional geometry splitting strategy. The results show that the proposed method can considerably increase the calculation efficiency in using geometry splitting method. It is expected that the proposed method will contribute to optimizing the computational cost as well as reducing the human errors in Monte Carlo simulation. Geometry splitting in Monte Carlo (MC) calculation is one of the most popular variance reduction techniques due to its simplicity, reliability and efficiency. For the use of the geometry splitting, the user should determine locations of geometry splitting and assign the relative importance of each region. Generally, the splitting parameters are decided by the user's experience. However, in this process, the splitting parameters can ineffectively or erroneously be selected. In order to prevent it, there is a recommendation to help the user eliminate guesswork, which is to split the geometry evenly. And then, the importance is estimated by a few iterations for preserving population of particle penetrating each region. However, evenly geometry splitting method can make the calculation inefficient due to the change in mean free path (MFP) of particles

A general purpose code for Monte Carlo simulations

International Nuclear Information System (INIS)

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

1984-01-01

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

Report on some methods of determining the state of convergence of Monte Carlo risk estimates

International Nuclear Information System (INIS)

Orford, J.L.; Hufton, D.; Johnson, K.

1991-05-01

The Department of the Environment is developing a methodology for assessing potential sites for the disposal of low and intermediate level radioactive wastes. Computer models are used to simulate the groundwater transport of radioactive materials from a disposal facility back to man. Monte Carlo methods are being employed to conduct a probabilistic risk assessment (pra) of potential sites. The models calculate time histories of annual radiation dose to the critical group population. The annual radiation dose to the critical group in turn specifies the annual individual risk. The distribution of dose is generally highly skewed and many simulation runs are required to predict the level of confidence in the risk estimate i.e. to determine whether the risk estimate is converged. This report describes some statistical methods for determining the state of convergence of the risk estimate. The methods described include the Shapiro-Wilk test, calculation of skewness and kurtosis and normal probability plots. A method for forecasting the number of samples needed before the risk estimate is converged is presented. Three case studies were conducted to examine the performance of some of these techniques. (author)

Estimation of the dose deposited by electron beams in radiotherapy in voxelised phantoms using the Monte Carlo simulation platform GATE based on GEANT4 in a grid environment

International Nuclear Information System (INIS)

Perrot, Y.

2011-01-01

Radiation therapy treatment planning requires accurate determination of absorbed dose in the patient. Monte Carlo simulation is the most accurate method for solving the transport problem of particles in matter. This thesis is the first study dealing with the validation of the Monte Carlo simulation platform GATE (GEANT4 Application for Tomographic Emission), based on GEANT4 (Geometry And Tracking) libraries, for the computation of absorbed dose deposited by electron beams. This thesis aims at demonstrating that GATE/GEANT4 calculations are able to reach treatment planning requirements in situations where analytical algorithms are not satisfactory. The goal is to prove that GATE/GEANT4 is useful for treatment planning using electrons and competes with well validated Monte Carlo codes. This is demonstrated by the simulations with GATE/GEANT4 of realistic electron beams and electron sources used for external radiation therapy or targeted radiation therapy. The computed absorbed dose distributions are in agreement with experimental measurements and/or calculations from other Monte Carlo codes. Furthermore, guidelines are proposed to fix the physics parameters of the GATE/GEANT4 simulations in order to ensure the accuracy of absorbed dose calculations according to radiation therapy requirements. (author)

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.

Energy deposition evaluation for ultra-low energy electron beam irradiation systems using calibrated thin radiochromic film and Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Matsui, S., E-mail: smatsui@gpi.ac.jp; Mori, Y. [The Graduate School for the Creation of New Photonics Industries, 1955-1 Kurematsucho, Nishiku, Hamamatsu, Shizuoka 431-1202 (Japan); Nonaka, T.; Hattori, T.; Kasamatsu, Y.; Haraguchi, D.; Watanabe, Y.; Uchiyama, K.; Ishikawa, M. [Hamamatsu Photonics K.K. Electron Tube Division, 314-5 Shimokanzo, Iwata, Shizuoka 438-0193 (Japan)

2016-05-15

For evaluation of on-site dosimetry and process design in industrial use of ultra-low energy electron beam (ULEB) processes, we evaluate the energy deposition using a thin radiochromic film and a Monte Carlo simulation. The response of film dosimeter was calibrated using a high energy electron beam with an acceleration voltage of 2 MV and alanine dosimeters with uncertainty of 11% at coverage factor 2. Using this response function, the results of absorbed dose measurements for ULEB were evaluated from 10 kGy to 100 kGy as a relative dose. The deviation between the responses of deposit energy on the films and Monte Carlo simulations was within 15%. As far as this limitation, relative dose estimation using thin film dosimeters with response function obtained by high energy electron irradiation and simulation results is effective for ULEB irradiation processes management.

MBR Monte Carlo Simulation in PYTHIA8

Science.gov (United States)

Ciesielski, R.

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

Monte Carlo simulation of a gas-sampled hadron calorimeter

Energy Technology Data Exchange (ETDEWEB)

Chang, C Y; Kunori, S; Rapp, P; Talaga, R; Steinberg, P; Tylka, A J; Wang, Z M

1988-02-15

A prototype of the OPAL barrel hadron calorimeter, which is a gas-sampled calorimeter using plastic streamer tubes, was exposed to pions at energies between 1 and 7 GeV. The response of the detector was simulated using the CERN GEANT3 Monte Carlo program. By using the observed high energy muon signals to deduce details of the streamer formation, the Monte Carlo program was able to reproduce the observed calorimeter response. The behavior of the hadron calorimeter when placed behind a lead glass electromagnetic calorimeter was also investigated.

Effect of phantom dimension variation on Monte Carlo simulation speed and precision

International Nuclear Information System (INIS)

Lin Hui; Xu Yuanying; Xu Liangfeng; Li Guoli; Jiang Jia

2007-01-01

There is a correlation between Monte Carlo simulation speed and the phantom dimension. The effect of the phantom dimension on the Monte Carlo simulation speed and precision was studied based on a fast Monte Carlo code DPM. The results showed that when the thickness of the phantom was reduced, the efficiency would increase exponentially without compromise of its precision except for the position at the tailor. When the width of the phantom was reduced to outside the penumbra, the effect on the efficiency would be neglectable. However when it was reduced to within the penumbra, the efficiency would be increased at some extent without precision loss. This result was applied to a clinic head case, and the remarkable increased efficiency was acquired. (authors)

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

International Nuclear Information System (INIS)

Wang Yongbo; Wu Huapeng; Handroos, Heikki

2011-01-01

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

A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix

DEFF Research Database (Denmark)

Cherchi, Elisabetta; Guevara, Cristian Angelo

2012-01-01

of parameters increases is usually known as the “curse of dimensionality” in the simulation methods. We investigate this problem in the case of the random coefficients Logit model. We compare the traditional Maximum Simulated Likelihood (MSL) method with two alternative estimation methods: the Expectation......–Maximization (EM) and the Laplace Approximation (HH) methods that do not require simulation. We use Monte Carlo experimentation to investigate systematically the performance of the methods under different circumstances, including different numbers of variables, sample sizes and structures of the variance...

Perfusion CT of the Brain and Liver and of Lung Tumors: Use of Monte Carlo Simulation for Patient Dose Estimation for Examinations With a Cone-Beam 320-MDCT Scanner.

Science.gov (United States)

Cros, Maria; Geleijns, Jacob; Joemai, Raoul M S; Salvadó, Marçal

2016-01-01

The purpose of this study was to estimate the patient dose from perfusion CT examinations of the brain, lung tumors, and the liver on a cone-beam 320-MDCT scanner using a Monte Carlo simulation and the recommendations of the International Commission on Radiological Protection (ICRP). A Monte Carlo simulation based on the Electron Gamma Shower Version 4 package code was used to calculate organ doses and the effective dose in the reference computational phantoms for an adult man and adult woman as published by the ICRP. Three perfusion CT acquisition protocols--brain, lung tumor, and liver perfusion--were evaluated. Additionally, dose assessments were performed for the skin and for the eye lens. Conversion factors were obtained to estimate effective doses and organ doses from the volume CT dose index and dose-length product. The sex-averaged effective doses were approximately 4 mSv for perfusion CT of the brain and were between 23 and 26 mSv for the perfusion CT body protocols. The eye lens dose from the brain perfusion CT examination was approximately 153 mGy. The sex-averaged peak entrance skin dose (ESD) was 255 mGy for the brain perfusion CT studies, 157 mGy for the lung tumor perfusion CT studies, and 172 mGy for the liver perfusion CT studies. The perfusion CT protocols for imaging the brain, lung tumors, and the liver performed on a 320-MDCT scanner yielded patient doses that are safely below the threshold doses for deterministic effects. The eye lens dose, peak ESD, and effective doses can be estimated for other clinical perfusion CT examinations from the conversion factors that were derived in this study.

A bottom collider vertex detector design, Monte-Carlo simulation and analysis package

International Nuclear Information System (INIS)

Lebrun, P.

1990-01-01

A detailed simulation of the BCD vertex detector is underway. Specifications and global design issues are briefly reviewed. The BCD design based on double sided strip detector is described in more detail. The GEANT3-based Monte-Carlo program and the analysis package used to estimate detector performance are discussed in detail. The current status of the expected resolution and signal to noise ratio for the ''golden'' CP violating mode B d → π + π - is presented. These calculations have been done at FNAL energy (√s = 2.0 TeV). Emphasis is placed on design issues, analysis techniques and related software rather than physics potentials. 20 refs., 46 figs

SELF-ABSORPTION CORRECTIONS BASED ON MONTE CARLO SIMULATIONS

Directory of Open Access Journals (Sweden)

Kamila Johnová

2016-12-01

Full Text Available The main aim of this article is to demonstrate how Monte Carlo simulations are implemented in our gamma spectrometry laboratory at the Department of Dosimetry and Application of Ionizing Radiation in order to calculate the self-absorption within the samples. A model of real HPGe detector created for MCNP simulations is presented in this paper. All of the possible parameters, which may influence the self-absorption, are at first discussed theoretically and lately described using the calculated results.

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...

Monte-Carlo simulations of neutron shielding for the ATLAS forward region

CERN Document Server

Stekl, I; Kovalenko, V E; Vorobel, V; Leroy, C; Piquemal, F; Eschbach, R; Marquet, C

2000-01-01

The effectiveness of different types of neutron shielding for the ATLAS forward region has been studied by means of Monte-Carlo simulations and compared with the results of an experiment performed at the CERN PS. The simulation code is based on GEANT, FLUKA, MICAP and GAMLIB. GAMLIB is a new library including processes with gamma-rays produced in (n, gamma), (n, n'gamma) neutron reactions and is interfaced to the MICAP code. The effectiveness of different types of shielding against neutrons and gamma-rays, composed from different types of material, such as pure polyethylene, borated polyethylene, lithium-filled polyethylene, lead and iron, were compared. The results from Monte-Carlo simulations were compared to the results obtained from the experiment. The simulation results reproduce the experimental data well. This agreement supports the correctness of the simulation code used to describe the generation, spreading and absorption of neutrons (up to thermal energies) and gamma-rays in the shielding materials....

Isotopic depletion with Monte Carlo

International Nuclear Information System (INIS)

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

1996-06-01

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

Optical coherence tomography: Monte Carlo simulation and improvement by optical amplification

DEFF Research Database (Denmark)

Tycho, Andreas

2002-01-01

An advanced novel Monte Carlo simulation model of the detection process of an optical coherence tomography (OCT) system is presented. For the first time it is shown analytically that the applicability of the incoherent Monte Carlo approach to model the heterodyne detection process of an OCT system...... is firmly justified. This is obtained by calculating the heterodyne mixing of the reference and sample beams in a plane conjugate to the discontinuity in the sample probed by the system. Using this approach, a novel expression for the OCT signal is derived, which only depends uopon the intensity...... flexibility of Monte Carlo simulations, this new model is demonstrated to be excellent as a numerical phantom, i.e., as a substitute for otherwise difficult experiments. Finally, a new model of the signal-to-noise ratio (SNR) of an OCT system with optical amplification of the light reflected from the sample...

Monte Carlo simulation models of breeding-population advancement.

Science.gov (United States)

J.N. King; G.R. Johnson

1993-01-01

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

Combining four Monte Carlo estimators for radiation momentum deposition

International Nuclear Information System (INIS)

Hykes, Joshua M.; Urbatsch, Todd J.

2011-01-01

Using four distinct Monte Carlo estimators for momentum deposition - analog, absorption, collision, and track-length estimators - we compute a combined estimator. In the wide range of problems tested, the combined estimator always has a figure of merit (FOM) equal to or better than the other estimators. In some instances the FOM of the combined estimator is only a few percent higher than the FOM of the best solo estimator, the track-length estimator, while in one instance it is better by a factor of 2.5. Over the majority of configurations, the combined estimator's FOM is 10 - 20% greater than any of the solo estimators' FOM. The numerical results show that the track-length estimator is the most important term in computing the combined estimator, followed far behind by the analog estimator. The absorption and collision estimators make negligible contributions. (author)

Monte Carlo FLUKA code simulation for study of {sup 68}Ga production by direct proton-induced reaction

Energy Technology Data Exchange (ETDEWEB)

Mokhtari Oranj, Leila; Kakavand, Tayeb [Physics Faculty, Zanjan University, P.O. Box 451-313, Zanjan (Iran, Islamic Republic of); Sadeghi, Mahdi, E-mail: msadeghi@nrcam.org [Agricultural, Medical and Industrial Research School, Nuclear Science and Technology Research Institute, P.O. Box 31485-498, Karaj (Iran, Islamic Republic of); Aboudzadeh Rovias, Mohammadreza [Agricultural, Medical and Industrial Research School, Nuclear Science and Technology Research Institute, P.O. Box 31485-498, Karaj (Iran, Islamic Republic of)

2012-06-11

{sup 68}Ga is an important radionuclide for positron emission tomography. {sup 68}Ga can be produced by the {sup 68}Zn(p,n){sup 68}Ga reaction in a common biomedical cyclotrons. To facilitate optimization of target design and study activation of materials, Monte Carlo code can be used to simulate the irradiation of the target materials with charged hadrons. In this paper, FLUKA code simulation was employed to prototype a Zn target for the production of {sup 68}Ga by proton irradiation. Furthermore, the experimental data were compared with the estimated values for the thick target yield produced in the irradiation time according to FLUKA code. In conclusion, FLUKA code can be used for estimation of the production yield.

Monte Carlo simulation of a clinical linear accelerator

International Nuclear Information System (INIS)

Lin, S.-Y.; Chu, T.-C.; Lin, J.-P.

2001-01-01

The effects of the physical parameters of an electron beam from a Siemens PRIMUS clinical linear accelerator (linac) on the dose distribution in water were investigated by Monte Carlo simulation. The EGS4 user code, OMEGA/BEAM, was used in this study. Various incident electron beams, for example, with different energies, spot sizes and distances from the point source, were simulated using the detailed linac head structure in the 6 MV photon mode. Approximately 10 million particles were collected in the scored plane, which was set under the reticle to form the so-called phase space file. The phase space file served as a source for simulating the dose distribution in water using DOSXYZ. Dose profiles at D max (1.5 cm) and PDD curves were calculated following simulating about 1 billion histories for dose profiles and 500 million histories for percent depth dose (PDD) curves in a 30x30x30 cm 3 water phantom. The simulation results were compared with the data measured by a CEA film and an ion chamber. The results show that the dose profiles are influenced by the energy and the spot size, while PDD curves are primarily influenced by the energy of the incident beam. The effect of the distance from the point source on the dose profile is not significant and is recommended to be set at infinity. We also recommend adjusting the beam energy by using PDD curves and, then, adjusting the spot size by using the dose profile to maintain the consistency of the Monte Carlo results and measured data

Experimental and Monte Carlo simulated spectra of a liquid-metal-jet x-ray source

International Nuclear Information System (INIS)

Marziani, M.; Gambaccini, M.; Di Domenico, G.; Taibi, A.; Cardarelli, P.

2014-01-01

A prototype x-ray system based on a liquid-metal-jet anode was evaluated within the framework of the LABSYNC project. The generated spectrum was measured using a CZT-based spectrometer and was compared with spectra simulated by three Monte Carlo codes: MCNPX, PENELOPE and EGS5. Notable differences in the simulated spectra were found. These are mainly attributable to differences in the models adopted for the electron-impact ionization cross section. The simulation that more closely reproduces the experimentally measured spectrum was provided by PENELOPE. - Highlights: • The x-ray spectrum of a liquid-jet x-ray anode was measured with a CZT spectrometer. • Results were compared with Monte Carlo simulations using MCNPX, PENELOPE, EGS5. • Notable differences were found among the Monte Carlo simulated spectra. • The key role was played by the electron-impact ionization cross-section model used. • The experimentally measured spectrum was closely reproduced by the PENELOPE code

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

International Nuclear Information System (INIS)

Goldstein, M.

1980-04-01

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

Study of TXRF experimental system by Monte Carlo simulation

International Nuclear Information System (INIS)

Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T.; Anjos, Marcelino J.; Conti, Claudio C.

2011-01-01

The Total-Reflection X-ray Fluorescence (TXRF) technique offers unique possibilities to study the concentrations of a wide range of trace elements in various types of samples. Besides that, the TXRF technique is widely used to study the trace elements in biological, medical and environmental samples due to its multielemental character as well as simplicity of sample preparation and quantification methods used. In general the TXRF experimental setup is not simple and might require substantial experimental efforts. On the other hand, in recent years, experimental TXRF portable systems have been developed. It has motivated us to develop our own TXRF portable system. In this work we presented a first step in order to optimize a TXRF experimental setup using Monte Carlo simulation by MCNP code. The results found show that the Monte Carlo simulation method can be used to investigate the development of a TXRF experimental system before its assembly. (author)

Mosaic crystal algorithm for Monte Carlo simulations

CERN Document Server

Seeger, P A

2002-01-01

An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)

Monte Carlo simulation: tool for the calibration in analytical determination of radionuclides

International Nuclear Information System (INIS)

Gonzalez, Jorge A. Carrazana; Ferrera, Eduardo A. Capote; Gomez, Isis M. Fernandez; Castro, Gloria V. Rodriguez; Ricardo, Niury Martinez

2013-01-01

This work shows how is established the traceability of the analytical determinations using this calibration method. Highlights the advantages offered by Monte Carlo simulation for the application of corrections by differences in chemical composition, density and height of the samples analyzed. Likewise, the results obtained by the LVRA in two exercises organized by the International Agency for Atomic Energy (IAEA) are presented. In these exercises (an intercomparison and a proficiency test) all reported analytical results were obtained based on calibrations in efficiency by Monte Carlo simulation using the DETEFF program

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Science.gov (United States)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Depth-of-interaction estimates in pixelated scintillator sensors using Monte Carlo techniques

International Nuclear Information System (INIS)

Sharma, Diksha; Sze, Christina; Bhandari, Harish; Nagarkar, Vivek; Badano, Aldo

2017-01-01

Image quality in thick scintillator detectors can be improved by minimizing parallax errors through depth-of-interaction (DOI) estimation. A novel sensor for low-energy single photon imaging having a thick, transparent, crystalline pixelated micro-columnar CsI:Tl scintillator structure has been described, with possible future application in small-animal single photon emission computed tomography (SPECT) imaging when using thicker structures under development. In order to understand the fundamental limits of this new structure, we introduce cartesianDETECT2, an open-source optical transport package that uses Monte Carlo methods to obtain estimates of DOI for improving spatial resolution of nuclear imaging applications. Optical photon paths are calculated as a function of varying simulation parameters such as columnar surface roughness, bulk, and top-surface absorption. We use scanning electron microscope images to estimate appropriate surface roughness coefficients. Simulation results are analyzed to model and establish patterns between DOI and photon scattering. The effect of varying starting locations of optical photons on the spatial response is studied. Bulk and top-surface absorption fractions were varied to investigate their effect on spatial response as a function of DOI. We investigated the accuracy of our DOI estimation model for a particular screen with various training and testing sets, and for all cases the percent error between the estimated and actual DOI over the majority of the detector thickness was ±5% with a maximum error of up to ±10% at deeper DOIs. In addition, we found that cartesianDETECT2 is computationally five times more efficient than MANTIS. Findings indicate that DOI estimates can be extracted from a double-Gaussian model of the detector response. We observed that our model predicts DOI in pixelated scintillator detectors reasonably well.

Monte Carlo simulation of the ARGO

International Nuclear Information System (INIS)

Depaola, G.O.

1997-01-01

We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)

The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations.

Science.gov (United States)

Liu, Chunping; Laporte, Audrey; Ferguson, Brian S

2008-09-01

In the health economics literature there is an ongoing debate over approaches used to estimate the efficiency of health systems at various levels, from the level of the individual hospital - or nursing home - up to that of the health system as a whole. The two most widely used approaches to evaluating the efficiency with which various units deliver care are non-parametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Productivity researchers tend to have very strong preferences over which methodology to use for efficiency estimation. In this paper, we use Monte Carlo simulation to compare the performance of DEA and SFA in terms of their ability to accurately estimate efficiency. We also evaluate quantile regression as a potential alternative approach. A Cobb-Douglas production function, random error terms and a technical inefficiency term with different distributions are used to calculate the observed output. The results, based on these experiments, suggest that neither DEA nor SFA can be regarded as clearly dominant, and that, depending on the quantile estimated, the quantile regression approach may be a useful addition to the armamentarium of methods for estimating technical efficiency.

GEANT Monte Carlo simulations for the GREAT spectrometer

International Nuclear Information System (INIS)

Andreyev, A.N.; Butler, P.A.; Page, R.D.; Appelbe, D.E.; Jones, G.D.; Joss, D.T.; Herzberg, R.-D.; Regan, P.H.; Simpson, J.; Wadsworth, R.

2004-01-01

GEANT Monte Carlo simulations for the recently developed GREAT spectrometer are presented. Some novel applications of the spectrometer for γ-ray, conversion-electron and β-decay spectroscopy are discussed. The conversion-electron spectroscopy of heavy nuclei with strongly converted transitions and the extension of the recoil decay tagging method to β-decaying nuclei are considered in detail

Monte Carlo simulation of a CZT detector

International Nuclear Information System (INIS)

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

2008-01-01

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

Monte Carlo simulation for radiographic applications

International Nuclear Information System (INIS)

Tillack, G.R.; Bellon, C.

2003-01-01

Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de

Monte Carlo simulation of AB-copolymers with saturating bonds

DEFF Research Database (Denmark)

Chertovich, A.C.; Ivanov, V.A.; Khokhlov, A.R.

2003-01-01

Structural transitions in a single AB-copolymer chain where saturating bonds can be formed between A- and B-units are studied by means of Monte Carlo computer simulations using the bond fluctuation model. Three transitions are found, coil-globule, coil-hairpin and globule-hairpin, depending...

Diagrammatic Monte Carlo simulations of staggered fermions at finite coupling

CERN Document Server

Vairinhos, Helvio

2016-01-01

Diagrammatic Monte Carlo has been a very fruitful tool for taming, and in some cases even solving, the sign problem in several lattice models. We have recently proposed a diagrammatic model for simulating lattice gauge theories with staggered fermions at arbitrary coupling, which extends earlier successful efforts to simulate lattice QCD at finite baryon density in the strong-coupling regime. Here we present the first numerical simulations of our model, using worm algorithms.

GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications

Science.gov (United States)

Lemaréchal, Yannick; Bert, Julien; Falconnet, Claire; Després, Philippe; Valeri, Antoine; Schick, Ulrike; Pradier, Olivier; Garcia, Marie-Paule; Boussion, Nicolas; Visvikis, Dimitris

2015-07-01

In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400  × 250  × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10-6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications.

GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications

International Nuclear Information System (INIS)

Lemaréchal, Yannick; Bert, Julien; Schick, Ulrike; Pradier, Olivier; Garcia, Marie-Paule; Boussion, Nicolas; Visvikis, Dimitris; Falconnet, Claire; Després, Philippe; Valeri, Antoine

2015-01-01

In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125 I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400  × 250  × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10 −6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications. (paper)

Microcanonical Monte Carlo approach for computing melting curves by atomistic simulations

OpenAIRE

Davis, Sergio; Gutiérrez, Gonzalo

2017-01-01

We report microcanonical Monte Carlo simulations of melting and superheating of a generic, Lennard-Jones system starting from the crystalline phase. The isochoric curve, the melting temperature $T_m$ and the critical superheating temperature $T_{LS}$ obtained are in close agreement (well within the microcanonical temperature fluctuations) with standard molecular dynamics one-phase and two-phase methods. These results validate the use of microcanonical Monte Carlo to compute melting points, a ...

Timesaving techniques for decision of electron-molecule collisions in Monte Carlo simulation of electrical discharges

International Nuclear Information System (INIS)

Sugawara, Hirotake; Mori, Naoki; Sakai, Yosuke; Suda, Yoshiyuki

2007-01-01

Techniques to reduce the computational load for determination of electron-molecule collisions in Monte Carlo simulations of electrical discharges have been presented. By enhancing the detection efficiency of the no-collision case in the decision scheme of the collisional events, we can decrease the frequency of access to time-consuming subroutines to calculate the electron collision cross sections of the gas molecules for obtaining the collision probability. A benchmark test and an estimation to evaluate the present techniques have shown a practical timesaving efficiency

Applications of the Monte Carlo simulation in dosimetry and medical physics problems

International Nuclear Information System (INIS)

Rojas C, E. L.

2010-01-01

At the present time the computers use to solve important problems extends to all the areas. These areas can be of social, economic, of engineering, of basic and applied science, etc. With and appropriate handling of computation programs and information can be carried out calculations and simulations of real models, to study them and to solve theoretical or application problems. The processes that contain random variables are susceptible of being approached with the Monte Carlo method. This is a numeric method that, thanks to the improvements in the processors of the computers, it can apply in many tasks more than what was made in the principles of their practical application (at the beginning of the decade of 1950). In this work the application of the Monte Carlo method will be approached in the simulation of the radiation interaction with the matter, to investigate dosimetric aspects of some problems that exist in the medical physics area. Also, contain an introduction about some historical data and some general concepts related with the Monte Carlo simulation are revised. (Author)

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)

Power distribution system reliability evaluation using dagger-sampling Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Hu, Y.; Zhao, S.; Ma, Y. [North China Electric Power Univ., Hebei (China). Dept. of Electrical Engineering

2009-03-11

A dagger-sampling Monte Carlo simulation method was used to evaluate power distribution system reliability. The dagger-sampling technique was used to record the failure of a component as an incident and to determine its occurrence probability by generating incident samples using random numbers. The dagger sampling technique was combined with the direct sequential Monte Carlo method to calculate average values of load point indices and system indices. Results of the 2 methods with simulation times of up to 100,000 years were then compared. The comparative evaluation showed that less computing time was required using the dagger-sampling technique due to its higher convergence speed. When simulation times were 1000 years, the dagger-sampling method required 0.05 seconds to accomplish an evaluation, while the direct method required 0.27 seconds. 12 refs., 3 tabs., 4 figs.

Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression.

Science.gov (United States)

Walker, Jeffrey A

2016-01-01

Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori . Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using O'Brien's OLS test, Anderson's permutation [Formula: see text]-test, two permutation F -tests (including GlobalAncova), and a rotation z -test (Roast). The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors) of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS distributions suggest that the GLS results in

Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression

Directory of Open Access Journals (Sweden)

Jeffrey A. Walker

2016-10-01

Full Text Available Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set. The original analysis of these data used a linear model (GLS of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. Methods The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS linear models and generalized estimating equation (GEE models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation ${r}_{F}^{2}$ r F 2 -test, two permutation F-tests (including GlobalAncova, and a rotation z-test (Roast. The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. Results GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS

A New Approach to Monte Carlo Simulations in Statistical Physics

Science.gov (United States)

Landau, David P.

2002-08-01

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

Monte Carlo simulations on a 9-node PC cluster

International Nuclear Information System (INIS)

Gouriou, J.

2001-01-01

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

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.

Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Suman, Vitisha [Health Physics Division, Bhabha Atomic Research Centre, Mumbai 400085 (India); Sarkar, P.K., E-mail: pksarkar02@gmail.com [Manipal Centre for Natural Sciences, Manipal University, Manipal 576104 (India)

2014-02-11

A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra.

Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation

International Nuclear Information System (INIS)

Suman, Vitisha; Sarkar, P.K.

2014-01-01

A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra

Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.

Science.gov (United States)

Serebrinsky, Santiago A

2011-03-01

We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.

A Monte Carlo error simulation applied to calibration-free X-ray diffraction phase analysis

International Nuclear Information System (INIS)

Braun, G.E.

1986-01-01

Quantitative phase analysis of a system of n phases can be effected without the need for calibration standards provided at least n different mixtures of these phases are available. A series of linear equations relating diffracted X-ray intensities, weight fractions and quantitation factors coupled with mass balance relationships can be solved for the unknown weight fractions and factors. Uncertainties associated with the measured X-ray intensities, owing to counting of random X-ray quanta, are used to estimate the errors in the calculated parameters utilizing a Monte Carlo simulation. The Monte Carlo approach can be generalized and applied to any quantitative X-ray diffraction phase analysis method. Two examples utilizing mixtures of CaCO 3 , Fe 2 O 3 and CaF 2 with an α-SiO 2 (quartz) internal standard illustrate the quantitative method and corresponding error analysis. One example is well conditioned; the other is poorly conditioned and, therefore, very sensitive to errors in the measured intensities. (orig.)

Estimation of radiation dose and risk to children undergoing cardiac catheterization for the treatment of a congenital heart disease using Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Yakoumakis, Emmanuel; Kostopoulou, Helen; Dimitriadis, Anastastios; Georgiou, Evaggelos [University of Athens, Medical Physics Department, Medical School, Athens (Greece); Makri, Triantafilia [' Agia Sofia' Hospital, Medical Physics Unit, Athens (Greece); Tsalafoutas, Ioannis [Anticancer-Oncology Hospital of Athens ' Agios Savvas' , Medical Physics Department, Athens (Greece)

2013-03-15

Children diagnosed with congenital heart disease often undergo cardiac catheterization for their treatment, which involves the use of ionizing radiation and therefore a risk of radiation-induced cancer. The purpose of this study was to calculate the effective and equivalent organ doses (H{sub T}) in those children and estimate the risk of exposure-induced death. Fifty-three children were divided into three groups: atrial septal defect (ASD), ventricular septal defect (VSD) and patent ductus arteriosus (PDA). In all procedures, the exposure conditions and the dose-area product meters readings were recorded for each individual acquisition. Monte Carlo simulations were run using the PCXMC 2.0 code and mathematical phantoms simulating a child's anatomy. The H{sub T} values to all irradiated organs and the resulting E and risk of exposure-induced death values were calculated. The average dose-area product values were, respectively, 40 {+-} 12 Gy.cm{sup 2} for the ASD, 17.5 {+-} 0.7 Gy.cm{sup 2} for the VSD and 9.5 {+-} 1 Gy.cm{sup 2} for the PDA group. The average E values were 40 {+-} 12, 22 {+-} 2.5 and 17 {+-} 3.6 mSv for ASD, VSD and PDA groups, respectively. The respective estimated risk of exposure-induced death values per procedure were 0.109, 0.106 and 0.067%. Cardiac catheterizations in children involve a considerable risk for radiation-induced cancer that has to be further reduced. (orig.)

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

International Nuclear Information System (INIS)

Shimizu, Takashi

2007-01-01

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

Random number generators for large-scale parallel Monte Carlo simulations on FPGA

Science.gov (United States)

Lin, Y.; Wang, F.; Liu, B.

2018-05-01

Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.

Monte Carlo molecular simulation of phase-coexistence for oil production and processing

KAUST Repository

Li, Jun; Sun, Shuyu; Calo, Victor M.

2011-01-01

The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components

A methodological approach to a realistic evaluation of skin absorbed doses during manipulation of radioactive sources by means of GAMOS Monte Carlo simulations

Science.gov (United States)

Italiano, Antonio; Amato, Ernesto; Auditore, Lucrezia; Baldari, Sergio

2018-05-01

The accurate evaluation of the radiation burden associated with radiation absorbed doses to the skin of the extremities during the manipulation of radioactive sources is a critical issue in operational radiological protection, deserving the most accurate calculation approaches available. Monte Carlo simulation of the radiation transport and interaction is the gold standard for the calculation of dose distributions in complex geometries and in presence of extended spectra of multi-radiation sources. We propose the use of Monte Carlo simulations in GAMOS, in order to accurately estimate the dose to the extremities during manipulation of radioactive sources. We report the results of these simulations for 90Y, 131I, 18F and 111In nuclides in water solutions enclosed in glass or plastic receptacles, such as vials or syringes. Skin equivalent doses at 70 μm of depth and dose-depth profiles are reported for different configurations, highlighting the importance of adopting a realistic geometrical configuration in order to get accurate dosimetric estimations. Due to the easiness of implementation of GAMOS simulations, case-specific geometries and nuclides can be adopted and results can be obtained in less than about ten minutes of computation time with a common workstation.

Monte Carlo simulation of discrete γ-ray detectors

International Nuclear Information System (INIS)

Bakkali, A.; Tamda, N.; Parmentier, M.; Chavanelle, J.; Pousse, A.; Kastler, B.

2005-01-01

Needs in medical diagnosis, especially for early and reliable breast cancer detection, lead us to consider developments in scintillation crystals and position sensitive photomultiplier tubes (PSPMT) in order to develop a high-resolution medium field γ-ray imaging device. However the ideal detector for γ-rays represents a compromise between many conflicting requirements. In order to optimize different parameters involved in the detection process, we have developed a Monte Carlo simulation software. Its aim was to study the light distribution produced by a gamma photon interacting with a pixellated scintillation crystal coupled to a PSPMT array. Several crystal properties were taken into account as well as the intrinsic response of PSPMTs. Images obtained by simulations are compared with experimental results. Agreement between simulation and experimental results validate our simulation model

Application of subset simulation in reliability estimation of underground pipelines

International Nuclear Information System (INIS)

Tee, Kong Fah; Khan, Lutfor Rahman; Li, Hongshuang

2014-01-01

This paper presents a computational framework for implementing an advanced Monte Carlo simulation method, called Subset Simulation (SS) for time-dependent reliability prediction of underground flexible pipelines. The SS can provide better resolution for low failure probability level of rare failure events which are commonly encountered in pipeline engineering applications. Random samples of statistical variables are generated efficiently and used for computing probabilistic reliability model. It gains its efficiency by expressing a small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment and compared with direct Monte Carlo simulation (MCS) method. Reliability of a buried flexible steel pipe with time-dependent failure modes, namely, corrosion induced deflection, buckling, wall thrust and bending stress has been assessed in this study. The analysis indicates that corrosion induced excessive deflection is the most critical failure event whereas buckling is the least susceptible during the whole service life of the pipe. The study also shows that SS is robust method to estimate the reliability of buried pipelines and it is more efficient than MCS, especially in small failure probability prediction

Estimating the Partition Function Zeros by Using the Wang-Landau Monte Carlo Algorithm

Energy Technology Data Exchange (ETDEWEB)

Kim, Seung-Yeon [Korea National University of Transportation, Chungju (Korea, Republic of)

2017-03-15

The concept of the partition function zeros is one of the most efficient methods for investigating the phase transitions and the critical phenomena in various physical systems. Estimating the partition function zeros requires information on the density of states Ω(E) as a function of the energy E. Currently, the Wang-Landau Monte Carlo algorithm is one of the best methods for calculating Ω(E). The partition function zeros in the complex temperature plane of the Ising model on an L × L square lattice (L = 10 ∼ 80) with a periodic boundary condition have been estimated by using the Wang-Landau Monte Carlo algorithm. The efficiency of the Wang-Landau Monte Carlo algorithm and the accuracies of the partition function zeros have been evaluated for three different, 5%, 10%, and 20%, flatness criteria for the histogram H(E).

On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample

DEFF Research Database (Denmark)

Oukbir, J.; Arnaud, M.

2001-01-01

We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...

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.

Monte Carlo simulation of radiative processes in electron-positron scattering

International Nuclear Information System (INIS)

Kleiss, R.H.P.

1982-01-01

The Monte Carlo simulation of scattering processes has turned out to be one of the most successful methods of translating theoretical predictions into experimentally meaningful quantities. It is the purpose of this thesis to describe how this approach can be applied to higher-order QED corrections to several fundamental processes. In chapter II a very brief overview of the currently interesting phenomena in e +- scattering is given. It is argued that accurate information on higher-order QED corrections is very important and that the Monte Carlo approach is one of the most flexible and general methods to obtain this information. In chapter III the author describes various techniques which are useful in this context, and makes a few remarks on the numerical aspects of the proposed method. In the following three chapters he applies this to the processes e + e - → μ + μ - (γ) and e + e - → qanti q(sigma). In chapter IV he motivates his choice of these processes in view of their experimental and theoretical relevance. The formulae necessary for a computer simulation of all quantities of interest, up to order α 3 , is given. Chapters V and VI describe how this simulation can be performed using the techniques mentioned in chapter III. In chapter VII it is shown how additional dynamical quantities, namely the polarization of the incoming and outgoing particles, can be incorporated in our treatment, and the relevant formulae for the example processes mentioned above are given. Finally, in chapter VIII the author presents some examples of the comparison between theoretical predictions based on Monte Carlo simulations as outlined here, and the results from actual experiments. (Auth.)

Latent degradation indicators estimation and prediction: A Monte Carlo approach

Science.gov (United States)

Zhou, Yifan; Sun, Yong; Mathew, Joseph; Wolff, Rodney; Ma, Lin

2011-01-01

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Systematic uncertainties on Monte Carlo simulation of lead based ADS

International Nuclear Information System (INIS)

Embid, M.; Fernandez, R.; Garcia-Sanz, J.M.; Gonzalez, E.

1999-01-01

Computer simulations of the neutronic behaviour of ADS systems foreseen for actinide and fission product transmutation are affected by many sources of systematic uncertainties, both from the nuclear data and by the methodology selected when applying the codes. Several actual ADS Monte Carlo simulations are presented, comparing different options both for the data and for the methodology, evaluating the relevance of the different uncertainties. (author)

Computed radiography simulation using the Monte Carlo code MCNPX

International Nuclear Information System (INIS)

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

2009-01-01

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

Computed radiography simulation using the Monte Carlo code MCNPX

Energy Technology Data Exchange (ETDEWEB)

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

2010-09-15

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

Estimating the occurrence of foreign material in Advanced Gas-cooled Reactors: A Bayesian Monte Carlo approach

International Nuclear Information System (INIS)

Mason, Paolo

2014-01-01

Highlights: • The amount of a specific type of foreign material found in UK AGRs has been estimated. • The estimate is based on very few instances of detection in numerous inspections. • A Bayesian Monte Carlo approach was used. • The study supports safety case claims on coolant flow impairment. • The methodology is applicable to any inspection campaign on any plant system. - Abstract: The current occurrence of a particular sort of foreign material in eight UK Advanced Gas-cooled Reactors has been estimated by means of a parametric approach. The study includes both variability, treated in analytic fashion via the combination of standard probability distributions, and the uncertainty in the parameters of the model of choice, whose posterior distribution was inferred in Bayesian fashion by means of a Monte Carlo route consisting in the conditional acceptance of sets of model parameters drawn from a prior distribution based on engineering judgement. The model underlying the present study specifically refers to the re-loading and inspection routines of UK Advanced Gas-cooled Reactors. The approach to inference here presented, however, is of general validity and can be applied to the outcome of any inspection campaign on any plant system, and indeed to any situation in which the outcome of a stochastic process is more easily simulated than described by a probability density or mass function

Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

Directory of Open Access Journals (Sweden)

S. Kim

2015-06-01

Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.

Monte Carlo simulation of muon radiation environment in China Jinping Underground Laboratory

International Nuclear Information System (INIS)

Su Jian; Zeng Zhi; Liu Yue; Yue Qian; Ma Hao; Cheng Jianping

2012-01-01

Muon radiation background of China Jinping Underground Laboratory (CJPL) was simulated by Monte Carlo method. According to the Gaisser formula and the MUSIC soft, the model of cosmic ray muons was established. Then the yield and the average energy of muon-induced photons and muon-induced neutrons were simulated by FLUKA. With the single-energy approximation, the contribution to the radiation background of shielding structure by secondary photons and neutrons was evaluated. The estimation results show that the average energy of residual muons is 369 GeV and the flux is 3.17 × 10 -6 m -2 · s -1 . The fluence rate of secondary photons is about 1.57 × 10 -4 m -2 · s -1 , and the fluence rate of secondary neutrons is about 8.37 × 10 -7 m -2 · s -1 . The muon radiation background of CJPL is lower than those of most other underground laboratories in the world. (authors)

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

NARCIS (Netherlands)

Leitao Rodriguez, A.; Grzelak, L.A.; Oosterlee, C.W.

2017-01-01

In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math.

The Monte Carlo simulation of the Ladon photon beam facility

International Nuclear Information System (INIS)

Strangio, C.

1976-01-01

The backward compton scattering of laser light against high energy electrons has been simulated with a Monte Carlo method. The main features of the produced photon beam are reported as well as a careful description of the numerical calculation

Accurate and precise determination of critical properties from Gibbs ensemble Monte Carlo simulations

International Nuclear Information System (INIS)

Dinpajooh, Mohammadhasan; Bai, Peng; Allan, Douglas A.; Siepmann, J. Ilja

2015-01-01

Since the seminal paper by Panagiotopoulos [Mol. Phys. 61, 813 (1997)], the Gibbs ensemble Monte Carlo (GEMC) method has been the most popular particle-based simulation approach for the computation of vapor–liquid phase equilibria. However, the validity of GEMC simulations in the near-critical region has been questioned because rigorous finite-size scaling approaches cannot be applied to simulations with fluctuating volume. Valleau [Mol. Simul. 29, 627 (2003)] has argued that GEMC simulations would lead to a spurious overestimation of the critical temperature. More recently, Patel et al. [J. Chem. Phys. 134, 024101 (2011)] opined that the use of analytical tail corrections would be problematic in the near-critical region. To address these issues, we perform extensive GEMC simulations for Lennard-Jones particles in the near-critical region varying the system size, the overall system density, and the cutoff distance. For a system with N = 5500 particles, potential truncation at 8σ and analytical tail corrections, an extrapolation of GEMC simulation data at temperatures in the range from 1.27 to 1.305 yields T c = 1.3128 ± 0.0016, ρ c = 0.316 ± 0.004, and p c = 0.1274 ± 0.0013 in excellent agreement with the thermodynamic limit determined by Potoff and Panagiotopoulos [J. Chem. Phys. 109, 10914 (1998)] using grand canonical Monte Carlo simulations and finite-size scaling. Critical properties estimated using GEMC simulations with different overall system densities (0.296 ≤ ρ t ≤ 0.336) agree to within the statistical uncertainties. For simulations with tail corrections, data obtained using r cut = 3.5σ yield T c and p c that are higher by 0.2% and 1.4% than simulations with r cut = 5 and 8σ but still with overlapping 95% confidence intervals. In contrast, GEMC simulations with a truncated and shifted potential show that r cut = 8σ is insufficient to obtain accurate results. Additional GEMC simulations for hard-core square-well particles with various

Multi-Subband Ensemble Monte Carlo simulations of scaled GAA MOSFETs

Science.gov (United States)

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

2018-05-01

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

Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

KAUST Repository

Moraes, Alvaro

2015-01-01

even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-05-15

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Monte Carlo Simulation of a Solvated Ionic Polymer with Cluster Morphology

National Research Council Canada - National Science Library

Matthews, Jessica L; Lada, Emily K; Weiland, Lisa M; Smith, Ralph C; Leo, Donald J

2005-01-01

.... Traditional rotational isomeric state theory is applied in combination with a Monte Carlo methodology to develop a simulation model of the conformation of Nafion polymer chains on a nanoscopic level...

Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation

International Nuclear Information System (INIS)

Marseguerra, M.; Zio, E.

2000-01-01

In this paper we present an optimization approach based on the combination of a Genetic Algorithms maximization procedure with a Monte Carlo simulation. The approach is applied within the context of plant logistic management for what concerns the choice of maintenance and repair strategies. A stochastic model of plant operation is developed from the standpoint of its reliability/availability behavior, i.e. of the failure/repair/maintenance processes of its components. The model is evaluated by Monte Carlo simulation in terms of economic costs and revenues of operation. The flexibility of the Monte Carlo method allows us to include several practical aspects such as stand-by operation modes, deteriorating repairs, aging, sequences of periodic maintenances, number of repair teams available for different kinds of repair interventions (mechanical, electronic, hydraulic, etc.), components priority rankings. A genetic algorithm is then utilized to optimize the components maintenance periods and number of repair teams. The fitness function object of the optimization is a profit function which inherently accounts for the safety and economic performance of the plant and whose value is computed by the above Monte Carlo simulation model. For an efficient combination of Genetic Algorithms and Monte Carlo simulation, only few hundreds Monte Carlo histories are performed for each potential solution proposed by the genetic algorithm. Statistical significance of the results of the solutions of interest (i.e. the best ones) is then attained exploiting the fact that during the population evolution the fit chromosomes appear repeatedly many times. The proposed optimization approach is applied on two case studies of increasing complexity

Six types Monte Carlo for estimating the current unavailability of Markov system with dependent repair

International Nuclear Information System (INIS)

Xiao Gang; Li Zhizhong

2004-01-01

Based on integral equaiton describing the life-history of Markov system, six types of estimators of the current unavailability of Markov system with dependent repair are propounded. Combining with the biased sampling of state transition time of system, six types of Monte Carlo for estimating the current unavailability are given. Two numerical examples are given to deal with the variances and efficiencies of the six types of Monte Carlo methods. (authors)

Monte Carlo simulations for the optimisation of low-background Ge detector designs

Energy Technology Data Exchange (ETDEWEB)

Hakenmueller, Janina; Heusser, Gerd; Maneschg, Werner; Schreiner, Jochen; Simgen, Hardy; Stolzenburg, Dominik; Strecker, Herbert; Weber, Marc; Westernmann, Jonas [Max-Planck-Institut fuer Kernphysik, Saupfercheckweg 1, 69117 Heidelberg (Germany); Laubenstein, Matthias [Laboratori Nazionali del Gran Sasso, Via G. Acitelli 22, 67100 Assergi L' Aquila (Italy)

2015-07-01

Monte Carlo simulations for the low-background Ge spectrometer Giove at the underground laboratory of MPI-K, Heidelberg, are presented. In order to reduce the cosmogenic background at the present shallow depth (15 m w.e.) the shielding of the spectrometer includes an active muon veto and a passive shielding (lead and borated PE layers). The achieved background suppression is comparable to Ge spectrometers operated in much greater depth. The geometry of the detector and the shielding were implemented using the Geant4-based toolkit MaGe. The simulations were successfully optimised by determining the correct diode position and active volume. With the help of the validated Monte Carlo simulation the contribution of the single components to the overall background can be examined. This includes a comparison between simulated results and measurements with different fillings of the sample chamber. Having reproduced the measured detector background in the simulation provides the possibility to improve the background by reverse engineering of the passive and active shield layers in the simulation.

Raman Monte Carlo simulation for light propagation for tissue with embedded objects

Science.gov (United States)

Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

2018-02-01

Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-04-15

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-04-01

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

Investigation of the SCS-CN initial abstraction ratio using a Monte Carlo simulation for the derived flood frequency curves

Science.gov (United States)

Caporali, E.; Chiarello, V.; Galeati, G.

2014-12-01

Peak discharges estimates for a given return period are of primary importance in engineering practice for risk assessment and hydraulic structure design. Different statistical methods are chosen here for the assessment of flood frequency curve: one indirect technique based on the extreme rainfall event analysis, the Peak Over Threshold (POT) model and the Annual Maxima approach as direct techniques using river discharge data. In the framework of the indirect method, a Monte Carlo simulation approach is adopted to determine a derived frequency distribution of peak runoff using a probabilistic formulation of the SCS-CN method as stochastic rainfall-runoff model. A Monte Carlo simulation is used to generate a sample of different runoff events from different stochastic combination of rainfall depth, storm duration, and initial loss inputs. The distribution of the rainfall storm events is assumed to follow the GP law whose parameters are estimated through GEV's parameters of annual maximum data. The evaluation of the initial abstraction ratio is investigated since it is one of the most questionable assumption in the SCS-CN model and plays a key role in river basin characterized by high-permeability soils, mainly governed by infiltration excess mechanism. In order to take into account the uncertainty of the model parameters, this modified approach, that is able to revise and re-evaluate the original value of the initial abstraction ratio, is implemented. In the POT model the choice of the threshold has been an essential issue, mainly based on a compromise between bias and variance. The Generalized Extreme Value (GEV) distribution fitted to the annual maxima discharges is therefore compared with the Pareto distributed peaks to check the suitability of the frequency of occurrence representation. The methodology is applied to a large dam in the Serchio river basin, located in the Tuscany Region. The application has shown as Monte Carlo simulation technique can be a useful

Study of Gamma spectra by Monte Carlo simulation

International Nuclear Information System (INIS)

Cantaragiu, A.; Gheorghies, A.; Borcia, C.

2008-01-01

The purpose of this paper is obtaining gamma ray spectra by means of a scintillation detector applying the Monte Carlo statistic simulation method using the EGS4 program. The Monte Carlo algorithm implies that the physical system is described by the probability density function which allows generating random figures and the result is taken as an average of numbers which were observed. The EGS4 program allows the simulation of the following physical processes: the photo-electrical effect, the Compton effect, the electron positron pairs generation and the Rayleigh diffusion. The gamma rays recorded by the detector are converted into electrical pulses and the gamma ray spectra are acquired and processed by means of the Nomad Plus portable spectrometer connected to a computer. As a gamma ray sources 137Cs and 60Co are used whose spectra drawn and used for study the interaction of the gamma radiations with the scintillation detector. The parameters which varied during the acquisition of the gamma ray spectra are the distance between source and detector and the measuring time. Due to the statistical processes in the detector, the peak looks like a Gauss distribution. The identification of the gamma quantum energy value is achieved by the experimental spectra peaks, thus gathering information about the position of the peak, the width and the area of the peak respectively. By means of the EGS4 program a simulation is run using these parameters and an 'ideal' spectrum is obtained, a spectrum which is not influenced by the statistical processes which take place inside the detector. Then, the convolution of the spectra is achieved by means of a normalised Gauss function. There is a close match between the experimental results and those simulated in the EGS4 program because the interactions which occurred during the simulation have a statistical behaviour close to the real one. (authors)

Backscattered radiation into a transmission ionization chamber: Measurement and Monte Carlo simulation

International Nuclear Information System (INIS)

Yoshizumi, Maira T.; Yoriyaz, Helio; Caldas, Linda V.E.

2010-01-01

Backscattered radiation (BSR) from field-defining collimators can affect the response of a monitor chamber in X-radiation fields. This contribution must be considered since this kind of chamber is used to monitor the equipment response. In this work, the dependence of a transmission ionization chamber response on the aperture diameter of the collimators was studied experimentally and using a Monte Carlo (MC) technique. According to the results, the BSR increases the chamber response of over 4.0% in the case of a totally closed collimator and 50 kV energy beam, using both techniques. The results from Monte Carlo simulation confirm the validity of the simulated geometry.

G4-STORK: A Geant4-based Monte Carlo reactor kinetics simulation code

International Nuclear Information System (INIS)

Russell, Liam; Buijs, Adriaan; Jonkmans, Guy

2014-01-01

Highlights: • G4-STORK is a new, time-dependent, Monte Carlo code for reactor physics applications. • G4-STORK was built by adapting and expanding on the Geant4 Monte Carlo toolkit. • G4-STORK was designed to simulate short-term fluctuations in reactor cores. • G4-STORK is well suited for simulating sub- and supercritical assemblies. • G4-STORK was verified through comparisons with DRAGON and MCNP. - Abstract: In this paper we introduce G4-STORK (Geant4 STOchastic Reactor Kinetics), a new, time-dependent, Monte Carlo particle tracking code for reactor physics applications. G4-STORK was built by adapting and expanding on the Geant4 Monte Carlo toolkit. The toolkit provides the fundamental physics models and particle tracking algorithms that track each particle in space and time. It is a framework for further development (e.g. for projects such as G4-STORK). G4-STORK derives reactor physics parameters (e.g. k eff ) from the continuous evolution of a population of neutrons in space and time in the given simulation geometry. In this paper we detail the major additions to the Geant4 toolkit that were necessary to create G4-STORK. These include a renormalization process that maintains a manageable number of neutrons in the simulation even in very sub- or supercritical systems, scoring processes (e.g. recording fission locations, total neutrons produced and lost, etc.) that allow G4-STORK to calculate the reactor physics parameters, and dynamic simulation geometries that can change over the course of simulation to illicit reactor kinetics responses (e.g. fuel temperature reactivity feedback). The additions are verified through simple simulations and code-to-code comparisons with established reactor physics codes such as DRAGON and MCNP. Additionally, G4-STORK was developed to run a single simulation in parallel over many processors using MPI (Message Passing Interface) pipes

PENELOPE, and algorithm and computer code for Monte Carlo simulation of electron-photon showers

Energy Technology Data Exchange (ETDEWEB)

Salvat, F.; Fernandez-Varea, J.M.; Baro, J.; Sempau, J.

1996-10-01

The FORTRAN 77 subroutine package PENELOPE performs Monte Carlo simulation of electron-photon showers in arbitrary for a wide energy range, from similar{sub t}o 1 KeV to several hundred MeV. Photon transport is simulated by means of the standard, detailed simulation scheme. Electron and positron histories are generated on the basis of a mixed procedure, which combines detailed simulation of hard events with condensed simulation of soft interactions. A simple geometry package permits the generation of random electron-photon showers in material systems consisting of homogeneous bodies limited by quadric surfaces, i.e. planes, spheres cylinders, etc. This report is intended not only to serve as a manual of the simulation package, but also to provide the user with the necessary information to understand the details of the Monte Carlo algorithm.

PENELOPE, an algorithm and computer code for Monte Carlo simulation of electron-photon showers

Energy Technology Data Exchange (ETDEWEB)

Salvat, F; Fernandez-Varea, J M; Baro, J; Sempau, J

1996-07-01

The FORTRAN 77 subroutine package PENELOPE performs Monte Carlo simulation of electron-photon showers in arbitrary for a wide energy range, from 1 keV to several hundred MeV. Photon transport is simulated by means of the standard, detailed simulation scheme. Electron and positron histories are generated on the basis of a mixed procedure, which combines detailed simulation of hard events with condensed simulation of soft interactions. A simple geometry package permits the generation of random electron-photon showers in material systems consisting of homogeneous bodies limited by quadric surfaces, i.e. planes, spheres, cylinders, etc. This report is intended not only to serve as a manual of the simulation package, but also to provide the user with the necessary information to understand the details of the Monte Carlo algorithm. (Author) 108 refs.

Sequential Monte Carlo simulation of collision risk in free flight air traffic

NARCIS (Netherlands)

Blom, H.A.P.; Bakker, G.; Krystul, J.; Everdij, M.H.C.; Klein Obbink, B.; Klompstra, M.B.

2005-01-01

Within HYBRIDGE a novel approach in speeding up Monte Carlo simulation of rare events has been developed. In the current report this method is extended for application to simulating collisions with a stochastic dynamical model of an air traffic operational concept. Subsequently this extended Monte

Monte Carlo Simulations Validation Study: Vascular Brachytherapy Beta Sources

International Nuclear Information System (INIS)

Orion, I.; Koren, K.

2004-01-01

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

APPLICATION OF QUEUING THEORY TO AUTOMATED TELLER MACHINE (ATM) FACILITIES USING MONTE CARLO SIMULATION

OpenAIRE

UDOANYA RAYMOND MANUEL; ANIEKAN OFFIONG

2014-01-01

This paper presents the importance of applying queuing theory to the Automated Teller Machine (ATM) using Monte Carlo Simulation in order to determine, control and manage the level of queuing congestion found within the Automated Teller Machine (ATM) centre in Nigeria and also it contains the empirical data analysis of the queuing systems obtained at the Automated Teller Machine (ATM) located within the Bank premises for a period of three (3) months. Monte Carlo Simulation is applied to th...

Monte Carlo simulations of neutron-scattering instruments using McStas

DEFF Research Database (Denmark)

Nielsen, K.; Lefmann, K.

2000-01-01

Monte Carlo simulations have become an essential tool for improving the performance of neutron-scattering instruments, since the level of sophistication in the design of instruments is defeating purely analytical methods. The program McStas, being developed at Rise National Laboratory, includes...

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

Monte Carlo simulation and experimental verification of radiotherapy electron beams

International Nuclear Information System (INIS)

Griffin, J.; Deloar, H. M.

2007-01-01

Full text: Based on fundamental physics and statistics, the Monte Carlo technique is generally accepted as the accurate method for modelling radiation therapy treatments. A Monte Carlo simulation system has been installed, and models of linear accelerators in the more commonly used electron beam modes have been built and commissioned. A novel technique for radiation dosimetry is also being investigated. Combining the advantages of both water tank and solid phantom dosimetry, a hollow, thin walled shell or mask is filled with water and then raised above the natural water surface to produce a volume of water with the desired irregular shape.

GATE Monte Carlo simulation of GE discovery 600 and a uniformity phantom

Energy Technology Data Exchange (ETDEWEB)

Sheen, Heesoon [Sungkyunkwan University, Seoul (Korea, Republic of); GE Healthcare Korea, Seoul (Korea, Republic of); Im, Kichun; Choi, Yong; Shin, Hanback [Sogang University, Seoul (Korea, Republic of); Han, Youngyih [Samsung Medical Center, Seoul (Korea, Republic of); Sungkyunkwan University, Seoul (Korea, Republic of); Chung, Kwangzoo; Cho, Junsang [Samsung Medical Center, Seoul (Korea, Republic of); Ahn, Sanghee [Sungkyunkwan University, Seoul (Korea, Republic of)

2014-12-15

GATE (Geant4 Application Tomography Emission) Monte Carlo simulations have been successful in the application of emission tomography for precise modeling of various physical processes. Most previous studies on Monte Carlo simulations have only involved performance assessments using virtual phantoms. Although that allows the performance of simulated positron emission tomography (PET) to be evaluated, it does not reflect the reality of practical conditions. This restriction causes substantial drawbacks in GATE simulations of real situations. To overcome the described limitation and to provide a method to enable simulation research relevant to clinically important issues, we conducted a GATE simulation using real data from a scanner rather than a virtual phantom and evaluated the scanner is performance. For that purpose, the system and the geometry of a commercial GE PET/ CT (computed tomography) scanner, BGO-based Discovery 600 (D600), was developed for the first time. The performance of the modeled PET system was evaluated by using the National Electrical Manufacturers Association NEMA NU 2-2007 protocols and results were compared with those of the reference data. The sensitivity, scatter fraction, noise-equivalent count rate (NECR), and resolution were estimated by using the protocol of the NEMA NU2-2007. Sensitivities were 9.01 cps/kBq at 0 cm and 9.43 cps/kBq at 10 cm. Scatter fractions were 39.5%. The NECR peak was 89.7 kcps at 14.7 kBq/cc. Resolutions were 4.8 mm in the transaxial plane and 5.9 mm in the axial plane at 1 cm, and 6.2 mm in the transaxial plane and 6.4 mm in the axial plane at 10 cm. The resolutions exceeded the limited value provided by the manufacturer. The uniformity phantom was simulated using the CT and the PET data. The output data in a ROOT format were converted and then reconstructed by using the C program and STIR (Software for Tomographic Image Reconstruction). The reconstructed images of the simulated uniformity phantom data had

GATE Monte Carlo simulation of GE Discovery 600 and a uniformity phantom

Science.gov (United States)

Sheen, Heesoon; Im, Ki Chun; Choi, Yong; Shin, Hanback; Han, Youngyih; Chung, Kwangzoo; Cho, Junsang; Ahn, Sang Hee

2014-12-01

GATE (Geant4 Application Tomography Emission) Monte Carlo simulations have been successful in the application of emission tomography for precise modeling of various physical processes. Most previous studies on Monte Carlo simulations have only involved performance assessments using virtual phantoms. Although that allows the performance of simulated positron emission tomography (PET) to be evaluated, it does not reflect the reality of practical conditions. This restriction causes substantial drawbacks in GATE simulations of real situations. To overcome the described limitation and to provide a method to enable simulation research relevant to clinically important issues, we conducted a GATE simulation using real data from a scanner rather than a virtual phantom and evaluated the scanner is performance. For that purpose, the system and the geometry of a commercial GE PET/ CT (computed tomography) scanner, BGO-based Discovery 600 (D600), was developed for the first time. The performance of the modeled PET system was evaluated by using the National Electrical Manufacturers Association NEMA NU 2-2007 protocols and results were compared with those of the reference data. The sensitivity, scatter fraction, noise-equivalent count rate (NECR), and resolution were estimated by using the protocol of the NEMA NU2-2007. Sensitivities were 9.01 cps/kBq at 0 cm and 9.43 cps/kBq at 10 cm. Scatter fractions were 39.5%. The NECR peak was 89.7 kcps @ 14.7 kBq/cc. Resolutions were 4.8 mm in the transaxial plane and 5.9 mm in the axial plane at 1 cm, and 6.2 mm in the transaxial plane and 6.4 mm in the axial plane at 10 cm. The resolutions exceeded the limited value provided by the manufacturer. The uniformity phantom was simulated using the CT and the PET data. The output data in a ROOT format were converted and then reconstructed by using the C program and STIR (Software for Tomographic Image Reconstruction). The reconstructed images of the simulated uniformity phantom data had

GATE Monte Carlo simulation of GE discovery 600 and a uniformity phantom

International Nuclear Information System (INIS)

Sheen, Heesoon; Im, Kichun; Choi, Yong; Shin, Hanback; Han, Youngyih; Chung, Kwangzoo; Cho, Junsang; Ahn, Sanghee

2014-01-01

GATE (Geant4 Application Tomography Emission) Monte Carlo simulations have been successful in the application of emission tomography for precise modeling of various physical processes. Most previous studies on Monte Carlo simulations have only involved performance assessments using virtual phantoms. Although that allows the performance of simulated positron emission tomography (PET) to be evaluated, it does not reflect the reality of practical conditions. This restriction causes substantial drawbacks in GATE simulations of real situations. To overcome the described limitation and to provide a method to enable simulation research relevant to clinically important issues, we conducted a GATE simulation using real data from a scanner rather than a virtual phantom and evaluated the scanner is performance. For that purpose, the system and the geometry of a commercial GE PET/ CT (computed tomography) scanner, BGO-based Discovery 600 (D600), was developed for the first time. The performance of the modeled PET system was evaluated by using the National Electrical Manufacturers Association NEMA NU 2-2007 protocols and results were compared with those of the reference data. The sensitivity, scatter fraction, noise-equivalent count rate (NECR), and resolution were estimated by using the protocol of the NEMA NU2-2007. Sensitivities were 9.01 cps/kBq at 0 cm and 9.43 cps/kBq at 10 cm. Scatter fractions were 39.5%. The NECR peak was 89.7 kcps at 14.7 kBq/cc. Resolutions were 4.8 mm in the transaxial plane and 5.9 mm in the axial plane at 1 cm, and 6.2 mm in the transaxial plane and 6.4 mm in the axial plane at 10 cm. The resolutions exceeded the limited value provided by the manufacturer. The uniformity phantom was simulated using the CT and the PET data. The output data in a ROOT format were converted and then reconstructed by using the C program and STIR (Software for Tomographic Image Reconstruction). The reconstructed images of the simulated uniformity phantom data had

'Odontologic dosimetric card' experiments and simulations using Monte Carlo methods

International Nuclear Information System (INIS)

Menezes, C.J.M.; Lima, R. de A.; Peixoto, J.E.; Vieira, J.W.

2008-01-01

The techniques for data processing, combined with the development of fast and more powerful computers, makes the Monte Carlo methods one of the most widely used tools in the radiation transport simulation. For applications in diagnostic radiology, this method generally uses anthropomorphic phantoms to evaluate the absorbed dose to patients during exposure. In this paper, some Monte Carlo techniques were used to simulation of a testing device designed for intra-oral X-ray equipment performance evaluation called Odontologic Dosimetric Card (CDO of 'Cartao Dosimetrico Odontologico' in Portuguese) for different thermoluminescent detectors. This paper used two computational models of exposition RXD/EGS4 and CDO/EGS4. In the first model, the simulation results are compared with experimental data obtained in the similar conditions. The second model, it presents the same characteristics of the testing device studied (CDO). For the irradiations, the X-ray spectra were generated by the IPEM report number 78, spectrum processor. The attenuated spectrum was obtained for IEC 61267 qualities and various additional filters for a Pantak 320 X-ray industrial equipment. The results obtained for the study of the copper filters used in the determination of the kVp were compared with experimental data, validating the model proposed for the characterization of the CDO. The results shower of the CDO will be utilized in quality assurance programs in order to guarantee that the equipment fulfill the requirements of the Norm SVS No. 453/98 MS (Brazil) 'Directives of Radiation Protection in Medical and Dental Radiodiagnostic'. We conclude that the EGS4 is a suitable code Monte Carlo to simulate thermoluminescent dosimeters and experimental procedures employed in the routine of the quality control laboratory in diagnostic radiology. (author)

Monte Carlo simulation of a mammographic test phantom

International Nuclear Information System (INIS)

Hunt, R. A.; Dance, D. R.; Pachoud, M.; Carlsson, G. A.; Sandborg, M.; Ullman, G.

2005-01-01

A test phantom, including a wide range of mammographic tissue equivalent materials and test details, was imaged on a digital mammographic system. In order to quantify the effect of scatter on the contrast obtained for the test details, calculations of the scatter-to-primary ratio (S/P) have been made using a Monte Carlo simulation of the digital mammographic imaging chain, grid and test phantom. The results show that the S/P values corresponding to the imaging conditions used were in the range 0.084-0.126. Calculated and measured pixel values in different regions of the image were compared as a validation of the model and showed excellent agreement. The results indicate the potential of Monte Carlo methods in the image quality-patient dose process optimisation, especially in the assessment of imaging conditions not available on standard mammographic units. (authors)

Monte Carlo simulation of mixed neutron-gamma radiation fields and dosimetry devices

International Nuclear Information System (INIS)

Zhang, Guoqing

2011-01-01

Monte Carlo methods based on random sampling are widely used in different fields for the capability of solving problems with a large number of coupled degrees of freedom. In this work, Monte Carlos methods are successfully applied for the simulation of the mixed neutron-gamma field in an interim storage facility and neutron dosimeters of different types. Details are discussed in two parts: In the first part, the method of simulating an interim storage facility loaded with CASTORs is presented. The size of a CASTOR is rather large (several meters) and the CASTOR wall is very thick (tens of centimeters). Obtaining the results of dose rates outside a CASTOR with reasonable errors costs usually hours or even days. For the simulation of a large amount of CASTORs in an interim storage facility, it needs weeks or even months to finish a calculation. Variance reduction techniques were used to reduce the calculation time and to achieve reasonable relative errors. Source clones were applied to avoid unnecessary repeated calculations. In addition, the simulations were performed on a cluster system. With the calculation techniques discussed above, the efficiencies of calculations can be improved evidently. In the second part, the methods of simulating the response of neutron dosimeters are presented. An Alnor albedo dosimeter was modelled in MCNP, and it has been simulated in the facility to calculate the calibration factor to get the evaluated response to a Cf-252 source. The angular response of Makrofol detectors to fast neutrons has also been investigated. As a kind of SSNTD, Makrofol can detect fast neutrons by recording the neutron induced heavy charged recoils. To obtain the information of charged recoils, general-purpose Monte Carlo codes were used for transporting incident neutrons. The response of Makrofol to fast neutrons is dependent on several factors. Based on the parameters which affect the track revealing, the formation of visible tracks was determined. For

Monte Carlo simulation of mixed neutron-gamma radiation fields and dosimetry devices

Energy Technology Data Exchange (ETDEWEB)

Zhang, Guoqing

2011-12-22

Monte Carlo methods based on random sampling are widely used in different fields for the capability of solving problems with a large number of coupled degrees of freedom. In this work, Monte Carlos methods are successfully applied for the simulation of the mixed neutron-gamma field in an interim storage facility and neutron dosimeters of different types. Details are discussed in two parts: In the first part, the method of simulating an interim storage facility loaded with CASTORs is presented. The size of a CASTOR is rather large (several meters) and the CASTOR wall is very thick (tens of centimeters). Obtaining the results of dose rates outside a CASTOR with reasonable errors costs usually hours or even days. For the simulation of a large amount of CASTORs in an interim storage facility, it needs weeks or even months to finish a calculation. Variance reduction techniques were used to reduce the calculation time and to achieve reasonable relative errors. Source clones were applied to avoid unnecessary repeated calculations. In addition, the simulations were performed on a cluster system. With the calculation techniques discussed above, the efficiencies of calculations can be improved evidently. In the second part, the methods of simulating the response of neutron dosimeters are presented. An Alnor albedo dosimeter was modelled in MCNP, and it has been simulated in the facility to calculate the calibration factor to get the evaluated response to a Cf-252 source. The angular response of Makrofol detectors to fast neutrons has also been investigated. As a kind of SSNTD, Makrofol can detect fast neutrons by recording the neutron induced heavy charged recoils. To obtain the information of charged recoils, general-purpose Monte Carlo codes were used for transporting incident neutrons. The response of Makrofol to fast neutrons is dependent on several factors. Based on the parameters which affect the track revealing, the formation of visible tracks was determined. For

Quantum Monte Carlo simulations for high-Tc superconductors

International Nuclear Information System (INIS)

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

1992-01-01

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

Monte Carlo simulation of MOSFET dosimeter for electron backscatter using the GEANT4 code.

Science.gov (United States)

Chow, James C L; Leung, Michael K K

2008-06-01

The aim of this study is to investigate the influence of the body of the metal-oxide-semiconductor field effect transistor (MOSFET) dosimeter in measuring the electron backscatter from lead. The electron backscatter factor (EBF), which is defined as the ratio of dose at the tissue-lead interface to the dose at the same point without the presence of backscatter, was calculated by the Monte Carlo simulation using the GEANT4 code. Electron beams with energies of 4, 6, 9, and 12 MeV were used in the simulation. It was found that in the presence of the MOSFET body, the EBFs were underestimated by about 2%-0.9% for electron beam energies of 4-12 MeV, respectively. The trend of the decrease of EBF with an increase of electron energy can be explained by the small MOSFET dosimeter, mainly made of epoxy and silicon, not only attenuated the electron fluence of the electron beam from upstream, but also the electron backscatter generated by the lead underneath the dosimeter. However, this variation of the EBF underestimation is within the same order of the statistical uncertainties as the Monte Carlo simulations, which ranged from 1.3% to 0.8% for the electron energies of 4-12 MeV, due to the small dosimetric volume. Such small EBF deviation is therefore insignificant when the uncertainty of the Monte Carlo simulation is taken into account. Corresponding measurements were carried out and uncertainties compared to Monte Carlo results were within +/- 2%. Spectra of energy deposited by the backscattered electrons in dosimetric volumes with and without the lead and MOSFET were determined by Monte Carlo simulations. It was found that in both cases, when the MOSFET body is either present or absent in the simulation, deviations of electron energy spectra with and without the lead decrease with an increase of the electron beam energy. Moreover, the softer spectrum of the backscattered electron when lead is present can result in a reduction of the MOSFET response due to stronger

Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations

DEFF Research Database (Denmark)

Thomsen, M.; Bergbäck Knudsen, Erik; Willendrup, Peter Kjær

2015-01-01

We show how radiological images of both single and multi material samples can be simulated using the Monte Carlo simulation tool McXtrace and how these images can be used to make a three dimensional reconstruction. Good numerical agreement between the X-ray attenuation coefficient in experimental...

Efficient Monte Carlo Simulations of Gas Molecules Inside Porous Materials.

Science.gov (United States)

Kim, Jihan; Smit, Berend

2012-07-10

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

Monte Carlo simulations in small animal PET imaging

Energy Technology Data Exchange (ETDEWEB)

Branco, Susana [Universidade de Lisboa, Faculdade de Ciencias, Instituto de Biofisica e Engenharia Biomedica, Lisbon (Portugal)], E-mail: susana.silva@fc.ul.pt; Jan, Sebastien [Service Hospitalier Frederic Joliot, CEA/DSV/DRM, Orsay (France); Almeida, Pedro [Universidade de Lisboa, Faculdade de Ciencias, Instituto de Biofisica e Engenharia Biomedica, Lisbon (Portugal)

2007-10-01

This work is based on the use of an implemented Positron Emission Tomography (PET) simulation system dedicated for small animal PET imaging. Geant4 Application for Tomographic Emission (GATE), a Monte Carlo simulation platform based on the Geant4 libraries, is well suited for modeling the microPET FOCUS system and to implement realistic phantoms, such as the MOBY phantom, and data maps from real examinations. The use of a microPET FOCUS simulation model with GATE has been validated for spatial resolution, counting rates performances, imaging contrast recovery and quantitative analysis. Results from realistic studies of the mouse body using {sup -}F and [{sup 18}F]FDG imaging protocols are presented. These simulations include the injection of realistic doses into the animal and realistic time framing. The results have shown that it is possible to simulate small animal PET acquisitions under realistic conditions, and are expected to be useful to improve the quantitative analysis in PET mouse body studies.

Fast analytical scatter estimation using graphics processing units.

Science.gov (United States)

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

Flexible polymers in a nematic medium : a Monte Carlo simulation

NARCIS (Netherlands)

Vliet, J.H. van; Luyten, M.C.; Brinke, G. ten

Monte Carlo simulations of self-avoiding random walks surrounded by aligned rods on a square lattice and a simple cubic lattice were performed to address the topological constraints involved for dilute solutions of flexible polymers in a highly oriented nematic solvent. The nematic constraint

Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations

DEFF Research Database (Denmark)

Kamran, Faisal; Andersen, Peter E.

2015-01-01

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

Monte Carlo simulation of a prototype photodetector used in radiotherapy

CERN Document Server

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

2000-01-01

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

Determination of the optical properties of turbid media from a single Monte Carlo simulation

International Nuclear Information System (INIS)

Kienle, A.; Patterson, M.S.

1996-01-01

We describe a fast, accurate method for determination of the optical coefficients of 'semi-infinite' and 'infinite' turbid media. For the particular case of time-resolved reflectance from a biological medium, we show that a single Monte Carlo simulation can be used to fit the data and to derive the absorption and reduced scattering coefficients. Tests with independent Monte Carlo simulations showed that the errors in the deduced absorption and reduced scattering coefficients are smaller than 1% and 2%, respectively. (author)

The use of Monte-Carlo simulation and order statistics for uncertainty analysis of a LBLOCA transient (LOFT-L2-5)

International Nuclear Information System (INIS)

Chojnacki, E.; Benoit, J.P.

2007-01-01

Best estimate computer codes are increasingly used in nuclear industry for the accident management procedures and have been planned to be used for the licensing procedures. Contrary to conservative codes which are supposed to give penalizing results, best estimate codes attempt to calculate accidental transients in a realistic way. It becomes therefore of prime importance, in particular for technical organization as IRSN in charge of safety assessment, to know the uncertainty on the results of such codes. Thus, CSNI has sponsored few years ago (published in 1998) the Uncertainty Methods Study (UMS) program on uncertainty methodologies used for a SBLOCA transient (LSTF-CL-18) and is now supporting the BEMUSE program for a LBLOCA transient (LOFT-L2-5). The large majority of BEMUSE participants (9 out of 10) use uncertainty methodologies based on a probabilistic modelling and all of them use Monte-Carlo simulations to propagate the uncertainties through their computer codes. Also, all of 'probabilistic participants' intend to use order statistics to determine the sampling size of the Monte-Carlo simulation and to derive the uncertainty ranges associated to their computer calculations. The first aim of this paper is to remind the advantages and also the assumptions of the probabilistic modelling and more specifically of order statistics (as Wilks' formula) in uncertainty methodologies. Indeed Monte-Carlo methods provide flexible and extremely powerful techniques for solving many of the uncertainty propagation problems encountered in nuclear safety analysis. However it is important to keep in mind that probabilistic methods are data intensive. That means, probabilistic methods cannot produce robust results unless a considerable body of information has been collected. A main interest of the use of order statistics results is to allow to take into account an unlimited number of uncertain parameters and, from a restricted number of code calculations to provide statistical

Monte Carlo simulation of PET images for injection doseoptimization

Czech Academy of Sciences Publication Activity Database

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

2013-01-01

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

Technical Note: On the efficiency of variance reduction techniques for Monte Carlo estimates of imaging noise.

Science.gov (United States)

Sharma, Diksha; Sempau, Josep; Badano, Aldo

2018-02-01

Monte Carlo simulations require large number of histories to obtain reliable estimates of the quantity of interest and its associated statistical uncertainty. Numerous variance reduction techniques (VRTs) have been employed to increase computational efficiency by reducing the statistical uncertainty. We investigate the effect of two VRTs for optical transport methods on accuracy and computing time for the estimation of variance (noise) in x-ray imaging detectors. We describe two VRTs. In the first, we preferentially alter the direction of the optical photons to increase detection probability. In the second, we follow only a fraction of the total optical photons generated. In both techniques, the statistical weight of photons is altered to maintain the signal mean. We use fastdetect2, an open-source, freely available optical transport routine from the hybridmantis package. We simulate VRTs for a variety of detector models and energy sources. The imaging data from the VRT simulations are then compared to the analog case (no VRT) using pulse height spectra, Swank factor, and the variance of the Swank estimate. We analyze the effect of VRTs on the statistical uncertainty associated with Swank factors. VRTs increased the relative efficiency by as much as a factor of 9. We demonstrate that we can achieve the same variance of the Swank factor with less computing time. With this approach, the simulations can be stopped when the variance of the variance estimates reaches the desired level of uncertainty. We implemented analytic estimates of the variance of Swank factor and demonstrated the effect of VRTs on image quality calculations. Our findings indicate that the Swank factor is dominated by the x-ray interaction profile as compared to the additional uncertainty introduced in the optical transport by the use of VRTs. For simulation experiments that aim at reducing the uncertainty in the Swank factor estimate, any of the proposed VRT can be used for increasing the relative

Monte Carlo simulation of asymmetrical growth of cube-shaped nanoparticles

International Nuclear Information System (INIS)

Wang Yuanyuan; Xie Huaqing; Wu Zihua; Xing Jiaojiao

2016-01-01

We simulated the asymmetrical growth of cube-shaped nanoparticles by applying the Monte Carlo method. The influence of the specific mechanisms on the crystal growth of nanoparticles has been phenomenologically described by efficient growth possibilities along different directions (or crystal faces). The roles of the thermodynamic and kinetic factors have been evaluated in three phenomenological models. The simulation results would benefit the understanding about the cause and manner of the asymmetrical growth of nanoparticles. (paper)

Coarse-grained stochastic processes and kinetic Monte Carlo simulators for the diffusion of interacting particles

Science.gov (United States)

Katsoulakis, Markos A.; Vlachos, Dionisios G.

2003-11-01

We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.

Many-integrated core (MIC) technology for accelerating Monte Carlo simulation of radiation transport: A study based on the code DPM

Science.gov (United States)

Rodriguez, M.; Brualla, L.

2018-04-01

Monte Carlo simulation of radiation transport is computationally demanding to obtain reasonably low statistical uncertainties of the estimated quantities. Therefore, it can benefit in a large extent from high-performance computing. This work is aimed at assessing the performance of the first generation of the many-integrated core architecture (MIC) Xeon Phi coprocessor with respect to that of a CPU consisting of a double 12-core Xeon processor in Monte Carlo simulation of coupled electron-photonshowers. The comparison was made twofold, first, through a suite of basic tests including parallel versions of the random number generators Mersenne Twister and a modified implementation of RANECU. These tests were addressed to establish a baseline comparison between both devices. Secondly, through the p DPM code developed in this work. p DPM is a parallel version of the Dose Planning Method (DPM) program for fast Monte Carlo simulation of radiation transport in voxelized geometries. A variety of techniques addressed to obtain a large scalability on the Xeon Phi were implemented in p DPM. Maximum scalabilities of 84 . 2 × and 107 . 5 × were obtained in the Xeon Phi for simulations of electron and photon beams, respectively. Nevertheless, in none of the tests involving radiation transport the Xeon Phi performed better than the CPU. The disadvantage of the Xeon Phi with respect to the CPU owes to the low performance of the single core of the former. A single core of the Xeon Phi was more than 10 times less efficient than a single core of the CPU for all radiation transport simulations.

Monte Carlo simulation of the scattered component of neutron capture prompt gamma-ray analyzer responses

International Nuclear Information System (INIS)

Jin, Y.; Verghese, K.; Gardner, R.P.

1986-01-01

This paper describes a major part of our efforts to simulate the entire spectral response of the neutron capture prompt gamma-ray analyzer for bulk media (or conveyor belt) samples by the Monte Carlo method. This would allow one to use such a model to augment or, in most cases, essentially replace experiments in the calibration and optimum design of these analyzers. In previous work, we simulated the unscattered gamma-ray intensities, but would like to simulate the entire spectral response as we did with the energy-dispersive x-ray fluorescence analyzers. To accomplish this, one must account for the scattered gamma rays as well as the unscattered and one must have available the detector response function to translate the incident gamma-ray spectrum calculated by the Monte Carlo simulation into the detected pulse-height spectrum. We recently completed our work on the germanium detector response function, and the present paper describes our efforts to simulate the entire spectral response by using it with Monte Carlo predicted unscattered and scattered gamma rays

Monte Carlo Simulation Tool Installation and Operation Guide

Energy Technology Data Exchange (ETDEWEB)

Aguayo Navarrete, Estanislao; Ankney, Austin S.; Berguson, Timothy J.; Kouzes, Richard T.; Orrell, John L.; Troy, Meredith D.; Wiseman, Clinton G.

2013-09-02

This document provides information on software and procedures for Monte Carlo simulations based on the Geant4 toolkit, the ROOT data analysis software and the CRY cosmic ray library. These tools have been chosen for its application to shield design and activation studies as part of the simulation task for the Majorana Collaboration. This document includes instructions for installation, operation and modification of the simulation code in a high cyber-security computing environment, such as the Pacific Northwest National Laboratory network. It is intended as a living document, and will be periodically updated. It is a starting point for information collection by an experimenter, and is not the definitive source. Users should consult with one of the authors for guidance on how to find the most current information for their needs.

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Pseudo-random number generators for Monte Carlo simulations on ATI Graphics Processing Units

Science.gov (United States)

Demchik, Vadim

2011-03-01

Basic uniform pseudo-random number generators are implemented on ATI Graphics Processing Units (GPU). The performance results of the realized generators (multiplicative linear congruential (GGL), XOR-shift (XOR128), RANECU, RANMAR, RANLUX and Mersenne Twister (MT19937)) on CPU and GPU are discussed. The obtained speed up factor is hundreds of times in comparison with CPU. RANLUX generator is found to be the most appropriate for using on GPU in Monte Carlo simulations. The brief review of the pseudo-random number generators used in modern software packages for Monte Carlo simulations in high-energy physics is presented.

Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation

Energy Technology Data Exchange (ETDEWEB)

Nilmeier, J. P.; Crooks, G. E.; Minh, D. D. L.; Chodera, J. D.

2011-10-24

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Here, we introduce a new class of moves based on nonequilibrium dynamics: candidate configurations are generated through a finite-time process in which a system is actively driven out of equilibrium, and accepted with criteria that preserve the equilibrium distribution. The acceptance rule is similar to the Metropolis acceptance probability, but related to the nonequilibrium work rather than the instantaneous energy difference. Our method is applicable to sampling from both a single thermodynamic state or a mixture of thermodynamic states, and allows both coordinates and thermodynamic parameters to be driven in nonequilibrium proposals. While generating finite-time switching trajectories incurs an additional cost, driving some degrees of freedom while allowing others to evolve naturally can lead to large enhancements in acceptance probabilities, greatly reducing structural correlation times. Using nonequilibrium driven processes vastly expands the repertoire of useful Monte Carlo proposals in simulations of dense solvated systems.

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)

The Cherenkov Telescope Array production system for Monte Carlo simulations and analysis

Science.gov (United States)

Arrabito, L.; Bernloehr, K.; Bregeon, J.; Cumani, P.; Hassan, T.; Haupt, A.; Maier, G.; Moralejo, A.; Neyroud, N.; pre="for the"> CTA Consortium, DIRAC Consortium,

2017-10-01

The Cherenkov Telescope Array (CTA), an array of many tens of Imaging Atmospheric Cherenkov Telescopes deployed on an unprecedented scale, is the next-generation instrument in the field of very high energy gamma-ray astronomy. An average data stream of about 0.9 GB/s for about 1300 hours of observation per year is expected, therefore resulting in 4 PB of raw data per year and a total of 27 PB/year, including archive and data processing. The start of CTA operation is foreseen in 2018 and it will last about 30 years. The installation of the first telescopes in the two selected locations (Paranal, Chile and La Palma, Spain) will start in 2017. In order to select the best site candidate to host CTA telescopes (in the Northern and in the Southern hemispheres), massive Monte Carlo simulations have been performed since 2012. Once the two sites have been selected, we have started new Monte Carlo simulations to determine the optimal array layout with respect to the obtained sensitivity. Taking into account that CTA may be finally composed of 7 different telescope types coming in 3 different sizes, many different combinations of telescope position and multiplicity as a function of the telescope type have been proposed. This last Monte Carlo campaign represented a huge computational effort, since several hundreds of telescope positions have been simulated, while for future instrument response function simulations, only the operating telescopes will be considered. In particular, during the last 18 months, about 2 PB of Monte Carlo data have been produced and processed with different analysis chains, with a corresponding overall CPU consumption of about 125 M HS06 hours. In these proceedings, we describe the employed computing model, based on the use of grid resources, as well as the production system setup, which relies on the DIRAC interware. Finally, we present the envisaged evolutions of the CTA production system for the off-line data processing during CTA operations and

Chain segmentation for the Monte Carlo solution of particle transport problems

International Nuclear Information System (INIS)

Ragheb, M.M.H.

1984-01-01

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

Coupling photon Monte Carlo simulation and CAD software. Application to X-ray nondestructive evaluation

International Nuclear Information System (INIS)

Tabary, J.; Gliere, A.

2001-01-01

A Monte Carlo radiation transport simulation program, EGS Nova, and a computer aided design software, BRL-CAD, have been coupled within the framework of Sindbad, a nondestructive evaluation (NDE) simulation system. In its current status, the program is very valuable in a NDE laboratory context, as it helps simulate the images due to the uncollided and scattered photon fluxes in a single NDE software environment, without having to switch to a Monte Carlo code parameters set. Numerical validations show a good agreement with EGS4 computed and published data. As the program's major drawback is the execution time, computational efficiency improvements are foreseen. (orig.)

Study of the replacement correction factors for ionization chamber dosimetry by Monte Carlo simulations

Science.gov (United States)

Wang, Lilie

In ionization chamber radiation dosimetry, the introduction of the ion chamber into medium will unavoidably distort the radiation field near the chamber because the chamber cavity material (air) is different from the medium. A replacement correction factor, Prepl was introduced in order to correct the chamber readings to give an accurate radiation dose in the medium without the presence of the chamber. Generally it is very hard to measure the values of Prepl since they are intertwined with the chamber wall effect. In addition, the P repl values always come together with the stopping-power ratio of the two media involved. This makes the problem of determining the P repl values even more complicated. Monte Carlo simulation is an ideal method to investigate the replacement correction factors. In this study, four different methods of calculating the values of Prepl by Monte Carlo simulation are discussed. Two of the methods are designated as 'direct' methods in the sense that the evaluation of the stopping-power ratio is not necessary. The systematic uncertainties of the two direct methods are estimated to be about 0.1-0.2% which comes from the ambiguous definition of the energy cutoff Delta used in the Spencer-Attix cavity theory. The two direct methods are used to calculate the values of P repl for both plane-parallel chambers and cylindrical thimble chambers in either electron beams or photon beams. The calculation results are compared to measurements. For electron beams, good agreements are obtained. For thimble chambers in photon beams, significant discrepancies are observed between calculations and measurements. The experiments are thus investigated and the procedures are simulated by the Monte Carlo method. It is found that the interpretation of the measured data as the replacement correction factors in dosimetry protocols are not correct. In applying the calculation to the BIPM graphite chamber in a 60Co beam, the calculated values of P repl differ from those

Comparison of film dosimetry and Monte Carlo simulations in small field IMRT

Energy Technology Data Exchange (ETDEWEB)

Kim, S.R.; Suh, T.S.; Choe, B.Y.; Lee, H.K. [The Catholic Univ., Seoul (Korea, Republic of); Sohn. Jason W. [Washington Univ., St. Louis (United States)

2002-07-01

Intensity modulated radiation therapy(IMRT) is a recent useful technique that conforms a high dose to the target volume while restricting dose to the surrounding critical organs. In IMRT, the small size beam let is used for intensity modulation. Thus, dose calculation in small field is very important. But, dose calculation in small field is not accurate in recent RTP system because electronic disequilibrium and the effect of multiple scattering electron are not considered in dose calculation. and therefore, We have evaluated the errors of depth dose and beam profile between measurement data and Monte Carlo simulation. With a homogeneous phantom and two heterogeneous phantoms, A thermoluminescent dosimeter (TLD) and radiochromic films have been selected for dose measurement in 6 MV photon beams. A linear accelerator Varian 2300C (Varian Medical Systems, USA) equipped with a multileaf collimator have been used in dose measurement. The results of simulations using the Monte Carlo systems BEAM/EGS4 (NRC, Canada) to model the beam geometry have been compared with dose measurements. Generally good agreements were found between measurements and dose calculations of Monte Carlo simulation. But some discrepancies were found in this study. Thus further study will be needed to compensate these errors.

Clinical treatment planning for stereotactic radiotherapy, evaluation by Monte Carlo simulation

International Nuclear Information System (INIS)

Kairn, T.; Aland, T.; Kenny, J.; Knight, R.T.; Crowe, S.B.; Langton, C.M.; Franich, R.D.; Johnston, P.N.

2010-01-01

Full text: This study uses re-evaluates the doses delivered by a series of clinical stereotactic radiotherapy treatments, to test the accuracy of treatment planning predictions for very small radiation fields. Stereotactic radiotherapy treatment plans for meningiomas near the petrous temporal bone and the foramen magnum (incorp rating fields smaller than I c m2) were examined using Monte Carlo simulations. Important differences between treatment planning predictions and Monte Carlo calculations of doses delivered to stereotactic radiotherapy patients are apparent. For example, in one case the Monte Carlo calculation shows that the delivery a planned meningioma treatment would spare the patient's critical structures (eyes, brainstem) more effectively than the treatment plan predicted, and therefore suggests that this patient could safely receive an increased dose to their tumour. Monte Carlo simulations can be used to test the dose predictions made by a conventional treatment planning system, for dosimetrically challenging small fields, and can thereby suggest valuable modifications to clinical treatment plans. This research was funded by the Wesley Research Institute, Australia. The authors wish to thank Andrew Fielding and David Schlect for valuable discussions of aspects of this work. The authors are also grateful to Muhammad Kakakhel, for assisting with the design and calibration of our linear accelerator model, and to the stereotactic radiation therapy team at Premion, who designed the treatment plans. Computational resources and services used in this work were provided by the HPC and Research Support Unit, QUT, Brisbane, Australia. (author)

Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting

Energy Technology Data Exchange (ETDEWEB)

Bootsma, G. J., E-mail: Gregory.Bootsma@rmp.uhn.on.ca [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada); Verhaegen, F. [Department of Radiation Oncology - MAASTRO, GROW—School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht 6201 BN (Netherlands); Medical Physics Unit, Department of Oncology, McGill University, Montreal, Quebec H3G 1A4 (Canada); Jaffray, D. A. [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada); Ontario Cancer Institute, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5G 2M9 (Canada)

2015-01-15

Purpose: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). Methods: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithm which computes the scatter detector response, S{sub MC}. S{sub MC} is fit to a function, S{sub F}, and if the fit of S{sub F} is within a specified goodness of fit (GOF), the simulations are terminated. The fit, S{sub F}, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. Results: Pearson’s correlation, r, proved to be a

Monte Carlo simulation of lower hybrid current drive in tokamaks

International Nuclear Information System (INIS)

Sipilae, S.K.; Heikkinen, J.A.

1994-01-01

In the report a method for noninductive current drive studies based on three-dimensional simulation of test particle orbits is presented. A Monte Carlo momentum diffusion operator is developed to model the wave-particle interaction. The scheme can be utilised in studies of current drive efficiency as well as in examining the current density profiles caused by waves with a finite parallel wave number spectrum and a nonuniform power deposition profile in a toroidal configuration space of arbitrary shape. Calculations performed with a uniform poorer deposition profile of lower hybrid waves for axisymmetric magnetic configurations having different aspect ratios and poloidal cross-section shape confirm the semianalytic estimates for the current drive efficiency based on the solutions of the flux surface averaged Fokker-Planck equation for configurations with circular poloidal cross section. The consequences of the combined effect of radial diffusion, magnetic trapping and radially nonhomogeneous power deposition and background plasma parameter profiles are investigated

Molecular Dynamics and Monte Carlo simulations resolve apparent diffusion rate differences for proteins confined in nanochannels

Energy Technology Data Exchange (ETDEWEB)

Tringe, J.W., E-mail: tringe2@llnl.gov [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Ileri, N. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Levie, H.W. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Stroeve, P.; Ustach, V.; Faller, R. [Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Renaud, P. [Swiss Federal Institute of Technology, Lausanne, (EPFL) (Switzerland)

2015-08-18

Highlights: • WGA proteins in nanochannels modeled by Molecular Dynamics and Monte Carlo. • Protein surface coverage characterized by atomic force microscopy. • Models indicate transport characteristics depend strongly on surface coverage. • Results resolve of a four orders of magnitude difference in diffusion coefficient values. - Abstract: We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage. Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.

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

Energy Technology Data Exchange (ETDEWEB)

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

2002-06-21

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

Neutron shielding calculations in a proton therapy facility based on Monte Carlo simulations and analytical models: Criterion for selecting the method of choice

International Nuclear Information System (INIS)

Titt, U.; Newhauser, W. D.

2005-01-01

Proton therapy facilities are shielded to limit the amount of secondary radiation to which patients, occupational workers and members of the general public are exposed. The most commonly applied shielding design methods for proton therapy facilities comprise semi-empirical and analytical methods to estimate the neutron dose equivalent. This study compares the results of these methods with a detailed simulation of a proton therapy facility by using the Monte Carlo technique. A comparison of neutron dose equivalent values predicted by the various methods reveals the superior accuracy of the Monte Carlo predictions in locations where the calculations converge. However, the reliability of the overall shielding design increases if simulation results, for which solutions have not converged, e.g. owing to too few particle histories, can be excluded, and deterministic models are being used at these locations. Criteria to accept or reject Monte Carlo calculations in such complex structures are not well understood. An optimum rejection criterion would allow all converging solutions of Monte Carlo simulation to be taken into account, and reject all solutions with uncertainties larger than the design safety margins. In this study, the optimum rejection criterion of 10% was found. The mean ratio was 26, 62% of all receptor locations showed a ratio between 0.9 and 10, and 92% were between 1 and 100. (authors)

Kinetic Monte Carlo simulations of the effect of the exchange control layer thickness in CoPtCrB/CoPtCrSiO granular media

Science.gov (United States)

Almudallal, Ahmad M.; Mercer, J. I.; Whitehead, J. P.; Plumer, M. L.; van Ek, J.

2018-05-01

A hybrid Landau Lifshitz Gilbert/kinetic Monte Carlo algorithm is used to simulate experimental magnetic hysteresis loops for dual layer exchange coupled composite media. The calculation of the rate coefficients and difficulties arising from low energy barriers, a fundamental problem of the kinetic Monte Carlo method, are discussed and the methodology used to treat them in the present work is described. The results from simulations are compared with experimental vibrating sample magnetometer measurements on dual layer CoPtCrB/CoPtCrSiO media and a quantitative relationship between the thickness of the exchange control layer separating the layers and the effective exchange constant between the layers is obtained. Estimates of the energy barriers separating magnetically reversed states of the individual grains in zero applied field as well as the saturation field at sweep rates relevant to the bit write speeds in magnetic recording are also presented. The significance of this comparison between simulations and experiment and the estimates of the material parameters obtained from it are discussed in relation to optimizing the performance of magnetic storage media.

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

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

2010-01-01

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

Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics

Science.gov (United States)

Good, Brian

2013-01-01

Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.

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

Reliability Assessment of Active Distribution System Using Monte Carlo Simulation Method

Directory of Open Access Journals (Sweden)

Shaoyun Ge

2014-01-01

Full Text Available In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

Science.gov (United States)

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

2014-12-01

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

EGS4, Electron Photon Shower Simulation by Monte-Carlo

International Nuclear Information System (INIS)

1998-01-01

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

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

Science.gov (United States)

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

2011-10-11

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

Massive Parallelism of Monte-Carlo Simulation on Low-End Hardware using Graphic Processing Units

International Nuclear Information System (INIS)

Mburu, Joe Mwangi; Hah, Chang Joo Hah

2014-01-01

Within the past decade, research has been done on utilizing GPU massive parallelization in core simulation with impressive results but unfortunately, not much commercial application has been done in the nuclear field especially in reactor core simulation. The purpose of this paper is to give an introductory concept on the topic and illustrate the potential of exploiting the massive parallel nature of GPU computing on a simple monte-carlo simulation with very minimal hardware specifications. To do a comparative analysis, a simple two dimension monte-carlo simulation is implemented for both the CPU and GPU in order to evaluate performance gain based on the computing devices. The heterogeneous platform utilized in this analysis is done on a slow notebook with only 1GHz processor. The end results are quite surprising whereby high speedups obtained are almost a factor of 10. In this work, we have utilized heterogeneous computing in a GPU-based approach in applying potential high arithmetic intensive calculation. By applying a complex monte-carlo simulation on GPU platform, we have speed up the computational process by almost a factor of 10 based on one million neutrons. This shows how easy, cheap and efficient it is in using GPU in accelerating scientific computing and the results should encourage in exploring further this avenue especially in nuclear reactor physics simulation where deterministic and stochastic calculations are quite favourable in parallelization

Massive Parallelism of Monte-Carlo Simulation on Low-End Hardware using Graphic Processing Units

Energy Technology Data Exchange (ETDEWEB)

Mburu, Joe Mwangi; Hah, Chang Joo Hah [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2014-05-15

Within the past decade, research has been done on utilizing GPU massive parallelization in core simulation with impressive results but unfortunately, not much commercial application has been done in the nuclear field especially in reactor core simulation. The purpose of this paper is to give an introductory concept on the topic and illustrate the potential of exploiting the massive parallel nature of GPU computing on a simple monte-carlo simulation with very minimal hardware specifications. To do a comparative analysis, a simple two dimension monte-carlo simulation is implemented for both the CPU and GPU in order to evaluate performance gain based on the computing devices. The heterogeneous platform utilized in this analysis is done on a slow notebook with only 1GHz processor. The end results are quite surprising whereby high speedups obtained are almost a factor of 10. In this work, we have utilized heterogeneous computing in a GPU-based approach in applying potential high arithmetic intensive calculation. By applying a complex monte-carlo simulation on GPU platform, we have speed up the computational process by almost a factor of 10 based on one million neutrons. This shows how easy, cheap and efficient it is in using GPU in accelerating scientific computing and the results should encourage in exploring further this avenue especially in nuclear reactor physics simulation where deterministic and stochastic calculations are quite favourable in parallelization.

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.

A review: Functional near infrared spectroscopy evaluation in muscle tissues using Monte Carlo simulation

Science.gov (United States)

Halim, A. A. A.; Laili, M. H.; Salikin, M. S.; Rusop, M.

2018-05-01

Monte Carlo Simulation has advanced their quantification based on number of the photon counting to solve the propagation of light inside the tissues including the absorption, scattering coefficient and act as preliminary study for functional near infrared application. The goal of this paper is to identify the optical properties using Monte Carlo simulation for non-invasive functional near infrared spectroscopy (fNIRS) evaluation of penetration depth in human muscle. This paper will describe the NIRS principle and the basis for its proposed used in Monte Carlo simulation which focused on several important parameters include ATP, ADP and relate with blow flow and oxygen content at certain exercise intensity. This will cover the advantages and limitation of such application upon this simulation. This result may help us to prove that our human muscle is transparent to this near infrared region and could deliver a lot of information regarding to the oxygenation level in human muscle. Thus, this might be useful for non-invasive technique for detecting oxygen status in muscle from living people either athletes or working people and allowing a lots of investigation muscle physiology in future.

Monte Carlo simulations of lattice models for single polymer systems

Science.gov (United States)

Hsu, Hsiao-Ping

2014-10-01

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

Monte Carlo simulations of lattice models for single polymer systems

International Nuclear Information System (INIS)

Hsu, Hsiao-Ping

2014-01-01

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

Resistance scaling function for two-dimensional superconductors and Monte Carlo vortex-fluctuation simulations

International Nuclear Information System (INIS)

Minnhagen, P.; Weber, H.

1985-01-01

A Monte Carlo simulation of the Ginsburg-Landau Coulomb-gas model for vortex fluctuations is described and compared to the measured resistance scaling function for two-dimensional superconductors. This constitutes a new, more direct way of confirming the vortex-fluctuation explanation for the resistive tail of high-sheet-resistance superconducting films. The Monte Carlo data obtained indicate a striking accordance between theory and experiments

Monte-Carlo simulation of defect-cluster nucleation in metals during irradiation

International Nuclear Information System (INIS)

Nakasuji, Toshiki; Morishita, Kazunori; Ruan, Xiaoyong

2017-01-01

Highlights: • Monte-Carlo simulations were performed to investigate the nucleation process of copper-vacancy clusters in Fe. • Nucleation paths were obtained as a function of temperature and the damage rate. - Abstract: A multiscale modeling approach was applied to investigate the nucleation process of CRPs (copper rich precipitates, i.e., copper-vacancy clusters) in α-Fe containing 1 at.% Cu during irradiation. Monte-Carlo simulations were performed to investigate the nucleation process, with the rate theory equation analysis to evaluate the concentration of displacement defects, along with the molecular dynamics technique to know CRP thermal stabilities in advance. Our MC simulations showed that there is long incubation period at first, followed by a rapid growth of CRPs. The incubation period depends on irradiation conditions such as the damage rate and temperature. CRP’s composition during nucleation varies with time. The copper content of CRPs shows relatively rich at first, and then becomes poorer as the precipitate size increases. A widely-accepted model of CRP nucleation process is finally proposed.

Monte-Carlo simulation of defect-cluster nucleation in metals during irradiation

Energy Technology Data Exchange (ETDEWEB)

Nakasuji, Toshiki, E-mail: t-nakasuji@iae.kyoto-u.ac.jp [Graduate School of Energy Science, Kyoto University, Uji, Kyoto 611-0011 (Japan); Morishita, Kazunori [Institute of Advanced Energy, Kyoto University, Uji, Kyoto 611-0011 (Japan); Ruan, Xiaoyong [Graduate School of Energy Science, Kyoto University, Uji, Kyoto 611-0011 (Japan)

2017-02-15

Highlights: • Monte-Carlo simulations were performed to investigate the nucleation process of copper-vacancy clusters in Fe. • Nucleation paths were obtained as a function of temperature and the damage rate. - Abstract: A multiscale modeling approach was applied to investigate the nucleation process of CRPs (copper rich precipitates, i.e., copper-vacancy clusters) in α-Fe containing 1 at.% Cu during irradiation. Monte-Carlo simulations were performed to investigate the nucleation process, with the rate theory equation analysis to evaluate the concentration of displacement defects, along with the molecular dynamics technique to know CRP thermal stabilities in advance. Our MC simulations showed that there is long incubation period at first, followed by a rapid growth of CRPs. The incubation period depends on irradiation conditions such as the damage rate and temperature. CRP’s composition during nucleation varies with time. The copper content of CRPs shows relatively rich at first, and then becomes poorer as the precipitate size increases. A widely-accepted model of CRP nucleation process is finally proposed.

A Pipelined and Parallel Architecture for Quantum Monte Carlo Simulations on FPGAs

Directory of Open Access Journals (Sweden)

Akila Gothandaraman

2010-01-01

Full Text Available Recent advances in Field-Programmable Gate Array (FPGA technology make reconfigurable computing using FPGAs an attractive platform for accelerating scientific applications. We develop a deeply pipelined and parallel architecture for Quantum Monte Carlo simulations using FPGAs. Quantum Monte Carlo simulations enable us to obtain the structural and energetic properties of atomic clusters. We experiment with different pipeline structures for each component of the design and develop a deeply pipelined architecture that provides the best performance in terms of achievable clock rate, while at the same time has a modest use of the FPGA resources. We discuss the details of the pipelined and generic architecture that is used to obtain the potential energy and wave function of a cluster of atoms.

Asteroid mass estimation using Markov-chain Monte Carlo

Science.gov (United States)

Siltala, Lauri; Granvik, Mikael

2017-11-01

Estimates for asteroid masses are based on their gravitational perturbations on the orbits of other objects such as Mars, spacecraft, or other asteroids and/or their satellites. In the case of asteroid-asteroid perturbations, this leads to an inverse problem in at least 13 dimensions where the aim is to derive the mass of the perturbing asteroid(s) and six orbital elements for both the perturbing asteroid(s) and the test asteroid(s) based on astrometric observations. We have developed and implemented three different mass estimation algorithms utilizing asteroid-asteroid perturbations: the very rough 'marching' approximation, in which the asteroids' orbital elements are not fitted, thereby reducing the problem to a one-dimensional estimation of the mass, an implementation of the Nelder-Mead simplex method, and most significantly, a Markov-chain Monte Carlo (MCMC) approach. We describe each of these algorithms with particular focus on the MCMC algorithm, and present example results using both synthetic and real data. Our results agree with the published mass estimates, but suggest that the published uncertainties may be misleading as a consequence of using linearized mass-estimation methods. Finally, we discuss remaining challenges with the algorithms as well as future plans.

Validation of a Monte Carlo model used for simulating tube current modulation in computed tomography over a wide range of phantom conditions/challenges

Energy Technology Data Exchange (ETDEWEB)

Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Cagnon, Chris H.; McNitt-Gray, Michael F. [Departments of Biomedical Physics and Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024 (United States); DeMarco, John J. [Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California 90095 (United States)

2014-11-01

Purpose: Monte Carlo (MC) simulation methods have been widely used in patient dosimetry in computed tomography (CT), including estimating patient organ doses. However, most simulation methods have undergone a limited set of validations, often using homogeneous phantoms with simple geometries. As clinical scanning has become more complex and the use of tube current modulation (TCM) has become pervasive in the clinic, MC simulations should include these techniques in their methodologies and therefore should also be validated using a variety of phantoms with different shapes and material compositions to result in a variety of differently modulated tube current profiles. The purpose of this work is to perform the measurements and simulations to validate a Monte Carlo model under a variety of test conditions where fixed tube current (FTC) and TCM were used. Methods: A previously developed MC model for estimating dose from CT scans that models TCM, built using the platform of MCNPX, was used for CT dose quantification. In order to validate the suitability of this model to accurately simulate patient dose from FTC and TCM CT scan, measurements and simulations were compared over a wide range of conditions. Phantoms used for testing range from simple geometries with homogeneous composition (16 and 32 cm computed tomography dose index phantoms) to more complex phantoms including a rectangular homogeneous water equivalent phantom, an elliptical shaped phantom with three sections (where each section was a homogeneous, but different material), and a heterogeneous, complex geometry anthropomorphic phantom. Each phantom requires varying levels of x-, y- and z-modulation. Each phantom was scanned on a multidetector row CT (Sensation 64) scanner under the conditions of both FTC and TCM. Dose measurements were made at various surface and depth positions within each phantom. Simulations using each phantom were performed for FTC, detailed x–y–z TCM, and z-axis-only TCM to obtain

Monte Carlo simulation: tool for the calibration in analytical determination of radionuclides; Simulacion Monte Carlo: herramienta para la calibracion en determinaciones analiticas de radionucleidos

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, Jorge A. Carrazana; Ferrera, Eduardo A. Capote; Gomez, Isis M. Fernandez; Castro, Gloria V. Rodriguez; Ricardo, Niury Martinez, E-mail: cphr@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones (CPHR), La Habana (Cuba)

2013-07-01

This work shows how is established the traceability of the analytical determinations using this calibration method. Highlights the advantages offered by Monte Carlo simulation for the application of corrections by differences in chemical composition, density and height of the samples analyzed. Likewise, the results obtained by the LVRA in two exercises organized by the International Agency for Atomic Energy (IAEA) are presented. In these exercises (an intercomparison and a proficiency test) all reported analytical results were obtained based on calibrations in efficiency by Monte Carlo simulation using the DETEFF program.

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.

Parallel Monte Carlo simulation of aerosol dynamics

KAUST Repository

Zhou, K.

2014-01-01

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

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

CERN Document Server

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

2001-01-01

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

Comparative Performance of Four Single Extreme Outlier Discordancy Tests from Monte Carlo Simulations

Directory of Open Access Journals (Sweden)

Surendra P. Verma

2014-01-01

Full Text Available Using highly precise and accurate Monte Carlo simulations of 20,000,000 replications and 102 independent simulation experiments with extremely low simulation errors and total uncertainties, we evaluated the performance of four single outlier discordancy tests (Grubbs test N2, Dixon test N8, skewness test N14, and kurtosis test N15 for normal samples of sizes 5 to 20. Statistical contaminations of a single observation resulting from parameters called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or ε from ±1.1 up to ±200 for slippage of dispersion, as well as no contamination (δ=0 and ε=±1, were simulated. Because of the use of precise and accurate random and normally distributed simulated data, very large replications, and a large number of independent experiments, this paper presents a novel approach for precise and accurate estimations of power functions of four popular discordancy tests and, therefore, should not be considered as a simple simulation exercise unrelated to probability and statistics. From both criteria of the Power of Test proposed by Hayes and Kinsella and the Test Performance Criterion of Barnett and Lewis, Dixon test N8 performs less well than the other three tests. The overall performance of these four tests could be summarized as N2≅N15>N14>N8.

Numerical integration of the Langevin equation: Monte Carlo simulation

International Nuclear Information System (INIS)

Ermak, D.L.; Buckholz, H.

1980-01-01

Monte Carlo simulation techniques are derived for solving the ordinary Langevin equation of motion for a Brownian particle in the presence of an external force. These methods allow considerable freedom in selecting the size of the time step, which is restricted only by the rate of change in the external force. This approach is extended to the generalized Langevin equation which uses a memory function in the friction force term. General simulation techniques are derived which are independent of the form of the memory function. A special method requiring less storage space is presented for the case of the exponential memory function

Post-processing of Monte Carlo simulations for rapid BNCT source optimization studies

International Nuclear Information System (INIS)

Bleuel, D.L.; Chu, W.T.; Donahue, R.J.; Ludewigt, B.A.; Vujic, J.

2000-01-01

A great advantage of some neutron sources, such as accelerator-produced sources, is that they can be tuned to produce different spectra. Unfortunately, optimization studies are often time-consuming and difficult, as they require a lengthy Monte Carlo simulation for each source. When multiple characteristics, such as energy, angle, and spatial distribution of a neutron beam are allowed to vary, an overwhelming number of simulations may be required. Many optimization studies, therefore, suffer from a small number of datapoints, restrictive treatment conditions, or poor statistics. By scoring pertinent information from every particle tally in a Monte Carlo simulation, then applying appropriate source variable weight factors in a post-processing algorithm, a single simulation can be used to model any number of multiple sources. Through this method, the response to a new source can be modeled in minutes or seconds, rather than hours or days, allowing for the analysis of truly variable source conditions of much greater resolution than is normally possible when a new simulation must be run for each datapoint in a study. This method has been benchmarked and used to recreate optimization studies in a small fraction of the time spent in the original studies

Toward a Monte Carlo program for simulating vapor-liquid phase equilibria from first principles

Energy Technology Data Exchange (ETDEWEB)

McGrath, M; Siepmann, J I; Kuo, I W; Mundy, C J; Vandevondele, J; Sprik, M; Hutter, J; Mohamed, F; Krack, M; Parrinello, M

2004-10-20

Efficient Monte Carlo algorithms are combined with the Quickstep energy routines of CP2K to develop a program that allows for Monte Carlo simulations in the canonical, isobaric-isothermal, and Gibbs ensembles using a first principles description of the physical system. Configurational-bias Monte Carlo techniques and pre-biasing using an inexpensive approximate potential are employed to increase the sampling efficiency and to reduce the frequency of expensive ab initio energy evaluations. The new Monte Carlo program has been validated through extensive comparison with molecular dynamics simulations using the programs CPMD and CP2K. Preliminary results for the vapor-liquid coexistence properties (T = 473 K) of water using the Becke-Lee-Yang-Parr exchange and correlation energy functionals, a triple-zeta valence basis set augmented with two sets of d-type or p-type polarization functions, and Goedecker-Teter-Hutter pseudopotentials are presented. The preliminary results indicate that this description of water leads to an underestimation of the saturated liquid density and heat of vaporization and, correspondingly, an overestimation of the saturated vapor pressure.

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

International Nuclear Information System (INIS)

Diamantis, Nikolaos G.; Manousakis, Efstratios

2016-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

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

Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations.

Science.gov (United States)

Núñez, M; Vlachos, D G

2015-01-28

Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

Fast Monte Carlo-simulator with full collimator and detector response modelling for SPECT

International Nuclear Information System (INIS)

Sohlberg, A.O.; Kajaste, M.T.

2012-01-01

Monte Carlo (MC)-simulations have proved to be a valuable tool in studying single photon emission computed tomography (SPECT)-reconstruction algorithms. Despite their popularity, the use of Monte Carlo-simulations is still often limited by their large computation demand. This is especially true in situations where full collimator and detector modelling with septal penetration, scatter and X-ray fluorescence needs to be included. This paper presents a rapid and simple MC-simulator, which can effectively reduce the computation times. The simulator was built on the convolution-based forced detection principle, which can markedly lower the number of simulated photons. Full collimator and detector response look-up tables are pre-simulated and then later used in the actual MC-simulations to model the system response. The developed simulator was validated by comparing it against 123 I point source measurements made with a clinical gamma camera system and against 99m Tc software phantom simulations made with the SIMIND MC-package. The results showed good agreement between the new simulator, measurements and the SIMIND-package. The new simulator provided near noise-free projection data in approximately 1.5 min per projection with 99m Tc, which was less than one-tenth of SIMIND's time. The developed MC-simulator can markedly decrease the simulation time without sacrificing image quality. (author)

Computer simulation of stochastic processes through model-sampling (Monte Carlo) techniques.

Science.gov (United States)

Sheppard, C W.

1969-03-01

A simple Monte Carlo simulation program is outlined which can be used for the investigation of random-walk problems, for example in diffusion, or the movement of tracers in the blood circulation. The results given by the simulation are compared with those predicted by well-established theory, and it is shown how the model can be expanded to deal with drift, and with reflexion from or adsorption at a boundary.

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

Energy Technology Data Exchange (ETDEWEB)

Sharma, D; Badano, A [Division of Imaging, Diagnostics and Software Reliability, OSEL/CDRH, Food & Drug Administration, MD (United States); Sempau, J [Technical University of Catalonia, Barcelona (Spain)

2016-06-15

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

Science.gov (United States)

Croce, Pierpaolo; Zappasodi, Filippo; Merla, Arcangelo; Chiarelli, Antonio Maria

2017-08-01

Objective. Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown. Approach. Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF). Main results. We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements. Significance. The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

Exploring uncertainty in glacier mass balance modelling with Monte Carlo simulation