Monte Carlo radiation transport: A revolution in science

International Nuclear Information System (INIS)

Hendricks, J.

1993-01-01

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

Importance estimation in Monte Carlo modelling of neutron and photon transport

International Nuclear Information System (INIS)

Mickael, M.W.

1992-01-01

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

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...

A Monte Carlo reflectance model for soil surfaces with three-dimensional structure

Science.gov (United States)

Cooper, K. D.; Smith, J. A.

1985-01-01

A Monte Carlo soil reflectance model has been developed to study the effect of macroscopic surface irregularities larger than the wavelength of incident flux. The model treats incoherent multiple scattering from Lambertian facets distributed on a periodic surface. Resulting bidirectional reflectance distribution functions are non-Lambertian and compare well with experimental trends reported in the literature. Examples showing the coupling of the Monte Carlo soil model to an adding bidirectional canopy of reflectance model are also given.

Modelling of electron contamination in clinical photon beams for Monte Carlo dose calculation

International Nuclear Information System (INIS)

Yang, J; Li, J S; Qin, L; Xiong, W; Ma, C-M

2004-01-01

The purpose of this work is to model electron contamination in clinical photon beams and to commission the source model using measured data for Monte Carlo treatment planning. In this work, a planar source is used to represent the contaminant electrons at a plane above the upper jaws. The source size depends on the dimensions of the field size at the isocentre. The energy spectra of the contaminant electrons are predetermined using Monte Carlo simulations for photon beams from different clinical accelerators. A 'random creep' method is employed to derive the weight of the electron contamination source by matching Monte Carlo calculated monoenergetic photon and electron percent depth-dose (PDD) curves with measured PDD curves. We have integrated this electron contamination source into a previously developed multiple source model and validated the model for photon beams from Siemens PRIMUS accelerators. The EGS4 based Monte Carlo user code BEAM and MCSIM were used for linac head simulation and dose calculation. The Monte Carlo calculated dose distributions were compared with measured data. Our results showed good agreement (less than 2% or 2 mm) for 6, 10 and 18 MV photon beams

Monte Carlo modeling of a High-Sensitivity MOSFET dosimeter for low- and medium-energy photon sources

International Nuclear Information System (INIS)

Wang, Brian; Kim, C.-H.; Xu, X. George

2004-01-01

Metal-oxide-semiconductor field effect transistor (MOSFET) dosimeters are increasingly utilized in radiation therapy and diagnostic radiology. While it is difficult to characterize the dosimeter responses for monoenergetic sources by experiments, this paper reports a detailed Monte Carlo simulation model of the High-Sensitivity MOSFET dosimeter using Monte Carlo N-Particle (MCNP) 4C. A dose estimator method was used to calculate the dose in the extremely thin sensitive volume. Efforts were made to validate the MCNP model using three experiments: (1) comparison of the simulated dose with the measurement of a Cs-137 source, (2) comparison of the simulated dose with analytical values, and (3) comparison of the simulated energy dependence with theoretical values. Our simulation results show that the MOSFET dosimeter has a maximum response at about 40 keV of photon energy. The energy dependence curve is also found to agree with the predicted value from theory within statistical uncertainties. The angular dependence study shows that the MOSFET dosimeter has a higher response (about 8%) when photons come from the epoxy side, compared with the kapton side for the Cs-137 source

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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.

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

Science.gov (United States)

Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.

2016-02-01

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn's Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

International Nuclear Information System (INIS)

Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.

2016-01-01

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

Energy Technology Data Exchange (ETDEWEB)

Pfeiffer, M., E-mail: mpfeiffer@irs.uni-stuttgart.de; Nizenkov, P., E-mail: nizenkov@irs.uni-stuttgart.de; Mirza, A., E-mail: mirza@irs.uni-stuttgart.de; Fasoulas, S., E-mail: fasoulas@irs.uni-stuttgart.de [Institute of Space Systems, University of Stuttgart, Pfaffenwaldring 29, D-70569 Stuttgart (Germany)

2016-02-15

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.

The SGHWR version of the Monte Carlo code W-MONTE. Part 1. The theoretical model

International Nuclear Information System (INIS)

Allen, F.R.

1976-03-01

W-MONTE provides a multi-group model of neutron transport in the exact geometry of a reactor lattice using Monte Carlo methods. It is currently restricted to uniform axial properties. Material data is normally obtained from a preliminary WIMS lattice calculation in the transport group structure. The SGHWR version has been required for analysis of zero energy experiments and special aspects of power reactor lattices, such as the unmoderated lattice region above the moderator when drained to dump height. Neutron transport is modelled for a uniform infinite lattice, simultaneously treating the cases of no leakage, radial leakage or axial leakage only, and the combined effects of radial and axial leakage. Multigroup neutron balance edits are incorporated for the separate effects of radial and axial leakage to facilitate the analysis of leakage and to provide effective diffusion theory parameters for core representation in reactor cores. (author)

Multilevel sequential Monte Carlo samplers

KAUST Repository

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

2016-01-01

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

Multilevel sequential Monte Carlo samplers

KAUST Repository

Beskos, Alexandros

2016-08-29

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2013-01-01

The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.

Quasi Monte Carlo methods for optimization models of the energy industry with pricing and load processes; Quasi-Monte Carlo Methoden fuer Optimierungsmodelle der Energiewirtschaft mit Preis- und Last-Prozessen

Energy Technology Data Exchange (ETDEWEB)

Leoevey, H.; Roemisch, W. [Humboldt-Univ., Berlin (Germany)

2015-07-01

We discuss progress in quasi Monte Carlo methods for numerical calculation integrals or expected values and justify why these methods are more efficient than the classic Monte Carlo methods. Quasi Monte Carlo methods are found to be particularly efficient if the integrands have a low effective dimension. That's why We also discuss the concept of effective dimension and prove on the example of a stochastic Optimization model of the energy industry that such models can posses a low effective dimension. Modern quasi Monte Carlo methods are therefore for such models very promising. [German] Wir diskutieren Fortschritte bei Quasi-Monte Carlo Methoden zur numerischen Berechnung von Integralen bzw. Erwartungswerten und begruenden warum diese Methoden effizienter sind als die klassischen Monte Carlo Methoden. Quasi-Monte Carlo Methoden erweisen sich als besonders effizient, falls die Integranden eine geringe effektive Dimension besitzen. Deshalb diskutieren wir auch den Begriff effektive Dimension und weisen am Beispiel eines stochastischen Optimierungsmodell aus der Energiewirtschaft nach, dass solche Modelle eine niedrige effektive Dimension besitzen koennen. Moderne Quasi-Monte Carlo Methoden sind deshalb fuer solche Modelle sehr erfolgversprechend.

Optimizing Availability of a Framework in Series Configuration Utilizing Markov Model and Monte Carlo Simulation Techniques

Directory of Open Access Journals (Sweden)

Mansoor Ahmed Siddiqui

2017-06-01

Full Text Available This research work is aimed at optimizing the availability of a framework comprising of two units linked together in series configuration utilizing Markov Model and Monte Carlo (MC Simulation techniques. In this article, effort has been made to develop a maintenance model that incorporates three distinct states for each unit, while taking into account their different levels of deterioration. Calculations are carried out using the proposed model for two distinct cases of corrective repair, namely perfect and imperfect repairs, with as well as without opportunistic maintenance. Initially, results are accomplished using an analytical technique i.e., Markov Model. Validation of the results achieved is later carried out with the help of MC Simulation. In addition, MC Simulation based codes also work well for the frameworks that follow non-exponential failure and repair rates, and thus overcome the limitations offered by the Markov Model.

Parameter uncertainty and model predictions: a review of Monte Carlo results

International Nuclear Information System (INIS)

Gardner, R.H.; O'Neill, R.V.

1979-01-01

Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered

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.

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.

Calibration and Monte Carlo modelling of neutron long counters

CERN Document Server

Tagziria, H

2000-01-01

The Monte Carlo technique has become a very powerful tool in radiation transport as full advantage is taken of enhanced cross-section data, more powerful computers and statistical techniques, together with better characterisation of neutron and photon source spectra. At the National Physical Laboratory, calculations using the Monte Carlo radiation transport code MCNP-4B have been combined with accurate measurements to characterise two long counters routinely used to standardise monoenergetic neutron fields. New and more accurate response function curves have been produced for both long counters. A novel approach using Monte Carlo methods has been developed, validated and used to model the response function of the counters and determine more accurately their effective centres, which have always been difficult to establish experimentally. Calculations and measurements agree well, especially for the De Pangher long counter for which details of the design and constructional material are well known. The sensitivit...

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

International Nuclear Information System (INIS)

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

2004-01-01

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

Linear filtering applied to Monte Carlo criticality calculations

International Nuclear Information System (INIS)

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

1975-01-01

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

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.

Yet another Monte Carlo study of the Schwinger model

International Nuclear Information System (INIS)

Sogo, K.; Kimura, N.

1986-01-01

Some methodological improvements are introduced in the quantum Monte Carlo simulation of the 1 + 1 dimensional quantum electrodynamics (the Schwinger model). Properties at finite temperatures are investigated, concentrating on the existence of the chirality transition and of the deconfinement transition. (author)

Yet another Monte Carlo study of the Schwinger model

International Nuclear Information System (INIS)

Sogo, K.; Kimura, N.

1986-03-01

Some methodological improvements are introduced in the quantum Monte Carlo simulation of the 1 + 1 dimensional quantum electrodynamics (the Schwinger model). Properties at finite temperatures are investigated, concentrating on the existence of the chirality transition and of the deconfinement transition. (author)

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

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

International Nuclear Information System (INIS)

He, Tongming Tony

2003-01-01

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

Exploring uncertainty in glacier mass balance modelling with Monte Carlo simulation

NARCIS (Netherlands)

Machguth, H.; Purves, R.S.; Oerlemans, J.; Hoelzle, M.; Paul, F.

2008-01-01

By means of Monte Carlo simulations we calculated uncertainty in modelled cumulative mass balance over 400 days at one particular point on the tongue of Morteratsch Glacier, Switzerland, using a glacier energy balance model of intermediate complexity. Before uncertainty assessment, the model was

Overview and applications of the Monte Carlo radiation transport kit at LLNL

International Nuclear Information System (INIS)

Sale, K. E.

1999-01-01

Modern Monte Carlo radiation transport codes can be applied to model most applications of radiation, from optical to TeV photons, from thermal neutrons to heavy ions. Simulations can include any desired level of detail in three-dimensional geometries using the right level of detail in the reaction physics. The technology areas to which we have applied these codes include medical applications, defense, safety and security programs, nuclear safeguards and industrial and research system design and control. The main reason such applications are interesting is that by using these tools substantial savings of time and effort (i.e. money) can be realized. In addition it is possible to separate out and investigate computationally effects which can not be isolated and studied in experiments. In model calculations, just as in real life, one must take care in order to get the correct answer to the right question. Advancing computing technology allows extensions of Monte Carlo applications in two directions. First, as computers become more powerful more problems can be accurately modeled. Second, as computing power becomes cheaper Monte Carlo methods become accessible more widely. An overview of the set of Monte Carlo radiation transport tools in use a LLNL will be presented along with a few examples of applications and future directions

A vectorized Monte Carlo code for modeling photon transport in SPECT

International Nuclear Information System (INIS)

Smith, M.F.; Floyd, C.E. Jr.; Jaszczak, R.J.

1993-01-01

A vectorized Monte Carlo computer code has been developed for modeling photon transport in single photon emission computed tomography (SPECT). The code models photon transport in a uniform attenuating region and photon detection by a gamma camera. It is adapted from a history-based Monte Carlo code in which photon history data are stored in scalar variables and photon histories are computed sequentially. The vectorized code is written in FORTRAN77 and uses an event-based algorithm in which photon history data are stored in arrays and photon history computations are performed within DO loops. The indices of the DO loops range over the number of photon histories, and these loops may take advantage of the vector processing unit of our Stellar GS1000 computer for pipelined computations. Without the use of the vector processor the event-based code is faster than the history-based code because of numerical optimization performed during conversion to the event-based algorithm. When only the detection of unscattered photons is modeled, the event-based code executes 5.1 times faster with the use of the vector processor than without; when the detection of scattered and unscattered photons is modeled the speed increase is a factor of 2.9. Vectorization is a valuable way to increase the performance of Monte Carlo code for modeling photon transport in SPECT

Adaptable three-dimensional Monte Carlo modeling of imaged blood vessels in skin

Science.gov (United States)

Pfefer, T. Joshua; Barton, Jennifer K.; Chan, Eric K.; Ducros, Mathieu G.; Sorg, Brian S.; Milner, Thomas E.; Nelson, J. Stuart; Welch, Ashley J.

1997-06-01

In order to reach a higher level of accuracy in simulation of port wine stain treatment, we propose to discard the typical layered geometry and cylindrical blood vessel assumptions made in optical models and use imaging techniques to define actual tissue geometry. Two main additions to the typical 3D, weighted photon, variable step size Monte Carlo routine were necessary to achieve this goal. First, optical low coherence reflectometry (OLCR) images of rat skin were used to specify a 3D material array, with each entry assigned a label to represent the type of tissue in that particular voxel. Second, the Monte Carlo algorithm was altered so that when a photon crosses into a new voxel, the remaining path length is recalculated using the new optical properties, as specified by the material array. The model has shown good agreement with data from the literature. Monte Carlo simulations using OLCR images of asymmetrically curved blood vessels show various effects such as shading, scattering-induced peaks at vessel surfaces, and directionality-induced gradients in energy deposition. In conclusion, this augmentation of the Monte Carlo method can accurately simulate light transport for a wide variety of nonhomogeneous tissue geometries.

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.

Development of M3C code for Monte Carlo reactor physics criticality calculations

International Nuclear Information System (INIS)

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

2015-06-01

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

Automatic modeling for the monte carlo transport TRIPOLI code

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-09-01

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

Burnup calculations using Monte Carlo method

International Nuclear Information System (INIS)

Ghosh, Biplab; Degweker, S.B.

2009-01-01

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

Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

KAUST Repository

Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.

2010-01-01

model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order

Shell-model Monte Carlo studies of nuclei

International Nuclear Information System (INIS)

Dean, D.J.

1997-01-01

The pair content and structure of nuclei near N = Z are described in the frwnework of shell-model Monte Carlo (SMMC) calculations. Results include the enhancement of J=0 T=1 proton-neutron pairing at N=Z nuclei, and the maxked difference of thermal properties between even-even and odd-odd N=Z nuclei. Additionally, a study of the rotational properties of the T=1 (ground state), and T=0 band mixing seen in 74 Rb is presented

Automatic modeling for the Monte Carlo transport code Geant4

International Nuclear Information System (INIS)

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

2015-01-01

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

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

CERN Document Server

Li, Shu; The ATLAS collaboration

2017-01-01

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

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate statistics

International Nuclear Information System (INIS)

Weathers, J.B.; Luck, R.; Weathers, J.W.

2009-01-01

The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate statistics

Energy Technology Data Exchange (ETDEWEB)

Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com

2009-11-15

The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.

Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model

International Nuclear Information System (INIS)

Dimov, I.; Georgieva, R.; Ostromsky, Tz.

2012-01-01

Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobol's global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobol's quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobol's ΛΠ τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobol's sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobol's global sensitivity indices in the presence of computational difficulties have been provided. - Highlights: ► Variance-based global sensitivity analysis is performed for the air pollution model UNI-DEM. ► The main effect of input parameters dominates over higher-order interactions. ► Ozone concentrations are influenced mostly by variability of three chemical reactions rates. ► The newly developed MCA-MSS for multidimensional integration is compared with other approaches. ► More precise approaches like MCA-MSS should be applied when the needed accuracy has not been achieved.

APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

Science.gov (United States)

Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

Monte Carlo investigation of the one-dimensional Potts model

International Nuclear Information System (INIS)

Karma, A.S.; Nolan, M.J.

1983-01-01

Monte Carlo results are presented for a variety of one-dimensional dynamical q-state Potts models. Our calculations confirm the expected universal value z = 2 for the dynamic scaling exponent. Our results also indicate that an increase in q at fixed correlation length drives the dynamics into the scaling regime

Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model

International Nuclear Information System (INIS)

Stotler, D.P.

2005-01-01

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

Monte Carlo Modelling of Mammograms : Development and Validation

International Nuclear Information System (INIS)

Spyrou, G.; Panayiotakis, G.; Bakas, A.; Tzanakos, G.

1998-01-01

A software package using Monte Carlo methods has been developed for the simulation of x-ray mammography. A simplified geometry of the mammographic apparatus has been considered along with the software phantom of compressed breast. This phantom may contain inhomogeneities of various compositions and sizes at any point. Using this model one can produce simulated mammograms. Results that demonstrate the validity of this simulation are presented. (authors)

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

Science.gov (United States)

Schafer, Steven A.

1996-05-01

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

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 Modelling of Single-Crystal Diffuse Scattering from Intermetallics

Directory of Open Access Journals (Sweden)

Darren J. Goossens

2016-02-01

Full Text Available Single-crystal diffuse scattering (SCDS reveals detailed structural insights into materials. In particular, it is sensitive to two-body correlations, whereas traditional Bragg peak-based methods are sensitive to single-body correlations. This means that diffuse scattering is sensitive to ordering that persists for just a few unit cells: nanoscale order, sometimes referred to as “local structure”, which is often crucial for understanding a material and its function. Metals and alloys were early candidates for SCDS studies because of the availability of large single crystals. While great progress has been made in areas like ab initio modelling and molecular dynamics, a place remains for Monte Carlo modelling of model crystals because of its ability to model very large systems; important when correlations are relatively long (though still finite in range. This paper briefly outlines, and gives examples of, some Monte Carlo methods appropriate for the modelling of SCDS from metallic compounds, and considers data collection as well as analysis. Even if the interest in the material is driven primarily by magnetism or transport behaviour, an understanding of the local structure can underpin such studies and give an indication of nanoscale inhomogeneity.

Monte Carlo shielding analyses using an automated biasing procedure

International Nuclear Information System (INIS)

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

1988-01-01

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

Monte Carlo modeling of human tooth optical coherence tomography imaging

International Nuclear Information System (INIS)

Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen

2013-01-01

We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth. (paper)

Application of Monte Carlo codes to neutron dosimetry

International Nuclear Information System (INIS)

Prevo, C.T.

1982-01-01

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

A sequential Monte Carlo model of the combined GB gas and electricity network

International Nuclear Information System (INIS)

Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick

2013-01-01

A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets

Monte Carlo study of superconductivity in the three-band Emery model

International Nuclear Information System (INIS)

Frick, M.; Pattnaik, P.C.; Morgenstern, I.; Newns, D.M.; von der Linden, W.

1990-01-01

We have examined the three-band Hubbard model for the copper oxide planes in high-temperature superconductors using the projector quantum Monte Carlo method. We find no evidence for s-wave superconductivity

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.

Monte Carlo Modelling of Mammograms : Development and Validation

Energy Technology Data Exchange (ETDEWEB)

Spyrou, G; Panayiotakis, G [Univercity of Patras, School of Medicine, Medical Physics Department, 265 00 Patras (Greece); Bakas, A [Technological Educational Institution of Athens, Department of Radiography, 122 10 Athens (Greece); Tzanakos, G [University of Athens, Department of Physics, Divission of Nuclear and Particle Physics, 157 71 Athens (Greece)

1999-12-31

A software package using Monte Carlo methods has been developed for the simulation of x-ray mammography. A simplified geometry of the mammographic apparatus has been considered along with the software phantom of compressed breast. This phantom may contain inhomogeneities of various compositions and sizes at any point. Using this model one can produce simulated mammograms. Results that demonstrate the validity of this simulation are presented. (authors) 16 refs, 4 figs

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

Science.gov (United States)

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

2017-08-01

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

Model unspecific search in CMS. Treatment of insufficient Monte Carlo statistics

Energy Technology Data Exchange (ETDEWEB)

Lieb, Jonas; Albert, Andreas; Duchardt, Deborah; Hebbeker, Thomas; Knutzen, Simon; Meyer, Arnd; Pook, Tobias; Roemer, Jonas [III. Physikalisches Institut A, RWTH Aachen University (Germany)

2016-07-01

In 2015, the CMS detector recorded proton-proton collisions at an unprecedented center of mass energy of √(s)=13 TeV. The Model Unspecific Search in CMS (MUSiC) offers an analysis approach of these data which is complementary to dedicated analyses: By taking all produced final states into consideration, MUSiC is sensitive to indicators of new physics appearing in final states that are usually not investigated. In a two step process, MUSiC first classifies events according to their physics content and then searches kinematic distributions for the most significant deviations between Monte Carlo simulations and observed data. Such a general approach introduces its own set of challenges. One of them is the treatment of situations with insufficient Monte Carlo statistics. Complementing introductory presentations on the MUSiC event selection and classification, this talk will present a method of dealing with the issue of low Monte Carlo statistics.

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

Science.gov (United States)

Temleitner, László; Pusztai, László; Schweika, Werner

2007-08-22

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

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

International Nuclear Information System (INIS)

Leppaenen, J.

2007-01-01

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

Specialized Monte Carlo codes versus general-purpose Monte Carlo codes

International Nuclear Information System (INIS)

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

2002-01-01

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

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.

SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations

Science.gov (United States)

Baes, M.; Camps, P.

2015-09-01

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

International Nuclear Information System (INIS)

Wang, Yuhe; Mazur, Thomas R.; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H. Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H. Harold

2016-01-01

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model.

Science.gov (United States)

Wang, Yuhe; Mazur, Thomas R; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H Harold

2016-07-01

The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian's kmc. An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

Energy Technology Data Exchange (ETDEWEB)

Wang, Yuhe; Mazur, Thomas R.; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H. Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H. Harold, E-mail: hli@radonc.wustl.edu [Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, Missouri 63110 (United States)

2016-07-15

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this

Modelling of the RA-1 reactor using a Monte Carlo code

International Nuclear Information System (INIS)

Quinteiro, Guillermo F.; Calabrese, Carlos R.

2000-01-01

It was carried out for the first time, a model of the Argentine RA-1 reactor using the MCNP Monte Carlo code. This model was validated using data for experimental neutron and gamma measurements at different energy ranges and locations. In addition, the resulting fluxes were compared with the data obtained using a 3D diffusion code. (author)

Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

International Nuclear Information System (INIS)

Stern, R.E.; Song, J.; Work, D.B.

2017-01-01

The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

Competing probabilistic models for catch-effort relationships in wildlife censuses

Energy Technology Data Exchange (ETDEWEB)

Skalski, J.R.; Robson, D.S.; Matsuzaki, C.L.

1983-01-01

Two probabilistic models are presented for describing the chance that an animal is captured during a wildlife census, as a function of trapping effort. The models in turn are used to propose relationships between sampling intensity and catch-per-unit-effort (C.P.U.E.) that were field tested on small mammal populations. Capture data suggests a model of diminshing C.P.U.E. with increasing levels of trapping intensity. The catch-effort model is used to illustrate optimization procedures in the design of mark-recapture experiments for censusing wild populations. 14 references, 2 tables.

Reservoir Modeling Combining Geostatistics with Markov Chain Monte Carlo Inversion

DEFF Research Database (Denmark)

Zunino, Andrea; Lange, Katrine; Melnikova, Yulia

2014-01-01

We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear...

Modeling granular phosphor screens by Monte Carlo methods

International Nuclear Information System (INIS)

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

2006-01-01

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

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

Science.gov (United States)

Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.

2012-11-01

A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.

A Monte Carlo modeling alternative for the API Gamma Ray Calibration Facility

International Nuclear Information System (INIS)

Galford, J.E.

2017-01-01

The gamma ray pit at the API Calibration Facility, located on the University of Houston campus, defines the API unit for natural gamma ray logs used throughout the petroleum logging industry. Future use of the facility is uncertain. An alternative method is proposed to preserve the gamma ray API unit definition as an industry standard by using Monte Carlo modeling to obtain accurate counting rate-to-API unit conversion factors for gross-counting and spectral gamma ray tool designs. - Highlights: • A Monte Carlo alternative is proposed to replace empirical calibration procedures. • The proposed Monte Carlo alternative preserves the original API unit definition. • MCNP source and materials descriptions are provided for the API gamma ray pit. • Simulated results are presented for several wireline logging tool designs. • The proposed method can be adapted for use with logging-while-drilling tools.

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

International Nuclear Information System (INIS)

Paul P.H. Wilson

2005-01-01

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

Monte Carlo wave packet approach to dissociative multiple ionization in diatomic molecules

DEFF Research Database (Denmark)

Leth, Henriette Astrup; Madsen, Lars Bojer; Mølmer, Klaus

2010-01-01

A detailed description of the Monte Carlo wave packet technique applied to dissociative multiple ionization of diatomic molecules in short intense laser pulses is presented. The Monte Carlo wave packet technique relies on the Born-Oppenheimer separation of electronic and nuclear dynamics...... and provides a consistent theoretical framework for treating simultaneously both ionization and dissociation. By simulating the detection of continuum electrons and collapsing the system onto either the neutral, singly ionized or doubly ionized states in every time step the nuclear dynamics can be solved....... The computational effort is restricted and the model is applicable to any molecular system where electronic Born-Oppenheimer curves, dipole moment functions, and ionization rates as a function of nuclear coordinates can be determined....

A novel Monte Carlo approach to hybrid local volatility models

NARCIS (Netherlands)

A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

2017-01-01

textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

High-energy particle Monte Carlo at Los Alamos

International Nuclear Information System (INIS)

Prael, R.E.

1985-01-01

A major computational effort at Los Alamos has been the development of a code system based on the HETC code for the transport of nucleons, pions, and muons. The Los Alamos National Laboratory version of HETC utilizes MCNP geometry and interfaces with MCNP for the transport of neutrons below 20 MeV and photons at any energy. A major recent effort has been the development of the PHT code for treating the gamma cascade in excited nuclei (the residual nuclei from an HETC calculation) by the Monte Carlo method to generate a photon source for MCNP. The HETC/MCNP code system has been extensively used for design studies of accelerator targets and shielding, including the design of LAMPF-II. It is extensively used for the design and analysis of accelerator experiments. Los Alamos National Laboratory has been an active member of the International Collaboration on Advanced Neutron Sources; as such we engage in shared code development and computational efforts. In the past few years, additional effort has been devoted to the development of a Chen-model intranuclear cascade code (INCA1) featuring a cluster model for the nucleus and deuteron pickup reactions. Concurrently, the INCA2 code for the breakup of light, excited nuclei using the Fermi breakup model has been developed. Together, they have been used for the calculation of neutron and proton cross sections in the energy ranges appropriate to medical accelerators, and for the computation of tissue kerma factors

Radiation Modeling with Direct Simulation Monte Carlo

Science.gov (United States)

Carlson, Ann B.; Hassan, H. A.

1991-01-01

Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.

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

Science.gov (United States)

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

2017-09-01

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

Skin fluorescence model based on the Monte Carlo technique

Science.gov (United States)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2003-10-01

The novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account spatial distribution of fluorophores following the collagen fibers packing, whereas in epidermis and stratum corneum the distribution of fluorophores assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the NIR spectral region, while fluorescence of sensor layer embedded in epidermis is localized at the adjusted depth. The model is also able to simulate the skin fluorescence spectra.

Monte Carlo techniques in radiation therapy

CERN Document Server

Verhaegen, Frank

2013-01-01

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

Modelling of the RA-1 reactor using a Monte Carlo code; Modelado del reactor RA-1 utilizando un codigo Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Quinteiro, Guillermo F; Calabrese, Carlos R [Comision Nacional de Energia Atomica, General San Martin (Argentina). Dept. de Reactores y Centrales Nucleares

2000-07-01

It was carried out for the first time, a model of the Argentine RA-1 reactor using the MCNP Monte Carlo code. This model was validated using data for experimental neutron and gamma measurements at different energy ranges and locations. In addition, the resulting fluxes were compared with the data obtained using a 3D diffusion code. (author)

Experimental validation of a Monte Carlo proton therapy nozzle model incorporating magnetically steered protons

International Nuclear Information System (INIS)

Peterson, S W; Polf, J; Archambault, L; Beddar, S; Bues, M; Ciangaru, G; Smith, A

2009-01-01

The purpose of this study is to validate the accuracy of a Monte Carlo calculation model of a proton magnetic beam scanning delivery nozzle developed using the Geant4 toolkit. The Monte Carlo model was used to produce depth dose and lateral profiles, which were compared to data measured in the clinical scanning treatment nozzle at several energies. Comparisons were also made between measured and simulated off-axis profiles to test the accuracy of the model's magnetic steering. Comparison of the 80% distal dose fall-off values for the measured and simulated depth dose profiles agreed to within 1 mm for the beam energies evaluated. Agreement of the full width at half maximum values for the measured and simulated lateral fluence profiles was within 1.3 mm for all energies. The position of measured and simulated spot positions for the magnetically steered beams agreed to within 0.7 mm of each other. Based on these results, we found that the Geant4 Monte Carlo model of the beam scanning nozzle has the ability to accurately predict depth dose profiles, lateral profiles perpendicular to the beam axis and magnetic steering of a proton beam during beam scanning proton therapy.

Monte Carlo Methods in Physics

International Nuclear Information System (INIS)

Santoso, B.

1997-01-01

Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained

Monte Carlos of the new generation: status and progress

International Nuclear Information System (INIS)

Frixione, Stefano

2005-01-01

Standard parton shower monte carlos are designed to give reliable descriptions of low-pT physics. In the very high-energy regime of modern colliders, this is may lead to largely incorrect predictions of the basic reaction processes. This motivated the recent theoretical efforts aimed at improving monte carlos through the inclusion of matrix elements computed beyond the leading order in QCD. I briefly review the progress made, and discuss bottom production at the Tevatron

Monte Carlo Studies of Phase Separation in Compressible 2-dim Ising Models

Science.gov (United States)

Mitchell, S. J.; Landau, D. P.

2006-03-01

Using high resolution Monte Carlo simulations, we study time-dependent domain growth in compressible 2-dim ferromagnetic (s=1/2) Ising models with continuous spin positions and spin-exchange moves [1]. Spins interact with slightly modified Lennard-Jones potentials, and we consider a model with no lattice mismatch and one with 4% mismatch. For comparison, we repeat calculations for the rigid Ising model [2]. For all models, large systems (512^2) and long times (10^ 6 MCS) are examined over multiple runs, and the growth exponent is measured in the asymptotic scaling regime. For the rigid model and the compressible model with no lattice mismatch, the growth exponent is consistent with the theoretically expected value of 1/3 [1] for Model B type growth. However, we find that non-zero lattice mismatch has a significant and unexpected effect on the growth behavior.Supported by the NSF.[1] D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, second ed. (Cambridge University Press, New York, 2005).[2] J. Amar, F. Sullivan, and R.D. Mountain, Phys. Rev. B 37, 196 (1988).

A Monte Carlo model for 3D grain evolution during welding

Science.gov (United States)

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

2017-09-01

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

Modeling Dynamic Objects in Monte Carlo Particle Transport Calculations

International Nuclear Information System (INIS)

Yegin, G.

2008-01-01

In this study, the Multi-Geometry geometry modeling technique was improved in order to handle moving objects in a Monte Carlo particle transport calculation. In the Multi-Geometry technique, the geometry is a superposition of objects not surfaces. By using this feature, we developed a new algorithm which allows a user to make enable or disable geometry elements during particle transport. A disabled object can be ignored at a certain stage of a calculation and switching among identical copies of the same object located adjacent poins during a particle simulation corresponds to the movement of that object in space. We called this powerfull feature as Dynamic Multi-Geometry technique (DMG) which is used for the first time in Brachy Dose Monte Carlo code to simulate HDR brachytherapy treatment systems. Our results showed that having disabled objects in a geometry does not effect calculated dose values. This technique is also suitable to be used in other areas such as IMRT treatment planning systems

Multilevel sequential Monte-Carlo samplers

KAUST Repository

Jasra, Ajay

2016-01-01

Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

Multilevel sequential Monte-Carlo samplers

KAUST Repository

Jasra, Ajay

2016-01-05

Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

Verification of the VEF photon beam model for dose calculations by the voxel-Monte-Carlo-algorithm

International Nuclear Information System (INIS)

Kriesen, S.; Fippel, M.

2005-01-01

The VEF linac head model (VEF, virtual energy fluence) was developed at the University of Tuebingen to determine the primary fluence for calculations of dose distributions in patients by the Voxel-Monte-Carlo-Algorithm (XVMC). This analytical model can be fitted to any therapy accelerator head by measuring only a few basic dose data; therefore, time-consuming Monte-Carlo simulations of the linac head become unnecessary. The aim of the present study was the verification of the VEF model by means of water-phantom measurements, as well as the comparison of this system with a common analytical linac head model of a commercial planning system (TMS, formerly HELAX or MDS Nordion, respectively). The results show that both the VEF and the TMS models can very well simulate the primary fluence. However, the VEF model proved superior in the simulations of scattered radiation and in the calculations of strongly irregular MLC fields. Thus, an accurate and clinically practicable tool for the determination of the primary fluence for Monte-Carlo-Simulations with photons was established, especially for the use in IMRT planning. (orig.)

[Verification of the VEF photon beam model for dose calculations by the Voxel-Monte-Carlo-Algorithm].

Science.gov (United States)

Kriesen, Stephan; Fippel, Matthias

2005-01-01

The VEF linac head model (VEF, virtual energy fluence) was developed at the University of Tübingen to determine the primary fluence for calculations of dose distributions in patients by the Voxel-Monte-Carlo-Algorithm (XVMC). This analytical model can be fitted to any therapy accelerator head by measuring only a few basic dose data; therefore, time-consuming Monte-Carlo simulations of the linac head become unnecessary. The aim of the present study was the verification of the VEF model by means of water-phantom measurements, as well as the comparison of this system with a common analytical linac head model of a commercial planning system (TMS, formerly HELAX or MDS Nordion, respectively). The results show that both the VEF and the TMS models can very well simulate the primary fluence. However, the VEF model proved superior in the simulations of scattered radiation and in the calculations of strongly irregular MLC fields. Thus, an accurate and clinically practicable tool for the determination of the primary fluence for Monte-Carlo-Simulations with photons was established, especially for the use in IMRT planning.

Monte Carlo modelling of TRIGA research reactor

Science.gov (United States)

El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.

2010-10-01

The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.

Setup of HDRK-Man voxel model in Geant4 Monte Carlo code

Energy Technology Data Exchange (ETDEWEB)

Jeong, Jong Hwi; Cho, Sung Koo; Kim, Chan Hyeong [Hanyang Univ., Seoul (Korea, Republic of); Choi, Sang Hyoun [Inha Univ., Incheon (Korea, Republic of); Cho, Kun Woo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2008-10-15

Many different voxel models, developed using tomographic images of human body, are used in various fields including both ionizing and non-ionizing radiation fields. Recently a high-quality voxel model/ named HDRK-Man, was constructed at Hanyang University and used to calculate the dose conversion coefficients (DCC) values for external photon and neutron beams using the MCNPX Monte Carlo code. The objective of the present study is to set up the HDRK-Man model in Geant4 in order to use it in more advanced calculations such as 4-D Monte Carlo simulations and space dosimetry studies involving very high energy particles. To that end, the HDRK-Man was ported to Geant4 and used to calculate the DCC values for external photon beams. The calculated values were then compared with the results of the MCNPX code. In addition, a computational Linux cluster was built to improve the computing speed in Geant4.

Monte Carlo model of diagnostic X-ray dosimetry

International Nuclear Information System (INIS)

Khrutchinsky, Arkady; Kutsen, Semion; Gatskevich, George

2008-01-01

Full text: A Monte Carlo simulation of absorbed dose distribution in patient's tissues is often used in a dosimetry assessment of X-ray examinations. The results of such simulations in Belarus are presented in the report based on an anthropomorphic tissue-equivalent Rando-like physical phantom. The phantom corresponds to an adult 173 cm high and of 73 kg and consists of a torso and a head made of tissue-equivalent plastics which model soft (muscular), bone, and lung tissues. It consists of 39 layers (each 25 mm thick), including 10 head and neck ones, 16 chest and 13 pelvis ones. A tomographic model of the phantom has been developed from its CT-scan images with a voxel size of 0.88 x 0.88 x 4 mm 3 . A necessary pixelization in Mathematics-based in-house program was carried out for the phantom to be used in the radiation transport code MCNP-4b. The final voxel size of 14.2 x 14.2 x 8 mm 3 was used for the reasonable computer consuming calculations of absorbed dose in tissues and organs in various diagnostic X-ray examinations. MCNP point detectors allocated through body slices obtained as a result of the pixelization were used to calculate the absorbed dose. X-ray spectra generated by the empirical TASMIP model were verified on the X-ray units MEVASIM and SIREGRAPH CF. Absorbed dose distributions in the phantom volume were determined by the corresponding Monte Carlo simulations with a set of point detectors. Doses in organs of the adult phantom computed from the absorbed dose distributions by another Mathematics-based in-house program were estimated for 22 standard organs for various standard X-ray examinations. The results of Monte Carlo simulations were compared with the results of direct measurements of the absorbed dose in the phantom on the X-ray unit SIREGRAPH CF with the calibrated thermo-luminescent dosimeter DTU-01. The measurements were carried out in specified locations of different layers in heart, lungs, liver, pancreas, and stomach at high voltage of

Monte Carlo evaluation of path integral for the nuclear shell model

International Nuclear Information System (INIS)

Lang, G.H.

1993-01-01

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

Automatic modeling for the Monte Carlo transport code Geant4 in MCAM

International Nuclear Information System (INIS)

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

2014-01-01

Geant4 is a widely used Monte Carlo transport simulation package. Its geometry models could be described in geometry description markup language (GDML), but it is time-consuming and error-prone to describe the geometry models manually. This study implemented the conversion between computer-aided design (CAD) geometry models and GDML models. The conversion program was integrated into Multi-Physics Coupling Analysis Modeling Program (MCAM). The tests, including FDS-Ⅱ model, demonstrated its accuracy and feasibility. (authors)

An analytical model for backscattered luminance in fog: comparisons with Monte Carlo computations and experimental results

International Nuclear Information System (INIS)

Taillade, Frédéric; Dumont, Eric; Belin, Etienne

2008-01-01

We propose an analytical model for backscattered luminance in fog and derive an expression for the visibility signal-to-noise ratio as a function of meteorological visibility distance. The model uses single scattering processes. It is based on the Mie theory and the geometry of the optical device (emitter and receiver). In particular, we present an overlap function and take the phase function of fog into account. The results of the backscattered luminance obtained with our analytical model are compared to simulations made using the Monte Carlo method based on multiple scattering processes. An excellent agreement is found in that the discrepancy between the results is smaller than the Monte Carlo standard uncertainties. If we take no account of the geometry of the optical device, the results of the model-estimated backscattered luminance differ from the simulations by a factor 20. We also conclude that the signal-to-noise ratio computed with the Monte Carlo method and our analytical model is in good agreement with experimental results since the mean difference between the calculations and experimental measurements is smaller than the experimental uncertainty

Monte Carlo technique for very large ising models

Science.gov (United States)

Kalle, C.; Winkelmann, V.

1982-08-01

Rebbi's multispin coding technique is improved and applied to the kinetic Ising model with size 600*600*600. We give the central part of our computer program (for a CDC Cyber 76), which will be helpful also in a simulation of smaller systems, and describe the other tricks necessary to go to large lattices. The magnetization M at T=1.4* T c is found to decay asymptotically as exp(-t/2.90) if t is measured in Monte Carlo steps per spin, and M( t = 0) = 1 initially.

Progress towards an effective model for FeSe from high-accuracy first-principles quantum Monte Carlo

Science.gov (United States)

Busemeyer, Brian; Wagner, Lucas K.

While the origin of superconductivity in the iron-based materials is still controversial, the proximity of the superconductivity to magnetic order is suggestive that magnetism may be important. Our previous work has suggested that first-principles Diffusion Monte Carlo (FN-DMC) can capture magnetic properties of iron-based superconductors that density functional theory (DFT) misses, but which are consistent with experiment. We report on the progress of efforts to find simple effective models consistent with the FN-DMC description of the low-lying Hilbert space of the iron-based superconductor, FeSe. We utilize a procedure outlined by Changlani et al.[1], which both produces parameter values and indications of whether the model is a good description of the first-principles Hamiltonian. Using this procedure, we evaluate several models of the magnetic part of the Hilbert space found in the literature, as well as the Hubbard model, and a spin-fermion model. We discuss which interaction parameters are important for this material, and how the material-specific properties give rise to these interactions. U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program under Award No. FG02-12ER46875, as well as the NSF Graduate Research Fellowship Program.

Modeling to Mars: a NASA Model Based Systems Engineering Pathfinder Effort

Science.gov (United States)

Phojanamongkolkij, Nipa; Lee, Kristopher A.; Miller, Scott T.; Vorndran, Kenneth A.; Vaden, Karl R.; Ross, Eric P.; Powell, Bobby C.; Moses, Robert W.

2017-01-01

The NASA Engineering Safety Center (NESC) Systems Engineering (SE) Technical Discipline Team (TDT) initiated the Model Based Systems Engineering (MBSE) Pathfinder effort in FY16. The goals and objectives of the MBSE Pathfinder include developing and advancing MBSE capability across NASA, applying MBSE to real NASA issues, and capturing issues and opportunities surrounding MBSE. The Pathfinder effort consisted of four teams, with each team addressing a particular focus area. This paper focuses on Pathfinder team 1 with the focus area of architectures and mission campaigns. These efforts covered the timeframe of February 2016 through September 2016. The team was comprised of eight team members from seven NASA Centers (Glenn Research Center, Langley Research Center, Ames Research Center, Goddard Space Flight Center IV&V Facility, Johnson Space Center, Marshall Space Flight Center, and Stennis Space Center). Collectively, the team had varying levels of knowledge, skills and expertise in systems engineering and MBSE. The team applied their existing and newly acquired system modeling knowledge and expertise to develop modeling products for a campaign (Program) of crew and cargo missions (Projects) to establish a human presence on Mars utilizing In-Situ Resource Utilization (ISRU). Pathfinder team 1 developed a subset of modeling products that are required for a Program System Requirement Review (SRR)/System Design Review (SDR) and Project Mission Concept Review (MCR)/SRR as defined in NASA Procedural Requirements. Additionally, Team 1 was able to perform and demonstrate some trades and constraint analyses. At the end of these efforts, over twenty lessons learned and recommended next steps have been identified.

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

International Nuclear Information System (INIS)

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

2008-01-01

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

R and D on automatic modeling methods for Monte Carlo codes FLUKA

International Nuclear Information System (INIS)

Wang Dianxi; Hu Liqin; Wang Guozhong; Zhao Zijia; Nie Fanzhi; Wu Yican; Long Pengcheng

2013-01-01

FLUKA is a fully integrated particle physics Monte Carlo simulation package. It is necessary to create the geometry models before calculation. However, it is time- consuming and error-prone to describe the geometry models manually. This study developed an automatic modeling method which could automatically convert computer-aided design (CAD) geometry models into FLUKA models. The conversion program was integrated into CAD/image-based automatic modeling program for nuclear and radiation transport simulation (MCAM). Its correctness has been demonstrated. (authors)

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation

NARCIS (Netherlands)

Minasny, B.; Vrugt, J.A.; McBratney, A.B.

2011-01-01

This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior

Verification of the shift Monte Carlo code with the C5G7 reactor benchmark

International Nuclear Information System (INIS)

Sly, N. C.; Mervin, B. T.; Mosher, S. W.; Evans, T. M.; Wagner, J. C.; Maldonado, G. I.

2012-01-01

Shift is a new hybrid Monte Carlo/deterministic radiation transport code being developed at Oak Ridge National Laboratory. At its current stage of development, Shift includes a parallel Monte Carlo capability for simulating eigenvalue and fixed-source multigroup transport problems. This paper focuses on recent efforts to verify Shift's Monte Carlo component using the two-dimensional and three-dimensional C5G7 NEA benchmark problems. Comparisons were made between the benchmark eigenvalues and those output by the Shift code. In addition, mesh-based scalar flux tally results generated by Shift were compared to those obtained using MCNP5 on an identical model and tally grid. The Shift-generated eigenvalues were within three standard deviations of the benchmark and MCNP5-1.60 values in all cases. The flux tallies generated by Shift were found to be in very good agreement with those from MCNP. (authors)

Monte Carlo treatment planning and high-resolution alpha-track autoradiography for neutron capture therapy

Energy Technology Data Exchange (ETDEWEB)

Zamenhof, R.G.; Lin, K.; Ziegelmiller, D.; Clement, S.; Lui, C.; Harling, O.K.

Monte Carlo simulations of thermal neutron flux distributions in a mathematical head model have been compared to experimental measurements in a corresponding anthropomorphic gelatin-based head phantom irradiated by a thermal neutron beam as presently available at the MITR-II Research Reactor. Excellent agreement between Monte Carlo and experimental measurements has encouraged us to employ the Monte Carlo simulation technique to approach treatment planning problems in neutron capture therapy. We have also implemented a high-resolution alpha-track autoradiography technique originally developed in our laboratory at MIT. Initial autoradiograms produced by this technique meet our expectations in terms of the high resolution available and the ability to etch tracks without concommitant destruction of stained tissue. Our preliminary results with computer-aided track distribution analysis indicate that this approach is very promising in being able to quantify boron distributions in tissue at the subcellular level with a minimum amount of operator effort necessary.

Monte Carlo and analytical model predictions of leakage neutron exposures from passively scattered proton therapy

International Nuclear Information System (INIS)

Pérez-Andújar, Angélica; Zhang, Rui; Newhauser, Wayne

2013-01-01

Purpose: Stray neutron radiation is of concern after radiation therapy, especially in children, because of the high risk it might carry for secondary cancers. Several previous studies predicted the stray neutron exposure from proton therapy, mostly using Monte Carlo simulations. Promising attempts to develop analytical models have also been reported, but these were limited to only a few proton beam energies. The purpose of this study was to develop an analytical model to predict leakage neutron equivalent dose from passively scattered proton beams in the 100-250-MeV interval.Methods: To develop and validate the analytical model, the authors used values of equivalent dose per therapeutic absorbed dose (H/D) predicted with Monte Carlo simulations. The authors also characterized the behavior of the mean neutron radiation-weighting factor, w R , as a function of depth in a water phantom and distance from the beam central axis.Results: The simulated and analytical predictions agreed well. On average, the percentage difference between the analytical model and the Monte Carlo simulations was 10% for the energies and positions studied. The authors found that w R was highest at the shallowest depth and decreased with depth until around 10 cm, where it started to increase slowly with depth. This was consistent among all energies.Conclusion: Simple analytical methods are promising alternatives to complex and slow Monte Carlo simulations to predict H/D values. The authors' results also provide improved understanding of the behavior of w R which strongly depends on depth, but is nearly independent of lateral distance from the beam central axis

Supercomputer and cluster performance modeling and analysis efforts:2004-2006.

Energy Technology Data Exchange (ETDEWEB)

Sturtevant, Judith E.; Ganti, Anand; Meyer, Harold (Hal) Edward; Stevenson, Joel O.; Benner, Robert E., Jr. (.,; .); Goudy, Susan Phelps; Doerfler, Douglas W.; Domino, Stefan Paul; Taylor, Mark A.; Malins, Robert Joseph; Scott, Ryan T.; Barnette, Daniel Wayne; Rajan, Mahesh; Ang, James Alfred; Black, Amalia Rebecca; Laub, Thomas William; Vaughan, Courtenay Thomas; Franke, Brian Claude

2007-02-01

This report describes efforts by the Performance Modeling and Analysis Team to investigate performance characteristics of Sandia's engineering and scientific applications on the ASC capability and advanced architecture supercomputers, and Sandia's capacity Linux clusters. Efforts to model various aspects of these computers are also discussed. The goals of these efforts are to quantify and compare Sandia's supercomputer and cluster performance characteristics; to reveal strengths and weaknesses in such systems; and to predict performance characteristics of, and provide guidelines for, future acquisitions and follow-on systems. Described herein are the results obtained from running benchmarks and applications to extract performance characteristics and comparisons, as well as modeling efforts, obtained during the time period 2004-2006. The format of the report, with hypertext links to numerous additional documents, purposefully minimizes the document size needed to disseminate the extensive results from our research.

Use of Monte Carlo modeling approach for evaluating risk and environmental compliance

International Nuclear Information System (INIS)

Higley, K.A.; Strenge, D.L.

1988-09-01

Evaluating compliance with environmental regulations, specifically those regulations that pertain to human exposure, can be a difficult task. Historically, maximum individual or worst-case exposures have been calculated as a basis for evaluating risk or compliance with such regulations. However, these calculations may significantly overestimate exposure and may not provide a clear understanding of the uncertainty in the analysis. The use of Monte Carlo modeling techniques can provide a better understanding of the potential range of exposures and the likelihood of high (worst-case) exposures. This paper compares the results of standard exposure estimation techniques with the Monte Carlo modeling approach. The authors discuss the potential application of this approach for demonstrating regulatory compliance, along with the strengths and weaknesses of the approach. Suggestions on implementing this method as a routine tool in exposure and risk analyses are also presented. 16 refs., 5 tabs

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

CERN Document Server

Li, Shu; The ATLAS collaboration

2017-01-01

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

Monte Carlo codes and Monte Carlo simulator program

International Nuclear Information System (INIS)

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

1990-03-01

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

New model for mines and transportation tunnels external dose calculation using Monte Carlo simulation

International Nuclear Information System (INIS)

Allam, Kh. A.

2017-01-01

In this work, a new methodology is developed based on Monte Carlo simulation for tunnels and mines external dose calculation. Tunnels external dose evaluation model of a cylindrical shape of finite thickness with an entrance and with or without exit. A photon transportation model was applied for exposure dose calculations. A new software based on Monte Carlo solution was designed and programmed using Delphi programming language. The variation of external dose due to radioactive nuclei in a mine tunnel and the corresponding experimental data lies in the range 7.3 19.9%. The variation of specific external dose rate with position in, tunnel building material density and composition were studied. The given new model has more flexible for real external dose in any cylindrical tunnel structure calculations. (authors)

Monte Carlo Treatment Planning for Advanced Radiotherapy

DEFF Research Database (Denmark)

Cronholm, Rickard

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

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 tests of the Rasch model based on scalability coefficients

DEFF Research Database (Denmark)

Christensen, Karl Bang; Kreiner, Svend

2010-01-01

that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence......For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient...

Monte Carlo modeling of neutron imaging at the SINQ spallation source

International Nuclear Information System (INIS)

Lebenhaft, J.R.; Lehmann, E.H.; Pitcher, E.J.; McKinney, G.W.

2003-01-01

Modeling of the Swiss Spallation Neutron Source (SINQ) has been used to demonstrate the neutron radiography capability of the newly released MPI-version of the MCNPX Monte Carlo code. A detailed MCNPX model was developed of SINQ and its associated neutron transmission radiography (NEUTRA) facility. Preliminary validation of the model was performed by comparing the calculated and measured neutron fluxes in the NEUTRA beam line, and a simulated radiography image was generated for a sample consisting of steel tubes containing different materials. This paper describes the SINQ facility, provides details of the MCNPX model, and presents preliminary results of the neutron imaging. (authors)

Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

KAUST Repository

Martinez, Josue G.

2010-06-01

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

New software library of geometrical primitives for modelling of solids used in Monte Carlo detector simulations

CERN Multimedia

CERN. Geneva

2012-01-01

We present our effort for the creation of a new software library of geometrical primitives, which are used for solid modelling in Monte Carlo detector simulations. We plan to replace and unify current geometrical primitive classes in the CERN software projects Geant4 and ROOT with this library. Each solid is represented by a C++ class with methods suited for measuring distances of particles from the surface of a solid and for determination as to whether the particles are located inside, outside or on the surface of the solid. We use numerical tolerance for determining whether the particles are located on the surface. The class methods also contain basic support for visualization. We use dedicated test suites for validation of the shape codes. These include also special performance and numerical value comparison tests for help with analysis of possible candidates of class methods as well as to verify that our new implementation proposals were designed and implemented properly. Currently, bridge classes are u...

Parallel Monte Carlo reactor neutronics

International Nuclear Information System (INIS)

Blomquist, R.N.; Brown, F.B.

1994-01-01

The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved

Monte Carlo modeling for realizing optimized management of failed fuel replacement

International Nuclear Information System (INIS)

Morishita, Kazunori; Yamamoto, Yasunori; Nakasuji, Toshiki

2014-01-01

Fuel cladding is one of the key components in a fission reactor to keep confining radioactive materials inside a fuel tube. During reactor operation, the cladding is however sometimes breached and radioactive materials leak from the fuel ceramic pellet into the coolant water through the breach. The primary coolant water is therefore monitored so that any leak is quickly detected, where the coolant water is periodically sampled and the concentration of, for example the radioactive iodine 131 (I-131), is measured. Depending on the measured concentration, the faulty fuel assembly with leaking rod is removed from the reactor and replaced by new one immediately or at the next refueling. In the present study, an effort has been made to develop a methodology to optimize the management for replacement of failed fuels due to cladding failures using the I-131 concentration measured in the sampled coolant water. A model numerical equation is proposed to describe the time evolution of I-131 concentration due to fuel leaks, and is then solved using the Monte-Carlo method as a function of sampling rate. Our results have indicated that, in order to achieve the rationalized management of failed fuels, higher resolution to detect a small amount of I-131 is not necessarily required but more frequent sampling is favorable. (author)

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-05-15

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

Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling

Directory of Open Access Journals (Sweden)

Dennis Fok

2014-02-01

Full Text Available We put forward a brand choice model with unobserved heterogeneity that concerns responsiveness to marketing efforts. We introduce two latent segments of households. The first segment is assumed to respond to marketing efforts, while households in the second segment do not do so. Whether a specific household is a member of the first or the second segment at a specific purchase occasion is described by household-specific characteristics and characteristics concerning buying behavior. Households may switch between the two responsiveness states over time. When comparing the performance of our model with alternative choice models that account for various forms of heterogeneity for three different datasets, we find better face validity for our parameters. Our model also forecasts better.

Successful vectorization - reactor physics Monte Carlo code

International Nuclear Information System (INIS)

Martin, W.R.

1989-01-01

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

EGS-Ray, a program for the visualization of Monte-Carlo calculations in the radiation physics

International Nuclear Information System (INIS)

Kleinschmidt, C.

2001-01-01

A Windows program is introduced which allows a relatively easy and interactive access to Monte Carlo techniques in clinical radiation physics. Furthermore, this serves as a visualization tool of the methodology and the results of Monte Carlo simulations. The program requires only little effort to formulate and calculate a Monte Carlo problem. The Monte Carlo module of the program is based on the well-known EGS4/PRESTA code. The didactic features of the program are presented using several examples common to the routine of the clinical radiation physicist. (orig.) [de

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-08-15

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

Exponentially-convergent Monte Carlo via finite-element trial spaces

International Nuclear Information System (INIS)

Morel, Jim E.; Tooley, Jared P.; Blamer, Brandon J.

2011-01-01

Exponentially-Convergent Monte Carlo (ECMC) methods, also known as adaptive Monte Carlo and residual Monte Carlo methods, were the subject of intense research over a decade ago, but they never became practical for solving the realistic problems. We believe that the failure of previous efforts may be related to the choice of trial spaces that were global and thus highly oscillatory. As an alternative, we consider finite-element trial spaces, which have the ability to treat fully realistic problems. As a first step towards more general methods, we apply piecewise-linear trial spaces to the spatially-continuous two-stream transport equation. Using this approach, we achieve exponential convergence and computationally demonstrate several fundamental properties of finite-element based ECMC methods. Finally, our results indicate that the finite-element approach clearly deserves further investigation. (author)

Monte Carlo modeling of the Fastscan whole body counter response

International Nuclear Information System (INIS)

Graham, H.R.; Waller, E.J.

2015-01-01

Monte Carlo N-Particle (MCNP) was used to make a model of the Fastscan for the purpose of calibration. Two models were made one for the Pickering Nuclear Site, and one for the Darlington Nuclear Site. Once these models were benchmarked and found to be in good agreement, simulations were run to study the effect different sized phantoms had on the detected response, and the shielding effect of torso fat was not negligible. Simulations into the nature of a source being positioned externally on the anterior or posterior of a person were also conducted to determine a ratio that could be used to determine if a source is externally or internally placed. (author)

Novel extrapolation method in the Monte Carlo shell model

International Nuclear Information System (INIS)

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

2010-01-01

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

Monte Carlo and Quasi-Monte Carlo Sampling

CERN Document Server

Lemieux, Christiane

2009-01-01

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

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.

Automatic mesh adaptivity for hybrid Monte Carlo/deterministic neutronics modeling of difficult shielding problems

International Nuclear Information System (INIS)

Ibrahim, Ahmad M.; Wilson, Paul P.H.; Sawan, Mohamed E.; Mosher, Scott W.; Peplow, Douglas E.; Wagner, John C.; Evans, Thomas M.; Grove, Robert E.

2015-01-01

The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, eliminating the need for a world-class super computer

Fission yield calculation using toy model based on Monte Carlo simulation

International Nuclear Information System (INIS)

Jubaidah; Kurniadi, Rizal

2015-01-01

Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R c ), mean of left curve (μ L ) and mean of right curve (μ R ), deviation of left curve (σ L ) and deviation of right curve (σ R ). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90

Fission yield calculation using toy model based on Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Jubaidah, E-mail: jubaidah@student.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia); Physics Department, Faculty of Mathematics and Natural Science – State University of Medan. Jl. Willem Iskandar Pasar V Medan Estate – North Sumatera, Indonesia 20221 (Indonesia); Kurniadi, Rizal, E-mail: rijalk@fi.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia)

2015-09-30

Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90

Assesment of advanced step models for steady state Monte Carlo burnup calculations in application to prismatic HTGR

Directory of Open Access Journals (Sweden)

Kępisty Grzegorz

2015-09-01

Full Text Available In this paper, we compare the methodology of different time-step models in the context of Monte Carlo burnup calculations for nuclear reactors. We discuss the differences between staircase step model, slope model, bridge scheme and stochastic implicit Euler method proposed in literature. We focus on the spatial stability of depletion procedure and put additional emphasis on the problem of normalization of neutron source strength. Considered methodology has been implemented in our continuous energy Monte Carlo burnup code (MCB5. The burnup simulations have been performed using the simplified high temperature gas-cooled reactor (HTGR system with and without modeling of control rod withdrawal. Useful conclusions have been formulated on the basis of results.

The Effort Paradox: Effort Is Both Costly and Valued.

Science.gov (United States)

Inzlicht, Michael; Shenhav, Amitai; Olivola, Christopher Y

2018-04-01

According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) effort, sometimes we select options precisely because they require effort. Given the increasing recognition of effort's role in motivation, cognitive control, and value-based decision-making, considering this neglected side of effort will not only improve formal computational models, but also provide clues about how to promote sustained mental effort across time. Copyright © 2018 Elsevier Ltd. All rights reserved.

Converting boundary representation solid models to half-space representation models for Monte Carlo analysis

International Nuclear Information System (INIS)

Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.

2007-01-01

Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)

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

Energy Technology Data Exchange (ETDEWEB)

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

1996-03-01

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

Monte Carlo based diffusion coefficients for LMFBR analysis

International Nuclear Information System (INIS)

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

2010-01-01

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

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.

GPU based Monte Carlo for PET image reconstruction: detector modeling

International Nuclear Information System (INIS)

Légrády; Cserkaszky, Á; Lantos, J.; Patay, G.; Bükki, T.

2011-01-01

Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)

MONTE CARLO ANALYSES OF THE YALINA THERMAL FACILITY WITH SERPENT STEREOLITHOGRAPHY GEOMETRY MODEL

Energy Technology Data Exchange (ETDEWEB)

Talamo, A.; Gohar, Y.

2015-01-01

This paper analyzes the YALINA Thermal subcritical assembly of Belarus using two different Monte Carlo transport programs, SERPENT and MCNP. The MCNP model is based on combinatorial geometry and universes hierarchy, while the SERPENT model is based on Stereolithography geometry. The latter consists of unstructured triangulated surfaces defined by the normal and vertices. This geometry format is used by 3D printers and it has been created by: the CUBIT software, MATLAB scripts, and C coding. All the Monte Carlo simulations have been performed using the ENDF/B-VII.0 nuclear data library. Both MCNP and SERPENT share the same geometry specifications, which describe the facility details without using any material homogenization. Three different configurations have been studied with different number of fuel rods. The three fuel configurations use 216, 245, or 280 fuel rods, respectively. The numerical simulations show that the agreement between SERPENT and MCNP results is within few tens of pcms.

Topological excitations and Monte-Carlo simulation of the Abelian-Higgs model

International Nuclear Information System (INIS)

Ranft, J.

1981-01-01

The phase structure and topological excitations, in particular the magnetic monopole current density, are investigated in a Monte-Carlo simulation of the lattice version of the four-dimensional Abelian-Higgs model. The monopole current density is found to be large in the confinement phase and rapidly decreasing in the Coulomb and Higgs phases. This result supports the view that confinement is neglected with the condensation of monopole-antimonopole pairs

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.

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

Energy Technology Data Exchange (ETDEWEB)

Alcaraz, Olga; Trullàs, Joaquim, E-mail: quim.trullas@upc.edu [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord UPC B4-B5, 08034 Barcelona (Spain); Tahara, Shuta [Department of Physics and Earth Sciences, Faculty of Science, University of the Ryukyus, Okinawa 903-0213 (Japan); Kawakita, Yukinobu [J-PARC Center, Japan Atomic Energy Agency (JAEA), Ibaraki 319-1195 (Japan); Takeda, Shin’ichi [Department of Physics, Faculty of Sciences, Kyushu University, Fukuoka 819-0395 (Japan)

2016-09-07

The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å{sup −1} related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

International Nuclear Information System (INIS)

Alcaraz, Olga; Trullàs, Joaquim; Tahara, Shuta; Kawakita, Yukinobu; Takeda, Shin’ichi

2016-01-01

The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å −1 related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

Science.gov (United States)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently

Environmental dose rate heterogeneity of beta radiation and its implications for luminescence dating: Monte Carlo modelling and experimental validation

DEFF Research Database (Denmark)

Nathan, R.P.; Thomas, P.J.; Jain, M.

2003-01-01

and identify the likely size of these effects on D-e distributions. The study employs the MCNP 4C Monte Carlo electron/photon transport model, supported by an experimental validation of the code in several case studies. We find good agreement between the experimental measurements and the Monte Carlo...

Shell model Monte Carlo investigation of rare earth nuclei

International Nuclear Information System (INIS)

White, J. A.; Koonin, S. E.; Dean, D. J.

2000-01-01

We utilize the shell model Monte Carlo method to study the structure of rare earth nuclei. This work demonstrates the first systematic full oscillator shell with intruder calculations in such heavy nuclei. Exact solutions of a pairing plus quadrupole Hamiltonian are compared with the static path approximation in several dysprosium isotopes from A=152 to 162, including the odd mass A=153. Some comparisons are also made with Hartree-Fock-Bogoliubov results from Baranger and Kumar. Basic properties of these nuclei at various temperatures and spin are explored. These include energy, deformation, moments of inertia, pairing channel strengths, band crossing, and evolution of shell model occupation numbers. Exact level densities are also calculated and, in the case of 162 Dy, compared with experimental data. (c) 2000 The American Physical Society

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.

The Physical Models and Statistical Procedures Used in the RACER Monte Carlo Code

International Nuclear Information System (INIS)

Sutton, T.M.; Brown, F.B.; Bischoff, F.G.; MacMillan, D.B.; Ellis, C.L.; Ward, J.T.; Ballinger, C.T.; Kelly, D.J.; Schindler, L.

1999-01-01

This report describes the MCV (Monte Carlo - Vectorized)Monte Carlo neutron transport code [Brown, 1982, 1983; Brown and Mendelson, 1984a]. MCV is a module in the RACER system of codes that is used for Monte Carlo reactor physics analysis. The MCV module contains all of the neutron transport and statistical analysis functions of the system, while other modules perform various input-related functions such as geometry description, material assignment, output edit specification, etc. MCV is very closely related to the 05R neutron Monte Carlo code [Irving et al., 1965] developed at Oak Ridge National Laboratory. 05R evolved into the 05RR module of the STEMB system, which was the forerunner of the RACER system. Much of the overall logic and physics treatment of 05RR has been retained and, indeed, the original verification of MCV was achieved through comparison with STEMB results. MCV has been designed to be very computationally efficient [Brown, 1981, Brown and Martin, 1984b; Brown, 1986]. It was originally programmed to make use of vector-computing architectures such as those of the CDC Cyber- 205 and Cray X-MP. MCV was the first full-scale production Monte Carlo code to effectively utilize vector-processing capabilities. Subsequently, MCV was modified to utilize both distributed-memory [Sutton and Brown, 1994] and shared memory parallelism. The code has been compiled and run on platforms ranging from 32-bit UNIX workstations to clusters of 64-bit vector-parallel supercomputers. The computational efficiency of the code allows the analyst to perform calculations using many more neutron histories than is practical with most other Monte Carlo codes, thereby yielding results with smaller statistical uncertainties. MCV also utilizes variance reduction techniques such as survival biasing, splitting, and rouletting to permit additional reduction in uncertainties. While a general-purpose neutron Monte Carlo code, MCV is optimized for reactor physics calculations. It has the

City Logistics Modeling Efforts : Trends and Gaps - A Review

NARCIS (Netherlands)

Anand, N.R.; Quak, H.J.; Van Duin, J.H.R.; Tavasszy, L.A.

2012-01-01

In this paper, we present a review of city logistics modeling efforts reported in the literature for urban freight analysis. The review framework takes into account the diversity and complexity found in the present-day city logistics practice. Next, it covers the different aspects in the modeling

Monte Carlo simulation of diblock copolymer microphases by means of a 'fast' off-lattice model

DEFF Research Database (Denmark)

Besold, Gerhard; Hassager, O.; Mouritsen, Ole G.

1999-01-01

We present a mesoscopic off-lattice model for the simulation of diblock copolymer melts by Monte Carlo techniques. A single copolymer molecule is modeled as a discrete Edwards chain consisting of two blocks with vertices of type A and B, respectively. The volume interaction is formulated in terms...

Modeling Replenishment of Ultrathin Liquid Perfluoro polyether Z Films on Solid Surfaces Using Monte Carlo Simulation

International Nuclear Information System (INIS)

Mayeed, M.S.; Kato, T.

2014-01-01

Applying the reptation algorithm to a simplified perfluoro polyether Z off-lattice polymer model an NVT Monte Carlo simulation has been performed. Bulk condition has been simulated first to compare the average radius of gyration with the bulk experimental results. Then the model is tested for its ability to describe dynamics. After this, it is applied to observe the replenishment of nano scale ultrathin liquid films on solid flat carbon surfaces. The replenishment rate for trenches of different widths (8, 12, and 16 nms for several molecular weights) between two films of perfluoro polyether Z from the Monte Carlo simulation is compared to that obtained solving the diffusion equation using the experimental diffusion coefficients of Ma et al. (1999), with room condition in both cases. Replenishment per Monte Carlo cycle seems to be a constant multiple of replenishment per second at least up to 2 nm replenished film thickness of the trenches over the carbon surface. Considerable good agreement has been achieved here between the experimental results and the dynamics of molecules using reptation moves in the ultrathin liquid films on solid surfaces.

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)

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

Status of Monte Carlo at Los Alamos

International Nuclear Information System (INIS)

Thompson, W.L.; Cashwell, E.D.

1980-01-01

At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time

Monte Carlo tools for Beyond the Standard Model Physics , April 14-16

DEFF Research Database (Denmark)

Badger...[], Simon; Christensen, Christian Holm; Dalsgaard, Hans Hjersing

2011-01-01

This workshop aims to gather together theorists and experimentalists interested in developing and using Monte Carlo tools for Beyond the Standard Model Physics in an attempt to be prepared for the analysis of data focusing on the Large Hadron Collider. Since a large number of excellent tools....... To identify promising models (or processes) for which the tools have not yet been constructed and start filling up these gaps. To propose ways to streamline the process of going from models to events, i.e. to make the process more user-friendly so that more people can get involved and perform serious collider...

Monte Carlo modeling of fiber-scintillator flow-cell radiation detector geometry

International Nuclear Information System (INIS)

Rucker, T.L.; Ross, H.H.; Tennessee Univ., Knoxville; Schweitzer, G.K.

1988-01-01

A Monte Carlo computer calculation is described which models the geometric efficiency of a fiber-scintillator flow-cell radiation detector designed to detect radiolabeled compounds in liquid chromatography eluates. By using special mathematical techniques, an efficiency prediction with a precision of 1% is obtained after generating only 1000 random events. Good agreement is seen between predicted and experimental efficiency except for very low energy beta emission where the geometric limitation on efficiency is overcome by pulse height limitations which the model does not consider. The modeling results show that in the test system, the detection efficiency for low energy beta emitters is limited primarily by light generation and collection rather than geometry. (orig.)

Adaptive Multilevel Monte Carlo Simulation

KAUST Repository

Hoel, H

2011-08-23

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

Modelling the IRSN's radio-photo-luminescent dosimeter using the MCPNX Monte Carlo code

International Nuclear Information System (INIS)

Hocine, N.; Donadille, L.; Huet, Ch.; Itie, Ch.

2010-01-01

The authors report the modelling of the new radio-photo-luminescent (RPL) dosimeter of the IRSN using the MCPNX Monte Carlo code. The Hp(10) and Hp(0, 07) dose equivalents are computed for different irradiation configurations involving photonic beams (gamma and X) defined according to the ISO 4037-1 standard. Results are compared to experimental measurements performed on the RPL dosimeter. The agreement is good and the model is thus validated

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...

Studies on top-quark Monte Carlo modelling for Top2016

CERN Document Server

The ATLAS collaboration

2016-01-01

This note summarises recent studies on Monte Carlo simulation setups of top-quark pair production used by the ATLAS experiment and presents a new method to deal with interference effects for the $Wt$ single-top-quark production which is compared against previous techniques. The main focus for the top-quark pair production is on the improvement of the modelling of the Powheg generator interfaced to the Pythia8 and Herwig7 shower generators. The studies are done using unfolded data at centre-of-mass energies of 7, 8, and 13 TeV.

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

Science.gov (United States)

Zhang, Zhiyong

2014-12-01

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

A Monte Carlo study of the two-dimensional melting mechanism

NARCIS (Netherlands)

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

1983-01-01

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

Statistical implications in Monte Carlo depletions - 051

International Nuclear Information System (INIS)

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

2010-01-01

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

Extrapolation method in the Monte Carlo Shell Model and its applications

International Nuclear Information System (INIS)

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

2011-01-01

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

A monte carlo simulation model for the steady-state plasma in the scrape-off layer

International Nuclear Information System (INIS)

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

1995-12-01

A new Monte Carlo simulation model for the scrape-off layer (SOL) plasma is proposed to investigate a feasibility of so-called 'high temperature divertor operation'. In the model, Coulomb collision effect is accurately described by a nonlinear Monte Carlo collision operator; a conductive heat flux into the SOL is effectively modelled via randomly exchanging the source particles and SOL particles; secondary electrons are included. The steady state of the SOL plasma, which satisfies particle and energy balances and the neutrality constraint, is determined in terms of total particle and heat fluxes across the separatrix, the edge plasma temperature, the secondary electron emission rate, and the SOL size. The model gives gross features of the SOL such as plasma temperatures and densities, the total sheath potential drop, and the sheath energy transmission factor. The simulations are performed for collisional SOL plasma to confirm the validity of the proposed model. It is found that the potential drop and the electron energy transmission factor are in close agreement with theoretical predictions. The present model can provide primarily useful information for collisionless SOL plasma which is difficult to be understood analytically. (author)

The MC21 Monte Carlo Transport Code

International Nuclear Information System (INIS)

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

2007-01-01

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

Quantum Monte Carlo simulation for S=1 Heisenberg model with uniaxial anisotropy

International Nuclear Information System (INIS)

Tsukamoto, Mitsuaki; Batista, Cristian; Kawashima, Naoki

2007-01-01

We perform quantum Monte Carlo simulations for S=1 Heisenberg model with an uniaxial anisotropy. The system exhibits a phase transition as we vary the anisotropy and a long range order appears at a finite temperature when the exchange interaction J is comparable to the uniaxial anisotropy D. We investigate quantum critical phenomena of this model and obtain the line of the phase transition which approaches a power-law with logarithmic corrections at low temperature. We derive the form of logarithmic corrections analytically and compare it to our simulation results

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

Using a Monte Carlo model to predict dosimetric properties of small radiotherapy photon fields

International Nuclear Information System (INIS)

Scott, Alison J. D.; Nahum, Alan E.; Fenwick, John D.

2008-01-01

Accurate characterization of small-field dosimetry requires measurements to be made with precisely aligned specialized detectors and is thus time consuming and error prone. This work explores measurement differences between detectors by using a Monte Carlo model matched to large-field data to predict properties of smaller fields. Measurements made with a variety of detectors have been compared with calculated results to assess their validity and explore reasons for differences. Unshielded diodes are expected to produce some of the most useful data, as their small sensitive cross sections give good resolution whilst their energy dependence is shown to vary little with depth in a 15 MV linac beam. Their response is shown to be constant with field size over the range 1-10 cm, with a correction of 3% needed for a field size of 0.5 cm. BEAMnrc has been used to create a 15 MV beam model, matched to dosimetric data for square fields larger than 3 cm, and producing small-field profiles and percentage depth doses (PDDs) that agree well with unshielded diode data for field sizes down to 0.5 cm. For fields sizes of 1.5 cm and above, little detector-to-detector variation exists in measured output factors, however for a 0.5 cm field a relative spread of 18% is seen between output factors measured with different detectors--values measured with the diamond and pinpoint detectors lying below that of the unshielded diode, with the shielded diode value being higher. Relative to the corrected unshielded diode measurement, the Monte Carlo modeled output factor is 4.5% low, a discrepancy that is probably due to the focal spot fluence profile and source occlusion modeling. The large-field Monte Carlo model can, therefore, currently be used to predict small-field profiles and PDDs measured with an unshielded diode. However, determination of output factors for the smallest fields requires a more detailed model of focal spot fluence and source occlusion.

Learning of state-space models with highly informative observations: A tempered sequential Monte Carlo solution

Science.gov (United States)

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

2018-05-01

Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems. Some problems of this type that were previously intractable can now be solved on standard personal computers thanks to recent advances in Monte Carlo methods. In particular, for learning of unknown parameters in nonlinear state-space models, methods based on the particle filter (a Monte Carlo method) have proven very useful. A notoriously challenging problem, however, still occurs when the observations in the state-space model are highly informative, i.e. when there is very little or no measurement noise present, relative to the amount of process noise. The particle filter will then struggle in estimating one of the basic components for probabilistic learning, namely the likelihood p (data | parameters). To this end we suggest an algorithm which initially assumes that there is substantial amount of artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we, in the end, recover the original problem or possibly a very close approximation of it. The main component in our algorithm is a sequential Monte Carlo (SMC) sampler, which gives our proposed method a clear resemblance to the SMC2 method. Another natural link is also made to the ideas underlying the approximate Bayesian computation (ABC). We illustrate it with numerical examples, and in particular show promising results for a challenging Wiener-Hammerstein benchmark problem.

Monte Carlo study of radiation-induced demagnetization using the two-dimensional Ising model

International Nuclear Information System (INIS)

Samin, Adib; Cao, Lei

2015-01-01

A simple radiation-damage model based on the Ising model for magnets is proposed to study the effects of radiation on the magnetism of permanent magnets. The model is studied in two dimensions using a Monte Carlo simulation, and it accounts for the radiation through the introduction of a localized heat pulse. The model exhibits qualitative agreement with experimental results, and it clearly elucidates the role that the coercivity and the radiation particle’s energy play in the process. A more quantitative agreement with experiment will entail accounting for the long-range dipole–dipole interactions and the crystalline anisotropy.

Monte Carlo study of radiation-induced demagnetization using the two-dimensional Ising model

Energy Technology Data Exchange (ETDEWEB)

Samin, Adib; Cao, Lei

2015-10-01

A simple radiation-damage model based on the Ising model for magnets is proposed to study the effects of radiation on the magnetism of permanent magnets. The model is studied in two dimensions using a Monte Carlo simulation, and it accounts for the radiation through the introduction of a localized heat pulse. The model exhibits qualitative agreement with experimental results, and it clearly elucidates the role that the coercivity and the radiation particle’s energy play in the process. A more quantitative agreement with experiment will entail accounting for the long-range dipole–dipole interactions and the crystalline anisotropy.

State-to-state models of vibrational relaxation in Direct Simulation Monte Carlo (DSMC)

Science.gov (United States)

Oblapenko, G. P.; Kashkovsky, A. V.; Bondar, Ye A.

2017-02-01

In the present work, the application of state-to-state models of vibrational energy exchanges to the Direct Simulation Monte Carlo (DSMC) is considered. A state-to-state model for VT transitions of vibrational energy in nitrogen and oxygen, based on the application of the inverse Laplace transform to results of quasiclassical trajectory calculations (QCT) of vibrational energy transitions, along with the Forced Harmonic Oscillator (FHO) state-to-state model is implemented in DSMC code and applied to flows around blunt bodies. Comparisons are made with the widely used Larsen-Borgnakke model and the in uence of multi-quantum VT transitions is assessed.

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

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)

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

Machine Learning Approach for Software Reliability Growth Modeling with Infinite Testing Effort Function

Directory of Open Access Journals (Sweden)

Subburaj Ramasamy

2017-01-01

Full Text Available Reliability is one of the quantifiable software quality attributes. Software Reliability Growth Models (SRGMs are used to assess the reliability achieved at different times of testing. Traditional time-based SRGMs may not be accurate enough in all situations where test effort varies with time. To overcome this lacuna, test effort was used instead of time in SRGMs. In the past, finite test effort functions were proposed, which may not be realistic as, at infinite testing time, test effort will be infinite. Hence in this paper, we propose an infinite test effort function in conjunction with a classical Nonhomogeneous Poisson Process (NHPP model. We use Artificial Neural Network (ANN for training the proposed model with software failure data. Here it is possible to get a large set of weights for the same model to describe the past failure data equally well. We use machine learning approach to select the appropriate set of weights for the model which will describe both the past and the future data well. We compare the performance of the proposed model with existing model using practical software failure data sets. The proposed log-power TEF based SRGM describes all types of failure data equally well and also improves the accuracy of parameter estimation more than existing TEF and can be used for software release time determination as well.

A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

KAUST Repository

Dao, Ngocanh; Genton, Marc G.

2014-01-01

Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte

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

DEFF Research Database (Denmark)

Nonejad, Nima

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

Monte Carlo modelling of a-Si EPID response: The effect of spectral variations with field size and position

International Nuclear Information System (INIS)

Parent, Laure; Seco, Joao; Evans, Phil M.; Fielding, Andrew; Dance, David R.

2006-01-01

This study focused on predicting the electronic portal imaging device (EPID) image of intensity modulated radiation treatment (IMRT) fields in the absence of attenuation material in the beam with Monte Carlo methods. As IMRT treatments consist of a series of segments of various sizes that are not always delivered on the central axis, large spectral variations may be observed between the segments. The effect of these spectral variations on the EPID response was studied with fields of various sizes and off-axis positions. A detailed description of the EPID was implemented in a Monte Carlo model. The EPID model was validated by comparing the EPID output factors for field sizes between 1x1 and 26x26 cm 2 at the isocenter. The Monte Carlo simulations agreed with the measurements to within 1.5%. The Monte Carlo model succeeded in predicting the EPID response at the center of the fields of various sizes and offsets to within 1% of the measurements. Large variations (up to 29%) of the EPID response were observed between the various offsets. The EPID response increased with field size and with field offset for most cases. The Monte Carlo model was then used to predict the image of a simple test IMRT field delivered on the beam axis and with an offset. A variation of EPID response up to 28% was found between the on- and off-axis delivery. Finally, two clinical IMRT fields were simulated and compared to the measurements. For all IMRT fields, simulations and measurements agreed within 3%--0.2 cm for 98% of the pixels. The spectral variations were quantified by extracting from the spectra at the center of the fields the total photon yield (Y total ), the photon yield below 1 MeV (Y low ), and the percentage of photons below 1 MeV (P low ). For the studied cases, a correlation was shown between the EPID response variation and Y total , Y low , and P low

Monte Carlo techniques in diagnostic and therapeutic nuclear medicine

International Nuclear Information System (INIS)

Zaidi, H.

2002-01-01

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

Simplest Validation of the HIJING Monte Carlo Model

CERN Document Server

Uzhinsky, V.V.

2003-01-01

Fulfillment of the energy-momentum conservation law, as well as the charge, baryon and lepton number conservation is checked for the HIJING Monte Carlo program in $pp$-interactions at $\\sqrt{s}=$ 200, 5500, and 14000 GeV. It is shown that the energy is conserved quite well. The transverse momentum is not conserved, the deviation from zero is at the level of 1--2 GeV/c, and it is connected with the hard jet production. The deviation is absent for soft interactions. Charge, baryon and lepton numbers are conserved. Azimuthal symmetry of the Monte Carlo events is studied, too. It is shown that there is a small signature of a "flow". The situation with the symmetry gets worse for nucleus-nucleus interactions.

Monte Carlo impurity transport modeling in the DIII-D transport

International Nuclear Information System (INIS)

Evans, T.E.; Finkenthal, D.F.

1998-04-01

A description of the carbon transport and sputtering physics contained in the Monte Carlo Impurity (MCI) transport code is given. Examples of statistically significant carbon transport pathways are examined using MCI's unique tracking visualizer and a mechanism for enhanced carbon accumulation on the high field side of the divertor chamber is discussed. Comparisons between carbon emissions calculated with MCI and those measured in the DIII-D tokamak are described. Good qualitative agreement is found between 2D carbon emission patterns calculated with MCI and experimentally measured carbon patterns. While uncertainties in the sputtering physics, atomic data, and transport models have made quantitative comparisons with experiments more difficult, recent results using a physics based model for physical and chemical sputtering has yielded simulations with about 50% of the total carbon radiation measured in the divertor. These results and plans for future improvement in the physics models and atomic data are discussed

Estimation of inspection effort

International Nuclear Information System (INIS)

Mullen, M.F.; Wincek, M.A.

1979-06-01

An overview of IAEA inspection activities is presented, and the problem of evaluating the effectiveness of an inspection is discussed. Two models are described - an effort model and an effectiveness model. The effort model breaks the IAEA's inspection effort into components; the amount of effort required for each component is estimated; and the total effort is determined by summing the effort for each component. The effectiveness model quantifies the effectiveness of inspections in terms of probabilities of detection and quantities of material to be detected, if diverted over a specific period. The method is applied to a 200 metric ton per year low-enriched uranium fuel fabrication facility. A description of the model plant is presented, a safeguards approach is outlined, and sampling plans are calculated. The required inspection effort is estimated and the results are compared to IAEA estimates. Some other applications of the method are discussed briefly. Examples are presented which demonstrate how the method might be useful in formulating guidelines for inspection planning and in establishing technical criteria for safeguards implementation

Shell-model Monte Carlo simulations of the BCS-BEC crossover in few-fermion systems

DEFF Research Database (Denmark)

Zinner, Nikolaj Thomas; Mølmer, Klaus; Özen, C.

2009-01-01

We study a trapped system of fermions with a zero-range two-body interaction using the shell-model Monte Carlo method, providing ab initio results for the low particle number limit where mean-field theory is not applicable. We present results for the N-body energies as function of interaction...

A Monte Carlo Investigation of the Box-Cox Model and a Nonlinear Least Squares Alternative.

OpenAIRE

Showalter, Mark H

1994-01-01

This paper reports a Monte Carlo study of the Box-Cox model and a nonlinear least squares alternative. Key results include the following: the transformation parameter in the Box-Cox model appears to be inconsistently estimated in the presence of conditional heteroskedasticity; the constant term in both the Box-Cox and the nonlinear least squares models is poorly estimated in small samples; conditional mean forecasts tend to underestimate their true value in the Box-Cox model when the transfor...

New-generation Monte Carlo shell model for the K computer era

International Nuclear Information System (INIS)

Shimizu, Noritaka; Abe, Takashi; Yoshida, Tooru; Otsuka, Takaharu; Tsunoda, Yusuke; Utsuno, Yutaka; Mizusaki, Takahiro; Honma, Michio

2012-01-01

We present a newly enhanced version of the Monte Carlo shell-model (MCSM) method by incorporating the conjugate gradient method and energy-variance extrapolation. This new method enables us to perform large-scale shell-model calculations that the direct diagonalization method cannot reach. This new-generation framework of the MCSM provides us with a powerful tool to perform very advanced large-scale shell-model calculations on current massively parallel computers such as the K computer. We discuss the validity of this method in ab initio calculations of light nuclei, and propose a new method to describe the intrinsic wave function in terms of the shell-model picture. We also apply this new MCSM to the study of neutron-rich Cr and Ni isotopes using conventional shell-model calculations with an inert 40 Ca core and discuss how the magicity of N = 28, 40, 50 remains or is broken. (author)

Hamiltonian Monte Carlo study of (1+1)-dimensional models with restricted supersymmetry on the lattice

International Nuclear Information System (INIS)

Ranft, J.; Schiller, A.

1984-01-01

Lattice versions with restricted suppersymmetry of simple (1+1)-dimensional supersymmetric models are numerically studied using a local hamiltonian Monte Carlo method. The pattern of supersymmetry breaking closely follows the expectations of Bartels and Bronzan obtain in an alternative lattice formulation. (orig.)

Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

Science.gov (United States)

Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

2012-01-01

Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

Bayesian Monte Carlo method

International Nuclear Information System (INIS)

Rajabalinejad, M.

2010-01-01

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

Ensemble bayesian model averaging using markov chain Monte Carlo sampling

Energy Technology Data Exchange (ETDEWEB)

Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL

2008-01-01

Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.

A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

KAUST Repository

Dao, Ngocanh

2014-04-03

Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, B [Northwestern Memorial Hospital, Chicago, IL (United States); Georgia Institute of Technology, Atlanta, GA (Georgia); Wang, C [Georgia Institute of Technology, Atlanta, GA (Georgia)

2016-06-15

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities. These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell

Monte Carlo study of the phase diagram for the two-dimensional Z(4) model

International Nuclear Information System (INIS)

Carneiro, G.M.; Pol, M.E.; Zagury, N.

1982-05-01

The phase diagram of the two-dimensional Z(4) model on a square lattice is determined using a Monte Carlo method. The results of this simulation confirm the general features of the phase diagram predicted theoretically for the ferromagnetic case, and show the existence of a new phase with perpendicular order. (Author) [pt

Monte Carlo Transport for Electron Thermal Transport

Science.gov (United States)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2015-11-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Monte Carlo modelling of Schottky diode for rectenna simulation

Science.gov (United States)

Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.

2017-09-01

Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

International Nuclear Information System (INIS)

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

2016-01-01

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

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-29

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-28

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

Monte Carlo modelling of large scale NORM sources using MCNP.

Science.gov (United States)

Wallace, J D

2013-12-01

The representative Monte Carlo modelling of large scale planar sources (for comparison to external environmental radiation fields) is undertaken using substantial diameter and thin profile planar cylindrical sources. The relative impact of source extent, soil thickness and sky-shine are investigated to guide decisions relating to representative geometries. In addition, the impact of source to detector distance on the nature of the detector response, for a range of source sizes, has been investigated. These investigations, using an MCNP based model, indicate a soil cylinder of greater than 20 m diameter and of no less than 50 cm depth/height, combined with a 20 m deep sky section above the soil cylinder, are needed to representatively model the semi-infinite plane of uniformly distributed NORM sources. Initial investigation of the effect of detector placement indicate that smaller source sizes may be used to achieve a representative response at shorter source to detector distances. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

The First 24 Years of Reverse Monte Carlo Modelling, Budapest, Hungary, 20-22 September 2012

Science.gov (United States)

Keen, David A.; Pusztai, László

2013-11-01

This special issue contains a collection of papers reflecting the content of the fifth workshop on reverse Monte Carlo (RMC) methods, held in a hotel on the banks of the Danube in the Budapest suburbs in the autumn of 2012. Over fifty participants gathered to hear talks and discuss a broad range of science based on the RMC technique in very convivial surroundings. Reverse Monte Carlo modelling is a method for producing three-dimensional disordered structural models in quantitative agreement with experimental data. The method was developed in the late 1980s and has since achieved wide acceptance within the scientific community [1], producing an average of over 90 papers and 1200 citations per year over the last five years. It is particularly suitable for the study of the structures of liquid and amorphous materials, as well as the structural analysis of disordered crystalline systems. The principal experimental data that are modelled are obtained from total x-ray or neutron scattering experiments, using the reciprocal space structure factor and/or the real space pair distribution function (PDF). Additional data might be included from extended x-ray absorption fine structure spectroscopy (EXAFS), Bragg peak intensities or indeed any measured data that can be calculated from a three-dimensional atomistic model. It is this use of total scattering (diffuse and Bragg), rather than just the Bragg peak intensities more commonly used for crystalline structure analysis, which enables RMC modelling to probe the often important deviations from the average crystal structure, to probe the structures of poorly crystalline or nanocrystalline materials, and the local structures of non-crystalline materials where only diffuse scattering is observed. This flexibility across various condensed matter structure-types has made the RMC method very attractive in a wide range of disciplines, as borne out in the contents of this special issue. It is however important to point out that since

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

International Nuclear Information System (INIS)

Wagner, J.C.; Haghighat, A.

1998-01-01

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

Microcanonical Monte Carlo

International Nuclear Information System (INIS)

Creutz, M.

1986-01-01

The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena

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

DEFF Research Database (Denmark)

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

2002-01-01

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

Monte Carlo studies of high-transverse-energy hadronic interactions

International Nuclear Information System (INIS)

Corcoran, M.D.

1985-01-01

A four-jet Monte Carlo calculation has been used to simulate hadron-hadron interactions which deposit high transverse energy into a large-solid-angle calorimeter and limited solid-angle regions of the calorimeter. The calculation uses first-order QCD cross sections to generate two scattered jets and also produces beam and target jets. Field-Feynman fragmentation has been used in the hadronization. The sensitivity of the results to a few features of the Monte Carlo program has been studied. The results are found to be very sensitive to the method used to ensure overall energy conservation after the fragmentation of the four jets is complete. Results are also sensitive to the minimum momentum transfer in the QCD subprocesses and to the distribution of p/sub T/ to the jet axis and the multiplicities in the fragmentation. With reasonable choices of these features of the Monte Carlo program, good agreement with data at Fermilab/CERN SPS energies is obtained, comparable to the agreement achieved with more sophisticated parton-shower models. With other choices, however, the calculation gives qualitatively different results which are in strong disagreement with the data. These results have important implications for extracting physics conclusions from Monte Carlo calculations. It is not possible to test the validity of a particular model or distinguish between different models unless the Monte Carlo results are unambiguous and different models exhibit clearly different behavior

V and V Efforts of Auroral Precipitation Models: Preliminary Results

Science.gov (United States)

Zheng, Yihua; Kuznetsova, Masha; Rastaetter, Lutz; Hesse, Michael

2011-01-01

Auroral precipitation models have been valuable both in terms of space weather applications and space science research. Yet very limited testing has been performed regarding model performance. A variety of auroral models are available, including empirical models that are parameterized by geomagnetic indices or upstream solar wind conditions, now casting models that are based on satellite observations, or those derived from physics-based, coupled global models. In this presentation, we will show our preliminary results regarding V&V efforts of some of the models.

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.

Exploring cluster Monte Carlo updates with Boltzmann machines.

Science.gov (United States)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Exploring cluster Monte Carlo updates with Boltzmann machines

Science.gov (United States)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Clinical Management and Burden of Prostate Cancer: A Markov Monte Carlo Model

Science.gov (United States)

Sanyal, Chiranjeev; Aprikian, Armen; Cury, Fabio; Chevalier, Simone; Dragomir, Alice

2014-01-01

Background Prostate cancer (PCa) is the most common non-skin cancer among men in developed countries. Several novel treatments have been adopted by healthcare systems to manage PCa. Most of the observational studies and randomized trials on PCa have concurrently evaluated fewer treatments over short follow-up. Further, preceding decision analytic models on PCa management have not evaluated various contemporary management options. Therefore, a contemporary decision analytic model was necessary to address limitations to the literature by synthesizing the evidence on novel treatments thereby forecasting short and long-term clinical outcomes. Objectives To develop and validate a Markov Monte Carlo model for the contemporary clinical management of PCa, and to assess the clinical burden of the disease from diagnosis to end-of-life. Methods A Markov Monte Carlo model was developed to simulate the management of PCa in men 65 years and older from diagnosis to end-of-life. Health states modeled were: risk at diagnosis, active surveillance, active treatment, PCa recurrence, PCa recurrence free, metastatic castrate resistant prostate cancer, overall and PCa death. Treatment trajectories were based on state transition probabilities derived from the literature. Validation and sensitivity analyses assessed the accuracy and robustness of model predicted outcomes. Results Validation indicated model predicted rates were comparable to observed rates in the published literature. The simulated distribution of clinical outcomes for the base case was consistent with sensitivity analyses. Predicted rate of clinical outcomes and mortality varied across risk groups. Life expectancy and health adjusted life expectancy predicted for the simulated cohort was 20.9 years (95%CI 20.5–21.3) and 18.2 years (95% CI 17.9–18.5), respectively. Conclusion Study findings indicated contemporary management strategies improved survival and quality of life in patients with PCa. This model could be used

Validating a virtual source model based in Monte Carlo Method for profiles and percent deep doses calculation

Energy Technology Data Exchange (ETDEWEB)

Del Nero, Renata Aline; Yoriyaz, Hélio [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Nakandakari, Marcos Vinicius Nakaoka, E-mail: hyoriyaz@ipen.br, E-mail: marcos.sake@gmail.com [Hospital Beneficência Portuguesa de São Paulo, SP (Brazil)

2017-07-01

The Monte Carlo method for radiation transport data has been adapted for medical physics application. More specifically, it has received more attention in clinical treatment planning with the development of more efficient computer simulation techniques. In linear accelerator modeling by the Monte Carlo method, the phase space data file (phsp) is used a lot. However, to obtain precision in the results, it is necessary detailed information about the accelerator's head and commonly the supplier does not provide all the necessary data. An alternative to the phsp is the Virtual Source Model (VSM). This alternative approach presents many advantages for the clinical Monte Carlo application. This is the most efficient method for particle generation and can provide an accuracy similar when the phsp is used. This research propose a VSM simulation with the use of a Virtual Flattening Filter (VFF) for profiles and percent deep doses calculation. Two different sizes of open fields (40 x 40 cm² and 40√2 x 40√2 cm²) were used and two different source to surface distance (SSD) were applied: the standard 100 cm and custom SSD of 370 cm, which is applied in radiotherapy treatments of total body irradiation. The data generated by the simulation was analyzed and compared with experimental data to validate the VSM. This current model is easy to build and test. (author)

Implementation of 3D models in the Monte Carlo code MCNP

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1998-12-01

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

Three-dimensional Monte Carlo model of pulsed-laser treatment of cutaneous vascular lesions

Science.gov (United States)

Milanič, Matija; Majaron, Boris

2011-12-01

We present a three-dimensional Monte Carlo model of optical transport in skin with a novel approach to treatment of side boundaries of the volume of interest. This represents an effective way to overcome the inherent limitations of ``escape'' and ``mirror'' boundary conditions and enables high-resolution modeling of skin inclusions with complex geometries and arbitrary irradiation patterns. The optical model correctly reproduces measured values of diffuse reflectance for normal skin. When coupled with a sophisticated model of thermal transport and tissue coagulation kinetics, it also reproduces realistic values of radiant exposure thresholds for epidermal injury and for photocoagulation of port wine stain blood vessels in various skin phototypes, with or without application of cryogen spray cooling.

Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

NARCIS (Netherlands)

Vrugt, J.A.; Braak, ter C.J.F.; Clark, M.P.; Hyman, J.M.; Robinson, B.A.

2008-01-01

There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled

[Psychosocial factors at work and cardiovascular diseases: contribution of the Effort-Reward Imbalance model].

Science.gov (United States)

Niedhammer, I; Siegrist, J

1998-11-01

The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.

Modeling of the YALINA booster facility by the Monte Carlo code MONK

International Nuclear Information System (INIS)

Talamo, A.; Gohar, Y.; Kondev, F.; Kiyavitskaya, H.; Serafimovich, I.; Bournos, V.; Fokov, Y.; Routkovskaya, C.

2007-01-01

The YALINA-Booster facility has been modeled according to the benchmark specifications defined for the IAEA activity without any geometrical homogenization using the Monte Carlo codes MONK and MCNP/MCNPX/MCB. The MONK model perfectly matches the MCNP one. The computational analyses have been extended through the MCB code, which is an extension of the MCNP code with burnup capability because of its additional feature for analyzing source driven multiplying assemblies. The main neutronics arameters of the YALINA-Booster facility were calculated using these computer codes with different nuclear data libraries based on ENDF/B-VI-0, -6, JEF-2.2, and JEF-3.1.

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

Science.gov (United States)

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

2017-03-01

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

Review of the Monte Carlo and deterministic codes in radiation protection and dosimetry

Energy Technology Data Exchange (ETDEWEB)

Tagziria, H

2000-02-01

Modelling a physical system can be carried out either stochastically or deterministically. An example of the former method is the Monte Carlo technique, in which statistically approximate methods are applied to exact models. No transport equation is solved as individual particles are simulated and some specific aspect (tally) of their average behaviour is recorded. The average behaviour of the physical system is then inferred using the central limit theorem. In contrast, deterministic codes use mathematically exact methods that are applied to approximate models to solve the transport equation for the average particle behaviour. The physical system is subdivided in boxes in the phase-space system and particles are followed from one box to the next. The smaller the boxes the better the approximations become. Although the Monte Carlo method has been used for centuries, its more recent manifestation has really emerged from the Manhattan project of the Word War II. Its invention is thought to be mainly due to Metropolis, Ulah (through his interest in poker), Fermi, von Neuman andRichtmeyer. Over the last 20 years or so, the Monte Carlo technique has become a powerful tool in radiation transport. This is due to users taking full advantage of richer cross section data, more powerful computers and Monte Carlo techniques for radiation transport, with high quality physics and better known source spectra. This method is a common sense approach to radiation transport and its success and popularity is quite often also due to necessity, because measurements are not always possible or affordable. In the Monte Carlo method, which is inherently realistic because nature is statistical, a more detailed physics is made possible by isolation of events while rather elaborate geometries can be modelled. Provided that the physics is correct, a simulation is exactly analogous to an experimenter counting particles. In contrast to the deterministic approach, however, a disadvantage of the

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

International Nuclear Information System (INIS)

Bultinck, E; Bogaerts, A

2011-01-01

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

Development and application of the automated Monte Carlo biasing procedure in SAS4

International Nuclear Information System (INIS)

Tang, J.S.; Broadhead, B.L.

1993-01-01

An automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete-ordinates calculation are used to generate biasing parameters for a three-dimensional Monte Carlo calculation. The automated procedure consisting of cross-section processing, adjoint flux determination, biasing parameter generation, and the initiation of a MORSE-SGC/S Monte Carlo calculation has been implemented in the SAS4 module of the SCALE computer code system. The automated procedure has been used extensively in the investigation of both computational and experimental benchmarks for the NEACRP working group on shielding assessment of transportation packages. The results of these studies indicate that with the automated biasing procedure, Monte Carlo shielding calculations of spent fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost. The systematic biasing approach described in this paper can also be applied to other similar shielding problems

Monte Carlo Modeling the UCN τ Magneto-Gravitational Trap

Science.gov (United States)

Holley, A. T.; UCNτ Collaboration

2016-09-01

The current uncertainty in our knowledge of the free neutron lifetime is dominated by the nearly 4 σ discrepancy between complementary ``beam'' and ``bottle'' measurement techniques. An incomplete assessment of systematic effects is the most likely explanation for this difference and must be addressed in order to realize the potential of both approaches. The UCN τ collaboration has constructed a large-volume magneto-gravitational trap that eliminates the material interactions which complicated the interpretation of previous bottle experiments. This is accomplished using permanent NdFeB magnets in a bowl-shaped Halbach array to confine polarized UCN from the sides and below and the earth's gravitational field to trap them from above. New in situ detectors that count surviving UCN provide a means of empirically assessing residual systematic effects. The interpretation of that data, and its implication for experimental configurations with enhanced precision, can be bolstered by Monte Carlo models of the current experiment which provide the capability for stable tracking of trapped UCN and detailed modeling of their polarization. Work to develop such models and their comparison with data acquired during our first extensive set of systematics studies will be discussed.

Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system

International Nuclear Information System (INIS)

Penchev, Petar; Maeder, Ulf; Fiebich, Martin; Zink, Klemens; University Hospital Marburg

2015-01-01

The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and X-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.

Dynamic bounds coupled with Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

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

2011-02-15

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

Coded aperture optimization using Monte Carlo simulations

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

Collectivity in heavy nuclei in the shell model Monte Carlo approach

International Nuclear Information System (INIS)

Özen, C.; Alhassid, Y.; Nakada, H.

2014-01-01

The microscopic description of collectivity in heavy nuclei in the framework of the configuration-interaction shell model has been a major challenge. The size of the model space required for the description of heavy nuclei prohibits the use of conventional diagonalization methods. We have overcome this difficulty by using the shell model Monte Carlo (SMMC) method, which can treat model spaces that are many orders of magnitude larger than those that can be treated by conventional methods. We identify a thermal observable that can distinguish between vibrational and rotational collectivity and use it to describe the crossover from vibrational to rotational collectivity in families of even-even rare-earth isotopes. We calculate the state densities in these nuclei and find them to be in close agreement with experimental data. We also calculate the collective enhancement factors of the corresponding level densities and find that their decay with excitation energy is correlated with the pairing and shape phase transitions. (author)

Optical roughness BRDF model for reverse Monte Carlo simulation of real material thermal radiation transfer.

Science.gov (United States)

Su, Peiran; Eri, Qitai; Wang, Qiang

2014-04-10

Optical roughness was introduced into the bidirectional reflectance distribution function (BRDF) model to simulate the reflectance characteristics of thermal radiation. The optical roughness BRDF model stemmed from the influence of surface roughness and wavelength on the ray reflectance calculation. This model was adopted to simulate real metal emissivity. The reverse Monte Carlo method was used to display the distribution of reflectance rays. The numerical simulations showed that the optical roughness BRDF model can calculate the wavelength effect on emissivity and simulate the real metal emissivity variance with incidence angles.

A Monte Carlo Simulation Framework for Testing Cosmological Models

Directory of Open Access Journals (Sweden)

Heymann Y.

2014-10-01

Full Text Available We tested alternative cosmologies using Monte Carlo simulations based on the sam- pling method of the zCosmos galactic survey. The survey encompasses a collection of observable galaxies with respective redshifts that have been obtained for a given spec- troscopic area of the sky. Using a cosmological model, we can convert the redshifts into light-travel times and, by slicing the survey into small redshift buckets, compute a curve of galactic density over time. Because foreground galaxies obstruct the images of more distant galaxies, we simulated the theoretical galactic density curve using an average galactic radius. By comparing the galactic density curves of the simulations with that of the survey, we could assess the cosmologies. We applied the test to the expanding-universe cosmology of de Sitter and to a dichotomous cosmology.

A Monte Carlo Simulation approach for the modeling of free-molecule squeeze-film damping of flexible microresonators

KAUST Repository

Leung, Roger; Cheung, Howard; Gang, Hong; Ye, Wenjing

2010-01-01

Squeeze-film damping on microresonators is a significant damping source even when the surrounding gas is highly rarefied. This article presents a general modeling approach based on Monte Carlo (MC) simulations for the prediction of squeeze

Report on International Collaboration Involving the FE Heater and HG-A Tests at Mont Terri

Energy Technology Data Exchange (ETDEWEB)

Houseworth, Jim [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rutqvist, Jonny [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Asahina, Daisuke [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Fei [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Vilarrasa, Victor [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liu, Hui-Hai [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Birkholzer, Jens [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2013-11-01

Nuclear waste programs outside of the US have focused on different host rock types for geological disposal of high-level radioactive waste. Several countries, including France, Switzerland, Belgium, and Japan are exploring the possibility of waste disposal in shale and other clay-rich rock that fall within the general classification of argillaceous rock. This rock type is also of interest for the US program because the US has extensive sedimentary basins containing large deposits of argillaceous rock. LBNL, as part of the DOE-NE Used Fuel Disposition Campaign, is collaborating on some of the underground research laboratory (URL) activities at the Mont Terri URL near Saint-Ursanne, Switzerland. The Mont Terri project, which began in 1995, has developed a URL at a depth of about 300 m in a stiff clay formation called the Opalinus Clay. Our current collaboration efforts include two test modeling activities for the FE heater test and the HG-A leak-off test. This report documents results concerning our current modeling of these field tests. The overall objectives of these activities include an improved understanding of and advanced relevant modeling capabilities for EDZ evolution in clay repositories and the associated coupled processes, and to develop a technical basis for the maximum allowable temperature for a clay repository.

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

International Nuclear Information System (INIS)

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

2000-01-01

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

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 Monte Carlo study of time-aggregation in continuous-time and discrete-time parametric hazard models.

NARCIS (Netherlands)

Hofstede, ter F.; Wedel, M.

1998-01-01

This study investigates the effects of time aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to various continuous and discrete-time processes, and aggregated into daily, weekly and monthly intervals. These data are

Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer.

Science.gov (United States)

Castonguay, Thomas C; Wang, Feng

2008-03-28

In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

Monte Carlo modelling of the Belgian materials testing reactor BR2: present status

International Nuclear Information System (INIS)

Verboomen, B.; Aoust, Th.; Raedt, Ch. de; Beeckmans de West-Meerbeeck, A.

2001-01-01

A very detailed 3-D MCNP-4B model of the BR2 reactor was developed to perform all neutron and gamma calculations needed for the design of new experimental irradiation rigs. The Monte Carlo model of BR2 includes the nearly exact geometrical representation of fuel elements (now with their axially varying burn-up), of partially inserted control and regulating rods, of experimental devices and of radioisotope production rigs. The multiple level-geometry possibilities of MCNP-4B are fully exploited to obtain sufficiently flexible tools to cope with the very changing core loading. (orig.)

Modeling the cathode region of noble gas mixture discharges using Monte Carlo simulation

International Nuclear Information System (INIS)

Donko, Z.; Janossy, M.

1992-10-01

A model of the cathode dark space of DC glow discharges was developed in order to study the effects caused by mixing small amounts (≤2%) of other noble gases (Ne, Ar, Kr and Xe) to He. The motion of charged particles was described by Monte Carlo simulation. Several discharge parameters (electron and ion energy distribution functions, electron and ion current densities, reduced ionization coefficients, and current density-voltage characteristics) were obtained. Small amounts of admixtures were found to modify significantly the discharge parameters. Current density-voltage characteristics obtained from the model showed good agreement with experimental data. (author) 40 refs.; 14 figs

Preliminary validation of a Monte Carlo model for IMRT fields

International Nuclear Information System (INIS)

Wright, Tracy; Lye, Jessica; Mohammadi, Mohammad

2011-01-01

Full text: A Monte Carlo model of an Elekta linac, validated for medium to large (10-30 cm) symmetric fields, has been investigated for small, irregular and asymmetric fields suitable for IMRT treatments. The model has been validated with field segments using radiochromic film in solid water. The modelled positions of the multileaf collimator (MLC) leaves have been validated using EBT film, In the model, electrons with a narrow energy spectrum are incident on the target and all components of the linac head are included. The MLC is modelled using the EGSnrc MLCE component module. For the validation, a number of single complex IMRT segments with dimensions approximately 1-8 cm were delivered to film in solid water (see Fig, I), The same segments were modelled using EGSnrc by adjusting the MLC leaf positions in the model validated for 10 cm symmetric fields. Dose distributions along the centre of each MLC leaf as determined by both methods were compared. A picket fence test was also performed to confirm the MLC leaf positions. 95% of the points in the modelled dose distribution along the leaf axis agree with the film measurement to within 1%/1 mm for dose difference and distance to agreement. Areas of most deviation occur in the penumbra region. A system has been developed to calculate the MLC leaf positions in the model for any planned field size.

A Monte Carlo modeling alternative for the API Gamma Ray Calibration Facility.

Science.gov (United States)

Galford, J E

2017-04-01

The gamma ray pit at the API Calibration Facility, located on the University of Houston campus, defines the API unit for natural gamma ray logs used throughout the petroleum logging industry. Future use of the facility is uncertain. An alternative method is proposed to preserve the gamma ray API unit definition as an industry standard by using Monte Carlo modeling to obtain accurate counting rate-to-API unit conversion factors for gross-counting and spectral gamma ray tool designs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue.

Science.gov (United States)

Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A

2011-11-01

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.

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.

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

A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

Science.gov (United States)

Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

2018-04-01

Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

Monte Carlo simulations with Symanzik's improved actions in the lattice 0(3) non-linear sigma-model

International Nuclear Information System (INIS)

Berg, B.; Montvay, I.; Meyer, S.

1983-10-01

The scaling properties of the lattice 0(3) non-linear delta-model are studied. The mass-gap, energy-momentum dispersion, correlation functions are measured by numerical Monte Carlo methods. Symanzik's tree-level and 1-loop improved actions are compared to the standard (nearest neigbour) action. (orig.)

Monte Carlo - Advances and Challenges

International Nuclear Information System (INIS)

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

2008-01-01

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

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…

A Monte Carlo-based treatment-planning tool for ion beam therapy

CERN Document Server

Böhlen, T T; Dosanjh, M; Ferrari, A; Haberer, T; Parodi, K; Patera, V; Mairan, A

2013-01-01

Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), theMCTP tool is able to perform TP studies u...

Study of the validity of a combined potential model using the Hybrid Reverse Monte Carlo method in Fluoride glass system

Directory of Open Access Journals (Sweden)

M. Kotbi

2013-03-01

Full Text Available The choice of appropriate interaction models is among the major disadvantages of conventional methods such as Molecular Dynamics (MD and Monte Carlo (MC simulations. On the other hand, the so-called Reverse Monte Carlo (RMC method, based on experimental data, can be applied without any interatomic and/or intermolecular interactions. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term into the acceptance criteria. This method is referred to as the Hybrid Reverse Monte Carlo (HRMC method. The idea of this paper is to test the validity of a combined potential model of coulomb and Lennard-Jones in a Fluoride glass system BaMnMF7 (M = Fe,V using HRMC method. The results show a good agreement between experimental and calculated characteristics, as well as a meaningful improvement in partial pair distribution functions (PDFs. We suggest that this model should be used in calculating the structural properties and in describing the average correlations between components of fluoride glass or a similar system. We also suggest that HRMC could be useful as a tool for testing the interaction potential models, as well as for conventional applications.

Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models

Science.gov (United States)

Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.

2013-12-01

We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

Energy Technology Data Exchange (ETDEWEB)

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

Directory of Open Access Journals (Sweden)

Gareth W. Peters

2017-09-01

Full Text Available The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method to calculate capital allocations for a general insurance company is developed, with a focus on coherent capital allocation that is compliant with the Swiss Solvency Test. The data used is based on the balance sheet of a representative stylized company. For each line of business in that company, allocations are calculated for the one-year risk with dependencies based on correlations given by the Swiss Solvency Test. Two different approaches for dealing with parameter uncertainty are discussed and simulation algorithms based on (pseudo-marginal Sequential Monte Carlo algorithms are described and their efficiency is analysed.

Neutrino oscillation parameter sampling with MonteCUBES

Science.gov (United States)

Blennow, Mattias; Fernandez-Martinez, Enrique

2010-01-01

We present MonteCUBES ("Monte Carlo Utility Based Experiment Simulator"), a software package designed to sample the neutrino oscillation parameter space through Markov Chain Monte Carlo algorithms. MonteCUBES makes use of the GLoBES software so that the existing experiment definitions for GLoBES, describing long baseline and reactor experiments, can be used with MonteCUBES. MonteCUBES consists of two main parts: The first is a C library, written as a plug-in for GLoBES, implementing the Markov Chain Monte Carlo algorithm to sample the parameter space. The second part is a user-friendly graphical Matlab interface to easily read, analyze, plot and export the results of the parameter space sampling. Program summaryProgram title: MonteCUBES (Monte Carlo Utility Based Experiment Simulator) Catalogue identifier: AEFJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFJ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 69 634 No. of bytes in distributed program, including test data, etc.: 3 980 776 Distribution format: tar.gz Programming language: C Computer: MonteCUBES builds and installs on 32 bit and 64 bit Linux systems where GLoBES is installed Operating system: 32 bit and 64 bit Linux RAM: Typically a few MBs Classification: 11.1 External routines: GLoBES [1,2] and routines/libraries used by GLoBES Subprograms used:Cat Id ADZI_v1_0, Title GLoBES, Reference CPC 177 (2007) 439 Nature of problem: Since neutrino masses do not appear in the standard model of particle physics, many models of neutrino masses also induce other types of new physics, which could affect the outcome of neutrino oscillation experiments. In general, these new physics imply high-dimensional parameter spaces that are difficult to explore using classical methods such as multi-dimensional projections and minimizations, such as those

Monte Carlo methods

Directory of Open Access Journals (Sweden)

Bardenet Rémi

2013-07-01

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

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

ATLAS Data Challenge 2 A massive Monte Carlo production on the GRID

CERN Document Server

González de la Hoz, S; Lozano, J; Salt, J; Fassi, F; March, L; Adams, D; Deng, W; Nevski, P; Smith, J; Yu, D; Zhao, X; Poulard, G; Goossens, L; Nairz, A; Branco, M; Benekos, N C; Sturrock, R; Walker, R; Vetterli, M; Chudoba, J; Tas, P; Duckeck, G; Kennedy, J; Nielsen, J; Wäänänen, A; Bernardet, K; Negri, G; Rebatto, D; De Salvo, A; Perini, L; Vaccarossa, L; Ould-Saada, F; Read, A; Merino, G; Smirnova, O G; Ellert, M; Quing, D; Brochu, F; Gieraltowski, J; Youssef, S; De, K; Oz-turk, N; Sosebee, M; Severini, H; Gardner, R; Mambeli, M; Smirnov, Y; European Grid Conference

2005-01-01

The study and validation of the ATLAS Computing Model started three years ago and will continue for few years in the context of the so-called Data Chal-lenges (DC). DC1 was conducted during 2002-03; the main goals achieved were to set up the simulation data production infrastructure in a real worldwide collaborative effort and to gain experience in exercising an ATLAS wide production model. DC2 (from May until December 2004) is divided into three phases: (i) generate Monte Carlo data using GEANT4 on three different Grid projects: LCG, GRID3 and NorduGrid; (ii) simulate the first pass recon-struction of real data expected in 2007, and (iii) test the Distributed Analysis model. Experience with the use of the system in world-wide DC2 production of ten million events will be presented. We also present how the three Grid fla-vours are operated. Finally we discuss the first prototypes of Distributed Analy-sis systems.

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

Science.gov (United States)

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

2017-12-01

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

Transfer-Matrix Monte Carlo Estimates of Critical Points in the Simple Cubic Ising, Planar and Heisenberg Models

NARCIS (Netherlands)

Nightingale, M.P.; Blöte, H.W.J.

1996-01-01

The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the statistical noise can be reduced considerably by a similarity

Monte Carlo simulations of the NJL model near the nonzero temperature phase transition

International Nuclear Information System (INIS)

Strouthos, Costas; Christofi, Stavros

2005-01-01

We present results from numerical simulations of the Nambu-Jona-Lasinio model with an SU(2)xSU(2) chiral symmetry and N c = 4,8, and 16 quark colors at nonzero temperature. We performed the simulations by utilizing the hybrid Monte Carlo and hybrid Molecular Dynamics algorithms. We show that the model undergoes a second order phase transition. The critical exponents measured are consistent with the classical 3d O(4) universality class and hence in accordance with the dimensional reduction scenario. We also show that the Ginzburg region is suppressed by a factor of 1/N c in accordance with previous analytical predictions. (author)

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)

Monte Carlo Simulation Of The Portfolio-Balance Model Of Exchange Rates: Finite Sample Properties Of The GMM Estimator

OpenAIRE

Hong-Ghi Min

2011-01-01

Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.

Effort-reward imbalance and organisational injustice among aged nurses: a moderated mediation model.

Science.gov (United States)

Topa, Gabriela; Guglielmi, Dina; Depolo, Marco

2016-09-01

To test the effort-reward imbalance model among older nurses, expanding it to include the moderation of overcommitment and age in the stress-health complaints relationship, mediated by organisational injustice. The theoretical framework included the effort-reward imbalance, the uncertainty management and the socio-emotional selectivity models. Employing a two-wave design, the participants were 255 nurses aged 45 years and over, recruited from four large hospitals in Spain (Madrid and Basque Country). The direct effect of imbalance on health complaints was supported: it was significant when overcommitment was low but not when it was high. Organisational injustice mediated the influence of effort-reward imbalance on health complaints. The conditional effect of the mediation of organisational injustice was significant in three of the overcommitment/age conditions but it weakened, becoming non-significant, when the level of overcommitment was low and age was high. The study tested the model in nursing populations and expanded it to the settings of occupational health and safety at work. The results of this study highlight the importance of effort-reward imbalance and organisational justice for creating healthy work environments. © 2016 John Wiley & Sons Ltd.

Modeling of the 3RS tau protein with self-consistent field method and Monte Carlo simulation

NARCIS (Netherlands)

Leermakers, F.A.M.; Jho, Y.S.; Zhulina, E.B.

2010-01-01

Using a model with amino acid resolution of the 196 aa N-terminus of the 3RS tau protein, we performed both a Monte Carlo study and a complementary self-consistent field (SCF) analysis to obtain detailed information on conformational properties of these moieties near a charged plane (mimicking the

Synergies Between Grace and Regional Atmospheric Modeling Efforts

Science.gov (United States)

Kusche, J.; Springer, A.; Ohlwein, C.; Hartung, K.; Longuevergne, L.; Kollet, S. J.; Keune, J.; Dobslaw, H.; Forootan, E.; Eicker, A.

2014-12-01

In the meteorological community, efforts converge towards implementation of high-resolution (precipitation, evapotranspiration and runoff data; confirming that the model does favorably at representing observations. We show that after GRACE-derived bias correction, basin-average hydrological conditions prior to 2002 can be reconstructed better than before. Next, comparing GRACE with CLM forced by EURO-CORDEX simulations allows identifying processes needing improvement in the model. Finally, we compare COSMO-EU atmospheric pressure, a proxy for mass corrections in satellite gravimetry, with ERA-Interim over Europe at timescales shorter/longer than 1 month, and spatial scales below/above ERA resolution. We find differences between regional and global model more pronounced at high frequencies, with magnitude at sub-grid scale and larger scale corresponding to 1-3 hPa (1-3 cm EWH); relevant for the assessment of post-GRACE concepts.

Monte Carlo steps per spin vs. time in the master equation II: Glauber kinetics for the infinite-range ising model in a static magnetic field

Energy Technology Data Exchange (ETDEWEB)

Oh, Suhk Kun [Chungbuk National University, Chungbuk (Korea, Republic of)

2006-01-15

As an extension of our previous work on the relationship between time in Monte Carlo simulation and time in the continuous master equation in the infinit-range Glauber kinetic Ising model in the absence of any magnetic field, we explored the same model in the presence of a static magnetic field. Monte Carlo steps per spin as time in the MC simulations again turns out to be proportional to time in the master equation for the model in relatively larger static magnetic fields at any temperature. At and near the critical point in a relatively smaller magnetic field, the model exhibits a significant finite-size dependence, and the solution to the Suzuki-Kubo differential equation stemming from the master equation needs to be re-scaled to fit the Monte Carlo steps per spin for the system with different numbers of spins.

Monte Carlo numerical study of lattice field theories

International Nuclear Information System (INIS)

Gan Cheekwan; Kim Seyong; Ohta, Shigemi

1997-01-01

The authors are interested in the exact first-principle calculations of quantum field theories which are indeed exact ones. For quantum chromodynamics (QCD) at low energy scale, a nonperturbation method is needed, and the only known such method is the lattice method. The path integral can be evaluated by putting a system on a finite 4-dimensional volume and discretizing space time continuum into finite points, lattice. The continuum limit is taken by making the lattice infinitely fine. For evaluating such a finite-dimensional integral, the Monte Carlo numerical estimation of the path integral can be obtained. The calculation of light hadron mass in quenched lattice QCD with staggered quarks, 3-dimensional Thirring model calculation and the development of self-test Monte Carlo method have been carried out by using the RIKEN supercomputer. The motivation of this study, lattice QCD formulation, continuum limit, Monte Carlo update, hadron propagator, light hadron mass, auto-correlation and source size dependence are described on lattice QCD. The phase structure of the 3-dimensional Thirring model for a small 8 3 lattice has been mapped. The discussion on self-test Monte Carlo method is described again. (K.I.)

Restricted primitive model for electrical double layers: modified HNC theory of density profiles and Monte Carlo study of differential capacitance

International Nuclear Information System (INIS)

Ballone, P.; Pastore, G.; Tosi, M.P.

1986-02-01

Interfacial properties of an ionic fluid next to a uniformly charged planar wall are studied in the restricted primitive model by both theoretical and Monte Carlo methods. The system is a 1:1 fluid of equisized charged hard spheres in a state appropriate to 1M aqueous electrolyte solutions. The interfacial density profiles of counterions and coions are evaluated by extending the hypernetted chain approximation (HNC) to include the leading bridge diagrams for the wall-ion correlations. The theoretical results compare well with those of grand canonical Monte Carlo computations of Torrie and Valleau over the whole range of surface charge density considered by these authors, thus resolving the earlier disagreement between statistical mechanical theories and simulation data at large charge densities. In view of the importance of the model as a testing ground for theories of the diffuse layer, the Monte Carlo calculations are tested by considering alternative choices for the basic simulation cell and are extended so as to allow an evaluation of the differential capacitance of the model interface by two independent methods. These involve numerical differentiation of the mean potential drop as a function of the surface charge density or alternatively an appropriate use of a fluctuation theory formula for the capacitance. The results of these two Monte Carlo approaches consistently indicate an initially smooth increase of the diffuse layer capacitance followed by structure at large charge densities, this behaviour being connected with layering of counterions as already revealed in the density profiles reported by Torrie and Valleau. (author)

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

Science.gov (United States)

Brdar, S.; Seifert, A.

2018-01-01

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

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

Science.gov (United States)

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

2018-05-01

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

Integrating multiple distribution models to guide conservation efforts of an endangered toad

Science.gov (United States)

Treglia, Michael L.; Fisher, Robert N.; Fitzgerald, Lee A.

2015-01-01

Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.

Monte Carlo investigation of the dosimetric properties of the new 103Pd BrachySeedTMPd-103 Model Pd-1 source

International Nuclear Information System (INIS)

Chan, Gordon H.; Prestwich, William V.

2002-01-01

Recently, 103 Pd brachytherapy sources have been increasingly used for interstitial implants as an alternative to 125 I sources. The BrachySeed TM Pd-103 Model Pd-1 seed is one of the latest in a series of new brachytherapy sources that have become available commercially. The dosimetric properties of the seed were investigated by Monte Carlo simulation, which was performed using the Integrated Tiger Series CYLTRAN code. Following the AAPM Task Group 43 formalism, the dose rate constant, radial dose function, and anisotropy parameters were determined. The dose rate constant, Λ, was calculated to be 0.613±3% cGy h -1 U -1 . This air kerma strength was derived from Monte Carlo simulation using the point extrapolation method. The radial dose function, g(r), was computed at distances from 0.15 to 10 cm. The anisotropy function, F(r,θ), and anisotropy factor, φ an (r), were calculated at distances from 0.5 to 7 cm. The anisotropy constant, φ(bar sign) an , was determined to be 0.978, which is closer to unity than most other 103 Pd seeds, indicating a high degree of uniformity in dose distribution. The dose rate constant and the radial dose function were also investigated by analytical modeling, which served as an independent evaluation of the Monte Carlo data, and found to be in good agreement with the Monte Carlo results

The effort-reward imbalance work-stress model and daytime salivary cortisol and dehydroepiandrosterone (DHEA) among Japanese women.

Science.gov (United States)

Ota, Atsuhiko; Mase, Junji; Howteerakul, Nopporn; Rajatanun, Thitipat; Suwannapong, Nawarat; Yatsuya, Hiroshi; Ono, Yuichiro

2014-09-17

We examined the influence of work-related effort-reward imbalance and overcommitment to work (OC), as derived from Siegrist's Effort-Reward Imbalance (ERI) model, on the hypothalamic-pituitary-adrenocortical (HPA) axis. We hypothesized that, among healthy workers, both cortisol and dehydroepiandrosterone (DHEA) secretion would be increased by effort-reward imbalance and OC and, as a result, cortisol-to-DHEA ratio (C/D ratio) would not differ by effort-reward imbalance or OC. The subjects were 115 healthy female nursery school teachers. Salivary cortisol, DHEA, and C/D ratio were used as indexes of HPA activity. Mixed-model analyses of variance revealed that neither the interaction between the ERI model indicators (i.e., effort, reward, effort-to-reward ratio, and OC) and the series of measurement times (9:00, 12:00, and 15:00) nor the main effect of the ERI model indicators was significant for daytime salivary cortisol, DHEA, or C/D ratio. Multiple linear regression analyses indicated that none of the ERI model indicators was significantly associated with area under the curve of daytime salivary cortisol, DHEA, or C/D ratio. We found that effort, reward, effort-reward imbalance, and OC had little influence on daytime variation patterns, levels, or amounts of salivary HPA-axis-related hormones. Thus, our hypotheses were not supported.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-08-20

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

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.

Image based Monte Carlo modeling for computational phantom

International Nuclear Information System (INIS)

Cheng, M.; Wang, W.; Zhao, K.; Fan, Y.; Long, P.; Wu, Y.

2013-01-01

Full text of the publication follows. The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verification of the models for Monte Carlo (MC) simulation are very tedious, error-prone and time-consuming. In addition, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling. The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients (Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection. (authors)

Sampling from a polytope and hard-disk Monte Carlo

International Nuclear Information System (INIS)

Kapfer, Sebastian C; Krauth, Werner

2013-01-01

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

Kinetic Monte-Carlo modeling of hydrogen retention and re-emission from Tore Supra deposits

International Nuclear Information System (INIS)

Rai, A.; Schneider, R.; Warrier, M.; Roubin, P.; Martin, C.; Richou, M.

2009-01-01

A multi-scale model has been developed to study the reactive-diffusive transport of hydrogen in porous graphite [A. Rai, R. Schneider, M. Warrier, J. Nucl. Mater. (submitted for publication). http://dx.doi.org/10.1016/j.jnucmat.2007.08.013.]. The deposits found on the leading edge of the neutralizer of Tore Supra are multi-scale in nature, consisting of micropores with typical size lower than 2 nm (∼11%), mesopores (∼5%) and macropores with a typical size more than 50 nm [C. Martin, M. Richou, W. Sakaily, B. Pegourie, C. Brosset, P. Roubin, J. Nucl. Mater. 363-365 (2007) 1251]. Kinetic Monte-Carlo (KMC) has been used to study the hydrogen transport at meso-scales. Recombination rate and the diffusion coefficient calculated at the meso-scale was used as an input to scale up and analyze the hydrogen transport at macro-scale. A combination of KMC and MCD (Monte-Carlo diffusion) method was used at macro-scales. Flux dependence of hydrogen recycling has been studied. The retention and re-emission analysis of the model has been extended to study the chemical erosion process based on the Kueppers-Hopf cycle [M. Wittmann, J. Kueppers, J. Nucl. Mater. 227 (1996) 186].

Monte Carlo simulations of phase transitions and lattice dynamics in an atom-phonon model for spin transition compounds

International Nuclear Information System (INIS)

Apetrei, Alin Marian; Enachescu, Cristian; Tanasa, Radu; Stoleriu, Laurentiu; Stancu, Alexandru

2010-01-01

We apply here the Monte Carlo Metropolis method to a known atom-phonon coupling model for 1D spin transition compounds (STC). These inorganic molecular systems can switch under thermal or optical excitation, between two states in thermodynamical competition, i.e. high spin (HS) and low spin (LS). In the model, the ST units (molecules) are linked by springs, whose elastic constants depend on the spin states of the neighboring atoms, and can only have three possible values. Several previous analytical papers considered a unique average value for the elastic constants (mean-field approximation) and obtained phase diagrams and thermal hysteresis loops. Recently, Monte Carlo simulation papers, taking into account all three values of the elastic constants, obtained thermal hysteresis loops, but no phase diagrams. Employing Monte Carlo simulation, in this work we obtain the phase diagram at T=0 K, which is fully consistent with earlier analytical work; however it is more complex. The main difference is the existence of two supplementary critical curves that mark a hysteresis zone in the phase diagram. This explains the pressure hysteresis curves at low temperature observed experimentally and predicts a 'chemical' hysteresis in STC at very low temperatures. The formation and the dynamics of the domains are also discussed.

A Monte Carlo study of the ''minus sign problem'' in the t-J model using an intel IPSC/860 hypercube

International Nuclear Information System (INIS)

Kovarik, M.D.; Barnes, T.; Tennessee Univ., Knoxville, TN

1993-01-01

We describe a Monte Carlo simulation of the 2-dimensional t-J model on an Intel iPSC/860 hypercube. The problem studied is the determination of the dispersion relation of a dynamical hole in the t-J model of the high temperature superconductors. Since this problem involves the motion of many fermions in more than one spatial dimensions, it is representative of the class of systems that suffer from the ''minus sign problem'' of dynamical fermions which has made Monte Carlo simulation very difficult. We demonstrate that for small values of the hole hopping parameter one can extract the entire hole dispersion relation using the GRW Monte Carlo algorithm, which is a simulation of the Euclidean time Schroedinger equation, and present results on 4 x 4 and 6 x 6 lattices. We demonstrate that a qualitative picture at higher hopping parameters may be found by extrapolating weak hopping results where the minus sign problem is less severe. Generalization to physical hopping parameter values will only require use of an improved trial wavefunction for importance sampling

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

MCNP-X Monte Carlo Code Application for Mass Attenuation Coefficients of Concrete at Different Energies by Modeling 3 × 3 Inch NaI(Tl Detector and Comparison with XCOM and Monte Carlo Data

Directory of Open Access Journals (Sweden)

Huseyin Ozan Tekin

2016-01-01

Full Text Available Gamma-ray measurements in various research fields require efficient detectors. One of these research fields is mass attenuation coefficients of different materials. Apart from experimental studies, the Monte Carlo (MC method has become one of the most popular tools in detector studies. An NaI(Tl detector has been modeled, and, for a validation study of the modeled NaI(Tl detector, the absolute efficiency of 3 × 3 inch cylindrical NaI(Tl detector has been calculated by using the general purpose Monte Carlo code MCNP-X (version 2.4.0 and compared with previous studies in literature in the range of 661–2620 keV. In the present work, the applicability of MCNP-X Monte Carlo code for mass attenuation of concrete sample material as building material at photon energies 59.5 keV, 80 keV, 356 keV, 661.6 keV, 1173.2 keV, and 1332.5 keV has been tested by using validated NaI(Tl detector. The mass attenuation coefficients of concrete sample have been calculated. The calculated results agreed well with experimental and some other theoretical results. The results specify that this process can be followed to determine the data on the attenuation of gamma-rays with other required energies in other materials or in new complex materials. It can be concluded that data from Monte Carlo is a strong tool not only for efficiency studies but also for mass attenuation coefficients calculations.

Combinatorial nuclear level density by a Monte Carlo method

International Nuclear Information System (INIS)

Cerf, N.

1994-01-01

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

Efforts - Final technical report on task 4. Physical modelling calidation

DEFF Research Database (Denmark)

Andreasen, Jan Lasson; Olsson, David Dam; Christensen, T. W.

The present report is documentation for the work carried out in Task 4 at DTU Physical modelling-validation on the Brite/Euram project No. BE96-3340, contract No. BRPR-CT97-0398, with the title Enhanced Framework for forging design using reliable three-dimensional simulation (EFFORTS). The report...

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.

An opportunity cost model of subjective effort and task performance

Science.gov (United States)

Kurzban, Robert; Duckworth, Angela; Kable, Joseph W.; Myers, Justus

2013-01-01

Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternate explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost – that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternate explanations both for the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across subdisciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternate models might be empirically distinguished. PMID:24304775

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)

Kinetic Monte Carlo modeling of the efficiency roll-off in a multilayer white organic light-emitting device

NARCIS (Netherlands)

Mesta, M.; van Eersel, H.; Coehoorn, R.; Bobbert, P.A.

2016-01-01

Triplet-triplet annihilation (TTA) and triplet-polaron quenching (TPQ) in organic light-emitting devices (OLEDs) lead to a roll-off of the internal quantum efficiency (IQE) with increasing current density J. We employ a kinetic Monte Carlo modeling study to analyze the measured IQE and color balance

Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling

International Nuclear Information System (INIS)

Schaefer, C.; Jansen, A. P. J.

2013-01-01

We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

Benchmarking time-dependent neutron problems with Monte Carlo codes

International Nuclear Information System (INIS)

Couet, B.; Loomis, W.A.

1990-01-01

Many nuclear logging tools measure the time dependence of a neutron flux in a geological formation to infer important properties of the formation. The complex geometry of the tool and the borehole within the formation does not permit an exact deterministic modelling of the neutron flux behaviour. While this exact simulation is possible with Monte Carlo methods the computation time does not facilitate quick turnaround of results useful for design and diagnostic purposes. Nonetheless a simple model based on the diffusion-decay equation for the flux of neutrons of a single energy group can be useful in this situation. A combination approach where a Monte Carlo calculation benchmarks a deterministic model in terms of the diffusion constants of the neutrons propagating in the media and their flux depletion rates thus offers the possibility of quick calculation with assurance as to accuracy. We exemplify this approach with the Monte Carlo benchmarking of a logging tool problem, showing standoff and bedding response. (author)

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

Science.gov (United States)

Hanson, John M.; Beard, Bernard B.

2010-01-01

This paper is focused on applying Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically the verification must show that requirement "x" is met for at least "y" % of cases, with, say, 10% consumer risk or 90% confidence. Two particular aspects of making these runs for requirements verification will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase but that will be known for each assembled vehicle (can be used to determine the payload capability and overall behavior of that vehicle), other items that become known before or on flight day (can be used for flight day trajectory design and go/no go decision), and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met or not and enables the user to determine how many Monte Carlo samples are required. Order statistics is not new, but may not be known in general to the GN&C community. The methods also apply to determining the design values of parameters of interest in driving the vehicle design. The paper briefly discusses when it is desirable to fit a distribution to the experimental Monte Carlo results rather than using order statistics.

Monte Carlo Methods in ICF

Science.gov (United States)

Zimmerman, George B.

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

Monte Carlo methods in ICF

International Nuclear Information System (INIS)

Zimmerman, George B.

1997-01-01

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

Application of the three-component bidirectional reflectance distribution function model to Monte Carlo calculation of spectral effective emissivities of nonisothermal blackbody cavities.

Science.gov (United States)

Prokhorov, Alexander; Prokhorova, Nina I

2012-11-20

We applied the bidirectional reflectance distribution function (BRDF) model consisting of diffuse, quasi-specular, and glossy components to the Monte Carlo modeling of spectral effective emissivities for nonisothermal cavities. A method for extension of a monochromatic three-component (3C) BRDF model to a continuous spectral range is proposed. The initial data for this method are the BRDFs measured in the plane of incidence at a single wavelength and several incidence angles and directional-hemispherical reflectance measured at one incidence angle within a finite spectral range. We proposed the Monte Carlo algorithm for calculation of spectral effective emissivities for nonisothermal cavities whose internal surface is described by the wavelength-dependent 3C BRDF model. The results obtained for a cylindroconical nonisothermal cavity are discussed and compared with results obtained using the conventional specular-diffuse model.

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.

Transport appraisal and Monte Carlo simulation by use of the CBA-DK model

DEFF Research Database (Denmark)

Salling, Kim Bang; Leleur, Steen

2011-01-01

calculation, where risk analysis is carried out using Monte Carlo simulation. Special emphasis has been placed on the separation between inherent randomness in the modeling system and lack of knowledge. These two concepts have been defined in terms of variability (ontological uncertainty) and uncertainty......This paper presents the Danish CBA-DK software model for assessment of transport infrastructure projects. The assessment model is based on both a deterministic calculation following the cost-benefit analysis (CBA) methodology in a Danish manual from the Ministry of Transport and on a stochastic...... (epistemic uncertainty). After a short introduction to deterministic calculation resulting in some evaluation criteria a more comprehensive evaluation of the stochastic calculation is made. Especially, the risk analysis part of CBA-DK, with considerations about which probability distributions should be used...

SU-E-J-145: Validation of An Analytical Model for in Vivo Range Verification Using GATE Monte Carlo Simulation in Proton Therapy

International Nuclear Information System (INIS)

Lee, C; Lin, H; Chao, T; Hsiao, I; Chuang, K

2015-01-01

Purpose: Predicted PET images on the basis of analytical filtering approach for proton range verification has been successful developed and validated using FLUKA Monte Carlo (MC) codes and phantom measurements. The purpose of the study is to validate the effectiveness of analytical filtering model for proton range verification on GATE/GEANT4 Monte Carlo simulation codes. Methods: In this study, we performed two experiments for validation of predicted β+-isotope by the analytical model with GATE/GEANT4 simulations. The first experiments to evaluate the accuracy of predicting β+-yields as a function of irradiated proton energies. In second experiment, we simulate homogeneous phantoms of different materials irradiated by a mono-energetic pencil-like proton beam. The results of filtered β+-yields distributions by the analytical model is compared with those of MC simulated β+-yields in proximal and distal fall-off ranges. Results: The results investigate the distribution between filtered β+-yields and MC simulated β+-yields distribution in different conditions. First, we found that the analytical filtering can be applied over the whole range of the therapeutic energies. Second, the range difference between filtered β+-yields and MC simulated β+-yields at the distal fall-off region are within 1.5mm for all materials used. The findings validated the usefulness of analytical filtering model on range verification of proton therapy on GATE Monte Carlo simulations. In addition, there is a larger discrepancy between filtered prediction and MC simulated β+-yields using GATE code, especially in proximal region. This discrepancy might Result from the absence of wellestablished theoretical models for predicting the nuclear interactions. Conclusion: Despite the fact that large discrepancies of the distributions between MC-simulated and predicted β+-yields were observed, the study prove the effectiveness of analytical filtering model for proton range verification using

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-11-01

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

MCNP-REN a Monte Carlo tool for neutron detector design

CERN Document Server

Abhold, M E

2002-01-01

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

A continuation multilevel Monte Carlo algorithm

KAUST Repository

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

2014-01-01

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

History and future perspectives of the Monte Carlo shell model -from Alphleet to K computer-

International Nuclear Information System (INIS)

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

2013-01-01

We report a history of the developments of the Monte Carlo shell model (MCSM). The MCSM was proposed in order to perform large-scale shell-model calculations which direct diagonalization method cannot reach. Since 1999 PC clusters were introduced for parallel computation of the MCSM. Since 2011 we participated the High Performance Computing Infrastructure Strategic Program and developed a new MCSM code for current massively parallel computers such as K computer. We discuss future perspectives concerning a new framework and parallel computation of the MCSM by incorporating conjugate gradient method and energy-variance extrapolation

Monte Carlo modeling of neutron and gamma-ray imaging systems

International Nuclear Information System (INIS)

Hall, J.

1996-04-01

Detailed numerical prototypes are essential to design of efficient and cost-effective neutron and gamma-ray imaging systems. We have exploited the unique capabilities of an LLNL-developed radiation transport code (COG) to develop code modules capable of simulating the performance of neutron and gamma-ray imaging systems over a wide range of source energies. COG allows us to simulate complex, energy-, angle-, and time-dependent radiation sources, model 3-dimensional system geometries with ''real world'' complexity, specify detailed elemental and isotopic distributions and predict the responses of various types of imaging detectors with full Monte Carlo accuray. COG references detailed, evaluated nuclear interaction databases allowingusers to account for multiple scattering, energy straggling, and secondary particle production phenomena which may significantly effect the performance of an imaging system by may be difficult or even impossible to estimate using simple analytical models. This work presents examples illustrating the use of these routines in the analysis of industrial radiographic systems for thick target inspection, nonintrusive luggage and cargoscanning systems, and international treaty verification

Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model

Directory of Open Access Journals (Sweden)

Davide Viganò

2016-01-01

Full Text Available Compactness, reliability, readiness, and construction simplicity of solid rocket motors make them very appealing for commercial launcher missions and embarked systems. Solid propulsion grants high thrust-to-weight ratio, high volumetric specific impulse, and a Technology Readiness Level of 9. However, solid rocket systems are missing any throttling capability at run-time, since pressure-time evolution is defined at the design phase. This lack of mission flexibility makes their missions sensitive to deviations of performance from nominal behavior. For this reason, the reliability of predictions and reproducibility of performances represent a primary goal in this field. This paper presents an analysis of SRM performance uncertainties throughout the implementation of a quasi-1D numerical model of motor internal ballistics based on Shapiro’s equations. The code is coupled with a Monte Carlo algorithm to evaluate statistics and propagation of some peculiar uncertainties from design data to rocker performance parameters. The model has been set for the reproduction of a small-scale rocket motor, discussing a set of parametric investigations on uncertainty propagation across the ballistic model.

Recommender engine for continuous-time quantum Monte Carlo methods

Science.gov (United States)

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

2017-03-01

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

Monte Carlo Modeling Electronuclear Processes in Cascade Subcritical Reactor

CERN Document Server

Bznuni, S A; Zhamkochyan, V M; Polyanskii, A A; Sosnin, A N; Khudaverdian, A G

2000-01-01

Accelerator driven subcritical cascade reactor composed of the main thermal neutron reactor constructed analogous to the core of the VVER-1000 reactor and a booster-reactor, which is constructed similar to the core of the BN-350 fast breeder reactor, is taken as a model example. It is shown by means of Monte Carlo calculations that such system is a safe energy source (k_{eff}=0.94-0.98) and it is capable of transmuting produced radioactive wastes (neutron flux density in the thermal zone is PHI^{max} (r,z)=10^{14} n/(cm^{-2} s^{-1}), neutron flux in the fast zone is respectively equal PHI^{max} (r,z)=2.25 cdot 10^{15} n/(cm^{-2} s^{-1}) if the beam current of the proton accelerator is k_{eff}=0.98 and I=5.3 mA). Suggested configuration of the "cascade" reactor system essentially reduces the requirements on the proton accelerator current.

Monte Carlo Modeling of Crystal Channeling at High Energies

CERN Document Server

Schoofs, Philippe; Cerutti, Francesco

Charged particles entering a crystal close to some preferred direction can be trapped in the electromagnetic potential well existing between consecutive planes or strings of atoms. This channeling effect can be used to extract beam particles if the crystal is bent beforehand. Crystal channeling is becoming a reliable and efficient technique for collimating beams and removing halo particles. At CERN, the installation of silicon crystals in the LHC is under scrutiny by the UA9 collaboration with the goal of investigating if they are a viable option for the collimation system upgrade. This thesis describes a new Monte Carlo model of planar channeling which has been developed from scratch in order to be implemented in the FLUKA code simulating particle transport and interactions. Crystal channels are described through the concept of continuous potential taking into account thermal motion of the lattice atoms and using Moliere screening function. The energy of the particle transverse motion determines whether or n...

Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence.

Science.gov (United States)

Aoun, Bachir

2016-05-05

A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.

Grain-boundary melting: A Monte Carlo study

DEFF Research Database (Denmark)

Besold, Gerhard; Mouritsen, Ole G.

1994-01-01

Grain-boundary melting in a lattice-gas model of a bicrystal is studied by Monte Carlo simulation using the grand canonical ensemble. Well below the bulk melting temperature T(m), a disordered liquidlike layer gradually emerges at the grain boundary. Complete interfacial wetting can be observed...... when the temperature approaches T(m) from below. Monte Carlo data over an extended temperature range indicate a logarithmic divergence w(T) approximately - ln(T(m)-T) of the width of the disordered layer w, in agreement with mean-field theory....

Engineering local optimality in quantum Monte Carlo algorithms

Science.gov (United States)

Pollet, Lode; Van Houcke, Kris; Rombouts, Stefan M. A.

2007-08-01

Quantum Monte Carlo algorithms based on a world-line representation such as the worm algorithm and the directed loop algorithm are among the most powerful numerical techniques for the simulation of non-frustrated spin models and of bosonic models. Both algorithms work in the grand-canonical ensemble and can have a winding number larger than zero. However, they retain a lot of intrinsic degrees of freedom which can be used to optimize the algorithm. We let us guide by the rigorous statements on the globally optimal form of Markov chain Monte Carlo simulations in order to devise a locally optimal formulation of the worm algorithm while incorporating ideas from the directed loop algorithm. We provide numerical examples for the soft-core Bose-Hubbard model and various spin- S models.

Voxel2MCNP: a framework for modeling, simulation and evaluation of radiation transport scenarios for Monte Carlo codes

International Nuclear Information System (INIS)

Pölz, Stefan; Laubersheimer, Sven; Eberhardt, Jakob S; Harrendorf, Marco A; Keck, Thomas; Benzler, Andreas; Breustedt, Bastian

2013-01-01

The basic idea of Voxel2MCNP is to provide a framework supporting users in modeling radiation transport scenarios using voxel phantoms and other geometric models, generating corresponding input for the Monte Carlo code MCNPX, and evaluating simulation output. Applications at Karlsruhe Institute of Technology are primarily whole and partial body counter calibration and calculation of dose conversion coefficients. A new generic data model describing data related to radiation transport, including phantom and detector geometries and their properties, sources, tallies and materials, has been developed. It is modular and generally independent of the targeted Monte Carlo code. The data model has been implemented as an XML-based file format to facilitate data exchange, and integrated with Voxel2MCNP to provide a common interface for modeling, visualization, and evaluation of data. Also, extensions to allow compatibility with several file formats, such as ENSDF for nuclear structure properties and radioactive decay data, SimpleGeo for solid geometry modeling, ImageJ for voxel lattices, and MCNPX’s MCTAL for simulation results have been added. The framework is presented and discussed in this paper and example workflows for body counter calibration and calculation of dose conversion coefficients is given to illustrate its application. (paper)

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

Science.gov (United States)

Lecca, Paola

2018-01-01

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

Effect of burst and recombination models for Monte Carlo transport of interacting carriers in a-Se x-ray detectors on Swank noise

Energy Technology Data Exchange (ETDEWEB)

Fang, Yuan, E-mail: yuan.fang@fda.hhs.gov [Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993-0002 and Department of Electrical and Computer Engineering, The University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Karim, Karim S. [Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Badano, Aldo [Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993-0002 (United States)

2014-01-15

Purpose: The authors describe the modification to a previously developed Monte Carlo model of semiconductor direct x-ray detector required for studying the effect of burst and recombination algorithms on detector performance. This work provides insight into the effect of different charge generation models for a-Se detectors on Swank noise and recombination fraction. Methods: The proposed burst and recombination models are implemented in the Monte Carlo simulation package, ARTEMIS, developed byFang et al. [“Spatiotemporal Monte Carlo transport methods in x-ray semiconductor detectors: Application to pulse-height spectroscopy in a-Se,” Med. Phys. 39(1), 308–319 (2012)]. The burst model generates a cloud of electron-hole pairs based on electron velocity, energy deposition, and material parameters distributed within a spherical uniform volume (SUV) or on a spherical surface area (SSA). A simple first-hit (FH) and a more detailed but computationally expensive nearest-neighbor (NN) recombination algorithms are also described and compared. Results: Simulated recombination fractions for a single electron-hole pair show good agreement with Onsager model for a wide range of electric field, thermalization distance, and temperature. The recombination fraction and Swank noise exhibit a dependence on the burst model for generation of many electron-hole pairs from a single x ray. The Swank noise decreased for the SSA compared to the SUV model at 4 V/μm, while the recombination fraction decreased for SSA compared to the SUV model at 30 V/μm. The NN and FH recombination results were comparable. Conclusions: Results obtained with the ARTEMIS Monte Carlo transport model incorporating drift and diffusion are validated with the Onsager model for a single electron-hole pair as a function of electric field, thermalization distance, and temperature. For x-ray interactions, the authors demonstrate that the choice of burst model can affect the simulation results for the generation

Effect of burst and recombination models for Monte Carlo transport of interacting carriers in a-Se x-ray detectors on Swank noise

International Nuclear Information System (INIS)

Fang, Yuan; Karim, Karim S.; Badano, Aldo

2014-01-01

Purpose: The authors describe the modification to a previously developed Monte Carlo model of semiconductor direct x-ray detector required for studying the effect of burst and recombination algorithms on detector performance. This work provides insight into the effect of different charge generation models for a-Se detectors on Swank noise and recombination fraction. Methods: The proposed burst and recombination models are implemented in the Monte Carlo simulation package, ARTEMIS, developed byFang et al. [“Spatiotemporal Monte Carlo transport methods in x-ray semiconductor detectors: Application to pulse-height spectroscopy in a-Se,” Med. Phys. 39(1), 308–319 (2012)]. The burst model generates a cloud of electron-hole pairs based on electron velocity, energy deposition, and material parameters distributed within a spherical uniform volume (SUV) or on a spherical surface area (SSA). A simple first-hit (FH) and a more detailed but computationally expensive nearest-neighbor (NN) recombination algorithms are also described and compared. Results: Simulated recombination fractions for a single electron-hole pair show good agreement with Onsager model for a wide range of electric field, thermalization distance, and temperature. The recombination fraction and Swank noise exhibit a dependence on the burst model for generation of many electron-hole pairs from a single x ray. The Swank noise decreased for the SSA compared to the SUV model at 4 V/μm, while the recombination fraction decreased for SSA compared to the SUV model at 30 V/μm. The NN and FH recombination results were comparable. Conclusions: Results obtained with the ARTEMIS Monte Carlo transport model incorporating drift and diffusion are validated with the Onsager model for a single electron-hole pair as a function of electric field, thermalization distance, and temperature. For x-ray interactions, the authors demonstrate that the choice of burst model can affect the simulation results for the generation

SU-F-T-575: Verification of a Monte-Carlo Small Field SRS/SBRT Dose Calculation System

International Nuclear Information System (INIS)

Sudhyadhom, A; McGuinness, C; Descovich, M

2016-01-01

Purpose: To develop a methodology for validation of a Monte-Carlo dose calculation model for robotic small field SRS/SBRT deliveries. Methods: In a robotic treatment planning system, a Monte-Carlo model was iteratively optimized to match with beam data. A two-part analysis was developed to verify this model. 1) The Monte-Carlo model was validated in a simulated water phantom versus a Ray-Tracing calculation on a single beam collimator-by-collimator calculation. 2) The Monte-Carlo model was validated to be accurate in the most challenging situation, lung, by acquiring in-phantom measurements. A plan was created and delivered in a CIRS lung phantom with film insert. Separately, plans were delivered in an in-house created lung phantom with a PinPoint chamber insert within a lung simulating material. For medium to large collimator sizes, a single beam was delivered to the phantom. For small size collimators (10, 12.5, and 15mm), a robotically delivered plan was created to generate a uniform dose field of irradiation over a 2×2cm 2 area. Results: Dose differences in simulated water between Ray-Tracing and Monte-Carlo were all within 1% at dmax and deeper. Maximum dose differences occurred prior to dmax but were all within 3%. Film measurements in a lung phantom show high correspondence of over 95% gamma at the 2%/2mm level for Monte-Carlo. Ion chamber measurements for collimator sizes of 12.5mm and above were within 3% of Monte-Carlo calculated values. Uniform irradiation involving the 10mm collimator resulted in a dose difference of ∼8% for both Monte-Carlo and Ray-Tracing indicating that there may be limitations with the dose calculation. Conclusion: We have developed a methodology to validate a Monte-Carlo model by verifying that it matches in water and, separately, that it corresponds well in lung simulating materials. The Monte-Carlo model and algorithm tested may have more limited accuracy for 10mm fields and smaller.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Analysis of polytype stability in PVT grown silicon carbide single crystal using competitive lattice model Monte Carlo simulations

Directory of Open Access Journals (Sweden)

Hui-Jun Guo

2014-09-01

Full Text Available Polytype stability is very important for high quality SiC single crystal growth. However, the growth conditions for the 4H, 6H and 15R polytypes are similar, and the mechanism of polytype stability is not clear. The kinetics aspects, such as surface-step nucleation, are important. The kinetic Monte Carlo method is a common tool to study surface kinetics in crystal growth. However, the present lattice models for kinetic Monte Carlo simulations cannot solve the problem of the competitive growth of two or more lattice structures. In this study, a competitive lattice model was developed for kinetic Monte Carlo simulation of the competition growth of the 4H and 6H polytypes of SiC. The site positions are fixed at the perfect crystal lattice positions without any adjustment of the site positions. Surface steps on seeds and large ratios of diffusion/deposition have positive effects on the 4H polytype stability. The 3D polytype distribution in a physical vapor transport method grown SiC ingot showed that the facet preserved the 4H polytype even if the 6H polytype dominated the growth surface. The theoretical and experimental results of polytype growth in SiC suggest that retaining the step growth mode is an important factor to maintain a stable single 4H polytype during SiC growth.

Exploring Monte Carlo methods

CERN Document Server

Dunn, William L

2012-01-01

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

Science.gov (United States)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Optimization of the Monte Carlo code for modeling of photon migration in tissue.

Science.gov (United States)

Zołek, Norbert S; Liebert, Adam; Maniewski, Roman

2006-10-01

The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.

Monte Carlo applications to radiation shielding problems

International Nuclear Information System (INIS)

Subbaiah, K.V.

2009-01-01

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

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...

A Monte Carlo model for the intermittent plasticity of micro-pillars

International Nuclear Information System (INIS)

Ng, K S; Ngan, A H W

2008-01-01

Earlier compression experiments on micrometre-sized aluminium pillars, fabricated by focused-ion beam milling, using a flat-punch nanoindenter revealed that post-yield deformation during constant-rate loading was jerky with interspersing strain bursts and linear elastic segments. Under load hold, the pillars crept mainly by means of sporadic strain bursts. In this work, a Monte Carlo simulation model is developed, with two statistics gathered from the load-ramp experiments as input, to account for the jerky deformation during the load ramp as well as load hold. Under load-ramp conditions, the simulations successfully captured other experimental observations made independently from the two inputs, namely, the diverging behaviour of the jerky stress–strain response at higher stresses, the increase in burst frequency and burst size with stress and the overall power-law distribution of the burst size. The model also predicts creep behaviour agreeable with the experimental observations, namely, the occurrence of sporadic bursts with frequency depending on stress, creep time and pillar dimensions

Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

Energy Technology Data Exchange (ETDEWEB)

Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

2006-06-15

The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

Modelling a gamma irradiation process using the Monte Carlo method

International Nuclear Information System (INIS)

Soares, Gabriela A.; Pereira, Marcio T.

2011-01-01

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

Modelling a gamma irradiation process using the Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

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

2011-07-01

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

Monte Carlo principles and applications

Energy Technology Data Exchange (ETDEWEB)

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

1976-03-01

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

Monte Carlo methods in ICF

International Nuclear Information System (INIS)

Zimmerman, G.B.

1997-01-01

Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics

Design and analysis of Monte Carlo experiments

NARCIS (Netherlands)

Kleijnen, Jack P.C.; Gentle, J.E.; Haerdle, W.; Mori, Y.

2012-01-01

By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to

A Monte-Carlo simulation of the behaviour of electron swarms in hydrogen using an anisotropic scattering model

International Nuclear Information System (INIS)

Blevin, H.A.; Fletcher, J.; Hunter, S.R.

1978-05-01

In a recent paper, a Monte-Carlo simulation of electron swarms in hydrogen using an isotropic scattering model was reported. In this previous work discrepancies between the predicted and measured electron transport parameters were observed. In this paper a far more realistic anisotropic scattering model is used. Good agreement between predicted and experimental data is observed and the simulation code has been used to calculate various parameters which are not directly measurable

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...

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.

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

Energy Technology Data Exchange (ETDEWEB)

Richet, Y

2006-12-15

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

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

Science.gov (United States)

Liechty, Derek S.

2014-01-01

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

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

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

EURADOS intercomparison exercise on Monte Carlo modelling of a medical linear accelerator.

Science.gov (United States)

Caccia, Barbara; Le Roy, Maïwenn; Blideanu, Valentin; Andenna, Claudio; Arun, Chairmadurai; Czarnecki, Damian; El Bardouni, Tarek; Gschwind, Régine; Huot, Nicolas; Martin, Eric; Zink, Klemens; Zoubair, Mariam; Price, Robert; de Carlan, Loïc

2017-01-01

In radiotherapy, Monte Carlo (MC) methods are considered a gold standard to calculate accurate dose distributions, particularly in heterogeneous tissues. EURADOS organized an international comparison with six participants applying different MC models to a real medical linear accelerator and to one homogeneous and four heterogeneous dosimetric phantoms. The aim of this exercise was to identify, by comparison of different MC models with a complete experimental dataset, critical aspects useful for MC users to build and calibrate a simulation and perform a dosimetric analysis. Results show on average a good agreement between simulated and experimental data. However, some significant differences have been observed especially in presence of heterogeneities. Moreover, the results are critically dependent on the different choices of the initial electron source parameters. This intercomparison allowed the participants to identify some critical issues in MC modelling of a medical linear accelerator. Therefore, the complete experimental dataset assembled for this intercomparison will be available to all the MC users, thus providing them an opportunity to build and calibrate a model for a real medical linear accelerator.

A three-dimensional self-learning kinetic Monte Carlo model: application to Ag(111)

International Nuclear Information System (INIS)

Latz, Andreas; Brendel, Lothar; Wolf, Dietrich E

2012-01-01

The reliability of kinetic Monte Carlo (KMC) simulations depends on accurate transition rates. The self-learning KMC method (Trushin et al 2005 Phys. Rev. B 72 115401) combines the accuracy of rates calculated from a realistic potential with the efficiency of a rate catalog, using a pattern recognition scheme. This work expands the original two-dimensional method to three dimensions. The concomitant huge increase in the number of rate calculations on the fly needed can be avoided by setting up an initial database, containing exact activation energies calculated for processes gathered from a simpler KMC model. To provide two representative examples, the model is applied to the diffusion of Ag monolayer islands on Ag(111), and the homoepitaxial growth of Ag on Ag(111) at low temperatures.

Development of numerical models for Monte Carlo simulations of Th-Pb fuel assembly

Directory of Open Access Journals (Sweden)

Oettingen Mikołaj

2017-01-01

Full Text Available The thorium-uranium fuel cycle is a promising alternative against uranium-plutonium fuel cycle, but it demands many advanced research before starting its industrial application in commercial nuclear reactors. The paper presents the development of the thorium-lead (Th-Pb fuel assembly numerical models for the integral irradiation experiments. The Th-Pb assembly consists of a hexagonal array of ThO2 fuel rods and metallic Pb rods. The design of the assembly allows different combinations of rods for various types of irradiations and experimental measurements. The numerical model of the Th-Pb assembly was designed for the numerical simulations with the continuous energy Monte Carlo Burnup code (MCB implemented on the supercomputer Prometheus of the Academic Computer Centre Cyfronet AGH.

Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.

Science.gov (United States)

Kinjo, Akira R

2017-01-01

A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated.

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

Science.gov (United States)

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

CERN Document Server

Nuyens, Dirk

2016-01-01

This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.

Mission Analysis, Operations, and Navigation Toolkit Environment (Monte) Version 040

Science.gov (United States)

Sunseri, Richard F.; Wu, Hsi-Cheng; Evans, Scott E.; Evans, James R.; Drain, Theodore R.; Guevara, Michelle M.

2012-01-01

Monte is a software set designed for use in mission design and spacecraft navigation operations. The system can process measurement data, design optimal trajectories and maneuvers, and do orbit determination, all in one application. For the first time, a single software set can be used for mission design and navigation operations. This eliminates problems due to different models and fidelities used in legacy mission design and navigation software. The unique features of Monte 040 include a blowdown thruster model for GRAIL (Gravity Recovery and Interior Laboratory) with associated pressure models, as well as an updated, optimalsearch capability (COSMIC) that facilitated mission design for ARTEMIS. Existing legacy software lacked the capabilities necessary for these two missions. There is also a mean orbital element propagator and an osculating to mean element converter that allows long-term orbital stability analysis for the first time in compiled code. The optimized trajectory search tool COSMIC allows users to place constraints and controls on their searches without any restrictions. Constraints may be user-defined and depend on trajectory information either forward or backwards in time. In addition, a long-term orbit stability analysis tool (morbiter) existed previously as a set of scripts on top of Monte. Monte is becoming the primary tool for navigation operations, a core competency at JPL. The mission design capabilities in Monte are becoming mature enough for use in project proposals as well as post-phase A mission design. Monte has three distinct advantages over existing software. First, it is being developed in a modern paradigm: object- oriented C++ and Python. Second, the software has been developed as a toolkit, which allows users to customize their own applications and allows the development team to implement requirements quickly, efficiently, and with minimal bugs. Finally, the software is managed in accordance with the CMMI (Capability Maturity Model

Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model

International Nuclear Information System (INIS)

Cubasch, U.; Santer, B.D.; Hegerl, G.; Hoeck, H.; Maier-Reimer, E.; Mikolajwicz, U.; Stoessel, A.; Voss, R.

1992-01-01

The Monte Carlo approach, which has increasingly been used during the last decade in the field of extended range weather forecasting, has been applied for climate change experiments. Four integrations with a global coupled ocean-atmosphere model have been started from different initial conditions, but with the same greenhouse gas forcing according to the IPCC scenario A. All experiments have been run for a period of 50 years. The results indicate that the time evolution of the global mean warming depends strongly on the initial state of the climate system. It can vary between 6 and 31 years. The Monte Carlo approach delivers information about both the mean response and the statistical significance of the response. While the individual members of the ensemble show a considerable variation in the climate change pattern of temperature after 50 years, the ensemble mean climate change pattern closely resembles the pattern obtained in a 100 year integration and is, at least over most of the land areas, statistically significant. The ensemble averaged sea-level change due to thermal expansion is significant in the global mean and locally over wide regions of the Pacific. The hydrological cycle is also significantly enhanced in the global mean, but locally the changes in precipitation and soil moisture are masked by the variability of the experiments. (orig.)

FluorWPS: A Monte Carlo ray-tracing model to compute sun-induced chlorophyll fluorescence of three-dimensional canopy

Science.gov (United States)

A model to simulate radiative transfer (RT) of sun-induced chlorophyll fluorescence (SIF) of three-dimensional (3-D) canopy, FluorWPS, was proposed and evaluated. The inclusion of fluorescence excitation was implemented with the ‘weight reduction’ and ‘photon spread’ concepts based on Monte Carlo ra...

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

Improving system modeling accuracy with Monte Carlo codes

International Nuclear Information System (INIS)

Johnson, A.S.

1996-01-01

The use of computer codes based on Monte Carlo methods to perform criticality calculations has become common-place. Although results frequently published in the literature report calculated k eff values to four decimal places, people who use the codes in their everyday work say that they only believe the first two decimal places of any result. The lack of confidence in the computed k eff values may be due to the tendency of the reported standard deviation to underestimate errors associated with the Monte Carlo process. The standard deviation as reported by the codes is the standard deviation of the mean of the k eff values for individual generations in the computer simulation, not the standard deviation of the computed k eff value compared with the physical system. A more subtle problem with the standard deviation of the mean as reported by the codes is that all the k eff values from the separate generations are not statistically independent since the k eff of a given generation is a function of k eff of the previous generation, which is ultimately based on the starting source. To produce a standard deviation that is more representative of the physical system, statistically independent values of k eff are needed

Estimation of total Effort and Effort Elapsed in Each Step of Software Development Using Optimal Bayesian Belief Network

Directory of Open Access Journals (Sweden)

Fatemeh Zare Baghiabad

2017-09-01

Full Text Available Accuracy in estimating the needed effort for software development caused software effort estimation to be a challenging issue. Beside estimation of total effort, determining the effort elapsed in each software development step is very important because any mistakes in enterprise resource planning can lead to project failure. In this paper, a Bayesian belief network was proposed based on effective components and software development process. In this model, the feedback loops are considered between development steps provided that the return rates are different for each project. Different return rates help us determine the percentages of the elapsed effort in each software development step, distinctively. Moreover, the error measurement resulted from optimized effort estimation and the optimal coefficients to modify the model are sought. The results of the comparison between the proposed model and other models showed that the model has the capability to highly accurately estimate the total effort (with the marginal error of about 0.114 and to estimate the effort elapsed in each software development step.

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Overview 2004 of NASA Stirling-Convertor CFD-Model Development and Regenerator R&D Efforts

Science.gov (United States)

Tew, Roy C.; Dyson, Rodger W.; Wilson, Scott D.; Demko, Rikako

2005-01-01

This paper reports on accomplishments in 2004 in development of Stirling-convertor CFD model at NASA GRC and via a NASA grant, a Stirling regenerator-research effort being conducted via a NASA grant (a follow-on effort to an earlier DOE contract), and a regenerator-microfabrication contract for development of a "next-generation Stirling regenerator." Cleveland State University is the lead organization for all three grant/contractual efforts, with the University of Minnesota and Gedeor Associates as subcontractors. Also, the Stirling Technology Co. and Sunpower, Inc. are both involved in all three efforts, either as funded or unfunded participants. International Mezzo Technologies of Baton Rouge, LA is the regenerator fabricator for the regenerator-microfabrication contract. Results of the efforts in these three areas are summarized.

Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model

Science.gov (United States)

Morin, Mario A.; Ficarazzo, Francesco

2006-04-01

Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.

Monte Carlo modelling for neutron guide losses

International Nuclear Information System (INIS)

Cser, L.; Rosta, L.; Toeroek, Gy.

1989-09-01

In modern research reactors, neutron guides are commonly used for beam conducting. The neutron guide is a well polished or equivalently smooth glass tube covered inside by sputtered or evaporated film of natural Ni or 58 Ni isotope where the neutrons are totally reflected. A Monte Carlo calculation was carried out to establish the real efficiency and the spectral as well as spatial distribution of the neutron beam at the end of a glass mirror guide. The losses caused by mechanical inaccuracy and mirror quality were considered and the effects due to the geometrical arrangement were analyzed. (author) 2 refs.; 2 figs

EchoSeed Model 6733 Iodine-125 brachytherapy source: Improved dosimetric characterization using the MCNP5 Monte Carlo code

Energy Technology Data Exchange (ETDEWEB)

Mosleh-Shirazi, M. A.; Hadad, K.; Faghihi, R.; Baradaran-Ghahfarokhi, M.; Naghshnezhad, Z.; Meigooni, A. S. [Center for Research in Medical Physics and Biomedical Engineering and Physics Unit, Radiotherapy Department, Shiraz University of Medical Sciences, Shiraz 71936-13311 (Iran, Islamic Republic of); Radiation Research Center and Medical Radiation Department, School of Engineering, Shiraz University, Shiraz 71936-13311 (Iran, Islamic Republic of); Comprehensive Cancer Center of Nevada, Las Vegas, Nevada 89169 (United States)

2012-08-15

This study primarily aimed to obtain the dosimetric characteristics of the Model 6733 {sup 125}I seed (EchoSeed) with improved precision and accuracy using a more up-to-date Monte-Carlo code and data (MCNP5) compared to previously published results, including an uncertainty analysis. Its secondary aim was to compare the results obtained using the MCNP5, MCNP4c2, and PTRAN codes for simulation of this low-energy photon-emitting source. The EchoSeed geometry and chemical compositions together with a published {sup 125}I spectrum were used to perform dosimetric characterization of this source as per the updated AAPM TG-43 protocol. These simulations were performed in liquid water material in order to obtain the clinically applicable dosimetric parameters for this source model. Dose rate constants in liquid water, derived from MCNP4c2 and MCNP5 simulations, were found to be 0.993 cGyh{sup -1} U{sup -1} ({+-}1.73%) and 0.965 cGyh{sup -1} U{sup -1} ({+-}1.68%), respectively. Overall, the MCNP5 derived radial dose and 2D anisotropy functions results were generally closer to the measured data (within {+-}4%) than MCNP4c and the published data for PTRAN code (Version 7.43), while the opposite was seen for dose rate constant. The generally improved MCNP5 Monte Carlo simulation may be attributed to a more recent and accurate cross-section library. However, some of the data points in the results obtained from the above-mentioned Monte Carlo codes showed no statistically significant differences. Derived dosimetric characteristics in liquid water are provided for clinical applications of this source model.

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.

Feasibility Study of Core Design with a Monte Carlo Code for APR1400 Initial core

Energy Technology Data Exchange (ETDEWEB)

Kim, Jinsun; Chang, Do Ik; Seong, Kibong [KEPCO NF, Daejeon (Korea, Republic of)

2014-10-15

The Monte Carlo calculation becomes more popular and useful nowadays due to the rapid progress in computing power and parallel calculation techniques. There have been many attempts to analyze a commercial core by Monte Carlo transport code using the enhanced computer capability, recently. In this paper, Monte Carlo calculation of APR1400 initial core has been performed and the results are compared with the calculation results of conventional deterministic code to find out the feasibility of core design using Monte Carlo code. SERPENT, a 3D continuous-energy Monte Carlo reactor physics burnup calculation code is used for this purpose and the KARMA-ASTRA code system, which is used for a deterministic code of comparison. The preliminary investigation for the feasibility of commercial core design with Monte Carlo code was performed in this study. Simplified core geometry modeling was performed for the reactor core surroundings and reactor coolant model is based on two region model. The reactivity difference at HZP ARO condition between Monte Carlo code and the deterministic code is consistent with each other and the reactivity difference during the depletion could be reduced by adopting the realistic moderator temperature. The reactivity difference calculated at HFP, BOC, ARO equilibrium condition was 180 ±9 pcm, with axial moderator temperature of a deterministic code. The computing time will be a significant burden at this time for the application of Monte Carlo code to the commercial core design even with the application of parallel computing because numerous core simulations are required for actual loading pattern search. One of the remedy will be a combination of Monte Carlo code and the deterministic code to generate the physics data. The comparison of physics parameters with sophisticated moderator temperature modeling and depletion will be performed for a further study.

Present status and future prospects of neutronics Monte Carlo

International Nuclear Information System (INIS)

Gelbard, E.M.

1990-01-01

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

Practical Application of Monte Carlo Code in RTP

International Nuclear Information System (INIS)

Mohamad Hairie Rabir; Julia Abdul Karim; Muhammad Rawi Mohamed Zin; Na'im Syauqi Hamzah; Mark Dennis Anak Usang; Abi Muttaqin Jalal Bayar; Muhammad Khairul Ariff Mustafa

2015-01-01

Monte Carlo neutron transport codes are widely used in various reactor physics applications in RTP and other related nuclear and radiation research in Nuklear Malaysia. The main advantage of the method is the capability to model geometry and interaction physics without major approximations. The disadvantage is that the modelling of complicated systems is very computing-intensive, which restricts the applications to some extent. The importance of Monte Carlo calculation is likely to increase in the future, along with the development in computer capacities and parallel calculation. This paper presents several calculation activities, its achievements and challenges in using MCNP code for neutronics analysis, nuclide inventory and source term calculation, shielding and dose evaluation. (author)

Direct aperture optimization for IMRT using Monte Carlo generated beamlets

International Nuclear Information System (INIS)

Bergman, Alanah M.; Bush, Karl; Milette, Marie-Pierre; Popescu, I. Antoniu; Otto, Karl; Duzenli, Cheryl

2006-01-01

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5x5.0 mm 2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is ∼33% compared to fluence-based optimization methods

Monte Carlo modelling of germanium crystals that are tilted and have rounded front edges

International Nuclear Information System (INIS)

Gasparro, Joel; Hult, Mikael; Johnston, Peter N.; Tagziria, Hamid

2008-01-01

Gamma-ray detection efficiencies and cascade summing effects in germanium detectors are often calculated using Monte Carlo codes based on a computer model of the detection system. Such a model can never fully replicate reality and it is important to understand how various parameters affect the results. This work concentrates on quantifying two issues, namely (i) the effect of having a Ge-crystal that is tilted inside the cryostat and (ii) the effect of having a model of a Ge-crystal with rounded edges (bulletization). The effect of the tilting is very small (in the order of per mille) when the tilting angles are within a realistic range. The effect of the rounded edges is, however, relatively large (5-10% or higher) particularly for gamma-ray energies below 100 keV

Monte Carlo modelling of germanium crystals that are tilted and have rounded front edges

Energy Technology Data Exchange (ETDEWEB)

Gasparro, Joel [EC-JRC-IRMM, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440 Geel (Belgium); Hult, Mikael [EC-JRC-IRMM, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440 Geel (Belgium)], E-mail: mikael.hult@ec.europa.eu; Johnston, Peter N. [Applied Physics, Royal Melbourne Institute of Technology, GPO Box 2476V, Melbourne 3001 (Australia); Tagziria, Hamid [EC-JRC-IPSC, Institute for the Protection and the Security of the Citizen, Via E. Fermi 1, I-21020 Ispra (Vatican City State, Holy See,) (Italy)

2008-09-01

Gamma-ray detection efficiencies and cascade summing effects in germanium detectors are often calculated using Monte Carlo codes based on a computer model of the detection system. Such a model can never fully replicate reality and it is important to understand how various parameters affect the results. This work concentrates on quantifying two issues, namely (i) the effect of having a Ge-crystal that is tilted inside the cryostat and (ii) the effect of having a model of a Ge-crystal with rounded edges (bulletization). The effect of the tilting is very small (in the order of per mille) when the tilting angles are within a realistic range. The effect of the rounded edges is, however, relatively large (5-10% or higher) particularly for gamma-ray energies below 100 keV.

Dynamic Value at Risk: A Comparative Study Between Heteroscedastic Models and Monte Carlo Simulation

Directory of Open Access Journals (Sweden)

José Lamartine Távora Junior

2006-12-01

Full Text Available The objective of this paper was to analyze the risk management of a portfolio composed by Petrobras PN, Telemar PN and Vale do Rio Doce PNA stocks. It was verified if the modeling of Value-at-Risk (VaR through the place Monte Carlo simulation with volatility of GARCH family is supported by hypothesis of efficient market. The results have shown that the statistic evaluation in inferior to dynamics, evidencing that the dynamic analysis supplies support to the hypothesis of efficient market of the Brazilian share holding market, in opposition of some empirical evidences. Also, it was verified that the GARCH models of volatility is enough to accommodate the variations of the shareholding Brazilian market, since the model is capable to accommodate the great dynamic of the Brazilian market.

Monte Carlo simulations in theoretical physic

International Nuclear Information System (INIS)

Billoire, A.

1991-01-01

After a presentation of the MONTE CARLO method principle, the method is applied, first to the critical exponents calculations in the three dimensions ISING model, and secondly to the discrete quantum chromodynamic with calculation times in function of computer power. 28 refs., 4 tabs

Application of the Monte Carlo method for building up models for octanol-water partition coefficient of platinum complexes

Science.gov (United States)

Toropov, Andrey A.; Toropova, Alla P.

2018-06-01

Predictive model of logP for Pt(II) and Pt(IV) complexes built up with the Monte Carlo method using the CORAL software has been validated with six different splits into the training and validation sets. The improving of the predictive potential of models for six different splits has been obtained using so-called index of ideality of correlation. The suggested models give possibility to extract molecular features, which cause the increase or vice versa decrease of the logP.

A Methodology to Reduce the Computational Effort in the Evaluation of the Lightning Performance of Distribution Networks

Directory of Open Access Journals (Sweden)

Ilaria Bendato

2016-11-01

Full Text Available The estimation of the lightning performance of a power distribution network is of great importance to design its protection system against lightning. An accurate evaluation of the number of lightning events that can create dangerous overvoltages requires a huge computational effort, as it implies the adoption of a Monte Carlo procedure. Such a procedure consists of generating many different random lightning events and calculating the corresponding overvoltages. The paper proposes a methodology to deal with the problem in two computationally efficient ways: (i finding out the minimum number of Monte Carlo runs that lead to reliable results; and (ii setting up a procedure that bypasses the lightning field-to-line coupling problem for each Monte Carlo run. The proposed approach is shown to provide results consistent with existing approaches while exhibiting superior Central Processing Unit (CPU time performances.

Geometrical splitting in Monte Carlo

International Nuclear Information System (INIS)

Dubi, A.; Elperin, T.; Dudziak, D.J.

1982-01-01

A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs

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

International Nuclear Information System (INIS)

Zuo Yinghong; Wang Jianguo

2012-01-01

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

Maintenance personnel performance simulation (MAPPS) model: overview and evaluation efforts

International Nuclear Information System (INIS)

Knee, H.E.; Haas, P.M.; Siegel, A.I.; Bartter, W.D.; Wolf, J.J.; Ryan, T.G.

1984-01-01

The development of the MAPPS model has been completed and the model is currently undergoing evaluation. These efforts are addressing a number of identified issues concerning practicality, acceptability, usefulness, and validity. Preliminary analysis of the evaluation data that has been collected indicates that MAPPS will provide comprehensive and reliable data for PRA purposes and for a number of other applications. The MAPPS computer simulation model provides the user with a sophisticated tool for gaining insights into tasks performed by NPP maintenance personnel. Its wide variety of input parameters and output data makes it extremely flexible for application to a number of diverse applications. With the demonstration of favorable model evaluation results, the MAPPS model will represent a valuable source of NPP maintainer reliability data and provide PRA studies with a source of data on maintainers that has previously not existed

Monte Carlo particle-trajectory models for neutral cometary gases. I. Models and equations. II. The spatial morphology of the Lyman-alpha coma

International Nuclear Information System (INIS)

Combi, M.R.; Smyth, W.H.

1988-01-01

The mathematical derivations of various methods employed in the Monte Carlo particle-trajectory model (MCPTM) are presented, and the application of the MCPTM to the calculation of the photochemical heating of the inner coma through the partial thermalization of cometary hydrogen atoms produced by the photodissociation of water is discussed. This model is then used to explain the observed morphology of the spatially extended Ly-alpha comas of comets. The rocket and Skylab images of the Ly-alpha coma of Comet Kohoutek are examined. 90 references

The Effect of the Demand Control and Effort Reward Imbalance Models on the Academic Burnout of Korean Adolescents

Science.gov (United States)

Lee, Jayoung; Puig, Ana; Lee, Sang Min

2012-01-01

The purpose of this study was to examine the effects of the Demand Control Model (DCM) and the Effort Reward Imbalance Model (ERIM) on academic burnout for Korean students. Specifically, this study identified the effects of the predictor variables based on DCM and ERIM (i.e., demand, control, effort, reward, Demand Control Ratio, Effort Reward…

Development of Monte Carlo-based pebble bed reactor fuel management code

International Nuclear Information System (INIS)

Setiadipura, Topan; Obara, Toru

2014-01-01

Highlights: • A new Monte Carlo-based fuel management code for OTTO cycle pebble bed reactor was developed. • The double-heterogeneity was modeled using statistical method in MVP-BURN code. • The code can perform analysis of equilibrium and non-equilibrium phase. • Code-to-code comparisons for Once-Through-Then-Out case were investigated. • Ability of the code to accommodate the void cavity was confirmed. - Abstract: A fuel management code for pebble bed reactors (PBRs) based on the Monte Carlo method has been developed in this study. The code, named Monte Carlo burnup analysis code for PBR (MCPBR), enables a simulation of the Once-Through-Then-Out (OTTO) cycle of a PBR from the running-in phase to the equilibrium condition. In MCPBR, a burnup calculation based on a continuous-energy Monte Carlo code, MVP-BURN, is coupled with an additional utility code to be able to simulate the OTTO cycle of PBR. MCPBR has several advantages in modeling PBRs, namely its Monte Carlo neutron transport modeling, its capability of explicitly modeling the double heterogeneity of the PBR core, and its ability to model different axial fuel speeds in the PBR core. Analysis at the equilibrium condition of the simplified PBR was used as the validation test of MCPBR. The calculation results of the code were compared with the results of diffusion-based fuel management PBR codes, namely the VSOP and PEBBED codes. Using JENDL-4.0 nuclide library, MCPBR gave a 4.15% and 3.32% lower k eff value compared to VSOP and PEBBED, respectively. While using JENDL-3.3, MCPBR gave a 2.22% and 3.11% higher k eff value compared to VSOP and PEBBED, respectively. The ability of MCPBR to analyze neutron transport in the top void of the PBR core and its effects was also confirmed

Tracking in full Monte Carlo detector simulations of 500 GeV e+e- collisions

International Nuclear Information System (INIS)

Ronan, M.T.

2000-01-01

In full Monte Carlo simulation models of future Linear Collider detectors, charged tracks are reconstructed from 3D space points in central tracking detectors. The track reconstruction software is being developed for detailed physics studies that take realistic detector resolution and background modeling into account. At this stage of the analysis, reference tracking efficiency and resolutions for ideal detector conditions are presented. High performance detectors are being designed to carry out precision studies of e + e - annihilation events in the energy range of 500 GeV to 1.5 TeV. Physics processes under study include Higgs mass and branching ratio measurements, measurement of possible manifestations of Supersymmetry (SUSY), precision Electro-Weak (EW) studies and searches for new phenomena beyond their current expectations. The relatively-low background machine environment at future Linear Colliders will allow precise measurements if proper consideration is given to the effects of the backgrounds on these studies. In current North American design studies, full Monte Carlo detector simulation and analysis is being used to allow detector optimization taking into account realistic models of machine backgrounds. In this paper the design of tracking software that is being developed for full detector reconstruction is discussed. In this study, charged tracks are found from simulated space point hits allowing for the straight-forward addition of background hits and for the accounting of missing information. The status of the software development effort is quantified by some reference performance measures, which will be modified by future work to include background effects

Monte Carlo method for random surfaces

International Nuclear Information System (INIS)

Berg, B.

1985-01-01

Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)

Development and verification of an analytical algorithm to predict absorbed dose distributions in ocular proton therapy using Monte Carlo simulations

International Nuclear Information System (INIS)

Koch, Nicholas C; Newhauser, Wayne D

2010-01-01

Proton beam radiotherapy is an effective and non-invasive treatment for uveal melanoma. Recent research efforts have focused on improving the dosimetric accuracy of treatment planning and overcoming the present limitation of relative analytical dose calculations. Monte Carlo algorithms have been shown to accurately predict dose per monitor unit (D/MU) values, but this has yet to be shown for analytical algorithms dedicated to ocular proton therapy, which are typically less computationally expensive than Monte Carlo algorithms. The objective of this study was to determine if an analytical method could predict absolute dose distributions and D/MU values for a variety of treatment fields like those used in ocular proton therapy. To accomplish this objective, we used a previously validated Monte Carlo model of an ocular nozzle to develop an analytical algorithm to predict three-dimensional distributions of D/MU values from pristine Bragg peaks and therapeutically useful spread-out Bragg peaks (SOBPs). Results demonstrated generally good agreement between the analytical and Monte Carlo absolute dose calculations. While agreement in the proximal region decreased for beams with less penetrating Bragg peaks compared with the open-beam condition, the difference was shown to be largely attributable to edge-scattered protons. A method for including this effect in any future analytical algorithm was proposed. Comparisons of D/MU values showed typical agreement to within 0.5%. We conclude that analytical algorithms can be employed to accurately predict absolute proton dose distributions delivered by an ocular nozzle.

Multi-Model Ensemble Wake Vortex Prediction

Science.gov (United States)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Review of the Monte Carlo and deterministic codes in radiation protection and dosimetry

International Nuclear Information System (INIS)

Tagziria, H.

2000-02-01

Modelling a physical system can be carried out either stochastically or deterministically. An example of the former method is the Monte Carlo technique, in which statistically approximate methods are applied to exact models. No transport equation is solved as individual particles are simulated and some specific aspect (tally) of their average behaviour is recorded. The average behaviour of the physical system is then inferred using the central limit theorem. In contrast, deterministic codes use mathematically exact methods that are applied to approximate models to solve the transport equation for the average particle behaviour. The physical system is subdivided in boxes in the phase-space system and particles are followed from one box to the next. The smaller the boxes the better the approximations become. Although the Monte Carlo method has been used for centuries, its more recent manifestation has really emerged from the Manhattan project of the Word War II. Its invention is thought to be mainly due to Metropolis, Ulah (through his interest in poker), Fermi, von Neuman and Richtmeyer. Over the last 20 years or so, the Monte Carlo technique has become a powerful tool in radiation transport. This is due to users taking full advantage of richer cross section data, more powerful computers and Monte Carlo techniques for radiation transport, with high quality physics and better known source spectra. This method is a common sense approach to radiation transport and its success and popularity is quite often also due to necessity, because measurements are not always possible or affordable. In the Monte Carlo method, which is inherently realistic because nature is statistical, a more detailed physics is made possible by isolation of events while rather elaborate geometries can be modelled. Provided that the physics is correct, a simulation is exactly analogous to an experimenter counting particles. In contrast to the deterministic approach, however, a disadvantage of the

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

Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort

Directory of Open Access Journals (Sweden)

Eliana Vassena

2017-06-01

Full Text Available In the last two decades the anterior cingulate cortex (ACC has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.

Development of self-learning Monte Carlo technique for more efficient modeling of nuclear logging measurements

International Nuclear Information System (INIS)

Zazula, J.M.

1988-01-01

The self-learning Monte Carlo technique has been implemented to the commonly used general purpose neutron transport code MORSE, in order to enhance sampling of the particle histories that contribute to a detector response. The parameters of all the biasing techniques available in MORSE, i.e. of splitting, Russian roulette, source and collision outgoing energy importance sampling, path length transformation and additional biasing of the source angular distribution are optimized. The learning process is iteratively performed after each batch of particles, by retrieving the data concerning the subset of histories that passed the detector region and energy range in the previous batches. This procedure has been tested on two sample problems in nuclear geophysics, where an unoptimized Monte Carlo calculation is particularly inefficient. The results are encouraging, although the presented method does not directly minimize the variance and the convergence of our algorithm is restricted by the statistics of successful histories from previous random walk. Further applications for modeling of the nuclear logging measurements seem to be promising. 11 refs., 2 figs., 3 tabs. (author)

Quantum Monte Carlo algorithms for electronic structure at the petascale; the endstation project.

Energy Technology Data Exchange (ETDEWEB)

Kim, J; Ceperley, D M; Purwanto, W; Walter, E J; Krakauer, H; Zhang, S W; Kent, P.R. C; Hennig, R G; Umrigar, C; Bajdich, M; Kolorenc, J; Mitas, L

2008-10-01

Over the past two decades, continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting of the properties of matter from fundamental principles. By solving the Schrodinger equation through a stochastic projection, it achieves the greatest accuracy and reliability of methods available for physical systems containing more than a few quantum particles. QMC enjoys scaling favorable to quantum chemical methods, with a computational effort which grows with the second or third power of system size. This accuracy and scalability has enabled scientific discovery across a broad spectrum of disciplines. The current methods perform very efficiently at the terascale. The quantum Monte Carlo Endstation project is a collaborative effort among researchers in the field to develop a new generation of algorithms, and their efficient implementations, which will take advantage of the upcoming petaflop architectures. Some aspects of these developments are discussed here. These tools will expand the accuracy, efficiency and range of QMC applicability and enable us to tackle challenges which are currently out of reach. The methods will be applied to several important problems including electronic and structural properties of water, transition metal oxides, nanosystems and ultracold atoms.

grmonty: A MONTE CARLO CODE FOR RELATIVISTIC RADIATIVE TRANSPORT

International Nuclear Information System (INIS)

Dolence, Joshua C.; Gammie, Charles F.; Leung, Po Kin; Moscibrodzka, Monika

2009-01-01

We describe a Monte Carlo radiative transport code intended for calculating spectra of hot, optically thin plasmas in full general relativity. The version we describe here is designed to model hot accretion flows in the Kerr metric and therefore incorporates synchrotron emission and absorption, and Compton scattering. The code can be readily generalized, however, to account for other radiative processes and an arbitrary spacetime. We describe a suite of test problems, and demonstrate the expected N -1/2 convergence rate, where N is the number of Monte Carlo samples. Finally, we illustrate the capabilities of the code with a model calculation, a spectrum of the slowly accreting black hole Sgr A* based on data provided by a numerical general relativistic MHD model of the accreting plasma.

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.

Modeling and Evaluating Pilot Performance in NextGen: Review of and Recommendations Regarding Pilot Modeling Efforts, Architectures, and Validation Studies

Science.gov (United States)

Wickens, Christopher; Sebok, Angelia; Keller, John; Peters, Steve; Small, Ronald; Hutchins, Shaun; Algarin, Liana; Gore, Brian Francis; Hooey, Becky Lee; Foyle, David C.

2013-01-01

NextGen operations are associated with a variety of changes to the national airspace system (NAS) including changes to the allocation of roles and responsibilities among operators and automation, the use of new technologies and automation, additional information presented on the flight deck, and the entire concept of operations (ConOps). In the transition to NextGen airspace, aviation and air operations designers need to consider the implications of design or system changes on human performance and the potential for error. To ensure continued safety of the NAS, it will be necessary for researchers to evaluate design concepts and potential NextGen scenarios well before implementation. One approach for such evaluations is through human performance modeling. Human performance models (HPMs) provide effective tools for predicting and evaluating operator performance in systems. HPMs offer significant advantages over empirical, human-in-the-loop testing in that (1) they allow detailed analyses of systems that have not yet been built, (2) they offer great flexibility for extensive data collection, (3) they do not require experimental participants, and thus can offer cost and time savings. HPMs differ in their ability to predict performance and safety with NextGen procedures, equipment and ConOps. Models also vary in terms of how they approach human performance (e.g., some focus on cognitive processing, others focus on discrete tasks performed by a human, while others consider perceptual processes), and in terms of their associated validation efforts. The objectives of this research effort were to support the Federal Aviation Administration (FAA) in identifying HPMs that are appropriate for predicting pilot performance in NextGen operations, to provide guidance on how to evaluate the quality of different models, and to identify gaps in pilot performance modeling research, that could guide future research opportunities. This research effort is intended to help the FAA

Current and future applications of Monte Carlo

International Nuclear Information System (INIS)

Zaidi, H.

2003-01-01

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

Results of the Monte Carlo 'simple case' benchmark exercise

International Nuclear Information System (INIS)

2003-11-01

A new 'simple case' benchmark intercomparison exercise was launched, intended to study the importance of the fundamental nuclear data constants, physics treatments and geometry model approximations, employed by Monte Carlo codes in common use. The exercise was also directed at determining the level of agreement which can be expected between measured and calculated quantities, using current state or the art modelling codes and techniques. To this end, measurements and Monte Carlo calculations of the total (or gross) neutron count rates have been performed using a simple moderated 3 He cylindrical proportional counter array or 'slab monitor' counting geometry, deciding to select a very simple geometry for this exercise

Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling

DEFF Research Database (Denmark)

Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan

2008-01-01

uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...

Diagrammatic Monte Carlo for the weak-coupling expansion of non-Abelian lattice field theories: Large-N U (N ) ×U (N ) principal chiral model

Science.gov (United States)

Buividovich, P. V.; Davody, A.

2017-12-01

We develop numerical tools for diagrammatic Monte Carlo simulations of non-Abelian lattice field theories in the t'Hooft large-N limit based on the weak-coupling expansion. First, we note that the path integral measure of such theories contributes a bare mass term in the effective action which is proportional to the bare coupling constant. This mass term renders the perturbative expansion infrared-finite and allows us to study it directly in the large-N and infinite-volume limits using the diagrammatic Monte Carlo approach. On the exactly solvable example of a large-N O (N ) sigma model in D =2 dimensions we show that this infrared-finite weak-coupling expansion contains, in addition to powers of bare coupling, also powers of its logarithm, reminiscent of resummed perturbation theory in thermal field theory and resurgent trans-series without exponential terms. We numerically demonstrate the convergence of these double series to the manifestly nonperturbative dynamical mass gap. We then develop a diagrammatic Monte Carlo algorithm for sampling planar diagrams in the large-N matrix field theory, and apply it to study this infrared-finite weak-coupling expansion for large-N U (N ) ×U (N ) nonlinear sigma model (principal chiral model) in D =2 . We sample up to 12 leading orders of the weak-coupling expansion, which is the practical limit set by the increasingly strong sign problem at high orders. Comparing diagrammatic Monte Carlo with conventional Monte Carlo simulations extrapolated to infinite N , we find a good agreement for the energy density as well as for the critical temperature of the "deconfinement" transition. Finally, we comment on the applicability of our approach to planar QCD at zero and finite density.

Continuous-time quantum Monte Carlo impurity solvers

Science.gov (United States)

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

2011-04-01

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

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

KAUST Repository

Liang, Faming

2009-03-01

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

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

KAUST Repository

Liang, Faming

2009-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo

DEFF Research Database (Denmark)

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

2012-01-01

This paper discusses the estimation of the failure probability of wind turbines required by codes of practice for designing them. The Standard Monte Carlo (SMC) simulations may be used for this reason conceptually as an alternative to the popular Peaks-Over-Threshold (POT) method. However......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy...... is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated...

Modelling phase separation in Fe-Cr system using different atomistic kinetic Monte Carlo techniques

International Nuclear Information System (INIS)

Castin, N.; Bonny, G.; Terentyev, D.; Lavrentiev, M.Yu.; Nguyen-Manh, D.

2011-01-01

Atomistic kinetic Monte Carlo (AKMC) simulations were performed to study α-α' phase separation in Fe-Cr alloys. Two different energy models and two approaches to estimate the local vacancy migration barriers were used. The energy models considered are a two-band model Fe-Cr potential and a cluster expansion, both fitted to ab initio data. The classical Kang-Weinberg decomposition, based on the total energy change of the system, and an Artificial Neural Network (ANN), employed as a regression tool were used to predict the local vacancy migration barriers 'on the fly'. The results are compared with experimental thermal annealing data and differences between the applied AKMC approaches are discussed. The ability of the ANN regression method to accurately predict migration barriers not present in the training list is also addressed by performing cross-check calculations using the nudged elastic band method.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-10-01

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

Fundamental Drop Dynamics and Mass Transfer Experiments to Support Solvent Extraction Modeling Efforts

International Nuclear Information System (INIS)

Christensen, Kristi; Rutledge, Veronica; Garn, Troy

2011-01-01

In support of the Nuclear Energy Advanced Modeling Simulation Safeguards and Separations (NEAMS SafeSep) program, the Idaho National Laboratory (INL) worked in collaboration with Los Alamos National Laboratory (LANL) to further a modeling effort designed to predict mass transfer behavior for selected metal species between individual dispersed drops and a continuous phase in a two phase liquid-liquid extraction (LLE) system. The purpose of the model is to understand the fundamental processes of mass transfer that occur at the drop interface. This fundamental understanding can be extended to support modeling of larger LLE equipment such as mixer settlers, pulse columns, and centrifugal contactors. The work performed at the INL involved gathering the necessary experimental data to support the modeling effort. A custom experimental apparatus was designed and built for performing drop contact experiments to measure mass transfer coefficients as a function of contact time. A high speed digital camera was used in conjunction with the apparatus to measure size, shape, and velocity of the drops. In addition to drop data, the physical properties of the experimental fluids were measured to be used as input data for the model. Physical properties measurements included density, viscosity, surface tension and interfacial tension. Additionally, self diffusion coefficients for the selected metal species in each experimental solution were measured, and the distribution coefficient for the metal partitioning between phases was determined. At the completion of this work, the INL has determined the mass transfer coefficient and a velocity profile for drops rising by buoyancy through a continuous medium under a specific set of experimental conditions. Additionally, a complete set of experimentally determined fluid properties has been obtained. All data will be provided to LANL to support the modeling effort.

Monte Carlo methods for the reliability analysis of Markov systems

International Nuclear Information System (INIS)

Buslik, A.J.

1985-01-01

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

Particle-gamma and particle-particle correlations in nuclear reactions using Monte Carlo Hauser-Feshback model

Energy Technology Data Exchange (ETDEWEB)

Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Watanabe, Takehito [Los Alamos National Laboratory; Chadwick, Mark [Los Alamos National Laboratory

2010-01-01

Monte Carlo simulations for particle and {gamma}-ray emissions from an excited nucleus based on the Hauser-Feshbach statistical theory are performed to obtain correlated information between emitted particles and {gamma}-rays. We calculate neutron induced reactions on {sup 51}V to demonstrate unique advantages of the Monte Carlo method. which are the correlated {gamma}-rays in the neutron radiative capture reaction, the neutron and {gamma}-ray correlation, and the particle-particle correlations at higher energies. It is shown that properties in nuclear reactions that are difficult to study with a deterministic method can be obtained with the Monte Carlo simulations.

Investigation of Psychological Health and Migraine Headaches Among Personnel According to Effort-Reward Imbalance Model

Directory of Open Access Journals (Sweden)

Z. Darami

2012-05-01

Full Text Available Background and aims: The relationship between physical-mental health and Migraine headaches and stress, especially job stress, is known. Many factors can construct job stress in work settings. The factor that has gained much attention recently is inequality (imbalance of employees’ effort versus the reward they gain. The aim of the current attempt was to investigate the validity of effort-reward imbalance model and indicate the relation of this model with migraine headaches and psychological well-being among subjects in balance and imbalance groups. Methods: Participants were 180 personnel of Oil distribution company located in Isfahan city, and instruments used were General health questionnaire (Goldberg & Hilier, Social Re-adjustment Rating Scale (Holmes & Rahe, Ahvaz Migraine Questionnaire (Najariyan and Effort-reward imbalance scale (Van Vegchel & et al.   Results: The result of exploratory and confirmatory factor analysis for investigating the Construct validity of the effort-reward imbalance model showed that in both analyses, the two factor model was confirmed. Moreover, findings indicate that balance group was in better psychological (p<0/01 and physical (migraine (p<0/05 status comparing to the imbalance group. These findings indicate the significance of justice to present appropriate reward relative to personnel performance on their health.   Conclusion: Implication of these findings can improve Iranian industrial personnel health from both physical and psychological aspects.  

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 method for critical systems in infinite volume: The planar Ising model.

Science.gov (United States)

Herdeiro, Victor; Doyon, Benjamin

2016-10-01

In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three-, and four-point of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.

Monte Carlo simulation of gas Cerenkov detectors

International Nuclear Information System (INIS)

Mack, J.M.; Jain, M.; Jordan, T.M.

1984-01-01

Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier

How Might Draining Lake Campotosto Affect Stress and Seismicity on the Monte Gorzano Normal Fault, Central Italy?

Science.gov (United States)

Verdecchia, A.; Deng, K.; Harrington, R. M.; Liu, Y.

2017-12-01

It is broadly accepted that large variations of water level in reservoirs may affect the stress state on nearby faults. While most studies consider the relationship between lake impoundment and the occurrence of large earthquakes or seismicity rate increases in the surrounding region, very few examples focus on the effects of lake drainage. The second largest reservoir in Europe, Lake Campotosto, is located on the hanging wall of the Monte Gorzano fault, an active normal fault responsible for at least two M ≥ 6 earthquakes in historical times. The northern part of this fault ruptured during the August 24, 2016, Mw 6.0 Amatrice earthquake, increasing the probability for a future large event on the southern section where an aftershock sequence is still ongoing. The proximity of the Campotosto reservoir to the active fault aroused general concern with respect to the stability of the three dams bounding the reservoir if the southern part of the Monte Gorzano fault produces a moderate earthquake. Local officials have proposed draining the reservoir as hazard mitigation strategy to avoid possible future catastrophes. In efforts to assess how draining the reservoir might affect earthquake nucleation on the fault, we use a finite-element poroelastic model to calculate the evolution of stress and pore pressure in terms of Coulomb stress changes that would be induced on the Monte Gorzano fault by emptying the Lake Campotosto reservoir. Preliminary results show that an instantaneous drainage of the lake will produce positive Coulomb stress changes, mostly on the shallower part of the fault (0 to 2 km), while a stress drop of the order of 0.2 bar is expected on the Monte Gorzano fault between 0 and 8 km depth. Earthquake hypocenters on the southern portion of the fault currently nucleate between 5 and 13 km depth, with activity distributed nearby the reservoir. Upcoming work will model the effects of varying fault geometry and elastic parameters, including geological

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.

Uncertainty analysis in Monte Carlo criticality computations

International Nuclear Information System (INIS)

Qi Ao

2011-01-01

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

Incentive Design and Mis-Allocated Effort

OpenAIRE

Schnedler, Wendelin

2013-01-01

Incentives often distort behavior: they induce agents to exert effort but this effort is not employed optimally. This paper proposes a theory of incentive design allowing for such distorted behavior. At the heart of the theory is a trade-off between getting the agent to exert effort and ensuring that this effort is used well. The theory covers various moral-hazard models, ranging from traditional single-task to multi-task models. It also provides -for the first time- a formalization and proof...

MONTE CARLO SIMULATION AND VALUATION: A STOCHASTIC APPROACH SIMULAÇÃO DE MONTE CARLO E VALUATION: UMA ABORDAGEM ESTOCÁSTICA

Directory of Open Access Journals (Sweden)

Marcos Roberto Gois de Oliveira

2013-01-01

Full Text Available Among the various business valuation methodologies, the discounted cash flow is still the most adopted nowadays on both academic and professional environment. Although many authors support thatmethodology as the most adequate one for business valuation, its projective feature implies in an uncertaintyissue presents in all financial models based on future expectations, the risk that the projected assumptionsdoes not occur. One of the alternatives to measure the risk inherent to the discounted cash flow valuation isto add Monte Carlo Simulation to the deterministic business valuation model in order to create a stochastic model, which can perform a statistic analysis of risk. The objective of this work was to evaluate thepertinence regarding the Monte Carlo Simulation adoption to measure the uncertainty inherent to the business valuation using discounted cash flow, identifying whether the Monte Carlo simulation enhance theaccuracy of this asset pricing methodology. The results of this work assures the operational e icacy ofdiscounted cash flow business valuation using Monte Carlo Simulation, confirming that the adoption of thatmethodology allows a relevant enhancement of the results in comparison with those obtained by using thedeterministic business valuation model.Dentre as diversas metodologias de avaliação de empresas, a avaliação por fluxo de caixa descontadocontinua sendo a mais adotada na atualidade, tanto no meio acadêmico como no profissional. Embora  essametodologia seja considerada por diversos autores como a mais adequada para a avaliação de empresas no contexto atual, seu caráter projetivo remete a um componente de incerteza presente em todos os modelos baseados em expectativas futuras o risco de as premissas de projeção adotadas não se concretizarem. Uma das alternativas para a mensuração do risco inerente à avaliação de empresas pelo fluxo de caixa descontadoconsiste na incorporação da Simulação de Monte

Monte Carlo code for neutron radiography

International Nuclear Information System (INIS)

Milczarek, Jacek J.; Trzcinski, Andrzej; El-Ghany El Abd, Abd; Czachor, Andrzej

2005-01-01

The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms

Monte Carlo code for neutron radiography

Energy Technology Data Exchange (ETDEWEB)

Milczarek, Jacek J. [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)]. E-mail: jjmilcz@cyf.gov.pl; Trzcinski, Andrzej [Institute for Nuclear Studies, Swierk, 05-400 Otwock (Poland); El-Ghany El Abd, Abd [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland); Nuclear Research Center, PC 13759, Cairo (Egypt); Czachor, Andrzej [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)

2005-04-21

The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms.