A neurocomputational model of automatic sequence production.

Science.gov (United States)

Helie, Sebastien; Roeder, Jessica L; Vucovich, Lauren; Rünger, Dennis; Ashby, F Gregory

2015-07-01

Most behaviors unfold in time and include a sequence of submovements or cognitive activities. In addition, most behaviors are automatic and repeated daily throughout life. Yet, relatively little is known about the neurobiology of automatic sequence production. Past research suggests a gradual transfer from the associative striatum to the sensorimotor striatum, but a number of more recent studies challenge this role of the BG in automatic sequence production. In this article, we propose a new neurocomputational model of automatic sequence production in which the main role of the BG is to train cortical-cortical connections within the premotor areas that are responsible for automatic sequence production. The new model is used to simulate four different data sets from human and nonhuman animals, including (1) behavioral data (e.g., RTs), (2) electrophysiology data (e.g., single-neuron recordings), (3) macrostructure data (e.g., TMS), and (4) neurological circuit data (e.g., inactivation studies). We conclude with a comparison of the new model with existing models of automatic sequence production and discuss a possible new role for the BG in automaticity and its implication for Parkinson's disease.

Automatic Monte-Carlo tuning for minimum bias events at the LHC

Energy Technology Data Exchange (ETDEWEB)

Kama, Sami

2010-06-22

The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10{sup 34} cm{sup -2}s{sup -1}. At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN{sub ch}/d{eta}, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and

Automatic Monte-Carlo tuning for minimum bias events at the LHC

International Nuclear Information System (INIS)

Kama, Sami

2010-01-01

The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10 34 cm -2 s -1 . At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN ch /dη, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and CMS show higher

Automatic construction of 3D-ASM intensity models by simulating image acquisition: application to myocardial gated SPECT studies.

Science.gov (United States)

Tobon-Gomez, Catalina; Butakoff, Constantine; Aguade, Santiago; Sukno, Federico; Moragas, Gloria; Frangi, Alejandro F

2008-11-01

Active shape models bear a great promise for model-based medical image analysis. Their practical use, though, is undermined due to the need to train such models on large image databases. Automatic building of point distribution models (PDMs) has been successfully addressed and a number of autolandmarking techniques are currently available. However, the need for strategies to automatically build intensity models around each landmark has been largely overlooked in the literature. This work demonstrates the potential of creating intensity models automatically by simulating image generation. We show that it is possible to reuse a 3D PDM built from computed tomography (CT) to segment gated single photon emission computed tomography (gSPECT) studies. Training is performed on a realistic virtual population where image acquisition and formation have been modeled using the SIMIND Monte Carlo simulator and ASPIRE image reconstruction software, respectively. The dataset comprised 208 digital phantoms (4D-NCAT) and 20 clinical studies. The evaluation is accomplished by comparing point-to-surface and volume errors against a proper gold standard. Results show that gSPECT studies can be successfully segmented by models trained under this scheme with subvoxel accuracy. The accuracy in estimated LV function parameters, such as end diastolic volume, end systolic volume, and ejection fraction, ranged from 90.0% to 94.5% for the virtual population and from 87.0% to 89.5% for the clinical population.

Automatic differentiation algorithms in model analysis

NARCIS (Netherlands)

Huiskes, M.J.

2002-01-01

Title: Automatic differentiation algorithms in model analysis
Author: M.J. Huiskes
Date: 19 March, 2002

In this thesis automatic differentiation algorithms and derivative-based methods

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

KAUST Repository

Li, Jun

2011-01-01

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

Shell model the Monte Carlo way

International Nuclear Information System (INIS)

Ormand, W.E.

1995-01-01

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

Shell model the Monte Carlo way

Energy Technology Data Exchange (ETDEWEB)

Ormand, W.E.

1995-03-01

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

Automatic terrain modeling using transfinite element analysis

KAUST Repository

Collier, Nathan; Calo, Victor M.

2010-01-01

An automatic procedure for modeling terrain is developed based on L2 projection-based interpolation of discrete terrain data onto transfinite function spaces. The function space is refined automatically by the use of image processing techniques

Monte Carlo Numerical Models for Nuclear Logging Applications

Directory of Open Access Journals (Sweden)

Fusheng Li

2012-06-01

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

Aspects of perturbative QCD in Monte Carlo shower models

International Nuclear Information System (INIS)

Gottschalk, T.D.

1986-01-01

The perturbative QCD content of Monte Carlo models for high energy hadron-hadron scattering is examined. Particular attention is given to the recently developed backwards evolution formalism for initial state parton showers, and the merging of parton shower evolution with hard scattering cross sections. Shower estimates of K-factors are discussed, and a simple scheme is presented for incorporating 2 → QCD cross sections into shower model calculations without double counting. Additional issues in the development of hard scattering Monte Carlo models are summarized. 69 references, 20 figures

Automatic crown cover mapping to improve forest inventory

Science.gov (United States)

Claude Vidal; Jean-Guy Boureau; Nicolas Robert; Nicolas Py; Josiane Zerubia; Xavier Descombes; Guillaume Perrin

2009-01-01

To automatically analyze near infrared aerial photographs, the French National Institute for Research in Computer Science and Control developed together with the French National Forest Inventory (NFI) a method for automatic crown cover mapping. This method uses a Reverse Jump Monte Carlo Markov Chain algorithm to locate the crowns and describe those using ellipses or...

Applying Hierarchical Model Calibration to Automatically Generated Items.

Science.gov (United States)

Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.

This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…

Advancements in reactor physics modelling methodology of Monte Carlo Burnup Code MCB dedicated to higher simulation fidelity of HTR cores

International Nuclear Information System (INIS)

Cetnar, Jerzy

2014-01-01

The recent development of MCB - Monte Carlo Continuous Energy Burn-up code is directed towards advanced description of modern reactors, including double heterogeneity structures that exist in HTR-s. In this, we exploit the advantages of MCB methodology in integrated approach, where physics, neutronics, burnup, reprocessing, non-stationary process modeling (control rod operation) and refined spatial modeling are carried in a single flow. This approach allows for implementations of advanced statistical options like analysis of error propagation, perturbation in time domain, sensitivity and source convergence analyses. It includes statistical analysis of burnup process, emitted particle collection, thermal-hydraulic coupling, automatic power profile calculations, advanced procedures of burnup step normalization and enhanced post processing capabilities. (author)

Monte Carlo simulation of Markov unreliability models

International Nuclear Information System (INIS)

Lewis, E.E.; Boehm, F.

1984-01-01

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

SPQR: a Monte Carlo reactor kinetics code

International Nuclear Information System (INIS)

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

1980-02-01

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

Automatic 3d Building Model Generations with Airborne LiDAR Data

Science.gov (United States)

Yastikli, N.; Cetin, Z.

2017-11-01

LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

Directory of Open Access Journals (Sweden)

N. Yastikli

2017-11-01

Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified

Studies of Monte Carlo Modelling of Jets at ATLAS

CERN Document Server

Kar, Deepak; The ATLAS collaboration

2017-01-01

The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets.  Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.

Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

Directory of Open Access Journals (Sweden)

Peng Song

2012-01-01

Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

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

Neuro-fuzzy system modeling based on automatic fuzzy clustering

Institute of Scientific and Technical Information of China (English)

Yuangang TANG; Fuchun SUN; Zengqi SUN

2005-01-01

A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

Conditional Monte Carlo randomization tests for regression models.

Science.gov (United States)

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

Automatic Flight Controller With Model Inversion

Science.gov (United States)

Meyer, George; Smith, G. Allan

1992-01-01

Automatic digital electronic control system based on inverse-model-follower concept being developed for proposed vertical-attitude-takeoff-and-landing airplane. Inverse-model-follower control places inverse mathematical model of dynamics of controlled plant in series with control actuators of controlled plant so response of combination of model and plant to command is unity. System includes feedback to compensate for uncertainties in mathematical model and disturbances imposed from without.

Model-Based Reasoning in Humans Becomes Automatic with Training.

Directory of Open Access Journals (Sweden)

Marcos Economides

2015-09-01

Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

Automatic terrain modeling using transfinite element analysis

KAUST Repository

Collier, Nathan

2010-05-31

An automatic procedure for modeling terrain is developed based on L2 projection-based interpolation of discrete terrain data onto transfinite function spaces. The function space is refined automatically by the use of image processing techniques to detect regions of high error and the flexibility of the transfinite interpolation to add degrees of freedom to these areas. Examples are shown of a section of the Palo Duro Canyon in northern Texas.

Development and applications of Super Monte Carlo Simulation Program for Advanced Nuclear Energy Systems

Energy Technology Data Exchange (ETDEWEB)

Wu, Y., E-mail: yican.wu@fds.org.cn [Inst. of Nuclear Energy Safety Technology, Hefei, Anhui (China)

2015-07-01

'Full text:' Super Monte Carlo Simulation Program for Advanced Nuclear Energy Systems (SuperMC) is a CAD-based Monte Carlo (MC) program for integrated simulation of nuclear system by making use of hybrid MC-deterministic method and advanced computer technologies. The main usability features are automatic modeling of geometry and physics, visualization and virtual simulation and cloud computing service. SuperMC 2.3, the latest version, can perform coupled neutron and photon transport calculation. SuperMC has been verified by more than 2000 benchmark models and experiments, and has been applied in tens of major nuclear projects, such as the nuclear design and analysis of International Thermonuclear Experimental Reactor (ITER) and China Lead-based reactor (CLEAR). Development and applications of SuperMC are introduced in this presentation. (author)

Development and applications of Super Monte Carlo Simulation Program for Advanced Nuclear Energy Systems

International Nuclear Information System (INIS)

Wu, Y.

2015-01-01

'Full text:' Super Monte Carlo Simulation Program for Advanced Nuclear Energy Systems (SuperMC) is a CAD-based Monte Carlo (MC) program for integrated simulation of nuclear system by making use of hybrid MC-deterministic method and advanced computer technologies. The main usability features are automatic modeling of geometry and physics, visualization and virtual simulation and cloud computing service. SuperMC 2.3, the latest version, can perform coupled neutron and photon transport calculation. SuperMC has been verified by more than 2000 benchmark models and experiments, and has been applied in tens of major nuclear projects, such as the nuclear design and analysis of International Thermonuclear Experimental Reactor (ITER) and China Lead-based reactor (CLEAR). Development and applications of SuperMC are introduced in this presentation. (author)

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

Automatic procedure for realistic 3D finite element modelling of human brain for bioelectromagnetic computations

International Nuclear Information System (INIS)

Aristovich, K Y; Khan, S H

2010-01-01

Realistic computer modelling of biological objects requires building of very accurate and realistic computer models based on geometric and material data, type, and accuracy of numerical analyses. This paper presents some of the automatic tools and algorithms that were used to build accurate and realistic 3D finite element (FE) model of whole-brain. These models were used to solve the forward problem in magnetic field tomography (MFT) based on Magnetoencephalography (MEG). The forward problem involves modelling and computation of magnetic fields produced by human brain during cognitive processing. The geometric parameters of the model were obtained from accurate Magnetic Resonance Imaging (MRI) data and the material properties - from those obtained from Diffusion Tensor MRI (DTMRI). The 3D FE models of the brain built using this approach has been shown to be very accurate in terms of both geometric and material properties. The model is stored on the computer in Computer-Aided Parametrical Design (CAD) format. This allows the model to be used in a wide a range of methods of analysis, such as finite element method (FEM), Boundary Element Method (BEM), Monte-Carlo Simulations, etc. The generic model building approach presented here could be used for accurate and realistic modelling of human brain and many other biological objects.

FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

Science.gov (United States)

De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.

2013-02-01

We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.

PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH

Directory of Open Access Journals (Sweden)

T. Mikhaylovskaya

2009-01-01

Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.

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.

The Role of Item Models in Automatic Item Generation

Science.gov (United States)

Gierl, Mark J.; Lai, Hollis

2012-01-01

Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…

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.

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...

forecasting with nonlinear time series model: a monte-carlo

African Journals Online (AJOL)

PUBLICATIONS1

Carlo method of forecasting using a special nonlinear time series model, called logistic smooth transition ... We illustrate this new method using some simulation ..... in MATLAB 7.5.0. ... process (DGP) using the logistic smooth transi-.

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%

ModelMage: a tool for automatic model generation, selection and management.

Science.gov (United States)

Flöttmann, Max; Schaber, Jörg; Hoops, Stephan; Klipp, Edda; Mendes, Pedro

2008-01-01

Mathematical modeling of biological systems usually involves implementing, simulating, and discriminating several candidate models that represent alternative hypotheses. Generating and managing these candidate models is a tedious and difficult task and can easily lead to errors. ModelMage is a tool that facilitates management of candidate models. It is designed for the easy and rapid development, generation, simulation, and discrimination of candidate models. The main idea of the program is to automatically create a defined set of model alternatives from a single master model. The user provides only one SBML-model and a set of directives from which the candidate models are created by leaving out species, modifiers or reactions. After generating models the software can automatically fit all these models to the data and provides a ranking for model selection, in case data is available. In contrast to other model generation programs, ModelMage aims at generating only a limited set of models that the user can precisely define. ModelMage uses COPASI as a simulation and optimization engine. Thus, all simulation and optimization features of COPASI are readily incorporated. ModelMage can be downloaded from http://sysbio.molgen.mpg.de/modelmage and is distributed as free software.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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.

Automatic trend estimation

CERN Document Server

Vamos¸, C˘alin

2013-01-01

Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

Science.gov (United States)

Dore, C.; Murphy, M.

2013-02-01

This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

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

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

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

[Modeling and implementation method for the automatic biochemistry analyzer control system].

Science.gov (United States)

Wang, Dong; Ge, Wan-cheng; Song, Chun-lin; Wang, Yun-guang

2009-03-01

In this paper the system structure The automatic biochemistry analyzer is a necessary instrument for clinical diagnostics. First of is analyzed. The system problems description and the fundamental principles for dispatch are brought forward. Then this text puts emphasis on the modeling for the automatic biochemistry analyzer control system. The objects model and the communications model are put forward. Finally, the implementation method is designed. It indicates that the system based on the model has good performance.

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

AUTOMATIC TEXTURE MAPPING OF ARCHITECTURAL AND ARCHAEOLOGICAL 3D MODELS

Directory of Open Access Journals (Sweden)

T. P. Kersten

2012-07-01

Full Text Available Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Automatic Texture Mapping of Architectural and Archaeological 3d Models

Science.gov (United States)

Kersten, T. P.; Stallmann, D.

2012-07-01

Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Inter Genre Similarity Modelling For Automatic Music Genre Classification

OpenAIRE

Bagci, Ulas; Erzin, Engin

2009-01-01

Music genre classification is an essential tool for music information retrieval systems and it has been finding critical applications in various media platforms. Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modelling (IGS) to improve the performance of automatic music genre classification. Inter-genre similarity information is extracted over the mis-classified feature population....

Monte Carlo Euler approximations of HJM term structure financial models

KAUST Repository

Björk, Tomas

2012-11-22

We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.

Monte Carlo Euler approximations of HJM term structure financial models

KAUST Repository

Bjö rk, Tomas; Szepessy, Anders; Tempone, Raul; Zouraris, Georgios E.

2012-01-01

We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.

Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

Science.gov (United States)

Hansen, T. M.; Cordua, K. S.

2017-12-01

Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

Automatic generation of Fortran programs for algebraic simulation models

International Nuclear Information System (INIS)

Schopf, W.; Rexer, G.; Ruehle, R.

1978-04-01

This report documents a generator program by which econometric simulation models formulated in an application-orientated language can be transformed automatically in a Fortran program. Thus the model designer is able to build up, test and modify models without the need of a Fortran programmer. The development of a computer model is therefore simplified and shortened appreciably; in chapter 1-3 of this report all rules are presented for the application of the generator to the model design. Algebraic models including exogeneous and endogeneous time series variables, lead and lag function can be generated. In addition, to these language elements, Fortran sequences can be applied to the formulation of models in the case of complex model interrelations. Automatically the generated model is a module of the program system RSYST III and is therefore able to exchange input and output data with the central data bank of the system and in connection with the method library modules can be used to handle planning problems. (orig.) [de

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.

Hypothesis testing of scientific Monte Carlo calculations

Science.gov (United States)

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

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.

Monte Carlo methods for shield design calculations

International Nuclear Information System (INIS)

Grimstone, M.J.

1974-01-01

A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)

Automatization of hydrodynamic modelling in a Floreon+ system

Science.gov (United States)

Ronovsky, Ales; Kuchar, Stepan; Podhoranyi, Michal; Vojtek, David

2017-07-01

The paper describes fully automatized hydrodynamic modelling as a part of the Floreon+ system. The main purpose of hydrodynamic modelling in the disaster management is to provide an accurate overview of the hydrological situation in a given river catchment. Automatization of the process as a web service could provide us with immediate data based on extreme weather conditions, such as heavy rainfall, without the intervention of an expert. Such a service can be used by non scientific users such as fire-fighter operators or representatives of a military service organizing evacuation during floods or river dam breaks. The paper describes the whole process beginning with a definition of a schematization necessary for hydrodynamic model, gathering of necessary data and its processing for a simulation, the model itself and post processing of a result and visualization on a web service. The process is demonstrated on a real data collected during floods in our Moravian-Silesian region in 2010.

Model study of an automatic controller of the IBR-2 pulsed reactor

International Nuclear Information System (INIS)

Pepelyshev, Yu.N.; Popov, A.K.

2007-01-01

For calculation of power transients in the IBR-2 reactor a special mathematical model of dynamics taking into account the discontinuous jump of reactivity by an automatic controller with the step motor is created. In the model the nonlinear dependence of the energy of power pulse on the reactivity and the influence of warming up of the reactor on the reactivity by means of introduction of a nonlinear feedback 'power-pulse energy - reactivity' are taken into account. With the help of the model the transients of relative deviation of power-pulse energy are calculated at various (random, mixed and regular) reactivity disturbances at the reactor mean power 1.475 MW. It is shown that to improve the quality of processes the choice of such regular values of parameters of the automatic controller is expedient, at which the least effect of smoothing of a signal acting on an automatic controller and the least speed of an automatic controller are provided, and the reduction of efficiency of one step of the automatic controller and introduction of a five-percent dead space are also expedient

Using suggestion to model different types of automatic writing.

Science.gov (United States)

Walsh, E; Mehta, M A; Oakley, D A; Guilmette, D N; Gabay, A; Halligan, P W; Deeley, Q

2014-05-01

Our sense of self includes awareness of our thoughts and movements, and our control over them. This feeling can be altered or lost in neuropsychiatric disorders as well as in phenomena such as "automatic writing" whereby writing is attributed to an external source. Here, we employed suggestion in highly hypnotically suggestible participants to model various experiences of automatic writing during a sentence completion task. Results showed that the induction of hypnosis, without additional suggestion, was associated with a small but significant reduction of control, ownership, and awareness for writing. Targeted suggestions produced a double dissociation between thought and movement components of writing, for both feelings of control and ownership, and additionally, reduced awareness of writing. Overall, suggestion produced selective alterations in the control, ownership, and awareness of thought and motor components of writing, thus enabling key aspects of automatic writing, observed across different clinical and cultural settings, to be modelled. Copyright © 2014. Published by Elsevier Inc.

Automatic modeling using PENELOPE of two HPGe detectors used for measurement of environmental samples by γ-spectrometry from a few sets of experimental efficiencies

Science.gov (United States)

Guerra, J. G.; Rubiano, J. G.; Winter, G.; Guerra, A. G.; Alonso, H.; Arnedo, M. A.; Tejera, A.; Mosqueda, F.; Martel, P.; Bolivar, J. P.

2018-02-01

The aim of this paper is to characterize two HPGe gamma-ray detectors used in two different laboratories for environmental radioactivity measurements, so as to perform efficiency calibrations by means of Monte Carlo Simulation. To achieve such an aim, methodologies developed in previous papers have been applied, based on the automatic optimization of the model of detector, so that the differences between computational and reference FEPEs are minimized. In this work, such reference FEPEs have been obtained experimentally from several measurements of the IAEA RGU-1 reference material for specific source-detector arrangements. The models of both detectors built through these methodologies have been validated by comparing with experimental results for several reference materials and different measurement geometries, showing deviations below 10% in most cases.

Monte Carlo simulation on nuclear energy study. Annual report of Nuclear Code Evaluation Committee

International Nuclear Information System (INIS)

Sakurai, Kiyoshi; Yamamoto, Toshihiro

1999-03-01

In this report, research results discussed in 1998 fiscal year at Nuclear Code Evaluation Special Committee of Nuclear Code Committee were summarised. Present status of Monte Carlo calculation in high energy region investigated / discussed at Monte Carlo simulation working-group and automatic compilation system for MCNP cross sections developed at MCNP high temperature library compilation working-group were described. The 6 papers are indexed individually. (J.P.N.)

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 paper sliceform design from 3D solid models.

Science.gov (United States)

Le-Nguyen, Tuong-Vu; Low, Kok-Lim; Ruiz, Conrado; Le, Sang N

2013-11-01

A paper sliceform or lattice-style pop-up is a form of papercraft that uses two sets of parallel paper patches slotted together to make a foldable structure. The structure can be folded flat, as well as fully opened (popped-up) to make the two sets of patches orthogonal to each other. Automatic design of paper sliceforms is still not supported by existing computational models and remains a challenge. We propose novel geometric formulations of valid paper sliceform designs that consider the stability, flat-foldability and physical realizability of the designs. Based on a set of sufficient construction conditions, we also present an automatic algorithm for generating valid sliceform designs that closely depict the given 3D solid models. By approximating the input models using a set of generalized cylinders, our method significantly reduces the search space for stable and flat-foldable sliceforms. To ensure the physical realizability of the designs, the algorithm automatically generates slots or slits on the patches such that no two cycles embedded in two different patches are interlocking each other. This guarantees local pairwise assembility between patches, which is empirically shown to lead to global assembility. Our method has been demonstrated on a number of example models, and the output designs have been successfully made into real paper sliceforms.

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

International Nuclear Information System (INIS)

Turner, S.A.

1996-02-01

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

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

Science.gov (United States)

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

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.

Next Generation Model 8800 Automatic TLD Reader

International Nuclear Information System (INIS)

Velbeck, K.J.; Streetz, K.L.; Rotunda, J.E.

1999-01-01

BICRON NE has developed an advanced version of the Model 8800 Automatic TLD Reader. Improvements in the reader include a Windows NT TM -based operating system and a Pentium microprocessor for the host controller, a servo-controlled transport, a VGA display, mouse control, and modular assembly. This high capacity reader will automatically read fourteen hundred TLD Cards in one loading. Up to four elements in a card can be heated without mechanical contact, using hot nitrogen gas. Improvements in performance include an increased throughput rate and more precise card positioning. Operation is simplified through easy-to-read Windows-type screens. Glow curves are displayed graphically along with light intensity, temperature, and channel scaling. Maintenance and diagnostic aids are included for easier troubleshooting. A click of a mouse will command actions that are displayed in easy-to-understand English words. Available options include an internal 90 Sr irradiator, automatic TLD calibration, and two different extremity monitoring modes. Results from testing include reproducibility, reader stability, linearity, detection threshold, residue, primary power supply voltage and frequency, transient voltage, drop testing, and light leakage. (author)

TestDose: A nuclear medicine software based on Monte Carlo modeling for generating gamma camera acquisitions and dosimetry

Energy Technology Data Exchange (ETDEWEB)

Garcia, Marie-Paule, E-mail: marie-paule.garcia@univ-brest.fr; Villoing, Daphnée [UMR 1037 INSERM/UPS, CRCT, 133 Route de Narbonne, 31062 Toulouse (France); McKay, Erin [St George Hospital, Gray Street, Kogarah, New South Wales 2217 (Australia); Ferrer, Ludovic [ICO René Gauducheau, Boulevard Jacques Monod, St Herblain 44805 (France); Cremonesi, Marta; Botta, Francesca; Ferrari, Mahila [European Institute of Oncology, Via Ripamonti 435, Milano 20141 (Italy); Bardiès, Manuel [UMR 1037 INSERM/UPS, CRCT, 133 Route de Narbonne, Toulouse 31062 (France)

2015-12-15

Purpose: The TestDose platform was developed to generate scintigraphic imaging protocols and associated dosimetry by Monte Carlo modeling. TestDose is part of a broader project (www.dositest.com) whose aim is to identify the biases induced by different clinical dosimetry protocols. Methods: The TestDose software allows handling the whole pipeline from virtual patient generation to resulting planar and SPECT images and dosimetry calculations. The originality of their approach relies on the implementation of functional segmentation for the anthropomorphic model representing a virtual patient. Two anthropomorphic models are currently available: 4D XCAT and ICRP 110. A pharmacokinetic model describes the biodistribution of a given radiopharmaceutical in each defined compartment at various time-points. The Monte Carlo simulation toolkit GATE offers the possibility to accurately simulate scintigraphic images and absorbed doses in volumes of interest. The TestDose platform relies on GATE to reproduce precisely any imaging protocol and to provide reference dosimetry. For image generation, TestDose stores user’s imaging requirements and generates automatically command files used as input for GATE. Each compartment is simulated only once and the resulting output is weighted using pharmacokinetic data. Resulting compartment projections are aggregated to obtain the final image. For dosimetry computation, emission data are stored in the platform database and relevant GATE input files are generated for the virtual patient model and associated pharmacokinetics. Results: Two samples of software runs are given to demonstrate the potential of TestDose. A clinical imaging protocol for the Octreoscan™ therapeutical treatment was implemented using the 4D XCAT model. Whole-body “step and shoot” acquisitions at different times postinjection and one SPECT acquisition were generated within reasonable computation times. Based on the same Octreoscan™ kinetics, a dosimetry

Development of a practical Monte Carlo based fuel management system for the Penn State University Breazeale Research Reactor (PSBR)

International Nuclear Information System (INIS)

Tippayakul, Chanatip; Ivanov, Kostadin; Frederick Sears, C.

2008-01-01

A practical fuel management system for the he Pennsylvania State University Breazeale Research Reactor (PSBR) based on the advanced Monte Carlo methodology was developed from the existing fuel management tool in this research. Several modeling improvements were implemented to the old system. The improved fuel management system can now utilize the burnup dependent cross section libraries generated specifically for PSBR fuel and it is also able to update the cross sections of these libraries by the Monte Carlo calculation automatically. Considerations were given to balance the computation time and the accuracy of the cross section update. Thus, certain types of a limited number of isotopes, which are considered 'important', are calculated and updated by the scheme. Moreover, the depletion algorithm of the existing fuel management tool was replaced from the predictor only to the predictor-corrector depletion scheme to account for burnup spectrum changes during the burnup step more accurately. An intermediate verification of the fuel management system was performed to assess the correctness of the newly implemented schemes against HELIOS. It was found that the agreement of both codes is good when the same energy released per fission (Q values) is used. Furthermore, to be able to model the reactor at various temperatures, the fuel management tool is able to utilize automatically the continuous cross sections generated at different temperatures. Other additional useful capabilities were also added to the fuel management tool to make it easy to use and be practical. As part of the development, a hybrid nodal diffusion/Monte Carlo calculation was devised to speed up the Monte Carlo calculation by providing more converged initial source distribution for the Monte Carlo calculation from the nodal diffusion calculation. Finally, the fuel management system was validated against the measured data using several actual PSBR core loadings. The agreement of the predicted core

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.

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

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 ...

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 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.

Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation

DEFF Research Database (Denmark)

Mangado Lopez, Nerea; Ceresa, Mario; Duchateau, Nicolas

2016-01-01

. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient......'s CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns......Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging...

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)

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

Automatic discovery of the communication network topology for building a supercomputer model

Science.gov (United States)

Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim

2016-10-01

The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.

AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models

DEFF Research Database (Denmark)

Fournier, David A.; Skaug, Hans J.; Ancheta, Johnoel

2011-01-01

Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated as a nonlinear optimization problem.Automatic Differentiation Model Builder (ADMB) is a programming framework based on automatic differentiation, aimed at highly nonlinear models with a large number...... of such a feature is the generic implementation of Laplace approximation of high-dimensional integrals for use in latent variable models. We also review the literature in which ADMB has been used, and discuss future development of ADMB as an open source project. Overall, the main advantages ofADMB are flexibility...

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition

Science.gov (United States)

Lu, Haiping; Plataniotis, Konstantinos N.; Venetsanopoulos, Anastasios N.

2007-12-01

This paper proposes a full-body layered deformable model (LDM) inspired by manually labeled silhouettes for automatic model-based gait recognition from part-level gait dynamics in monocular video sequences. The LDM is defined for the fronto-parallel gait with 22 parameters describing the human body part shapes (widths and lengths) and dynamics (positions and orientations). There are four layers in the LDM and the limbs are deformable. Algorithms for LDM-based human body pose recovery are then developed to estimate the LDM parameters from both manually labeled and automatically extracted silhouettes, where the automatic silhouette extraction is through a coarse-to-fine localization and extraction procedure. The estimated LDM parameters are used for model-based gait recognition by employing the dynamic time warping for matching and adopting the combination scheme in AdaBoost.M2. While the existing model-based gait recognition approaches focus primarily on the lower limbs, the estimated LDM parameters enable us to study full-body model-based gait recognition by utilizing the dynamics of the upper limbs, the shoulders and the head as well. In the experiments, the LDM-based gait recognition is tested on gait sequences with differences in shoe-type, surface, carrying condition and time. The results demonstrate that the recognition performance benefits from not only the lower limb dynamics, but also the dynamics of the upper limbs, the shoulders and the head. In addition, the LDM can serve as an analysis tool for studying factors affecting the gait under various conditions.

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

MCB. A continuous energy Monte Carlo burnup simulation code

International Nuclear Information System (INIS)

Cetnar, J.; Wallenius, J.; Gudowski, W.

1999-01-01

A code for integrated simulation of neutrinos and burnup based upon continuous energy Monte Carlo techniques and transmutation trajectory analysis has been developed. Being especially well suited for studies of nuclear waste transmutation systems, the code is an extension of the well validated MCNP transport program of Los Alamos National Laboratory. Among the advantages of the code (named MCB) is a fully integrated data treatment combined with a time-stepping routine that automatically corrects for burnup dependent changes in reaction rates, neutron multiplication, material composition and self-shielding. Fission product yields are treated as continuous functions of incident neutron energy, using a non-equilibrium thermodynamical model of the fission process. In the present paper a brief description of the code and applied methods are given. (author)

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.

Automatic generation of anatomic characteristics from cerebral aneurysm surface models.

Science.gov (United States)

Neugebauer, M; Lawonn, K; Beuing, O; Preim, B

2013-03-01

Computer-aided research on cerebral aneurysms often depends on a polygonal mesh representation of the vessel lumen. To support a differentiated, anatomy-aware analysis, it is necessary to derive anatomic descriptors from the surface model. We present an approach on automatic decomposition of the adjacent vessels into near- and far-vessel regions and computation of the axial plane. We also exemplarily present two applications of the geometric descriptors: automatic computation of a unique vessel order and automatic viewpoint selection. Approximation methods are employed to analyze vessel cross-sections and the vessel area profile along the centerline. The resulting transition zones between near- and far- vessel regions are used as input for an optimization process to compute the axial plane. The unique vessel order is defined via projection into the plane space of the axial plane. The viewing direction for the automatic viewpoint selection is derived from the normal vector of the axial plane. The approach was successfully applied to representative data sets exhibiting a broad variability with respect to the configuration of their adjacent vessels. A robustness analysis showed that the automatic decomposition is stable against noise. A survey with 4 medical experts showed a broad agreement with the automatically defined transition zones. Due to the general nature of the underlying algorithms, this approach is applicable to most of the likely aneurysm configurations in the cerebral vasculature. Additional geometric information obtained during automatic decomposition can support correction in case the automatic approach fails. The resulting descriptors can be used for various applications in the field of visualization, exploration and analysis of cerebral aneurysms.

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.

Path Tracking Control of Automatic Parking Cloud Model considering the Influence of Time Delay

Directory of Open Access Journals (Sweden)

Yiding Hua

2017-01-01

Full Text Available This paper establishes the kinematic model of the automatic parking system and analyzes the kinematic constraints of the vehicle. Furthermore, it solves the problem where the traditional automatic parking system model fails to take into account the time delay. Firstly, based on simulating calculation, the influence of time delay on the dynamic trajectory of a vehicle in the automatic parking system is analyzed under the transverse distance Dlateral between different target spaces. Secondly, on the basis of cloud model, this paper utilizes the tracking control of an intelligent path closer to human intelligent behavior to further study the Cloud Generator-based parking path tracking control method and construct a vehicle path tracking control model. Moreover, tracking and steering control effects of the model are verified through simulation analysis. Finally, the effectiveness and timeliness of automatic parking controller in the aspect of path tracking are tested through a real vehicle experiment.

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.

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.

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)

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...

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

International Nuclear Information System (INIS)

Wu, Y.; Song, J.; Zheng, H.; Sun, G.; Hao, L.; Long, P.; Hu, L.

2013-01-01

SuperMC is a (Computer-Aided-Design) CAD-based Monte Carlo (MC) program for integrated simulation of nuclear systems developed by FDS Team (China), making use of hybrid MC-deterministic method and advanced computer technologies. The design aim, architecture and main methodology of SuperMC are presented in this paper. The taking into account of multi-physics processes and the use of advanced computer technologies such as automatic geometry modeling, intelligent data analysis and visualization, high performance parallel computing and cloud computing, contribute to the efficiency of the code. SuperMC2.1, the latest version of the code for neutron, photon and coupled neutron and photon transport calculation, has been developed and validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model

The design of control algorithm for automatic start-up model of HWRR

International Nuclear Information System (INIS)

Guo Wenqi

1990-01-01

The design of control algorithm for automatic start-up model of HWRR (Heavy Water Research Reactor), the calculation of μ value and the application of digital compensator are described. Finally The flow diagram of the automatic start-up and digital compensator program for HWRR are given

Automatic commissioning of a GPU-based Monte Carlo radiation dose calculation code for photon radiotherapy

International Nuclear Information System (INIS)

Tian, Zhen; Jia, Xun; Jiang, Steve B; Graves, Yan Jiang

2014-01-01

Monte Carlo (MC) simulation is commonly considered as the most accurate method for radiation dose calculations. Commissioning of a beam model in the MC code against a clinical linear accelerator beam is of crucial importance for its clinical implementation. In this paper, we propose an automatic commissioning method for our GPU-based MC dose engine, gDPM. gDPM utilizes a beam model based on a concept of phase-space-let (PSL). A PSL contains a group of particles that are of the same type and close in space and energy. A set of generic PSLs was generated by splitting a reference phase-space file. Each PSL was associated with a weighting factor, and in dose calculations the particle carried a weight corresponding to the PSL where it was from. Dose for each PSL in water was pre-computed, and hence the dose in water for a whole beam under a given set of PSL weighting factors was the weighted sum of the PSL doses. At the commissioning stage, an optimization problem was solved to adjust the PSL weights in order to minimize the difference between the calculated dose and measured one. Symmetry and smoothness regularizations were utilized to uniquely determine the solution. An augmented Lagrangian method was employed to solve the optimization problem. To validate our method, a phase-space file of a Varian TrueBeam 6 MV beam was used to generate the PSLs for 6 MV beams. In a simulation study, we commissioned a Siemens 6 MV beam on which a set of field-dependent phase-space files was available. The dose data of this desired beam for different open fields and a small off-axis open field were obtained by calculating doses using these phase-space files. The 3D γ-index test passing rate within the regions with dose above 10% of d max dose for those open fields tested was improved averagely from 70.56 to 99.36% for 2%/2 mm criteria and from 32.22 to 89.65% for 1%/1 mm criteria. We also tested our commissioning method on a six-field head-and-neck cancer IMRT plan. The

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.

Fully automatic adjoints: a robust and efficient mechanism for generating adjoint ocean models

Science.gov (United States)

Ham, D. A.; Farrell, P. E.; Funke, S. W.; Rognes, M. E.

2012-04-01

The problem of generating and maintaining adjoint models is sufficiently difficult that typically only the most advanced and well-resourced community ocean models achieve it. There are two current technologies which each suffer from their own limitations. Algorithmic differentiation, also called automatic differentiation, is employed by models such as the MITGCM [2] and the Alfred Wegener Institute model FESOM [3]. This technique is very difficult to apply to existing code, and requires a major initial investment to prepare the code for automatic adjoint generation. AD tools may also have difficulty with code employing modern software constructs such as derived data types. An alternative is to formulate the adjoint differential equation and to discretise this separately. This approach, known as the continuous adjoint and employed in ROMS [4], has the disadvantage that two different model code bases must be maintained and manually kept synchronised as the model develops. The discretisation of the continuous adjoint is not automatically consistent with that of the forward model, producing an additional source of error. The alternative presented here is to formulate the flow model in the high level language UFL (Unified Form Language) and to automatically generate the model using the software of the FEniCS project. In this approach it is the high level code specification which is differentiated, a task very similar to the formulation of the continuous adjoint [5]. However since the forward and adjoint models are generated automatically, the difficulty of maintaining them vanishes and the software engineering process is therefore robust. The scheduling and execution of the adjoint model, including the application of an appropriate checkpointing strategy is managed by libadjoint [1]. In contrast to the conventional algorithmic differentiation description of a model as a series of primitive mathematical operations, libadjoint employs a new abstraction of the simulation

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

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.

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.

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.

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)

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...

GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

Science.gov (United States)

Wang, Jie; Shen, Yuzhong

2011-01-01

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

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.

Automatic Detection and Resolution of Lexical Ambiguity in Process Models

NARCIS (Netherlands)

Pittke, F.; Leopold, H.; Mendling, J.

2015-01-01

System-related engineering tasks are often conducted using process models. In this context, it is essential that these models do not contain structural or terminological inconsistencies. To this end, several automatic analysis techniques have been proposed to support quality assurance. While formal

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

Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

Directory of Open Access Journals (Sweden)

Y.A. Ahmed

2015-09-01

Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

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.

MDTS: automatic complex materials design using Monte Carlo tree search

Science.gov (United States)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Developing free software for automatic registration for the quality control of IMRT with movies

International Nuclear Information System (INIS)

Moral, F. del; Meilan, E.; Pereira, L.; Salvador, F.; Munoz, V.; Salgado, M.

2011-01-01

In this work, as the commissioner of the e-JMRT, a Monte Carlo calculation network for IMRT planning, has developed software for the automatic recording of the image of the film with the results of the planning system.

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

Automatic 3D modeling of the urban landscape

NARCIS (Netherlands)

Esteban, I.; Dijk, J.; Groen, F.

2010-01-01

In this paper we present a fully automatic system for building 3D models of urban areas at the street level. We propose a novel approach for the accurate estimation of the scale consistent camera pose given two previous images. We employ a new method for global optimization and use a novel sampling

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.

CMS Monte Carlo production in the WLCG computing grid

International Nuclear Information System (INIS)

Hernandez, J M; Kreuzer, P; Hof, C; Khomitch, A; Mohapatra, A; Filippis, N D; Pompili, A; My, S; Abbrescia, M; Maggi, G; Donvito, G; Weirdt, S D; Maes, J; Mulders, P v; Villella, I; Wakefield, S; Guan, W; Fanfani, A; Evans, D; Flossdorf, A

2008-01-01

Monte Carlo production in CMS has received a major boost in performance and scale since the past CHEP06 conference. The production system has been re-engineered in order to incorporate the experience gained in running the previous system and to integrate production with the new CMS event data model, data management system and data processing framework. The system is interfaced to the two major computing Grids used by CMS, the LHC Computing Grid (LCG) and the Open Science Grid (OSG). Operational experience and integration aspects of the new CMS Monte Carlo production system is presented together with an analysis of production statistics. The new system automatically handles job submission, resource monitoring, job queuing, job distribution according to the available resources, data merging, registration of data into the data bookkeeping, data location, data transfer and placement systems. Compared to the previous production system automation, reliability and performance have been considerably improved. A more efficient use of computing resources and a better handling of the inherent Grid unreliability have resulted in an increase of production scale by about an order of magnitude, capable of running in parallel at the order of ten thousand jobs and yielding more than two million events per day

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.

Development of a cerebral circulation model for the automatic control of brain physiology.

Science.gov (United States)

Utsuki, T

2015-01-01

In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.

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

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 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

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.

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

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

Monte-Carlo Simulation and Automated Test Bench for Developing a Multichannel NIR-Based Vital-Signs Monitor.

Science.gov (United States)

Bruser, Christoph; Strutz, Nils; Winter, Stefan; Leonhardt, Steffen; Walter, Marian

2015-06-01

Unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms using only non-invasive vibration sensors mounted in beds promises to unlock new applications in home and low acuity monitoring. This paper presents a novel concept for such a system based on an array of near infrared (NIR) sensors placed underneath a regular bed mattress. We focus on modeling and analyzing the underlying technical measurement principle with the help of a 2D model of a polyurethane foam mattress and Monte-Carlo simulations of the opto-mechanical interaction responsible for signal genesis. Furthermore, a test rig to automatically and repeatably impress mechanical vibrations onto a mattress is introduced and used to identify the properties of a prototype implementation of the proposed measurement principle. Results show that NIR-based sensing is capable of registering miniscule deformations of the mattress with a high spatial specificity. As a final outlook, proof-of-concept measurements with the sensor array are presented which demonstrate that cardiorespiratory movements of the body can be detected and that automatic heart rate estimation at competitive error levels is feasible with the proposed approach.

Using UML to Model Web Services for Automatic Composition

OpenAIRE

Amal Elgammal; Mohamed El-Sharkawi

2010-01-01

There is a great interest paid to the web services paradigm nowadays. One of the most important problems related to the web service paradigm is the automatic composition of web services. Several frameworks have been proposed to achieve this novel goal. The most recent and richest framework (model) is the Colombo model. However, even for experienced developers, working with Colombo formalisms is low-level, very complex and timeconsuming. We propose to use UML (Unified Modeling Language) to mod...

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

Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation.

Science.gov (United States)

Mangado, Nerea; Ceresa, Mario; Duchateau, Nicolas; Kjer, Hans Martin; Vera, Sergio; Dejea Velardo, Hector; Mistrik, Pavel; Paulsen, Rasmus R; Fagertun, Jens; Noailly, Jérôme; Piella, Gemma; González Ballester, Miguel Ángel

2016-08-01

Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.

Small-Scale Helicopter Automatic Autorotation : Modeling, Guidance, and Control

NARCIS (Netherlands)

Taamallah, S.

2015-01-01

Our research objective consists in developing a, model-based, automatic safety recovery system, for a small-scale helicopter Unmanned Aerial Vehicle (UAV) in autorotation, i.e. an engine OFF flight condition, that safely flies and lands the helicopter to a pre-specified ground location. In pursuit

Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data

Science.gov (United States)

Yu, Q.; Helmholz, P.; Belton, D.; West, G.

2014-04-01

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.

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

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 codes and Monte Carlo simulator program

International Nuclear Information System (INIS)

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

1990-03-01

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

Monte Carlo 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

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)

Automatic Generation of Cycle-Approximate TLMs with Timed RTOS Model Support

Science.gov (United States)

Hwang, Yonghyun; Schirner, Gunar; Abdi, Samar

This paper presents a technique for automatically generating cycle-approximate transaction level models (TLMs) for multi-process applications mapped to embedded platforms. It incorporates three key features: (a) basic block level timing annotation, (b) RTOS model integration, and (c) RTOS overhead delay modeling. The inputs to TLM generation are application C processes and their mapping to processors in the platform. A processor data model, including pipelined datapath, memory hierarchy and branch delay model is used to estimate basic block execution delays. The delays are annotated to the C code, which is then integrated with a generated SystemC RTOS model. Our abstract RTOS provides dynamic scheduling and inter-process communication (IPC) with processor- and RTOS-specific pre-characterized timing. Our experiments using a MP3 decoder and a JPEG encoder show that timed TLMs, with integrated RTOS models, can be automatically generated in less than a minute. Our generated TLMs simulated three times faster than real-time and showed less than 10% timing error compared to board measurements.

Automatic generation of statistical pose and shape models for articulated joints.

Science.gov (United States)

Xin Chen; Graham, Jim; Hutchinson, Charles; Muir, Lindsay

2014-02-01

Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint like the wrist. We present a novel framework for simultaneous registration and segmentation of multiple 3-D (CT or MR) volumes of different subjects at various articulated positions. The framework starts with a pose model generated from 3-D volumes captured at different articulated positions of a single subject (template). This initial pose model is used to register the template volume to image volumes from new subjects. During this process, the Grow-Cut algorithm is used in an iterative refinement of the segmentation of the bone along with the pose parameters. As each new subject is registered and segmented, the pose model is updated, improving the accuracy of successive registrations. We applied the algorithm to CT images of the wrist from 25 subjects, each at five different wrist positions and demonstrated that it performed robustly and accurately. More importantly, the resulting segmentations allowed a statistical pose model of the carpal bones to be generated automatically without interaction. The evaluation results show that our proposed framework achieved accurate registration with an average mean target registration error of 0.34 ±0.27 mm. The automatic segmentation results also show high consistency with the ground truth obtained semi-automatically. Furthermore, we demonstrated the capability of the resulting statistical pose and shape models by using them to generate a measurement tool for scaphoid-lunate dissociation diagnosis, which achieved 90% sensitivity and specificity.

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...

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

International Nuclear Information System (INIS)

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

2003-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2003-07-01

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

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...

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 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)

A general graphical user interface for automatic reliability modeling

Science.gov (United States)

Liceaga, Carlos A.; Siewiorek, Daniel P.

1991-01-01

Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.

Component simulation in problems of calculated model formation of automatic machine mechanisms

Directory of Open Access Journals (Sweden)

Telegin Igor

2017-01-01

Full Text Available The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gaps in kinematic pairs, friction forces, design and technological loads. As an example in the paper there are considered a formalization of stages in the computer model formation of the cutting mechanism in cold stamping automatic machine AV1818 and methods of for the computation of their parameters on the basis of its solid-state model.

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.

Automatic Model-Based Generation of Parameterized Test Cases Using Data Abstraction

NARCIS (Netherlands)

Calamé, Jens R.; Ioustinova, Natalia; Romijn, J.M.T.; Smith, G.; van de Pol, Jan Cornelis

2007-01-01

Developing test suites is a costly and error-prone process. Model-based test generation tools facilitate this process by automatically generating test cases from system models. The applicability of these tools, however, depends on the size of the target systems. Here, we propose an approach to

Automatic creation of Markov models for reliability assessment of safety instrumented systems

International Nuclear Information System (INIS)

Guo Haitao; Yang Xianhui

2008-01-01

After the release of new international functional safety standards like IEC 61508, people care more for the safety and availability of safety instrumented systems. Markov analysis is a powerful and flexible technique to assess the reliability measurements of safety instrumented systems, but it is fallible and time-consuming to create Markov models manually. This paper presents a new technique to automatically create Markov models for reliability assessment of safety instrumented systems. Many safety related factors, such as failure modes, self-diagnostic, restorations, common cause and voting, are included in Markov models. A framework is generated first based on voting, failure modes and self-diagnostic. Then, repairs and common-cause failures are incorporated into the framework to build a complete Markov model. Eventual simplification of Markov models can be done by state merging. Examples given in this paper show how explosively the size of Markov model increases as the system becomes a little more complicated as well as the advancement of automatic creation of Markov models

CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

Science.gov (United States)

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-04-01

Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

CT-based patient modeling for head and neck hyperthermia treatment planning: Manual versus automatic normal-tissue-segmentation

International Nuclear Information System (INIS)

Verhaart, René F.; Fortunati, Valerio; Verduijn, Gerda M.; Walsum, Theo van; Veenland, Jifke F.; Paulides, Margarethus M.

2014-01-01

Background and purpose: Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H and N) carcinoma. Hyperthermia treatment planning (HTP) guided H and N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. Material and methods: CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Results: Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Conclusions: Automatically generated 3D patient models can be introduced in the clinic for H and N HTP

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.

Monte Carlo method implementation on IPSC 860 for the resolution of the Boltzmann equation

International Nuclear Information System (INIS)

AloUGES, Francois

1993-01-01

This note deals with the implementation on a massively parallel machine (IPSC-860) of a Monte-Carlo method aiming at resolving the Boltzmann equation. The parallelism of the machine incites to consider a multi-domain approach and poses the problem of the automatic generation of local meshes from a non-structured 3-D global mesh [fr

Uncertainties in models of tropospheric ozone based on Monte Carlo analysis: Tropospheric ozone burdens, atmospheric lifetimes and surface distributions

Science.gov (United States)

Derwent, Richard G.; Parrish, David D.; Galbally, Ian E.; Stevenson, David S.; Doherty, Ruth M.; Naik, Vaishali; Young, Paul J.

2018-05-01

Recognising that global tropospheric ozone models have many uncertain input parameters, an attempt has been made to employ Monte Carlo sampling to quantify the uncertainties in model output that arise from global tropospheric ozone precursor emissions and from ozone production and destruction in a global Lagrangian chemistry-transport model. Ninety eight quasi-randomly Monte Carlo sampled model runs were completed and the uncertainties were quantified in tropospheric burdens and lifetimes of ozone, carbon monoxide and methane, together with the surface distribution and seasonal cycle in ozone. The results have shown a satisfactory degree of convergence and provide a first estimate of the likely uncertainties in tropospheric ozone model outputs. There are likely to be diminishing returns in carrying out many more Monte Carlo runs in order to refine further these outputs. Uncertainties due to model formulation were separately addressed using the results from 14 Atmospheric Chemistry Coupled Climate Model Intercomparison Project (ACCMIP) chemistry-climate models. The 95% confidence ranges surrounding the ACCMIP model burdens and lifetimes for ozone, carbon monoxide and methane were somewhat smaller than for the Monte Carlo estimates. This reflected the situation where the ACCMIP models used harmonised emissions data and differed only in their meteorological data and model formulations whereas a conscious effort was made to describe the uncertainties in the ozone precursor emissions and in the kinetic and photochemical data in the Monte Carlo runs. Attention was focussed on the model predictions of the ozone seasonal cycles at three marine boundary layer stations: Mace Head, Ireland, Trinidad Head, California and Cape Grim, Tasmania. Despite comprehensively addressing the uncertainties due to global emissions and ozone sources and sinks, none of the Monte Carlo runs were able to generate seasonal cycles that matched the observations at all three MBL stations. Although

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)

An automatic fault management model for distribution networks

Energy Technology Data Exchange (ETDEWEB)

Lehtonen, M; Haenninen, S [VTT Energy, Espoo (Finland); Seppaenen, M [North-Carelian Power Co (Finland); Antila, E; Markkila, E [ABB Transmit Oy (Finland)

1998-08-01

An automatic computer model, called the FI/FL-model, for fault location, fault isolation and supply restoration is presented. The model works as an integrated part of the substation SCADA, the AM/FM/GIS system and the medium voltage distribution network automation systems. In the model, three different techniques are used for fault location. First, by comparing the measured fault current to the computed one, an estimate for the fault distance is obtained. This information is then combined, in order to find the actual fault point, with the data obtained from the fault indicators in the line branching points. As a third technique, in the absence of better fault location data, statistical information of line section fault frequencies can also be used. For combining the different fault location information, fuzzy logic is used. As a result, the probability weights for the fault being located in different line sections, are obtained. Once the faulty section is identified, it is automatically isolated by remote control of line switches. Then the supply is restored to the remaining parts of the network. If needed, reserve connections from other adjacent feeders can also be used. During the restoration process, the technical constraints of the network are checked. Among these are the load carrying capacity of line sections, voltage drop and the settings of relay protection. If there are several possible network topologies, the model selects the technically best alternative. The FI/IL-model has been in trial use at two substations of the North-Carelian Power Company since November 1996. This chapter lists the practical experiences during the test use period. Also the benefits of this kind of automation are assessed and future developments are outlined

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.

A new method for automatic discontinuity traces sampling on rock mass 3D model

Science.gov (United States)

Umili, G.; Ferrero, A.; Einstein, H. H.

2013-02-01

A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

Science.gov (United States)

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

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.

RefDB: The Reference Database for CMS Monte Carlo Production

CERN Document Server

Lefébure, V

2003-01-01

RefDB is the CMS Monte Carlo Reference Database. It is used for recording and managing all details of physics simulation, reconstruction and analysis requests, for coordinating task assignments to world-wide distributed Regional Centers, Grid-enabled or not, and trace their progress rate. RefDB is also the central database that the workflow-planner contacts in order to get task instructions. It is automatically and asynchronously updated with book-keeping run summaries. Finally it is the end-user interface to data catalogues.

Modelling of scintillator based flat-panel detectors with Monte-Carlo simulations

International Nuclear Information System (INIS)

Reims, N; Sukowski, F; Uhlmann, N

2011-01-01

Scintillator based flat panel detectors are state of the art in the field of industrial X-ray imaging applications. Choosing the proper system and setup parameters for the vast range of different applications can be a time consuming task, especially when developing new detector systems. Since the system behaviour cannot always be foreseen easily, Monte-Carlo (MC) simulations are keys to gain further knowledge of system components and their behaviour for different imaging conditions. In this work we used two Monte-Carlo based models to examine an indirect converting flat panel detector, specifically the Hamamatsu C9312SK. We focused on the signal generation in the scintillation layer and its influence on the spatial resolution of the whole system. The models differ significantly in their level of complexity. The first model gives a global description of the detector based on different parameters characterizing the spatial resolution. With relatively small effort a simulation model can be developed which equates the real detector regarding signal transfer. The second model allows a more detailed insight of the system. It is based on the well established cascade theory, i.e. describing the detector as a cascade of elemental gain and scattering stages, which represent the built in components and their signal transfer behaviour. In comparison to the first model the influence of single components especially the important light spread behaviour in the scintillator can be analysed in a more differentiated way. Although the implementation of the second model is more time consuming both models have in common that a relatively small amount of system manufacturer parameters are needed. The results of both models were in good agreement with the measured parameters of the real system.

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

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)

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.

USING AFFORDABLE DATA CAPTURING DEVICES FOR AUTOMATIC 3D CITY MODELLING

Directory of Open Access Journals (Sweden)

B. Alizadehashrafi

2017-11-01

Full Text Available In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1 were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2, the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.

Automatic, Global and Dynamic Student Modeling in a Ubiquitous Learning Environment

Directory of Open Access Journals (Sweden)

Sabine Graf

2009-03-01

Full Text Available Ubiquitous learning allows students to learn at any time and any place. Adaptivity plays an important role in ubiquitous learning, aiming at providing students with adaptive and personalized learning material, activities, and information at the right place and the right time. However, for providing rich adaptivity, the student model needs to be able to gather a variety of information about the students. In this paper, an automatic, global, and dynamic student modeling approach is introduced, which aims at identifying and frequently updating information about students’ progress, learning styles, interests and knowledge level, problem solving abilities, preferences for using the system, social connectivity, and current location. This information is gathered in an automatic way, using students’ behavior and actions in different learning situations provided by different components/services of the ubiquitous learning environment. By providing a comprehensive student model, students can be supported by rich adaptivity in every component/service of the learning environment. Furthermore, the information in the student model can help in giving teachers a better understanding about the students’ learning process.

Using Affordable Data Capturing Devices for Automatic 3d City Modelling

Science.gov (United States)

Alizadehashrafi, B.; Abdul-Rahman, A.

2017-11-01

In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1) were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS) applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2), the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.

Automatic Offline Formulation of Robust Model Predictive Control Based on Linear Matrix Inequalities Method

Directory of Open Access Journals (Sweden)

Longge Zhang

2013-01-01

Full Text Available Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Numerical examples are given to illustrate their effectiveness.

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).

Automatic generation of groundwater model hydrostratigraphy from AEM resistivity and boreholes

DEFF Research Database (Denmark)

Marker, Pernille Aabye; Foged, N.; Christiansen, A. V.

2014-01-01

Regional hydrological models are important tools in water resources management. Model prediction uncertainty is primarily due to structural (geological) non-uniqueness which makes sampling of the structural model space necessary to estimate prediction uncertainties. Geological structures and hete...... and discharge observations. The method was applied to field data collected at a Danish field site. Our results show that a competitive hydrological model can be constructed from the AEM dataset using the automatic procedure outlined above....

Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.

Science.gov (United States)

Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K

2017-10-01

Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

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)

Model Considerations for Memory-based Automatic Music Transcription

Science.gov (United States)

Albrecht, Štěpán; Šmídl, Václav

2009-12-01

The problem of automatic music description is considered. The recorded music is modeled as a superposition of known sounds from a library weighted by unknown weights. Similar observation models are commonly used in statistics and machine learning. Many methods for estimation of the weights are available. These methods differ in the assumptions imposed on the weights. In Bayesian paradigm, these assumptions are typically expressed in the form of prior probability density function (pdf) on the weights. In this paper, commonly used assumptions about music signal are summarized and complemented by a new assumption. These assumptions are translated into pdfs and combined into a single prior density using combination of pdfs. Validity of the model is tested in simulation using synthetic data.

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)

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.

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.

Interdependence between measures of extent and severity of myocardial perfusion defects provided by automatic quantification programs

DEFF Research Database (Denmark)

El-Ali, Henrik Hussein; Palmer, John; Carlsson, Marcus

2005-01-01

To evaluate the accuracy of the values of lesion extent and severity provided by the two automatic quantification programs AutoQUANT and 4D-MSPECT using myocardial perfusion images generated by Monte Carlo simulation of a digital phantom. The combination between a realistic computer phantom and a...

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.

Vectorized Monte Carlo

International Nuclear Information System (INIS)

Brown, F.B.

1981-01-01

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

LEARNING VECTOR QUANTIZATION FOR ADAPTED GAUSSIAN MIXTURE MODELS IN AUTOMATIC SPEAKER IDENTIFICATION

Directory of Open Access Journals (Sweden)

IMEN TRABELSI

2017-05-01

Full Text Available Speaker Identification (SI aims at automatically identifying an individual by extracting and processing information from his/her voice. Speaker voice is a robust a biometric modality that has a strong impact in several application areas. In this study, a new combination learning scheme has been proposed based on Gaussian mixture model-universal background model (GMM-UBM and Learning vector quantization (LVQ for automatic text-independent speaker identification. Features vectors, constituted by the Mel Frequency Cepstral Coefficients (MFCC extracted from the speech signal are used to train the New England subset of the TIMIT database. The best results obtained (90% for gender- independent speaker identification, 97 % for male speakers and 93% for female speakers for test data using 36 MFCC features.

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.

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.

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...

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

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)

A fast fiducial marker tracking model for fully automatic alignment in electron tomography

KAUST Repository

Han, Renmin; Zhang, Fa; Gao, Xin

2017-01-01

Automatic alignment, especially fiducial marker-based alignment, has become increasingly important due to the high demand of subtomogram averaging and the rapid development of large-field electron microscopy. Among the alignment steps, fiducial marker tracking is a crucial one that determines the quality of the final alignment. Yet, it is still a challenging problem to track the fiducial markers accurately and effectively in a fully automatic manner.In this paper, we propose a robust and efficient scheme for fiducial marker tracking. Firstly, we theoretically prove the upper bound of the transformation deviation of aligning the positions of fiducial markers on two micrographs by affine transformation. Secondly, we design an automatic algorithm based on the Gaussian mixture model to accelerate the procedure of fiducial marker tracking. Thirdly, we propose a divide-and-conquer strategy against lens distortions to ensure the reliability of our scheme. To our knowledge, this is the first attempt that theoretically relates the projection model with the tracking model. The real-world experimental results further support our theoretical bound and demonstrate the effectiveness of our algorithm. This work facilitates the fully automatic tracking for datasets with a massive number of fiducial markers.The C/C ++ source code that implements the fast fiducial marker tracking is available at https://github.com/icthrm/gmm-marker-tracking. Markerauto 1.6 version or later (also integrated in the AuTom platform at http://ear.ict.ac.cn/) offers a complete implementation for fast alignment, in which fast fiducial marker tracking is available by the

A fast fiducial marker tracking model for fully automatic alignment in electron tomography

KAUST Repository

Han, Renmin

2017-10-20

Automatic alignment, especially fiducial marker-based alignment, has become increasingly important due to the high demand of subtomogram averaging and the rapid development of large-field electron microscopy. Among the alignment steps, fiducial marker tracking is a crucial one that determines the quality of the final alignment. Yet, it is still a challenging problem to track the fiducial markers accurately and effectively in a fully automatic manner.In this paper, we propose a robust and efficient scheme for fiducial marker tracking. Firstly, we theoretically prove the upper bound of the transformation deviation of aligning the positions of fiducial markers on two micrographs by affine transformation. Secondly, we design an automatic algorithm based on the Gaussian mixture model to accelerate the procedure of fiducial marker tracking. Thirdly, we propose a divide-and-conquer strategy against lens distortions to ensure the reliability of our scheme. To our knowledge, this is the first attempt that theoretically relates the projection model with the tracking model. The real-world experimental results further support our theoretical bound and demonstrate the effectiveness of our algorithm. This work facilitates the fully automatic tracking for datasets with a massive number of fiducial markers.The C/C ++ source code that implements the fast fiducial marker tracking is available at https://github.com/icthrm/gmm-marker-tracking. Markerauto 1.6 version or later (also integrated in the AuTom platform at http://ear.ict.ac.cn/) offers a complete implementation for fast alignment, in which fast fiducial marker tracking is available by the

MCOR - Monte Carlo depletion code for reference LWR calculations

Energy Technology Data Exchange (ETDEWEB)

Puente Espel, Federico, E-mail: fup104@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Tippayakul, Chanatip, E-mail: cut110@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Ivanov, Kostadin, E-mail: kni1@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Misu, Stefan, E-mail: Stefan.Misu@areva.com [AREVA, AREVA NP GmbH, Erlangen (Germany)

2011-04-15

Research highlights: > Introduction of a reference Monte Carlo based depletion code with extended capabilities. > Verification and validation results for MCOR. > Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations. Additionally

MCOR - Monte Carlo depletion code for reference LWR calculations

International Nuclear Information System (INIS)

Puente Espel, Federico; Tippayakul, Chanatip; Ivanov, Kostadin; Misu, Stefan

2011-01-01

Research highlights: → Introduction of a reference Monte Carlo based depletion code with extended capabilities. → Verification and validation results for MCOR. → Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations

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

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.)

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

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.

ARIADNE - A Monte Carlo for QCD cascades in the colour dipole formulation

International Nuclear Information System (INIS)

Pettersson, U.

1988-04-01

We present a Monte Carlo program for generating QCD cascades, based on the colour dipole approximation. In this formulation the gluons are radiated from dipoles that are stretched from one colour charge to the corresponding anti-charge. The subsequent emission of gluons thus corresponds to the dipoles being split into smaller and smaller dipoles. This formulation automatically takes into account the angular ordering and the ordering in transverse momenta, and it also gives some nontrivial azimuthal effects. (author)

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 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...

Modelling the adoption of automatic milking systems in Noord-Holland

OpenAIRE

Matteo Floridi; Fabio Bartolini; Jack Peerlings; Nico Polman; Davide Viaggi

2013-01-01

Innovation and new technology adoption represent two central elements for the business and industry development process in agriculture. One of the most relevant innovations in dairy farms is the robotisation of the milking process through the adoption of Automatic Milking Systems (AMS). The purpose of this paper is to assess the impact of selected Common Agricultural Policy measures on the adoption of AMS in dairy farms. The model developed is a dynamic farm-household model that is able to si...

Automatic mesh adaptivity for CADIS and FW-CADIS neutronics modeling of difficult shielding problems

International Nuclear Information System (INIS)

Ibrahim, A. M.; Peplow, D. E.; Mosher, S. W.; Wagner, J. C.; Evans, T. M.; Wilson, P. P.; Sawan, M. E.

2013-01-01

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 macro-material 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 de-couples 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, obviating the need for a world-class super computer. (authors)

Coupling the MCNP Monte Carlo code and the FISPACT activation code with automatic visualization of the results of simulations

International Nuclear Information System (INIS)

Bourauel, Peter; Nabbi, Rahim; Biel, Wolfgang; Forrest, Robin

2009-01-01

The MCNP 3D Monte Carlo computer code is used not only for criticality calculations of nuclear systems but also to simulate transports of radiation and particles. The findings so obtained about neutron flux distribution and the associated spectra allow information about materials activation, nuclear heating, and radiation damage to be obtained by means of activation codes such as FISPACT. The stochastic character of particle and radiation transport processes normally links findings to the materials cells making up the geometry model of MCNP. Where high spatial resolution is required for the activation calculations with FISPACT, fine segmentation of the MCNP geometry becomes compulsory, which implies considerable expense for the modeling process. For this reason, an alternative simulation technique has been developed in an effort to automate and optimize data transfer between MCNP and FISPACT. (orig.)

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.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

Science.gov (United States)

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

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.

The ACR-program for automatic finite element model generation for part through cracks

International Nuclear Information System (INIS)

Leinonen, M.S.; Mikkola, T.P.J.

1989-01-01

The ACR-program (Automatic Finite Element Model Generation for Part Through Cracks) has been developed at the Technical Research Centre of Finland (VTT) for automatic finite element model generation for surface flaws using three dimensional solid elements. Circumferential or axial cracks can be generated on the inner or outer surface of a cylindrical or toroidal geometry. Several crack forms are available including the standard semi-elliptical surface crack. The program can be used in the development of automated systems for fracture mechanical analyses of structures. The tests for the accuracy of the FE-mesh have been started with two-dimensional models. The results indicate that the accuracy of the standard mesh is sufficient for practical analyses. Refinement of the standard mesh is needed in analyses with high load levels well over the limit load of the structure

Automatic Conversion of a Conceptual Model to a Standard Multi-view Web Services Definition

Directory of Open Access Journals (Sweden)

Anass Misbah

2018-03-01

Full Text Available Information systems are becoming more and more heterogeneous and here comes the need to have more generic transformation algorithms and more automatic generation Meta rules. In fact, the large number of terminals, devices, operating systems, platforms and environments require a high level of adaptation. Therefore, it is becoming more and more difficult to validate, generate and implement manually models, designs and codes.Web services are one of the technologies that are used massively nowadays; hence, it is considered as one of technologies that require the most automatic rules of validation and automation. Many previous works have dealt with Web services by proposing new concepts such as Multi-view Web services, standard WSDL implementation of Multi-view Web services and even further Generic Meta rules for automatic generation of Multi-view Web services.In this work we will propose a new way of generating Multi-view Web ser-vices, which is based on an engine algorithm that takes as input both an initial Conceptual Model and user’s matrix and then unroll a generic algorithm to gen-erate dynamically a validated set of points of view. This set of points of view will be transformed to a standard WSDL implementation of Multi-view Web services by means of the automatic transformation Meta rules.

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.

Genetic Programming for Automatic Hydrological Modelling

Science.gov (United States)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

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)

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

Science.gov (United States)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

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

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...

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

Energy Technology Data Exchange (ETDEWEB)

He, Baochun; Huang, Cheng; Zhou, Shoujun; Hu, Qingmao; Jia, Fucang, E-mail: fc.jia@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055 (China); Sharp, Gregory [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Fang, Chihua; Fan, Yingfang [Department of Hepatology (I), Zhujiang Hospital, Southern Medical University, Guangzhou 510280 (China)

2016-05-15

Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

Science.gov (United States)

He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

2016-05-01

A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver

Model-based automatic generation of grasping regions

Science.gov (United States)

Bloss, David A.

1993-01-01

The problem of automatically generating stable regions for a robotic end effector on a target object, given a model of the end effector and the object is discussed. In order to generate grasping regions, an initial valid grasp transformation from the end effector to the object is obtained based on form closure requirements, and appropriate rotational and translational symmetries are associated with that transformation in order to construct a valid, continuous grasping region. The main result of this algorithm is a list of specific, valid grasp transformations of the end effector to the target object, and the appropriate combinations of translational and rotational symmetries associated with each specific transformation in order to produce a continuous grasp region.

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

Non-analogue Monte Carlo method, application to neutron simulation; Methode de Monte Carlo non analogue, application a la simulation des neutrons

Energy Technology Data Exchange (ETDEWEB)

Morillon, B.

1996-12-31

With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.

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

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...

Iterative optimisation of Monte Carlo detector models using measurements and simulations

Energy Technology Data Exchange (ETDEWEB)

Marzocchi, O., E-mail: olaf@marzocchi.net [European Patent Office, Rijswijk (Netherlands); Leone, D., E-mail: debora.leone@kit.edu [Institute for Nuclear Waste Disposal, Karlsruhe Institute of Technology, Karlsruhe (Germany)

2015-04-11

This work proposes a new technique to optimise the Monte Carlo models of radiation detectors, offering the advantage of a significantly lower user effort and therefore an improved work efficiency compared to the prior techniques. The method consists of four steps, two of which are iterative and suitable for automation using scripting languages. The four steps consist in the acquisition in the laboratory of measurement data to be used as reference; the modification of a previously available detector model; the simulation of a tentative model of the detector to obtain the coefficients of a set of linear equations; the solution of the system of equations and the update of the detector model. Steps three and four can be repeated for more accurate results. This method avoids the “try and fail” approach typical of the prior techniques.

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)

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...

Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model Generation for ns-3

Science.gov (United States)

2015-12-01

more protocols (especially at different layers of the OSI model ), implementing an inference engine to extract inter- and intrapacket dependencies, and...ARL-TR-7543 ● DEC 2015 US Army Research Laboratory Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model ...ICMP) Model Generation for ns-3 by Jaime C Acosta and Felipe Jovel Survivability/Lethality Analysis Directorate, ARL Felipe Sotelo and Caesar

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.

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.

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.

Check and visualization of input geometry data using the geometrical module of the Monte Carlo code MCU: WWER-440 pressure vessel dosimetry benchmarks

International Nuclear Information System (INIS)

Gurevich, M.; Zaritsky, S.; Osmera, B.; Mikus, J.

1997-01-01

The Monte Carlo method gives the opportunity to conduct the calculations of neutron and photon flux without any simplifications of the 3-D geometry of the nuclear power and experimental devices. So, each graduated Monte Carlo code includes the combinatorial geometry module and tools for the geometry description giving a possibility to describe very complex systems with a number of hierarchy levels of the geometrical objects. Such codes as usual have special modules for the visual checking of geometry input information. These geometry opportunities could be used for all cases when the accurate 3-D description of the complex geometry becomes a necessity. The description (specification) of benchmark experiments is one of the such cases. Such accurate and uniform description detects all mistakes and ambiguities in the starting information of various kinds (drawings, reports etc.). Usually the quality of different parts of the starting information (generally produced by different persons during the different stages of the device elaboration and operation) is different. After using the above mentioned modules and tools, the resultant geometry description can be used as a standard for this device. One can automatically produce any type of the device figure. The detail geometry description can be used as input for different calculation models carrying out (not only for Monte Carlo). The application of that method to the description of the WWER-440 mock-ups is represented in the report. The mock-ups were created on the reactor LR-O (NRI) and the reactor vessel dosimetry benchmarks were developed on the basis of these mock-up experiments. The NCG-8 module of the Russian Monte Carlo code MCU was used. It is the combinatorial multilingual universal geometrical module. The MCU code was certified by Russian Nuclear Regulatory Body. Almost all figures for mentioned benchmarks specifications were made by the MCU visualization code. The problem of the automatic generation of the

Intelligent Monte Carlo phase-space division and importance estimation

International Nuclear Information System (INIS)

Booth, T.E.

1989-01-01

Two years ago, a quasi-deterministic method (QD) for obtaining the Monte Carlo importance function was reported. Since then, a number of very complex problems have been solved with the aid of QD. Not only does QD estimate the importance far faster than the (weight window) generator currently in MCNP, QD requires almost no user intervention in contrast to the generator. However, both the generator and QD require the user to divide the phase-space into importance regions. That is, both methods will estimate the importance of a phase-space region, but the user must define the regions. In practice this is tedious and time consuming, and many users are not particularly good at defining sensible importance regions. To make full use of the fat that QD is capable of getting good importance estimates in tens of thousands of phase-space regions relatively easily, some automatic method for dividing the phase space will be useful and perhaps essential. This paper describes recent progress toward an automatic and intelligent phase-space divider

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.

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

Automatic Construction of Finite Algebras

Institute of Scientific and Technical Information of China (English)

张健

1995-01-01

This paper deals with model generation for equational theories,i.e.,automatically generating (finite)models of a given set of (logical) equations.Our method of finite model generation and a tool for automatic construction of finite algebras is described.Some examples are given to show the applications of our program.We argue that,the combination of model generators and theorem provers enables us to get a better understanding of logical theories.A brief comparison betwween our tool and other similar tools is also presented.

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.

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.

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

Automatic component calibration and error diagnostics for model-based accelerator control. Phase I final report

International Nuclear Information System (INIS)

Carl Stern; Martin Lee

1999-01-01

Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models

Automatic component calibration and error diagnostics for model-based accelerator control. Phase I final report

CERN Document Server

Carl-Stern

1999-01-01

Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models.

A generic method for automatic translation between input models for different versions of simulation codes

International Nuclear Information System (INIS)

Serfontein, Dawid E.; Mulder, Eben J.; Reitsma, Frederik

2014-01-01

A computer code was developed for the semi-automatic translation of input models for the VSOP-A diffusion neutronics simulation code to the format of the newer VSOP 99/05 code. In this paper, this algorithm is presented as a generic method for producing codes for the automatic translation of input models from the format of one code version to another, or even to that of a completely different code. Normally, such translations are done manually. However, input model files, such as for the VSOP codes, often are very large and may consist of many thousands of numeric entries that make no particular sense to the human eye. Therefore the task, of for instance nuclear regulators, to verify the accuracy of such translated files can be very difficult and cumbersome. This may cause translation errors not to be picked up, which may have disastrous consequences later on when a reactor with such a faulty design is built. Therefore a generic algorithm for producing such automatic translation codes may ease the translation and verification process to a great extent. It will also remove human error from the process, which may significantly enhance the accuracy and reliability of the process. The developed algorithm also automatically creates a verification log file which permanently record the names and values of each variable used, as well as the list of meanings of all the possible values. This should greatly facilitate reactor licensing applications

A generic method for automatic translation between input models for different versions of simulation codes

Energy Technology Data Exchange (ETDEWEB)

Serfontein, Dawid E., E-mail: Dawid.Serfontein@nwu.ac.za [School of Mechanical and Nuclear Engineering, North West University (PUK-Campus), PRIVATE BAG X6001 (Internal Post Box 360), Potchefstroom 2520 (South Africa); Mulder, Eben J. [School of Mechanical and Nuclear Engineering, North West University (South Africa); Reitsma, Frederik [Calvera Consultants (South Africa)

2014-05-01

A computer code was developed for the semi-automatic translation of input models for the VSOP-A diffusion neutronics simulation code to the format of the newer VSOP 99/05 code. In this paper, this algorithm is presented as a generic method for producing codes for the automatic translation of input models from the format of one code version to another, or even to that of a completely different code. Normally, such translations are done manually. However, input model files, such as for the VSOP codes, often are very large and may consist of many thousands of numeric entries that make no particular sense to the human eye. Therefore the task, of for instance nuclear regulators, to verify the accuracy of such translated files can be very difficult and cumbersome. This may cause translation errors not to be picked up, which may have disastrous consequences later on when a reactor with such a faulty design is built. Therefore a generic algorithm for producing such automatic translation codes may ease the translation and verification process to a great extent. It will also remove human error from the process, which may significantly enhance the accuracy and reliability of the process. The developed algorithm also automatically creates a verification log file which permanently record the names and values of each variable used, as well as the list of meanings of all the possible values. This should greatly facilitate reactor licensing applications.

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.

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

MATHEMATICAL MODELING OF THE UNPUT DEVICES IN AUTOMATIC LOCOMOTIVE SIGNALING SYSTEM

Directory of Open Access Journals (Sweden)

O. O. Gololobova

2014-03-01

Full Text Available Purpose. To examine the operation of the automatic locomotive signaling system (ALS, to find out the influence of external factors on the devices operation and the quality of the code information derived from track circuit information, as well as to enable modeling of failure occurrences that may appear during operation. Methodology. To achieve this purpose, the main obstacles in ALS operation and the reasons for their occurrence were considered and the system structure principle was researched. The mathematical model for input equipment of the continuous automatic locomotive signaling system (ALS with the number coding was developed. It was designed taking into account all the types of code signals “R”, “Y”, “RY” and equivalent scheme of replacing the filter with a frequency of 50 Hz. Findings. The operation of ALSN with a signal current frequency of 50 Hz was examined. The adequate mathematical model of input equipment of ALS with a frequency of 50 Hz was developed. Originality. The computer model of input equipment of ALS system in the environment of MATLAB+Simulink was developed. The results of the computer modeling on the outlet of the filter during delivering every type of code combination were given in the article. Practical value. With the use of developed mathematical model of ALS system operation we have an opportunity to study, research and determine behavior of the circuit during the normal operation mode and failure occurrences. Also there is a possibility to develop and apply different scheme decisions in modeling environment MATLAB+Simulink for reducing the influence of obstacles on the functional capability of ALS and to model the occurrence of possible difficulties.

Automatic Generation of Symbolic Model for Parameterized Synchronous Systems

Institute of Scientific and Technical Information of China (English)

Wei-Wen Xu

2004-01-01

With the purpose of making the verification of parameterized system more general and easier, in this paper, a new and intuitive language PSL (Parameterized-system Specification Language) is proposed to specify a class of parameterized synchronous systems. From a PSL script, an automatic method is proposed to generate a constraint-based symbolic model. The model can concisely symbolically represent the collections of global states by counting the number of processes in a given state. Moreover, a theorem has been proved that there is a simulation relation between the original system and its symbolic model. Since the abstract and symbolic techniques are exploited in the symbolic model, state-explosion problem in traditional verification methods is efficiently avoided. Based on the proposed symbolic model, a reachability analysis procedure is implemented using ANSI C++ on UNIX platform. Thus, a complete tool for verifying the parameterized synchronous systems is obtained and tested for some cases. The experimental results show that the method is satisfactory.

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

Semi-automatic registration of 3D orthodontics models from photographs

Science.gov (United States)

Destrez, Raphaël.; Treuillet, Sylvie; Lucas, Yves; Albouy-Kissi, Benjamin

2013-03-01

In orthodontics, a common practice used to diagnose and plan the treatment is the dental cast. After digitization by a CT-scan or a laser scanner, the obtained 3D surface models can feed orthodontics numerical tools for computer-aided diagnosis and treatment planning. One of the pre-processing critical steps is the 3D registration of dental arches to obtain the occlusion of these numerical models. For this task, we propose a vision based method to automatically compute the registration based on photos of patient mouth. From a set of matched singular points between two photos and the dental 3D models, the rigid transformation to apply to the mandible to be in contact with the maxillary may be computed by minimizing the reprojection errors. During a precedent study, we established the feasibility of this visual registration approach with a manual selection of singular points. This paper addresses the issue of automatic point detection. Based on a priori knowledge, histogram thresholding and edge detection are used to extract specific points in 2D images. Concurrently, curvatures information detects 3D corresponding points. To improve the quality of the final registration, we also introduce a combined optimization of the projection matrix with the 2D/3D point positions. These new developments are evaluated on real data by considering the reprojection errors and the deviation angles after registration in respect to the manual reference occlusion realized by a specialist.

A model based method for automatic facial expression recognition

NARCIS (Netherlands)

Kuilenburg, H. van; Wiering, M.A.; Uyl, M. den

2006-01-01

Automatic facial expression recognition is a research topic with interesting applications in the field of human-computer interaction, psychology and product marketing. The classification accuracy for an automatic system which uses static images as input is however largely limited by the image

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)

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)

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.

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.

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

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.

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.

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

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

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.

Component simulation in problems of calculated model formation of automatic machine mechanisms

OpenAIRE

Telegin Igor; Kozlov Alexander; Zhirkov Alexander

2017-01-01

The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gap...

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.

AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES

Directory of Open Access Journals (Sweden)

J. Kang

2016-06-01

Full Text Available In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

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.

Automatic Generation of 3D Building Models with Multiple Roofs

Institute of Scientific and Technical Information of China (English)

Kenichi Sugihara; Yoshitugu Hayashi

2008-01-01

Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

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

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

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.

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.

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.

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

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

Advanced Monte Carlo methods for thermal radiation transport

Science.gov (United States)

Wollaber, Allan B.

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

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.

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG.

Science.gov (United States)

Supratak, Akara; Dong, Hao; Wu, Chao; Guo, Yike

2017-11-01

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-engineered features, which require prior knowledge of sleep analysis. Only a few of them encode the temporal information, such as transition rules, which is important for identifying the next sleep stages, into the extracted features. In the proposed model, we utilize convolutional neural networks to extract time-invariant features, and bidirectional-long short-term memory to learn transition rules among sleep stages automatically from EEG epochs. We implement a two-step training algorithm to train our model efficiently. We evaluated our model using different single-channel EEGs (F4-EOG (left), Fpz-Cz, and Pz-Oz) from two public sleep data sets, that have different properties (e.g., sampling rate) and scoring standards (AASM and R&K). The results showed that our model achieved similar overall accuracy and macro F1-score (MASS: 86.2%-81.7, Sleep-EDF: 82.0%-76.9) compared with the state-of-the-art methods (MASS: 85.9%-80.5, Sleep-EDF: 78.9%-73.7) on both data sets. This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different data sets without utilizing any hand-engineered features.

Radiation dosimetry by automatic image analysis of dicentric chromosomes

International Nuclear Information System (INIS)

Bayley, R.; Carothers, A.; Farrow, S.; Gordon, J.; Ji, L.; Piper, J.; Rutovitz, D.; Stark, M.; Chen, X.; Wald, N.; Pittsburgh Univ., PA

1991-01-01

A system for scoring dicentric chromosomes by image analysis comprised fully automatic location of mitotic cells, automatic retrieval, focus and digitisation at high resolution, automatic rejection of nuclei and debris and detection and segmentation of chromosome clusters, automatic centromere location, and subsequent rapid interactive visual review of potential dicentric chromosomes to confirm positives and reject false positives. A calibration set of about 15000 cells was used to establish the quadratic dose response for 60 Co γ-irradiation. The dose-response function parameters were established by a maximum likelihood technique, and confidence limits in the dose response and in the corresponding inverse curve, of estimated dose for observed dicentric frequency, were established by Monte Carlo techniques. The system was validated in a blind trial by analysing a test comprising a total of about 8000 cells irradiated to 1 of 10 dose levels, and estimating the doses from the observed dicentric frequency. There was a close correspondence between the estimated and true doses. The overall sensitivity of the system in terms of the proportion of the total population of dicentrics present in the cells analysed that were detected by the system was measured to be about 40%. This implies that about 2.5 times more cells must be analysed by machine than by visual analysis. Taking this factor into account, the measured review time and false positive rates imply that analysis by the system of sufficient cells to provide the equivalent of a visual analysis of 500 cells would require about 1 h for operator review. (author). 20 refs.; 4 figs.; 5 tabs

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 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

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.

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.

PEST modules with regularization for the acceleration of the automatic calibration in hydrodynamic models

Directory of Open Access Journals (Sweden)

Polomčić Dušan M.

2015-01-01

Full Text Available The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneous zones with parameter values of porous media or zones with the given boundary conditions has been outdated. However, the consequence of this kind of automatic calibration is that a significant amount of time is required to perform the calculation. The duration of calibration is measured in hours, sometimes even days. PEST contains two modules for the shortening of that process - Parallel PEST and BeoPEST. The paper presents performed experiments and analysis of different cases of PEST module usage, based on which the reduction in the time required to calibrate the model is done.

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

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.)

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 method using octree structure in photon and electron transport

International Nuclear Information System (INIS)

Ogawa, K.; Maeda, S.

1995-01-01

Most of the early Monte Carlo calculations in medical physics were used to calculate absorbed dose distributions, and detector responses and efficiencies. Recently, data acquisition in Single Photon Emission CT (SPECT) has been simulated by a Monte Carlo method to evaluate scatter photons generated in a human body and a collimator. Monte Carlo simulations in SPECT data acquisition are generally based on the transport of photons only because the photons being simulated are low energy, and therefore the bremsstrahlung productions by the electrons generated are negligible. Since the transport calculation of photons without electrons is much simpler than that with electrons, it is possible to accomplish the high-speed simulation in a simple object with one medium. Here, object description is important in performing the photon and/or electron transport using a Monte Carlo method efficiently. The authors propose a new description method using an octree representation of an object. Thus even if the boundaries of each medium are represented accurately, high-speed calculation of photon transport can be accomplished because the number of voxels is much fewer than that of the voxel-based approach which represents an object by a union of the voxels of the same size. This Monte Carlo code using the octree representation of an object first establishes the simulation geometry by reading octree string, which is produced by forming an octree structure from a set of serial sections for the object before the simulation; then it transports photons in the geometry. Using the code, if the user just prepares a set of serial sections for the object in which he or she wants to simulate photon trajectories, he or she can perform the simulation automatically using the suboptimal geometry simplified by the octree representation without forming the optimal geometry by handwriting

A Method for Modeling the Virtual Instrument Automatic Test System Based on the Petri Net

Institute of Scientific and Technical Information of China (English)

MA Min; CHEN Guang-ju

2005-01-01

Virtual instrument is playing the important role in automatic test system. This paper introduces a composition of a virtual instrument automatic test system and takes the VXIbus based a test software platform which is developed by CAT lab of the UESTC as an example. Then a method to model this system based on Petri net is proposed. Through this method, we can analyze the test task scheduling to prevent the deadlock or resources conflict. At last, this paper analyzes the feasibility of this method.

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.

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.

Development of a new model to evaluate the probability of automatic plant trips for pressurized water reactors

Energy Technology Data Exchange (ETDEWEB)

Shimada, Yoshio [Institute of Nuclear Safety System Inc., Mihama, Fukui (Japan); Kawai, Katsunori; Suzuki, Hiroshi [Mitsubishi Heavy Industries Ltd., Tokyo (Japan)

2001-09-01

In order to improve the reliability of plant operations for pressurized water reactors, a new fault tree model was developed to evaluate the probability of automatic plant trips. This model consists of fault trees for sixteen systems. It has the following features: (1) human errors and transmission line incidents are modeled by the existing data, (2) the repair of failed components is considered to calculate the failure probability of components, (3) uncertainty analysis is performed by an exact method. From the present results, it is confirmed that the obtained upper and lower bound values of the automatic plant trip probability are within the existing data bound in Japan. Thereby this model can be applicable to the prediction of plant performance and reliability. (author)

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.

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.

Automatic orientation and 3D modelling from markerless rock art imagery

Science.gov (United States)

Lerma, J. L.; Navarro, S.; Cabrelles, M.; Seguí, A. E.; Hernández, D.

2013-02-01

This paper investigates the use of two detectors and descriptors on image pyramids for automatic image orientation and generation of 3D models. The detectors and descriptors replace manual measurements and are used to detect, extract and match features across multiple imagery. The Scale-Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) will be assessed based on speed, number of features, matched features, and precision in image and object space depending on the adopted hierarchical matching scheme. The influence of applying in addition Area Based Matching (ABM) with normalised cross-correlation (NCC) and least squares matching (LSM) is also investigated. The pipeline makes use of photogrammetric and computer vision algorithms aiming minimum interaction and maximum accuracy from a calibrated camera. Both the exterior orientation parameters and the 3D coordinates in object space are sequentially estimated combining relative orientation, single space resection and bundle adjustment. The fully automatic image-based pipeline presented herein to automate the image orientation step of a sequence of terrestrial markerless imagery is compared with manual bundle block adjustment and terrestrial laser scanning (TLS) which serves as ground truth. The benefits of applying ABM after FBM will be assessed both in image and object space for the 3D modelling of a complex rock art shelter.

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

Automatic Generation of Building Models with Levels of Detail 1-3

Science.gov (United States)

Nguatem, W.; Drauschke, M.; Mayer, H.

2016-06-01

We present a workflow for the automatic generation of building models with levels of detail (LOD) 1 to 3 according to the CityGML standard (Gröger et al., 2012). We start with orienting unsorted image sets employing (Mayer et al., 2012), we compute depth maps using semi-global matching (SGM) (Hirschmüller, 2008), and fuse these depth maps to reconstruct dense 3D point clouds (Kuhn et al., 2014). Based on planes segmented from these point clouds, we have developed a stochastic method for roof model selection (Nguatem et al., 2013) and window model selection (Nguatem et al., 2014). We demonstrate our workflow up to the export into CityGML.

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.

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)

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

Application of inactive cycle stopping criteria for Monte Carlo Wielandt calculations

International Nuclear Information System (INIS)

Shim, H. J.; Kim, C. H.

2009-01-01

The Wielandt method is incorporated into Monte Carlo (MC) eigenvalue calculation as a way to speed up fission source convergence. To make the most of the MC Wielandt method, however, it is highly desirable to halt inactive cycle runs in a timely manner because it requires a much longer computational time to execute a single cycle MC run than the conventional MC eigenvalue calculations. This paper presents an algorithm to detect the onset of the active cycles and thereby to stop automatically the inactive cycle MC runs based on two anterior stopping criteria. The effectiveness of the algorithm is demonstrated by applying it to a slow convergence problem. (authors)

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.

Hidden Markov models in automatic speech recognition

Science.gov (United States)

Wrzoskowicz, Adam

1993-11-01

This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.

Model of Random Polygon Particles for Concrete and Mesh Automatic Subdivision

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

In order to study the constitutive behavior of concrete in mesoscopic level, a new method is proposed in this paper. This method uses random polygon particles to simulate full grading broken aggregates of concrete. Based on computational geometry, we carry out the automatic generation of the triangle finite element mesh for the model of random polygon particles of concrete. The finite element mesh generated in this paper is also applicable to many other numerical methods.

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

Towards the Availability of the Distributed Cluster Rendering System: Automatic Modeling and Verification

DEFF Research Database (Denmark)

Wang, Kemin; Jiang, Zhengtao; Wang, Yongbin

2012-01-01

, whenever the number of node-n and related parameters vary, we can create the PRISM model file rapidly and then we can use PRISM model checker to verify ralated system properties. At the end of this study, we analyzed and verified the availability distributions of the Distributed Cluster Rendering System......In this study, we proposed a Continuous Time Markov Chain Model towards the availability of n-node clusters of Distributed Rendering System. It's an infinite one, we formalized it, based on the model, we implemented a software, which can automatically model with PRISM language. With the tool...

Automatic Learning of Fine Operating Rules for Online Power System Security Control.

Science.gov (United States)

Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

2016-08-01

Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.

Towards Automatic Semantic Labelling of 3D City Models

Science.gov (United States)

Rook, M.; Biljecki, F.; Diakité, A. A.

2016-10-01

The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.

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.)

Constraint optimization model of a scheduling problem for a robotic arm in automatic systems

DEFF Research Database (Denmark)

Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten

2014-01-01

are characteristics of the painting process application itself. Unlike spot-welding, painting tasks require movement of the entire robot arm. In addition to minimizing intertask duration, the scheduler must strive to maximize painting quality and the problem is formulated as a multi-objective optimization problem....... The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...... of the entire software system for automatic generation of robot programs for painting....

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

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.

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)

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.

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.

PEST modules with regularization for the acceleration of the automatic calibration in hydrodynamic models

OpenAIRE

Polomčić, Dušan M.; Bajić, Dragoljub I.; Močević, Jelena M.

2015-01-01

The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneou...

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

SU-E-T-256: Development of a Monte Carlo-Based Dose-Calculation System in a Cloud Environment for IMRT and VMAT Dosimetric Verification

Energy Technology Data Exchange (ETDEWEB)

Fujita, Y [Tokai University School of Medicine, Isehara, Kanagawa (Japan)

2015-06-15

Purpose: Intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) are techniques that are widely used for treating cancer due to better target coverage and critical structure sparing. The increasing complexity of IMRT and VMAT plans leads to decreases in dose calculation accuracy. Monte Carlo simulations are the most accurate method for the determination of dose distributions in patients. However, the simulation settings for modeling an accurate treatment head are very complex and time consuming. The purpose of this work is to report our implementation of a simple Monte Carlo simulation system in a cloud-computing environment for dosimetric verification of IMRT and VMAT plans. Methods: Monte Carlo simulations of a Varian Clinac linear accelerator were performed using the BEAMnrc code, and dose distributions were calculated using the DOSXYZnrc code. Input files for the simulations were automatically generated from DICOM RT files by the developed web application. We therefore must only upload the DICOM RT files through the web interface, and the simulations are run in the cloud. The calculated dose distributions were exported to RT Dose files that can be downloaded through the web interface. The accuracy of the calculated dose distribution was verified by dose measurements. Results: IMRT and VMAT simulations were performed and good agreement results were observed for measured and MC dose comparison. Gamma analysis with a 3% dose and 3 mm DTA criteria shows a mean gamma index value of 95% for the studied cases. Conclusion: A Monte Carlo-based dose calculation system has been successfully implemented in a cloud environment. The developed system can be used for independent dose verification of IMRT and VMAT plans in routine clinical practice. The system will also be helpful for improving accuracy in beam modeling and dose calculation in treatment planning systems. This work was supported by JSPS KAKENHI Grant Number 25861057.

SU-E-T-256: Development of a Monte Carlo-Based Dose-Calculation System in a Cloud Environment for IMRT and VMAT Dosimetric Verification

International Nuclear Information System (INIS)

Fujita, Y

2015-01-01

Purpose: Intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) are techniques that are widely used for treating cancer due to better target coverage and critical structure sparing. The increasing complexity of IMRT and VMAT plans leads to decreases in dose calculation accuracy. Monte Carlo simulations are the most accurate method for the determination of dose distributions in patients. However, the simulation settings for modeling an accurate treatment head are very complex and time consuming. The purpose of this work is to report our implementation of a simple Monte Carlo simulation system in a cloud-computing environment for dosimetric verification of IMRT and VMAT plans. Methods: Monte Carlo simulations of a Varian Clinac linear accelerator were performed using the BEAMnrc code, and dose distributions were calculated using the DOSXYZnrc code. Input files for the simulations were automatically generated from DICOM RT files by the developed web application. We therefore must only upload the DICOM RT files through the web interface, and the simulations are run in the cloud. The calculated dose distributions were exported to RT Dose files that can be downloaded through the web interface. The accuracy of the calculated dose distribution was verified by dose measurements. Results: IMRT and VMAT simulations were performed and good agreement results were observed for measured and MC dose comparison. Gamma analysis with a 3% dose and 3 mm DTA criteria shows a mean gamma index value of 95% for the studied cases. Conclusion: A Monte Carlo-based dose calculation system has been successfully implemented in a cloud environment. The developed system can be used for independent dose verification of IMRT and VMAT plans in routine clinical practice. The system will also be helpful for improving accuracy in beam modeling and dose calculation in treatment planning systems. This work was supported by JSPS KAKENHI Grant Number 25861057

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.

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.

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].

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

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 mathematical model of an automatic assembler to stack fuel pellets

International Nuclear Information System (INIS)

Jarvis, R.G.; Joynes, R.; Bretzlaff, C.I.

1980-11-01

Fuel elements for CANDU reactors are assembled from stacks of cylindrical UO 2 pellets, with close tolerances on lengths and diameters. Present stacking techniques involve extensive manual operations and they can be speeded up and reduced in cost by an automated device. If gamma-active fuel is handled such a device is essential. An automatic fuel pellet assembly process was modelled mathematically. The model indicated a suitable sequence of pellet manipulations to arrive at a stack length that was always within tolerance. This sequence was used as the inital input for the design of mechanical hardware. The mechanical design and the refinement of the mathematical model proceeded simultaneously. Mechanical constraints were allowed for in the model, and its optimized sequence of operations was incorporated in a microcomputer program to control the mechanical hardware. (auth)

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

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

Automatic anatomy recognition via multiobject oriented active shape models.

Science.gov (United States)

Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

2010-12-01

This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a

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.

Towards an automatic model transformation mechanism from UML state machines to DEVS models

Directory of Open Access Journals (Sweden)

Ariel González

2015-08-01

Full Text Available The development of complex event-driven systems requires studies and analysis prior to deployment with the goal of detecting unwanted behavior. UML is a language widely used by the software engineering community for modeling these systems through state machines, among other mechanisms. Currently, these models do not have appropriate execution and simulation tools to analyze the real behavior of systems. Existing tools do not provide appropriate libraries (sampling from a probability distribution, plotting, etc. both to build and to analyze models. Modeling and simulation for design and prototyping of systems are widely used techniques to predict, investigate and compare the performance of systems. In particular, the Discrete Event System Specification (DEVS formalism separates the modeling and simulation; there are several tools available on the market that run and collect information from DEVS models. This paper proposes a model transformation mechanism from UML state machines to DEVS models in the Model-Driven Development (MDD context, through the declarative QVT Relations language, in order to perform simulations using tools, such as PowerDEVS. A mechanism to validate the transformation is proposed. Moreover, examples of application to analyze the behavior of an automatic banking machine and a control system of an elevator are presented.

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

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.

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)

Mathematical modelling and quality indices optimization of automatic control systems of reactor facility

International Nuclear Information System (INIS)

Severin, V.P.

2007-01-01

The mathematical modeling of automatic control systems of reactor facility WWER-1000 with various regulator types is considered. The linear and nonlinear models of neutron power control systems of nuclear reactor WWER-1000 with various group numbers of delayed neutrons are designed. The results of optimization of direct quality indexes of neutron power control systems of nuclear reactor WWER-1000 are designed. The identification and optimization of level control systems with various regulator types of steam generator are executed

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

Monte Carlo Simulation of the Echo Signals from Low-Flying Targets for Airborne Radar

Directory of Open Access Journals (Sweden)

Mingyuan Man

2014-01-01

Full Text Available A demonstrated hybrid method based on the combination of half-space physical optics method (PO, graphical-electromagnetic computing (GRECO, and Monte Carlo method on echo signals from low-flying targets based on actual environment for airborne radar is presented in this paper. The half-space physical optics method , combined with the graphical-electromagnetic computing (GRECO method to eliminate the shadow regions quickly and rebuild the target automatically, is employed to calculate the radar cross section (RCS of the conductive targets in half space fast and accurately. The direct echo is computed based on the radar equation. The reflected paths from sea or ground surface cause multipath effects. In order to accurately obtain the echo signals, the phase factors are modified for fluctuations in multipath, and the statistical average value of the echo signals is obtained using the Monte Carlo method. A typical simulation is performed, and the numerical results show the accuracy of the proposed method.

NASCENT: an automatic protein interaction network generation tool for non-model organisms.

Science.gov (United States)

Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

2009-04-24

Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

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.

Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

Science.gov (United States)

Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

2013-03-13

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

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...

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling.

Science.gov (United States)

Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief; Lilley, John; Sebag-Montefiore, David

2018-07-01

To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort. Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated. The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05). The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP

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.

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.

Unidirectional high fiber content composites: Automatic 3D FE model generation and damage simulation

DEFF Research Database (Denmark)

Qing, Hai; Mishnaevsky, Leon

2009-01-01

A new method and a software code for the automatic generation of 3D micromechanical FE models of unidirectional long-fiber-reinforced composite (LFRC) with high fiber volume fraction with random fiber arrangement are presented. The fiber arrangement in the cross-section is generated through random...

Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling

Directory of Open Access Journals (Sweden)

M. Alvioli

2016-11-01

Full Text Available Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.

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

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

Development of the Automatic Modeling System for Reaction Mechanisms Using REX+JGG

Science.gov (United States)

Takahashi, Takahiro; Kawai, Kohei; Nakai, Hiroyuki; Ema, Yoshinori

The identification of appropriate reaction models is very helpful for developing chemical vapor deposition (CVD) processes. In this study, we developed an automatic modeling system that analyzes experimental data on the cross- sectional shapes of films deposited on substrates with nanometer- or micrometer-sized trenches. The system then identifies a suitable reaction model to describe the film deposition. The inference engine used by the system to model the reaction mechanism was designed using real-coded genetic algorithms (RCGAs): a generation alternation model named "just generation gap" (JGG) and a real-coded crossover named "real-coded ensemble crossover" (REX). We studied the effect of REX+JGG on the system's performance, and found that the system with REX+JGG was the most accurate and reliable at model identification among the algorithms that we studied.

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

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 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.

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...

Monte Carlo simulation of the turbulent transport of airborne contaminants

International Nuclear Information System (INIS)

Watson, C.W.; Barr, S.

1975-09-01

A generalized, three-dimensional Monte Carlo model and computer code (SPOOR) are described for simulating atmospheric transport and dispersal of small pollutant clouds. A cloud is represented by a large number of particles that we track by statistically sampling simulated wind and turbulence fields. These fields are based on generalized wind data for large-scale flow and turbulent energy spectra for the micro- and mesoscales. The large-scale field can be input from a climatological data base, or by means of real-time analyses, or from a separate, subjectively defined data base. We introduce the micro- and mesoscale wind fluctuations through a power spectral density, to include effects from a broad spectrum of turbulent-energy scales. The role of turbulence is simulated in both meander and dispersal. Complex flow fields and time-dependent diffusion rates are accounted for naturally, and shear effects are simulated automatically in the ensemble of particle trajectories. An important adjunct has been the development of computer-graphics displays. These include two- and three-dimensional (perspective) snapshots and color motion pictures of particle ensembles, plus running displays of differential and integral cloud characteristics. The model's versatility makes it a valuable atmospheric research tool that we can adapt easily into broader, multicomponent systems-analysis codes. Removal, transformation, dry or wet deposition, and resuspension of contaminant particles can be readily included