Guideline for radiation transport simulation with the Monte Carlo method
Today, the photon and neutron transport calculations with the Monte Carlo method have been progressed with advanced Monte Carlo codes and high-speed computers. Monte Carlo simulation is rather suitable expression than the calculation. Once Monte Carlo codes become more friendly and performance of computer progresses, most of the shielding problems will be solved by using the Monte Carlo codes and high-speed computers. As those codes prepare the standard input data for some problems, the essential techniques for solving the Monte Carlo method and variance reduction techniques of the Monte Carlo calculation might lose the interests to the general Monte Carlo users. In this paper, essential techniques of the Monte Carlo method and the variance reduction techniques, such as importance sampling method, selection of estimator, and biasing technique, are described to afford a better understanding of the Monte Carlo method and Monte Carlo code. (author)
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo
Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)
2011-07-01
This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)
Simulation and the Monte Carlo Method, Student Solutions Manual
Rubinstein, Reuven Y
2012-01-01
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, suc
A new lattice Monte Carlo method for simulating dielectric inhomogeneity
Duan, Xiaozheng; Wang, Zhen-Gang; Nakamura, Issei
We present a new lattice Monte Carlo method for simulating systems involving dielectric contrast between different species by modifying an algorithm originally proposed by Maggs et al. The original algorithm is known to generate attractive interactions between particles that have different dielectric constant than the solvent. Here we show that such attractive force is spurious, arising from incorrectly biased statistical weight caused by the particle motion during the Monte Carlo moves. We propose a new, simple algorithm to resolve this erroneous sampling. We demonstrate the application of our algorithm by simulating an uncharged polymer in a solvent with different dielectric constant. Further, we show that the electrostatic fields in ionic crystals obtained from our simulations with a relatively small simulation box correspond well with results from the analytical solution. Thus, our Monte Carlo method avoids the need for the Ewald summation in conventional simulation methods for charged systems. This work was supported by the National Natural Science Foundation of China (21474112 and 21404103). We are grateful to Computing Center of Jilin Province for essential support.
Non-analogue Monte Carlo method, application to neutron simulation
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. Nowadays, only the Monte Carlo method offers such possibilities. 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
Research on Monte Carlo simulation method of industry CT system
There are a series of radiation physical problems in the design and production of industry CT system (ICTS), including limit quality index analysis; the effect of scattering, efficiency of detectors and crosstalk to the system. Usually the Monte Carlo (MC) Method is applied to resolve these problems. Most of them are of little probability, so direct simulation is very difficult, and existing MC methods and programs can't meet the needs. To resolve these difficulties, particle flux point auto-important sampling (PFPAIS) is given on the basis of auto-important sampling. Then, on the basis of PFPAIS, a particular ICTS simulation method: MCCT is realized. Compared with existing MC methods, MCCT is proved to be able to simulate the ICTS more exactly and effectively. Furthermore, the effects of all kinds of disturbances of ICTS are simulated and analyzed by MCCT. To some extent, MCCT can guide the research of the radiation physical problems in ICTS. (author)
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
'Odontologic dosimetric card' experiments and simulations using Monte Carlo methods
The techniques for data processing, combined with the development of fast and more powerful computers, makes the Monte Carlo methods one of the most widely used tools in the radiation transport simulation. For applications in diagnostic radiology, this method generally uses anthropomorphic phantoms to evaluate the absorbed dose to patients during exposure. In this paper, some Monte Carlo techniques were used to simulation of a testing device designed for intra-oral X-ray equipment performance evaluation called Odontologic Dosimetric Card (CDO of 'Cartao Dosimetrico Odontologico' in Portuguese) for different thermoluminescent detectors. This paper used two computational models of exposition RXD/EGS4 and CDO/EGS4. In the first model, the simulation results are compared with experimental data obtained in the similar conditions. The second model, it presents the same characteristics of the testing device studied (CDO). For the irradiations, the X-ray spectra were generated by the IPEM report number 78, spectrum processor. The attenuated spectrum was obtained for IEC 61267 qualities and various additional filters for a Pantak 320 X-ray industrial equipment. The results obtained for the study of the copper filters used in the determination of the kVp were compared with experimental data, validating the model proposed for the characterization of the CDO. The results shower of the CDO will be utilized in quality assurance programs in order to guarantee that the equipment fulfill the requirements of the Norm SVS No. 453/98 MS (Brazil) 'Directives of Radiation Protection in Medical and Dental Radiodiagnostic'. We conclude that the EGS4 is a suitable code Monte Carlo to simulate thermoluminescent dosimeters and experimental procedures employed in the routine of the quality control laboratory in diagnostic radiology. (author)
Methods for variance reduction in Monte Carlo simulations
Bixler, Joel N.; Hokr, Brett H.; Winblad, Aidan; Elpers, Gabriel; Zollars, Byron; Thomas, Robert J.
2016-03-01
Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, due to the probabilistic nature of these simulations, large numbers of photons are often required in order to generate relevant results. Here, we present methods for reduction in the variance of dose distribution in a computational volume. Dose distribution is computed via tracing of a large number of rays, and tracking the absorption and scattering of the rays within discrete voxels that comprise the volume. Variance reduction is shown here using quasi-random sampling, interaction forcing for weakly scattering media, and dose smoothing via bi-lateral filtering. These methods, along with the corresponding performance enhancements are detailed here.
A new DNB design method using the system moment method combined with Monte Carlo simulation
A new statistical method of core thermal design for pressurized water reactors is presented. It not only quantifies the DNBR parameter uncertainty by the system moment method, but also combines the DNBR parameter with correlation uncertainty using Monte Carlo technique. The randomizing function for Monte Carlo simulation was expressed in a form of reciprocal-multiplication of DNBR parameter and correlation uncertainty factors. The results of comparisons with the conventional methods show that the DNBR limit calculated by this method is in good agreement with that by the SCU method with less computational effort and it is considered applicable to the current DNB design
Hybrid Monte-Carlo method for simulating neutron and photon radiography
We present a Hybrid Monte-Carlo method (HMCM) for simulating neutron and photon radiographs. HMCM utilizes the combination of a Monte-Carlo particle simulation for calculating incident film radiation and a statistical post-processing routine to simulate film noise. Since the method relies on MCNP for transport calculations, it is easily generalized to most non-destructive evaluation (NDE) simulations. We verify the method's accuracy through ASTM International's E592-99 publication, Standard Guide to Obtainable (E)quivalent Penetrameter Sensitivity for Radiography of Steel Plates [1]. Potential uses for the method include characterizing alternative radiological sources and simulating NDE radiographs
Hybrid Monte-Carlo method for simulating neutron and photon radiography
Wang, Han; Tang, Vincent
2013-11-01
We present a Hybrid Monte-Carlo method (HMCM) for simulating neutron and photon radiographs. HMCM utilizes the combination of a Monte-Carlo particle simulation for calculating incident film radiation and a statistical post-processing routine to simulate film noise. Since the method relies on MCNP for transport calculations, it is easily generalized to most non-destructive evaluation (NDE) simulations. We verify the method's accuracy through ASTM International's E592-99 publication, Standard Guide to Obtainable Equivalent Penetrameter Sensitivity for Radiography of Steel Plates [1]. Potential uses for the method include characterizing alternative radiological sources and simulating NDE radiographs.
Simulating rotationally inelastic collisions using a Direct Simulation Monte Carlo method
Schullian, O; Vaeck, N; van der Avoird, A; Heazlewood, B R; Rennick, C J; Softley, T P
2015-01-01
A new approach to simulating rotational cooling using a direct simulation Monte Carlo (DSMC) method is described and applied to the rotational cooling of ammonia seeded into a helium supersonic jet. The method makes use of ab initio rotational state changing cross sections calculated as a function of collision energy. Each particle in the DSMC simulations is labelled with a vector of rotational populations that evolves with time. Transfer of energy into translation is calculated from the mean energy transfer for this population at the specified collision energy. The simulations are compared with a continuum model for the on-axis density, temperature and velocity; rotational temperature as a function of distance from the nozzle is in accord with expectations from experimental measurements. The method could be applied to other types of gas mixture dynamics under non-uniform conditions, such as buffer gas cooling of NH$_3$ by He.
Study of the quantitative analysis approach of maintenance by the Monte Carlo simulation method
This study is examination of the quantitative valuation by Monte Carlo simulation method of maintenance activities of a nuclear power plant. Therefore, the concept of the quantitative valuation of maintenance that examination was advanced in the Japan Society of Maintenology and International Institute of Universality (IUU) was arranged. Basis examination for quantitative valuation of maintenance was carried out at simple feed water system, by Monte Carlo simulation method. (author)
External individual monitoring: experiments and simulations using Monte Carlo Method
In this work, we have evaluated the possibility of applying the Monte Carlo simulation technique in photon dosimetry of external individual monitoring. The GEANT4 toolkit was employed to simulate experiments with radiation monitors containing TLD-100 and CaF2:NaCl thermoluminescent detectors. As a first step, X ray spectra were generated impinging electrons on a tungsten target. Then, the produced photon beam was filtered in a beryllium window and additional filters to obtain the radiation with desired qualities. This procedure, used to simulate radiation fields produced by a X ray tube, was validated by comparing characteristics such as half value layer, which was also experimentally measured, mean photon energy and the spectral resolution of simulated spectra with that of reference spectra established by international standards. In the construction of thermoluminescent dosimeter, two approaches for improvements have. been introduced. The first one was the inclusion of 6% of air in the composition of the CaF2:NaCl detector due to the difference between measured and calculated values of its density. Also, comparison between simulated and experimental results showed that the self-attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account. Then, in the second approach, the light attenuation coefficient of CaF2:NaCl compound estimated by simulation to be 2,20(25) mm-1 was introduced. Conversion coefficients Cp from air kerma to personal dose equivalent were calculated using a slab water phantom with polymethyl-metacrilate (PMMA) walls, for reference narrow and wide X ray spectrum series [ISO 4037-1], and also for the wide spectra implanted and used in routine at Laboratorio de Dosimetria. Simulations of backscattered radiations by PMMA slab water phantom and slab phantom of ICRU tissue-equivalent material produced very similar results. Therefore, the PMMA slab water phantom that can be easily constructed with low price can
MONTE CARLO METHOD AND APPLICATION IN @RISK SIMULATION SYSTEM
Gabriela Ižaríková
2015-12-01
Full Text Available The article is an example of using the software simulation @Risk designed for simulation in Microsoft Excel spread sheet, demonstrated the possibility of its usage in order to show a universal method of solving problems. The simulation is experimenting with computer models based on the real production process in order to optimize the production processes or the system. The simulation model allows performing a number of experiments, analysing them, evaluating, optimizing and afterwards applying the results to the real system. A simulation model in general is presenting modelling system by using mathematical formulations and logical relations. In the model is possible to distinguish controlled inputs (for instance investment costs and random outputs (for instance demand, which are by using a model transformed into outputs (for instance mean value of profit. In case of a simulation experiment at the beginning are chosen controlled inputs and random (stochastic outputs are generated randomly. Simulations belong into quantitative tools, which can be used as a support for a decision making.
The factorization method for Monte Carlo simulations of systems with a complex with
Ambjørn, J.; Anagnostopoulos, K. N.; Nishimura, J.; Verbaarschot, J. J. M.
2004-03-01
We propose a method for Monte Carlo simulations of systems with a complex action. The method has the advantages of being in principle applicable to any such system and provides a solution to the overlap problem. In some cases, like in the IKKT matrix model, a finite size scaling extrapolation can provide results for systems whose size would make it prohibitive to simulate directly.
Simulating Compton scattering using Monte Carlo method: COSMOC library
Adámek, K.; Bursa, Michal
Opava: Silesian University, 2014 - (Stuchlík, Z.), s. 1-10. (Publications of the Institute of Physics. 7). ISBN 9788075101266. ISSN 2336-5668. [RAGtime /14.-16./. Opava (CZ), 18.09. 2012 -22.09. 2012 ] Institutional support: RVO:67985815 Keywords : Monte Carlo * Compton scattering * C++ Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
A Method for Estimating Annual Energy Production Using Monte Carlo Wind Speed Simulation
Birgir Hrafnkelsson
2016-04-01
Full Text Available A novel Monte Carlo (MC approach is proposed for the simulation of wind speed samples to assess the wind energy production potential of a site. The Monte Carlo approach is based on historical wind speed data and reserves the effect of autocorrelation and seasonality in wind speed observations. No distributional assumptions are made, and this approach is relatively simple in comparison to simulation methods that aim at including the autocorrelation and seasonal effects. Annual energy production (AEP is simulated by transforming the simulated wind speed values via the power curve of the wind turbine at the site. The proposed Monte Carlo approach is generic and is applicable for all sites provided that a sufficient amount of wind speed data and information on the power curve are available. The simulated AEP values based on the Monte Carlo approach are compared to both actual AEP and to simulated AEP values based on a modified Weibull approach for wind speed simulation using data from the Burfell site in Iceland. The comparison reveals that the simulated AEP values based on the proposed Monte Carlo approach have a distribution that is in close agreement with actual AEP from two test wind turbines at the Burfell site, while the simulated AEP of the Weibull approach is such that the P50 and the scale are substantially lower and the P90 is higher. Thus, the Weibull approach yields AEP that is not in line with the actual variability in AEP, while the Monte Carlo approach gives a realistic estimate of the distribution of AEP.
Particle behavior simulation in thermophoresis phenomena by direct simulation Monte Carlo method
Wada, Takao
2014-07-01
A particle motion considering thermophoretic force is simulated by using direct simulation Monte Carlo (DSMC) method. Thermophoresis phenomena, which occur for a particle size of 1 μm, are treated in this paper. The problem of thermophoresis simulation is computation time which is proportional to the collision frequency. Note that the time step interval becomes much small for the simulation considering the motion of large size particle. Thermophoretic forces calculated by DSMC method were reported, but the particle motion was not computed because of the small time step interval. In this paper, the molecule-particle collision model, which computes the collision between a particle and multi molecules in a collision event, is considered. The momentum transfer to the particle is computed with a collision weight factor, where the collision weight factor means the number of molecules colliding with a particle in a collision event. The large time step interval is adopted by considering the collision weight factor. Furthermore, the large time step interval is about million times longer than the conventional time step interval of the DSMC method when a particle size is 1 μm. Therefore, the computation time becomes about one-millionth. We simulate the graphite particle motion considering thermophoretic force by DSMC-Neutrals (Particle-PLUS neutral module) with above the collision weight factor, where DSMC-Neutrals is commercial software adopting DSMC method. The size and the shape of the particle are 1 μm and a sphere, respectively. The particle-particle collision is ignored. We compute the thermophoretic forces in Ar and H2 gases of a pressure range from 0.1 to 100 mTorr. The results agree well with Gallis' analytical results. Note that Gallis' analytical result for continuum limit is the same as Waldmann's result.
New methods for the Monte Carlo simulation of neutron noise experiments in Ads
This paper presents two improvements to speed up the Monte-Carlo simulation of neutron noise experiments. The first one is to separate the actual Monte Carlo transport calculation from the digital signal processing routines, while the second is to introduce non-analogue techniques to improve the efficiency of the Monte Carlo calculation. For the latter method, adaptations to the theory of neutron noise experiments were made to account for the distortion of the higher-moments of the calculated neutron noise. Calculations were performed to test the feasibility of the above outlined scheme and to demonstrate the advantages of the application of the track length estimator. It is shown that the modifications improve the efficiency of these calculations to a high extent, which turns the Monte Carlo method into a powerful tool for the development and design of on-line reactivity measurement systems for ADS
We present a new, nondestructive, method for determining chemical potentials in Monte Carlo and molecular dynamics simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials in which the Monte Carlo method is used to determine success or failure of the creation/destruction attempts; we thus call the method a detailed balance method. The method allows one to obtain estimates of the chemical potential for a given species in any closed ensemble simulation; the closed ensemble is paired with a ''natural'' open ensemble for the purpose of obtaining creation and destruction probabilities. We present results for the Lennard-Jones system and also for an embedded atom model of liquid palladium, and compare to previous results in the literature for these two systems. We are able to obtain an accurate estimate of the chemical potential for the Lennard-Jones system at higher densities than reported in the literature
Highlights: • The subdivision combines both advantages of uniform and non-uniform schemes. • The grid models were proved to be more efficient than traditional CSG models. • Monte Carlo simulation performance was enhanced by Optimal Spatial Subdivision. • Efficiency gains were obtained for realistic whole reactor core models. - Abstract: Geometry navigation is one of the key aspects of dominating Monte Carlo particle transport simulation performance for large-scale whole reactor models. In such cases, spatial subdivision is an easily-established and high-potential method to improve the run-time performance. In this study, a dedicated method, named Optimal Spatial Subdivision, is proposed for generating numerically optimal spatial grid models, which are demonstrated to be more efficient for geometry navigation than traditional Constructive Solid Geometry (CSG) models. The method uses a recursive subdivision algorithm to subdivide a CSG model into non-overlapping grids, which are labeled as totally or partially occupied, or not occupied at all, by CSG objects. The most important point is that, at each stage of subdivision, a conception of quality factor based on a cost estimation function is derived to evaluate the qualities of the subdivision schemes. Only the scheme with optimal quality factor will be chosen as the final subdivision strategy for generating the grid model. Eventually, the model built with the optimal quality factor will be efficient for Monte Carlo particle transport simulation. The method has been implemented and integrated into the Super Monte Carlo program SuperMC developed by FDS Team. Testing cases were used to highlight the performance gains that could be achieved. Results showed that Monte Carlo simulation runtime could be reduced significantly when using the new method, even as cases reached whole reactor core model sizes
Research of Monte Carlo method used in simulation of different maintenance processes
The paper introduces two kinds of Monte Carlo methods used in equipment life process simulation under the least maintenance: condition: method of producing the interval of lifetime, method of time scale conversion. The paper also analyzes the characteristics and the using scope of the two methods. By using the conception of service age reduction factor, the model of equipment's life process under incomplete maintenance condition is established, and also the life process simulation method applicable to this situation is invented. (authors)
Application of Macro Response Monte Carlo method for electron spectrum simulation
During the past years several variance reduction techniques for Monte Carlo electron transport have been developed in order to reduce the electron computation time transport for absorbed dose distribution. We have implemented the Macro Response Monte Carlo (MRMC) method to evaluate the electron spectrum which can be used as a phase space input for others simulation programs. Such technique uses probability distributions for electron histories previously simulated in spheres (called kugels). These probabilities are used to sample the primary electron final state, as well as the creation secondary electrons and photons. We have compared the MRMC electron spectra simulated in homogeneous phantom against the Geant4 spectra. The results showed an agreement better than 6% in the spectra peak energies and that MRMC code is up to 12 time faster than Geant4 simulations
Reliability Assessment of Active Distribution System Using Monte Carlo Simulation Method
Shaoyun Ge
2014-01-01
Full Text Available In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.
GHAREHPETIAN, G. B.
2009-06-01
Full Text Available The analysis of the risk of partial and total blackouts has a crucial role to determine safe limits in power system design, operation and upgrade. Due to huge cost of blackouts, it is very important to improve risk assessment methods. In this paper, Monte Carlo simulation (MCS was used to analyze the risk and Gaussian Mixture Method (GMM has been used to estimate the probability density function (PDF of the load curtailment, in order to improve the power system risk assessment method. In this improved method, PDF and a suggested index have been used to analyze the risk of loss of load. The effect of considering the number of generation units of power plants in the risk analysis has been studied too. The improved risk assessment method has been applied to IEEE 118 bus and the network of Khorasan Regional Electric Company (KREC and the PDF of the load curtailment has been determined for both systems. The effect of various network loadings, transmission unavailability, transmission capacity and generation unavailability conditions on blackout risk has been investigated too.
Datema, C.P. E-mail: c.datema@iri.tudelft.nl; Bom, V.R.; Eijk, C.W.E. van
2002-08-01
Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.
Direct simulation Monte Carlo calculation of rarefied gas drag using an immersed boundary method
Jin, W.; Kleijn, C. R.; van Ommen, J. R.
2016-06-01
For simulating rarefied gas flows around a moving body, an immersed boundary method is presented here in conjunction with the Direct Simulation Monte Carlo (DSMC) method in order to allow the movement of a three dimensional immersed body on top of a fixed background grid. The simulated DSMC particles are reflected exactly at the landing points on the surface of the moving immersed body, while the effective cell volumes are taken into account for calculating the collisions between molecules. The effective cell volumes are computed by utilizing the Lagrangian intersecting points between the immersed boundary and the fixed background grid with a simple polyhedra regeneration algorithm. This method has been implemented in OpenFOAM and validated by computing the drag forces exerted on steady and moving spheres and comparing the results to that from conventional body-fitted mesh DSMC simulations and to analytical approximations.
Coherent-wave Monte Carlo method for simulating light propagation in tissue
Kraszewski, Maciej; Pluciński, Jerzy
2016-03-01
Simulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative transfer equation, allows to simulate only propagation of light averaged over the ensemble of turbid medium realizations. This makes them unuseful for simulating phenomena connected to coherence properties of light. We propose a new method for simulating propagation of coherent light (e.g. laser beam) in biological tissue, that we called Coherent-Wave Monte Carlo method. This method is based on direct computation of optical interaction between scatterers inside the random medium, what allows to reduce amount of memory and computation time required for simulation. We present the theoretical basis of the proposed method and its comparison with finite-difference methods for simulating light propagation in scattering media in Rayleigh approximation regime.
Application of direct simulation Monte Carlo method for analysis of AVLIS evaporation process
The computation code of the direct simulation Monte Carlo (DSMC) method was developed in order to analyze the atomic vapor evaporation in atomic vapor laser isotope separation (AVLIS). The atomic excitation temperatures of gadolinium atom were calculated for the model with five low lying states. Calculation results were compared with the experiments obtained by laser absorption spectroscopy. Two types of DSMC simulations which were different in inelastic collision procedure were carried out. It was concluded that the energy transfer was forbidden unless the total energy of the colliding atoms exceeds a threshold value. (author)
Comparing Subspace Methods for Closed Loop Subspace System Identification by Monte Carlo Simulations
David Di Ruscio
2009-10-01
Full Text Available A novel promising bootstrap subspace system identification algorithm for both open and closed loop systems is presented. An outline of the SSARX algorithm by Jansson (2003 is given and a modified SSARX algorithm is presented. Some methods which are consistent for closed loop subspace system identification presented in the literature are discussed and compared to a recently published subspace algorithm which works for both open as well as for closed loop data, i.e., the DSR_e algorithm as well as the bootstrap method. Experimental comparisons are performed by Monte Carlo simulations.
Reliability assessments based on probabilistic fracture mechanics can give insight into the effects of changes in design parameters, operational conditions and maintenance schemes. Although they are often not capable of providing absolute reliability values, these methods at least allow the ranking of different solutions among alternatives. Due to the variety of possible solutions for design, operation and maintenance problems numerous probabilistic reliability assessments have to be carried out. This is a laborous task especially for crack containing welds of nuclear pipes subjected to fatigue. The objective of this paper is to compare the Monte Carlo simulation method and a newly developed approximative approach using the Markov process ansatz for this task
Monte Carlo simulation methods of determining red bone marrow dose from external radiation
Objective: To provide evidence for a more reasonable method of determining red bone marrow dose by analyzing and comparing existing simulation methods. Methods: By utilizing Monte Carlo simulation software MCNPX, the absorbed doses of red hone marrow of Rensselaer Polytechnic Institute (RPI) adult female voxel phantom were calculated through 4 different methods: direct energy deposition.dose response function (DRF), King-Spiers factor method and mass-energy absorption coefficient (MEAC). The radiation sources were defined as infinite plate.sources with the energy ranging from 20 keV to 10 MeV, and 23 sources with different energies were simulated in total. The source was placed right next to the front of the RPI model to achieve a homogeneous anteroposterior radiation scenario. The results of different simulated photon energy sources through different methods were compared. Results: When the photon energy was lower than 100 key, the direct energy deposition method gave the highest result while the MEAC and King-Spiers factor methods showed more reasonable results. When the photon energy was higher than 150 keV taking into account of the higher absorption ability of red bone marrow at higher photon energy, the result of the King-Spiers factor method was larger than those of other methods. Conclusions: The King-Spiers factor method might be the most reasonable method to estimate the red bone marrow dose from external radiation. (authors)
Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method
Cave, H. M.; Tseng, K.-C.; Wu, J.-S.; Jermy, M. C.; Huang, J.-C.; Krumdieck, S. P.
2008-06-01
An unsteady sampling routine for a general parallel direct simulation Monte Carlo method called PDSC is introduced, allowing the simulation of time-dependent flow problems in the near continuum range. A post-processing procedure called DSMC rapid ensemble averaging method (DREAM) is developed to improve the statistical scatter in the results while minimising both memory and simulation time. This method builds an ensemble average of repeated runs over small number of sampling intervals prior to the sampling point of interest by restarting the flow using either a Maxwellian distribution based on macroscopic properties for near equilibrium flows (DREAM-I) or output instantaneous particle data obtained by the original unsteady sampling of PDSC for strongly non-equilibrium flows (DREAM-II). The method is validated by simulating shock tube flow and the development of simple Couette flow. Unsteady PDSC is found to accurately predict the flow field in both cases with significantly reduced run-times over single processor code and DREAM greatly reduces the statistical scatter in the results while maintaining accurate particle velocity distributions. Simulations are then conducted of two applications involving the interaction of shocks over wedges. The results of these simulations are compared to experimental data and simulations from the literature where there these are available. In general, it was found that 10 ensembled runs of DREAM processing could reduce the statistical uncertainty in the raw PDSC data by 2.5-3.3 times, based on the limited number of cases in the present study.
Numerical simulation of C/O spectroscopy in logging by Monte-Carlo method
Numerical simulation of ratio of C/O spectroscopy in logging by Monte-Carlo method is made in this paper. Agree well with the measured spectra, the simulated spectra can meet the requirement of logging practice. Vari- ous kinds of C/O ratios affected by different formation oil saturations,borehole oil fractions, casing sizes and concrete ring thicknesses are investigated. In order to achieve accurate results of processing the spectra, this paper presents a new method for unfolding the C/O inelastic gamma spectroscopy, and analysis for the spectra using the method, The result agrees with the fact. These rules and method can be used as calibrating tools and logging interpretation. (authors)
Computed tomography (CT) is one of the most used techniques in medical diagnosis, and its use has become one of the main sources of exposure of the population to ionising radiation. This work concentrates on the paediatric patients, since children exhibit higher radiosensitivity than adults. Nowadays, patient doses are estimated through two standard CT dose index (CTDI) phantoms as a reference to calculate CTDI volume (CTDIvol) values. This study aims at improving the knowledge about the radiation exposure to children and to better assess the accuracy of the CTDIvol method. The effectiveness of the CTDIvol method for patient dose estimation was then investigated through a sensitive study, taking into account the doses obtained by three methods: CTDIvol measured, CTDIvol values simulated with Monte Carlo (MC) code MCNPX and the recent proposed method Size-Specific Dose Estimate (SSDE). In order to assess organ doses, MC simulations were executed with paediatric voxel phantoms. (authors)
Research on Reliability Modelling Method of Machining Center Based on Monte Carlo Simulation
Chuanhai Chen
2013-03-01
Full Text Available The aim of this study is to get the reliability of series system and analyze the reliability of machining center. So a modified method of reliability modelling based on Monte Carlo simulation for series system is proposed. The reliability function, which is built by the classical statistics method based on the assumption that machine tools were repaired as good as new, may be biased in the real case. The reliability functions of subsystems are established respectively and then the reliability model is built according to the reliability block diagram. Then the fitting reliability function of machine tools is established using the failure data of sample generated by Monte Carlo simulation, whose inverse reliability function is solved by the linearization technique based on radial basis function. Finally, an example of the machining center is presented using the proposed method to show its potential application. The analysis results show that the proposed method can provide an accurate reliability model compared with the conventional method.
A Monte Carlo simulation based inverse propagation method for stochastic model updating
Bao, Nuo; Wang, Chunjie
2015-08-01
This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.
On-the-fly nuclear data processing methods for Monte Carlo simulations of fast spectrum systems
Walsh, Jon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-08-31
The presentation summarizes work performed over summer 2015 related to Monte Carlo simulations. A flexible probability table interpolation scheme has been implemented and tested with results comparing favorably to the continuous phase-space on-the-fly approach.
Monte Carlo codes GEANT 4 and MUSIC have been used to calculate background components of low-level HPGe gamma-ray spectrometers operating in a shallow underground laboratory. The simulated background gamma-ray spectra have been comparable with spectra measured at the Ogoya underground laboratory operating at the depth of 270 m w.e. (water equivalent). The Monte Carlo simulations have proved to be useful approach in estimation of background characteristics of HPGe spectrometers before their construction. (author)
Kadoura, Ahmad
2011-06-06
Lennard‐Jones (L‐J) and Buckingham exponential‐6 (exp‐6) potential models were used to produce isotherms for methane at temperatures below and above critical one. Molecular simulation approach, particularly Monte Carlo simulations, were employed to create these isotherms working with both canonical and Gibbs ensembles. Experiments in canonical ensemble with each model were conducted to estimate pressures at a range of temperatures above methane critical temperature. Results were collected and compared to experimental data existing in literature; both models showed an elegant agreement with the experimental data. In parallel, experiments below critical temperature were run in Gibbs ensemble using L‐J model only. Upon comparing results with experimental ones, a good fit was obtained with small deviations. The work was further developed by adding some statistical studies in order to achieve better understanding and interpretation to the estimated quantities by the simulation. Methane phase diagrams were successfully reproduced by an efficient molecular simulation technique with different potential models. This relatively simple demonstration shows how powerful molecular simulation methods could be, hence further applications on more complicated systems are considered. Prediction of phase behavior of elemental sulfur in sour natural gases has been an interesting and challenging field in oil and gas industry. Determination of elemental sulfur solubility conditions helps avoiding all kinds of problems caused by its dissolution in gas production and transportation processes. For this purpose, further enhancement to the methods used is to be considered in order to successfully simulate elemental sulfur phase behavior in sour natural gases mixtures.
Wind Turbine Placement Optimization by means of the Monte Carlo Simulation Method
S. Brusca
2014-01-01
Full Text Available This paper defines a new procedure for optimising wind farm turbine placement by means of Monte Carlo simulation method. To verify the algorithm’s accuracy, an experimental wind farm was tested in a wind tunnel. On the basis of experimental measurements, the error on wind farm power output was less than 4%. The optimization maximises the energy production criterion; wind turbines’ ground positions were used as independent variables. Moreover, the mathematical model takes into account annual wind intensities and directions and wind turbine interaction. The optimization of a wind farm on a real site was carried out using measured wind data, dominant wind direction, and intensity data as inputs to run the Monte Carlo simulations. There were 30 turbines in the wind park, each rated at 20 kW. This choice was based on wind farm economics. The site was proportionally divided into 100 square cells, taking into account a minimum windward and crosswind distance between the turbines. The results highlight that the dominant wind intensity factor tends to overestimate the annual energy production by about 8%. Thus, the proposed method leads to a more precise annual energy evaluation and to a more optimal placement of the wind turbines.
Simulation of the self-powered detectors sensibility using the Monte Carlo method
This work presents a Monte Carlo simulation of Cobalt self-powered detectors, determining the detectors sensitivities to the neutron field. Several detectors, which results are published, were simulated in order to check the performance of this simulation. Furthermore, the sensitivity variation with the geometric parameters and with the irradiation time in the reactor was evaluated. (author)
Simulation of nuclear material identification system based on Monte Carlo sampling method
Background: Caused by the danger of radioactivity, nuclear material identification is sometimes a difficult problem. Purpose: In order to reflect the particle transport processes in nuclear fission and present the effectiveness of the signatures of Nuclear Materials Identification System (NMIS), based on physical principles and experimental statistical data. Methods: We established a Monte Carlo simulation model of nuclear material identification system and then acquired three channels of time domain pulse signal. Results: Auto-Correlation Functions (AC), Cross-Correlation Functions (CC), Auto Power Spectral Densities (APSD) and Cross Power Spectral Densities (CPSD) between channels can obtain several signatures, which can show some characters of nuclear material. Conclusions: The simulation results indicate that the way can help to further study the features of the system. (authors)
Self-optimizing Monte Carlo method for nuclear well logging simulation
Liu, Lianyan
1997-09-01
In order to increase the efficiency of Monte Carlo simulation for nuclear well logging problems, a new method has been developed for variance reduction. With this method, an importance map is generated in the regular Monte Carlo calculation as a by-product, and the importance map is later used to conduct the splitting and Russian roulette for particle population control. By adopting a spatial mesh system, which is independent of physical geometrical configuration, the method allows superior user-friendliness. This new method is incorporated into the general purpose Monte Carlo code MCNP4A through a patch file. Two nuclear well logging problems, a neutron porosity tool and a gamma-ray lithology density tool are used to test the performance of this new method. The calculations are sped up over analog simulation by 120 and 2600 times, for the neutron porosity tool and for the gamma-ray lithology density log, respectively. The new method enjoys better performance by a factor of 4~6 times than that of MCNP's cell-based weight window, as per the converged figure-of-merits. An indirect comparison indicates that the new method also outperforms the AVATAR process for gamma-ray density tool problems. Even though it takes quite some time to generate a reasonable importance map from an analog run, a good initial map can create significant CPU time savings. This makes the method especially suitable for nuclear well logging problems, since one or several reference importance maps are usually available for a given tool. Study shows that the spatial mesh sizes should be chosen according to the mean-free-path. The overhead of the importance map generator is 6% and 14% for neutron and gamma-ray cases. The learning ability towards a correct importance map is also demonstrated. Although false-learning may happen, physical judgement can help diagnose with contributon maps. Calibration and analysis are performed for the neutron tool and the gamma-ray tool. Due to the fact that a very
Matsumiya, T. [Nippon Steel Corporation, Tokyo (Japan)
1996-08-20
The Monte Carlo method was used to simulate an equilibrium diagram, and structural formation of transformation and recrystallization. In simulating the Cu-A equilibrium diagram, the calculation was performed by laying 24 face centered cubic lattices including four lattice points in all of the three directions, and using a simulation cell consisting of lattice points of a total of 24{sup 3}{times}4 points. Although this method has a possibility to discover existence of an unknown phase as a result of the calculation, problems were found left in handling of lattice mitigation, and in simulation of phase diagrams over phases with different crystal structures. In simulation of the transformation and recrystallization, discussions were given on correspondence of 1MCS to time when the lattice point size is increased, and on handling of nucleus formation. As a result, it was estimated that in three-dimensional grain growth, the average grain size is proportional to 1/3 power of the MCS number, and the real time against 1MCS is proportional to three power of the lattice point size. 11 refs., 8 figs., 2 tabs.
Samejima, Masaki; Akiyoshi, Masanori; Mitsukuni, Koshichiro; Komoda, Norihisa
We propose a business scenario evaluation method using qualitative and quantitative hybrid model. In order to evaluate business factors with qualitative causal relations, we introduce statistical values based on propagation and combination of effects of business factors by Monte Carlo simulation. In propagating an effect, we divide a range of each factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we decide an effect of each arc using contribution degree and sum all effects. Through applied results to practical models, it is confirmed that there are no differences between results obtained by quantitative relations and results obtained by the proposed method at the risk rate of 5%.
Gamma ray energy loss spectra simulation in NaI detectors with the Monte Carlo method
With the aim of studying and applying the Monte Carlo method, a computer code was developed to calculate the pulse height spectra and detector efficiencies for gamma rays incident on NaI (Tl) crystals. The basic detector processes in NaI (Tl) detectors are given together with an outline of Monte Carlo methods and a general review of relevant published works. A detailed description of the application of Monte Carlo methods to ν-ray detection in NaI (Tl) detectors is given. Comparisons are made with published, calculated and experimental, data. (Author)
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
A method of modelling the dynamic motion of multileaf collimators (MLCs) for intensity-modulated radiation therapy (IMRT) was developed and implemented into the Monte Carlo simulation. The simulation of the dynamic MLCs (DMLCs) was based on randomizing leaf positions during a simulation so that the number of particle histories being simulated for each possible leaf position was proportional to the monitor units delivered to that position. This approach was incorporated into an EGS4 Monte Carlo program, and was evaluated in simulating the DMLCs for Varian accelerators (Varian Medical Systems, Palo Alto, CA, USA). The MU index of each segment, which was specified in the DMLC-control data, was used to compute the cumulative probability distribution function (CPDF) for the leaf positions. This CPDF was then used to sample the leaf positions during a real-time simulation, which allowed for either the step-shoot or sweeping-leaf motion in the beam delivery. Dose intensity maps for IMRT fields were computed using the above Monte Carlo method, with its accuracy verified by film measurements. The DMLC simulation improved the operational efficiency by eliminating the need to simulate multiple segments individually. More importantly, the dynamic motion of the leaves could be simulated more faithfully by using the above leaf-position sampling technique in the Monte Carlo simulation. (author)
Ertekin Öztekin Öztekin
2015-12-01
Full Text Available Design of the distance of bolts to each other and design of the distance of bolts to the edge of connection plates are made based on minimum and maximum boundary values proposed by structural codes. In this study, reliabilities of those distances were investigated. For this purpose, loading types, bolt types and plate thicknesses were taken as variable parameters. Monte Carlo Simulation (MCS method was used in the reliability computations performed for all combination of those parameters. At the end of study, all reliability index values for all those distances were presented in graphics and tables. Results obtained from this study compared with the values proposed by some structural codes and finally some evaluations were made about those comparisons. Finally, It was emphasized in the end of study that, it would be incorrect of the usage of the same bolt distances in the both traditional designs and the higher reliability level designs.
Simulation of Watts Bar initial startup tests with continuous energy Monte Carlo methods
The Consortium for Advanced Simulation of Light Water Reactors is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable numeric reference for VERA neutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients. (author)
Multi-level Monte Carlo Methods for Efficient Simulation of Coulomb Collisions
Ricketson, Lee
2013-10-01
We discuss the use of multi-level Monte Carlo (MLMC) schemes--originally introduced by Giles for financial applications--for the efficient simulation of Coulomb collisions in the Fokker-Planck limit. The scheme is based on a Langevin treatment of collisions, and reduces the computational cost of achieving a RMS error scaling as ɛ from O (ɛ-3) --for standard Langevin methods and binary collision algorithms--to the theoretically optimal scaling O (ɛ-2) for the Milstein discretization, and to O (ɛ-2 (logɛ)2) with the simpler Euler-Maruyama discretization. In practice, this speeds up simulation by factors up to 100. We summarize standard MLMC schemes, describe some tricks for achieving the optimal scaling, present results from a test problem, and discuss the method's range of applicability. This work was performed under the auspices of the U.S. DOE by the University of California, Los Angeles, under grant DE-FG02-05ER25710, and by LLNL under contract DE-AC52-07NA27344.
Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods
Godfrey, Andrew T [ORNL; Gehin, Jess C [ORNL; Bekar, Kursat B [ORNL; Celik, Cihangir [ORNL
2014-01-01
The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.
Multiple-scaling methods for Monte Carlo simulations of radiative transfer in cloudy atmosphere
Two multiple-scaling methods for Monte Carlo simulations were derived from integral radiative transfer equation for calculating radiance in cloudy atmosphere accurately and rapidly. The first one is to truncate sharp forward peaks of phase functions for each order of scattering adaptively. The truncated functions for forward peaks are approximated as quadratic functions; only one prescribed parameter is used to set maximum truncation fraction for various phase functions. The second one is to increase extinction coefficients in optically thin regions for each order scattering adaptively, which could enhance the collision chance adaptively in the regions where samples are rare. Several one-dimensional and three-dimensional cloud fields were selected to validate the methods. The numerical results demonstrate that the bias errors were below 0.2% for almost all directions except for glory direction (less than 0.4%) and the higher numerical efficiency could be achieved when quadratic functions were used. The second method could decrease radiance noise to 0.60% for cumulus and accelerate convergence in optically thin regions. In general, the main advantage of the proposed methods is that we could modify the atmospheric optical quantities adaptively for each order of scattering and sample important contribution according to the specific atmospheric conditions.
Analysis of the Tandem Calibration Method for Kerma Area Product Meters Via Monte Carlo Simulations
The IAEA recommends that uncertainties of dosimetric measurements in diagnostic radiology for risk assessment and quality assurance should be less than 7% on the confidence level of 95%. This accuracy is difficult to achieve with kerma area product (KAP) meters currently used in clinics. The reasons range from the high energy dependence of KAP meters to the wide variety of configurations in which KAP meters are used and calibrated. The tandem calibration method introduced by Poeyry, Komppa and Kosunen in 2005 has the potential to make the calibration procedure simpler and more accurate compared to the traditional beam-area method. In this method, two positions of the reference KAP meter are of interest: (a) a position close to the field KAP meter and (b) a position 20 cm above the couch. In the close position, the distance between the two KAP meters should be at least 30 cm to reduce the effect of back scatter. For the other position, which is recommended for the beam-area calibration method, the distance of 70 cm between the KAP meters was used in this study. The aim of this work was to complement existing experimental data comparing the two configurations with Monte Carlo (MC) simulations. In a geometry consisting of a simplified model of the VacuTec 70157 type KAP meter, the MCNP code was used to simulate the kerma area product, PKA, for the two (close and distant) reference planes. It was found that PKA values for the tube voltage of 40 kV were about 2.5% lower for the distant plane than for the close one. For higher tube voltages, the difference was smaller. The difference was mainly caused by attenuation of the X ray beam in air. Since the problem with high uncertainties in PKA measurements is also caused by the current design of X ray machines, possible solutions are discussed. (author)
Mean field simulation for Monte Carlo integration
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
ZHANG Jun; GUO Fan
2015-01-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system’s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system’s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
Monte-Carlo method simulation of the Bremsstrahlung mirror reflection experiment
Full text: To detect gamma-ray mirror reflection on macroscopic smooth surface a search experiment at microtron MT-22S with 330 meter flying distance is in progress. Measured slip angles (i.e. angles between incident ray and reflector surface) don't exceed tens of micro-radian. Under such angles an effect of the reflection could be easily veiled due to negative background conditions. That is why the process needed to be simulated by Monte-Carlo method as accurate as possible and corresponding computer program was developed. A first operating mode of the MT-22S generates 13 MeV electrons that are incident on a Bremsstrahlung target. So energies of gamma-rays were simulated to be in the range of 0.01†12.5 MeV and be distributed by known Shift formula. When any gamma-quantum was incident on the reflector it resulted in following two cases. If its slip angle was more than the critical one, gamma-quantum was to be absorbed by the reflector and the program started to simulate next event. In the other case the program replaced incident gamma-quantum trajectory parameters by the reflected ones. The gamma-quantum trajectory behind the reflector was traced till its detector. Any gamma-quantum that got the detector was to be registered. As any simulated gamma-quantum was of random energy the critical slip angle of every simulated event was evaluated by the following formula: αcrit = eh/E √ZNAρ/πAm. Table values of the absorption coefficients were used for random simulation of gamma-quanta absorption in the air. And it was assumed that any gamma-quantum interaction with air resulted in its disappearance. Dependence of different flying distances (120 and 330 m), gap heights (10, 20 and 50 μ) of the gap collimator and inclinations (20 and 40 μrad) of the reflector's plane on detected gamma-quanta energy distribution and vertical angle one was studied with a help of the developed program
Verification of Burned Core Modeling Method for Monte Carlo Simulation of HANARO
The reactor core has been managed well by the HANARO core management system called HANAFMS. The heterogeneity of the irradiation device and core made the neutronic analysis difficult and sometimes doubtable. To overcome the deficiency, MCNP was utilized in neutron transport calculation of the HANARO. For the most part, a MCNP model with the assumption that all fuels are filled with fresh fuel assembly showed acceptable analysis results for a design of experimental devices and facilities. However, it sometimes revealed insufficient results in the design, which requires good accuracy like neutron transmutation doping (NTD), because it didn't consider the flux variation induced by depletion of the fuel. In this study, a depleted-core modeling method previously proposed was applied to build burned core model of HANARO and verified through a comparison of the calculated result from the depleted-core model and that from an experiment. The modeling method to establish a depleted-core model for the Monte Carlo simulation was verified by comparing the neutron flux distribution obtained by the zirconium activation method and the reaction rate of 30Si(n, γ) 31Si obtained by a resistivity measurement method. As a result, the reaction rate of 30Si(n, γ) 31Si also agreed well with about 3% difference. It was therefore concluded that the modeling method and resulting depleted-core model developed in this study can be a very reliable tool for the design of the planned experimental facility and a prediction of its performance in HANARO
Verification of Burned Core Modeling Method for Monte Carlo Simulation of HANARO
Cho, Dongkeun; Kim, Myongseop [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-05-15
The reactor core has been managed well by the HANARO core management system called HANAFMS. The heterogeneity of the irradiation device and core made the neutronic analysis difficult and sometimes doubtable. To overcome the deficiency, MCNP was utilized in neutron transport calculation of the HANARO. For the most part, a MCNP model with the assumption that all fuels are filled with fresh fuel assembly showed acceptable analysis results for a design of experimental devices and facilities. However, it sometimes revealed insufficient results in the design, which requires good accuracy like neutron transmutation doping (NTD), because it didn't consider the flux variation induced by depletion of the fuel. In this study, a depleted-core modeling method previously proposed was applied to build burned core model of HANARO and verified through a comparison of the calculated result from the depleted-core model and that from an experiment. The modeling method to establish a depleted-core model for the Monte Carlo simulation was verified by comparing the neutron flux distribution obtained by the zirconium activation method and the reaction rate of {sup 30}Si(n, γ) {sup 31}Si obtained by a resistivity measurement method. As a result, the reaction rate of {sup 30}Si(n, γ) {sup 31}Si also agreed well with about 3% difference. It was therefore concluded that the modeling method and resulting depleted-core model developed in this study can be a very reliable tool for the design of the planned experimental facility and a prediction of its performance in HANARO.
Stochastic method for accommodation of equilibrating basins in kinetic Monte Carlo simulations
Van Siclen, Clinton DeW.
2008-01-01
A computationally simple way to accommodate 'basins' of trapping sites in standard kinetic Monte Carlo simulations is presented. By assuming the system is effectively equilibrated in the basin, the residence time (time spent in the basin before escape) and the probabilities for transition to states outside the basin may be calculated. This is demonstrated for point defect diffusion over a periodic grid of sites containing a complex basin.
Optimization of Monte Carlo simulations
Bryskhe, Henrik
2009-01-01
This thesis considers several different techniques for optimizing Monte Carlo simulations. The Monte Carlo system used is Penelope but most of the techniques are applicable to other systems. The two mayor techniques are the usage of the graphics card to do geometry calculations, and raytracing. Using graphics card provides a very efficient way to do fast ray and triangle intersections. Raytracing provides an approximation of Monte Carlo simulation but is much faster to perform. A program was ...
A zero-variance (ZV) Monte Carlo transport method is a theoretical construct that, if it could be implemented on a practical computer, would produce the exact result after any number of histories. Unfortunately, ZV methods are impractical; to implement them, one must have complete knowledge of a certain adjoint flux, and acquiring this knowledge is an infinitely greater task than solving the original criticality or source-detector problem. (In fact, the adjoint flux itself yields the desired result, with no need of a Monte Carlo simulation) Nevertheless, ZV methods are of practical interest because it is possible to approximate them in ways that yield efficient variance-reduction schemes. Such implementations must be done carefully. For example, one must not change the mean of the final answer) The goal of variance reduction is to estimate the true mean with greater efficiency. In this paper, we describe new ZV methods for Monte Carlo criticality and source-detector problems. These methods have the same requirements (and disadvantages) as described earlier. However, their implementation is very different. Thus, the concept of approximating them to obtain practical variance-reduction schemes opens new possibilities. In previous ZV methods, (a) a single characteristic parameter (the k-eigenvalue or a detector response) of a forward transport problem is sought; (b) the exact solution of an adjoint problem must be known for all points in phase-space; and (c) a non-analog process, defined in terms of the adjoint solution, transports forward Monte Carlo particles from the source to the detector (in criticality problems, from the fission region, where a generation n fission neutron is born, back to the fission region, where generation n+1 fission neutrons are born). In the non-analog transport process, Monte Carlo particles (a) are born in the source region with weight equal to the desired characteristic parameter, (b) move through the system by an altered transport
A variance-reduced electrothermal Monte Carlo method for semiconductor device simulation
Muscato, Orazio; Di Stefano, Vincenza [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) Leibniz-Institut im Forschungsverbund Berlin e.V., Berlin (Germany)
2012-11-01
This paper is concerned with electron transport and heat generation in semiconductor devices. An improved version of the electrothermal Monte Carlo method is presented. This modification has better approximation properties due to reduced statistical fluctuations. The corresponding transport equations are provided and results of numerical experiments are presented.
Jin, Shengye; Tamura, Masayuki
2013-10-01
Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is
The TH-PPL CT teaching instrument, developed to Tsinghua University, adopts a 137Cs standard radiation source, which is shielded by one lead canister. This paper simulates and analyses the irradiation rate around the lead canister by a method, which combines Monte Carlo and practical measurement. The simulative result validates the correctness of this method. ICRU sphere's sediment energy is simulated, when the ICRU sphere is 50 mm far away from the lead canister. The personal dose will be calculated from the previous step, the results approve that the lead canister's protection is safe and Monte Carlo can be used in radioprotection analysis and optimum design of lead canister to shield radiation source. (authors)
Jimin Liang
2010-01-01
Full Text Available During the past decade, Monte Carlo method has obtained wide applications in optical imaging to simulate photon transport process inside tissues. However, this method has not been effectively extended to the simulation of free-space photon transport at present. In this paper, a uniform framework for noncontact optical imaging is proposed based on Monte Carlo method, which consists of the simulation of photon transport both in tissues and in free space. Specifically, the simplification theory of lens system is utilized to model the camera lens equipped in the optical imaging system, and Monte Carlo method is employed to describe the energy transformation from the tissue surface to the CCD camera. Also, the focusing effect of camera lens is considered to establish the relationship of corresponding points between tissue surface and CCD camera. Furthermore, a parallel version of the framework is realized, making the simulation much more convenient and effective. The feasibility of the uniform framework and the effectiveness of the parallel version are demonstrated with a cylindrical phantom based on real experimental results.
Efendiev, Yalchin R.
2013-08-21
In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate
Response of thermoluminescent dosimeters to photons simulated with the Monte Carlo method
Moralles, M.; Guimarães, C. C.; Okuno, E.
2005-06-01
Personal monitors composed of thermoluminescent dosimeters (TLDs) made of natural fluorite (CaF 2:NaCl) and lithium fluoride (Harshaw TLD-100) were exposed to gamma and X rays of different qualities. The GEANT4 radiation transport Monte Carlo toolkit was employed to calculate the energy depth deposition profile in the TLDs. X-ray spectra of the ISO/4037-1 narrow-spectrum series, with peak voltage (kVp) values in the range 20-300 kV, were obtained by simulating a X-ray Philips MG-450 tube associated with the recommended filters. A realistic photon distribution of a 60Co radiotherapy source was taken from results of Monte Carlo simulations found in the literature. Comparison between simulated and experimental results revealed that the attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account, while this effect is negligible for lithium fluoride. Differences between results obtained by heating the dosimeter from the irradiated side and from the opposite side allowed the determination of the light attenuation coefficient for CaF 2:NaCl (mass proportion 60:40) as 2.2 mm -1.
Monte Carlo simulation for soot dynamics
Zhou Kun
2012-01-01
Full Text Available A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
Monte carlo simulation for soot dynamics
Zhou, Kun
2012-01-01
A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
Simulation of clinical X-ray tube using the Monte Carlo Method - PENELOPE code
Breast cancer is the most common type of cancer among women. The main strategy to increase the long-term survival of patients with this disease is the early detection of the tumor, and mammography is the most appropriate method for this purpose. Despite the reduction of cancer deaths, there is a big concern about the damage caused by the ionizing radiation to the breast tissue. To evaluate these measures it was modeled a mammography equipment, and obtained the depth spectra using the Monte Carlo method - PENELOPE code. The average energies of the spectra in depth and the half value layer of the mammography output spectrum. (author)
GEANT4 is a Monte Carlo particle physics toolkit that simulates elementary particles moving through matter. GEANT4 allows a population of neutrons to be tracked in a multiplying medium as the population and the medium evolve. However, the population must be artificially stabilized so that it neither explodes nor vanishes. We present a stabilization method where the simulation is divided into short time intervals and the population is renormalized at the end of each interval. This method was used with a simple sphere of U235 to calculate the effective neutron multiplication factor (keff) from the continuous evolution of the neutron population. (author)
Monte Carlo simulation of granular fluids
Montanero, J. M.
2003-01-01
An overview of recent work on Monte Carlo simulations of a granular binary mixture is presented. The results are obtained numerically solving the Enskog equation for inelastic hard-spheres by means of an extension of the well-known direct Monte Carlo simulation (DSMC) method. The homogeneous cooling state and the stationary state reached using the Gaussian thermostat are considered. The temperature ratio, the fourth velocity moments and the velocity distribution functions are obtained for bot...
Lillhoek, J E [Swedish Radiation Protection Authority, Stockholm (Sweden); Grindborg, J-E [Swedish Radiation Protection Authority, Stockholm (Sweden); Lindborg, L [Department of Medical Radiation Physics, Karolinska Institutet and Stockholm University (Sweden); Gudowska, I [Department of Medical Radiation Physics, Karolinska Institutet and Stockholm University (Sweden); Carlsson, G Alm [Department of Radiation Physics, Faculty of Health Sciences, Linkoeping University (Sweden); Soederberg, J [Department of Radiation Physics, Faculty of Health Sciences, Linkoeping University (Sweden); Kopec, M [Department of Theoretical and Computational Physics, AGH University of Science and Technology, Krakow (Poland); Medin, J [Department of Radiation Oncology, Copenhagen University Hospital (Denmark)
2007-08-21
Nanodosimetric single-event distributions or their mean values may contribute to a better understanding of how radiation induced biological damages are produced. They may also provide means for radiation quality characterization in therapy beams. Experimental nanodosimetry is however technically challenging and Monte Carlo simulations are valuable as a complementary tool for such investigations. The dose-mean lineal energy was determined in a therapeutic p(65)+Be neutron beam and in a {sup 60}Co {gamma} beam using low-pressure gas detectors and the variance-covariance method. The neutron beam was simulated using the condensed history Monte Carlo codes MCNPX and SHIELD-HIT. The dose-mean lineal energy was calculated using the simulated dose and fluence spectra together with published data from track-structure simulations. A comparison between simulated and measured results revealed some systematic differences and different dependencies on the simulated object size. The results show that both experimental and theoretical approaches are needed for an accurate dosimetry in the nanometer region. In line with previously reported results, the dose-mean lineal energy determined at 10 nm was shown to be related to clinical RBE values in the neutron beam and in a simulated 175 MeV proton beam as well.
Nanodosimetric single-event distributions or their mean values may contribute to a better understanding of how radiation induced biological damages are produced. They may also provide means for radiation quality characterization in therapy beams. Experimental nanodosimetry is however technically challenging and Monte Carlo simulations are valuable as a complementary tool for such investigations. The dose-mean lineal energy was determined in a therapeutic p(65)+Be neutron beam and in a 60Co γ beam using low-pressure gas detectors and the variance-covariance method. The neutron beam was simulated using the condensed history Monte Carlo codes MCNPX and SHIELD-HIT. The dose-mean lineal energy was calculated using the simulated dose and fluence spectra together with published data from track-structure simulations. A comparison between simulated and measured results revealed some systematic differences and different dependencies on the simulated object size. The results show that both experimental and theoretical approaches are needed for an accurate dosimetry in the nanometer region. In line with previously reported results, the dose-mean lineal energy determined at 10 nm was shown to be related to clinical RBE values in the neutron beam and in a simulated 175 MeV proton beam as well
Lillhök, J. E.; Grindborg, J.-E.; Lindborg, L.; Gudowska, I.; Alm Carlsson, G.; Söderberg, J.; Kopeć, M.; Medin, J.
2007-08-01
Nanodosimetric single-event distributions or their mean values may contribute to a better understanding of how radiation induced biological damages are produced. They may also provide means for radiation quality characterization in therapy beams. Experimental nanodosimetry is however technically challenging and Monte Carlo simulations are valuable as a complementary tool for such investigations. The dose-mean lineal energy was determined in a therapeutic p(65)+Be neutron beam and in a 60Co γ beam using low-pressure gas detectors and the variance-covariance method. The neutron beam was simulated using the condensed history Monte Carlo codes MCNPX and SHIELD-HIT. The dose-mean lineal energy was calculated using the simulated dose and fluence spectra together with published data from track-structure simulations. A comparison between simulated and measured results revealed some systematic differences and different dependencies on the simulated object size. The results show that both experimental and theoretical approaches are needed for an accurate dosimetry in the nanometer region. In line with previously reported results, the dose-mean lineal energy determined at 10 nm was shown to be related to clinical RBE values in the neutron beam and in a simulated 175 MeV proton beam as well.
Simulation of Cone Beam CT System Based on Monte Carlo Method
Wang, Yu; Cao, Ruifen; Hu, Liqin; Li, Bingbing
2014-01-01
Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established based on Monte Carlo program and validated against the measurement. The BEAMnrc program was adopted to the KV x-ray tube. Both IOURCE-13 and ISOURCE-24 were chosen to simulate the path of beam particles. The measured Percentage Depth Dose (PDD) and lateral dose profiles under 1cm water were compared with the dose calculated by DOSXYZnrc program. The calculated PDD was better than 1% within the depth of 10cm. More than 85% points of calculated lateral dose profiles was within 2%. The correct CBCT system model helps to improve CBCT image quality for dose verification in ART and assess the CBCT image concomitant dose risk.
Hart, Vern P; Doyle, Timothy E
2013-09-01
A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed. PMID:24085080
This analysis is part of the report on ' Implementation of geometry module of 05R code in another Monte Carlo code', chapter 6.0: establishment of future activity related to geometry in Monte Carlo method. The introduction points out some problems in solving complex three-dimensional models which induce the need for developing more efficient geometry modules in Monte Carlo calculations. Second part include formulation of the problem and geometry module. Two fundamental questions to be solved are defined: (1) for a given point, it is necessary to determine material region or boundary where it belongs, and (2) for a given direction, all cross section points with material regions should be determined. Third part deals with possible connection with Monte Carlo calculations for computer simulation of geometry objects. R-function theory enables creation of geometry module base on the same logic (complex regions are constructed by elementary regions sets operations) as well as construction geometry codes. R-functions can efficiently replace functions of three-value logic in all significant models. They are even more appropriate for application since three-value logic is not typical for digital computers which operate in two-value logic. This shows that there is a need for work in this field. It is shown that there is a possibility to develop interactive code for computer modeling of geometry objects in parallel with development of geometry module
Using neutron source distinguish mustard gas bomb from the others with Monte Carlo simulation method
After Japan was defeated, the chemical weapon that left in China injured people constantly. It made very grave lost to the Chinese because of people's innocent to it. In these accidents, mustard gas bomb is the most. It is more difficult to distinguish mustard gas bomb from other normal bomb in out because it embedded in the earth for long time; leakage, eroding and rust appearance looked very serious. So the untouched measure method, neutron source inducing γ spectrum, showed very important. The Monte Carlo method was used in this paper to compute the γ spectrum when using neutron source irradiate mustard gas bomb. The characteristic radial of Cl, S, Fe and the other elements can picked up clearly. The result play some referenced role in analyzing γ spectrum. (authors)
In subcritical systems driven by an external neutron source, the experimental methods based on pulsed neutron source (PNS) and statistical techniques play an important role for reactivity measurement. Simulation of these methods is very time-consumed procedure. For simulations in Monte-Carlo programs several improvements for neutronic calculations have been made. This paper introduces a new method for simulating PNS and statistical measurements. In this method all events occurred in the detector during simulation are stored in a file using PTRAC feature in the MCNP. After that with a special code (or post-processing) PNS and statistical methods can be simulated. Additionally different shapes of neutron pulses and its lengths as well as dead time of detectors can be included into the simulation. The methods described above have been tested on the sub-critical assembly Yalina-Thermal, located in the Joint Institute for Power and Nuclear Research SOSNY in Minsk (Belarus). A good agreement between experiment and simulation was shown. (authors)
Proton Upset Monte Carlo Simulation
O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.
2009-01-01
The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.
Monte Carlo simulation of the microcanonical ensemble
We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references
A Monte Carlo simulation of photomultiplier resolution
A Monte Carlo simulation of dynode statistics has been used to generate multiphotoelectron distributions to compare with actual photomultiplier resolution results. In place of Poission of Polya statistics, in this novel approach, the basis for the simulation is an experimentally determined single electron response. The relevance of this method to the study of intrinsic line widths of scintillators is discussed
Testing planetary transit detection methods with grid-based Monte-Carlo simulations.
Bonomo, A. S.; Lanza, A. F.
The detection of extrasolar planets by means of the transit method is a rapidly growing field of modern astrophysics. The periodic light dips produced by the passage of a planet in front of its parent star can be used to reveal the presence of the planet itself, to measure its orbital period and relative radius, as well as to perform studies on the outer layers of the planet by analysing the light of the star passing through the planet's atmosphere. We have developed a new method to detect transits of Earth-sized planets in front of solar-like stars that allows us to reduce the impact of stellar microvariability on transit detection. A large Monte Carlo numerical experiment has been designed to test the performance of our approach in comparison with other transit detection methods for stars of different magnitudes and planets of different radius and orbital period, as will be observed by the space experiments CoRoT and Kepler. The large computational load of this experiment has been managed by means of the Grid infrastructure of the COMETA consortium.
Gimelshein, S. F.; Gimelshein, N. E.; Levin, D. A.; Ivanov, M. S.; Wysong, I. J.
2004-07-01
The conventional chemical reaction models of the direct simulation Monte Carlo method developed with the assumption of continuous rotational or vibrational modes that are shown to exhibit systematic errors when used with discrete energy modes. A reaction model is proposed that is consistent with the use of discrete energy distributions of rotational and vibrational modes, and is equally applicable to diatomic and polyatomic systems. The sensitivity of the model to variations of different reaction rate parameters is examined. The revised chemical reaction model is then applied to the modeling of hypersonic flows over spacecraft in the Martian and Earth atmospheres.
Oramas Polo, I.
2014-07-01
This paper presents the simulation of the gamma camera Park Isocam II by Monte Carlo code SIMIND. This simulation allows detailed assessment of the functioning of the gamma camera. The parameters evaluated by means of the simulation are: the intrinsic uniformity with different window amplitudes, the system uniformity, the extrinsic spatial resolution, the maximum rate of counts, the intrinsic sensitivity, the system sensitivity, the energy resolution and the pixel size. The results of the simulation are compared and evaluated against the specifications of the manufacturer of the gamma camera and taking into account the National Protocol for Quality Control of Nuclear Medicine Instruments of the Cuban Medical Equipment Control Center. The simulation reported here demonstrates the validity of the SIMIND Monte Carlo code to evaluate the performance of the gamma camera Park Isocam II and as result a computational model of the camera has been obtained. (Author)
Monte Carlo simulation of granular fluids
Montanero, J M
2003-01-01
An overview of recent work on Monte Carlo simulations of a granular binary mixture is presented. The results are obtained numerically solving the Enskog equation for inelastic hard-spheres by means of an extension of the well-known direct Monte Carlo simulation (DSMC) method. The homogeneous cooling state and the stationary state reached using the Gaussian thermostat are considered. The temperature ratio, the fourth velocity moments and the velocity distribution functions are obtained for both cases. The shear viscosity characterizing the momentum transport in the thermostatted case is calculated as well. The simulation results are compared with analytical predictions showing an excellent agreement.
A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
Liang, Yihao; Li, Yaohang
2016-01-01
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures. It adopts the sequential updating scheme of Metropolis algorithm, and makes no approximation in the computation of energy. It reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We use this method to simulate primitive model electrolytes. We measure very precisely all ion-ion pair correlation functions at high concentrations, and extract renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.
Mondal, Nagendra Nath
2010-01-01
The results of Monte Carlo Simulation (MCS) studies of Most likely position (MLP) and position vector (PV) methods in TOFPET system are presented. MCS based on GEANT3.21 is carried out where the geometry of a real TOFPET system is considered. Results not only manifest resolving powers (RP) of PV and MLP methods ~114% and ~36% but also exhibit shifting of reconstructed images from the original positions ~3% and ~63% respectively. Position conversion factors play a crucial role to reinstate the image position in the PV method and stipulate excellent images. A PV is a position reconstruction method of positron-electron annihilation points developed afresh without iteration and that makes its beauty by saving huge computational time and radiation dose of the patient.
Simulated Annealing using Hybrid Monte Carlo
Salazar, Rafael; Toral, Raúl
1997-01-01
We propose a variant of the simulated annealing method for optimization in the multivariate analysis of differentiable functions. The method uses global actualizations via the hybrid Monte Carlo algorithm in their generalized version for the proposal of new configurations. We show how this choice can improve upon the performance of simulated annealing methods (mainly when the number of variables is large) by allowing a more effective searching scheme and a faster annealing schedule.
Monte Carlo simulation and numerical integration
Geweke, John F.
1995-01-01
This is a survey of simulation methods in economics, with a specific focus on integration problems. It describes acceptance methods, importance sampling procedures, and Markov chain Monte Carlo methods for simulation from univariate and multivariate distributions and their application to the approximation of integrals. The exposition gives emphasis to combinations of different approaches and assessment of the accuracy of numerical approximations to integrals and expectations. The survey illus...
The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs
Improved Direct Simulation Monte Carlo method for solving modern problems of rarefied gases dynamics
Maltsev, Roman V
2012-01-01
First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important improvement is the scheme of temporal factors, allowing the use of different time step for different sorts of particles, thus reducing the complexity and/or resource usage in simulation of stationary problems with very different collisional cross-sections between components of a mixture. Other improvements include the similarity parameter for efficient estimation of the number of simulational particles required for 1D, 2D and 3D computations, the new scheme for solving axisymmetric problems, an approach to detect and reject repetitive collisions. Also, some advice on technical optimization of algorithm for modern computers is offered.
Tubman, Norm; Hammes-Schiffer, Sharon; Ceperley, David
2016-01-01
Simulating nonadiabatic effects with many-body wave function approaches is an open field with many challenges. Recent interest has been driven by new algorithmic developments and improved theoretical understanding of properties unique to electron-ion wave functions. Fixed-node diffusion Monte Caro is one technique that has shown promising results for simulating electron-ion systems. In particular, we focus on the CH molecule for which previous results suggested a relatively significant contribution to the energy from nonadiabatic effects. We propose a new wave function ansatz for diatomic systems which involves interpolating the determinant coefficients calculated from configuration interaction methods. We find this to be an improvement beyond previous wave function forms that have been considered. The calculated nonadiabatic contribution to the energy in the CH molecule is reduced compared to our previous results, but still remains the largest among the molecules under consideration.
We present a moment-based acceleration algorithm applied to Monte Carlo simulation of thermal radiative-transfer problems. Our acceleration algorithm employs a continuum system of moments to accelerate convergence of stiff absorption–emission physics. The combination of energy-conserving tallies and the use of an asymptotic approximation in optically thick regions remedy the difficulties of local energy conservation and mitigation of statistical noise in such regions. We demonstrate the efficiency and accuracy of the developed method. We also compare directly to the standard linearization-based method of Fleck and Cummings [1]. A factor of 40 reduction in total computational time is achieved with the new algorithm for an equivalent (or more accurate) solution as compared with the Fleck–Cummings algorithm
The variance reduction method can be classified to three technical categories that are source, collision, and transport biasing. All of the variance reduction techniques require specific parameters to control the transport probability. One of well-known methods to determine the optimized transport probability is called as the Consistent Adjoint Driven Importance Sampling (CADIS) method. The CADIS method uses adjoint function to reduce the error of the response. This method can give high variance reduction efficiency on the single response in any problem. However, the CADIS method cannot properly reduce individual relative error for the cases, which have more than two responses. In this study, a multi-response CADIS method was derived by considering each position of the responses. Using the multi-response CADIS method, a radiation transport problem was estimated by applying it into the source angular biasing. The results were compared with those of the CADIS approach and the analog MC method. In this study, a multi-response CADIS method was proposed for minimizing relative errors in various tally regions. To reduce all relative errors for various responses, a weight decision equation was derived. For the verification of the proposed method, a shielding problem was set and the MC simulations were pursued. The results with the proposed method were compared with those estimated by CADIS and analog MC methods. The analysis shows that the relative error of each tally region can be successfully and efficiently reduced for overall regions than the other methods. It can be utilized for accurate calculation of various radiation transport problems, as well as to save the calculation time. Therefore, it is expected that the proposed method can contribute the improvement of expandability in Monte Carlo simulation
Modulated pulse bathymetric lidar Monte Carlo simulation
Luo, Tao; Wang, Yabo; Wang, Rong; Du, Peng; Min, Xia
2015-10-01
A typical modulated pulse bathymetric lidar system is investigated by simulation using a modulated pulse lidar simulation system. In the simulation, the return signal is generated by Monte Carlo method with modulated pulse propagation model and processed by mathematical tools like cross-correlation and digital filter. Computer simulation results incorporating the modulation detection scheme reveal a significant suppression of the water backscattering signal and corresponding target contrast enhancement. More simulation experiments are performed with various modulation and reception variables to investigate the effect of them on the bathymetric system performance.
Monte Carlo Methods in Physics
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
Akihiko Takahashi; Nakahiro Yoshida
2005-01-01
We shall propose a new computational scheme with the asymptotic method to achieve variance reduction of Monte Carlo simulation for numerical analysis especially in finance. We not only provide general scheme of our method, but also show its effectiveness through numerical examples such as computing optimal portfolio and pricing an average option. Finally, we show mathematical validity of our method.
Weht, R; Estrin, D A; Chakravarty, C; Weht, Ruben O.; Kohanoff, Jorge; Estrin, Dario A.; Chakravarty, Charusita
1998-01-01
A novel method for simulating the statistical mechanics of molecular systems in which both nuclear and electronic degrees of freedom are treated quantum mechanically is presented. The scheme combines a path integral description of the nuclear variables with a first-principles adiabatic description of the electronic structure. The electronic problem is solved for the ground state within a density functional approach, with the electronic orbitals expanded in a localized (Gaussian) basis set. The discretized path integral is computed by a Metropolis Monte Carlo sampling technique on the normal modes of the isomorphic ring-polymer. An effective short-time action correct to order small Lithium clusters, namely Li$_4$ and Li$_5^+$. Structural and electronic properties computed within this fully quantum-mechanical scheme are presented and compared to those obtained within the classical nuclei approximation. Quantum delocalization effects are significant but tunneling turns out to be irrelevant at low temperatures.
Autocorrelations in hybrid Monte Carlo simulations
Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)
There are many problems related to multi-step Monte Carlo (MC) calculation. Surface Source Reading (SSR) and Surface Source Writing (SSW) options in MCNP, MC depletion calculation, accelerator shielding analysis using secondary particle source term calculation, and residual particle transport calculation caused by activation are the examples of the simulations. In these problems, the average values estimated from the MC result in the previous step are used as sources of MC simulation in the next step. Hence, the uncertainties of the results in previous step are usually not considered for calculating that of next step MC simulation even though they are propagated as the stepwise progression. In this study, a new method using the forward-adjoint calculation and the union tally is proposed for the estimation of real uncertainty. For the activation benchmark problems the responses and real uncertainties were estimated by using the proposed method. And, the results were compared with those estimated by the brute force technique and the adjoint-based approach. The result shows that the proposed approach gives an accurate result comparing with the reference results
Experience with the Monte Carlo Method
Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed
A method to perform multi-scale Monte Carlo simulations in the clinical setting
In order to model the track structure of clinical mega-voltage photon beams in a reasonable time, it is necessary to use a multiscale approach incorporating a track-structure algorithm for the regions of interest and a condensed history algorithm for the rest of the geometry. This paper introduces a multi-scale Monte Carlo system, which is used to hand off particle trajectory information between the two algorithms. Since condensed history algorithms ignore electrons with energy below a fixed threshold and those electrons are important to the track structure on the micrometre scale, it is necessary to hand over all charged particles to the track-structure algorithm only in a volume that extends beyond the scoring volume. Additionally, the system is validated against experimental results for radio-isotope gamma spectra. (authors)
Ródenas, J; Burgos, M C; Zarza, I; Gallardo, S
2005-01-01
Simulation of detector calibration using the Monte Carlo method is very convenient. The computational calibration procedure using the MCNP code was validated by comparing results of the simulation with laboratory measurements. The standard source used for this validation was a disc-shaped filter where fission and activation products were deposited. Some discrepancies between the MCNP results and laboratory measurements were attributed to the point source model adopted. In this paper, the standard source has been simulated using both point and surface source models. Results from both models are compared with each other as well as with experimental measurements. Two variables, namely, the collimator diameter and detector-source distance have been considered in the comparison analysis. The disc model is seen to be a better model as expected. However, the point source model is good for large collimator diameter and also when the distance from detector to source increases, although for smaller sizes of the collimator and lower distances a surface source model is necessary. PMID:16604596
Rodenas, J.; Pascual, A.; Zarza, I.; Serradell, V.; Ortiz, J.; Ballesteros, L.
2001-07-01
One of the most powerful tools used for environmental radioactivity measurements is a gamma spectrometer, which usually includes a hp ge detector. The detector should be calibrated in efficiency for each considered geometry. Simulation of the calibration procedure with a validated computer program becomes an important auxiliary tool for an environmental radioactivity laboratory being that it permits one to optimise calibration procedures and reduce the amount of radioactive wastes produced. The Monte Carlo method is applied to simulate the detection process and obtain spectrum peaks for each modelled geometry. An accurate detector model should be developed in order to obtain a good accuracy in the output of the calibration simulation. an important parameter in the detector model is the thickness of any absorber layer surrounding the Ge crystal, particularly the inactive Ge layer. In this paper, a sensitivity analysis on the inactive Ge layer thickness is performed using MCNP 4B code. Results are compared with experimental measured efficiency. A sensitivity analysis is also performed on the aluminium cap thickness. (Author) 5 refs.
Coded aperture optimization using Monte Carlo simulations
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.
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Aim, Karel; Lísal, Martin
2002. s. 1. [European Conference on Applied Thermodynamics ESAT 2002 /19./. 06.09.2002-10.09.2002, Santorini] Institutional research plan: CEZ:AV0Z4072921 Keywords : Simulation * Phase equilibria Subject RIV: CC - Organic Chemistry
Harries, Tim J
2015-01-01
We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo estimator and enables a complete treatment of the detailed microphysics, including polychromatic radiation and anisotropic scattering, in both the free-streaming and optically-thick limits. Since the new method is computationally demanding we have developed two new methods that speed up the algorithm. The first is a photon packet splitting algorithm that enables efficient treatment of the Monte Carlo process in very optically thick regions. The second is a parallelisation method that distributes the Monte Carlo workload over many instances of the hydrodynamic domain, resulting in excellent scaling of the radiation step. We also describe the implementation of a sink particle method that enables us to follow the accretion onto, and the growth of, the protostars. We detail the resu...
Simulation of neutron transport process, photons and charged particles within the Monte Carlo method
Description is given to the program system BRAND designed for the accurate solution of non-stationary transport equation of neutrons, photons and charged particles in the conditions of real three-dimensional geometry. An extensive set of local and non-local estimates provides an opportunity of calculating a great set of linear functionals normally being of interest in the calculation of reactors, radiation protection and experiment simulation. The process of particle interaction with substance is simulated on the basis of individual non-group data on each isotope of the composition. 24 refs
The Coarse Mesh Finite Difference Method (CMFD) has been widely used to accelerate the convergence of deterministic methods. It was shown that the CMFD acceleration technique is very effective for fission source convergence. It was expected that CMFD is also effective on active cycle by reducing inter-cycle correlation. However it turns out CMFD also has inter-cycle correlation. In order to reduce the inter-cycle correlation, well known technique superhistory method was adopted. In this paper, the tally performance of CMFD with superhistory method was studied with 1D homogeneous problem. The effect of CMFD with superhistory method on the MC was studied. It was shown that the inter-cycle correlation was reduced dramatically with CMFD and superhistory method. The magnitude of RMS real STD increases as the number of generations for superhistory increases. And the magnitude decreases with CMFD
Carsey, Thomas M.; Harden, Jeffrey J.
2015-01-01
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
Quantum Monte Carlo Simulations : Algorithms, Limitations and Applications
Raedt, H. De
1992-01-01
A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown
Restricted Collision List method for faster Direct Simulation Monte-Carlo (DSMC) collisions
Macrossan, Michael N.
2016-08-01
The 'Restricted Collision List' (RCL) method for speeding up the calculation of DSMC Variable Soft Sphere collisions, with Borgnakke-Larsen (BL) energy exchange, is presented. The method cuts down considerably on the number of random collision parameters which must be calculated (deflection and azimuthal angles, and the BL energy exchange factors). A relatively short list of these parameters is generated and the parameters required in any cell are selected from this list. The list is regenerated at intervals approximately equal to the smallest mean collision time in the flow, and the chance of any particle re-using the same collision parameters in two successive collisions is negligible. The results using this method are indistinguishable from those obtained with standard DSMC. The CPU time saving depends on how much of a DSMC calculation is devoted to collisions and how much is devoted to other tasks, such as moving particles and calculating particle interactions with flow boundaries. For 1-dimensional calculations of flow in a tube, the new method saves 20% of the CPU time per collision for VSS scattering with no energy exchange. With RCL applied to rotational energy exchange, the CPU saving can be greater; for small values of the rotational collision number, for which most collisions involve some rotational energy exchange, the CPU may be reduced by 50% or more.
Channon, H A; Hamilton, A J; D'Souza, D N; Dunshea, F R
2016-06-01
Monte Carlo simulation was investigated as a potential methodology to estimate sensory tenderness, flavour and juiciness scores of pork following the implementation of key pathway interventions known to influence eating quality. Correction factors were established using mean data from published studies investigating key production, processing and cooking parameters. Probability distributions of correction factors were developed for single pathway parameters only, due to lack of interaction data. Except for moisture infusion, ageing period, aitchbone hanging and cooking pork to an internal temperature of >74°C, only small shifts in the mean of the probability distributions of correction factors were observed for the majority of pathway parameters investigated in this study. Output distributions of sensory scores, generated from Monte Carlo simulations of input distributions of correction factors and for individual pigs, indicated that this methodology may be useful in estimating both the shift and variability in pork eating traits when different pathway interventions are applied. PMID:26869282
Monte Carlo simulation in the reaction rate's calculation with neutron-activation method
With MCNP/4B code, the influence of cut-off energy, flux tallies, nuclear databases and perturbation on the reaction rate's calculation with neutron-activation method are analysed. When the effective reaction threshold is chosen as the cut-off energy, calculation time is considerably reduced and yet the results are not changed. Comparing calculations with cell tallies (F4) with those performed with detector tallies (F5), the counting efficiency of cell tallies is higher and the results are slightly higher, but still credible. With different nuclear databases, calculated results can be different. The perturbation among the detectors doesn't effect on the calculated results. (authors)
Proton therapy facilities are shielded to limit the amount of secondary radiation to which patients, occupational workers and members of the general public are exposed. The most commonly applied shielding design methods for proton therapy facilities comprise semi-empirical and analytical methods to estimate the neutron dose equivalent. This study compares the results of these methods with a detailed simulation of a proton therapy facility by using the Monte Carlo technique. A comparison of neutron dose equivalent values predicted by the various methods reveals the superior accuracy of the Monte Carlo predictions in locations where the calculations converge. However, the reliability of the overall shielding design increases if simulation results, for which solutions have not converged, e.g. owing to too few particle histories, can be excluded, and deterministic models are being used at these locations. Criteria to accept or reject Monte Carlo calculations in such complex structures are not well understood. An optimum rejection criterion would allow all converging solutions of Monte Carlo simulation to be taken into account, and reject all solutions with uncertainties larger than the design safety margins. In this study, the optimum rejection criterion of 10% was found. The mean ratio was 26, 62% of all receptor locations showed a ratio between 0.9 and 10, and 92% were between 1 and 100. (authors)
Quantitative analysis for food products and natural samples, to determine the activity of each radionuclide, can be made by using a high-purity germanium (HPGe) gamma-ray spectrometer system. The analysis procedure is, in general, based upon the guidelines established by the Nuclear Safety Division of the Ministry of Education, Culture, Sports, Science and Technology in Japan (JP MEXT). In the case of gamma-ray spectrum analysis for large volume samples, re-entrant (marinelli) containers are commonly used. The effect of photon attenuation in a large-volume sample, so-called “self-absorption”, should be corrected for precise determination of the activity. As for marinelli containers, two accurate geometries are shown in the JP MEXT guidelines for 700 milliliter and 2 liter volumes. In the document, the functions to obtain the self-absorption coefficients for these specific shapes are also shown. Therefore, self-absorption corrections have been carried out only for these two containers with practical media. However, to measure radioactivity for samples in containers of volumes other than those described in the guidelines, the self-absorption correction functions must be obtained by measuring at least two standard multinuclide volume sources, which consist of different media or different linear attenuation coefficients. In this work, we developed a method to obtain these functions over a wide range of linear attenuation coefficients for self-absorption in various shapes of marinelli containers using a Monte Carlo simulation. This method was applied to a 1-liter marinelli container, which is widely used for the above quantitative analysis, although its self-absorption correction function has not yet been established. The validity of this method was experimentally checked through an analysis of natural samples with known activity levels. (author)
Harries, Tim J.
2015-01-01
We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo estimator and enables a complete treatment of the detailed microphysics, including polychromatic radiation and anisotropic scattering, in both the free-streaming and optically-thick limits. Since the new method is computationally demanding we have developed two ...
Harries, Tim J.
2015-04-01
We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo estimator and enables a complete treatment of the detailed microphysics, including polychromatic radiation and anisotropic scattering, in both the free-streaming and optically thick limits. Since the new method is computationally demanding we have developed two new methods that speed up the algorithm. The first is a photon packet splitting algorithm that enables efficient treatment of the Monte Carlo process in very optically thick regions. The second is a parallelization method that distributes the Monte Carlo workload over many instances of the hydrodynamic domain, resulting in excellent scaling of the radiation step. We also describe the implementation of a sink particle method that enables us to follow the accretion on to, and the growth of, the protostars. We detail the results of extensive testing and benchmarking of the new algorithms.
We present a single-particle Lennard–Jones (L-J) model for CO2 and N2. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO2 and N2 agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH4, CO2 and N2 are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. Since the single-particle model reduces the particle number and avoids the time-consuming Ewald summation used to evaluate Coulomb interactions, the proposed model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available
Li, Jun
2013-09-01
We present a single-particle Lennard-Jones (L-J) model for CO2 and N2. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO2 and N2 agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH4, CO2 and N2 are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. Since the single-particle model reduces the particle number and avoids the time-consuming Ewald summation used to evaluate Coulomb interactions, the proposed model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available. © 2013 Elsevier Inc.
Silva, H; Cardoso, J; Oliveira, C
2011-03-01
An ionisation chamber that directly measures the quantity personal dose equivalent, H(p)(10), is used as a secondary standard in some metrology laboratories. An ionisation chamber of this type was first developed by Ankerhold. Using the Monte-Carlo simulation, the dose in the sensitive volume as a function of the IC dimensions and the effects of the several components of the ionising chamber have been investigated. Based on these results, a new ionising chamber, lighter than the previous ones, is constructed and experimentally tested. PMID:21208934
Guimaraes, Carla da Costa
2005-07-01
In this work, we have evaluated the possibility of applying the Monte Carlo simulation technique in photon dosimetry of external individual monitoring. The GEANT4 toolkit was employed to simulate experiments with radiation monitors containing TLD-100 and CaF{sub 2}:NaCl thermoluminescent detectors. As a first step, X ray spectra were generated impinging electrons on a tungsten target. Then, the produced photon beam was filtered in a beryllium window and additional filters to obtain the radiation with desired qualities. This procedure, used to simulate radiation fields produced by a X ray tube, was validated by comparing characteristics such as half value layer, which was also experimentally measured, mean photon energy and the spectral resolution of simulated spectra with that of reference spectra established by international standards. In the construction of thermoluminescent dosimeter, two approaches for improvements have. been introduced. The first one was the inclusion of 6% of air in the composition of the CaF{sub 2}:NaCl detector due to the difference between measured and calculated values of its density. Also, comparison between simulated and experimental results showed that the self-attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account. Then, in the second approach, the light attenuation coefficient of CaF{sub 2}:NaCl compound estimated by simulation to be 2,20(25) mm{sup -1} was introduced. Conversion coefficients C{sub p} from air kerma to personal dose equivalent were calculated using a slab water phantom with polymethyl-metacrilate (PMMA) walls, for reference narrow and wide X ray spectrum series [ISO 4037-1], and also for the wide spectra implanted and used in routine at Laboratorio de Dosimetria. Simulations of backscattered radiations by PMMA slab water phantom and slab phantom of ICRU tissue-equivalent material produced very similar results. Therefore, the PMMA slab water phantom that can be easily
Monte-Carlo simulations: FLUKA vs. MCNPX
Oden, M.; Krása, Antonín; Majerle, Mitja; Svoboda, Ondřej; Wagner, Vladimír
Melville : AMER INST PHYSICS, 2007 - (Granja, C.; Leroy, C.; Štekl, I.), s. 219-221 ISBN 978-0-7354-0472-4. ISSN 0094-243X. - (AIP Conference Proceedings. 958). [4th International Summer School on Nuclear Physics Methods and Accelerators in Biology and Medicine . Praha (CZ), 08.07.2007-19.07.2007] R&D Projects: GA MŠk(CZ) LC07050 Institutional research plan: CEZ:AV0Z10480505 Keywords : neutron production * spallation reaction * Monte-Carlo simulation Subject RIV: BG - Nuclear , Atomic and Molecular Physics, Colliders
The Moment Guided Monte Carlo Method
Degond, Pierre; Dimarco, Giacomo; Pareschi, Lorenzo
2009-01-01
In this work we propose a new approach for the numerical simulation of kinetic equations through Monte Carlo schemes. We introduce a new technique which permits to reduce the variance of particle methods through a matching with a set of suitable macroscopic moment equations. In order to guarantee that the moment equations provide the correct solutions, they are coupled to the kinetic equation through a non equilibrium term. The basic idea, on which the method relies, consists in guiding the p...
Moura, Alfredo de; Esteves, António
2013-01-01
This paper describes the simulation of the phenomenon of nucleation of the precipitate Al3Sc in an Aluminum Scandium alloy using the kinetic Monte Carlo (kMC) method and the density-based clustering with noise (DBSCAN) method to filter the simulation data. To conduct this task, kMC and DBSCAN algorithms were implemented in C language. The study covers a range of temperatures, concentrations, and dimensions, going from 573K to 873K, 0.25% to 5%, and 50x50x50 to 100x100x100. The Al3Sc precipita...
Shell model Monte Carlo methods
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
Atomistic Monte Carlo simulation of lipid membranes
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss......Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and...
A two-dimensional fluid-Monte Carlo hybrid model is used to simulate a capacitively-coupled parallel-plate rf discharge. The 2-D model assumes azimuthal symmetry and accounts for a ground shield about the electrodes as well as grounded chamber walls. The hybrid model consists of a Monte Carlo method for generating rates and a fluid model for transporting electrons and ions. In the fluid model, the electrons are transported using the continuity equation; and the electric fields are solved self-consistently using Poisson's equation. The Monte Carlo model transports electrons using the fluid-generated periodic electric field. The ionization rates are then obtained using the electron energy distribution function. An averaging method is used to speed the solution by transporting the ions in a time-averaged electric field with a corrected ambipolar-type diffusion. The simulation switches between the conventional and the averaging fluid model. Typically, the simulation runs from 10's to 100's of averaging fluid cycles before reentering the conventional fluid model for 10's of cycles. Speed increases of a factor of 100 are possible
Monte Carlo simulation in statistical physics an introduction
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
Methods for Monte Carlo procedure in radiation measurement by SPECT (single photon emission computed tomography) and 3-D PET (3-dimensional positron emission tomography) are described together with its application to develop and optimize the scattering correction method in 201Tl-SPECT. In the medical technology, the Monte Carlo simulation makes it possible to quantify the behavior of a photon like scattering and absorption, and which can be performed by the use of EGS4 simulation code consisting from Step A - E. With the method, data collection procedures of the diagnostic equipments for nuclear medicine and application to develop the transmission radiation source for SPECT are described. Precision of the scattering correction method is also evaluated in the SPECT by the Monte Carlo simulation. The simulation is a useful tool for evaluating the behavior of radiation in the human body which can not be actually measured. (K.H.)
This study settles on a contribution to the elaboration of slow protons transport simulation. Atomic inner shell ionization is studied in the Plane Wave Born Approximations and in the Binary Encounter Approximation. BRINKMAN-KRAMER's theory and DMITRIEV's theory are used to study charge exchange phenomena. Protons slowing down is studied with the BRICE's stopping power, with the VAVILOV and SYMON's energy straggling distributions and with the MOLIERE, KEIL and MEYER's angular deflexion distributions. Transport simulation is made with Monte Carlo Method; K electrons motion is also taken into account
Extending canonical Monte Carlo methods
Velazquez, L.; Curilef, S.
2010-02-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C < 0. The resulting framework appears to be a suitable generalization of the methodology associated with the so-called dynamical ensemble, which is applied to the extension of two well-known Monte Carlo methods: the Metropolis importance sampling and the Swendsen-Wang cluster algorithm. These Monte Carlo algorithms are employed to study the anomalous thermodynamic behavior of the Potts models with many spin states q defined on a d-dimensional hypercubic lattice with periodic boundary conditions, which successfully reduce the exponential divergence of the decorrelation time τ with increase of the system size N to a weak power-law divergence \\tau \\propto N^{\\alpha } with α≈0.2 for the particular case of the 2D ten-state Potts model.
Quantum Monte Carlo methods algorithms for lattice models
Gubernatis, James; Werner, Philipp
2016-01-01
Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in ...
The mass attenuation coefficients, μ/ρ, the linear attenuation coefficients, μ and the mean free path, MFP of normal and heavy concretes; ordinary, hematite-serpentine, ilmenite-limonite, basalt-magnetite, ilmenite, steel-scrap and steel-magnetite have been investigated using Geant4 Monte Carlo method at photon energies 1.5, 2, 3, 4, 5 and 6 MeV. The mass attenuation coefficients, the linear attenuation coefficient and the mean free path for the concretes were found dependent upon chemical compositions, density and the photon energy. The linear attenuation coefficient values for the selected concretes increase with the density and decrease with the energy. The mean free path thickness for the all the concretes decrease with increase in iron content and increase with increase the photon energy. The Geant4 Monte Carlo simulation method results have been compared with experimental and theoretical XCOM data, and showed a very good agreement. Our investigation validates the utilization of the Geant4 Monte Carlo simulation method for high energy photon interactions. (author)
Hao Wang; Guo-quan Liu; Xiang-ge Qin
2009-01-01
Three-dimensional normal grain growth was appropriately simulated using a Potts model Monte Carlo algorithm.The quasi-stationary grain size distribution obtained from simulation agreed well with the experimental result of pure iron.The Weibull function with a parameter β=2.77 and the Yu-Liu function with a parameter v =2.71 fit the quasi-stationary grain size distribution well.The grain volume distribution is a function that decreased exponentially with increasing grain volume.The distribution of boundary area of grains has a peak at S/=0.5,where S is the boundary area of a grain and is the mean boundary area of all grains in the system.The lognormal function fits the face number distribution well and the peak of the face number distribution is f=10.The mean radius of f=faced grains is not proportional to the face number,but appears to be related by a curve convex upward.In the 2D cross-section,both the perimeter law and the Aboav-Weaire law are observed to hold.
Monte Carlo and detector simulation in OOP
Object-Oriented Programming techniques are explored with an eye towards applications in High Energy Physics codes. Two prototype examples are given: MCOOP (a particle Monte Carlo generator) and GISMO (a detector simulation/analysis package). The OOP programmer does no explicit or detailed memory management nor other bookkeeping chores; hence, the writing, modification, and extension of the code is considerably simplified. Inheritance can be used to simplify the class definitions as well as the instance variables and action methods of each class; thus the work required to add new classes, parameters, or new methods is minimal. The software industry is moving rapidly to OOP since it has been proven to improve programmer productivity, and promises even more for the future by providing truly reusable software. The High Energy Physics community clearly needs to follow this trend
KIT is developing large-scale customized cryogenic pumps with charcoal-coated panels working at 4.5K for the ITER project. An important aspect in the design is the heat load to the cryogenic supply system. In this paper, the feasibilities of different approaches to thermal heat radiation calculations are discussed by studying a simple geometry. Then, the Monte Carlo Ray Trace (MCRT) method is used to calculate thermal radiation heat loads to the cryopanel circuit, the thermal shield circuit, and the valve head when the cryopump is run in the stand-by, pumping, and regeneration modes. The MCRT calculations were performed with out newly developed Monte Carlo simulation program ProVac3D. (author)
Kovtanyuk, Andrey E.
2012-01-01
Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.
Monte Carlo simulation techniques : The development of a general framework
Nilsson, Emma
2009-01-01
Algorithmica Research AB develops software application for the financial markets. One of their products is Quantlab that is a tool for quantitative analyses. An effective method to value several financial instruments is Monte Carlo simulation. Since it is a common method Algorithmica is interesting in investigating if it is possible to create a Monte Carlo framework. A requirement from Algorithmica is that the framework is general and this is the main problem to solve. It is difficult to gene...
Self-consistent electro-thermal simulations of AlGaN/GaN diodes by means of Monte Carlo method
In this contribution we present the results from the simulation of an AlGaN/GaN heterostructure diode by means of a Monte Carlo tool where thermal effects have been included. Two techniques are investigated: (i) a thermal resistance method (TRM), and (ii) an advanced electro-thermal model (ETM) including the solution of the steady-state heat diffusion equation. Initially, a systematic study at constant temperature is performed in order to calibrate the electronic model. Once this task is performed, the electro-thermal methods are coupled with the Monte Carlo electronic simulations. For the TRM, several values of thermal resistances are employed, and for the ETM method, the dependence on the thermal-conductivity, thickness and die length is analyzed. It is found that the TRM with well-calibrated values of thermal resistances provides a similar behavior to ETM simulations under the hypothesis of constant thermal conductivity. Our results are validated with experimental measurements finding the best agreement when the ETM is used with a temperature-dependent thermal conductivity. (paper)
Whitmore, Alexander Jason
temperature field for the MCRT program; together the equations are solved iteratively. These iterations repeat until convergence is reached for a steady state temperature field. The energy equation was solved using a finite volume method. The window's thermal conductivity is modeled as a function of temperature. This thermal model is used to investigate the effects of different materials, receiver geometries, interior convection coefficients and exterior convection coefficients. To prevent devitrification and the ultimate failure of the window, the window needs to stay below the devitrification temperature of the material. In addition, the temperature gradients within the window need to be kept to a minimum to prevent thermal stresses. A San Diego State University colleague E-Fann Saung uses these temperature maps to insure that the mounting of the window does not produce thermal stresses which can cause cracking in the brittle fused quartz. The simulations in this thesis show that window temperatures are below the devitrification temperature of the window when there are cooling jets on both surfaces of the window. Natural convection on the exterior window surface was explored and it does not provide adequate cooling; therefore forced convection is required. Due to the low thermal conductivity of the window, the edge mounting thermal boundary condition has little effect on the maximum temperature of the window. The simulations also showed that the solar input flux absorbed less than 1% of the incoming radiation while the window absorbed closer to 20% of the infrared radiation emitted by the receiver. The main source of absorbed power in the window is located directly on the interior surface of the window where the infrared radiation is absorbed. The geometry of the receiver has a large impact on the amount of emitted power which reached the interior surface of the window, and using a conical shaped receiver dramatically reduced the receiver's infrared flux on the window. The
Combinatorial nuclear level density by a Monte Carlo method
Cerf, N.
1993-01-01
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 t...
Parallel Monte Carlo simulation of aerosol dynamics
Zhou, K.
2014-01-01
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Jadach, S; Placzek, W; Sapeta, S; Siodmok, A; Skrzypek, M
2016-01-01
We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...
The Moment Guided Monte Carlo Method
Degond, Pierre; Pareschi, Lorenzo
2009-01-01
In this work we propose a new approach for the numerical simulation of kinetic equations through Monte Carlo schemes. We introduce a new technique which permits to reduce the variance of particle methods through a matching with a set of suitable macroscopic moment equations. In order to guarantee that the moment equations provide the correct solutions, they are coupled to the kinetic equation through a non equilibrium term. The basic idea, on which the method relies, consists in guiding the particle positions and velocities through moment equations so that the concurrent solution of the moment and kinetic models furnishes the same macroscopic quantities.
Research of Monte Carlo Simulation in Commercial Bank Risk Management
BeimingXiao
2004-01-01
Simulation method is an important-tool in financial risk management. It can simulate financial variable or economic wriable and deal with non-linear or non-nominal issue. This paper analyzes the usage of "Monte Carlo" approach in commercial bank risk management.
Monte Carlo simulations for plasma physics
Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X. [National Inst. for Fusion Science, Toki, Gifu (Japan)
2000-07-01
Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)
The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool
Grau Carles, A.; Garcia Gomez-Tejedor, G.
2001-07-01
The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs.
Monte Carlo Simulation for Particle Detectors
Pia, Maria Grazia
2012-01-01
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...
Monte Carlo Simulation Of Emission Tomography And Other Medical Imaging Techniques
Harrison, Robert L.
2010-01-01
An introduction to Monte Carlo simulation of emission tomography. This paper reviews the history and principles of Monte Carlo simulation, then applies these principles to emission tomography using the public domain simulation package SimSET (a Simulation System for Emission Tomography) as an example. Finally, the paper discusses how the methods are modified for X-ray computed tomography and radiotherapy simulations.
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls).
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls).xml
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls)
U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...
Fast Lattice Monte Carlo Simulations of Polymers
Wang, Qiang; Zhang, Pengfei
2014-03-01
The recently proposed fast lattice Monte Carlo (FLMC) simulations (with multiple occupancy of lattice sites (MOLS) and Kronecker δ-function interactions) give much faster/better sampling of configuration space than both off-lattice molecular simulations (with pair-potential calculations) and conventional lattice Monte Carlo simulations (with self- and mutual-avoiding walk and nearest-neighbor interactions) of polymers.[1] Quantitative coarse-graining of polymeric systems can also be performed using lattice models with MOLS.[2] Here we use several model systems, including polymer melts, solutions, blends, as well as confined and/or grafted polymers, to demonstrate the great advantages of FLMC simulations in the study of equilibrium properties of polymers.
Adjoint Monte Carlo simulation of fixed-energy secondary radiation
Fixed energy secondary generation for adjoint Monte Carlo methods constitutes certain difficulties because of zero probability of reaching fixed value from continuous distribution. This paper proposes a possible approach to adjoint Monte Carlo simulation with fixed energy secondary radiation which does not contain any simplifying restriction. This approach uses the introduced before generalized particle concept developed for description of mixed-type radiation transport and allows adjoint Monte Carlo simulation of such processes. It treats particle type as additional discrete coordinate and always considers only one particle even for the interactions with many particles outgoing from the collision. The adjoint fixed energy secondary radiation simulation is performed as local energy estimator through the intermediate state with fixed energy. The proposed algorithm is tested on the example of coupled gamma/electron/positron transport with generation of annihilation radiation. Forward and adjoint simulation according to generalized particle concept show statistically similar results. (orig.)
Monte Carlo method in radiation transport problems
In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media
MONTE-CARLO SIMULATION OF ROAD TRANSPORT EMISSION
Adam Torok
2015-09-01
Full Text Available There are microscopic, mezoscopic and macroscopic models in road traffic analysis and forecasting. From microscopic models one can calculate the macroscopic data by aggregation. The following paper describes the disaggregation method of macroscopic state, which could lead to microscopic properties of traffic. In order to ensure the transform between macroscopic and microscopic states Monte-Carlo simulation was used. MS Excel macro environment was built to run Monte-Carlo simulation. With this method the macroscopic data can be disaggregated to macroscopic data and as a byproduct mezoscopic, regional data can be gained. These mezoscopic data can be used further on regional environmental or transport policy assessment.
Monte Carlo Simulations of Star Clusters
Giersz, M
2000-01-01
A revision of Stod\\'o{\\l}kiewicz's Monte Carlo code is used to simulate evolution of large star clusters. The survey on the evolution of multi-mass N-body systems influenced by the tidal field of a parent galaxy and by stellar evolution is discussed. For the first time, the simulation on the "star-by-star" bases of evolution of 1,000,000 body star cluster is presented. \\
Topological zero modes in Monte Carlo simulations
We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)
Monte Carlo simulation code modernization
CERN. Geneva
2015-01-01
The continual development of sophisticated transport simulation algorithms allows increasingly accurate description of the effect of the passage of particles through matter. This modelling capability finds applications in a large spectrum of fields from medicine to astrophysics, and of course HEP. These new capabilities however come at the cost of a greater computational intensity of the new models, which has the effect of increasing the demands of computing resources. This is particularly true for HEP, where the demand for more simulation are driven by the need of both more accuracy and more precision, i.e. better models and more events. Usually HEP has relied on the "Moore's law" evolution, but since almost ten years the increase in clock speed has withered and computing capacity comes in the form of hardware architectures of many-core or accelerated processors. To harness these opportunities we need to adapt our code to concurrent programming models taking advantages of both SIMD and SIMT architectures. Th...
Monte Carlo Simulation in Statistical Physics An Introduction
Binder, Kurt
2010-01-01
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...
Recent developments in neutron generator technology suggest that compact instruments with high neutron yield can be used for NAA and PGNAA in combination with high count rate spectrometers. For laboratories far away from Research Reactors (RRs), such devices could serve as an alternative for training students in radioanalytical and nuclear Chemistry and certain specialized applications. As Neutron activation analysis is a well established technique with a long history of documented applications it could be made available to countries where no research reactors or other neutron irradiation facilities exist by using the proposed approach. Prompt gamma neutron activation analysis (PGNAA) is a versatile analytical tool with many applications unique to the technique. As PGNAA is generally performed at RRs external neutron guides with relatively low N flux, the proposed instrument has a potential to supplement existing PGNAA facilities far away from RRs. Neutron generators, particularly the DD-NGs, are a cost effective, easy to operate and particularly safe alternative to other neutron sources, e.g. isotopic neutron sources like Cf-252 or Am/Be. The idea to combine new developments in DD-NG with moderator/shielding and detectors for fast gamma counting emerged from a recent IAEA Coordinated Research Project (CRP) on New Developments in PGNAA, and an IAEA technical meeting on Neutron Generators for Activation Analysis Purposesis currently under preparation. We report on the design and optimization of a Neutron Activation Analysis (NAA) and a Prompt Gamma Neutron Activation Analysis (PGNAA) chamber associated with a D-D neutron generator. The nominal yield of the generator is about 1010 fast neutrons per seconds (E=2.5MeV). MCNP-Monte Carlo N-Particle Transport simulation code and analytical equation, are used to optimize the setup with respect to thermal flux and radiation protection. Many moderators such as Graphite (G), Polyethylene (Poly), Heavy water (HW), Light water
Sun, Shuyu
2013-06-01
This paper introduces an efficient technique to generate new molecular simulation Markov chains for different temperature and density conditions, which allow for rapid extrapolation of canonical ensemble averages at a range of temperatures and densities different from the original conditions where a single simulation is conducted. Obtained information from the original simulation are reweighted and even reconstructed in order to extrapolate our knowledge to the new conditions. Our technique allows not only the extrapolation to a new temperature or density, but also the double extrapolation to both new temperature and density. The method was implemented for Lennard-Jones fluid with structureless particles in single-gas phase region. Extrapolation behaviors as functions of extrapolation ranges were studied. Limits of extrapolation ranges showed a remarkable capability especially along isochors where only reweighting is required. Various factors that could affect the limits of extrapolation ranges were investigated and compared. In particular, these limits were shown to be sensitive to the number of particles used and starting point where the simulation was originally conducted.
Lísal, Martin; Smith, W. R.
National Technical University of Athens, 2002, s. 161-162. [European Seminar on Applied Thermodynamics ESAT 2002 /19./. Santorini (GR), 06.09.2002-10.09.2002] Institutional research plan: CEZ:AV0Z4072921 Keywords : Monte Carlo * readting systems Subject RIV: CF - Physical ; Theoretical Chemistry
Computing Functionals of Multidimensional Diffusions via Monte Carlo Methods
Jan Baldeaux; Eckhard Platen
2012-01-01
We discuss suitable classes of diffusion processes, for which functionals relevant to finance can be computed via Monte Carlo methods. In particular, we construct exact simulation schemes for processes from this class. However, should the finance problem under consideration require e.g. continuous monitoring of the processes, the simulation algorithm can easily be embedded in a multilevel Monte Carlo scheme. We choose to introduce the finance problems under the benchmark approach, and find th...
Two Approaches to Accelerated Monte Carlo Simulation of Coulomb Collisions
Ricketson, Lee
2014-01-01
In plasma physics, the direct simulation of inter-particle Coulomb collisions is often necessary to capture the relevant physics, but presents a computational bottleneck because of the complexity of the process. In this thesis, we derive, test and discuss two methods for accelerating the simulation of collisions in plasmas in certain scenarios. The first is a hybrid fluid-Monte Carlo scheme that reduces the number of collisions that must be simulated. Coupling between the fluid and particl...
Jensen, Jørgen Juncher
2015-01-01
For non-linear systems the estimation of fatigue damage under stochastic loadings can be rather time-consuming. Usually Monte Carlo simulation (MCS) is applied, but the coefficient-of-variation (COV) can be large if only a small set of simulations can be done due to otherwise excessive CPU time. ...
Monte Carlo simulation of photon migration path in turbid media
无
2008-01-01
A new method of Monte Carlo simulation is developed to simulate the photon migration path in a scattering medium after an ultrashort-pulse laser beam comes into the medium.The most probable trajectory of photons at an instant can be obtained with this method.How the photon migration paths are affected by the optical parameters of the scattering medium is analyzed.It is also concluded that the absorption coefficient has no effect on the most probable trajectory of photons.
Mahsa Noori Asl
2013-01-01
Full Text Available Compton-scattered photons included within the photopeak pulse-height window result in the degradation of SPECT images both qualitatively and quantitatively. The purpose of this study is to evaluate and compare six scatter correction methods based on setting the energy windows in 99m Tc spectrum. SIMIND Monte Carlo simulation is used to generate the projection images from a cold-sphere hot-background phantom. For evaluation of different scatter correction methods, three assessment criteria including image contrast, signal-to-noise ratio (SNR and relative noise of the background (RNB are considered. Except for the dual-photopeak window (DPW method, the image contrast of the five cold spheres is improved in the range of 2.7-26%. Among methods considered, two methods show a nonuniform correction performance. The RNB for all of the scatter correction methods is ranged from minimum 0.03 for DPW method to maximum 0.0727 for the three energy window (TEW method using trapezoidal approximation. The TEW method using triangular approximation because of ease of implementation, good improvement of the image contrast and the SNR for the five cold spheres, and the low noise level is proposed as most appropriate correction method.
In conventional PET systems,the parallax error degrades image resolution and causes image distortion. To remedy this, a PET ring diameter has to be much larger than the required size of field of view (FOV), and therefore the cost goes up. Measurement of depth-of-interaction (DOI) information is effective to reduce the parallax error and improve the image quality. This study is aimed at developing a practical method to incorporate DOI information in PET sonogram generation and image reconstruction processes and evaluate its efficacy through Monte Carlo simulation. An animal PET system with 30-mm long LSO crystals and 2-mm DOI measurement accuracy was simulated and list-mode PET data were collected. A sonogram generation method was proposed to bin each coincidence event to the correct LOR location according to both incident crystal indices and DOI positions of the two annihilation photons. The sonograms were reconstructed with an iterative OSMAPEM (ordered subset maximum a posteriori expectation maximization) algorithm. Two phantoms (a rod source phantom and a Derenzo phantom) were simulated, and the benefits of DOI were investigated in terms of reconstructed source diameter (FWHM) and source positioning accuracy. The results demonstrate that the proposed method works well to incorporate DOI information in data processing, which not only overcomes the image distortion problem but also significantly improves image resolution and resolution uniformity and results in satisfactory image quality. (authors)
Monte Carlo Simulation Optimizing Design of Grid Ionization Chamber
ZHENG; Yu-lai; WANG; Qiang; YANG; Lu
2013-01-01
The grid ionization chamber detector is often used for measuring charged particles.Based on Monte Carlo simulation method,the energy loss distribution and electron ion pairs of alpha particle with different energy have been calculated to determine suitable filling gas in the ionization chamber filled with
Simulating Strongly Correlated Electron Systems with Hybrid Monte Carlo
LIU Chuan
2000-01-01
Using the path integral representation, the Hubbard and the periodic Anderson model on D-dimensional cubic lattice are transformed into field theories of fermions in D + 1 dimensions. These theories at half-filling possess a positive definite real symmetry fermion matrix and can be simulated using the hybrid Monte Carlo method.
Replica Exchange for Reactive Monte Carlo Simulations
Turner, C.H.; Brennan, J.K.; Lísal, Martin
2007-01-01
Roč. 111, č. 43 (2007), s. 15706-15715. ISSN 1932-7447 R&D Projects: GA ČR GA203/05/0725; GA AV ČR 1ET400720409; GA AV ČR 1ET400720507 Institutional research plan: CEZ:AV0Z40720504 Keywords : monte carlo * simulation * reactive system Subject RIV: CF - Physical ; Theoretical Chemistry
Archimedes, the Free Monte Carlo simulator
Sellier, Jean Michel D.
2012-01-01
Archimedes is the GNU package for Monte Carlo simulations of electron transport in semiconductor devices. The first release appeared in 2004 and since then it has been improved with many new features like quantum corrections, magnetic fields, new materials, GUI, etc. This document represents the first attempt to have a complete manual. Many of the Physics models implemented are described and a detailed description is presented to make the user able to write his/her own input deck. Please, fee...
Monte Carlo Simulation of Critical Casimir Forces
Vasilyev, Oleg A.
2015-03-01
In the vicinity of the second order phase transition point long-range critical fluctuations of the order parameter appear. The second order phase transition in a critical binary mixture in the vicinity of the demixing point belongs to the universality class of the Ising model. The superfluid transition in liquid He belongs to the universality class of the XY model. The confinement of long-range fluctuations causes critical Casimir forces acting on confining surfaces or particles immersed in the critical substance. Last decade critical Casimir forces in binary mixtures and liquid helium were studied experimentally. The critical Casimir force in a film of a given thickness scales as a universal scaling function of the ratio of the film thickness to the bulk correlation length divided over the cube of the film thickness. Using Monte Carlo simulations we can compute critical Casimir forces and their scaling functions for lattice Ising and XY models which correspond to experimental results for the binary mixture and liquid helium, respectively. This chapter provides the description of numerical methods for computation of critical Casimir interactions for lattice models for plane-plane, plane-particle, and particle-particle geometries.
This study presents the validity and ability of an aggregate mean free path cluster–cluster aggregation (AMP-CCA) model, which is a direct Monte Carlo simulation, to predict the aggregate morphology with diameters form about 15–200 nm by comparing the particle size distributions (PSDs) with the results of the previous stochastic approach. The PSDs calculated by the AMP-CCA model with the calculated aggregate as a coalesced spherical particle are in reasonable agreement with the results of the previous stochastic model regardless of the initial number concentration of particles. The shape analysis using two methods, perimeter fractal dimension and the shape categories, has demonstrated that the aggregate structures become complex with increasing the initial number concentration of particles. The AMP-CCA model provides a useful tool to calculate the aggregate morphology and PSD with reasonable accuracy
无
2008-01-01
A matrix stripping method for the conversion of in-situ gamma ray spectrum, obtained with portable Ge detector, to photon flux energy distribution is proposed. The detector response is fully described by its stripping matrix and full absorption efficiency curve. A charge collection efficiency function is introduced in the simulation to take into account the existence of a transition zone of increasing charge collection after the inactive Ge layer. Good agreement is obtained between simulated and experimental full absorption efficiencies. The characteristic stripping matrix is determined by Monte Carlo simulation for different incident photon energies using the Geant4 toolkit system. The photon flux energy distribution is deduced by stripping the measured spectrum of the partial absorption and cosmic ray events and then applying the full absorption efficiency curve. The stripping method is applied to a measured in-situ spectrum. The value of the absorbed dose rate in air deduced from the corresponding flux energy distribution agrees well with the value measured directly in-situ.
Ortiz Lora, A.; Miras del Rio, H.; Terron Leon, J. A.
2013-07-01
Following the recommendations of the IAEA, and as a further check, they have been Monte Carlo simulation of each one of the plates that are arranged at the Hospital. The objective of the work is the verification of the certificates of calibration and intends to establish criteria of action for its acceptance. (Author)
Kinetic Monte Carlo simulation of dislocation dynamics
A kinetic Monte Carlo simulation of dislocation motion is introduced. The dislocations are assumed to be composed of pure edge and screw segments confined to a fixed lattice. The stress and temperature dependence of the dislocation velocity is studied, and finite-size effects are discussed. It is argued that surfaces and boundaries may play a significant role in the velocity of dislocations. The simulated dislocations are shown to display kinetic roughening according to the exponents predicted by the Kardar-Parisi-Zhang equation. copyright 1999 The American Physical Society
Monte Carlo Simulation of Quantum Computation
Cerf, N. J.; Koonin, S. E.
1997-01-01
The many-body dynamics of a quantum computer can be reduced to the time evolution of non-interacting quantum bits in auxiliary fields by use of the Hubbard-Stratonovich representation of two-bit quantum gates in terms of one-bit gates. This makes it possible to perform the stochastic simulation of a quantum algorithm, based on the Monte Carlo evaluation of an integral of dimension polynomial in the number of quantum bits. As an example, the simulation of the quantum circuit for the Fast Fouri...
Monte Carlo methods for the self-avoiding walk
Janse van Rensburg, E J [Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3 (Canada)], E-mail: rensburg@yorku.ca
2009-08-14
The numerical simulation of self-avoiding walks remains a significant component in the study of random objects in lattices. In this review, I give a comprehensive overview of the current state of Monte Carlo simulations of models of self-avoiding walks. The self-avoiding walk model is revisited, and the motivations for Monte Carlo simulations of this model are discussed. Efficient sampling of self-avoiding walks remains an elusive objective, but significant progress has been made over the last three decades. The model still poses challenging numerical questions however, and I review specific Monte Carlo methods for improved sampling including general Monte Carlo techniques such as Metropolis sampling, umbrella sampling and multiple Markov Chain sampling. In addition, specific static and dynamic algorithms for walks are presented, and I give an overview of recent innovations in this field, including algorithms such as flatPERM, flatGARM and flatGAS. (topical review)
Monte Carlo methods for the self-avoiding walk
The numerical simulation of self-avoiding walks remains a significant component in the study of random objects in lattices. In this review, I give a comprehensive overview of the current state of Monte Carlo simulations of models of self-avoiding walks. The self-avoiding walk model is revisited, and the motivations for Monte Carlo simulations of this model are discussed. Efficient sampling of self-avoiding walks remains an elusive objective, but significant progress has been made over the last three decades. The model still poses challenging numerical questions however, and I review specific Monte Carlo methods for improved sampling including general Monte Carlo techniques such as Metropolis sampling, umbrella sampling and multiple Markov Chain sampling. In addition, specific static and dynamic algorithms for walks are presented, and I give an overview of recent innovations in this field, including algorithms such as flatPERM, flatGARM and flatGAS. (topical review)
Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro
2001-01-01
This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.
Multipurpose Monte Carlo simulator for photon transport in turbid media
Guerra, Pedro; Aguirre, Juan; Ortuño, Juan E.; María J Ledesma-Carbayo; Vaquero, Juan José; Desco, Manuel; Santos, Andrés
2009-01-01
Monte Carlo methods provide a flexible and rigorous solution to the problem of light transport in turbid media, which enable approaching complex geometries for a closed analytical solution is not feasible. The simulator implements local rules of propagation in the form of probability density functions that depend on the local optical properties of the tissue. This work presents a flexible simulator that can be applied in multiple applications related to optical tomography. In particular...
Monte Carlo methods for particle transport
Haghighat, Alireza
2015-01-01
The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...
Use of Monte Carlo Methods in brachytherapy
The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)
The impact of Monte Carlo simulation. A scientometric analysis of scholarly literature
A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications. (author)
To, Gary; Mahfouz, Mohamed R
2013-11-01
In recent years, wireless positioning and tracking devices based on semiconductor micro electro-mechanical system (MEMS) sensors have successfully integrated into the consumer electronics market. Information from the sensors is processed by an attitude estimation program. Many of these algorithms were developed primarily for aeronautical applications. The parameters affecting the accuracy and stability of the system vary with the intended application. The performance of these algorithms occasionally destabilize during human motion tracking activities, which does not satisfy the reliability and high accuracy demand in biomedical application. A previous study accessed the feasibility of using semiconductor based inertial measurement units (IMUs) for human motion tracking. IMU hardware has been redesigned and an attitude estimation algorithm using sequential Monte Carlo (SMC) methods, or particle filter, for quaternions was developed. The method presented in this paper uses von Mises-Fisher and a nonuniform simulation to provide density estimation of the rotation group SO(3). Synthetic signal simulation, robotics applications, and human applications have been investigated. PMID:23674420
Roé-Vellvé, N.; Pino, F.; Falcon, C.; Cot, A.; Gispert, J. D.; Marin, C.; Pavía, J.; Ros, D.
2014-08-01
SPECT studies with 123I-ioflupane facilitate the diagnosis of Parkinson’s disease (PD). The effect on quantification of image degradations has been extensively evaluated in human studies but their impact on studies of experimental PD models is still unclear. The aim of this work was to assess the effect of compensating for the degrading phenomena on the quantification of small animal SPECT studies using 123I-ioflupane. This assessment enabled us to evaluate the feasibility of quantitatively detecting small pathological changes using different reconstruction methods and levels of compensation for the image degrading phenomena. Monte Carlo simulated studies of a rat phantom were reconstructed and quantified. Compensations for point spread function (PSF), scattering, attenuation and partial volume effect were progressively included in the quantification protocol. A linear relationship was found between calculated and simulated specific uptake ratio (SUR) in all cases. In order to significantly distinguish disease stages, noise-reduction during the reconstruction process was the most relevant factor, followed by PSF compensation. The smallest detectable SUR interval was determined by biological variability rather than by image degradations or coregistration errors. The quantification methods that gave the best results allowed us to distinguish PD stages with SUR values that are as close as 0.5 using groups of six rats to represent each stage.
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational
Accelerated GPU based SPECT Monte Carlo simulations
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Meaningful timescales from Monte Carlo simulations of molecular systems
Costa, Liborio I
2016-01-01
A new Markov Chain Monte Carlo method for simulating the dynamics of molecular systems with atomistic detail is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.
Monte Carlo simulation with the Gate software using grid computing
Monte Carlo simulations are widely used in emission tomography, for protocol optimization, design of processing or data analysis methods, tomographic reconstruction, or tomograph design optimization. Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the 'Multiple Replications In Parallel' approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-science), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses. (authors)
Monte Carlo Simulation of an American Option
Gikiri Thuo
2007-04-01
Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.
Monte Carlo simulation of block copolymer brushes
We studied a simplified model of a polymer brush formed by linear chains, which were restricted to a simple cubic lattice. The chain macromolecules consisted of a sequence of two kinds of segment, arranged in a specific sequence. The chains were grafted to an impenetrable surface, i.e. they were terminally attached to the surface at one end. The number of chains was varied from low to high grafting density. The model system was studied under different solvent quality, from good to poor solvent. The properties of this model system were studied by means of Monte Carlo simulations. The sampling algorithm was based on local changes of the chain's conformations
Monte Carlo simulation for Kaonic deuterium studies
Full text: The SIDDHARTA experiment at the DAFNE collider measured the shift and with of the ground level in kaonic hydrogen caused by the strong interaction between the kaons and protons. The measurement of the X-ray transitions to the 1s level in kaonic deuterium will allow, together with the available results from kaonic hydrogen, to extract the isospin- dependent antikaon-nucleon scattering lengths. I will present the Monte Carlo simulation of the SIDDHARTA-2 setup, in the framework of GEANT4. The program is used to optimize the critical parameters of the setup in order to perform the kaonic deuterium measurement. (author)
Monte Carlo simulations for heavy ion dosimetry
Geithner, Oksana
2006-01-01
Water-to-air stopping power ratio ( ) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variabl...
Archimedes, the Free Monte Carlo simulator
Sellier, Jean Michel D
2012-01-01
Archimedes is the GNU package for Monte Carlo simulations of electron transport in semiconductor devices. The first release appeared in 2004 and since then it has been improved with many new features like quantum corrections, magnetic fields, new materials, GUI, etc. This document represents the first attempt to have a complete manual. Many of the Physics models implemented are described and a detailed description is presented to make the user able to write his/her own input deck. Please, feel free to contact the author if you want to contribute to the project.
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
Cemgil, A T; 10.1613/jair.1121
2011-01-01
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...
Calculating Variable Annuity Liability 'Greeks' Using Monte Carlo Simulation
Cathcart, Mark J.; Steven Morrison; McNeil, Alexander J.
2011-01-01
Hedging methods to mitigate the exposure of variable annuity products to market risks require the calculation of market risk sensitivities (or "Greeks"). The complex, path-dependent nature of these products means these sensitivities typically must be estimated by Monte Carlo simulation. Standard market practice is to measure such sensitivities using a "bump and revalue" method. As well as requiring multiple valuations, such approaches can be unreliable for higher order Greeks, e.g., gamma. In...
Smith, W.; Lísal, Martin
2002-01-01
Roč. 66, č. 1 (2002), s. 011104-1 - 011104-1. ISSN 1063-651X R&D Projects: GA ČR GA203/02/0805 Grant ostatní: NSERC(CA) OGP1041 Keywords : MC * simulation * reaction Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.397, year: 2002
A hybrid Monte Carlo and response matrix Monte Carlo method in criticality calculation
Full core calculations are very useful and important in reactor physics analysis, especially in computing the full core power distributions, optimizing the refueling strategies and analyzing the depletion of fuels. To reduce the computing time and accelerate the convergence, a method named Response Matrix Monte Carlo (RMMC) method based on analog Monte Carlo simulation was used to calculate the fixed source neutron transport problems in repeated structures. To make more accurate calculations, we put forward the RMMC method based on non-analog Monte Carlo simulation and investigate the way to use RMMC method in criticality calculations. Then a new hybrid RMMC and MC (RMMC+MC) method is put forward to solve the criticality problems with combined repeated and flexible geometries. This new RMMC+MC method, having the advantages of both MC method and RMMC method, can not only increase the efficiency of calculations, also simulate more complex geometries rather than repeated structures. Several 1-D numerical problems are constructed to test the new RMMC and RMMC+MC method. The results show that RMMC method and RMMC+MC method can efficiently reduce the computing time and variations in the calculations. Finally, the future research directions are mentioned and discussed at the end of this paper to make RMMC method and RMMC+MC method more powerful. (authors)
Rodenas, J. E-mail: jrodenas@iqn.upv.es; Pascual, A.; Zarza, I.; Serradell, V.; Ortiz, J.; Ballesteros, L
2003-01-11
Germanium crystals have a dead layer that causes a decrease in efficiency, since the layer is not useful for detection, but strongly attenuates photons. The thickness of this inactive layer is not well known due to the existence of a transition zone where photons are increasingly absorbed. Therefore, using data provided by manufacturers in the detector simulation model, some strong discrepancies appear between calculated and measured efficiencies. The Monte Carlo method is applied to simulate the calibration of a HP Ge detector in order to determine the total inactive germanium layer thickness and the active volume that are needed in order to obtain the minimum discrepancy between estimated and experimental efficiency. Calculations and measurements were performed for all of the radionuclides included in a standard calibration gamma cocktail solution. A Marinelli beaker was considered for this analysis, as it is one of the most commonly used sample container for environmental radioactivity measurements. Results indicated that a good agreement between calculated and measured efficiencies is obtained using a value for the inactive germanium layer thickness equal to approximately twice the value provided by the detector manufacturer. For all energy peaks included in the calibration, the best agreement with experimental efficiency was found using a combination of a small thickness of the inactive germanium layer and a small detection active volume.
Ródenas, J.; Pascual, A.; Zarza, I.; Serradell, V.; Ortiz, J.; Ballesteros, L.
2003-01-01
Germanium crystals have a dead layer that causes a decrease in efficiency, since the layer is not useful for detection, but strongly attenuates photons. The thickness of this inactive layer is not well known due to the existence of a transition zone where photons are increasingly absorbed. Therefore, using data provided by manufacturers in the detector simulation model, some strong discrepancies appear between calculated and measured efficiencies. The Monte Carlo method is applied to simulate the calibration of a HP Ge detector in order to determine the total inactive germanium layer thickness and the active volume that are needed in order to obtain the minimum discrepancy between estimated and experimental efficiency. Calculations and measurements were performed for all of the radionuclides included in a standard calibration gamma cocktail solution. A Marinelli beaker was considered for this analysis, as it is one of the most commonly used sample container for environmental radioactivity measurements. Results indicated that a good agreement between calculated and measured efficiencies is obtained using a value for the inactive germanium layer thickness equal to approximately twice the value provided by the detector manufacturer. For all energy peaks included in the calibration, the best agreement with experimental efficiency was found using a combination of a small thickness of the inactive germanium layer and a small detection active volume.
Accelerated Monte Carlo Methods for Coulomb Collisions
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
Kuklin, A I; Bogdzel, A A; Gordeliy, V I; Islamov, A H; Konovalov, V Yu; Rogov, A D; Florek, M
2002-01-01
The method and results of the measurements of absolute spectra and fluxes of thermal neutrons at small angle spectrometer YuMO at the fourth channel of the IBR-2 reactor with a comblike water moderator are presented. The experiments were carried out at different parameters of the YuMO instrument, which changes in collimation, exposition and time window width as well as with placement of cadmium screen. The spectra and fluxes were simulated by the Monte-Carlo method for different collimator sizes. Besides, neutron spectra and absolute fluxes at the neutron channel were calculated. The spectra of the scattered neutrons, which form neutron and gamma background at the spectrometer, were given. For the first time the radiation doses in the sample place were determined. The experimental data obtained in this work can be used for experiment planning, for the calculations of scattering cross-section and background, and also for optimization and modernization of the YuMO instrument. The used methods have commom charac...
Lísal, Martin; Smith, W. R.; Nezbeda, Ivo
2001-01-01
Roč. 181, 1-2 (2001), s. 127-146. ISSN 0378-3812 R&D Projects: GA ČR GA203/98/1446; GA AV ČR IAA4072712 Grant ostatní: NSERC(Ca) OGP1041 Institutional research plan: CEZ:AV0Z4072921 Keywords : computer simulations * mixtures * water Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.217, year: 2001
Probabilistic fire simulator - Monte Carlo simulation tool for fire scenarios
Risk analysis tool is developed for computing of the distributions of fire model output variables. The tool, called Probabilistic Fire Simulator, combines Monte Carlo simulation and CFAST two-zone fire model. In this work, it is used to calculate failure probability of redundant cables and fire detector activation times in a cable tunnel fire. Sensitivity of the output variables to the input variables is calculated in terms of the rank order correlations. (orig.)
Monte Carlo simulations on a 9-node PC cluster
Monte Carlo simulation methods are frequently used in the fields of medical physics, dosimetry and metrology of ionising radiation. Nevertheless, the main drawback of this technique is to be computationally slow, because the statistical uncertainty of the result improves only as the square root of the computational time. We present a method, which allows to reduce by a factor 10 to 20 the used effective running time. In practice, the aim was to reduce the calculation time in the LNHB metrological applications from several weeks to a few days. This approach includes the use of a PC-cluster, under Linux operating system and PVM parallel library (version 3.4). The Monte Carlo codes EGS4, MCNP and PENELOPE have been implemented on this platform and for the two last ones adapted for running under the PVM environment. The maximum observed speedup is ranging from a factor 13 to 18 according to the codes and the problems to be simulated. (orig.)
Image reconstruction using Monte Carlo simulation and artificial neural networks
PET data sets are subject to two types of distortions during acquisition: the imperfect response of the scanner and attenuation and scattering in the active distribution. In addition, the reconstruction of voxel images from the line projections composing a data set can introduce artifacts. Monte Carlo simulation provides a means for modeling the distortions and artificial neural networks a method for correcting for them as well as minimizing artifacts. (author) figs., tab., refs
Different models have been developed considering some features of the attenuating geometry. An ideal bare Marinelli model has been compared with the actual plastic model. Concerning the detector, a bare detector model has been improved including an Aluminium absorber layer and a dead layer of inactive Germanium. Calculation results of the Monte Carlo simulation have been compared with experimental measurements carried out in laboratory for various radionuclides from a calibration gamma cocktail solution with energies ranging in a wide interval. (orig.)
Monte Carlo simulation of transition radiation and δ electrons
This paper employs Monte Carlo simulations of the performance of a transition radiation detector (TRD). The program has been written for the TRD in the ZEUS spectrometer, which separates electrons from hadrons in the momentum range between 1 GeV/c and 30 GeV/c. Both, total charge method and cluster counting method were simulated taking into account various experimental parameters. In particular, it was found that the cluster counting method relies on a quantitative understanding of the background originating from the production of δ-electrons by charged particles. The results of the Monte Carlo calculations are in agreement with experimental data obtained with prototypes within a systematic uncertainty of 20%. We applied our Monte Carlo program to studies in order to find an optimum layout for the TRD within available space in the ZEUS spectrometer. In this context, the performance of TRD layouts with different geometries and materials has been evaluated comprehensively. The geometry found by optimization promises an improvement on hadron suppression by a factor of about two for both methods compared with present results from test measurements. Applying algorithms for a detailed analysis of the energy and space distributions of the clusters in the TRD, hadrons in the momentum range from 1 to 30 GeV/c can be suppressed to a level of less than 2%. This method of cluster analysing improves the suppression of hadrons by a factor of about two compared to the total charge method. (orig.)
Computing Functionals of Multidimensional Diffusions via Monte Carlo Methods
Baldeaux, Jan
2012-01-01
We discuss suitable classes of diffusion processes, for which functionals relevant to finance can be computed via Monte Carlo methods. In particular, we construct exact simulation schemes for processes from this class. However, should the finance problem under consideration require e.g. continuous monitoring of the processes, the simulation algorithm can easily be embedded in a multilevel Monte Carlo scheme. We choose to introduce the finance problems under the benchmark approach, and find that this approach allows us to exploit conveniently the analytical tractability of these diffusion processes.
Monte Carlo simulations of neoclassical transport in toroidal plasmas
FORTEC-3D code, which solves the drift-kinetic equation for torus plasmas and radial electric field using the δf Monte Carlo method, has developed to study the variety of issues relating to neoclassical transport phenomena in magnetic confinement plasmas. Here the numerical techniques used in FORTEC-3D are reviewed, and resent progress in the simulation method to simulate GAM oscillation is also explained. A band-limited white noise term is introduced in the equation of time evolution of radial electric field to excite GAM oscillation, which enables us to analyze GAM frequency using FORTEC-3D even in the case the collisionless GAM damping is fast. (author)
PRIMO: A graphical environment for the Monte Carlo simulation of Varian and Elekta linacs
Rodriguez, Manuel Jairo; Sempau Roma, Josep; Brualla, Lorenzo
2013-01-01
Background: The accurate Monte Carlo simulation of a linac requires a detailed description of its geometry and the application of elaborate variance-reduction techniques for radiation transport. Both tasks entail a substantial coding effort and demand advanced knowledge of the intricacies of the Monte Carlo system being used. Methods: PRIMO, a new Monte Carlo system that allows the effortless simulation of most Varian and Elekta linacs, including their multileaf collimators and electron appli...
Monte Carlo Simulations of the Photospheric Process
Santana, Rodolfo; Hernandez, Roberto A; Kumar, Pawan
2015-01-01
We present a Monte Carlo (MC) code we wrote to simulate the photospheric process and to study the photospheric spectrum above the peak energy. Our simulations were performed with a photon to electron ratio $N_{\\gamma}/N_{e} = 10^{5}$, as determined by observations of the GRB prompt emission. We searched an exhaustive parameter space to determine if the photospheric process can match the observed high-energy spectrum of the prompt emission. If we do not consider electron re-heating, we determined that the best conditions to produce the observed high-energy spectrum are low photon temperatures and high optical depths. However, for these simulations, the spectrum peaks at an energy below 300 keV by a factor $\\sim 10$. For the cases we consider with higher photon temperatures and lower optical depths, we demonstrate that additional energy in the electrons is required to produce a power-law spectrum above the peak-energy. By considering electron re-heating near the photosphere, the spectrum for these simulations h...
In this work we investigate the formation of Ge clusters on stepped Si substrate at elevated temperatures (≤ 300 °C) with the help of the kinetic Monte-Carlo (kMC) method. The modeling was performed for the case of low surface coverage in order to examine the process of Ge cluster growth at early stages. The temperature dependence of the development of Ge structures was explored and the transition from the growth in the middle of the steps to the growth at step edges was traced. Modeling shows that the formation of Ge clusters at the step edges begins at temperatures higher than 60 °C, whereas at temperatures below 60 °C clusters grow at the middle of the steps, and at 300 °C all Ge atoms are gathered at the bottom of the Si step edges. Results of the kMC simulations were compared to experiments and analytical evaluations. A cluster formation diagram linking deposition rate, terrace width, and transition temperature between different cluster formation modes is presented. - Highlights: • Modeling of the development of Ge structures at stepped Si substrate was performed. • It was shown that morphology of Ge clusters depends on the temperature. • The temperature ranges for each type of morphology were found. • A predictive cluster formation diagram is provided
Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds
Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.
2012-11-01
A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.
Monte Carlo simulation for simultaneous particle coagulation and deposition
ZHAO; Haibo; ZHENG; Chuguang
2006-01-01
The process of dynamic evolution in dispersed systems due to simultaneous particle coagulation and deposition is described mathematically by general dynamic equation (GDE). Monte Carlo (MC) method is an important approach of numerical solutions of GDE. However, constant-volume MC method exhibits the contradictory of low computation cost and high computation precision owing to the fluctuation of the number of simulation particles; constant-number MC method can hardly be applied to engineering application and general scientific quantitative analysis due to the continual contraction or expansion of computation domain. In addition, the two MC methods depend closely on the "subsystem" hypothesis, which constraints their expansibility and the scope of application. A new multi-Monte Carlo (MMC) method is promoted to take account of GDE for simultaneous particle coagulation and deposition. MMC method introduces the concept of "weighted fictitious particle" and is based on the "time-driven" technique. Furthermore MMC method maintains synchronously the computational domain and the total number of fictitious particles, which results in the latent expansibility of simulation for boundary condition, the space evolution of particle size distribution and even particle dynamics. The simulation results of MMC method for two special cases in which analytical solutions exist agree with analytical solutions well, which proves that MMC method has high and stable computational precision and low computation cost because of the constant and limited number of fictitious particles. Lastly the source of numerical error and the relative error of MMC method are analyzed, respectively.
Full text: Among various methods of hydrogen determination in materials [1] the nuclear recoil determination method (ERD) is the only way allowing one to analyze simultaneously the contents of all hydrogen isotopes. Using monochromatic fast neutrons for this purpose (method NERD) one carry out the analysis of thick specimens without their destruction and irrespective of their condition (gas, liquid, solid) [2]. The depth profiles of the hydrogen isotopes concentration are obtained from the energy spectra of the recoiled hydrogen nuclei. In this work some ways of improving the depth profile resolution and increasing sensitivity of the NERD method are analyzed. The operational experience with the NERD spectrometer, based on the neutron generator NG-150 at the INP AS RUz, has shown that the analytical characteristics of the method can be essentially improved. At existing NERD installation their worsening is mainly defined by the following reasons: - the background (n,p), (n,d), (n,t) reactions in the material (matrix) of the analyzed specimen and detectors could not be separated from the hydrogen recoiled ions. This circumstance restricts the definition limit of the method. - the geometry of measurement strongly affects on the depth resolution of the hydrogen profile as well as on the duration of measurement. These factors would preferably be known beforehand. We develop the procedure of simulation of energy spectra of hydrogen recoils as well as the charged particles from the reactions (n, p), (n, d) and (n, t) for specimens of various structure. Spectra are formed by the Monte Carlo method taking into account all features of the real procedure of analysis, such as the energy spectrum of the neutrons generated via the reactions d + T→n + α or d + D→n+3He in thick TiT target, geometry of measurement, losses of energy of the charged particles, the energy and angular straggling of the charged particles in the sample material, the energy resolution of the used
蒙特卡罗模拟光通过大气后的时间分布%Simulation of transmitted light through atmosphere by Monte Carlo method
吴真; 贺俊芳; 吴登科; 吕百达
2011-01-01
Different turbid media have different optical parameters such as absorption coefficient, scattering coefficient, anisotropic factor and refractive index.Monte Carlo method was used to simulate the influence of optical parameters on the transmitted photons for light transmitted through different atmospheres.The result shows that the temporal distribution of transmitted light has two peaks corresponding to ballistic photons and diffuse photons, respectively.Every optical parameter affects both the number and time range of ballistic photons, snake photons and diffuse photons.From the angle of statistical simulation, it is explained why atmosphere imaging is difficult when the refractive index of atmosphere is large.%采用蒙特卡罗方法模拟了光通过光学特性参数不同的大气后透射光时间分布.分析了大气的散射系数、吸收系数、不对称因子及折射率对透射光时间分布的影响.结果表明:透射光时间分布曲线存在两个峰,分别对应子弹光与漫射光.各光学参数界定了子弹光、蛇形光、漫射光的大小和时间范围,并从统计模拟的角度解释了折射率大的大气中难以成像的因为.
Application of Monte Carlo Simulations to Improve Basketball Shooting Strategy
Min, Byeong June
2016-01-01
The underlying physics of basketball shooting seems to be a straightforward example of the Newtonian mechanics that can easily be traced by numerical methods. However, a human basketball player does not make use of all the possible basketball trajectories. Instead, a basketball player will build up a database of successful shots and select the trajectory that has the greatest tolerance to small variations of the real world. We simulate the basketball player's shooting training as a Monte Carlo sequence to build optimal shooting strategies, such as the launch speed and angle of the basketball, and whether to take a direct shot or a bank shot, as a function of the player's court positions and height. The phase space volume that belongs to the successful launch velocities generated by Monte Carlo simulations are then used as the criterion to optimize a shooting strategy that incorporates not only mechanical, but human factors as well.
Atomistic Kinetic Monte Carlo Simulations of Polycrystalline Copper Electrodeposition
Treeratanaphitak, Tanyakarn; Abukhdeir, Nasser Mohieddin
2014-01-01
A high-fidelity kinetic Monte Carlo (KMC) simulation method (T. Treeratanaphitak, M. Pritzker, N. M. Abukhdeir, Electrochim. Acta 121 (2014) 407--414) using the semi-empirical multi-body embedded-atom method (EAM) potential has been extended to model polycrystalline metal electrodeposition. The presented KMC-EAM method enables true three-dimensional atomistic simulations of electrodeposition over experimentally relevant timescales. Simulations using KMC-EAM are performed over a range of overpotentials to predict the effect on deposit texture evolution. Results show strong agreement with past experimental results both with respect to deposition rates on various copper surfaces and roughness-time power law behaviour. It is found that roughness scales with time $\\propto t^\\beta$ where $\\beta=0.62 \\pm 0.12$, which is in good agreement with past experimental results. Furthermore, the simulations provide insights into sub-surface deposit morphologies which are not directly accessible from experimental measurements.
The derivation of Particle Monte Carlo methods for plasma modeling from transport equations
Longo, Savino
2008-01-01
We analyze here in some detail, the derivation of the Particle and Monte Carlo methods of plasma simulation, such as Particle in Cell (PIC), Monte Carlo (MC) and Particle in Cell / Monte Carlo (PIC/MC) from formal manipulation of transport equations.
Introduction to Monte Carlo methods: sampling techniques and random numbers
The Monte Carlo method describes a very broad area of science, in which many processes, physical systems and phenomena that are statistical in nature and are difficult to solve analytically are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions. As the number of individual events (called histories) is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. Assuming that the behavior of physical system can be described by probability density functions, then the Monte Carlo simulation can proceed by sampling from these probability density functions, which necessitates a fast and effective way to generate random numbers uniformly distributed on the interval (0,1). Particles are generated within the source region and are transported by sampling from probability density functions through the scattering media until they are absorbed or escaped the volume of interest. The outcomes of these random samplings or trials, must be accumulated or tallied in an appropriate manner to produce the desired result, but the essential characteristic of Monte Carlo is the use of random sampling techniques to arrive at a solution of the physical problem. The major components of Monte Carlo methods for random sampling for a given event are described in the paper
Multi-Level Monte Carlo Simulations with Importance Sampling
Przemyslaw S. Stilger and Ser-Huang Poon
2013-01-01
We present an application of importance sampling to multi-asset options under the Heston and the Bates models as well as to the Heston-Hull-White and the Heston-Cox-Ingersoll-Ross models. Moreover, we provide an efficient importance sampling scheme in a Multi-Level Monte Carlo simulation. In all cases, we explain how the Greeks can be computed in the different simulation schemes using the Likelihood Ratio Method, and how combining it with importance sampling leads to a significant variance re...
Monte Carlo simulations of single polymer force-extension relations
We present Monte Carlo simulations for studying the statistical mechanics of arbitrarily long single molecules under stretching. In many cases in which the thermodynamic limit is not satisfied, different statistical ensembles yield different macroscopic force-displacement curves. In this work we provide a description of the Monte Carlo simulations and discuss in details the assumptions adopted.
Accelerating particle-in-cell simulations using multilevel Monte Carlo
Ricketson, Lee
2015-11-01
Particle-in-cell (PIC) simulations have been an important tool in understanding plasmas since the dawn of the digital computer. Much more recently, the multilevel Monte Carlo (MLMC) method has accelerated particle-based simulations of a variety of systems described by stochastic differential equations (SDEs), from financial portfolios to porous media flow. The fundamental idea of MLMC is to perform correlated particle simulations using a hierarchy of different time steps, and to use these correlations for variance reduction on the fine-step result. This framework is directly applicable to the Langevin formulation of Coulomb collisions, as demonstrated in previous work, but in order to apply to PIC simulations of realistic scenarios, MLMC must be generalized to incorporate self-consistent evolution of the electromagnetic fields. We present such a generalization, with rigorous results concerning its accuracy and efficiency. We present examples of the method in the collisionless, electrostatic context, and discuss applications and extensions for the future.
Monte Carlo simulations for focusing elliptical guides
Valicu, Roxana [FRM2 Garching, Muenchen (Germany); Boeni, Peter [E20, TU Muenchen (Germany)
2009-07-01
The aim of the Monte Carlo simulations using McStas Programme was to improve the focusing of the neutron beam existing at PGAA (FRM II) by prolongation of the existing elliptic guide (coated now with supermirrors with m=3) with a new part. First we have tried with an initial length of the additional guide of 7,5cm and coatings for the neutron guide of supermirrors with m=4,5 and 6. The gain (calculated by dividing the intensity in the focal point after adding the guide by the intensity at the focal point with the initial guide) obtained for this coatings indicated that a coating with m=5 would be appropriate for a first trial. The next step was to vary the length of the additional guide for this m value and therefore choosing the appropriate length for the maximal gain. With the m value and the length of the guide fixed we have introduced an aperture 1 cm before the focal point and we have varied the radius of this aperture in order to obtain a focused beam. We have observed a dramatic decrease in the size of the beam in the focal point after introducing this aperture. The simulation results, the gains obtained and the evolution of the beam size will be presented.
Monte Carlo simulation framework for TMT
Vogiatzis, Konstantinos; Angeli, George Z.
2008-07-01
This presentation describes a strategy for assessing the performance of the Thirty Meter Telescope (TMT). A Monte Carlo Simulation Framework has been developed to combine optical modeling with Computational Fluid Dynamics simulations (CFD), Finite Element Analysis (FEA) and controls to model the overall performance of TMT. The framework consists of a two year record of observed environmental parameters such as atmospheric seeing, site wind speed and direction, ambient temperature and local sunset and sunrise times, along with telescope azimuth and elevation with a given sampling rate. The modeled optical, dynamic and thermal seeing aberrations are available in a matrix form for distinct values within the range of influencing parameters. These parameters are either part of the framework parameter set or can be derived from them at each time-step. As time advances, the aberrations are interpolated and combined based on the current value of their parameters. Different scenarios can be generated based on operating parameters such as venting strategy, optical calibration frequency and heat source control. Performance probability distributions are obtained and provide design guidance. The sensitivity of the system to design, operating and environmental parameters can be assessed in order to maximize the % of time the system meets the performance specifications.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
Extending canonical Monte Carlo methods: II
We have previously presented a methodology for extending canonical Monte Carlo methods inspired by a suitable extension of the canonical fluctuation relation C = β2(δE2) compatible with negative heat capacities, C α, as is shown in the particular case of the 2D seven-state Potts model where the exponent α = 0.14–0.18
Introduction to the Monte Carlo methods
Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab
Monte Carlo simulation for statistical decay of compound nucleus
We perform Monte Carlo simulations for particle and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory; the Monte Carlo Hauser-Feshbach (MCHF) method. The MCHF calculation, which gives us correlated information between emitted particles and γ-rays, will be a powerful tool in many applications, because we are able to probe nuclear reactions in more microscopic way. For example, the MCHF code can be used as an event generator in a radiation transport code. Having the correlated neutron and γ-ray emission process in the transport calculations, energy conservation is satisfied automatically event-by-event. In addition, the correlations amongst particles and γ-ray can be a signature of a particular nuclear reaction occurred in a nuclear system. We have been developing the MCHF code, CGM, which solves the Hauser-Feshbach equation with the Monte Carlo method. The code includes all the common models that emerge in a standard Hauser-Feshbach code, namely the particle transmission generator, the level density module, interface to the discrete level database, and so on. The code allows to emit multiple neutrons, as long as the excitation energy of the compound nucleus is larger than the neutron separation energy. The γ-ray competition is always included at each compound decay stage, and the angular momentum conservation holds too. In this paper, we discuss our technique to calculate the particle and γ-ray correlations in the statistical model framework, and some simulation examples are shown
Moura, Alfredo de
2012-01-01
Precipitate structures play a fundamental function in the material science due to the capacity of representing strong obstacles for dislocations movements within the material. This master thesis focuses on the elaboration and application of mechanical statistics knowledge, namely the kinetic Monte Carlo method, on the study and prediction of the phenomenon of precipitation in an aluminum alloy. The alloy under analysis is the aluminum scandium alloy. This thesis tackles subjects such as...
The infrared vibrational absorption spectra of (SF6)2 and (SiF4)2 dimers were studied in argon and nitrogen matrices. The model takes into account the interactions of local dipole moments of a dimer with matrix particles in the approximation of dipole-induced dipole and dipole-quadrupole interactions with the help of the Monte Carlo method. The calculated spectra sufficiently well reproduce the main characteristics of the experimental spectra. (authors)
To perform Monte Carlo simulation must also assign to each voxel a material, whose effective sections shall be used for the transport of particles. The allocation is made on the basis of the mass density of each voxel and is not two-way, that several different materials may apply to a same density composition. So the assignment is not fixed and depends on the user. Our study focuses on the allocation of materials from the mass densities, and its impact on clinical dosimetry. (Author)
Monte Carlo Methods for Rough Free Energy Landscapes: Population Annealing and Parallel Tempering
Machta, Jon; Ellis, Richard S.
2011-01-01
Parallel tempering and population annealing are both effective methods for simulating equilibrium systems with rough free energy landscapes. Parallel tempering, also known as replica exchange Monte Carlo, is a Markov chain Monte Carlo method while population annealing is a sequential Monte Carlo method. Both methods overcome the exponential slowing associated with high free energy barriers. The convergence properties and efficiency of the two methods are compared. For large systems, populatio...
On Monte Carlo Simulation and Analysis of Electricity Markets
This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio