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.
Dynamic bounds coupled with Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)
2011-02-15
For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.
Markov Chain Monte Carlo from Lagrangian Dynamics.
Lan, Shiwei; Stathopoulos, Vasileios; Shahbaba, Babak; Girolami, Mark
2015-04-01
Hamiltonian Monte Carlo (HMC) improves the computational e ciency of the Metropolis-Hastings algorithm by reducing its random walk behavior. Riemannian HMC (RHMC) further improves the performance of HMC by exploiting the geometric properties of the parameter space. However, the geometric integrator used for RHMC involves implicit equations that require fixed-point iterations. In some cases, the computational overhead for solving implicit equations undermines RHMC's benefits. In an attempt to circumvent this problem, we propose an explicit integrator that replaces the momentum variable in RHMC by velocity. We show that the resulting transformation is equivalent to transforming Riemannian Hamiltonian dynamics to Lagrangian dynamics. Experimental results suggests that our method improves RHMC's overall computational e ciency in the cases considered. All computer programs and data sets are available online (http://www.ics.uci.edu/~babaks/Site/Codes.html) in order to allow replication of the results reported in this paper.
Self-learning Monte Carlo (dynamical biasing)
International Nuclear Information System (INIS)
Matthes, W.
1981-01-01
In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)
Dynamic bounds coupled with Monte Carlo simulations
Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.
2011-01-01
For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper
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 simulated dynamical magnetization of single-chain magnets
Energy Technology Data Exchange (ETDEWEB)
Li, Jun; Liu, Bang-Gui, E-mail: bgliu@iphy.ac.cn
2015-03-15
Here, a dynamical Monte-Carlo (DMC) method is used to study temperature-dependent dynamical magnetization of famous Mn{sub 2}Ni system as typical example of single-chain magnets with strong magnetic anisotropy. Simulated magnetization curves are in good agreement with experimental results under typical temperatures and sweeping rates, and simulated coercive fields as functions of temperature are also consistent with experimental curves. Further analysis indicates that the magnetization reversal is determined by both thermal-activated effects and quantum spin tunnelings. These can help explore basic properties and applications of such important magnetic systems. - Highlights: • Monte Carlo simulated magnetization curves are in good agreement with experimental results. • Simulated coercive fields as functions of temperature are consistent with experimental results. • The magnetization reversal is understood in terms of the Monte Carlo simulations.
Geometry and Dynamics for Markov Chain Monte Carlo
Barp, Alessandro; Briol, François-Xavier; Kennedy, Anthony D.; Girolami, Mark
2018-03-01
Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the intuitions and knowledge of users of the methodology and our deep understanding of these theoretical foundations. The aim of this review is to provide a comprehensive introduction to the geometric tools used in Hamiltonian Monte Carlo at a level accessible to statisticians, machine learners and other users of the methodology with only a basic understanding of Monte Carlo methods. This will be complemented with some discussion of the most recent advances in the field which we believe will become increasingly relevant to applied scientists.
The Hybrid Monte Carlo (HMC) method and dynamic fermions
International Nuclear Information System (INIS)
Amaral, Marcia G. do
1994-01-01
Nevertheless the Monte Carlo method has been extensively used in the simulation of many types of theories, the successful application has been established only for models containing boson fields. With the present computer generation, the development of faster and efficient algorithms became necessary and urgent. This paper studies the HMC and the dynamic fermions
Molecular dynamics and Monte Carlo calculations in statistical mechanics
International Nuclear Information System (INIS)
Wood, W.W.; Erpenbeck, J.J.
1976-01-01
Monte Carlo and molecular dynamics calculations on statistical mechanical systems is reviewed giving some of the more significant recent developments. It is noted that the term molecular dynamics refers to the time-averaging technique for hard-core and square-well interactions and for continuous force-law interactions. Ergodic questions, methodology, quantum mechanical, Lorentz, and one-dimensional, hard-core, and square and triangular-well systems, short-range soft potentials, and other systems are included. 268 references
Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm
Gubernatis, James
2014-03-01
A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo
Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik
2018-05-01
Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.
Geometry and Dynamics for Markov Chain Monte Carlo
Barp, Alessandro; Briol, Francois-Xavier; Kennedy, Anthony D.; Girolami, Mark
2017-01-01
Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the in...
Dynamic Load Balancing of Parallel Monte Carlo Transport Calculations
International Nuclear Information System (INIS)
O'Brien, M; Taylor, J; Procassini, R
2004-01-01
The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since the particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations
Research on Monte Carlo improved quasi-static method for reactor space-time dynamics
International Nuclear Information System (INIS)
Xu Qi; Wang Kan; Li Shirui; Yu Ganglin
2013-01-01
With large time steps, improved quasi-static (IQS) method can improve the calculation speed for reactor dynamic simulations. The Monte Carlo IQS method was proposed in this paper, combining the advantages of both the IQS method and MC method. Thus, the Monte Carlo IQS method is beneficial for solving space-time dynamics problems of new concept reactors. Based on the theory of IQS, Monte Carlo algorithms for calculating adjoint neutron flux, reactor kinetic parameters and shape function were designed and realized. A simple Monte Carlo IQS code and a corresponding diffusion IQS code were developed, which were used for verification of the Monte Carlo IQS method. (authors)
Dynamic Monte Carlo simulations of radiatively accelerated GRB fireballs
Chhotray, Atul; Lazzati, Davide
2018-05-01
We present a novel Dynamic Monte Carlo code (DynaMo code) that self-consistently simulates the Compton-scattering-driven dynamic evolution of a plasma. We use the DynaMo code to investigate the time-dependent expansion and acceleration of dissipationless gamma-ray burst fireballs by varying their initial opacities and baryonic content. We study the opacity and energy density evolution of an initially optically thick, radiation-dominated fireball across its entire phase space - in particular during the Rph matter-dominated fireballs due to Thomson scattering. We quantify the new phases by providing analytical expressions of Lorentz factor evolution, which will be useful for deriving jet parameters.
Modeling Dynamic Objects in Monte Carlo Particle Transport Calculations
International Nuclear Information System (INIS)
Yegin, G.
2008-01-01
In this study, the Multi-Geometry geometry modeling technique was improved in order to handle moving objects in a Monte Carlo particle transport calculation. In the Multi-Geometry technique, the geometry is a superposition of objects not surfaces. By using this feature, we developed a new algorithm which allows a user to make enable or disable geometry elements during particle transport. A disabled object can be ignored at a certain stage of a calculation and switching among identical copies of the same object located adjacent poins during a particle simulation corresponds to the movement of that object in space. We called this powerfull feature as Dynamic Multi-Geometry technique (DMG) which is used for the first time in Brachy Dose Monte Carlo code to simulate HDR brachytherapy treatment systems. Our results showed that having disabled objects in a geometry does not effect calculated dose values. This technique is also suitable to be used in other areas such as IMRT treatment planning systems
Scouting the feasibility of Monte Carlo reactor dynamics simulations
International Nuclear Information System (INIS)
Legrady, David; Hoogenboom, J. Eduard
2008-01-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)
Scouting the feasibility of Monte Carlo reactor dynamics simulations
Energy Technology Data Exchange (ETDEWEB)
Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)
2008-07-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)
Partial multicanonical algorithm for molecular dynamics and Monte Carlo simulations.
Okumura, Hisashi
2008-09-28
Partial multicanonical algorithm is proposed for molecular dynamics and Monte Carlo simulations. The partial multicanonical simulation samples a wide range of a part of the potential-energy terms, which is necessary to sample the conformational space widely, whereas a wide range of total potential energy is sampled in the multicanonical algorithm. Thus, one can concentrate the effort to determine the weight factor only on the important energy terms in the partial multicanonical simulation. The partial multicanonical, multicanonical, and canonical molecular dynamics algorithms were applied to an alanine dipeptide in explicit water solvent. The canonical simulation sampled the states of P(II), C(5), alpha(R), and alpha(P). The multicanonical simulation covered the alpha(L) state as well as these states. The partial multicanonical simulation also sampled the C(7) (ax) state in addition to the states that were sampled by the multicanonical simulation. In the partial multicanonical simulation, furthermore, backbone dihedral angles phi and psi rotated more frequently than those in the multicanonical and canonical simulations. These results mean that the partial multicanonical algorithm has a higher sampling efficiency than the multicanonical and canonical algorithms.
Monte Carlo-molecular dynamics simulations for two-dimensional magnets
International Nuclear Information System (INIS)
Kawabata, C.; takeuchi, M.; Bishop, A.R.
1985-01-01
A combined Monte Carlo-molecular dynamics simulation technique is used to study the dynamic structure factor on a square lattice for isotropic Heisenberg and planar classical ferromagnetic spin Hamiltonians
Novotny, M.A.; Watanabe, Hiroshi; Ito, Nobuyasu
2010-01-01
The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing
Novotny, M.A.
2010-02-01
The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing Markov Chains method are given. Simulation results are presented to confirm the theoretical efficiencies. © 2010.
Monte Carlo-based simulation of dynamic jaws tomotherapy
Energy Technology Data Exchange (ETDEWEB)
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S. [Department of Molecular Imaging, Radiotherapy and Oncology, Universite Catholique de Louvain, 54 Avenue Hippocrate, 1200 Brussels, Belgium and Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 (United States); 21 Century Oncology., 1240 D' onofrio, Madison, Wisconsin 53719 (United States); TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 and Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Department of Radiotherapy and Oncology, Universite Catholique de Louvain, St-Luc University Hospital, 10 Avenue Hippocrate, 1200 Brussels (Belgium)
2011-09-15
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is
Monte Carlo-based simulation of dynamic jaws tomotherapy
International Nuclear Information System (INIS)
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S.
2011-01-01
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis
International Nuclear Information System (INIS)
Brown, F.B.
1981-01-01
Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes
Patti, Alessandro; Cuetos, Alejandro
2012-07-01
We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.
International Nuclear Information System (INIS)
Creutz, M.
1986-01-01
The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena
International Nuclear Information System (INIS)
Rajabalinejad, M.
2010-01-01
To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.
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
Directory of Open Access Journals (Sweden)
Bardenet Rémi
2013-07-01
Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.
The Monte Carlo dynamics of a binary Lennard-Jones glass-forming mixture
International Nuclear Information System (INIS)
Berthier, L; Kob, W
2007-01-01
We use a standard Monte Carlo algorithm to study the slow dynamics of a binary Lennard-Jones glass-forming mixture at low temperature. We find that the Monte Carlo approach is by far the most efficient way to simulate a stochastic dynamics since the relaxation is about 10 times faster than in Brownian dynamics and about 30 times faster than in stochastic dynamics. Moreover, the average dynamical behaviour of the system is in quantitative agreement with that obtained using Newtonian dynamics, apart from at very short times where thermal vibrations are suppressed. We show, however, that dynamic fluctuations quantified by four-point dynamic susceptibilities do retain a dependence on the microscopic dynamics, as recently predicted theoretically
General purpose dynamic Monte Carlo with continuous energy for transient analysis
Energy Technology Data Exchange (ETDEWEB)
Sjenitzer, B. L.; Hoogenboom, J. E. [Delft Univ. of Technology, Dept. of Radiation, Radionuclide and Reactors, Mekelweg 15, 2629JB Delft (Netherlands)
2012-07-01
For safety assessments transient analysis is an important tool. It can predict maximum temperatures during regular reactor operation or during an accident scenario. Despite the fact that this kind of analysis is very important, the state of the art still uses rather crude methods, like diffusion theory and point-kinetics. For reference calculations it is preferable to use the Monte Carlo method. In this paper the dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli4. Also, the method is extended for use with continuous energy. The first results of Dynamic Tripoli demonstrate that this kind of calculation is indeed accurate and the results are achieved in a reasonable amount of time. With the method implemented in Tripoli it is now possible to do an exact transient calculation in arbitrary geometry. (authors)
Murthy, K. P. N.
2001-01-01
An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...
The specific bias in dynamic Monte Carlo simulations of nuclear reactors
International Nuclear Information System (INIS)
Yamamoto, T.; Endo, H.; Ishizu, T.; Tatewaki, I.
2013-01-01
During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to 'false super-criticality' which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not critical. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in an over-estimation of the final power level. It should be noted that the bias will not be eliminated by refining the time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations. (authors)
International Nuclear Information System (INIS)
Cramer, S.N.
1984-01-01
The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described
Variational Monte Carlo Technique
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...
The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation
Chen, Jundong
2018-03-01
Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-01-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration
Cuetos, Alejandro; Patti, Alessandro
2015-08-01
We propose a simple but powerful theoretical framework to quantitatively compare Brownian dynamics (BD) and dynamic Monte Carlo (DMC) simulations of multicomponent colloidal suspensions. By extending our previous study focusing on monodisperse systems of rodlike colloids, here we generalize the formalism described there to multicomponent colloidal mixtures and validate it by investigating the dynamics in isotropic and liquid crystalline phases containing spherical and rodlike particles. In order to investigate the dynamics of multicomponent colloidal systems by DMC simulations, it is key to determine the elementary time step of each species and establish a unique timescale. This is crucial to consistently study the dynamics of colloidal particles with different geometry. By analyzing the mean-square displacement, the orientation autocorrelation functions, and the self part of the van Hove correlation functions, we show that DMC simulation is a very convenient and reliable technique to describe the stochastic dynamics of any multicomponent colloidal system. Our theoretical formalism can be easily extended to any colloidal system containing size and/or shape polydisperse particles.
Liu, Gui-Bin; Liu, Bang-Gui
2010-01-01
In this paper, we combine thermal effects with Landau-Zener (LZ) quantum tunneling effects in a dynamical Monte Carlo (DMC) framework to produce satisfactory magnetization curves of single-molecule magnet (SMM) systems. We use the giant spin approximation for SMM spins and consider regular lattices of SMMs with magnetic dipolar interactions (MDI). We calculate spin reversal probabilities from thermal-activated barrier hurdling, direct LZ tunneling, and thermal-assisted LZ tunnelings in the pr...
Energy Technology Data Exchange (ETDEWEB)
Tringe, J.W., E-mail: tringe2@llnl.gov [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Ileri, N. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Levie, H.W. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA (United States); Stroeve, P.; Ustach, V.; Faller, R. [Department of Chemical Engineering & Materials Science, University of California, Davis, CA (United States); Renaud, P. [Swiss Federal Institute of Technology, Lausanne, (EPFL) (Switzerland)
2015-08-18
Highlights: • WGA proteins in nanochannels modeled by Molecular Dynamics and Monte Carlo. • Protein surface coverage characterized by atomic force microscopy. • Models indicate transport characteristics depend strongly on surface coverage. • Results resolve of a four orders of magnitude difference in diffusion coefficient values. - Abstract: We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage. Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.
Monte Carlo codes and Monte Carlo simulator program
International Nuclear Information System (INIS)
Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.
1990-03-01
Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)
Reactor physics simulations with coupled Monte Carlo calculation and computational fluid dynamics
International Nuclear Information System (INIS)
Seker, V.; Thomas, J.W.; Downar, T.J.
2007-01-01
A computational code system based on coupling the Monte Carlo code MCNP5 and the Computational Fluid Dynamics (CFD) code STAR-CD was developed as an audit tool for lower order nuclear reactor calculations. This paper presents the methodology of the developed computer program 'McSTAR'. McSTAR is written in FORTRAN90 programming language and couples MCNP5 and the commercial CFD code STAR-CD. MCNP uses a continuous energy cross section library produced by the NJOY code system from the raw ENDF/B data. A major part of the work was to develop and implement methods to update the cross section library with the temperature distribution calculated by STARCD for every region. Three different methods were investigated and implemented in McSTAR. The user subroutines in STAR-CD are modified to read the power density data and assign them to the appropriate variables in the program and to write an output data file containing the temperature, density and indexing information to perform the mapping between MCNP and STAR-CD cells. Preliminary testing of the code was performed using a 3x3 PWR pin-cell problem. The preliminary results are compared with those obtained from a STAR-CD coupled calculation with the deterministic transport code DeCART. Good agreement in the k eff and the power profile was observed. Increased computational capabilities and improvements in computational methods have accelerated interest in high fidelity modeling of nuclear reactor cores during the last several years. High-fidelity has been achieved by utilizing full core neutron transport solutions for the neutronics calculation and computational fluid dynamics solutions for the thermal-hydraulics calculation. Previous researchers have reported the coupling of 3D deterministic neutron transport method to CFD and their application to practical reactor analysis problems. One of the principal motivations of the work here was to utilize Monte Carlo methods to validate the coupled deterministic neutron transport
International Nuclear Information System (INIS)
Fay, P.J.; Ray, J.R.; Wolf, R.J.
1994-01-01
We present a new, nondestructive, method for determining chemical potentials in Monte Carlo and molecular dynamics simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials in which the Monte Carlo method is used to determine success or failure of the creation/destruction attempts; we thus call the method a detailed balance method. The method allows one to obtain estimates of the chemical potential for a given species in any closed ensemble simulation; the closed ensemble is paired with a ''natural'' open ensemble for the purpose of obtaining creation and destruction probabilities. We present results for the Lennard-Jones system and also for an embedded atom model of liquid palladium, and compare to previous results in the literature for these two systems. We are able to obtain an accurate estimate of the chemical potential for the Lennard-Jones system at higher densities than reported in the literature
Monte Carlo study of four-spinon dynamic structure function in antiferromagnetic Heisenberg model
International Nuclear Information System (INIS)
Si-Lakhal, B.; Abada, A.
2003-11-01
Using Monte Carlo integration methods, we describe the behavior of the exact four-s pinon dynamic structure function S 4 in the antiferromagnetic spin 1/2 Heisenberg quantum spin chain as a function of the neutron energy ω and momentum transfer k. We also determine the fourspinon continuum, the extent of the region in the (k, ω) plane outside which S 4 is identically zero. In each case, the behavior of S 4 is shown to be consistent with the four-spinon continuum and compared to the one of the exact two-spinon dynamic structure function S 2 . Overall shape similarity is noted. (author)
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.
Monte Carlo and Quasi-Monte Carlo Sampling
Lemieux, Christiane
2009-01-01
Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
International Nuclear Information System (INIS)
Stapleton, S; Zavgorodni, S; Popescu, I A; Beckham, W A
2005-01-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
Stapleton, S.; Zavgorodni, S.; Popescu, I. A.; Beckham, W. A.
2005-02-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.
Vectorization of a Monte Carlo simulation scheme for nonequilibrium gas dynamics
Boyd, Iain D.
1991-01-01
Significant improvement has been obtained in the numerical performance of a Monte Carlo scheme for the analysis of nonequilibrium gas dynamics through an implementation of the algorithm which takes advantage of vector hardware, as presently demonstrated through application to three different problems. These are (1) a 1D standing-shock wave; (2) the flow of an expanding gas through an axisymmetric nozzle; and (3) the hypersonic flow of Ar gas over a 3D wedge. Problem (3) is illustrative of the greatly increased number of molecules which the simulation may involve, thanks to improved algorithm performance.
Summing Feynman graphs by Monte Carlo: Planar φ3-theory and dynamically triangulated random surfaces
International Nuclear Information System (INIS)
Boulatov, D.V.
1988-01-01
New combinatorial identities are suggested relating the ratio of (n-1)th and nth orders of (planar) perturbation expansion for any quantity to some average over the ensemble of all planar graphs of the nth order. These identities are used for Monte Carlo calculation of critical exponents γ str (string susceptibility) in planar φ 3 -theory and in the dynamically triangulated random surface (DTRS) model near the convergence circle for various dimensions. In the solvable case D=1 the exact critical properties of the theory are reproduced numerically. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Sjenitzer, Bart L.; Hoogenboom, J. Eduard, E-mail: B.L.Sjenitzer@TUDelft.nl, E-mail: J.E.Hoogenboom@TUDelft.nl [Delft University of Technology (Netherlands)
2011-07-01
A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)
International Nuclear Information System (INIS)
Sjenitzer, Bart L.; Hoogenboom, J. Eduard
2011-01-01
A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)
Dynamic Monte Carlo Simulations of Phase Ordering in Br Electrosorption on Ag(100)
Mitchell, S. J.; Brown, G.; Rikvold, P. A.
2000-03-01
We study the dynamics of Br electrosorption on single-crystal Ag(100) by Monte Carlo simulation. The system has a second-order phase transition from a low-coverage disordered phase at more negative potentials to a doubly degenerate c(2× 2) ordered phase at more positive potentials.(B.M. Ocko, et al.), Phys. Rev. Lett. 79, 1511 (1997). Effective lateral interactions were estimated by fitting equilibrium Monte Carlo isotherms to experiments. These are well described by nearest-neighbor exclusion and repulsive 1/r^3 interactions.(M.T.M. Koper, J. Electroanal. Chem. 450), 189 (1997). Considering adsorption/desorption and diffusion with barriers estimated from ab-initio calculations,(A. Ignaczak and J.A.N.F. Gomes, J. Electroanal. Chem. 420), 71 (1997). we simulate the time dependent Br coverage, order parameter, and x-ray scattering intensity following sudden potential steps across the phase boundary. For steps far into the ordered phase, dynamical scaling is observed. For smaller steps, the dynamics are more complicated. We also analyze hysteresis in a simulated cyclic-voltammetry experiment. Movies at http://www.scri.fsu.edu/ ~mitchell/.
Monte Carlo principles and applications
Energy Technology Data Exchange (ETDEWEB)
Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center
1976-03-01
The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.
International Nuclear Information System (INIS)
Dubi, A.; Gerstl, S.A.W.
1979-05-01
The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables
International Nuclear Information System (INIS)
Wollaber, Allan Benton
2016-01-01
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Energy Technology Data Exchange (ETDEWEB)
Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Energy Technology Data Exchange (ETDEWEB)
Brockway, D.; Soran, P.; Whalen, P.
1985-01-01
A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.
Monte Carlo study for the dynamical fluctuations inside a single jet in 2-jet events
International Nuclear Information System (INIS)
Zhang Kunshi; Liu Lianshou; Yin Jianwu; Chen Gang; Liu Chao
2002-01-01
The dynamical fluctuations inside a single jet in the 2-jet events produced in e + e - collisions at 91.2 GeV have been studied using Monte Carlo method. The results show that, the anisotropy of dynamical fluctuations inside a single jet changes remarkably with the variation of the cut parameter y cut . A transition point (γ p t = γ ψ ≠γ y ) exists, where the dynamical fluctuations are anisotropic in the longitudinal-transverse plan and isotropic in the transverse planes. It indicates that the y cut corresponding to the transition point is a physically reasonable cutting parameter for selecting jets and, meanwhile, the relative transverse momentum k t at the transition point is the scale for the determination of physical jets. This conclusion is in good agreement with the experimental fact that the third jet (gluon jet) was historically first discovered in the energy region 17-30 GeV in e + e - collisions
Dynamic Value at Risk: A Comparative Study Between Heteroscedastic Models and Monte Carlo Simulation
Directory of Open Access Journals (Sweden)
José Lamartine Távora Junior
2006-12-01
Full Text Available The objective of this paper was to analyze the risk management of a portfolio composed by Petrobras PN, Telemar PN and Vale do Rio Doce PNA stocks. It was verified if the modeling of Value-at-Risk (VaR through the place Monte Carlo simulation with volatility of GARCH family is supported by hypothesis of efficient market. The results have shown that the statistic evaluation in inferior to dynamics, evidencing that the dynamic analysis supplies support to the hypothesis of efficient market of the Brazilian share holding market, in opposition of some empirical evidences. Also, it was verified that the GARCH models of volatility is enough to accommodate the variations of the shareholding Brazilian market, since the model is capable to accommodate the great dynamic of the Brazilian market.
Monte-Carlo-based uncertainty propagation with hierarchical models—a case study in dynamic torque
Klaus, Leonard; Eichstädt, Sascha
2018-04-01
For a dynamic calibration, a torque transducer is described by a mechanical model, and the corresponding model parameters are to be identified from measurement data. A measuring device for the primary calibration of dynamic torque, and a corresponding model-based calibration approach, have recently been developed at PTB. The complete mechanical model of the calibration set-up is very complex, and involves several calibration steps—making a straightforward implementation of a Monte Carlo uncertainty evaluation tedious. With this in mind, we here propose to separate the complete model into sub-models, with each sub-model being treated with individual experiments and analysis. The uncertainty evaluation for the overall model then has to combine the information from the sub-models in line with Supplement 2 of the Guide to the Expression of Uncertainty in Measurement. In this contribution, we demonstrate how to carry this out using the Monte Carlo method. The uncertainty evaluation involves various input quantities of different origin and the solution of a numerical optimisation problem.
International Nuclear Information System (INIS)
Acharyya, Muktish
2011-01-01
The dynamical responses of Ising metamagnet (layered antiferromagnet) in the presence of a sinusoidally oscillating magnetic field are studied by Monte Carlo simulation. The time average staggered magnetisation plays the role of dynamic order parameter. A dynamical phase transition was observed and a phase diagram was plotted in the plane formed by field amplitude and temperature. The dynamical phase boundary is observed to shrink inward as the relative antiferromagnetic strength decreases. The results are compared with that obtained from pure ferromagnetic system. The shape of dynamic phase boundary observed to be qualitatively similar to that obtained from previous meanfield calculations. - Highlights: → The time average staggered magnetisation plays the role of dynamic order parameter. → A dynamical phase transition was observed and a phase diagram was plotted in the plane formed by field amplitude and temperature. → The dynamical phase boundary is observed to shrink inward as the relative antiferromagnetic strength decreases. → The results are compared with that obtained from pure ferromagnetic system. → The shape of dynamic phase boundary observed to be qualitatively similar to that obtained from previous meanfield calculation.
Monte Carlo Treatment Planning for Advanced Radiotherapy
DEFF Research Database (Denmark)
Cronholm, Rickard
This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...... and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...
Quantum dynamics at finite temperature: Time-dependent quantum Monte Carlo study
Energy Technology Data Exchange (ETDEWEB)
Christov, Ivan P., E-mail: ivan.christov@phys.uni-sofia.bg
2016-08-15
In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows a self-consistent treatment of the system of particles together with bath oscillators first for imaginary-time propagation of Schrödinger type of equations where both the system and the bath converge to their finite temperature ground state, and next for real time calculation where the dissipative dynamics is demonstrated. In that context the application of TDQMC appears as promising alternative to the path-integral related techniques where the real time propagation can be a challenge.
Dynamic Monte Carlo rate constants for magnetic Hamiltonians coupled to a phonon bath
Solomon, Lazarus; Novotny, Mark
2007-03-01
For quantitative comparisons between experimental time- dependent measurements and dynamic Monte Carlo simulations, a relation between the time constant in the simulation and real time is necessary. We calculate the transition rate for spin S system using the lattice frame method for a rigid spin cluster in an elastic medium [1]. We compare this with the transition rate for an Ising spin 12 system using the quantum- mechanical density-matrix method [2] with the results of ref [1,3]. These transition probabilities are different from those of either the Glauber or the Metropolis dynamics, and reflect the properties of the bosonic bath. Comparison with recent experiments [4] will be discussed. [1] E. M. Chudnovsky, D. A. Garanin, and R. Schilling (PRB 72, 2006) [2] K. Park, M. A. Novotny, and P. A. Rikvold (PRE 66, 2002) [3] K Saito, S. Takesue, and S. Miyashita, (PRE 61, 2002) [4] T. Meunier et al (Condensed Matter, 2006)
Guerra, Marta L.; Novotny, M. A.; Watanabe, Hiroshi; Ito, Nobuyasu
2009-01-01
We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.
Guerra, Marta L.
2009-02-23
We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.
Reversal time of jump-noise magnetization dynamics in nanomagnets via Monte Carlo simulations
Parthasarathy, Arun; Rakheja, Shaloo
2018-06-01
The jump-noise is a nonhomogeneous Poisson process which models thermal effects in magnetization dynamics, with special applications in low temperature escape rate phenomena. In this work, we develop improved numerical methods for Monte Carlo simulation of the jump-noise dynamics and validate the method by comparing the stationary distribution obtained empirically against the Boltzmann distribution. In accordance with the Néel-Brown theory, the jump-noise dynamics display an exponential relaxation toward equilibrium with a characteristic reversal time, which we extract for nanomagnets with uniaxial and cubic anisotropy. We relate the jump-noise dynamics to the equivalent Landau-Lifshitz dynamics up to second order correction for a general energy landscape and obtain the analogous Néel-Brown theory's solution of the reversal time. We find that the reversal time of jump-noise dynamics is characterized by Néel-Brown theory's solution at the energy saddle point for small noise. For large noise, the magnetization reversal due to jump-noise dynamics phenomenologically represents macroscopic tunneling of magnetization.
Dynamic connectivity algorithms for Monte Carlo simulations of the random-cluster model
International Nuclear Information System (INIS)
Elçi, Eren Metin; Weigel, Martin
2014-01-01
We review Sweeny's algorithm for Monte Carlo simulations of the random cluster model. Straightforward implementations suffer from the problem of computational critical slowing down, where the computational effort per edge operation scales with a power of the system size. By using a tailored dynamic connectivity algorithm we are able to perform all operations with a poly-logarithmic computational effort. This approach is shown to be efficient in keeping online connectivity information and is of use for a number of applications also beyond cluster-update simulations, for instance in monitoring droplet shape transitions. As the handling of the relevant data structures is non-trivial, we provide a Python module with a full implementation for future reference.
International Nuclear Information System (INIS)
Dalla Torre, J.; Fu, C.-C.; Willaime, F.; Barbu, A.; Bocquet, J.-L.
2006-01-01
The isochronal resistivity recovery in high purity α-iron irradiated by electrons was successfully reproduced by a multiscale modelling approach. The stability and mobility of small self-defect clusters determined by ab initio methods were used as input data for an event based Kinetic Monte Carlo (KMC) model, used to explore the defect population evolution during the annealing and to extract the resistivity recovery peaks. In this paper, we investigate the possibility of using an efficient mesoscale model, the Cluster Dynamics (CD), instead of KMC in this approach. The comparison between the two methods for various CD initial conditions shows the importance of spatial correlations between defects, which are neglected in the CD model. However, using appropriate initial conditions, e.g. starting from the concentration of Frenkel pairs after the uncorrelated stage I E , the CD model captures the main characteristics of subsequent defect population evolution, and it can therefore be used for fast and semi-quantitative investigations
Ab initio molecular dynamics simulation of liquid water by quantum Monte Carlo
International Nuclear Information System (INIS)
Zen, Andrea; Luo, Ye; Mazzola, Guglielmo; Sorella, Sandro; Guidoni, Leonardo
2015-01-01
Although liquid water is ubiquitous in chemical reactions at roots of life and climate on the earth, the prediction of its properties by high-level ab initio molecular dynamics simulations still represents a formidable task for quantum chemistry. In this article, we present a room temperature simulation of liquid water based on the potential energy surface obtained by a many-body wave function through quantum Monte Carlo (QMC) methods. The simulated properties are in good agreement with recent neutron scattering and X-ray experiments, particularly concerning the position of the oxygen-oxygen peak in the radial distribution function, at variance of previous density functional theory attempts. Given the excellent performances of QMC on large scale supercomputers, this work opens new perspectives for predictive and reliable ab initio simulations of complex chemical systems
International Nuclear Information System (INIS)
Okumura, Hisashi
2010-01-01
I review two new generalized-ensemble algorithms for molecular dynamics and Monte Carlo simulations of biomolecules, that is, the multibaric–multithermal algorithm and the partial multicanonical algorithm. In the multibaric–multithermal algorithm, two-dimensional random walks not only in the potential-energy space but also in the volume space are realized. One can discuss the temperature dependence and pressure dependence of biomolecules with this algorithm. The partial multicanonical simulation samples a wide range of only an important part of potential energy, so that one can concentrate the effort to determine a multicanonical weight factor only on the important energy terms. This algorithm has higher sampling efficiency than the multicanonical and canonical algorithms. (review)
Dynamic Monte Carlo study of isolated-gate InAs/AlSb HEMTs
International Nuclear Information System (INIS)
Rodilla, H; González, T; Mateos, J; Moschetti, G; Grahn, J
2011-01-01
In this work, by means of Monte Carlo simulations, the static and dynamic behavior of isolated-gate InAs/AlSb high electron mobility transistors (Sb-HEMTs) has been studied and compared with experimental results. The influence of the existence of a native oxide under the gate, the value of the surface charges in the gate recess and the possible variation of electron sheet carrier density, n s , have been studied. A decrease in the gate-source capacitance, transconductance and intrinsic cutoff frequency is observed because of the presence of the native oxide, while changes in the value of the surface charges in the recess only introduce a threshold voltage shift. The increase of n s shifts the maximum of the transconductance and intrinsic cutoff frequency to higher values of drain current and improves the agreement with the experimental results
Semiclassical Monte Carlo: A first principles approach to non-adiabatic molecular dynamics
International Nuclear Information System (INIS)
White, Alexander J.; Gorshkov, Vyacheslav N.; Wang, Ruixi; Tretiak, Sergei; Mozyrsky, Dmitry
2014-01-01
Modeling the dynamics of photophysical and (photo)chemical reactions in extended molecular systems is a new frontier for quantum chemistry. Many dynamical phenomena, such as intersystem crossing, non-radiative relaxation, and charge and energy transfer, require a non-adiabatic description which incorporate transitions between electronic states. Additionally, these dynamics are often highly sensitive to quantum coherences and interference effects. Several methods exist to simulate non-adiabatic dynamics; however, they are typically either too expensive to be applied to large molecular systems (10's-100's of atoms), or they are based on ad hoc schemes which may include severe approximations due to inconsistencies in classical and quantum mechanics. We present, in detail, an algorithm based on Monte Carlo sampling of the semiclassical time-dependent wavefunction that involves running simple surface hopping dynamics, followed by a post-processing step which adds little cost. The method requires only a few quantities from quantum chemistry calculations, can systematically be improved, and provides excellent agreement with exact quantum mechanical results. Here we show excellent agreement with exact solutions for scattering results of standard test problems. Additionally, we find that convergence of the wavefunction is controlled by complex valued phase factors, the size of the non-adiabatic coupling region, and the choice of sampling function. These results help in determining the range of applicability of the method, and provide a starting point for further improvement
Nedea, S.V.; Frijns, A.J.H.; Steenhoven, van A.A.; Markvoort, Albert. J.; Hilbers, P.A.J.
2005-01-01
We combine molecular dynamics (MD) and Monte Carlo (MC) simulations to study the properties of gas molecules confined between two hard walls of a microchannel or nanochannel. The coupling between MD and MC simulations is introduced by performing MD near the boundaries for accuracy and MC in the bulk
Monte Carlo simulation of the Varian Clinac 600C accelerator dynamic and physical wedges
Energy Technology Data Exchange (ETDEWEB)
Soares, S [Universidade da Beira Interior, Av. Marques d' Avila e Bolama, Covilha 6201-001 (Portugal); Chaves, A [Instituto Portugues de Oncologia Doutor Francisco Gentil (IPO), Av. Bissaya Barreto, Coimbra 3000-075 (Portugal); Peralta, L [Laboratorio de Instrumentacao e Fisica Experimental de PartIculas (LIP), Av. Elias Garcia no14 1o, Lisbon 1000-149 (Portugal); Lopes, Mc [Faculdade de Ciencias da Universidade de Lisboa, Campo Grande EdifIcio C5, Lisbon 1149-016 (Portugal)
2007-06-15
The present paper describes the study done on the dosimetric characteristics of the Varian Clinac 600C dynamic wedges (DW) and their comparison with the physical wedges (PW) in terms of the differences affecting the dose distributions, beam spectra, energy fluence and angular distributions. The geometry of the 4 MV photon beam and the dose distributions in a water phantom were simulated with GEANT3 and DPM Monte Carlo code systems. The DW was modelled through the constant movement of the upper jaws. The depth dose distributions and lateral profiles for the DW, PW and open fields were measured and compared with the Monte Carlo simulations and the global agreement was found to be within 3%. It was also found that the effects of a DW on beam spectral and angular distributions are much less significant than those produced by a PW. For example, in our study we found out that the 45{sup 0}PW, when compared with the corresponding open field, can introduce a 30% increase in the mean photon energy due to the beam hardening effect and that it can also introduce a 4.5% dose reduction in the build-up region because of the reduction of the contaminated electrons by the PW. For the DW neither this mean-energy increase nor such dose reduction was found. The PW, when compared to the DW, significantly alters the photon-beam spectrum and these dosimetric differences are significant and further investigation must be performed to quantify the impact in clinical use of these beams.
Monte Carlo algorithms with absorbing Markov chains: Fast local algorithms for slow dynamics
International Nuclear Information System (INIS)
Novotny, M.A.
1995-01-01
A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest order of these algorithms reduces to the n-fold way algorithm. These algorithms are applied to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field, and the agreement with theoretical predictions is very good. It is demonstrated that the higher-order algorithms can be many orders of magnitude faster than either the traditional Monte Carlo or n-fold way algorithms
Monte Carlo Methods in Physics
International Nuclear Information System (INIS)
Santoso, B.
1997-01-01
Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained
Huang, B. Y.; Lu, Z. X.; Zhang, Y.; Xie, Y. L.; Zeng, M.; Yan, Z. B.; Liu, J.-M.
2016-05-01
The polarization-electric field hysteresis loops and the dynamics of polarization switching in a two-dimensional antiferroelectric (AFE) lattice submitted to a time-oscillating electric field E(t) of frequency f and amplitude E0, is investigated using Monte Carlo simulation based on the Landau-Devonshire phenomenological theory on antiferroelectrics. It is revealed that the AFE double-loop hysteresis area A, i.e., the energy loss in one cycle of polarization switching, exhibits the single-peak frequency dispersion A(f), suggesting the unique characteristic time for polarization switching, which is independent of E0 as long as E0 is larger than the quasi-static coercive field for the antiferroelectric-ferroelectric transitions. However, the dependence of recoverable stored energy W on amplitude E0 seems to be complicated depending on temperature T and frequency f. A dynamic scaling behavior of the energy loss dispersion A(f) over a wide range of E0 is obtained, confirming the unique characteristic time for polarization switching of an AFE lattice. The present simulation may shed light on the dynamics of energy storage and release in AFE thin films.
Quantum Monte Carlo approaches for correlated systems
Becca, Federico
2017-01-01
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...
Kanjilal, Oindrila; Manohar, C. S.
2017-07-01
The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.
A Monte Carlo dosimetric quality assurance system for dynamic intensity-modulated radiotherapy
International Nuclear Information System (INIS)
Takegawa, Hideki; Yamamoto, Tokihiro; Miyabe, Yuki; Teshima, Teruki; Kunugi, Tomoaki; Yano, Shinsuke; Mizowaki, Takashi; Nagata, Yasushi; Hiraoka, Masahiro
2005-01-01
We are developing a Monte Carlo (MC) dose calculation system, which can resolve dosimetric issues derived from multileaf collimator (MLC) design for routine dosimetric quality assurance (QA) of intensity-modulated radiotherapy (IMRT). The treatment head of the medical linear accelerator equipped with MLC was modeled using the EGS4 MC code. A graphical user interface (GUI) application was developed to implement MC dose computation in the CT-based patient model and compare the MC calculated results with those of a commercial radiotherapy treatment planning (RTP) system, Varian Eclipse. To reduce computation time, the EGS4 MC code has been parallelized on massive parallel processing (MPP) system using the message passing interface (MPI). The MC treatment head model and MLC model were validated by the measurement data sets of percentage depth dose (PDD) and off-center ratio (OCR) in the water phantom and the film measurements for the static and dynamic test patterns, respectively. In the treatment head model, the MC calculated results agreed with those of measurements for both of PDD and OCR. The MC could reproduce all of the MLC dosimetric effects. A quantitative comparison between the results of MC and Eclipse was successfully performed with the GUI application. Parallel speed-up became almost linear. An MC dosimetric QA system for dynamic IMRT has been developed, however there were large dose discrepancies between the MC and the measurement in the MLC model simulation, which are now being investigated. (author)
Chen, Yunjie; Kale, Seyit; Weare, Jonathan; Dinner, Aaron R; Roux, Benoît
2016-04-12
A multiple time-step integrator based on a dual Hamiltonian and a hybrid method combining molecular dynamics (MD) and Monte Carlo (MC) is proposed to sample systems in the canonical ensemble. The Dual Hamiltonian Multiple Time-Step (DHMTS) algorithm is based on two similar Hamiltonians: a computationally expensive one that serves as a reference and a computationally inexpensive one to which the workload is shifted. The central assumption is that the difference between the two Hamiltonians is slowly varying. Earlier work has shown that such dual Hamiltonian multiple time-step schemes effectively precondition nonlinear differential equations for dynamics by reformulating them into a recursive root finding problem that can be solved by propagating a correction term through an internal loop, analogous to RESPA. Of special interest in the present context, a hybrid MD-MC version of the DHMTS algorithm is introduced to enforce detailed balance via a Metropolis acceptance criterion and ensure consistency with the Boltzmann distribution. The Metropolis criterion suppresses the discretization errors normally associated with the propagation according to the computationally inexpensive Hamiltonian, treating the discretization error as an external work. Illustrative tests are carried out to demonstrate the effectiveness of the method.
An Event-Driven Hybrid Molecular Dynamics and Direct Simulation Monte Carlo Algorithm
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Donev, A; Garcia, A L; Alder, B J
2007-07-30
A novel algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses event-driven molecular dynamics (MD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.
Reactor physics simulations with coupled Monte Carlo calculation and computational fluid dynamics
International Nuclear Information System (INIS)
Seker, V.; Thomas, J. W.; Downar, T. J.
2007-01-01
The interest in high fidelity modeling of nuclear reactor cores has increased over the last few years and has become computationally more feasible because of the dramatic improvements in processor speed and the availability of low cost parallel platforms. In the research here high fidelity, multi-physics analyses was performed by solving the neutron transport equation using Monte Carlo methods and by solving the thermal-hydraulics equations using computational fluid dynamics. A computation tool based on coupling the Monte Carlo code MCNP5 and the Computational Fluid Dynamics (CFD) code STAR-CD was developed as an audit tool for lower order nuclear reactor calculations. This paper presents the methodology of the developed computer program 'McSTAR' along with the verification and validation efforts. McSTAR is written in PERL programming language and couples MCNP5 and the commercial CFD code STAR-CD. MCNP uses a continuous energy cross section library produced by the NJOY code system from the raw ENDF/B data. A major part of the work was to develop and implement methods to update the cross section library with the temperature distribution calculated by STAR-CD for every region. Three different methods were investigated and two of them are implemented in McSTAR. The user subroutines in STAR-CD are modified to read the power density data and assign them to the appropriate variables in the program and to write an output data file containing the temperature, density and indexing information to perform the mapping between MCNP and STAR-CD cells. The necessary input file manipulation, data file generation, normalization and multi-processor calculation settings are all done through the program flow in McSTAR. Initial testing of the code was performed using a single pin cell and a 3X3 PWR pin-cell problem. The preliminary results of the single pin-cell problem are compared with those obtained from a STAR-CD coupled calculation with the deterministic transport code De
COOL: A code for Dynamic Monte Carlo Simulation of molecular dynamics
Barletta, Paolo
2012-02-01
Cool is a program to simulate evaporative and sympathetic cooling for a mixture of two gases co-trapped in an harmonic potential. The collisions involved are assumed to be exclusively elastic, and losses are due to evaporation from the trap. Each particle is followed individually in its trajectory, consequently properties such as spatial densities or energy distributions can be readily evaluated. The code can be used sequentially, by employing one output as input for another run. The code can be easily generalised to describe more complicated processes, such as the inclusion of inelastic collisions, or the possible presence of more than two species in the trap. New version program summaryProgram title: COOL Catalogue identifier: AEHJ_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHJ_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1 097 733 No. of bytes in distributed program, including test data, etc.: 18 425 722 Distribution format: tar.gz Programming language: C++ Computer: Desktop Operating system: Linux RAM: 500 Mbytes Classification: 16.7, 23 Catalogue identifier of previous version: AEHJ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 388 Does the new version supersede the previous version?: Yes Nature of problem: Simulation of the sympathetic process occurring for two molecular gases co-trapped in a deep optical trap. Solution method: The Direct Simulation Monte Carlo method exploits the decoupling, over a short time period, of the inter-particle interaction from the trapping potential. The particle dynamics is thus exclusively driven by the external optical field. The rare inter-particle collisions are considered with an acceptance/rejection mechanism, that is, by comparing a random number to the collisional probability
Lectures on Monte Carlo methods
Madras, Neal
2001-01-01
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati
International Nuclear Information System (INIS)
Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; Virginia Polytechnic Institute and State University; Savara, Aditya
2017-01-01
Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of “KMC stiffness” (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps / cpu-time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order to achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events -- allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm designed for use in achieving and simulating steady-state conditions in KMC simulations. Lastly, as shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.
Energy Technology Data Exchange (ETDEWEB)
Bousige, Colin; Boţan, Alexandru; Coasne, Benoît, E-mail: coasne@mit.edu [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Ulm, Franz-Josef [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Pellenq, Roland J.-M. [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); CINaM, CNRS/Aix Marseille Université, Campus de Luminy, 13288 Marseille Cedex 09 (France)
2015-03-21
We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.
Waseda, O.; Goldenstein, H.; Silva, G. F. B. Lenz e.; Neiva, A.; Chantrenne, P.; Morthomas, J.; Perez, M.; Becquart, C. S.; Veiga, R. G. A.
2017-10-01
The thermal stability of nanocrystalline Ni due to small additions of Mo or W (up to 1 at%) was investigated in computer simulations by means of a combined Monte Carlo (MC)/molecular dynamics (MD) two-steps approach. In the first step, energy-biased on-lattice MC revealed segregation of the alloying elements to grain boundaries. However, the condition for the thermodynamic stability of these nanocrystalline Ni alloys (zero grain boundary energy) was not fulfilled. Subsequently, MD simulations were carried out for up to 0.5 μs at 1000 K. At this temperature, grain growth was hindered for minimum global concentrations of 0.5 at% W and 0.7 at% Mo, thus preserving most of the nanocrystalline structure. This is in clear contrast to a pure Ni model system, for which the transformation into a monocrystal was observed in MD simulations within 0.2 μs at the same temperature. These results suggest that grain boundary segregation of low-soluble alloying elements in low-alloyed systems can produce high-temperature metastable nanocrystalline materials. MD simulations carried out at 1200 K for 1 at% Mo/W showed significant grain boundary migration accompanied by some degree of solute diffusion, thus providing additional evidence that solute drag mostly contributed to the nanostructure stability observed at lower temperature.
Monte Carlo calculations with dynamical fermions by a local stochastic process
International Nuclear Information System (INIS)
Rossi, P.; Zwanziger, D.
1984-01-01
We develop and test numerically a Monte Carlo method for fermions on a lattice which accounts for the effect of the fermionic determinant to arbitrary accuracy. It is tested numerically in a 4-dimensional model with SU(2) color group and scalar fermionic quarks interacting with gluons. Computer time grows linearly with the volume of the lattice and the updating of gluons is not restricted to small jumps. The method is based on random location updating, instead of an ordered sweep, in which quarks are updated, on the average, R times more frequently than gluons. It is proven that the error in R is only of order 1/R instead of 1/Rsup(1/2) as one might naively expect. Quarks are represented by pseudofermionic variables in M pseudoflavors (which requires M times more memory for each physical fermionic degree of freedom) with an error in M of order 1/M. The method is tested by calculating the self-energy of an external quark, a quantity which would be infinite in the absence of dynamical or sea quarks. For the quantities measured, the dependence on R -1 is linear for R >= 8, and, within our statistical uncertainty, M = 2 is already asymptotic. (orig.)
Pandey, R. B.; Jacobs, D. J.; Farmer, B. L.
2017-05-01
The effect of preferential binding of solute molecules within an aqueous solution on the structure and dynamics of the histone H3.1 protein is examined by a coarse-grained Monte Carlo simulation. The knowledge-based residue-residue and hydropathy-index-based residue-solvent interactions are used as input to analyze a number of local and global physical quantities as a function of the residue-solvent interaction strength (f). Results from simulations that treat the aqueous solution as a homogeneous effective solvent medium are compared to when positional fluctuations of the solute molecules are explicitly considered. While the radius of gyration (Rg) of the protein exhibits a non-monotonic dependence on solvent interaction over a wide range of f within an effective medium, an abrupt collapse in Rg occurs in a narrow range of f when solute molecules rapidly bind to a preferential set of sites on the protein. The structure factor S(q) of the protein with wave vector (q) becomes oscillatory in the collapsed state, which reflects segmental correlations caused by spatial fluctuations in solute-protein binding. Spatial fluctuations in solute binding also modify the effective dimension (D) of the protein in fibrous (D ˜ 1.3), random-coil (D ˜ 1.75), and globular (D ˜ 3) conformational ensembles as the interaction strength increases, which differ from an effective medium with respect to the magnitude of D and the length scale.
A dynamic Monte Carlo study of anomalous current voltage behaviour in organic solar cells
International Nuclear Information System (INIS)
Feron, K.; Fell, C. J.; Zhou, X.; Belcher, W. J.; Dastoor, P. C.
2014-01-01
We present a dynamic Monte Carlo (DMC) study of s-shaped current-voltage (I-V) behaviour in organic solar cells. This anomalous behaviour causes a substantial decrease in fill factor and thus power conversion efficiency. We show that this s-shaped behaviour is induced by charge traps that are located at the electrode interface rather than in the bulk of the active layer, and that the anomaly becomes more pronounced with increasing trap depth or density. Furthermore, the s-shape anomaly is correlated with interface recombination, but not bulk recombination, thus highlighting the importance of controlling the electrode interface. While thermal annealing is known to remove the s-shape anomaly, the reason has been not clear, since these treatments induce multiple simultaneous changes to the organic solar cell structure. The DMC modelling indicates that it is the removal of aluminium clusters at the electrode, which act as charge traps, that removes the anomalous I-V behaviour. Finally, this work shows that the s-shape becomes less pronounced with increasing electron-hole recombination rate; suggesting that efficient organic photovoltaic material systems are more susceptible to these electrode interface effects
Liu, Gui-Bin; Liu, Bang-Gui
2010-10-01
In this paper, we combine thermal effects with Landau-Zener (LZ) quantum tunneling effects in a dynamical Monte Carlo (DMC) framework to produce satisfactory magnetization curves of single-molecule magnet (SMM) systems. We use the giant spin approximation for SMM spins and consider regular lattices of SMMs with magnetic dipolar interactions (MDIs). We calculate spin-reversal probabilities from thermal-activated barrier hurdling, direct LZ tunneling, and thermal-assisted LZ tunnelings in the presence of sweeping magnetic fields. We do systematical DMC simulations for Mn12 systems with various temperatures and sweeping rates. Our simulations produce clear step structures in low-temperature magnetization curves, and our results show that the thermally activated barrier hurdling becomes dominating at high temperature near 3 K and the thermal-assisted tunnelings play important roles at intermediate temperature. These are consistent with corresponding experimental results on good Mn12 samples (with less disorders) in the presence of little misalignments between the easy axis and applied magnetic fields, and therefore our magnetization curves are satisfactory. Furthermore, our DMC results show that the MDI, with the thermal effects, have important effects on the LZ tunneling processes, but both the MDI and the LZ tunneling give place to the thermal-activated barrier hurdling effect in determining the magnetization curves when the temperature is near 3 K. This DMC approach can be applicable to other SMM systems and could be used to study other properties of SMM systems.
Plasma excitation processes in flue gas simulated with Monte Carlo electron dynamics
Energy Technology Data Exchange (ETDEWEB)
Tas, M.A.; Veldhuizen, E.M. van; Rutgers, W.R. [Eindhoven University of Technology (Netherlands). Div. of Electrical Energy Systems
1997-06-07
The excitation of gas molecules in flue gas by electron impact is calculated with a Monte Carlo (MC) algorithm for electron dynamics in partially ionized gases. The MC algorithm is straightforward for any mixture of molecules for which cross sections are available. Electron drift is simulated in the first case for homogeneous electric fields and in the second case for secondary electrons which are produced by electron-beam irradiation. The electron energy distribution function {epsilon}-bar{sub {theta}}, V-bar{sub d}, {lambda}-bar, the energy branching and the rate of excitation are calculated for standard gas mixtures of Ar-N{sub 2}, O{sub 2} and H{sub 2}O. These fundamental process parameters are needed for the study of reactions to remove NO{sub x} from flue gas. The calculated results indicate that the production of highly excited molecules in the high electric field of a streamer corona discharge has an efficiency similar to that of electron-beam irradiation. (author)
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.
Yang, Qian; Sing-Long, Carlos A; Reed, Evan J
2017-08-01
We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.
Advanced Multilevel Monte Carlo Methods
Jasra, Ajay; Law, Kody; Suciu, Carina
2017-01-01
This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.
Advanced Multilevel Monte Carlo Methods
Jasra, Ajay
2017-04-24
This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.
Monte Carlo simulation for IRRMA
International Nuclear Information System (INIS)
Gardner, R.P.; Liu Lianyan
2000-01-01
Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-03-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.
Adjoint electron Monte Carlo calculations
International Nuclear Information System (INIS)
Jordan, T.M.
1986-01-01
Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment
Monte Carlo theory and practice
International Nuclear Information System (INIS)
James, F.
1987-01-01
Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem
Suh, Donghyuk; Radak, Brian K.; Chipot, Christophe; Roux, Benoît
2018-01-01
Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield
Lim, J. T.; Gold, H. J.; Wilkerson, G. G.; Raper, C. D. Jr; Raper CD, J. r. (Principal Investigator)
1989-01-01
We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. The analysis provides insights as to the relative importance of certain physiological processes in controlling plant growth. Advantages and disadvantages of the strategy are discussed.
International Nuclear Information System (INIS)
Mayer, M.; Arstila, K.; Nordlund, K.; Edelmann, E.; Keinonen, J.
2006-01-01
Angular and energy distributions due to multiple small angle scattering were calculated with different models, namely from the analytical Szilagyi theory, the Monte-Carlo code MCERD in binary collision approximation and the molecular dynamics code MDRANGE, for 2 MeV 4 He in Au at backscattering geometry and for 20 MeV 127 I recoil analysis of carbon. The widths and detailed shapes of the distributions are compared, and reasons for deviations between the different models are discussed
Energy Technology Data Exchange (ETDEWEB)
Moreno, S. [Universidade da Beira Interior (UBI), Covilha (Portugal); Chaves, A.; Lopes, M.C. [Instituto Portugues de Oncologia Doutor Francisco Gentil (IPO), Coimbra (Portugal); Peralta, L. [Laboratorio de Instrumentacao e Fisica Experimental de Particulas (LIP), Lisboa (Portugal)]|[Universidade de Lisboa (Portugal). Faculdade de Ciencias
2004-07-01
The advent of linear accelerators (linac) with computer-controlled dynamic collimation systems and functional and anatomical imaging techniques allowed a more exact delimitation and localisation of the target volume. These advanced treatment techniques inevitably increase the complexity level of dose calculation because of the introduction of the temporal variable. On account of this, it is mandatory the usage of more accurate modelling techniques of the collimator components, as it is the case of Monte Carlo (MC) simulation, which has created an enormous interest in research and clinical practice. Because the patients bodies are not homogenous nor are their body surfaces plane and regular, the dose distribution may differ significantly from the standard distribution from the linac calibration. It is in the treatment planning systems, which include algorithms that are usually measured in homogeneous water phantoms specific for each correction that the dose distributions from each case are obtained. In a real treatment, exception made to superficial lesions, two or more radiation fields are used in order to obtain the recommended dose distributions. The simplest arrangement is made from two parallel and opposed fields that originate a homogeneous dose distribution in almost all the irradiated volume. The available resources are, for example, different types of energies and of radiation, the application of bolus, the protection of healthy structures, the usage of wedged filters and the application of dynamic wedges. A virtual or dynamic wedge, modelled through the movement of one of the jaws, when compared with a set of physical wedges offers an alternative calculation method of an arbitrary number of wedged fields, instead of the four traditional fields of 15 deg, 30 deg, 45 deg and 60 deg angle and obtained with physical wedges. The goal of this work consists in the study of the application of dynamic wedges in tailoring the radiation field by the Varian Clinac 600
Monte Carlo simulation of the Varian Clinac 600C accelerator using dynamic wedges
International Nuclear Information System (INIS)
Moreno, S.; Chaves, A.; Lopes, M.C.; Peralta, L.; Universidade de Lisboa
2004-01-01
The advent of linear accelerators (linac) with computer-controlled dynamic collimation systems and functional and anatomical imaging techniques allowed a more exact delimitation and localisation of the target volume. These advanced treatment techniques inevitably increase the complexity level of dose calculation because of the introduction of the temporal variable. On account of this, it is mandatory the usage of more accurate modelling techniques of the collimator components, as it is the case of Monte Carlo (MC) simulation, which has created an enormous interest in research and clinical practice. Because the patients bodies are not homogenous nor are their body surfaces plane and regular, the dose distribution may differ significantly from the standard distribution from the linac calibration. It is in the treatment planning systems, which include algorithms that are usually measured in homogeneous water phantoms specific for each correction that the dose distributions from each case are obtained. In a real treatment, exception made to superficial lesions, two or more radiation fields are used in order to obtain the recommended dose distributions. The simplest arrangement is made from two parallel and opposed fields that originate a homogeneous dose distribution in almost all the irradiated volume. The available resources are, for example, different types of energies and of radiation, the application of bolus, the protection of healthy structures, the usage of wedged filters and the application of dynamic wedges. A virtual or dynamic wedge, modelled through the movement of one of the jaws, when compared with a set of physical wedges offers an alternative calculation method of an arbitrary number of wedged fields, instead of the four traditional fields of 15 deg, 30 deg, 45 deg and 60 deg angle and obtained with physical wedges. The goal of this work consists in the study of the application of dynamic wedges in tailoring the radiation field by the Varian Clinac 600
International Nuclear Information System (INIS)
Valkealahti, Seppo.
1987-10-01
Monte Carlo simulation is used to investigate positron and electron slowing down in solid matter. The description of elastic scattering is based on accurate cross sections of effective crystalline atom potentials. Inelastic processes are described separately for each energby level y Gryzinski's excitation function. Various materials are studied and several electron and positron slowing down parameters and distributions are extracted. The results are used to analyze and interprete a number of recent experiments utilizing keV electron and positron beams. Molecular dynamics simulation methods are used to study (i) damage production in aluminum (110) surfaces due to low-energy argon ion bombardment and (ii) the premelting effects of solid noble gas surfaces. Appropriately constructed pair potentials were assigned between the particles and an electronic friction term proportional to the velocity was used for energetic ions. Of particular interest in (i) are the defect and implanted atom distributions, which are compared against recent experiments. In (ii) the simulations show the equilibrium existence of liquid-like layers on the densely packed surfaces well below the bulk melting temperature. In (i) the mean vacancy concentration depth depends only slightly on the incident angle. The total number of vacancies is almost independent of the incident ion dose for very oblique angles of incidence (0>45 deg C). Vancancy profile is found to have a clear peak in the topmost atomic layers and a broader tail deep in the material. The interstitial and Ar + ion profiles are clearly deeper in the material than the vacancy profile. In (ii), a layer-by-layer premelting of Lennard-Jones (111) surfaces is observed. Also the (100) surfaces premelt, but the disordering mechanism for the loosely packed (110) surfaces is roughening. Furthermore, a general rule seems to be that melting proceeds along the directions of high packing densities
SU-E-T-238: Monte Carlo Estimation of Cerenkov Dose for Photo-Dynamic Radiotherapy
Energy Technology Data Exchange (ETDEWEB)
Chibani, O; Price, R; Ma, C [Fox Chase Cancer Center, Philadelphia, PA (United States); Eldib, A [Fox Chase Cancer Center, Philadelphia, PA (United States); University Cairo (Egypt); Mora, G [de Lisboa, Codex, Lisboa (Portugal)
2014-06-01
Purpose: Estimation of Cerenkov dose from high-energy megavoltage photon and electron beams in tissue and its impact on the radiosensitization using Protoporphyrine IX (PpIX) for tumor targeting enhancement in radiotherapy. Methods: The GEPTS Monte Carlo code is used to generate dose distributions from 18MV Varian photon beam and generic high-energy (45-MV) photon and (45-MeV) electron beams in a voxel-based tissueequivalent phantom. In addition to calculating the ionization dose, the code scores Cerenkov energy released in the wavelength range 375–425 nm corresponding to the pick of the PpIX absorption spectrum (Fig. 1) using the Frank-Tamm formula. Results: The simulations shows that the produced Cerenkov dose suitable for activating PpIX is 4000 to 5500 times lower than the overall radiation dose for all considered beams (18MV, 45 MV and 45 MeV). These results were contradictory to the recent experimental studies by Axelsson et al. (Med. Phys. 38 (2011) p 4127), where Cerenkov dose was reported to be only two orders of magnitude lower than the radiation dose. Note that our simulation results can be corroborated by a simple model where the Frank and Tamm formula is applied for electrons with 2 MeV/cm stopping power generating Cerenkov photons in the 375–425 nm range and assuming these photons have less than 1mm penetration in tissue. Conclusion: The Cerenkov dose generated by high-energy photon and electron beams may produce minimal clinical effect in comparison with the photon fluence (or dose) commonly used for photo-dynamic therapy. At the present time, it is unclear whether Cerenkov radiation is a significant contributor to the recently observed tumor regression for patients receiving radiotherapy and PpIX versus patients receiving radiotherapy only. The ongoing study will include animal experimentation and investigation of dose rate effects on PpIX response.
Directory of Open Access Journals (Sweden)
Kecheng Yang
Full Text Available Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE, is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD-Monte Carlo (MC approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.
Chen, Yunjie; Roux, Benoît
2014-09-21
Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct
Chen, Yunjie; Roux, Benoît
2014-09-01
Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-01-01
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Accelerating staggered-fermion dynamics with the rational hybrid Monte Carlo algorithm
International Nuclear Information System (INIS)
Clark, M. A.; Kennedy, A. D.
2007-01-01
Improved staggered-fermion formulations are a popular choice for lattice QCD calculations. Historically, the algorithm used for such calculations has been the inexact R algorithm, which has systematic errors that only vanish as the square of the integration step size. We describe how the exact rational hybrid Monte Carlo (RHMC) algorithm may be used in this context, and show that for parameters corresponding to current state-of-the-art computations it leads to a factor of approximately seven decrease in cost as well as having no step-size errors
Monte Carlo methods and models in finance and insurance
Korn, Ralf; Kroisandt, Gerald
2010-01-01
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...
International Nuclear Information System (INIS)
Apetrei, Alin Marian; Enachescu, Cristian; Tanasa, Radu; Stoleriu, Laurentiu; Stancu, Alexandru
2010-01-01
We apply here the Monte Carlo Metropolis method to a known atom-phonon coupling model for 1D spin transition compounds (STC). These inorganic molecular systems can switch under thermal or optical excitation, between two states in thermodynamical competition, i.e. high spin (HS) and low spin (LS). In the model, the ST units (molecules) are linked by springs, whose elastic constants depend on the spin states of the neighboring atoms, and can only have three possible values. Several previous analytical papers considered a unique average value for the elastic constants (mean-field approximation) and obtained phase diagrams and thermal hysteresis loops. Recently, Monte Carlo simulation papers, taking into account all three values of the elastic constants, obtained thermal hysteresis loops, but no phase diagrams. Employing Monte Carlo simulation, in this work we obtain the phase diagram at T=0 K, which is fully consistent with earlier analytical work; however it is more complex. The main difference is the existence of two supplementary critical curves that mark a hysteresis zone in the phase diagram. This explains the pressure hysteresis curves at low temperature observed experimentally and predicts a 'chemical' hysteresis in STC at very low temperatures. The formation and the dynamics of the domains are also discussed.
Strategije drevesnega preiskovanja Monte Carlo
VODOPIVEC, TOM
2018-01-01
Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...
Variational Monte Carlo Technique
Indian Academy of Sciences (India)
ias
on the development of nuclear weapons in Los Alamos ..... cantly improved the paper. ... Carlo simulations of solids, Reviews of Modern Physics, Vol.73, pp.33– ... The computer algorithms are usually based on a random seed that starts the ...
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....
Monte Carlo simulation of the microcanonical ensemble
International Nuclear Information System (INIS)
Creutz, M.
1984-01-01
We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references
Is Monte Carlo embarrassingly parallel?
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)
2012-07-01
Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)
Is Monte Carlo embarrassingly parallel?
International Nuclear Information System (INIS)
Hoogenboom, J. E.
2012-01-01
Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)
Exact Monte Carlo for molecules
International Nuclear Information System (INIS)
Lester, W.A. Jr.; Reynolds, P.J.
1985-03-01
A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H 2 , and the singlet-triplet splitting in methylene are presented and discussed. 17 refs
Monte Carlo - Advances and Challenges
International Nuclear Information System (INIS)
Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.
2008-01-01
Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature
Cozmuta, Ioana; Blanco, Mario; Goddard, William A
2007-03-29
It is important for many industrial processes to design new materials with improved selective permeability properties. Besides diffusion, the molecule's solubility contributes largely to the overall permeation process. This study presents a method to calculate solubility coefficients of gases such as O2, H2O (vapor), N2, and CO2 in polymeric matrices from simulation methods (Molecular Dynamics and Monte Carlo) using first principle predictions. The generation and equilibration (annealing) of five polymer models (polypropylene, polyvinyl alcohol, polyvinyl dichloride, polyvinyl chloride-trifluoroethylene, and polyethylene terephtalate) are extensively described. For each polymer, the average density and Hansen solubilities over a set of ten samples compare well with experimental data. For polyethylene terephtalate, the average properties between a small (n = 10) and a large (n = 100) set are compared. Boltzmann averages and probability density distributions of binding and strain energies indicate that the smaller set is biased in sampling configurations with higher energies. However, the sample with the lowest cohesive energy density from the smaller set is representative of the average of the larger set. Density-wise, low molecular weight polymers tend to have on average lower densities. Infinite molecular weight samples do however provide a very good representation of the experimental density. Solubility constants calculated with two ensembles (grand canonical and Henry's constant) are equivalent within 20%. For each polymer sample, the solubility constant is then calculated using the faster (10x) Henry's constant ensemble (HCE) from 150 ps of NPT dynamics of the polymer matrix. The influence of various factors (bad contact fraction, number of iterations) on the accuracy of Henry's constant is discussed. To validate the calculations against experimental results, the solubilities of nitrogen and carbon dioxide in polypropylene are examined over a range of
Many-Body Quantum Spin Dynamics with Monte Carlo Trajectories on a Discrete Phase Space
Directory of Open Access Journals (Sweden)
J. Schachenmayer
2015-02-01
Full Text Available Interacting spin systems are of fundamental relevance in different areas of physics, as well as in quantum information science and biology. These spin models represent the simplest, yet not fully understood, manifestation of quantum many-body systems. An important outstanding problem is the efficient numerical computation of dynamics in large spin systems. Here, we propose a new semiclassical method to study many-body spin dynamics in generic spin lattice models. The method is based on a discrete Monte Carlo sampling in phase space in the framework of the so-called truncated Wigner approximation. Comparisons with analytical and numerically exact calculations demonstrate the power of the technique. They show that it correctly reproduces the dynamics of one- and two-point correlations and spin squeezing at short times, thus capturing entanglement. Our results open the possibility to study the quantum dynamics accessible to recent experiments in regimes where other numerical methods are inapplicable.
(U) Introduction to Monte Carlo Methods
Energy Technology Data Exchange (ETDEWEB)
Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-20
Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.
Carleo, Giuseppe; Cevolani, Lorenzo; Sanchez-Palencia, Laurent; Holzmann, Markus
2017-07-01
We introduce the time-dependent variational Monte Carlo method for continuous-space Bose gases. Our approach is based on the systematic expansion of the many-body wave function in terms of multibody correlations and is essentially exact up to adaptive truncation. The method is benchmarked by comparison to an exact Bethe ansatz or existing numerical results for the integrable Lieb-Liniger model. We first show that the many-body wave function achieves high precision for ground-state properties, including energy and first-order as well as second-order correlation functions. Then, we study the out-of-equilibrium, unitary dynamics induced by a quantum quench in the interaction strength. Our time-dependent variational Monte Carlo results are benchmarked by comparison to exact Bethe ansatz results available for a small number of particles, and are also compared to quench action results available for noninteracting initial states. Moreover, our approach allows us to study large particle numbers and general quench protocols, previously inaccessible beyond the mean-field level. Our results suggest that it is possible to find correlated initial states for which the long-term dynamics of local density fluctuations is close to the predictions of a simple Boltzmann ensemble.
Isotopic depletion with Monte Carlo
International Nuclear Information System (INIS)
Martin, W.R.; Rathkopf, J.A.
1996-06-01
This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation
Zimmerman, George B.
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
International Nuclear Information System (INIS)
Zimmerman, G.B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics
International Nuclear Information System (INIS)
Zimmerman, George B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.; Dean, D.J.; Langanke, K.
1997-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) 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, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)
A contribution Monte Carlo method
International Nuclear Information System (INIS)
Aboughantous, C.H.
1994-01-01
A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.
1996-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
Parallel Monte Carlo reactor neutronics
International Nuclear Information System (INIS)
Blomquist, R.N.; Brown, F.B.
1994-01-01
The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved
Elements of Monte Carlo techniques
International Nuclear Information System (INIS)
Nagarajan, P.S.
2000-01-01
The Monte Carlo method is essentially mimicking the real world physical processes at the microscopic level. With the incredible increase in computing speeds and ever decreasing computing costs, there is widespread use of the method for practical problems. The method is used in calculating algorithm-generated sequences known as pseudo random sequence (prs)., probability density function (pdf), test for randomness, extension to multidimensional integration etc
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).
Geometrical splitting in Monte Carlo
International Nuclear Information System (INIS)
Dubi, A.; Elperin, T.; Dudziak, D.J.
1982-01-01
A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs
Extending canonical Monte Carlo methods
International Nuclear Information System (INIS)
Velazquez, L; Curilef, S
2010-01-01
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 α with α≈0.2 for the particular case of the 2D ten-state Potts model
International Nuclear Information System (INIS)
Mercier, B.
1985-04-01
We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems
International Nuclear Information System (INIS)
Kennedy, D.C. II.
1987-01-01
This is an update on the progress of the BREMMUS Monte Carlo simulator, particularly in its current incarnation, BREM5. The present report is intended only as a follow-up to the Mark II/Granlibakken proceedings, and those proceedings should be consulted for a complete description of the capabilities and goals of the BREMMUS program. The new BREM5 program improves on the previous version of BREMMUS, BREM2, in a number of important ways. In BREM2, the internal loop (oblique) corrections were not treated in consistent fashion, a deficiency that led to renormalization scheme-dependence; i.e., physical results, such as cross sections, were dependent on the method used to eliminate infinities from the theory. Of course, this problem cannot be tolerated in a Monte Carlo designed for experimental use. BREM5 incorporates a new way of treating the oblique corrections, as explained in the Granlibakken proceedings, that guarantees renormalization scheme-independence and dramatically simplifies the organization and calculation of radiative corrections. This technique is to be presented in full detail in a forthcoming paper. BREM5 is, at this point, the only Monte Carlo to contain the entire set of one-loop corrections to electroweak four-fermion processes and renormalization scheme-independence. 3 figures
Statistical implications in Monte Carlo depletions - 051
International Nuclear Information System (INIS)
Zhiwen, Xu; Rhodes, J.; Smith, K.
2010-01-01
As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)
Sampling from a polytope and hard-disk Monte Carlo
International Nuclear Information System (INIS)
Kapfer, Sebastian C; Krauth, Werner
2013-01-01
The hard-disk problem, the statics and the dynamics of equal two-dimensional hard spheres in a periodic box, has had a profound influence on statistical and computational physics. Markov-chain Monte Carlo and molecular dynamics were first discussed for this model. Here we reformulate hard-disk Monte Carlo algorithms in terms of another classic problem, namely the sampling from a polytope. Local Markov-chain Monte Carlo, as proposed by Metropolis et al. in 1953, appears as a sequence of random walks in high-dimensional polytopes, while the moves of the more powerful event-chain algorithm correspond to molecular dynamics evolution. We determine the convergence properties of Monte Carlo methods in a special invariant polytope associated with hard-disk configurations, and the implications for convergence of hard-disk sampling. Finally, we discuss parallelization strategies for event-chain Monte Carlo and present results for a multicore implementation
GATE Monte Carlo simulation in radiation therapy for complex and dynamic beams in IMRT
International Nuclear Information System (INIS)
Benhalouche, Saadia
2014-01-01
Radiotherapy is one of the three methods of cancer treatment along with surgery and chemotherapy. It has evolved with the development of treatment techniques such as IMRT and VMAT along with IGRT for patient positioning. The aim is to effectively treat tumors while limiting the dose to healthy organs. In our work, we use the GATE Monte Carlo simulation platform to model a LINAC for a 6 MV photon beam. The resulting model is then validated with a dosimetric study by calculating relevant parameters for the beam quality. The LINAC model is then used for simulating clinical IMRT treatment plans in the ORL domain. Simulation results are compared with experimental measurements. We also explored the possibility of modeling the LINAC portal imaging system. This technique referred to as MV-CBCT combine the LINAC source with a flat panel detector to acquire 3D images of the patient. This part was validated first by acquiring 2D projections on patient and anthropomorphic phantom, and by reconstructing 3D volumes. Here again, validation was performed by comparing simulated and actual images. As a second step, a dosimetric validation was done by evaluating the dose deposited by IMRT beams, by means of portal signal only. We show in the present work the ability of GATE to perform complex IMRT treatments and portal images as they are performed routinely for dosimetric quality control. (author) [fr
Monte Carlo simulation of experiments
International Nuclear Information System (INIS)
Opat, G.I.
1977-07-01
An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)
Gukelberger, Jan; Kozik, Evgeny; Hafermann, Hartmut
2017-07-01
The dual fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations, however, neglect higher-order interaction vertices beyond two-particle scattering in the dual effective action and further truncate the diagrammatic expansion in the two-particle scattering vertex to a leading-order or ladder-type approximation. In this work, we compute the dual fermion expansion for the two-dimensional Hubbard model including all diagram topologies with two-particle interactions to high orders by means of a stochastic diagrammatic Monte Carlo algorithm. We benchmark the obtained self-energy against numerically exact diagrammatic determinant Monte Carlo simulations to systematically assess convergence of the dual fermion series and the validity of these approximations. We observe that, from high temperatures down to the vicinity of the DMFT Néel transition, the dual fermion series converges very quickly to the exact solution in the whole range of Hubbard interactions considered (4 ≤U /t ≤12 ), implying that contributions from higher-order vertices are small. As the temperature is lowered further, we observe slower series convergence, convergence to incorrect solutions, and ultimately divergence. This happens in a regime where magnetic correlations become significant. We find, however, that the self-consistent particle-hole ladder approximation yields reasonable and often even highly accurate results in this regime.
Edison, John R; Monson, Peter A
2013-06-21
This article addresses the accuracy of a dynamic mean field theory (DMFT) for fluids in porous materials [P. A. Monson, J. Chem. Phys. 128, 084701 (2008)]. The theory is used to study the relaxation processes of fluids in pores driven by step changes made to a bulk reservoir in contact with the pore. We compare the results of the DMFT to those obtained by averaging over large numbers of dynamic Monte Carlo (DMC) simulation trajectories. The problem chosen for comparison is capillary condensation in slit pores, driven by step changes in the chemical potential in the bulk reservoir and involving a nucleation process via the formation of a liquid bridge. The principal difference between the DMFT results and DMC is the replacement of a distribution of nucleation times and location along the pore for the formation of liquid bridges by a single time and location. DMFT is seen to yield an otherwise qualitatively accurate description of the dynamic behavior.
Directory of Open Access Journals (Sweden)
Solène Desmée
2017-07-01
Full Text Available Abstract Background Joint models of longitudinal and time-to-event data are increasingly used to perform individual dynamic prediction of a risk of event. However the difficulty to perform inference in nonlinear models and to calculate the distribution of individual parameters has long limited this approach to linear mixed-effect models for the longitudinal part. Here we use a Bayesian algorithm and a nonlinear joint model to calculate individual dynamic predictions. We apply this approach to predict the risk of death in metastatic castration-resistant prostate cancer (mCRPC patients with frequent Prostate-Specific Antigen (PSA measurements. Methods A joint model is built using a large population of 400 mCRPC patients where PSA kinetics is described by a biexponential function and the hazard function is a PSA-dependent function. Using Hamiltonian Monte Carlo algorithm implemented in Stan software and the estimated population parameters in this population as priors, the a posteriori distribution of the hazard function is computed for a new patient knowing his PSA measurements until a given landmark time. Time-dependent area under the ROC curve (AUC and Brier score are derived to assess discrimination and calibration of the model predictions, first on 200 simulated patients and then on 196 real patients that are not included to build the model. Results Satisfying coverage probabilities of Monte Carlo prediction intervals are obtained for longitudinal and hazard functions. Individual dynamic predictions provide good predictive performances for landmark times larger than 12 months and horizon time of up to 18 months for both simulated and real data. Conclusions As nonlinear joint models can characterize the kinetics of biomarkers and their link with a time-to-event, this approach could be useful to improve patient’s follow-up and the early detection of most at risk patients.
Lee, Kyoung O; Holmes, Thomas W; Calderon, Adan F; Gardner, Robin P
2012-05-01
Using a Monte Carlo (MC) simulation, random walks were used for pebble tracking in a two-dimensional geometry in the presence of a biased gravity field. We investigated the effect of viscosity damping in the presence of random Gaussian fluctuations. The particle tracks were generated by Molecular Dynamics (MD) simulation for a Pebble Bed Reactor. The MD simulations were conducted in the interaction of noncohesive Hertz-Mindlin theory where the random walk MC simulation has a correlation with the MD simulation. This treatment can easily be extended to include the generation of transient gamma-ray spectra from a single pebble that contains a radioactive tracer. Then the inverse analysis thereof could be made to determine the uncertainty of the realistic measurement of transient positions of that pebble by any given radiation detection system designed for that purpose. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Feder, Rene; Frost, Frank; Mayr, Stefan G.; Neumann, Horst; Bundesmann, Carsten [Leibniz-Institut fuer Oberflaechenmodifizierung e.V., Leipzig (Germany)
2012-07-01
Ion beam sputter processes deliver some intrinsic features influencing the growing film properties. Utilisation of these features needs to know how primary ion properties and geometrical process conditions influence the energy and spatial distribution of the sputtered and scattered particles. Beside complex experiments simulations are helpful to explain the correlation between primary parameters and thin film properties. The paper presents first results of two simulation codes with completely different approaches: Monte Carlo (MC) calculations with help of the well known TRIM.SP code and Molecular Dynamics calculations with an in-house developed code. First results of both simulation principles are compared for Argon ion bombardment on a Silicon target. Furthermore, a special experimental setup is outlined for validation of modelling. The setup allows the variation of ion beam parameters (ion species, ion energy, ion incidence angle on the target) and the measurement of the properties of sputtered and scattered particles.
Lépinoux, J.; Sigli, C.
2018-01-01
In a recent paper, the authors showed how the clusters free energies are constrained by the coagulation probability, and explained various anomalies observed during the precipitation kinetics in concentrated alloys. This coagulation probability appeared to be a too complex function to be accurately predicted knowing only the cluster distribution in Cluster Dynamics (CD). Using atomistic Monte Carlo (MC) simulations, it is shown that during a transformation at constant temperature, after a short transient regime, the transformation occurs at quasi-equilibrium. It is proposed to use MC simulations until the system quasi-equilibrates then to switch to CD which is mean field but not limited by a box size like MC. In this paper, we explain how to take into account the information available before the quasi-equilibrium state to establish guidelines to safely predict the cluster free energies.
Monte Carlo Particle Lists: MCPL
DEFF Research Database (Denmark)
Kittelmann, Thomas; Klinkby, Esben Bryndt; Bergbäck Knudsen, Erik
2017-01-01
A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular...... simulation packages. Program summary: Program Title: MCPL. Program Files doi: http://dx.doi.org/10.17632/cby92vsv5g.1 Licensing provisions: CC0 for core MCPL, see LICENSE file for details. Programming language: C and C++ External routines/libraries: Geant4, MCNP, McStas, McXtrace Nature of problem: Saving...
Monte Carlo techniques in radiation therapy
Verhaegen, Frank
2013-01-01
Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...
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
International Nuclear Information System (INIS)
Alcaraz, Olga; Trullàs, Joaquim; Tahara, Shuta; Kawakita, Yukinobu; Takeda, Shin’ichi
2016-01-01
The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å −1 related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.
Energy Technology Data Exchange (ETDEWEB)
Alcaraz, Olga; Trullàs, Joaquim, E-mail: quim.trullas@upc.edu [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord UPC B4-B5, 08034 Barcelona (Spain); Tahara, Shuta [Department of Physics and Earth Sciences, Faculty of Science, University of the Ryukyus, Okinawa 903-0213 (Japan); Kawakita, Yukinobu [J-PARC Center, Japan Atomic Energy Agency (JAEA), Ibaraki 319-1195 (Japan); Takeda, Shin’ichi [Department of Physics, Faculty of Sciences, Kyushu University, Fukuoka 819-0395 (Japan)
2016-09-07
The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å{sup −1} related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.
Monte Carlo surface flux tallies
International Nuclear Information System (INIS)
Favorite, Jeffrey A.
2010-01-01
Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.
Monte Carlo simulations of neutron scattering instruments
International Nuclear Information System (INIS)
Aestrand, Per-Olof; Copenhagen Univ.; Lefmann, K.; Nielsen, K.
2001-01-01
A Monte Carlo simulation is an important computational tool used in many areas of science and engineering. The use of Monte Carlo techniques for simulating neutron scattering instruments is discussed. The basic ideas, techniques and approximations are presented. Since the construction of a neutron scattering instrument is very expensive, Monte Carlo software used for design of instruments have to be validated and tested extensively. The McStas software was designed with these aspects in mind and some of the basic principles of the McStas software will be discussed. Finally, some future prospects are discussed for using Monte Carlo simulations in optimizing neutron scattering experiments. (R.P.)
Kwan, Betty P.; O'Brien, T. Paul
2015-06-01
The Aerospace Corporation performed a study to determine whether static percentiles of AE9/AP9 can be used to approximate dynamic Monte Carlo runs for radiation analysis of spiral transfer orbits. Solar panel degradation is a major concern for solar-electric propulsion because solar-electric propulsion depends on the power output of the solar panel. Different spiral trajectories have different radiation environments that could lead to solar panel degradation. Because the spiral transfer orbits only last weeks to months, an average environment does not adequately address the possible transient enhancements of the radiation environment that must be accounted for in optimizing the transfer orbit trajectory. Therefore, to optimize the trajectory, an ensemble of Monte Carlo simulations of AE9/AP9 would normally be run for every spiral trajectory to determine the 95th percentile radiation environment. To avoid performing lengthy Monte Carlo dynamic simulations for every candidate spiral trajectory in the optimization, we found a static percentile that would be an accurate representation of the full Monte Carlo simulation for a representative set of spiral trajectories. For 3 LEO to GEO and 1 LEO to MEO trajectories, a static 90th percentile AP9 is a good approximation of the 95th percentile fluence with dynamics for 4-10 MeV protons, and a static 80th percentile AE9 is a good approximation of the 95th percentile fluence with dynamics for 0.5-2 MeV electrons. While the specific percentiles chosen cannot necessarily be used in general for other orbit trade studies, the concept of determining a static percentile as a quick approximation to a full Monte Carlo ensemble of simulations can likely be applied to other orbit trade studies. We expect the static percentile to depend on the region of space traversed, the mission duration, and the radiation effect considered.
International Nuclear Information System (INIS)
Moore, J.G.
1974-01-01
The Monte Carlo code MONK is a general program written to provide a high degree of flexibility to the user. MONK is distinguished by its detailed representation of nuclear data in point form i.e., the cross-section is tabulated at specific energies instead of the more usual group representation. The nuclear data are unadjusted in the point form but recently the code has been modified to accept adjusted group data as used in fast and thermal reactor applications. The various geometrical handling capabilities and importance sampling techniques are described. In addition to the nuclear data aspects, the following features are also described; geometrical handling routines, tracking cycles, neutron source and output facilities. 12 references. (U.S.)
Monte Carlo lattice program KIM
International Nuclear Information System (INIS)
Cupini, E.; De Matteis, A.; Simonini, R.
1980-01-01
The Monte Carlo program KIM solves the steady-state linear neutron transport equation for a fixed-source problem or, by successive fixed-source runs, for the eigenvalue problem, in a two-dimensional thermal reactor lattice. Fluxes and reaction rates are the main quantities computed by the program, from which power distribution and few-group averaged cross sections are derived. The simulation ranges from 10 MeV to zero and includes anisotropic and inelastic scattering in the fast energy region, the epithermal Doppler broadening of the resonances of some nuclides, and the thermalization phenomenon by taking into account the thermal velocity distribution of some molecules. Besides the well known combinatorial geometry, the program allows complex configurations to be represented by a discrete set of points, an approach greatly improving calculation speed
Advanced Computational Methods for Monte Carlo Calculations
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-12
This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
Nested Sampling with Constrained Hamiltonian Monte Carlo
Betancourt, M. J.
2010-01-01
Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.
Czech Academy of Sciences Publication Activity Database
Zapoměl, Jaroslav; Ferfecki, Petr; Kozánek, Jan
2014-01-01
Roč. 8, č. 1 (2014), s. 129-138 ISSN 1802-680X Institutional support: RVO:61388998 Keywords : uncertain parameters of rigid motors * magnetorheological dampers * force transmission * Monte Carlo method Subject RIV: BI - Acoustics http://www.kme.zcu.cz/acm/acm/article/view/247/275
The MC21 Monte Carlo Transport Code
International Nuclear Information System (INIS)
Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H
2007-01-01
MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities
Monte Carlo simulation in nuclear medicine
International Nuclear Information System (INIS)
Morel, Ch.
2007-01-01
The Monte Carlo method allows for simulating random processes by using series of pseudo-random numbers. It became an important tool in nuclear medicine to assist in the design of new medical imaging devices, optimise their use and analyse their data. Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes. The availability to simulate time dependent processes opens up new horizons for Monte Carlo simulation in nuclear medicine. In a near future, these developments will allow to tackle simultaneously imaging and dosimetry issues and soon, case system Monte Carlo simulations may become part of the nuclear medicine diagnostic process. This paper describes some Monte Carlo method basics and the sampling methods that were developed for it. It gives a referenced list of different simulation software used in nuclear medicine and enumerates some of their present and prospective applications. (author)
Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya
2017-10-01
Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.
Energy Technology Data Exchange (ETDEWEB)
Kanjilal, Oindrila, E-mail: oindrila@civil.iisc.ernet.in; Manohar, C.S., E-mail: manohar@civil.iisc.ernet.in
2017-07-15
The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.
International Nuclear Information System (INIS)
Erpenbeck, J.J.
1989-01-01
The thermal transport properties of mixtures can be formulated in a number of ways, depending on the choice of driving forces for the transport of heat and matter, without violating the Onsager conditions. Here we treat transport in mixtures based on the driving forces -del ln T and -T del(μ/sub a//T), with T the temperature and μ/sub a/ the specific chemical potential, to obtain the Green-Kubo expressions and the Enskog theory for the corresponding transport coefficients which seem most amenable to molecular-dynamics evaluation. The transport properties of a hard-sphere mixture (mass ratio of 0.1, diameter ratio of 1.0, at a volume of three times close-packed volume), calculated by a Monte Carlo, molecular-dynamics method based on the Green-Kubo formulas, are compared with the predictions of the Enskog theory. The long-time behavior of the Green-Kubo time-correlation functions for shear viscosity, thermal conductivity, thermal diffusion, and mutual diffusion are found to be in good agreement with the predictions of mode-coupling theory. Except for viscosity, the contribution of the long-time tails to the transport coefficients is found to be significant. We obtain values, relative to Enskog, of 1.016 +- 0.007 for shear viscosity, 1.218 +- 0.009 for thermal conductivity, 1.267 +- 0.026 for thermal diffusion, and 1.117 +- 0.008 for mutual diffusion
Importance iteration in MORSE Monte Carlo calculations
International Nuclear Information System (INIS)
Kloosterman, J.L.; Hoogenboom, J.E.
1994-01-01
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation
Monte Carlo approaches to light nuclei
International Nuclear Information System (INIS)
Carlson, J.
1990-01-01
Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of 16 O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs
Monte Carlo approaches to light nuclei
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.
Importance iteration in MORSE Monte Carlo calculations
International Nuclear Information System (INIS)
Kloosterman, J.L.; Hoogenboom, J.E.
1994-02-01
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)
Monte Carlo Codes Invited Session
International Nuclear Information System (INIS)
Trama, J.C.; Malvagi, F.; Brown, F.
2013-01-01
This document lists 22 Monte Carlo codes used in radiation transport applications throughout the world. For each code the names of the organization and country and/or place are given. We have the following computer codes. 1) ARCHER, USA, RPI; 2) COG11, USA, LLNL; 3) DIANE, France, CEA/DAM Bruyeres; 4) FLUKA, Italy and CERN, INFN and CERN; 5) GEANT4, International GEANT4 collaboration; 6) KENO and MONACO (SCALE), USA, ORNL; 7) MC21, USA, KAPL and Bettis; 8) MCATK, USA, LANL; 9) MCCARD, South Korea, Seoul National University; 10) MCNP6, USA, LANL; 11) MCU, Russia, Kurchatov Institute; 12) MONK and MCBEND, United Kingdom, AMEC; 13) MORET5, France, IRSN Fontenay-aux-Roses; 14) MVP2, Japan, JAEA; 15) OPENMC, USA, MIT; 16) PENELOPE, Spain, Barcelona University; 17) PHITS, Japan, JAEA; 18) PRIZMA, Russia, VNIITF; 19) RMC, China, Tsinghua University; 20) SERPENT, Finland, VTT; 21) SUPERMONTECARLO, China, CAS INEST FDS Team Hefei; and 22) TRIPOLI-4, France, CEA Saclay
Advanced computers and Monte Carlo
International Nuclear Information System (INIS)
Jordan, T.L.
1979-01-01
High-performance parallelism that is currently available is synchronous in nature. It is manifested in such architectures as Burroughs ILLIAC-IV, CDC STAR-100, TI ASC, CRI CRAY-1, ICL DAP, and many special-purpose array processors designed for signal processing. This form of parallelism has apparently not been of significant value to many important Monte Carlo calculations. Nevertheless, there is much asynchronous parallelism in many of these calculations. A model of a production code that requires up to 20 hours per problem on a CDC 7600 is studied for suitability on some asynchronous architectures that are on the drawing board. The code is described and some of its properties and resource requirements ae identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resources of some asynchronous multiprocessor architectures. Arguments are made for programer aids and special syntax to identify and support important asynchronous parallelism. 2 figures, 5 tables
Adaptive Markov Chain Monte Carlo
Jadoon, Khan
2016-08-08
A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.
A Monte Carlo estimation of the marginal distributions in a problem of probabilistic dynamics
International Nuclear Information System (INIS)
Labeau, P.E.
1996-01-01
Modelling the effect of the dynamic behaviour of a system on its PSA study leads, in a Markovian framework, to a development at first order of the Chapman-Kolmogorov equation, whose solutions are the probability densities of the problem. Because of its size, there is no hope of solving directly these equations in realistic circumstances. We present in this paper a biased simulation giving the marginals and compare different ways of speeding up the integration of the equations of the dynamics
Solano, Carlos J F; Pothula, Karunakar R; Prajapati, Jigneshkumar D; De Biase, Pablo M; Noskov, Sergei Yu; Kleinekathöfer, Ulrich
2016-05-10
All-atom molecular dynamics simulations have a long history of applications studying ion and substrate permeation across biological and artificial pores. While offering unprecedented insights into the underpinning transport processes, MD simulations are limited in time-scales and ability to simulate physiological membrane potentials or asymmetric salt solutions and require substantial computational power. While several approaches to circumvent all of these limitations were developed, Brownian dynamics simulations remain an attractive option to the field. The main limitation, however, is an apparent lack of protein flexibility important for the accurate description of permeation events. In the present contribution, we report an extension of the Brownian dynamics scheme which includes conformational dynamics. To achieve this goal, the dynamics of amino-acid residues was incorporated into the many-body potential of mean force and into the Langevin equations of motion. The developed software solution, called BROMOCEA, was applied to ion transport through OmpC as a test case. Compared to fully atomistic simulations, the results show a clear improvement in the ratio of permeating anions and cations. The present tests strongly indicate that pore flexibility can enhance permeation properties which will become even more important in future applications to substrate translocation.
Monte Carlo investigation of the one-dimensional Potts model
International Nuclear Information System (INIS)
Karma, A.S.; Nolan, M.J.
1983-01-01
Monte Carlo results are presented for a variety of one-dimensional dynamical q-state Potts models. Our calculations confirm the expected universal value z = 2 for the dynamic scaling exponent. Our results also indicate that an increase in q at fixed correlation length drives the dynamics into the scaling regime
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo simulations for plasma physics
International Nuclear Information System (INIS)
Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X.
2000-07-01
Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)
Frontiers of quantum Monte Carlo workshop: preface
International Nuclear Information System (INIS)
Gubernatis, J.E.
1985-01-01
The introductory remarks, table of contents, and list of attendees are presented from the proceedings of the conference, Frontiers of Quantum Monte Carlo, which appeared in the Journal of Statistical Physics
Monte Carlo code development in Los Alamos
International Nuclear Information System (INIS)
Carter, L.L.; Cashwell, E.D.; Everett, C.J.; Forest, C.A.; Schrandt, R.G.; Taylor, W.M.; Thompson, W.L.; Turner, G.D.
1974-01-01
The present status of Monte Carlo code development at Los Alamos Scientific Laboratory is discussed. A brief summary is given of several of the most important neutron, photon, and electron transport codes. 17 references. (U.S.)
Experience with the Monte Carlo Method
Energy Technology Data Exchange (ETDEWEB)
Hussein, E M.A. [Department of Mechanical Engineering University of New Brunswick, Fredericton, N.B., (Canada)
2007-06-15
Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed.
Experience with the Monte Carlo Method
International Nuclear Information System (INIS)
Hussein, E.M.A.
2007-01-01
Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed
Monte Carlo Transport for Electron Thermal Transport
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2015-11-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
A continuation multilevel Monte Carlo algorithm
Collier, Nathan; Haji Ali, Abdul Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul
2014-01-01
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
Hybrid Monte Carlo methods in computational finance
Leitao Rodriguez, A.
2017-01-01
Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the
Critical dynamics of the Potts model: short-time Monte Carlo simulations
International Nuclear Information System (INIS)
Silva, Roberto da; Drugowich de Felicio, J.R.
2004-01-01
We calculate the new dynamic exponent θ of the 4-state Potts model, using short-time simulations. Our estimates θ1=-0.0471(33) and θ2=-0.0429(11) obtained by following the behavior of the magnetization or measuring the evolution of the time correlation function of the magnetization corroborate the conjecture by Okano et al. [Nucl. Phys. B 485 (1997) 727]. In addition, these values agree with previous estimate of the same dynamic exponent for the two-dimensional Ising model with three-spin interactions in one direction, that is known to belong to the same universality class as the 4-state Potts model. The anomalous dimension of initial magnetization x0=zθ+β/ν is calculated by an alternative way that mixes two different initial conditions. We have also estimated the values of the static exponents β and ν. They are in complete agreement with the pertinent results of the literature
Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.
2004-01-01
We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.
Multilevel Monte Carlo in Approximate Bayesian Computation
Jasra, Ajay
2017-02-13
In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.
Monte Carlo method applied to medical physics
International Nuclear Information System (INIS)
Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.
2000-01-01
The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)
Monte Carlo simulation of grain growth
Directory of Open Access Journals (Sweden)
Paulo Blikstein
1999-07-01
Full Text Available Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical behavior of the atoms is properly reproduced; microstructural evolution depends only on the real topology of the grains and not on any kind of geometric simplification. Computer simulation has the advantage of allowing the user to visualize graphically the procedures, even dynamically and in three dimensions. Single-phase alloy grain growth simulation was carried out by calculating the free energy of each atom in the lattice (with its present crystallographic orientation and comparing this value to another one calculated with a different random orientation. When the resulting free energy is lower or equal to the initial value, the new orientation replaces the former. The measure of time is the Monte Carlo Step (MCS, which involves a series of trials throughout the lattice. A very close relationship between experimental and theoretical values for the grain growth exponent (n was observed.
Off-shell dynamics of the O(3) NLS model beyond Monte Carlo and perturbation theory
International Nuclear Information System (INIS)
Balog, J.; Niedermaier, M.
1997-01-01
The off-shell dynamics of the O(3) non-linear sigma model is probed in terms of spectral densities and two-point functions by means of the form factor approach. The exact form factors of the spin field, Noether current, EM tensor and the topological charge density are computed up to six particles. The corresponding n≤6 particle spectral densities are used to compute the two-point functions, and are argued to deviate at most a few per mille from the exact answer in the entire energy range below 10 3 in units of the mass gap. To cover yet higher energies we propose an extrapolation scheme to arbitrary particle numbers based on a novel scaling hypothesis for the spectral densities. It yields candidate results for the exact two-point functions at all energy scales and allows us to exactly determine the values of two, previously unknown, non-perturbative constants. (orig.)
Dynamic analysis of once-through and closed fuel cycle economics using Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Choi, Sungyeol, E-mail: csy@kaeri.re.kr; Lee, Hyo Jik, E-mail: hyojik@kaeri.re.kr; Ko, Won Il, E-mail: nwiko@kaeri.re.kr
2014-10-01
Highlights: • Dynamic behavior of system costs, both reactor and fuel cycle costs, is analyzed. • Relative economics of once-through and closed fuel cycles is explored. • Probabilistic approaches are adopted for levelized electricity generation costs. • Main cost drivers for cost gaps between once-through and closed cycles are identified. - Abstract: Although no consensus about the best approach to manage spent fuels has been achieved, economics is one of the major criteria for assessing and selecting acceptable management options. This study compares the reactor and fuel cycle costs of the closed system associated with sodium-cooled fast reactors and pyroprocessing versus the once-through system. We specifically investigated the fuel cycle transition cases of the Republic of Korea from 2013 to 2100. The results revealed that the closed system (34.00 mills/kWh as a mean value) could be more expensive than the once-through system (32.75 mills/kWh). In contrast, the once-through fuel cycle costs (8.31 mills/kWh), excluding reactor costs, were projected to be greater than the closed fuel cycle costs (7.77 mills/kWh) because of the increased costs of interim storage estimated by the Korean government and the limited contribution of backend fuel cycle components to the discounted costs. The capital cost of sodium-cooled fast reactor is the largest component contributing to the cost gap between the two systems. Among fuel cycle components, pyroprocessing has the largest uncertainty contribution to the cost gap. We also calculated the breakeven unit costs of SFR capital cost and PWR spent fuel pyroprocessing cost.
Variational Monte Carlo study of pentaquark states
Energy Technology Data Exchange (ETDEWEB)
Mark W. Paris
2005-07-01
Accurate numerical solution of the five-body Schrodinger equation is effected via variational Monte Carlo. The spectrum is assumed to exhibit a narrow resonance with strangeness S=+1. A fully antisymmetrized and pair-correlated five-quark wave function is obtained for the assumed non-relativistic Hamiltonian which has spin, isospin, and color dependent pair interactions and many-body confining terms which are fixed by the non-exotic spectra. Gauge field dynamics are modeled via flux tube exchange factors. The energy determined for the ground states with J=1/2 and negative (positive) parity is 2.22 GeV (2.50 GeV). A lower energy negative parity state is consistent with recent lattice results. The short-range structure of the state is analyzed via its diquark content.
Successful vectorization - reactor physics Monte Carlo code
International Nuclear Information System (INIS)
Martin, W.R.
1989-01-01
Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)
Garion, C
2009-01-01
Modern particle accelerators require UHV conditions during their operation. In the accelerating cavities, breakdowns can occur, releasing large amount of gas into the vacuum chamber. To determine the pressure profile along the cavity as a function of time, the time-dependent behaviour of the gas has to be simulated. To do that, it is useful to apply accurate three-dimensional method, such as Test Particles Monte Carlo. In this paper, a time-dependent Test Particles Monte Carlo is used. It has been implemented in a Finite Element code, CASTEM. The principle is to track a sample of molecules during time. The complex geometry of the cavities can be created either in the FE code or in a CAD software (CATIA in our case). The interface between the two softwares to export the geometry from CATIA to CASTEM is given. The algorithm of particle tracking for collisionless flow in the FE code is shown. Thermal outgassing, pumping surfaces and electron and/or ion stimulated desorption can all be generated as well as differ...
International Nuclear Information System (INIS)
Ito, A.; Kenmotsu, T.; Kikuhara, Y.; Inai, K.; Ohya, K.; Wang, Y.; Irle, S.; Morokuma, K.; Nakamura, H.
2009-01-01
Full text: To understand the plasma-wall interaction on divertor plates, we investigate the interaction of hydrogen atoms and carbon materials used in the high heat flux components by the use of the following simulations. Monte-Carlo (MC) method based on binary collision approximation can calculate the sputtering process of hydrogen atoms on the carbon material quickly. Classical molecular dynamics (MD) method employs multi-body potential models and can treat realistic structures of crystal and molecule. The ab-initio method can calculate electron energy in quantum mechanics, which is regarded as realistic potential for atoms. In the present paper, the interaction of the hydrogen and the carbon material is investigated using the multi-scale (MC, MD and ab-initio) methods. The bombardment of hydrogen atoms onto the carbon material is simulated by the ACAT-code of the MC method, which cannot represent the structure of crystal, and the MD method using modified reactive empirical bond order (REBO) potential, which treats single crystal graphite and amorphous carbon. Consequently, we clarify that the sputtering yield and the reflection rate calculated by the ACAT-code agree with those on the amorphous carbon calculated by the MD. Moreover, there are many kinds of REBO potential for the MD. Adsorption, reflection and penetration rates between a hydrogen atom and a graphene surface are calculated by the MD simulations using the two kinds of potential model. For the incident energy of less than 1 eV, the MD simulation using the modified REBO potential, which is based on Brenner's REBO potential in 2002, shows that reflection is dominant, while the most popular Brenner's REBO potential in 1990 shows that adsorption is dominant. This reflection of the low energy injection is caused by a small potential barrier for the hydrogen atom in the modified REBO potential. The small potential barrier is confirmed by the ab-initio calculations, which are hybrid DFT (B3LYP/cc-pVDZ), ab
Monte Carlo strategies in scientific computing
Liu, Jun S
2008-01-01
This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
Off-diagonal expansion quantum Monte Carlo.
Albash, Tameem; Wagenbreth, Gene; Hen, Itay
2017-12-01
We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.
Reflections on early Monte Carlo calculations
International Nuclear Information System (INIS)
Spanier, J.
1992-01-01
Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances
Monte Carlo simulation of Markov unreliability models
International Nuclear Information System (INIS)
Lewis, E.E.; Boehm, F.
1984-01-01
A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)
Shell model the Monte Carlo way
International Nuclear Information System (INIS)
Ormand, W.E.
1995-01-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined
Shell model the Monte Carlo way
Energy Technology Data Exchange (ETDEWEB)
Ormand, W.E.
1995-03-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.
SPQR: a Monte Carlo reactor kinetics code
International Nuclear Information System (INIS)
Cramer, S.N.; Dodds, H.L.
1980-02-01
The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations
Current and future applications of Monte Carlo
International Nuclear Information System (INIS)
Zaidi, H.
2003-01-01
Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions (pdfs). As the number of individual events (called 'histories') is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic
Monte Carlo method for array criticality calculations
International Nuclear Information System (INIS)
Dickinson, D.; Whitesides, G.E.
1976-01-01
The Monte Carlo method for solving neutron transport problems consists of mathematically tracing paths of individual neutrons collision by collision until they are lost by absorption or leakage. The fate of the neutron after each collision is determined by the probability distribution functions that are formed from the neutron cross-section data. These distributions are sampled statistically to establish the successive steps in the neutron's path. The resulting data, accumulated from following a large number of batches, are analyzed to give estimates of k/sub eff/ and other collision-related quantities. The use of electronic computers to produce the simulated neutron histories, initiated at Los Alamos Scientific Laboratory, made the use of the Monte Carlo method practical for many applications. In analog Monte Carlo simulation, the calculation follows the physical events of neutron scattering, absorption, and leakage. To increase calculational efficiency, modifications such as the use of statistical weights are introduced. The Monte Carlo method permits the use of a three-dimensional geometry description and a detailed cross-section representation. Some of the problems in using the method are the selection of the spatial distribution for the initial batch, the preparation of the geometry description for complex units, and the calculation of error estimates for region-dependent quantities such as fluxes. The Monte Carlo method is especially appropriate for criticality safety calculations since it permits an accurate representation of interacting units of fissile material. Dissimilar units, units of complex shape, moderators between units, and reflected arrays may be calculated. Monte Carlo results must be correlated with relevant experimental data, and caution must be used to ensure that a representative set of neutron histories is produced
Energy Technology Data Exchange (ETDEWEB)
Liu, T; Lin, H; Gao, Y; Caracappa, P; Wang, G; Cong, W; Xu, X [Rensselaer Polytechnic Institute, Troy, NY (United States)
2016-06-15
Purpose: Dynamic bowtie filter is an innovative design capable of modulating the X-ray and balancing the flux in the detectors, and it introduces a new way of patient-specific CT scan optimizations. This study demonstrates the feasibility of performing fast Monte Carlo dose calculation for a type of dynamic bowtie filter for cone-beam CT (Liu et al. 2014 9(7) PloS one) using MIC coprocessors. Methods: The dynamic bowtie filter in question consists of a highly attenuating bowtie component (HB) and a weakly attenuating bowtie (WB). The HB is filled with CeCl3 solution and its surface is defined by a transcendental equation. The WB is an elliptical cylinder filled with air and immersed in the HB. As the scanner rotates, the orientation of WB remains the same with the static patient. In our Monte Carlo simulation, the HB was approximated by 576 boxes. The phantom was a voxelized elliptical cylinder composed of PMMA and surrounded by air (44cm×44cm×40cm, 1000×1000×1 voxels). The dose to the PMMA phantom was tallied with 0.15% statistical uncertainty under 100 kVp source. Two Monte Carlo codes ARCHER and MCNP-6.1 were compared. Both used double-precision. Compiler flags that may trade accuracy for speed were avoided. Results: The wall time of the simulation was 25.4 seconds by ARCHER on a 5110P MIC, 40 seconds on a X5650 CPU, and 523 seconds by the multithreaded MCNP on the same CPU. The high performance of ARCHER is attributed to the parameterized geometry and vectorization of the program hotspots. Conclusion: The dynamic bowtie filter modeled in this study is able to effectively reduce the dynamic range of the detected signals for the photon-counting detectors. With appropriate software optimization methods, the accelerator-based (MIC and GPU) Monte Carlo dose engines have shown good performance and can contribute to patient-specific CT scan optimizations.
Monte Carlo simulation applied to alpha spectrometry
International Nuclear Information System (INIS)
Baccouche, S.; Gharbi, F.; Trabelsi, A.
2007-01-01
Alpha particle spectrometry is a widely-used analytical method, in particular when we deal with pure alpha emitting radionuclides. Monte Carlo simulation is an adequate tool to investigate the influence of various phenomena on this analytical method. We performed an investigation of those phenomena using the simulation code GEANT of CERN. The results concerning the geometrical detection efficiency in different measurement geometries agree with analytical calculations. This work confirms that Monte Carlo simulation of solid angle of detection is a very useful tool to determine with very good accuracy the detection efficiency.
Simplified monte carlo simulation for Beijing spectrometer
International Nuclear Information System (INIS)
Wang Taijie; Wang Shuqin; Yan Wuguang; Huang Yinzhi; Huang Deqiang; Lang Pengfei
1986-01-01
The Monte Carlo method based on the functionization of the performance of detectors and the transformation of values of kinematical variables into ''measured'' ones by means of smearing has been used to program the Monte Carlo simulation of the performance of the Beijing Spectrometer (BES) in FORTRAN language named BESMC. It can be used to investigate the multiplicity, the particle type, and the distribution of four-momentum of the final states of electron-positron collision, and also the response of the BES to these final states. Thus, it provides a measure to examine whether the overall design of the BES is reasonable and to decide the physical topics of the BES
Burnup calculations using Monte Carlo method
International Nuclear Information System (INIS)
Ghosh, Biplab; Degweker, S.B.
2009-01-01
In the recent years, interest in burnup calculations using Monte Carlo methods has gained momentum. Previous burn up codes have used multigroup transport theory based calculations followed by diffusion theory based core calculations for the neutronic portion of codes. The transport theory methods invariably make approximations with regard to treatment of the energy and angle variables involved in scattering, besides approximations related to geometry simplification. Cell homogenisation to produce diffusion, theory parameters adds to these approximations. Moreover, while diffusion theory works for most reactors, it does not produce accurate results in systems that have strong gradients, strong absorbers or large voids. Also, diffusion theory codes are geometry limited (rectangular, hexagonal, cylindrical, and spherical coordinates). Monte Carlo methods are ideal to solve very heterogeneous reactors and/or lattices/assemblies in which considerable burnable poisons are used. The key feature of this approach is that Monte Carlo methods permit essentially 'exact' modeling of all geometrical detail, without resort to ene and spatial homogenization of neutron cross sections. Monte Carlo method would also be better for in Accelerator Driven Systems (ADS) which could have strong gradients due to the external source and a sub-critical assembly. To meet the demand for an accurate burnup code, we have developed a Monte Carlo burnup calculation code system in which Monte Carlo neutron transport code is coupled with a versatile code (McBurn) for calculating the buildup and decay of nuclides in nuclear materials. McBurn is developed from scratch by the authors. In this article we will discuss our effort in developing the continuous energy Monte Carlo burn-up code, McBurn. McBurn is intended for entire reactor core as well as for unit cells and assemblies. Generally, McBurn can do burnup of any geometrical system which can be handled by the underlying Monte Carlo transport code
Improvements for Monte Carlo burnup calculation
Energy Technology Data Exchange (ETDEWEB)
Shenglong, Q.; Dong, Y.; Danrong, S.; Wei, L., E-mail: qiangshenglong@tsinghua.org.cn, E-mail: d.yao@npic.ac.cn, E-mail: songdr@npic.ac.cn, E-mail: luwei@npic.ac.cn [Nuclear Power Inst. of China, Cheng Du, Si Chuan (China)
2015-07-01
Monte Carlo burnup calculation is development trend of reactor physics, there would be a lot of work to be done for engineering applications. Based on Monte Carlo burnup code MOI, non-fuel burnup calculation methods and critical search suggestions will be mentioned in this paper. For non-fuel burnup, mixed burnup mode will improve the accuracy of burnup calculation and efficiency. For critical search of control rod position, a new method called ABN based on ABA which used by MC21 will be proposed for the first time in this paper. (author)
A keff calculation method by Monte Carlo
International Nuclear Information System (INIS)
Shen, H; Wang, K.
2008-01-01
The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)
Monte Carlo electron/photon transport
International Nuclear Information System (INIS)
Mack, J.M.; Morel, J.E.; Hughes, H.G.
1985-01-01
A review of nonplasma coupled electron/photon transport using Monte Carlo method is presented. Remarks are mainly restricted to linerarized formalisms at electron energies from 1 keV to 1000 MeV. Applications involving pulse-height estimation, transport in external magnetic fields, and optical Cerenkov production are discussed to underscore the importance of this branch of computational physics. Advances in electron multigroup cross-section generation is reported, and its impact on future code development assessed. Progress toward the transformation of MCNP into a generalized neutral/charged-particle Monte Carlo code is described. 48 refs
Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.
1995-01-01
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width
Monte Carlo applications to radiation shielding problems
International Nuclear Information System (INIS)
Subbaiah, K.V.
2009-01-01
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling of physical and mathematical systems to compute their results. However, basic concepts of MC are both simple and straightforward and can be learned by using a personal computer. Uses of Monte Carlo methods require large amounts of random numbers, and it was their use that spurred the development of pseudorandom number generators, which were far quicker to use than the tables of random numbers which had been previously used for statistical sampling. In Monte Carlo simulation of radiation transport, the history (track) of a particle is viewed as a random sequence of free flights that end with an interaction event where the particle changes its direction of movement, loses energy and, occasionally, produces secondary particles. The Monte Carlo simulation of a given experimental arrangement (e.g., an electron beam, coming from an accelerator and impinging on a water phantom) consists of the numerical generation of random histories. To simulate these histories we need an interaction model, i.e., a set of differential cross sections (DCS) for the relevant interaction mechanisms. The DCSs determine the probability distribution functions (pdf) of the random variables that characterize a track; 1) free path between successive interaction events, 2) type of interaction taking place and 3) energy loss and angular deflection in a particular event (and initial state of emitted secondary particles, if any). Once these pdfs are known, random histories can be generated by using appropriate sampling methods. If the number of generated histories is large enough, quantitative information on the transport process may be obtained by simply averaging over the simulated histories. The Monte Carlo method yields the same information as the solution of the Boltzmann transport equation, with the same interaction model, but is easier to implement. In particular, the simulation of radiation
Simulation of transport equations with Monte Carlo
International Nuclear Information System (INIS)
Matthes, W.
1975-09-01
The main purpose of the report is to explain the relation between the transport equation and the Monte Carlo game used for its solution. The introduction of artificial particles carrying a weight provides one with high flexibility in constructing many different games for the solution of the same equation. This flexibility opens a way to construct a Monte Carlo game for the solution of the adjoint transport equation. Emphasis is laid mostly on giving a clear understanding of what to do and not on the details of how to do a specific game
Monte Carlo dose distributions for radiosurgery
International Nuclear Information System (INIS)
Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E.
2001-01-01
The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Structure and dynamics of Ebola virus matrix protein VP40 by a coarse-grained Monte Carlo simulation
Pandey, Ras; Farmer, Barry
Ebola virus matrix protein VP40 (consisting of 326 residues) plays a critical role in viral assembly and its functions such as regulation of viral transcription, packaging, and budding of mature virions into the plasma membrane of infected cells. How does the protein VP40 go through structural evolution during the viral life cycle remains an open question? Using a coarse-grained Monte Carlo simulation we investigate the structural evolution of VP40 as a function of temperature with the input of a knowledge-based residue-residue interaction. A number local and global physical quantities (e.g. mobility profile, contact map, radius of gyration, structure factor) are analyzed with our large-scale simulations. Our preliminary data show that the structure of the protein evolves through different state with well-defined morphologies which can be identified and quantified via a detailed analysis of structure factor.
Monte Carlo simulation of continuous-space crystal growth
International Nuclear Information System (INIS)
Dodson, B.W.; Taylor, P.A.
1986-01-01
We describe a method, based on Monte Carlo techniques, of simulating the atomic growth of crystals without the discrete lattice space assumed by conventional Monte Carlo growth simulations. Since no lattice space is assumed, problems involving epitaxial growth, heteroepitaxy, phonon-driven mechanisms, surface reconstruction, and many other phenomena incompatible with the lattice-space approximation can be studied. Also, use of the Monte Carlo method circumvents to some extent the extreme limitations on simulated timescale inherent in crystal-growth techniques which might be proposed using molecular dynamics. The implementation of the new method is illustrated by studying the growth of strained-layer superlattice (SLS) interfaces in two-dimensional Lennard-Jones atomic systems. Despite the extreme simplicity of such systems, the qualitative features of SLS growth seen here are similar to those observed experimentally in real semiconductor systems
Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations
DEFF Research Database (Denmark)
Kamran, Faisal; Andersen, Peter E.
2015-01-01
profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...
Testing a Fourier Accelerated Hybrid Monte Carlo Algorithm
Catterall, S.; Karamov, S.
2001-01-01
We describe a Fourier Accelerated Hybrid Monte Carlo algorithm suitable for dynamical fermion simulations of non-gauge models. We test the algorithm in supersymmetric quantum mechanics viewed as a one-dimensional Euclidean lattice field theory. We find dramatic reductions in the autocorrelation time of the algorithm in comparison to standard HMC.
Specialized Monte Carlo codes versus general-purpose Monte Carlo codes
International Nuclear Information System (INIS)
Moskvin, Vadim; DesRosiers, Colleen; Papiez, Lech; Lu, Xiaoyi
2002-01-01
The possibilities of Monte Carlo modeling for dose calculations and optimization treatment are quite limited in radiation oncology applications. The main reason is that the Monte Carlo technique for dose calculations is time consuming while treatment planning may require hundreds of possible cases of dose simulations to be evaluated for dose optimization. The second reason is that general-purpose codes widely used in practice, require an experienced user to customize them for calculations. This paper discusses the concept of Monte Carlo code design that can avoid the main problems that are preventing wide spread use of this simulation technique in medical physics. (authors)
Parallel processing Monte Carlo radiation transport codes
International Nuclear Information System (INIS)
McKinney, G.W.
1994-01-01
Issues related to distributed-memory multiprocessing as applied to Monte Carlo radiation transport are discussed. Measurements of communication overhead are presented for the radiation transport code MCNP which employs the communication software package PVM, and average efficiency curves are provided for a homogeneous virtual machine
Monte Carlo determination of heteroepitaxial misfit structures
DEFF Research Database (Denmark)
Baker, J.; Lindgård, Per-Anker
1996-01-01
We use Monte Carlo simulations to determine the structure of KBr overlayers on a NaCl(001) substrate, a system with large (17%) heteroepitaxial misfit. The equilibrium relaxation structure is determined for films of 2-6 ML, for which extensive helium-atom scattering data exist for comparison...
The Monte Carlo applied for calculation dose
International Nuclear Information System (INIS)
Peixoto, J.E.
1988-01-01
The Monte Carlo method is showed for the calculation of absorbed dose. The trajectory of the photon is traced simulating sucessive interaction between the photon and the substance that consist the human body simulator. The energy deposition in each interaction of the simulator organ or tissue per photon is also calculated. (C.G.C.) [pt
Monte Carlo code for neutron radiography
International Nuclear Information System (INIS)
Milczarek, Jacek J.; Trzcinski, Andrzej; El-Ghany El Abd, Abd; Czachor, Andrzej
2005-01-01
The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms
Monte Carlo code for neutron radiography
Energy Technology Data Exchange (ETDEWEB)
Milczarek, Jacek J. [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)]. E-mail: jjmilcz@cyf.gov.pl; Trzcinski, Andrzej [Institute for Nuclear Studies, Swierk, 05-400 Otwock (Poland); El-Ghany El Abd, Abd [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland); Nuclear Research Center, PC 13759, Cairo (Egypt); Czachor, Andrzej [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)
2005-04-21
The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms.
Monte Carlo method in neutron activation analysis
International Nuclear Information System (INIS)
Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.
2009-01-01
Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA
Computer system for Monte Carlo experimentation
International Nuclear Information System (INIS)
Grier, D.A.
1986-01-01
A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language
Scalable Domain Decomposed Monte Carlo Particle Transport
Energy Technology Data Exchange (ETDEWEB)
O' Brien, Matthew Joseph [Univ. of California, Davis, CA (United States)
2013-12-05
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.|info:eu-repo/dai/nl/101275080
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
Monte Carlo studies of ZEPLIN III
Dawson, J; Davidge, D C R; Gillespie, J R; Howard, A S; Jones, W G; Joshi, M; Lebedenko, V N; Sumner, T J; Quenby, J J
2002-01-01
A Monte Carlo simulation of a two-phase xenon dark matter detector, ZEPLIN III, has been achieved. Results from the analysis of a simulated data set are presented, showing primary and secondary signal distributions from low energy gamma ray events.
Biases in Monte Carlo eigenvalue calculations
Energy Technology Data Exchange (ETDEWEB)
Gelbard, E.M.
1992-12-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.
Biases in Monte Carlo eigenvalue calculations
Energy Technology Data Exchange (ETDEWEB)
Gelbard, E.M.
1992-01-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.
Design and analysis of Monte Carlo experiments
Kleijnen, Jack P.C.; Gentle, J.E.; Haerdle, W.; Mori, Y.
2012-01-01
By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to
Some problems on Monte Carlo method development
International Nuclear Information System (INIS)
Pei Lucheng
1992-01-01
This is a short paper on some problems of Monte Carlo method development. The content consists of deep-penetration problems, unbounded estimate problems, limitation of Mdtropolis' method, dependency problem in Metropolis' method, random error interference problems and random equations, intellectualisation and vectorization problems of general software
Monte Carlo simulations in theoretical physic
International Nuclear Information System (INIS)
Billoire, A.
1991-01-01
After a presentation of the MONTE CARLO method principle, the method is applied, first to the critical exponents calculations in the three dimensions ISING model, and secondly to the discrete quantum chromodynamic with calculation times in function of computer power. 28 refs., 4 tabs
Monte Carlo method for random surfaces
International Nuclear Information System (INIS)
Berg, B.
1985-01-01
Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the
Coded aperture optimization using Monte Carlo simulations
International Nuclear Information System (INIS)
Martineau, A.; Rocchisani, J.M.; Moretti, J.L.
2010-01-01
Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.
Biases in Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Gelbard, E.M.
1992-01-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ''fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (''replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here
Monte Carlo studies of uranium calorimetry
International Nuclear Information System (INIS)
Brau, J.; Hargis, H.J.; Gabriel, T.A.; Bishop, B.L.
1985-01-01
Detailed Monte Carlo calculations of uranium calorimetry are presented which reveal a significant difference in the responses of liquid argon and plastic scintillator in uranium calorimeters. Due to saturation effects, neutrons from the uranium are found to contribute only weakly to the liquid argon signal. Electromagnetic sampling inefficiencies are significant and contribute substantially to compensation in both systems. 17 references
Uncertainty analysis in Monte Carlo criticality computations
International Nuclear Information System (INIS)
Qi Ao
2011-01-01
Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.
Pore-scale uncertainty quantification with multilevel Monte Carlo
Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul
2014-01-01
. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost
Prospect on general software of Monte Carlo method
International Nuclear Information System (INIS)
Pei Lucheng
1992-01-01
This is a short paper on the prospect of Monte Carlo general software. The content consists of cluster sampling method, zero variance technique, self-improved method, and vectorized Monte Carlo method
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung; Liang, Faming
2009-01-01
in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method
A Monte Carlo study on event-by-event transverse momentum fluctuation at RHIC
International Nuclear Information System (INIS)
Xu Mingmei
2005-01-01
The experimental observation on the multiplicity dependence of event-by-event transverse momentum fluctuation in relativistic heavy ion collisions is studied using Monte Carlo simulation. It is found that the Monte Carlo generator HIJING is unable to describe the experimental phenomenon well. A simple Monte Carlo model is proposed, which can recover the data and thus shed some light on the dynamical origin of the multiplicity dependence of event-by-event transverse momentum fluctuation. (authors)
Applications of Monte Carlo method in Medical Physics
International Nuclear Information System (INIS)
Diez Rios, A.; Labajos, M.
1989-01-01
The basic ideas of Monte Carlo techniques are presented. Random numbers and their generation by congruential methods, which underlie Monte Carlo calculations are shown. Monte Carlo techniques to solve integrals are discussed. The evaluation of a simple monodimensional integral with a known answer, by means of two different Monte Carlo approaches are discussed. The basic principles to simualate on a computer photon histories reduce variance and the current applications in Medical Physics are commented. (Author)
Monte Carlo computation in the applied research of nuclear technology
International Nuclear Information System (INIS)
Xu Shuyan; Liu Baojie; Li Qin
2007-01-01
This article briefly introduces Monte Carlo Methods and their properties. It narrates the Monte Carlo methods with emphasis in their applications to several domains of nuclear technology. Monte Carlo simulation methods and several commonly used computer software to implement them are also introduced. The proposed methods are demonstrated by a real example. (authors)
Multiple-time-stepping generalized hybrid Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Atomistic Monte Carlo Simulation of Lipid Membranes
Directory of Open Access Journals (Sweden)
Daniel Wüstner
2014-01-01
Full Text Available Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA for the phospholipid dipalmitoylphosphatidylcholine (DPPC. We demonstrate rapid conformational equilibration for a single DPPC 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 the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.
Monte-Carlo simulation of the dynamic behavior of a CMOS inverter struck by a heavy ion
International Nuclear Information System (INIS)
Brisset, C.; Dollfus, P.; Hesto, P.
1994-01-01
The authors present a theoretical study using Monte-Carlo simulation of the behavior of a CMOS inverter struck by an ionizing particle. The inverter is made of two complementary enhancement-mode MOSFETs according to a SIMOX self-aligned technology with an effective gate length of 0.35 μm. The effect of the ionizing particle (heavy ion) is simulated by electron-hole pairs generation with an energy of 1 eV for each carrier. The authors studied the return to the steady-state of the device after a transient irradiation. Either the P-channel transistor or the N-channel transistor is irradiated, and the gate operating is considered in both cases of 0 V and 5 V input voltage. The irradiation of the off-state transistors induces a significant transient variation of the output voltage whereas irradiation of the on-state transistor has weak effects on the output. The return to the stationary regime, which is reached after about 50 ps in all irradiation cases, is achieved by evacuation of the carriers in excess through the different electrodes without trapping effect in the device
Subtle Monte Carlo Updates in Dense Molecular Systems
DEFF Research Database (Denmark)
Bottaro, Sandro; Boomsma, Wouter; Johansson, Kristoffer E.
2012-01-01
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce...... as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results...... suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions....
Monte Carlo-based tail exponent estimator
Barunik, Jozef; Vacha, Lukas
2010-11-01
In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.
No-compromise reptation quantum Monte Carlo
International Nuclear Information System (INIS)
Yuen, W K; Farrar, Thomas J; Rothstein, Stuart M
2007-01-01
Since its publication, the reptation quantum Monte Carlo algorithm of Baroni and Moroni (1999 Phys. Rev. Lett. 82 4745) has been applied to several important problems in physics, but its mathematical foundations are not well understood. We show that their algorithm is not of typical Metropolis-Hastings type, and we specify conditions required for the generated Markov chain to be stationary and to converge to the intended distribution. The time-step bias may add up, and in many applications it is only the middle of a reptile that is the most important. Therefore, we propose an alternative, 'no-compromise reptation quantum Monte Carlo' to stabilize the middle of the reptile. (fast track communication)
Multilevel Monte Carlo Approaches for Numerical Homogenization
Efendiev, Yalchin R.
2015-10-01
In this article, we study the application of multilevel Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the homogenized solutions. This is accomplished within MLMC by considering different sizes of representative volumes (RVEs). Many inexpensive computations with the smallest RVE size are combined with fewer expensive computations performed on larger RVEs. Likewise, when it comes to homogenized solutions, different levels of coarse-grid meshes are used to solve the homogenized equation. We show that, by carefully selecting the number of realizations at each level, we can achieve a speed-up in the computations in comparison to a standard Monte Carlo method. Numerical results are presented for both one-dimensional and two-dimensional test-cases that illustrate the efficiency of the approach.
Status of Monte Carlo at Los Alamos
International Nuclear Information System (INIS)
Thompson, W.L.; Cashwell, E.D.
1980-01-01
At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time
Monte Carlo simulations in skin radiotherapy
International Nuclear Information System (INIS)
Sarvari, A.; Jeraj, R.; Kron, T.
2000-01-01
The primary goal of this work was to develop a procedure for calculation the appropriate filter shape for a brachytherapy applicator used for skin radiotherapy. In the applicator a radioactive source is positioned close to the skin. Without a filter, the resultant dose distribution would be highly nonuniform.High uniformity is usually required however. This can be achieved using an appropriately shaped filter, which flattens the dose profile. Because of the complexity of the transport and geometry, Monte Carlo simulations had to be used. An 192 Ir high dose rate photon source was used. All necessary transport parameters were simulated with the MCNP4B Monte Carlo code. A highly efficient iterative procedure was developed, which enabled calculation of the optimal filter shape in only few iterations. The initially non-uniform dose distributions became uniform within a percent when applying the filter calculated by this procedure. (author)
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL
Directory of Open Access Journals (Sweden)
Luo Ronghua
2008-11-01
Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-01
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
Monte Carlo simulation of gas Cerenkov detectors
International Nuclear Information System (INIS)
Mack, J.M.; Jain, M.; Jordan, T.M.
1984-01-01
Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier
Hypothesis testing of scientific Monte Carlo calculations
Wallerberger, Markus; Gull, Emanuel
2017-11-01
The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-05
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
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...
Status of Monte Carlo at Los Alamos
International Nuclear Information System (INIS)
Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.
1980-05-01
Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner
Topological zero modes in Monte Carlo simulations
International Nuclear Information System (INIS)
Dilger, H.
1994-08-01
We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)
Handbook of Markov chain Monte Carlo
Brooks, Steve
2011-01-01
""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.
The lund Monte Carlo for jet fragmentation
International Nuclear Information System (INIS)
Sjoestrand, T.
1982-03-01
We present a Monte Carlo program based on the Lund model for jet fragmentation. Quark, gluon, diquark and hadron jets are considered. Special emphasis is put on the fragmentation of colour singlet jet systems, for which energy, momentum and flavour are conserved explicitly. The model for decays of unstable particles, in particular the weak decay of heavy hadrons, is described. The central part of the paper is a detailed description on how to use the FORTRAN 77 program. (Author)
Monte Carlo methods for preference learning
DEFF Research Database (Denmark)
Viappiani, P.
2012-01-01
Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....
Monte Carlo methods for shield design calculations
International Nuclear Information System (INIS)
Grimstone, M.J.
1974-01-01
A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)
General purpose code for Monte Carlo simulations
International Nuclear Information System (INIS)
Wilcke, W.W.
1983-01-01
A general-purpose computer called MONTHY has been written to perform Monte Carlo simulations of physical systems. To achieve a high degree of flexibility the code is organized like a general purpose computer, operating on a vector describing the time dependent state of the system under simulation. The instruction set of the computer is defined by the user and is therefore adaptable to the particular problem studied. The organization of MONTHY allows iterative and conditional execution of operations
Autocorrelations in hybrid Monte Carlo simulations
International Nuclear Information System (INIS)
Schaefer, Stefan; Virotta, Francesco
2010-11-01
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.)
Introduction to the Monte Carlo methods
International Nuclear Information System (INIS)
Uzhinskij, V.V.
1993-01-01
Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab
Sequential Monte Carlo with Highly Informative Observations
Del Moral, Pierre; Murray, Lawrence M.
2014-01-01
We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...
Monte Carlo codes use in neutron therapy
International Nuclear Information System (INIS)
Paquis, P.; Mokhtari, F.; Karamanoukian, D.; Pignol, J.P.; Cuendet, P.; Iborra, N.
1998-01-01
Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)
Quantum Monte Carlo calculations of light nuclei
International Nuclear Information System (INIS)
Pandharipande, V. R.
1999-01-01
Quantum Monte Carlo methods provide an essentially exact way to calculate various properties of nuclear bound, and low energy continuum states, from realistic models of nuclear interactions and currents. After a brief description of the methods and modern models of nuclear forces, we review the results obtained for all the bound, and some continuum states of up to eight nucleons. Various other applications of the methods are reviewed along with future prospects
Monte-Carlo simulation of electromagnetic showers
International Nuclear Information System (INIS)
Amatuni, Ts.A.
1984-01-01
The universal ELSS-1 program for Monte Carlo simulation of high energy electromagnetic showers in homogeneous absorbers of arbitrary geometry is written. The major processes and effects of electron and photon interaction with matter, particularly the Landau-Pomeranchuk-Migdal effect, are taken into account in the simulation procedures. The simulation results are compared with experimental data. Some characteristics of shower detectors and electromagnetic showers for energies up 1 TeV are calculated
Cost of splitting in Monte Carlo transport
International Nuclear Information System (INIS)
Everett, C.J.; Cashwell, E.D.
1978-03-01
In a simple transport problem designed to estimate transmission through a plane slab of x free paths by Monte Carlo methods, it is shown that m-splitting (m > or = 2) does not pay unless exp(x) > m(m + 3)/(m - 1). In such a case, the minimum total cost in terms of machine time is obtained as a function of m, and the optimal value of m is determined
Monte Carlo simulation of Touschek effect
Directory of Open Access Journals (Sweden)
Aimin Xiao
2010-07-01
Full Text Available We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian-distributed beam or for a general beam whose distribution function is given. In addition, scattered electrons can be tracked through the beam line and the local beam-loss rate and beam halo information recorded.
Direct Monte Carlo simulation of nanoscale mixed gas bearings
Directory of Open Access Journals (Sweden)
Kyaw Sett Myo
2015-06-01
Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.
Monte Carlo method for neutron transport problems
International Nuclear Information System (INIS)
Asaoka, Takumi
1977-01-01
Some methods for decreasing variances in Monte Carlo neutron transport calculations are presented together with the results of sample calculations. A general purpose neutron transport Monte Carlo code ''MORSE'' was used for the purpose. The first method discussed in this report is the method of statistical estimation. As an example of this method, the application of the coarse-mesh rebalance acceleration method to the criticality calculation of a cylindrical fast reactor is presented. Effective multiplication factor and its standard deviation are presented as a function of the number of histories and comparisons are made between the coarse-mesh rebalance method and the standard method. Five-group neutron fluxes at core center are also compared with the result of S4 calculation. The second method is the method of correlated sampling. This method was applied to the perturbation calculation of control rod worths in a fast critical assembly (FCA-V-3) Two methods of sampling (similar flight paths and identical flight paths) are tested and compared with experimental results. For every cases the experimental value lies within the standard deviation of the Monte Carlo calculations. The third method is the importance sampling. In this report a biased selection of particle flight directions discussed. This method was applied to the flux calculation in a spherical fast neutron system surrounded by a 10.16 cm iron reflector. Result-direction biasing, path-length stretching, and no biasing are compared with S8 calculation. (Aoki, K.)
Biased Monte Carlo optimization: the basic approach
International Nuclear Information System (INIS)
Campioni, Luca; Scardovelli, Ruben; Vestrucci, Paolo
2005-01-01
It is well-known that the Monte Carlo method is very successful in tackling several kinds of system simulations. It often happens that one has to deal with rare events, and the use of a variance reduction technique is almost mandatory, in order to have Monte Carlo efficient applications. The main issue associated with variance reduction techniques is related to the choice of the value of the biasing parameter. Actually, this task is typically left to the experience of the Monte Carlo user, who has to make many attempts before achieving an advantageous biasing. A valuable result is provided: a methodology and a practical rule addressed to establish an a priori guidance for the choice of the optimal value of the biasing parameter. This result, which has been obtained for a single component system, has the notable property of being valid for any multicomponent system. In particular, in this paper, the exponential and the uniform biases of exponentially distributed phenomena are investigated thoroughly
Quantum Monte Carlo for vibrating molecules
International Nuclear Information System (INIS)
Brown, W.R.; Lawrence Berkeley National Lab., CA
1996-08-01
Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H 2 O and C 3 vibrational states, using 7 PES's, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H 2 O and C 3 . In order to construct accurate trial wavefunctions for C 3 , the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C 3 the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C 3 PES's suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies
Lattice gauge theories and Monte Carlo simulations
International Nuclear Information System (INIS)
Rebbi, C.
1981-11-01
After some preliminary considerations, the discussion of quantum gauge theories on a Euclidean lattice takes up the definition of Euclidean quantum theory and treatment of the continuum limit; analogy is made with statistical mechanics. Perturbative methods can produce useful results for strong or weak coupling. In the attempts to investigate the properties of the systems for intermediate coupling, numerical methods known as Monte Carlo simulations have proved valuable. The bulk of this paper illustrates the basic ideas underlying the Monte Carlo numerical techniques and the major results achieved with them according to the following program: Monte Carlo simulations (general theory, practical considerations), phase structure of Abelian and non-Abelian models, the observables (coefficient of the linear term in the potential between two static sources at large separation, mass of the lowest excited state with the quantum numbers of the vacuum (the so-called glueball), the potential between two static sources at very small distance, the critical temperature at which sources become deconfined), gauge fields coupled to basonic matter (Higgs) fields, and systems with fermions
Generalized hybrid Monte Carlo - CMFD methods for fission source convergence
International Nuclear Information System (INIS)
Wolters, Emily R.; Larsen, Edward W.; Martin, William R.
2011-01-01
In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)
International Nuclear Information System (INIS)
Greensite, J.
1984-03-01
It is likely that the quark confinement mechanism at large N should be understood purely in terms of high-order planar Feynman diagrams; in particular, the center of the gauge group can play no role whatever. The author considers the diagrammatic expansion of loop integrals in planar wrong-sign phi4 theory. It is shown that the sum of all fishnet diagrams contributing to the loop can be expressed as the grand partition function of an unusual gas, whose dynamics can be simulated on a computer. The 'molecules' of this gas correspond to vertices of the position-space diagrams, the molecular interactions are determined by the propagators, and the coupling constant plays the role of a chemical potential. The most remarkable feature of this gas is the existence of a critical coupling gsub(c), where string formation takes place. As g → gsub(c) the fishnet vertices tend to cluster around the minimal surface of the loop, thereby forming a string. The role of asymptotic freedom in bringing the coupling to the critical point, and the connection to the Polyakov string, are also discussed. In the Hamiltonian formulation, a very straightforward explanation of quark confinement is presented. (Auth.)
Monte Carlo event generators in atomic collisions: A new tool to tackle the few-body dynamics
Ciappina, M. F.; Kirchner, T.; Schulz, M.
2010-04-01
We present a set of routines to produce theoretical event files, for both single and double ionization of atoms by ion impact, based on a Monte Carlo event generator (MCEG) scheme. Such event files are the theoretical counterpart of the data obtained from a kinematically complete experiment; i.e. they contain the momentum components of all collision fragments for a large number of ionization events. Among the advantages of working with theoretical event files is the possibility to incorporate the conditions present in a real experiment, such as the uncertainties in the measured quantities. Additionally, by manipulating them it is possible to generate any type of cross sections, specially those that are usually too complicated to compute with conventional methods due to a lack of symmetry. Consequently, the numerical effort of such calculations is dramatically reduced. We show examples for both single and double ionization, with special emphasis on a new data analysis tool, called four-body Dalitz plots, developed very recently. Program summaryProgram title: MCEG Catalogue identifier: AEFV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2695 No. of bytes in distributed program, including test data, etc.: 18 501 Distribution format: tar.gz Programming language: FORTRAN 77 with parallelization directives using scripting Computer: Single machines using Linux and Linux servers/clusters (with cores with any clock speed, cache memory and bits in a word) Operating system: Linux (any version and flavor) and FORTRAN 77 compilers Has the code been vectorised or parallelized?: Yes RAM: 64-128 kBytes (the codes are very cpu intensive) Classification: 2.6 Nature of problem: The code deals with single and double
Energy Technology Data Exchange (ETDEWEB)
Shaukat, Nadeem; Ryu, Min; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of)
2017-08-15
With ever-advancing computer technology, the Monte Carlo (MC) neutron transport calculation is expanding its application area to nuclear reactor transient analysis. Dynamic MC (DMC) neutron tracking for transient analysis requires efficient algorithms for delayed neutron generation, neutron population control, and initial condition modeling. In this paper, a new MC steady-state simulation method based on time-dependent MC neutron tracking is proposed for steady-state initial condition modeling; during this process, prompt neutron sources and delayed neutron precursors for the DMC transient simulation can easily be sampled. The DMC method, including the proposed time-dependent DMC steady-state simulation method, has been implemented in McCARD and applied for two-dimensional core kinetics problems in the time-dependent neutron transport benchmark C5G7-TD. The McCARD DMC calculation results show good agreement with results of a deterministic transport analysis code, nTRACER.
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.
Monte Carlo Volcano Seismic Moment Tensors
Waite, G. P.; Brill, K. A.; Lanza, F.
2015-12-01
Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.
An Overview of the Monte Carlo Application ToolKit (MCATK)
Energy Technology Data Exchange (ETDEWEB)
Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-01-07
MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library designed to build specialized applications and designed to provide new functionality in existing general-purpose Monte Carlo codes like MCNP; it was developed with Agile software engineering methodologies under the motivation to reduce costs. The characteristics of MCATK can be summarized as follows: MCATK physics – continuous energy neutron-gamma transport with multi-temperature treatment, static eigenvalue (k and α) algorithms, time-dependent algorithm, fission chain algorithms; MCATK geometry – mesh geometries, solid body geometries. MCATK provides verified, unit-tested Monte Carlo components, flexibility in Monte Carlo applications development, and numerous tools such as geometry and cross section plotters. Recent work has involved deterministic and Monte Carlo analysis of stochastic systems. Static and dynamic analysis is discussed, and the results of a dynamic test problem are given.
Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system
International Nuclear Information System (INIS)
Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo
2000-01-01
Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency
Investigating the impossible: Monte Carlo simulations
International Nuclear Information System (INIS)
Kramer, Gary H.; Crowley, Paul; Burns, Linda C.
2000-01-01
Designing and testing new equipment can be an expensive and time consuming process or the desired performance characteristics may preclude its construction due to technological shortcomings. Cost may also prevent equipment being purchased for other scenarios to be tested. An alternative is to use Monte Carlo simulations to make the investigations. This presentation exemplifies how Monte Carlo code calculations can be used to fill the gap. An example is given for the investigation of two sizes of germanium detector (70 mm and 80 mm diameter) at four different crystal thicknesses (15, 20, 25, and 30 mm) and makes predictions on how the size affects the counting efficiency and the Minimum Detectable Activity (MDA). The Monte Carlo simulations have shown that detector efficiencies can be adequately modelled using photon transport if the data is used to investigate trends. The investigation of the effect of detector thickness on the counting efficiency has shown that thickness for a fixed diameter detector of either 70 mm or 80 mm is unimportant up to 60 keV. At higher photon energies, the counting efficiency begins to decrease as the thickness decreases as expected. The simulations predict that the MDA of either the 70 mm or 80 mm diameter detectors does not differ by more than a factor of 1.15 at 17 keV or 1.2 at 60 keV when comparing detectors of equivalent thicknesses. The MDA is slightly increased at 17 keV, and rises by about 52% at 660 keV, when the thickness is decreased from 30 mm to 15 mm. One could conclude from this information that the extra cost associated with the larger area Ge detectors may not be justified for the slight improvement predicted in the MDA. (author)
Gaastra - Nedea, S.V.; Steenhoven, van A.A.; Markvoort, A.J.; Spijker, P.; Giordano, D.
2014-01-01
The influence of gas-surface interactions of a dilute gas confined between two parallel walls on the heat flux predictions is investigated using a combined Monte Carlo (MC) and molecular dynamics (MD) approach. The accommodation coefficients are computed from the temperature of incident and
Monte Carlo simulations on SIMD computer architectures
International Nuclear Information System (INIS)
Burmester, C.P.; Gronsky, R.; Wille, L.T.
1992-01-01
In this paper algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SIMD) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carl updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures
Monte Carlo Simulation of an American Option
Directory of Open Access Journals (Sweden)
Gikiri Thuo
2007-04-01
Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.
Monte Carlo study of the multiquark systems
International Nuclear Information System (INIS)
Kerbikov, B.O.; Polikarpov, M.I.; Zamolodchikov, A.B.
1986-01-01
Random walks have been used to calculate the energies of the ground states in systems of N=3, 6, 9, 12 quarks. Multiquark states with N>3 are unstable with respect to the spontaneous dissociation into color singlet hadrons. The modified Green's function Monte Carlo algorithm which proved to be more simple and much accurate than the conventional few body methods have been employed. In contrast to other techniques, the same equations are used for any number of particles, while the computer time increases only linearly V, S the number of particles
Monte Carlo eigenfunction strategies and uncertainties
International Nuclear Information System (INIS)
Gast, R.C.; Candelore, N.R.
1974-01-01
Comparisons of convergence rates for several possible eigenfunction source strategies led to the selection of the ''straight'' analog of the analytic power method as the source strategy for Monte Carlo eigenfunction calculations. To insure a fair game strategy, the number of histories per iteration increases with increasing iteration number. The estimate of eigenfunction uncertainty is obtained from a modification of a proposal by D. B. MacMillan and involves only estimates of the usual purely statistical component of uncertainty and a serial correlation coefficient of lag one. 14 references. (U.S.)
ATLAS Monte Carlo tunes for MC09
The ATLAS collaboration
2010-01-01
This note describes the ATLAS tunes of underlying event and minimum bias description for the main Monte Carlo generators used in the MC09 production. For the main shower generators, pythia and herwig (with jimmy), the MRST LO* parton distribution functions (PDFs) were used for the first time in ATLAS. Special studies on the performance of these, conceptually new, PDFs for high pt physics processes at LHC energies are presented. In addition, a tune of jimmy for CTEQ6.6 is presented, for use with MC@NLO.
Markov chains analytic and Monte Carlo computations
Graham, Carl
2014-01-01
Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies.A detailed and rigorous presentation of Markov chains with discrete time and state space.An appendix presenting probabilistic notions that are nec
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...
Monte Carlo method in radiation transport problems
International Nuclear Information System (INIS)
Dejonghe, G.; Nimal, J.C.; Vergnaud, T.
1986-11-01
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 [fr
Mosaic crystal algorithm for Monte Carlo simulations
Seeger, P A
2002-01-01
An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)
A note on simultaneous Monte Carlo tests
DEFF Research Database (Denmark)
Hahn, Ute
In this short note, Monte Carlo tests of goodness of fit for data of the form X(t), t ∈ I are considered, that reject the null hypothesis if X(t) leaves an acceptance region bounded by an upper and lower curve for some t in I. A construction of the acceptance region is proposed that complies to a...... to a given target level of rejection, and yields exact p-values. The construction is based on pointwise quantiles, estimated from simulated realizations of X(t) under the null hypothesis....
Monte Carlo methods to calculate impact probabilities
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
MBR Monte Carlo Simulation in PYTHIA8
Ciesielski, R.
We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.
Spectral functions from Quantum Monte Carlo
International Nuclear Information System (INIS)
Silver, R.N.
1989-01-01
In his review, D. Scalapino identified two serious limitations on the application of Quantum Monte Carlo (QMC) methods to the models of interest in High T c Superconductivity (HTS). One is the ''sign problem''. The other is the ''analytic continuation problem'', which is how to extract electron spectral functions from QMC calculations of the imaginary time Green's functions. Through-out this Symposium on HTS, the spectral functions have been the focus for the discussion of normal state properties including the applicability of band theory, Fermi liquid theory, marginal Fermi liquids, and novel non-perturbative states. 5 refs., 1 fig
An analysis of Monte Carlo tree search
CSIR Research Space (South Africa)
James, S
2017-02-01
Full Text Available Tree Search Steven James∗, George Konidaris† & Benjamin Rosman∗‡ ∗University of the Witwatersrand, Johannesburg, South Africa †Brown University, Providence RI 02912, USA ‡Council for Scientific and Industrial Research, Pretoria, South Africa steven....james@students.wits.ac.za, gdk@cs.brown.edu, brosman@csir.co.za Abstract Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in re- cent years. Despite the vast amount of research into MCTS, the effect of modifications...
Monte Carlo simulation for the transport beamline
Energy Technology Data Exchange (ETDEWEB)
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)
2013-07-26
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Monte Carlo simulation for the transport beamline
International Nuclear Information System (INIS)
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.; Tramontana, A.
2013-01-01
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery
Diffusion quantum Monte Carlo for molecules
International Nuclear Information System (INIS)
Lester, W.A. Jr.
1986-07-01
A quantum mechanical Monte Carlo method has been used for the treatment of molecular problems. The imaginary-time Schroedinger equation written with a shift in zero energy [E/sub T/ - V(R)] can be interpreted as a generalized diffusion equation with a position-dependent rate or branching term. Since diffusion is the continuum limit of a random walk, one may simulate the Schroedinger equation with a function psi (note, not psi 2 ) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs
Monte Carlo modelling for neutron guide losses
International Nuclear Information System (INIS)
Cser, L.; Rosta, L.; Toeroek, Gy.
1989-09-01
In modern research reactors, neutron guides are commonly used for beam conducting. The neutron guide is a well polished or equivalently smooth glass tube covered inside by sputtered or evaporated film of natural Ni or 58 Ni isotope where the neutrons are totally reflected. A Monte Carlo calculation was carried out to establish the real efficiency and the spectral as well as spatial distribution of the neutron beam at the end of a glass mirror guide. The losses caused by mechanical inaccuracy and mirror quality were considered and the effects due to the geometrical arrangement were analyzed. (author) 2 refs.; 2 figs
International Nuclear Information System (INIS)
Nakayama, Akira; Taketsugu, Tetsuya; Shiga, Motoyuki
2009-01-01
Efficiency of the ab initio hybrid Monte Carlo and ab initio path integral hybrid Monte Carlo methods is enhanced by employing an auxiliary potential energy surface that is used to update the system configuration via molecular dynamics scheme. As a simple illustration of this method, a dual-level approach is introduced where potential energy gradients are evaluated by computationally less expensive ab initio electronic structure methods. (author)
Energy Technology Data Exchange (ETDEWEB)
Zvejnieks, G. [Institute for Solid State Physics, University of Latvia, Kengaraga 8, LV-1063 Riga (Latvia); Ibenskas, A., E-mail: ibenskas@pfi.lt [Center for Physical Sciences and Technology, Semiconductor Physics Institute, Gostauto 11, LT-01108 Vilnius (Lithuania); Tornau, E.E. [Center for Physical Sciences and Technology, Semiconductor Physics Institute, Gostauto 11, LT-01108 Vilnius (Lithuania)
2015-11-15
Instability of the Au/Ni(111) surface alloy is studied in different CO gas pressure, p, and temperature limits using kinetic Monte Carlo simulations. We analyze the reaction front dynamics and formation of Au clusters using the model which takes into account surface adatom pair and three-body interactions, CO adsorption and desorption, catalytic carbonyl formation reaction, Au and Ni adatom diffusion and their concerted exchange. Variation of interaction parameters allows us to identify three possible reaction front propagation limits with different pressure dependencies: (i) slow channel-like flow in agreement with experimental data [1] (step flow rate, R, increases with p), (ii) intermediate regime (weak p–dependence), and (iii) fast homogeneous flow (R decreases with p). We find that only Au–Ni exchange, contrary to both Ni–CO and Au–CO exchanges, significantly reduces the number of screened Ni atoms inside the Au clusters and stimulates the occurrence of Ni-free Au clusters. The size of Au islands depends on both pressure and temperature. At a fixed temperature it decreases with pressure due to an increased step flow rate. In the high temperature limit, despite the step flow rate exponential increase with temperature, the cluster size increases due to an enhanced Au mobility. - Highlights: • Kinetic Monte Carlo study of Au–Ni surface alloy instability to CO pressure and temperature. • Three reaction front propagation regimes. • In channel-like regime, the step flow rate increases with CO pressure as in experiment. • Ni-free Au islands are obtained when Au-Ni adatom exchange mechanism is considered. • The size of Au islands decreases with pressure and increases with temperature.
International Nuclear Information System (INIS)
Zvejnieks, G.; Ibenskas, A.; Tornau, E.E.
2015-01-01
Instability of the Au/Ni(111) surface alloy is studied in different CO gas pressure, p, and temperature limits using kinetic Monte Carlo simulations. We analyze the reaction front dynamics and formation of Au clusters using the model which takes into account surface adatom pair and three-body interactions, CO adsorption and desorption, catalytic carbonyl formation reaction, Au and Ni adatom diffusion and their concerted exchange. Variation of interaction parameters allows us to identify three possible reaction front propagation limits with different pressure dependencies: (i) slow channel-like flow in agreement with experimental data [1] (step flow rate, R, increases with p), (ii) intermediate regime (weak p–dependence), and (iii) fast homogeneous flow (R decreases with p). We find that only Au–Ni exchange, contrary to both Ni–CO and Au–CO exchanges, significantly reduces the number of screened Ni atoms inside the Au clusters and stimulates the occurrence of Ni-free Au clusters. The size of Au islands depends on both pressure and temperature. At a fixed temperature it decreases with pressure due to an increased step flow rate. In the high temperature limit, despite the step flow rate exponential increase with temperature, the cluster size increases due to an enhanced Au mobility. - Highlights: • Kinetic Monte Carlo study of Au–Ni surface alloy instability to CO pressure and temperature. • Three reaction front propagation regimes. • In channel-like regime, the step flow rate increases with CO pressure as in experiment. • Ni-free Au islands are obtained when Au-Ni adatom exchange mechanism is considered. • The size of Au islands decreases with pressure and increases with temperature
Geometric allocation approaches in Markov chain Monte Carlo
International Nuclear Information System (INIS)
Todo, S; Suwa, H
2013-01-01
The Markov chain Monte Carlo method is a versatile tool in statistical physics to evaluate multi-dimensional integrals numerically. For the method to work effectively, we must consider the following key issues: the choice of ensemble, the selection of candidate states, the optimization of transition kernel, algorithm for choosing a configuration according to the transition probabilities. We show that the unconventional approaches based on the geometric allocation of probabilities or weights can improve the dynamics and scaling of the Monte Carlo simulation in several aspects. Particularly, the approach using the irreversible kernel can reduce or sometimes completely eliminate the rejection of trial move in the Markov chain. We also discuss how the space-time interchange technique together with Walker's method of aliases can reduce the computational time especially for the case where the number of candidates is large, such as models with long-range interactions
Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians
Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan
2018-02-01
Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.
Monte Carlo learning/biasing experiment with intelligent random numbers
International Nuclear Information System (INIS)
Booth, T.E.
1985-01-01
A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs
Discrete diffusion Monte Carlo for frequency-dependent radiative transfer
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Thompson, Kelly G.; Urbatsch, Todd J.
2011-01-01
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique. (author)
Monte Carlo criticality analysis for dissolvers with neutron poison
International Nuclear Information System (INIS)
Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.
1987-01-01
Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)
Temperature variance study in Monte-Carlo photon transport theory
International Nuclear Information System (INIS)
Giorla, J.
1985-10-01
We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2016-01-06
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul
2016-01-01
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul
2015-01-01
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
International Nuclear Information System (INIS)
Ohta, Shigemi
1996-01-01
The Self-Test Monte Carlo (STMC) method resolves the main problems in using algebraic pseudo-random numbers for Monte Carlo (MC) calculations: that they can interfere with MC algorithms and lead to erroneous results, and that such an error often cannot be detected without known exact solution. STMC is based on good randomness of about 10 10 bits available from physical noise or transcendental numbers like π = 3.14---. Various bit modifiers are available to get more bits for applications that demands more than 10 10 random bits such as lattice quantum chromodynamics (QCD). These modifiers are designed so that a) each of them gives a bit sequence comparable in randomness as the original if used separately from each other, and b) their mutual interference when used jointly in a single MC calculation is adjustable. Intermediate data of the MC calculation itself are used to quantitatively test and adjust the mutual interference of the modifiers in respect of the MC algorithm. STMC is free of systematic error and gives reliable statistical error. Also it can be easily implemented on vector and parallel supercomputers. (author)
Algorithms for Monte Carlo calculations with fermions
International Nuclear Information System (INIS)
Weingarten, D.
1985-01-01
We describe a fermion Monte Carlo algorithm due to Petcher and the present author and another due to Fucito, Marinari, Parisi and Rebbi. For the first algorithm we estimate the number of arithmetic operations required to evaluate a vacuum expectation value grows as N 11 /msub(q) on an N 4 lattice with fixed periodicity in physical units and renormalized quark mass msub(q). For the second algorithm the rate of growth is estimated to be N 8 /msub(q) 2 . Numerical experiments are presented comparing the two algorithms on a lattice of size 2 4 . With a hopping constant K of 0.15 and β of 4.0 we find the number of operations for the second algorithm is about 2.7 times larger than for the first and about 13 000 times larger than for corresponding Monte Carlo calculations with a pure gauge theory. An estimate is given for the number of operations required for more realistic calculations by each algorithm on a larger lattice. (orig.)
Quantum Monte Carlo for atoms and molecules
International Nuclear Information System (INIS)
Barnett, R.N.
1989-11-01
The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H 2 , LiH, Li 2 , and H 2 O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li 2 , and H 2 O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations, the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2015-01-07
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
Parallel Monte Carlo Search for Hough Transform
Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.
2017-10-01
We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.
Monte Carlo simulation for radiographic applications
International Nuclear Information System (INIS)
Tillack, G.R.; Bellon, C.
2003-01-01
Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de
Reactor perturbation calculations by Monte Carlo methods
International Nuclear Information System (INIS)
Gubbins, M.E.
1965-09-01
Whilst Monte Carlo methods are useful for reactor calculations involving complicated geometry, it is difficult to apply them to the calculation of perturbation worths because of the large amount of computing time needed to obtain good accuracy. Various ways of overcoming these difficulties are investigated in this report, with the problem of estimating absorbing control rod worths particularly in mind. As a basis for discussion a method of carrying out multigroup reactor calculations by Monte Carlo methods is described. Two methods of estimating a perturbation worth directly, without differencing two quantities of like magnitude, are examined closely but are passed over in favour of a third method based on a correlation technique. This correlation method is described, and demonstrated by a limited range of calculations for absorbing control rods in a fast reactor. In these calculations control rod worths of between 1% and 7% in reactivity are estimated to an accuracy better than 10% (3 standard errors) in about one hour's computing time on the English Electric KDF.9 digital computer. (author)
Odd-flavor Simulations by the Hybrid Monte Carlo
Takaishi, Tetsuya; Takaishi, Tetsuya; De Forcrand, Philippe
2001-01-01
The standard hybrid Monte Carlo algorithm is known to simulate even flavors QCD only. Simulations of odd flavors QCD, however, can be also performed in the framework of the hybrid Monte Carlo algorithm where the inverse of the fermion matrix is approximated by a polynomial. In this exploratory study we perform three flavors QCD simulations. We make a comparison of the hybrid Monte Carlo algorithm and the R-algorithm which also simulates odd flavors systems but has step-size errors. We find that results from our hybrid Monte Carlo algorithm are in agreement with those from the R-algorithm obtained at very small step-size.
Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Brown, F.
2007-01-01
Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)
Monte Carlo shielding analyses using an automated biasing procedure
International Nuclear Information System (INIS)
Tang, J.S.; Hoffman, T.J.
1988-01-01
A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost
Monte Carlo techniques for analyzing deep-penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1986-01-01
Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications
Igo - A Monte Carlo Code For Radiotherapy Planning
International Nuclear Information System (INIS)
Goldstein, M.; Regev, D.
1999-01-01
The goal of radiation therapy is to deliver a lethal dose to the tumor, while minimizing the dose to normal tissues and vital organs. To carry out this task, it is critical to calculate correctly the 3-D dose delivered. Monte Carlo transport methods (especially the Adjoint Monte Carlo have the potential to provide more accurate predictions of the 3-D dose the currently used methods. IG0 is a Monte Carlo code derived from the general Monte Carlo Program - MCNP, tailored specifically for calculating the effects of radiation therapy. This paper describes the IG0 transport code, the PIG0 interface and some preliminary results
Quantum statistical Monte Carlo methods and applications to spin systems
International Nuclear Information System (INIS)
Suzuki, M.
1986-01-01
A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures
Variational Variance Reduction for Monte Carlo Criticality Calculations
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Larsen, Edward W.
2001-01-01
A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions
Applications of the Monte Carlo method in radiation protection
International Nuclear Information System (INIS)
Kulkarni, R.N.; Prasad, M.A.
1999-01-01
This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)
Load Balancing of Parallel Monte Carlo Transport Calculations
International Nuclear Information System (INIS)
Procassini, R J; O'Brien, M J; Taylor, J M
2005-01-01
The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since he particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations
Graphics Processing Unit Accelerated Hirsch-Fye Quantum Monte Carlo
Moore, Conrad; Abu Asal, Sameer; Rajagoplan, Kaushik; Poliakoff, David; Caprino, Joseph; Tomko, Karen; Thakur, Bhupender; Yang, Shuxiang; Moreno, Juana; Jarrell, Mark
2012-02-01
In Dynamical Mean Field Theory and its cluster extensions, such as the Dynamic Cluster Algorithm, the bottleneck of the algorithm is solving the self-consistency equations with an impurity solver. Hirsch-Fye Quantum Monte Carlo is one of the most commonly used impurity and cluster solvers. This work implements optimizations of the algorithm, such as enabling large data re-use, suitable for the Graphics Processing Unit (GPU) architecture. The GPU's sheer number of concurrent parallel computations and large bandwidth to many shared memories takes advantage of the inherent parallelism in the Green function update and measurement routines, and can substantially improve the efficiency of the Hirsch-Fye impurity solver.
Advanced Markov chain Monte Carlo methods learning from past samples
Liang, Faming; Carrol, Raymond J
2010-01-01
This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem have been developed include, the modified Gibbs sampler, the methods based on auxiliary variables and the methods making use of past samples. The focus of this book is on the algorithms that make use of past samples. This book includes the multicanonical algorithm, dynamic weighting, dynamically weight
Understanding quantum tunneling using diffusion Monte Carlo simulations
Inack, E. M.; Giudici, G.; Parolini, T.; Santoro, G.; Pilati, S.
2018-03-01
In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1 /Δ2 , where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1 /Δ , i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.
Brolin, Gustav; Sjögreen Gleisner, Katarina; Ljungberg, Michael
2013-05-01
In dynamic renal scintigraphy, the main interest is the radiopharmaceutical redistribution as a function of time. Quality control (QC) of renal procedures often relies on phantom experiments to compare image-based results with the measurement setup. A phantom with a realistic anatomy and time-varying activity distribution is therefore desirable. This work describes a pharmacokinetic (PK) compartment model for 99mTc-MAG3, used for defining a dynamic whole-body activity distribution within a digital phantom (XCAT) for accurate Monte Carlo (MC)-based images for QC. Each phantom structure is assigned a time-activity curve provided by the PK model, employing parameter values consistent with MAG3 pharmacokinetics. This approach ensures that the total amount of tracer in the phantom is preserved between time points, and it allows for modifications of the pharmacokinetics in a controlled fashion. By adjusting parameter values in the PK model, different clinically realistic scenarios can be mimicked, regarding, e.g., the relative renal uptake and renal transit time. Using the MC code SIMIND, a complete set of renography images including effects of photon attenuation, scattering, limited spatial resolution and noise, are simulated. The obtained image data can be used to evaluate quantitative techniques and computer software in clinical renography.
International Nuclear Information System (INIS)
Bian Liang; Shu Yuan-Jie; Wang Xin-Feng
2012-01-01
Amorphous and crystalline poly (chloro-p-xylylene) (PPX C) membranes are constructed by using a novel computational technique, that is, a combined method of NVT+NPT-molecular dynamics (MD) and gradually reducing the size (GRS) methods. The related free volumes are defined as homology clusters. Then the sorption and the permeation of gases in PPX C polymers are studied using grand canonical Monte Carlo (GCMC) and NVT-MD methods. The results show that the crystalline PPX C membranes provide smaller free volumes for absorbing or transferring gases relative to the amorphous PPX C area. The gas sorption in PPX C membranes mainly belongs to the physical one, and H bonds can appear obviously in the amorphous area. By cluster analyzing on the mean square displacement of gases, we find that gases walk along the x axis in the crystalline area and walk randomly in the amorphous area. The calculated permeability coefficients are close to the experimental data. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)
International Nuclear Information System (INIS)
Chen, Ji; Ren, Xinguo; Li, Xin-Zheng; Alfè, Dario; Wang, Enge
2014-01-01
The finite-temperature phase diagram of hydrogen in the region of phase IV and its neighborhood was studied using the ab initio molecular dynamics (MD) and the ab initio path-integral molecular dynamics (PIMD). The electronic structures were analyzed using the density-functional theory (DFT), the random-phase approximation, and the diffusion Monte Carlo (DMC) methods. Taking the state-of-the-art DMC results as benchmark, comparisons of the energy differences between structures generated from the MD and PIMD simulations, with molecular and dissociated hydrogens, respectively, in the weak molecular layers of phase IV, indicate that standard functionals in DFT tend to underestimate the dissociation barrier of the weak molecular layers in this mixed phase. Because of this underestimation, inclusion of the quantum nuclear effects (QNEs) in PIMD using electronic structures generated with these functionals leads to artificially dissociated hydrogen layers in phase IV and an error compensation between the neglect of QNEs and the deficiencies of these functionals in standard ab initio MD simulations exists. This analysis partly rationalizes why earlier ab initio MD simulations complement so well the experimental observations. The temperature and pressure dependencies for the stability of phase IV were also studied in the end and compared with earlier results
Abhinav, S.; Manohar, C. S.
2018-03-01
The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.
Jing, Qingli; Bello, Roger Y.; Martín, Fernando; Palacios, Alicia; Madsen, Lars Bojer
2018-04-01
Recent research interests have been raised in uncovering and controlling ultrafast dynamics in excited neutral molecules. In this work we generalize the Monte Carlo wave packet (MCWP) approach to XUV-pump-IR-probe schemes to simulate the process of dissociative double ionization of H2 where singly excited states in H2 are involved. The XUV pulse is chosen to resonantly excite the initial ground state of H2 to the lowest excited electronic state of 1Σu + symmetry in H2 within the Franck-Condon region. The delayed intense IR pulse couples the excited states of 1Σu + symmetry with the nearby excited states of 1Σg + symmetry. It also induces the first ionization from H2 to H2 + and the second ionization from H2 + to H++H+. To reduce the computational costs in the MCWP approach, a sampling method is proposed to determine in time the dominant ionization events from H2 to H2+. By conducting a trajectory analysis, which is a unique possibility within the MCWP approach, the origins of the characteristic features in the nuclear kinetic energy release spectra are identified for delays ranging from 0 to 140 fs and the nuclear dynamics in the singly excited states in H2 is mapped out.
Selection of important Monte Carlo histories
International Nuclear Information System (INIS)
Egbert, Stephen D.
1987-01-01
The 1986 Dosimetry System (DS86) for Japanese A-bomb survivors uses information describing the behavior of individual radiation particles, simulated by Monte Carlo methods, to calculate the transmission of radiation into structures and, thence, into humans. However, there are practical constraints on the number of such particle 'histories' that may be used. First, the number must be sufficiently high to provide adequate statistical precision fir any calculated quantity of interest. For integral quantities, such as dose or kerma, statistical precision of approximately 5% (standard deviation) is required to ensure that statistical uncertainties are not a major contributor to the overall uncertainty of the transmitted value. For differential quantities, such as scalar fluence spectra, 10 to 15% standard deviation on individual energy groups is adequate. Second, the number of histories cannot be so large as to require an unacceptably large amount of computer time to process the entire survivor data base. Given that there are approx. 30,000 survivors, each having 13 or 14 organs of interest, the number of histories per organ must be constrained to less than several ten's of thousands at the very most. Selection and use of the most important Monte Carlo leakage histories from among all those calculated allows the creation of an efficient house and organ radiation transmission system for use at RERF. While attempts have been made during the adjoint Monte Carlo calculation to bias the histories toward an efficient dose estimate, this effort has been far from satisfactory. Many of the adjoint histories on a typical leakage tape are either starting in an energy group in which there is very little kerma or dose or leaking into an energy group with very little free-field couple with. By knowing the typical free-field fluence and the fluence-to-dose factors with which the leaking histories will be used, one can select histories rom a leakage tape that will contribute to dose
Energy Technology Data Exchange (ETDEWEB)
Okada, Kazuya [School of Akita Prefectural University, Yurihonjo (Japan); Satoh, Akira, E-mail: asatoh@akita-pu.ac.jp [Department of Machine Intelligence and System Engineering, Akita Prefectural University, Yurihonjo (Japan)
2017-09-01
Highlights: • Monte Carlo simulations have been employed for the aggregate structures. • Brownian dynamics simulations have been employed for the magneto-rheology. • Even a weak shear flow induces a significant regime change in the aggregates. • A strong external magnetic field drastically changes the aggregates. • The dependence of the viscosity on these factors is governed in a complex manner. - Abstract: In the present study, we address a suspension composed ferromagnetic rod-like particles to elucidate a regime change in the aggregate structures and the magneto-rheological characteristics. Monte Carlo simulations have been employed for investigating the aggregate structures in thermodynamic equilibrium, and Brownian dynamics simulations for magneto-rheological features in a simple shear flow. The main results obtained here are summarized as follows. For the case of thermodynamic equilibrium, the rod-like particles aggregate to form thick chain-like clusters and the neighboring clusters incline in opposite directions. If the external magnetic field is increased, the thick chain-like clusters in the magnetic field direction grow thicker by adsorbing the neighboring clusters that incline in the opposite direction. Hence, a significant phase change in the particle aggregates is not induced by an increase in the magnetic field strength. For the case of a simple shear flow, even a weak shear flow induces a significant regime change from the thick chain-like clusters of thermodynamic equilibrium into wall-like aggregates composed of short raft-like clusters. A strong external magnetic field drastically changes these aggregates into wall-like aggregates composed of thick chain-like clusters rather than the short raft-like clusters. The internal structure of these aggregates is not strongly influenced by a shear flow, and the formation of the short raft-like clusters is maintained inside the aggregates. The main contribution to the net viscosity is the
Response decomposition with Monte Carlo correlated coupling
International Nuclear Information System (INIS)
Ueki, T.; Hoogenboom, J.E.; Kloosterman, J.L.
2001-01-01
Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)
Response decomposition with Monte Carlo correlated coupling
Energy Technology Data Exchange (ETDEWEB)
Ueki, T.; Hoogenboom, J.E.; Kloosterman, J.L. [Delft Univ. of Technology (Netherlands). Interfaculty Reactor Inst.
2001-07-01
Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)
Monte Carlo simulations of low background detectors
International Nuclear Information System (INIS)
Miley, H.S.; Brodzinski, R.L.; Hensley, W.K.; Reeves, J.H.
1995-01-01
An implementation of the Electron Gamma Shower 4 code (EGS4) has been developed to allow convenient simulation of typical gamma ray measurement systems. Coincidence gamma rays, beta spectra, and angular correlations have been added to adequately simulate a complete nuclear decay and provide corrections to experimentally determined detector efficiencies. This code has been used to strip certain low-background spectra for the purpose of extremely low-level assay. Monte Carlo calculations of this sort can be extremely successful since low background detectors are usually free of significant contributions from poorly localized radiation sources, such as cosmic muons, secondary cosmic neutrons, and radioactive construction or shielding materials. Previously, validation of this code has been obtained from a series of comparisons between measurements and blind calculations. An example of the application of this code to an exceedingly low background spectrum stripping will be presented. (author) 5 refs.; 3 figs.; 1 tab
Homogenized group cross sections by Monte Carlo
International Nuclear Information System (INIS)
Van Der Marck, S. C.; Kuijper, J. C.; Oppe, J.
2006-01-01
Homogenized group cross sections play a large role in making reactor calculations efficient. Because of this significance, many codes exist that can calculate these cross sections based on certain assumptions. However, the application to the High Flux Reactor (HFR) in Petten, the Netherlands, the limitations of such codes imply that the core calculations would become less accurate when using homogenized group cross sections (HGCS). Therefore we developed a method to calculate HGCS based on a Monte Carlo program, for which we chose MCNP. The implementation involves an addition to MCNP, and a set of small executables to perform suitable averaging after the MCNP run(s) have completed. Here we briefly describe the details of the method, and we report on two tests we performed to show the accuracy of the method and its implementation. By now, this method is routinely used in preparation of the cycle to cycle core calculations for HFR. (authors)
Nuclear reactions in Monte Carlo codes
Ferrari, Alfredo
2002-01-01
The physics foundations of hadronic interactions as implemented in most Monte Carlo codes are presented together with a few practical examples. The description of the relevant physics is presented schematically split into the major steps in order to stress the different approaches required for the full understanding of nuclear reactions at intermediate and high energies. Due to the complexity of the problem, only a few semi-qualitative arguments are developed in this paper. The description will be necessarily schematic and somewhat incomplete, but hopefully it will be useful for a first introduction into this topic. Examples are shown mostly for the high energy regime, where all mechanisms mentioned in the paper are at work and to which perhaps most of the readers are less accustomed. Examples for lower energies can be found in the references. (43 refs) .
Angular biasing in implicit Monte-Carlo
International Nuclear Information System (INIS)
Zimmerman, G.B.
1994-01-01
Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise
An accurate nonlinear Monte Carlo collision operator
International Nuclear Information System (INIS)
Wang, W.X.; Okamoto, M.; Nakajima, N.; Murakami, S.
1995-03-01
A three dimensional nonlinear Monte Carlo collision model is developed based on Coulomb binary collisions with the emphasis both on the accuracy and implementation efficiency. The operator of simple form fulfills particle number, momentum and energy conservation laws, and is equivalent to exact Fokker-Planck operator by correctly reproducing the friction coefficient and diffusion tensor, in addition, can effectively assure small-angle collisions with a binary scattering angle distributed in a limited range near zero. Two highly vectorizable algorithms are designed for its fast implementation. Various test simulations regarding relaxation processes, electrical conductivity, etc. are carried out in velocity space. The test results, which is in good agreement with theory, and timing results on vector computers show that it is practically applicable. The operator may be used for accurately simulating collisional transport problems in magnetized and unmagnetized plasmas. (author)
Computation cluster for Monte Carlo calculations
International Nuclear Information System (INIS)
Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S.
2010-01-01
Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)
Monte Carlo stratified source-sampling
International Nuclear Information System (INIS)
Blomquist, R.N.; Gelbard, E.M.
1997-01-01
In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo open-quotes eigenvalue of the worldclose quotes problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. The original test-problem was treated by a special code designed specifically for that purpose. Recently ANL started work on a method for dealing with more realistic eigenvalue of the world configurations, and has been incorporating this method into VIM. The original method has been modified to take into account real-world statistical noise sources not included in the model problem. This paper constitutes a status report on work still in progress
Monte Carlo simulation of a CZT detector
International Nuclear Information System (INIS)
Chun, Sung Dae; Park, Se Hwan; Ha, Jang Ho; Kim, Han Soo; Cho, Yoon Ho; Kang, Sang Mook; Kim, Yong Kyun; Hong, Duk Geun
2008-01-01
CZT detector is one of the most promising radiation detectors for hard X-ray and γ-ray measurement. The energy spectrum of CZT detector has to be simulated to optimize the detector design. A CZT detector was fabricated with dimensions of 5x5x2 mm 3 . A Peltier cooler with a size of 40x40 mm 2 was installed below the fabricated CZT detector to reduce the operation temperature of the detector. Energy spectra of were measured with 59.5 keV γ-ray from 241 Am. A Monte Carlo code was developed to simulate the CZT energy spectrum, which was measured with a planar-type CZT detector, and the result was compared with the measured one. The simulation was extended to the CZT detector with strip electrodes. (author)
Vectorization of Monte Carlo particle transport
International Nuclear Information System (INIS)
Burns, P.J.; Christon, M.; Schweitzer, R.; Lubeck, O.M.; Wasserman, H.J.; Simmons, M.L.; Pryor, D.V.
1989-01-01
This paper reports that fully vectorized versions of the Los Alamos National Laboratory benchmark code Gamteb, a Monte Carlo photon transport algorithm, were developed for the Cyber 205/ETA-10 and Cray X-MP/Y-MP architectures. Single-processor performance measurements of the vector and scalar implementations were modeled in a modified Amdahl's Law that accounts for additional data motion in the vector code. The performance and implementation strategy of the vector codes are related to architectural features of each machine. Speedups between fifteen and eighteen for Cyber 205/ETA-10 architectures, and about nine for CRAY X-MP/Y-MP architectures are observed. The best single processor execution time for the problem was 0.33 seconds on the ETA-10G, and 0.42 seconds on the CRAY Y-MP
Computation cluster for Monte Carlo calculations
Energy Technology Data Exchange (ETDEWEB)
Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S. [Dep. Of Nuclear Physics and Technology, Faculty of Electrical Engineering and Information, Technology, Slovak Technical University, Ilkovicova 3, 81219 Bratislava (Slovakia)
2010-07-01
Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)
Monte Carlo calculations of channeling radiation
International Nuclear Information System (INIS)
Bloom, S.D.; Berman, B.L.; Hamilton, D.C.; Alguard, M.J.; Barrett, J.H.; Datz, S.; Pantell, R.H.; Swent, R.H.
1981-01-01
Results of classical Monte Carlo calculations are presented for the radiation produced by ultra-relativistic positrons incident in a direction parallel to the (110) plane of Si in the energy range 30 to 100 MeV. The results all show the characteristic CR(channeling radiation) peak in the energy range 20 keV to 100 keV. Plots of the centroid energies, widths, and total yields of the CR peaks as a function of energy show the power law dependences of γ 1 5 , γ 1 7 , and γ 2 5 respectively. Except for the centroid energies and power-law dependence is only approximate. Agreement with experimental data is good for the centroid energies and only rough for the widths. Adequate experimental data for verifying the yield dependence on γ does not yet exist
Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.
1998-01-01
A code package consisting of the Monte Carlo Library MCLIB, the executing code MC RUN, the web application MC Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown
Monte Carlo simulation of the ARGO
International Nuclear Information System (INIS)
Depaola, G.O.
1997-01-01
We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)
Geometric Monte Carlo and black Janus geometries
Energy Technology Data Exchange (ETDEWEB)
Bak, Dongsu, E-mail: dsbak@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); B.W. Lee Center for Fields, Gravity & Strings, Institute for Basic Sciences, Daejeon 34047 (Korea, Republic of); Kim, Chanju, E-mail: cjkim@ewha.ac.kr [Department of Physics, Ewha Womans University, Seoul 03760 (Korea, Republic of); Kim, Kyung Kiu, E-mail: kimkyungkiu@gmail.com [Department of Physics, Sejong University, Seoul 05006 (Korea, Republic of); Department of Physics, College of Science, Yonsei University, Seoul 03722 (Korea, Republic of); Min, Hyunsoo, E-mail: hsmin@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); Song, Jeong-Pil, E-mail: jeong_pil_song@brown.edu [Department of Chemistry, Brown University, Providence, RI 02912 (United States)
2017-04-10
We describe an application of the Monte Carlo method to the Janus deformation of the black brane background. We present numerical results for three and five dimensional black Janus geometries with planar and spherical interfaces. In particular, we argue that the 5D geometry with a spherical interface has an application in understanding the finite temperature bag-like QCD model via the AdS/CFT correspondence. The accuracy and convergence of the algorithm are evaluated with respect to the grid spacing. The systematic errors of the method are determined using an exact solution of 3D black Janus. This numerical approach for solving linear problems is unaffected initial guess of a trial solution and can handle an arbitrary geometry under various boundary conditions in the presence of source fields.
Radiation Modeling with Direct Simulation Monte Carlo
Carlson, Ann B.; Hassan, H. A.
1991-01-01
Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.
Monte Carlo work at Argonne National Laboratory
International Nuclear Information System (INIS)
Gelbard, E.M.; Prael, R.E.
1974-01-01
A simple model of the Monte Carlo process is described and a (nonlinear) recursion relation between fission sources in successive generations is developed. From the linearized form of these recursion relations, it is possible to derive expressions for the mean square coefficients of error modes in the iterates and for correlation coefficients between fluctuations in successive generations. First-order nonlinear terms in the recursion relation are analyzed. From these nonlinear terms an expression for the bias in the eigenvalue estimator is derived, and prescriptions for measuring the bias are formulated. Plans for the development of the VIM code are reviewed, and the proposed treatment of small sample perturbations in VIM is described. 6 references. (U.S.)
Methods for Monte Carlo simulations of biomacromolecules.
Vitalis, Andreas; Pappu, Rohit V
2009-01-01
The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.
Monte Carlo modelling of TRIGA research reactor
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
PEPSI: a Monte Carlo generator for polarized leptoproduction
International Nuclear Information System (INIS)
Mankiewicz, L.
1992-01-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions) a Monte Carlo program for the polarized deep inelastic leptoproduction mediated by electromagnetic interaction. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering and requires the standard polarization-independent JETSET routines to perform fragmentation into final hadrons. (orig.)
Closed-shell variational quantum Monte Carlo simulation for the ...
African Journals Online (AJOL)
Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.
Efficiency and accuracy of Monte Carlo (importance) sampling
Waarts, P.H.
2003-01-01
Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed
Exponential convergence on a continuous Monte Carlo transport problem
International Nuclear Information System (INIS)
Booth, T.E.
1997-01-01
For more than a decade, it has been known that exponential convergence on discrete transport problems was possible using adaptive Monte Carlo techniques. An adaptive Monte Carlo method that empirically produces exponential convergence on a simple continuous transport problem is described
Multiple histogram method and static Monte Carlo sampling
Inda, M.A.; Frenkel, D.
2004-01-01
We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From
A Monte Carlo approach to combating delayed completion of ...
African Journals Online (AJOL)
The objective of this paper is to unveil the relevance of Monte Carlo critical path analysis in resolving problem of delays in scheduled completion of development projects. Commencing with deterministic network scheduling, Monte Carlo critical path analysis was advanced by assigning probability distributions to task times.
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
New Approaches and Applications for Monte Carlo Perturbation Theory
Energy Technology Data Exchange (ETDEWEB)
Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan; Leppänen, Jaakko; Palmiotti, Giuseppe; Salvatores, Massimo; Sen, Sonat; Shwageraus, Eugene; Fratoni, Massimiliano
2017-02-01
This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.
A Monte Carlo algorithm for the Vavilov distribution
International Nuclear Information System (INIS)
Yi, Chul-Young; Han, Hyon-Soo
1999-01-01
Using the convolution property of the inverse Laplace transform, an improved Monte Carlo algorithm for the Vavilov energy-loss straggling distribution of the charged particle is developed, which is relatively simple and gives enough accuracy to be used for most Monte Carlo applications
Neutron point-flux calculation by Monte Carlo
International Nuclear Information System (INIS)
Eichhorn, M.
1986-04-01
A survey of the usual methods for estimating flux at a point is given. The associated variance-reducing techniques in direct Monte Carlo games are explained. The multigroup Monte Carlo codes MC for critical systems and PUNKT for point source-point detector-systems are represented, and problems in applying the codes to practical tasks are discussed. (author)
Crop canopy BRDF simulation and analysis using Monte Carlo method
Huang, J.; Wu, B.; Tian, Y.; Zeng, Y.
2006-01-01
This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and
Monte Carlo codes use in neutron therapy; Application de codes Monte Carlo en neutrontherapie
Energy Technology Data Exchange (ETDEWEB)
Paquis, P.; Mokhtari, F.; Karamanoukian, D. [Hopital Pasteur, 06 - Nice (France); Pignol, J.P. [Hopital du Hasenrain, 68 - Mulhouse (France); Cuendet, P. [CEA Centre d' Etudes de Saclay, 91 - Gif-sur-Yvette (France). Direction des Reacteurs Nucleaires; Fares, G.; Hachem, A. [Faculte des Sciences, 06 - Nice (France); Iborra, N. [Centre Antoine-Lacassagne, 06 - Nice (France)
1998-04-01
Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)
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.
Research on perturbation based Monte Carlo reactor criticality search
International Nuclear Information System (INIS)
Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang
2013-01-01
Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)
Statistics of Monte Carlo methods used in radiation transport calculation
International Nuclear Information System (INIS)
Datta, D.
2009-01-01
Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport
Reconstruction of Monte Carlo replicas from Hessian parton distributions
Energy Technology Data Exchange (ETDEWEB)
Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)
2017-03-20
We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.
Monte Carlo Solutions for Blind Phase Noise Estimation
Directory of Open Access Journals (Sweden)
Çırpan Hakan
2009-01-01
Full Text Available This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN channels. The main contributions of the paper are (i the development of a Monte Carlo framework for phase noise estimation, with special attention to sequential importance sampling and Rao-Blackwellization, (ii the interpretation of existing Monte Carlo solutions within this generic framework, and (iii the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past, the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that, on one hand, the Monte Carlo phase noise estimators outperform the existing estimators and, on the other hand, our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions.
Linear filtering applied to Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Morrison, G.W.; Pike, D.H.; Petrie, L.M.
1975-01-01
A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed
Problems in radiation shielding calculations with Monte Carlo methods
International Nuclear Information System (INIS)
Ueki, Kohtaro
1985-01-01
The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)
Cluster monte carlo method for nuclear criticality safety calculation
International Nuclear Information System (INIS)
Pei Lucheng
1984-01-01
One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further
International Nuclear Information System (INIS)
Noh, Yeelyong; Chang, Kwangpil; Seo, Yutaek; Chang, Daejun
2014-01-01
This study proposes a new methodology that combines dynamic process simulation (DPS) and Monte Carlo simulation (MCS) to determine the design pressure of fuel storage tanks on LNG-fueled ships. Because the pressure of such tanks varies with time, DPS is employed to predict the pressure profile. Though equipment failure and subsequent repair affect transient pressure development, it is difficult to implement these features directly in the process simulation due to the randomness of the failure. To predict the pressure behavior realistically, MCS is combined with DPS. In MCS, discrete events are generated to create a lifetime scenario for a system. The combination of MCS with long-term DPS reveals the frequency of the exceedance pressure. The exceedance curve of the pressure provides risk-based information for determining the design pressure based on risk acceptance criteria, which may vary with different points of view. - Highlights: • The realistic operation scenario of the LNG FGS system is estimated by MCS. • In repeated MCS trials, the availability of the FGS system is evaluated. • The realistic pressure profile is obtained by the proposed methodology. • The exceedance curve provides risk-based information for determining design pressure
Precharattana, Monamorn; Nokkeaw, Arthorn; Triampo, Wannapong; Triampo, Darapond; Lenbury, Yongwimon
2011-07-01
Acquired Immunodeficiency Syndrome (AIDS) is responsible for millions of deaths worldwide. To date, many drug treatment regimens have been applied to AIDS patients but none has resulted in a successful cure. This is mainly due to the fact that free HIV particles are frequently in mutation, and infected CD4(+) T cells normally reside in the lymphoid tissue where they cannot (so far) be eradicated. We present a stochastic cellular automaton (CA) model to computationally study what could be an alternative treatment, namely Leukapheresis (LCAP), to remove HIV infected leukocytes in the lymphoid tissue. We base our investigations on Monte Carlo computer simulations. Our major objective is to investigate how the number of infected CD4(+) T cells changes in response to LCAP during the short-time (weeks) and long-time (years) scales of HIV/AIDS progression in an infected individual. To achieve our goal, we analyze the time evolution of the CD4(+) T cell population in the lymphoid tissue (i.e., the lymph node) for HIV dynamics in treatment situations with various starting times and frequencies and under a no treatment condition. Our findings suggest that the effectiveness of the treatment depends mainly on the treatment starting time and the frequency of the LCAP. Other factors (e.g., the removal proportion, the treatment duration, and the state of removed cells) that likely influence disease progression are subjects for further investigation. Copyright © 2011 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Kruschwitz, Craig; Ming Wu; Moy, Ken; Rochau, Greg
2008-01-01
We present here results of continued efforts to understand the performance of microchannel plate (MCP)-based, high-speed, gated, x-ray detectors. This work involves the continued improvement of a Monte Carlo simulation code to describe MCP performance coupled with experimental efforts to better characterize such detectors. Our goal is a quantitative description of MCP saturation behavior in both static and pulsed modes. We have developed a new model of charge buildup on the walls of the MCP channels and measured its effect on MCP gain. The results are compared to experimental data obtained with a short-pulse, high-intensity ultraviolet laser; these results clearly demonstrate MCP saturation behavior in both DC and pulsed modes. The simulations compare favorably to the experimental results. The dynamic range of the detectors in pulsed operation is of particular interest when fielding an MCP-based camera. By adjusting the laser flux we study the linear range of the camera. These results, too, are compared to our simulations
Spot: a new Monte Carlo solver for fast alpha particles
International Nuclear Information System (INIS)
Schneider, M.; Eriksson, L.G.; Basiuk, V.; Imbeaux, F.
2004-01-01
The predictive transport code CRONOS has been augmented by an orbit following Monte Carlo code, SPOT (Simulation of Particle Orbits in a Tokamak). The SPOT code simulates the dynamics of nonthermal particles, and takes into account effects of finite orbit width and collisional transport of fast ions. Recent developments indicate that it might be difficult to avoid, at least transiently, current holes in a reactor. They occur already on existing tokamaks during advanced tokamak scenarios. The SPOT code has been used to study the alpha particle behaviour in the presence of current holes for both JET and ITER relevant parameters. (authors)
Hybrid SN/Monte Carlo research and results
International Nuclear Information System (INIS)
Baker, R.S.
1993-01-01
The neutral particle transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S N ) and stochastic (Monte Carlo) methods are applied. The Monte Carlo and S N regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid Monte Carlo/S N method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S N is well suited for by themselves. The hybrid method has been successfully applied to realistic shielding problems. The vectorized Monte Carlo algorithm in the hybrid method has been ported to the massively parallel architecture of the Connection Machine. Comparisons of performance on a vector machine (Cray Y-MP) and the Connection Machine (CM-2) show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when realistic problems requiring variance reduction are considered. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well
Microcanonical Monte Carlo approach for computing melting curves by atomistic simulations
Davis, Sergio; Gutiérrez, Gonzalo
2017-01-01
We report microcanonical Monte Carlo simulations of melting and superheating of a generic, Lennard-Jones system starting from the crystalline phase. The isochoric curve, the melting temperature $T_m$ and the critical superheating temperature $T_{LS}$ obtained are in close agreement (well within the microcanonical temperature fluctuations) with standard molecular dynamics one-phase and two-phase methods. These results validate the use of microcanonical Monte Carlo to compute melting points, a ...
Sequential Monte Carlo simulation of collision risk in free flight air traffic
Blom, H.A.P.; Bakker, G.; Krystul, J.; Everdij, M.H.C.; Klein Obbink, B.; Klompstra, M.B.
2005-01-01
Within HYBRIDGE a novel approach in speeding up Monte Carlo simulation of rare events has been developed. In the current report this method is extended for application to simulating collisions with a stochastic dynamical model of an air traffic operational concept. Subsequently this extended Monte
Energy Technology Data Exchange (ETDEWEB)
Garcia-Molina, Rafael [Departamento de Fisica, Centro de Investigacion en Optica y Nanofisica (CIOyN), Universidad de Murcia, E-30100 Murcia (Spain); Abril, Isabel [Departament de Fisica Aplicada, Universitat d' Alacant, E-03080 Alacant (Spain); Heredia-Avalos, Santiago [Departament de Fisica, Enginyeria de Sistemes i Teoria del Senyal, Universitat d' Alacant, E-03080 Alacant (Spain); Kyriakou, Ioanna; Emfietzoglou, Dimitris, E-mail: rgm@um.es [Medical Physics Laboratory, University of Ioannina Medical School, GR-45110 Ioannina (Greece)
2011-10-07
We have evaluated the spatial distribution of energy deposition by proton beams in liquid water using the simulation code SEICS (Simulation of Energetic Ions and Clusters through Solids), which combines molecular dynamics and Monte Carlo techniques and includes the main interaction phenomena between the projectile and the target constituents: (i) the electronic stopping force due to energy loss to target electronic excitations, including fluctuations due to the energy-loss straggling, (ii) the elastic scattering with the target nuclei, with their corresponding energy loss and (iii) the dynamical changes in projectile charge state due to electronic capture and loss processes. An important feature of SEICS is the accurate account of the excitation spectrum of liquid water, based on a consistent solid-state description of its energy-loss-function over the whole energy and momentum space. We analyse how the above-mentioned interactions affect the depth distribution of the energy delivered in liquid water by proton beams with incident energies of the order of several MeV. Our simulations show that the position of the Bragg peak is determined mainly by the stopping power, whereas its width can be attributed to the energy-loss straggling. Multiple elastic scattering processes contribute slightly only at the distal part of the Bragg peak. The charge state of the projectiles only changes when approaching the end of their trajectories, i.e. near the Bragg peak. We have also simulated the proton-beam energy distribution at several depths in the liquid water target, and found that it is determined mainly by the fluctuation in the energy loss of the projectile, evaluated through the energy-loss straggling. We conclude that a proper description of the target excitation spectrum as well as the inclusion of the energy-loss straggling is essential in the calculation of the proton beam depth-dose distribution.
International Nuclear Information System (INIS)
Sadeghi, Mahmood; Kalantar, Mohsen
2014-01-01
Highlights: • Defining a DG dynamic planning problem. • Applying a new evolutionary algorithm called “CMAES” in planning process. • Considering electricity price and fuel price variation stochastic conditions. • Scenario generation and reduction with MCS and backward reduction programs. • Considering approximately all of the costs of the distribution system. - Abstract: This paper presents a dynamic DG planning problem considering uncertainties related to the intermittent nature of the DG technologies such as wind turbines and solar units in addition to the stochastic economic conditions. The stochastic economic situation includes the uncertainties related to the fuel and electricity price of each year. The Monte Carlo simulation is used to generate the possible scenarios of uncertain situations and the produced scenarios are reduced through backward reduction program. The aim of this paper is to maximize the revenue of the distribution system through the benefit cost analysis alongside the encouraging and punishment functions. In order to close to reality, the different growth rates for the planning period are selected. In this paper the Covariance Matrix Adaptation Evolutionary Strategy is introduced and is used to find the best planning scheme of the DG units. The different DG types are considered in the planning problem. The main assumption of this paper is that the DISCO is the owner of the distribution system and the DG units. The proposed method is tested on a 9 bus test distribution system and the results are compared with the known genetic algorithm and PSO methods to show the applicability of the CMAES method in this problem
International Nuclear Information System (INIS)
Garcia-Molina, Rafael; Abril, Isabel; Heredia-Avalos, Santiago; Kyriakou, Ioanna; Emfietzoglou, Dimitris
2011-01-01
We have evaluated the spatial distribution of energy deposition by proton beams in liquid water using the simulation code SEICS (Simulation of Energetic Ions and Clusters through Solids), which combines molecular dynamics and Monte Carlo techniques and includes the main interaction phenomena between the projectile and the target constituents: (i) the electronic stopping force due to energy loss to target electronic excitations, including fluctuations due to the energy-loss straggling, (ii) the elastic scattering with the target nuclei, with their corresponding energy loss and (iii) the dynamical changes in projectile charge state due to electronic capture and loss processes. An important feature of SEICS is the accurate account of the excitation spectrum of liquid water, based on a consistent solid-state description of its energy-loss-function over the whole energy and momentum space. We analyse how the above-mentioned interactions affect the depth distribution of the energy delivered in liquid water by proton beams with incident energies of the order of several MeV. Our simulations show that the position of the Bragg peak is determined mainly by the stopping power, whereas its width can be attributed to the energy-loss straggling. Multiple elastic scattering processes contribute slightly only at the distal part of the Bragg peak. The charge state of the projectiles only changes when approaching the end of their trajectories, i.e. near the Bragg peak. We have also simulated the proton-beam energy distribution at several depths in the liquid water target, and found that it is determined mainly by the fluctuation in the energy loss of the projectile, evaluated through the energy-loss straggling. We conclude that a proper description of the target excitation spectrum as well as the inclusion of the energy-loss straggling is essential in the calculation of the proton beam depth-dose distribution.
Directory of Open Access Journals (Sweden)
R. B. Pandey
2015-09-01
Full Text Available The self-organizing dynamics of lysozymes (an amyloid protein with 148 residues with different numbers of protein chains, Nc = 1,5,10, and 15 (concentration 0.004 – 0.063 is studied by a coarse-grained Monte Carlo simulation with knowledge-based residue-residue interactions. The dynamics of an isolated lysozyme (Nc = 1 is ultra-slow (quasi-static at low temperatures and becomes diffusive asymptotically on raising the temperature. In contrast, the presence of interacting proteins leads to concentration induced protein diffusion at low temperatures and concentration-tempering sub-diffusion at high temperatures. Variation of the radius of gyration of the protein with temperature shows a systematic transition from a globular structure (at low T to a random coil (high T conformation when the proteins are isolated. The crossover from globular to random coil becomes sharper upon increasing the protein concentration (i.e. with Nc = 5,10, with larger Rg at higher temperatures and concentration; Rg becomes smaller on adding more protein chains (e.g. Nc = 15 a non-monotonic response to protein concentration. Analysis of the structure factor (S(q provides an estimate of the effective dimension (D ≥ 3, globular conformation at low temperature, and D ∼ 1.7, random coil, at high temperatures of the isolated protein. With many interacting proteins, the morphology of the self-assembly varies with scale, i.e. at the low temperature (T = 0.015, D ∼ 2.9 on the scale comparable to the radius of gyration of the protein, and D ∼ 2.3 at the large scale over the entire sample. The global network of fibrils appears at high temperature (T = 0.021 with D ∼ 1.7 (i.e. a random coil morphology at large scale involving tenuous distribution of micro-globules (at small scales.
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
International Nuclear Information System (INIS)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Monte Carlo based diffusion coefficients for LMFBR analysis
International Nuclear Information System (INIS)
Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira
2010-01-01
A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)
Present status and future prospects of neutronics Monte Carlo
International Nuclear Information System (INIS)
Gelbard, E.M.
1990-01-01
It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)
International Nuclear Information System (INIS)
Thireou, Trias; Rubio Guivernau, Jose Luis; Atlamazoglou, Vassilis; Ledesma, Maria Jesus; Pavlopoulos, Sotiris; Santos, Andres; Kontaxakis, George
2006-01-01
A realistic dynamic positron-emission tomography (PET) thoracic study was generated, using the 4D NURBS-based (non-uniform rational B-splines) cardiac-torso (NCAT) phantom and a sophisticated model of the PET imaging process, simulating two solitary pulmonary nodules. Three data reduction and blind source separation methods were applied to the simulated data: principal component analysis, independent component analysis and similarity mapping. All methods reduced the initial amount of image data to a smaller, comprehensive and easily managed set of parametric images, where structures were separated based on their different kinetic characteristics and the lesions were readily identified. The results indicate that the above-mentioned methods can provide an accurate tool for the support of both visual inspection and subsequent detailed kinetic analysis of the dynamic series via compartmental or non-compartmental models
A radiating shock evaluated using Implicit Monte Carlo Diffusion
International Nuclear Information System (INIS)
Cleveland, M.; Gentile, N.
2013-01-01
Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)
Recommender engine for continuous-time quantum Monte Carlo methods
Huang, Li; Yang, Yi-feng; Wang, Lei
2017-03-01
Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.
Discrete Diffusion Monte Carlo for Electron Thermal Transport
Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory
2014-10-01
The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.
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
Neutron flux calculation by means of Monte Carlo methods
International Nuclear Information System (INIS)
Barz, H.U.; Eichhorn, M.
1988-01-01
In this report a survey of modern neutron flux calculation procedures by means of Monte Carlo methods is given. Due to the progress in the development of variance reduction techniques and the improvements of computational techniques this method is of increasing importance. The basic ideas in application of Monte Carlo methods are briefly outlined. In more detail various possibilities of non-analog games and estimation procedures are presented, problems in the field of optimizing the variance reduction techniques are discussed. In the last part some important international Monte Carlo codes and own codes of the authors are listed and special applications are described. (author)
Uncertainty Propagation in Monte Carlo Depletion Analysis
International Nuclear Information System (INIS)
Shim, Hyung Jin; Kim, Yeong-il; Park, Ho Jin; Joo, Han Gyu; Kim, Chang Hyo
2008-01-01
A new formulation aimed at quantifying uncertainties of Monte Carlo (MC) tallies such as k eff and the microscopic reaction rates of nuclides and nuclide number densities in MC depletion analysis and examining their propagation behaviour as a function of depletion time step (DTS) is presented. It is shown that the variance of a given MC tally used as a measure of its uncertainty in this formulation arises from four sources; the statistical uncertainty of the MC tally, uncertainties of microscopic cross sections and nuclide number densities, and the cross correlations between them and the contribution of the latter three sources can be determined by computing the correlation coefficients between the uncertain variables. It is also shown that the variance of any given nuclide number density at the end of each DTS stems from uncertainties of the nuclide number densities (NND) and microscopic reaction rates (MRR) of nuclides at the beginning of each DTS and they are determined by computing correlation coefficients between these two uncertain variables. To test the viability of the formulation, we conducted MC depletion analysis for two sample depletion problems involving a simplified 7x7 fuel assembly (FA) and a 17x17 PWR FA, determined number densities of uranium and plutonium isotopes and their variances as well as k ∞ and its variance as a function of DTS, and demonstrated the applicability of the new formulation for uncertainty propagation analysis that need be followed in MC depletion computations. (authors)
Pseudopotentials for quantum-Monte-Carlo-calculations
International Nuclear Information System (INIS)
Burkatzki, Mark Thomas
2008-01-01
The author presents scalar-relativistic energy-consistent Hartree-Fock pseudopotentials for the main-group and 3d-transition-metal elements. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The author demonstrates their transferability through extensive benchmark calculations of atomic excitation spectra as well as molecular properties. In particular, the author computes the vibrational frequencies and binding energies of 26 first- and second-row diatomic molecules using post Hartree-Fock methods, finding excellent agreement with the corresponding all-electron values. The author shows that the presented pseudopotentials give superior accuracy than other existing pseudopotentials constructed specifically for QMC. The localization error and the efficiency in QMC are discussed. The author also presents QMC calculations for selected atomic and diatomic 3d-transitionmetal systems. Finally, valence basis sets of different sizes (VnZ with n=D,T,Q,5 for 1st and 2nd row; with n=D,T for 3rd to 5th row; with n=D,T,Q for the 3d transition metals) optimized for the pseudopotentials are presented. (orig.)
SERPENT Monte Carlo reactor physics code
International Nuclear Information System (INIS)
Leppaenen, J.
2010-01-01
SERPENT is a three-dimensional continuous-energy Monte Carlo reactor physics burnup calculation code, developed at VTT Technical Research Centre of Finland since 2004. The code is specialized in lattice physics applications, but the universe-based geometry description allows transport simulation to be carried out in complicated three-dimensional geometries as well. The suggested applications of SERPENT include generation of homogenized multi-group constants for deterministic reactor simulator calculations, fuel cycle studies involving detailed assembly-level burnup calculations, validation of deterministic lattice transport codes, research reactor applications, educational purposes and demonstration of reactor physics phenomena. The Serpent code has been publicly distributed by the OECD/NEA Data Bank since May 2009 and RSICC in the U. S. since March 2010. The code is being used in some 35 organizations in 20 countries around the world. This paper presents an overview of the methods and capabilities of the Serpent code, with examples in the modelling of WWER-440 reactor physics. (Author)
A continuation multilevel Monte Carlo algorithm
Collier, Nathan
2014-09-05
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.
Radon counting statistics - a Monte Carlo investigation
International Nuclear Information System (INIS)
Scott, A.G.
1996-01-01
Radioactive decay is a Poisson process, and so the Coefficient of Variation (COV) of open-quotes nclose quotes counts of a single nuclide is usually estimated as 1/√n. This is only true if the count duration is much shorter than the half-life of the nuclide. At longer count durations, the COV is smaller than the Poisson estimate. Most radon measurement methods count the alpha decays of 222 Rn, plus the progeny 218 Po and 214 Po, and estimate the 222 Rn activity from the sum of the counts. At long count durations, the chain decay of these nuclides means that every 222 Rn decay must be followed by two other alpha decays. The total number of decays is open-quotes 3Nclose quotes, where N is the number of radon decays, and the true COV of the radon concentration estimate is 1/√(N), √3 larger than the Poisson total count estimate of 1/√3N. Most count periods are comparable to the half lives of the progeny, so the relationship between COV and count time is complex. A Monte-Carlo estimate of the ratio of true COV to Poisson estimate was carried out for a range of count periods from 1 min to 16 h and three common radon measurement methods: liquid scintillation, scintillation cell, and electrostatic precipitation of progeny. The Poisson approximation underestimates COV by less than 20% for count durations of less than 60 min
Monte Carlo simulations for heavy ion dosimetry
Energy Technology Data Exchange (ETDEWEB)
Geithner, O.
2006-07-26
Water-to-air stopping power ratio (s{sub w,air}) 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 variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)
The Monte Carlo calculation of gamma family
International Nuclear Information System (INIS)
Shibata, Makio
1980-01-01
The method of the Monte Carlo calculation for gamma family was investigated. The effects of the variation of values or terms of parameters on observed quantities were studied. The terms taken for the standard calculation are the scaling law for the model, simple proton spectrum for primary cosmic ray, a constant cross section of interaction, zero probability of neutral pion production, and the bending of the curve of primary energy spectrum. This is called S model. Calculations were made by changing one of above mentioned parameters. The chamber size, the mixing of gamma and hadrons, and the family size were fitted to the practical ECC data. When the model was changed from the scaling law to the CKP model, the energy spectrum of the family was able to be expressed by the CKP model better than the scaling law. The scaling law was better in the symmetry around the family center. It was denied that primary cosmic ray mostly consists of heavy particles. The increase of the interaction cross section was necessary in view of the frequency of the families. (Kato, T.)
Monte Carlo Production Management at CMS
Boudoul, G.; Pol, A; Srimanobhas, P; Vlimant, J R; Franzoni, Giovanni
2015-01-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events.During the runI of LHC (2010-2012), CMS has produced over 12 Billion simulated events,organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up).In order toaggregate the information needed for the configuration and prioritization of the events production,assure the book-keeping and of all the processing requests placed by the physics analysis groups,and to interface with the CMS production infrastructure,the web-based service Monte Carlo Management (McM) has been developed and put in production in 2012.McM is based on recent server infrastructure technology (CherryPy + java) and relies on a CouchDB database back-end.This contribution will coverthe one and half year of operational experience managing samples of simulated events for CMS,the evolution of its functionalitiesand the extension of its capabi...
Monte Carlo benchmarking: Validation and progress
International Nuclear Information System (INIS)
Sala, P.
2010-01-01
Document available in abstract form only. Full text of publication follows: Calculational tools for radiation shielding at accelerators are faced with new challenges from the present and next generations of particle accelerators. All the details of particle production and transport play a role when dealing with huge power facilities, therapeutic ion beams, radioactive beams and so on. Besides the traditional calculations required for shielding, activation predictions have become an increasingly critical component. Comparison and benchmarking with experimental data is obviously mandatory in order to build up confidence in the computing tools, and to assess their reliability and limitations. Thin target particle production data are often the best tools for understanding the predictive power of individual interaction models and improving their performances. Complex benchmarks (e.g. thick target data, deep penetration, etc.) are invaluable in assessing the overall performances of calculational tools when all ingredients are put at work together. A review of the validation procedures of Monte Carlo tools will be presented with practical and real life examples. The interconnections among benchmarks, model development and impact on shielding calculations will be highlighted. (authors)
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. ...
The GENIE neutrino Monte Carlo generator
International Nuclear Information System (INIS)
Andreopoulos, C.; Bell, A.; Bhattacharya, D.; Cavanna, F.; Dobson, J.; Dytman, S.; Gallagher, H.; Guzowski, P.; Hatcher, R.; Kehayias, P.; Meregaglia, A.; Naples, D.; Pearce, G.; Rubbia, A.; Whalley, M.; Yang, T.
2010-01-01
GENIE is a new neutrino event generator for the experimental neutrino physics community. The goal of the project is to develop a 'canonical' neutrino interaction physics Monte Carlo whose validity extends to all nuclear targets and neutrino flavors from MeV to PeV energy scales. Currently, emphasis is on the few-GeV energy range, the challenging boundary between the non-perturbative and perturbative regimes, which is relevant for the current and near future long-baseline precision neutrino experiments using accelerator-made beams. The design of the package addresses many challenges unique to neutrino simulations and supports the full life-cycle of simulation and generator-related analysis tasks. GENIE is a large-scale software system, consisting of ∼120000 lines of C++ code, featuring a modern object-oriented design and extensively validated physics content. The first official physics release of GENIE was made available in August 2007, and at the time of the writing of this article, the latest available version was v2.4.4.
Quantum Monte Carlo: Faster, More Reliable, And More Accurate
Anderson, Amos Gerald
2010-06-01
The Schrodinger Equation has been available for about 83 years, but today, we still strain to apply it accurately to molecules of interest. The difficulty is not theoretical in nature, but practical, since we're held back by lack of sufficient computing power. Consequently, effort is applied to find acceptable approximations to facilitate real time solutions. In the meantime, computer technology has begun rapidly advancing and changing the way we think about efficient algorithms. For those who can reorganize their formulas to take advantage of these changes and thereby lift some approximations, incredible new opportunities await. Over the last decade, we've seen the emergence of a new kind of computer processor, the graphics card. Designed to accelerate computer games by optimizing quantity instead of quality in processor, they have become of sufficient quality to be useful to some scientists. In this thesis, we explore the first known use of a graphics card to computational chemistry by rewriting our Quantum Monte Carlo software into the requisite "data parallel" formalism. We find that notwithstanding precision considerations, we are able to speed up our software by about a factor of 6. The success of a Quantum Monte Carlo calculation depends on more than just processing power. It also requires the scientist to carefully design the trial wavefunction used to guide simulated electrons. We have studied the use of Generalized Valence Bond wavefunctions to simply, and yet effectively, captured the essential static correlation in atoms and molecules. Furthermore, we have developed significantly improved two particle correlation functions, designed with both flexibility and simplicity considerations, representing an effective and reliable way to add the necessary dynamic correlation. Lastly, we present our method for stabilizing the statistical nature of the calculation, by manipulating configuration weights, thus facilitating efficient and robust calculations. Our
Monte Carlo Wave Packet Theory of Dissociative Double Ionization
DEFF Research Database (Denmark)
Leth, Henriette Astrup; Madsen, Lars Bojer; Mølmer, Klaus
2009-01-01
Nuclear dynamics in strong-field double ionization processes is predicted using a stochastic Monte Carlo wave packet technique. Using input from electronic structure calculations and strong-field electron dynamics the description allows for field-dressed dynamics within a given molecule as well...
Ottosson, R O; Karlsson, A; Behrens, C F
2010-08-21
The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a
Energy Technology Data Exchange (ETDEWEB)
Ottosson, R O; Karlsson, A; Behrens, C F, E-mail: riolot01@heh.regionh.d [Department of Oncology (R), Division of Radiophysics (52AA), Copenhagen University Hospital Herlev, Herlev Ringvej 75, DK-2730 Herlev (Denmark)
2010-08-21
The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a
International Nuclear Information System (INIS)
Ottosson, R O; Karlsson, A; Behrens, C F
2010-01-01
The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a
Directory of Open Access Journals (Sweden)
Meagan C Small
Full Text Available Resistance to macrolide antibiotics is conferred by mutation of A2058 to G or methylation by Erm methyltransferases of the exocyclic N6 of A2058 (E. coli numbering that forms the macrolide binding site in the 50S subunit of the ribosome. Ketolides such as telithromycin mitigate A2058G resistance yet remain susceptible to Erm-based resistance. Molecular details associated with macrolide resistance due to the A2058G mutation and methylation at N6 of A2058 by Erm methyltransferases were investigated using empirical force field-based simulations. To address the buried nature of the macrolide binding site, the number of waters within the pocket was allowed to fluctuate via the use of a Grand Canonical Monte Carlo (GCMC methodology. The GCMC water insertion/deletion steps were alternated with Molecular Dynamics (MD simulations to allow for relaxation of the entire system. From this GCMC/MD approach information on the interactions between telithromycin and the 50S ribosome was obtained. In the wild-type (WT ribosome, the 2'-OH to A2058 N1 hydrogen bond samples short distances with a higher probability, while the effectiveness of telithromycin against the A2058G mutation is explained by a rearrangement of the hydrogen bonding pattern of the 2'-OH to 2058 that maintains the overall antibiotic-ribosome interactions. In both the WT and A2058G mutation there is significant flexibility in telithromycin's imidazole-pyridine side chain (ARM, indicating that entropic effects contribute to the binding affinity. Methylated ribosomes show lower sampling of short 2'-OH to 2058 distances and also demonstrate enhanced G2057-A2058 stacking leading to disrupted A752-U2609 Watson-Crick (WC interactions as well as hydrogen bonding between telithromycin's ARM and U2609. This information will be of utility in the rational design of novel macrolide analogs with improved activity against methylated A2058 ribosomes.
MORGENSTERN, [No Value; FRICK, M; VONDERLINDEN, W
We present quantum simulation studies for a system of strongly correlated fermions coupled to local anharmonic phonons. The Monte Carlo calculations are based on a generalized version of the Projector Quantum Monte Carlo Method allowing a simultaneous treatment of fermions and dynamical phonons. The
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.
2010-01-01
model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order
Time step length versus efficiency of Monte Carlo burnup calculations
International Nuclear Information System (INIS)
Dufek, Jan; Valtavirta, Ville
2014-01-01
Highlights: • Time step length largely affects efficiency of MC burnup calculations. • Efficiency of MC burnup calculations improves with decreasing time step length. • Results were obtained from SIE-based Monte Carlo burnup calculations. - Abstract: We demonstrate that efficiency of Monte Carlo burnup calculations can be largely affected by the selected time step length. This study employs the stochastic implicit Euler based coupling scheme for Monte Carlo burnup calculations that performs a number of inner iteration steps within each time step. In a series of calculations, we vary the time step length and the number of inner iteration steps; the results suggest that Monte Carlo burnup calculations get more efficient as the time step length is reduced. More time steps must be simulated as they get shorter; however, this is more than compensated by the decrease in computing cost per time step needed for achieving a certain accuracy
GE781: a Monte Carlo package for fixed target experiments
Davidenko, G.; Funk, M. A.; Kim, V.; Kuropatkin, N.; Kurshetsov, V.; Molchanov, V.; Rud, S.; Stutte, L.; Verebryusov, V.; Zukanovich Funchal, R.
The Monte Carlo package for the fixed target experiment B781 at Fermilab, a third generation charmed baryon experiment, is described. This package is based on GEANT 3.21, ADAMO database and DAFT input/output routines.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.
Optix: A Monte Carlo scintillation light transport code
Energy Technology Data Exchange (ETDEWEB)
Safari, M.J., E-mail: mjsafari@aut.ac.ir [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Afarideh, H. [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Ghal-Eh, N. [School of Physics, Damghan University, PO Box 36716-41167, Damghan (Iran, Islamic Republic of); Davani, F. Abbasi [Nuclear Engineering Department, Shahid Beheshti University, PO Box 1983963113, Tehran (Iran, Islamic Republic of)
2014-02-11
The paper reports on the capabilities of Monte Carlo scintillation light transport code Optix, which is an extended version of previously introduced code Optics. Optix provides the user a variety of both numerical and graphical outputs with a very simple and user-friendly input structure. A benchmarking strategy has been adopted based on the comparison with experimental results, semi-analytical solutions, and other Monte Carlo simulation codes to verify various aspects of the developed code. Besides, some extensive comparisons have been made against the tracking abilities of general-purpose MCNPX and FLUKA codes. The presented benchmark results for the Optix code exhibit promising agreements. -- Highlights: • Monte Carlo simulation of scintillation light transport in 3D geometry. • Evaluation of angular distribution of detected photons. • Benchmark studies to check the accuracy of Monte Carlo simulations.
Dosimetric measurements and Monte Carlo simulation for achieving ...
Indian Academy of Sciences (India)
Research Articles Volume 74 Issue 3 March 2010 pp 457-468 ... Food irradiation; electron accelerator; Monte Carlo; dose uniformity. ... for radiation processing of food and medical products is being commissioned at our centre in Indore, India.
Usefulness of the Monte Carlo method in reliability calculations
International Nuclear Information System (INIS)
Lanore, J.M.; Kalli, H.
1977-01-01
Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels
Monte Carlo techniques for analyzing deep penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications
Suppression of the initial transient in Monte Carlo criticality simulations
International Nuclear Information System (INIS)
Richet, Y.
2006-12-01
Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)
Monte Carlo calculations of electron diffusion in materials
International Nuclear Information System (INIS)
Schroeder, U.G.
1976-01-01
By means of simulated experiments, various transport problems for 10 Mev electrons are investigated. For this purpose, a special Monte-Carlo programme is developed, and with this programme calculations are made for several material arrangements. (orig./LN) [de
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)
2013-07-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
International Nuclear Information System (INIS)
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.
2013-01-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Calculation of toroidal fusion reactor blankets by Monte Carlo
International Nuclear Information System (INIS)
Macdonald, J.L.; Cashwell, E.D.; Everett, C.J.
1977-01-01
A brief description of the calculational method is given. The code calculates energy deposition in toroidal geometry, but is a continuous energy Monte Carlo code, treating the reaction cross sections as well as the angular scattering distributions in great detail
The Monte Carlo simulation of the Ladon photon beam facility
International Nuclear Information System (INIS)
Strangio, C.
1976-01-01
The backward compton scattering of laser light against high energy electrons has been simulated with a Monte Carlo method. The main features of the produced photon beam are reported as well as a careful description of the numerical calculation
Monte Carlo variance reduction approaches for non-Boltzmann tallies
International Nuclear Information System (INIS)
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed
Monte Carlo techniques for analyzing deep penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs
Combinatorial nuclear level density by a Monte Carlo method
International Nuclear Information System (INIS)
Cerf, N.
1994-01-01
We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki
2015-01-01
informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method
Studies of Monte Carlo Modelling of Jets at ATLAS
Kar, Deepak; The ATLAS collaboration
2017-01-01
The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets. Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.
Herwig: The Evolution of a Monte Carlo Simulation
CERN. Geneva
2015-01-01
Monte Carlo event generation has seen significant developments in the last 10 years starting with preparation for the LHC and then during the first LHC run. I will discuss the basic ideas behind Monte Carlo event generators and then go on to discuss these developments, focussing on the developments in Herwig(++) event generator. I will conclude by presenting the current status of event generation together with some results of the forthcoming new version of Herwig, Herwig 7.
Clinical considerations of Monte Carlo for electron radiotherapy treatment planning
International Nuclear Information System (INIS)
Faddegon, Bruce; Balogh, Judith; Mackenzie, Robert; Scora, Daryl
1998-01-01
Technical requirements for Monte Carlo based electron radiotherapy treatment planning are outlined. The targeted overall accuracy for estimate of the delivered dose is the least restrictive of 5% in dose, 5 mm in isodose position. A system based on EGS4 and capable of achieving this accuracy is described. Experience gained in system design and commissioning is summarized. The key obstacle to widespread clinical use of Monte Carlo is lack of clinically acceptable measurement based methodology for accurate commissioning
Monte Carlo method for solving a parabolic problem
Directory of Open Access Journals (Sweden)
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
NUEN-618 Class Project: Actually Implicit Monte Carlo
Energy Technology Data Exchange (ETDEWEB)
Vega, R. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunner, T. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-12-14
This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.
Monte Carlo methods and applications in nuclear physics
International Nuclear Information System (INIS)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs
Monte Carlo methods and applications in nuclear physics
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Study of the Transition Flow Regime using Monte Carlo Methods
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Modern analysis of ion channeling data by Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)
2005-10-15
Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.
Monte Carlos of the new generation: status and progress
International Nuclear Information System (INIS)
Frixione, Stefano
2005-01-01
Standard parton shower monte carlos are designed to give reliable descriptions of low-pT physics. In the very high-energy regime of modern colliders, this is may lead to largely incorrect predictions of the basic reaction processes. This motivated the recent theoretical efforts aimed at improving monte carlos through the inclusion of matrix elements computed beyond the leading order in QCD. I briefly review the progress made, and discuss bottom production at the Tevatron
Monte carlo sampling of fission multiplicity.
Energy Technology Data Exchange (ETDEWEB)
Hendricks, J. S. (John S.)
2004-01-01
Two new methods have been developed for fission multiplicity modeling in Monte Carlo calculations. The traditional method of sampling neutron multiplicity from fission is to sample the number of neutrons above or below the average. For example, if there are 2.7 neutrons per fission, three would be chosen 70% of the time and two would be chosen 30% of the time. For many applications, particularly {sup 3}He coincidence counting, a better estimate of the true number of neutrons per fission is required. Generally, this number is estimated by sampling a Gaussian distribution about the average. However, because the tail of the Gaussian distribution is negative and negative neutrons cannot be produced, a slight positive bias can be found in the average value. For criticality calculations, the result of rejecting the negative neutrons is an increase in k{sub eff} of 0.1% in some cases. For spontaneous fission, where the average number of neutrons emitted from fission is low, the error also can be unacceptably large. If the Gaussian width approaches the average number of fissions, 10% too many fission neutrons are produced by not treating the negative Gaussian tail adequately. The first method to treat the Gaussian tail is to determine a correction offset, which then is subtracted from all sampled values of the number of neutrons produced. This offset depends on the average value for any given fission at any energy and must be computed efficiently at each fission from the non-integrable error function. The second method is to determine a corrected zero point so that all neutrons sampled between zero and the corrected zero point are killed to compensate for the negative Gaussian tail bias. Again, the zero point must be computed efficiently at each fission. Both methods give excellent results with a negligible computing time penalty. It is now possible to include the full effects of fission multiplicity without the negative Gaussian tail bias.
Dosimetry applications in GATE Monte Carlo toolkit.
Papadimitroulas, Panagiotis
2017-09-01
Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Continuous-time quantum Monte Carlo impurity solvers
Gull, Emanuel; Werner, Philipp; Fuchs, Sebastian; Surer, Brigitte; Pruschke, Thomas; Troyer, Matthias
2011-04-01
Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states. Program summaryProgram title: dmft Catalogue identifier: AEIL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: ALPS LIBRARY LICENSE version 1.1 No. of lines in distributed program, including test data, etc.: 899 806 No. of bytes in distributed program, including test data, etc.: 32 153 916 Distribution format: tar.gz Programming language: C++ Operating system: The ALPS libraries have been tested on the following platforms and compilers: Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher) MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0) IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers Compaq Tru64 UNIX with Compq C++ Compiler (cxx) SGI IRIX with MIPSpro C++ Compiler (CC) HP-UX with HP C++ Compiler (aCC) Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher) RAM: 10 MB-1 GB Classification: 7.3 External routines: ALPS [1], BLAS/LAPACK, HDF5 Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as
Pore-scale uncertainty quantification with multilevel Monte Carlo
Icardi, Matteo
2014-01-06
Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.
Adaptive time-stepping Monte Carlo integration of Coulomb collisions
Särkimäki, K.; Hirvijoki, E.; Terävä, J.
2018-01-01
We report an accessible and robust tool for evaluating the effects of Coulomb collisions on a test particle in a plasma that obeys Maxwell-Jüttner statistics. The implementation is based on the Beliaev-Budker collision integral which allows both the test particle and the background plasma to be relativistic. The integration method supports adaptive time stepping, which is shown to greatly improve the computational efficiency. The Monte Carlo method is implemented for both the three-dimensional particle momentum space and the five-dimensional guiding center phase space. Detailed description is provided for both the physics and implementation of the operator. The focus is in adaptive integration of stochastic differential equations, which is an overlooked aspect among existing Monte Carlo implementations of Coulomb collision operators. We verify that our operator converges to known analytical results and demonstrate that careless implementation of the adaptive time step can lead to severely erroneous results. The operator is provided as a self-contained Fortran 95 module and can be included into existing orbit-following tools that trace either the full Larmor motion or the guiding center dynamics. The adaptive time-stepping algorithm is expected to be useful in situations where the collision frequencies vary greatly over the course of a simulation. Examples include the slowing-down of fusion products or other fast ions, and the Dreicer generation of runaway electrons as well as the generation of fast ions or electrons with ion or electron cyclotron resonance heating.
A Monte Carlo dose calculation tool for radiotherapy treatment planning
International Nuclear Information System (INIS)
Ma, C.-M.; Li, J.S.; Pawlicki, T.; Jiang, S.B.; Deng, J.; Lee, M.C.; Koumrian, T.; Luxton, M.; Brain, S.
2002-01-01
A Monte Carlo user code, MCDOSE, has been developed for radiotherapy treatment planning (RTP) dose calculations. MCDOSE is designed as a dose calculation module suitable for adaptation to host RTP systems. MCDOSE can be used for both conventional photon/electron beam calculation and intensity modulated radiotherapy (IMRT) treatment planning. MCDOSE uses a multiple-source model to reconstruct the treatment beam phase space. Based on Monte Carlo simulated or measured beam data acquired during commissioning, source-model parameters are adjusted through an automated procedure. Beam modifiers such as jaws, physical and dynamic wedges, compensators, blocks, electron cut-outs and bolus are simulated by MCDOSE together with a 3D rectilinear patient geometry model built from CT data. Dose distributions calculated using MCDOSE agreed well with those calculated by the EGS4/DOSXYZ code using different beam set-ups and beam modifiers. Heterogeneity correction factors for layered-lung or layered-bone phantoms as calculated by both codes were consistent with measured data to within 1%. The effect of energy cut-offs for particle transport was investigated. Variance reduction techniques were implemented in MCDOSE to achieve a speedup factor of 10-30 compared to DOSXYZ. (author)
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul
2015-01-01
Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki
2015-01-07
Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments
International Nuclear Information System (INIS)
Pevey, Ronald E.
2005-01-01
Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL
Alternative implementations of the Monte Carlo power method
International Nuclear Information System (INIS)
Blomquist, R.N.; Gelbard, E.M.
2002-01-01
We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency
Present status of transport code development based on Monte Carlo method
International Nuclear Information System (INIS)
Nakagawa, Masayuki
1985-01-01
The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)
Monte Carlo systems used for treatment planning and dose verification
Energy Technology Data Exchange (ETDEWEB)
Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)
2017-04-15
General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo
Monte Carlo Techniques for Nuclear Systems - Theory Lectures
International Nuclear Information System (INIS)
Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM
2016-01-01
These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations
Monte Carlo Techniques for Nuclear Systems - Theory Lectures
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.
2016-11-29
These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations
Meaningful timescales from Monte Carlo simulations of particle systems with hard-core interactions
Energy Technology Data Exchange (ETDEWEB)
Costa, Liborio I., E-mail: liborio78@gmail.com
2016-12-01
A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.
Nonlinear Spatial Inversion Without Monte Carlo Sampling
Curtis, A.; Nawaz, A.
2017-12-01
High-dimensional, nonlinear inverse or inference problems usually have non-unique solutions. The distribution of solutions are described by probability distributions, and these are usually found using Monte Carlo (MC) sampling methods. These take pseudo-random samples of models in parameter space, calculate the probability of each sample given available data and other information, and thus map out high or low probability values of model parameters. However, such methods would converge to the solution only as the number of samples tends to infinity; in practice, MC is found to be slow to converge, convergence is not guaranteed to be achieved in finite time, and detection of convergence requires the use of subjective criteria. We propose a method for Bayesian inversion of categorical variables such as geological facies or rock types in spatial problems, which requires no sampling at all. The method uses a 2-D Hidden Markov Model over a grid of cells, where observations represent localized data constraining the model in each cell. The data in our example application are seismic properties such as P- and S-wave impedances or rock density; our model parameters are the hidden states and represent the geological rock types in each cell. The observations at each location are assumed to depend on the facies at that location only - an assumption referred to as `localized likelihoods'. However, the facies at a location cannot be determined solely by the observation at that location as it also depends on prior information concerning its correlation with the spatial distribution of facies elsewhere. Such prior information is included in the inversion in the form of a training image which represents a conceptual depiction of the distribution of local geologies that might be expected, but other forms of prior information can be used in the method as desired. The method provides direct (pseudo-analytic) estimates of posterior marginal probability distributions over each variable
A residual Monte Carlo method for discrete thermal radiative diffusion
International Nuclear Information System (INIS)
Evans, T.M.; Urbatsch, T.J.; Lichtenstein, H.; Morel, J.E.
2003-01-01
Residual Monte Carlo methods reduce statistical error at a rate of exp(-bN), where b is a positive constant and N is the number of particle histories. Contrast this convergence rate with 1/√N, which is the rate of statistical error reduction for conventional Monte Carlo methods. Thus, residual Monte Carlo methods hold great promise for increased efficiency relative to conventional Monte Carlo methods. Previous research has shown that the application of residual Monte Carlo methods to the solution of continuum equations, such as the radiation transport equation, is problematic for all but the simplest of cases. However, the residual method readily applies to discrete systems as long as those systems are monotone, i.e., they produce positive solutions given positive sources. We develop a residual Monte Carlo method for solving a discrete 1D non-linear thermal radiative equilibrium diffusion equation, and we compare its performance with that of the discrete conventional Monte Carlo method upon which it is based. We find that the residual method provides efficiency gains of many orders of magnitude. Part of the residual gain is due to the fact that we begin each timestep with an initial guess equal to the solution from the previous timestep. Moreover, fully consistent non-linear solutions can be obtained in a reasonable amount of time because of the effective lack of statistical noise. We conclude that the residual approach has great potential and that further research into such methods should be pursued for more general discrete and continuum systems
International Nuclear Information System (INIS)
Xu, Zuwei; Zhao, Haibo; Zheng, Chuguang
2015-01-01
This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are
bhlight: GENERAL RELATIVISTIC RADIATION MAGNETOHYDRODYNAMICS WITH MONTE CARLO TRANSPORT
International Nuclear Information System (INIS)
Ryan, B. R.; Gammie, C. F.; Dolence, J. C.
2015-01-01
We present bhlight, a numerical scheme for solving the equations of general relativistic radiation magnetohydrodynamics using a direct Monte Carlo solution of the frequency-dependent radiative transport equation. bhlight is designed to evolve black hole accretion flows at intermediate accretion rate, in the regime between the classical radiatively efficient disk and the radiatively inefficient accretion flow (RIAF), in which global radiative effects play a sub-dominant but non-negligible role in disk dynamics. We describe the governing equations, numerical method, idiosyncrasies of our implementation, and a suite of test and convergence results. We also describe example applications to radiative Bondi accretion and to a slowly accreting Kerr black hole in axisymmetry
An update on the BQCD Hybrid Monte Carlo program
Haar, Taylor Ryan; Nakamura, Yoshifumi; Stüben, Hinnerk
2018-03-01
We present an update of BQCD, our Hybrid Monte Carlo program for simulating lattice QCD. BQCD is one of the main production codes of the QCDSF collaboration and is used by CSSM and in some Japanese finite temperature and finite density projects. Since the first publication of the code at Lattice 2010 the program has been extended in various ways. New features of the code include: dynamical QED, action modification in order to compute matrix elements by using Feynman-Hellman theory, more trace measurements (like Tr(D-n) for K, cSW and chemical potential reweighting), a more flexible integration scheme, polynomial filtering, term-splitting for RHMC, and a portable implementation of performance critical parts employing SIMD.
An update on the BQCD Hybrid Monte Carlo program
Directory of Open Access Journals (Sweden)
Haar Taylor Ryan
2018-01-01
Full Text Available We present an update of BQCD, our Hybrid Monte Carlo program for simulating lattice QCD. BQCD is one of the main production codes of the QCDSF collaboration and is used by CSSM and in some Japanese finite temperature and finite density projects. Since the first publication of the code at Lattice 2010 the program has been extended in various ways. New features of the code include: dynamical QED, action modification in order to compute matrix elements by using Feynman-Hellman theory, more trace measurements (like Tr(D-n for K, cSW and chemical potential reweighting, a more flexible integration scheme, polynomial filtering, term-splitting for RHMC, and a portable implementation of performance critical parts employing SIMD.
A study of Monte Carlo radiative transfer through fractal clouds
Energy Technology Data Exchange (ETDEWEB)
Gautier, C.; Lavallec, D.; O`Hirok, W.; Ricchiazzi, P. [Univ. of California, Santa Barbara, CA (United States)] [and others
1996-04-01
An understanding of radiation transport (RT) through clouds is fundamental to studies of the earth`s radiation budget and climate dynamics. The transmission through horizontally homogeneous clouds has been studied thoroughly using accurate, discreet ordinates radiative transfer models. However, the applicability of these results to general problems of global radiation budget is limited by the plane parallel assumption and the fact that real clouds fields show variability, both vertically and horizontally, on all size scales. To understand how radiation interacts with realistic clouds, we have used a Monte Carlo radiative transfer model to compute the details of the photon-cloud interaction on synthetic cloud fields. Synthetic cloud fields, generated by a cascade model, reproduce the scaling behavior, as well as the cloud variability observed and estimated from cloud satellite data.
Hybrid Monte Carlo algorithm with fat link fermion actions
International Nuclear Information System (INIS)
Kamleh, Waseem; Leinweber, Derek B.; Williams, Anthony G.
2004-01-01
The use of APE smearing or other blocking techniques in lattice fermion actions can provide many advantages. There are many variants of these fat link actions in lattice QCD currently, such as flat link irrelevant clover (FLIC) fermions. The FLIC fermion formalism makes use of the APE blocking technique in combination with a projection of the blocked links back into the special unitary group. This reunitarization is often performed using an iterative maximization of a gauge invariant measure. This technique is not differentiable with respect to the gauge field and thus prevents the use of standard Hybrid Monte Carlo simulation algorithms. The use of an alternative projection technique circumvents this difficulty and allows the simulation of dynamical fat link fermions with standard HMC and its variants. The necessary equations of motion for FLIC fermions are derived, and some initial simulation results are presented. The technique is more general however, and is straightforwardly applicable to other smearing techniques or fat link actions
Monte Carlo studies of high-transverse-energy hadronic interactions
International Nuclear Information System (INIS)
Corcoran, M.D.
1985-01-01
A four-jet Monte Carlo calculation has been used to simulate hadron-hadron interactions which deposit high transverse energy into a large-solid-angle calorimeter and limited solid-angle regions of the calorimeter. The calculation uses first-order QCD cross sections to generate two scattered jets and also produces beam and target jets. Field-Feynman fragmentation has been used in the hadronization. The sensitivity of the results to a few features of the Monte Carlo program has been studied. The results are found to be very sensitive to the method used to ensure overall energy conservation after the fragmentation of the four jets is complete. Results are also sensitive to the minimum momentum transfer in the QCD subprocesses and to the distribution of p/sub T/ to the jet axis and the multiplicities in the fragmentation. With reasonable choices of these features of the Monte Carlo program, good agreement with data at Fermilab/CERN SPS energies is obtained, comparable to the agreement achieved with more sophisticated parton-shower models. With other choices, however, the calculation gives qualitatively different results which are in strong disagreement with the data. These results have important implications for extracting physics conclusions from Monte Carlo calculations. It is not possible to test the validity of a particular model or distinguish between different models unless the Monte Carlo results are unambiguous and different models exhibit clearly different behavior
Study on random number generator in Monte Carlo code
International Nuclear Information System (INIS)
Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi
2011-01-01
The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)
Parallel MCNP Monte Carlo transport calculations with MPI
International Nuclear Information System (INIS)
Wagner, J.C.; Haghighat, A.
1996-01-01
The steady increase in computational performance has made Monte Carlo calculations for large/complex systems possible. However, in order to make these calculations practical, order of magnitude increases in performance are necessary. The Monte Carlo method is inherently parallel (particles are simulated independently) and thus has the potential for near-linear speedup with respect to the number of processors. Further, the ever-increasing accessibility of parallel computers, such as workstation clusters, facilitates the practical use of parallel Monte Carlo. Recognizing the nature of the Monte Carlo method and the trends in available computing, the code developers at Los Alamos National Laboratory implemented the message-passing general-purpose Monte Carlo radiation transport code MCNP (version 4A). The PVM package was chosen by the MCNP code developers because it supports a variety of communication networks, several UNIX platforms, and heterogeneous computer systems. This PVM version of MCNP has been shown to produce speedups that approach the number of processors and thus, is a very useful tool for transport analysis. Due to software incompatibilities on the local IBM SP2, PVM has not been available, and thus it is not possible to take advantage of this useful tool. Hence, it became necessary to implement an alternative message-passing library package into MCNP. Because the message-passing interface (MPI) is supported on the local system, takes advantage of the high-speed communication switches in the SP2, and is considered to be the emerging standard, it was selected
Monte Carlo methods for the reliability analysis of Markov systems
International Nuclear Information System (INIS)
Buslik, A.J.
1985-01-01
This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator
A general transform for variance reduction in Monte Carlo simulations
International Nuclear Information System (INIS)
Becker, T.L.; Larsen, E.W.
2011-01-01
This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)
Acceleration of monte Carlo solution by conjugate gradient method
International Nuclear Information System (INIS)
Toshihisa, Yamamoto
2005-01-01
The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)
Pflock, Tobias J; Oellerich, Silke; Krapf, Lisa; Southall, June; Cogdell, Richard J; Ullmann, G Matthias; Köhler, Jürgen
2011-07-21
We performed time-resolved spectroscopy on homoarrays of LH2 complexes from the photosynthetic purple bacterium Rhodopseudomonas acidophila. Variations of the fluorescence transients were monitored as a function of the excitation fluence and the repetition rate of the excitation. These parameters are directly related to the excitation density within the array and to the number of LH2 complexes that still carry a triplet state prior to the next excitation. Comparison of the experimental observations with results from dynamic Monte Carlo simulations for a model cluster of LH2 complexes yields qualitative agreement without the need for any free parameter and reveals the mutual relationship between energy transfer and annihilation processes.
Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations
Hoogenboom, J. Eduard; Dufek, Jan
2014-06-01
This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.
Improved Monte Carlo Method for PSA Uncertainty Analysis
International Nuclear Information System (INIS)
Choi, Jongsoo
2016-01-01
The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard
Monte Carlo simulation of neutron counters for safeguards applications
International Nuclear Information System (INIS)
Looman, Marc; Peerani, Paolo; Tagziria, Hamid
2009-01-01
MCNP-PTA is a new Monte Carlo code for the simulation of neutron counters for nuclear safeguards applications developed at the Joint Research Centre (JRC) in Ispra (Italy). After some preliminary considerations outlining the general aspects involved in the computational modelling of neutron counters, this paper describes the specific details and approximations which make up the basis of the model implemented in the code. One of the major improvements allowed by the use of Monte Carlo simulation is a considerable reduction in both the experimental work and in the reference materials required for the calibration of the instruments. This new approach to the calibration of counters using Monte Carlo simulation techniques is also discussed.