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Journal articles on the topic 'Particle Monte Carlo'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Zarezadeh, Zakarya, and Giovanni Costantini. "Particle diffusion Monte Carlo (PDMC)." Monte Carlo Methods and Applications 25, no. 2 (June 1, 2019): 121–30. http://dx.doi.org/10.1515/mcma-2019-2037.

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Abstract General expressions for anisotropic particle diffusion Monte Carlo (PDMC) in a d-dimensional space are presented. The calculations of ground state energy of a helium atom for solving the many-body Schrödinger equation is carried out by the proposed method. The accuracy and stability of the results are discussed relative to other alternative methods, and our experimental results within the statistical errors agree with the quantum Monte Carlo methods. We also clarify the benefits of the proposed method by modeling the quantum probability density of a free particle in a plane (energy eigenfunctions). The proposed model represents a remarkable improvement in terms of performance, accuracy and computational time over standard MCMC method.

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2

Garren, L., I. G. Knowles, T. Sjöstrand, and T. Trippe. "Monte carlo particle numbering scheme." European Physical Journal C 15, no. 1-4 (March 2000): 205–7. http://dx.doi.org/10.1007/bf02683426.

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3

Kittelmann, T., E. Klinkby, E. B. Knudsen, P. Willendrup, X. X. Cai, and K. Kanaki. "Monte Carlo Particle Lists: MCPL." Computer Physics Communications 218 (September 2017): 17–42. http://dx.doi.org/10.1016/j.cpc.2017.04.012.

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4

Achával, P. I., C. A. Rodríguez Luca, and C. L. Di Prinzio. "KINETIC EVOLUTION OF A 3D SPHERICAL CRYSTAL WITH MOBILE PARTICLES USING MONTE CARLO." Anales AFA Vol.30, Vol.30 N.2 (2019): 25–30. http://dx.doi.org/10.31527/analesafa.2019.30.2.25.

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In this work, the evolution of a tridimensional (3D) spherical crystal with mobile particles using a Monte Carlo algorithm is presented. The mean radius R of spherical crystal without particles changes according to the law: R2 = -4kt + Ro2, where Ro is the initial radius and k is a crystal constant. However, this law is modified when mobile particles are included. The effect of two types of mobile particles on the grain boundary migration of a spherical grain was also studied. One type of particle remained located in the middle of the grain boundary once it was incorporated (CT), and the other type of particle remained at the grain boundary without having any particular location (NC). It could be seen that the CT particle slowed down more the grain boundary migration than the NC particles. It was also found that the rate of reduction of the grain area is inversely proportional to the concentration of CT particles in the grain boundary for all the CT particles concentrations. Finally, it was established that the grain reaches a limit radius for CT particles which is related to the amount of particles that can be accommodated in the grain boundary.

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5

Shymanska, Alla V., and Vitali A. Babakov. "Fast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication." International Journal of Applied Physics and Mathematics 5, no. 3 (2015): 218–26. http://dx.doi.org/10.17706/ijapm.2015.5.3.218-226.

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6

Smith, Lyndon. "Monte Carlo simulation of particle behaviour." Metal Powder Report 56, no. 1 (January 2001): 32–35. http://dx.doi.org/10.1016/s0026-0657(01)80080-1.

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7

Castier, Marcelo, Oscar Delgado Cuéllar, and Frederico W. Tavares. "Monte Carlo simulation of particle segregation." Powder Technology 97, no. 3 (July 1998): 200–207. http://dx.doi.org/10.1016/s0032-5910(98)00009-6.

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8

Fitzgerald, Mark, and Rick Picard. "ACCELERATED MONTE CARLO FOR PARTICLE DISPERSION." Communications in Statistics: Theory and Methods 30, no. 11 (January 1, 2001): 2459–71. http://dx.doi.org/10.1081/sta-100107698.

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9

Andrieu, Christophe, Arnaud Doucet, and Roman Holenstein. "Particle Markov chain Monte Carlo methods." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72, no. 3 (June 2010): 269–342. http://dx.doi.org/10.1111/j.1467-9868.2009.00736.x.

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10

Sobol, Ilya M., and Boris V. Shukhman. "On average dimensions of particle transport estimators." Monte Carlo Methods and Applications 24, no. 2 (June 1, 2018): 147–51. http://dx.doi.org/10.1515/mcma-2018-0013.

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Abstract We considered average dimensions of the weighted Monte Carlo algorithm for a particle transport problem with multi-scattering setting and estimated the probability of particles penetration through a layer. The average dimension {\hat{d}} of the algorithm turned out to be small so that quasi-Monte Carlo estimates of the probability converge much faster than the Monte Carlo estimates. We justified the reasons to expect that the convergence of quasi-Monte Carlo estimates continue to be faster as the thickness of the layer increases. Here we calculated {\hat{d}} without the use of the ANOVA expansion.

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11

Jin, Nai Gao, Fei Mo Li, and Zhao Xing Li. "Quasi-Monte Carlo Gaussian Particle Filtering Acceleration Using CUDA." Applied Mechanics and Materials 130-134 (October 2011): 3311–15. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.3311.

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A CUDA accelerated Quasi-Monte Carlo Gaussian particle filter (QMC-GPF) is proposed to deal with real-time non-linear non-Gaussian problems. GPF is especially suitable for parallel implementation as a result of the elimination of resampling step. QMC-GPF is an efficient counterpart of GPF using QMC sampling method instead of MC. Since particles generated by QMC method provides the best-possible distribution in the sampling space, QMC-GPF can make more accurate estimation with the same number of particles compared with traditional particle filter. Experimental results show that our GPU implementation of QMC-GPF can achieve the maximum speedup ratio of 95 on NVIDIA GeForce GTX 460.

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12

Madhavrao, L. Rao, and Raj Rajagopalan. "Monte Carlo simulations for sintering of particle aggregates." Journal of Materials Research 4, no. 5 (October 1989): 1251–56. http://dx.doi.org/10.1557/jmr.1989.1251.

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A new Monte Carlo simulation procedure is developed for the initial stages of sintering of randomly packed particles. This simulation takes into account the possibility of crack initiation due to the stresses generated by the sintering particles and can accommodate both localized stresses and stress propagation. This procedure is used to investigate the sintering of two-dimensional aggregates of copper particles, and the results are compared with the results of model experiments available in the literature. The two-dimensional simulations presented here lead to shrinkage in area, decreases in perimeter, and particle rearrangements that are physically consistent with the expected behavior and experimental results. The proposed procedure can be extended to accommodate more complex features of sintering and to account for the material-dependent effects of stresses. It can also be used as a probe of sintering of bulk materials with random microstructure and to identify and design model experiments.

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13

Miodownik, Mark A., and J. W. Martin. "Monte Carlo Simulations of Particle/Boundary Interactions." Materials Science Forum 207-209 (February 1996): 529–32. http://dx.doi.org/10.4028/www.scientific.net/msf.207-209.529.

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14

Qiu, Fulian, Terry A. Egerton, and Ian L. Cooper. "Monte Carlo simulation of nano-particle sintering." Powder Technology 182, no. 1 (February 2008): 42–50. http://dx.doi.org/10.1016/j.powtec.2007.05.007.

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15

Booth, Thomas E. "Common misconceptions in Monte Carlo particle transport." Applied Radiation and Isotopes 70, no. 7 (July 2012): 1042–51. http://dx.doi.org/10.1016/j.apradiso.2011.11.037.

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16

Romano, Paul K., and Benoit Forget. "The OpenMC Monte Carlo particle transport code." Annals of Nuclear Energy 51 (January 2013): 274–81. http://dx.doi.org/10.1016/j.anucene.2012.06.040.

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17

Dumonteil, Eric, Fausto Malvagi, Andrea Zoia, Alain Mazzolo, Davide Artusio, Cyril Dieudonné, and Clélia De Mulatier. "Particle clustering in Monte Carlo criticality simulations." Annals of Nuclear Energy 63 (January 2014): 612–18. http://dx.doi.org/10.1016/j.anucene.2013.09.008.

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18

Lankosz, M., B. Holynska, P. A. Pella, and D. H. Blackburn. "Research in the Quantitative Analysis of Individual Particles by X-Ray Fluorescence Spectrometry." Advances in X-ray Analysis 36 (1992): 11–16. http://dx.doi.org/10.1154/s0376030800018589.

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In a previous publication, we compared measurements of the x-ray microfluorescence of calcium and iron from homogeneous spherical glass particles with the results of Monte Carlo simulation. That work was performed to verify a Monte Carlo model developed for the characterization of particle size effects using a polished flat sample of the same composition as a reference standard. The present work extends our comparison to synthetic glass particles containing elements of higher atomic number. We also modified our Monte Carlo model to include simulation of x-ray fluorescence from elements in irregular shaped synthetic particles. In addition, the Compton scattering from spherical and irregular shaped particles was simulated using Monte Carlo and compared with experimental measurements.

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19

Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 04 (December 2005): 1053–68. http://dx.doi.org/10.1017/s0021900200001108.

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Particle filters are Monte Carlo methods that aim to approximate the optimal filter of a partially observed Markov chain. In this paper, we study the case in which the transition kernel of the Markov chain depends on unknown parameters: we construct a particle filter for the simultaneous estimation of the parameter and the partially observed Markov chain (adaptive estimation) and we prove the convergence of this filter to the correct optimal filter, as time and the number of particles go to infinity. The filter presented here generalizes Del Moral's Monte Carlo particle filter.

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20

Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 4 (December 2005): 1053–68. http://dx.doi.org/10.1239/jap/1134587816.

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Particle filters are Monte Carlo methods that aim to approximate the optimal filter of a partially observed Markov chain. In this paper, we study the case in which the transition kernel of the Markov chain depends on unknown parameters: we construct a particle filter for the simultaneous estimation of the parameter and the partially observed Markov chain (adaptive estimation) and we prove the convergence of this filter to the correct optimal filter, as time and the number of particles go to infinity. The filter presented here generalizes Del Moral's Monte Carlo particle filter.

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21

Zhou, Kun. "Monte Carlo simulation for soot dynamics." Thermal Science 16, no. 5 (2012): 1391–94. http://dx.doi.org/10.2298/tsci1205391z.

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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.

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22

Jiang, Xiao, and Tat Leung Chan. "A new weighted fraction Monte Carlo method for particle coagulation." International Journal of Numerical Methods for Heat & Fluid Flow 31, no. 9 (February 4, 2021): 3009–29. http://dx.doi.org/10.1108/hff-07-2020-0449.

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Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

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23

Guessasma, Sofiane, and N. Rouag. "Introduction of Second Phase Particle Shape in Monte Carlo Grain Growth Simulation." Materials Science Forum 467-470 (October 2004): 981–84. http://dx.doi.org/10.4028/www.scientific.net/msf.467-470.981.

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This paper deals with the study of particle shape effect in grain growth inhibition. As it is difficult to quantify analytically such effect during growth kinetic because of particle distribution variation, computer simulation was implemented. Monte Carlo simulation was chosen to follow grain growth in presence of incoherent particles varying their size, fraction and morphology. Results suggested a correlated effect between particle eccentricity and fraction to control growth inhibition. Moreover, particle size controlled better growth kinetic, as it was possible to inhibit particle shape effect by giving a size advantage to particles having a high symmetry.

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24

Skenderović, Ivan, Gregor Kotalczyk, and Frank Kruis. "Dual Population Balance Monte Carlo Simulation of Particle Synthesis by Flame Spray Pyrolysis." Processes 6, no. 12 (December 6, 2018): 253. http://dx.doi.org/10.3390/pr6120253.

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The Dual Population Balance Monte Carlo Method (DPBMC) takes into account the full size spectrum of the droplet and particle phase. Droplet and particle size distributions are rendered by weighted simulation particles. This allows for an accurate description of particle nucleation and coagulation and droplet combustion, simultaneously. Internal droplet properties such as temperature and concentrations fields are used to define criteria for the onset of droplet breakage in the framework of weighted Monte Carlo droplets. We discuss the importance of droplet polydispersity on particle formation in metal oxide particle synthesis, which is shown to strongly affect particle formation and growth. The method is applied to particle synthesis from metal nitrate precursor solutions with flame spray pyrolysis (FSP) and compared to experiments from literature.

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25

Baring, Matthew G., Donald C. Ellison, and Frank C. Jones. "Monte Carlo Simulations of Particle Acceleration at Oblique Shocks." International Astronomical Union Colloquium 142 (1994): 547–52. http://dx.doi.org/10.1017/s0252921100077794.

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AbstractThe Fermi shock acceleration mechanism may be responsible for the production of high-energy cosmic rays in a wide variety of environments. Modeling of this phenomenon has largely focused on plane-parallel shocks, and one of the most promising techniques for its study is the Monte Carlo simulation of particle transport in shocked fluid flows. One of the principal problems in shock acceleration theory is the mechanism and efficiency of injection of particles from the thermal gas into the accelerated population. The Monte Carlo technique is ideally suited to addressing the injection problem directly, and previous applications of it to the quasi-parallel Earth bow shock led to very successful modeling of proton and heavy ion spectra, as well as other observed quantities. Recently this technique has been extended to oblique shock geometries, in which the upstream magnetic field makes a significant angle ΘB1 to the shock normal. In this paper, spectral results from test particle Monte Carlo simulations of cosmic-ray acceleration at oblique, nonrelativistic shocks are presented. The results show that low Mach number shocks have injection efficiencies that are relatively insensitive to (though not independent of) the shock obliquity, but that there is a dramatic drop in efficiency for shocks of Mach number 30 or more as the obliquity increases above 15°. Cosmic-ray distributions just upstream of the shock reveal prominent bumps at energies below the thermal peak; these disappear far upstream but might be observable features close to astrophysical shocks.Subject headings: acceleration of particles — cosmic rays — shock waves

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26

GEPNER, DORON. "MONTE–CARLO THERMODYNAMIC BETHE ANSATZ." International Journal of Modern Physics B 20, no. 14 (June 10, 2006): 2049–64. http://dx.doi.org/10.1142/s0217979206034522.

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We introduce a Monte–Carlo simulation approach to thermodynamic Bethe ansatz (TBA). We exemplify the method on one-particle integrable models, which include a free boson and a free fermions systems along with the scaling Lee–Yang model (SLYM). It is confirmed that the central charges and energies are correct to a very good precision, typically 0.1% or so. The advantage of the method is that it allows the calculation of all the dimensions and even the particular partition function.

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27

Cong-An, Xu, Xu Congqi, Dong Yunlong, Xiong Wei, Chai Yong, and Li Tianmei. "A Novel Sequential Monte Carlo-Probability Hypothesis Density Filter for Particle Impoverishment Problem." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 6872–77. http://dx.doi.org/10.1166/jctn.2016.5640.

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As a typical implementation of the probability hypothesis density (PHD) filter, sequential Monte Carlo PHD (SMC-PHD) is widely employed in highly nonlinear systems. However, diversity loss of particles introduced by the resampling step, which can be called particle impoverishment problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this paper, a novel SMC-PHD filter based on particle compensation is proposed to solve the problem. Firstly, based on an analysis of the particle impoverishment problem, a new particle compensatory method is developed to improve the particle diversity. Then, all the particles are integrated into the SMC-PHD filter framework. Compared with the SMC-PHD filter, simulation results demonstrate that the proposed particle compensatory SMC-PHD filter is capable of overcoming the particle impoverishment problem, which indicate good application prospects.

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28

BEKDA, A., M. DJEBLI, and N. BELDJOUDI. "Monte Carlo simulation in a strongly coupled linear chain." Journal of Plasma Physics 74, no. 5 (October 2008): 629–38. http://dx.doi.org/10.1017/s0022377808007162.

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AbstractMonte Carlo simulation is conducted for a strongly coupled one-dimensional confined-particles system. We deal with an infinite chain of positively charged dust particles. The particles interact through the Yukawa screened potential. It is found that a critical value exists for the number of closest neighbors that are involved in the interaction. The inter-particle distance at equilibrium is found. Using these results, we study the dust-acoustic as well as the dust-lattice modes for two situations. In the first we neglect the friction force while in the second situation the presence of an ambient gas in plasma is considered.

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29

Punjabi, Alkesh, Allen Boozer, Maria Lam, Myung-Hee Kim, and Kathy Burke. "Monte Carlo calculations for transport due to MHD modes." Journal of Plasma Physics 44, no. 3 (December 1990): 405–30. http://dx.doi.org/10.1017/s0022377800015282.

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The three basic mechanisms that produce either classical or anomalous transport are spatial variation of magnetic field strength, spatial variation of electrostatic potential in magnetic surfaces, and loss of magnetic surfaces. A Monte Carlo code is written to study transport due to these three mechanisms interacting with collisional effects. The equations of motion are obtained from the canonical drift Hamiltonian, but non-canonical co-ordinates are used to simplify the integrations. The code is applied to the reversed-field-pinch ZT-40 and the Tokapole II. For ZT-40 the Bessel-function model is used to represent the magnetic field geometry. The effects of pitch-angle scattering, loop voltage and the break-up of magnetic surfaces resulting from resistive MHD perturbations on the drift particle trajectories are illustrated. The particle diffusion coefficients are obtained for varying amplitudes of resistive MHD perturbations. For Tokapole II the spectrum of both the ideal and resistive MHD perturbations is constructed from the experimental data. The drift trajectories for trapped and passing electrons in the presence of such perturbations are obtained. The particle diffusion coefficients for the neo-classical regime in Tokapole II are obtained for varying collision frequency. By comparing the transport coefficients for various groups of particles with the experimental data, we hope to obtain far more information on the transport mechanisms than can be obtained by the standard confinement time measurements. The various groups of particles that can be studied using the code include runaway electrons, thermal electrons, and both passing and trapped diagnostic beam ions.

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30

Sato, Yo, Sam Cunliffe, Frank Meier, and Anze Zupanc. "Monte Carlo matching in the Belle II software." EPJ Web of Conferences 251 (2021): 03021. http://dx.doi.org/10.1051/epjconf/202125103021.

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The Belle II experiment is an upgrade to the Belle experiment, and is located at the SuperKEKB facility in KEK, Tsukuba, Japan. The Belle II software is completely new and is used for everything from triggering data, generation of Monte Carlo events, tracking, clustering, to high-level analysis. One important feature is the matching between the combinations of reconstructed objects which form particle candidates and the underlying simulated particles from the event generators. This is used to study detector effects, analysis backgrounds, and efficiencies. This document describes the algorithm that is used by Belle II.

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31

Li Gang, 李刚, 张宝印 Zhang Baoyin, 邓力 Deng Li, 胡泽华 Hu Zehua, and 马彦 Ma Yan. "Development of Monte Carlo particle transport code JMCT." High Power Laser and Particle Beams 25, no. 1 (2013): 158–62. http://dx.doi.org/10.3788/hplpb20132501.0158.

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32

Shifren, L., and D. K. Ferry. "Particle Monte Carlo simulation of Wigner function tunneling." Physics Letters A 285, no. 3-4 (July 2001): 217–21. http://dx.doi.org/10.1016/s0375-9601(01)00344-9.

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33

Myers, A. M., J. R. Doyle, J. R. Abelson, and D. N. Ruzic. "Monte Carlo simulations of magnetron sputtering particle transport." Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films 9, no. 3 (May 1991): 614–18. http://dx.doi.org/10.1116/1.577375.

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34

Sancho, M., V. Giner, and G. Martínez. "Monte Carlo simulation of dielectrophoretic particle chain formation." Physical Review E 55, no. 1 (January 1, 1997): 544–48. http://dx.doi.org/10.1103/physreve.55.544.

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35

Louvin, Henri, Eric Dumonteil, Tony Lelièvre, Mathias Rousset, and Cheikh M. Diop. "Adaptive Multilevel Splitting for Monte Carlo particle transport." EPJ Web of Conferences 153 (2017): 06006. http://dx.doi.org/10.1051/epjconf/201715306006.

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Wrobel, Frédéric, Antoine Touboul, Jean-Roch Vaillé, Jérôme Boch, and Frédéric Saigné. "Monte Carlo simulation of particle-induced bit upsets." EPJ Web of Conferences 153 (2017): 06033. http://dx.doi.org/10.1051/epjconf/201715306033.

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Louvin, Henri, Eric Dumonteil, Tony Lelièvre, Mathias Rousset, and Cheikh M. Diop. "Adaptive multilevel splitting for Monte Carlo particle transport." EPJ Nuclear Sciences & Technologies 3 (2017): 29. http://dx.doi.org/10.1051/epjn/2017022.

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38

Jansen, G. H. "Fast Monte Carlo simulation of charged particle beams." Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 5, no. 1 (January 1987): 146. http://dx.doi.org/10.1116/1.583849.

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39

Orkoulas, G. "Spatial updating Monte Carlo algorithms in particle simulations." Molecular Simulation 36, no. 7-8 (June 2010): 516–25. http://dx.doi.org/10.1080/08927022.2010.496785.

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40

Kirk, J. G., and P. Schneider. "Particle acceleration at shocks - A Monte Carlo method." Astrophysical Journal 322 (November 1987): 256. http://dx.doi.org/10.1086/165720.

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41

Akhtar, M. Kamal, G. Glenn Lipscomb, and Sotiris E. Pratsinis. "Monte Carlo Simulation of Particle Coagulation and Sintering." Aerosol Science and Technology 21, no. 1 (January 1994): 83–93. http://dx.doi.org/10.1080/02786829408959698.

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42

Cloth, P., and D. Filges. "Development of vectorized Monte Carlo particle transport programs." Progress in Nuclear Energy 24, no. 1-3 (January 1990): 165–73. http://dx.doi.org/10.1016/0149-1970(90)90033-2.

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43

Mendes, Eduardo F., Christopher K. Carter, David Gunawan, and Robert Kohn. "A flexible particle Markov chain Monte Carlo method." Statistics and Computing 30, no. 4 (January 14, 2020): 783–98. http://dx.doi.org/10.1007/s11222-019-09916-7.

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44

Negele, J. W. "Monte Carlo studies of nuclear many-particle systems." Journal of Statistical Physics 43, no. 5-6 (June 1986): 991–1015. http://dx.doi.org/10.1007/bf02628326.

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45

Morgan, L. W. G., and D. Kotlyar. "Weighted-delta-tracking for Monte Carlo particle transport." Annals of Nuclear Energy 85 (November 2015): 1184–88. http://dx.doi.org/10.1016/j.anucene.2015.07.038.

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46

Tickner, James. "Arbitrary perturbations in Monte Carlo neutral-particle transport." Computer Physics Communications 185, no. 6 (June 2014): 1628–38. http://dx.doi.org/10.1016/j.cpc.2014.03.003.

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47

Willemsen, S. M., T. J. H. Vlugt, H. C. J. Hoefsloot, and B. Smit. "Combining Dissipative Particle Dynamics and Monte Carlo Techniques." Journal of Computational Physics 147, no. 2 (December 1998): 507–17. http://dx.doi.org/10.1006/jcph.1998.6099.

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48

Phaneesh, Kalale Raghavendra Rao, Anirudh Bhat, Gautam Mukherjee, and Kishore T. Kashyap. "Effect of Particle Size on the Zener Limit: A Monte Carlo Simulation Approach." Advanced Materials Research 560-561 (August 2012): 152–55. http://dx.doi.org/10.4028/www.scientific.net/amr.560-561.152.

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2D Potts model Monte Carlo simulation was carried out on a square lattice to investigate the effects of varying the size of second phase particles on the Zener limit of grain growth, in two-phase polycrystals. Simulations were carried out on a 1000^2 size matrix with Q-state of 64, dispersed with second phase particles of various sizes and surface fractions, and run to stagnation. Different grain growth parameters such as mean grain size, largest grain size, fraction of second phase particles lying on grain boundaries, etc., were computed for the pinned microstructures. The pinned average grain size or the Zener limit increased with increase in particle size, as per the classic Smith-Zener equation. The Zener limit scaled inversely with the square root of the particle fraction for all particle sizes, while it scaled exponentially with the fraction of second phase particles lying on the grain boundaries (ϕ), for all particle sizes tested.

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49

Bedkowski, Janusz Marian, and Timo Röhling. "Online 3D LIDAR Monte Carlo localization with GPU acceleration." Industrial Robot: An International Journal 44, no. 4 (June 19, 2017): 442–56. http://dx.doi.org/10.1108/ir-11-2016-0309.

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Purpose This paper aims to focus on real-world mobile systems, and thus propose relevant contribution to the special issue on “Real-world mobile robot systems”. This work on 3D laser semantic mobile mapping and particle filter localization dedicated for robot patrolling urban sites is elaborated with a focus on parallel computing application for semantic mapping and particle filter localization. The real robotic application of patrolling urban sites is the goal; thus, it has been shown that crucial robotic components have reach high Technology Readiness Level (TRL). Design/methodology/approach Three different robotic platforms equipped with different 3D laser measurement system were compared. Each system provides different data according to the measured distance, density of points and noise; thus, the influence of data into final semantic maps has been compared. The realistic problem is to use these semantic maps for robot localization; thus, the influence of different maps into particle filter localization has been elaborated. A new approach has been proposed for particle filter localization based on 3D semantic information, and thus, the behavior of particle filter in different realistic conditions has been elaborated. The process of using proposed robotic components for patrolling urban site, such as the robot checking geometrical changes of the environment, has been detailed. Findings The focus on real-world mobile systems requires different points of view for scientific work. This study is focused on robust and reliable solutions that could be integrated with real applications. Thus, new parallel computing approach for semantic mapping and particle filter localization has been proposed. Based on the literature, semantic 3D particle filter localization has not yet been elaborated; thus, innovative solutions for solving this issue have been proposed. Recently, a semantic mapping framework that was already published was developed. For this reason, this study claimed that the authors’ applied studies during real-world trials with such mapping system are added value relevant for this special issue. Research limitations/implications The main problem is the compromise between computer power and energy consumed by heavy calculations, thus our main focus is to use modern GPGPU, NVIDIA PASCAL parallel processor architecture. Recent advances in GPGPUs shows great potency for mobile robotic applications, thus this study is focused on increasing mapping and localization capabilities by improving the algorithms. Current limitation is related with the number of particles processed by a single processor, and thus achieved performance of 500 particles in real-time is the current limitation. The implication is that multi-GPU architectures for increasing the number of processed particle can be used. Thus, further studies are required. Practical implications The research focus is related to real-world mobile systems; thus, practical aspects of the work are crucial. The main practical application is semantic mapping that could be used for many robotic applications. The authors claim that their particle filter localization is ready to integrate with real robotic platforms using modern 3D laser measurement system. For this reason, the authors claim that their system can improve existing autonomous robotic platforms. The proposed components can be used for detection of geometrical changes in the scene; thus, many practical functionalities can be applied such as: detection of cars, detection of opened/closed gate, etc. […] These functionalities are crucial elements of the safe and security domain. Social implications Improvement of safe and security domain is a crucial aspect of modern society. Protecting critical infrastructure plays an important role, thus introducing autonomous mobile platforms capable of supporting human operators of safe and security systems could have a positive impact if viewed from many points of view. Originality/value This study elaborates the novel approach of particle filter localization based on 3D data and semantic mapping. This original work could have a great impact on the mobile robotics domain, and thus, this study claims that many algorithmic and implementation issues were solved assuming real-task experiments. The originality of this work is influenced by the use of modern advanced robotic systems being a relevant set of technologies for proper evaluation of the proposed approach. Such a combination of experimental hardware and original algorithms and implementation is definitely an added value.

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Kurniadi, Rizal, Abdul Waris, and Sparisoma Viridi. "Monte Carlo simulation based toy model for fission process." International Journal of Modern Physics C 27, no. 03 (February 23, 2016): 1650030. http://dx.doi.org/10.1142/s0129183116500303.

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Nuclear fission has been modeled notoriously using two approaches method, macroscopic and microscopic. This work will propose another approach, where the nucleus is treated as a toy model. The aim is to see the usefulness of particle distribution in fission yield calculation. Inasmuch nucleus is a toy, then the Fission Toy Model (FTM) does not represent real process in nature completely. The fission event in FTM is represented by one random number. The number is assumed as width of distribution probability of nucleon position in compound nuclei when fission process is started. By adopting the nucleon density approximation, the Gaussian distribution is chosen as particle distribution. This distribution function generates random number that randomizes distance between particles and a central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. The yield is determined from portion of nuclei distribution which is proportional with portion of mass numbers. By using modified FTM, characteristic of particle distribution in each fission event could be formed before fission process. These characteristics could be used to make prediction about real nucleons interaction in fission process. The results of FTM calculation give information that the [Formula: see text] value seems as energy.

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