Academic literature on the topic 'Particle Monte Carlo'
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Journal articles on the topic "Particle Monte Carlo"
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.
Full textGarren, 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.
Full textKittelmann, 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.
Full textAchával, 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.
Full textShymanska, 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.
Full textSmith, 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.
Full textCastier, 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.
Full textFitzgerald, 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.
Full textAndrieu, 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.
Full textSobol, 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.
Full textDissertations / Theses on the topic "Particle Monte Carlo"
Holenstein, Roman. "Particle Markov chain Monte Carlo." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/7319.
Full textLi, Lulu Ph D. Massachusetts Institute of Technology. "Acceleration methods for Monte Carlo particle transport simulations." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112521.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 166-175).
Performing nuclear reactor core physics analysis is a crucial step in the process of both designing and understanding nuclear power reactors. Advancements in the nuclear industry demand more accurate and detailed results from reactor analysis. Monte Carlo (MC) eigenvalue neutron transport methods are uniquely qualified to provide these results, due to their accurate treatment of space, angle, and energy dependencies of neutron distributions. Monte Carlo eigenvalue simulations are, however, challenging, because they must resolve the fission source distribution and accumulate sufficient tally statistics, resulting in prohibitive run times. This thesis proposes the Low Order Operator (LOO) acceleration method to reduce the run time challenge, and provides analyses to support its use for full-scale reactor simulations. LOO is implemented in the continuous energy Monte Carlo code, OpenMC, and tested in 2D PWR benchmarks. The Low Order Operator (LOO) acceleration method is a deterministic transport method based on the Method of Characteristics. Similar to Coarse Mesh Finite Difference (CMFD), the other acceleration method evaluated in this thesis, LOO parameters are constructed from Monte Carlo tallies. The solutions to the LOO equations are then used to update Monte Carlo fission sources. This thesis deploys independent simulations to rigorously assess LOO, CMFD, and unaccelerated Monte Carlo, simulating up to a quarter of a trillion neutron histories for each simulation. Analysis and performance models are developed to address two aspects of the Monte Carlo run time challenge. First, this thesis demonstrates that acceleration methods can reduce the vast number of neutron histories required to converge the fission source distribution before tallies can be accumulated. Second, the slow convergence of tally statistics is improved with the acceleration methods for the earlier active cycles. A theoretical model is developed to explain the observed behaviors and predict convergence rates. Finally, numerical results and theoretical models shed light on the selection of optimal simulation parameters such that a desired statistical uncertainty can be achieved with minimum neutron histories. This thesis demonstrates that the conventional wisdom (e.g., maximizing the number of cycles rather than the number of neutrons per cycle) in performing unaccelerated MC simulations can be improved simply by using more optimal parameters. LOO acceleration provides reduction of a factor of at least 2.2 in neutron histories, compared to the unaccelerated Monte Carlo scheme, and the CPU time and memory overhead associated with LOO are small.
by Lulu Li.
Ph. D.
Torfeh, Eva. "Monte Carlo microdosimetry of charged-particle microbeam irradiations." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0159/document.
Full textThe interaction of charged particles with matter leads to a very localized energy deposits in sub-micrometric tracks. This unique property makes this type of ionizing radiation particularly interesting for deciphering the radiation-induced molecular mechanisms at the cell scale. Charged particle microbeams (CPMs) provide the ability to target a given cell compartment at the micrometer scale with a controlled dose down to single particle. My work focused on irradiations carried out with the CPM at the AIFIRA facility in the CENBG (Applications Interdisciplinaires des Faisceaux d’Ions en Région Aquitaine). This microbeam delivers protons and alpha particles and is dedicated to targeted irradiation in vitro (human cells) and in vivo (C. elegans).In addition to their interest for experimental studies, the energy deposits and the interactions of charged particles with matter can be modeled precisely along their trajectory using track structure codes based on Monte Carlo methods. These simulation tools allow a precise characterization of the micro-dosimetry of the irradations from the detailed description of the physical interactions at the nanoscale to the prediction of the number of DNA damage, their complexity and their distribution in space.During my thesis, I developed micro-dosimetric models based on the Geant4-DNA modeling toolkit in two cases. The first concerns the simulation of the energy distribution deposited in a cell nucleus and the calculation of the number of different types of DNA damage (single and double strand breaks) at the nanometric and micrometric scales, for different types and numbers of delivered particles. These simulations are compared with experimental measurements of the kinetics of GFP-labeled (Green Fluorescent Protein) DNA repair proteins in human cells. The second is the dosimetry of irradiation of a multicellular organism to study the genetic instability in a living organism during development (C. elegans). I simulated the distribution of the energy deposited in different compartments of a realistic 3D model of a C. elegans embryo following proton irradiations. Finally, and in parallel with these two studies, I developed a protocol to characterize the AIFIRA microbeam using fluorescent nuclear track detector (FNTD) for proton and alpha particle irradiations. This type of detector makes it possible to visualize in 3D the incident particle tracks with a resolution of about 200 nm and to examine the quality of the cellular irradiations carried out by the CPM
Miryusupov, Shohruh. "Particle methods in finance." Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E069.
Full textThe thesis introduces simulation techniques that are based on particle methods and it consists of two parts, namely rare event simulation and a homotopy transport for stochastic volatility model estimation. Particle methods, that generalize hidden Markov models, are widely used in different fields such as signal processing, biology, rare events estimation, finance, etc. There are a number of approaches that are based on Monte Carlo methods that allow to approximate a target density such as Markov Chain Monte Carlo (MCMC), sequential Monte Carlo (SMC). We apply SMC algorithms to estimate default probabilities in a stable process based intensity process to compute a credit value adjustment (CV A) with a wrong way risk (WWR). We propose a novel approach to estimate rare events, which is based on the generation of Markov Chains by simulating the Hamiltonian system. We demonstrate the properties, that allows us to have ergodic Markov Chain and show the performance of our approach on the example that we encounter in option pricing.In the second part, we aim at numerically estimating a stochastic volatility model, and consider it in the context of a transportation problem, when we would like to find "an optimal transport map" that pushes forward the measure. In a filtering context, we understand it as the transportation of particles from a prior to a posterior distribution in pseudotime. We also proposed to reweight transported particles, so as we can direct to the area, where particles with high weights are concentrated. We showed the application of our method on the example of option pricing with SteinStein stochastic volatility model and illustrated the bias and variance
Persing, Adam. "Some contributions to particle Markov chain Monte Carlo algorithms." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/23277.
Full textLyberatos, Andreas. "Monte Carlo simulations of interaction effects in fine particle ferromagnets." Thesis, Imperial College London, 1986. http://hdl.handle.net/10044/1/38088.
Full textNowak, Michel. "Accelerating Monte Carlo particle transport with adaptively generated importance maps." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS403/document.
Full textMonte Carlo methods are a reference asset for the study of radiation transport in shielding problems. Their use naturally implies the sampling of rare events and needs to be tackled with variance reduction methods. These methods require the definition of an importance function/map. The aim of this study is to propose an adaptivestrategy for the generation of such importance maps during the Montne Carlo simulation. The work was performed within TRIPOLI-4®, a Monte Carlo transport code developped at the nuclear energy division of CEA in Saclay, France. The core of this PhD thesis is the implementation of a forward-weighted adjoint score that relies on the trajectories sampled with Adaptive Multilevel Splitting, a robust variance reduction method. It was validated with the integration of a deterministic module in TRIPOLI-4®. Three strategies were proposed for the reintegrationof this score as an importance map and accelerations were observed. Two of these strategies assess the convergence of the adjoint score during exploitation phases by evalutating the figure of merit yielded by the use of the current adjoint score. Finally, the smoothing of the importance map with machine learning algorithms concludes this work with a special focus on Kernel Density Estimators
Norris, Michael K. "INCORPORATING HISTOGRAMS OF ORIENTED GRADIENTS INTO MONTE CARLO LOCALIZATION." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1629.
Full textHorelik, Nicholas E. (Nicholas Edward). "Domain decomposition for Monte Carlo particle transport simulations of nuclear reactors." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/97859.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 151-158).
Monte Carlo (MC) neutral particle transport methods have long been considered the gold-standard for nuclear simulations, but high computational cost has limited their use significantly. However, as we move towards higher-fidelity nuclear reactor analyses the method has become competitive with traditional deterministic transport algorithms for the same level of accuracy, especially considering the inherent parallelism of the method and the ever-increasing concurrency of modern high performance computers. Yet before such analysis can be practical, several algorithmic challenges must be addressed, particularly in regards to the memory requirements of the method. In this thesis, a robust domain decomposition algorithm is proposed to alleviate this, along with models and analysis to support its use for full-scale reactor analysis. Algorithms were implemented in the full-physics Monte Carlo code OpenMC, and tested for a highly-detailed PWR benchmark: BEAVRS. The proposed domain decomposition implementation incorporates efficient algorithms for scalable inter-domain particle communication in a manner that is reproducible with any pseudo-random number seed. Algorithms are also proposed to scalably manage material and tally data with on-the-fly allocation during simulation, along with numerous optimizations required for scalability as the domain mesh is refined and divided among thousands of compute processes. The algorithms were tested on two supercomputers, namely the Mira Blue Gene/Q and the Titan XK7, demonstrating good performance with realistic tallies and materials requiring over a terabyte of aggregate memory. Performance models were also developed to more accurately predict the network and load imbalance penalties that arise from communicating particles between distributed compute nodes tracking different spatial domains. These were evaluated using machine properties and tallied particle movement characteristics, and empirically validated with observed timing results from the new implementation. Network penalties were shown to be almost negligible with per-process particle counts as low as 1000, and load imbalance penalties higher than a factor of four were not observed or predicted for finer domain meshes relevant to reactor analysis. Load balancing strategies were also explored, and intra-domain replication was shown to be very effective at improving parallel efficiencies without adding significant complexity to the algorithm or burden to the user. Performance of the strategy was quantified with a performance model, and shown to agree well with observed timings. Imbalances were shown to be almost completely removed for the finest domain meshes. Finally, full-core studies were carried out to demonstrate the efficacy of domain-decomposed Monte Carlo in tackling the full scope of the problem. A detailed mesh required for a robust depletion treatment was used, and good performance was demonstrated for depletion tallies with 206 nuclides. The largest runs scored six reaction rates for each nuclide in 51M regions for a total aggregate memory requirement of 1.4TB, and particle tracking rates were consistent with those observed for smaller non-domain- decomposed runs with equivalent tally complexity. These types of runs were previously not achievable with traditional Monte Carlo methods, and can be accomplished with domain decomposition with between 1.4x and 1.75x overhead with simple load balancing.
by Nicholas Edward Horelik.
Ph. D.
Romano, Paul K. (Paul Kollath). "Parallel algorithms for Monte Carlo particle transport simulation on exascale computing architectures." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/80415.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 191-199).
Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallal efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O([square root]N) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes - in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters.
by Paul Kollath Romano.
Ph.D.
Books on the topic "Particle Monte Carlo"
Haghighat, Alireza. Monte Carlo Methods for Particle Transport. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429198397.
Full textKovanen, M. A. Monte Carlo study of charged particle behaviour in tokamak plasmas. Lappeenranta: Lappeenranta University of Technology, 1992.
Find full textLászló, Koblinger, ed. Monte Carlo particle transport methods: Neutron and photon calculations. Boca Raton: CRC Press, 1991.
Find full textGallis, Michael A. On the modeling of thermochemical non-equilibrium in particle simulations. London: Imperial College of Science, Technology & Medicine, Dept. of Aeronautics, 1995.
Find full textKling, Andreas, Fernando J. C. Baräo, Masayuki Nakagawa, Luis Távora, and Pedro Vaz, eds. Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-18211-2.
Full textQuerlioz, Damien. The Wigner Monte-Carlo method for nanoelectronic devices: Particle description of quantum transport and decoherence. London: ISTE, 2010.
Find full textPhilippe, Dollfus, ed. The Wigner Monte-Carlo method for nanoelectronic devices: Particle description of quantum transport and decoherence. London: ISTE, 2010.
Find full textDapor, Maurizio. Electron-Beam Interactions with Solids: Application of the Monte Carlo Method to Electron Scattering Problems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.
Find full textRubilar, R. Comparison of the TEP method for neutral particle transport in the plasma edge with Monte Carlo. Atlanta, Ga: Fusion Research Center, Georgia Institute of Technology, 2000.
Find full textSatō, Akira. Introduction to practice of molecular simulation: Molecular dynamics, Monte Carlo, Brownian dynamics, Lattice Boltzmann, dissipative particle dynamics. Amsterdam: Elsevier, 2011.
Find full textBook chapters on the topic "Particle Monte Carlo"
Andrieu, Christophe, Arnaud Doucet, and Roman Holenstein. "Particle Markov Chain Monte Carlo for Efficient Numerical Simulation." In Monte Carlo and Quasi-Monte Carlo Methods 2008, 45–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04107-5_3.
Full textKleiss, Ronald. "Phase Space Monte Carlo." In Particle Production Spanning MeV and TeV Energies, 281–94. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4126-0_10.
Full textGuiaş, Flavius. "An Improved Implementation of Stochastic Particle Methods and Applications to Coagulation Equations." In Monte Carlo and Quasi-Monte Carlo Methods 2006, 383–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-74496-2_22.
Full textDel Moral, Pierre, Gareth W. Peters, and Christelle Vergé. "An Introduction to Stochastic Particle Integration Methods: With Applications to Risk and Insurance." In Monte Carlo and Quasi-Monte Carlo Methods 2012, 39–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41095-6_3.
Full textSpanier, Jerome. "Quasi-Monte Carlo Methods for Particle Transport Problems." In Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 121–48. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-2552-2_6.
Full textHaghighat, Alireza. "Geometry and particle tracking." In Monte Carlo Methods for Particle Transport, 173–85. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429198397-9.
Full textMusso, Christian, Nadia Oudjane, and Francois Gland. "Improving Regularised Particle Filters." In Sequential Monte Carlo Methods in Practice, 247–71. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3437-9_12.
Full textHaghighat, Alireza. "Fixed-Source Monte Carlo Particle Transport." In Monte Carlo Methods for Particle Transport, 117–35. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429198397-6.
Full textBooth, Thomas. "Particle Transport Applications." In Rare Event Simulation using Monte Carlo Methods, 215–42. Chichester, UK: John Wiley & Sons, Ltd, 2009. http://dx.doi.org/10.1002/9780470745403.ch10.
Full textPitt, Michael K., and Neil Shephard. "Auxiliary Variable Based Particle Filters." In Sequential Monte Carlo Methods in Practice, 273–93. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3437-9_13.
Full textConference papers on the topic "Particle Monte Carlo"
Murata, Masaya, Hidehisa Nagano, and Kunio Kashino. "Monte Carlo filter particle filter." In 2015 European Control Conference (ECC). IEEE, 2015. http://dx.doi.org/10.1109/ecc.2015.7330967.
Full textDaum, Frederick E., and Jim Huang. "Quasi-Monte Carlo hybrid particle filters." In Defense and Security, edited by Oliver E. Drummond. SPIE, 2004. http://dx.doi.org/10.1117/12.532487.
Full textLingling Zhao, Peijun Ma, and Xiaohong Su. "Multiresolutional Quasi-Monte Carlo-based particle filters." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5358144.
Full textWang, Danling, Qin Zhang, and John Morris. "Distributed Markov Chain Monte Carlo Particle Filtering." In 2009 2nd International Conference on Computer Science and its Applications (CSA). IEEE, 2009. http://dx.doi.org/10.1109/csa.2009.5404264.
Full textSweezy, Jeremy, Steve Nolen, Terry Adams, and Anthony Zukaitis. "A Particle Population Control Method for Dynamic Monte Carlo." In SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo, edited by D. Caruge, C. Calvin, C. M. Diop, F. Malvagi, and J. C. Trama. Les Ulis, France: EDP Sciences, 2014. http://dx.doi.org/10.1051/snamc/201403202.
Full textVickery, Curtis M. "Air Filter Pleat Flow Simulations With Monte Carlo Particle Deposition." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/cie-4438.
Full textGao, Hongzhi, and Richard Green. "A sequential Monte Carlo method for particle filters." In 2008 23rd International Conference Image and Vision Computing New Zealand (IVCNZ). IEEE, 2008. http://dx.doi.org/10.1109/ivcnz.2008.4762108.
Full textMartino, L., V. Elvira, and F. Louzada. "Weighting a resampled particle in Sequential Monte Carlo." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551711.
Full textGray, Ander, Andrew Davis, and Edoardo Patelli. "Towards an Interval Particle Transport Monte Carlo Method." In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore: Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_0035-cd.
Full textDaum, Fred. "Quasi-Monte Carlo particle filters: the JV filter." In Defense and Security Symposium, edited by Oliver E. Drummond. SPIE, 2006. http://dx.doi.org/10.1117/12.663914.
Full textReports on the topic "Particle Monte Carlo"
O'Brien, Matthew Joseph. Scalable Domain Decomposed Monte Carlo Particle Transport. Office of Scientific and Technical Information (OSTI), December 2013. http://dx.doi.org/10.2172/1116906.
Full textO'Brien, M. Material Interface Reconstruction for Monte Carlo Particle Tracking. Office of Scientific and Technical Information (OSTI), March 2006. http://dx.doi.org/10.2172/895426.
Full textHeifetz, D. B. Vectorizing and macrotasking Monte Carlo neutral particle algorithms. Office of Scientific and Technical Information (OSTI), April 1987. http://dx.doi.org/10.2172/6210623.
Full textHartmann Siantar, C. L., W. P. Chandler, J. A. Rathkopf, M. M. Svatos, and R. M. White. PEREGRINE: An all-particle Monte Carlo code for radiation therapy. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/72922.
Full textD.P. Stotler. Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model. Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/840785.
Full textBleile, R. Enhancing Monte Carlo Particle Transport for Modern Many-Core Architectures. Office of Scientific and Technical Information (OSTI), February 2021. http://dx.doi.org/10.2172/1769170.
Full textBleile, R. Enhancing Monte Carlo Particle Transport for Modern Many-Core Architectures. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1773584.
Full textBurke, Timothy Patrick. Development of MGMC: A proxy Multi-Group Monte Carlo Particle Transport Application. Office of Scientific and Technical Information (OSTI), February 2020. http://dx.doi.org/10.2172/1599007.
Full textKerns, J. A. Alpha particle density and energy distributions in tandem mirrors using Monte-Carlo techniques. Office of Scientific and Technical Information (OSTI), May 1986. http://dx.doi.org/10.2172/5728137.
Full textAydemir, A. Y. A unified Monte Carlo interpretation of particle simulations and applications to nonneutral plasmas. Office of Scientific and Technical Information (OSTI), September 1993. http://dx.doi.org/10.2172/10186681.
Full text