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Relevant bibliographies by topics / Direct Simulation Monte Carlo

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Academic literature on the topic 'Direct Simulation Monte Carlo'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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Journal articles on the topic "Direct Simulation Monte Carlo"

1

Danforth, Amanda L., and Lyle N. Long. "Nonlinear acoustic simulations using direct simulation Monte Carlo." Journal of the Acoustical Society of America 116, no. 4 (October 2004): 1948–55. http://dx.doi.org/10.1121/1.1785614.

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Alexander, Francis J., and Alejandro L. Garcia. "The Direct Simulation Monte Carlo Method." Computers in Physics 11, no. 6 (1997): 588. http://dx.doi.org/10.1063/1.168619.

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Carlson, Ann B., and H. A. Hassan. "Radiation modeling with direct simulation Monte Carlo." Journal of Thermophysics and Heat Transfer 6, no. 4 (October 1992): 631–36. http://dx.doi.org/10.2514/3.11544.

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TSUTSUI, Shingo, and Keiichi FUTAGI. "The Application Example of Direct Simulation Monte Carlo Method to Turbo-molecular Pump." Journal of the Vacuum Society of Japan 58, no. 7 (2015): 253–56. http://dx.doi.org/10.3131/jvsj2.58.253.

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Alamatsaz, Arghavan, and Ayyaswamy Venkattraman. "Characterizing deviation from equilibrium in direct simulation Monte Carlo simulations." Physics of Fluids 31, no. 4 (April 2019): 042005. http://dx.doi.org/10.1063/1.5093732.

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Liou, William W., and Yichuan Fang. "Forced Couette flow simulations using direct simulation Monte Carlo method." Physics of Fluids 16, no. 12 (December 2004): 4211–20. http://dx.doi.org/10.1063/1.1801092.

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Lo, Ming-Chung, Chien-Yu Pan, and Jong-Shinn Wu. "On an Axisymmetric Direct Simulation Monte Carlo Method." International Journal of Computational Fluid Dynamics 35, no. 5 (May 28, 2021): 373–87. http://dx.doi.org/10.1080/10618562.2021.1955867.

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Hong, Andrew, and Aaron Morris. "Novel direct simulation Monte Carlo method for spherocylinders." Powder Technology 399 (February 2022): 117085. http://dx.doi.org/10.1016/j.powtec.2021.117085.

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Sharipov, Felix. "Direct Simulation Monte Carlo Method Applied to Aerothermodynamics." Journal of the Brazilian Society of Mechanical Sciences 23, no. 4 (2001): 441–52. http://dx.doi.org/10.1590/s0100-73862001000400005.

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Carlson, Ann B., and Richard G. Wilmoth. "Shock interference prediction using direct simulation Monte Carlo." Journal of Spacecraft and Rockets 29, no. 6 (November 1992): 780–85. http://dx.doi.org/10.2514/3.25531.

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Dissertations / Theses on the topic "Direct Simulation Monte Carlo"

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Alves, Nuno Franco Rodrigues. "Direct simulation Monte Carlo of non-equilbrium rarefied flows." Thesis, Queen Mary, University of London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421089.

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Buxton, Robert Charles. "Direct simulation Monte Carlo modelling of physical vapour deposition." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426851.

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Armour, Jessica D. "On the Gap-Tooth direct simulation Monte Carlo method." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/72863.

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Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, February 2012.
"February 2012." Cataloged from PDF version of thesis.
Includes bibliographical references (p. [73]-74).
This thesis develops and evaluates Gap-tooth DSMC (GT-DSMC), a direct Monte Carlo simulation procedure for dilute gases combined with the Gap-tooth method of Gear, Li, and Kevrekidis. The latter was proposed as a means of reducing the computational cost of microscopic (e.g. molecular) simulation methods using simulation particles only in small regions of space (teeth) surrounded by (ideally) large gaps. This scheme requires an algorithm for transporting particles between teeth. Such an algorithm can be readily developed and implemented within direct Monte Carlo simulations of dilute gases due to the non-interacting nature of the particle-simulators. The present work develops and evaluates particle treatment at the boundaries associated with diffuse-wall boundary conditions and investigates the drawbacks associated with GT-DSMC implementations which detract from the theoretically large computational benefit associated with this algorithm (the cost reduction is linear in the gap-to-tooth ratio). Particular attention is paid to the additional numerical error introduced by the gap-tooth algorithm as well as the additional statistical uncertainty introduced by the smaller number of particles. We find the numerical error introduced by transporting particles to adjacent teeth to be considerable. Moreover, we find that due to the reduced number of particles in the simulation domain, correlations persist longer, and thus statistical uncertainties are larger than DSMC for the same number of particles per cell. This considerably reduces the computational benefit associated with the GT-DSMC algorithm. We conclude that the GT-DSMC method requires more development, particularly in the area of error and uncertainty reduction, before it can be used as an effective simulation method.
by Jessica D. Armour.
S.M.

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Rangaraj, Dharanipathy. "Multicomponent aerosol dynamics : exploration of direct simulation Monte Carlo technique /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144452.

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Wishart, Stuart Jackson. "A Parallel Solution Adaptive Implementation of the Direct Simulation Monte Carlo Method." University of Sydney. School of Aerospace, Mechanical and Mechatronic Engineering, 2005. http://hdl.handle.net/2123/619.

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This thesis deals with the direct simulation Monte Carlo (DSMC) method of analysing gas flows. The DSMC method was initially proposed as a method for predicting rarefied flows where the Navier-Stokes equations are inaccurate. It has now been extended to near continuum flows. The method models gas flows using simulation molecules which represent a large number of real molecules in a probabilistic simulation to solve the Boltzmann equation. Molecules are moved through a simulation of physical space in a realistic manner that is directly coupled to physical time such that unsteady flow characteristics are modelled. Intermolecular collisions and moleculesurface collisions are calculated using probabilistic, phenomenological models. The fundamental assumption of the DSMC method is that the molecular movement and collision phases can be decoupled over time periods that are smaller than the mean collision time. Two obstacles to the wide spread use of the DSMC method as an engineering tool are in the areas of simulation configuration, which is the configuration of the simulation parameters to provide a valid solution, and the time required to obtain a solution. For complex problems, the simulation will need to be run multiple times, with the simulation configuration being modified between runs to provide an accurate solution for the previous run�s results, until the solution converges. This task is time consuming and requires the user to have a good understanding of the DSMC method. Furthermore, the computational resources required by a DSMC simulation increase rapidly as the simulation approaches the continuum regime. Similarly, the computational requirements of three-dimensional problems are generally two orders of magnitude more than two-dimensional problems. These large computational requirements significantly limit the range of problems that can be practically solved on an engineering workstation or desktop computer. The first major contribution of this thesis is in the development of a DSMC implementation that automatically adapts the simulation. Rather than modifying the simulation configuration between solution runs, this thesis presents the formulation of algorithms that allow the simulation configuration to be automatically adapted during a single run. These adaption algorithms adjust the three main parameters that effect the accuracy of a DSMC simulation, namely the solution grid, the time step and the simulation molecule number density. The second major contribution extends the parallelisation of the DSMC method. The implementation developed in this thesis combines the capability to use a cluster of computers to increase the maximum size of problem that can be solved while simultaneously allowing excess computational resources to decrease the total solution time. Results are presented to verify the accuracy of the underlying DSMC implementation, the utility of the solution adaption algorithms and the efficiency of the parallelisation implementation.

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Basik, Beata-Marie. "Direct simulation Monte Carlo model of a couette flow of granular materials." Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=60433.

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Since life-threatening natural phenomena, such as, snow avalanches and lava flows, and many industrial and agricultural material handling processes may be classified as granular flows, establishing constitutive relationships which model granular flow behaviour is of prime importance. While laboratory experiments attempting to support granular flow theory have been plagued by poor instrumentation, numerical simulations are becoming increasingly helpful in understanding the nature of these flows. The present investigation describes such a simulation developed within the framework of the Direct Simulation Monte Carlo model for rarefied gases presented in Bird (1976) and granular flow kinetic theory according to Lun, et al. (1984). More specifically, the model generates a Couette flow of smooth, inelastic, homogeneous, spherical granular particles. Two different boundary condition models are used to model the flow field's upper and lower boundaries: the Periodic Boundary Condition (PBC) model and the Finite Shear Layer (FSL) model. An essentially uniform shear flow with virtually no slip at the boundaries results from both boundary conditions. Stress and granular temperature results obtained with the PBC and FSL models for the lower range of solids fractions ($ nu < 0.3)$ compare very well with the Lun, et al. (1984) theory. At higher solids fractions, while the total stresses generated with both boundary models are in reasonable agreement with the latter theory and results from other numerical work, higher than expected streaming stresses appear to be compensating for lower than expected collisional stresses; as a result, granular temperature in this range of solids fractions proves to be higher than predicted.

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Parsons, Timothy Langdon. "Object-reuse-oriented design of direct simulation Monte-Carlo software for rarefied gas dynamics." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314287.

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Simmons, Russell. "Direct Simulation Monte Carlo modelling of surface catalytic events in high enthalpy rarefied gas flows." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318865.

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Ahmad, Abdul Ossman. "Advances in an open-source direct simulation Monte Carlo technique for hypersonic rarefied gas flows." Thesis, University of Strathclyde, 2013. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=26579.

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Hypersonic vehicles that travel through rarefied gas environments are very expensive to design through experimental methods. In the last few decades major work has been carried out in developing numerical methods to capture these types of flows to a certain degree of accuracy. This accuracy is increased using particle based numerical techniques as opposed to continuum computational fluid dynamics. However, one of the modern problems of particle based techniques is the high computational cost associated with it. This thesis presents an enhanced open-source particle based technique to capture high speed rarefied gas flows. This particle based technique is called dsmcFoam and is based on the direct simulation Monte Carlo technique. As a result of the author's work dsmcFoam has become more efficient and accurate. Benchmark studies of the standard dsmcFoam solver will be presented before introducing the main advances. The results of the benchmark investigations are compared with analytical solutions, other DSMC codes and experimental data available in the literature. And excellent agreement is found when good DSMC practice has been followed. The main advances of dsmcFoam discussed are a routine for selecting collision pairs called the transient adaptive sub-cell (TASC) method and a dynamic wall temperature model (DWTM). The DWTM relates the wall temperature to the heat flux. In addition, verification and validation studies are undertaken of the DWTM. Furthermore, the widely used conventional 8 sub-cell method used to select possible collision pairs becomes very cumbersome to employ properly. This is because many mesh refinement stages are required in order to obtain accurate data. Instead of mesh refinement the TASC technique automatically employs more sub-cells, and these sub-cells are based on the number of particles in a cell. Finally, parallel efficiency tests of dsmcFoam are presented in this thesis along with a new domain decomposition technique for parallel processing. This technique splits up the computational domain based on the number of particles, such that each processor has the same number of particles to work with.

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Mirza, Asim [Verfasser]. "Entwicklung eines partikelbasierten Kontinuumsverfahrens zur bidirektionalen Kopplung mit der Direct Simulation Monte Carlo Methode / Asim Mirza." München : Verlag Dr. Hut, 2019. http://d-nb.info/1198542985/34.

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Books on the topic "Direct Simulation Monte Carlo"

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Koura, Katsuhisa. Comparison between the null-collision and time-counter direct-simulation Monte Carlo methods: leading-edge flow. Tokyo: National Aerospace Laboratory, 1989.

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Koura, Katsuhisa. A sensitivity test for accuracy in evaluation of molecular collision number in the direct-simulation Monte Carlo method. Tokyo, Japan: National Aerospace Laboratory, 1990.

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3

Gallis, M. A. Modelling of ionisation reactions and of the resulting electric fields in one-dimensional hypersonic shock waves with the direct simulation Monte Carlo method. London, England: Imperial College of Science Technology & Medicine, Dept. of Aeronautics, 1992.

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Gallis, M. A. The maximum entropy approach applied to energy exchange, chemical reactions and ionisation in the direct simulation Monte Carlo method for rarefied hypersonic flows. London: Imperial College of Science Technology and Medicine, 1993.

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Mooney, Christopher. Monte Carlo Simulation. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 1997. http://dx.doi.org/10.4135/9781412985116.

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Monte Carlo simulation. Thousand Oaks, Calif: Sage Publications, 1997.

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Zhu, Zhen, and Hari Rajagopalan. Monte Carlo Simulation. 2455 Teller Road, Thousand Oaks California 91320 United States: SAGE Publications, Inc., 2023. http://dx.doi.org/10.4135/9781071908969.

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Hess, Karl, ed. Monte Carlo Device Simulation. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4026-7.

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Thomopoulos, Nick T. Essentials of Monte Carlo Simulation. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6022-0.

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Brandimarte, Paolo. Handbook in Monte Carlo Simulation. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118593264.

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Book chapters on the topic "Direct Simulation Monte Carlo"

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Mukinovic, M., and G. Brenner. "Direct Monte Carlo Simulation of low-speed flows." In Lecture Notes in Computational Science and Engineering, 313–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92744-0_39.

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Garcia, Alejandro L. "Hydrodynamic Fluctuations and the Direct Simulation Monte Carlo Method." In Microscopic Simulations of Complex Flows, 177–88. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-1339-7_12.

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Walenta, Z. A., and K. Lener. "Direct Monte-Carlo simulation of developing detonation in gas." In Shock Waves, 227–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85168-4_35.

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Reschke, Wladimir, Marcel Pfeiffer, and Stefanos Fasoulas. "Enabling Simulations of Droplets with the Direct Simulation Monte Carlo Method." In Fluid Mechanics and Its Applications, 57–68. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33338-6_5.

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Bird, G. A. "The Direct Simulation Monte Carlo Method: Current Status and Perspectives." In Microscopic Simulations of Complex Flows, 1–13. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-1339-7_1.

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Benzi, John, and M. Damodaran. "Parallel Three Dimensional Direct Simulation Monte Carlo for Simulating Micro Flows." In Lecture Notes in Computational Science and Engineering, 91–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92744-0_11.

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Bird, G. A. "A Contemporary Implementation of the Direct Simulation Monte Carlo Method." In Microscopic Simulations of Complex Hydrodynamic Phenomena, 239–53. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-2314-1_18.

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Alexander, Francis J. "The Direct Simulation Monte Carlo Method: Going Beyond Continuum Hydrodynamics." In Handbook of Materials Modeling, 2513–22. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-3286-2_132.

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Alexander, Francis J. "The Direct Simulation Monte Carlo Method: Going Beyond Continuum Hydrodynamics." In Handbook of Materials Modeling, 2513–22. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/978-1-4020-3286-8_132.

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Liang, Jie. "Parallel Direct Simulation Monte Carlo Using Graphics Processing Unit with CUDA." In Communications in Computer and Information Science, 354–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-53962-6_31.

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Conference papers on the topic "Direct Simulation Monte Carlo"

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Schrock, Christopher, and Aihua Wood. "Distributional Direct Simulation Monte Carlo Methods." In 10th AIAA/ASME Joint Thermophysics and Heat Transfer Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-4501.

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Balakrishnan, Kaushik, John B. Bell, Aleksandar Donev, and Alejandro L. Garcia. "Fluctuating hydrodynamics and direct simulation Monte Carlo." In 28TH INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4769610.

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Camberos, Jose, Robert Greendyke, and Larry Lambe. "On Direct Simulation Quasi-Monte Carlo Methods." In 40th Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-3915.

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CARLSON, ANN, and H. HASSAN. "Radiation modeling with direct simulation Monte Carlo." In 26th Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-1409.

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CARLSON, ANN, and RICHARD WILMOTH. "Shock interference prediction using direct simulation Monte Carlo." In 30th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-492.

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Vedula, Prakash, and Dustin Otten. "Importance Sampling Based Direct Simulation Monte Carlo Method." In 10th AIAA/ASME Joint Thermophysics and Heat Transfer Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-5061.

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Summers, Sarah, and Robert Greendyke. "Improved Collision Modeling for Direct Simulation Monte Carlo." In 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-652.

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WILMOTH, RICHARD. "Direct simulation Monte Carlo analysis on parallel processors." In 24th Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1666.

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Gallis, Michael, and Timothy Bartel. "Direct Simulation Monte Carlo modeling of viscous interactions." In 33rd Thermophysics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1999. http://dx.doi.org/10.2514/6.1999-3453.

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Tatarskii, V. V. "Direct Monte Carlo simulation of the ocean surface." In IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174). IEEE, 1998. http://dx.doi.org/10.1109/igarss.1998.703817.

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Reports on the topic "Direct Simulation Monte Carlo"

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Boyd, Iain D. A Threshold Line Dissociation Model for the Direct Simulation Monte Carlo Method,. Fort Belvoir, VA: Defense Technical Information Center, May 1996. http://dx.doi.org/10.21236/ada324950.

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BARTEL, TIMOTHY J., STEVEN J. PLIMPTON, and MICHAIL A. GALLIS. Icarus: A 2-D Direct Simulation Monte Carlo (DSMC) Code for Multi-Processor Computers. Office of Scientific and Technical Information (OSTI), October 2001. http://dx.doi.org/10.2172/789256.

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Campbell, David, Dean Wadsworth, Douglas VanGilder, Ingrid Wysong, and Carolyn Kaplan. SUPREM-DSMC: A New Scalable, Parallel, Reacting, Multidimensional Direct Simulation Monte Carlo Flow Code. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada407889.

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Campbell, David, Dean Wadsworth, Ingrid Wysong, and Carolyn Kaplan. SUPREM DSMC: A New Scalable, Parallel, Reacting, Multidimensional Direct Simulation Monte Carlo Flow Code. Fort Belvoir, VA: Defense Technical Information Center, February 2000. http://dx.doi.org/10.21236/ada409492.

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Garcia, A. L., F. Baras, and M. M. Mansour. Comment on ``Simulation of a two-dimensional Rayleigh-Benard system using the direct simulation Monte Carlo method``. Office of Scientific and Technical Information (OSTI), June 1994. http://dx.doi.org/10.2172/371414.

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Pacheco, Jose, Zakari Eckert, Russell Hooper, Melissa Finley, and Ronald Manginell. A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1648851.

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Bartel, T., S. Plimpton, J. Johannes, and J. Payne. Icarus: A 2D direct simulation Monte Carlo (DSMC) code for parallel computers. User`s manual - V.3.0. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/399675.

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Glaser, R. Monte Carlo simulation of scenario probability distributions. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/632934.

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Xu, S. L., B. Lai, and P. J. Viccaro. APS undulator and wiggler sources: Monte-Carlo simulation. Office of Scientific and Technical Information (OSTI), February 1992. http://dx.doi.org/10.2172/10134610.

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Douglas, L. J. Monte Carlo Simulation as a Research Management Tool. Office of Scientific and Technical Information (OSTI), June 1986. http://dx.doi.org/10.2172/1129252.

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