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NTIS 바로가기Physics of fluids, v.31 no.6, 2019년, pp.066101 -
Myong, R. S. (ANSYS, Inc. 2 , Lebanon, New Hampshire 03766, USA) , Karchani, A. (Supercomputing Modeling and Simulation Center, Korea Institute of Science and Technology Information (KISTI) 3 , Daejeon, South Korea) , Ejtehadi, O.
In 1963, G. A. Bird published a research note on his investigation of a rigid sphere gas reaching translational equilibrium using a Monte Carlo type method. Since then, the method has been developed into a primary workhorse to computationally solve the Boltzmann kinetic equation. As it is increasing...
Phys. Fluids 6 1518 1963 10.1063/1.1710976 Approach to translational equilibrium in a rigid sphere gas
Molecular Gas Dynamics 1976
Molecular Gas Dynamics and the Direct Simulation of Gas Flows 1994
Phys. Fluids 29 047105 2017 10.1063/1.4979793 New chemical-DSMC method in numerical simulation of axisymmetric rarefied reactive flow
Phys. Fluids 30 106111 2018 10.1063/1.5047791 On the unsteadiness of shock-laminar boundary layer interactions of hypersonic flows over a double cone
Phys. Fluids 27 072002 2015 10.1063/1.4927069 Investigation of cold-to-hot transfer and thermal separation zone through nano step geometries
Phys. Fluids 30 102002 2018 10.1063/1.5052253 Oscillatory rarefied gas flow inside a three dimensional rectangular cavity
Phys. Fluids 27 084105 2015 10.1063/1.4928338 Direct simulation Monte Carlo investigation of the Richtmyer-Meshkov instability
Phys. Rev. Lett. 118 064501 2017 10.1103/physrevlett.118.064501 Molecular-level simulations of turbulence and its decay
Verification and Validation in Scientific Computing 2010
Phys. Fluids 11 2788 1999 10.1063/1.870137 Thermodynamically consistent hydrodynamic computational models for high-Knudsen-number gas flows
J. Comput. Phys. 273 160 2014 10.1016/j.jcp.2014.05.013 A triangular discontinuous Galerkin method for non-Newtonian implicit constitutive models of rarefied and microscale gases
Phys. Fluids 28 082003 2016 10.1063/1.4959202 Microscopic molecular dynamics characterization of the second-order non-Navier-Fourier constitutive laws in the Poiseuille gas flow
J. Phys. Soc. Jpn. 49 2050 1980 10.1143/jpsj.49.2050 Direct simulation scheme derived from the Boltzmann equation. II. Multicomponent gas mixtures
J. Phys. Soc. Jpn. 52 3382 1983 10.1143/jpsj.52.3382 Interrelations between various direct simulation methods for solving the Boltzmann equation
SIAM J. Numer. Anal. 26 45 1989 10.1137/0726004 A convergence proof for Nanbu’s simulation method for the full Boltzmann equation
J. Stat. Phys. 66 1011 1992 10.1007/bf01055714 A convergence proof for Bird’s direct simulation Monte Carlo method for the Boltzmann equation
Phys. Fluids 29 3107 1986 10.1063/1.865961 Comparison of the molecular dynamics method and the direct simulation Monte Carlo technique for flows around simple geometries
Phys. Fluids 10 1540 1998 10.1063/1.869674 Cell size dependence of transport coefficients in stochastic particle algorithms
Phys. Fluids 12 2621 2000 10.1063/1.1289691 Time step truncation error in direct simulation Monte Carlo
Phys. Fluids 12 2634 2000 10.1063/1.1289393 Analysis of discretization in the direct simulation Monte Carlo
Phys. Rev. E 69 042201 2004 10.1103/physreve.69.042201 Molecular gas dynamics observations of Chapman-Enskog behavior and departures therefrom in nonequilibrium gases
Sophisticated DSMC
Phys. Fluids 21 017103 2009 10.1063/1.3067865 Accuracy and efficiency of the sophisticated direct simulation Monte Carlo algorithm for simulating noncontinuum gas flows
J. Comput. Phys. 228 4532 2009 10.1016/j.jcp.2009.03.021 Convergence behavior of a new DSMC algorithm
Commun. Comput. Phys. 10 807 2011 10.4208/cicp.090210.311210a Convergence detection in direct simulation Monte Carlo calculations for steady state flows
Comput. Fluids 115 98 2015 10.1016/j.compfluid.2015.03.022 Convergence analysis of the direct simulation Monte Carlo based on the physical laws of conservation
Phys. Fluids 29 062003 2017 10.1063/1.4985712 On the convergence of the simplified Bernoulli trial collision scheme in rarefied Fourier flow
Phys. Fluids 18 017104 2006 10.1063/1.2166449 Normal solutions of the Boltzmann equation for highly nonequilibrium Fourier flow and Couette flow
Comput. Fluids 161 23 2018 10.1016/j.compfluid.2017.11.005 On the consequences of successively repeated collisions in no-time-counter collision scheme in DSMC
Phys. Rev. A 34 1454 1986 10.1103/physreva.34.1454 Nonequilibrium fluctuations studied by a rarefied-gas simulation
J. Comput. Phys. 109 30 1993 10.1006/jcph.1993.1196 Reduction of simulation cost and error for particle simulations of rarefied flows
J. Comput. Phys. 126 434 1996 10.1006/jcph.1996.0148 Statistical error analysis for the direct simulation Monte Carlo technique
J. Comput. Phys. 145 382 1998 10.1006/jcph.1998.6018 Reduction of the number of particles in the stochastic weighted particle method for the Boltzmann equation
J. Comput. Phys. 187 274 2003 10.1016/s0021-9991(03)00099-8 Statistical error in particle simulations of hydrodynamic phenomena
J. Comput. Phys. 227 6249 2008 10.1016/j.jcp.2008.03.015 Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method
Comput. Fluids 38 475 2009 10.1016/j.compfluid.2008.04.010 Improved sampling techniques for the direct simulation Monte Carlo method
Comput. Math. Math. Phys. 50 335 2010 10.1134/s0965542510020156 Estimation of the statistical error of the direct simulation Monte Carlo method
Russ. J. Numer. Anal. Math. Modell. 25 147 2010 10.1515/rjnamm.2010.010 Some approaches to error analysis and optimization of the DSMC method
Comput. Fluids 105 251 2014 10.1016/j.compfluid.2014.09.032 Theoretical and numerical analysis of approaches to evaluation of statistical error of the DSMC method
Comput. Fluids 58 102 2012 10.1016/j.compfluid.2012.01.007 Selection of sampling numerical parameters for the DSMC method
Commun. Comput. Phys. 20 1183 2016 10.4208/cicp.080815.240316a A probabilistic automatic steady state detection method for the direct simulation Monte Carlo
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