Sensitivity Analysis of Direct Simulation Monte Carlo Parameters for Ionizing Hypersonic Flows

2018 ◽  
Vol 32 (1) ◽  
pp. 90-102 ◽  
Author(s):  
Kyle J. Higdon ◽  
David B. Goldstein ◽  
Philip L. Varghese
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Direct Simulation Monte Carlo ◽  
Hypersonic Flows ◽  
Direct Simulation ◽  
Simulation Monte Carlo

Reaction cross sections for two direct simulation Monte Carlo models: Accuracy and sensitivity analysis

2012 ◽  
Vol 24 (4) ◽  
pp. 042002 ◽  
Author(s):  
Ingrid Wysong ◽  
Sergey Gimelshein ◽  
Natalia Gimelshein ◽  
William McKeon ◽  
Fabrizio Esposito
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Cross Sections ◽  
Direct Simulation Monte Carlo ◽  
Reaction Cross ◽  
Direct Simulation ◽  
Simulation Monte Carlo ◽  
Reaction Cross Sections

scholarly journals Open-Source Direct Simulation Monte Carlo Chemistry Modeling for Hypersonic Flows

AIAA Journal ◽  
2015 ◽  
Vol 53 (6) ◽  
pp. 1670-1680 ◽  
Author(s):  
Thomas J. Scanlon ◽  
Craig White ◽  
Matthew K. Borg ◽  
Rodrigo C. Palharini ◽  
Erin Farbar ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Open Source ◽  
Direct Simulation Monte Carlo ◽  
Hypersonic Flows ◽  
Direct Simulation ◽  
Chemistry Modeling ◽  
Simulation Monte Carlo

Numerical Methods for the Kinetic Theory of Fluids

2018 ◽  
Author(s):  
Sauro Succi
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Numerical Methods ◽  
Kinetic Theory ◽  
Computational Efficiency ◽  
Lattice Boltzmann ◽  
Direct Simulation Monte Carlo ◽  
Particle Methods ◽  
Direct Simulation ◽  
Simulation Monte Carlo

This chapter provides a bird’s eye view of the main numerical particle methods used in the kinetic theory of fluids, the main purpose being of locating Lattice Boltzmann in the broader context of computational kinetic theory. The leading numerical methods for dense and rarified fluids are Molecular Dynamics (MD) and Direct Simulation Monte Carlo (DSMC), respectively. These methods date of the mid 50s and 60s, respectively, and, ever since, they have undergone a series of impressive developments and refinements which have turned them in major tools of investigation, discovery and design. However, they are both very demanding on computational grounds, which motivates a ceaseless demand for new and improved variants aimed at enhancing their computational efficiency without losing physical fidelity and vice versa, enhance their physical fidelity without compromising computational viability.

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