Published October 1, 2017 | Version v1
Journal article

Evaluation of new collision-pair selection models in DSMC

  • 1. Aviation Technology Research Institute, Ferdowsi University of Mashhad, PO Box 91779-48974, Mashhad (Iran, Islamic Republic of)
  • 2. High Performance Computing (HPC) Laboratory, Department of Mechanical Engineering, Ferdowsi University of Mashhad, PO Box 91775-1111, Mashhad (Iran, Islamic Republic of)

Description

The current paper investigates new collision-pair selection procedures in a direct simulation Monte Carlo (DSMC) method. Collision partner selection based on the random procedure from nearest neighbor particles and deterministic selection of nearest neighbor particles have already been introduced as schemes that provide accurate results in a wide range of problems. In the current research, new collision-pair selections based on the time spacing and direction of the relative movement of particles are introduced and evaluated. Comparisons between the new and existing algorithms are made considering appropriate test cases including fluctuations in homogeneous gas, 2D equilibrium flow, and Fourier flow problem. Distribution functions for number of particles and collisions in cell, velocity components, and collisional parameters (collision separation, time spacing, relative velocity, and the angle between relative movements of particles) are investigated and compared with existing analytical relations for each model. The capability of each model in the prediction of the heat flux in the Fourier problem at different cell numbers, numbers of particles, and time steps is examined. For new and existing collision-pair selection schemes, the effect of an alternative formula for the number of collision-pair selections and avoiding repetitive collisions are investigated via the prediction of the Fourier heat flux. The simulation results demonstrate the advantages and weaknesses of each model in different test cases. (paper: classical statistical mechanics, equilibrium and non-equilibrium)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-5468/aa8c38

Additional details

Identifiers

Publishing Information

Journal Title
Journal of Statistical Mechanics
Journal Volume
2017
Journal Issue
10
Journal Page Range
[20 p.]
ISSN
1742-5468

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49080055
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
ALGORITHMS; COLLISIONS; COMPUTERIZED SIMULATION; DISTRIBUTION FUNCTIONS; HEAT FLUX; MONTE CARLO METHOD; PARTICLES; RANDOMNESS
Descriptors DEC
CALCULATION METHODS; FUNCTIONS; MATHEMATICAL LOGIC; SIMULATION