Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
522688 | Journal of Computational Physics | 2007 | 8 Pages |
Abstract
Use of a high-order deterministic sampling technique in direct simulation Monte-Carlo (DSMC) simulations eliminates statistical noise and improves computational performance by orders of magnitude. In this paper it is also shown that if a random timestep is used in place of a fixed timestep, there is an additional improvement in performance. This performance can be increased by using a timestep that samples a random variable with a high-kurtosis probability density function. As a simple example of the method, the one-dimensional diffusion equation with an exponentially-distributed timestep is simulated, and a performance gain of approximately two is obtained. Applications to numerical simulations of fluids and plasmas are indicated.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
William Peter,