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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
