No Cover Image

Journal article 328 views 42 downloads

Nano–particle drag prediction at low Reynolds number using a direct Boltzmann–BGK solution approach / B. Evans

Journal of Computational Physics

Swansea University Author: Evans, Ben

Abstract

This paper outlines a novel approach for solution of the Boltzmann-BGK equation describing molecular gas dynamics applied to the challenging problem of drag prediction of a 2D circular nano–particle at transitional Knudsen number (0.0214) and low Reynolds number (0.25–2.0). The numerical scheme util...

Full description

Published in: Journal of Computational Physics
ISSN: 0021-9991
Published: 2017
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa35652
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: This paper outlines a novel approach for solution of the Boltzmann-BGK equation describing molecular gas dynamics applied to the challenging problem of drag prediction of a 2D circular nano–particle at transitional Knudsen number (0.0214) and low Reynolds number (0.25–2.0). The numerical scheme utilises a discontinuous-Galerkin finite element discretisation for the physical space representing the problem particle geometry and a high order discretisation for molecular velocity space describing the molecular distribution function. The paper shows that this method produces drag predictions that are aligned well with the range of drag predictions for this problem generated from the alternative numerical approaches of molecular dynamics codes and a modified continuum scheme. It also demonstrates the sensitivity of flow-field solutions and therefore drag predictions to the wall absorption parameter used to construct the solid wall boundary condition used in the solver algorithm. The results from this work has applications in fields ranging from diagnostics and therapeutics in medicine to the fields of semiconductors and xerographics.
Keywords: nano–particle; drag; Boltzmann; molecular dynamics; discontinuous Galerkin; finite element
College: College of Engineering