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A high-order moment approach for capturing non-equilibrium phenomena in the transition regime

Published online by Cambridge University Press:  25 September 2009

XIAO-JUN GU*
Affiliation:
Computational Science and Engineering Department, STFC Daresbury Laboratory, Warrington WA4 4AD, UK
DAVID R. EMERSON
Affiliation:
Computational Science and Engineering Department, STFC Daresbury Laboratory, Warrington WA4 4AD, UK
*
Email address for correspondence: xiaojun.gu@stfc.ac.uk

Abstract

The method of moments is employed to extend the validity of continuum-hydrodynamic models into the transition-flow regime. An evaluation of the regularized 13 moment equations for two confined flow problems, planar Couette and Poiseuille flows, indicates some important limitations. For planar Couette flow at a Knudsen number of 0.25, they fail to reproduce the Knudsen-layer velocity profile observed using a direct simulation Monte Carlo approach, and the higher-order moments are not captured particularly well. Moreover, for Poiseuille flow, this system of equations creates a large slip velocity leading to significant overprediction of the mass flow rate for Knudsen numbers above 0.4. To overcome some of these difficulties, the theory of regularized moment equations is extended to 26 moment equations. This new set of equations highlights the importance of both gradient and non-gradient transport mechanisms and is shown to overcome many of the limitations observed in the regularized 13 moment equations. In particular, for planar Couette flow, they can successfully capture the observed Knudsen-layer velocity profile well into the transition regime. Moreover, this new set of equations can correctly predict the Knudsen layer, the velocity profile and the mass flow rate of pressure-driven Poiseuille flow for Knudsen numbers up to 1.0 and captures the bimodal temperature profile in force-driven Poiseuille flow. Above this value, the 26 moment equations are not able to accurately capture the velocity profile in the centre of the channel. However, they are able to capture the basic trends and successfully predict a Knudsen minimum at the correct value of the Knudsen number.

Type
Papers
Copyright
Copyright © Cambridge University Press 2009

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