Title

An Efficient Localized Radial Basis Function Meshless Method For Fluid Flow And Conjugate Heat Transfer

Abstract

A localized radial basis function (RBF) meshless method is developed for coupled viscous fluid flow and convective heat transfer problems. The method is based on new localized radial-basis function (RBF) expansions using Hardy Multiquadrics for the sought-after unknowns. An efficient set of formulae are derived to compute the RBF interpolation in terms of vector products thus providing a substantial computational savings over traditional meshless methods. Moreover, the approach developed in this paper is applicable to explicit or implicit time marching schemes as well as steady-state iterative methods. We apply the method to viscous fluid flow and conjugate heat transfer (CHT) modeling. The incompressible Navier-Stokes are time marched using a Helmholtz potential decomposition for the velocity field. When CHT is considered, the same RBF expansion is used to solve the heat conduction problem in the solid regions enforcing temperature and heat flux continuity of the solid/fluid interfaces. The computation is accelerated by distributing the load over several processors via a domain decomposition along with an interface interpolation tailored to pass information through each of the domain interfaces to ensure conservation of field variables and derivatives. Numerical results are presented for several cases including channel flow, flow in a channel with a square step obstruction, and a jet flow into a square cavity. Results are compared with commercial computational fluid dynamics code predictions. The proposed localized meshless method approach is shown to produce accurate results while requiring a much-reduced effort in problem preparation in comparison to other traditional numerical methods. Copyright © 2007 by ASME.

Publication Date

2-1-2007

Publication Title

Journal of Heat Transfer

Volume

129

Issue

2

Number of Pages

124-136

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1115/1.2402181

Socpus ID

34248398491 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/34248398491

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