Title

A Coupled Localized Rbf Meshless/Drbem Formulation For Accurate Modeling Of Incompressible Fluid Flows

Keywords

Dual reciprocity boundary element method; Incompressible fluid flows; Meshless methods; Radial basis functions

Abstract

Velocity-pressure coupling schemes for the solution of incompressible fluid flow problems in Computational Fluid Dynamics (CFD) rely on the formulation of Poisson-like equations through projection methods. The solution of these Poisson-like equations represent the pressure correction and the velocity correction to ensure proper satisfaction of the conservation of mass equation at each step of a time-marching scheme or at each level of an iteration process. Inaccurate solutions of these Poisson-like equations result in meaningless instantaneous or intermediate approximations that do not represent the proper time-accurate behavior of the flow. The fact that these equations must be solved to convergence at every step of the overall solution process introduces a major bottleneck for the efficiency of the method. We present a formulation that achieves high levels of accuracy and efficiency by properly solving the Poisson equations at each step of the solution process by formulating a Localized RBF Collocation Meshless Method (LRC-MM) solution approach for the approximation of the diffusive and convective derivatives while employing the same framework to implement a Dual-Reciprocity Boundary Element Method (DR-BEM) for the solution of the ensuing Poisson equations. The same boundary discretization and point distribution employed in the LRC-MM is used for the DR-BEM. The methodology is implemented and tested in the solution of a backward-facing step problem.

Publication Date

1-1-2017

Publication Title

International Journal of Computational Methods and Experimental Measurements

Volume

5

Issue

3

Number of Pages

359-368

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.2495/CMEM-V5-N3-359-368

Socpus ID

85064190013 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85064190013

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