4.5 Article

Impact of Artificial Compressibility on the Numerical Solution of Incompressible Nanofluid Flow

Journal

CMC-COMPUTERS MATERIALS & CONTINUA
Volume 74, Issue 3, Pages 5123-5139

Publisher

TECH SCIENCE PRESS
DOI: 10.32604/cmc.2023.034008

Keywords

Navier-Stokes equations; incompressible flow; artificial compres-sibility; convergence rate; convection flow

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The numerical solution of compressible flows is more prevalent than that of incompressible flows. The artificial compressibility approach is widely used to solve incompressible Navier-Stokes equations numerically. This paper assesses the effect of the compressibility factor on the convergence speed and accuracy of results for various types of thermo-flow.
The numerical solution of compressible flows has become more prevalent than that of incompressible flows. With the help of the artificial compressibility approach, incompressible flows can be solved numerically using the same methods as compressible ones. The artificial compressibility scheme is thus widely used to numerically solve incompressible Navier-Stokes equations. Any numerical method highly depends on its accuracy and speed of convergence. Although the artificial compressibility approach is utilized in several numerical simulations, the effect of the compressibility factor on the accuracy of results and convergence speed has not been investigated for nanofluid flows in previous studies. Therefore, this paper assesses the effect of this factor on the convergence speed and accuracy of results for various types of thermo-flow. To improve the stability and convergence speed of time discretizations, the fifth-order Runge-Kutta method is applied. A computer program has been written in FORTRAN to solve the discretized equations in different Reynolds and Grashof numbers for various grids. The results demonstrate that the artificial compressibility factor has a noticeable effect on the accuracy and convergence rate of the simulation. The optimum artificial compressibility is found to be between 1 and 5. These findings can be utilized to enhance the performance of commercial numerical simulation tools, including ANSYS and COMSOL.

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