Robust semidirect finite difference methods for solving the Navier–Stokes and energy equations
作者:
J. Ward Macarthur,
Suhas V. Patankar,
期刊:
International Journal for Numerical Methods in Fluids
(WILEY Available online 1989)
卷期:
Volume 9,
issue 3
页码: 325-340
ISSN:0271-2091
年代: 1989
DOI:10.1002/fld.1650090307
出版商: John Wiley&Sons, Ltd
关键词: Semidirect methods;Finite difference formulation;Robust solutions;Navier–Stokes and energy equations
数据来源: WILEY
摘要:
AbstractSemidirect solution techniques can be an effective alternative to the more conventional iterative approaches used in many finite difference methods. This paper summarizes several semidirect techniques which generally have not been applied to the Navier–Stokes and energy equations in finite difference form. The methods presented use both successive substitution and Jacobian‐based updates as well as two variations of Broyden's full matrix update. A hybrid method is also presented, as is a norm‐reducing search technique that can be used to enhance the convergence characteristics of any semidirect approach. These methods have been compared with the well known iterative methods SIMPLE and SIMPLER. The comparison was performed on the natural convection and driven cavity problems. The semidirect methods proved to be reliably convergent without the need fora priorispecification of variable under‐relaxation factors, which was necessary with the iterative methods. Natural convection and driven cavity solutions have been readily obtained with the proposed methods for Rayleigh and Reynolds numbers up to 109and 106respectively. Of the semidirect techniques, the hybrid approach was the most robust. From an arbitrary zero initial guess this method was able to obtain a solution to the natural convection problem for Rayleigh numbers three orders of magnitude larger than was possible with the Newton‐Raphson update. The computational effort required by the semidirect methods is comparable to that required by the iterative methods; however, the memory requirements can be significantl
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