A comparative study of three iterative methods for solution of incompressible fluid flow equations

This paper contrasts the performances of three iterative solvers for large sparse linear systems arising in the numerical computations of incompressible Navier-Stokes equations. The emphasis is on the traditional GaussSeidel (GS) and Point Successive Over-relaxation (PSOR) algorithms as well as Krylov projection techniques such as Generalized Minimal Residual (GMRES). The performances of these three methods for the secondorder finite difference algebraic equations are comparatively studied by their application to solve a benchmark problem in Computational Fluid Dynamics (CFD). It is found that as the mesh size increases, GMRES gives the fastest convergence rate in terms of cpu time and number of iterations.