Preconditioned Linear Solvers for Large Eddy Simulation

Efficient solution of linear systems of equations stemming from cell centered Finite Volume Discretization in Large Eddy Simulation is critical in large-scale sim- ulations. This paper presents a class of sparse matrix iterative solvers combining Algebraic Multigrid (AMG) and Krylov Space techniques with the idea of combining residual reduction techniques to improve efficiency over the current solver technology. Emphasis is placed on choosing combinations of a solver, a preconditioner and a smoother and setting control parameters that yield the most efficient solution. Results show consistent superiority of AMG-preconditioned Conjugate Gradient solvers for matrices under consideration.