Matrix-free second-order methods in implicit time integration for compressible flows using automatic differentiation

Abstract

In the numerical simulation of inviscid and viscous compressible fluid flow, implicit time integration schemes based on Newton-Krylov methods are frequently used. A crucial ingredient of Krylov subspace methods is the evaluation of the product of the Jacobian matrix of the spatial operator, e.g., fluxes, and a Krylov vector. In this article, we consider a matrix-free, consistently second-order accurate implementation of the Jacobian-vector product within the flow solver QUADFLOW using automatic differentiation. The convergences of the non-linear iteration using first-and second-order accurate Jacobian-vector products are compared. Different algorithmic parameters such as the CFL number and the choice of the preconditioner are taken into account. Investigations of inviscid flow around an airfoil and a wing of an aircraft, as well as the viscous laminar flow over a flat plate demonstrate that the convergence of the Newton-Krylov solver can significantly be improved using consistently second-order accurate matrix-vector products, compared to standard first-order approximations. It has been shown that a hybrid strategy using a blend between first-order and second-order accurate matrix-vector products is the best choice to obtain an efficient and robust algorithm.