Domain decomposition preconditioners for high-order discretisations of the heterogeneous Helmholtz equation

04/08/2020 ∙ by Shihua Gong, et al. ∙ 0

We consider one-level additive Schwarz domain decomposition preconditioners for the Helmholtz equation with variable coefficients (modelling wave propagation in heterogeneous media), subject to boundary conditions that include wave scattering problems. Absorption is included as a parameter in the problem. This problem is discretised using H^1-conforming nodal finite elements of fixed local degree p on meshes with diameter h = h(k), chosen so that the error remains bounded with increasing k. The action of the one-level preconditioner consists of the parallel solution of problems on subdomains (which can be of general geometry), each equipped with an impedance boundary condition. We prove rigorous estimates on the norm and field of values of the left- or right-preconditioned matrix that show explicitly how the absorption, the heterogeneity in the coefficients and the dependence on the degree enter the estimates. These estimates prove rigorously that, with enough absorption and for k large enough, GMRES is guaranteed to converge in a number of iterations that is independent of k,p, and the coefficients. The theoretical threshold for k to be large enough depends on p and on the local variation of coefficients in subdomains (and not globally). Extensive numerical experiments are given for both the absorptive and the propagative cases; in the latter case we investigate examples both when the coefficients are nontrapping and when they are trapping. These experiments (i) support our theory in terms of dependence on polynomial degree and the coefficients; (ii) support the sharpness of our field of values estimates in terms of the level of absorption required.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 29

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.