Preconditioned Discontinuous Galerkin Method for Elliptic Interface Problem on Unfitted Mesh with Reconstructed Discontinuous Approximation
This work provides a robust and efficient preconditioning technique for high-order unfitted finite element methods, addressing a key computational bottleneck in interface problems.
The paper develops an optimal preconditioner for the elliptic interface problem on unfitted meshes using a reconstructed discontinuous Galerkin method, achieving condition number independent of mesh size, coefficient, and interface location. Numerical experiments in 2D and 3D confirm optimal convergence and robustness.
In this paper, we develop an efficient preconditioned unfitted finite element method for the elliptic interface problem, based on the reconstructed discontinuous approximation. The approximation method for interface problems is originally proposed in [Li et al. SIAM J. Sci. Comput. 42(2), 2020], in which an arbitrarily high-order approximation space with one degree of freedom per element is constructed by solving local least squares fitting problems. The space can be applied within the cut discontinuous Galerkin framework, where the jump conditions across the interface are weakly enforced by the Nitsche's penalty method. In this work, the local least squares problem is modified by introducing appropriate constraints, which allows us to naturally ensure the stability near the interface by the reconstructed space, and further enables us to establish a norm equivalence between the high-order space and the lowest-order space. This equivalence property motivates us to construct a preconditioner from the piecewise constant space, and this preconditioning method is shown to be optimal in the sense that the upper bound of the condition number of the preconditioned system is independent of the mesh size, the coefficient and the interface location relative to the unfitted mesh. We also present the multigrid algorithms that serve as the inverse of the lowest-order system matrix. Numerical experiments in both two and three dimensions confirm the optimal convergence rates under error measurements and illustrate the efficiency and the robustness of the preconditioning method.