Abstract
Augmented immersed interface methods have been developed recently for interface problems and problems on irregular domains including CFD applications with free boundaries and moving interfaces. In an augmented method, one or several augmented variables are introduced along the interface or boundary so that one can get efficient discretizations. The augmented variables should be chosen such that the interface or boundary conditions are satisfied. The key to the success of the augmented methods often relies on the interpolation scheme to couple the augmented variables with the governing differential equations through the interface or boundary conditions. This has been done using a least squares interpolation (under-determined) for which the singular value decomposition (SVD) is used to solve for the interpolation coefficients. In this paper, based on properties of the finite element method, a new augmented immersed finite element method (IFEM) that does not need the interpolations is proposed for elliptic interface problems that have a piecewise constant coefficient. Thus the new augmented method is more efficient and simple than the old one that uses interpolations. The method then is extended to Poisson equations on irregular domains with a Dirichlet boundary condition. Numerical experiments with arbitrary interfaces/irregular domains and large jump ratios are provided to demonstrate the accuracy and the efficiency of the new augmented methods. Numerical results also show that the number of GMRES iterations is independent of the mesh size and nearly independent of the jump in the coefficient.
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Ji, H., Chen, J. & Li, Z. A new augmented immersed finite element method without using SVD interpolations. Numer Algor 71, 395–416 (2016). https://doi.org/10.1007/s11075-015-9999-0
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DOI: https://doi.org/10.1007/s11075-015-9999-0
Keywords
- Interface problem
- Piecewise constant coefficient
- Immersed finite element
- Augmented immersed finite element method
- Poisson equation on irregular domain
- Fast poisson solver
- Least squares interpolation using SVD