Abstract
The main purpose of the study is to develop a fast singular boundary method for solving the three-dimensional (3D) potential problems. It is a difficult issue to simulate the large-scale problems by the traditional SBM, because of the fully populated coefficient matrix. A fast direct algorithm based on recursive skeletonization factorization (RSF) is combined in the SBM to reduce the CPU time and memory requirements in this study. For the dense coefficient matrix in the SBM, a hierarchically generalized LU decomposition is constructed to invert it fast and accurately. The numerical results demonstrate the great performance of the RSF-SBM for solving large-scale 3D potential problems.
Published Version
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