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Accelerating the Convergence of Algebraic Multigrid for Quadratic Finite Element Method by Using Grid Information and p-Multigrid

机译:利用网格信息和p-Multigrid加速二次有限元方法的代数多重网格的收敛

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This paper proposes a new multigrid method to efficiently solve the finite element approximation of static or quasi-static electromagnetic problems with quadratic nodal finite elements on unstructured grids in 2D and 3D by using grid information and p-multigrid. Unlike the traditional algebraic multigrid (AMG), the new method constructs the first level coarse grid from the grid information of the finest grid directly, by using the natural geometrical coarsening relationship between the P2 and P1 elements. Then, the algebraic equations of the first level coarse grid are constructed based on the special relationship between the basis functions of quadratic finite element and its linear counterpart. At last, the traditional AMG is applied to solve the algebraic equations of the first coarse level rather than that of the finest grid. Several techniques of convenient and economic implementation are discussed. For the problems tested, the proposed method is much more efficient than the conjugate gradient method with incomplete Cholesky preconditioning; in addition, compared with traditional Krylov subspace accelerated AMG, the new method may save about 30% to 40% CPU time while achieving the same accuracy in practical computations.
机译:本文提出了一种新的多重网格方法,该方法可以利用网格信息和p-multigrid有效地解决二维和3D非结构化网格上具有二次节点有限元的静态或准静态电磁问题的有限元逼近。与传统的代数多重网格(AMG)不同,该新方法通过使用P2和P1元素之间的自然几何粗化关系,直接根据最佳网格的网格信息构造第一级粗网格。然后,基于二次有限元的基函数与其线性对应项之间的特殊关系,构造了第一级粗网格的代数方程。最后,将传统的AMG应用于求解第一个粗级而不是最细网格的代数方程。讨论了一些方便,经济的实现技术。对于所测试的问题,该方法比具有不完整Cholesky预处理的共轭梯度方法要有效得多。此外,与传统的Krylov子空间加速AMG相比,新方法可以节省大约30%到40%的CPU时间,同时在实际计算中达到相同的精度。

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