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The Orthonormalized Generalized Finite Element Method - OGFEM: Efficient and stable reduction of approximation errors through multiple orthonormalized enriched basis functions

机译:正交归一化的有限元方法-OGFEM:通过多个正交归一化的丰富基函数来有效且稳定地减少逼近误差

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An extension of the Generalized Finite Element Method (GFEM) is proposed with which we efficiently reduce approximation errors. The new method constructs a stiffness matrix with a conditioning that is significantly better than the Stable Generalized Finite Element Method (SGFEM) and the Finite Element Method (FEM). Accordingly, the risk of a severe loss of accuracy in the computed solution, which burdens the GFEM, is prevented. Furthermore, the computational cost of the inversion of the associated stiffness matrix is significantly reduced. The GFEM employs a set of enriched basis functions which is chosen to improve the rate at which the approximation converges to the exact solution. The stiffness matrix constructed from these basis functions is often ill-conditioned and the accuracy of the solution cannot be guaranteed. We prevent this by orthonormalizing the basis functions and refer to the method as the Orthonormalized Generalized Finite Element Method (OGFEM). Because the OGFEM has the flexibility to orthonormalize either a part or all of the basis functions, the method can be considered as a generalization of the GFEM. The method is applicable with single or multiple global and/or local enrichment functions. Problems in blending elements are avoided by a modification of the enrichment functions. The method is demonstrated for the one-dimensional modified Helmholtz and Poisson equations and compared with the FEM, GFEM and SGFEM. (C) 2014 Elsevier B.V. All rights reserved.
机译:提出了广义有限元方法(GFEM)的扩展,通过它我们可以有效地减少近似误差。新方法构造的刚度矩阵的条件明显优于稳定广义有限元方法(SGFEM)和有限元方法(FEM)。因此,避免了在计算解决方案中严重损失准确性的风险,这给GFEM带来了负担。此外,显着降低了相关联的刚度矩阵求逆的计算成本。 GFEM采用了一组丰富的基函数,可以选择这些函数来提高近似值收敛到精确解的速率。由这些基函数构造的刚度矩阵通常是病态的,无法保证求解的准确性。我们通过对基函数进行正态化来防止这种情况,并将该方法称为正交化广义有限元法(OGFEM)。因为OGFEM可以灵活地对部分或全部基本函数进行正态化,所以该方法可以视为GFEM的一般化。该方法适用于单个或多个全局和/或局部富集功能。通过修改浓缩功能避免了混合元素的问题。该方法针对一维修正的Helmholtz和Poisson方程进行了演示,并与FEM,GFEM和SGFEM进行了比较。 (C)2014 Elsevier B.V.保留所有权利。

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