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A Residual Based Error Estimator Using Radial Basis Functions

机译:基于径向基函数的基于残差的误差估计器

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摘要

In this paper, a novel residual based error estimator using radial basis functions (RBFs) is proposed. The error estimator evaluates the residual in the strong-form governing equation in the local domain through direct integration. Due to the higher order continuous feature of the RBFs, the higher derivatives of the field function in the strong-form governing equation can be obtained using RBFs. The numerical examples show that the new residual based error estimator is simple, versatile robust and yet effective in the adaptive analyses. It is not only suitable for adaptive analysis that uses numerical method formulated based on mesh, e.g. finite element method, but also meshfree methods where the conventional residual based and recovery based error estimator cannot be used. Furthermore the present error estimator is also feasible for numerical method that is formulated based on both strong and weak formulation in the adaptive analyses.
机译:本文提出了一种新的基于径向基函数(RBF)的基于残差的误差估计器。误差估计器通过直接积分评估局部域中强形式控制方程中的残差。由于RBF的高阶连续特征,可以使用RBF来获得强形式控制方程中场函数的高阶导数。数值算例表明,新的基于残差的误差估计器简单,通用性强并且在自适应分析中仍然有效。它不仅适用于使用基于网格的数值方法制定的自适应分析,例如有限元法,但也不能采用无网格法,其中不能使用常规的基于残差和基于恢复的误差估计器。此外,本发明的误差估计器对于在自适应分析中基于强和弱公式两者而公式化的数值方法也是可行的。

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