Radial Basis Function ENO and WENO Finite Difference Methods Based on the Optimization of Shape Parameters

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• 作者：Jingyang Guo ; Jae-Hun Jung
• 关键词：Essentially non ; oscillatory method ; Weighted essentially non ; oscillatory method ; Radial basis function interpolation ; Finite difference method
• 刊名：Journal of Scientific Computing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：70
• 期：2
• 页码：551-575
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Algorithms; Computational Mathematics and Numerical Analysis; Appl.Mathematics/Computational Methods of Engineering; Theoretical, Mathematical and Computational Physics;
• 出版者：Springer US
• ISSN：1573-7691
• 卷排序：70

文摘

We present adaptive finite difference ENO/WENO methods with infinitely smooth radial basis functions (RBFs). These methods slightly perturb the polynomial reconstruction coefficients with RBFs as the reconstruction basis and enhance accuracy in the smooth region by locally optimizing the shape parameters. Compared to the classical ENO/WENO methods, the RBF-ENO/WENO methods provide more accurate reconstructions and sharper solution profiles near the jump discontinuity. Furthermore the RBF-ENO/WENO methods are easy to implement in the existing classical ENO/WENO code. The numerical results in 1D and 2D presented in this paper show that the proposed finite difference RBF-ENO/WENO methods perform better than the classical ENO/WENO methods.