基于最小二乘切换的非结构化网格梯度估计方法

IF 0.3 Q4 MATHEMATICS, APPLIED
Seungpyo Seo, Changsoo Lee, Eunsa Kim, Kyeol Yune, Chongam Kim
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引用次数: 1

摘要

通过在两种最小二乘法之间进行切换,提出了一种准确、高效的非结构化网格梯度估计方法。不同的测试用例表明,与格林-高斯方法相比,最小二乘方法的梯度估计具有更好的特性。在此基础上,研究了两种优点互补的最小二乘法的转换问题。选择最小二乘矩阵的条件数作为切换判据,因为它与梯度误差有明显的相关性,并且可以方便地从网格的几何信息中计算。为了说明一般网格上的切换过程,利用模板向量和三角关系对条件数进行了分析。然后,建立了切换准则的阈值。最后,通过各种二维和三维应用验证了切换加权最小二乘法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LEAST-SQUARE SWITCHING PROCESS FOR ACCURATE AND EFFICIENT GRADIENT ESTIMATION ON UNSTRUCTURED GRID
An accurate and efficient gradient estimation method on unstructured grid is presented by proposing a switching process between two Least-Square methods. Diverse test cases show that the gradient estimation by Least-Square methods exhibit better characteristics compared to Green-Gauss approach. Based on the investigation, switching between the two LeastSquare methods, whose merit complements each other, is pursued. The condition number of the Least-Square matrix is adopted as the switching criterion, because it shows clear correlation with the gradient error, and it can be easily calculated from the geometric information of the grid. To illustrate switching process on general grid, condition number is analyzed using stencil vectors and trigonometric relations. Then, the threshold of switching criterion is established. Finally, the capability of Switching Weighted Least-Square method is demonstrated through various twoand three-dimensional applications.
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