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Kernel-Based Meshless Collocation Methods for Solving Coupled Bulk-Surface Partial Differential Equations

机译:基于内核的耦合堆积表面偏微分方程的内核啮合方法

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摘要

A meshless kernel-based method is developed to solve coupled second-order elliptic PDEs in bulk domains and surfaces, subject to Robin boundary conditions. It combines a least-squares kernel collocation method with a surface-type intrinsic approach. Therefore, we can use each pair for discrete point sets, RBF kernels (globally and restrictedly), trial spaces, and some essential assumptions, for the search of least-squares solutions in bulks and on surfaces respectively. We first give error estimates for domain-type Robin-boundary problems. Based on this and existing results for surface PDEs, we discuss the theoretical requirements for the employed Sobolev kernels. Then, we select the orders of smoothness for the kernels in bulks and on surfaces. Lastly, several numerical experiments are demonstrated to test the robustness of the coupled method for accuracy and convergence rates under different settings.
机译:基于网眼核的基于内核的方法是开发的,以解决批量域和表面的耦合二阶椭圆PDE,受到罗宾边界条件的影响。它结合了一种具有表面类型的内在方法的最小二乘核搭配方法。因此,我们可以为离散点集,RBF内核(全球和限制),试验空间和一些基本假设一起使用各对,用于分别搜索块和表面上的最小二乘解。我们首先给出域型Robin边界问题的错误估计。基于表面PDE的此类和现有结果,我们讨论了所采用的SoboLev内核的理论要求。然后,我们选择块状和曲面上内核的平滑度顺序。最后,证明了几个数值实验以测试耦合方法的稳健性,以便在不同的设置下的准确性和收敛速率。

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