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A regularized least-squares radial point collocation method (RLS-RPCM) for adaptive analysis

机译:用于自适应分析的正则化最小二乘径向点配置方法(RLS-RPCM)

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摘要

This paper presents a stabilized meshfree method formulated based on the strong formulation and local approximation using radial basis functions (RBFs). The purpose of this paper is two folds. First, a regularization procedure is developed for stabilizing the solution of the radial point collocation method (RPCM). Second, an adaptive scheme using the stabilized RPCM and residual based error indicator is established. It has been shown in this paper that the features of the meshfree strong-form method can facilitated an easier implementation of adaptive analysis. A new error indicator based on the residual is devised and used in this work. As shown in the numerical examples, the new error indicator can reflect the quality of the local approximation and the global accuracy of the solution. A number of examples have been presented to demonstrate the effectiveness of the present method for adaptive analysis.
机译:本文提出了一种稳定的无网格方法,该方法基于强公式和使用径向基函数(RBF)的局部逼近。本文的目的有两个方面。首先,开发了一种正则化程序来稳定径向点配置方法(RPCM)的求解。其次,建立使用稳定的RPCM和基于残差的误差指示符的自适应方案。本文表明,无网格强形式方法的特征可以促进自适应分析的更容易实现。在这项工作中设计并使用了一个基于残差的新错误指示器。如数值示例所示,新的误差指示器可以反映局部逼近的质量和解决方案的整体精度。已经提出了许多例子来证明本方法用于自适应分析的有效性。

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