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|Title:||A regularized least-squares radial point collocation method (RLS-RPCM) for adaptive analysis|
Radial basis function
|Source:||Kee, B.B.T., Liu, G.R., Lu, C. (2007-10). A regularized least-squares radial point collocation method (RLS-RPCM) for adaptive analysis. Computational Mechanics 40 (5) : 837-853. ScholarBank@NUS Repository. https://doi.org/10.1007/s00466-006-0145-7|
|Abstract:||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. © 2006 Springer Verlag.|
|Source Title:||Computational Mechanics|
|Appears in Collections:||Staff Publications|
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