Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00466-006-0145-7
Title: A regularized least-squares radial point collocation method (RLS-RPCM) for adaptive analysis
Authors: Kee, B.B.T.
Liu, G.R. 
Lu, C.
Keywords: Adaptive analysis
Delaunay diagram
Error indicator
Meshfree method
Radial basis function
Regularization technique
Strong-form formulation
Issue Date: Oct-2007
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
URI: http://scholarbank.nus.edu.sg/handle/10635/54774
ISSN: 01787675
DOI: 10.1007/s00466-006-0145-7
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