A nodal integration scheme for meshfree Galerkin methods using the virtual element decomposition
Author
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Silva Valenzuela, R.
Author
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Ortiz Bernardin, Alejandro
Author
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Sukumar, N.
Author
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Artioli, E.
Author
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Hitschfeld Kahler, Nancy
Admission date
dc.date.accessioned
2020-06-02T19:41:16Z
Available date
dc.date.available
2020-06-02T19:41:16Z
Publication date
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2020
Cita de ítem
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Int J Numer Methods Eng. 2020; 121: 2174–2205
es_ES
Identifier
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10.1002/nme.6304
Identifier
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https://repositorio.uchile.cl/handle/2250/175150
Abstract
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In this article, we present a novel nodal integration scheme for meshfree Galerkin methods, which draws on the mathematical framework of the virtual element method. We adopt linear maximum-entropy basis functions for the discretization of field variables, although the proposed scheme is applicable to any linear meshfree approximant. In our approach, the weak form integrals are nodally integrated using nodal representative cells that carry the nodal displacements and state variables such as strains and stresses. The nodal integration is performed using the virtual element decomposition, wherein the bilinear form is decomposed into a consistency part and a stability part that ensure consistency and stability of the method. The performance of the proposed nodal integration scheme is assessed through benchmark problems in linear and nonlinear analyses of solids for small displacements and small-strain kinematics. Numerical results are presented for linear elastostatics and linear elastodynamics and viscoelasticity. We demonstrate that the proposed nodally integrated meshfree method is accurate, converges optimally, and is more reliable and robust than a standard cell-based Gauss integrated meshfree method.
es_ES
Patrocinador
dc.description.sponsorship
University of Rome Tor Vergata Mission Sustainability Programme: SPY-E81I18000540005.
Comisión Nacional de Investigación Científica y Tecnológica (CONICYT), CONICYT FONDECYT: 1181192, 1181506.
Ministry of Education, Universities and Research (MIUR), Research Projects of National Relevance (PRIN): 2017L7X3CS 004.