Article (Scientific journals)
A fully smoothed XFEM for analysis of axisymmetric problems with weak discontinuities
Wan, Detao; Hu, Dean; Natarajan, Sundararajan et al.
2017In International Journal for Numerical Methods in Engineering, 110 (3), p. 203-226
Peer reviewed
 

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Keywords :
SmXFEM; indefinite integral; Green’s divergence theorem; mass matrix; weak discontinuity; axisymmetric problem
Abstract :
[en] In this paper, we propose a fully smoothed extended finite element method (SmXFEM) for axisymmetric problems with weak discontinuities. The salient feature of the proposed approach is that all the terms in the stiffness and mass matrixes can be computed by smoothing technique. This is accomplished by combining the Green’s divergence theorem with the evaluation of indefinite integral based on smoothing technique, which is used to transform the domain integral into boundary integral. The proposed technique completely eliminates the need for isoparametric mapping and the computing of Jacobian matrix even for the mass matrix. When employed over the enriched elements, the proposed technique does not require sub-triangulation for the purpose of numerical integration. The accuracy and convergence properties of the proposed technique are demonstrated with a few problems in elastostatics and elastodynamics with weak discontinuities. It can be seen that the proposed technique yields stable and accurate solutions and is less sensitive to mesh distortion.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Wan, Detao
Hu, Dean
Natarajan, Sundararajan
Bordas, Stéphane ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Yang, Gang
External co-authors :
yes
Language :
English
Title :
A fully smoothed XFEM for analysis of axisymmetric problems with weak discontinuities
Publication date :
2017
Journal title :
International Journal for Numerical Methods in Engineering
Volume :
110
Issue :
3
Pages :
203-226
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Funders :
National Natural Science Foundation of China (11272118, 11372106)
Natural Science Foundation of Hunan Province (2016JJ1009)
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since 19 February 2018

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