Article (Scientific journals)
A linear smoothed higher-order CS-FEM for the analysis of notched laminated composites
Wan, Detao; Hu, Dean; Natarajan, Sundararajan et al.
2017In Engineering Analysis with Boundary Elements, 85, p. 127-135
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Keywords :
Eight-node serendipity quadrilateral element; Linear smoothing technique; CS-FEM; Stress concentration; Laminated composite
Abstract :
[en] Higher-order elements with highly accurate solutions are attractive for stress analysis and stress concentration problems. However, the distorted eight-node serendipity quadrilateral element is known to yield inaccurate re- sults and sub-optimal convergence rate. In this paper, we present a higher order CS-FEM to alleviate the effect of distorted mesh and guarantee the quality of solutions by employing a linear smoothing technique over eight-node quadratic serendipity elements. The modified. strain matrix is computed by the divergence theorem between the nodal shape functions and their derivatives using Taylor’s expansion of the weak form. The proposed method eliminates the need for isoparametric mapping and numerical studies demonstrate that the proposed method is insensitive to mesh distortion. The improved accuracy and superior convergence rates are numerically demon- strated with a few benchmark problems. The analysis of the stress concentration around cutouts also proves that the present method has good performance for the laminated composites.
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
Long, Ting
External co-authors :
yes
Language :
English
Title :
A linear smoothed higher-order CS-FEM for the analysis of notched laminated composites
Publication date :
2017
Journal title :
Engineering Analysis with Boundary Elements
ISSN :
0955-7997
Publisher :
Elsevier, United Kingdom
Volume :
85
Pages :
127-135
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Funders :
National Natural Science Foundation of China ( 11672105 , 11372106 )
Natural Science Foundation of Hunan Province ( 2016JJ1009 )
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since 18 February 2018

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