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A computational approach for crack identification in plate structures using XFEM, XIGA, PSO and Jaya algorithm.

Authors :
Khatir, Samir
Abdel Wahab, Magd
Source :
Theoretical & Applied Fracture Mechanics. Oct2019, Vol. 103, pN.PAG-N.PAG. 1p.
Publication Year :
2019

Abstract

• CPU Time for XIGA and XFEM based on inverse problem. • Jaya and PSO for crack idetification. • XIGA is much better than XFEM. • The objective of NURBS order for best convergence and fast simulation is provided. In this paper, a creative and intelligent approach based on an inverse problem that accurately predicts crack location in plate structures is presented. The eXtended Finite Element (XFEM) and the eXtended IsoGeometric Analysis (XIGA) are combined with two optimization techniques, namely Particle Swarm Optimization (PSO) and Jaya algorithm to predict the crack location. The superiority of XIGA is demonstrated by using various NURBS orders to reduce the number of elements, provide fast simulation and achieve best convergence compared with XFEM. Four numerical-optimization techniques are considered in this paper, namely XFEM-Jaya, XIGA-Jaya, XFEM-PSO and XIGA-PSO. In the optimization techniques, the objective function minimizes the difference between the calculated and measured displacements and strains. Convergence studies for various positions of a crack and a hole in plates are performed and the results show that Jaya algorithm significantly performs more accurate and faster than PSO. In addition, the proposed techniques are validated using experimental data and another numerical-optimization technique, i.e. XFEM coupled with Genetic Algorithm (GA), presented in literature. The comparisons show that XIGA-Jaya performs the best of all considered techniques. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01678442
Volume :
103
Database :
Academic Search Index
Journal :
Theoretical & Applied Fracture Mechanics
Publication Type :
Academic Journal
Accession number :
138726321
Full Text :
https://doi.org/10.1016/j.tafmec.2019.102240