An effective computational approach based on XFEM and a novel three-step detection algorithm for multiple complex flaw clusters

•An effective computational approach for detecting multiple complex flaw clusters is presented.•Forward problem is solved by XFEM to avoid re-meshing as changing the flaw geometry.•A novel three-step strategy is developed for solving inverse problem.•“Queue and Kill” method is proposed to identify a...

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Veröffentlicht in:Computers & Structures Jg. 193; S. 207 - 225
Hauptverfasser: Ma, Chunping, Yu, Tiantang, Van Lich, Le, Quoc Bui, Tinh
Format: Journal Article
Sprache:Englisch
Japanisch
Veröffentlicht: New York Elsevier Ltd 01.12.2017
Elsevier BV
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ISSN:0045-7949, 1879-2243
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Abstract •An effective computational approach for detecting multiple complex flaw clusters is presented.•Forward problem is solved by XFEM to avoid re-meshing as changing the flaw geometry.•A novel three-step strategy is developed for solving inverse problem.•“Queue and Kill” method is proposed to identify and eliminate the improper candidate.•The three-step strategy can save computational time and reduce the sensor number. This paper presents an effective computational approach comprised of forward and inverse analyses for detection of multiple complex flaw clusters in elastic solids. A three-step detection strategy is introduced for inverse analysis, whereas extended finite element method (XFEM) is adopted for forward analysis. The use of XFEM is to avoid re-meshing during the change of flaw geometries. The three-step detection strategy involves: firstly, an optimization method that couples an improved discrete artificial bee colony algorithm and hierarchical clustering analysis (IDABC-HCA) is used to capture subdomains containing flaws with limited measure points in the global domain; secondly, additional measure points are introduced locally within each captured subdomain, where the number of flaws and the rough geometry of each flaw are quickly determined with the IDABC-HCA; finally, true geometries of flaws are obtained on the basis of the rough geometries by the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. To save computational time, “Queue and Kill” method is proposed to actively identify and eliminate the improper candidate flaws and/or flaw clusters. Three numerical examples of multiple flaw detection that include simple and complex flaw geometries are analyzed. The results demonstrate that the proposed approach can effectively detect multiple complex flaw clusters without prior information of the flaw number.
AbstractList •An effective computational approach for detecting multiple complex flaw clusters is presented.•Forward problem is solved by XFEM to avoid re-meshing as changing the flaw geometry.•A novel three-step strategy is developed for solving inverse problem.•“Queue and Kill” method is proposed to identify and eliminate the improper candidate.•The three-step strategy can save computational time and reduce the sensor number. This paper presents an effective computational approach comprised of forward and inverse analyses for detection of multiple complex flaw clusters in elastic solids. A three-step detection strategy is introduced for inverse analysis, whereas extended finite element method (XFEM) is adopted for forward analysis. The use of XFEM is to avoid re-meshing during the change of flaw geometries. The three-step detection strategy involves: firstly, an optimization method that couples an improved discrete artificial bee colony algorithm and hierarchical clustering analysis (IDABC-HCA) is used to capture subdomains containing flaws with limited measure points in the global domain; secondly, additional measure points are introduced locally within each captured subdomain, where the number of flaws and the rough geometry of each flaw are quickly determined with the IDABC-HCA; finally, true geometries of flaws are obtained on the basis of the rough geometries by the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. To save computational time, “Queue and Kill” method is proposed to actively identify and eliminate the improper candidate flaws and/or flaw clusters. Three numerical examples of multiple flaw detection that include simple and complex flaw geometries are analyzed. The results demonstrate that the proposed approach can effectively detect multiple complex flaw clusters without prior information of the flaw number.
This paper presents an effective computational approach comprised of forward and inverse analyses for detection of multiple complex flaw clusters in elastic solids. A three-step detection strategy is introduced for inverse analysis, whereas extended finite element method (XFEM) is adopted for forward analysis. The use of XFEM is to avoid re-meshing during the change of flaw geometries. The three-step detection strategy involves: firstly, an optimization method that couples an improved discrete artificial bee colony algorithm and hierarchical clustering analysis (IDABC-HCA) is used to capture subdomains containing flaws with limited measure points in the global domain; secondly, additional measure points are introduced locally within each captured subdomain, where the number of flaws and the rough geometry of each flaw are quickly determined with the IDABC-HCA; finally, true geometries of flaws are obtained on the basis of the rough geometries by the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. To save computational time, "Queue and Kill" method is proposed to actively identify and eliminate the improper candidate flaws and/or flaw clusters. Three numerical examples of multiple flaw detection that include simple and complex flaw geometries are analyzed. The results demonstrate that the proposed approach can effectively detect multiple complex flaw clusters without prior information of the flaw number.
Author Quoc Bui, Tinh
Yu, Tiantang
Van Lich, Le
Ma, Chunping
Author_xml – sequence: 1
  givenname: Chunping
  surname: Ma
  fullname: Ma, Chunping
  organization: Department of Engineering Mechanics, Hohai University, Nanjing 211100, PR China
– sequence: 2
  givenname: Tiantang
  surname: Yu
  fullname: Yu, Tiantang
  email: tiantangyu@hhu.edu.cn
  organization: Department of Engineering Mechanics, Hohai University, Nanjing 211100, PR China
– sequence: 3
  givenname: Le
  surname: Van Lich
  fullname: Van Lich, Le
  organization: Department of Mechanical Engineering and Science, Kyoto University, Nishikyo-ku, Kyoto 615-8540, Japan
– sequence: 4
  givenname: Tinh
  surname: Quoc Bui
  fullname: Quoc Bui, Tinh
  email: buiquoctinh@duytan.edu.vn, bui.t.aa@m.titech.ac.jp
  organization: Institute for Research and Development, Duy Tan University, Da Nang City, Viet Nam
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Keywords Flaw clusters
Discrete artificial bee colony algorithm
Hierarchical clustering analysis
Inverse problem
XFEM
BFGS
Language English
Japanese
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Snippet •An effective computational approach for detecting multiple complex flaw clusters is presented.•Forward problem is solved by XFEM to avoid re-meshing as...
This paper presents an effective computational approach comprised of forward and inverse analyses for detection of multiple complex flaw clusters in elastic...
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SubjectTerms BFGS
Cluster analysis
Clustering
Computation
Discrete artificial bee colony algorithm
Finite element analysis
Finite element method
Flaw clusters
Geometry
Hierarchical clustering analysis
Inverse problem
Meshing
Nondestructive testing
Optimization
Queues
Search algorithms
Solids
Swarm intelligence
XFEM
Title An effective computational approach based on XFEM and a novel three-step detection algorithm for multiple complex flaw clusters
URI https://dx.doi.org/10.1016/j.compstruc.2017.08.009
https://cir.nii.ac.jp/crid/1871146592665898496
https://www.proquest.com/docview/1966075583
Volume 193
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