A novel computational inverse technique for load identification using the shape function method of moving least square fitting

Jie Liu, Xingsheng Sun, Xu Han, Chao Jiang, Dejie Yu

Research output: Contribution to journalArticlepeer-review

85 Scopus citations

Abstract

Based on shape function method of moving least square fitting (SFM-MLSF), dynamic load is identified. The time domain of load is discretized and the local load is approximated by SFM under LSF. With this local domain moving, whole load is described. The response matrix is formed through assembling the responses of shape function loads in all local domains and the forward model is established. The regularization is adopted to overcome the ill-posedness of load reconstruction. Compared with Green's kernel function method (GKFM), SFM-MLSF approximates load more smoothly, so the ill-posedness is improved. Numerical simulations demonstrate the efficiency of SFM-MLSF.

Original languageEnglish
Pages (from-to)127-137
Number of pages11
JournalComputers and Structures
Volume144
DOIs
StatePublished - Nov 2014

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Ltd. All rights reserved.

Keywords

  • Ill-posed problems
  • Inverse problem
  • Load identification
  • Moving least square fitting
  • Regularization method
  • Shape function method

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Modeling and Simulation
  • General Materials Science
  • Mechanical Engineering
  • Computer Science Applications

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