Journal
COMPUTERS & STRUCTURES
Volume 144, Issue -, Pages 127-137Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compstruc.2014.08.002
Keywords
Load identification; Shape function method; Moving least square fitting; Ill-posed problems; Regularization method; Inverse problem
Funding
- National Science Foundation of China [11202076, 11232004]
- Key Project of Chinese National Programs for Fundamental Research and Development [2010CB832705]
- Doctoral Fund of Ministry of Education of China [20120161120003]
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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. (C) 2014 Elsevier Ltd. All rights reserved.
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