Structural Engineering and Mechanics

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Feasibility study of improved particle swarm optimization in kriging metamodel based structural model updating

  • Qin, Shiqiang (School of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Hu, Jia (School of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Zhou, Yun-Lai (Department of Civil and Environmental Engineering, National University of Singapore) ;
  • Zhang, Yazhou (School of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Kang, Juntao (School of Civil Engineering and Architecture, Wuhan University of Technology)
  • Received : 2018.10.04
  • Accepted : 2019.03.05
  • Published : 2019.06.10
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Abstract

This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

Keywords

Acknowledgement

Supported by : Natural Science Foundation of China, Central Universities

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