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Rotation-Based Multi-Particle Collision Algorithm with Hooke–Jeeves Approach Applied to the Structural Damage Identification

  • Reynier Hernández Torres
  • Haroldo Fraga de Campos VelhoEmail author
  • Leonardo Dagnino Chiwiacowsky
Chapter

Abstract

A hybrid metaheuristic combining the Multi-Particle Collision Algorithm (MPCA) with the Hooke–Jeeves (HJ) method is applied to identify structural damage. A new version of the MPCA is formulated with the rotation-based learning mechanism to the exploration search. The inverse problem of damage identification is formulated as an optimization problem assuming the displacement time history as experimental data. The objective function is the square difference between the measured displacement and the displacement calculated by the forward model. The approach was tested on a cantilevered beam structure. Time-invariant damages were assumed to generate the synthetic displacement data. Noiseless and noisy data were considered. Finite element method was used for solving the direct problem. The comparison with standard MPCA-HJ and the new version of the hybrid method are reported. The use of these hybrid algorithms allows to obtain good estimations using a full set of data, or using a reduced dataset with a low level of noise in data.

Notes

Acknowledgements

The authors acknowledge the support from the National Council for Research and Development (CNPq) under grants numbers 159547/2013-0 and 312924/2017-8.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Reynier Hernández Torres
    • 1
  • Haroldo Fraga de Campos Velho
    • 1
    Email author
  • Leonardo Dagnino Chiwiacowsky
    • 2
  1. 1.Associated Laboratory for Computing and Applied Mathematics (LAC)National Institute for Space Research (INPE)São José dos CamposBrazil
  2. 2.Graduate Program in Industrial Engineering (PPGEP)University of Caxias do Sul (UCS)Bento GonçalvesBrazil

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