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Stochastic Finite Element Model Updating by Bootstrapping

  • Vahid YaghoubiEmail author
  • Majid K. Vakilzadeh
  • Anders T. Johansson
  • Thomas Abrahamsson
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

This paper presents a new stochastic finite element model calibration framework for estimation of the uncertainty in model parameters, which combines the principles of bootstrapping with the technique of FE model calibration with damping equalization. The bootstrapping allows to quantify the uncertainty bounds on the model parameters by constructing a number of resamples, with replacement, of the experimental data and solving the FE model calibration problem on the resampled datasets. To a great extent, the success of the calibration problem depends on the starting value for the parameters. The formulation of FE model calibration with damping equalization gives a smooth metric with a large radius of convergence to the global minimum and its solution can be viewed as the initial estimate for the model parameters. In this study, practical suggestions are made to improve the performance of this algorithm in dealing with noisy measurements. The performance of the proposed stochastic calibration algorithm is illustrated using simulated data for a six degree-of-freedom mass-spring model.

Keywords

Stochastic FE model calibration Frequency response Experiment design 0.632 Bootstrap Uncertainty quantification 

Notes

Acknowledgment

The authors would like to express their gratitude to Prof. Tomas McKelvey for the discussions.

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Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  • Vahid Yaghoubi
    • 1
    Email author
  • Majid K. Vakilzadeh
    • 1
  • Anders T. Johansson
    • 1
  • Thomas Abrahamsson
    • 1
  1. 1.Department of Applied MechanicsChalmers University of TechnologyGöteborgSweden

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