Finite element model updating accounting for modeling uncertainty

Rodrigo Astroza, Andres Alessandri, Joel P. Conte

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel approach to deal with modeling uncertainty when updating mechanics-based finite element (FE) models is presented. In this method, a dual adaptive filtering approach is adopted, where the Unscented Kalman filter (UKF) is used to estimate the unknown parameters of the nonlinear FE model and a linear Kalman filter (KF) is employed to estimate the diagonal terms of the covariance matrix of the simulation error vector based on a covariance-matching technique. Numerically simulated response data of a two-dimensional three-story three-bay steel frame structure with eight unknown material model parameters subjected to seismic base excitation is employed to illustrate and validate the proposed methodology. The results of the validation studies show that the proposed approach significantly outperforms the parameter-only estimation approach widely investigated and used in the literature.

Original languageEnglish
Title of host publicationModel Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019
EditorsRobert Barthorpe
PublisherSpringer New York LLC
Pages211-221
Number of pages11
ISBN (Print)9783030120740
DOIs
StatePublished - 2020
Event37th IMAC, A Conference and Exposition on Structural Dynamics, 2019 - Orlando, United States
Duration: 28 Jan 201931 Jan 2019

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652

Conference

Conference37th IMAC, A Conference and Exposition on Structural Dynamics, 2019
Country/TerritoryUnited States
CityOrlando
Period28/01/1931/01/19

Bibliographical note

Funding Information:
R. Astroza acknowledges the financial support from the Chilean National Commission for Scientific and Technological Research (CONICYT), through FONDECYT research grant No. 11160009.

Funding Information:
Acknowledgements R. Astroza acknowledges the financial support from the Chilean National Commission for Scientific and Technological Research (CONICYT), through FONDECYT research grant No. 11160009.

Publisher Copyright:
© Society for Experimental Mechanics, Inc. 2020.

Keywords

  • Dual filtering
  • Finite element model
  • Modeling uncertainty
  • Parameter estimation

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