Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process

Juan Castiglione; Rodrigo Astroza; Saeed Eftekhar Azam; Daniel Linzell

doi:10.1007/978-3-030-47638-0_9

Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process

Juan Castiglione, Rodrigo Astroza^*, Saeed Eftekhar Azam, Daniel Linzell

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.

Original language	English
Title of host publication	Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020
Editors	Zhu Mao
Publisher	Springer
Pages	83-86
Number of pages	4
ISBN (Print)	9783030487782
DOIs	https://doi.org/10.1007/978-3-030-47638-0_9
State	Published - 2020
Event	38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 - Houston, United States Duration: 10 Feb 2020 → 13 Feb 2020

Publication series

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

Conference

Conference	38th IMAC, A Conference and Exposition on Structural Dynamics, 2020
Country/Territory	United States
City	Houston
Period	10/02/20 → 13/02/20

Bibliographical note

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

Keywords

Auto-regressive model
Finite element model
Input estimation
Kalman filter
Model updating

Access to Document

10.1007/978-3-030-47638-0_9

Cite this

Castiglione, J., Astroza, R., Azam, S. E., & Linzell, D. (2020). Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process. In Z. Mao (Ed.), Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 (pp. 83-86). (Conference Proceedings of the Society for Experimental Mechanics Series). Springer. https://doi.org/10.1007/978-3-030-47638-0_9

Castiglione, Juan ; Astroza, Rodrigo ; Azam, Saeed Eftekhar et al. / Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process. Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020. editor / Zhu Mao. Springer, 2020. pp. 83-86 (Conference Proceedings of the Society for Experimental Mechanics Series).

@inproceedings{25033cdb512f46b3865b81e3f5f8612f,

title = "Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process",

abstract = "A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.",

keywords = "Auto-regressive model, Finite element model, Input estimation, Kalman filter, Model updating",

author = "Juan Castiglione and Rodrigo Astroza and Azam, {Saeed Eftekhar} and Daniel Linzell",

note = "Publisher Copyright: {\textcopyright} 2020, The Society for Experimental Mechanics, Inc.; 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 ; Conference date: 10-02-2020 Through 13-02-2020",

year = "2020",

doi = "10.1007/978-3-030-47638-0_9",

language = "English",

isbn = "9783030487782",

series = "Conference Proceedings of the Society for Experimental Mechanics Series",

publisher = "Springer",

pages = "83--86",

editor = "Zhu Mao",

booktitle = "Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020",

}

Castiglione, J, Astroza, R, Azam, SE & Linzell, D 2020, Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process. in Z Mao (ed.), Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020. Conference Proceedings of the Society for Experimental Mechanics Series, Springer, pp. 83-86, 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020, Houston, United States, 10/02/20. https://doi.org/10.1007/978-3-030-47638-0_9

Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process. / Castiglione, Juan; Astroza, Rodrigo; Azam, Saeed Eftekhar et al.
Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020. ed. / Zhu Mao. Springer, 2020. p. 83-86 (Conference Proceedings of the Society for Experimental Mechanics Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process

AU - Castiglione, Juan

AU - Astroza, Rodrigo

AU - Azam, Saeed Eftekhar

AU - Linzell, Daniel

PY - 2020

Y1 - 2020

N2 - A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.

AB - A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.

KW - Auto-regressive model

KW - Finite element model

KW - Input estimation

KW - Kalman filter

KW - Model updating

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DO - 10.1007/978-3-030-47638-0_9

M3 - Conference contribution

AN - SCOPUS:85120432664

SN - 9783030487782

T3 - Conference Proceedings of the Society for Experimental Mechanics Series

SP - 83

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BT - Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020

A2 - Mao, Zhu

PB - Springer

T2 - 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020

Y2 - 10 February 2020 through 13 February 2020

ER -

Castiglione J, Astroza R, Azam SE, Linzell D. Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process. In Mao Z, editor, Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020. Springer. 2020. p. 83-86. (Conference Proceedings of the Society for Experimental Mechanics Series). doi: 10.1007/978-3-030-47638-0_9

Output-Only Nonlinear Finite Element Model Updating Using Autoregressive Process

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Keywords

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