A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters

Antonios Kamariotis; Luca Sardi; Iason Papaioannou; Eleni N. Chatzi; Daniel Straub

doi:10.1007/978-3-031-04090-0_2

A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters

Antonios Kamariotis, Luca Sardi, Iason Papaioannou, Eleni N. Chatzi, Daniel Straub

Associate Professorship of Engineering Risk Analysis

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

Abstract

Many preventive maintenance schemes for managing structural deterioration rely on stochastic deterioration models. In this context, continuous structural health information can be employed within a Bayesian framework to update the distributions of the time-invariant deterioration model parameters. Bayesian parameter estimation can be performed either in an online or an offline fashion. In this contribution, we investigate different online and offline algorithms implemented for learning the model parameters, and their uncertainty, considering a probabilistic model of fatigue crack growth that is updated with continuous crack monitoring measurements. The numerical investigations provide insights on the performance of the different algorithms in terms of accuracy of the posterior estimates and computational cost.

Original language	English
Title of host publication	Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022
Editors	Zhu Mao
Publisher	Springer
Pages	17-20
Number of pages	4
ISBN (Print)	9783031040894
DOIs	https://doi.org/10.1007/978-3-031-04090-0_2
State	Published - 2023
Event	40th IMAC, A Conference and Exposition on Structural Dynamics, 2022 - Orlando, United States Duration: 7 Feb 2022 → 10 Feb 2022

Publication series

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

Conference

Conference	40th IMAC, A Conference and Exposition on Structural Dynamics, 2022
Country/Territory	United States
City	Orlando
Period	7/02/22 → 10/02/22

Keywords

Bayesian inference
Markov chain Monte Carlo
Particle filter
Structural deterioration
Uncertainty quantification

Access to Document

10.1007/978-3-031-04090-0_2

Cite this

Kamariotis, A., Sardi, L., Papaioannou, I., Chatzi, E. N., & Straub, D. (2023). A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters. In Z. Mao (Ed.), Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022 (pp. 17-20). (Conference Proceedings of the Society for Experimental Mechanics Series). Springer. https://doi.org/10.1007/978-3-031-04090-0_2

Kamariotis, Antonios ; Sardi, Luca ; Papaioannou, Iason et al. / A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters. Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022. editor / Zhu Mao. Springer, 2023. pp. 17-20 (Conference Proceedings of the Society for Experimental Mechanics Series).

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title = "A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters",

abstract = "Many preventive maintenance schemes for managing structural deterioration rely on stochastic deterioration models. In this context, continuous structural health information can be employed within a Bayesian framework to update the distributions of the time-invariant deterioration model parameters. Bayesian parameter estimation can be performed either in an online or an offline fashion. In this contribution, we investigate different online and offline algorithms implemented for learning the model parameters, and their uncertainty, considering a probabilistic model of fatigue crack growth that is updated with continuous crack monitoring measurements. The numerical investigations provide insights on the performance of the different algorithms in terms of accuracy of the posterior estimates and computational cost.",

keywords = "Bayesian inference, Markov chain Monte Carlo, Particle filter, Structural deterioration, Uncertainty quantification",

author = "Antonios Kamariotis and Luca Sardi and Iason Papaioannou and Chatzi, {Eleni N.} and Daniel Straub",

note = "Publisher Copyright: {\textcopyright} 2023, The Society for Experimental Mechanics, Inc.; 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022 ; Conference date: 07-02-2022 Through 10-02-2022",

year = "2023",

doi = "10.1007/978-3-031-04090-0_2",

language = "English",

isbn = "9783031040894",

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

publisher = "Springer",

pages = "17--20",

editor = "Zhu Mao",

booktitle = "Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022",

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Kamariotis, A, Sardi, L, Papaioannou, I, Chatzi, EN & Straub, D 2023, A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters. in Z Mao (ed.), Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022. Conference Proceedings of the Society for Experimental Mechanics Series, Springer, pp. 17-20, 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, Orlando, United States, 7/02/22. https://doi.org/10.1007/978-3-031-04090-0_2

A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters. / Kamariotis, Antonios; Sardi, Luca; Papaioannou, Iason et al.
Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022. ed. / Zhu Mao. Springer, 2023. p. 17-20 (Conference Proceedings of the Society for Experimental Mechanics Series).

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

TY - GEN

T1 - A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters

AU - Kamariotis, Antonios

AU - Sardi, Luca

AU - Papaioannou, Iason

AU - Chatzi, Eleni N.

AU - Straub, Daniel

PY - 2023

Y1 - 2023

N2 - Many preventive maintenance schemes for managing structural deterioration rely on stochastic deterioration models. In this context, continuous structural health information can be employed within a Bayesian framework to update the distributions of the time-invariant deterioration model parameters. Bayesian parameter estimation can be performed either in an online or an offline fashion. In this contribution, we investigate different online and offline algorithms implemented for learning the model parameters, and their uncertainty, considering a probabilistic model of fatigue crack growth that is updated with continuous crack monitoring measurements. The numerical investigations provide insights on the performance of the different algorithms in terms of accuracy of the posterior estimates and computational cost.

AB - Many preventive maintenance schemes for managing structural deterioration rely on stochastic deterioration models. In this context, continuous structural health information can be employed within a Bayesian framework to update the distributions of the time-invariant deterioration model parameters. Bayesian parameter estimation can be performed either in an online or an offline fashion. In this contribution, we investigate different online and offline algorithms implemented for learning the model parameters, and their uncertainty, considering a probabilistic model of fatigue crack growth that is updated with continuous crack monitoring measurements. The numerical investigations provide insights on the performance of the different algorithms in terms of accuracy of the posterior estimates and computational cost.

KW - Bayesian inference

KW - Markov chain Monte Carlo

KW - Particle filter

KW - Structural deterioration

KW - Uncertainty quantification

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BT - Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022

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Kamariotis A, Sardi L, Papaioannou I, Chatzi EN, Straub D. A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters. In Mao Z, editor, Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022. Springer. 2023. p. 17-20. (Conference Proceedings of the Society for Experimental Mechanics Series). doi: 10.1007/978-3-031-04090-0_2

A Comparative Assessment of Online and Offline Bayesian Estimation of Deterioration Model Parameters

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