Comparison of state of the art sampling-based Bayesian Updating techniques

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • M. B. Dodt
  • M. Kitahara
  • M. Broggi
  • M. Beer

Externe Organisationen

  • KU Leuven
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksProceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022
Herausgeber/-innenMichael Beer, Enrico Zio, Kok-Kwang Phoon, Bilal M. Ayyub
Seiten59-66
Seitenumfang8
PublikationsstatusVeröffentlicht - 2024
Veranstaltung8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 - Hannover, Deutschland
Dauer: 4 Sept. 20227 Sept. 2022

Abstract

Nowadays, model updating has an increasing importance in many areas of interest for engineering applications such as structural health monitoring or risk and reliability assessment. As a matter of fact, it allows for solving a plethora of inverse problems with high computationally efficiency, allowing for example to monitor structural parameter, to detect damage quickly and to timely intervene with mitigating actions. Among the algorithms available to solve Bayesian updating, methods based on sampling present a flexibility that allows solving the problem numerically, either based on Markov Chain Monte Carlo (MCMC) method or based on the usage of Bayesian updating with structural reliability (BUS) methods. Additionally, BUS can be coupled with additional methods such as surrogate modelling and efficient simulation methods to further improve its numerical efficiency. Thus, engineering practitioners need to understand which possible combination of the available algorithms should be used to solve their needs. In this paper, we provide an overview of different MCMC and BUS methods, directly calling the model and also employing the Kriging meta-model, covering in detail the advantages and disadvantages of each method as well as their applicability. The investigated methods are applied to solve model updating and model class selection. Two numerical examples are used to verify and test the analysed methods, drawing conclusion on their accuracy, performance, robustness, numerical efficiency and ability to perform model class selection.

ASJC Scopus Sachgebiete

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Comparison of state of the art sampling-based Bayesian Updating techniques. / Dodt, M. B.; Kitahara, M.; Broggi, M. et al.
Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. Hrsg. / Michael Beer; Enrico Zio; Kok-Kwang Phoon; Bilal M. Ayyub. 2024. S. 59-66.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Dodt, MB, Kitahara, M, Broggi, M & Beer, M 2024, Comparison of state of the art sampling-based Bayesian Updating techniques. in M Beer, E Zio, K-K Phoon & BM Ayyub (Hrsg.), Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. S. 59-66, 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022, Hannover, Deutschland, 4 Sept. 2022. https://doi.org/10.3850/978-981-18-5184-1_MS-02-146-cd
Dodt, M. B., Kitahara, M., Broggi, M., & Beer, M. (2024). Comparison of state of the art sampling-based Bayesian Updating techniques. In M. Beer, E. Zio, K.-K. Phoon, & B. M. Ayyub (Hrsg.), Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 (S. 59-66) https://doi.org/10.3850/978-981-18-5184-1_MS-02-146-cd
Dodt MB, Kitahara M, Broggi M, Beer M. Comparison of state of the art sampling-based Bayesian Updating techniques. in Beer M, Zio E, Phoon KK, Ayyub BM, Hrsg., Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. 2024. S. 59-66 doi: 10.3850/978-981-18-5184-1_MS-02-146-cd
Dodt, M. B. ; Kitahara, M. ; Broggi, M. et al. / Comparison of state of the art sampling-based Bayesian Updating techniques. Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. Hrsg. / Michael Beer ; Enrico Zio ; Kok-Kwang Phoon ; Bilal M. Ayyub. 2024. S. 59-66
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