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Bayesian model updating in time domain with metamodel-based reliability method

Bayesian model updating in time domain with metamodel-based reliability method
Bayesian model updating in time domain with metamodel-based reliability method

In this study, a two-step approximate Bayesian computation (ABC) updating framework using dynamic response data is developed. In this framework, the Euclidian and Bhattacharyya distances are utilized as uncertainty quantification (UQ) metrics to define approximate likelihood functions in the first and second steps, respectively. A new Bayesian inference algorithm combining Bayesian updating with structural reliability methods (BUS) with the adaptive Kriging model is then proposed to effectively execute the ABC updating framework. The performance of the proposed procedure is demonstrated with a seismic-isolated bridge model updating application using simulated seismic response data. This application denotes that the Bhattacharyya distance is a powerful UQ metric with the capability to recreate wholly the distribution of target observations, and the proposed procedure can provide satisfactory results with much reduced computational demand compared with other well-known methods, such as transitional Markov chain Monte Carlo (TMCMC).

Adaptive Kriging, Bayesian model updating, Bayesian updating with structural reliability method, Bhattacharyya distance, Metamodeling, Stochastic model updating
2376-7642
Kitahara, Masaru
6b8dae61-067b-41ca-a7ef-913ca2a42b6e
Bi, Sifeng
93deb24b-fda1-4b18-927b-6225976d8d3f
Broggi, Matteo
104881e3-cd8d-4909-9049-a914be5ee548
Beer, Michael
e44760ce-70c0-44f2-bb18-7197ba142788
Kitahara, Masaru
6b8dae61-067b-41ca-a7ef-913ca2a42b6e
Bi, Sifeng
93deb24b-fda1-4b18-927b-6225976d8d3f
Broggi, Matteo
104881e3-cd8d-4909-9049-a914be5ee548
Beer, Michael
e44760ce-70c0-44f2-bb18-7197ba142788

Kitahara, Masaru, Bi, Sifeng, Broggi, Matteo and Beer, Michael (2021) Bayesian model updating in time domain with metamodel-based reliability method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7 (3), [0001149]. (doi:10.1061/AJRUA6.0001149).

Record type: Article

Abstract

In this study, a two-step approximate Bayesian computation (ABC) updating framework using dynamic response data is developed. In this framework, the Euclidian and Bhattacharyya distances are utilized as uncertainty quantification (UQ) metrics to define approximate likelihood functions in the first and second steps, respectively. A new Bayesian inference algorithm combining Bayesian updating with structural reliability methods (BUS) with the adaptive Kriging model is then proposed to effectively execute the ABC updating framework. The performance of the proposed procedure is demonstrated with a seismic-isolated bridge model updating application using simulated seismic response data. This application denotes that the Bhattacharyya distance is a powerful UQ metric with the capability to recreate wholly the distribution of target observations, and the proposed procedure can provide satisfactory results with much reduced computational demand compared with other well-known methods, such as transitional Markov chain Monte Carlo (TMCMC).

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More information

Accepted/In Press date: 22 March 2021
e-pub ahead of print date: 2 June 2021
Published date: 1 September 2021
Keywords: Adaptive Kriging, Bayesian model updating, Bayesian updating with structural reliability method, Bhattacharyya distance, Metamodeling, Stochastic model updating

Identifiers

Local EPrints ID: 490437
URI: http://eprints.soton.ac.uk/id/eprint/490437
ISSN: 2376-7642
PURE UUID: d5d4b6d4-faa2-4761-b823-7746fe3c8b67
ORCID for Sifeng Bi: ORCID iD orcid.org/0000-0002-8600-8649

Catalogue record

Date deposited: 28 May 2024 16:43
Last modified: 29 May 2024 02:09

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Contributors

Author: Masaru Kitahara
Author: Sifeng Bi ORCID iD
Author: Matteo Broggi
Author: Michael Beer

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