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Bayesian structural identification of a suspension bridge using temperature and traffic loading

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conference contribution
posted on 2022-06-07, 12:59 authored by Andre JesusAndre Jesus, MR Salami, R Westgate, K Koo, J Brownjohn, I Laory
Large civil infrastructure such as long suspension bridges are critical connecting elements, whose behaviour is difficult to discern and should be constantly monitored for safety. Critical factors relevant for this purpose usually are non-directly measurable, having therefore to be inferred, based on monitored data. This structural identification is usually highly susceptible to uncertainties, having numerous methodologies been developed for this purpose. This paper presents an enhanced modular Bayesian approach for structural identification, able to comprehensively quantify uncertainties in data interpreted by a physics-based model. Gaussian processes are used as emulators of the model response surface and existent modelling discrepancies. The Metropolis Hastings algorithm was used to expand the original methodology for multiple parameters inference. This method was applied to calibrate a finite element model of Tamar suspension bridge using long-term monitoring data. Measurements of temperature, traffic, mid-span displacement and natural frequencies in a one year span were used for identification of the prestress in the main/side cables of the bridge and stiffness of its thermal expansion gap. Results indicate a relative increase in the force of the suspension cables, while the expansion gap stiffness remains considerably low. This work is believed to pave a new way for identification of critical properties in large-scale infrastructures.

Funding

DTP 2016-2017 University of Warwick

Engineering and Physical Sciences Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings

Pages

757 - 766

Source

8th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2017)

Publisher

International Society for Structural Health Monitoring of Intelligent Infrastructure (SHMII)

Version

  • AM (Accepted Manuscript)

Rights holder

© International Society for Structural Health Monitoring of Intelligent Infrastructure

Publisher statement

This paper appears here with the permission of the publisher. This paper was accepted for publication in SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings and the definitive published version is available at https://www.proceedings.com/39899.html

Publication date

2018-08-31

Copyright date

2017

ISBN

9781925553055; 9781510864573

Language

  • en

Editor(s)

Tommy Chan; Saeed Mahini

Location

Brisbane, Australia

Event dates

5th December 2017 - 8th December 2017

Depositor

Dr Andre Jesus. Deposit date: 4 June 2022

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