Bayesian Finite-Element Model Updating of Bridges Considering Boundary Condition Uncertainties
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 4
Abstract
A Bayesian finite-element model updating method for updating the additional rotational and horizontal constraints of bridge boundary conditions using modal parameters is proposed. First, the spring constant is considered as an uncertain parameter in the stiffness matrix to show the effect of the boundary conditions in the model updating process. Moreover, the substructuring method is considered for solving eigenvalue problems. By reducing the size of the characteristic equations, the substructure approach overcomes the drawbacks and inefficiency of the model updating process caused by the abundance of the updated parameters in actual engineering applications. Bayesian model updating subsequently is used to quantify the uncertainties that exist in bridge model updating, including the uncertainties caused by boundary conditions. By introducing an adaptive transitional Markov chain Monte Carlo algorithm to obtain the posterior probability of parameters, the computational efficiency is improved. The posterior variance of the updating parameters clearly demonstrates the merit of the modified boundary conditions. Its application to a bridge structure demonstrates that the proposed method is efficient and applicable for engineering problems.
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Data Availability Statement
All data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
This research work was jointly supported by the National Natural Science Foundation of China (Grant nos. 52250011, and 52222807), and the National Key R&D Program of China (Grant no. 2022YFB2602700).
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 4 • December 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Feb 1, 2024
Accepted: May 22, 2024
Published online: Aug 16, 2024
Published in print: Dec 1, 2024
Discussion open until: Jan 16, 2025
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