Full long-term buffeting analysis of suspension bridges using Gaussian process surrogate modelling and importance sampling Monte Carlo simulations

Dario Fernandez Castellon, Aksel Fenerci, Petersen, Øyvind Wiig and Øiseth, Ole

Reliability Engineering and System Safety, 2023, vol. 235, issue C

Abstract: Recent findings from full-scale measurements campaigns and analytical investigations of the design buffeting response of long-span bridges suggest that the assumptions adopted in most wind-resistant design guidelines are not strictly conservative. In such cases, a full long-term analysis is the most accurate alternative for reliability-based design. However, the application of such methodology becomes unfeasible due to the corresponding computational demand. Notably, many evaluations of the buffeting response are required, and time-consuming numerical integration is traditionally used to evaluate the long-term response. To overcome these drawbacks, this paper proposes a framework to increase the computational efficacy of long-term analyses for the wind-resistant design of long-span bridges by combining two strategies. First, the buffeting response is estimated with a Gaussian process regression that requires less time than the traditional multimodal buffeting response estimation. Then, long-term analysis is carried out using importance sampling Monte Carlo simulations that converge faster than the traditional analysis based on numerical integration. The computational framework is demonstrated in a case study of a proposed super-long suspension bridge subjected to loads induced by wind buffeting. The advantage of the proposed framework is verified, as it requires less than 1% of the computational demand of the traditional full long-term analysis.

Date: 2023
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001266

DOI: 10.1016/j.ress.2023.109211

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