Reliability-based structural assessment of steel truss bridges subjected to failure scenarios

Journal Article (2025)
Author(s)

Santiago López (Universidade de Vigo)

Brais Barros (Universitat Politécnica de Valencia)

Manuel Buitrago (Universitat Politécnica de Valencia)

Oswaldo Napoles (TU Delft - Applied Probability)

Jose M. Adam (Universitat Politécnica de Valencia)

B. Riveiro (Universidade de Vigo)

Research Group
Applied Probability
DOI related publication
https://doi.org/10.1016/j.engstruct.2025.120850
More Info
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Publication Year
2025
Language
English
Research Group
Applied Probability
Volume number
341
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Abstract

Economic losses of bridge failures can mount to millions of dollars per day and spiral quickly. In particular, steel truss bridges are highly vulnerable to member failures, which, if propagated, can cause severe disruptions to the entire system. The vulnerability of these structures has been underscored in recent bridge collapses, which were initiated by the propagation of localised member failures (e.g., I-35W Mississippi Bridge). This paper proposes a methodology for the structural assessment of member failure scenarios in steel truss bridges. A quantitative index (SoD) is proposed to evaluate the consequences of member failures in all bridge elements. The methodology includes a Bayesian Network that captures the relationship between load models and structural responses. Additionally, the methodology integrates Extreme Value Analysis and computes the expected SoD for a 100-year return period. Two complementary approaches are suggested for the analysis of the member failure scenarios. The first approach focuses on the failure scenario itself, examining the post-failure effects in all bridge elements. The second approach evaluates the response of individual elements to various failure scenarios, allowing an in-depth understanding of how different member failures influence specific bridge elements. The methodology has been tested on a railway steel truss bridge in which eleven member failures were simulated. Results allowed to identify the level of significance for the scenarios, providing insights to guide SHM strategies, prioritise interventions and optimise maintenance efforts. This work aims to simplify engineering efforts and support bridge management entities in their crucial fight to improve the bridge's structural safety.