Identifying and estimating causal effects of bridge failures from observational data

被引:0
作者
Çiftçioğlu A.Ö. [1 ]
Naser M.Z. [2 ,3 ]
机构
[1] Department of Civil Engineering, Manisa Celal Bayar University
[2] School of Civil & Environmental Engineering and Earth Sciences (SCEEES), Clemson University
[3] Artificial Intelligence Research Institute for Science and Engineering (AIRISE), Clemson University
来源
Journal of Infrastructure Intelligence and Resilience | 2024年 / 3卷 / 01期
关键词
Bridges; Causal inference; Counterfactuals; Failure; Hazards; Vulnerability;
D O I
10.1016/j.iintel.2023.100068
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
This paper presents a causal analysis aimed at identifying and estimating causal effects with regard to bridge failures under extreme events. Observational data on about 299 bridge incidents were used to conduct this causal investigation and examine bridges’ performance. As causal investigations can also deliver counterfactual assessments of parallel worlds, a causal analysis can serve as a high-merit methodology to evaluate the performance of critical bridges. Our findings quantify the causal impacts of various factors spanning the characteristics of bridges, traffic demands, and incident type (i.e., fire, high wind, scour/flood, earthquake, and impact/collision). More specifically, our analysis reveals high causal effects related to the used structural system, construction materials, and demand served. © 2023 The Authors
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