Browsing by Subject "Counterfactuals"

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    Revisiting Forgotten Fire Tests: Causal Inference and Counterfactuals for Learning Idealized Fire-Induced Response of RC Columns
    (Springer, 2023) Naser M.Z.; Çiftçioğlu A.Ö.
    The expensive nature and unique facilities required for fire testing make it difficult to conduct comprehensive experimental campaigns. As such, engineers can often afford to test a small number of specimens. This complicates attaining a proper inference, especially when addressing questions in the form of what would have been the fire response of a particular specimen had it been twice as large? Or had it been made from a different material grade? In hindsight, answering causal and hypothetical (counterfactual) questions goes beyond the capacity of statistical and machine learning methods which were built to address observational data. To overcome the above challenges, this paper presents a causal approach to answering such questions. In this approach, principles of causal inference are adopted to reconstruct the deformation-time history of reinforced concrete (RC) columns and propose an idealized fire response for these columns. The findings of this study indicate the significant influence of the loading level, aggregate type, and longitudinal steel ratio on the deformation history of fire-exposed RC columns. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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    Identifying and estimating causal effects of bridge failures from observational data
    (Elsevier B.V., 2024) Çiftçioğlu A.Ö.; Naser M.Z.
    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