Revisiting Forgotten Fire Tests: Causal Inference and Counterfactuals for Learning Idealized Fire-Induced Response of RC Columns

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dc.contributor.authorNaser M.Z.
dc.contributor.authorÇiftçioğlu A.Ö.
dc.date.accessioned2024-07-22T08:02:33Z
dc.date.available2024-07-22T08:02:33Z
dc.date.issued2023
dc.description.abstractThe 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.
dc.identifier.DOI-ID10.1007/s10694-023-01405-8
dc.identifier.issn00152684
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/11895
dc.language.isoEnglish
dc.publisherSpringer
dc.subjectConcrete testing
dc.subjectFlammability testing
dc.subjectLearning systems
dc.subjectReinforced concrete
dc.subjectCausal inferences
dc.subjectCounterfactuals
dc.subjectExperimental campaign
dc.subjectFire response
dc.subjectFire tests
dc.subjectMachine learning methods
dc.subjectMaterial grades
dc.subjectObservational data
dc.subjectReinforced concrete column
dc.subjectStatistical learning methods
dc.subjectFires
dc.titleRevisiting Forgotten Fire Tests: Causal Inference and Counterfactuals for Learning Idealized Fire-Induced Response of RC Columns
dc.typeArticle

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