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Data-Driven Distress Identification in Bridge Cap Beams: Field-Validated Nonlinear Analysis and Prospects for Adaptive Learning

dc.contributor.authorRaheem, Ibrahim A.
dc.contributor.authorChorzepa, Mi G.
dc.contributor.authorKim, S. Sonny
dc.contributor.authorBirgisson, Bjorn
dc.contributor.authorLim, Edwin
dc.date.accessioned2026-08-20T11:59:50Z
dc.date.available2026-08-20T11:59:50Z
dc.date.copyright2025/12/15
dc.date.issued2026
dc.identifier.otherJPCFEV.CFENG-5265.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312952
dc.description.abstractAbstractThis study presents a structured framework for evaluating distress in bridge bent caps by integrating field observations, latent design features, and nonlinear finite-element analysis (FEA). Distressed elements are identified using National Bridge ...
dc.publisherAmerican Society of Civil Engineers
dc.titleData-Driven Distress Identification in Bridge Cap Beams: Field-Validated Nonlinear Analysis and Prospects for Adaptive Learning
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue1
dc.journal.titleJournal of Performance of Constructed Facilities
dc.identifier.doi10.1061/JPCFEV.CFENG-5265
dc.journal.fristpage04025077-1
dc.journal.lastpage04025077-12
dc.page12
dc.treeJournal of Performance of Constructed Facilities:;2026:;Volume ( 040 ):;issue: 001
dc.contenttypeFulltext


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