Reliability-based design shear resistance of headed studs in solid slabs predicted by machine learning models

نویسندگان

چکیده

The economical and reliable design of steel-concrete composite structures relies on accurate predictions the resistance headed studs transferring longitudinal shear forces between two materials. existing mechanics-based or empirical equations do not always produce safe stud resistance. This study presents evaluation nine machine learning (ML) algorithms development optimized ML models for predicting were trained tested using databases push-out test results in both normal weight lightweight concrete. reliability model was evaluated accordance with European US practices. Reduction coefficients required to satisfy Eurocode requirements determined. Resistance factors used practice also obtained. developed interpreted SHapley Additive exPlanations (SHAP) method. Predictions by compared those descriptive equations, which demonstrated a higher accuracy models. A web application that conveniently provides nominal resistances practices created deployed cloud.

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ژورنال

عنوان ژورنال: Architecture, Structures and Construction

سال: 2022

ISSN: ['2730-9886', '2730-9894']

DOI: https://doi.org/10.1007/s44150-022-00078-1