This paper presents an investigation on the shear resistance of corrugated web steel beams (CWBs) with a circular
web opening. A total of five specimens with different diameters of web openings were designed and tested with vertical load
applied on the top flange at mid-span. The ultimate strengths, failure modes, and load versus middle displacement curves were
obtained from the tests. Following the tests, numerical models of the CWBs were developed and validated against the test
results. The influence of the web plate thickness, steel grade, opening diameter, and location on the shear strength of the CWBs
was extensively investigated. An XGBoost machine learning model for shear resistance prediction was trained based on 256
CWB samples. The XGBoost model with optimal hyperparameters showed excellent accuracy and exceeded the accuracy of the
available design equations. The effects of geometric parameters and material properties on the shear resistance were evaluated
using the SHAP method.
Key Words
circular web opening; corrugated web steel beam; experimental study; machine learning; inelastic shear
buckling; shear strength
Address
Yan-Wen Li:1)State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
2)Department of Architecture and Architectural Engineering, Kyoto University, Kyoto, Japan
Guo-Qiang Li:State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
Lei Xiao:1)State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
2)Department of Building & Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
Michael C.H. Yam:Department of Building & Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
Jing-Zhou Zhang:1)State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
2)Department of Building & Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
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