Shear resistance of corrugated web steel beams with circular web openings: Test and machine learning-based prediction

Yan Wen Li, Guo Qiang Li, Lei Xiao, Michael C.H. Yam, Jing Zhou Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)103-117
Number of pages15
JournalSteel and Composite Structures
Volume47
Issue number1
DOIs
Publication statusPublished - 10 Apr 2023

Keywords

  • circular web opening
  • corrugated web steel beam
  • experimental study
  • inelastic shear buckling
  • machine learning
  • shear strength

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Metals and Alloys

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