Geometric Reconstruction-Driven Load Capacity Evaluation for Locally Buckled Steel Members

Abstract

Conventional contact-based inspection techniques face significant challenges in accurately modeling the complex 3D geometry of locally buckled steel members, which hinder reliable assessment of their residual load-carrying capacity. To overcome these limitations, this study proposes a method for analyzing the bearing capacity of locally buckled steel members using geometric reconstruction models, enabling precise evaluation of their load-carrying capacity. The research methodology encompasses three primary aspects: (1) model preprocessing; (2) load-bearing capacity analysis of specimens; and (3) experimental validation. Model preprocessing involves three key tasks: point cloud model reconstruction and optimization; evaluation of the effect of external factors on model accuracy; and parametric modeling with verification of geometric accuracy. The load-bearing capacity of damaged specimens was analyzed by predicting the residual capacity of the corresponding parametric models using finite element software. Finally, axial compression tests on equal-leg single-angle steel specimens were conducted to validate the accuracy of the finite element analysis results, thereby demonstrating the effectiveness of the proposed method. Key findings include: (1) the overlap ratio has the most significant influence on model accuracy; at an overlap level of 18, the comprehensive mean absolute error is below 0.005, and model-specimen similarity between the angle steel parametric model and the angle steel specimen reaches 0.99 (no significant difference at 95% confidence level); (2) among the extracted key feature data, the elastic stiffness, peak load, and peak displacement all exhibit relative errors less than 10%, while peak strain in deformation zones shows larger deviations; and (3) among the 44 statistically key characteristic data points, 41 exhibit relative errors less than 10%, confirming the method’s high reliability for practical engineering applications.