A stochastic imperfection simulation method from high-fidelity measurements on cold-formed steel studs

Abstract

This paper presents a stochastic imperfection simulation method towards cold-formed steel (CFS) studs, the data of which is generated from a high-thruput laser measurement device. An accurate hand-held laser scanner is applied to investigate about 19 types of CFS studs that widely used in current Chinese markets. point cloud models of which are reconstructed. A developed imperfection pattern recognition algorithm efficiently processes the high-fidelity point cloud models and automatically characterizes the imperfections based on the local, distortional, and global buckling modes. The measured imperfection data is statistically analyzed, where statistical models and inter-correlation models of mode imperfections are carefully obtained thereafter. The inter-correlation matrices and statistical models are parametrized for stochastic analysis. A data-driven stochastic imperfection simulation method thus is proposed based on the as-real correlation parameters and statistical data. The generated imperfection models are compared with the measured imperfections to validate the proposed simulation method. The investigation provides consolidated data foundations for the imperfection sensitivity analysis. The evaluation of CFS studs’ reliability can be insightfully conducted; thus, the imperfection design in the general specification is advised. The proposed imperfection simulation method based on inter-correlation parameters and as-measured statistical models also contributes to the development of trending simulation-based design of cold-formed steel structures.This work was financially supported by Quota Project for Promoting the Connotation Development of Colleges and Universities - Young Scholars of Beijing Talent Project (02082721010), Basic Research Funds for Municipal Universities (X21062). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author (s) and do not necessarily reflect the views of the sponsors or other participants