Geometric Properties of Steel Components with Stability and Fatigue Risks Using 3D-Laser-Scanning

Abstract

Nowadays, 3D laser scanning technology is extensively employed in laboratory investigations of steel structural components, providing accurate geometric dimensions to reduce uncertainties caused by indeterminate geometry in experimental results. It is often used in conjunction with the Finite Element (FE) Method and analytical solutions, which are more accurate deterministic operators in the research on steel structures. However, establishing a common methodological framework for transferring or mapping 3D-scanned information into finite element models for complex steel structures with stability and fatigue risks remains an ongoing task. In light of this, this study has developed a 3D scanning platform capable of obtaining accurate geometric dimensions for various types of steel components. Different coordinate systems and point cloud mapping algorithms have been established for different types of components to construct actual finite element models with initial imperfections. The feasibility of the self-developed 3D scanning platform and finite element modelling has been validated through three experimental cases: weld details, steel girders, and cylindrical shells. The research findings demonstrate that the captured point cloud can be automatically processed and corrected using the developed algorithm. The scanned data can then be input into the numerical model using various mapping algorithms tailored to the specific geometric properties of the specimens. The differences between the experimental test results and the simulated results obtained from the 3D-scanned finite element models remain within a small range. The self-developed 3D scanning platform and finite element modelling technique effectively capture the actual dimensions of different steel components, enabling the prediction of their stability and fatigue risks through numerical simulations.