Automated Generation of Geometric FE Models for Timber Structures Using 3D Point Cloud Data
Abstract
Manual geometric modeling of timber structures is time-intensive and error-prone, impeding efficient structural analysis. To overcome this limitation, this study develops an automated framework for the rapid generation of 3D geometric finite element (FE) models directly from LiDAR point clouds. The methodology first employs a region-growing algorithm for component segmentation. This is followed by the integration of geometric feature extraction techniques to robustly determine the position, orientation, boundaries, and dimensions of structural elements. The extracted geometric information is then output as an executable APDL (ANSYS Parametric Design Language) file for parametric geometric modeling, incorporating interfaces for customizing material and connection properties. The proposed framework accurately reconstructs geometries with high fidelity. It effectively addresses challenges arising from occlusions and incomplete point cloud data through boundary inference and contact relationship analysis. This approach demonstrates substantial promise for applications in both heritage conservation and modern timber engineering.
Reference
Lin Chen; Liufang Jiang; Haibei Xiong. (2025). Automated Generation of Geometric FE Models for Timber Structures Using 3D Point Cloud Data. Buildings. https://doi.org/10.3390/buildings15132213
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