Strength prediction of timber boards using 3D FE-analysis

Timber boards are numerically reconstructed in the full 3D space based on knot information on the wood surface. The 3D model is then transformed into a full 3D-FEM model and successively used for tensile strength prediction. By knowing the exact locations of the knots, as the main strength governing parameters in timber boards, simulations are run for a large quality range of wood laminations. This includes low-medium quality Douglas fir and medium-high quality spruce boards. ABAQUS and PYTHON are used for the numerical simulations. An automatic link is programmed to extract data of the database and to create the 3D geometrical model. From the numerical simulations, three mathematical methods are presented to calculate the stress concentration factors (SCFs) around the 3D heterogeneous defects in anisotropic wooden boards. Additionally, the explicit dynamic analysis are run to obtain the dynamic modulus of elasticity (MoE _dyn ). To reduce the dependency of the numerical predictions on the real density of the boards, the average density of each sample is used for the simulations. Each board is tested in tension physically and is used for the validation of the model. The FEM results are used in a regression analysis to analyze the correlation with the visual measurements and to predict the tensile strength. Based on the results of a multiple regression analysis, two SCFs and MoE _dyn are sufficient to accurately predict the strength of spruce and Douglas fir boards. The results of the current study show that an improvement in the strength prediction of wood is possible in comparison with current machine grading systems based on dynamic MoE and knot parameters.