Veröffentlichungen und Präsentationen

Due to climate change impacts and the worsening growth conditions of Norway spruce (Picea abies) the species composition of European forests is being diversified, incorporating more hardwoods as well as drought-resistant softwood species, such as Douglas-fir (Pseudotsuga menziesii). As a result, there is a demand for enhanced strength prediction and grading methods for Douglas-fir to ensure proper allocation to the most appropriate end products. In this study, X-ray computed tomography images from 53 Douglas-fir logs were employed to predict the stiffness of sawn timber. From the 3D data the density, knot volume and pith distance through out the log could be determined. From this data virtual 2D boards were cut according to the real cutting pattern. The density distribution of each board was then used to resolve the fibre orientations around knots with an existing fibre reconstruction algorithm. For the finite element model, a locally varying coordinate system was developed based on the acquired fiber orientations, utilizing an orthotropic stiffness tensor that was linearly scaled with density at each integration point. As knots significantly influence the overall stiffness of a board, multiple stiffness properties were explored. Given the size of the data sets and the number of boards the Java® API of COMSOL Multiphysics® was utilized and accessed with Python® to automatically set up the simulations for each board. They were virtually tested by a prescribed displacement of one end and a fixed condition on the other. The modulus of elasticity (MOE) was calculated from the reaction forces and compared to the real MOE from physical tests. The preliminary results show that the model can reliable resolve the stress concentrations around the knots. However the calculated MOE is generally overestimating the real stiffness so more investigation has to be done in future studies.