Prediction of Douglas Fir Sawn Timber Yield Based on Log Computed Tomography

Abstract

Climate change affects the growth conditions for Norway spruce (Picea abies) which is the most important species for the European construction timber industry. As a countermeasure, the species mix in European forests is being changed to include more hardwood, but also more drought-resistant softwood species, for example Douglas-fir (Pseudotsuga menziesii). Previous research has shown that Douglas-fir can on the one hand be suitable to produce highstrength material. On the other hand, however, Douglas-fir wood can also have a considerably lower strength than what is expected from spruce. Therefore, there is need for improved strength prediction and strength grading methods for Douglas-fir, to enable the correct allocation of Douglas-fir roundwood to the most suitable target product. In the present study, computed tomography (CT) image reconstructions of 53 Douglas-fir logs were used to predict the strength of the sawn timber and thus to identify logs which are suitable to produce glulam lamellas. To achieve this, statistical modelling was combined with Finite Element (FE) modelling of destructive tensile tests, based on simulated fibre orientations for the boards.