Adhesives free bark panels: An alternative application for a waste material.

The proportion of bark in tree trunks is in the range of ~ 10-20%. This large amount of material is currently mainly considered as a by- or even waste-product by the timber processing industry. Recently, efforts towards the use of bark have been made, e.g. as a raw material to harvest different chemical compounds or as an additive for wood particle boards. Our motivation for this work was to keep the bark in an almost natural state and explore alternative processes and applications for use. The traditional method of de-barking tree trunks by peeling was used to harvest large bark pieces. Two pieces of peeled bark were placed crosswise, with the rhytidom side (outer bark) facing each other. After different conditioning steps, bark pieces were hot pressed to panels without adding adhesives. These experiments on bark samples of different Central European tree species suggest that production of panels with species dependent properties is possible and feasible. This is a step towards producing sustainable panels by using a natural waste material, while retaining its beneficial structure and its natural chemical composition.

Development and evaluation of a novel 3D simulation software for modelling wood stacks.

Assessing the solid wood content is crucial when acquiring stacked roundwood. A frequently used method for this is to multiply determined conversion factors by the measured gross volume. However, the conversion factors are influenced by several log and stack parameters. Although these parameters have been identified and studied, their individual influence has not yet been analyzed using a broad statistical basis. This is due to the considerable financial resources that the data collection entails. To overcome this shortcoming, a 3D-simulation model was developed. It generates virtual wood stacks of randomized composition based on one individual data set of logs, which may be real or defined by the user. In this study, the development and evaluation of the simulation model are presented. The model was evaluated by conducting a sensitivity and a quantitative analysis of the simulation outcomes based on real measurements of 405 logs of Norway spruce and 20 stacks constituted with these. The results of the simulation outcomes revealed a small overestimation of the net volume of real stacks: by 1.2% for net volume over bark and by 3.2% for net volume under bark. Furthermore, according to the calculated mean bias error (MBE), the model underestimates the gross volume by 0.02%. In addition, the results of the sensitivity analysis confirmed the capability of the model to adequately consider variations in the input parameters and to provide reliable outcomes.

Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale.

Within the wood supply chain, the measurement of roundwood plays a key role due to its high economic impact. While wood industry mainly processes the solid wood, the bark mostly remains as an industrial by-product. In Central Europe, it is common that the wood is sold over bark but that the price is calculated on a timber volume under bark. However, logs are often measured as stacks and, thus, the volume includes not only the solid wood content but also the bark portion. Mostly, the deduction factors used to estimate the solid wood content are based on bark thickness. The aim of this study was to compare the estimation of bark volume from scaling formulae with the real bark volume, obtained by xylometric technique. Moreover, the measurements were performed using logs under practice conditions and using discs under laboratory conditions. The mean bark volume was 6.9 dm3 and 26.4 cm3 for the Norway spruce logs and the Scots pine discs respectively. Whereas the results showed good performances regarding the root mean square error, the coefficient of determination (R2) and the mean absolute error for the volume estimation of the total volume of discs and logs (over bark), the performances were much lower for the bark volume estimations only.