The investment scenario applied to forestry development analyzes the fundamental changes in the production structure, among other things. These changes refer to the priority development of the pulp and paper industry through the chain of large-scale woodworking facilities, where pulp, paper and cardboard manufacturing plants are the key links. Such facilities include sawmilling facilities, wood-processing factories, and timber factories. Those provide a significant economic benefit, so improving them is one of the top priorities. Considering this priority is the purpose of this article. The goal was achieved using common and scientific research methods, including mathematical modeling.Theoretical research resulted in three sets of formulas adapted for evaluating the pulpwood barking from theoretical findings on image recognition.

In the coming decades, wood waste management for biofuel production is regarded as a promising renewable energy source and a key factor in reducing carbon dioxide emissions. Mechanical grinding is seen as one of the main techniques in wood waste pre-treatment operations that increases the value of feedstock used for fuel. The application potential of the ground product highly depends on the energy effi ciency of the process.This work aimed to establish a consistent pattern for estimating the energy consumption required for grinding spruce and pine barking waste depending on the degree to which materials are ground and their relative moisture content. The energy consumption parameters at grinding were analyzed employing three grinding energy models of Rittinger, Kripichev-Kik, and Bond. The results of estimation showed that specifi c energy consumption is associated with relative moisture content and the grinding degree by nonlinear dependence according to the Kripichev-Kik grinding model for spruce and pine bark. It has been established that the specifi c energy consumptionat grinding spruce and pine barking waste at the optimum humidity of 25% and 27%, respectively, is proportional to the natural logarithm of the grinding degree. It was concluded that the wood waste grinding by 5-15 times requires higher energy consumption at optimum moisture content, which is 5-10% and 7-14% of the heating value for spruce and pine, respectively. The knowledge acquired through this research will contribute to developing possible approaches for wood waste recycling in a more energy-effi cient way.

No abstract

No abstract