Artur Wójcik

Modeling and Simulation of Biomass Drying Using Artificial Neural Networks

Willow (Salix viminalis) is a moist material after the crops. Therefore, the content of water in this type of material has to be lowered by drying before any further mechanical or thermal processing, in order to increase its calorific value. The process of drying is energy-intensive. Thus it is advisable to search for optimal methods and parameters of drying. The optimisation requires evolving a model that is based on the crucial parameters of the process. One of the possible solutions is to apply models of Artificial Neural Networks. Artificial Neural Networks belong to the group of methods of artificial computational intelligence and are often used in modelling various phenomena and processes. The aim of this work was to develop models using Artificial Neural Networks to describe the process of convective drying of the willow woodchips. As a result of presented work we obtained neural models describing alterations of water content, changes of the temperature and the mass of the chips. The presented models are highly accurate. We used experimentally obtained data in order to validate the models. It is important to underline that the data were not applied while the artificial neural networks were being developed. Subsequently, the models were used to simulate the process of drying what allowed us to define the optimal parameters of drying willow woodchips characterised by different moisture content.

Influence of Storing Miscanthus x gigantheus on Its Mechanical and Energetic Properties

The purpose of the study was to analyze the effect of storage of a Giant miscanthus on its mechanical and energy properties. The research material came from an experimental plantation of the Faculty of Production Engineering and Energetics of the University of Agriculture in Cracow. It was compared to plant material stored under cover where it was protected from atmospheric agents such as rain, snow and wind. The studies compared energy properties such as calorific value, moisture content and ash content. The second part of the research was used to determine selected mechanical properties—unit destructive force. Measured calorific value in two groups was: storage = Yes: 16,568 [kJ/kg], storage = No: 15,897 [kJ/kg]. Mean values of Pj (unitary destructive force) for stored and not-stored miscanthus were different. For X1—storage = Yes Pj = 48.27 [N] and for storage = No Pj = 40.73 [N].

The Dynamic Model of Willow Biomass Production

The paper presents methods and tools for building computer simulation models for supporting decision-making activities. The cultivation of energy crops for biomass production is a continuous process in which delays are very important along with other factors the values of which may denote a function of many parameters. The harvest of energy plants is a discrete process, so the simulation must combine both of these processes. The paper presents the method of constructing a model for growing energy crops and interprets conclusions resulting from the operation of the model, for changing values of the decision parameters.

The Research into Determination of the Particle-Size Distribution of Granular Materials by Digital Image Analysis

The granular materials, in particular fragmented biomass and cereal grains, are widely used in the power industry, the food industry, and agriculture. These materials are subjected to various processing methods and automated transport processes, which encourages implementation of fast tools (methods) for evaluation of the basic physical properties of these materials. The particle-size distribution is one of the basic characteristics of granular materials. The classic measurement methods are very time-consuming. Digital Image Analysis (DIA) provides new possibilities for quick, real-time measurements. The paper presents the study of the possibility of using DIA to determine the particle-size distribution of granular materials. The results obtained with DIA showed correlations with the actual particle-size composition at the values ranging from 0.63 to 0.89 R 2 .