Solid biofuels can be defined as processed and unprocessed biomass. By definition it can be divided into: natural fuels (as obtained) and synthetic fuels (after mechanical and chemical treatment). Raw materials for the production of solid biofuels may include: wood, stalk plants, peat, sewage sludge and grains of cereals. These raw materials can be used directly as fuel or as a half-finished product for further production. The aim of the work was to analyze trends and research topics in the production of solid biofuels. This analysis was made using bibliometric techniques. Bibliometric analyzes allow to indicate the research topics, authors, as well as research institutions that significantly influence a given discipline. The research and analysis were carried out on scientific articles taken from the Scopus database in 2014-2018. The downloaded data have been cleaned and processed in the VOSviewer program. This program allows to analyze the frequency of occurrence of keywords in years and to present results in graphic form. Next, a detailed analysis of the content of the publications and classification according to selected criteria was carried out. The main countries that carry out research in this area are: Spain, Italy, Brazil, the Czech Republic and China. The main research areas were: Energy, Environmental Science, Agricultural and Biological Sciences, Chemical Engineering and Engineering. The most popular research topics throughout the research period were: biomass (raw materials, properties), biomass agglomeration processes (briquetting, pelleting), energy properties research, thermal biomass treatment (torrefaction, gasification and others), research on production and biochar properties and other.
The objective of the paper was to carry out a bibliometric quantitative analysis of publications concerning the application of artificial neural networks in the research area - agriculture and a bibliometric quantitative analysis and subject analysis with regard to agricultural engineering. A number of scientific publications devoted to the ANN found in the data base of the Web of Science - in documents published to 2015 was a basis for the quantitative analysis. Research on the use of artificial neural networks in the research area - agriculture is extending systematically. Moreover, a rapidly growing number of citations prove a continuous increase in the scientists’ interest in possibilities of the ANN applications. The quantitative analysis of scientific publications in 5 selected scientific journals and thematically related to agricultural engineering (indexed in the Web of Science) allowed a statement that 236 scientific articles from 1996- 2015 were related to the ANN application. The biggest number of publications was reported in Computers and Electronics in Agriculture - 118 articles. In 2011-2015 there was a growing trend in dynamics of publishing of scientific papers devoted to the ANN application to agricultural engineering. Thus, we may assume that the research related to application of the artificial neural networks to agricultural engineering will be continued and their scope and number will be still growing. The thematic analysis of the most often quoted publications from 2011-2015 in the journal Computers and Electronics in Agriculture, proved that they concern both the issues related to the classification problem as well as to modelling processes and systems. We should suppose that the subjects related to modelling of drying processes and application of neural networks for image analysis will grow dynamically in the following years.
So far, there are no results for research on the biomechanical parameters of giant miscanthus stalks taking into account both the influence of moisture content and the internode, from which the samples were taken. Therefore, the aim of the research was to comprehensively investigate the influence of the internode number (NrNod) and water content (MC) on the values of selected biomechanical parameters (modulus of elasticity and maximum stress) determined using various stress tests (three-point bending and compression along the fibers). The research was carried out for dry stalks of different humidities and for different internodes. The results obtained in this study proved that the independent variables of the water content and the internode number cause a statistically significant influence on the values of the examined biomechanical parameters of the miscanthus stem: the modulus of elasticity in compression, the maximum stress in compression, the modulus of elasticity in bending and the maximum stress in bending. The values of the modulus of elasticity (MOE) increase when increasing the NrNod. For individual internodes, MOE values are higher with a higher MC. The values of the maximum stress (σ) also increase when increasing the internode number. For individual internodes, the σ values are lower with a higher MC.
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