This paper investigates the potential sources of renewable energy, in particular biofuels. Biofuels tend to contain multiple harmful impurities that need to be separated if the biofuel is to have good energy performance, and the systems that run on it to produce electricity or heat are to operate more reliably. The paper discusses use of hydrocyclones as the most productive and reliable biofuel purification method. It dwells upon the factors that negatively affect separation of mixtures in a hydrocyclone, which are attributable to the complex hydrodynamics of the flow in such a unit. In order to eliminate these factors, the authors hereof have developed two hydrocyclone designs. An experimental test bench was designed and made to test these designs. Parts of the units were 3D printed from an environmentally friendly material. For testing, we used a biodiesel made from waste cooking oil with an impurity content of 23%. Experiments showed a maximum separation rate of 94.2%. The proposed solutions did improve the effectiveness of biodiesel mixture separation. These designs can be effectively used to separate non-homogeneous mixtures.
Mining operations have a significant negative impact on the surrounding ecosystems. The operation of mines and quarries creates a large amount of waste that accumulate and are practically unrecyclable in the environment. The involvement of these wastes in economic activity is an extremely urgent task. This can make the economy more sustainable and reduce its influence on ecosystems. This work presents the attempts of using quarry wastes as a fertilizer applied for growing tea crops. The novelty of this research involves revealing the quarry wastes as a fertilizer when growing Camellia sinensis (L.) O. Kuntze and assessing changes in the productivity of this plant when applying these calcium wastes. The waste of a quarry intended for extracting crushed stone was studied in this article. The composition of the waste was analyzed. Fertilizers used for manuring the soil were prepared based on the waste. Two experimental sites were selected. One of them was a control, where Camellia sinensis (L.) O. Kuntze was grown without using fertilizers. Fertilizers obtained from the waste were applied on the second site. The experimental work proceeded for 10 years. When discussing the results, special attention was paid to climatic conditions. This was caused by the need to show that it was the use of the fertilizer that influenced the change in the yield, not the climatic conditions. As a result of using calcium fertilizers based on the waste, the productivity of Camellia sinensis (L.) O. Kuntze was increased. The application of the fertilizers based on the quarry wastes was shown to provide an increase in the yield. The possibility of using calcium fertilizers to overcome unfavorable agroclimatic conditions during the tea cultivation was also demonstrated. To assess the climatic impact of applying new fertilizers, three-dimensional modeling in the “gnuplot v.5.4” software was used. As a result, an increase in the average annual precipitation, from 1000 to 1980 mm/year, in the range of the average annual air temperature, from 14 to 16 °C, was found to lead to an increase (when using a new fertilizer) in the yield of Camellia sinensis (L.) O. Kuntze up to 4.8 times (from 20 to 95 centner/ha). The results have shown that applying fertilizers based on the quarry wastes is also possible in unfavorable climatic conditions.
Adaptation to dynamic market changes and choosing the optimal development strategy based on the results of marketing activities today become a central problem for Russian industrial enterprises. Among the factors that determine the need to improve marketing practices, the costs of managing the flow of marketing information, the time to implement marketing opportunities and confront threats, knowledge of technologies, markets, their application and updating to ensure competitiveness, etc. are of decisive importance. The object of study is industrial enterprises that implements marketing activities. The subject of the research is the industrial enterprise marketing management process. The goal is to investigate the features of evaluating the effectiveness of industrial enterprise marketing activities based on a balanced scorecard. This article discusses a package of techniques for the development and use of a balanced scorecard to assess the effectiveness of industrial enterprise marketing activities. The advantages of evaluating the effectiveness of industrial enterprise marketing management using the concept of a balanced scorecard, which are focused on the future, accuracy, resource efficiency, objectivity, usefulness and timeliness, are substantiated.
The paper presents the results of studies on the use of plastic lubricants with ultrafine diamond-graphite powder in rolling bearings. Under operating conditions, even with a short-term toughening of the operation mode, it is possible to establish the boundary mode of friction due to the extrusion of lubricant from the zone of the rolling elements contact with the tracks of the rings. This leads to an increase in friction torque and an increase in temperature, which affects the performance of rolling bearings. Reducing slippage, lowering the working temperature, limiting the friction torque can be achieved due to the quality of the lubricants used with improved anti-wear and antifriction properties. Tribological studies have established that the introduction of ultrafine diamond-graphite powder into the composition of basic industrial lubricants significantly improves their performance. The introduction of ultrafine diamond-graphite powder into a lubricant reduces the amount of rolling bearings wear 1.6–1.8 times, the friction torque - to 23–25 %. The temperature of the bearing assembly decreases by 16–20 %. The presence of a lubricant that can significantly reduce friction forces. It reduces the amount of internal stresses and retards the development of fatigue cracks, which can increase the service life of rolling bearings 1.5–2 times.
of the theory of self-configuring machine learning algorithms for modeling and predicting the characteristics of components of complex systems".
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