Present article is dedicated to the analysis of problems of the oil industry of Russia and is aimed at the development of a mechanism for its growth. The research is based on the results of the economic analysis that has been carried out on the basis of statistical data from the government and major oil companies as well as on the basis of analytical reports of independent companies. Among the main identified problems of the oil refining industry it can be mentioned following problems: insufficient volumes of raw material processing, lack of refinery capacities, remote location of oil extraction and refinery plants from the end users and unbalanced tax system in the industry. Specified problems are being solved on the level of companies and the state that brings results, however, there is no clear development mechanism of the oil refining industry so far. The authors suggest a development scheme for the Russian oil refining industry implying cooperation of businesses and the state. The implementation of the proposed scheme will ensure the investments for the extension of production and obtaining a product with a higher added value as well as increasing the competitiveness of the Russian oil products.

In this study, we utilized multiphase computational fluid dynamics (CFD), and discrete element method (DEM). Effect of the kinetic parameters of the roasting process in a fluidized bed was investigated. Our results indicate that it is possible to numerically integrate the coupled CFD-DEM system without significantly increasing computational overhead. It is also clear, however, that reactor operating conditions, reaction kinetics, and multiphase flow dynamics have major impacts on the roasting products exiting the reactor. We find that, with the same pre-exponential factors and mean activation energies, inclusion of distributed activation energies in the kinetics can shift the predicted average value of the exit gas-solidphase and its statistical distribution, compared to single-valued activation-energy kinetics. These findings imply that accurate resolution of the reaction activation energy distributions will be important for optimizing roasting processes.

This article is devoted to the development of a method for probability estimate of failure of an asynchronous motor as a part of electric drive with a frequency converter. The proposed method is based on a comprehensive method of diagnostics of vibration and electrical characteristics that take into account the quality of the supply network and the operating conditions. The developed diagnostic system allows to increase the accuracy and quality of diagnoses by determining the probability of failure-free operation of the electromechanical equipment, when the parameters deviate from the norm. This system uses an artificial neural networks (ANNs). The results of the system for estimator the technical condition are probability diagrams of the technical state and quantitative evaluation of the defects of the asynchronous motor and its components.