The maintenance of oil pumps is a complex task for any operating organization, and for an industrial enterprise in the oil and gas sector of the economy, this issue has a high degree of urgency. One of the reasons for this is a wide spread of pumping equipment in all areas of oil and gas enterprises. At the same time, an aggressive environment, uneven load, remote facilities, and harsh climatic zones (especially in the areas of the Arctic region or production platforms) are factors that make it relevant to develop special systems that help or simplify the maintenance of pumping equipment. Dynamic modeling is one of the modern technologies which allows for solving the urgent issue of assessing the technical condition of equipment. It is the basis of systems that carry out diagnostics and prognostic calculations and allow for assessing the dynamic state of objects under various conditions of their operation, among other functions. Augmented reality technology is a technology that allows for reducing the time for equipment maintenance by reducing the time for searching and processing various information required in the maintenance process. This paper presents an investigation of the effectiveness of an augmented reality and a dynamic simulation system collaboration in oil pump maintenance. Since there is insufficient research on the joint application of these two technologies, the urgent issue is to prove the effectiveness of such collaboration. For this purpose, this paper provides a description of the system structure, gives a description of the development process of the augmented reality system application and tests the application using Microsoft HoloLens 2.

The purpose of this study is to analyze the main factors of socialization that affect a person at the stage of admission to a higher education institution. The study is based on a 2020 survey of students of St. Petersburg Mining University. The paper analyzes such factors as family influence, academic performance, changes in the circle of friends, and new conditions. As a result, each of the studied factors was characterized, as well as the phenomenon of value conflict and the possibility to consider high academic performance at university as an indicator of successful socialization were noted.

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.