The paper aims to study the stress-strain state of the surface layer in a VT95 aluminum alloy part during its shot-impact treatment in the sequence of “shot-impact treatment–flap-wheel trimming” operations. The research objects included large parts, such as panels and cladding of complex shapes used in aircraft, missile, and shipbuilding industries. Computer simulation in the Ansys Workbench 19.0 software package was used to develop a methodology for determining residual stresses. As a result of simulating the studied treatment sequence, a visual representation of the residual stress formation pattern, as well as physical values and distribution curves of residual stresses, were obtained. The distribution pattern of residual stresses after performing two types of treatment was established to be similar. The maximum value of residual stresses, obtained as a result of performing a shot-impact treatment of the part surface with a shot of 3.0 mm in diameter at a shot-impact rate of 25 m/s, reaches about 600 MPa at a depth of 1.0 mm. Following the shot-impact treatment, flap-wheel trimming is performed in the finite element simulation as a set of abrasive grains at a rate of 18.316 m/s. The removal of the 25-, 50-, and 75-μm layer from the surface of the plate during trimming contributes to the shearing of the upper part in the residual stress diagram and, as a result, to a decrease in the values of residual stresses in the shot-impact treatment–flap-wheel trimming sequence to 400 MPa. In addition, along with an increase in the thickness of the layer removed from the surface during trimming, the value of residual stresses decreases more slowly. In this case, the thickness of the removed layer causes no effect on the depth of residual compression stresses (about 0.7 mm). The developed finite element model makes it possible to predict and control the level and magnitude of residual stresses in an aluminum alloy sample at the stage of its preparation for both a shot-impact treatment operation and the combination of shotimpact treatment and flap-wheel trimming.

In this article, we set out to analyse and select new materials at the design preparation stage for the manufacture of composite products to replace conventional structural metals. In the study, a multi-criteria analysis of multivariate systems based on matrix analysis was used. For comparative examination, the well-known reference data, recommendations based on the scientific research of materials, as well as technical, economic and qualitative data of forming methods for these materials, were used, taking into account their specific properties. A comparative analysis was carried out for eight different materials used for the design of polymer composite products, aiming to replace conventional structural materials under three comparability conditions. The first condition considers all selected physical and mechanical properties of the materials and their costs. The second condition emphasises the ultimate strength of the material, its elastic modulus and cost. The third condition is partially similar to the second condition, with the exception of the compressive strength. It was established that the most rational composite for the product design under the first and second conditions is a basalt fibre-reinforced polymer, with the highest weight criterion coefficient (q) of 0.3947 in the first case and 0.3955 in the second case. For the third condition of comparability, carbon fibre was found to be the optimal composite material with the highest q value of 0.3341. The methodology allows product materials, tool materials, cutting regimes and tool geometry to be analysed and selected based on the accumulated knowledge base derived from empirical research. The developed methodology was tested under the three comparability conditions. Theoretical studies showed that the use of the methodology could increase the efficiency of pre-production by 2–3 times, depending on the complexity of the evaluated system.

The aim is to develop and substantiate a complex of technical and economic requirements for the design of a self-feed drilling machine produced in the Russian Federation, which is particularly relevant in the context of import substitution. The study considers self-feed drilling machines produced by Atlas Copco, Desoutter and Recoules as references to match their performance and specifications. By analogy with these machines, the limiting weight and overall dimensions of the developed machine should be up to 6 kg and 320x110x450 mm, respectively. The selection of motors for spindle rotation and axial feed is carried out by drilling a hole with a diameter of 12 mm in a mixed 58 mm thick stack using a carbide drill. This stack includes steel sheets (30KhGSA grade), polymer composite materials (carbon fibre-based), titanium alloy (Vt6 grade) and aluminium alloy (1933 grade). The required power for the electric drives was determined using cutting conditions specified in reference manuals and by drilling tests of a mixed stack carried out using a DMC 635 V machine equipped with a Kistler 9123CQ05 plate dynamometer. Oscillograms of axial force and torque showed that the highest resistance occurs when drilling the titanium alloy. The following specifications were calculated and confirmed for the projected self-feed drilling machine: the required power for the electric drives is 1.5 kW for the feed drive and 2.8 kW for the spindle rotation drive. The maximum required rotation speed is 1940 rpm, and the maximum required feed rate is 4.5 mm/rev. In order to grind chips and suppress potential auto-oscillations of the drill, it is recommended that the modulations of the feed and spindle rotation speeds created by a computer numerical control system be used. Future research will involve the production and testing of a prototype self-feed drilling machine, designed in accordance with the provided recommendations.

This study is aimed at developing a technological approach for managing the automated control of the production process of photopolymer-based products. Thermometric analysis was proposed and used to identify the onset and completion of the polymerisation process of the studied products using a homebuilt automated laboratory setup based on the industrial additive polymerisation unit AZ3000. The principle of extremal control was used to develop the operation algorithm. Samples measuring 25x25x3 mm were manufactured from the extensively used photopolymer composite ROEHM R-50. The controlled parameters of the photopolymerization process, including the temperature in the active zone and on the product surface, were scientifically justified. The developed algorithm, implemented as a software package written for the AtMega 328 processor in C++ within the AVR Studio environment, offers precise control over the onset and completion of the polymerisation process within the product. The structural characteristics of the test photopolymer materials were studied. It was found that the hardness of the photopolymer samples increased from 109.12 to 117.5 HL. This demonstrated the functionality of the developed algorithm for the control system of the photopolymerisation process. The testing of the developed technological approach and algorithm for automated control of additive manufacturing using photopolymer materials indicates that it is possible to obtain components with predetermined strength characteristics. The use of such components adds a new dimension to the selection of photopolymer materials for the manufacture of products in various fields of mechanical engineering, including transport and aviation.

We address the problem of improving the calculation accuracy of power flow in a medium-voltage distribution network based on the measurements of smart meters installed on the secondary side of 6(10)/0.4 kV transformers. In order to account for the effect of unbalanced loads in the low-voltage network on power flow in the medium-voltage network, three-phase three-wire lines were reduced to a single-line option. This enabled the use of symmetric mode calculation programs for the asymmetric mode. The loads in the medium-voltage network were determined by adding power losses in transformer windings and core to the loads measured on the secondary side of transformers. The calculation of winding power losses using the methods of phase coordinates and symmetrical components involves determination of currents in the windings of each phase according to 48 sections of load capacity and voltage module measurements, performed by the smart meter during the day. The correctness of expressions for calculating power losses in transformer windings is confirmed by the equality of total losses in phase coordinates and symmetrical components. The negative sequence power losses in transformer windings were found to be close to zero, while zero sequence losses are significantly lower than the positive sequence losses for almost all transformers with a double star-zero winding connection scheme, regardless of the load factor and rated power. The conducted studies confirmed the possibility and effectiveness of using smart meter measurements for determining loads and calculating power flow in the medium-voltage network. This conclusion was illustrated using an actual distribution network with 26 transformers. Future research should aim to clarify the mathematical models of transformers in the joint calculation of medium- and low-voltage distribution networks.

In this work, we investigate the effect of home charging stations for electric vehicles on voltage deviations in a 0.4 kV suburban distribution network. A 10/0.4 kV transformer substation and a 0.4 kV distribution network, supplying electricity to 114 private residential buildings, were selected as the research objects. In order to assess the effect of home charging stations on voltage deviations, a stochastic quasi-dynamic model of the electrical network was developed in the Python programming language using the Pandapower library. This model allows daily profiles of power consumption and voltage to be simulated at various numbers and connection points of home charging stations, taking the random behavior of electric vehicle owners into account. For maintaining the voltage level within the permissible limits, inverters for on-board chargers of electric vehicles in terms of reactive power sources and the shift of the charging start time to the night hours are considered. According to the simulation results, when 30% of 0.4 kV suburban distribution network consumers use a home charging station, the load on the main section of the supply line can briefly approach 100% and the depth of negative voltage deviations can exceed 20%. The Volt-Var control by on-board chargers of electric vehicles was established to reduce significantly voltage deviations in the distribution network (reducing the duration of voltage deviations below −5%, i.e., from 27.3 to 12.9%) with an insignificant effect on the charge duration of electric vehicles. The results obtained can be used in the long-term planning of distribution electric networks in the context of a widespread use of electric vehicles.

The study aims to analyze the unit commitment models and mechanisms that are used in the wholesale electricity and capacity market in Russia and other countries, as well as to consider the methods and criteria for taking into account the system security constraints in these models. The subject matter of the study includes energy systems: wholesale energy and capacity markets in Russia, the United Kingdom, EU countries, Australia, and the United States of America. In this work, various scientific information sources were collected and analytically reviewed. The study considers the performance framework of the wholesale electricity and capacity market in different countries and the main control mechanisms in solving the unit commitment problem, as well as studying and analyzing the legal and regulatory framework in solving optimization problems. It is shown that within the domestic model, the Russian Power System Operator conducts unit commitment according to the submitted price bids, taking into account the needs of the market and the energy system balance. The considered and analyzed unit commitment scheme adopted in the Russian electric power industry fails to take full account of system security, which prompts further study of this issue. The performed comparative analysis of principles underlying the performance of models and the specifics of solving unit commitment problems revealed the strengths and weaknesses in the approaches adopted in different countries both in terms of the legislation and models. The conducted analytical study helped to formulate the key points for each model that can be used to solve the unit commitment problem.

We determine the kinetic patterns of melting in a heat-generating cylindrical element under invariable supercritical conditions using numerical modelling. The study focuses on the melting process in a homogeneous sample that generates heat either through a chemical reaction or electromagnetic heating. The thermophysical properties of the sample were assumed to be constant in both solid and liquid phases. The main tool used in the study was a numerical model based on the nonstationary Stefan problem in a heat-generating body, which incorporates the descriptions of heat conduction and melting processes. The phase transition was described in terms of enthalpy. In order to select the parameters of the numerical model (grid steps), the accuracy of the difference scheme was investigated. The study presents calculated dependencies of the main melting characteristics (melting time and the maximum sample temperature at melting) on control parameters (heat generation intensity, the heat effect of melting and the ratio of thermal conductivity coefficients of the phases). By using specified approximations (temperature averaging and quasi-stationary distribution), formulas were derived to estimate the melting time of the sample. The calculations showed that the variations in the thermal properties of the sample (thermal conductivity coefficients and heat effect) significantly influence the melting rate. It was demonstrated that although the relationship between the melting time and the intensity of heat generation and the thermal effect of the phase transition is consistent with the approximate models, there is a significant quantitative difference between them, in particular, for small deviations from the critical heat generation intensity. The calculations can be used to assess the thermomechanical stability of materials with internal heat generation. The developed numerical model allows melting processes to be investigated under a wide range of conditions, including varying boundary conditions.

The present study aims to develop and test a prototype of an intelligent automatic system for monitoring the success of starting asynchronous motors with a squirrel-cage rotor using the physical model of a local power supply system. The prototype implements stepwise predictive control, which checks the partial conditions of the process success at each step based on critical parameter models of both the engine and the supply network. The development is based on the use of the LabVIEW software suite, parametric identification methods, physical simulation, analog and digital signal filtering, auto-regulation theory, mathematical analysis, and statistics. The study experimentally proved the possibility and effectiveness of predictive start-up control for asynchronous motors of local power supply systems in terms of the magnitude, rate, and pattern of variations in the operating parameters of motor stator windings without a direct measurement of the shaft velocity. The error of the developed models for determining the critical mode parameters, affecting the success of starting the asynchronous motor, is demonstrated to be less or equal to 4%. The error in the predictive estimate of the start-up duration for an asynchronous motor did not exceed 14%. It is demonstrated that in 91% of experiments with the start-ups of an asynchronous motor using the physical model of a local power supply system under the variations of circuit-mode conditions, the automatic system prototype reliably identified the success/failure of the engine start at various stages of the process. If a failure was detected, the prototype ensured the interruption of start-ups in the early stages. The studies revealed no cases of non-issuance by the automatic system of a command to interrupt the start-up process under the conditions of its failure. Therefore, intelligent automatic systems for monitoring the success of starting asynchronous motors in local power supply systems will reduce the likelihood of damage to motors and equipment of power supply networks, preserve their serviceability, and improve the reliability of power supply to consumers.

The aim was to develop digital models of traction power supply systems with nonlinear stationary loads in order to determine asymmetric and non-sinusoidal modes. To this end, methods based on phase coordinates were implemented in the Fazonord software package (version 5.3.4.1–2024). The models included the following elements: 220 kV transmission lines, 40 MV·A transformers, 25 kV traction networks of double-track sections and a converter unit powering the industrial transport power supply system. The developed models identified asymmetrical and nonsinusoidal modes during the movement of a train on a specific section of the main railway. It was demonstrated that the nonlinear stationary load generated by a six-pulse converter results in an increase in harmonic coefficients at the 10 and 220 kV inputs of the traction substation feeding the rectifier, exceeding 25% on the 10 kV busbars. This phenomenon should be considered when selecting means to reduce harmonic distortion. These include passive filters, active conditioners and new-generation electric rolling stock with four-quadrant converters. The maximum asymmetry coefficients on the 10 kV busbars of traction substations ranged from 4.8...9%. These values can be reduced down to acceptable limits using phase-controlled reactive power sources or balancing transformers. The presented models allow all the parameters of the AC railway power supply system to be adequately determined under stationary loads with nonlinear voltage-current characteristics. The developed method is versatile and can be used for calculating modes of supply and traction networks of various structures and designs.

In this article, we set out to identify and analyze the key features of aggregating microgrids into energy communities, with a focus on the predominance of industrial or residential loads. Research methods included a literature review and meta-analysis in the field of planning, modelling and management of microenergy systems and their communities. In addition, a methodological approach combining multi-criteria decision-making methods and artificial intelligence was used. The efficiency of the approach was demonstrated by the establishment of two types of energy communities for remote settlements on the Sea of Japan coast, which integrated residential and industrial loads. The “Autonomous Operator” model, which involved a two-level optimization and reinforcement learning algorithm based on Monte Carlo tree search, was tested in order to determine the optimal economic management of operation modes of the potential energy community. At the lower level, the problem of finding market equilibrium was solved by minimizing the function of total operating costs. At the upper level, the management strategy that provides the optimal profit distribution among the community members was selected. Two scenarios of microgrid integration and operation in an energy community were studied: industrial and public types. The research demonstrated that operating settlements as energy communities is a more economically and ecologically advantageous approach than operating them individually. The results indicated that the levelized cost of electricity (LCOE) decreased more significantly when combining settlements in an industrial-type energy community (from 22 rub/kWh to 6 rub/kWh) compared to a public-type community (from 22 rub/kWh to 9 rub/kWh). The analysis of the above characteristics of different types of energy communities can help designers to determine the possibilities, features and consequences of aggregating microgrids of different types under various territorial and climatic conditions.

The main objective of this research is to analyze current problems and methods proposed for solving problems of design, operation and planning for the development of future sustainable electric power systems, taking into account the integration of renewable energy sources, the integration of heat and gas networks using highspeed communication channels. The author’s method of ensuring system stability and protecting the integrity of electric power systems is outlined. To ensure stable operation of future electric power systems, it is proposed to use methods of multi-level optimization and control of digital power systems, smart grid technologies and methods for processing vector measurements based on cyber-secure communication channels. It has been established that the proposed schemes make it possible to ensure the stability of the system and protect its integrity. In order to demonstrate the effectiveness of such approaches, an example is given of solving the problem of preventing rolling blackouts of the power system by purposefully separating/isolating the system based on the author’s twostage controlled isolation algorithm. It is shown that to solve the problems of modern electric power industry, it is effective to use new telecommunication technologies, means of ensuring situational awareness and schemes for protecting the integrity of systems based on modern methods of operations research and artificial intelligence. The multicriteria optimization method proposed by the authors uses minimization of the objective function of power flow disruption and takes into account restrictions on the consistency of generator operation. The method was tested on an IEEE test circuit consisting of 118 nodes. Test calculations confirmed that the method allows for minimal power imbalance and minimal disruption of power flows. Thus, the results of the work open up new opportunities for improving the monitoring and protection of future sustainable electricity systems, including taking into account the integration of renewable energy sources, heat and gas networks.

The aim of the study was to adapt the technology of electric dehydration of oil for use with coal tar (a by-product of coke production for blast furnace smelting) in order to remove ash (tar decanter sludge) and water. The research focuses on coal tar generated in coke ovens, which forms a colloidal system with water and ash. The method of electric dehydration was employed in the study, which is currently used to remove water from the oil–water colloidal system. The construction of the 2-EG-160-2 electric dehydrator was examined, along with the specifics of introducing coal tar into it in comparison to oil. It was demonstrated that, under the proposed operational conditions for the electric dehydrator, the coal tar and tar decanter sludge would settle at the bottom of the unit due to their higher density than that of water (the density of coal tar is approximately 1200 kg/m³ and higher). A scheme for integrating the electric dehydrator into the de-ashing process at a coke-chemical plant was proposed. The process of separating coal tar in the electric dehydrator was calculated. The results demonstrated that the efficiency of the equipment in the dehydration of coal tar, in comparison to oil, is considerably lower due to its higher density and viscosity (approximately 40 times higher at 80°C). Consequently, the performance of the electric dehydrator for coal tar would be approximately 40,000 tons, as opposed to approximately 1 million tons for oil. Nevertheless, the aforementioned performance per electric dehydrator is sufficient to meet the dehydration needs of AO “Ural Steel” for coal tar. Therefore, it is recommended that the electric dehydrator be integrated into the general coal tar dehydration scheme in order to ensure that the required quality standards for the tar are met, allowing it to be used and sold as a target product.

We study the distribution of boron between silicon and slag of the CaO-SiO₂, MgO-SiO₂, CaO-MgO-SiO₂, and CaO-Al₂O₃-SiO₂ systems under reducing conditions with the purpose of determining the feasibility of using boroncontaining materials to eliminate slagging in the melting zone during industrial silicon smelting in ore smelting furnaces. To that end, we used model slags obtained by melting chemically pure oxides, as well as silicon-based alloys with an admixture of boron. High-purity 5N silicon produced by Kazakhstan Solar Silicon LLP was used. Boron alloys were manufactured independently by melting silicon with boron. The experiments included holding liquid slag and alloys in graphite crucibles at a temperature of 1600°C under poorly reducing conditions. The boron content in slag and silicon samples was analyzed by inductively coupled plasma mass spectrometry. The boron distribution coefficient in the above systems was established to range from 2 to 2.5 for the entire melt area of these systems at 1600°C. The boron distribution coefficient was demonstrated to decrease under an increase in the content of Al₂O₃ in the CaO-Al₂O₃-SiO₂ triplet system, which agrees with the data obtained by other authors. The use of graphite crucibles in experiments creates reducing conditions, similar to those in the hearth of an ore smelting furnace. Therefore, this approach provides more adequate data in predicting the equilibrium boron content in silicon in comparison with the experiments conducted using alumina crucibles by other authors. It was also found that the boron distribution coefficient does not depend on the magnesium oxide content in double (MgO-SiO₂) and triplet (CaO-MgO-SiO₂) systems. In conclusion, our results lift restrictions on the content of boron in boron-containing fluxes during industrial silicon smelting.

In this study, we develop a roasting method for removing arsenic from sulfide copper-arsenic-containing materials. The object of the study was fine dust from copper smelting production of the following composition (wt%): 34.89 – Zn; 20.02 – Cu; 17.74 – Pb; 17.07 – Fe; 7.12 – As; 0.92 – Sb; 0.69 – Sn; 0.63 – Ca; 0.42 – Mo; and 0.34 – K. The chemical composition of the materials was analyzed using an SHIMADZU EDX-7000 energy dispersive X-ray fluorescence spectrometer and a Bruker D8 Advance diffractometer. The roasting process was carried out in a laboratory tube furnace at a temperature of 550–800°C for 60–120 minutes with the addition of 25–50% of FeS₂ to the charge. Optimal conditions for reducing residual arsenic in the calcine to less than 0.3 wt% were identified: a temperature of 750–800°C, a duration of 1.5–2.0 h (in an inert atmosphere), and the use of 30 wt% of pyrite concentrate in the charge. Arsenic removal to the gas phase reached 91–96%. It is shown that in order to reduce the processing temperature to 600°C, it is necessary to add a reducing agent (coke fines) to the mixture of copper smelting dust with pyrite or increase the proportion of pyrite in the test charge to 50 wt% and hold the mixture for 1.5–2.0 h under inert atmosphere (argon and nitrogen) or low-oxygen blast. Arsenic removal to the gas phase reached 97%. X-ray spectral analysis of the residue deposited on the cooled ends of quartz tubes following the release of gases formed during roasting revealed that this material is predominantly (up to 93%) composed of arsenic. The resulting calcine contained 94 wt% of iron, zinc, copper and lead compounds. Therefore, the calcine obtained during the roasting of fine dust from copper smelting production is suitable for returning to the copper production process.