Physico-chemical, structural and engineering prerequisites of modeling and optimization of tribological coatings based on polyamides in friction units of automobile and special units are considered. The analysis of the stress-strain state of the elements of the cardan transmission, carried out in CAE-systems Pro/ENGINEER Mechanica and LS-DYNA, allowed establishing the optimal thickness of tribological coating with minimum stresses. Composite materials based on commercially available polyamide PA-6 and adhesive sublayer for formation of tribological coatings on parts of the cardan shaft of trucks and special equipment are developed. It is proposed to introduce a polyamide resin based on aminoamides of resin acids of rosin, which has high compatibility with the polyamide matrix, provides plasticizing effect and uniform distribution of dispersed particles of modifier over the composite volume. When polyamide resin is used as an adhesive sublayer on the surfaces of the cardan transmission elements, increased interaction at the boundary “coating – sublayer” is provided. The developed composite coatings and adhesive sublayers, optimized by design solutions, have been tested in the cardan shafts produced by Belkard OJSC as a full-fledged alternative to imported analogues.

The influence of centrifugal forces on the crystallization process of aluminum-magnesium alloy AMг6 (АЛ23, ASTM-518.0 (G8A)) has been studied. A physicochemical and phase analysis of the structures of AMг6 castings obtained by centrifugal casting was carried out. It is established that crystallization of this alloy under conditions of increased centrifugal forces characterized by the gravity load coefficient 300–500 allows forming the structure without formation of brittle phase β(Mg₂Al₃), which is formed at other traditional casting methods, including centrifugal casting with the load up to 250g. In addition, it was determined that increasing the load from 300g to 500g allows  reducing the granularity of the material about 2 times (to values of about 50 microns) and contributes to the purification of the melt from brittle iron-silicon compounds in the solid solution of aluminum. Thus, the share of such compounds is reduced by 10%, and in comparison with the initial charge of melting – by 20 %. The investigated load increase makes it possible to increase the degree of alloying of the crystal lattice of the aluminum phase and to obtain material with increased strength and plasticity by at least 10 and 30 %, respectively. As a result of researches the alloy AMг6 with strength 275/230 MPa and relative elongation 8.9/18.6 % at temperature of material 20/300 °С accordingly is obtained. The prospects of using the obtained aluminium-magnesium alloys with improved properties are shown.

It is proposed that when implementing into practice the design of the aggregate-modular approach for creating hydraulic control units for hydraulic drives of process equipment, the problem of optimal design of aggregatemodular hydraulic control units be solved by developing and using connection and assembly modules that implement invariant mathematical models and, when designing, design algorithms aimed at forming the structure of hydraulic channels and assembly housings determined by basic hydraulic diagrams. Optimization of parameters of connection dimensions of connection and mounting modules based on criteria: volume and weight, hydraulic pressure losses, labor intensity and manufacturing cost, allows to perform parametric synthesis of aggregate-modular hydraulic control units. The analysis of the general criterion of optimality of connection and mounting modules is carried out taking into account the technological process of manufacturing modules. It is established that if the entire service life of the product is taken into account, the costs of cost and processing of the blank of connection and mounting modules can be neglected. Thus, the process of optimization of parameters of connection and mounting modules is simplified. The obtained result can be used in designing mounting housings of hydraulic control units of technological equipment.

The results of an experimental study of the thermal decomposition of sodium hexafluorosilicate Na₂SiF₆, performed under isothermal conditions at temperatures of 600, 700, 800 and 900 °C, are discussed. It is shown that the kinetics of this process can be described using the Avrami–Erofeev equation with a variable exponent n. The range of this exponent is from 0.541 to 1.545. The average value of the exponent n, calculated for all study variants, was 0.761. As is known, the Avrami–Erofeev equation describes the kinetics of thermal decomposition of a substance in a condensed state, determined by the nucleation process. This suggests that in the case of thermal decomposition of sodium hexafluorosilicate in the temperature range of 600–900 °C, this process is the limiting stage of the overall process. It was found that the decomposition rate of the pyrolytic Na₂SiF₆ increases with increasing temperature. The average value of activation energy was 63.23 kJ/mol. The average value of pre-exponential factor A was 1.807 10² min^–1. The results can be used in the development of equipment for obtaining polycrystalline silicon of semiconductor quality, which is the main raw material for the production of equipment used in micro- and power electronics and photovoltaics.

The paper presents the results of research and development of a methodology for optimizing parameters of tracking estimators for object coordinates and motion parameters. The methodology is based on a comprehensive approach to training dataset formation considering various types of object motion and application of specialized optimization algorithms. The developed algorithms implement a complete optimization cycle, including training dataset formation, data preprocessing, parameter optimization, and verification of obtained results. The results of practical application of the methodology for optimizing parameters of non-adaptive Kalman filter and Interacting Multiple Model (IMM) filter under various observation conditions and object motion patterns are demonstrated. Based on simulation modeling, it is shown that the application of the developed methodology significantly improves the accuracy of estimating coordinates and motion parameters compared to traditional approaches to parameter selection. Special attention is paid to studying the stability of obtained solutions to changes in observation conditions and object motion patterns. The obtained results are advisable to use in development and modernization of radar data tracking systems, air traffic control systems, air and ground situation monitoring complexes, as well as in other applications requiring high-precision estimation of object motion parameters under a priori uncertainty.

The automation of the radiotherapy preparation process is demonstrated through the development and machine learning of a multi-criteria ionizing radiation dose distribution model, using artificial intelligence tools embedded in the RapidPlan module of the Eclipse v16.1 (Varian Medical Systems) treatment planning system. A retrospective data analysis of 40 patients with thoracic and lumbar spine pathologies was performed to train the model. For each patient, a radiation dose distribution model was created using stereotactic radiation therapy with an inverse planning method and a dose fractionation regimen of 6 Gy in 5 fractions. The performance of the developed model was evaluated on a test set of 10 patients. Verification results confirm the model’s suitability for clinical application in oncological healthcare facilities and the prospect of using it to create personalized treatment plans. Automation of the pre-radiotherapy preparation process reduced the time spent on computer modeling of the three-dimensional ionizing radiation dose distribution and improved the quality of specialized medical care provided by stereotactic radiation therapy.