This paper proposes a predictive model to help oil workers build a reliable model for identifying oilwell failures. It can help geologists experienced with Machine Learning to improve the accuracy of failure identification and a more accurate approach to well-maintenance planning. This study is based on output data statistics such as per-well daily oil flowmeter readings. The volatility of these indications makes it possible to determine the probability of an oilwell failure. This method makes it possible to rank wells according to the principle of the most probable failures for workers making decisions. The use of predictive diagnostics can help to detect equipment problems early, thereby minimizing unplanned downtime. Unplanned sudden oilwell failures increase the company’s operating costs, as well as increase risks of environmental pollution. © 2024 «OilGasScientificResearchProject» Institute. All rights reserved.

Screw compressors are critical equipment in oil and gas production and transportation, where efficiency losses caused by rotor geometry, inlet pressure pulsations, and harsh climatic conditions can accumulate into substantial annual energy penalties and reliability degradation. This study provides a quantitative assessment of these coupled effects within a unified multiphysics framework that combines time-accurate transient CFD simulations based on a fixed Cartesian immersed-boundary formulation with a climate-calibrated offline physics-based digital twin—functioning as a digital shadow with one-way data flow from archival SCADA records—a reduced-order seasonal model with no real-time updating, calibrated against a full calendar year of SCADA records and validated against a held-out cold-season dataset (October–December 2022, Tamb = −15 to +8 °C); summer-period predictions rely on calibrated extrapolation beyond the validation window—an integration not previously demonstrated for oil-flooded screw compressors. Two rotor profile configurations (Type A and Type B) were analyzed to quantify geometry-driven differences in static pressure distribution, leakage tendency, and pulsation sensitivity. Transient suction conditions were modeled using harmonic and quasi-random inlet pressure disturbances to evaluate pressure amplification, phase lag, leakage intensification, and efficiency degradation. Seasonal performance was assessed by integrating temperature-dependent gas properties, oil viscosity behavior, and external heat transfer into an annual climatic load framework.

Reliable and energy-efficient capacity control in high-pressure single-rotor screw compressors requires precise regulation of adjustable ring mechanisms operating under combined gas and thermal loading. Thermo-mechanical deformation, friction-induced torque demand, and stress concentration near discharge windows significantly influence structural integrity, clearance stability, and actuation performance. This study presents an integrated thermo-structural and analytical investigation of a regulating ring system with a hydraulic wedge-groove drive concept. Three groups of geometric variants (nine configurations total) were analyzed using coupled Steady-State Thermal and Static Structural finite element modeling in ANSYS 19.2. Thermal asymmetry between suction (22 °C) and discharge (120 °C) regions produced peak thermally induced deformation of 0.17–0.18 mm, consuming up to 60–70% of nominal operating clearance. Neglecting thermal effects underestimated peak thermally induced structural deformation of the regulating ring by 12–15%. Among the configurations, variant 2b provided the most balanced response, reducing peak equivalent stress by 12–15% and required actuation torque by 8–11%. An analytical model for friction torque and driving force was derived based on distributed contact pressure. The results reveal quadratic sensitivity of torque to contact radius and strong dependence on groove geometry. The proposed framework supports reliable clearance design and efficient actuation in heavy-duty rotating machinery. © 2026 by the authors.

This study examines the corrosion behavior of mild steel in sodium sulfate solutions containing phosphates of different compositions. The research evaluates how various phosphate additives influence the corrosion rate and protective properties of the steel surface in aggressive environments.

Relevance: The global transition to electrification of transportation, aerospace, and industry is increasing the demand for efficient, lightweight, and heat-resistant electric motor systems. Advances in additive manufacturing (AM), especially in the field of metal-ceramic composites, are a breakthrough in the field of electric motor modernization. This study examines overcoming the limitations associated with polymer and aluminum structures by integrating metal-ceramic composites into brushless DC motors (BLDC). Objective: To evaluate the practical feasibility, thermal efficiency, and design advantages of 3D-printed metal-ceramic composites for DC motors under standard thermal and electromagnetic conditions. Methods: Three 500-watt motor designs were modeled in Autodesk Fusion 360: a polymer-based motor (PETG, ABS, PEEK via FDM), an engine with a metal-ceramic body based on ALO₃ and ceramic bearings, and a conventional aluminum motor. Each design provided 240 watts of power on 12 windings. Thermal loads, bearing friction, and magnetic fields were evaluated in the simulation. AM methods included SLS, DML, and SLM. Results: The temperature in the plastic engines reached 285.7 °C, in the aluminum engines-117.5 °C, and in the metal-ceramic version-89.9 °C. The composite engine has a thinner body and integrated cooling. Discussion and conclusions: The AM metal-ceramic coating provides excellent thermal control, structural strength and design freedom-an ideal solution for next-generation electric drive systems, despite the higher cost and complexity of processing. © National Academy of Sciences of the Republic of Kazakhstan, 2025.

This study investigates the purification and characterization of gellan gum (GG) for use in ocular drug delivery systems. Different GG fractions were obtained and analyzed for their molecular properties and mucoadhesive behavior. The results demonstrated that GG formulations can effectively adhere to the ocular surface and improve drug retention.

Relevance. Acoustic emission systems and complexes are currently considered a sensitive method for detecting forming defects. However, defect detection in selective laser melting of heat-resistant alloys using acoustic emission becomes challenging under the influence of noise. The impact of noise significantly complicates the identification of factors influencing the defect formation process, and it also makes it much harder to interpret the parameters of acoustic emission that characterize the state of the object under control. Objective. Study of filtering methods in case of extraneous influences to improve the reliability of the results of recording acoustic signals and improve the identification process. Methods. This article presents the results of the implementation of the developed method of cascade digital filtering. The method is based on high-frequency digital filters, approximated by a second-order Butterworth polynomial model. Amplitude, time, and frequency fragments of acoustic emission signals, which characterize the defect formation process during the manufacturing of products, are highlighted. A relationship between the measurements of the signal’s amplitude parameters, the laser power of the system, and the nitrogen content in the heat-resistant alloy is established. The dependence of the laser power and nitrogen content percentage is approximated using the least squares method and visualized based on a scatter plot. Results and conclusions. The developed relationship describes and characterizes the influence of the listed factors on the defect formation process, and its adequacy is confirmed by calculating the coefficients of determination and significance. It is shown that the application of the cascade filtering method for signal identification significantly increases the effectiveness of the acoustic emission method. The developed cascade filtering method can also be applied when studying the acoustic properties and stresses caused by the physical fields of various rocks. © 2025, National Academy of Sciences of the Republic of Kazakhstan. All rights reserved.

In the mining industry, when breaking rocks, oversized pieces are formed that exceed the dimensions of the technological equipment. To carry out secondary rock fragmentation in quarries, it is proposed to use an electromagnetic hammer. At the D.A. Kunayev Institute of Mining, a prototype of a mediumclass electromagnetic hammer with an impact energy of up to 6000 J has been developed. The use of the electromagnetic hammer for breaking oversized pieces in the mining industry will increase the efficiency, environmental friendliness, andautomation of the technological processes of rock and ore fragmentation. To develop a competitive prototype of a rock-breaking hammer, it is necessary to justify its dynamic parameters. A microprocessor-based measurement system was developed to measure the dynamic parameters of the prototype of the electromagnetic hammer, followed by the calculation of the energy characteristics of the prototype using the software “Matlab.” A digital sensor “HC-SR04” and a microprocessor controller “Arduino Mega 2560” were used to measure the height of the moving part of the electromagnetic hammer. To eliminate measurement errors, calculate the dynamics of the plunger’s velocity, acceleration and impact energy values, and plot the dependency graphs, the “Matlab” program version R2021b was used. Experiments were conducted by supplying the power voltage to the upper coil with a current value of 120 amperes, while the lower coils received the power voltage with current values of 70, 100, and 120 amperes. The data obtained, after processing in the “Matlab” software, allowed for the construction of dynamic parameter graphs for the prototype. The analysis of the graphs revealed the design flaws of this prototype, the elimination of which will improve the technological characteristics of new developments.

The objective of this study was to investigate the fundamental aspects of acrylic resin and zirconia nanoparticle interaction to analyze the optical properties and subsequent changes in refractive index with incremental loading of nanoparticles. Poly(methyl methacrylate) (PMMA) reinforced with zirconia nanoparticles were prepared by dip coating, spin coating and solvent casting techniques. An overall understanding of the polymer nanocomposite film has been achieved using the spectroscopic and morphological studies. The vital aspect of this whole study is to derive a simple yet an efficient nanocomposite film capable of imparting extraordinary optical properties. Within the limitations of this research a very crucial property of the material has been revealed. The RI as well as the optical transparency of the nanocomposite film has been steadily maintained with a significant increase of RI by the magnitude of 0.06 and ~100% light transmittance on incorporation of pure zirconia nanoparticles into PMMA matrix has been achieved. The best technique found was spin coating as it could yield thin films and better transparency and higher refractive index.

This study focuses on the chemical modification of the polysaccharides chitosan and gellan gum to produce water-soluble amphoteric polyelectrolytes. The modified polymers were used to stabilize gold nanospheres (AuNSs) and gold nanorods (AuNRs), whose structural and physicochemical properties were thoroughly characterized. The results confirmed successful polymer modification and effective stabilization of gold nanoparticles with suitable sizes and shapes for biomedical applications.