Arkhangelsk State Technical University

This research presents a comprehensive investigation of electromagnetic gearing systems for automotive powertrain applications, evaluating their potential to replace conventional mechanical automatic transmissions. Three fundamental electromagnetic architectures - Variable Volume Approach (VVA), Fixed Volume Approach (FVA or separate drive of individually magnetized ring), and Fixed Volume Approach Pole-based (FVAP) - are analyzed through five distinct design configurations employing harmonic and geometric sequencing. A rigorous analytical framework is developed to assess electromagnetic coupling dynamics, evaluating critical parameters including energy density, volumetric constraints, magnetic flux distribution, and torque transmission characteristics. Performance assessment using Gray Relational Analysis (GRA) reveals the FVAP configuration as superior (GRA grade: 0.95), demonstrating optimal torque density (3.01 MNm/m³ FEM) and specific torque (320-344 Nm/kg). Comparative analysis shows electromagnetic systems achieve 20–22 % higher specific torque than optimal range of mechanical planetary gears about (267–282 Nm/kg), though their volumetric torque density remains below conventional systems (3–5 MNm/m³). The study identifies key performance trade-offs: VVAH (0.72) and VVAG (0.68) deliver competitive torque but exhibit elevated flux leakage, while FVAG (0.58) and FVAH (0.64) show balanced but limited performance. The research highlights electromagnetic gearing as a transformative technology for weight-sensitive applications, offering inherent advantages including contactless operation, adaptive torque control, and reduced maintenance. Findings suggest these systems are particularly suitable for electric and hybrid vehicle architectures where power density and efficiency are critical. Future development pathways focus on advanced magnetic materials and superconducting implementations to bridge the volumetric performance gap. This work provides a foundational framework for next-generation transmission systems, establishing quantitative performance benchmarks and design guidelines for electromagnetic gearing in automotive applications.

For the first time, the current work has carried out a chemical treatment of a novel ligno-cellulose fiber that is extracted from the bark of an unexplored plant of Careya arborea. Careya arborea (CA), a flowering tree known for its green berries, thrives in the Indian subcontinent and Afghanistan. This research was focused on extracting fibers from the bark of the Cary tree for the first time to corroborate the influence of chemical treatment on its different characteristics. These CA fibers have a high proportion of cellulose, consisting of 71.17 wt percent, together with 27.86 wt percent of hemicellulose, and a reduced density of 1140 kg/m3, making them a suitable candidate for creating lightweight applications in a variety of industries. Chemical treatment has done on the cay fiber with the concentrations of NaOH 5 (wt%), 10 (wt%), and 15 (wt%) solution mixture to improve their characteristics. Estimated the difference between Chemically processed and non-processed Cary fibers and corroborated in results. We performed a number of experiments, including FTIR, XRD, SEM, EDAX, AFM, and TGA, to fully comprehend the changing properties. Chemical testing showed that cellulose changed from its non-crystalline state to cellulose, proving that the treatment was successful in changing the fibre structure. Additionally, the thermo-gravimetric examination showed higher thermal stability 248 °C–325 °C and a rise in the crystallinity index, indicating the treated fibers’ improved potential for high-temperature applications. The treated Cary fibers exhibited excellent surface properties, promising improved adhesion, mechanical performance, offering lightweight and sustainable solutions for diverse applications.

The ongoing research focuses on exploring the potential of Careya arborea (CA) fiber, banana fiber (BF), and epoxy composites as sustainable alternatives to petroleum-based products and synthetic fibers. The aim is to enhance the interfacial bonding and overall performance of these composites while reducing reliance on traditional materials. The study investigates the adhesion between CA fiber, BF (both chemically treated), and epoxy with polylactic acid (PLA) coating. Specifically, it examined how the PLA coating affects the mechanical properties, including tensile strength, flexural strength, impact resistance, and water absorption behavior, of the fabricated composites. Mechanical characterizations of the composite specimens are conducted following ASTM standards. The PLA-coated and NaOH-treated specimens significantly improved their tensile strength (20.56%) and flexural strength (16.7%), and significantly reduced their water absorption capacity (by 47.6%) compared to the untreated ones. These findings highlight the promise of using treated natural fibers and PLA coatings to create more sustainable and high-performance composite materials.

В статье разработана онтология самоочищающейся способности атмосферы от антропогенных загрязнителей и выявлено влияние на нее значимых факторов. По данным сайта https://rp5.ru, в созданной базе данных в СУБД MySQL рассчитаны и проанализированы среднегодовые и среднемесячные значения метеорологических показателей накопления загрязнения атмосферы (МПЗА), МПЗА2, МПЗА3, и показателей самоочищения атмосферы (ПСА), усовершенствованный метеорологический показатель атмосферы (УМПА) для крупных промышленных городов Ангарск, Братск, Иркутск с высоким уровнем загрязнения атмосферы за 2010-2023 годы. Показано, что с коэффициентом детерминации 95,8-99,9% вместо показателя МПЗА3 можно использовать более простой для вычисления МПЗА2, вместо сложного для вычисления показателя ПСА – применять показатель 1/МПЗА. В Иркутске в мае только в 7,1% случаев в атмосфере формируются благоприятные условия для рассеивания загрязнений, а в Ангарске и Братске благоприятных условий для их рассеивания нет.

The potential of memristive biosensors as an effective and dynamic link between engineering and biology, providing direct and functional communication for extracting information about biological processes in the human body, is discussed. Memristors can be part of a processing chain and, in the future, combine signal conversion with subsequent processing, acting as intelligent sensors. An energy-informational memristor model describing this nonlinear physical and technical effect and a parametric block diagram for describing such nonlinearity are proposed. To obtain a model of the nonlinear physico-technical effect of a memristor within the framework of the energy-informational model of circuits, a special functional dependence in the “charge-pulse” plane was revealed. It is noted that the memristive effect is observed not only in electrical circuits, but is also described for mechanical, thermal, diffusion, and optical circuits, which are well represented in terms of an energy-informational circuit model. The presented model of the memristive effect will expand the knowledge base of the computer-aided design system by including passports of memristive physical and technical effects. A classification of biosensors based on memristive effects is proposed, which will make it possible to supplement the knowledge bases of the computer-aided design system with passports of memristive physical and technical effects in accordance with this classification and parametric structural schemes of memristive physical and technical effects. The systematization of knowledge based on the identification of the characteristics and features of biosensors, as well as the classification of various types of memristors, will automate the process of choosing the most appropriate type of memristor, taking into account the required characteristics and features of the biosensor, which will lead to an increase in the efficiency of synthesis of new designs of memristive biosensors.