Computer modelling is increasingly essential for advancing the practice of the most widespread and efficient basic oxygen furnace (BOF) steelmaking process. An urgent problem in the BOF process is the need for greater durability of the refractory lining in the top-blown converter. One of the most advanced methods of hot repair for the converter lining is the inter-melting slagging technology for refractories, with a durable skull coating. An essential task in implementing the progressive slag-splashing process is ensuring proper and stable durability of the slag-splashing lances used. A mathematical model of the thermal regime of the top water-cooled slag-splashing lance barrel during the hot repair operation of the converter lining by the slag-splashing method has been developed. The regularities of heat transfer and temperature changes in the outer pipe of the slag-splashing lance for two primary forms of blast devices, operated under technological conditions of lining slagging in top-blown converters with typical capacities of 160 tonnes and 250 tonnes, are numerically investigated. Regression dependencies for estimating the thermal regime of the slag-splashing lance barrel at different cooling water flow rates have been obtained. The results obtained are used to design a slag-splashing lance and to develop its operating technology during hot repair of the lining of a 250-tonne top-blown converter with the use of the slagging method. The results contribute to the development and improvement of automated design systems, the modernisation of slag-splashing lances, and the control of BOF steelmaking. They also contribute to the development and improvement of automated design and modernisation systems, as well as to the solution of optimisation and predictive analysis problems for the thermal regime of slag-splashing lances in the context of BOF steelmaking control.
Due to harmful emissions from vehicles on fossil fuels, rising prices for petroleum products and natural gas, the use of electric vehicles is on the rise. The rapid growth of electric vehicle production will ultimately satisfy these problems in cities. Outside the city, it is advisable to develop intercity electric transport, primarily rail, which can significantly reduce the cost of passenger and freight transportation. The paper considers the possibility of using switched reluctance motors in the traction drives of railway locomotives to replace less efficient, outdated direct current motors. It was designed in a direct current motor housing to study the static characteristics of the switched reluctance traction motor. A simulation model of a switched reluctance motor was developed, and its static characteristics were calculated at various supply voltages and load torque when operating in traction electric drives of railway transport. A comparison of the traction, mechanical and energy characteristics of a switched reluctance motor and a direct current traction motor at different supply voltages was carried out to assess the efficiency of its application. With this approach, as with direct current motors, the supply voltage of the switched reluctance motors was regulated by changing the wiring diagram. An algorithm for controlling the switched reluctance motor through pulse-width modulation of its phase voltage to form a family of traction characteristics is proposed. The study results showed that the proposed approach to regulating the rotation speed of the switched reluctance motor allows for the formation of the required number of traction characteristics and, if necessary, for performing stepwise or smooth transitions between them to regulate the vehicle speed. The results indicate the efficiency of switched reluctance motors in direct current traction electric locomotives.
One of the most essential characteristics of a complex technical system is that it performs ‘an important useful function only with the assistance of a human operator and standard infrastructures…’ [1]. At the earliest stages of the development of a system, deciding whether the human operator should be regarded as part of the complex system or an external entity is necessary. In most cases, the human operator should be treated as an external entity.Most complex technical systems cannot function without the active involvement of a human operator, who retains responsibility for decision-making, control, and management functions. From a functional standpoint, operators can be considered an integral part of the system. However, the system designer rarely possesses sufficient authority over the operator to incorporate them fully into the system’s design. From the perspective of the systems engineer, the human operator instead represents an element of the system’s environment.Under this paradigm, the systems engineer must devote particular attention to the design and development of the operator interface, which is a critically important aspect of any complex technical system [2]. Accordingly, the development of universal technical solutions that enhance the quality of the human–machine interface in complex technical systems represents both a significant and timely challenge, the resolution of which can be applied across a wide range of practical applications.The primary objective of the present work is to improve the performance of the human–machine interface by compensating for the inertial and nonlinear characteristics of the human operator as a control element within a complex technical system.
Modelling heat and mass transfer processes is essential in designing and optimising technological processes in power engineering, mechanical engineering, metallurgy, chemical industry, and other engineering fields. For the mathematical description of such processes, differential equations of heat conduction and diffusion are used, the solution of which requires the application of efficient numerical methods, especially in the case of complex geometries and diverse boundary conditions. This study presents a unified methodology for the numerical solution of boundary value problems of heat conduction with internal heat sources, based on locally one-dimensional implicit finite difference schemes derived using the integral-interpolation method (balance method) in Cartesian and cylindrical coordinate systems. Special attention is given to discretising boundary conditions of the first, second, and third kinds, focusing on Robin conditions, the most commonly encountered in engineering practice. A quasi-linear approximation scheme and spatial splitting schemes are recommended to increase the efficiency of numerical solutions. This approach enables the application of the unconditionally stable Tridiagonal Matrix Algorithm (TDMA). The introduction of indica-tor coefficients provides flexibility in implementation, allowing the balance equation to be used variably by manipulating the terms responsible for heat fluxes and the location of com-putational nodes. This ensures ease of implementation and improves code readability, facili-tating software development for computational modelling. The results of the numerical simu-lation obtained using the proposed method are compared with known analytical and numerical solutions and demonstrate high accuracy. The proposed methodology opens broader opportu-nities for modelling thermal regimes in complex engineering systems.
Digital transformation (DT) in the energy sector is pivotal in meeting energy transformation challenges. DT is reshaping energy production, distribution, and consumption by integrating advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, and digital twins. While existing research has extensively documented individual technological applications, there remains a significant gap in understanding how these technologies interact synergistically in real-world implementations [11]. Comprehensive analyses comparing digital transformation outcomes across different socioeconomic contexts are limited, particularly regarding the scalability of swarm electrification models. These technologies collectively address the ‘three Ds’ – decentralisation, decarbonisation, and digitalisation – essential for the evolution of modern energy systems. By leveraging these innovations, the sector can significantly enhance efficiency, optimise renewable energy integration, and expand access to underserved regions.One of the most impactful applications of DT is in the realm of decentralised energy systems, exemplified by swarm electrification. This concept, pioneered by Groh et al [3], utilises interconnected solar home systems (SHSs) to form scalable microgrids that evolve from standalone setups to full integration with national grids. These systems empower communities by facilitating energy sharing, reducing operational costs, and creating new income streams. Case studies from Kenya, Madagascar, Yemen, Germany, and Bolivia demonstrate the real-world success of swarm electrification in bridging the energy access gap while advancing sustainability goals.AI plays a pivotal role in digital energy systems by enabling predictive maintenance, optimising energy flows, and improving system reliability. Algorithms analyse vast datasets in real time to forecast energy demand, detect anomalies, and automate grid management. IoT further complements AI by providing the physical infrastructure to gather and transmit data, enabling real-time monitoring and control of energy assets. Together, AI and IoT support the development of smart grids and energy communities, fostering greater flexibility and resilience in energy networks.Blockchain technology is emerging as a transformative tool for energy trading and distribution. By enabling peer-to-peer (P2P) energy markets, blockchain enhances transparency and reduces transaction costs. This decentralisation of energy trading allows consumers to become prosumers, actively participating in energy production and exchange. Projects such as Esmat et al. decentralised platforms exemplify how blockchain empowers individuals and communities to take ownership of their energy futures while ensuring security and scalability.Despite these advancements, the implementation of digital technologies in energy systems is facing significant challenges. High initial costs, the complexity of integration, and cybersecurity risks pose barriers to widespread deployment. Furthermore, the digital divide in underserved regions limits equitable access to these transformative solutions. Environmental concerns related to the energy consumption of digital infrastructures, such as data centres and blockchain networks, also require attention. Addressing these issues necessitates a multi-stakeholder approach involving policymakers, industry leaders, and researchers to create enabling environments for innovation.This review provides a comprehensive analysis of the role of DT in advancing energy systems, focusing on AI, IoT, blockchain, and swarm electrification. It synthesises insights from over 100 scholarly sources, including real-world case studies, and evaluates the social, economic and technological impact of digitalisation on energy systems. The study adopts a mixed-method approach, integrating literature analysis, quantitative modelling, and case study evaluations to provide actionable insights for policymakers and industry practitioners.The findings of this review highlight the transformative potential of DT in addressing energy challenges, particularly in achieving the United Nations Sustainable Development Goal 7 [2]: universal access to affordable, reliable, and modern energy. By adopting digital innovations, energy providers can enhance operational efficiency, integrate renewable energy sources, and support community-based energy initiatives. The concept of swarm electrification exemplifies how decentralised approaches can complement centralised grids, ensuring scalability and adaptability to local needs.Policy recommendations emphasise the need for financial incentives, capacity-building programmes, and regulatory frameworks to facilitate digital adoption. Investment in human capital is particularly critical, as skilled personnel are required to implement and manage complex digital systems. International cooperation and knowledge sharing are essential to ensure digital transformation efforts align with global sustainability goals.In conclusion, DT represents a paradigm shift in energy systems, offering solutions to some of the sector’s most pressing challenges. Realising its full potential requires overcoming technical, financial, and institutional barriers. This review underscores the importance of a collaborative, multidisciplinary approach to harnessing the power of digital technologies for sustainable energy transitions.
