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The burning chamber wall of the ramjet engine is facing an extremely thermal environment during normal conditions. Thermal protection measures must be taken on the wall surface of the combustion chamber. At the same time, the aircraft faces high-power electrical demand problems under high-speed cruising states. To address these issues, a second fluid-closed Brayton cycle system was introduced in this paper. Helium was utilized as the secondary fluid medium, while kerosene was used as the final heat sink. The ramjet engine chamber wall was cooled by the helium cycle system. At the same time, part of the heat absorbed by the helium cycle was transformed into electric power by a generator. This work proposes a new method of thermal management in a closed cycle. Unlike traditional methods, this proposal can regulate the mass flow rate of helium based on the requirement of heat load. A zero-dimensional numerical calculation method was established for thermodynamic analysis. The results show that as the equivalence ratio of 0.8~1.5 for the kerosene flow rate, the system can suffer the thermal load of 200~350 kJ/kg on the combustion chamber wall at the maximum kerosene allowable temperature. To ensure the normal operation of the circulating system, the mass flow ratio between the helium and the air changes from 0.02 to 0.045. Compared with the direct kerosene cooling method, the second fluid circulation method leads to the kerosene equivalent saving ratio by 2% to 14%; at the same time, such a system could generate 160~500 kJ/kg of electrical energy. This new thermal management method can achieve kerosene saving, electric power generating and suffering more thermal loads under the premise of satisfying normal work. Full article

Magnetic levitation (maglev) offers unique opportunities for guided transport; however, only a few existing maglev systems have demonstrated their potential benefits. This paper explores the potential of maglev-derived systems (MDS) in conventional rail, focusing on the use of linear motors to enhance freight operations. Such traction boosters provide additional propulsion capabilities by reducing the train consist’s dependence on wheel–rail adhesion and improving performance without needing an additional locomotive. The study analyses the Gothenburg–Borås railway in Sweden, a single-track, mixed-traffic line with limited capacity and slow speeds, where installing linear motors on uphill sections would allow freight trains to match the performance of passenger trains, even under challenging adhesion conditions. Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. The results show that freight trains can achieve desired speeds but at the cost of increased energy consumption. A system-level cost–benefit analysis reveals a positive impact with a positive benefit-to-cost ratio. Although energy consumption increases, the time savings and reduced CO₂ emissions from shifting goods from road to rail demonstrate substantial economic and environmental benefits, improving the efficiency and sustainability of rail freight traffic. Full article

Small air-launched unmanned aerial vehicles (UAVs) face challenges in range and endurance due to their compact size and lightweight design. To address these issues, this paper introduces a multi-phase wind energy harvesting trajectory planning method designed to optimize the onboard electrical energy consumption during rendezvous and formation flight of air-launched fixed-wing swarms. This method strategically manages gravitational potential energy from air-launch deployments and harvests wind energy that aligns with the UAV’s flight speed. We integrate wind energy harvesting strategies for single vehicles with the spatial–temporal coordination of the swarm system. Considering the wind effects into the trajectory planning allows UAVs to enhance their operational capabilities and extend mission duration without changes on the vehicle design. The trajectory planning method is formalized as an optimal control problem (OCP) that ensures spatial–temporal coordination, inter-vehicle collision avoidance, and incorporates a 3-degree of freedom kinematic model of UAVs, extending wind energy harvesting trajectory optimization from an individual UAV to swarm-level applications. The cost function is formulized to comprehensively evaluate electrical energy consumption, endurance, and range. Simulation results demonstrate significant energy savings in both low- and high-altitude mission scenarios. Efficient wind energy utilization can double the maximum formation rendezvous distance and even allow for rendezvous without electrical power consumption when the phase durations are extended reasonably. The subsequent formation flight phase exhibits a maximum endurance increase of 58%. This reduction in electrical energy consumption directly extends the range and endurance of air-launched swarm, thereby enhancing the mission capabilities of the swarm in subsequent flight. Full article

The safety of 18650 lithium-ion batteries is critical for the reliability and durability of electric vehicles, especially as interest in sustainable transportation grows. Battery failures, such as fires or explosions, pose significant risks to both users and manufacturers, highlighting the need for advanced power systems. This study used finite element method (FEM) simulations and crash tests to evaluate battery safety in accident scenarios. The results showed that mechanical damage, especially from collisions, can cause internal short circuits, increasing the risk of thermal runaway, especially when combined with high temperatures during normal operation or charging. This can be caused by mechanical damage to the battery causing a change in the distance inside the battery, causing it to short circuit. The results highlight the importance of designing battery systems that prevent internal short circuits, especially under extreme conditions, and the need for continuous monitoring of battery parameters to detect early signs of failure. In the context of improving battery safety, the battery not only saves lives, but also extends vehicle life, reduces electronic waste, and increases energy efficiency, which is consistent with global efforts to minimize the environmental impact of technology and promote safer transportation. Full article

The regional imbalance of power supply and use is an important factor affecting the efficient and sustainable development of China’s power system. It is necessary to achieve the better matching of power supply and use through the optimization of the national power network layout. From a mathematical point of view, the power network layout’s optimization is a typical mixed-integer non-linear programming problem. The present paper proposes a novel method based on the Random Walk algorithm with Compulsive Evolution for China’s power network layout optimization to improve the network economy. In this method, the length of transmission lines and the amount of cross-regional power transmission between nodes are synchronously optimized. The proposed method was used to find the minimum total cost (TC) of the power transmission network on the basis of energy supply and use balance. The proposed method is applied to the optimization of power network of different scales. Results indicated that, compared with the optimization method that only optimizes the transmission line length, the TC of municipal and provincial power grids can be significantly reduced by the recommended methods. Moreover, for the national power network, through simultaneous optimization, the TC savings in 30 years of operation are significant. Full article

The advent and application of biophilic architecture bring numerous environmental, economic, and energy-efficiency benefits, playing a crucial role in advancing low-carbon, energy-saving, healthy, comfortable, and sustainable development within the construction industry. Thanks to its many advantages—such as aesthetic enhancement, improved microclimates, and negative carbon potential—biophilic architecture has been widely adopted in building design, particularly as a response to the escalating environmental crisis. Integrating plants with various architectural forms can optimize building performance, especially by reducing operational energy consumption. This study uses knowledge mapping tools like CiteSpace 6.1.R3 and VOSviewer 1.6.19 to analyze 2309 research papers from the Web of Science (WoS) published over the past decade on the topic of “energy efficiency in biophilic architecture”. It conducts visual analyses of publication trends, collaborative networks, and key themes. The research categorizes plant–architecture integration methods, focusing on three primary areas: green roofs, vertical green systems, and green photovoltaic systems. Additionally, it reviews the ways in which biophilic architecture contributes to energy savings, the research methodologies employed, energy-saving rates, and the factors influencing these outcomes. Finally, a SWOT framework is constructed to assess the strengths, weaknesses, opportunities, and potential threats of biophilic architecture, as well as its future development prospects. The findings indicate that integrating plants with building roofs is an effective energy-saving strategy, achieving energy savings of up to 70%. Furthermore, combining biophilic elements with photovoltaic systems can enhance the efficiency of solar energy generation. This study offers valuable insights for architects and researchers in designing more energy-efficient and sustainable buildings. Full article

To address global warming challenges, industry, transportation, residential, and other sectors must adapt to reduce the greenhouse effect. One promising solution is the use of renewable energy and energy-saving mechanisms. This paper analyzes several renewable energy sources and storage systems, taking into consideration the possibility of integrating them with smart homes. The integration process requires the development of smart home energy management systems coupled with renewable energy and energy storage elements. Furthermore, a real-life solar energy power plant composed of programmable components was designed and mounted on the roof of a single-family residential building. Based on a long-term analysis of its operation, the main advantages and disadvantages of the proposed implementation solution are highlighted, exemplifying the concepts presented in the paper. Being composed of programmable components, which allow the implementation of custom algorithms and monitoring applications to optimize its operation, the system will be used as a prototyping platform in future research. The evaluation of the developed system over a period of one year showed that, even when using a basic implementation such as the one in this paper, significant savings regarding a household’s energy consumption can be achieved (36% of the energy bought from the supplier, meaning EUR 545 from a total of EUR 1497). Finally, based on the analysis of the developed prototype system, the main technical challenges that must be addressed in the future to efficiently manage renewable energy storage and use in today’s smart homes were identified. Full article

In the face of increasing environmental challenges, carbon emissions from industrial parks have become a global focal point, particularly as electricity consumption serves as a major source of carbon emissions that requires effective management. Despite proactive efforts by governments and industry stakeholders to transition industrial parks toward cleaner production methods, traditional energy management systems exhibit significant limitations in data collection, real-time monitoring, and intelligent analysis, making it difficult to meet the urgent demands for carbon reduction. To address these challenges, this study proposes a carbon data management approach for industrial parks based on digital twin technology and develops an intelligent system that integrates monitoring, environmental surveillance, energy management, and carbon emission monitoring. The system supports efficient energy-saving and carbon-reducing decision making by real-time collection of energy consumption data. By incorporating Building Information Modeling (BIM) and Internet of Things (IoT) technologies, the system facilitates the integration and visualization of multi-source data, significantly enhancing the transparency of carbon data. The results of the carbon reduction validation system demonstrate that the application of this platform and its associated facilities can significantly reduce carbon emissions in the park, providing robust support for the transition of industrial parks toward low-carbon and sustainable development. Full article

The rising popularity of UAVs and other autonomous control systems coupled with real-time operating systems has increased the complexity of developing systems with the proper robustness, performance, and reactivity. The growing demand for more sophisticated computational tasks, proportionally larger payloads, battery limitations, and smaller take-off mass requires higher energy efficiency for all avionics and mission computers. This paper aims to develop a technique for experimentally studying the indicators of reactivity and energy consumption in a computing platform for unmanned aerial vehicles (UAVs). The paper provides an experimental assessment of the `Boryviter 0.1’ computing platform, which is implemented on the ATSAMV71 microprocessor and operates under the open-source FreeRTOS operating system. The results are the basis for developing algorithms and energy-efficient design strategies for the mission computer to solve the optimization problem. This paper provides experimental results of measurements of the energy consumed by the microcontroller and estimates of the reduction in system energy consumption due to additional time costs for suspending and resuming the computer’s operation. The results show that the `Boryviter 0.1’ computing platform can be used as a UAV mission computer for typical flight control tasks requiring real-time computing under the influence of external factors. As a further work direction, we plan to investigate the proposed energy-saving algorithms within the planned NASA F’Prime software flight framework. Such an investigation, which should use the mission computer’s actual flight computation load, will help to qualify the obtained energy-saving methods and their implementation results. Full article

In this work, we develop a detailed analysis of the current outlook for electric vehicle charging technology, focusing on the various levels and types of charging protocols and connectors used. We propose a charging station for electric cars powered by solar photovoltaic energy, performing the analysis of the solar resource in the selected location, sizing the photovoltaic power plant to cover the demand completely, and exploring different configurations such as grid connection or physical and virtual electric energy storage. Despite the current development applying for specific working conditions, operating voltage, charging rate, power demand, etc., the proposed configuration is modular, adaptable, and resilient. The simulated system operates within the 360 V to 800 V range of direct current for charging the electric vehicles, with a selectable power range between 20 and 180 kW. The basic layout includes four charging poles, each servicing all working voltages. An oversized PV plant powers the charging station at any time of the year, saving money compared to the alternative of the electric storage unit. In addition, we build simulation tools and algorithms that optimize the design of future projects, providing a solid basis for sustainable energy infrastructure planning and design. Full article

This study aims to improve the microclimate conditions in a mechanically ventilated broiler house by proposing and evaluating a ventilation-control algorithm based on heat-energy balance analysis. The new algorithm is designed to optimise the ventilation-rate requirement and thereby improve control of the indoor temperature. The analysis of one year of operational data collected at the experimental farm indicates that the current ventilation-control system successfully maintained optimal indoor temperatures for 74% of the time. In contrast, the proposed algorithm has the potential to improve this number significantly (up to 92%). The new algorithm was implemented and evaluated at two broiler houses (control and experimental) starting from day 20 to day 34 during one rearing period under high-temperature conditions. The results confirm that the new algorithm effectively reduced indoor temperatures by 1.5–2 °C during the day, which reduces heat stress significantly. Even though cooling pad usage increased to about eight times, the reduction in tunnel fan usage (to about 52%) led to significant energy savings. Furthermore, broiler mortality was reduced by 16.5%, which means there is also potential for improved productivity. The proposed ventilation control algorithm can effectively enhance microclimate conditions and energy efficiency in broiler production, though longer-term studies are required to fully assess its impact on growth performance. Full article

Worldwide, populations face issues related to water and energy consumption. Water scarcity has intensified globally, particularly in arid and semiarid regions. Projections indicate that by 2030, global water demand will rise by 50%, leading to critical shortages, further intensified by the impacts of climate change. Moreover, wastewater treatment needs further development, given the presence of persistent organic pollutants, such as dyes and pharmaceuticals. In addition, the continuous increase in energy demand and rising prices directly impact households and businesses, highlighting the importance of energy savings through effective building insulation. In this regard, tannin-furanic foams are recognized as promising sustainable foams due to their fire resistance, low thermal conductivity, and high water and chemical stability. In this study, tannin and lignin rigid foams were explored not only for their traditional applications but also as versatile materials suitable for wastewater treatment. Furthermore, a systematic approach demonstrates the complete replacement of the tannin-furan foam phenol source with two lignins that mainly differ in molecular weight and pH, as well as how these parameters affect the rigid foam structure and methylene blue (MB) removal capacity. Alkali-lignin-based foams exhibited notable MB adsorption capacity (220 mg g⁻¹), with kinetic and equilibrium data analysis suggesting a multilayer adsorption process. The prepared foams demonstrated the ability to be recycled for at least five adsorption-desorption cycles and exhibited effective flame retardant properties. When exposed to a butane flame for 5 min, the foams did not release smoke or ignite, nor did they contribute to flame propagation, with the red glow dissipating only 20 s after flame exposure. Full article

Current energy-saving lighting control algorithms often face the dilemma of local optimality, which limits the energy-saving potential and comfort improvement of indoor lighting systems. The control parameters of the lighting system are optimized using a genetic simulated annealing algorithm to achieve the global optimal solution and enhance energy-saving efficacy in indoor lighting. The local search ability of the algorithm is enhanced by simulated annealing processing of excellent individuals after genetic operation. The genetic probability is adaptively adjusted according to the number of iterations and the fitness of the population, so that the algorithm enriches the population diversity in the early stage and avoids the “premature” convergence of the algorithm. A lamp illuminance model based on an artificial neural network and an indoor natural illuminance model based on a workbench are proposed to evaluate the lighting comfort, which provides a basis for constructing the fitness function of the optimization algorithm. Through the simulation experiment, the genetic simulated annealing algorithm is applied to the lighting scene introduced in this paper and compared with the traditional particle swarm optimization algorithm and genetic algorithm, the lighting energy saving performance is significantly improved. Full article

This article presents the issue of energy waste in manufacturing processes, focusing on reducing unnecessary energy consumption and CO₂ emissions. A significant challenge in modern production is identifying and minimizing energy waste, which not only increases operational costs but also contributes to environmental degradation. An improvement methodology referred to as 2E-DAmIcS is proposed. A distinguishing feature of the methodology is a risk map of energy waste in the production process. Application of the methodology is demonstrated using the example of a lead–acid battery production process. It is shown that even small but well-diagnosed changes to the process make it possible to significantly reduce energy consumption. The proposed methodology offers practical tools for managers and decision-makers in various industries to systematically identify and minimize energy waste. It highlights the importance of cross-disciplinary collaboration among specialists in technology, energy consumption, and statistical analysis to optimize energy use. By applying this approach, companies can achieve both financial savings and environmental benefits, contributing to more sustainable production practices. Full article

The heating energy consumption in public buildings in cold regions is notably significant, presenting substantial scope for energy savings and emission reductions. Flexible loads can actively participate in controlling the operation of the power grid, improving the energy utilization and the economy of the system. This study introduces flexible loads into the operation optimization of energy systems, establishing mathematical models for flexible thermal and electrical loads. A two-stage operation optimization method is proposed: the first stage simulates the starting and stopping control conditions of equipment at varying temperatures and times, selecting the optimal time period to regulate the thermal loads; the second stage employs a multi-objective particle swarm optimization algorithm to optimize the scheduling of the system’s electrical load. Finally, an empirical analysis is carried out in a public building in Shenyang City as an example, and the results indicate that optimal scheduling of flexible thermal and electrical loads reduces the daily operating cost of the energy supply system by RMB 124.12 and decreases carbon emissions by 22.7%. Full article