Energy Consumption Research Articles

A Regenerable Bi‐Based Catalyst for Efficient and Stable Electrochemical CO2 Reduction to Formate at Industrial Current Densities

AbstractRenewable electricity shows immense potential as a driving force for the carbon dioxide reduction reaction (CO2RR) in production of formate (HCOO−) at industrial current density, providing a promising path for value‐added chemicals and chemical manufacturing. However, achieving high selectivity and stable production of HCOO− at industrial current density remains a challenge. Here, we present a robust Bi0.6Cu0.4 NSs catalyst capable of regenerating necessary catalytic core (Bi−O) through cyclic voltammetry (CV) treatment. Notably, at 260 mA cm−2, faradaic efficiency of HCOO− reaches an exceptional selectivity to 99.23 %, maintaining above 90 % even after 400 h, which is longest reaction time reported at the industrial current density. Furthermore, in stability test, the catalyst was constructed by CV reconstruction to achieve stable and efficient production of HCOO−. In 20 h reaction test, the catalyst has a rate of HCOO− production of 13.24 mmol m−2 s−1, a HCOO− concentration of 1.91 mol L−1, and an energy consumption of 129.80 kWh kmol−1. In situ Raman spectroscopy reveals the formation of Bi−O structure during the gradual transformation of catalyst from Bi0.6Cu0.4 NBs to Bi0.6Cu0.4 NSs. Theoretical studies highlight the pivotal role of Bi−O structure in modifying the adsorption behavior of reaction intermediates, which further reduces energy barrier for *OCHO conversion in CO2RR.

Directed interactive topology optimization design for multi-agent affine formation maneuver control

This paper investigates the directed interactive topology optimization design problem for multi-agent affine formation maneuver control. Firstly, considering the optimization indexes such as information interaction cost and information spreading energy consumption, a directed topology optimization model satisfying affine formation maneuver is established, including two sub-models of topology structure construction and weight allocation. Secondly, aiming at the topological structure construction for affine formation maneuver, a directed k-rooted graph detection method is proposed, which can realize the solution of d +1 -rooted constraint for directed information interaction topology, and then an improved NSGA-II topological structure construction optimization algorithm is designed. Finally, a formation of seven agents in twodimensional space is taken as an example for simulation verification. The results show that the improved topology NSGA -II topology construction optimization The algorithm has better optimization effects, can effectively provide a variety of feasible directed interactive topologies for affine formation maneuver control, and the generated interactive topology can meet the requirements of directed d +1 -rooted graph.

Silage harvesting for small farms by using vacuum sealing in flexible polymer containers on a converted trailer

The article presents an analysis of milk production in Kazakhstan and identifies the reason for its low level, which is due to deficient feed, especially in small farms and in the private sector. The difficulty of saving the limited silage volume is due to the lack of preparation technology for preventing spoilage. The objective of this work is to complete the necessary equipment of a mobile tractor-trailer to reduce the specific energy consumption when preparing silage in flexible containers using a vacuum seal to increase the productivity of dairy cattle farming in smallholder and the private sector of the Republic. The basic rational parameters for sealing the silage by vacuum in the field on a mobile tractor-trailer for ease of transport and storage are obtained: silage weight in a flexible container – 769.6 kg, geometric dimensions of the sealed container by height (0.90 m), width (0.85 m) and length (0.85 m). The efficiency of the specific energy consumption of the proposed method for silage preparation is established at 35% compared with the traditional method. The recommended technology of silage preparation in flexible containers will be possible when conventional tractor-trailers are retrofitted with standard portable equipment (internal combustion engine-based (ICE) electric generator, vacuum pump, film welder).

Comprehensive technical analysis of post-combustion carbon capture and storage based on monoethanolamine absorption for petrochemical industry in Indonesia

Abstract The implementation of carbon capture and storage in the petrochemical industry is one of the means of decarbonization. This research focuses on a comprehensive technical analysis of the deployment of post-combustion carbon capture and storage based on monoethanolamine absorption in the petrochemical industry. The olefin complex petrochemical industry in Tuban, Indonesia, is the basis for the analysis, which includes a steam cracker, polyethylene, polypropylene, and raw pyrolysis gasoline hydrotreating units, with capacities of 1000, 940, 600, and 570 kilotons/year, respectively. The total energy consumption is about 16 024.53 GJ/h, and the CO2 emissions are about 1.6 megatons/year. Based on these plant systems, comprehensive technical analyses of the implementation of carbon capture and storage in that industry were performed using Aspen HYSYS® simulation software. Sensitivity analysis was carried out to determine the total CO2 captured, energy intensity, monoethanolamine consumption, and net CO2 captured in various scenarios based on the number of absorber column stages, absorption pressure, and desorption temperature. The CO2 storage site is about 100 km away and is transported by an onshore pipeline with a supercritical phase of CO2. The optimal net CO2 capture value is achieved by setting up a 50-stage absorber column with a pressure of 1 barg and a temperature of 110°C at the top of the desorber column, resulting in a CO2 capture yield of 86.4% and an energy intensity of 12.6 GJ/ton CO2. Under these conditions, the net CO2 captured in the scenario based on gas power plants’ electricity is 0.225 megatons/year, while in the scenario based on gas power plants incorporating 30% biomass electricity, it is 0.544 megatons/year. With increased use of renewable energy in carbon capture and storage facilities, more net CO2 is captured. This study can be applied to various cases of post-combustion carbon capture and storage implementation in the industrial sector, especially in the petrochemical industry.

Addressing governance challenges of digitalisation and sustainability: The case of central bank digital currency

AbstractDigitalisation and environmental sustainability are widely discussed topics. However, their nexus remains underexplored and can pose significant challenges for governments and industries alike. The environmental implications of digitalisation are becoming increasingly pertinent with the advent of central bank digital currencies (CBDCs) and their inherent energy consumption and production of e‐waste. On the other hand, digitalisation could potentially support sustainability efforts. This begs the question of how systems of governance, such as regulatory frameworks and internal organisational governance, should harmonise digitalisation and sustainability goals. Such harmonisation entails ensuring that digitalisation processes are environmentally responsible while exploring how the application and features of digitalisation can help achieve environmental goals. By drawing insights from the case study of CBDCs, this article will utilise the paradigm of adaptive governance to seek potential solutions to the environmental implications of digitalisation.

Cooling Performance of a Nano Phase Change Material Emulsions-Based Liquid Cooling Battery Thermal Management System for High-Capacity Square Lithium-Ion Batteries

This study investigated the application of nanophase change material emulsions (NPCMEs) for thermal management in high-capacity ternary lithium-ion batteries. We formulated an NPCME of n-octadecane (n-OD) and n-eicosane (n-E) with a mass fraction of 10%, whose phase change temperatures are 25.5 °C and 32.5 °C, respectively, with specific heat capacities 2.1 and 2.4 times greater than water. Experiments were conducted to evaluate the thermal control performance and latent heat utilization efficiency of these NPCMEs. The NPCMEs with an n-OD mass fraction of 10% (NPCME-n-OD), particularly reduced the battery pack’s maximum temperature and temperature difference to 41.6 °C and 3.72 °C under a 2 C discharge rate, lower than the water-cooled group by 1.3 °C and 0.3 °C. This suggests that nano emulsions with phase change temperatures close to ambient temperatures exhibit superior cooling performance. Increased flow rates from 50 mL/min to 75 mL/min significantly lowered temperatures, resulting in temperature reductions of 2.73 °C for the NPCME-n-OD group and 3.37 °C for the NPCME-n-E group. However, the latent heat utilization efficiency of the nano emulsions decreased, leading to increased system energy consumption. Also, it was found that the inlet temperature of the NPCMEs was very important for good thermal management. The right inlet temperatures make it easier to use phase change latent heat, while excessively high temperatures may make thermal management less effective.

Resource optimization of multi-UAV assisted communication system based on user scheduling

In order to improve the transmission rate of the multi-user mobile communication downlink wireless transmission system, a resource optimization method for multi-unmanned aerial vehicle (UAV) assisted communication system based on user scheduling and trajectory optimization is proposed. The proposed method establishes an optimization problem with the maximization of the total multi-user throughput as the criterion under the constraints of user scheduling, total energy consumption of UAVs and user service quality requirements. In order to solve this non-convex problem, the original non-convex problem is decomposed into three easy-to-handle non-convex sub-problems by using the block coordinate descent method (BCD). The sub-problems are transformed and solved by introducing slack variables, first-order Taylor expressions, continuous convex approximation (SCA) and other methods, and then alternately iteratively optimized to obtain an approximate suboptimal solution to the original non-convex problem. Simulation results show that the proposed algorithm can effectively improve the total system throughput and has good convergence in both single and multi-UAV communication systems.

Contribution-Based Resource Allocation for Effective Federated Learning in UAV-Assisted Edge Networks.

This paper considers UAVs as edge computing nodes and investigates a novel network resource allocation method for federated learning within a three-layer wireless network architecture containing cloud, edges (UAVs), and clients. To address the issue of fair bandwidth resource allocation among clients participating in federated learning, a contribution calculation strategy based on the Shapley value (SV) used as the weight for model aggregation is proposed. On this basis, a client selection and wireless resource allocation method based on model contribution is further designed. By reducing the training and aggregation frequency of the low-contribution clients during the asynchronous aggregation phase, the limited bandwidth resources are allocated to high-contribution clients, thus improving the convergence speed and accuracy of the global model. Simulation experiments demonstrate that the proposed method can significantly reduce the system delay and total energy consumption with gains between 15% and 50% while also improving the final accuracy of the global model by 0.3% and 2% on both short-term and long-term perspectives, respectively.

Incorporation of Phase Change Materials in Buildings

This review paper explores the integration of phase change materials (PCMs) in building insulation systems to enhance energy efficiency and thermal comfort. Through an extensive analysis of existing literature, the thermal performance of PCM-enhanced building envelopes is evaluated under diverse environmental conditions. This review highlights that PCMs effectively moderate indoor temperatures by absorbing and releasing heat during phase transitions, maintaining a stable indoor climate. This paper also delves into the detailed concepts of PCMs, including their classification and various applications within building insulation. It is noted that different types of PCMs have unique thermal properties and potential uses, which can be tailored to specific building requirements and climatic conditions. Furthermore, cost–benefit and environmental assessments presented in the reviewed studies suggest that incorporating PCMs into building materials offers significant potential for reducing energy consumption and mitigating environmental impacts. These assessments indicate that PCMs can lead to substantial energy savings by decreasing the reliance on heating and cooling systems, thereby lowering overall energy costs and carbon emissions. However, despite the promising outlook, this review identifies a need for further research to optimize PCM formulations and integration methods. This optimization is essential for overcoming current challenges and facilitating the widespread adoption of PCMs in the construction industry. Addressing issues such as long-term durability, compatibility with existing building materials, and cost-effectiveness will be crucial for maximizing the benefits of PCMs in enhancing energy efficiency and sustainability in buildings. Overall, this review underscores the transformative potential of PCMs in building insulation practices. By providing a comprehensive overview of PCM classifications, applications, and their impacts on energy efficiency and environmental sustainability, this paper lays the groundwork for future advancements and research directions in the field of PCM-enhanced building technologies.

Evaluation on tension-compression anisotropic behavior of recycled asphalt mixture

The utilization of recycled asphalt pavement (RAP) is the effective way to improve resource conservation and reduce energy consumption. The asphalt mixture is a kind of typical anisotropic pavement materials due to its heterogeneity in composition and microstructure. This could lead to the differences of mechanical response between the tensile and compressive direction. However, there are limited researches to study the effect of RAP on the tension-compression anisotropic behavior of asphalt mixture. The strength, modulus and fatigue resistance tests are carried out and different loading modes are adopted. The results show that the tension-compression anisotropic behavior is more prominent with the increase of RAP content. The regenerant served as a kind of typical additive could alleviate this effect. In addition, the result of dynamic modulus test shows that the tension-compression anisotropic behavior has an increasing trend with the decrease of frequency and the increment of temperature. The ranking of fatigue life is opposite for the direct tensile and compressive loading mode, and the fatigue life ratio of compression to tension also show positive relation with the RAP content. Due to the difference in the stress mode, the fatigue life between the indirect tensile loading and four-point bending loading also show opposite trend, and the indirect tensile fatigue life has a larger discreteness.

An adaptive meta-imitation learning-based recommendation environment simulator: A case study on ship-cargo matching

High-quality shipping is one of the effective ways for sustainable cities in inland river basins to improve transportation efficiency and reduce energy consumption. Currently, the biggest challenge faced by shipping is the high empty-ship rate, which makes it impossible to directly apply machine learning methods due to the cold-start problem. Although some researchers have tried to utilize deep reinforcement learning(DRL)-based recommendation that do not rely on manually labeled data to alleviate the cold-start problem, progress has been slow due to the lack of available training environment. Therefore, this paper introduces an adaptive meta-imitation learning-based recommendation environment simulator, termed AMIL-Simulator. Specifically, we construct a conditionally guided diffusion model to simulate shipowner behavior in a dynamically changing environment. Moreover, we propose a shipowner reward model based on adaptive meta-imitation learning, enabling the learning of shipowner rewards across multiple tasks, even when confronted with limited samples and imbalanced categories. By conducting extensive quantitative experimental evaluations and shipowner-cargo matching studies, the results demonstrate the effectiveness of AMIL-Simulator, particularly in smaller-scale and cold-start environments.

Performance of Windcatchers in Improving Indoor Air Quality, Thermal Comfort, and Energy Efficiency: A Review

The growing concerns over climate change and energy scarcity have highlighted the need for building energy conservation. Windcatchers, renowned for their effective ventilation capabilities, have emerged as a pivotal solution for saving energy and improving indoor thermal comfort. Serving as rooftop installations, windcatchers harness high-altitude airflow to provide fresh indoor air while expelling stale air. This comprehensive review encompasses over 96 studies published between 2000 and 2024, examining the performance of various types of windcatchers. The review reviews previous articles and concludes that using different types of wind catchers in hot and arid areas can increase indoor air velocity by about 10–50%, reduce building energy consumption by about 20–50%, and increase thermal comfort duration by about 25–50%. The article combines the perspectives of multiple disciplines such as architecture, environmental engineering, and sustainable design, providing a new perspective for the study of windcatchers. The article not only summarizes the design and performance of existing wind catchers, but also provides 13 suggestions for the design of wind capture towers, while also identifying areas for future research, such as combining wind capture machines with other passive cooling technologies and evaluating their performance under different climate and urban conditions.

Analysis of fly-around mission with spinning tether system for space station observation

This paper presents the mission scenarios of using spinning tether system to conduct space stations fly-around mission and validates its feasibility. The main challenge of fly-around mission lies in the difficulty of balancing low fuel consumption and long-term fly-around observation. To deal with this problem, a novel spinning tether system is proposed. Firstly, the fly-around process with spinning tether system is introduced, and the tether system is modeled based on Newton-Euler method with a novel description of spinning motion. Secondly, Given the unique structural limitations of space stations, two fly-around schemes and referenced fly-around trajectories are detailed. Thirdly, a backstepping controller is proposed for tracking the reference motion of fly-around satellites, and the fuel consumption among different fly-around schemes is compared and analyzed. In the end, numerical results validate that under the proposed control strategy, the spinning tether system can maintain a stable fly-around configuration in both the planar and vertical plane, the symmetrical formation configuration prevents the central space station from being affected by the motion of fly-around satellites. Moreover, energy consumption analysis indicates that tethered system can save 62.8 % of impulse compared to traditional schemes when flying in the planar plane, making it the most energy-efficient option.

Energy consumption analysis of trains based on multi-mode virtual coupling operation control strategies

Urban rail transit, as a main mode of travel, has always been concerned with the balanced relationship between energy consumption and transport efficiency. The advent of the virtually coupled train set (VCTS) has significantly enhanced the efficiency of existing railway lines. Both energy consumption and comfort during the operation of VCTS control technology have emerged as significant challenges for the development of VCTS since the inception of onsite testing. A review of the current research status of VCTS control systems has revealed that the majority of current formation control systems are focused on the safe operation of formation trains, the stability of train control systems, and safe train separation models. However, a case study has shown there is a strong correlation between train operating intervals, train control strategies, and train operating energy consumption. Therefore, it is necessary to design and plan the operation modes of formation trains for different train operation requirements. This paper presents four distinct control modes, developed through the integration of the most prevalent VCTS control strategies, operational modes, and operational requirements. The design of these control modes is guided by considerations of energy consumption, safety, and comfort during train operation. A case study of Beijing Subway Line 11 revealed a significant correlation between energy consumption, control mode, and safety under different control modes. In particular, the correlation between train running intervals and energy consumption in a high-precision tracking state provides valuable technical support for the future operation of VCTS technology in different periods, scenarios, and environments.

From roads to roofs: How urban and rural mobility influence building energy consumption

Understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.

Life cycle assessment of metal powder production: a Bayesian stochastic Kriging model-based autonomous estimation

Metal powder contributes to the environmental burdens of additive manufacturing (AM) substantially. Current life cycle assessments (LCAs) of metal powders present considerable variations of lifecycle environmental inventory due to process divergence, spatial heterogeneity, or temporal fluctuation. Most importantly, the amounts of LCA studies on metal powder are limited and primarily confined to partial material types. To this end, based on the data surveyed from a metal powder supplier, this study conducted an LCA of titanium and nickel alloy produced by electrode-inducted and vacuum-inducted melting gas atomization, respectively. Given that energy consumption dominates the environmental burden of powder production and is influenced by metal materials’ physical properties, we proposed a Bayesian stochastic Kriging model to estimate the energy consumption during the gas atomization process. This model considered the inherent uncertainties of training data and adaptively updated the parameters of interest when new environmental data on gas atomization were available. With the predicted energy use information of specific powder, the corresponding lifecycle environmental impacts can be further autonomously estimated in conjunction with the other surveyed powder production stages. Results indicated the environmental impact of titanium alloy powder is slightly higher than that of nickel alloy powder and their lifecycle carbon emissions are around 20 kg CO2 equivalency. The proposed Bayesian stochastic Kriging model showed more accurate predictions of energy consumption compared with conventional Kriging and stochastic Kriging models. This study enables data imputation of energy consumption during gas atomization given the physical properties and producing technique of powder materials.

Implementation of Regenerative Thermal Oxidation Device Based on High-Heating Device for Low-Emission Combustion

In this paper, a heating device is implemented by considering two large factors in a 100 cmm RTO design. First, when the combustion chamber is used for a long time with a high temperature of 750–1100 °C depending on the high concentration VOC gas capacity, there is a problem that the combustion chamber explodes or the function of the rotary is stopped due to the fatigue and load of the device. To prevent this, the 100 cmm RTO design with a changed rotary position is improved. Second, an RTO design with a high-heating element is implemented to combust VOC gas discharged from the duct at a stable temperature. Through this, low-emission combustion emissions and energy consumption are reduced. By implementing a high heat generation device, the heat storage combustion oxidation function is improved through the preservation of renewable heat. Over 177 h of demonstration time, we improved the function of 100 cm by discharging 99% of VOC’s removal efficiency, 95.78% of waste heat recovery rate, 21.95% of fuel consumption, and 3.9 ppm of nitrogen oxide concentration.

Thermal Bending Simulation and Experimental Study of 3D Ultra-Thin Glass Components for Smartwatches.

The heating system is an essential component of the glass molding process. It is responsible for heating the glass to an appropriate temperature, allowing it to soften and be easily molded. However, the energy consumption of the heating system becomes particularly significant in large-scale production. This study utilized G-11 glass for the simulation analysis and developed a finite element model for the thermal conduction of a 3D ultra-thin glass molding system, as well as a thermal bending model for smartwatches. Using finite element software, the heat transfer between the mold and the glass was modeled, and the temperature distribution and thermal stress under various processing conditions were predicted. The findings of the simulation, when subjected to a numerical analysis, showed that heating rate techniques significantly affect energy consumption. This study devised a total of four heating strategies. Upon comparison, optimizing with heating strategy 4, which applies an initial heating rate of 35 mJ/(mm2·s) during the initial phase (0 to 60 s) and subsequently escalates to 45 mJ/(mm2·s) during the second phase (60 to 160 s), resulted in a reduction of 4.396% in the system's thermal output and a notable decrease of 7.875% in the heating duration, respectively. Furthermore, a single-factor research method was employed to study the forming process parameters. By comparing the numerical simulation results, it was found that within the temperature range of 615-625 °C, a molding pressure of 25-35 MPa, a heating rate of 1.5-2.5 °C/s, a cooling rate of 0.5-1 °C/s, and a pulse pressure of 45-55 Hz, the influence on residual stress and shape deviation in the glass was minimal. The relative error range was within the 20% acceptable limit, according to the experimental validation, which offered crucial direction and ideas for process development.

Elliptic curves cryptography for lightweight devices in IoT system

The Internet of Things (IoT) is revolutionizing industries by connecting billions of devices, ranging from home appliances to industrial machines, to the internet. This transformation enables unprecedented automation, data collection, and process optimization. However, the widespread adoption of IoT also introduces significant security challenges, especially for lightweight devices with limited computational power and energy resources. Ensuring secure communication and data integrity in such constrained environments is critical. This paper explores and compares the performance of implemented algorithms within IoT devices. A comparison between Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) implementations is made to identify a lightweight, secure, and efficient solution for IoT environments. Our results indicate that ECC outperforms RSA in terms of memory requirements, overall energy consumption, key sizes, signature generation time, key generation and execution time, and decryption time in a resource-constrained environment. However, RSA performs better in signature verification and encryption.

Application of DEA Models to Develop Strategies for Improving the Energy Efficiency of National Economies: Focusing on SDGs and Best Practices in European Countries

Objective: This study aims to develop a strategy for improving the energy efficiency of national economies through the application of DEA (Data Envelopment Analysis) models. The research focuses on adopting the best practices from European countries in the context of SDGs. Theoretical Framework: The research is grounded in the framework of sustainable development and energy efficiency, focusing on the UN Sustainable Development Goals (SDG 12). DEA models are utilized to assess energy efficiency across various European economies, considering economic, environmental, and energy-related factors. Method: DEA models were applied to assess energy efficiency by analyzing input variables such as energy intensity, CO₂ emissions, and energy consumption. The model used a comparative analysis of 38 European countries, with special attention to the weights (λ) in the VRS model, allowing for variable returns to scale. The data were sourced from Eurostat and the World Bank. Results and Discussion: The results indicated that countries like Ireland and Albania serve as key reference units for Ukraine, highlighting the effectiveness of transitioning to renewable energy sources and reducing dependence on fossil fuels. The analysis demonstrated that inefficient countries could improve their performance by following the strategies of their reference units, specifically in reducing energy consumption and emissions. Research Implications: The study provides practical insights into how less efficient countries, like Ukraine, can enhance their energy policies by adopting successful practices from European nations, ultimately contributing to global sustainability goals. Originality/Value: This research contributes to the literature by offering a structured methodology for enhancing energy efficiency in national economies through DEA modeling. It emphasizes the significance of renewable energy in sustainable development and presents a comparative framework applicable to a broad range of countries.