Search Results (20,928)

With the rapid growth of the low-altitude economy, the number of unmanned aerial vehicles (UAVs) has grown rapidly. It is challenging to plan substantial UAV trajectories in complex urban low-altitude airspace, considering the airspace capacity, inter-vehicle safety, and communication reliability. To deal with this challenge, we propose a dual-scale grid-based trajectory planning approach that separates the global routing and local refinement. Specifically, we discretize the three-dimensional airspace into coarse macro-grids for capacity-constrained routing and high-quality communication-aided fine micro-grids for collision-free trajectory refinement. Both consider an altitude-dependent energy model. To handle the complex dual-scale grid trajectory planning of UAVs, we propose a priority-driven dual-grid Theta* with adaptive relaxation (DGTAR) to balance the global planning efficiency and local obstacle avoidance accuracy. First, we design a priority-driven capacity allocation mechanism to enforce safe separation among UAVs. Then, a combined planner is proposed, which integrates a Theta*-enhanced global search with a sampling-based refinement algorithm, invoking on-demand boundary relaxation to ensure the feasibility. Simulation results reveal that the proposed method DGTAR achieves reductions in many aspects compared with benchmark mechanisms, while maintaining a high planning success rate in congested scenarios. Full article

This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption in selected stages of agricultural transport equipment component production. The research focused on manufacturing companies from the agricultural machinery sector, characterized by high energy intensity and operational complexity. The empirical study was conducted among 121 experts representing manufacturing enterprises. The results indicate that enterprises achieve the highest level of implementation in organizational and Lean Manufacturing-related activities, particularly in reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technological and investment-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, remain implemented to a significantly lower extent. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The study confirms the multidimensional nature of energy efficiency and highlights the importance of integrating Lean Manufacturing principles with digital technologies and systemic energy management. The proposed research model may serve as a practical diagnostic tool supporting the identification of key improvement areas for sustainable production development in manufacturing enterprises. This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption at selected stages of agricultural transport equipment component manufacturing. The research focused on manufacturing companies operating in the agricultural machinery sector, which is characterized by high energy intensity and operational complexity. The empirical study involved 121 experts representing manufacturing enterprises. The results indicate that organizational and Lean Manufacturing-related practices exhibit the highest levels of implementation, particularly those aimed at reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technology-intensive and capital-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, show substantially lower implementation levels. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The findings confirm the multidimensional nature of industrial energy efficiency and highlight the importance of integrating Lean Manufacturing principles with digital technologies and systematic energy management. The proposed research model may serve as a practical diagnostic tool for identifying key areas for improvement in the development of sustainable manufacturing. Full article

This study investigates the aerodynamic and thermal impacts of tire sidewall cooling fins on a passenger vehicle using high-fidelity computational fluid dynamics (CFD) simulations. Continuous heat accumulation from tire rotation and road friction can degrade structural durability. To address this thermal challenge, a parametric study was conducted on the DrivAer notchback vehicle model across various fin angles from −67.5° to 67.5°. The results revealed a distinct design space that offers simultaneous aero-thermal improvements. Specifically, the 22.5° fin configuration demonstrates a dual-benefit performance, achieving a 3.79% net reduction in overall vehicle drag alongside a 17.36% increase in the average heat transfer coefficient (HTC). Conversely, the −22.5° configuration yields the maximum cooling enhancement with a 30.49% increase in average HTC but incurs a 2.52% drag penalty. Microdrag and Turbulent Kinetic Energy (TKE) analyses successfully explain the underlying fluid mechanisms governing these trade-offs. These findings provide practical design guidelines for flow control on rotating wheels, showing that tire sidewall geometries can enhance full-vehicle aerodynamic efficiency and tire thermal reliability. Full article

To address the challenge that microelectromechanical system (MEMS) gyroscope electrostatic force-modulated closed-loop self-excited driving circuits experience significant dynamic variations in capacitive load and driving demand under different operating conditions, such as start-up, steady-state resonance maintenance, and environmental perturbations, making it difficult to simultaneously achieve strong driving capability, stable oscillation, and low power consumption, this paper proposes a high-energy-efficiency adaptive output operational amplifier architecture. Based on a dynamic load-sensing mechanism, the design introduces a three-threshold decision scheme combining a high threshold, a low threshold, and a mid-supply reference voltage. By coordinating a continuous-time voltage detection circuit with a bidirectional shift register, the proposed approach enables accurate identification of the output state and the load level. A time-division-multiplexed two-stage control strategy is adopted to rapidly compensate for the drive capability under abrupt load changes, while proactively disabling redundant output units under steady-state conditions, thereby achieving power delivery on demand. The output stage employs a Class-AB push–pull structure integrating an improved low-leakage single-pole double-throw (SPDT) switch, which hard shuts off the power transistors in the non-operating state to effectively eliminate the subthreshold leakage current. Circuit simulations in a 0.18 μm CMOS process demonstrate that the proposed operational amplifier can adaptively regulate its output current in real time according to variations in the gyroscope driving demand, ensuring sufficient an electrostatic driving force and oscillation stability during transient conditions while significantly reducing static power consumption during the resonance steady state. The proposed design provides an effective solution for high-performance and high-energy-efficiency interface circuit design in MEMS gyroscope electrostatic force-modulated closed-loop self-excited driving systems. Full article

The integration of Unmanned Aerial Vehicle (UAV) swarms with Cell-Free massive Multiple Input Multiple Output (CF-mMIMO) networks offers promising prospects for large-scale crop monitoring in precision agriculture. CF-mMIMO provides macro-diversity and uniform channel quality across large agricultural fields. However, practical deployment demands jointly optimizing 3D trajectories and transmit power to maximize energy efficiency and field coverage simultaneously. This is challenging due to the limited battery capacity, mandatory return-to-depot constraints, and collision avoidance requirements. In this paper, we introduce a joint sensing–communication utility function that captures the trade-off between energy efficiency and field coverage completeness. To provide a scalable and distributed solution for rotary-wing UAV swarms, we develop a multi-agent deep reinforcement learning (MADRL) methodology based on the Multi-Agent Proximal Policy Optimization (MAPPO) approach. We adopt the Centralized Training with Decentralized Execution (CTDE) strategy, in which a CF-mMIMO central processing unit (CPU) serves as a global critic during training. At execution time, each UAV independently runs a lightweight local policy that adapts its trajectory and transmit power in real time based on battery state and air-to-ground channel variations. Simulation results reveal that the proposed MAPPO-CTDE approach outperforms existing benchmarks. Unlike prior methods that require instantaneous global CSI or neglect the sensing–communication coupling, the proposed approach simultaneously achieves high field coverage completeness, robust communication energy efficiency, and a high depot-return rate under hard battery constraints without any inter-UAV communication overhead at execution time. Full article

As an innovative structural system aligned with construction industrialization, prefabricated Steel-Reinforced Concrete (SRC) structures are characterized by high load-bearing capacity, efficient material utilization, and rapid construction. In this study, the mechanical behavior, failure mechanisms, and ductility characteristics of a prefabricated SRC multi-floored grain warehouse frame were investigated through quasi-static cyclic loading tests. To complement the experimental program, high-fidelity numerical models were developed using Abaqus, incorporating concrete plastic damage and steel material nonlinearity. The simulation results were rigorously validated against the experimental data. The findings indicate that the specimens exhibited typical shear failure modes with full hysteretic loops, demonstrating substantial energy dissipation capacity (equivalent viscous damping coefficient of 0.261). Notably, the results of the parametric study indicate that the integration of wall panels can significantly increase the load-bearing capacity and lateral stiffness of the frame system. The ductility of the samples was excellent, with displacement ductility coefficients ranging from 3.1 to 3.7. The ultimate inter-story drift angles at failure (1/49–1/38) substantially exceeded the code-specified limit (1/50), indicating robust collapse-prevention capacity. The numerical results strongly agreed with the experimental observations in terms of the hysteretic behavior, failure patterns, and skeleton curves, confirming the reliability of the modeling strategy for subsequent seismic performance analyses and parametric evaluations. Full article

Due to the rapid development of the textile industry and increased consumption of various textiles composed of both synthetic and natural fibers, large amounts of textile waste are produced, leading to environmental and economic problems on a global scale. Turning textile waste into carbon materials that can be used in a broad range of applications has become a viable solution to address this challenge in terms of sustainability and value generation. Natural and synthetic textile fibers have distinctive molecular structures with relatively high carbon content and variable chemical functionality; therefore, they have been identified as highly promising precursors for fabricating carbon materials with various electrochemical and environmental applications. At the same time, the properties of carbonized and activated textile fibers are strongly dependent on the molecular transformations taking place during thermal treatment and functionalization of textile fibers. This review will provide a comprehensive overview of the molecular evolution of natural and synthetic textile fibers during carbonization and activation processes in terms of dehydration, depolymerization, aromatization, heteroatom preservation, and graphitization mechanisms. The effect of precursor chemical composition, pyrolysis conditions, activation process, and heteroatom incorporation on the structure of carbonized and activated textile fibers and their physical and electrochemical properties will be analyzed. Particular emphasis is placed on electrochemical applications, including capacitive deionization, supercapacitors, electrocatalysis, and emerging smart electrochemical textile systems, highlighting how molecular transformation, pore engineering, and surface chemistry govern charge storage, ion adsorption, and catalytic behavior. In addition, major characterization techniques such as Raman spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and Brunauer–Emmett–Teller surface area analysis will be reviewed and discussed in relation to understanding the interdependence between molecular structure and material properties. Finally, recent issues related to feedstock heterogeneity, scalability, energy efficiency, and sustainability of processing are highlighted, and future perspectives on multifunctional carbon structures and circular utilization of textile waste are discussed. Full article

The growing global energy demand and increasing environmental concerns have created the need for the development of efficient, safe, and sustainable energy storage technologies. While lithium-ion batteries (LIBs) have dominated the energy storage market due to their high energy density and long cycle life, concerns regarding lithium resource scarcity, high cost, and safety risks associated with flammable organic electrolytes have motivated research on alternative batteries. In this context, aqueous zinc-ion batteries (AZIBs) have attracted significant attention as a promising next-generation energy storage system because of their inherent safety, resulting from the utilization of non-flammable aqueous electrolytes, and environmental friendliness, as well as natural abundance and low cost of zinc. Nevertheless, they face various challenges, which hinder their practical applications. Among them, the intrinsic limitations of the cathode materials, including their poor electronic conductivity, sluggish reaction kinetics and structural degradation during charge–discharge cycles, are considered particularly significant. Thus, the scientific community has explored various mitigation strategies, including the combination of cathode materials with carbon-based nanomaterials, such as reduced graphene oxide (rGO), with exceptional physicochemical properties. The present critical review discusses the most recent scientific work published in the literature during the last three years, referring to the combination of rGO with conventional cathode materials, such as manganese-based oxides, vanadium-based oxides, Prussian blue analogues, etc., for the development of next-generation AZIBs with superior electrochemical performance, long-term cycling durability, intrinsic safety, and enhanced sustainability. Full article

Nova eruptions exhibit diverse photometric and spectroscopic properties traditionally classified using empirical light-curve morphology and spectral taxonomy. However, these observational classifications do not uniquely constrain the underlying eruption physics. This review examines the coupling between light-curve evolution, spectral development, ejecta dynamics, and multi-wavelength emission in classical and recurrent novae, with particular emphasis on the role of shocks and multi-phase outflows. Recent observations across optical, radio, X-ray, and gamma-ray wavelengths demonstrate that nova ejecta are intrinsically structured, anisotropic, and dynamically interacting systems, challenging the traditional interpretation of novae as spherically symmetric thermonuclear explosions. We synthesise observational and theoretical studies that link decline timescales, spectral transitions, expansion velocities, and high-energy emission to fundamental physical parameters, including white dwarf mass, accretion rate, ejecta geometry, and shock energetics. Using a compiled multi-parameter dataset of classical, recurrent, and symbiotic novae, we demonstrate that many commonly used observational diagnostics are intrinsically degenerate, with similar observable properties arising from different physical conditions. We argue that nova diversity is better understood within a continuous multi-dimensional parameter space rather than through purely empirical classifications. The implications of this framework for mass retention efficiency and the evolution of recurrent novae toward Type Ia supernova progenitors are discussed. Finally, we outline a predictive observational framework integrating photometric, spectroscopic, and high-energy diagnostics for future nova studies. Full article

Facing China’s complex operating environment, in which the spot electricity market is still at an early stage of development and the mechanism price policy for new energy is implemented in parallel, this paper addresses the mechanism adaptability challenges that arise when high-proportion new energy participates in the spot electricity market on a full-volume basis. A trading and settlement mechanism with trading flexibility, multi-timescale coordination, and policy alignment is then constructed. Full-volume electricity on both the generation and consumption sides is incorporated into spot market clearing and settlement, thereby strengthening the role of the spot market in resource allocation. Differentiated bidding, settlement, and responsibility-bearing mechanisms are further designed according to electricity type and participant category, thereby clarifying responsibility boundaries and supporting imbalance-fund allocation. A multi-timescale trading mechanism is constructed to link short-cycle flexible trading, day-ahead bidding, intraday rolling adjustment, and real-time balancing. In addition, a differentiated medium- and long-term contract mechanism and a secondary settlement system are designed to meet the needs of system peak-regulation and market risk management. These designs also support coordination with the mechanism price policy for new energy, priority generation of hydropower and nuclear power, guaranteed electricity consumption, and grid-company agency purchasing. Case studies show that the proposed mechanism can help mitigate market efficiency distortions, improve the adaptability of the spot market to high-proportion new energy, and support the reasonable allocation of policy-related compensation costs and system regulation costs. Full article

The growing demand for sustainable energy has intensified interest in converting abundant agricultural residues into renewable fuels. Among these feedstocks, corn stover represents a promising biomass for thermochemical conversion due to its high volatile matter content and widespread availability. This study investigates syngas production and product distribution from corn stover via pyrolysis and steam gasification in an atmospheric fixed-bed tubular furnace at temperatures of 650–850 °C. Furthermore, the effects of steam-to-carbon (S/C) ratio and nickel aluminate (NiAl₂O₄) catalyst loading at 650 °C were also investigated to determine their influence on product distribution and syngas composition. Increasing temperature significantly enhanced gas production in both processes, while steam gasification consistently produced higher gas yields than pyrolysis. At an S/C ratio of 3, the gas yield increased from 37% to 58.6%, with a 55.1% increase in H₂ production after 60 min compared with the pyrolysis baseline. Furthermore, incorporation of NiAl₂O₄ improved the H₂ yield and H₂/CO molar ratio while suppressing CO₂ and CH₄ formation, indicating enhanced catalytic reforming and secondary cracking of pyrolysis vapors. These findings demonstrate that optimizing steam addition and nickel aluminate catalyst loading effectively promotes hydrogen-rich syngas from corn stover and provides valuable insight for the development of efficient biomass-to-fuel conversion technologies. Full article

This study aimed to examine the integrated effects of Carbon Accounting (CA), Digital Transformation (DT), Energy Efficiency (EE), and Global Uncertainty (GU) on enhancing Financial Decision-Making Quality (FDMQ) and improving Sustainability Performance (SP) in high-emission industrial companies. Drawing on Dynamic Capabilities Theory, the study proposed that these practices represent interconnected organizational capabilities that enhance firms’ adaptive capacity and their ability to create sustainable value, while Global Uncertainty represents a contextual factor that may influence the effectiveness of these capabilities. The study adopted a quantitative longitudinal research design using Panel Data Analysis based on secondary data obtained from annual financial reports, sustainability reports, and corporate disclosures of industrial companies listed on the Palestine Exchange. The sample consisted of ten industrial companies observed over the period 2020–2025, resulting in 59 firm-year observations. The Fixed Effects Model was employed to examine the direct relationships among the study variables, complemented by mediation and moderation analyses to investigate the mediating role of Financial Decision-Making Quality and the moderating effect of Global Uncertainty. The empirical findings revealed that Carbon Accounting, Digital Transformation, and Energy Efficiency positively affect Financial Decision-Making Quality, indicating that firms with more advanced environmental accounting systems, stronger digital capabilities, and higher operational efficiency are better positioned to make effective financial decisions. Furthermore, these organizational capabilities were found to have direct positive effects on Sustainability Performance. In contrast, Global Uncertainty was found to negatively affect both Financial Decision-Making Quality and Sustainability Performance, while also weakening the positive effects of organizational capabilities on financial decision-making. The results further confirmed that Financial Decision-Making Quality plays a significant mediating role in the relationship between organizational capabilities and Sustainability Performance. Overall, the findings support the assumptions of Dynamic Capabilities Theory by demonstrating that achieving sustainability in high-emission industries requires the integration of environmental, digital, and financial capabilities within a coordinated organizational system rather than treating them as isolated practices. Full article

Biological methanation of carbon dioxide (CO₂) using hydrogen (H₂) offers a promising route for upgrading biogas and storing renewable energy within existing gas infrastructures. However, the low solubility of H₂ in aqueous systems remains a major bottleneck, limiting its bioavailability and overall conversion efficiency. In this study, three H₂ delivery strategies—direct bubbling, sparging, and diffusion through submerged silicone tubing—were systematically compared in a lab-scale continuous stirred-tank reactor (CSTR) to evaluate their relative mass-transfer performance. H₂ addition via silicone tubing yielded substantially higher initial H₂ mass-transfer rates than sparging and bubbling, with increases of approximately 3.8-fold and 5.3-fold, respectively, under the tested conditions. Based on these findings, silicone-based H₂ delivery was applied in both in situ and ex situ configurations for biomethanation. In both setups, the methane (CH₄) fraction in the biogas increased from approximately 48% to over 85% upon H₂ addition, while no H₂ accumulation in the reactor headspace was observed. Under the applied low organic loading conditions, biogas production remained stable, indicating that H₂ addition did not adversely affect process performance within the investigated operational window. Overall, this study provides a comparative assessment of H₂ delivery strategies and highlights the trade-off between mass-transfer performance and engineering feasibility. While silicone diffusion enhances H₂ availability in anaerobic systems at the laboratory scale, extrapolating from the experimentally determined H₂ flux suggests that an impractically large silicone surface area would be required for scale-up. This reflects a fundamental limitation of diffusion-based H₂ delivery in stirred-tank reactors and underscores the need for alternative reactor concepts, such as dedicated ex situ systems or high-surface-area gas–liquid contactors. Despite extensive research on hydrogenotrophic methanation, quantitative links between H₂ mass transfer, reactor design, and scalability remain insufficiently resolved. Full article

Membrane distillation (MD) technology has become an effective solution to freshwater scarcity due to its low energy consumption, high separation efficiency, and ability to handle highly concentrated saline wastewater. Nevertheless, issues such as membrane wetting, membrane fouling, and low membrane flux severely limit its large-scale application. Composite membranes prepared using metal–organic framework (MOF) materials as fillers have become a research hotspot due to their advantages, such as permeable microporous channels, customizable pore structures, and modifiable active sites. These properties enable them to effectively reduce temperature polarization and concentration polarization phenomena. This article describes the characteristics of MOF materials and their current applications in the field of MD, with a comparative analysis of the applicability of MOF polycrystalline membranes and MOF composite membranes in MD, and discusses the working principle of MOFs in enhancing the performance of MD. Finally, the problems and challenges associated with the use of MOFs in MD applications are analyzed. This study aims to provide theoretical guidance for the application of MOF materials in the field of MD seawater desalination. Full article

Dielectric capacitors are employed in defense and automotive applications owing to their ultrahigh charge–discharge rates. To mitigate the high leakage current density of Na_0.5Bi_0.5TiO₃ (NBT), SrTiO₃ (STO), which exhibits excellent insulation performance, is incorporated into the NBT lattice to enhance both the breakdown field strength and the relaxor characteristics. Furthermore, the ionic radius of Sr²⁺ (0.1180 nm) is slightly larger than the average ionic radius of (NaBi)²⁺ (0.1025 nm). As a result, the introduction of STO induces lattice distortion, disrupts long-range ordering, and promotes the formation of short-range ordered domains, thereby strengthening the relaxor behavior (the relaxation degree γ increased from 1.63 to 1.84). Consequently, the 0.95(Na_0.5Bi_0.5)(Fe_0.02Ti_0.99)O₃-0.05SrTiO₃ thin film achieves a recoverable energy storage density (W_rec) of 43.88 J/cm³ and an efficiency (η) of 73.95%. In addition, the thin film exhibits excellent temperature stability over a range of 10 to 170 °C, good frequency stability from 0.1 to 2.0 kHz, and robust fatigue endurance up to 1 × 10⁸ switching cycles. This work provides reliable technical and theoretical guidance for the application of NBT-based materials in energy storage. Full article