Search Results (12,489)

Traditional grid-forming converter (GFC) control faces fundamental challenges in maintaining DC bus stability during rapid power transients, primarily due to the limited dynamic response capability of source-side energy storage devices. To address this, this paper proposes a hybrid control strategy integrating long short-term memory (LSTM) networks with a joint GFC and storage converter (SC) control scheme. The LSTM detects short-term voltage trends from historical DC bus data to generate a feedforward compensation signal, while the joint SC-GFC control dynamically incorporates the GFC’s inertial power demand into the SC’s power reference. Hardware-in-the-loop experiments show that, compared to traditional independent control under the same step transient conditions, the proposed method can reduce power overshoot by approximately 79.2%. The LSTM-enhanced joint control maintains stable power flow and significantly suppresses low-frequency oscillations, validating the necessity of data-driven trend prediction for achieving superior inertial support in practical constrained environments. This work provides a communication-free, practical solution for enhancing GFC performance. Full article

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented by T-Spherical Fuzzy-Valued Neutrosophic Numbers and aggregated before a score function is used at the explicit scalarization boundary. Standard MEREC then derives objective criterion weights from criterion-removal effects, and standard EDAS ranks alternatives by their positive and negative distances from the average score profile. The application evaluates nine technologies against ten criteria using assessments from thirty domain specialists. The corrected MEREC calculation assigns the greatest weights to carbon reduction potential (0.127), electricity demand reduction (0.125), maintenance complexity (0.124), operational cost efficiency (0.123), and cooling efficiency (0.123). The final ranking is Direct-to-Chip Liquid Cooling, Liquid Immersion Cooling, AI-Enabled Energy Management, Water-Side Free Cooling, Free-Air Cooling, Rear-Door Heat Exchanger Cooling, Hot/Cold Aisle Containment, Renewable-Powered Cooling, and Thermal Storage-Assisted Cooling. Weight perturbation, q-parameter, leave-one-expert-out, alternative-deletion, dominated-alternative, and multi-method comparisons show that the leading tier is robust, although the exact order of the two liquid-cooling technologies is sensitive in some scenarios. The findings provide a transparent and reproducible decision-support basis while explicitly acknowledging the information compression and rank-reversal limitations of score-based MCDM. Full article

With the increasing penetration of wind and photovoltaic generation, microgrids are playing an increasingly important role in promoting renewable energy accommodation, enhancing operational flexibility, and enabling low-carbon energy management. However, the strong uncertainty of renewable generation and load demand, together with the coupling effects of electricity, hydrogen, and carbon markets, poses significant challenges to the optimal planning and operation of microgrid energy storage systems. To address these issues, this paper proposes a bi-level optimal sizing framework for an electric–hydrogen hybrid energy storage system (EHH-ESS) in a microgrid under multi-market coupling. First, typical wind–solar–load scenarios are generated using a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), so as to capture the stochastic characteristics and temporal correlations of renewable generation and load demand. Then, a multi-market coupling index (MCI), integrating electricity price, hydrogen price, and carbon price signals, is constructed to characterize time-varying economic and low-carbon operating incentives and to guide coordinated dispatch decisions. On this basis, a bi-level multi-objective optimization model is established. The upper level determines the optimal capacities of battery storage, electrolyzers, fuel cells, and hydrogen tanks, while the lower level performs hourly coordinated operation of the microgrid under multi-market conditions. The model considers annual equivalent total cost, renewable energy curtailment rate, and carbon emissions as objective functions, and is solved using the NSGA-III algorithm. Compared with the no-storage benchmark, the proposed scheme improves the annual operating economics and renewable-energy accommodation under the studied market conditions. The proposed method significantly reduces annual operating cost and improves renewable energy accommodation. However, under the current carbon price and grid emission factor settings, the optimal economic solution increases carbon emissions relative to the baseline, indicating a trade-off between economic arbitrage and low-carbon operation. Full article

The decarbonization of maritime transportation requires shipboard energy systems to coordinate conventional generators, renewable energy sources, energy storage devices, and thermal energy units under voyage-dependent operating constraints. This paper develops a configurable hybrid multienergy ship system for coordinated electrical and thermal energy scheduling. The proposed framework functionally separates the propulsion subsystem from the service and thermal subsystem while retaining system-level coordination among photovoltaic generation, wind generation, diesel generators, micro gas turbines, energy storage batteries, and thermal energy units. A convolutional neural network is employed to provide short-term photovoltaic power forecasts for day-ahead scheduling. The resulting scheduling problem simultaneously considers voyage completion, power balance, equipment operating limits, ramp-rate constraints, battery charging and discharging restrictions, operating costs, and pollutant emission treatment costs. The nonlinear operating logic is reformulated as a mixed-integer optimization problem and solved using CPLEX. A representative coastal voyage case study is used to evaluate the proposed framework. The results demonstrate that the method can coordinate multiple shipboard energy sources, satisfy the prescribed electrical and thermal demands, and provide a set of Pareto-optimal solutions describing the trade-off between operating cost and emission-related cost. The proposed framework provides a system-level scheduling approach for supporting the economic and low-carbon operation of hybrid multienergy ships under increasingly stringent maritime emission reduction requirements. Full article

The present work presents a new synthetic jet piezoelectric pump designed to address the airflow delivery needs arising from the increasing power density of high-performance microelectronics. Traditional miniaturized cooling techniques suffer from low efficiency, bulky size, and high cost, while microfluidic cooling has emerged as a vital chip thermal management method with outstanding miniature heat removal capacity. We systematically designed the vibration mode and pump structure, adopting the sixth-order resonant frequency as the operating frequency. A dual resonant layer with stiffness-guided fixed boundaries was employed to enhance vibration efficiency and energy conversion, together with an optimized flow channel layout and parametric design. Experiments conducted under 35 V square-wave excitation demonstrate that the 20 mm × 20 mm × 2.5 mm pump delivers a flow rate of 1.6 L/min and a back pressure of 2.7 kPa. This work provides a feasible technical route for large-scale airflow delivery applications of synthetic jet piezoelectric pumps, with potential for thermal management in microelectronic devices, while balancing excellent performance and low manufacturing cost. Full article

The development of efficient photocatalysts for hydrogen production is a key challenge for sustainable energy technologies. In this study, strontium titanate (SrTiO₃) was synthesized via a citrate-assisted sol-gel method and subsequently modified by deposition-precipitation using nominal HAuCl₄ precursor concentrations of 1.0, 1.5, and 2.0 mM. The resulting materials were characterized by XRD, Raman spectroscopy, UV-Vis diffuse reflectance spectroscopy, SEM with EDS, and X-ray fluorescence (XRF). Au incorporation did not produce detectable changes in the SrTiO₃ crystalline phase or its optical band gap, which remained at 3.19–3.20 eV. The additional absorption band centered near 550 nm was consistent with the localized surface plasmon resonance of metallic Au nanoparticles. Microscopy indicated increasing surface coverage and aggregation at the highest nominal precursor concentration. Under irradiation with a low-pressure Hg lamp, all Au-containing materials presented substantially greater H₂ evolution than pristine SrTiO₃, whereas the comparatively small differences among the Au-modified samples indicated an apparent activity plateau across the evaluated concentration range. Because the Au-associated absorption band near 550 nm lies outside the main 254 nm emission of the lamp and the SrTiO₃ band gap remained mostly unchanged, the enhanced H₂ evolution is consistent with improved interfacial charge separation in the Au/SrTiO₃ system. A Schottky-junction-mediated pathway is proposed based on the observed activity trends and the electronic properties reported for Au/SrTiO₃ interfaces, rather than to a plasmonic or band-gap-tuning effect. The selected STO/Au 2.0 mM material retained approximately 97% of its initial apparent H₂ evolution rate after three consecutive cycles, indicating favorable short-term activity retention. Overall, this comparatively simple synthesis route provides a practical baseline for investigating the influence of nominal Au precursor concentration on H₂ evolution over SrTiO₃. Full article

Woody biomass is often promoted as a low-carbon energy source in global decarbonization efforts. However, LCA (life cycle assessment) evaluations of woody biomass-to-energy systems show very different environmental performance. Variations in technology and methodology across investigations can cause these inconsistencies. This review paper analyzes methodologies of LCAs of woody biomass conversion routes such as combustion, combined heat and power, gasification, pyrolysis, torrefaction-assisted systems, and new bioenergy with carbon capture configurations. A systematic literature review was conducted using Scopus, SpringerLink, and ScienceDirect, identifying 4272 records, of which 98 studies were retained for detailed analysis following the application of defined inclusion and exclusion criteria. Functional unit selection, from biomass mass per unit to power or heat per unit, is highly variable, affecting comparability. Forest carbon stock fluctuations, infrastructure, and end-of-life treatment are inconsistently included in cradle-to-grave system boundaries. Static GWP100 methods are often used in biogenic carbon removal without considering temporal carbon dynamics. The importance of pretreatment steps like drying, pelletizing, and torrefaction cannot be overstated, even though they have a direct impact on the quality of the fuel, the efficiency of transportation, and the effectiveness of the conversion process downstream. The large range of stated emission levels for comparable technologies is further influenced by logistics assumptions, plant scale, and allocation mechanisms in cogeneration systems. The review synthesizes these methodological differences and proposes a harmonization methodology to increase woody biomass LCA transparency and comparability. By identifying important sources of outcome variability, this study helps policymakers, project developers, and industry stakeholders evaluate biomass energy investments and bring clarity to environmental decisions. Full article

Against China’s dual carbon peaking and carbon neutrality strategic goals, nationwide digital transformation brings both carbon abatement dividends and potential energy rebound risks, and its full low-carbon potential is constrained by local industrial foundations and regional economic development stages. Most existing studies merely treat industrial upgrading as an intermediate transmission channel, with little discussion of its moderating influence. Moreover, few threshold analyses take the comprehensive level of regional economic development as the core threshold variable to capture the boundary conditions of digital decarbonization effects. Based on balanced panel data covering 30 provincial-level regions of China from 2011 to 2023, this paper constructs a multi-dimensional digital economy index via the entropy weight method. Prior to formal regression, we conduct Pearson correlation analysis and mean-centered VIF multicollinearity diagnostics to avoid biased estimation. Two-way fixed-effects regression, moderation tests, Bootstrap-based regional heterogeneity comparison and Hansen’s single threshold model are adopted for empirical analysis. The results show that digital economy development significantly curbs carbon emission intensity; a one-standard-deviation increase in the digital economy composite index is associated with an approximately 9.7% decline in carbon emission intensity. The mean-centered interaction term DIG × UIS is significantly negative at the 1% level, proving that service-oriented industrial upgrading strengthens the carbon reduction effect of digitalization. The mitigation effect displays distinct spatial divergence: the estimated coefficient equals −2.638 for eastern provinces, −3.585 for central regions and −1.700 for western areas. Bootstrap inter-group coefficient tests confirm statistically significant gaps between east–west and central–western subgroups. Threshold regression identifies a single threshold of logarithmic per capita GDP at 11.94. After crossing this economic development threshold, the inhibitory coefficient of the digital economy rises markedly from −0.844 to −1.473. This study enriches the theoretical system of digital low-carbon transition by jointly uncovering the moderating role of industrial upgrading and the stage threshold constraint of economic development and offers differentiated digital low-carbon policy guidance for provincial governments. Full article

Renewable power plants connected to low-system-strength grids are increasingly dominated by inverter-based resources (IBRs). Their point of common coupling (PCC) voltage is therefore shaped not only by reactive-power support but also by active-power ramps, network impedance, short-circuit capacity, and converter limits. Conventional Q-V droop control, fixed power-factor control, Volt/VAR control, and fixed active-power/reactive-power (P/Q) decoupling schemes often absorb active-power excursions into the voltage error, which can drive excessive reactive-power injection during fault clearing, post-fault power recovery, and phase-angle disturbances. Here, an active-power–voltage-coupling-aware reactive-power compensation (APVQ-RC) method is proposed for plant-level voltage control. The method estimates local P-V and Q-V voltage sensitivities online, reconstructs an effective voltage error, and produces a capacity-constrained reactive-power reference through smooth coupling activation. The reduced-order evaluation includes estimator conditioning, excitation screening, sensitivity-estimation error and empirical 95% estimator-error intervals, sensitivity to the smoothing factor and window length, measurement noise, converter capability saturation, and computational timing. Under P-V-coupled transients, APVQ-RC reduces voltage overshoot and reactive-power compensation energy while retaining Q-V-like support during voltage-sag-dominated events. Compared with the best scanned fixed P/Q baseline, it reduces overshoot, reactive-power compensation energy, and reactive-power peak by 42.03%, 60.35%, and 8.90%, respectively; the representative single-step calculation time is 0.0188 ms within a 1 ms control cycle. These results indicate millisecond-scale plant-level feasibility within the reduced model, while electromagnetic-transient, hardware-in-the-loop, and field validation remain necessary before deployment. Full article

Eco-friendly lubricant manufacturing focuses on using biodegradable, renewable base oils, such as waste oil, and green-synthesized nanomaterials, such as agricultural residue-based nanoparticles, in order to replace conventional toxic lubricants with biodegradable alternatives and reduce environmental impact. These nanolubricants are produced through low-energy methods like mechanical, microwave, or chemical-free synthesis that can result in improvement in their performance. The produced lubricants exhibit enhanced tribological properties, including reduced friction and wear. Several formulations also raise the thermal degradation onset above that of their mineral benchmarks, although oxidative stability remains the weakest property of bio-based systems. This approach addresses industrial demands for sustainable, cost-effective, and environmentally compliant lubrication technologies. Our study reviews sustainable, eco-friendly synthesis methods for producing high-performance nanolubricants from different waste oils, including cooking and mineral oils. In addition to the incorporation of residue-based nanoparticles (e.g., eggshell) in waste oils, the performance and properties of bio-based lubricants with engineered nanoparticles, such as metal nano-oxides and carbon-based nanomaterials, are also reviewed for comparison purposes. Within bio-based fluids at moderate contact severity, residue-derived additives are found to match their engineered counterparts in terms of friction and wear, while engineered two-dimensional lamellar additives retain an advantage under extreme-pressure conditions where residue-derived particles have not yet been evaluated. Neither class has been assessed by life cycle or biodegradation testing as a finished formulation. Full article

The increasing demand for sustainable and environmentally synthesis routes has driven significant interest in biogenic precursors for nanomaterial fabrication. Among these, egg-derived materials—including eggshell, eggshell membrane (ESM), egg white, and egg yolk—have emerged as versatile, low-cost, and multifunctional resources for green nanotechnology. This review provides a comprehensive and critical analysis of the physicochemical properties and functional roles of egg-derived components in nanomaterial synthesis. A comparative evaluation of egg-derived and conventional synthesis methods is presented, highlighting the trade-off between environmental sustainability and control over physicochemical parameters. Egg-derived approaches offer reduced toxicity, lower energy consumption, and intrinsic functionalization, but remain limited by compositional variability, reduced reproducibility, and challenges in process scalability. Furthermore, an application-oriented framework is proposed for selecting appropriate egg-derived precursors based on material type, targeted functionality, and processing constraints. The review also identifies key limitations, including mechanistic uncertainties, organic residue formation, and regulatory considerations, and outlines future research directions focused on process standardization, in situ characterization, and hybrid synthesis strategies. Full article

Background: Alcohol-related conditions may influence both injury patterns and in-hospital management in orthopaedic trauma. This study evaluated the clinical characteristics, injury mechanisms, treatment patterns, and hospital outcomes of adults with acute orthopaedic trauma and documented alcohol use, with particular attention to geriatric vulnerability and alcohol withdrawal. Methods: This retrospective single-centre cohort included adults admitted between January 2018 and December 2025 with acute musculoskeletal trauma and an alcohol-related diagnosis during the same hospitalisation. Patients were classified according to their predominant recorded alcohol-related presentation. Geriatric patients, defined as those aged 65 years or older, were compared with younger adults. Injury mechanisms, comorbidities, operative treatment, intensive care unit involvement, hospital length of stay, mortality, and recorded hospitalisation costs were analysed. Results: The final cohort comprised 294 patients, including 87 geriatric patients. Geriatric patients more frequently sustained same-level or low-energy falls than younger adults (46.0% versus 25.6%; Holm-adjusted p = 0.005) and had a higher prevalence of proximal femoral fractures (40.2% versus 21.7%; OR 2.42, 95% CI 1.41 to 4.16). Any recorded ICU involvement was more frequent among geriatric patients, although prolonged ICU stays of 24 h or longer did not differ significantly between age groups. Alcohol withdrawal was documented in 46 patients and was associated with longer hospitalisation and a longer admission-to-surgery interval. In-hospital mortality occurred in 5 of 46 patients with documented withdrawal (10.9%) and 5 of 248 without withdrawal (2.0%; unadjusted OR 5.93, 95% CI 1.64 to 21.37; p = 0.010). Conclusions: Orthopaedic trauma patients with documented alcohol use represent a clinically heterogeneous population. Geriatric patients showed greater vulnerability to low-energy trauma, proximal femoral fracture, comorbidity, and intensive care involvement, while alcohol withdrawal identified patients with a more complex hospital course. Early recognition of withdrawal risk and enhanced inpatient safety measures may improve orthopaedic care. These findings support careful assessment of alcohol-related risk, early recognition of withdrawal, and heightened inpatient safety precautions. Full article

A pursuer and an evader can exploit low-energy, non-Keplerian trajectories in cislunar space, making it difficult to obtain the saddle point for impulsive orbital pursuit–evasion games (OPEG). To address this problem, this paper first establishes a zero-sum differential game model based on the circular restricted three-body problem (CR3BP), where the terminal interception time is taken as the performance objective. The necessary optimality conditions for impulsive maneuvers are then derived using Pontryagin’s Maximum Principle (PMP), which transforms the optimal control problem into multipoint boundary value problems (MPBVPs). Subsequently, to overcome the high sensitivity of the MPBVPs to initial costate vectors in shooting methods, a two-layer hybrid initial-guess strategy combining a genetic algorithm with a time-domain coarse-grid search method is proposed for the single-impulse case. Furthermore, a receding-horizon strategy is introduced to generate the initial impulse sequence guess stage by stage for multiple-impulse cases. Finally, numerical simulations demonstrate that the proposed initial-guess strategy can effectively obtain the Stackelberg equilibrium solution for representative cislunar scenarios, including distant retrograde orbits (DROs) and Halo orbits. Meanwhile, the effects of observation delay and three-dimensional orbital characteristics on the game outcomes are also discussed based on dynamic game theory. Full article

Battery packs for new energy vehicles have evolved from simple load-bearing and protective assemblies into multifunctional safety structures integrating structural support, crash protection, thermal-runaway mitigation, flame retardancy, electrical insulation, electromagnetic interference shielding, waterproof sealing, and long-term reliability. Fiber-reinforced polymer composites are promising for upper covers, underbody shields, trays, cross beams, side frames, and local protective structures because of their low density, corrosion resistance, design flexibility, and functional-integration potential. However, composite-part performance is strongly governed by forming. Resin flow, impregnation, curing or cooling shrinkage, fiber orientation, filler dispersion, and interfacial bonding may induce voids, dry spots, resin-rich regions, delamination, warpage, and fiber waviness, thereby affecting load bearing, sealing, thermal protection, and durability. This review focuses on composite-forming technologies for new energy-vehicle battery packs. It summarizes component-level service requirements and material systems and compares representative forming routes, including sheet molding compound (SMC), prepreg compression molding/wet compression molding (PCM/WCM), resin transfer molding/high-pressure resin transfer molding (RTM/HP-RTM), vacuum-assisted resin transfer molding (VARTM), long-fiber thermoplastic direct processing (LFT-D), glass-mat thermoplastic (GMT), thermoplastic sheet forming, pultrusion, and multi-material joining. These routes are evaluated from six dimensions: material form, forming cycle, typical defects, representative mechanical performance, applicable components, and engineering maturity. The review further discusses defect mechanisms, performance effects, detection and control methods, and the roles of in-line monitoring, non-destructive testing, process simulation, machine learning, and digital twins in closed-loop quality manufacturing. Finally, engineering challenges are examined in multi-material joining, thermal-safety integration, low-carbon recycling, and standard certification. Composite-material battery-pack structures should therefore be developed as coordinated design and closed-loop manufacturing systems linking materials, processes, defects, performance, and validation. Full article

High reclaimed asphalt pavement (RAP) contents are often limited by insufficient restoration of field-aged SBS-modified asphalt and the lack of a comprehensive method for rejuvenator dosage selection. This study aimed to develop a multi-performance-based approach for determining the dosage of an epoxy-based reactive rejuvenator under high-RAP conditions. Rejuvenated binders with different dosages were evaluated using conventional tests, DSR, MSCR, BBR, and LAS tests. Continuous low-temperature grading temperature, dissipated energy ratio, and entropy-weight TOPSIS were used for comprehensive evaluation, while GPC was employed to characterize molecular-weight distribution. The rejuvenator improved low-temperature relaxation, fatigue resistance, energy dissipation, and workability, whereas excessive dosages reduced rutting resistance and elastic recovery. Entropy-weight TOPSIS ranked RA-6 highest, with a relative closeness coefficient of 0.66504, and this ranking was consistent with the overall trends obtained from individual performance tests, supporting the feasibility of the proposed evaluation method. GPC results showed systematic changes in molecular-weight distribution after rejuvenation. For the investigated material system, 6% is recommended among the tested dosages. The proposed framework provides a practical basis for dosage determination when material characteristics and performance requirements vary. Full article