Search Results (29,138)

Ice storms threaten distribution network resilience through combined mechanical loading and secondary failures, increasing the risk of prolonged power interruptions. This paper proposes a two-stage robust energy storage planning strategy for evolving ice storm conditions. A line failure probability model combines wind, ice, and gravity loads with fuzzy inference of secondary hazard effects to generate time-varying failure scenarios. Overall and important load resilience indices characterize system performance and the restoration of essential electricity services. The optimization model coordinates energy storage siting, sizing, and scheduling while accounting for investment, operation, electricity purchase, and load-loss costs. The model is solved using column-and-constraint generation and evaluated on a modified IEEE 33-bus distribution network. In the reported worst-case scenario, total energy not supplied decreases from 18.4 to 10.9 MWh with energy storage, a reduction of 40.8%. Energy not supplied to important loads decreases from 1.33 to 0.24 MW—a reduction of 82.0%. These reductions quantify unserved energy rather than changes in the absolute resilience indices. The results indicate that coordinated storage planning and scheduling can reduce outage consequences and prioritize important loads within the evaluated network, scenarios, and benchmark parameter settings. Full article

Growing wind and photovoltaic generation increases the demand for large-scale, long-duration energy storage. Pumped hydro compressed-air energy storage (PHCAES) stores and releases energy through pressure transfer between water and compressed air, using air pressure to provide an equivalent hydraulic head and thereby reducing dependence on natural elevation while retaining hydraulic energy conversion and the potential for near-isothermal operation. This review establishes a taxonomy of hydraulically coupled compressed-air storage comprising PHCAES, liquid-piston systems, hydraulically compensated constant-pressure CAES, and hydraulic–pneumatic cascade or hybrid systems. Variable- and constant-pressure PHCAES are compared with pumped hydro energy storage (PHES) and compressed-air energy storage (CAES) in terms of efficiency, economics and environmental implications; this is followed by a critical analysis of the mechanisms governing PHCAES performance. The results show that improved siting flexibility is the principal conditional advantage of PHCAES, rather than inherently higher efficiency or lower cost. Its net performance depends on pressure–volume matching, gas–liquid heat transfer, hydraulic-machine operation, auxiliary consumption and storage infrastructure. Pressure regulation and thermal enhancement are beneficial only when their gains exceed the associated compression, throttling and auxiliary losses. The principal research gap is the lack of engineering-scale, full-cycle validation using consistent electrical, economic and lifecycle assessment boundaries, which currently prevents robust comparison with PHES and CAES. Full article

In distribution network and microgrids, energy storage (ES) systems possess four-quadrant operational capabilities, making them inherently high-quality resources for reactive power (RP) regulation. However, existing research has primarily focused on optimizing the active power of ES to achieve economic objectives, while the potential for RP and voltage control has not been fully explored. Meanwhile, traditional RP optimization methods have inherent limitations in terms of real-time performance, addressing uncertainty, and handling nonlinear problems. To address these challenges, this paper proposes a data-driven adaptive RP and voltage control method for distribution network with ES using deep reinforcement learning (DRL)–Soft Actor–Critic (SAC) algorithm. First of all, this method models the grid’s RP and voltage control problem as a sequential decision-making process, with the core being the construction of a control agent that integrates grid operational states with a deep neural network. Through continuous interaction with the environment, this agent autonomously learns and dynamically adapts to the random fluctuations in photovoltaic (PV) output and load without relying on precise physical models. Secondly, this paper sets minimizing network losses, voltage deviations, and the operational costs of RP equipment in ES as comprehensive optimization objectives, translating them into a reward function within the DRL-SAC framework. Leveraging the powerful nonlinear mapping capabilities and extremely fast forward computation speed of deep neural networks, the strategy achieves a data-driven approximation of the optimal RP control strategy in complex grid environments. Finally, the superiority of the strategy is comprehensively verified on the modified IEEE 33-bus system under three typical operating conditions (daytime fluctuation, extreme weather, sudden load change). The results show that the voltage qualification rate is increased to 99.1% and the network loss is reduced by 33.7%, providing an engineering-feasible solution for ES systems to participate in distribution network RP and voltage regulation. Full article

Synthetic fibre composites deliver high mechanical performance at a substantial energy and carbon cost, motivating a shift to renewable reinforcements. Flax and hemp are credible candidates, but their uptake is constrained by thermal stability and inherent combustibility, and their performance depends strongly on how completely the laminate is consolidated during manufacture. Vacuum-Assisted Resin Infusion Moulding (VARIM) yields low-void, well-consolidated laminates, yet the thermal and acoustic behaviour of VARIM-processed flax and hemp composites has not been compared directly. This study evaluates unidirectional flax/epoxy and hemp/epoxy laminates, each consisting of five plies produced under identical VARIM conditions, using TGA, DSC, limiting oxygen index (LOI) and UL 94 HB testing, SEM, and four-microphone impedance tube transmission loss (TL) measurements (ASTM E2611). Both laminates remained thermally stable to approximately 200–220 °C. Hemp/epoxy recorded a higher 5 wt.% degradation temperature (222 versus 207 °C), char residue (10.22 versus 9.29 wt.%) and average TL (13.22 versus 11.56 dB, 250–2000 Hz), while both laminates returned an identical LOI of 21.54% and a UL 94 HB rating. The fibre-governed properties therefore differed between the two laminates whereas the flammability response, governed by the shared epoxy matrix, did not. The glass transition temperature also differed (71.9 versus 65.3 °C) but is attributed to a small difference in degree of cure rather than to the reinforcement. The results provide baseline data for selecting VARIM-processed bio-composites for thermal management and passive noise control. The findings support Sustainable Development Goals (SDGs) 9, 12, and 13 through the development of sustainable, low-carbon bio-composite materials. Full article

Decarbonizing shipping requires reducing emissions without compromising the performance of large commercial vessels. Nuclear propulsion using small modular reactors (SMRs) has recently attracted renewed interest as a long-term alternative to fossil-fuel engines for large container ships. This study provides a technical, environmental, and economic assessment of SMR propulsion for a typical 15,000-TEU container ship, compared to conventional heavy fuel oil (HFO) propulsion. The analysis covers propulsion power requirements, energy conversion efficiency, additional electrical power needs, operational emissions, and total costs over 25 years. Under the study’s assumptions, the conventional system consumes about 50,400 tonnes of HFO annually, resulting in approximately 156,940 tonnes of CO₂ emissions per year, along with significant NO_x, SO_x, particulate, and CO emissions. A 70 MWe SMR-based propulsion design is then evaluated, considering energy conversion losses and the ship’s auxiliary power needs. The power balance indicates that the proposed SMR system can meet propulsion demands and provide surplus electrical capacity. Economically, the estimated 25-year total cost for the SMR option is about USD 376.7 million, compared to USD 452.0 million for the HFO case. Sensitivity analysis shows that this economic advantage depends on HFO prices, SMR capital costs, the discount rate, and operating life. Overall, SMR propulsion appears to be a technically and economically viable option for large container ships, though its adoption will depend on regulatory requirements, safety standards, infrastructure, and further advancements in marine nuclear technology. Full article

Centralized sewer networks are rarely feasible for scattered mountain villages across China. Their construction costs stay high, and uneven terrain easily triggers pipe blockages and infiltration. Most existing rural wastewater treatment devices run on fixed operating schedules. They maintain full aeration even during low water inflow, wasting electricity and destabilizing effluent quality. This study reports a full-scale summer field assessment of an integrated attached-growth biofilm reactor deployed at the sewage treatment station serving Miaodong and Miaoxi Villages, Ruyang County, Henan Province, China. The system combines hydrolysis acidification, two-stage biological contact oxidation, sedimentation, post-sedimentation polishing, and a cloud-connected monitoring and control module. The control system adjusts influent pumping, aeration, internal reflux, and sludge discharge in response to measured hydraulic and dissolved-oxygen signals. The design treatment capacity was 850 m³ d⁻¹. During the 25-day monitoring period, the packing filling ratio was 70%, dissolved oxygen was maintained at 2.0–4.0 mg L⁻¹, and water temperature was 20 ± 5 °C. Average COD removal reached 91.1%, ammonium nitrogen (NH₄⁺-N) removal reached 88.9%, total nitrogen (TN) removal reached 83.5%, and total phosphorus (TP) removal achieved 81.7%. The average unit electricity consumption was 0.195 kWh·m⁻³. Because no fixed-frequency reference operation was conducted under identical influent and environmental conditions, the specific energy-saving contribution of the adaptive control module could not be quantitatively isolated. The reported value should therefore be interpreted as system-level field performance rather than as a verified percentage reduction attributable exclusively to intelligent control. The average TP concentration after polishing was 0.59 mg L⁻¹, exceeding the 0.5 mg L⁻¹ Class A limit of GB 18918-2002. The results characterize summer operation under the investigated loading and temperature conditions and should not be extrapolated directly to year-round compliance, winter operation, or heavy-rainfall events. Full article

Pedestrian localisation in emergency environments is challenged by degraded Global Positioning System (GPS) availability, mobile-anchor uncertainty, radio-frequency interference, non-line-of-sight distortion, and inertial drift. Reporting only valid-estimate error may conceal localisation outages and recovery burden. This study proposes Hybrid S9, an adaptive, device-centric localisation framework with a structurally invariant hierarchical controller that selects among GPS, Bluetooth Low Energy (BLE)-assisted Extended Kalman Filter (EKF) correction, zero-velocity update (ZUPT), kinematic coasting, and Particle Filter (PF) recovery according to measurement quality, uncertainty, and mobility state. The framework is evaluated in Normal, Urban Canyon, and Search and Rescue regimes using valid-estimate mean absolute error (MAE), availability, penalised mean error (PME), and operation cost. In the degraded regimes, Hybrid S9 maintains near-complete localisation availability while reducing operation cost. Dedicated severe-degradation experiments verify PF activation, posterior state and covariance transfer, and controlled de-escalation. Full article

As global climate change intensifies, decarbonizing the power system is key to achieving carbon-reduction targets. Inspired by the multi-objective ant-lion optimization (MALO) method and deep neural networks (DNNs), this study proposes an innovative approach to address the complex carbon reduction challenges faced by energy-consuming enterprises. The proposed fully connected deep neural networks with multi-head self-attention mechanisms based on the multi-objective ant-lion optimization algorithm (FCDNN-MHSAM-MALO, FMM) integrate the advantages of MALO and DNN. MALO plays a key role in optimizing the decision variables in economic scheduling. By contrast, DNN predicts the search direction of the optimal solution by learning historical optimization results. This reduces the number of iterations, improves computational efficiency, and speeds up the solution process. The multi-head self-attention mechanism calculates the importance of various input features, enabling the model to focus on factors that significantly impact the scheduling solution. This attention-driven approach improves prediction accuracy and enables MALO to optimize from an earlier starting point, thus achieving global convergence more efficiently. Compared with several state-of-the-art algorithms on IEEE 118- and IEEE 300-bus systems, the simulation results show that (1) both carbon dioxide emissions and costs can be reduced: carbon emissions are reduced by at least 1.02% and the cost is lowered by at least 0.64% when the FMM algorithm is adopted; (2) better real-time performance: an at least 17.11% reduction in computation time is achieved using FMM; and (3) better stability performance: the curves obtained by FMM for the two cases are closer to the Pareto frontier. Full article

Converting waste slurry from underground construction into foamed lightweight soil (FLS) offers a route to waste valorization, but its durability under repeated moisture changes requires evaluation. This study compared FLS prepared with ordinary Portland cement (OPC), alkali-activated slag–fly ash (AASF), and hybrid OPC-AASF. Engineering properties and resistance to 18 wetting and drying (W-D) cycles were evaluated alongside pore structure evolution, microstructural changes, and environmental and economic indicators. Increasing soil content reduced unconfined compressive strength (UCS), with OPC-AASF showing a more gradual decline than OPC. All systems exhibited non-monotonic strength evolution during cycling. After 18 cycles, the UCS losses relative to the 28 d baseline were 1.9%–5.8% for OPC-AASF and 12.3%–17.6% for AASF. In selected specimens, X-ray computed tomography showed that lower macroporosity did not necessarily correspond to better strength retention. The greater strength loss in AASF was accompanied by spatial pore enrichment, coarse low-sphericity pores, and local interfacial damage. X-ray diffraction indicated retention of the main crystalline phases, while scanning electron microscopy showed better local pore wall and interfacial continuity in OPC-AASF. On a common dry-solids mass basis, the hybrid mixture containing 40% soil required 76.0% less OPC than a theoretical OPC foam concrete without waste soil. The estimated carbon emissions, energy intensity, and material cost associated with raw material inputs were 72.2%, 68.0%, and 48.1% lower, respectively. These findings support OPC-AASF as a cement-reduced stabilization system for lightweight backfill, combining waste slurry reuse with strength retention under repeated moisture fluctuations. Full article

In this paper, we propose an instantaneous chirp-rate-driven adaptive window Chirplet transform algorithm for the analysis of strong time-varying nonlinear frequency-modulated signals with uncorrelated components. In this approach, the length of the sliding window in the Chirplet transform is dynamically adjusted according to the estimated instantaneous chirp rate of each signal component of an initial time–frequency result from short-time Fourier transform (STFT). A boundary constraint determined from the modal support intervals of the signal is utilized to restrain the allowable searching frequency range of the instantaneous frequency (IF) trajectories and incorporated into a cost-function-based IF extraction method to improve accuracy in the IF estimation. The effectiveness of the proposed algorithm is validated using a simulated nonlinear frequency-modulated (FM) signal with two uncorrelated components, and two sets of experimental bearing vibration signals. It is shown that the proposed algorithm can accurately track the frequency modulation of a strong FM signal dynamically to render an accurate estimation of the IFs and modal amplitudes of a strong FM signal. A comparison study also verifies that the proposed algorithm can produce a better energy-concentrated time–frequency result compared to other commonly employed time–frequency analysis techniques, particularly when the signal is contaminated by noise. Full article

To address power supply–demand mismatch in hydrogen–electric hybrid ships under load fluctuations, variations in energy states, and limited power-supply capability, this paper develops a power-deficit-constrained hierarchical energy-management strategy. Rather than directly determining the power commands of individual energy units, the upper-level PPO-Lagrangian controller adaptively regulates the ECMS equivalent factor according to system states and explicit power-deficit constraint feedback, while the lower-level ECMS performs instantaneous power allocation among the fuel cell, battery, and diesel generator. The resulting allocation determines the realized constraint cost, which is fed back to update the Lagrange multiplier and subsequent equivalent-factor regulation, thereby forming a closed-loop cross-layer coordination mechanism. Simulations were conducted using navigation data from a nearshore bulk carrier and compared with representative energy-management strategies. The results show that the proposed strategy can achieve favorable performance in power-deficit suppression, constraint feasibility, diesel-generator dependence, and operational economy under load disturbances and component degradation, providing a methodological basis for further real-time implementation and experimental validation of constrained energy management in hydrogen–electric ships. Full article

Polyhydroxyalkanoates (PHAs) are a structurally diverse family of microbially synthesised, biodegradable polyesters that accumulate as intracellular carbon and energy reserves under conditions of nutrient imbalance. Their combination of adjustable mechanical performance with controlled hydrolytic and enzymatic degradation, and non-toxic degradation intermediates (ex. D-3-hydroxybutyrate) has made them a longstanding candidate biomaterial for human tissue engineering, drug delivery, and resorbable implants. Comparatively, their application in veterinary medicine remains an emerging and fragmented field, despite an arguably stronger practical case: veterinary practice faces acute pressure to replace non-degradable sutures, orthopaedic hardware, and single-use plastics with materials that avoid secondary retrieval surgery, that can be produced at low cost for large-scale animal use, and that align with growing regulatory and consumer demand for sustainable animal healthcare. This review consolidates current understanding of PHA biosynthesis, covering the core: phaA-phaB-phaC pathway, medium-chain-length variants, microbial producers, feedstock flexibility, and metabolic engineering strategies for yield improvement. It also examines material modification strategies, including blending, chemical grafting, surface functionalisation, electrospinning, and additive manufacturing, used to adapt PHAs for specific veterinary form factors. The clinical and preclinical evidence base is presented in detail across wound management, orthopaedic and soft-tissue regeneration, cardiovascular tissue engineering, drug delivery, and surgical devices, with attention to species-specific considerations in companion animals, horses, and food-producing ruminants. This review relies exclusively on peer-reviewed literature for its quantitative claims, while transparently noting where veterinary-specific data are lacking, extrapolated from rodent or human models, or in need of independent verification. Persistent barriers like production cost, batch-to-batch variability, absence of veterinary-specific regulatory pathways, and limited long-term in vivo safety data in large animals are analysed critically, alongside translational opportunities including waste-feedstock valorisation, hybrid PHA/ceramic and PHA/natural-polymer composites, and stimuli-responsive formulations. We conclude that PHAs are scientifically well positioned but institutionally under-validated for veterinary translation, and we outline a concrete research agenda to close this gap. Full article

Driven by the rapid development of deep-space exploration, artificial intelligence, and new energy vehicles, the integration density of power devices has been significantly improved, creating an urgent demand for electronic packaging interconnection materials with low thermal resistance, high reliability, and thermomechanical stress resistance. Porous metals have become a major research focus for packaging interconnection materials owing to their high specific surface area; controllable porous structure; and excellent thermal, electrical, and mechanical properties. Among various porous metals, porous metal has attracted extensive attention in the field of electronic packaging interconnection due to its low cost, high thermal conductivity, superior wettability, and good processability. This paper systematically reviews the research progress of porous copper (Cu)-based interconnection materials in electronic packaging, covering the preparation methods, interconnection methods and reliability of porous Cu-based interconnection materials. In addition, the existing challenges in the preparation, interconnection processes, and reliability evaluation are summarized, which provides clear research directions for the structural optimization and engineering application of such materials in the future. Full article

Air-cooled tricone bits are widely used on rotary drilling rigs to achieve high production rates in open-pit mines. Their performance and service life are influenced by rock properties, machine characteristics, and operational parameters. Hole flushing accounts for approximately 50% of the energy consumed during drilling and affects penetration rates, bit life, and drilling costs. Although studies have focused on selecting suitable tricone bits, nozzle diameter selection has received limited attention and is commonly based on manufacturer recommendations or theoretical calculations involving assumptions. In this study, a practical method was developed to determine an appropriate nozzle diameter for tricone bits used in an open-pit lignite mine in the Soma Basin of Türkiye. This method includes theoretical calculations, together with field measurements and observations, to verify whether the drill rig and compressor operate properly and whether the drilling-performance parameters remain within acceptable limits. The field results indicated that appropriately selected smaller nozzle diameters can direct more compressed air toward the bearings, improving cooling and reducing bearing-related wear, and contributing to longer bit life without adversely affecting drilling performance. The results show that nozzle selection should consider compressor capacity, airflow distribution, bearing protection, and field performance in addition to theoretical calculations. Full article

Aiming at the problems of high energy consumption, high carbon emissions from data centers and the difficulty of renewable energy accommodation in distribution networks driven by rapid growth in computing tasks, this paper proposes a collaborative trading method for data center–power grid–energy storage systems to improve spatiotemporal flexibility. Firstly, an integrated mechanism model including IT equipment, HVAC cooling systems, delay-tolerant batch tasks and UPS energy storage is established to quantify multi-dimensional internal flexible regulation potential. Secondly, an improved k-means algorithm is adopted for scenario reduction of wind–PV outputs, and a stochastic-robust collaborative trading optimization model considering carbon emission cost is constructed. Multiple practical constraints are incorporated, including power balance, power flow limits, nodal voltage bounds, task service latency and state of charge limits of energy storage. An improved particle swarm optimization with premature-convergence indicator is developed to solve this nonlinear, non-convex, mixed-variable problem. Simulations are carried out on a modified IEEE 33-node test system over a 24 h scheduling horizon. Numerical results demonstrate that compared with the conventional demand-response strategy, the proposed method reduces total operational cost by 10.7%, curtails wind–PV abandoned power, and achieves 28.6% peak-shaving ratio for data center load. Monte Carlo repeated experiments indicate that the improved Particle Swarm Optimization (PSO) reaches a 95% feasible solution rate with an average computation time of 26.8 s for day-ahead dispatch, which satisfies practical engineering requirements. Full article