Search Results (50,013)

Offshore wind energy is emerging as a vital component of the global transition to renewable energy, leveraging consistent wind conditions and higher power density compared to onshore systems. Integrating variable offshore wind power with hydrogen production via electrolysis provides a strategic pathway to convert surplus electricity into a storable and transportable energy carrier, thereby mitigating grid congestion, curtailment, and variability challenges. This review systematically examines the integration of offshore wind farms and hydrogen production technologies. Key components of the review include a comparative analysis of electrolyzer technologies, their suitability for offshore deployment, and the implications for energy storage and transport. The analysis employs a multi-step framework: (1) extensive search of the literature in scientific databases, (2) qualitative and quantitative assessment of system performance, and (3) synthesis of findings to identify trends and research gaps, enabling a thorough examination of technical challenges in the marine environment, and economic and policy barriers. The review highlights recent advancements, technical challenges, and economic considerations related to deployment of offshore wind-to-hydrogen systems. This review provides a comprehensive understanding of the current state of offshore hydrogen production, identifies research gaps, and outlines policy recommendations to accelerate its deployment. Offshore wind-powered hydrogen emerges as a cornerstone of a resilient, low-carbon energy future. The systematic approach ensures actionable insights and robust conclusions, facilitating the alignment of technological advancements with global decarbonization goals. Full article

Mission-oriented supply chains involve multi-phase tasks, strong resource interdependencies, and stringent reliability requirements, which make demand planning complex and uncertain. This study develops a structured demand modeling framework to support multi-phase mission-oriented supply chains under budget and reliability constraints by integrating digital twin technology with an adaptive inertia weight particle swarm optimization (AIW-PSO) algorithm. The supply support process is decomposed into four sequential phases—storage, transportation, preparation, and execution—and phase-specific demand models are constructed based on system reliability theory, explicitly incorporating redundancy, maintainability, and repairability. In this work, digital twin technology functions as a data acquisition and virtual experimentation layer that supports parameter calibration, state-aware scenario simulation, and event-triggered re-optimization rather than continuous real-time control. Physical-state updates are mapped to model parameters such as phase durations, failure rates, repair rates, and instantaneous availability, after which the integrated optimization model is re-solved using a warm-start strategy to generate updated demand plans. The resulting multi-phase demand optimization problem is solved using AIW-PSO to enhance global search performance and mitigate premature convergence. The proposed method is validated using a representative mission-oriented supply support scenario with operational and simulated data. Simulation results demonstrate that, under identical budget constraints, the proposed approach achieves higher mission completion capability than conventional PSO-based methods, providing effective and practical decision support for multi-phase mission-oriented supply chain planning. Full article

The physiological relevance of in vitro models is limited because conventional two-dimensional cell culture systems are unable to replicate the structural and functional complexity of native tissues. Extracellular matrix (ECM)-mimetic hydrogels have become important platforms for tissue engineering applications. This work developed hybrid hydrogels that mimic important biochemical and mechanical characteristics of cardiac tissue by combining decellularized bovine pericardium-derived (dBP) ECM, gellan gum (GG), and spermine (SPM). Although dBP offers tissue-specific biological cues, processing compromises its mechanical integrity. This limitation was overcome by adding GG, whose ionic gelation properties were optimized using DMEM and SPM. The hydrogels’ mechanical, biological, physicochemical, and structural characteristics were all evaluated. Under physiologically simulated conditions, the formulations showed quick gelation and long-term stability; scanning electron microscopy revealed an interconnected, ECM-like porous microarchitecture. While uniaxial compression testing provided Young’s modulus values comparable to native myocardium, rheological analysis revealed a concentration-dependent increase in storage modulus with increasing SPM content. H9C2 cardiomyoblasts were used in cytocompatibility studies to confirm that cell viability, morphology, and cytoskeletal organization were all preserved. All of these findings support the potential application of dBP−GG−SPM hydrogels in advanced in vitro cardiac models by showing that they successfully replicate important characteristics of cardiac ECM. Full article

Urban integrated energy systems (UIESs) are increasingly exposed to uncertainties arising from wind and photovoltaic variability, load fluctuations, and equipment failures, highlighting the need for refined reserve assessment and coordinated operation. This study develops a unified framework that jointly models renewable and load deviations together with a load-dependent failure probability model, using Monte Carlo sampling and K-means scenario reduction to obtain representative system states. A reserve-capacity-oriented optimisation model is formulated to minimise total operating cost—including thermal generation, energy-storage operation, and reserve cost—while satisfying power balance, reserve adequacy, unit operating limits, and state-of-charge constraints. Application to a UIES comprising a 1000 kW load, 800 kW photovoltaic unit, 100 kW wind turbine, five thermal power units (total capacity 1000 kW), and a 250 kW/370 kWh energy storage system shows that reserve requirements fluctuate between −100 kW (downward) and 500 kW (upward) across different scenarios, with uncertainty-driven reserves dominating and failure-related reserves remaining below 100 kW. The optimisation results indicate coordinated operation between thermal units and storage, with storage absorbing surplus renewable output, supporting peak shaving, and providing most upward and all downward reserves. The total operating costs under typical summer and winter scenarios are 2264.02 CNY and 3122.89 CNY, respectively, confirming the method’s ability to improve reserve estimation accuracy and support economical and reliable UIES operation under uncertainty. Full article

Phenyl-silicone rubber is the elastomer of choice for cryogenic and high-temperature static seals, yet quantitative links between thermo-oxidative aging and sealing reliability are still lacking. Here, sub-ambient (−70 °C to 25 °C) and room-temperature mechanical tests, compression set aging, SEM, FT-IR, and finite-element simulations are integrated to trace how aging translates into contact-pressure decay of an Omega-profile gasket. Compression set rises monotonically with time and temperature; an Arrhenius model derived from 80 to 140 °C data predicts 34 d (10% set) and 286 d (45% set) of storage life at 25 °C. SEM reveals a progressive shift from ductile dimple fracture to brittle, honeycomb porosity, while FT-IR confirms limited surface oxidation without bulk chain scission. Finite element analyses show that contact pressure always peaks at the two lateral necks; short-term aging increases in the shear modulus C₁₀ from 1.87 to 2.27 MPa, raising CPRESS by 8~21%, yet this benefit is ultimately offset by displacement loss from compression set (8.0 mm to 6.1 mm), yielding a net pressure reduction of 0.006 MPa. Critically, even under the most severe coupled condition (56 days aging with compression set), the predicted CPRESS remains above the 0.1 MPa leak-tightness criterion across the entire cryogenic service envelope. This framework provides deterministic boundaries for temperature, aging duration, and allowable preload relaxation, enabling risk-informed maintenance and replacement scheduling for safety-critical phenyl-silicone seals. Full article

Fish is highly prone to spoilage due to a combination of intrinsic biochemical processes and microbial proliferation, which together drive rapid quality deterioration during post-harvest handling and storage. These processes are further accelerated by factors such as elevated temperatures, mechanical damage, and suboptimal handling. In Mediterranean aquaculture, ice slurry is the standard harvesting method. This study aimed to characterize the initial post-harvest enzymatic activity of key proteolytic enzymes, calpain, collagenase, cathepsin B (CTSB), and cathepsin L (CTSL), in the white muscle of three commercially important species (Sparus aurata, Dicentrarchus labrax, and Pagrus major) harvested under standard practices across three seawater harvest temperatures (low, medium, and high). Muscle samples were collected over a 13-day chilled storage period post-harvest, and enzymatic activity was assessed using standardized fluorometric assays. Our findings establish the basal post-mortem proteolytic profiles for each species and reveal marked species-specific differences in enzyme activity patterns. Calpain and collagenase exhibited early and parallel activation, while CTSB and CTSL showed a coordinated increase during storage. Harvest temperature emerged as a critical factor, with the highest enzymatic activities consistently observed during the moderate temperature period. These results underscore the importance of species-specific physiology and seasonal conditions in shaping post-harvest filet degradation, offering a basis for refining harvest strategies to enhance quality management in Mediterranean aquaculture. Full article

Ecosystem vulnerability assessment is paramount for local environmental stability and lasting economic progress. This study selects Hubei Province as the research area, applying multi-source spatiotemporal datasets spanning the period 2000–2023. A pressure–state–response (PSR) framework, incorporating 14 distinct indicators, was developed. The selection criteria for these indicators adhered to principles of scientific rigor, all-encompassing scope, statistical representativeness, and practical applicability. The chosen indicators effectively encompass natural, anthropogenic, and socio-economic drivers, aligning with the specific ecological attributes and key vulnerability factors pertinent to Hubei Province. The analytic network process (ANP) method and entropy weighting (EW) method were integrated to ascertain comprehensive weights, thereby computing the ecological vulnerability index (EVI). In the meantime, we analyzed temporal and spatial EVI shifts. Spatial autocorrelation analysis, the geodetic detector, the Theil–Sen median, the Mann–Kendall trend test, and the Grey–Markov model were employed to elucidate spatial distribution, driving factors, and future trends. Results indicate that Hubei Province exhibited mild ecological vulnerability from 2000 to 2023, but with a notable deteriorating trend: extreme vulnerability areas expanded from 0.34% to 0.94%, while moderate and severe vulnerability zones also increased. Eastern regions demonstrate elevated vulnerability, but they were lower in the west, correlating with human activity intensity. The global Moran’s I index ranged from 0.8579 to 0.8725, signifying a significant positive spatial correlation of ecological vulnerability, with the highly vulnerable areas concentrated in regions with intense human activities, while the less vulnerable areas are located in ecologically intact areas. Habitat quality index and carbon sinks emerged as key drivers, possibly stemming from the forest–wetland composite ecosystem’s high dependence on water conservation, biodiversity maintenance, and carbon storage functions. Future projections based on Grey–Markov models indicate that ecological fragility in Hubei Province will exhibit an upward trend, with ecological conservation pressures continuing to intensify. This research offers a preliminary reference basis of grounds for ecological zoning, as well as sustainable regional development in Hubei Province, while also providing a theoretical and practical framework for constructing an ecological security pattern within the Yangtze River Economic Belt (YREB) and facilitating ecological governance in analogous river basins globally, thereby contributing to regional sustainable development goals. Full article

Large field-of-view (FOV) infrared imaging, widely utilized in applications including target detection and remote sensing, generates massive datasets that pose significant challenges for transmission and storage. To address this issue, we propose an efficient lossless compression method for large FOV infrared video. Our approach employs a hybrid prediction strategy within the transform domain. The video frames are first decomposed into low- and high-frequency components via the discrete wavelet transform. For the low-frequency subbands, an improved low-latency Multi-view High-Efficiency Video Coding (MV-HEVC) encoder is adopted, where the background reference frames are treated as one view to enable more accurate inter-frame prediction. For high-frequency components, pixel-wise clustered edge prediction is applied. Furthermore, the prediction residuals are reduced by optimal direction prediction, according to the principle of minimizing residual energy. Experimental results demonstrate that our method significantly outperforms mainstream video compression techniques. While maintaining compression performance comparable to MV-HEVC, the proposed method exhibits a 19.3-fold improvement in computational efficiency. Full article

Depleted oil and gas reservoirs, owing to their large storage capacity and well-established infrastructure, are attractive sites for storing green energy carriers such as natural gas, hydrogen, and compressed air. During injection–production cycling in underground gas storage (UGS), variations in effective stress can cause repeated stress disturbances in the reservoir and surrounding rock, which may trigger borehole sand production. In this study, laboratory sand-production simulation tests were conducted to evaluate the effects of cyclic-loading stage, upper stress limit, and cycling frequency on borehole damage and sand-production behavior. The results show that sand production is stage-dependent. During the rapid-hardening and stable stages, the borehole remains largely intact and sand production is negligible. Once the failure and collapse stages are reached, borehole integrity deteriorates and sand production increases sharply, with fine particles becoming dominant. Cumulative sand production increases with the upper stress limit. Increasing the upper limit from 80% to 95% leads to a 2.53-fold increase in produced sand mass, together with a higher fine-sand fraction and a shift in the particle-size distribution (PSD) toward smaller sizes. The cycling frequency also plays an important role. When the frequency decreases, cumulative sand production increases and becomes 53.1% higher than the baseline at 0.001 Hz. Meanwhile, the median particle size (D50) decreases, indicating stronger particle breakage under low-frequency cycling. These findings provide guidance for designing injection–production schemes for UGS and for selecting appropriate sand-control completion strategies. Full article

The demand for ready-to-eat salads made from leafy vegetables such as wild rocket (Diplotaxis tenuifolia L.) continues to increase, driven by consumer preference for convenience foods with high levels of bioactive compounds. However, reducing the environmental impact of wild rocket production requires both organically enriched growing substrates and sustainable alternatives to conventional plastic packaging. This study assessed the effects of three cultivation substrates and three biodegradable packaging materials (polylactic acid (PL), cellulose kraft (CK), and kraft-reinforced polylactic acid (PLK)) on the postharvest performance of wild rocket stored at 4 °C for 7 and 14 days. Plants were grown in coco peat (CP), coco peat supplemented with livestock compost (90:10; CP+LC), and coco peat mixed with mushroom compost (50:50; CP+MC). Yield and key pre- and postharvest quality attributes, including nitrate accumulation, phenolic content, antioxidant capacity, colour, and weight loss, were evaluated. The CP+LC substrate resulted in the highest harvest yield, whereas CP promoted higher phenolic content and antioxidant capacity. Among the packaging materials, PLK provided the most balanced internal atmosphere, effectively reducing dehydration and condensation while preserving superior sensory quality after 14 days of storage. Overall, the combination of organic compost amendments, particularly CP+LC, with PLK bio-based packaging represents a promising and sustainable strategy for maintaining postharvest quality and reduce the environmental footprint of minimally processed wild rocket within short food supply chains. Full article

Semi-dry desulfurization ash (SDA) is generated in rapidly increasing quantities and remains underutilised, despite its high CaO content, which makes it a promising candidate for CO₂ storage via carbonation curing. However, the carbonation behaviour and consolidation mechanism of standalone SDA compacts are not yet well understood. In this study, SDA compacts were prepared at water-to-solid (w/s) ratios of 1.5:10 and 1.83:10 and subjected to carbonation curing for 0–24 h under controlled CO₂ conditions. Compressive strength, CO₂ uptake, and microstructural evolution were assessed using XRD, TG–DTG, FTIR, and SEM. CO₂ uptake increased with curing time and reached approximately 20% after 24 h, whereas compressive strength exhibited a non-linear response, peaking at 8.67 MPa after 6 h at w/s = 1.5:10 and declining thereafter. Phase and microstructural analyses indicate that strength development is governed by the transformation of Ca(OH)₂ to CaCO₃ polymorphs, with early densification followed by increased porosity as calcite coarsens. Sulphur-bearing phases (e.g., CaSO₃·0.5H₂O) remain largely inert under the tested conditions. These findings demonstrate that carbonation curing can significantly enhance CO₂ fixation in SDA and generate low-strength construction materials while also highlighting the need to optimise mix design and curing parameters to mitigate strength loss at extended curing times. Full article

Phase change materials (PCMs) have emerged as an innovative solution in thermal energy storage and thermal management systems (TMS) owing to their outstanding latent heat of fusion during the phase change process. This study is especially addressed to the battery TMS based on Organic PCMs for fast charging/discharging applications of lithium-ion batteries (LIBs). These fast processes generate excessive heat during operation, degrade battery performance, decrease energy efficiency, and reduce the lifespan and safety of batteries. Organic PCMs exhibit desirable properties, including high latent heat capacity, good thermal characteristics, low cost, and ease of integration. The major challenge for the successful application of organic PCM comprises its low thermal conductivity, which impacts the heat storage and release rates. PCM-based Paraffin Wax (PW) has been designed by including expanded graphite (EG) as a high thermal conductivity additive in high latent heat of paraffin wax. Experiments focused on the effects of heating methods (microwaves/S-type EG composition and conventional electric oven/S’-type EG composition) of expandable graphite on the thermophysical properties of different PW/EG composites. The crystal and chemical structure of the study samples were analyzed by X-ray diffraction and Fourier-Transform Infrared spectroscopy. The battery module created with PW/EG composites were ample examined using charging/discharging experiments at five different C-rates. The effect of current rates on battery surface temperature is investigated in two cases: with PCM cooling and with air cooling. A 20.43% decrease in battery temperature is found at 5C rate with PCM cooling and a maximum reduction in battery charging time of 43.77%. Full article

The growing demand for electricity in residential sectors and the global need to decarbonize power systems are accelerating the transformation toward smart and sustainable energy networks. Smart homes and smart grids, integrating renewable generation, energy storage, and intelligent control systems, represent a crucial step toward achieving energy efficiency and carbon neutrality. However, ensuring real-time optimization, interoperability, and sustainability across these distributed energy resources (DERs) remains a key challenge. This paper presents a comprehensive review of artificial intelligence (AI) applications for sustainable energy management and low-carbon technology integration in smart grids and smart homes. The review explores how AI-driven techniques include machine learning, deep learning, and bio-inspired optimization algorithms such as particle swarm optimization (PSO), whale optimization algorithm (WOA), and cuckoo optimization algorithm (COA) enhance forecasting, adaptive scheduling, and real-time energy optimization. These techniques have shown significant potential in improving demand-side management, dynamic load balancing, and renewable energy utilization efficiency. Moreover, AI-based home energy management systems (HEMSs) enable predictive control and seamless coordination between grid operations and distributed generation. This review also discusses current barriers, including data heterogeneity, computational overhead, and the lack of standardized integration frameworks. Future directions highlight the need for lightweight, scalable, and explainable AI models that support decentralized decision-making in cyber-physical energy systems. Overall, this paper emphasizes the transformative role of AI in enabling sustainable, flexible, and intelligent power management across smart residential and grid-level systems, supporting global energy transition goals and contributing to the realization of carbon-neutral communities. Full article

This study introduces a predictive model based on artificial neural networks (ANNs) for estimating the dynamic performance of commercially available sensible thermal energy storage (STES) systems. The model was trained and validated using high-resolution experimental data measured from two vertical cylindrical tanks (0.3 m³ each) including internal heat exchangers and operating under both heating and cooling modes. A comprehensive sensitivity analysis was conducted on 28 ANN architectures by varying the number of hidden neurons and input delays. The optimal configuration, designated as ANN5 (12 neurons, delay = 1), demonstrated superior accuracy in predicting temperature profiles and energy exchange. Validation against an independent dataset confirmed the model’s robustness, achieving normalized root mean square errors (NRMSEs) between 0.0022 and 0.0061 for the hot tank and between 0.0057 and 0.0283 for the cold tank. Energy prediction errors were within −3.87% for charging and 0.09% for discharging in heating mode, and 7.08% for charging and 0.13% discharging in cooling mode, respectively. These results highlight the potential of ANN-based approaches for real-time control, forecasting, and digital twin applications in STES systems. Full article

Smart agricultural systems need stable thermal environments for greenhouses, livestock housing, and on-farm processing. However, renewable heat sources such as solar collectors and heat pumps often cause fluctuations that challenge reliable operation. Thermal energy storage (TES)—particularly water-based sensible tanks, stratified reservoirs, and phase-change material (PCM) systems—provides an effective solution by decoupling heat supply and demand. In this review, tank-based TES technologies for agricultural applications, focusing on design, integration with renewable energy systems, and control strategies, are critically examined. Key performance aspects, including thermal stratification, state-of-charge estimation, and advanced predictive control, are analyzed to identify best practices and limitations. The review finds that sensible TES remains dominant in farm applications due to its low cost and durability, while latent (PCM/ice) and thermochemical storage provide a higher energy density and long-duration potential but are presently limited by material stability, system complexity, and cost. From an environmental perspective, TES contributes to reducing fossil fuel dependence, improving resource efficiency, lowering greenhouse gas emissions, and boosting the resilience of rural farming systems. Overall, TES is recognized as a key enabling technology for climate-smart, energy-efficient, and sustainable agricultural operations. However, remaining research gaps include long-term field validation, standardized performance metrics, and life-cycle environmental assessment. Full article