Search Results (750)

Enhancing the real-world performance of sustainably designed and certified green buildings remains a significant challenge, particularly in hot climates where efforts to improve thermal comfort often conflict with energy efficiency goals. In the United Arab Emirates (UAE), even newly constructed facilities with green building certifications present opportunities for retrofitting and performance optimization. This study investigates the energy and thermal comfort performance of a LEED Gold-certified, mixed-use university campus in Dubai through a calibrated digital twin developed using IES thermal modelling software. The analysis evaluated existing sustainable design strategies alongside three retrofit energy conservation measures (ECMs): (1) improved building envelope U-values, (2) installation of additional daylight sensors, and (3) optimization of fan coil unit efficiency. Simulation results demonstrated that the three ECMs collectively achieved a total reduction of 15% in annual energy consumption. Thermal comfort was assessed using operative temperature distributions, Predicted Mean Vote (PMV), and Predicted Percentage of Dissatisfaction (PPD) metrics. While fan coil optimization yielded the highest energy savings, it led to less favorable comfort outcomes. In contrast, enhancing envelope U-values maintained indoor conditions consistently within ASHRAE-recommended comfort zones. To further support energy reduction and progress toward Net Zero targets, the study also evaluated the integration of a 228.87 kW rooftop solar photovoltaic (PV) system, which offset 8.09% of the campus’s annual energy demand. By applying data-driven thermal modelling to assess retrofit impacts on both energy performance and occupant comfort in a certified green building, this study addresses a critical gap in the literature and offers a replicable framework for advancing building performance in hot climate regions. Full article

In the present work, the optimization of ceramic-based composite WC(Co,Ni) welds by laser cladding was carried out using response surface methodology based on finite element analysis. The heat distribution and temperature field of laser-melted WC(Co,Ni) ceramic coatings were simulated using ANSYS software, which allowed the computation of the distribution of residual stresses. The results show that the isotherms in the simulation of the temperature field are elliptical in shape, and that the isotherms in front of the moving heat source are dense with a larger temperature gradient, while the isotherms behind the heat source are sparse with a smaller temperature gradient. In addition, the observed microstructural evolution shows that the melting zone domains of WC(Co,Ni) are mainly composed of unmelted carbides. These carbides are dendritic, rod-like, leaf-like, or net-like, and are agglomerated into smaller groups. The W content of these unmelted carbides exceeds 80%, while the C content is around 1.5–3.0%. The grey areas are composed of WC, Co and Ni compounds. Based on the regression model, a quadratic model was successfully constructed. A three-dimensional profile model of the residual stress behaviour was further explored. The estimated values of the RSM-based FEA model for residual stress are very similar to the actual results, which shows that the model is effective in reducing residual stress by laser cladding. Full article

Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions between hydrological drivers and ecosystem responses by analyzing daily eddy covariance flux data from a wetland forest in North Carolina, USA, spanning 2009–2019. We analyzed temporal patterns of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RE) under both flooded and non-flooded conditions and evaluated their relationships with observed tree mortality. Generalized Additive Modeling (GAM) revealed that groundwater table depth (GWT), leaf area index (LAI), NEE, and net radiation (Rn) were key predictors of mortality transitions (R² = 0.98). Elevated GWT induces root anoxia; declining LAI reduces productivity; elevated NEE signals physiological breakdown; and higher Rn may amplify evapotranspiration stress. Receiver Operating Characteristic (ROC) analysis revealed critical early warning thresholds for tree mortality: GWT = 2.23 cm, LAI = 2.99, NEE = 1.27 g C m⁻² d⁻¹, and Rn = 167.54 W m⁻². These values offer a basis for forecasting forest mortality risk and guiding early warning systems. Our findings highlight the dominant role of hydrological variability in ecosystem degradation and offer a threshold-based framework for early detection of mortality risks. This approach provides insights into managing coastal forest resilience amid accelerating sea level rise. Full article

This paper aims to find an efficient optimization algorithm to bring down the cost function without compromising the stability of the system and respect the operational constraints of the Hybrid Renewable Energy System. To accomplish this, MATLAB simulations were carried out using three optimization techniques: Grey Wolf Optimization (GWO), Teaching–Learning-Based Optimization (TLBO), and Multi-Objective Particle Swarm Optimization (MOPSO). The study compared their outcomes to identify which method yielded the most effective performance. The research included a statistical analysis to evaluate how consistently and stably each optimization method performed. The analysis revealed optimal values for the output power of photovoltaic systems (PVs), wind turbines (WTs), diesel generator capacity (DGs), and battery storage (BS). A one-year period was used to confirm the optimized configuration through the analysis of capital investment and fuel consumption. Among the three methods, GWO achieved the best fitness value of 0.24593 with an LPSP of 0.12528, indicating high system reliability. MOPSO exhibited the fastest convergence behaviour. TLBO yielded the lowest Net Present Cost (NPC) of 213,440 and a Cost of Energy (COE) of 1.91446/kW, though with a comparatively higher fitness value of 0.26628. The analysis suggests that GWO is suitable for applications requiring high reliability, TLBO is preferable for cost-sensitive solutions, and MOPSO is advantageous for obtaining quick, approximate results. Full article

Objectives: This study examined the impact of a low-sugar flavored beverage on total fluid intake and hydration biomarkers during intermittent exercise in a hot environment among healthy children. Methods: Twenty-one children (11 girls, 8–10 y) completed a randomized, crossover study with two trials. Each trial involved three bouts of 10 min walking, 5 min rest, 10 min walking, and 35 min rest for a total of 3 h in a hot (29.9 ± 0.6 °C) and dry environment (26 ± 7% relative humidity). Walking intensity was 69 ± 7% of age-predicted maximum heart rate. Participants consumed either plain water (W) or a low-sugar flavored beverage (FB). Body weight, fluid intake, urine samples, and perceptual ratings were collected. Results: Total ad libitum fluid intake was significantly higher with the FB (946 ± 535 mL) than with W (531 ± 267 mL; p < 0.05). This difference was 128% higher for FB compared to W, with 19 out of the 21 children ingesting more fluids in FB versus W. Children rated the FB as more likable across all time points (p < 0.05). Net fluid balance was better with FB at 60, 70, 85, 135, and 145 min (p < 0.05), though not different at the 3 h mark. Urine volume was higher with FB (727 ± 291 mL) than with W (400 ± 293 mL; p < 0.05). Urine osmolality was significantly higher in the W trial at 120 and 180 min (p < 0.05). Conclusions: A flavored, low-sugar beverage enhanced ad libitum fluid intake and improved hydration markers compared to water during exercise in the heat, supporting its potential as a practical rehydration strategy for children. Full article

Dark asphalt surfaces, absorbing about 95% of solar radiation and warming to 60–70 °C during summer, intensify urban heat while providing substantial prospects for energy extraction. This review evaluates four primary technologies—asphalt solar collectors (ASCs, including phase change material (PCM) integration), photovoltaic (PV) systems, vibration-based harvesting, thermoelectric generators (TEGs)—focusing on their principles, efficiencies, and urban applications. ASCs achieve up to 30% efficiency with a 150–300 W/m² output, reducing pavement temperatures by 0.5–3.2 °C, while PV pavements yield 42–49% efficiency, generating 245 kWh/m² and lowering temperatures by an average of 6.4 °C. Piezoelectric transducers produce 50.41 mW under traffic loads, and TEGs deliver 0.3–5.0 W with a 23 °C gradient. Applications include powering sensors, streetlights, and de-icing systems, with ASCs extending pavement life by 3 years. Hybrid systems, like PV/T, achieve 37.31% efficiency, enhancing UHI mitigation and emissions reduction. Economically, ASCs offer a 5-year payback period with a USD 3000 net present value, though PV and piezoelectric systems face cost and durability challenges. Environmental benefits include 30–40% heat retention for winter use and 17% increased PV self-use with EV integration. Despite significant potential, high costs and scalability issues hinder adoption. Future research should optimize designs, develop adaptive materials, and validate systems under real-world conditions to advance sustainable urban infrastructure. Full article

Improving photovoltaic (PV) panel performance under extreme climatic conditions is critical for advancing sustainable energy systems. In hyper-arid regions, elevated operating temperatures significantly reduce panel efficiency. This study investigates and compares three cooling techniques—air cooling, water cooling, and porous media cooling—using thermal and electrical modeling based on CFD simulations in ANSYS. The numerical model replicates a PV system operating under peak solar irradiance (900 W/m²) and realistic ambient conditions in Adrar, Algeria. Simulation results show that air cooling leads to a modest temperature reduction of 6 °C and a marginal efficiency gain of 0.25%. Water cooling, employing a top-down laminar flow, reduces cell temperature by over 35 °C and improves net electrical output by 30.9%, despite pump energy consumption. Porous media cooling, leveraging passive evaporation through gravel, decreases panel temperature by around 30 °C and achieves a net output gain of 26.3%. Mesh sensitivity and validation against experimental data support the accuracy of the model. These findings highlight the significant potential of water and porous material cooling strategies to enhance PV performance in hyper-arid environments. The study also demonstrates that porous media can deliver high thermal effectiveness with minimal energy input, making it a suitable low-cost option for off-grid applications. Future work will integrate long-term climate data, real diffuser geometries, and experimental validation to further refine these models. Full article

Structural health monitoring in resource-constrained environments demands crack segmentation models that match the accuracy of heavyweight convolutional networks while conforming to the power, memory, and latency limits of watt-level edge devices. This study presents a lightweight dual-attention network, which is a four-stage U-Net compressed to one-quarter of the channel depth and augmented—exclusively at the deepest layer—with a compact dual-attention block that couples channel excitation with spatial self-attention. The added mechanism increases computation by only 19%, limits the weight budget to 7.4 MB, and remains fully compatible with post-training INT8 quantization. On a pixel-labelled concrete crack benchmark, the proposed network achieves an intersection over union of 0.827 and an F1 score of 0.905, thus outperforming CrackTree, Hybrid 2020, MobileNetV3, and ESPNetv2. While refined weight initialization and Dice-augmented loss provide slight improvements, ablation experiments show that the dual-attention module is the main factor influencing accuracy. With 110 frames per second on a 10 W Jetson Nano and 220 frames per second on a 5 W Coral TPU achieved without observable accuracy loss, hardware-in-the-loop tests validate real-time viability. Thus, the proposed network offers cutting-edge crack segmentation at the kiloflop scale, thus facilitating ongoing, on-device civil infrastructure inspection. Full article

The utilization of thermal energy from co-produced water during natural gas production offers a promising pathway to enhance energy efficiency and reduce carbon emissions. This study proposes a techno-economic evaluation model to assess the feasibility and profitability of geothermal energy recovery from co-produced water in marginal gas wells. A wellbore fluid flow and heat transfer model is developed and validated against field data, with deviations in calculated wellhead temperature and pressure within 10%, demonstrating the model’s reliability. Sensitivity analyses are conducted to investigate the influence of key technical and economic parameters on project performance. The results show that electricity price, heat price, and especially government one-off subsidies have a significant impact on the net present value (NPV), whereas the effects of insulation length and annular fluid thermal conductivity are comparatively limited. Under optimal conditions—including 2048 m of insulated tubing, annular protection fluid with a thermal conductivity of 0.4 W/(m·°C), a 30% increase in heat and electricity prices, and a 30% government capital subsidy—the project breaks even in the 14th year, with the 50-year NPV reaching 0.896 M$. This study provides a practical framework for evaluating and optimizing geothermal energy recovery from co-produced water, offering guidance for future sustainable energy development. Full article

Objectives: The objective of this study was to examine the neuromuscular fatigue response to playing in a singles pickleball tournament, as measured by performance on a countermovement jump test (CMJ). We hypothesized that players would exhibit neuromuscular fatigue after the tournament. Methods: Six adult pickleball players (five male and one female, M ± SD: 40.2 ± 10.1 years old, height = 178.7 ± 12.3 cm, body mass = 85.4 ± 16.7 kg) participated in a 15 game singles pickleball tournament. Prior to the tournament, everyone completed the CMJ to assess lower body strength and power on paired Hawkin Dynamics force plates. After the tournament, players repeated the CMJ. Mixed-effects regression modeling was used to examine changes in key outcomes measured from the CMJ. Results: All nine outcomes from the CMJ significantly changed from pre to post-tournament (e.g., means for net impulse increased from 2.32 ± 0.22 to 2.40 ± 0.18 N·s, p = 0.0006; RSImod increased from 0.28 ± 0.07 to 0.33 ± 0.05, p = 0.0001, and propulsive peak power increased from 41.79 ± 6.14 to 44.34 ± 4.70 W/kg, p < 0.0001). All the changes demonstrated improved performance in the CMJ test. Seven out of the nine outcomes demonstrated a large effect size by the partial-eta square statistic, with η²-partial of 0.153–0.487, and three key outcomes (RSImod, propulsive peak power, and propulsive mean power) also demonstrated large effect sizes by the F² statistic (F² of 0.4603–0.9495). Conclusions: Contrary to our hypothesis, participants did not demonstrate significant neuromuscular fatigue. In contrast, they showed significant improvements in CMJ performance. It is possible that adequate rest between games prevented neuromuscular fatigue; alternately, singles pickleball may not provide enough stimulus in the lower body musculature to induce neuromuscular fatigue. Full article

Unveiling the relationship between the “Water–Carbon–Ecology” (W-C-E) footprints embodied in regional trade and resource flows is crucial for enhancing the synergistic benefits between economic development and environmental protection. This study constructs an association framework based on the Multi-Regional Input–Output (MRIO) model to systematically evaluate the “W-C-E” footprints and resource flow characteristics of the Yangtze River Economic Belt and the Yellow River Basin. By integrating import and export trade data, this study reveals the patterns of resource flows within and outside these regions. This research delineates the connection patterns between the “W-C-E” footprints and resource flows across three dimensions: spatial, sectoral, and environmental–economic factors. The results indicate that the Yangtze River Economic Belt has gained significant economic benefits from regional trade but also bears substantial environmental costs. Import and export trade further exacerbate the imbalance in regional resource flows, with the Yangtze River Economic Belt exporting many embodied resources through high-energy-consuming products, while the Yellow River Basin increases resource input by importing products such as food and tobacco. Sectoral analysis reveals that agriculture, electricity and water supply, and mining are the sectors with the highest net output of “W-C-E” footprints in both regions, whereas services, food and tobacco, and construction are the sectors with the highest net input. The comprehensive framework of this study can be extended to the analysis of resource–environment–economic systems in other regions, providing methodological support for depicting complex human–land system linkage patterns. Full article

With rising energy costs and the need for sustainable power solutions in urban South African settings, grid-tied renewable energy systems have become viable alternatives for reducing dependence on traditional grid supply. This study investigates the techno-economic feasibility of a grid-connected hybrid photovoltaic (PV) and battery storage system designed for a commercial facility located in Johannesburg, South Africa—an area characterized by a subtropical highland climate. We conducted the analysis using the HOMER Grid software and evaluated the performance of the proposed PV/battery system against the baseline grid-only configuration. Simulation results indicate that the optimal systems, comprising 337 kW of flat-plate PV and 901 kWh of lithium-ion battery storage, offers a significant reduction in electricity expenditure, lowering the annual utility cost from $39,229 to $897. The system demonstrates a simple payback period of less than two years and achieves a net present value (NPV) of approximately $449,491 over a 25-year project lifespan. In addition to delivering substantial cost savings, the proposed configuration also enhances energy resilience. Sensitivity analyses were conducted to assess the impact of variables such as inflation rate, discount rate, and load profile fluctuations on system performance and economic returns. The results affirm the suitability of hybrid grid-tied PV/battery systems for cost-effective, sustainable urban energy solutions in climates with high solar potential. Full article

This article uses FLUENT to construct a two-dimensional axisymmetric numerical model of a cryogenic hydrogen charging pipeline. By loading with initial temperature gradient and transient initial pressure disturbance, the basic characteristics of low-temperature hydrogen Taconis thermoacoustic oscillation are calculated, including temperature, heat flux density distribution, pressure amplitude, and frequency. The instability boundary of hydrogen TAO is also obtained. The results show that (1) the temperature distribution and flow characteristics of the gas inside the pipeline exhibit significant periodic changes. In the first half of the oscillation period, the cold-end gas moves towards the end of the pipeline. Low-viscosity cold hydrogen is easily heated and rapidly expands. In the second half of the cycle, the expanding cold gas pushes the hot-end gas to move towards the cold end, forming a low-pressure zone and causing gas backflow. (2) Thermoacoustic oscillation can also cause additional thermal leakage on the pipeline wall. The average heat flux during one cycle is 1150.1 W/m² for inflow and 1087.7 W/m² for outflow, with a net inflow heat flux of 62.4 W/m². (3) The instability boundary of the system is mainly determined by the temperature ratio of the cold and hot ends α, temperature gradient β, and length ratio of the cold and hot ends ξ. Increasing the pipe diameter and minimizing the pipe length can effectively weaken the amplitude of thermoacoustic oscillations. This study provides theoretical support for predicting thermoacoustic oscillations in low-temperature hydrogen transport pipeline systems and offers insights for system stability control and design verification. Full article

Powder injection molding (PIM) has been used to produce nearly net-shaped samples of tungsten-based alloys. These alloys have been previously shown to have favorable characteristics when compared with standard ITER-grade tungsten. Six different alloys were produced with this method: W-1TiC, W-2Y₂O₃, W-3Re-1TiC, W-3Re-2Y₂O₃, W-1HfC and W-1La₂O₃-1TiC. These were tested alongside ITER-grade tungsten in the PSI-2 linear plasma device under ITER-relevant plasma and heat loads to assess their suitability for use in a fusion reactor. All materials showed good behavior when exposed to the lower pulse number tests (≤1000 ELM-like pulses), although standard tungsten performed slightly better, with no observable difference in surface roughness. High-power shots, namely one laser pulse of 1.6 GWm⁻², revealed that samples containing yttria are more prone to melting and droplet ejection. After high pulse number tests (10,000 and 100,000 pulses), with and without plasma, the reference tungsten showed the most cracking and highest surface roughness of all materials, while the PIM samples seemed to have a higher resistance to cracking. This can be attributed to the higher ductility of these alloys, particularly those containing rhenium. This means that tungsten-based alloys, whether produced via PIM or other methods, could potentially be used in certain areas of a fusion reactor. Full article

Underwater image enhancement is a challenging task due to the unique optical properties of water, which often lead to color distortion, low contrast, and detail loss. At the present stage, the methods based on the CNN have the problem of insufficient global attention, and the methods based on Transformer generally have the problem of quadratic complexity. To address this challenge, we propose a dual-branch network architecture based on the W-shaped Mamba: UWMambaNet. Our method integrates the color contrast enhancement branch and the detail enhancement branch, and each branch is dedicated to improving specific aspects of underwater images. The color contrast enhancement branch utilizes the RGB and Lab color spaces and uses the Mamba block for advanced feature fusion to enhance color fidelity and contrast. The detail enhancement branch adopts a multi-scale feature extraction strategy to capture fine and contextual details through parallel convolutional paths. The Mamba module is added to the dual branches, and state-space modeling is used to capture the long-range dependencies and spatial relationships in the image data. This enables effective modeling of the complex interactions and light propagation effects inherent in the underwater environment. Experimental results show that our method significantly improves the visual quality of underwater images and is superior to existing technologies in terms of quantitative indicators and visualization effects; compared to the best candidate models on the UIEB and EUVP datasets, UWMambaNet improves UCIQE by 3.7% and 2.4%, respectively. Full article