Search Results (2,389)

Surface icing poses a significant risk to unmanned aerial vehicles (UAVs) and compact aerospace platforms, where limited onboard power and space require efficient anti-/de-icing surfaces. In this study, micro/nanostructures were fabricated on TC4 titanium alloy (Ti–6Al–4V) surfaces by femtosecond laser processing at different scanning speeds. The effects of scanning speed on surface morphology, wettability, static freezing, dynamic droplet behavior, and electrothermal de-icing performance were systematically investigated. Increasing the scanning speed induced nonlinear changes in microstructure height and surface roughness, while variations in ablation intensity caused nonuniform material redistribution. The surface processed at 250 mm/s showed the best anti-icing performance, with a water contact angle of 157.5 ± 0.5° and a maximum freezing delay 21.5 times longer than untreated TC4. During electrothermal de-icing, melting initiated at discrete ice–substrate contact points, forming coalesced meltwater films, while interfacial stress concentration promoted crack propagation and rapid ice detachment. Compared with untreated surfaces, ice detachment time (250 mm/s) achieved complete ice detachment at approximately 152 s, whereas ice on the untreated surface remained adhered after 270 s of continuous heating, representing a de-icing time reduction of at least 44%. These results demonstrate that combining laser-fabricated microstructures with electrothermal heating effectively reduces real ice–substrate contact, providing an enhanced anti-/de-icing strategy for lightweight, long-endurance UAV applications under identical electrical input. Full article

Metal foams and nanofluids are recognized as attractive and effective heat transfer enhancement methods. This study numerically investigates forced convection heat transfer and second-law thermodynamic behavior of water and a 0.02% Cu–MXene/water hybrid nanofluid flowing through a tube partially filled with metal foam. Three configurations are examined: a clear tube as the reference case; Case A (three discrete foam blocks occupying 3/16 of the tube length); and Case B (a single block occupying 9/16), using four metal-foam types (aluminum 30/45 PPI, copper 40 PPI, and nickel 60 PPI). The governing equations are solved using the finite-volume method with the SIMPLER algorithm and validated against published experimental and numerical data. Results show that Case B provides higher heat-transfer rates and performance evaluation criterion (PEC) values than Case A, although at the expense of larger pressure-drop and pumping-power penalties. The highest heat-transfer enhancement is obtained with Cu-40 PPI foam and the hybrid nanofluid in Case B, where the average Nusselt number increases by a factor of 3.33 at a Reynolds number of Re = 200 relative to water in the clear tube. Higher-thermal-conductivity foams, combined with the hybrid nanofluid, provide greater thermohydraulic benefits than lower-conductivity foams with water. The second-law analysis reveals that increasing Re reduces thermal irreversibility but increases frictional irreversibility, highlighting the competing effects of heat-transfer enhancement and hydraulic resistance. Overall, the Cu-40 PPI/hybrid nanofluid combination in Case B at low Re provides the most favorable performance among the investigated conditions. Full article

Degraded industrial sites in arid and semi-arid regions often suffer from loose surface substrates, weak water-retention capacity, high wind-erosion risk, and poor early vegetation establishment. Combining photovoltaic (PV) deployment with ecological utilization may improve near-surface habitats by shading, reducing wind speed, and regulating soil heat and moisture. This study investigated an ash storage yard of a coal-fired power plant in Ordos, Inner Mongolia, China, by comparing soil temperature, soil moisture, and near-surface wind-speed responses under three representative fixed PV tilt angles of 36°, 43°, and 50°, together with the corresponding early plant-growth suitability. A multi-physics model coupling near-surface airflow, water-vapor transport, and porous-media hydrothermal migration was established. A Gaussian suitability function combined with AHP-CRITIC weighting was used to construct a model-based comprehensive growth index (CGI) from soil temperature and moisture, while short-term field monitoring was used to validate afternoon soil hydrothermal trends. Among the three scenarios, the 36° configuration produced the widest horizontal heat–moisture-affected zone and the highest CGI values for alfalfa and Elymus nutans, reaching 0.7741 and 0.6875, respectively. Relative to the outside reference area, the rear PV zone reduced the near-surface wind speed by 33–40% and increased the plant heights of alfalfa and Elymus nutans by 49.4% and 37.8%, respectively. A first-order PVsyst assessment showed that the 43° configuration achieved the highest specific energy yield of 1814 kWh kWp⁻¹ year⁻¹, whereas the annual grid-connected output at 36° was only 0.59% lower. These findings indicate that the 36° configuration may provide a favorable compromise between early vegetation establishment and photovoltaic electricity generation among the tested scenarios. By linking renewable-energy production with microenvironment regulation and early vegetation establishment, the proposed framework provides a decision basis for the multifunctional and sustainable reuse of degraded industrial land. Nevertheless, the results represent a site-specific, single-season assessment and should not be interpreted as a universal optimum. Full article

PV/T collectors and Air Source Heat Pump (ASHP) are widely studied for building heating, but solar intermittency and ASHP low-temperature frosting limit their large-scale deployment. A novel PV/T-ASHP coupled heating system is proposed to cut building carbon emissions and relieve ASHP performance degradation in cold zones. Circulating water cools PV/T panels to boost power generation, and the warmed water preheats ASHP evaporator inlet air to reduce frosting and defrosting frequency. With a Xi’an office building as the research object, validated TRNSYS 18.0 models are established for comparative analysis with conventional systems and cross-climate evaluation in Xi’an, Beijing, Shanghai and Chengdu. Results show the new system lifts PV/T combined efficiency by 17.56%, reduces energy consumption by 19.9%, and achieves an average COP of 3.2. Across climate zones, its COP rises 11.5–24.6% and 50-year carbon emissions fall 16.4–26.2%, supporting low-carbon heating promotion for office buildings. Full article

Magnetothermally responsive nanocarriers represent a promising platform for spatio-temporally controlled drug delivery by combining alternating magnetic field (AMF)-induced heating with thermally triggered cargo release. Among the available architectures, magnetite-core/mesoporous-silica-shell (Fe₃O₄@mSiO₂) nanoparticles functionalized with thermoresponsive polymer gatekeepers are particularly attractive. These systems integrate a magnetic heat source, a mesoporous drug reservoir, and temperature-dependent control of pore accessibility. This review examines the fundamental principles of magnetic hyperthermia, including heat-generation mechanisms, specific absorption rate (SAR), intrinsic loss power (ILP), AMF parameters and safety, and the interplay between Néel and Brownian relaxation. It also critically discusses core–shell synthesis and architecture, drug-loading strategies, PNIPAM-, PNVCL-, and other LCST-type gatekeepers, and the physicochemical characterization required to validate the complete nanocarrier. Evidence for combined magnetic hyperthermia and chemotherapy is assessed together with hemocompatibility, immunogenicity, oxidative stress, biodistribution, degradation, long-term retention, and clearance. Although promising magnetothermal release and therapeutic effects have been reported, evidence remains dominated by in vitro studies, with limited in vivo validation. Current clinical experience concerns locally administered iron-oxide hyperthermia rather than complete thermoresponsive Fe₃O₄@mSiO₂ drug-delivery systems. Translation will require standardized magnetothermal and release testing, reproducible scale-up, validated sterilization and endotoxin control, component-resolved pharmacokinetics, and integrated development of the nanocarrier and AMF applicator. Full article

To improve the antifouling and self-cleaning performance of 3003 aluminum alloy, a fluorine-free water-repellent surface was fabricated by combining nanosecond laser texturing with subsequent heat treatment. The effects of scanning speed, laser power, pulse frequency, and scanning interval on surface wettability were systematically investigated. Under the optimal conditions of 2700 mm/s, 6 W, 35 kHz, and 20 μm, the surface achieved a maximum static water contact angle of 154.3 ± 0.8°. Surface characterization showed that laser processing generated hierarchical micro-/nano-scale structures, while heat treatment promoted surface chemical evolution associated with enhanced hydrophobicity. The highly water-repellent behavior resulted from the synergistic effect of hierarchical roughness and heat-treatment-induced surface chemical changes. The fabricated surface exhibited effective self-cleaning performance, achieving a SiO₂ removal efficiency of 98.8% under the specified test conditions. In addition, relatively high water repellency was retained after repeated water-impact and tape-peeling tests. These results demonstrate that nanosecond laser texturing combined with heat treatment provides a simple and environmentally friendly strategy for fabricating water-repellent AA3003 surfaces for antifouling and surface-protection applications. Full article

The extensive use of high-resolution digital elevation data, along with continuous improvements in computing power and geographic information system (GIS) tools. Has driven the development of spatial data processing, management, and spatial interpolation methods. This study aims to construct a high-quality spatial distribution map of thermal comfort in densely populated areas of northwestern Jordan using climate data collected from six meteorological stations between 1991 and 2024, based on the indoor temperature index (IAT). To analyze the spatial variability of climate elements, a digital elevation model (DEM) with a spatial resolution of 30 m was used and resampled to a 0.5-km grid. Spatial interpolation employed inverse distance weighting (IDW), with each grid cell using data from the three nearest meteorological stations. The results showed that areas with higher temperatures inside the villas were clearly concentrated in the summer, especially in the lowlands near the Jordan Valley. Indicating that these areas are more susceptible to thermal stress. The model results also show that it performs well in predicting thermal comfort, with a coefficient of determination (R²) between 0.95 and 0.98 and mean squared error (MSE) between 0.35 and 0.50. which reflects the ability of these models to represent the relationship between climate variables and predict thermal comfort levels with a high degree of accuracy. The results indicate significant spatiotemporal differences in thermal comfort within the study area, with longer durations of heat stress in summer. This highlights the importance of combining geospatial methods with numerical simulations in studying the impacts of climate change and supporting urban planning and climate adaptation strategies. Full article

Rapid growth in artificial intelligence, machine learning, and high-performance computing has substantially increased data centre rack power densities, resulting in higher heat generation and more demanding cooling requirements. As water remains widely used in many cooling systems, understanding the relationship between cooling technologies and water consumption is essential for improving cooling efficiency and sustainability. This paper presents a survey of reported water usage effectiveness (WUE) across 83 data centre entries, providing a combined dataset that links WUE with heat-rejection categories. The reported data shows that 23 of these data centres exceed 0.4 L/kWh, which is a sustainability target specified by the Climate Neutral Data Centre Pact for new data centres in water-stressed regions using potable water. Dry facilities employing closed-loop liquid cooling require essentially no water, while evaporative systems typically report water usage effectiveness values up to 2.5 L/kWh. Reported WUE is a facility-level operational metric, set by the proportion of the IT heat load rejected by evaporation, which depends on the heat-rejection topology, ambient wet-bulb conditions, and operating set points. A higher server-side heat transfer coefficient permits a higher coolant supply temperature for a given chip temperature limit, widening the range of ambient conditions under which heat can be rejected without evaporative assistance. Server-side heat transfer is therefore an enabling condition for low WUE rather than a determinant of it. One-dimensional heat transfer models are developed to estimate heat transfer coefficients for different server-level cooling mechanisms widely used for cooling servers within data centres, including air cooling, single-phase immersion cooling, direct liquid cooling, and two-phase immersion cooling. Air cooling, with the lowest heat transfer coefficient, remains widely used in small-scale facilities, whereas direct liquid cooling and two-phase immersion cooling achieve coefficients up to three orders of magnitude higher and are increasingly deployed in high-density installations. These coefficients are used to derive an equivalent evaporative water demand, an upper-bound estimate of the water that would be evaporated in rejecting the heat each mechanism removes; it shares the units of reported WUE but describes thermal capability rather than facility water consumption. Full article

Cold-climate dwellings can face coincident electricity and domestic hot-water shortfalls in winter, when solar availability is at its lowest. This study evaluates an integrated residential system for Aomori, Japan, combining photovoltaics, evacuated-tube solar water heating, and battery storage with electrolysis, compressed-hydrogen storage, and a PEM fuel cell operated in combined-heat-and-power mode. Building on a screening-level annual-balance analysis, a coupled annual TRNSYS simulation with a 0.125 h time step resolved battery dispatch, electrolyzer part-load operation, hydrogen compression and finite storage, seasonal fuel-cell operation, and heat recovery. The results show that the principal value of seasonal hydrogen lies in improving winter supply adequacy, dispatchability, and heat recovery rather than annual conversion efficiency. Fuel-cell heat recovery increased the number of days satisfying the hot-water screening indicator—a daily mean tank temperature of at least 43 °C—from 221 to 332. A reserve-aware criterion identified a 225 W electrolyzer operating-power cap as the positive-reserve case; 205 W was near-cyclic with a negligible margin, whereas the original 475 W cap was substantially oversized. The hydrogen pathway remained markedly less efficient than direct photovoltaic and solar-thermal use, and the estimated storage hardware’s lower bound substantially exceeded the break-even capital ceiling supported by the annual operating value. Seasonal hydrogen can therefore strengthen winter energy adequacy and heat recovery but is not yet cost-effective at the single-dwelling scale under the investigated conditions. Full article

Dielectric barrier discharge (DBD) plasma actuators have attracted increasing attention for anti-icing and de-icing applications due to their ability to combine surface heating and plasma-induced flow control. Their electro-thermal behavior is strongly influenced by exposed electrode material, geometry, and dielectric configuration, often leading to localized hot-spot formation and reduced operational stability. However, the impact of exposed electrode material and electrode thickness remains poorly understood, representing a significant gap in understanding the electrical and thermal response of these devices. This study presents an experimental electro-thermal investigation of DBD plasma actuators employing copper, aluminum, and hybrid copper–aluminum exposed electrodes. Copper and aluminum were selected as exposed materials because they present two contrasting electrical–thermal extremes. The actuators were tested using dielectric barrier thicknesses of 1 mm and 2 mm, considering both standard and enlarged (10 times) exposed electrode thickness. The electrical diagnostics show that aluminum electrodes promote stronger and more uniformly distributed microdischarges due to enhanced discharge initiation, but at the expense of increased power consumption. In contrast, copper electrodes exhibit lower power demand but lead to concentrated current density and localized thermal hot spots. Motivated by this electrical–thermal trade-off, a hybrid electrode was developed to combine the high electrical stability of copper with the discharge uniformity of aluminum. The hybrid configuration demonstrates intermediate power consumption and significantly improved thermal uniformity, effectively mitigating hot spot formation. These results highlight the importance of exposed electrode electrical properties in the electrical and thermal characterization of DBD plasma actuators and identify the hybrid configuration as a promising solution for future thermally driven ice-mitigation applications. Full article

This paper develops a measurable unified electric–thermal energy indicator for converter-dominated microgrids, containing virtual synchronous generator (VSG) and virtual asynchronous machine (VAM) dynamics. The principal contribution comprises the scalar energy indicator $H_{\Sigma }$ and its normalized margin ${\eta }_{\mathrm{stab}}$; together, they combine active-power–frequency, reactive-power–voltage, thermal-flow, current-boundary, and electric–thermal coupling information obtained from point-of-common-coupling measurements and thermal states. A bounded event-triggered thermal–electric action is used only as a secondary demonstration of how the indicator can support current-constrained coordination; it is not proposed as a replacement for the inner VSG controller. Local positive-definiteness, dissipation, invariant-sublevel-set, and two-time-scale conditions are derived in an explicitly defined operating domain. The framework was evaluated in a three-phase Simulink/Simscape model using a 26-run matrix of disturbance and parameter cases, together with three severe-case baselines and four reduced-order channel-isolation cases. For voltage-sag depths of 5–20%, the event increase in $H_{\Sigma }/H_{\mathrm{crit}}$ rose from 0.137 to 0.385. In the severe 20% combined case, bounded coordination increased the minimum margin from 0.048 to 0.138, with 0.0897 kWh of heat-load reduction; however, its trajectory was identical to that of the matched current-threshold trigger, so no controller-performance superiority is claimed. Omitting $H_{qv}$, $H_{th}$, $H_{lim}$ and $H_{cpl}$ eliminated 100.0%, 99.7%, 90.8% and 87.3%, respectively, of the corresponding event-window sensitivity. Under deep-current saturation, the limiter gain fell to 0.466 and ${\eta }_{\mathrm{stab}}$ reached zero, numerically identifying a boundary beyond which the local stability guarantee must not be extrapolated. Full article

Building on a previously developed valve-controlled reversible loop heat pipe (RLHP) and the corresponding RLHP-embedded wall, component- and wall-scale experiments were conducted. The heat-transfer performance of the RLHP was evaluated at filling ratios of 10–70% and heating powers of 25–400 W, and its forward and reverse operation was evaluated at the component scale using a filling ratio of 50%. The on–off dynamic responses of the RLHP-embedded wall and a reference wall were subsequently compared under heating powers of 20–200 W. The results showed that filling ratios ranging from 40% to 70% provided a relatively effective operating range under the tested conditions. Among the tested filling ratios, 50% exhibited the lowest and most stable apparent equivalent thermal resistance, with an average value of approximately 0.039 m²·K/W. At 400 W, the quasi-steady average temperature differences during forward and reverse operation were 17.2 °C and 16.9 °C, respectively. At 200 W, the first-hour temperature rise on the unheated side was approximately 6 °C for the RLHP-embedded wall, compared with 1.2 °C for the reference wall. During the combined heating-off–valve-closed stage, the heat-retention duration increased with the preceding heating power. Full article

Kelp is a high-moisture, flexible, sheet-like marine biomass whose drying behavior is strongly affected by the coupled effects of radiative heating, convective vapor removal, internal moisture migration, tissue shrinkage, curling, and material overlap. Traditional sun drying and hot-air drying remain widely used but are limited by long processing cycles, environmental dependence, high energy consumption, and inconsistent product quality. With the development of infrared heating, heat-pump dehumidification, Internet of Things (IoT)-enabled sensing, fifth-generation (5G) mobile communication, multiphysics simulation, and digital control, kelp drying is progressively shifting toward monitored, model-assisted, and intelligent processing. This review critically summarizes recent advances in kelp and related seaweed drying, with particular emphasis on infrared-assisted heat and mass transfer, drying kinetics, coupled computational fluid dynamics–finite element method (CFD–FEM) simulation, quality evaluation, and intelligent control. Representative published studies demonstrate the engineering potential of these approaches. In a suspended infrared-array kelp drying system, an infrared power density of 1.2 kW m−2 combined with an air velocity of 3 m s−1 maintained the drying temperature at approximately 55–62 °C, while relative humidity decreased from about 80% to 20–30%. Under these conditions, the Page model achieved R² = 0.987 and RMSE = 0.019, the rehydration ratio exceeded 94%, and the total color difference remained below ΔE = 6.5. A recent CFD–FEM–MATLAB workflow further reported a composite operating-condition index of J = 0.4535, with mapped mean and maximum kelp surface temperatures of 62.23 and 63.57 °C, respectively. These quantitative results indicate that the key challenge in infrared kelp drying is not simply to increase heat input, but to coordinate radiation distribution, airflow organization, internal moisture transport, structural response, and quality preservation. Future research should therefore focus on experimentally validated heat–mass-transfer models, adaptive sensing and control, multi-objective optimization, and pilot-scale verification under realistic production conditions. Full article

Recently, the Internet of Things (IoT) has evolved into the Artificial Intelligence of Things (AIoT) through its combination with artificial intelligence (AI) technology and has become capable of providing intelligent services in all industrial sectors. Globally, energy consumption within buildings is continuously increasing alongside the advancement of IT and AI technologies. Since this increase is attributed to various causes—ranging from large-scale climate change to small-scale indoor environmental factors (air quality) and health factors—research aimed at reducing indoor energy consumption is actively underway. In particular, in the home environment where people spend a significant portion of their day, maintaining indoor air quality (IAQ) is critical for health, and energy conservation in heating, ventilation, and air conditioning (HVAC) systems is essential. In Korea, the number of single-person households is increasing and was expected to reach 36.1% of all households by 2024, leading people to live in increasingly smaller homes. This study aimed to verify residents using contactless facial recognition to prevent pandemics such as COVID-19 and to provide comfortable indoor air quality. Resident facial recognition was performed by identifying residents’ faces in images captured by the Pi camera using OpenCV’s Haar feature-based cascade classifier. Indoor air quality measurements were conducted in four indoor locations, measuring various environmental factors (PM_2.5, CO₂, etc.) based on environmental sensors and the IoT. Furthermore, to manage indoor air quality, AI was utilized based on the measurement data to classify the four spaces, with a success rate of 96%. Additionally, considering the indoor area of the experimental environment (97 m²), it was confirmed that operating a 70 W air purifier only when the resident is indoors can reduce power consumption by approximately 33–75% compared to running it 24 h a day. Full article

Cooling electricity consumption in central air-conditioning systems of large public buildings accounts for a substantial share of urban electricity use and is strongly influenced by outdoor meteorological conditions. Under increasingly frequent extreme summer heat events, accurate cooling-load forecasting is important for HVAC operation, building energy management, urban electricity security, and power-system planning. This study investigates the effects of measured outdoor meteorological inputs on cooling-load forecasting for a large public building in Guangzhou. Consecutive hourly cooling-load data and measured meteorological data, including outdoor air temperature, relative humidity, solar radiation, wind speed, and wind direction, were collected from June to September 2022. The corresponding 2023 dataset was analyzed separately using the same modeling and evaluation procedure to assess cross-year repeatability; data from the two years were not combined. Correlation and univariate linear regression analyses were first used for preliminary candidate-input screening. Nine Long Short-Term Memory sub-models with different meteorological input combinations were then developed and compared using the 2022 dataset, and the selected input configuration was subsequently re-evaluated using the separate 2023 dataset. Solar radiation exhibited the strongest marginal association with cooling load, followed by outdoor air temperature and relative humidity. The negative association of relative humidity reflected its coupled variation with temperature and solar radiation during the investigated summer period. For the 2022 dataset, the model using outdoor air temperature, relative humidity, and solar radiation achieved the lowest MAPE. Compared with the model using all five meteorological variables, it reduced MAE, RMSE, and MAPE by 14.55%, 7.24%, and 19.07%, respectively, while R² increased from 0.9542 to 0.9601. Evaluation using the 2023 dataset showed corresponding reductions of 20.01%, 18.37%, and 25.81% in MAE, RMSE, and MAPE, respectively, together with an increase in R² from 0.9592 to 0.9708. Full article