Search Results (4,859)

Thermal stress in hot–humid urban environments constitutes a persistent sustainability challenge, driven by the interaction of extreme temperatures, high atmospheric moisture, and heat-retaining urban surfaces, which collectively intensify outdoor discomfort and increase cooling-energy demand. Within this context, soft landscape systems have gained recognition as nature-based solutions capable of moderating microclimates and enhancing residential livability; however, their systematic prioritization based on integrated sustainability performance remains insufficiently addressed, particularly in Gulf-region residential developments. This study proposes a sustainability-oriented decision-support framework that evaluates and prioritizes soft landscape strategies for thermal comfort enhancement using the Analytic Hierarchy Process (AHP) as the core analytical method. Expert judgments were elicited and structured across five sustainability-driven criteria—shading effectiveness, evapotranspiration potential, airflow facilitation, aesthetic–psychological comfort, and implementation and maintenance cost—and applied to five soft landscape alternatives. To verify the physical plausibility of the expert-derived prioritization, microclimate simulations were conducted using ENVI-met under extreme summer conditions, representing the hottest day of the year, at key diurnal intervals. The results reveal a clear dominance of shading-based mechanisms, with tree canopy systems emerging as the most effective and sustainable intervention due to their superior radiative control, ecological cooling capacity, and perceptual benefits. Simulation outputs confirm that canopy-driven strategies achieve the most substantial reductions in mean radiant temperature during peak thermal stress, while surface-based interventions provide secondary benefits primarily related to diurnal heat dissipation. At peak thermal stress (14:00), Scenario 2 reduced mean radiant temperature (MRT) from 71.69 °C to 54.23 °C (≈24% reduction) and PMV from 7.33 to 5.70 (≈22% reduction) relative to existing conditions. By integrating expert-based multi-criteria evaluation with simulation-based thermal verification, the study advances a robust and transferable framework for climate-responsive residential landscape planning. The findings reposition soft landscape systems as essential climatic infrastructure, offering actionable guidance for enhancing thermal resilience, reducing cooling-energy dependence, and supporting sustainable residential development in hot–humid regions. Full article

This paper introduced a simple, efficient method to prepare mechanically strong lignin-based foams (lignofoams) with open-cell structures using a facile baking technique. The self-expansion of lignin occurred without any additional chemical blowing agents, foaming agents, plasticizers, or lubricants. During heating, kraft lignin softened, and the internal water, either initially adsorbed or generated in situ through the dehydration of hydroxyl groups, acted as a natural blowing agent for foaming a porous foam structure. Incorporating a small amount of polypropylene (PP) enhanced mechanical properties by coating the inner walls of open cells. The porous, softened composite was then cooled to room temperature and solidified into the self-expanded lignofoam. The resulting lignofoams exhibited tunable densities ranging from 0.21 to 0.49 g/cm³ and a maximum compressive strength of 3.6 MPa. The lignofoam also showed excellent thermal insulation properties with low thermal conductive coefficients (0.057–0.098 W/mK). These features highlight the great potential of lignofoam for a bio-based thermal insulation material for construction applications. Full article

The high energy consumption and spatiotemporal thermal asymmetry of data center cooling systems have become critical bottlenecks constraining their green and sustainable development. Traditional point-type temperature sensors suffer from insufficient spatial coverage, while conventional feedback control strategies exhibit delayed responses and limited adaptability under dynamic workloads. To address these challenges, this study proposes a real-time thermal symmetry management framework for data centers based on distributed fiber optic temperature sensing and model predictive control (MPC). The proposed system employs Brillouin scattering-based distributed sensing to continuously acquire high-density temperature measurements from thousands of points along a single optical fiber, enabling fine-grained perception of the three-dimensional thermal field. On this basis, a hybrid prediction model integrating thermodynamic physical equations with a Temporal Convolutional Network–Bidirectional Gated Recurrent Unit (TCN–BiGRU) deep neural network is developed to achieve accurate and stable spatiotemporal temperature forecasting. Furthermore, a symmetry-aware MPC controller is designed with the dual objectives of minimizing cooling energy consumption and suppressing thermal field deviations, thereby restoring temperature uniformity through rolling-horizon optimization. Experimental validation in a production data center demonstrates that the distributed sensing system achieves a measurement deviation of 0.12 °C, while the hybrid prediction model attains a root mean square error of 0.41 °C, representing a 26.8% improvement over baseline methods. The MPC-based control strategy reduces daily cooling energy consumption by 14.4%, improves the power usage effectiveness (PUE) from 1.58 to 1.47, and significantly enhances both thermal symmetry and operational safety. The Thermal Symmetry Index (TSI) decreased from 0.060 to 0.035, indicating a 41.7% improvement in spatial temperature distribution uniformity. The TSI is defined as the ratio of spatial temperature standard deviation to mean temperature, where lower values indicate better thermal uniformity; TSI < 0.03 represents excellent symmetry, 0.03–0.05 indicates good symmetry, and TSI > 0.08 suggests significant asymmetry requiring intervention. These results provide an effective and practical solution for intelligent operation, energy-efficient control, and low-carbon transformation of next-generation green data centers. Full article

This study presents and systematizes a high-reliability measurement and technological dataset suitable for prediction-based validation of the Spent Fuel Interim Storage Facility (SFISF) of the Paks Nuclear Power Plant. The primary objective of this dataset is not the validation of a general-purpose software tool, but to establish a reproducible experimental basis for the objective and quantitative validation of a three-dimensional, facility-scale heat transfer and buoyancy-driven flow model of the SFISF, developed using the finite difference method (FDM), in a passively cooled system where heat conduction, thermal radiation, and natural convection simultaneously occur. The applied measurement systems (SMAS, CTRS, and the in-house developed CFEPR), their spatial arrangement, accuracy characteristics, as well as data post-processing and the generation of model execution inputs are described in detail. Special emphasis is placed on the functional separation of the available data into initialization data, model execution data, and independent validation datasets, ensuring that model assessment does not rely on calibration or parameter fitting. Furthermore, the estimation of decay heat generated by the stored fuel assemblies is presented using both a standard correlation method (ANSI/ANS-5.1) and isotope inventory-based calculations, and the discrepancies between these approaches are treated as input uncertainties and sensitivity analysis factors. The spectral solar load is considered based on the ASTM G-173 reference spectrum, while during cloudy periods an effective irradiance estimation derived from on-site lux measurements is applied. The results indicate that the available measurement and technological information is sufficient for supporting reproducible, transparent, and quantitative validation studies of the three-dimensional numerical model of the SFISF, as well as for assessing the impact of dominant input uncertainties. Full article

Against the backdrop of the ever-expanding practical applications of magnetic nanofluids, the self-driven flow and heat transfer characteristics of water-based Fe₃O₄ magnetic nanofluids were experimentally investigated under a uniform magnetic field in the closed-loop pipeline system in this work. Specifically, Fe₃O₄ nanoparticles were synthesized using the co-precipitation method, and stable magnetic nanofluids with concentrations ranging from 0.025 wt% to 0.150 wt% were prepared using sodium citrate as a dispersant. In the presence of a magnetic field, a closed-loop system that integrates heating and cooling branches was established. Furthermore, the effects of magnetic field strength, temperature difference between the heating and cooling sections, magnetic nanofluid concentration, and pipeline length on the self-circulation flow velocity were discussed, leading to insights into the heat transfer characteristics of the magnetic nanofluid. The results showed that the circulation flow velocity increases with the increase in magnetic field strength, magnetic nanofluid concentration, and temperature difference, while it decreases with the increase in pipeline length. Correspondingly, the heat transfer coefficient between the pipeline wall and the fluid increased significantly with the increase in circulation flow velocity. The priority of factors on the thermomagnetic effect is ranked as magnetic field strength > pipeline length > temperature difference > magnetic nanofluid concentration. Full article

As global warming intensifies, urban heat stress is increasing. Urban blue–green spaces (UBGSs) reduce heat exposure, and refined planning can enhance cooling in space-limited cities. Yet drivers and mechanisms at the urban-agglomeration scale remain unclear. This study quantified the cooling intensity (CI) of 162 UBGS across 27 cities in the Yangtze River Delta using summer 2020 land surface temperature data (June–August). CI is defined as the average temperature difference (ΔLST) between the UBGS and its surrounding buffer. Extreme gradient boosting (XGBoost) and Shapley additive explanations (SHAP) methods were applied to analyze the driving factors. Key findings include (1) the top five factors by SHAP value: Area (0.38), buffer NDBI (0.16), lake/river landscape shape index (0.07), buffer tree height (0.06), and buffer population (0.06). (2) CI rises with Area only up to 50 hm² and then plateaus at ~6 °C. Buffer NDBI strengthens CI, with faster gains when buffer NDBI < −0.2. Water-shape effects are stepwise, and a lake/river shape index of 5–8 delivers near-optimal cooling. Interactions indicate stronger cooling in large parks with high water coverage and in sites combining complex water edges with dominant grassland patches. These findings support structure-focused UBGS design and targeted mitigation in dense urban areas. Full article

Elastocaloric cooling is an emerging solid-state refrigeration technology that leverages the latent heat exchange of shape memory alloys under mechanical stress. This study investigates the energy performance of a solid-to-solid elastocaloric cooling heat pump to enhance heat transfer efficiency and overall system performance. A Matlab-based numerical model, developed using the finite volume method, was employed to simulate the system. The energy performances of the elastocaloric heat pump are analyzed by varying the frequency of the cycle, the elastocaloric refrigerants, and the types of thermal diodes, from ideal up to realistic Peltier switches. The results demonstrate that the strategic use of thermal diodes significantly improves heat flow directionality, reducing thermal losses and enhancing the efficiency of the elastocaloric cooling process with a system that employs a realistic Peltier thermal diode, guaranteeing specific cooling powers up to 6500 W kg⁻¹. The maximum COPs of the system with ideal thermal diodes range from 60 to 10. These findings contribute to the development of more efficient solid-state cooling technologies, offering a viable alternative to conventional systems, especially for electronic circuit cooling applications. Full article

With the development of manufacturing towards stricter precision requirements and increasingly complex geometric shapes, dimensional accuracy has become a key factor affecting precision engineering components used in many industries. Effective cooling and lubrication methods have always been a meaningful way to improve the surface quality of cutting materials. Minimum-quantity lubrication technology mixes compressed air with cutting fluid, produces a spray at ambient temperature, and guides these droplets to the cutting area under the action of high-pressure air to promote penetration into the contact area between the tool, workpiece, and chip. Minimum-quantity lubrication can be used to increase cutting speed, cool workpieces, improve workpiece quality, and significantly reduce the pollution caused by cutting fluid to the environment. However, minimum-quantity lubrication technology still cannot meet the requirements of sustainable machining in cutting processes. A test device platform for milling 6030 aluminum alloy with minimal quantity lubrication was established, and different cooling methods were used to analyze the effect on surface roughness. The spindle speed n, feed rate f, and cutting depth a_p are selected as optimization variables, with surface roughness as the optimization objective. Single-factor experiments were conducted to determine the optimal range for these variables. Subsequently, a model was constructed using the response surface methodology and solved using Design-Expert software. The interaction effects of spindle speed, feed rate, and depth of cut on surface roughness were analyzed. Additionally, genetic algorithms were employed to optimize cutting process parameters for the best combination. The results demonstrated that by combining Response Surface Methodology (RSM)and genetic algorithms, when the spindle speed n was 2520 r/min, the feed rate f was 48 mm/min, and the depth of cut a_p was 0.08 mm, the actual surface roughness after milling reached 0.148 µm, representing a 74.57% reduction compared to the initial surface roughness. This research method provides a theoretical foundation and technical support for optimizing minimal quantity lubrication (MQL) cutting processes. Full article

The applications of nanofluids are widely beneficial in heat transmission and cooling systems. Nanofluid viscosity and thermal conductivity have a substantial effect on heat transfer applications and on devices such as solar and geothermal systems. Machine learning models enable faster, less expensive modeling of nanofluid thermophysical properties. These models are secure for future studies and in the development of nanotechnology. In this review, shape, size, temperature, and volume concentration are considered as inputs to develop several machine learning methods, such as artificial neural networks, support vector regression, decision trees, and random forests. These models were analyzed by comparing their R² values, and the results indicated that machine learning-based models generally exhibited more reliable performance than the other approaches. The observation in this review was that thermal conductivity increases with temperature and volume fractions, whereas viscosity decreases with size, temperature, and volume fractions. To determine the optimal nanoparticle type, size, and concentration for specific applications such as data center cooling and high-heat-flux electronics, future research may employ ML-based optimization techniques. Full article

The triply periodic minimal surface structure is receiving significant attention amongst the engineering community. The advantage of using such a structure is its ability to provide lightweight cooling to surfaces. In this paper, attention is drawn to a gyroid structure composed of a shell network and a solid network, with a porosity of 0.7. Three different flow rates, using water as the circulating fluid, are experimentally applied to cool a square surface with a base of 37.5 mm and a height of 12.7 mm. It was found that this structure provided a high cooling rate, achieving a Nusselt number around 100 with a solid lattice and 160 for a shell lattice. It is also noted that the TPMS area plays a significant role, thereby increasing the cooling rate. When the TPMS height is 90% of the initial height of 12.7 mm, the performance of both structures is found to be well accepted. Pressure drop is reduced, and the heat performance is improved. The circulating flow above the structure marginally reduced the pressure drop. The performance evaluation criteria for the shell network ranged from 95 < PEC to < 225, and for the solid network from 125 < PEC to < 155. The optimization method has been applied across the entire height range using response surface methodology. It is found that the optimum TPMS height is for an aspect ratio of 95.1%. Full article

With the core advantages of high energy efficiency, high power density, and reliable operation, high-voltage permanent magnet motors have become the mainstream development direction of modern motor technology. However, the risk of demagnetization caused by excessive temperature increases in permanent magnets has become a key bottleneck restricting motor performance and operational reliability, which makes research on the flow and heat transfer characteristics of motor cooling systems of great engineering value. Taking the 710 kW high-voltage permanent magnet motors as the research object, this study established a global flow field mathematical model covering the internal and external air duct cooling systems of the motor based on the theories of computational fluid dynamics and numerical heat transfer, and systematically analyzed the flow characteristics and distribution laws of cooling air. The thermal–fluid coupling numerical method was employed to simulate the temperature field of the motor, and the overall temperature distribution of the motor, temperature gradient of key components, and maximum temperature value were accurately obtained. To verify the validity of the established model, a test platform for the cooling system performance was designed and built. Measuring points for wind speed, air temperature, and component temperature were arranged at key positions, such as the stator radial ventilation ducts, and experimental tests were conducted under the rated operating conditions. The results show that the flow field distribution of the internal and external air ducts of the motor is reasonable and that the cooling air flows uniformly, with the external and internal circulating air volumes reaching 1.2 m³/s and 0.6 m³/s, respectively, which meets the heat dissipation requirements. The maximum temperature of 95 °C occurs in the stator winding area, and the maximum temperature of the permanent magnets is controlled within the safe range of 65 °C. The simulation results were in good agreement with the experimental data, with an average relative error of only 4%, which fell within the engineering allowable range, thus verifying the accuracy and reliability of the established global model and thermal–fluid coupling calculation method. This study reveals the thermal–fluid coupling transfer mechanism of high-voltage permanent magnet motors and provides a theoretical basis and engineering reference for the optimal design, precise temperature rise control, and reliability improvement of motor cooling systems. Full article

Many compressed air devices are energy inefficient. One example is using air nozzles above pastry lines to remove flour and cool products. These nozzles consume excessive energy, particularly when mounted too high, requiring stronger airflow. Adjustable nozzle height and energy-efficient nozzles should be used with careful control of air pressure, flow rate, and activation time, ensuring efficient and adaptive control. Additionally, sensor-based control should activate airflow only when pastries are present and until the correct amount of powder material has been blown out, as the nozzles often operate unnecessarily. Accurate measurement of powder volume after blow-off remains a challenge. With the use of computer vision methodology, the system would continuously read the measured values and determine not only the optimal moment to interrupt device operation but also dynamically adjust key parameters. This paper demonstrates that computer vision can estimate powder volume using two non-contact 3D methods: a depth camera, and a structured light scanner. Their accuracy, reliability, advantages, and limitations are analyzed. The results show that the structured light scanner can be used in the case of a static model (the conveyor belt with products stops at the moment when it is necessary to perform a 3D measurement). This approach shows higher repeatability and gives a more accurate 3D model. On the other hand, for the dynamic model (the conveyor belt with products moves while the 3D measurement device is fixed), the depth camera can be used because, at minimum rotation speeds of the substrate, it shows higher accuracy and enables faster adaptive modeling and creation of the necessary data. Full article

In the process of using the freezing method to uncover coal from stone gates, the thermal evolution profiles of the coal body during the freezing process tend to be complex due to the presence of gas and moisture. To investigate the temperature response of coal containing gas under different freezing temperature conditions, a self-developed low-temperature freezing test system for coal containing water and gas was used to conduct freezing and cooling tests at different freezing temperatures (−5 °C to −30 °C). The temperature changes at various measuring points inside the coal over time were monitored in real time, and the temperature distribution, cooling law, and strain evolution process of the coal in the axial and radial directions were analyzed. The experimental results show that the cooling process of the center point of the coal can be divided into four stages: rapid cooling, extremely slow temperature drop, relatively slow cooling, and stable constant temperature. The time required to reach the stable constant temperature stage is inversely proportional to the freezing temperature, and corresponding prediction formulas have been established based on this. The standardized coal briquettes exhibit a gradient distribution characteristic of gradually increasing temperature from outside to inside in both axial and radial directions, with the radial temperature distribution being well matched by an exponential decay model. The strain of coal is affected by both thermal shrinkage and ice-induced expansion. The occurrence time of frost heave is positively correlated with freezing temperature, while the strain of frost heave is negatively correlated with freezing temperature. The axial frost heave effect is significantly stronger than the radial effect, but the radial frost heave occurs slightly earlier than the axial effect. This study reveals the thermal-mechanical coupling response mechanism of gas-containing coal during the low-temperature freezing process, and the research results can provide theoretical support for parameter optimization and engineering application of low-temperature freezing anti-outburst technology. Full article

Using the seeding method, nickel-based single-crystal superalloy DD6 specimens with different growth orientations were prepared in a liquid metal cooling (LMC) directional solidification furnace. Subsequent standard heat treatment was carried out, and the influence of growth orientation on the microstructure of the (001) crystal plane of the alloy after heat treatment was investigated. Results show that with the increase in growth orientation deviation angle from the <001> orientation, the area fraction of residual eutectic content is reduced, the average size and volume of pore and γ′ strengthening phase increase, and the cubicity of the γ′ strengthening phase decreases. The growth orientation does not significantly affect the morphology of residual eutectic content or the morphology of the strengthening phase of the γ′ in the dendrite cores and interdendrite regions. However, the size uniformity of the γ′ strengthening phase in dendrite cores and the width of the γ matrix channels decrease as the growth orientation deviation angle increases. Full article

To effectively prevent and control coal spontaneous combustion, a novel heat-sensitive hydrogel for mine fire prevention and extinguishment was developed using hydroxypropyl methylcellulose (HPMC) and the organic flame-retardant, sodium alginate (SA). The hydrogel was prepared through single-factor variable control and material compounding. First, the optimal formulation of the hydrogel was determined using analytical instruments and techniques, including a viscometer, vacuum drying oven, and the inverted test tube method. Subsequently, its microstructural characteristics were examined using scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). Finally, a fire suppression test platform was established to perform comparative experiments, verifying the hydrogel’s fire prevention, extinguishing, and cooling performance. Experimental results demonstrated that the optimal hydrogel formulation consists of 2.5 wt% HPMC and 0.3 wt% SA. At this ratio, the hydrogel exhibits excellent fluidity and water retention, ensuring prolonged coverage and wetting of coal surfaces. The gel undergoes a sol–gel phase transition at 58 °C, enabling it to fill voids, bind and reinforce coal particles, and reduce exposed surface area. After drying, the hydrogel forms a uniformly smooth surface capable of both coating the coal body and encapsulating individual coal particles. Following the hydrogel treatment, the coal sample retains its original functional groups, indicating that no chemical reactions occur during mixing. Compared with traditional inhibitors, the hydrogel demonstrates superior fire suppression performance, more effectively covering and encapsulating burning coal. It rapidly reduces the temperature to 28 °C by the cooling effect of water evaporation from the hydrogel, and it maintains thermal stability, achieving outstanding fire-extinguishing efficiency. Full article