Search Results (3,790)

At present, the global shortage of water resources has led to serious challenges, and traditional water production technologies such as seawater desalination and atmospheric water harvesting have certain limitations due to inflexible operation and environmental conditions. This study proposes a novel water production system (called “NeWater” system in this paper), which combines saline water desalination with atmospheric water-harvesting technologies to simultaneously produce freshwater from brackish water or seawater and ambient air. To evaluate its performance, an integrated thermodynamic and mathematical model of the system was developed and validated. The NeWater system consists of a vapor compression refrigeration unit (VRU), a direct evaporation unit (DEU), up to four heat exchangers, some valves, and auxiliary components. The system can be applied to areas and scenarios where traditional desalination technologies, like reverse osmosis and thermal-based desalination, are not feasible. By switching between different operating modes, the system can adapt to varying environmental humidity and temperature conditions to maximize its freshwater productivity. Based on the principles of mass and energy conservation, a performance simulation model of the NeWater system was developed, with which the impacts of some key design and operation parameters on system performance were studied in this paper. The results show that the performances of the VRU and DEU had a significant influence on system performance in terms of freshwater production and specific energy consumption. Under optimal conditions, the total freshwater yield could be increased by up to 1.9 times, while the specific energy consumption was reduced by up to 48%. The proposed system provides a sustainable and scalable water production solution for water-scarce regions. Optimization of the NeWater system and the selection of VRUs are beyond the scope of this paper and will be the focus of future research. Full article

The origin of life embodies two fundamental questions: how and when did life begin? It is commonly conjectured that life began on Earth around 4 billion years ago. This requires that the complex organization of RNA, DNA, triplet codon, protein, and lipid membrane (RDTPM) architecture was easy to establish between the time the Earth cooled enough for liquid water and the time when early microorganisms appeared. These bracketing events create a narrow window of time to construct a completely operational self-replicating organic system of very high complexity. Another conjecture is that life did not begin on Earth but was seeded from life-bearing space objects (e.g., asteroids, comets, space dust), commonly referred to as panspermia. The second conjecture implies that life formed somewhere else and was part of the solar nebula, originating from an earlier generation star where there was more time available for the development of life. In this paper, the goal is to provide a hypothetical perspective related to the timing for the origin of pre-biotic chemistry and life itself. Using a form of complexity growth, biological features spanning from the present day back to early life on Earth were examined for trends across time. Genome sizes, gene number, protein–protein binding sites, energy for cell construction, mass of individual cells, the rate of cell mass growth, and a molecular complexity measure all yield highly significant regressions of linearly increasing complexity when plotted over the last 4 Gyr (billion years). When extrapolated back in time, intersections with simple complexities associated with each variable yield a mean value of 8.6 Gyr before the present time. This era coincides with the peak of star and planet formation in the universe. This speculative analysis is consistent with the second conjecture for the origin of life. The major assumptions of such an analysis are presented and discussed. Full article

Litchi (Litchi chinensis Sonn.) is a pillar of the tropical agricultural economy in southern China, yet its production faces increasing instability due to climate change. Traditional agronomic models often fail to capture the complex, non-linear interactions between meteorological drivers and yield formation in perennial fruit trees. To address this challenge, the study constructed a yield prediction framework using an optimized Random Forest (RF) model integrated with interpretable machine learning (SHAP), based on a comprehensive dataset from 17 major production regions in Hainan Province (2000–2022). The model demonstrated robust predictive capability at the provincial scale (R² = 0.564, RMSE = 2.1 t/ha) and high consistency across regions (R² ranging from 0.51 to 0.94). Feature importance analysis revealed that heat accumulation (specifically growing degree days above 20 °C) is the dominant driver, explaining over 85% of yield variability. Crucially, scenario simulations uncovered asymmetric climate risks across phenological stages: while moderate warming generally enhances yield by promoting vegetative growth and ripening, it acts as a stressor during the Fruit Development stage, where temperatures exceeding 26 °C trigger yield decline. Furthermore, the yield penalty for drought during Flowering (−8.09%) far outweighed the marginal benefits of surplus rainfall, identifying this window as critically sensitive to water deficits. These findings underscore the necessity of phenology-aligned adaptation strategies—specifically, securing irrigation during flowering and deploying cooling interventions during fruit development—providing a data-driven basis for climate-smart management in tropical agriculture. Full article

With advancements in simulation technology, fluid–thermal interaction (FTI) has become a vital tool in machinery powertrain development. Traditional engine cooling systems, with mechanically coupled components like water pumps and fans, lack adaptive cooling control. Electronic cooling systems, however, use variable-speed components to enhance performance. Combining FTI simulations with intelligent optimization algorithms offers a novel approach to designing control strategies for these systems. This study establishes a multi-objective optimization model for pump and fan speed control in electronic cooling systems. Using MATLAB/Simulink 2018 and Fluent 2022R1, co-simulations were performed, and an elite-strategy-based NSGA-II algorithm was implemented. Different weights were assigned to optimization objectives based on engine performance requirements. The results provide fitted functions for heat exchange capacity and cylinder liner temperature versus flow rates, along with optimal solutions for a 65 kW engine under three weight configurations. These findings support control strategy design and demonstrate the integration of FTI with genetic algorithms. Full article

Cool roof and green roof have been acknowledged as effective heat mitigation strategies for fighting against the urban heat island (UHI). However, empirical data in hot–humid climate are still insufficient. Experimental conventional, cool and green roofs (three types) were established to comprehensively investigate the thermal performances in Hong Kong under typical summer conditions, as retrofitting strategies for an office building. The holistic vertical thermal behavior was investigated. The comparative cooling potentials were assessed. The results reveal a “vertical thermal sequence” in peak temperatures of each substrate layer for the conventional, cool and green roofs on a sunny day. However, local reversion in the thermal sequence may occur on a rainy day. Green roof-plot C (GR_C) demonstrates the highest thermal damping effect, followed by plot B (GR_B), A (GR_A) and the cool roof (CR) in summer. On a sunny day, the thermal dampening effectiveness of the substrates in the three green roofs is consistent: drainage > soil > water reservoir > root barrier. The holistic vertical thermal profiling was constructed in a high-rise office context in Hong Kong. The diurnal temperature profiles indicate all roof systems could effectively attenuate the temperature fluctuations. The daily maximum surface temperature reduction (SDMR) was introduced for cooling potential characterization of the cool roof and green roofs with multiple vegetation types. On a sunny day, the cool roof and green roofs all showed significant cooling potential. SDMR on the concrete tile of the best performing system was GR_C (26 °C), followed by GR_B (22.4 °C), GR_A (20.7 °C) and CR (13.3 °C), respectively. The SDMR on the ceiling ranked as GR_C, GR_B, GR_A and CR, with 2.9 °C, 2.4 °C, 2.1 °C and 2.1 °C, separately. On a rainy day, the cooling effect was still present but greatly diminished. A critical insight of a “warming effect at the ceiling” of the green roof was revealed. This research offers critical insights for unlocking rooftop cooling potential, endorsing cool roof and green roof as pivotal solutions for sustainable urban environments. Full article

Interactions between surface water and groundwater in arid regions regulate their response to climate and human impacts. In the salar systems of the Altiplano-Puna plateau (Bolivia, Chile, Argentina), understanding how surface waters connect to groundwater is crucial for accurate modeling and assessment. This study introduces new data and analysis using subsurface thermal profiles and modeling to identify flow patterns and possible surface water links. We document, to our knowledge, for the first time in the literature, deep-seated cooling of the subsurface caused by extreme evaporation rates. The subsurface is cooled by 4–5 degrees Celsius below the mean annual air temperature to depths greater than 50 m, even though groundwater inflow waters are elevated by 10 degrees °C due to geothermal heating. Three thermal zones are observed along the southern edge of Salar de Atacama, with temperature dropping from 28 °C to about 12 °C over 2.5 km. A 2D numerical model of groundwater and heat flow was developed to test various hydrological scenarios and understand the factors controlling the thermal regime. Two flow scenarios at the southern margin were examined: a diffuse flow model with uniform flow and flux to the surface and a focused flow model with preferential discharge at a topographic slope break. Results indicate that the focused flow scenario matches thermal data, with warm inflow water discharging into a transition zone between freshwater and brine, cooling through evaporation, re-infiltration, and surface flow, then re-emerging near lagoons at the halite nucleus margin. This research offers valuable insights into the groundwater hydraulics in the Salar de Atacama and can aid in monitoring environmental changes causally linked to lithium mining and upgradient freshwater extraction. Full article

As shallow coal resources become increasingly depleted, coal mining is extending to greater depths, making mine thermal hazards an increasingly prominent issue. This paper proposes a novel system for synergistic geothermal energy extraction from deep coal mine aquifers and coal seam cooling, aimed at achieving integrated geothermal exploitation and mine thermal hazard control. Based on a high-temperature mine in the Yuanyanghu Mining Area of Ningxia, a dual-stage, single-branch three-dimensional numerical model was established to simulate the effects of water injection pressure, water injection temperature, and level spacing on the system’s cooling performance and geothermal energy extraction efficiency. The results indicate that increasing injection pressure enhances early-stage geothermal energy extraction capacity and coal seam cooling rate, but the heat extraction power declines over long-term operation as the produced water temperature approaches the injection temperature. Lowering injection temperature significantly improves water–rock heat exchange efficiency, accelerates coal seam cooling, and increases geothermal energy extraction. Increasing level spacing helps improve geothermal energy extraction power but weakens the direct cooling effect on the coal seam. Considering the influence patterns of each parameter, the optimal combination was determined as water injection pressure of 10 MPa, water injection temperature of 10 °C, and level spacing of 80 m, which delivers the best overall performance by enabling rapid coal seam cooling and sustained geothermal energy extraction, with a cumulative geothermal output reaching 129.45 MW after 10 years of operation. This study provides a theoretical basis and technical reference for the integrated management of thermal hazards and geothermal resource development in deep coal mines. Full article

Two-stage absorption lithium bromide (Li-Br) refrigeration technology can utilize low-temperature heat sources to achieve refrigeration, thus it holds promising application prospects in the utilization of low-temperature waste heat. However, the performance of two-stage lithium bromide absorption chillers during variable operating conditions is difficult to accurately predict, necessitating further research. Unlike existing simulation-based studies, this paper employs an experimental approach for the first time to investigate the variable-condition performance of a two-stage lithium bromide absorption chiller. A 10 kW two-stage absorption Li-Br chiller was tested under variable operating conditions, including variations in chilled water outlet temperature, cooling water inlet temperature, hot water inlet temperature, and hot water flow rate. The experimental results indicate that each 1 °C increase in the chilled water outlet temperature leads to an additional 0.282 kW in cooling capacity and a 0.0071 increase in coefficient of performance (COP). Similarly, a 1 °C decrease in the cooling water inlet temperature results in a 0.366 kW increase in cooling capacity and a 0.0055 improvement in COP. When the hot water inlet temperature rises by 1 °C, the cooling capacity increases by 0.324 kW, while the COP remains nearly unchanged. Furthermore, a 10% increase in the hot water mass flow rate enhances the cooling capacity by approximately 5% and improves the COP by about 1%. Full article

The conventional reactive cooling strategy, which relies on static thresholds, has become inadequate for managing dynamically changing heat loads, often resulting in energy inefficiency and increased risk of local hot spots. In this study, we develop a data center cooling optimization system that integrates distributed sensor arrays for predictive analysis. By deploying high-density temperature and humidity sensors both inside and outside server racks, a real-time, high-fidelity three-dimensional digital twin of the data center’s thermal environment is constructed. Time-series analysis combined with Long Short-Term Memory algorithms is employed to forecast temperature and humidity based on the extensive environmental data collected, achieving high predictive accuracy with a root mean square error of 0.25 and an R² value of 0.985. Building on these predictions, a proactive cooling control strategy is formulated to dynamically adjust fan speeds and the opening degree of chilled-water valves in computer room air conditioning units, changing the cooling approach from passive to preemptive prevention of overheating. Compared with conventional proportional–integral–differential control, the developed system significantly reduces overall energy consumption and maintains all equipment within safe operating temperatures. Specifically, the framework has reduced the energy consumption of the cooling system by 37.5%, lowered the overall power usage effectiveness of the data center by 12% (1.48 to 1.30), and suppressed the cumulative hotspot duration (temperature 27 °C) by nearly 96% (from 48 to 2 h). Full article

Traditional firefighting protective clothing materials, such as meta- and para-aramid fibers, provide significant thermal protection but often fail to adequately manage heat stress and moisture, especially due to the incorporation of semi-permeable membranes within the three-layer garment structure known as turnout gear. Integrating hydrogels into textiles for firefighting personal protective clothing (PPC) could enhance thermoregulation and moisture management, providing firefighters with improved comfort and safety. Hydrogels are three-dimensional, hydrophilic polymer networks capable of holding substantial amounts of water. Their high water content and excellent thermal properties make them ideal for cooling applications. Therefore, this review focuses on the potential of hydrogel-infused textiles to improve firefighters’ PPC by enhancing thermal comfort and moisture management. Specifically, hydrogel structures and engineered properties for enhanced performance are presented, including smart hydrogels and hydration customization mechanisms. Hydrogel integration into firefighting PPC for moisture management and improved thermoregulation is explored, including current and future market projections and state-of-the-art clinical trial findings. Overall, the future of hydrogel-integrated textiles for firefighting PPC is bright, with numerous advancements and trends poised to enhance the safety, comfort, and performance of protective gear. Full article

This study aimed to prepare water-based nanofluids using Al₂O₃ nanoparticles with different types of surfactants, and to investigate the colloidal and thermophysical properties of the obtained nanofluids. In this context, water-based Al₂O₃ nanofluids have been prepared using six surfactants with anionic, cationic, and nonionic characteristics SDS, CTAC, PVP, Tween 80, PVA, and Triton X-100. The electrostatic colloidal stability of the prepared samples has been determined by zeta potential and particle size measurements. To understand the interactions at the molecular level and the stabilities in terms of interaction Gibbs free energy, nanoparticle–surfactant interactions have been modeled using the DFT (Density Functional Theory) method. The overall colloidal stability rankings of nanofluids have been performed using both zeta potential measurements and DFT analysis. Furthermore, the thermophysical properties of nanofluids, which are crucial for industrial applications, have been measured. The results showed that the type of surfactant has a significant effect on the colloidal and thermophysical properties of nanofluids. It has been concluded that Al₂O₃-SDS and Al₂O₃-CTAC nanofluids can be used in cooling systems due to their high zeta potential and thermal conductivity, and low viscosity and size. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

In this paper, characteristic ultraviolet absorption spectra are presented for benzene and chlorobenzene in transparent hexagonal water–ice solutions at temperatures between 273 K and 78 K. In addition, the liquid solution spectra at 292 K have also been included. The two lowest symmetry-forbidden transitions from the ground state (¹A_1g) to the first excited level of symmetry (B_2u), denoted as ¹B_2u ← ¹A_1g, and the transition from the ground state to the second excited level of symmetry (¹B_1u), denoted as ¹B_1u ← ¹A_1g, of benzene are recorded. The two lowest transitions of chlorobenzene from the ground state (¹A₁) to the first excited level of symmetry (¹B₂), denoted as ¹B₂ ← ¹A₁, and the transition from the ground state to the second excited level of symmetry (¹A₁) denoted as, ¹A₁ ← ¹A₁, are also studied. The bands are obtained for slowly cooled transparent water–ice solutions. Such ice samples, that were frozen from liquid water and cooled, show gradual changes in the spectra. Our study shows the spectra at eight temperatures, separating the spectra in different regions based on the range for the bands from ground state to the first and second excited states of benzene and chlorobenzene, observing changes in the integrated absorbances as a function of the temperature. For the spectra recorded at 78 K, the peak absorbances as a function of the wavelength are presented and tentatively assigned. Peak assignments are based on the known literature of benzene and chlorobenzene. The temperature range of our study covers some of the average temperatures that have been found in the icy moons of Saturn and the polar regions of Earth. Full article

Grinding is an essential process in mineral processing. Hydrogen-based mineral phase transformation, used to efficiently process refractory iron ores, can alter the physical and chemical properties of the ore, affecting its grinding characteristics. This paper uses iron ore from Baoshan, Shanxi Province, as the raw material for laboratory-scale hydrogen-based mineral phase transformation (HMPT) experiments and grinding tests. It examines the impact of four cooling methods on the ore’s grinding characteristics. The results show that samples cooled in a reducing atmosphere to 200 °C and then water-quenched exhibit the best relative grindability. For the same grinding time, the content of coarse-sized particles (+0.074 mm) in the product is lowest, while the fine-sized particles (−0.030 mm) is highest. The grinding kinetic parameters of the samples with this cooling method are the highest. After 2 min of grinding, the value of n is 1.3363, and the particle size distribution of the product is the most uniform. The BET and SEM test results indicate that samples with this cooling method have more internal pores, the largest pore size, and the most surface cracks and pores. This paper clarifies the effects of the HMPT cooling methods on grinding characteristics, providing a theoretical foundation for the efficient separation of iron ores. Full article

Introduction: Open-circuit cooling systems (OCCSs), integral to many industrial processes, often release blowdown water containing elevated concentrations of treatment chemicals. These discharges, if uncontrolled, pose substantial risks to aquatic ecosystems and human health. This study addresses the environmental implications of chemical emissions from OCCS blowdown through the development of a predictive model designed to estimate contaminant concentrations in receiving water bodies. Methods: The research employs a computational model based on mass-balance equations to simulate the dynamics of chemical emissions from blowdown water. It incorporates key operational variables, including flow rates, degradation rates, and evaporation characteristics. The model evaluates two chemical dosing strategies, continuous and fractional, and their resultant pollutant dispersal patterns in river systems. Validation was performed using empirical data from sulfuric acid (H₂SO₄) applications at a nuclear power plant between 2015 and 2022. Results: The model demonstrated strong agreement with observed sulfate ion concentrations in the receiving water body, confirming its predictive reliability. Continuous dosing resulted in stable levels of pollutants, while fractional dosing caused temporary peaks that did not exceed regulatory limits. Conclusion: The modeling of blowdown water reveals important implications for river water quality and suggests that current wastewater management practices may be insufficient, benefiting from the integration of predictive modeling for blowdown discharges in industrial settings. Full article