Search Results (3,050)

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

Coastal power plants draw seawater from the open ocean through their cooling-water circulation systems. The cooling water falls over an overflow weir inside the siphon well, entraining large quantities of air, and generates a foam pollution plume upon discharge to the sea. By combining physical model experiments with numerical simulation, this study investigates the key factors governing foam stability and the aeration behavior of the water downstream of the siphon-well overflow weir. The principal conclusions are as follows: among the three single-factor variables tested in controlled laboratory conditions—temperature, salinity, and shellfish-flesh suspension concentration—the biological substance proxy showed the strongest effect on foam stability; when the shellfish-flesh suspension concentration reaches 20% (mass/volume basis, independently prepared), the foam volume and half-life increase by factors of 1.4 and 3.36, respectively, relative to the 4% baseline condition. When the dimensionless aeration depth z/z₉₀ < 0.75, the air-concentration profile rises relatively slowly with depth, whereas it increases more rapidly as the free surface is approached. Within the investigated viscosity range of 1.0–8.3 mPa·s (1.0 mPa·s for the pure-water control and 1.5–8.3 mPa·s for the measured viscosities of the 4–20% shellfish-flesh suspensions), the cross-sectional mean air concentration shows an overall decreasing trend as the liquid-phase viscosity increases, and the total bubble number density decreases correspondingly. The findings provide a laboratory-based indication of the mechanisms that must be addressed in the development of physical foam-suppression technologies; confirmation against field discharge water is required. Full article

Battery electric vehicle (BEV) fires in road tunnels can intensify thermal, smoke transport, visibility, and CO exposure hazards under confined ventilation. This study evaluated the combined mitigation performance of water mist and semi-transverse mechanical ventilation. A three-dimensional PyroSim/FDS model of a 200 m × 10 m × 5 m tunnel was established with a 7 MW BEV design fire at the midpoint. The prescribed-source model was assessed against a reduced-scale lithium-ion battery tunnel experiment; at the representative monitoring location, the simulated temperature history reproduced the main trend, with deviations of approximately 7% and 10% at the first and second peaks. Thirty-six coupled cases examined ventilation mode, nominal opening velocity, nozzle arrangement and spacing, flow rate input, droplet diameter, and spray cone angle. Supply ventilation improved hot-smoke-layer cooling and visibility, whereas exhaust ventilation more effectively reduced the local CO volume fraction. Under the baseline weighting scheme, the highest-ranked case reduced the peak local ceiling-region and near-fire gas temperatures by 77.8% and 82.2%, increased average visibility during 200–500 s by 42.9%, and achieved a comprehensive relative mitigation index (CRMI) of 56.6%. Two supplementary nominal 10 MW simulations showed that this case retained substantial thermal control, reducing the two peak temperatures by 65.7% and 74.1%, but did not improve local visibility or CO. Thus, the thermal-mitigation trend persisted at the higher nominal input, whereas the full multi-hazard ranking was not transferable across fire sizes. Full article

The coal gangue waste dumps formed by open-pit coal mining are prone to low-temperature oxidation and heat storage, creating deep hidden high-temperature abnormal areas, continuously releasing toxic gases, and causing complex disasters such as slope instability and water and soil pollution. At present, self-ignition prevention and control technology is only applicable to the shallow treatment of small and flat gangue mountains. For large, deep, high-temperature waste dumps with significant height differences, multiple steps, and large areas, there is a lack of an integrated, complete set of technologies. The multi-field coupling mechanism of grouting fire extinguishing lacks engineering verification, and there is no quantitative evaluation system combining long and short periods. This paper takes the deep spontaneous-combustion high-temperature area of the No. 5 spoil dump of Lutian Coal Mine of Wuhai Energy as the research object. With the core goals of precisely delineating the fire zone space, revealing the multi-field coupling fire extinguishing mechanism of grouting, and establishing a long-term quantitative evaluation system, this study proposes a multi-process joint governance technology, along with a standardized hole filling and zoned differentiated grouting parameter system. The research systematically demonstrated technical feasibility through on-site drilling, large-scale grouting construction, and full-process quality control and error analysis. The results show that the 50 m interval geothermal gradient boreholes can accurately identify high-temperature distributions in the deep part of the dump from 0 to 34 m. The maximum combustion depth of the fourth-level and fifth-level platforms is 34 m and 20 m, respectively. A total of 1578 grouting boreholes have been constructed, with a total grouting volume of 139,289.3 cubic meters. After the treatment, the concentrations of toxic gases were all below the detection limits of the equipment, and the single cooling range reached 43% to 87%. This research refined relevant theories on the spontaneous combustion control of large-scale multi-step waste dumps, established standardized engineering processes, and provided theoretical and engineering references for the prevention and control of spontaneous combustion of solid waste in similar mines. It holds significant value for the ecological safety of mines and regional pollution control. Full article

The scientific paper is focused on research into the effect of the end tanks’ material on the automotive engine’s radiator and the effect of the air-cooling mode on the efficiency of heat dissipation under engine idling conditions. Aluminium (AL) and plastic (PL) end tanks are compared when changing the cooling mode by fan on the radiator F1, the ram air fan F2 in the range of 6 to 10 m/s, and their combination F1+F2, in relation to cooling time and heat transfer parameters. The temperature parameters of the coolant during the cooling process are evaluated, and the values for the heat transfer rate, total heat transfer coefficient, and thermal efficiency are calculated. The correlating equations are created for the total heat transfer coefficient depending on the cooling mode. The AL radiator is more efficient in terms of total heat transfer coefficient compared to the PL radiator, ranging from 15.3% to 66.4% for all cooling modes. The combination of F1 and F2 cooling modes resulted in more efficient heat dissipation from both radiators. In the combined cooling mode, with a ram air velocity of 10 m/s, the PL radiator achieved maximum thermal efficiency of 94.3% at the cooling time of 55 s. The full-aluminium radiator is suitable for high-performance applications. Full article

Accurate HVAC load identification from low-frequency smart-meter data is important for commercial-building demand response and energy management, but remains difficult when high-frequency measurements, detailed physical models, and HVAC submeters are unavailable. This paper proposes a hybrid data-driven and knowledge-driven framework that integrates HVAC load disaggregation with day-ahead forecasting. Operating modes are first identified from normalized daily load shapes and calendar features using K-medoids clustering. For each mode, a non-HVAC baseline is constructed from mode-wise low-load observations, cyclic smoothing, and a label-free shape correction based on the representative operating profile and lower-tail load dispersion. HVAC load is then obtained as the physically constrained residual between whole-building load and the corrected baseline. Historical disaggregation estimates are subsequently used as pseudo-labels for a leakage-controlled Extra-Trees forecasting model that combines target-day weather and calendar information with admissible historical load features. Experiments on three 15 min NREL ComStock commercial-building datasets show that the proposed disaggregation method achieves R² values of 0.8308–0.9246 across building types, while the proposed forecasting model attains an R² of 0.7812 on the held-out test period. The results demonstrate an interpretable and submeter-free approach for HVAC load analysis under low-frequency metering, with the strongest performance under cooling-dominated conditions. Full article

Battery thermal management systems (BTMSs) are essential for maintaining the performance, efficiency, durability, and safety of electric-vehicle battery packs. Although fin-enhanced air-cooled BTMSs offer a simple and leakage-free cooling solution, their practical implementation is often limited by increased weight, insufficient temperature uniformity, and restricted heat-dissipation capability under high thermal loads. This study numerically investigates a compact air-cooled BTMS for two types of cylindrical lithium-ion batteries using aluminum and polypropylene (PP-$\beta$) circumferential fins in inline and staggered cell arrangements. Unlike previous fin-based air-cooling investigations, the present study combines a compact 2 × 4 battery pack with transverse and longitudinal center-to-center cell pitches of 1.2D, a direct comparison between metallic and lightweight polymer fins, and an assessment of two 18650 battery types with different capacities, thermophysical properties, and heat-generation characteristics. A three-dimensional steady-state conjugate heat-transfer model was developed in ANSYS Fluent to evaluate the effects of fin number, fin material, cell arrangement, ambient temperature, and inlet airflow velocity under discharge rates ranging from 1 C to 4 C. The results reveal that increasing the number of fins consistently reduced the maximum cell temperature but increased the pressure drop. The inline configuration generally achieved a lower maximum temperature and higher Nusselt number (Nu), whereas the staggered arrangement maintained a substantially lower pressure drop. Relative to the corresponding finless configurations, the Nu increased by 64.4–71.2% for the inline arrangement and 86.4–98.1% for the staggered arrangement. Polypropylene fins provided thermal performance close to that of aluminum fins in terms of maximum temperature while reducing the total fin mass by approximately 44.8%; however, aluminum fins maintained better temperature uniformity. These findings quantify the trade-offs among thermal performance, pressure drop, compact cell spacing, and system weight, providing design guidance for compact fin-enhanced air-cooled BTMSs. Full article

The stability and reliability of temperature sensors in industrial cooling systems are critical to process quality, energy efficiency, and operational safety. However, existing approaches lack systematic stability metrics and intelligent predictive capabilities. This study proposes an AI-driven framework integrating stability feature engineering with machine learning models for fault identification and early prediction of temperature sensors in power plant cooling systems. The framework introduces three physics-based stability indicators—rolling standard deviation (σ_roll), variation intensity index (VII), and short-term variation magnitude (ΔT_short)—to quantify sensor signal quality. These features, combined with operational parameters, are used to train support vector machine (SVM) and Long Short-Term Memory (LSTM) models for binary classification. The framework is validated using over 260,000 one-minute records per unit collected from three parallel steam-turbine generating units (Units 1, 2, and 3) of the same coastal thermal power plant. Each unit is served by an independent once-through seawater cooling loop instrumented with redundant Pt-100 temperature sensors at the inlet and outlet manifolds; the three units differ in their operating profile—Unit 1 operates under variable load with frequent cold-start events, Unit 2 under moderate variable load, and Unit 3 under stable high-load conditions—with data collected at 1 min intervals from January to June 2025. Under an explicitly anomaly-positive evaluation, with the full confusion matrix reported for every unit and model, classification performance is limited and strongly unit-dependent. In real-time identification, AUC-based ranking ability varies across units (SVM AUC = 0.65, 0.75, and 0.98 for Units 1–3; LSTM AUC = 0.66, 0.31, and 0.52), but under the extreme class imbalance (anomaly rate ≈ 0.07–0.13% in the test partitions), the calibrated operating-point precision and F1-scores remain low for all unit–model combinations (F1 ≤ 0.26, MCC ≤ 0.28). McNemar’s test indicates statistically significant paired differences for Units 1 and 2 but not for Unit 3. These results show that, on this dataset, neither model attains reliable anomaly classification, and that all reported metrics must be interpreted together with the disclosed confusion-matrix counts and severe class imbalance. The primary contribution of the framework is therefore methodological—physics-based stability indicators, redundant sensor cross-checking, and an operational false-alarm analysis—rather than high-accuracy prediction, and the study highlights the difficulty of learning-based prediction for rare, rule-defined thermal sensor anomalies. Full article

In this study, brick plant waste was used to produce alkali-activated mortars. Four mixtures with identical compositions but different mixing sequences and curing methods were prepared. Two were conventionally produced using a pre-cooled 10 M potassium hydroxide (KOH) solution and sodium silicate (Na₂SiO₃), with one cured at ambient conditions and the other at an elevated temperature. The remaining two used modified mixing sequences to utilize internally generated heat for curing (direct KOH powder addition and addition of KOH dissolved in water immediately before mixing). The influence of mixing sequence and curing method on mechanical properties and high-temperature performance was evaluated after exposure to 600 °C through residual flexural and compressive strengths, mass loss, and visual examination of specimen cross-sections. The two best-performing mortars were further characterized by Fourier-transform infrared spectroscopy (FT-IR) and field-emission scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (FE-SEM-EDS), while the mixture combining favorable high-temperature performance with simple preparation was additionally analyzed for thermal conductivity and specific heat capacity. The conventionally prepared, elevated-temperature-cured mixture exhibited the lowest room-temperature flexural and compressive strengths (2.7 and 12.9 MPa, respectively) but the best high-temperature performance, with flexural and compressive strength increases of 14.8% and 10.9%, respectively, after exposure to high temperature. Visual assessment may suggest some degree of structural densification in this mixture and in the mixture prepared by direct addition of KOH powder to the dry components, whereas the other two mixtures may exhibit signs of partial weakening in the interfacial transition zone (ITZ). Among the internally cured mixtures, direct KOH powder addition produced slightly better room- and high-temperature performance than adding KOH dissolved in water immediately before mixing. FT-IR and FE-SEM-EDS confirmed the formation of potassium and sodium aluminosilicate hydrate, (K,N)-A-S-H, gel in the conventionally prepared, elevated-temperature-cured mixture and the mixture with direct KOH powder addition. The nearly unchanged compressive strength of the KOH-powder-based mixture was associated with a high retention of thermal conductivity (93%) and specific heat capacity (80%) after high-temperature exposure. Full article

Roofing systems strongly influence the energy performance and environmental footprint of buildings, particularly in hot–arid climates such as Saudi Arabia, where cooling dominates electricity demand; however, the comparative lifecycle environmental performance of alternative roofing strategies remains underexplored in this specific climatic and market context. This study therefore aims to evaluate and compare the environmental performance of four sustainable roofing strategies against a conventional flat roof (FR) baseline in order to provide evidence-based guidance for climate-specific roofing selection in Saudi Arabia. This study conducts a comparative cradle-to-grave lifecycle assessment (LCA) of four sustainable roofing strategies considering the hot–arid climate of Saudi Arabia. Green roof (GR), cool roof (CR), solar photovoltaic roof (SPV), and roof canopy (RC) were assessed using the ReCiPe 2016 method in the SimaPro software. The environmental impacts of these strategies were assessed across product, construction, use, and end-of-life stages relative to conventional flat roofs (FRs). The results indicate that the production stage consistently contributes the highest environmental impacts, with increases ranging from 30 to 3000% for GR, CR, and RC and exceeding 10,000% for SPV. On the other hand, the use stage offers the greatest reductions ranging from 10 to 200%, particularly for SPV and CR, due to operational energy savings and electricity generation. Overall, CR demonstrates the most balanced environmental performance, combining high impact reductions with minimal trade-offs, while SPV provides significant climate and fossil resource benefits but increases mineral resource use. These findings highlight the importance of climate-specific and resource-conscious selection of roofing strategies in Saudi Arabia and provide a transferable comparative LCA framework that can inform sustainable roofing decisions in other hot–arid and hot–humid regions, in support of the Kingdom’s Vision 2030 objectives for sustainable urban development. Full article

Hybridizing concentrated solar power (CSP) with residual biomass allows supercritical CO₂ (sCO₂) power cycles to deliver dispatchable low-carbon electricity, but it is unclear whether the extra equipment of the more efficient layouts adds a life-cycle burden that offsets their thermodynamic gain. This work reports what is, to the authors’ knowledge, the first unified energy, exergy, environmental and exergoenvironmental comparison of two combined sCO₂–organic Rankine cycle (ORC) configurations—a simple and a recompression Brayton layout, both with reheating, regeneration and a toluene bottoming ORC—driven by a solar tower and a coconut-shell-biomass furnace. Life-cycle impacts are quantified with Eco-indicator 99, a damage-oriented method that scores construction, operation and decommissioning damage in milli-points (mPts), and are allocated to the exergy streams through the exergoenvironmental balance. Both cycles are modelled in Python with CoolProp properties and validated against published sCO₂ analyses (efficiency deviation below 7.3%). The recompression layout reaches 54.3% thermal and 32.0% second-law efficiency and cuts the exergy destruction from 173 to 128 kW. Its larger construction impact (22.6 vs. 20.1 mPts/h) is negligible against the shared biomass reheater (429.4 mPts/h), so it is also marginally cleaner overall (459 vs. 472 mPts/h). Efficiency-oriented layout selection is therefore environmentally safe, and the remaining leverage lies in the biomass supply chain. Full article

Cooling crystallization of DL-methionine requires the joint control of crystallization yield and bulk density because operating conditions that favor one response may impair the other. Here, single-factor experiments, Plackett–Burman screening, and a three-factor Box–Behnken response-surface design were combined to identify a local operating window. Stirring speed, crystallization time, and solution pH were retained for response-surface modeling. The quadratic models for crystallization yield and bulk density were significant, with R² values of 0.9910 and 0.9892, respectively, and nonsignificant lack-of-fit terms. Multi-response optimization selected a stirring speed of approximately 332 r/min, a crystallization time of 1.47 h, and a pH of 5.55. Three validation experiments produced yields of 48.98–49.57% and bulk densities of 0.2925–0.3035 g/mL, with relative errors below 5% compared with the model predictions. X-ray diffraction showed no detectable change in the principal DL-methionine crystal phase across representative products. X-ray photoelectron spectroscopy further showed closely matched near-surface C 1s, N 1s, O 1s, and S 2p features between the raw material and the product obtained under the optimized conditions. The sodium nitroprusside assay gave total methionine contents of 99.64–99.79% for the raw material and five representative products; for the model-selected product, the colorimetric result (99.79%) agreed with the amino acid analyzer result (99.93%) to within 0.14%. The combined PB–BBD/RSM workflow therefore supports local parameter selection within the tested design space while maintaining the principal crystal phase, near-surface chemical-state profile, and total methionine content of the recovered product. Full article

Hydrogen storage and separation remain major technical challenges limiting the broader implementation of hydrogen-based energy systems. Metal–hydride alloys offer a promising solution because they enable reversible hydrogen storage within their crystal structure and can selectively absorb hydrogen from multicomponent gas mixtures. However, the practical application of metal–hydride systems requires storage vessels that combine sufficient mechanical strength with effective heat removal, as hydrogen absorption is accompanied by significant heat generation that can reduce the reaction rate and usable storage capacity. This study addresses hydrogen storage within the crystal structure of metal alloys and introduces the potential of metal–hydride (MH) alloys for hydrogen separation from gas mixtures. It subsequently presents the structural design and strength assessment of a low-pressure, double-walled, tubular steel MH storage vessel intended for hydrogen storage in a MnTiVFeZr-based alloy. Structural simulations were performed in ANSYS 2025 R2 Static Structural at three operating pressures: 3, 5, and 7 MPa. For all three simulated pressure conditions, the gravimetric hydrogen storage capacity of the alloy was 0.992 ± 0.016 wt.%. Following the selection of the most suitable design with an operating pressure of 3 MPa, an analytical calculation was performed to verify the results obtained from the numerical analysis. The storage vessel was subsequently manufactured and subjected to experimental strength validation using the test procedures specified in the STN EN 13322-2 standard. The design of the low-pressure tubular steel MH storage vessel also incorporates an efficient thermal management system based on a combination of active and passive cooling modules. The passive cooling module takes the form of an internal heat-transfer enhancement element, which is inserted into the primary storage vessel together with the MH alloy. The active cooling module uses a coolant flowing around the outer wall of the primary vessel. The optimal design of the aluminium passive cooling module was selected from four variants based on a steady-state temperature-field analysis conducted in ANSYS CFX. The selected module was subsequently manufactured and integrated into the proposed storage vessel. The vessel equipped with the passive cooling element was then subjected to experimental temperature measurements during hydrogen absorption by the MH alloy. The experimentally obtained data were compared with the numerical simulation results to evaluate the temperature fields within the vessel and the heat dissipation from the core of the MH storage system during hydrogen absorption. The main contribution of this work is the development of a mechanically validated and thermally managed tubular metal–hydride vessel that integrates structural design, numerical optimisation, manufacturing, and full-scale experimental testing within a single methodology. The proposed approach provides a practical basis for the further development and scaling of low-pressure metal–hydride systems for hydrogen storage, purification, and separation applications. Full article

In response to issues such as disordered airflow distribution and prominent local hotspots in campus non-standard data centers, this study took a non-standard raised-floor air-supply data center at a university in Hangzhou as the research object, and used a combination of on-site measurements and computational fluid dynamics (CFD) numerical simulation to investigate the optimization of the thermal environment. The temperature and air velocity of the data center were measured using a handheld hot-wire anemometer, and a standard k-ε turbulence model was established on the 6SigmaDC platform (now Cadence Reality DC Design Pro, version 2024.1). Model accuracy was confirmed through grid independence verification with three mesh levels and statistical error metrics (MAE, MBE, RMSE) across multiple measurement zones. The results show that the mean absolute error of temperature does not exceed 0.9 °C in all zones and the mean absolute error of air velocity does not exceed 0.20 m/s, indicating that the model effectively reproduces the airflow distribution and thermal environment of the data center. On this basis, to address the uneven airflow distribution in the underfloor plenum, an optimization strategy was proposed that involved the installation of composite baffles and the coordinated adjustment of variable floor tile openings. Eight representative simulation scenarios were designed, with the coefficient of variation and air supply uniformity index as evaluation indicators. Results indicate that the combined effect of perforated baffles and variable floor tile openings is the optimal strategy, reducing the range of net airflow among air supply outlets from 0.100 to 0.077 m³/s, decreasing the coefficient of variation from 12.8% to 10.8%, and increasing the air supply uniformity index by 10.7%. Whole-room thermal environment verification shows that the optimal scheme reduces the supply heat index (SHI) from 0.42 to 0.35, with an estimated PUE reduction of about 0.03, achieving both airflow uniformity improvement and energy-saving benefits. By improving the cooling efficiency and reducing the PUE, this retrofit strategy contributes to the sustainable operation of small-to-medium-sized campus data centers, supporting energy efficiency and carbon footprint reduction goals under green campus and low-carbon initiatives. Full article

The growing demand for natural, skin-compatible cosmetic cleansers has driven interest in oil-based systems that can effectively remove waterproof cosmetics while remaining physicochemically stable. This study characterized hemp seed oil and evaluated it as a component of a water-in-oil (W/O) microemulsion makeup remover. Hemp seed oil showed good oxidative stability (peroxide value = 1.87 ± 0.23 mEq/kg). It contained 0.134 ± 0.01 mg gallic acid equivalents/g of oil weight of phenolic compounds. The oil was rich in linoleic and α-linolenic acids and contained α-tocopherol. Microemulsions were prepared by combining hemp seed oil with castor oil (C:H) or sunflower oil (S:H) at three oil ratios and four surfactant HLB values (4.3–12). From 72 candidate formulations, only sunflower oil:hemp seed oil systems in the ratio of 3:7 and HLB of 9.5 showed the best overall balance of stability, maintaining droplet size, low PDI, and consistent viscosity/turbidity over 2 months of storage and heating–cooling cycle testing. This formulation also exhibited cleansing efficiency (ΔE = 9.64), which was slightly lower than a commercial cleansing oil (ΔE = 9.74). These results illustrate the potential of hemp seed oil to be developed into a stable, effective W/O microemulsion cleansing system for cosmetic application. Full article