Search Results (3,052)

This study analyzes the compressive behavior and reliability of Al-Mg-Si (6061) metal matrix composites reinforced with different weight fractions of Al₂O₃ and SiC ceramics and cast with graphite and steel molds. Compression tests were carried out according to ASTM E9 with 0–8 wt.% reinforcement. The mold material significantly influenced the strength due to the cooling rate and interfacial adhesion. A two-parameter Weibull model assessed statistical reliability and extracted the shape (β) and scale (η) parameters using linear regression. Advanced models—lifelines (frequentist) and Bayesian models—were also applied. Graphite molds yielded composites with higher shape parameters (β = 6.27 for Al₂O₃; 5.49 for SiC) than steel molds (β = 4.66 for Al₂O₃; 4.79 for SiC). The scale values ranged from 490–523 MPa. The lifelines showed similar trends, with the graphite molds exhibiting higher consistency and scale (ρ = 7.45–9.36, λ = 479.71–517.49 MPa). Bayesian modeling using PyMC provided posterior distributions that better captured the uncertainty. Graphite mold samples had higher shape parameters (α = 6.98 for Al₂O₃; 8.46 for SiC) and scale values of 489.07–530.64 MPa. Bayesian models provided wider reliability limits, especially for SiC steel. Both methods confirmed the Weibull behavior. Lifelines proved to be computationally efficient, while Bayesian analysis provided deeper insight into reliability and variability. Full article

This study assessed the critical fire resistance of bridge cables by investigating post-fire tensile degradation of high-strength steel wires (1860, 1960, 2100 MPa) heated under initial stress (10% and 40% of design strength) to 300 °C, 400 °C, 500 °C, and 600 °C followed by cooling to an ambient temperature. Tensile tests determined reduction coefficients (RCs) for proportional limit (σ_p), yield strength (σ_y), ultimate strength (σ_u), elastic modulus (E), and elongation (δ) relative to ambient values, with constitutive models for σ_p, σ_y, and σ_uRCs integrating temperature, stress, and grade. Visual observation showed intensified wire hue and reduced necking with increasing temperature. All RCs remained stable up to 300 °C; beyond this temperature, σ_p, σ_y, and σ_uRCs progressively decreased, averaging 77.5%, 65.7%, and 61.9% at 600 °C under lower-level initial stress (10%) and 74.1%, 63.8%, and 60.6% at 400 °C under higher-level initial stress (40%). Elastic modulus exhibited minimal variation, whereas elongation reached its minimum at 400 °C under lower-level initial stress but its maximum at 400 °C under higher-level initial stress. The impact of lower-level initial stress on mechanical properties was negligible, showing a less than 3.2% average RC decrease at 600 °C. Higher-level initial stress accelerated mechanical property degradation with increasing temperature, with comparable degradation patterns observed across different steel wire strength grades. The models confirm maximum temperature dominance in degradation, supporting a recommended critical fire-resistant temperature of approximately 400 °C for bridge cable wires. Full article

With the growing demand for energy, oil and gas exploration and development are progressively moving into deep and ultra-deep formations, where extreme temperatures and pressures create complex challenges for drilling operations. While drilling fluids are critical for controlling bottom-hole pressure, cooling drill bits, and removing cuttings, accurately characterizing their rheological behavior under high-temperature and high-pressure (HTHP) conditions remains a key focus, as existing research has limitations in model applicability and parameter prediction range under extreme downhole environments. To address this, the study aims to determine the optimal rheological model and establish a reliable mathematical prediction model for drilling fluid rheological parameters under HTHP conditions, enhancing the precision of downhole temperature and pressure calculations. Rheological experiments were conducted on eight field-collected samples (4 water-based and four oil-based drilling fluids) using a Chandler 7600 HTHP rheometer, with test conditions up to 247 °C and 140 MPa; nonlinear fitting via a hybrid Levenberg–Marquardt and Universal Global Optimization algorithm and multivariate regression were employed for model development. Results showed that oil-based and water-based drilling fluids exhibited distinct rheological responses to temperature and pressure, with the Herschel–Bulkley model achieving superior fitting accuracy (coefficient of determination > 0.999). The derived prediction model for Herschel–Bulkley parameters, accounting for temperature-pressure coupling, demonstrated high accuracy (R² > 0.95) in validation. This research provides an optimized rheological modeling approach and a robust prediction tool for HTHP drilling fluids, supporting safer and more efficient deep and ultra-deep drilling operations. Full article

This study numerically investigated how varying pulse durations of water mist systems influence fire dynamics in long, narrow underground enclosures. A Fire Dynamics Simulator (FDS) model was built to represent a pulse-actuated, fine water mist test rig, and simulations of oil pan fires were performed to quantify the evolution of temperature and radiative heat flux. Results show that an 8 s spray followed by an 8 s pause yields the most effective suppression cycle. When spray and pause durations are equal, periodic momentum exchange resonates with the buoyant plume, intensifying the mixing of gas and enhancing cooling near the fire seat. Compared with continuous discharge, pulsed mist generates stronger buoyancy-driven disturbances and delivers superior performance in terms of local heat’s extraction and extinguishment. This study has, for the first time, determined the optimal pulse cycle (8 s spray/8 s stop) for oil pool fires in narrow and long underground spaces through FDS simulation, and revealed the enhancement effect of the gas disturbance resonance mechanism on fire suppression efficiency. Full article

One of the most important applications of solar energy is electricity generation using photovoltaic (PV) panels. Yet, as the temperature of PV modules rises, both their efficiency and service life decline. A common approach to mitigate this issue is cooling with fins, a design that is now widely adopted. However, traditional fin-based cooling systems often fail to deliver adequate performance in hot regions with strong solar radiation. In particular, passive cooling alone shows limited effectiveness under conditions of high ambient temperatures and intense sunlight, such as those typical in Malaysia. To address this limitation, hybrid cooling strategies, especially those integrating both air and water, have emerged as promising solutions for enhancing PV performance. In this study, an experimental and economic investigations were carried out on a PV cooling system combining copper tubes and aluminium fins, tested under Malaysian climatic conditions. The economic feasibility was evaluated using the Simple Payback Period (SPP) method. An outdoor test was conducted over four consecutive days (10–13 June 2024), comparing a conventional PV module with one fitted with the hybrid cooling system (active and passive). The cooled module achieved noticeable surface temperature reductions of 2.56 °C, 2.15 °C, 2.08 °C, and 2.58 °C across the four days. The system also delivered a peak power gain of 66.85 W, corresponding to a 2.82% efficiency improvement. Economic analysis showed that the system’s payback period is 4.52 years, with the total energy value increasing by USD 477.88, representing about a 2.81% improvement compared to the reference panel. In summary, the hybrid cooling method demonstrates clear advantages in lowering panel temperature, enhancing electrical output, and ensuring favorable economic performance. Full article

This study explores a submerged architectural strategy for data center deployment in coal mining subsidence water bodies, aiming to simultaneously address the underutilization of post-mining landscapes, the high-carbon operation of data centers, and the implementation challenges of China’s dual carbon goals. The proposed structure integrates wall-mounted plate heat exchangers into the façades of underwater data halls, using the natural convection of surrounding water as a low-grade heat sink to replace conventional cooling towers and achieve passive, low-carbon cooling. A thermal exchange model was developed based on heat transfer principles and validated by comparing outputs from TRNSYS simulations and MATLAB-based parameterized calculations, showing a deviation of less than 3% under all test conditions. The model was then used to estimate energy consumption, PUE, and carbon emissions under typical IT load scenarios. Results indicate a 42.5–64.3% reduction in cooling energy use and a 37.7–75.1% reduction in carbon emissions compared to conventional solutions, while a PUE range of 1.06–1.15 is maintained. The system also offers strong spatial adaptability and scalability, presenting a sustainable solution for redeveloping subsidence zones that supports ecological restoration and digital transformation in resource-depleted urban regions. Full article

In the three-roll planetary rolling process, excessively high surface temperature of the rolls can easily lead to copper adhesion, deterioration of roll surface quality, shortened rolling lifespan, and severely affect the quality of copper tube products as well as production efficiency. To improve the cooling efficiency of the roll cooling system, this study developed a fluid–solid–heat coupled model and validated it experimentally to investigate the effects of nozzle diameter, spray angle, and axial position of the spray ring on the cooling performance of the roll surface. Given the low computational efficiency of finite element simulations, three machine learning models—Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Support Vector Machine (SVM)—were introduced and evaluated to identify the most suitable predictive model. Subsequently, the Particle Swarm Optimization (PSO) algorithm was employed to optimize the geometric parameters of the spray ring. The results show that the maximum deviation between the coupled model predictions and experimental data was 4.36%, meeting engineering accuracy requirements. Among the three machine learning models, the RF model demonstrated the best performance, achieving RMSE, MAE, and R² values of 1.7336, 1.3203, and 0.9082, respectively, on the test set. The combined RF-PSO optimization approach increased the heat transfer coefficient by 44.72%, providing a robust theoretical foundation for practical process parameter optimization and precision tube manufacturing. Full article

The advent of silicon carbide (SiC) semiconductors in electric traction enables several benefits, including the shift to passive cooling. However, it requires a conjugate heat transfer analysis to understand the temperature distribution and variation. While steady-state solutions exist, transient conditions in rail vehicles remain challenging. This paper develops two analytical models to predict temperature distribution and variation, validated against numerical simulations. An electric motor model estimates power losses in the converter, defining heat dissipation. The complete model is tested under realistic drive cycles, linking operational conditions to power losses and free flow speed. The results show the model effectively captures temperature variations, with higher losses during acceleration and larger temperature surges of around 70 K at lower speeds. Furthermore, the temperature at the junction was observed to be 20 K higher than at the base position and to exceed 420 K at a more downstream location. Thus, the proposed method captures the temperature variations considering different physical effects with reasonable accuracy and significantly faster computation times than transient numerical simulations. Full article

Injection molding is widely used for mass-producing plastic components, demanding precise thermal control to optimize cycle times and part quality. Traditional CNC-machined molds limit design flexibility and restrict advanced cooling features like conformal cooling channels (CCCs). Integrating CCCs improves cooling performance, reduces cycle times, and offers more efficient, cost-effective designs. Additive manufacturing (AM), especially Metal-Fused Filament Fabrication (Metal-FFF), offers geometries unattainable by machining. While most mold research focuses on Laser Powder Bed Fusion (LPBF), the feasibility of Metal-FFF molds remains underexplored. This study presents the design, fabrication, and experimental evaluation of an injection mold produced via Metal-FFF with integrated CCCs. The process included computational design, resistance simulations, fabrication, debinding, sintering, and post-processing, followed by testing under injection molding conditions. Results show that Metal-FFF molds with CCCs boost cooling efficiency, cutting cycle times by about 30% compared to conventional molds, while offering greater design freedom and economic benefits. Nonetheless, issues such as porosity and shrinkage need further refinement to fully leverage this technology for industrial use. Full article

This study investigated the effect of supersolidus liquid-phase sintering conditions on the powder particle bonding and the AlN-phase formation of an AlSi10Mg alloy. Sintering was conducted at temperatures between 550 and 579 °C, with a holding duration of 2 h under a nitrogen atmosphere. The sintering cycles included four heating segments, performed at rates ranging from 0.2 to 5 °C/min for a total of between 5 and 15 h, and a cooling segment performed at two different cooling rates, 0.15 and 5 °C/min, resulting in durations of 12 and 70 h, respectively. Three powder batches exhibiting different particle size distributions were tested. An X-ray diffractometer, optical microscopy, and scanning electron microscopy were used to characterize phase formation and particle bonding. The results show that higher sintering temperatures and faster heating/cooling rates led to a lower fraction of AlN. In contrast, lower sintering temperatures or slow heating promoted the development of a thicker AlN shell around powder particles, inhibiting the bonding of the AlSi10Mg powder and preventing densification via the sintering process. These findings suggest that sintering at temperatures between 570 and 575 °C, with heating and cooling rates of at least 2 °C/min, constitutes a more favorable window for the densification of AlSi10Mg under a nitrogen atmosphere. Full article

Lithium-ion batteries (LIBs) have garnered extensive application across various domains. However, frequent safety incidents associated with these LIBs have emerged as a significant impediment to their further advancement. Consequently, there is an urgent necessity to develop a novel fire extinguishing agent that possesses both rapid fire suppression and efficient cooling capabilities, thereby effectively mitigating the occurrence and propagation of fires in LIBs. This study pioneers the development of an adaptive thermosensitive microcapsule (TM) fire extinguishing agent synthesized via in situ polymerization. The TM encapsulates a ternary composite core—perfluorohexanone (C₆F₁₂O), heptafluorocyclopentane (C₅H₃F₇), and 2-bromo-3,3,3-trifluoropropene (2-BTP)—within a melamine–urea–formaldehyde (MUF) resin shell. The TM was prepared via in situ polymerization, combined with FE-SEM, FTIR, TG–DSC, and laser particle size analysis to verify that the TM had a uniform particle size and complete coating structure. The results demonstrate that the TM can effectively suppress the thermal runaway (TR) of LIBs through the synergistic effects of physical cooling, chemical suppression, and gas isolation. Specifically, the peak TR temperature of a single-cell LIB is reduced by 14.0 °C, and the heating rate is decreased by 0.17 °C/s. Additionally, TM successfully blocked the propagation of TR thereby preventing its spread in the dual-LIB module test. Limitations of single-component agents are overcome by this innovative system by leveraging the ternary core’s complementary functionalities, enabling autonomous TR suppression without external systems. Furthermore, the TM design integrates precise thermal responsiveness, environmental friendliness, and cost-effectiveness, offering a transformative safety solution for next-generation LIBs. Full article

High-entropy alloys (HEAs) exhibit superior properties for extreme environments, yet the effects of laser scanning speed on the microstructure and performance of laser-clad NiAlNbTiV HEA coatings remain unclear. This study systematically investigates NiAlNbTiV coatings on 316 stainless steel fabricated at scanning speeds of 800–1100 mm/min via laser cladding. Characterizations via XRD, SEM/EDS, microhardness testing, high-temperature wear testing, and electrochemical measurements reveal that increasing scanning speed enhances the cooling rate, promoting γ-(Ni, Fe) solid solution formation, intensifying TiV peaks, and reducing Fe-Nb intermetallics. Higher speeds refine grains and needle-like crystal distributions but introduce point defects and cracks at 1100 mm/min. Microhardness decreases from 606.2 HV (800 mm/min) to 522.4 HV (1100 mm/min). The 800 mm/min coating shows optimal wear resistance (wear volume: 0.0117 mm³) due to dense eutectic hard phases, while higher speeds degrade wear performance via increased defects. Corrosion resistance follows a non-linear trend, with the 900 mm/min coating achieving the lowest corrosion current density (1.656 μA·cm⁻²) due to fine grains and minimal defects. This work provides parametric optimization guidance for laser-clad HEA coatings in extreme-condition engineering applications. Full article

This study investigates the microstructure evolution and mechanical properties of DSS2209 duplex stainless steel fabricated via cold metal transfer wire arc additive manufacturing (CMT-WAAM). The as-deposited thin-wall components exhibit significant microstructural heterogeneity along the build height due to thermal history variations. Optical microscopy, SEM-EDS, and EBSD analyses reveal distinct phase distributions: the bottom region features elongated blocky austenite with Widmanstätten austenite (WA) due to rapid substrate-induced cooling; the middle region shows equiaxed blocky austenite with reduced grain boundary austenite (GBA) and WA, attributed to interlayer thermal cycling promoting recrystallization and grain refinement (average austenite grain size: 4.16 μm); and the top region displays coarse blocky austenite from slower cooling. Secondary austenite (γ₂) forms in interlayer remelted zones with Cr depletion, impacting pitting resistance. Mechanical testing demonstrates anisotropy; horizontal specimens exhibit higher strength (UTS: 610 MPa, YS: 408 MPa) due to layer-uniform microstructures, while vertical specimens show greater ductility (elongation) facilitated by columnar grains aligned with the build direction. Hardness ranges uniformly between 225–239 HV. The study correlates process-induced thermal gradients (e.g., cooling rates, interlayer cycling) with microstructural features (recrystallization fraction, grain size, phase morphology) and performance, providing insights for optimizing WAAM of large-scale duplex stainless steel components like marine propellers. Full article

This study investigated the performance of a hybrid desiccant dehumidification system integrated with a post-cooling mechanism, focusing on its application to energy-efficient indoor climate control. A liquid desiccant system using magnesium chloride (MgCl₂) was tested in its pure form and in combination with silica gel at 10% and 20% concentrations to enhance its moisture removal capabilities. The key parameters, including the air velocity (3–6 m/s), desiccant flow rate (1–3 LPM), and desiccant composition, were varied to analyze their effects on the dehumidification efficiency, moisture removal rate (MRR), temperature reduction after post-cooling, and coefficient of performance (COP). The results show that post-cooling using a crossflow heat exchanger effectively lowered the exit air temperature, ensuring thermal comfort. Addition of silica gel significantly improved system performance. The MgCl₂ + 20% silica gel mixture achieved the highest dehumidification efficiency of 0.86, the greatest temperature drop of 1.95 °C, and the maximum COP of 2.36 at optimal flow conditions. While the dehumidification efficiency declined with increasing air velocity due to reduced contact time, the COP increased owing to the higher thermal processing of the air stream. This study highlights the potential of optimized hybrid desiccant systems as sustainable solutions for building air conditioning, aligning with the key Sustainable Development Goals (SDGs) related to clean energy, climate action, and sustainable infrastructure. Full article

Heatwaves are increasing in frequency and intensity owing to climate change, posing severe health risks to urban populations, particularly vulnerable groups. This study investigates public perceptions, adaptive behavior, and policy awareness regarding extreme heat in Gwangju Metropolitan City, South Korea, a heat-prone urban area. Using a mixed-methods approach, we analyzed primary survey data from 814 residents and secondary data from the 2020 Gwangju Citizen Heatwave Awareness Survey. Statistical analyses, including chi-squared and t-tests, examined differences across socioeconomic age groups. Results indicate that while general awareness of heatwave risks is high, low-income residents exhibit lower perceived severity, limited access to mechanical cooling, and greater reliance on passive avoidance behaviors. Awareness and use of municipal cooling shelters were low, with satisfaction hindered by concerns over accessibility, cleanliness, and operational hours. Television and emergency text alerts were the main information channels; however, trust and perceived usefulness were limited. Policy recommendations include spatially targeted shelter placement informed by vulnerability mapping, improved operational standards, diversified risk communication, and enhanced community engagement. This study underscores the importance of equity-driven adaptation strategies and provides practical insights for global municipalities facing similar climate-related heat risks. Full article