Search Results (13,437)

Functionally graded porous beams are increasingly used in lightweight engineering structures, where thermal effects and material inhomogeneity significantly influence vibration behavior. In this study, the thermoelastic free vibration of functionally graded porous Euler–Bernoulli beams with temperature-dependent material properties is investigated by considering uniform and symmetric porosity distributions, together with uniform, linear, and nonlinear temperature fields. The governing equations are derived based on classical Euler–Bernoulli beam theory and solved using the Differential Transformation Method, while the accuracy of the semi-analytical formulation is verified through a Hermite-based finite element model. The results show that increasing temperature reduces the bending stiffness due to thermal axial forces and leads to a rapid decrease in natural frequency as the critical buckling temperature is approached. Increasing porosity generally decreases the natural frequency, although a slight increase may occur in symmetric distributions because of the accompanying reduction in mass density. The present study provides a computational framework for the thermo-vibration analysis of functionally graded porous beams in lightweight structural applications. Full article

Uneven urbanization can lead to significant quantities of vacant and abandoned land while exacerbating urban heat island (UHI) effects and simultaneously adversely affecting socioeconomically disadvantaged communities. This study examines the correlation between land surface temperature (LST) and urban vacant and abandoned land in socially vulnerable neighborhoods in Houston, TX, USA, where extreme heat can present significant environmental and public health challenges. Six critical study locations exhibiting a social vulnerability index (SVI) over 0.7 and average land surface temperature (LST) values surpassing 82 °F (27.8 °C) are analyzed through spatial analytics and drone footage. Findings indicate that vegetated vacant spaces help mitigate urban heat by decreasing land surface temperature, but abandoned structures exacerbate temperatures due to heat retention from non-permeable surfaces. Findings suggest that elevated socioeconomic vulnerability correlates with increased land surface temperature, exacerbating heat-related hazards in at-risk communities. In this six-site sample, the abandonment rate exhibited a positive correlation with the site mean land surface temperature (exploratory linear fit: +2.42 °F [0.74, 4.11]/+1.35 °C [0.41, 2.28] per +1% increase in abandonment; to be interpreted as exploratory and potentially confounded). Results provide critical insights for climate resilience planning and urban heat reduction through high-resolution thermal and geographical analysis, highlighting the impact of vacant and abandoned land on LST. Such findings endorse certain urban cooling techniques, including land reutilization and green infrastructure, to enhance environmental equality and adaptation. Full article

The large-scale accumulation of steel slag from steelmaking and the over-exploitation of natural aggregates pose significant environmental and resource challenges. Focusing on the arid-cold region of Xinjiang, China, this study proposes the use of steel slag as a substitute for natural aggregates in pavement engineering. Through experimental performance evaluation and regionalized life cycle assessment (LCA), the technical feasibility and carbon reduction potential of this application were comprehensively evaluated. Results indicate that steel slag asphalt mixtures meet or exceed specification requirements in terms of high-temperature stability, water stability, and low-temperature crack resistance. However, volume stability decreases slightly with higher steel slag content and finer particle size, necessitating pretreatment for long-term durability. A local life cycle assessment model considering regional transportation factors was applied to the G30 Luhuo Expressway project. During the materialization stage, steel slag was used to replace 30% of the natural aggregates, reducing approximately 6718 kg of carbon dioxide equivalent emissions (31.4%). This, to some extent, reduced the extraction of natural resources, saved land resources, and alleviated the problems of resource shortage and price fluctuations. Sensitivity analysis reveals a positive correlation between carbon reduction and steel slag content, while transport distance strongly influences overall benefits, with a critical threshold of about 78 km defining the effective utilization range. Furthermore, a multi-objective optimization model balancing service life, cost, and carbon reduction was developed to identify an optimal steel slag content scheme, maximizing comprehensive benefits under constrained conditions. This work confirms the technical viability of steel slag pavement in extreme climates and provides a systematic framework integrating environmental benefits and logistical constraints, supporting regional industrial synergy and promoting circular economy practices in low-carbon infrastructure. Full article

This study presents an integrated optimization framework that combines the Design of Experiments (DOE) approach with Machine Learning (ML) techniques to minimize defects in the injection molding of Fuel Vapor Charcoal Canisters. The research focuses on five critical process parameters—melt temperature, mold temperature, filling time, pressure holding time, and pure cooling time—whose combined influence on major molding defects (warpage, shrinkage, shear stress, residual stress, and short shots) was systematically investigated. A Taguchi L25 orthogonal array was employed to structure the experiments and identify the optimal parameter levels through signal-to-noise (S/N) ratio analysis using the “smaller-the-better” quality criterion. The Taguchi results revealed that pressure holding time was the most influential factor, followed by mold temperature and melt temperature. Simulation results from SolidWorks Plastics confirmed the reduction in major defects under the optimized settings. To further validate and generalize the DOE findings, a Random Forest regression model was trained on the same dataset to capture nonlinear interactions between parameters. The model achieved an average RMSE of 2.451 ± 0.591 in five-fold cross-validation, demonstrating strong predictive accuracy. Feature importance analysis indicated that pressure holding time accounted for approximately 77.5% of the variance in the defect index, reaffirming its dominant role. A 3D response surface of the global parameter space (mold temperature vs. pressure holding time) revealed a distinct minimum defect region, consistent with the DOE-optimized settings. The Taguchi analysis identified the optimal parameter settings as Melt Temperature at Level 2, Mould Temperature at Level 3, Filling Time at Level 4, Pressure Holding Time at Level 5, and Pure Cooling Time at Level 4, which collectively produced the highest S/N ratios and the lowest overall defect index. The overall discrepancy between DOE and ML predictions was only 12.5%, confirming methodological consistency. The integration of DOE and ML not only enhances parameter interpretability and defect prediction accuracy but also provides a scalable, data-driven approach for intelligent process control and quality assurance in automotive injection molding. Full article

For the western Patagonia region (Argentina), climate change models predict a 1–3 °C increase in temperature and a 10%–30% reduction in precipitation. Patagonia native forests are home to a variety of soil fungi, including ectomycorrhizal fungi (EcM), which play a crucial role in drought-tolerant trees. However, the responses of soil fungi to changes in rainfall remain poorly understood. To evaluate shifts in soil fungal communities’ response under reduced precipitation scenarios and identify potentially drought-tolerant EcM species, we took 144 composite soil samples associated with Nothofagus forests along an east–west rainfall gradient. We used environmental DNA to estimate alpha and beta diversity of soil fungi and EcM. Soil fungal richness did not differ across precipitation treatments, whereas EcM richness declined with decreasing precipitation. Shannon and inverse Simpson indices of EcM decreased under reduced precipitation, whereas no significant effects were observed on soil fungi, highlighting the EcM vulnerability to water limitation. Soil fungi community composition changes along the rainfall gradient due to species replacement. Tarzetta sp., Cortinarius sp., and Russula sp. were found in drier plots, indicating a potential association with drought tolerance. Selecting native drought-tolerant EcM for forest management and restoration can improve seedling establishment and ecosystem resilience under climate change. Full article

Arsenic (As) is a ubiquitous and highly toxic metalloid with well-established carcinogenicity. Its accumulation and secondary release from lake sediments pose potential risks to lake ecosystem integrity and human health. Meanwhile, the ongoing intensification of lake eutrophication at the global scale has altered the sources, composition, and environmental behavior of internally derived dissolved organic matter (DOM). These changes have profoundly influenced As mobilization and transformation at the sediment-water interface (SWI). To advance understanding of the regulatory roles and underlying mechanisms of algal dissolved organic matter (ADOM) and submerged macrophyte dissolved organic matter (SMDOM) in As biogeochemical cycling under lake ecosystem regime shifts, extensive findings from the international literature were synthesized. The characteristic properties and environmental behaviors of ADOM and SMDOM were systematically compared, and their distinct regulatory pathways in lacustrine systems were further summarized. Results indicate that ADOM is typically characterized by low molecular weight, weak aromaticity, and high bioavailability. It can enhance As dissolution and mobilization from sediments through direct complexation, competition for adsorption sites, and stimulation of microbial metabolism and Fe(III) reduction. In contrast, SMDOM exhibits higher molecular weight, greater aromaticity, and a higher degree of humification. It tends to form stable complexes with mineral phases. Under the influence of radial oxygen loss (ROL) from submerged macrophyte roots during the growth phase, its capacity to promote mineral reduction is relatively limited. This process favors stable As retention in sediments. The regulatory effects of ADOM and SMDOM on As behavior are strongly modulated by environmental factors such as pH, redox potential (Eh), temperature, and light conditions, as well as by microbial communities. ADOM is more sensitive to reducing environments and photochemical processes. SMDOM, in contrast, exerts more persistent control under oxidizing conditions and at mineral-water interfaces. In addition, ADOM more readily drives microbial community shifts toward assemblages with enhanced capacities for Fe(III) reduction and As reduction or methylation. SMDOM is less likely to trigger strongly reducing processes. Based on these mechanisms, the outbreak and decay phases in algal-dominated lakes often correspond to critical periods of enhanced As mobilization and elevated ecological risk. In submerged macrophyte-dominated lakes, the decay phase may represent an important window for sedimentary As release. Finally, a conceptual framework describing the differential regulation of As biogeochemical cycling by ADOM and SMDOM is proposed. This framework provides a theoretical basis for As risk identification, the determination of critical risk periods, and the development of management strategies across lakes with different trophic states. Full article

To investigate the deterioration law of the mechanical properties of PVA-fiber-reinforced rubber concrete under the combined action of high-temperature and salt erosion, physical index tests, dynamic mechanical property experiments, and microstructural morphology observations were carried out on specimens subjected to different temperatures (ambient temperature, 100 °C, 300 °C) and various solution attacks (water, 5% NaCl, 5% Na₂SO₄, and 5% NaCl + 5% Na₂SO₄ mixture). The results show that, after exposure to 300 °C, the PVA fibers melt and the rubber pyrolyzes, since this temperature exceeds their melting points. A residual pore network is formed inside the matrix, and the damage degree of ultrasonic pulse velocity is about 2.3 times that of the 100 °C group. Although salt solution and its crystallization products can physically fill the pores and cause a partial recovery of pulse velocity, this change is mainly due to the alteration of the pore medium and does not represent a substantial restoration of the microstructure. The effects of different salt solutions on dynamic mechanical properties vary significantly: Sulfate erosion improves the dynamic performance significantly at ambient temperature by forming gypsum and ettringite to fill pores, but this strengthening effect disappears after 300 °C. Sodium chloride attack generates Friedel’s salt and consumes C₃A, leading to general strength deterioration. In composite salt erosion, the competitive and synergistic effects of Cl⁻ and SO₄²⁻ destabilize erosion products and weaken interfacial bonding, resulting in consistent decreases in dynamic compressive strength and elastic modulus under all temperatures and impact pressures. The strength reduction reaches 66.2% after 300 °C. Microscopic analysis confirms that composite salt erosion leads to the dissolution of ettringite and loose structure, which verifies the synergistic deterioration law of macroscopic properties. This study systematically reveals the damage evolution mechanism of PVA-fiber-reinforced rubber concrete under the coupled action of high-temperature and salt erosion, and provides a theoretical basis for the dynamic bearing capacity evaluation and durability design of concrete structures in such coupled environments. Full article

Thermally induced self-healing technology is regarded as an effective approach to mitigating the frequent occurrence of asphalt pavement distresses. Its efficiency, however, is highly dependent on the thermal conductivity of asphalt mixtures, which conventional aggregates can hardly satisfy. Meanwhile, high-titanium heavy slag (HTHS), an industrial solid waste rich in TiO₂, has been stockpiled in large quantities, and its large-scale resource utilization remains a critical challenge. Against this background, HTHS was employed in this study to replace limestone at equal mass ratios for the preparation of seven asphalt mastics (replacement rates of 0%, 20%, 40%, 60%, 80%, 100%, and neat asphalt) and four types of asphalt mixtures differentiated by coarse and fine aggregate compositions. The results indicate that with increasing HTHS content, the proportion of structural asphalt in the mastic increased markedly, leading to significant improvements in temperature susceptibility, high-temperature stability, and rutting resistance. Compared with the 100% limestone system, the penetration index (PI) of the 100% HTHS mastic increased by 8.4%, the softening point rose by 18.0%, and the rutting resistance factor at five temperatures from 46 °C to 70 °C increased by 21.8%, 56.8%, 79.2%, 171.7%, and 169.6%, respectively. Although low-temperature ductility decreased by 21.3% due to the reduction in free asphalt, it remained within acceptable limits. Regarding asphalt mixture performance, both high-temperature stability and low-temperature cracking resistance improved progressively with increasing HTHS replacement, showing increases of 75.56% and 11.75%, respectively, at full replacement. Water stability decreased by approximately 9% owing to the porous and water-absorptive nature of the slag, yet still satisfied specification requirements. In addition, the incorporation of HTHS significantly enhanced the thermal conductivity of the system, with increases of 0.125 W/(m·K) for asphalt mastics and 0.666 W/(m·K) for asphalt mixtures, corresponding to improvements of 33.7% and 32.2%, respectively. This study confirms that HTHS can serve as a viable asphalt pavement material capable of meeting the thermal conductivity requirements of thermally induced self-healing technology, while simultaneously providing a promising pathway for its large-scale resource utilization. Full article

The green synthesis of nanomaterials has emerged as a sustainable and environmentally friendly approach, gaining significant attention in recent years for its potential in a wide range of multifunctional applications. Among these materials, zinc oxide nanoparticles (ZnO NPs) stand out due to their remarkable versatility and effectiveness in fields such as industry (food, chemistry, and cosmetics), nanomedicine, cancer therapy, drug delivery, optoelectronics, sensors, and environmental remediation. This study focuses on bioinspired strategies for the facile synthesis of ZnO NPs, employing natural polysaccharide gums as mediators. Acting as both reducing and stabilizing agents, natural gums not only facilitate the eco-friendly production of ZnO NPs but also enhance their stability and functionality. Natural gum-mediated green synthesis typically yields stable, spherical ZnO particles, often in the 10–100 nm range. Typical reaction conditions are the use of zinc acetate dihydrate or zinc nitrate (0.01–0.5 M) as precursors, with low gum concentrations of 0.1–1.0% (w/v) in distilled water, alkaline conditions (pH from 8 to 12), often achieved by adding NaOH, which aids in the reduction and capping by the gum, at reaction temperature between 60 °C and 80 °C, under continuous stirring. The dried precipitate is often calcined at 400 °C to 600 °C to remove organic residues and enhance crystallinity. This approach underscores the potential of biopolymer-assisted synthesis in advancing green nanotechnology for sustainable and practical applications. Utilizing environmentally benign materials such as natural gums for the synthesis of ZnO NPs offers significant advantages, including enhanced eco-friendliness and biocompatibility, making them suitable for a wide range of applications without the involvement of toxic reagents. This review provides an in-depth analysis of the synthesis and characterization techniques employed in the eco-friendly production of ZnO NPs using different natural gums from biological sources and its environmental applications (e.g., pollutant removal and increased agriculture sustainability). Full article

The escalating power density in Active Phased Array Radar has made the thermal management of Transmitter and Receiver (T/R) modules a critical bottleneck for radar performance. To address the thermal resistance of traditional cold plates, this study investigates an innovative embedded cooling strategy utilizing micro-pyramid arrays and advanced nanofluids. Thermal performance was evaluated using maximum temperature, maximum temperature difference and surface temperature standard deviation (ST). Higher pyramid density markedly enhances temperature uniformity, an effect that scales positively with the power load. Under a 100 W condition, the 8-circle micro-pyramids configuration (the densest structure with roughness Ra = 1.3) achieved a 22.58 K reduction in maximum temperature and a 22.5% improvement in temperature uniformity compared to the 2-circle structure, and outperformed the 4-circle structure by 16.98 K and 17.9%, respectively. Furthermore, a comparative analysis of nanofluids (Al₂O₃, CuO, graphene, and h-BN) is conducted and it is found that graphene nanofluid exhibits the best overall heat transfer enhancement because of its high thermal conductivity and moderate reduction in specific heat capacity. The thermal performance of the nanofluid is evaluated by comparing the maximum temperatures of the heat source at the 8-circle structure. The synergistic coupling of graphene nanofluid with the 8-circle array yields a remarkable 35.38% enhancement in temperature uniformity at 100 W. The enhancement mechanisms are mainly attributed to intrinsic thermophysical properties of the nanoparticles and convection caused by denser pyramid array. The aforementioned findings provide important guidance for the thermal management design of antenna and other high-density integrated electronic systems with embedded cold plate design demand. Full article

Exhaust after-treatment (EAT) thermal management remains a critical challenge for diesel engines operating under low-load conditions, where low exhaust temperatures delay catalyst light-off and reduce emission control efficiency. This operating regime is common in marine auxiliary engines and onboard diesel generator sets during hoteling, maneuvering, and partial-electrical-load conditions. Conventional strategies such as late fuel injection or exhaust throttling can increase exhaust temperature but often result in significant fuel consumption penalties. This study numerically investigates the combined use of late exhaust valve opening (LEVO) and cylinder deactivation (CDA) to enhance EAT thermal management with a reduced fuel penalty. A six-cylinder diesel engine is analyzed at a low-load condition (1200 RPM, 2.5 bar BMEP) using a calibrated one-dimensional engine simulation model. LEVO applied to all cylinders increases exhaust temperature to approximately 250 °C, but with a considerable increase in fuel consumption. When two cylinders are deactivated and the remaining cylinders operate with LEVO, airflow and pumping losses decrease, enabling higher exhaust temperatures at comparable fuel consumption levels. Despite a 30% reduction in exhaust mass flow rate, the higher exhaust temperature dominates EAT heat transfer. Consequently, the combined strategy increases EAT heat transfer by up to 143% and achieves exhaust temperatures approaching 295 °C. These results indicate that combined valve timing and load redistribution through CDA can improve the exhaust temperature–mass flow trade-off, providing a potential pathway for enhanced EAT warm-up during low-load operation within the limitations of the numerical model. Full article

Baihua Reservoir, a typical large waterbody in the karst region of southwestern China and an essential drinking water source, is characterized by a high carbonate buffering capacity that profoundly shapes the structure and function of its phytoplankton community. This study systematically elucidates the multi-dimensional driving mechanisms underlying seasonal phytoplankton community assembly in karst reservoirs by integrating multiple analytical models—including the Neutral Community Model, β-diversity decomposition, co-occurrence network analysis, XGBoost-SHAP machine learning, and Partial Least Squares Path Modeling—based on monthly sampling at five sites from 2020 to 2024. The results revealed that: (1) Stochastic processes dominated community assembly across all four seasons, while deterministic processes played a crucial role in local species turnover. (2) The co-occurrence network structure showed significant seasonal dynamics, with the composition of keystone species adaptively shifting in response to changing environmental conditions. (3) The key environmental factors influencing the phytoplankton community exhibited clear seasonal patterns, primarily pH, NH₃-N, and COD_Mn in spring; water temperature, COD_Mn, and NH₃-N in summer; TN, TP, and pH in autumn; and pH, water temperature, and DO in winter. To support the sustainable management of karst reservoirs, we propose seasonally differentiated strategies derived from our phytoplankton community analysis: target COD_Mn reduction in spring and summer, focus on TN and TP load control in autumn, prioritize water column stability in winter, and maintain hydrological connectivity and pH monitoring year-round. This approach enhances phytoplankton community stability, safeguards drinking water safety, and provides a targeted management model for similar reservoir ecosystems globally. Full article

Oxy-fuel combustion is a near-zero emission technology that utilizes high-concentration O₂ in place of air, combined with recycled flue gas, to achieve efficient combustion and enable effective CO₂ capture. In this study, air (21% O₂/79% N₂) was used as the control atmosphere, and rice straw combustion experiments were conducted using thermogravimetric analysis and differential scanning calorimetry and differential scanning calorimetry coupled with mass spectrometry (TG-MS) at heating rates of 10, 20, and 30 °C/min under oxy-fuel conditions of 30% O₂/70% CO₂, 50% O₂/50% CO₂, and 70% O₂/30%CO₂. The combustion behavior, pollutant emissions, reaction kinetics, and underlying mechanisms were systematically evaluated. The results show that CO₂ in oxy-fuel atmospheres exhibits a higher thermal inertia, due to its greater density and specific heat capacity, thereby enhancing flame stability. Oxy-fuel atmospheres reduce the ignition temperature (Tᵢ) and burnout temperature (T_f), shorten the combustion duration, shift DTG and DSC peaks to lower temperatures, and result in sharper peaks along with an increased ignition index (Cᵢ), burnout index (C_b), and comprehensive combustion index (S). Mass spectrometry (MS) analysis reveals that oxy-fuel atmospheres combined with heating rates of 20–30 °C/min suppress O₂ diffusion and thermal NO formation, reducing NO_x emissions by over 75% and simultaneously inhibiting the release of SO₂ and COS. Kinetic analysis using the FWO and Friedman methods shows that the activation energy decreases from 210.5 kJ/mol and 219.1 kJ/mol under air conditions to 110.5 kJ/mol and 114.6 kJ/mol in oxy-fuel atmospheres, representing a reduction in reaction barriers of 47.5% and 47.7%, respectively. The reaction mechanisms were identified as three-dimensional diffusion-controlled processes at heating rates of 20–30 °C/min, and random nucleation followed by growth under high O₂ concentration conditions at a heating rate of 30 °C/min. Optimizing the combustion atmosphere and heating rate enhances the rice straw combustion efficiency and reduces pollutant emissions, thereby providing theoretical support for its clean and efficient utilization. Full article

The push for higher energy density in electric vehicles has resulted in large-sized lithium-ion batteries, but their geometric upscaling exacts a heavy thermal price. Under high-rate discharge, these massive cells become heat traps, risking thermal runaway. To tame this instability, this paper engineered a hybrid management strategy fusing liquid cooling, Phase Change Materials (PCMs), and flow deflectors. With a primary focus on the structural optimization of the cooling channel, a three-dimensional numerical model, calibrated using experimentally determined thermophysical properties, was developed to overcome the thermal bottlenecks of conventional cooling architectures. Results indicated that the initial channel optimization effectively reduced the maximum temperature to 327.7 K, but it still remained near the safety threshold. Integrating PCM radically altered the thermal landscape, slashing the outlet temperature differential by 41.67% (from 2.76 K to 1.61 K) compared to pure liquid cooling and blunting peak thermal spikes. Furthermore, to overcome laminar stagnation, strategic deflector baffles were introduced to agitate the coolant, enhancing heat dissipation. Specifically, the optimal half-coverage (L = 1/2) baffle configuration successfully lowered the maximum temperature to 322.42 K while substantially reducing the system pressure drop from 948.16 Pa to 627.57 Pa, achieving a 33.33% reduction compared to the full-coverage scheme. Finally, a multi-variable sensitivity analysis confirmed the extraordinary engineering robustness of the optimized configuration, demonstrating a negligible maximum temperature fluctuation of less than 0.5% despite ±10% operational and material uncertainties. This synergistic system actively stabilizes the thermal envelope, offering a robust engineering blueprint for next-generation high-power battery packs. Full article

Industrial-scale Anaerobic Digestion (AD) is a key technology for the energy recovery of agro-industrial and municipal waste and for the mitigation of greenhouse gas emissions; however, the actual operational performance of industrial biodigesters continues to show significant discrepancies with respect to the theoretical values reported in the scientific literature. In this context, there is still a lack of systematic analysis to identify which operating parameters are consistently monitored in industrial settings and which remain insufficiently explored, particularly those that describe the overall state of the digestion environment. To address this gap, a systematic literature review was conducted in the Scopus database for the period 2000–2026, complemented by a bibliometric analysis using VOSviewer software v1.6.18. 3. After applying inclusion criteria focused exclusively on industrial-scale and pilot systems, 1327 documents corresponding to the category of operating parameters were selected and analyzed using keyword co-occurrence networks and evaluation of occurrence frequencies and total link intensities. The analysis shows a marked concentration of the literature on a small set of classic parameters, highlighting pH (154 occurrences, 3667 link intensities), temperature (147 occurrences, 3255 link intensities), and ammonia (131 occurrences, 2824 link intensities) as the most recurrent variables in the industrial operation of anaerobic digesters. Complementarily, parameters such as chemical oxygen demand, total and volatile solids, and hydrogen sulfide have progressively increased their presence since 2015, mainly associated with effluent quality assessment, nutrient recovery, and overall process sustainability. In contrast, variables that integrate the state of the environment, such as electrical conductivity, oxidation-reduction potential, and the rheological properties of digestate, appear in less than $5\%$ of the studies analyzed, despite their ability to integrate information on stability, buffer capacity, and overall operating conditions. Taken together, these findings highlight an imbalance between the intensive use of traditional parameters and the limited incorporation of integrative indicators in industrial monitoring, suggesting that their systematic inclusion, together with the development of soft sensors and predictive models, could contribute to improving operational control and reducing the gap between the theoretical performance and actual behavior of industrial biodigesters. Full article