Search Results (1,204)

Urban thermal environments critically impact human settlements and sustainable urban development. In this study, a multi-index framework integrating Landsat TM/ETM+/OLI observations (2004–2019) is developed to quantify the contributions of “source–sink” landscapes to urban heat island (UHI) dynamics in Guangzhou, China, with direct implications for advancing sustainable development. Urban–rural gradient analysis was combined with emerging spatiotemporal hotspot modeling, revealing the following results: (1) there were thermal spatial heterogeneity with pronounced heat accumulation in core urban zones and improved thermal profiles in northern sectors, reflecting a transition from “more sources, fewer sinks” in the southwest to “fewer sources, more sinks” in the northeast; (2) UHIs were effectively mitigated within 25–35 km of the city center, with the landscape effect index (LI > 1) indicating successful sink-dominated cooling; (3) spatiotemporal hotspots were observed, including persistent UHIs in old urban areas contrasting with environmentally vulnerable coldspots in suburban mountainous regions, highlighting uneven thermal risks. This framework provides actionable strategies for sustainable urban planning, including optimizing green–blue infrastructure in UHI cores, enforcing cool material standards, and zoning expansion based on source–sink dynamics. This study bridges landscape ecology and sustainable development, offering a replicable model for cities worldwide to mitigate UHI effects through evidence-based landscape management. Full article

Urban heat exposure has become an increasingly critical environmental issue under the dual pressures of global climate warming and rapid urbanization, posing significant threats to public health and urban sustainability. However, conventional linear regression models often fail to capture the complex, nonlinear interactions among multiple environmental factors, and studies confined to single LCZ types lack a comprehensive understanding of urban thermal mechanisms. This study takes the central urban area of Zhengzhou as a case and proposes an integrated “Local Climate Zone (LCZ) framework + random forest-based multi-factor contribution analysis” approach. By incorporating multi-temporal Landsat imagery, this method effectively identifies nonlinear drivers of heat exposure across different urban morphological units. Compared to traditional approaches, the proposed model retains spatial heterogeneity while uncovering intricate regulatory pathways among contributing factors, demonstrating superior adaptability and explanatory power. Results indicate that (1) high-density built-up zones (LCZ1 and E) constitute the core of heat exposure, with land surface temperatures (LSTs) 6–12 °C higher than those of natural surfaces and LCZ3 reaching a peak LST of 49.15 °C during extreme heat events; (2) NDVI plays a dominant cooling role, contributing 50.5% to LST mitigation in LCZ3, with the expansion of low-NDVI areas significantly enhancing cooling potential (up to 185.39 °C·km²); (3) LCZ5 exhibits an anomalous spatial pattern with low-temperature patches embedded within high-temperature surroundings, reflecting the nonlinear impacts of urban form and anthropogenic heat sources. The findings demonstrate that the LCZ framework, combined with random forest modeling, effectively overcomes the limitations of traditional linear models, offering a robust analytical tool for decoding urban heat exposure mechanisms and informing targeted climate adaptation strategies. Full article

Fire retardancy and thermal management are critical for energy-efficient, fire-safe buildings. Natural wood, a mainstream construction material, possesses inherent advantages but lacks such dual functionality. Silicified wood was fabricated via multi-cycle silicification of native wood, where SiO₂ uniformly infiltrates and fills the lumens. The treated wood material displays an improved limiting oxygen index (LOI) from 21.9% to 36.0%, and delayed ignition from 15 s to 50 s, compared to untreated wood. It demonstrates a low thermal conductivity of 0.074 W·m⁻¹·K⁻¹, showing enhanced emissivity. When heated on a 75 °C hot plate, the silicified wood surface reaches ~50 °C after 5 s, versus ~60 °C for native wood. These enhancements collectively improve thermal management performance, achieving insulation through reduced thermal conduction and passive cooling via optimized infrared regulation. Ultimate tensile stress remains nearly unchanged post-treatment, while toughness is significantly improved. This work advances wood as a sustainable building material, with promising potential for fire-safe, energy-efficient construction applications. Full article

Power electronics convert and control electrical power in applications ranging from electric motors to telecommunications and computing. Ongoing efforts to miniaturize these systems and boost power density demand advanced thermal management solutions to maintain optimal cooling and temperature control. Spray cooling offers an effective means of removing high heat fluxes and keeping power electronics within safe operating temperatures. This study presents an experimental investigation of flash spray cooling in a closed-loop system using R410A refrigerant. In particular, two nozzles with different spraying angles are used to study the effects of the distance between the spray nozzle and a heated flat surface, as well as the mass flow rate of the coolant. Results indicate that three key flow-pattern factors—surface coverage, impingement intensity, and liquid film dynamics—govern the heat transfer mechanisms and determine cooling efficiency. Flash spray cooling using refrigerants like R410A demonstrates strong potential as a high-performance thermal management strategy for next-generation power electronics. Full article

This study investigates the uplift and exhumation history of the southern segment of the western margin of the Ordos Basin using low-temperature thermochronology, including zircon (U-Th)/He (ZHe), apatite fission-track (AFT), and apatite (U-Th)/He (AHe) data, combined with thermal history modeling. The study area exhibits a complex structural framework shaped by multiple deformation events, leading to the formation of extensively developed fault systems. Such faulting can adversely affect hydrocarbon preservation. To better constrain the timing of fault reactivation in this area, we carried out an integrated study involving low-temperature thermochronology and burial history modeling. The results reveal a complex, multi-phase thermal-tectonic evolution since the Late Paleozoic. The ZHe ages (291–410 Ma) indicate deep burial and heating related to Late Devonian–Early Permian tectonism and basin sedimentation, reflecting early orogenic activity along the western North China Craton. During the Late Jurassic to Early Cretaceous (165–120 Ma), the study area experienced widespread and differential uplift and cooling, controlled by the Yanshanian Orogeny. Samples on the western side of the fault show earlier and more rapid cooling than those on the eastern side, suggesting a fault-controlled, basinward-propagating exhumation pattern. The cooling period indicated by AHe data and thermal models reflects the Cenozoic uplift, likely induced by far-field compression from the rising northeastern Tibetan Plateau. These findings emphasize the critical role of inherited faults not only as thermal-tectonic boundaries during the Mesozoic but also as a pathway for hydrocarbon migration. Meanwhile, thermal history models based on borehole data further reveal that the study area underwent prolonged burial and heating during the Mesozoic, reaching peak temperatures for hydrocarbon generation in the Late Jurassic. The timing of major cooling events corresponds to the main stages of hydrocarbon expulsion and migration. In particular, the differential uplift since the Mesozoic created structural traps and migration pathways that likely facilitated hydrocarbon accumulation along the western fault zones. The spatial and temporal differences among the samples underscore the structural segmentation and dynamic response of the continental interior to both regional and far-field tectonic forces, while also providing crucial constraints on the petroleum system evolution in this tectonically complex region. Full article

Warpage is among the most prevalent defects affecting injection molded parts. In this study, we aimed to develop methods to minimize warpage through mold design. Common strategies include matching the cavity geometry to the intended shape of the part, adjusting cavity dimensions to offset material shrinkage, and optimizing the cooling system and critical injection molding parameters. These optimization methods can offer significant improvements, but recently introduced methods that optimize the molded part and mold cavity shape result in higher levels of warpage reduction. In these methods, optimization of the shape of the molded part is achieved by shaping it in the opposite direction of warpage—a method known as inverse contouring. Inverse contouring of molded parts is a design technique in which mold cavities are intentionally modified to incorporate compensatory geometric deviations in regions anticipated to exhibit significant warpage. The final result after molded part ejection and warpage is a significant reduction in deviations between the warped and reference molded part geometries. In this study, a two-step approach for minimizing warpage was used: the first step was optimizing the most significant injection molding parameters, and the second was inverse contouring. In the first step, Response Surface Methodology (RSM) and Autodesk Moldflow Insight 2023 simulations were used to optimize molded part warpage based on three processing parameters: melt temperature, target mold temperature, and coolant temperature. For improved accuracy, a Computer-Aided Design (CAD) model of the warped molded part was exported into ZEISS Inspect 2023 software and aligned with the reference CAD geometry of the molded part. The maximal warpage value after the initial simulation was 1.85 mm based on Autodesk Moldflow Insight simulations and 1.67 mm based on ZEISS Inspect alignment. After RSM optimization, the maximal warpage was 0.73 mm. In the second step, inverse contouring was performed on the molded part, utilizing the initial injection molding simulation results to further reduce warpage. In this step, the CAD model of the redesigned, inverse-contoured molded part was imported into Moldflow Insight to conduct a second iteration of the injection molding simulation. The simulation results were exported into ZEISS Inspect software for a final analysis and comparison with the reference CAD model. The warpage values after inverse contouring were reduced within the range of ±0.30 mm, which represents a significant decrease in warpage of approximately 82%. Both steps are presented in a case study on an injection molded part made of polybutylene terephthalate (PBT) with 30% glass fiber (GF). Full article

The electronics industry has significantly contributed to the development of efficient heat dissipation systems. One widely used technique is pool boiling, a simple method requiring no moving parts or complex structures. It enables the removal of large amounts of heat at relatively low temperature differences. Enhancing pool boiling performance involves increasing the critical heat flux and the heat transfer coefficient, which defines how effectively a surface can transfer heat to a cooling fluid. This method is commonly applied in cooling electronic devices, digital circuits, and power systems. In this study, pool boiling at atmospheric pressure was investigated using copper surfaces. To validate the Rohsenow model used to estimate the maximum bubble departure diameter, a planimetric approach was applied. Measurements included average contact angle (CA), surface tension (σ), and droplet diameter for four working fluids: deionised water, ethanol, Novec-649, and FC-72. For each fluid, at least 15 measurements of CA and σ were conducted using the Young–Laplace model. This study provides a comprehensive analysis of the influence of contact angle and surface tension on nucleate boiling using four different fluids on copper surfaces. The novelty lies in combining high-precision experimental measurements with validation of the Rohsenow model, offering new insights into surface-fluid interactions critical for thermal system performance. Full article

Welding, as a critical process for achieving permanent material joining through localized heating or pressure, is extensively applied in mechanical manufacturing and transportation industries, significantly enhancing the assembly efficiency of complex structures. However, the associated localized high temperatures and rapid cooling often induce uneven thermal expansion and contraction, leading to complex stress evolution and residual stress distributions that compromise dimensional accuracy and structural integrity. In this study, we propose a combined heat source model based on the geometric characteristics of the weld pool to simulate the arc welding process of large flange shafts made of Fe-C-Mn-Cr low-alloy medium carbon steel. Simulations were performed under different welding durations and shaft diameters, and the model was validated through experimental welding tests. The results demonstrate that the proposed model accurately predicts weld pool geometry (depth error of only 2.2%) and temperature field evolution. Meanwhile, experimental and simulated deformations are presented with 95% confidence intervals (95% CI), showing good agreement. Residual stresses were primarily concentrated in the weld and heat-affected zones, exhibiting a typical “increase–steady peak–decrease” distribution along the welding direction. A welding duration of 90 s effectively reduced residual stress differentials perpendicular to the welding direction by 19%, making it more suitable for medium carbon steel components of this scale. The close agreement between simulation and experimental data verifies the model’s reliability and indicates its potential applicability to the welding simulation of other large-scale critical components, thereby providing theoretical support for process optimization. Full article

Dynamic line rating (DLR) is an effective technique for real-time assessments on current-carrying capacities of overhead lines (OHLs), improving efficiencies and preventing overloads of transmission networks. Most research related to DLR forecasting mainly translates predictions of weather conditions into DLR forecasts or directly trains artificial intelligence models from DLR observations. Less attention has been given to the predictability of effective wind speeds (EWS) that describe overall convective cooling effects of varying weather conditions along OHLs, which could increase the reliability of DLR forecasts. To assess the effectiveness of EWS concepts in improving DLR predictions, this paper develops an EWS-based method for convective cooling predictions which are critical parameters dominating DLRs of overhead conductors. The EWS is first calculated from actual measurements of wind speeds and directions relative to OHL orientation based on the thermal model of overhead conductors. Then, an autoregressive model along with the Fourier series is employed to predict ultra-short-term EWS variations for up to three 10-min steps ahead, which are eventually converted into predictions of convective cooling effects along OHLs. The proposed EWS-based method is tested based on wind condition measurements in proximity to an OHL. Furthermore, to examine the impacts of angles between wind directions and line orientation on EWS estimation and thus EWS-based convective cooling predictions, the forecasting performance is assessed in the context of different line orientations. Results demonstrate that EWS-based ultra-short-term convective cooling predictions consistently outperform traditional forecasts from original wind conditions across all the tested line orientations. This highlights the significance of the EWS concept in reducing the complexity of DLR forecasting caused by the circular nature of wind directions, and in enhancing the accuracy of convective cooling predictions. Full article

Strain monitoring during the service life of a nuclear containment structure is an effective means to evaluate whether the structure is operating safely. Due to the failure of embedded strain sensors, surface-mounted strain sensors should be installed on the outer wall of the structure. However, whether the data from these substitute sensors can reasonably reflect the internal deformation behavior requires further investigation. To ensure the feasibility of the added strain sensors, a refined 3D model of a Chinese Pressurized Reactor (CPR1000) nuclear containment structure was developed in ANSYS 19.1 to study the internal and external deformation laws during a containment test (CTT). Solid reinforcement and cooling methods were employed to simulate prestressed cables and pre-tension application. The influence of ordinary steel bars in concrete was modeled using the smeared model, while interactions between the steel liner and concrete were simulated through coupled nodes. The model’s validity was verified against embedded strain sensor data recorded during a CTT. Furthermore, concrete and prestressed material parameters were refined through a sensitivity analysis. Finally, the variation law between the internal and external deformation of the containment structure was investigated under typical CTT loading conditions. Strain values in the wall thickness direction exhibited an essentially linear relationship. Near the equipment hatch, however, the strain distribution pattern was significantly influenced by the spatial arrangement of prestressed cables. Refined FEM and sensor systems are vital containment monitoring tools. Critically, surface-mounted strain sensors offer a feasible approach for inferring internal stress states and deformation behavior. This study provides theoretical support and a technical foundation for the safe assessment and maintenance of nuclear containment structures during operational service. Full article

Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy inputs. This review systematically examines recent advances in CCHP optimization under high-RE scenarios, with a focus on flexibility-enabled operation mechanisms and uncertainty-aware optimization strategies. It first analyzes the evolving architecture of variable RE-driven CCHP systems and core challenges arising from RE intermittency, demand volatility, and multi-energy coupling. Subsequently, it categorizes key flexibility resources and clarifies their roles in mitigating uncertainties. The review further elaborates on optimization methodologies tailored to high-RE contexts, along with their comparative analysis and selection criteria. Additionally, it details the formulation of optimization models, model formulation, and solution techniques. Key findings include the following: Generalized energy storage, which integrates physical and virtual storage, increases renewable energy utilization by 12–18% and reduces costs by 45%. Hybrid optimization strategies that combine robust optimization and deep reinforcement learning lower operational costs by 15–20% while strengthening system robustness against renewable energy volatility by 30–40%. Multi-energy synergy and exergy-efficient flexibility resources collectively improve system efficiency by 8–15% and reduce carbon emissions by 12–18%. Overall, this work provides a comprehensive technical pathway for enhancing the efficiency, stability, and low-carbon performance of CCHP systems in high-RE environments, supporting their scalable contribution to global decarbonization efforts. Full article

To achieve energy conservation, emission reduction, and green low-carbon goals for gas storage facilities, it is crucial to efficiently recover and utilize waste heat during gas injection while maintaining natural gas cooling rates. However, existing sensible and latent heat storage technologies cannot sustain long-term thermal storage or seasonal utilization of waste heat. Thermal chemical energy storage, with its high energy density and low thermal loss during prolonged storage, offers an effective solution for efficient recovery and long-term storage of waste heat in gas storage facilities. This study proposes a novel heat recovery method by combining a moving bed with mixed hydrated salts (CaCl₂·6H₂O and MgSO₄·7H₂O). By constructing both small-scale and full-scale three-dimensional models in Fluent, which couple the desorption and endothermic processes of hydrated salts, the study analyzes the temperature and flow fields within the moving bed during heat exchange, thereby verifying the feasibility of this approach. Furthermore, the effects of key parameters, including the inlet temperatures of hydrated salt particles and natural gas, flow velocity, and mass flow ratio on critical performance indicators such as the outlet temperatures of natural gas and hydrated salts, the overall heat transfer coefficient, the waste heat recovery efficiency, and the mass fraction of hydrated salt desorption are systematically investigated. The results indicate that in the small-scale model (1164 × 312 × 49 mm) the outlet temperatures of natural gas and mixed hydrated salts are 79.8 °C and 49.3 °C, respectively, with a waste heat recovery efficiency of only 33.6%. This low recovery rate is primarily due to the insufficient residence time of high-velocity natural gas (10.5 m·s⁻¹) and hydrated salt particles (2 mm·s⁻¹) in the moving bed, which limits heat exchange efficiency. In contrast, the full-scale moving bed (3000 × 1500 × 90 mm) not only accounts for variations in natural gas inlet temperature during the three-stage compression process but also allows for optimized operational adjustments. These optimizations ensure a natural gas outlet temperature of 41.3 °C, a hydrated salt outlet temperature of 82.5 °C, a significantly improved waste heat recovery efficiency of 94.2%, and a hydrated salt desorption mass fraction of 69.2%. This configuration enhances the safety of the gas injection system while maximizing both natural gas waste heat recovery and the efficient utilization of mixed hydrated salts. These findings provide essential theoretical guidance and data support for the effective recovery and seasonal utilization of waste heat in gas storage reservoirs. Full article

This study analyzes the dynamics of temperature and moisture in a cylindrical silo with a conical roof and floor used for storing corn in the Bajío region of Mexico, considering conditions both with and without aeration. The model incorporates external temperature fluctuations, solar radiation, grain moisture equilibrium with air humidity through the sorption isotherm (water activity), and grain respiration to simulate real storage conditions. The model is based on continuity, momentum, energy, and moisture conservation equations in porous media. This model was solved using the finite element method (FEM) to evaluate temperature and interstitial humidity variations during January and May, representing cold and warm environmental conditions, respectively. The simulations show that, without aeration, grain temperature progressively accumulates in the center and bottom region of the silo, reaching critical values for safe storage. In January, the low ambient temperature favors the natural dissipation of heat. In contrast, in May, the combination of high ambient temperatures and solar radiation intensifies thermal accumulation, increasing the risk of grain deterioration. However, implementing aeration periods allowed for a reduction in the silo’s internal temperature, achieving more homogeneous cooling and reducing the threats of mold and insect proliferation. For January, an airflow rate of 0.15 m³/(min·ton) was optimal for maintaining the temperature within the safe storage range (≤17 °C). In contrast, in May, neither this airflow rate nor the accumulation of 120 h of aeration was sufficient to achieve optimal storage temperatures. This indicates that, under warm conditions, the aeration strategy needs to be reconsidered, assessing whether a higher airflow rate, longer periods, or a combination of both could improve heat dissipation. The results also show that interstitial relative humidity remains stable with nocturnal aeration, minimizing moisture absorption in January and preventing excessive drying in May. However, it was identified that aeration period management must be adaptive, taking environmental conditions into account to avoid issues such as re-wetting or excessive grain drying. Full article

The thermal insulation performance of liquid hydrogen (LH₂) storage tanks is critical for long-distance transportation. The active cooled shield (ACS) technologies, such as the liquid nitrogen cooled shield (LNCS) and the vapor hydrogen cooled shield (VHVCS) are important thermal insulation methods. Many researchers installed the VHVCS inside the multilayer insulation (MLI) and obtained the optimal position. However, the MLI layer is often thinner than the vacuum interlayer between the inner and outer tanks, and there is a large vacuum interlayer between the outermost side of MLI and the inner wall of the outer tank. It is unknown whether the insulation performance can be improved if we install ACS in the mentioned vacuum interlayer and separate a portion of the MLI to be installed on the outer surface of ACS. In this configuration, the number of inner MLI (IMLI) layers and the ACS position are interdependent, a coupling that has not been thoroughly investigated. Therefore, thermodynamic models for MLI, MLI-LNCS, and MLI-VHVCS schemes were developed based on the Layer-by-Layer method. By applying Robin boundary conditions, the temperature distribution and heat leakage of the MLI scheme were predicted. Considering the coupled effects of IMLI layer count and ACS position, a co-optimization strategy was adopted, based on an alternating iterative search algorithm. The results indicate that for the MLI-LNCS scheme, the optimal number of IMLI layers and LNCS position are 36 layers and 49%, respectively. For the MLI-VHVCS scheme, the optimal values are 21 layers and 39%, respectively. Compared to conventional MLI, the MLI-LNCS scheme achieves an 88.09% reduction in heat leakage. However, this improvement involves increased system complexity and higher operational costs from LN₂ circulation. In contrast, the MLI-VHVCS scheme achieves a 62.74% reduction in heat leakage, demonstrating that using sensible heat from cryogenic vapor can significantly improve the thermal insulation performance of LH₂ storage tanks. The work of this paper provides a reference for the design and optimization of the insulation scheme of LH₂ storage tanks. Full article

This study aims to classify the Heat Risk Index (HRI), a critical component in climate change adaptation efforts, and to demonstrate how the cooling effect of trees influences HRI levels in areas suitable for afforestation. Istanbul, a global metropolis, was selected as the study area. Spatial analyses were conducted at the neighborhood scale. Within this scope, an afforestation scenario was implemented for a selected neighborhood to explore how HRI values could be reduced. The neighborhood-level approach constitutes the distinctive aspect of this study. The HRI analysis was classified into five levels using three interrelated variables: lack of tree canopy, population density, and land surface temperature (LST). ArcGIS Pro 3.5.2, a geographic information systems software, was employed as the primary analytical tool. The analysis revealed that 24.97% of Istanbul’s neighborhoods fell into the “relatively high” risk category, while 36.45% fell into the “higher–intermediate” risk category. In this context, a critical neighborhood sample from the higher–intermediate risk group, representing the largest proportion, was selected for scenario testing. The scenario demonstrated that a 6% increase in afforestation within the neighborhood lowered its HRI classification by one level. As a result, the method applied in this scenario was proven applicable for use in climate adaptation planning. Full article