Search Results (3,996)

Historic residential buildings in Lingnan are affected by hot–humid and disaster-prone weather conditions, including high temperature, high humidity, intense solar radiation, monsoon winds, and typhoon-related climate stress, which challenge indoor thermal comfort, daylighting, natural ventilation, and adaptive reuse. Taking Jingzu Jiashu, a historic Chaoshan residence associated with overseas remittance culture, as a case study, this study develops a simulation workflow for climate-adaptive green retrofit. Digital documentation, architectural survey, material investigation, and climate data were integrated to establish a baseline model. PMV, DA300, and ACH/ACR were used to evaluate thermal comfort, daylighting, and natural ventilation. The baseline results show summer overheating, insufficient daylighting in deep rooms, and inadequate ventilation in representative rooms. Comfortable hours accounted for only 7.29–7.78%, thermally uncomfortable hours reached 42.84–51.53%, and the maximum PMV reached 4.65 in the rear hall and 3.54–3.65 in representative rooms. The effective daylight areas of the front and rear rooms were approximately 40% and 31%, while baseline ACH values ranged from 1.06 to 1.89 h⁻¹. An integrated retrofit strategy was proposed, including functional reorganization, envelope optimization, opening adjustment, ventilation-path organization, and courtyard/transitional-space improvement. After retrofit, comfortable hours increased to 32.00–42.45%, thermally uncomfortable hours decreased to 17.25–21.28%, maximum PMV values decreased to 1.82–1.86, daylight areas increased to 81% and 74%, and ACH values rose to 2.97–4.49 h⁻¹. The results indicate that building performance simulation can provide quantitative support for climate-adaptive green retrofit of historic Chaoshan residences in Lingnan, offering a methodological reference for healthier, lower-carbon, and more resilient reuse of similar historic dwellings. Full article

Land surface reflectance and temperatures data products are generated from data acquired with the Operational Land Imager and Thermal Infrared Sensor on the Landsat 8 and 9 satellites. The surface temperatures (ST) in the Level 2 surface products (L2SP) are produced using a single channel algorithm, which takes no consideration of the presence of cold thin cirrus clouds, that re-emit thermal radiation at lower temperatures. The errors in the ST data products over cirrus-contaminated areas can be larger than 10 K. Our recent analysis of Level 1 top of the atmosphere (TOA) data products (L1TP) and L2SP data products acquired over different geographic regions, show that it is possible to use the correlations between the Level 1 TOA reflectances of Band 9 (referred as the cirrus band) and the Level 2 ST data products to remove thin cirrus induced errors in the daytime Level 2 ST data products over water. The corrected daytime ST datasets have standard deviations reduced to about 1 K, similar to results with no cirrus present. End users of the Level 2 ST data products are encouraged to test this method to make cirrus corrections to the existing daytime ST data products, and to more broadly apply its results and further its applicability. Full article

Winter underuse of urban parks in severe-cold cities limits year-round outdoor activity, especially for cold-sensitive users. This study developed a comfort–risk–adaptation framework integrating thermal perception, model-estimated cold-stress risk, and behavioral responses. Field microclimate measurements and synchronous questionnaires were conducted in Nanhu Park, Changchun, China, under clear winter conditions, yielding 386 paired human–environment samples. The Universal Thermal Climate Index (UTCI), Required Clothing Insulation (IREQ), wind chill temperature (WCT), and contact cooling indicators were used to quantify thermal exposure and cold-stress risk. Results showed significant spatial differences in wind speed, solar radiation, mean radiant temperature, and UTCI, while air temperature and humidity varied little. The neutral UTCI was 3.14 °C (unweighted) and 3.70 °C (weighted), and the 80% thermal acceptability threshold was −15.24 °C (95% CI: −16.14 to −14.22 °C). Despite acceptable thermal perception, physiological cold-stress risks remained under certain conditions. The findings highlight the need to integrate solar access, wind mitigation, low-conductivity materials, and moderate activity routes to improve winter usability in severe-cold urban parks. Results are condition-specific and reflect observed users under clear to partly cloudy winter daytime conditions rather than universal thresholds. Full article

Hybrid nanofluids with enhanced thermal conductivity have emerged as promising candidates for efficient heat removal in advanced energy systems and next-generation thermal management technologies. In particular, the use of viscoelastic base fluids embedded with radiatively active nanoparticles enables improved thermal regulation in solar collectors, electronic cooling units, and high-temperature industrial processes. This study presents a comparative thermal investigation of mono- and hybrid nanofluids comprising the ferro-oxide (Fe₃O₄) and copper (Cu) metallic particles dispersed in ethylene glycol (C₂H₆O₂), under magnetohydrodynamic (MHD) viscoelastic flow over a stretched surface. Accurate modeling of heat and mass phenomena in such fluids arises from their growing application in advanced thermal systems, including cooling technologies, electronic devices, and renewable energy modules. Unlike conventional models, the current analysis incorporates the Cattaneo–Christov heat flux framework to capture non-Fourier thermal relaxation effects, alongside the influence of thermal radiation and solutal transport. The developed system is truncated into dimensionless form with the proper choice of appropriate quantities, whose solution methodology is based on the implementation of a Runge–Kutta scheme. Compiled observations suggest that the hybrid nanomaterial exhibits more pronounced thermal recovery, while mono nanofluid attributes lower impact. Moreover, increasing the viscoelastic and magnetic parameters leads to notable variations in temperature and concentration distributions. This work advances the current literature by simultaneously integrating viscoelastic rheology, dual nanoparticle suspensions, and non-classical heat conduction laws, providing new insights for optimizing thermal performance in engineering applications. Full article

Partial shading is one of the main factors that degrade the output performance and operational reliability of photovoltaic (PV) arrays. It not only causes power loss and multi-peak P–V characteristics, but also induces current mismatch, reverse bias, and local hotspot formation. In this study, an electro-thermal PV module model under partial shading conditions is developed and validated, and an improved sparrow search algorithm (ISSA) is proposed for maximum power point tracking (MPPT) of PV arrays under static and dynamic complex operating conditions. The electrical model is established based on the single-diode model with irradiance, temperature, and Bishop reverse bias corrections, while the thermal model considers solar absorption, heat generation, convection, radiation, and heat conduction. The coupled model is validated against published experimental and numerical results. The predicted peak hotspot temperature is 111.9 °C, corresponding to a relative error of 2.7%; the average absolute errors of current and voltage are 0.20–0.25 A and approximately 0.3 V, respectively, and the maximum relative error of peak temperature is 3.7%. Based on the validated model, a MATLAB/Simulink MPPT platform is constructed to compare particle swarm optimization (PSO), the standard sparrow search algorithm (SSA), and the proposed ISSA. The results show that SSA achieves better global tracking performance than PSO under severe partial shading and dynamic irradiance transitions. Furthermore, by introducing Tent chaotic initialization and random walk perturbation, ISSA significantly improves the convergence speed and reduces steady-state power fluctuation while maintaining high tracking efficiency. Under static shading conditions, ISSA reduces the convergence time from 0.44 s to 0.25 s, 0.24 s to 0.15 s, and 0.44 s to 0.26 s for light, moderate, and severe shading cases, respectively. Under dynamic conditions, ISSA also shortens the post-transition convergence time and suppresses output power oscillation. These results demonstrate that the proposed ISSA-based MPPT method is suitable for PV arrays operating under partial shading and dynamic weather conditions. Full article

Current research on the energy performance of tilted façades is largely confined to specific climatic contexts or individual case studies, with limited systematic investigation of the energy-saving mechanisms across different climate zones in China. Comparative analyses based on Chinese building energy-efficiency standards remain particularly insufficient. This study investigates four representative Chinese cities corresponding to major climate zones—Harbin, Beijing, Shanghai, and Guangzhou—as research cases. A parametric office-building model was developed using the Ladybug–Honeybee simulation platform to evaluate annual cooling and heating energy consumption under different window-to-wall ratios (WWRs = 0.2, 0.4, and 0.6) and south-facing façade tilt angles ranging from 0° to 25°. A simplified thermal calculation model incorporating envelope heat transfer and solar heat gain was further combined with multiple linear regression analysis to examine the driving factors behind energy-consumption variations across climate zones. The results indicate that the energy-saving effectiveness of tilted façades decreases with decreasing latitude. During the cooling season, high-latitude cities exhibit the greatest reduction in cooling demand, with Harbin showing a maximum energy saving exceeding 16%, whereas Guangzhou shows a reduction of only approximately 5%. During the heating season, the tilted façades lead to a certain increase in energy consumption, but this adverse effect also diminishes with decreasing latitude. In terms of annual overall energy performance, Beijing, Shanghai, and Guangzhou achieve total energy savings of approximately 4–5%, while Harbin in the severe cold zone shows limited overall benefits. An analysis of solar radiation characteristics reveals that tilted façades substantially reduce direct solar radiation (by approximately 90%), thereby decreasing total solar heat gain, a trend that aligns closely with the reduction in cooling energy consumption. Moreover, higher window-to-wall ratios are associated with greater energy-saving effects, indicating that outwardly inclined façades are more suitable for office buildings with relatively large glazed areas. Overall, the energy-saving potential of tilted façades is primarily influenced by solar radiation conditions and the balance between cooling and heating demands. Such façades demonstrate good application value in regions with relatively balanced cooling and heating demands or cooling-dominated climates, whereas their application in severe cold regions requires more comprehensive evaluation. This study establishes an analytical framework for assessing the energy performance of tilted façades across different climate zones in China, providing theoretical support and design guidance for climate-adaptive design and form-based energy optimization. Full article

Recent theoretical studies propose that Hawking radiation may not emerge strictly at the event horizon but rather from the spatially extended region surrounding a black hole, commonly referred to as the quantum atmosphere. In this work, we explore how this concept influences nonlocal quantum correlations in a bosonic bipartite system located at a certain distance from a Schwarzschild black hole. By employing the measurement-induced nonlocality (MIN) as a quantifier of quantum correlations, we analyze the response of bosonic fields to the thermal and geometric characteristics associated with the Hartle–Hawking vacuum. Those features are associated with the coordinate-dependent metric components of the Schwarzschild background. In this manner, we extend previous studies that primarily focused on the fermionic systems. Our results reveal that when the quantum atmosphere is taken into account, the behavior of MIN departs from its conventional near-horizon profile. In particular, bosonic nonlocal correlations are found to exhibit a pronounced degradation at a finite radial distance from the event horizon and to ultimately vanish as the scaled distance increases further. To some extent this behavior contrasts with the previously considered fermionic case, indicating that bosonic fields provide a potentially stronger response to the quantum atmosphere. Full article

Existing residential buildings constructed under earlier thermal-design standards often lack effective external solar control systems. Building envelope retrofits must extend beyond mere cooling load reductions; instead, they require a holistic evaluation of summer heat rejection, winter solar gain preservation, transmitted solar exposure, and retrofit-induced embodied carbon. This study develops a screening-level method for climate-adaptive passive shading retrofits. The workflow integrates hourly solar-position reconstruction, facade irradiance mapping, shading geometry interception, and a reduced-order 2R2C thermal network. NSGA-II is used to generate Pareto-optimal alternatives, CV-TOPSIS is applied to identify representative trade-off solutions, and a life-cycle-informed carbon payback check within an A1–A4 + B6 boundary is used to test whether operational carbon savings can offset the upfront carbon of shading components and glazing replacement. Five Chinese cities—Haikou, Shanghai, Beijing, Lhasa, and Urumqi—are selected to represent the transition from cooling- to heating-dominated climates. For comparative screening, the reduced-order model shows acceptable agreement with an EnergyPlus benchmark, with NMBE, CV(RMSE), and $R^2$ values of +2.11%, 28.25%, and 0.804, respectively. The selected solutions reveal strong climate dependence in both shading morphology and carbon performance. For instance, Haikou exhibits the largest annual electricity savings (2030.3 kWh/yr) and the shortest Carbon Payback Period (1.8 years). In Lhasa, by contrast, the CV-TOPSIS-selected compromise scheme reduces the transmitted solar exposure proxy but increases annual energy use by 706.1 kWh/yr, indicating that this selected compromise, rather than fixed shading in general, is not carbon-effective within the defined boundary. The proposed method supports climate-specific retrofit screening by jointly considering heating–cooling balance, solar radiation conditions, and regional grid carbon intensity. Full article

The increasing generation of wood ash (WA) from biomass combustion presents both an environmental challenge and an opportunity for sustainable resource utilization. This review provides a comprehensive assessment of recent advances in the valorization of WA for the development of sustainable engineering materials within a circular economy framework. Unlike previous studies that primarily focus on isolated applications of WA, this work integrates multiple technical dimensions, including material characterization, advanced manufacturing technologies, mechanical performance evaluation, computational modelling, and industrial commercialization pathways. Wood ash typically exhibits alkaline characteristics (pH 9–13.5) and particle sizes ranging from 1 to 1000 µm, enabling its application in a wide range of material systems. In cementitious materials, partial replacement of cement with WA (0.10–20%) generally improves mechanical performance, whereas excessive incorporation may reduce structural integrity. The high silica content (>62%) in certain WA types also enables its utilization in lightweight glass systems and radiation-shielding materials. Furthermore, WA has emerged as a promising functional filler in polymeric and ceramic composites, where additions above 0.5% can enhance dynamic mechanical properties and thermal stability. The review also examines standardized inspection and testing procedures, including quality control (QC) and quality assurance (QA) frameworks based on American Society for Testing and Materials (ASTM), Canadian Standards Association (CSA), and European standards, to ensure the reliability of WA-derived materials. Recent developments in artificial intelligence, machine learning, and computational modelling are highlighted for predicting mechanical behavior, optimizing processing parameters, and enabling digitalized manufacturing systems. In addition, circular manufacturing strategies and economic evaluation models, including break-even analysis, are discussed to assess the industrial feasibility of WA-based products. By integrating circular economy principles with materials engineering, digital technologies, and economic assessment, this review establishes a holistic framework for transforming wood ash from an industrial residue into value-added sustainable materials for construction, energy, and advanced composite applications. Full article

Infrared small target detection (ISTD) remains challenging in complex cluttered environments because targets usually occupy only a few pixels and exhibit weak thermal radiation with limited texture information. The problem becomes more severe in high-resolution infrared imaging systems, where sliding-window inference is commonly adopted under memory and computational constraints. However, the truncated field of view may lead to contextual information loss and increased false alarms in cluttered regions. To address these issues, we propose the Selective Contextual Uplift and Attention Network (SCUA-Net). The proposed network adopts a U-Net++-style densely nested encoder–decoder architecture to enhance multi-scale feature interaction and preserve fine-grained weak-target features. In addition, a Global-Context Calibration Coordinate Attention (GCC-CA) module is introduced to inject window-level contextual statistics into coordinate attention, thereby improving clutter suppression and localization robustness under sliding-window inference. During training, a joint optimization strategy combining Online Hard Example Mining (OHEM) and Dice Loss is employed to alleviate severe foreground–background imbalance. During inference, Gaussian-weighted fusion is adopted to reduce stitching artifacts between adjacent windows. Experimental results on NUDT-SIRST and IRSTD-1k validate the effectiveness of the proposed method. SCUA-Net achieves 99.15% Pd, 0.558 × 10⁻⁶ Fa, and 0.9570 IoU on NUDT-SIRST, while maintaining competitive performance on IRSTD-1k at 161.6 FPS on an NVIDIA RTX 4090 platform, demonstrating favorable accuracy, robustness, and real-time performance in complex infrared scenarios. Full article

In chemical industrial parks, evacuation during LPG tank leakage is governed not only by travel distance but by the loss of safe corridors, failed exits, and congestion induced by spatially coupled vapor exposure, explosion overpressure, and thermal radiation. Existing consequence assessment studies usually delineate hazardous zones, while evacuation models often optimize routes on a fixed network with available exits and simplified capacity constraints; the coupling between multi-hazard consequence fields and capacity-constrained evacuation assignment remains insufficient. This study proposes a spatially constrained, congestion-aware evacuation optimization framework. ALOHA-derived AEGL exposure, vapor cloud explosion overpressure, and jet fire radiation zones are mapped onto the plant network to identify unsafe nodes, unavailable links, and failed exits. A capacity-constrained model is then established to minimize system-level RSET under an ASET constraint, and a congestion-aware ant colony algorithm balances evacuees among available exits by incorporating risk and density penalties. In a petrochemical plant case with 717 evacuees and 74 nodes, Gate 3 failure makes the nearest-exit strategy infeasible, whereas the proposed strategy reduces RSET from 560.8 to 504.9 s. The framework links accident consequence assessment with actionable evacuation routing for chemical parks. Full article

As climate change intensifies heat extremes, the Urban Heat Island (UHI) effect amplifies local thermal stress. Assessing the UHI using robust observational data, whether ground- and/or satellite-based, is essential for climate risk assessment and evidence-based urban adaptation. Therefore, this study aims to provide a comprehensive climatological assessment of air temperature patterns and UHI intensity across the Lisbon Metropolitan Area (LMA) over a 26-year period (2000–2025). The methodology employs a dense, high-quality integrated network of in-situ weather stations from the Portuguese Institute for Sea and Atmosphere (IPMA) and the National Water Resources Information System (SNIRH). To bridge critical gaps in traditional climate assessments, this research implements a dual-perspective approach that combines the high temporal resolution of MSG-SEVIRI and the spatial precision of MODIS Land Surface Temperature (LST). This framework accurately captures the lag effects between surface heating and atmospheric response. Validation results demonstrate that satellite-derived LST is a robust proxy for monitoring the nocturnal UHI, with differences generally below 1 °C compared with near-surface air temperature observations (T2m). However, daytime LST significantly overestimates atmospheric temperatures, with deviations of 2–8 °C due to solar radiation and urban geometry. The selection of rural reference stations constitutes a critical methodological factor, as a baseline shift can alter perceived UHI intensities by more than 3 °C. Despite these sensitivities, the results unequivocally confirm a persistent and spatially heterogeneous UHI effect in Lisbon, which intensifies during extreme heat events by up to an additional 4 °C. Analysis of the 2003 and 2018 heatwaves reveals surface LST anomalies exceeding 10 °C and urban–rural thermal differentials reaching up to 7 °C under conditions of suppressed maritime breezes. These nocturnal anomalies are particularly pronounced in densely built-up areas, limiting thermal dissipation and preventing physiological recovery. Integrating multi-sensor satellite data with in-situ validation provides a new benchmark for climate risk assessments, delivering the reliable, reproducible data required to strengthen long-term urban resilience under increasingly frequent extreme heat events. Full article

This study investigates the structural sensitivity of a large-span steel space frame at Yanjiao Station to environmental disturbances during the critical “flexible suspension” stage of asymmetric hydraulic lifting. First, by analyzing the offset between the center of mass and the center of stiffness—induced by the asymmetric lifting configuration—the study systematically examines the spatial eccentric amplification effect under a coupled thermal-wind field. To this end, a non-uniform solar radiation model based on the Axis-Aligned Bounding Box (AABB) algorithm is integrated with a refined finite element model, enabling a full-factor parametric analysis under 20 coupled load conditions. The results reveal a significant time lag in the structural temperature field, with 12:00 identified as the critical time for maximum thermal deformation. The wind-induced response follows a “bimodal evolution” pattern, and the maximum translational-torsional coupling effect occurs at wind direction angles of 60° and 120°. Further analysis of the multi-field coupling mechanism indicates that the wind field dominates the deformation mode, while the temperature field amplifies the resulting response. Consequently, the peak displacement reaches 192.50 mm, which represents a 360.81% increase compared to the dead load baseline. The cantilever end is identified as the primary vulnerable region. Based on these findings, a “wind direction–time” two-dimensional monitoring strategy is proposed. This strategy provides scientific quantitative criteria and theoretical support for the construction safety of large-span structures, as well as for the development of a comprehensive early warning and health monitoring system. Full article

High-efficiency perfect absorption, spanning the entire visible region, plays an increasingly significant role in applications such as solar energy harvesting, photodetection, and thermal radiation management. However, the complexity and manufacturing difficulty of the currently proposed structures hinder large-scale application. In this work, we propose a broadband perfect absorber based on a tungsten–silicon nitride–tungsten (W-Si₃N₄-W) sandwich multilayer film. We combine the unique broadband absorption capability and high-temperature stability of material W with the low-loss characteristic of material Si₃N₄. By optimizing the geometrical parameters of the structure, we successfully achieved an average absorption efficiency exceeding 94% across a wide wavelength ranging from 500 nm to 900 nm. This work paves the way for developing high-performance, stable, and broadband absorption devices. Full article

The accurate detection and quantification of electromagnetic radiation in the infrared (IR) and terahertz (THz) regions are critical for modern applications, yet they remain challenging due to the “THz gap” and the limitations of current room-temperature technologies. This paper proposes a novel uncooled IR–THz power sensor based on a hybrid graphene oxide (GO) and polydimethylsiloxane (PDMS) bilayer integrated into a surface plasmon resonance (SPR) architecture in the Kretschmann configuration. The device exploits the broadband optical absorption of GO to efficiently convert incident radiation into heat, while the high thermo-optic coefficient of the PDMS layer translates these thermal variations into measurable refractive index shifts. Finite Element Method (FEM) modeling was employed to optimize the sensor design, predicting a linear angular shift of 0.093 deg/mW. Experimental results confirm the theoretical expectations, demonstrating a high sensitivity of 0.083 deg/mW and an exceptionally low limit of detection and resolution on the order of 15 nW. By eliminating the need for cryogenic cooling or vacuum packaging, this platform offers a compact, low-cost, and high-performance solution for next-generation IR–THz metrology. Full article