Search Results (2,366)

Urban regeneration interventions extend beyond the renewal of physical building stock and the improvement of living conditions, as they also reshape local microclimatic conditions. This study examines changes in Surface Urban Heat Island (SUHI) patterns within an urban regeneration area in Istanbul, Türkiye, using multi-temporal remote sensing data. Landsat imagery from 2019, 2020, 2022, and 2023 was used to derive Land Surface Temperature (LST), the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), and SUHI intensity. Pearson correlation analysis, Getis–Ord Gi* hot spot analysis, and zonal statistics were applied to evaluate statistical relationships, spatial clustering, and local thermal changes within the regeneration areas. The findings show that urban regeneration did not produce a uniform thermal response. Demolition reduced built-up intensity, whereas redevelopment of previously vegetated or open parcels increased impervious surface cover and limited vegetation recovery. Correlation results revealed strong negative associations between NDVI and both LST and SUHI, while NDBI was positively associated with these thermal variables, indicating that land-cover composition was strongly associated with local thermal conditions. Overall, the study demonstrates that renewing building stock alone may not be sufficient to ensure improvement in the urban thermal environment. Strengthening green infrastructure, expanding permeable surfaces, and embedding climate-responsive planning measures into regeneration strategies are therefore critical. The results also indicate that multi-temporal remote sensing, combined with spatial statistics and zonal assessment, provides an effective decision-support framework for monitoring SUHI dynamics and evaluating the environmental performance of urban regeneration initiatives. Full article

HVAC control trades energy against thermal comfort, complicated by two building features: thermal mass spreads a setpoint change over hours, and the input-to-outcome mapping shifts across the year. Model-free algorithms such as PPO, SAC, and TD3 carry no model of building dynamics and cannot evaluate a setpoint’s downstream effect. We apply a Latent Dynamics Learning and Planning (LDLP) framework that learns a latent model of the building’s thermal response and plans with Monte Carlo Tree Search inside it. We also gate a reward formulation common in prior work, applying its comfort penalty only while the building is occupied. On Sinergym’s 5Zone environment under hot, mixed, and cool climates, LDLP is evaluated against PPO, SAC, TD3 and Sampled EfficientZero, an independent model-based controller run at the same budget. With energy normalized for the comfort achieved, LDLP consumes 4% to 26% less than PPO and SAC under the standard reward and 1% to 19% less under the gated reward. Running the same model with one simulation per decision, which removes planning, multiplies its normalized energy fivefold. Under the gated reward the deterministic TD3 policy degenerates onto a few fixed setpoints, so we report action diversity alongside the conventional metrics. Full article

Achieving net-zero energy and zero-emission buildings is a critical pathway toward decarbonizing the built environment, particularly in cooling-dominated regions where operational energy demand remains exceptionally high. Existing university buildings in hot–humid climates face significant challenges due to intensive cooling requirements, limited passive cooling potential, and the economic burden associated with large-scale renewable energy deployment. This study develops and evaluates a climate-responsive retrofit framework that integrates sequential energy optimization, CFD-based passive-cooling analysis, and on-site renewable energy systems to transform an operational university building in Jeddah, Saudi Arabia, into a nearly net-zero energy building (NZEB). A high-fidelity DesignBuilder–EnergyPlus model was calibrated using three years of monthly measured electricity consumption data, achieving strong agreement with utility records (NMBE = 2.19%, CV(RMSE) = 7.93%). The proposed framework prioritizes demand-side load reduction through optimized HVAC operation, envelope enhancement, daylight-responsive lighting control, natural ventilation, and Passive Downdraught Evaporative Cooling (PDEC) before renewable energy integration. The baseline building exhibited an Energy Use Intensity (EUI) of 613 kWh/m²·year, with cooling accounting for approximately 70% of total electricity consumption. Sequential optimization reduced annual energy demand by 58%, while CFD-supported passive cooling strategies provided an additional 17% reduction in cooling energy and improved indoor airflow performance. Crucially, nearly 80% of total energy savings were realized prior to photovoltaic (PV) deployment. A 1586-kW rooftop photovoltaic system subsequently offset the residual annual demand, achieving a nearly net-zero annual energy balance. Over 25 years, the proposed retrofit pathway reduced life-cycle costs from 7.51 million SAR to 3.13 million SAR. The findings demonstrate that climate-responsive demand reduction is the primary enabler of NZEBs in hot–humid regions, substantially reducing renewable energy requirements and long-term economic costs while providing a scalable pathway to decarbonize existing campus infrastructure. Full article

Personal thermal management (PTM) textiles can reduce building energy consumption and improve personal comfort, yet their practical application is constrained by the inherent trade-off between flexibility, thermal insulation, and mechanical strength. Herein, porous single-component polyimide (PI) fibers were fabricated via coagulation bath-modulated wet spinning of 3,3′,4,4′-benzophenone tetracarboxylic dianhydride (BTDA)–4,4′-oxydianiline (ODA) poly(amic acid) (PAA). By tuning the EtOH/H₂O ratio (20/80–60/40) and winding speed (2.6–13.1 mm/s), the fiber cross-sectional morphology evolves from finger-like macropores to uniform spongy networks, with diameters controllable from 120 to 335 μm. The PI porous fibers exhibit a maximum tensile strength of 56.79 MPa, elongation at break of 13.89%, toughness of 4.98 MJ/m³, and thermal conductivity as low as 0.043 W·m⁻¹·K⁻¹. The highly imidized structure was confirmed by FTIR (imidization index = 0.848), and TGA revealed high thermal stability with 5% weight loss temperatures of 491 °C (N₂) and 488 °C (air). Compared with commercial insulators, a single-layer PI fabric (0.892 mm) shows thermal insulation comparable to that of the thicker aramid 1313 fabric (1.588 mm) under the same 100–200 °C hot-plate conditions, while also exhibiting self-extinguishing behavior equivalent to that of aramid 1313. The 5-layer PI stack (3.637 mm) is only half as thick as glass fiber cotton (7.342 mm) but retains 84–91% of its temperature difference, delivering 1.7–1.8 times higher thickness-normalized insulation efficiency. The ultrathin porous PI fabrics integrate robust mechanical performance, excellent thermal shielding, and flame retardancy, and are promising for extreme-environment thermal management including fire protection, spacecraft thermal control, and battery insulation. Full article

Lithium-ion battery energy storage stations are being rapidly deployed for peak regulation, renewable energy integration, and emergency power supply in power systems. Their fire risk is governed by interacting factors, including cell thermal runaway, equipment failure, operating environment, personnel behavior, management systems, and information systems, and is characterized by coupling, dynamic evolution, and confined-space fire spread. Existing static risk assessment methods cannot fully represent feedback among multiple risk factors or connect risk assessment results with the physical-field evolution of fires in energy storage compartments. This study develops an integrated grey relational analysis, system dynamics, and FDS framework. Personnel, equipment, environmental, management, and information risk factors are first established, and their weights are calculated using grey relational analysis. A system dynamics model is then used to analyze the temporal evolution of overall risk and subsystem risk responses. Finally, FDS is applied to simulate fire spread in a 30 ft containerized lithium-ion battery energy storage compartment under no-suppression and water-mist suppression conditions. The results show that the central fire-source region and battery module layer are key areas of gas-phase high-temperature accumulation and potential fire spread. In the no-suppression scenario, the high-temperature region remains localized near the fire source at 3.0 s, expands along the module layer from 30.0 to 50.0 s, and approaches a relatively stable distribution after 70.0 s. Under the investigated simulation conditions, water mist reduces near-source heating, weakens smoke-layer development, and slows spatial fire spread through evaporative cooling, reduced thermal radiation feedback, and disturbance of the hot smoke layer. These findings provide a methodological reference for fire risk assessment and fire suppression design in containerized battery energy storage stations. Full article

Since pioneering fluid-flow models for the Iberian and French Variscan belt, advances in geochronology, thermochronology, and geodynamic modeling have improved our understanding of late Variscan crustal evolution. New datasets suggest tungsten and gold mineralization do not represent distinct metallogenic events, but successive expressions of a long-lived hydrothermal evolution linked to crustal melting, granite emplacement, exhumation, and thermal collapse. Fluid drainage along shear zones drove silicification and arsenic precipitation, building an efficient trap for later gold deposition. As the hot, rapidly exhumed crust evolved, it progressively became a gold-bearing hydrothermal system, its architecture developing from the mountain-range scale down to microfractures. The resulting metallogenic model is therefore hierarchical rather than episodic, built through progressive construction of efficient traps. Quartz first forms the mechanical trap, massive deposition creating competent bodies prone to repeated brittle reactivation. Arsenopyrite is then deposited along the same zones, within shear environments reactivated during exhumation, establishing the principal chemical trap for gold enrichment with a polymetallic signature (Ag, Sb, Pb, Cu, Zn, Bi, Te). This late stage results from repeated microfracturing, promoting remobilization and native gold enrichment. The economically significant gold stage thus culminates this hydrothermal evolution, reflecting the progressive self-organization of the system during orogenic collapse. Full article

This study employs a multi-method, high-precision research approach to evaluate the thermal comfort performance of a window-based direct evaporative cooling (DEC) air conditioning system installed in a university dormitory building (50 rooms) in Beijing. To compensate for the insufficiency of single-day test data, the study was conducted continuously for 30 days from 1 June to 30 June 2026 (00:00–23:59 daily). Eight calibrated sensor sets were deployed in each of the 50 rooms (that is, eight fixed sensor sets per room × 50 rooms = 400 synchronously logged spatial measurement points, each integrating a fixed SHT35 temperature/humidity sensor with a matched hot-wire anemometer probe; this unusually dense, building-scale simultaneous deployment is uncommon in previous dormitory studies), recording data simultaneously across all rooms throughout the test period with the DEC units continuously operating. The research integrates field physical measurement data, standardized subjective questionnaire surveys (200 within-person paired questionnaires, each pairing a student’s retrospective recall of the pre-DEC condition with an in situ vote collected during DEC operation), and advanced computational thermophysiological modeling results based on the frameworks of ISO 7730–2021 and ASHRAE Standard 55–2023. Environmental parameters, including dry-bulb temperature (Ta), relative humidity (RH), and air velocity (Va), were monitored at eight spatially distributed points per room with a 10 Hz sampling frequency and a one-hour median resolution. The mean radiant temperature (Tr) was approximated as equal to Ta due to the absence of globe temperature measurements, and this simplification is discussed as a limitation. Simultaneously, through a single-session questionnaire (June 24–30) compliant with ISO 10551 and the Appendix B requirements of ANSI/ASHRAE Standard 55, which paired each respondent’s retrospective recall of the early-June pre-DEC (non-cooled) condition with a concurrent vote collected during DEC operation—a recalled-pre/concurrent-post design rather than two separate real-time pre-/post-intervention surveys—data on clothing ensembles, activity levels, and subjective thermal sensation votes (TSV) were collected. The acquired data were input into a customized simulation platform developed in the Fortran language (which was debugged and cross-validated against the ISO 7730/ASHRAE Standard 55 reference implementation to within 0.01 PMV scale units), which employs the Fanger two-node thermoregulation model to accurately calculate and predict the predicted mean vote (PMV), predicted percentage of dissatisfied (PPD) occupants, new effective temperature (ET*), and standard effective temperature (SET*). The results indicate that the DEC unit achieved a stable outlet temperature reduction of Δt = 3.87 °C (inlet temperature 31.72 °C, outlet temperature 27.85 °C), with an average wet-bulb air temperature of 18.66 °C and an average outlet relative humidity of 58.3% (inlet RH: 42.1%), confirming the expected humidifying effect of direct evaporative cooling while maintaining an average indoor relative humidity of 42.07%—a result particularly relevant to Beijing’s dry-to-semi-humid summer environment, where evaporative cooling is thermodynamically favorable. Because no DEC-off baseline period was monitored, the measured indoor conditions are reported as observational associations with DEC operation rather than as effects attributable exclusively to the unit; the pre-DEC satisfaction level was recalled retrospectively within the same single session and is therefore subject to recall/contrast bias; and all energy-saving figures are theoretical nameplate estimates rather than metered energy consumption. Full article

Municipal solid waste-to-energy (MSW-WTE) boilers are increasingly operated at higher steam temperatures and pressures to improve efficiency. Under these conditions, heat-transfer surfaces are exposed to high-temperature oxidation, chlorine-induced corrosion, molten-salt corrosion and thermomechanically coupled damage, which compromise long-term operational safety. Thermal spraying offers flexibility in tailoring coating composition and microstructure and is therefore widely used to improve the service reliability of these surfaces. This review examines the corrosive environments, principal damage mechanisms and development of thermal spray protection systems for MSW-WTE boiler heat-transfer surfaces. It first considers how variations in temperature, flue-gas composition and deposit evolution among boiler regions influence corrosion behavior, with particular emphasis on chlorine-induced active oxidation, sulfate/chloride-assisted hot corrosion and molten-salt corrosion. It then relates spraying processes and coating microstructures to the corrosion-protection mechanisms, advantages and limitations of MCrAlY, NiCr/NiCrMo and carbide-reinforced coatings under different service conditions. Finally, future developments in multifunctional coatings, structural optimization and condition-based maintenance are discussed. By linking corrosive environments, damage mechanisms, coating structures and service reliability, this review provides a framework for the design and engineering application of protective coatings for MSW-WTE boiler heat-transfer surfaces. Full article

Chemical green growth removers designed to control algae, which are classified as biocidal products, are used in open-air environments and, in some cases, over large areas such as roofs, façades, fences, or pavements, and can have adverse environmental effects. To minimise the use of green growth removers, users must have access to information on appropriate non-chemical alternatives against the target organisms. In this study, the authors developed an efficacy test for non-chemical green growth removal methods using a high-pressure cleaner with cold and hot water. After determining a dose-response curve concerning the efficacy of high water temperature on green growth control, naturally infested surfaces of a wooden fence and sandstone were treated with different water pressures and temperatures: 15 and 70 °C for both surfaces, 60, 70, 90, and 100 bar for the wooden fence, and 120 and 170 bar for sandstone. The results after six months showed that all treatments on the wooden fence remained highly effective (>96%). The efficacy of the treatments on the sandstone was lower, with the highest efficacy of 90% achieved with cold (15 °C) water and a water pressure of 170 bar. In summary, the methods used demonstrated high efficacy, constituting a sustainable alternative for algaecides. The regreening after six months remained low if thorough removal of the green growth was ensured. Full article

Effective management of urban Asian water monitor (Varanus salvator (Laurenti, 1768)) populations requires precise individual identification, yet traditional physical-marking methods remain invasive and labor-intensive. This study developed a non-invasive, automated photographic re-identification (Re-ID) system using deep learning and computer vision to facilitate population monitoring in semi-urban environments. We evaluated seven deep learning configurations based on ResNet50 incorporating Squeeze-and-Excitation (SE), Convolutional Block Attention Module (CBAM), and Batch Normalization neck (BNNeck) optimizations and benchmarked them against traditional feature matching (HotSpotter) using an open-set evaluation dataset of 3311 images across 161 Side-IDs focusing on unique lateral head-scale patterns. HotSpotter demonstrated immediate field viability, achieving a Rank-1 accuracy of 99.88% and a mean Average Precision (mAP) of 90.40%. Among the deep learning architectures, the baseline ResNet50 achieved the highest Rank-1 accuracy of 75.39% and mAP of 55.97%. As a decision-support framework, the deep learning pipeline achieved over 87% Rank-5 accuracy, drastically reducing manual screening effort and cognitive load during capture–mark–recapture surveys. This non-invasive framework establishes a scalable, welfare-friendly protocol for long-term urban wildlife management and biodiversity monitoring. Full article

The generation of Dead Hot Maps (DHMs) is an important part of PHENIX data analysis, as it helps reduce detector-related biases. During this step, detector units with abnormal behavior are identified, such as dead, hot, or extremely hot channels. Removing these channels from the analysis prevents detector effects from changing the measured collision distributions. This helps ensure that the final data sample represents the underlying collision physics more reliably. In this work, the standard DHM construction procedure is compared with anomaly detection methods that are commonly used in data analysis and data mining. These methods can offer simpler and faster alternatives to the conventional approach, with lower computational demand and less need for manual work. Five techniques were tested: Z-score analysis, Local Outlier Factor (LOF), One-Class Support Vector Machine (OCSVM), Isolation Forest (IF), and Kernel Density Estimation (KDE). The main goal was to examine which method gives a detector mask that is closest to the established statistical reference and is also physically reasonable. The results suggest that these anomaly detection approaches may be useful for detector monitoring and calibration tasks. Some of the tested methods are easy to apply, computationally efficient, and do not require special hardware. Because of this, they could be included in future automated detector quality control workflows. Their simple implementation also makes them suitable for use in different software environments. In this way, these methods may support faster and more consistent identification of anomalous detector towers. Full article

Cornhusks are widely employed as reinforcing fillers in biocomposite fabrication, where conventional manufacturing processes rely on petroleum-derived resins or adhesives. This reliance not only poses substantial risks to human health and ecological environments, but also leads to the unsatisfactory mechanical performance of the final products. Developing a feasible strategy to eliminate petroleum-based binders while simultaneously enhancing the mechanical strength of the biocomposites remains a challenge. In this paper, we present an adhesive-free approach to produce high-performance, sustainable biomass structural materials directly from raw cornhusks, without prior pulverization, via a combined alkaline retting and hot-pressing treatment. Benefiting from the synergistic effects of highly aligned cellulose fibers and a densely compacted multi-layer structure, the resulting structural material exhibits a tensile strength of 136 MPa and a flexural strength of 127 MPa. These values are higher than those of conventional density fiberboards (approximately 20 MPa and 40 MPa). After 72 h of water immersion, the material shows a water absorption rate of 38% and a thickness swelling rate of 16%, both of which are lower than the corresponding parameters of traditional density fiberboards (around 60% and 20%). Its initial thermal degradation temperature reaches 251 °C, showing good thermal stability. Furthermore, the as-fabricated cornhusk-based structural material, which combines high mechanical strength, water resistance, and thermal resistance, exhibits zero formaldehyde emissions. It can serve as a promising alternative to traditional petroleum-bonded biomass density boards, for applications in furniture manufacturing and interior decoration. Full article

Traditional dwellings in humid subtropical China contain climate-adaptive spatial elements, yet their outdoor thermal-comfort performance and passive optimization potential remain insufficiently quantified. This study examined three traditional Minnan mansions in Quanzhou, Fujian Province, to evaluate how courtyards, alleyways, recessed entrance spaces, and peripheral vegetation regulate summer outdoor thermal environments. Field microclimate monitoring, UAV photogrammetry, and ENVI-met/BioMet simulations were combined, and baseline models were validated using measured air temperature and relative humidity data. Single-element scenarios were developed for ground albedo adjustment, courtyard shading, alleyway green pergolas, recessed entrance shading, increased fengshui woodland density, and optimized woodland layout, followed by multi-element combined strategies. The results indicate that shading and vegetation-related measures reduced daytime heat stress primarily by limiting solar radiation exposure, improving near-ground thermal and humidity conditions, and modifying local wind fields. Combined strategies produced more stable UTCI improvements than individual interventions, with a maximum UTCI reduction of 7.5 °C. In contrast, high-albedo paving reduced local air temperature but could worsen UTCI by increasing reflected short-wave radiation. These findings provide quantitative support for low-intervention thermal environment optimization and climate-adaptive renewal of traditional dwellings in humid–hot regions. Full article

Owing to their exceptional thermal insulation and protective capabilities, thermal barrier coatings (TBCs) are widely applied to critical hot-section components of aero-engines. However, under increasingly harsh service environments, internal defects such as delamination tend to form within the coatings, posing a severe threat to engine operational safety and service life. To effectively evaluate delamination defects in TBCs, this study employs the immersion ultrasonic pulse-echo technique to inspect specimens subjected to various thermal cycling treatments. Four specimens, subjected respectively to 21, 32, 43, and 54 thermal cycles at 1200 °C, were tested. Ultrasonic response data were systematically acquired via normal incidence scanning from both the superalloy substrate side and the ceramic top coat side. Combining Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT) based on the generalized Morse wavelet, Wavelet Packet Energy Entropy (WPEE), and peak-to-peak amplitude variations of the second echo, multi-dimensional features were extracted from ultrasonic signals across the frequency domain, joint time-frequency domain, and energy distribution profiles. Through comparative analysis, ultrasonic waveform and time-frequency characteristics representing defect evolution were obtained. A significant monotonically decreasing trend of WPEE with the aggravation of interfacial delamination was established, characterizing the acoustic energy confinement process induced by interfacial damage. Furthermore, a multilayer finite element (FE) model reasonably reproduced dynamic acoustic wave propagation; numerical results are in agreement with experimental data, validating the feasibility of the proposed detection method. The detection and evaluation framework established in this study provides a reference for safety monitoring and lifespan prediction of aero-engine TBCs. Full article

Early-age cracking severely limits concrete durability in hot, arid environments due to rapid plastic and drying shrinkage. This study evaluates the cracking sensitivity of cement-based materials incorporating four local supplementary cementitious materials (SCMs): limestone filler from Djebel Béchar, natural pozzolan, silica fume, and gypsum under simulated arid conditions (55 °C, 12% relative humidity, 10 km/h wind). Using a custom climatic chamber, prismatic cement-grout specimens with internal restraints were tested. SCMs were evaluated at substitution rates of 2% to 8%. Limestone was further tested at higher rates (up to 40%) and in binary combinations. Findings were validated using micro-concrete with limestone substitutions (0–35%) combined with 4% natural pozzolan. Cracking sensitivity was assessed using maximum crack width and a cracking index, along with setting times and mechanical strengths. Results indicate that limestone filler demonstrated the most favourable performance. A 4% limestone substitution yielded a single crack with a maximum width of 0.1 mm, while an 8% substitution resulted in five cracks of about 0.2 mm. The optimal cracking index was achieved at a 35% limestone substitution rate, which also successfully extended initial and final setting times. While binary SCM combinations significantly reduced cracking compared to the unsubstituted reference, they did not outperform the optimal 35% single limestone substitution. Furthermore, the 28-day compressive and flexural tensile strengths of the micro-concrete were effectively maintained at up to 35% limestone combined with 4% pozzolan. Overall, these preliminary findings demonstrate that crushed limestone fines from Djebel Béchar are highly promising as partial cement replacements to improve concrete durability in arid climates. Further durability assessments and statistical validation are recommended to confirm these benefits for practical field applications. Full article