Search Results (167)

Individuals often adopt distinct behavioral patterns to adapt to different weather conditions. However, most studies on outdoor thermal comfort fail to consider weather variability and associated individual factors as interventions. This study conducted 12 days of field measurements and surveys across two residential areas in Wuhan, categorizing the sampled data based on background temperatures. Thermal benchmarks were developed for different age and gender groups under varying weather conditions, with comparative analyses conducted to evaluate differences in thermal comfort responses. With changes in outdoor temperature, the most comfortable thermal sensation in winter showed a wider fluctuation, ranging from 0.13 to 1.58, while in summer, it ranged between −1.76 and −1.18. The relationship between thermal sensation and comfort varied more significantly among different age groups in winter, while in summer, the differences were more evident between genders. As summer temperatures rose, younger and middle-aged individuals showed a greater increase in thermal sensitivity compared to the elderly. Similarly, males exhibited higher sensitivity than females. In terms of thermally acceptable temperatures, the upper limit was similar across age groups, around 35 °C. However, the lower limit varied as follows: the elderly had the lowest acceptable lower limit of around 0–3 °C; middle-aged individuals tolerated 4–7 °C higher; and young people tolerated 10–12 °C higher than the elderly. Between genders, the upper limit was also similar, but females tolerated 7–10 °C lower temperatures than males. In the context of outdoor thermal comfort studies in residential areas of Wuhan, the Universal Thermal Climate Index demonstrated better applicability than the Physiologically Equivalent Temperature. Overall, by analyzing thermal benchmark models for different demographic groups under varying weather conditions, this study enhances the understanding of how outdoor environments influence thermal comfort and provides valuable insights for targeted microclimate regulation and urban design strategies. Full article

Concrete used in high-risk infrastructures must withstand elevated temperatures and thermal shocks. This study investigated the thermal transfer behavior of explosion-proof concrete exposed to 100–400 °C through a combined experimental and numerical approach. X-ray diffraction (XRD) revealed that the dominant crystalline phases remained identifiable across this range, but peak broadening and intensity reduction indicated partial decomposition of hydration products and microstructural disorder. Thermal conductivity reached its maximum of 1.48 W/(m·K) at 100 °C and decreased at higher temperatures due to porosity growth and microcracking, reflecting detrimental alterations in heat conduction pathways. In contrast, the specific heat capacity increased from 963.89 J/(kg·K) at 100 °C to 1122.22 J/(kg·K) at 400 °C, enhancing the material’s heat absorption. Density initially decreased with temperature but showed a temporary rebound at 300 °C due to secondary hydration, before dropping sharply to 1830 kg/m³ at 400 °C. Numerical simulations confirmed that high temperatures reduce surface–core temperature gradients, leading to more uniform but structurally weakened heat transfer. These findings highlight that explosion-proof concrete retains acceptable thermal stability below 200 °C, while significant degradation occurs beyond 300 °C. The novelty of this work lies in integrating experimental thermophysical tests with finite element simulations to link microstructural changes with macroscopic thermal behavior. Practically, the results provide guidance for optimizing concrete formulations and protective strategies in fire- and explosion-prone facilities such as LNG storage units and petrochemical infrastructures. Full article

Cuscohygrine (CUS) and hygrine (HYG) are pyrrolidine alkaloids proposed as biomarkers of coca leaf consumption, a culturally accepted practice in some Latin American countries. Differentiating legal coca use from illicit cocaine consumption holds forensic importance. While LC-MS/MS is preferred, GC-MS remains widely used in Latin American toxicology labs due to accessibility. This study critically evaluates the analytical limitations of GC-MS for detecting CUS and HYG in biological matrices. Key parameters—injector temperature (180–290 °C), injection mode (split/splitless), solvent, liner condition, and matrix—were systematically studied. GC-MS showed significant limitations: low-abundance, non-specific fragments (m/z 42, 84, 98, 140) failed to meet the identification criteria in SIM mode. Thermal degradation of CUS to HYG and CUS-d6 to HYG-d3 was observed, especially with splitless injection and aged liners. Matrix effects produced signal enhancement ranging from +29% to +316%, meaning that analyte responses in biological samples were significantly higher than in neat standards, likely due to reduced degradation or adsorption. Although deuterated internal standards (CUS-d6) partially corrected signal variability and matrix enhancement, these corrections were not sufficient to overcome the fundamental limitations of GC-MS, including poor ion specificity and compound instability. These findings support the need for LC-MS/MS-based approaches for reliable alkaloid detection and question the suitability of GC-MS for CUS analysis in forensic toxicology contexts. Full article

This study presents a simulation-based evaluation of advanced control strategies for residential air conditioning systems, including On–Off, PI, and Model Predictive Control (MPC) approaches. A black-box system model was identified using an ARX(2,2,0) structure, achieving over 90% prediction accuracy (FIT) for indoor temperature and power consumption. Six controllers were implemented and benchmarked in a high-fidelity Simscape environment under a realistic 48-h summer temperature profile. The proposed MPC scheme, particularly when incorporating outdoor temperature gradient logic, reduced energy consumption by up to 30% compared to conventional PI control while maintaining indoor thermal comfort within the acceptable range. This virtual design workflow shortens the development cycle by deferring climatic chamber testing to the final validation phase. Full article

Traditional Chinese Kang heating systems have been used for over two millennia in northern China, yet their thermal efficiency and optimal design parameters lack scientific validation. This study aims to establish evidence-based guidelines for Kang-to-room area ratios to enhance thermal comfort and energy efficiency in rural architecture. We conducted direct measurements in a controlled experimental house (24 m²) in Huludao City, collecting temperature and humidity data from Kang surfaces and interior spaces over five-day periods. A benchmark curve for heat flux density was developed based on specific fuelwood consumption rates (1 kg/m²). TRNSYS simulations were employed to validate experimental data and analyze thermal performance in the historical Qingning Palace (352 m²) at Shenyang Imperial Palace. The benchmark curve demonstrated high accuracy with a Mean Absolute Error of 0.46 °C and Root Mean Square Error of 0.53 °C when compared to measured temperatures over the 48 h validation period; these values are well within acceptable ranges for calibrated thermal models. Simulations revealed optimal thermal comfort conditions when heat dissipation parameters were scaled appropriately for building size. The optimal Kang-to-room area ratio ranges from 0.28 to 0.69, with the existing Qingning Palace ratio (0.34) falling within this range, validating traditional design wisdom. This research provides a scientific foundation for sustainable architectural practices, bridging traditional knowledge with contemporary thermal engineering principles for both heritage preservation and modern rural construction applications. Full article

College student military training is an organized, high-intensity, short-term militarized activity in China; this study aims to explore the differences in thermal perception between different intensities of military training. Questionnaires and microclimate measurements were conducted during summer military training in cold regions, including the Protective and Rescue Training and Assessment (PRTA), Formation Training (FT), the Shooting and Tactical Training and Assessment (STTA), the Route March (RM), and Dagger Practice (DP). The results indicated that (1) there was no significant correlation between the intensity of the activity and votes on thermal perception. The strongest thermal sensations, the lowest comfort, and the lowest thermal acceptability were experienced during FT, with a lower activity intensity. (2) Air temperature (T_a), globe temperature (T_g), relative humidity (RH), mean radiant temperature (T_mrt), and solar radiation (G) had significant effects on the TSV. (3) FT involved the lowest neutral temperatures (NUTCI/NPET), while DP and RM training had the highest NUTCI and NPET values, respectively. The neutral temperature range during military training was narrower compared to that in other aerobic activities. This study reveals, for the first time, the non-traditional correlation between military training intensity and thermal perception, confirming the specificity of thermal sensations in mandatory training and providing a theoretical basis for optimizing military training arrangements and developing thermal protection strategies. Full article

Hydrogen is a promising fuel in the current transition to zero-net CO₂ emissions. However, most practical combustion equipment is not yet ready to burn pure hydrogen without adaptation. In the meantime, blending hydrogen with natural gas is an interesting option. This work reports a computational study of the performance of swirl-stabilized natural gas/hydrogen flames in a novel combustion chamber design. The combustor employs an air-staging strategy, introducing secondary air through a top-mounted plenum in a direction opposite to the fuel jet. The thermal load is fixed at 5 kW, and the effects of fuel composition (hydrogen molar fraction ranging from zero to one), excess air coefficient (λ = 1.3, 1.5 or 1.7), and primary air fraction (α = 50–100%) on the velocity, temperature, and emissions are analysed. The results show that secondary air changes the flow pattern, reducing the central recirculation zone and lowering the temperature in the primary reaction zone while increasing it further downstream. Secondary air improves the performance of the combustor for pure hydrogen flames, reducing NO emissions to less than 50 ppm for λ = 1.3 and 50% primary air. For natural gas/hydrogen blends, a sufficiently high excess air level is required to keep CO emissions within acceptable limits. Full article

This paper investigates the measurement capability, dynamic response, and mechanical reliability of all 3D-printed multi-material thermistors. The thermistor design consisted of three main components: a polycarbonate (PC) substrate, a silver (Ag) electrode pair, and a poly(3,4-ethylenedioxythophene):poly(4-styrenesulfonate) (PEDOT:PSS) thermosensitive layer. The thermistors were fabricated using two manufacturing techniques: fused deposition modeling (FDM) for the substrate and micro-dispensing for the Ag and PEDOT:PSS films. Two designs with different sensing areas, D1 (90 mm²) and D2 (54 mm²), were fabricated. As the indicator of measurement capability, the highest thermal indexes were recorded as 905.64 and 813.03 K for D1 and D2 thermistors, respectively. Thermistors exhibited comparable dynamic performance, with normalized resistance variations ranging from 0.96 to 1 for temperature changes between 25 and 45 °C. The sensing area influenced both measurement capability and dynamic performance, where larger sensing areas enhanced measurement capability but extended the time required to complete dynamic cycles, around 400 s for D1 versus 350 s for D2. Adhesion tests revealed a strong bonding between the PEDOT:PSS and Ag layer with less than 5% material removal. However, the adhesion of the PEDOT:PSS to the PC substrate was weak, with over 65% material removal. Morphological analysis indicated that the poor adhesion was caused by suboptimal surface properties of the 3D-printed substrate, even resulting in gaps between these two surfaces. This study demonstrates that our all 3D-printed multi-material thermistors can match reported measurement performance with an acceptable dynamic performance while highlighting the need to improve 3D-printed substrate surface properties to enhance the performance of such multi-material structures. Full article

Due to its gelling and thickening properties, sweet potato starch (Ipomoea batatas L.) could be a promising ingredient to improve characteristics such as the viscosity and consistency of foods like dressings. The objective of this study was to use sweet potato starch by adding it to salad dressing-type emulsion formulations. Sweet potato starch was characterized (microscopic appearance, granule size, and thermal properties). Four formulations (F1–F4) were developed incorporating different amounts of sweet potato starch (2 and 4%), and were characterized by particle size, emulsion stability, rheology, and sensory analysis. The starch granules were oval shaped, with a size range of 10–33 μm, and a temperature and enthalpy gelatinization (ΔH) of 69.08 °C and 10.72 J/g, respectively. The formulations were evaluated for 30 days, the particle size had a range of 2.18–13.88 μm, the emulsion stability was 98.89–100%, all formulations presented a creaming index at 0%, and the coalescence rate obtained values between −2.33 × 10⁻⁸ and 7 × 10⁻⁸Kc (s⁻¹) showing a significant difference. The consistency coefficient (K) was obtained, 2.477–35.207 Pa·sⁿ, and there was no significant difference between F1 and F2 with respect to a commercial dressing. In the sensory analysis, F2 presented greater acceptance. The values obtained suggest that sweet potato starch could be used in this type of food, showing similarities to the commercial brand. Full article

In this study, a numerical model of a microchannel gas cooler was developed using a segment-by-segment approach for thermohydraulic performance evaluation. State-of-the-art heat transfer and pressure drop correlations were used to determine the air and refrigerant side heat transfer coefficients and friction factors. The developed model was validated against a wide range of experimental data and was found to accurately predict the gas cooler capacity (Q) and pressure drop (ΔP) within an acceptable margin of error. Furthermore, advanced machine learning algorithms such as extreme gradient boosting (XGB), random forest (RF), support vector regression (SVR), k-nearest neighbors (KNNs), and artificial neural networks (ANNs) were employed to analyze their predictive capability. Over 11,000 data points from the numerical model were used, with 80% of the data for training and 20% for testing. The evaluation metrics, such as the coefficient of determination (R², 0.99841–0.99836) and mean squared error values (0.09918–0.10639), demonstrated high predictive efficacy and accuracy, with only slight variations among the models. All models accurately predict the Q, with the XGB and ANN models showing superior performance in ΔP prediction. Notably, the ANN model emerges as the most accurate method for refrigerant and air outlet temperatures predictions. These findings highlight the potential of machine learning as a robust tool for optimizing thermal system performance and guiding the design of energy-efficient heat exchange technologies. Full article

The increasing demand for induction hobs necessitates efficient cooling systems to ensure the safe operation of electronic cut-outs. This study investigates the thermal representation of three different ignition designs integrated into an induction hob cooling system. A simplified model consisting of a radial fan, a daughterboard, and the electronics installed in the systems is used for the maintenance of the system. Remote measurements of air velocities at the cooler outlets are compared with the results obtained through programmable system dynamics (CFD) operations using FloEFD v2021.1 software. The findings of the study using the k-ε turbulence model show that Type 1 temperature is resistant to the lowest surface temperature for both the closest (IGBT 1) and the farthest (IGBT 2) temperature to the fan. Conversely, Type 3 temperatures exhibited high temperatures. Air velocity comparisons showed a maximum error rate of 30%, which is acceptable considering the variability in Type 1. Measurement system evaluation and DOE study were continued to increase the experimental range. This study demonstrates the utility offered by heatsink design in optimizing the cooling system of induction hobs and provides valuable insights for integrating thermal management systems. Full article

Local data about indoor thermal comfort are in short supply, which are always different from the predicted results produced by models shown in previous studies. Shopping malls that consume substantial energy need to save energy, provided that thermal comfort is maintained. Therefore, this research investigated indoor thermal comfort using field measurements and questionnaires in a typical shopping mall in Danyang, China, with a hot summer and cold winter climate in order to explore local demands and energy-saving potential. The findings are as follows: (1) The average air temperature ($T_a$) and operative temperature ($T_{op}$) are 26.7 °C and 26.4 °C, which implies a minor influence from radiation and other factors on $T_a$. Women are more sensitive to changes in outdoor temperature since clothing insulation ($I_{cl}$) varies by gender: 0.31 clo and 0.36 clo for male and female individuals, respectively. (2) The thermal neutral temperature (TNT) derived from the thermal sensation vote (TSV) is 25.26 °C, which is significantly higher than the 21.77 °C obtained from the predicted mean vote (PMV) model. (3) There is a wide range of acceptable temperatures for thermal comfort because the highest temperature was identified by the thermal comfort vote (TCV) at 27.55 °C, followed closely by 27.48 °C, 26.78 °C, and 25.32 °C, which were separately derived from the thermal acceptance vote (TAV), TSV, and predicted percentage of dissatisfied (PPD) people; these were based on an upper limit of the acceptable 80% range. (4) In total, 94.85% of respondents accepted the indoor air quality, although the median concentration of CO₂ was 772 ppm, and the neutral relative humidity level was 70.60%. Meanwhile, there is an important relationship between air quality satisfaction and operative temperature; thus, the temperature (26.93 °C) with peak satisfaction can enhance air quality perception and thermal comfort. (5) The energy savings that can be achieved are 25.77% and 9.12% at most based on acceptable thermal comfort compared with baseline energy consumption at 23 °C and 26 °C, respectively. Full article

High-temperature thermal images enable monitoring and controlling processes in metal, semiconductors, and ceramic manufacturing but also monitor activities of volcanoes or contrasting wildfires. Infrared thermal cameras require knowledge of the emissivity coefficient, while multispectral pyrometers provide fast and accurate temperature measurements with limited spatial resolution. Bayer-pattern cameras offer a compromise by capturing multiple spectral bands with high spatial resolution. However, temperature estimation from color remains challenging due to spectral overlaps among the color filters in the Bayer pattern, and a widely accepted calibration method is still missing. In this paper, the quantum efficiency of an imaging system including the camera sensor, lens, and filters is inferred from a sequence of images acquired by looking at a black body source between 700 °C and 1100 °C. The physical model of the camera, based on the Planck law and the optimized quantum efficiency, allows the calculation of the Planckian locus in the color space of the camera. A regression neural network, trained on a synthetic dataset representing the Planckian locus, predicts temperature pixel by pixel in the 700 °C to 3500 °C range from live images. Experiments done with a color camera, a multispectral camera, and a furnace for heat treatment of metals as ground truth show that our calibration procedure leads to temperature prediction with accuracy and precision of a few tens of Celsius degrees in the calibration temperature range. Tests on a temperature-calibrated halogen bulb prove good generalization capability to a wider temperature range while being robust to noise. Full article

The growing demand for high-power battery output in the ever-evolving electric vehicle and energy storage sectors necessitates the development of efficient thermal management systems. High-power lithium-ion batteries (LIBs), known for their outstanding performance, are widely used across various applications. However, effectively managing the thermal conditions of high-power battery packs remains a critical challenge that limits the operational efficiency and hinders broader market acceptance. The high charge and discharge rates in LIBs generate significant heat, and, as a result, inadequate heat dissipation adversely impacts battery performance, lifespan, and safety. This study utilized theoretical analysis, numerical simulations, and experimental methodologies to address these issues. Considering the anisotropic heat transfer characteristics of laminated pouch cells, this study developed a fluid–solid coupling simulation model tailored to the liquid-cooled structure of pouch battery modules, supported by an experimental test setup. A U-shaped “bathtub-type” cooling structure was designed for a 48 V/8 Ah high-power-density battery pack intended for start–stop power supply applications. This design aimed to resolve heat dissipation challenges, optimize the cooling efficiency, and ensure stable operation under varying conditions. During the performance assessments of the cooling structure conducted through simulations and experiments, extreme discharge conditions (320 A) and pulse charging/discharging cycles (80 A) at ambient temperatures of up to 45 °C were simulated. An analysis of the temperature distribution and its temporal evolution led to critical insights. The results showed that, under these severe conditions, the maximum temperature of the battery module remained below 60 °C, with temperature uniformity maintained within a 5 °C range and cell uniformity within 2 °C. Consequently, the battery pack meets the operational requirements for start–stop power supply applications and provides an effective solution for thermal management in high-power-density environments. Full article

This study evaluated outdoor thermal comfort in commercial and residential mixed-use blocks in hot and humid climates. A subjective survey questionnaire examined thermal environment metrics, individual data, and 141 pedestrian responses. The findings indicated that the average air temperature (31.8 °C) and relative humidity (65.8%) of the four mixed-use blocks were considerably high. The thermal environment differed between each block owing to the influence of block texture and building form. In addition, subjective sensation scores differed among the blocks, aligning with subjective preferences, though subjective acceptability remained largely within a “neutral” range across all blocks. The relationship between thermal environment and subjective perception was intricate, as their patterns of variation were not merely characterized by simple positive or negative correlations but were influenced by a multitude of factors. Multiple linear regression analysis indicated that air temperature, relative humidity, and mean radiant temperature were crucial factors affecting subjective acceptability, all demonstrating statistical significance at p-value < 0.05. Furthermore, this study examined the effect of morphological features on thermal comfort, identifying texture density, street height-to-width ratio (D/H), and orientation strategy as significant factors. The research provides valuable insights into outdoor thermal comfort in mixed-use blocks and provides recommendations for enhancing thermal environment management. Full article