Appropriate clothing is important for maintaining operative capability during cold weather operations. This study examined the impact of different cold weather combat uniforms on body temperature, manual performance, comfort and perspiration among nine male soldiers (aged 24 ± 4 years) in field conditions (–2 to 5 °C). They completed three trials, consisting of a 1-h walk at 5 km/h and 1 h passive standing, wearing uniforms with varying insulation levels (1.9, 2.2 and 2.5 Clo). The results show that uniform type and insulation significantly affect skin temperature, moisture accumulation and manual dexterity in mild sub-Arctic winter conditions. Results also indicate that the insulation and design of hand protection significantly influence hand and finger skin temperatures, which in turn affects manual performance, independent of overall clothing insulation. Finally, while models like required clothing insulation (IREQ) are useful for initial recommendations, individual adjustments are needed to maintain comfort and prevent cold weather injuries.

Thermal comfort in office buildings is a key factor in occupant well-being and productivity, yet it poses a challenge due to the diversity of individual thermal characteristics and preferences. This study aims to investigate the relationships among thermal discomfort of occupants in office buildings, the ventilation mode, and individual occupant characteristics under actual-use conditions. Three buildings with a hybrid ventilation mode (natural ventilation and air-conditioning) and one building with central air-conditioning were evaluated. Data on thermal discomfort and occupant characteristics were collected via electronic questionnaires. A total of 7564 records were collected, of which 945 corresponded to clearly defined thermal discomfort (488 for heat discomfort and 457 for cold discomfort). The results showed that heat discomfort was more frequent among men and cold discomfort among women, with gender emerging as the most consistent individual factor associated with discomfort. The 30–50 age group, occupants with normal body mass index, lower clothing insulation, and lower metabolic rate accounted for a higher absolute number of discomfort reports; however, proportional analyses indicated relatively similar discomfort rates across these categories, reinforcing that thermal perception results from the combined influence of building operation and individual sensitivity rather than from isolated individual characteristics. A higher incidence of thermal discomfort, mainly due to cold, was also observed in air-conditioned environments. Among women, 68.8% of cold discomfort votes were associated with air-conditioning, while among men, it was 83.2%. In summary, the results highlight the need for strategies to personalise thermal comfort, with individual control and adaptive temperature adjustments in office buildings.

Stratum ventilation (SV) has emerged as a promising approach for simultaneously addressing indoor thermal comfort, airflow effectiveness, and energy efficiency. Yet, most prior research considers predictive modeling, optimization, and decision-support separately, which reduces their usefulness in practice. To overcome this gap, the present study develops an integrated hybrid framework that links machine learning models, metaheuristic optimization, and multi-criteria decision-making into a unified workflow for SV enhancement. The proposed methodology unfolds in four sequential phases: (1) data preparation and statistical assessment, (2) development of predictive models using artificial neural networks (ANN) optimized through genetic algorithm (GA) and leader Harris Hawks optimization (LHHO), (3) multi-objective optimization employing NSGA-III, and (4) ranking of Pareto-optimal solutions with the VIKOR method to accommodate different operational priorities. The findings indicate that GA-assisted ANN consistently achieved superior prediction accuracy (R > 0.995) compared to LHHO-ANN. Optimal thermal comfort was obtained with supply air velocities of 1.18–1.20 m/s, supply air temperatures around 22.0–22.2 °C, and clothing insulation levels near 1.0 clo. Ventilation performance benefited from small vane angles (≤ 5°) and cooler wall surface temperatures (≤ 12 °C), while stratification was mitigated under wider vane angles (> 10°) combined with moderately higher wall surface temperatures (13–14 °C). Heating efficiency proved robust across all candidate solutions, with a consistent utilization coefficient of approximately 1.58. The VIKOR-based ranking organized the Pareto front into ten representative design scenarios, each offering a balanced trade-off among comfort, air quality, and energy use under varying preference weights. By structuring prediction, optimization, and decision-making in a single framework, this study delivers actionable strategies for tailoring SV operation in diverse settings such as office buildings emphasizing comfort, healthcare spaces requiring ventilation effectiveness, and large halls where stratification control is critical.

Thermal image-driven clothing insulation estimation using a fine-tuned multimodal large language model

ABSTRACT Thermal insulation materials are essential for preserving human warmth in cold climates, and biomimetic strategies inspired by natural structures offer powerful design principles. Motivated by the feather architecture of penguins, which endure year‐round temperatures of approximately −40°C to −60°C, a high‐performance thermal‐insulation (HPTI) material that reproduces the key features of feather structure by balancing thermal resistance, ultralow mass, and mechanical flexibility is reported. The HPTI is fabricated via a two‐step electrospinning process with tailored spinning parameters to produce a hierarchical, feather‐like architecture: a fluffy, air‐holding polyimide (PI) nanofiber aerogel paired with a compact PI nanofiber windproof membrane, yielding an ultralow bulk density of 4.15 mg/cm 3 . Surface hydrophobicity is excellent, with water contact angles of 147° (aerogel) and 130° (windproof membrane). The assembled material with an areal density of 190 g/m 2 achieves a thermal‐insulation ratio of 97.81%, a clothing insulation (clo) value of 6.518, and a heat‐transfer coefficient of 0.72 W/K·m 2 . Combined with favorable compressibility and mechanical compliance, these characteristics make the HPTI a promising candidate for lightweight, flexible garments and protective systems intended for extreme‐cold applications, while offering a scalable route to bioinspired thermal‐management materials.

Medical personnel wearing barrier clothing protecting against infectious agents are at risk of heat stress resulting from limited heat exchange with the environment. The aim of the study was to assess the impact of changing underwear on the thermal parameters of protective clothing sets and on the expected safe working time. The study used a Newton thermal manikin to determine the thermal insulation and water vapor resistance of clothing sets consisting of three types of underwear (standard medical underwear and short and long thermal underwear) worn under two types of barrier suits. The obtained data were used to conduct physiological simulations in the Predicted Heat Strain (PHS) program, estimating the time it takes for core body temperature to rise to 38 °C in conditions of 22 °C and 35 °C. The results showed that replacing medical underwear with thermal underwear at 22 °C extended safe working time by 24%. In hot conditions (35 °C), the positive impact was smaller, extending working time by a maximum of 4%. Changing the inner layer is an effective method of improving comfort and safety in barrier clothing, especially in thermoneutral conditions.

Purpose Amid rising global temperatures and resource constraints among developing economies, this study investigates gender-based variations in thermal comfort preferences and their impact on energy-related behaviours in Ghanaian university housing. Grounded in Gender Schema Theory, the research explores how thermal discomfort influences behavioural adaptation and social interactions. Design/methodology/approach The study used a cross-sectional survey of 735 university students across several campuses in Ghana. Quantitative analyses included independent-sample t-tests and multiple linear regression, with gender incorporated as an interaction term to evaluate moderation effects. Findings The results reveal that female students preferred warmer indoor temperatures more than males and engaged in thermally adaptive behaviours more frequently. Discomfort was indeed exacerbated, particularly among female occupants, by environmental determinants such as limited clothing insulation (mean Clo = 0.6), low air velocity (mean = 0.33 m/s), elevated relative humidity (mean = 78%) and high indoor temperatures (mean = 31.7 °C). These conditions contributed to an increase in thermal stress and sedentary activity levels (Met = 1.3), which also occurred. Research limitations/implications Female students demonstrated greater behavioural responsiveness toward these environmental stressors, which validated the limitations of prevailing male-centric thermal models and underscored the need for gender-sensitive approaches to indoor environmental design and management. Social implications Inclusive thermal comfort strategies may enhance social cohesion and promote equitable energy practices in student housing management. Originality/value This study introduces a gender-sensitive framework to the discourse on thermal comfort, advocating adaptive ventilation systems, preference-based roommate matching and participatory energy governance.

This paper presents study of thermal comfort calculations in public buildings, using Fanger’s method and ASHRAE standards. The influence of six main parameters – air temperature, radiant temperature, air velocity, relative humidity, metabolic rate, and clothing insulation – on human comfort sensation is analyzed. Results show that Fanger’s method provides a more accurate evaluation of parameter interaction, while ASHRAE offers simplified comfort ranges for practical design. The comfort zone for the analyzed cases ranges between 18–24 °C, depending on specific indoor conditions.

Abstract Climate change is increasing the awareness of thermal comfort issues, with many studies examining the aspects of factors and models from different perspectives. However, no comprehensive mappings have been conducted in previous review to explain the dynamics of the shifting of factors and models that can be used as a reference. Therefore, this study aimed to trace, identify, and map the shifting of indoor thermal comfort factors and models in the literature and provide a comprehensive map for future investigation. The identification process was carried out by tracing the development of thermal comfort theories from 1970 to 2019 and reviewing the state-of-the-art study on thermal comfort from 2020 to 2025. The results showed that there were six well-established thermal comfort factors used in many models, including air temperature, air velocity, relative humidity, mean radiant temperature, metabolic rate, and clothing insulation. Later studies, in the other hand, focus more on the application of new methodologies and approach to better couple thermal comfort solution with building energy efficiency to ensure more sustainable future.

Reliability of lookup table methods for estimating clothing insulation: Experimental verification using typical garments

Since psychological and physiological responses to repeated exposure to mild heat has not been fully studied, the present study was designed to confirm overshooting responses in thermal sensation after repeated exposure to mild heat (i.e., the cooling period), the manner of change in the thermal sensation responses (TSRs) and the thermal comfort responses (TCRs) during the cooling period, and effect of short-term heat acclimation during repeated exposure to mild heat. In the summer, eight young adult male subjects (a mean age of 21.1 ± 1.4 years; a mean height of 173.1 ± 5.6 cm and a mean weight of 58.8 ± 7.5 kg) with clothing insulation (Icl, clo) of 0.3 clo first stayed in the control room at 26 °C for 15 min, then moved to the main testing room at 33 °C for 10 min (condition 1), 15 min (condition 2), or 20 min (condition 3), and finally returned to the control room for 15 min. The exposure was repeated five times. TSR and TCR were recorded in a 5-min interval from the beginning of the first exposure. The tympanic temperature (Tty), skin temperatures at the chest, forearm, front of the thigh, and front of the shin, and ECG and heart rate were continuously monitored. Local sweat rates at the same sites of skin temperature were monitored at the end of each exposure. Changes in Tty and mean skin temperature (bar{mathrm{T}}_{mathrm{sk}}) indicated no significant difference between conditions and no indication of short-term heat acclimation. Since the subjects voted nearly “cold” when bar{mathrm{T}}_{mathrm{sk}} remained high at the beginning of the cooling period, overshooting responses in thermal sensation were repeatedly observed in all conditions. The subjects voted “slightly cool” at the end of cooling period while bar{mathrm{T}}_{mathrm{sk}} kept decreasing during the cooling period. The thermally neutral bar{mathrm{T}}_{mathrm{sk}} was then estimated to be 0.3 °C—4.2 °C lower than bar{mathrm{T}}_{mathrm{sk}} observed prior to the first exposure. Thus, a residual effect on TSR during the cooling period was confirmed. Changes in the mean sweat rate, TSR and TCR showed significant differences between conditions but no indication of short-term heat acclimation. However, change in heart rate and ECG analysis implied the effect of short-term heat acclimation.

Cold constitution refers to a phenomenon in which individuals have a higher sensitivity to cold and feel colder than others. This research aimed to examine the associations of morphological characteristics, personal factors, thermal perceptions, and local skin temperature (tsk) with cold constitution by conducting a field experiment. It also explored differences in these aspects between individuals with and without cold constitution, in a thermoneutral office environment during summer and winter, and in 89 and 75 sedentary workers, respectively. A questionnaire survey was conducted to classify the cold constitution (CC) and non-cold constitution (NC) groups. The results indicated that females and individuals with lower body mass index (BMI) were more likely to have cold constitution. The CC group exhibited a significantly lower metabolic rate (M) in both seasons, lower thermal sensation votes, warmer thermal preference, and a greater predicted percentage of dissatisfied in summer (p < 0.01). No significant differences were observed in clothing insulation between the groups; however, winter clothing was significantly higher compared to summer for both groups (p < 0.01). Furthermore, the CC group exhibited significantly lower local skin temperatures at distal body parts (p < 0.01). Significant correlations were observed for gender, BMI, M, thermal sensations, and distal tsk with cold constitution. Adjusting the effects of gender and BMI, most correlations with cold constitution weakened. However, thermal sensation remained significant in summer, while no correlation was observed with tsk. These findings emphasize the significant associations of morphological characteristics, personal factors, and thermal perceptions with cold constitution and show the importance of assessing the thermal environment.

This study aims to create environmentally comfortable building designs in hot and dry steppe climates using more effective approaches. The purpose of this study is to assess the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia), taking into account the orientation of buildings, for better building thermal performance. For this purpose, residential buildings with different orientations were selected in the study region ‘Garmian—northern Iraq’, and their thermal performance was evaluated. The results show how MRT contributes to the buildings’ thermal comfort. The outcomes of this research provide innovative empirical quantification of the correlation of MRT-Tia, as the regression coefficient (β) represents the rate of change in Tia per unit increase in MRT and ranges by orientation in the study area. The findings demonstrate that north-facing buildings buffer radiant heat gain (β~0.52), resulting in a 0.5 °C increase in indoor air temperature for each 1 °C rise in MRT. Moreover, west orientation delivers promising winter passive heating (MRT up to 22 °C and indoor air temperature up to 22.8 °C with a β of ~0.82). However, south-facing buildings perform poorly in the winter, with low MRT and a weak β (~0.44), contrasting with passive solar design strategies that favor south-facing buildings in the northern hemisphere. Furthermore, in the summer, the MRT is always higher than Tia, while it is lower in winter, indicating poor envelope and fenestration thermal insulation properties, which lead to excessive energy usage to maintain thermal comfort. Finally, the study suggests the novel quantified MRT-Tia mathematical correlation responds to the orientations for such climates, offering both diagnostic and predictive tools for thermal comfort performance optimization. This study is the first to empirically quantify orientation-specific MRT–Tia relationships in BSh climates, offering a novel diagnostic tool for sustainable building design. This study involved field observations in 36 residential row houses across four orientations. Key environmental and personal variables measured included mean radiant temperature (MRT), indoor air temperature (Tia), air velocity, relative humidity, metabolic rate, and clothing insulation.

Purpose This paper aims to examine thermal comfort and conservation conditions in a historic living museum by evaluating the indoor environmental conditions of the Vicarage, situated in a historic area of the northeastern USA. The study’s primary objective is to assess and understand the conservation environment and thermal comfort of historic living museums. It uses thermal comfort models to evaluate comfortable temperatures, thermal sensations and thermal indices within the spaces. The historic village serves as a living museum, reflecting the lifestyles of rural New England residents during the 18th and 19th centuries. Design/methodology/approach The research involves conducting physical measurements in selected buildings to assess thermal comfort and conservation conditions in one of these structures. The study focuses on the Vicarage due to its importance to the village and its representation of historical residences in that region of New England. The primary source of heating during the cold winter months is the fireplace, while the building naturally ventilates in the warm season. Findings The average temperatures and relative humidity in the heated spaces ranged from 17.6 °C to 19.0 °C and from 47.6% to 60.8%, respectively. The mean temperature in an unheated space (i.e. without access to a fireplace) was 14.0 °C. The average air velocity varied from 0.03to 0.18 m/s due to the limited hours the windows remained open during the survey. This investigation highlights the following finding: spaces directly connected to the heating source are more comfortable than those that are not. The average clothing insulation (clo) values of individuals emulating 18th and 19th-century lifestyles exceed the clo values reported in recent research for the same season. Spaces with direct access to the fireplace have fewer people with a dissatisfied perception than those without this access. Practical implications The research can guide owners and managers of historic sites, such as living museums, on essential aspects to improve the performance of these buildings. The research also provides insights into the thermal environment of living museums and offers strategies to enhance their conservation conditions. Originality/value This study offers further insights into thermal comfort and conservation conditions in historic buildings, thereby enhancing the understanding of how occupants’ perceptions, adaptations and comfort within indoor environments have evolved. Moreover, the study examines various modifications or strategies (e.g. using dehumidifiers to reduce RH below 60%, using light-colored surfaces to increase lighting levels, etc.) that could be explored for living museums, while also assessing the associated challenges (such as the risk of molds, low lighting levels, etc.) that impact the comfort and conservation conditions of such buildings. The research provides valuable insights into past lifestyles and the adaptive strategies people used to cope with varying thermal environments across different seasons, including extreme weather conditions.

This study evaluates the performance of an Artificial Neural Network-based model (ANN-BM) to predict occupant thermal comfort and the efficiency of a wind-catcher room in warm climates. The ANN-BM predicts the Nusselt number on heated and cooled walls (Nuhw and Nucw), air exchange effectiveness (AEE), predicted mean vote (PMV), and predicted percentage of dissatisfied (PPD) in naturally ventilated buildings. Predictor variables include outdoor temperature, temperature difference (ΔT) between walls, air velocity, relative humidity, clothing insulation and activity level, selected through independence and importance analysis. The model achieved an R 2 of 0.960, with mean absolute errors of 2.83 (Nuhw), 3.05 (Nucw), 0.006 (AEE), 0.2677 (PMV), and 6.58% (PPD), demonstrating superior accuracy compared to traditional methods and multilinear models (R 2 = 0.83). Additionally, computation time was reduced by over 99% compared to CFD simulations. This highlights the model’s effectiveness and efficiency in evaluating ventilation, thermal performance, and thermal comfort in naturally ventilated buildings.

Dynamic detection models for clothing insulation and metabolic rate based on computer vision

This study analyzes two machine learning models, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), to predict thermal insulation of cotton fabric woven with twill. The input parameters include fabric thickness, ends per inch (EPI), and picks per inch (PPI). The ANN model has a 3-8-1 network structure, with output and hidden layers having sigmoid and linear activation functions. The ANFIS model employs sugeno-type fuzzy logic, while the network is trained using the feedforward backpropagation Levenberg-Marquardt technique. The weighted average approach was used in the defuzzification process. MATLAB was used to create both models. The ANN model performs well in predictions, as evidenced by its R2 value of 0.9942, which indicates a significant correlation between the target and prediction values. The ANN model's exceptional performance metrics, such as a mean absolute percentage error (MAPE) of 1.31401 and a root mean squared error (RMSE) of 0.00176, demonstrate its precision and reliability. However, the ANFIS model has considerably lower accuracy metrics, with an R2 value of 0.9570. The ANN offers more accuracy and precision than the ANFIS model, which has an RMSE of 0.00489 and a MAPE of 2.07495. This study will improve the textile engineering prediction model by revealing the intricate connection between fabric characteristics and the thermal insulation of clothing composed of cotton fabric's twill structure.

Indoor environmental quality profoundly impacts student learning outcomes and teacher effectiveness, particularly in primary education, where children spend most of their developmental years. The study compares the New Zealand Ministry of Education’s Designing Quality Learning Spaces (DQLS) version 2.0 for primary school classrooms with international standards set by OECD countries to develop IAQ and thermal comfort best practices in New Zealand across six climate zones. The research evaluates indoor air quality (IAQ) and thermal comfort factors affecting students’ and teachers’ health and performance. Using Ladybug and Honeybee plugin tools in Grasshopper with Energy Plus, integrated into Rhino 7 software, the study employed advanced building optimisation methods, using multi-criteria optimisation and parametric modelling. This approach enabled a comprehensive analysis of building envelope parameters for historical classroom designs, the Avalon block (constructed between 1955 and 2000). Optimise window-to-wall ratios, ceiling heights, window placement, insulation values (R-values), clothing insulation (Clo), and window opening schedules. Our findings demonstrate that strategic modifications to the building envelope can significantly improve occupant comfort and energy performance. Specifically, increasing ceiling height by 0.8 m, raising windows by 0.3 m vertically, and reducing the window-to-wall ratio to 25% created optimal conditions across multiple performance criteria. These targeted adjustments improved adaptive thermal comfort, ventilation, carbon dioxide, and energy efficiency while maintaining local and international standards. The implications of the findings extend beyond the studied classrooms, offering evidence-based strategies for overall design and building performance guidelines in educational facilities. This research demonstrates the efficacy of applying computational design optimisation during early design phases, providing policymakers and architects with practical solutions that could inform future revisions of New Zealand’s school design standards and align them more closely with international best practices for educational environments.

The climate of the Hungarian lowland (Central European region, Pannonian Plain area) can be characterized by Köppen’s Cfb climate formula (C—warm temperate, f—no seasonality in the annual course of precipitation, b—warm summer). This characterization does not provide information about the human thermal load and thermal perception. The aim of this work is to fill this gap. We focused on the morning, clear-sky periods of the day, when the heat supply provided by the weather is the lowest. The human thermal load of clear-sky mornings was estimated using the new clothing thermal resistance–operative temperature (rcl–To) model. In contrast to IREQ-type (Required Clothing Insulation) models, this model parametrizes the total metabolic heat flux density (M) as a function of anthropometric data (body mass, height, sex, age). In the simulations, the selected persons walk (M values range between 135 and 170 W m−2) or stand (M values range between 84 and 96 W m−2), while their body mass index (BMI) varies between 25 and 37 kg m−2. The following main results should be highlighted: (1) Human activity has a significant impact on rcl; it ranges between 0 and 3.5 clo during walking and between 0 and 6.7 clo during standing. (2) The interpersonal variability of rcl increases with increasing heat deficit accordingly; in the case of a walking person, it is around 1 clo in the largest heat deficits and around 0 clo in the smallest heat deficits. Since, in general, anticyclones increase the heat deficit while cyclones reduce it, extreme thermal loads are associated with anticyclones. It should be mentioned that the interpersonal variability of the human thermal load cannot be analyzed without databases containing people’s anthropometric data.

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 (Ta) and operative temperature (Top) are 26.7 °C and 26.4 °C, which implies a minor influence from radiation and other factors on Ta. Women are more sensitive to changes in outdoor temperature since clothing insulation (Icl) 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.