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Face masks' wearing for a long duration brings thermal discomfort, especially in hot climate cities. The face masks' thermal insulation and its effect on outdoor thermal comfort have been rarely investigated. In this study, five types of face masks and their thermal insulations have been tested by using a thermal manikin in the climate chamber. Experimental results are assessed by using physiological equivalent temperature (PET) and standard effective temperature (SET*) for thermal comfort with masks at three walking speeds both in summer and winter. Slight differences in thermal insulation are observed among the different masks, the values of PET and SET* rise with increasing mask thermal insulation, and they are generally higher in summer than in winter. Moreover, the variation of SET* is more obvious than PET with same masks at different walking speeds. And the differences of SET* with and without masks appear to rise significantly for fast walking. Results further indicate that the individuals' physical discomfort caused by wearing masks cannot simply be assumed as an additional effect of the clothing thermal insulation. The findings enrich the clothing thermal insulation database, explore the differences in thermal indices if the face mask is used, and provide advice on heat mitigation with masks outdoors. [ABSTRACT FROM AUTHOR]

Active heating in extremely cold weather clothing would be useful to save the life of an injured or sick person due to low metabolic rate. A fully dressed thermal manikin is useful in evaluating the performance of the active heating ensemble. The thermal manikin tests are time-consuming and could be done only after making the complete ensemble. An experiment that is designed to evaluate the performance of an active heating fabric fixed to a set of layers of extreme cold climate clothing using a guarded hot plate instrument would save a lot of time as it skips the processes of garmenting and subsequent evaluation on the thermal manikin. In this work, a guarded hot plate placed inside a cold chamber is used to investigate the external heating required for the prolonged comfort of the wearer at various sub-zero ambient temperatures, clothing insulation and metabolic heat. A plain woven active heating fabric sandwiched between a knitted fabric and nonwoven of different insulation/thickness is used to perform experiments. The external heat required to keep the test plate (representing the human skin) at 307 ± 1 K (34 ± 1 °C) is measured at different experimental conditions. Further, a one-dimensional numerical model based on coupled conduction–radiation heat transfer with heat generation was developed and validated with experimental results. The experimental temperature profiles match well with the numerical temperature profiles at different locations, justifying the numerical methodology adopted in this work. This suggests that the developed numerical model would also be useful to estimate the required active heating as per the wearer's requirement and an available power source. Both the experimental and numerical results suggest that the external active heating required to maintain test plate (skin) temperatures within the human skin comfortable range is a function of ambient temperature, metabolic heat and clothing (nonwoven) insulation. [ABSTRACT FROM AUTHOR]

Providing suitable indoor thermal conditions in educational buildings is crucial to ensuring the performance and well-being of students. International standards and building codes state that thermal conditions should be considered during the indoor design process and sizing of heating, ventilation and air conditioning systems. Clothing insulation is one of the main factors influencing the occupants' thermal perception. In this context, a field survey was conducted in higher education buildings to analyse and evaluate the clothing insulation of university students. The results showed that the mean clothing insulation values were 0.60 clo and 0.72 clo for male and female students, respectively. Significant differences were found between seasons. Correlations were found between indoor and outdoor air temperature, radiant temperature, the temperature measured at 6 a.m., and running mean temperature. Based on the collected data, a predictive clothing insulation model, based on an artificial neural network (ANN) algorithm, was developed using indoor and outdoor air temperature, radiant temperature, the temperature measured at 6 a.m. and running mean temperature, gender, and season as input parameters. The ANN model showed a performance of R2 = 0.60 and r = 0.80. Fifty percent of the predicted values differed by less than 0.1 clo from the actual value, whereas this percentage only amounted to 32% if the model defined in the ASHRAE-55 Standard was applied. [ABSTRACT FROM AUTHOR]

Cold protection for outdoor workers is crucial for their health and thermal safety in winter. Personal heating is considered an effective measure to solve the problem, which can significantly improve thermal comfort. However, according to the present studies, a uniform assessment of different personal heating measures is hard to obtain. This study explored four typical types of personal heating measures (electrically heated garment, electrically heated garment with an aerogel layer, electrically heated seat, and chemically heated insole) in different cold environments. Clothing insulation, effective heating power (Peff), and heating efficiency (η) were measured by a thermal manikin with a constant temperature in nine environmental conditions. Three levels of two critical environmental factors (air temperature (Ta): −5 °C, −10 °C, and −15 °C; air velocity (Va): <0.1 m/s, 0.5 m/s, and 1.0 m/s) were crossed orthogonally to form the nine environmental conditions. The results indicated that Ta had no significant effect on clothing insulation, while elevated Va significantly decreased clothing insulation. When Va increased from 0 m/s to 1 m/s, the air layer inside the garment was squeezed, causing a 0.6–0.9 clo decrease in total clothing insulation. Decreased Ta and elevated Va reduced the Peff and η of electrical heating measures while they improved the Peff and η of chemical heating insoles. The Peff and η of the garment dropped to 8.2 W and 21%, respectively, at −15 °C and 1.0 m/s. In addition, the aerogel layer could effectively improve the Peff and η of the garment. The improvement was weakened by decreased Ta and elevated Va. The corrective power values of personal heating measures in different environments were calculated to guide the design and application of personal heating. [ABSTRACT FROM AUTHOR]

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Ambient temperature steps between typical non-work and hot work environments will lead to clothing heat storage and release, which is crucial for human health and thermal comfort. In this study, the influence of five types of ambient temperature steps (from 0ºC/5ºC/10ºC/15ºC/20ºC to 40ºC to 0ºC/5ºC/10ºC/15ºC/20ºC) on the heat storage and release in clothing was investigated using a thermal manikin. A moving and temperature-controlled refrigerated incubator was constructed to realize the temperature step conditions. Results showed that ambient temperature step magnitude was positively related to heat storage and release. Some 80% of the amount of heat storage would be completed in around 10 min after the temperature steps. Increasing the inner clothing layer weight and specific heat capacity for local clothing at the chest, thigh and calf improved their heat storage against the large temperature step conditions. As for the abdomen, its heat storage was the largest. However, the clothing layer configuration impacted its heat release, so it was necessary to guide the heat transfer to the skin. The heat storage in the outer layer was increased by 2% to 39% due to adding the inner layer of the garment. The stored heat discharged completely until the temperature step magnitude exceeded 32.5°C. A multiple linear regression formula was proposed to obtain the clothing average heat storage by considering ambient temperature step magnitude and clothing insulation. The results of this study could contribute to the optimization of thermal protective clothing and improvement of the research on human thermal comfort. [ABSTRACT FROM AUTHOR]

Energy-saving is a mandatory research topic since the growing population demands additional energy yearly. Moreover, climate change requires more attention to reduce the impact of generating more CO2. As a result, some new research areas need to be explored to create innovative energy-saving alternatives in electrical devices that have high energy consumption. One research area of interest is the computer visual classification for reducing energy consumption and keeping thermal comfort in thermostats. Usually, connected thermostats obrtain information from sensors for detecting persons and scheduling autonomous operations to save energy. However, there is a lack of knowledge of how computer vision can be deployed in embedded digital systems to analyze clothing insulation in connected thermostats to reduce energy consumption and keep thermal comfort. The clothing classification algorithm embedded in a digital system for saving energy could be a companion device in connected thermostats to obtain the clothing insulation. Currently, there is no connected thermostat in the market using complementary computer visual classification systems to analyze the clothing insulation factor. Hence, this proposal aims to develop and evaluate an embedded real-time clothing classifier that could help to improve the efficiency of heating and ventilation air conditioning systems in homes or buildings. This paper compares six different one-stage object detection and classification algorithms trained with a small custom dataset in two embedded systems and a personal computer to compare the models. In addition, the paper describes how the classifier could interact with the thermostat to tune the temperature set point to save energy and keep thermal comfort. The results confirm that the proposed real-time clothing classifier could be implemented as a companion device in connected thermostats to provide additional information to end-users about making decisions on saving energy. [ABSTRACT FROM AUTHOR]

Thermal comfort standards are required for overall indoor satisfaction and energy conservation. Even though the lower Himalayan region of Darjeeling has seen rapid growth in population due to its temperate type of climate, and thus resulting in manifold construction of concrete buildings, very few research on the built environment are reported from the region. In this paper, the author has discussed the yearlong thermal comfort study conducted in a naturally ventilated 3-storey un-insulated concrete building located at lower Himalayan region of Darjeeling, India. The mean indoor operative temperature were 16.7°C, 19.0°C and 22.3°C, the clothing insulation were 0.94 clo, 0.78 clo and 0.57 clo and the mean Griffiths' comfort temperature were 18.1°C, 19.6°C and 22.4°C during the cool, moderate and warm seasons, respectively. Seasonal and gender-wise differences are reported in the paper. A logistic regression is presented to show the variation of single and multiple layers of clothing used by subjects to adapt with the plummeting temperature. A modification in the comfort standards for the region with lower and upper limits as 16.2°C and 23.3°C is also proposed. [ABSTRACT FROM AUTHOR]

Providing suitable indoor thermal conditions in educational buildings is crucial to ensuring the performance and well-being of students. International standards and building codes state that thermal conditions should be considered during the indoor design process and sizing of heating, ventilation and air conditioning systems. Clothing insulation is one of the main factors influencing the occupants’ thermal perception. In this context, a field survey was conducted in higher education buildings to analyse and evaluate the clothing insulation of university students. The results showed that the mean clothing insulation values were 0.60 clo and 0.72 clo for male and female students, respectively. Significant differences were found between seasons. Correlations were found between indoor and outdoor air temperature, radiant temperature, the temperature measured at 6 a.m., and running mean temperature. Based on the collected data, a predictive clothing insulation model, based on an artificial neural network (ANN) algorithm, was developed using indoor and outdoor air temperature, radiant temperature, the temperature measured at 6 a.m. and running mean temperature, gender, and season as input parameters. The ANN model showed a performance of R2 = 0.60 and r = 0.80. Fifty percent of the predicted values differed by less than 0.1 clo from the actual value, whereas this percentage only amounted to 32% if the model defined in the ASHRAE-55 Standard was applied.

Barring a few reports on the clothing insulation of sari and salwar-Kurti, little is known about the other traditional ensembles men use in South Asia and beyond. To accurately account for the thermal insulation on the human body, simulation studies necessitate insulation on various body parts. This study reports the segmental level insulation of 52 traditional ensembles of both genders recorded in a climate chamber.  Indian garments are worn as ensembles. We focused on the drape, as traditional ensembles offer great opportunities for thermal adaptation through changing drape. We researched on 41 sari ensembles, four salwar-kurti and seven men’s’ ensembles, such as dhoti, pancha and lungi. More than the material, drape has a significant effect on the clothing insulation. For the same pieces of garments, the clo value of the ensemble varied by as much as 3.1 to 32 %, through changing drape in saris, the lower values being associated with lighter saris. A similar trend but somewhat lower variation was noticed in men’s’ ensembles. This makes the sari an all weather ensemble. Interestingly in the pancha ensemble, men can achieve 47% reduction in the clo value with minor variations. The adaptation possibility in traditional ensembles is enormous.

Abstract To accurately simulate human physiology and thermal comfort, certain human physiological and comfort models categorize the human body into multiple parts. Most of these body parts are normally clothed, which must be quantified in the simulation. However, existing databases of clothing evaporative resistance only characterize the evaporative resistance of the whole body and not those of individual body parts. This implies that each body part has the same level of clothing evaporative resistance. In this research, we measure the local clothing insulation and evaporative resistance. Here, we present the local thermal characteristic values as well as the values for the whole body.

Cold protection for outdoor workers is crucial for their health and thermal safety in winter. Personal heating is considered an effective measure to solve the problem, which can significantly improve thermal comfort. However, according to the present studies, a uniform assessment of different personal heating measures is hard to obtain. This study explored four typical types of personal heating measures (electrically heated garment, electrically heated garment with an aerogel layer, electrically heated seat, and chemically heated insole) in different cold environments. Clothing insulation, effective heating power (Peff), and heating efficiency (η) were measured by a thermal manikin with a constant temperature in nine environmental conditions. Three levels of two critical environmental factors (air temperature (Ta): −5 °C, −10 °C, and −15 °C; air velocity (Va): Ta had no significant effect on clothing insulation, while elevated Va significantly decreased clothing insulation. When Va increased from 0 m/s to 1 m/s, the air layer inside the garment was squeezed, causing a 0.6–0.9 clo decrease in total clothing insulation. Decreased Ta and elevated Va reduced the Peff and η of electrical heating measures while they improved the Peff and η of chemical heating insoles. The Peff and η of the garment dropped to 8.2 W and 21%, respectively, at −15 °C and 1.0 m/s. In addition, the aerogel layer could effectively improve the Peff and η of the garment. The improvement was weakened by decreased Ta and elevated Va. The corrective power values of personal heating measures in different environments were calculated to guide the design and application of personal heating.

Women across South-Asia wear the sari. It is versatile as the drape modifies the clothing insulation, for a given ensemble. We tested three Indian ensembles of saris (for four drapes) with a thermal manikin following ISO: 9920 protocols. The insulation on all the sixteen body parts and the whole-body were recorded. This provides information for advanced thermalcomfort modeling needing clothing insulation at segmentation level. The sari offered a wide range of insulation (0.94 to 0.62) for a given set of garments. Winter ensembles provided 1.11 – 1.39 clo while the summer and monsoon ensembles had 0.62 – 0.96 clo. We noted the clothing insulation varying by about 48 - 51 % due to the changes in drape on the upper bodyalone. The findings of this research are more than a correction of clo value of saris.

Energy-saving is a mandatory research topic since the growing population demands additional energy yearly. Moreover, climate change requires more attention to reduce the impact of generating more CO2. As a result, some new research areas need to be explored to create innovative energy-saving alternatives in electrical devices that have high energy consumption. One research area of interest is the computer visual classification for reducing energy consumption and keeping thermal comfort in thermostats. Usually, connected thermostats obrtain information from sensors for detecting persons and scheduling autonomous operations to save energy. However, there is a lack of knowledge of how computer vision can be deployed in embedded digital systems to analyze clothing insulation in connected thermostats to reduce energy consumption and keep thermal comfort. The clothing classification algorithm embedded in a digital system for saving energy could be a companion device in connected thermostats to obtain the clothing insulation. Currently, there is no connected thermostat in the market using complementary computer visual classification systems to analyze the clothing insulation factor. Hence, this proposal aims to develop and evaluate an embedded real-time clothing classifier that could help to improve the efficiency of heating and ventilation air conditioning systems in homes or buildings. This paper compares six different one-stage object detection and classification algorithms trained with a small custom dataset in two embedded systems and a personal computer to compare the models. In addition, the paper describes how the classifier could interact with the thermostat to tune the temperature set point to save energy and keep thermal comfort. The results confirm that the proposed real-time clothing classifier could be implemented as a companion device in connected thermostats to provide additional information to end-users about making decisions on saving energy.

Thermal comfort standards are essential to ensure comfortable and enjoyable indoor conditions, and they also help in optimizing energy use. Thermal comfort studies, either climate chamber‐based or field investigation, are conducted across the globe in order to ascertain the comfort limits as per the climatic and other adaptive features. However, very few studies are conducted when the occupants are subjected to a stressed condition, like the COVID‐19 lockdown, which may not only have the health impacts but also have psychological impacts on the adaptation. In this paper, we present the results of the online study conducted regarding the status of thermal comfort during the COVID‐19 lockdown in India. A total of 406 complete responses were collected from subjects located across 3 different climatic regions of India, that is, cold climate, composite climate, and hot and humid climate. Variations in clothing insulation, thermal sensation, and preference were noted across the different climatic regions. We also present the variation in opening of windows and running of fans with the variation in outdoor mean air temperature. The self‐judged productivity, comfort, desire to go outdoors, and effectiveness of working from home were seen to vary with the increase in the days of lockdown. [ABSTRACT FROM AUTHOR]

Achieving a balance between energy efficiency and thermal comfort is a key aspect of sustainable building design. Traditional control methods typically maintain indoor air temperature within predetermined limits, disregarding variable factors such as occupancy activity and clothing levels, which influence thermal comfort. Conversely, comfort-based control strategies present an opportunity to automate heating and cooling systems, enabling them to dynamically respond to variations in thermal comfort. To achieve this, real-time information on clothing insulation (and its adjustment) is indispensable for accurately estimating thermal comfort. In this study, we explore the potential of a novel detection approach capable of classifying clothing insulation in real-time and utilizing this information to optimize the operation of building energy systems. By doing so, the proposed method facilitates the delivery of indoor conditions tailored to user requirements and potentially reduces energy wastage. The development of a two-stage, computer vision-based framework for occupancy detection and clothing insulation classification forms the core of this approach. Leveraging deep learning algorithms, this framework performs detection and recognition tasks, even with limited training data effectively, enabling real-time classification of light, medium and heavy clothing. To address the nonlinearity of traditional predicted mean vote (PMV) models, we applied a piecewise linearization approach to our PMV-based optimal control strategy. We evaluated the performance of this detection method through initial experimental field tests conducted in a case study university building. The results demonstrate the proposed method's ability to classify clothing insulation levels and generate real-time profiles. We further analyze the impact of our proposed approach on thermal comfort and energy performance through scenario-based modelling and simulations. The initial results showed the potential of integrating our method with PMV-based controls to enhance thermal comfort and overcome the limitations of predefined values or fixed schedules. However, while our study confirms the feasibility of classifying clothing insulation levels for multiple occupants engaged in diverse indoor activities, it also highlights the need for further refinement to enhance detection accuracy and ensure seamless integration with building energy systems. [Display omitted] • YOLO & GoogLeNet algorithms ensure accurate occupant clothing insulation classification. • Case study validates successful detection in a lecture room in a university building. • Detection approach successfully handles multiple occupants' clothing variations during different activities. • Scenario-based simulations demonstrate energy savings and optimize thermal comfort. • Lightweight CPU usage and fast response times ensure practical implementation. [ABSTRACT FROM AUTHOR]

• A vision-based model for estimating real-time personal factors was developed. • The model simultaneously estimates metabolic rate and clothing insulation. • A real-time PMV-based control algorithm was developed for both individual and group. • The algorithm enhanced thermal comfort of occupants compared to conventional methods. • The core technique was verified to balance energy and comfort in building operations. To optimize thermal comfort for occupants' wellbeing and health care, it's essential to adjust heating and cooling systems in real-time based on occupants' thermal preferences. For this, personal factors affect individual thermal comfort, such as metabolic rate and clothing insulation, should be estimated in real-time. The aim of this research is introducing an intelligent model capable of estimating metabolic rate and clothing insulation values from indoor images, suitable for both single and multi-occupant scenarios. Additionally, a control algorithm considering a real-time predicted mean vote (PMV), was developed using the proposed model, and its implications for thermal comfort and energy efficiency were investigated. Utilizing advanced computer vision methodologies, the model achieved a remarkable 95% training accuracy, and its reliability was further validated through experimentation. Evaluations of the PMV-based algorithm underscored its efficacy in enhancing thermal comfort relative to conventional methods in both individual and multi-occupant settings. Conversely, energy use was contingent upon the personal factors. In group settings, the mode values of metabolic rate and clothing insulation were effective for determining a representative PMV. In conclusion, the real-time PMV-based control represents a pioneering approach to augment thermal comfort using actual occupant data, paving the way for a synergistic balance between comfort augmentation and energy saving. [ABSTRACT FROM AUTHOR]

The sari is everyday attire for most women throughout the year all across South-Asia. It is a versatile ensemble because, a single set of garments can provide different levels of insulation just by changing the drape. We tested three Indian ensembles of saris (for four drapes) with a thermal manikin following ISO: 9920 protocols. The insulation on all the sixteen body parts and the whole-body were recorded. This provides information for advanced thermal comfort modelling needing clothing insulation at segmentation level.The sari offered a wide range of insulation (0.94 to 0.62) for a given set of garments. Winter ensembles provided 1.11 – 1.39 clo while the summer and monsoon ensembles had 0.62 – 0.96 clo.

Clothing insulation is an important factor in the thermal comfort research, and thus an accurate clothing insulation model is much required. This study develops a new model, which takes into account the sex difference for the dress. Its accuracy was verified experimentally, and the established thermodynamic model is useful to predict occupants' clothing behavior and to evaluate thermal comfort. [ABSTRACT FROM AUTHOR]

• An application of thermal depth images from a mobile robot to human thermal comfort measurement is proposed. • The proposed method is based on an established thermal comfort measure in the architecture domain. • Thermal comfort measurement is performed more conveniently than existing methods by using thermal-depth images. • Quantitative evaluations have been conducted for clothing insulation and PMV measurement. This paper describes an application of thermal-depth images to human thermal comfort measurement. A mobile monitoring of the elderly and residents of care houses is one of the promising applications of mobile assistive robots. Monitoring if a person feels comfortable is an important task of such robots. We rely on an established comfort measure in the architecture domain, namely, predicted mean vote (PMV). PMV is calculated mainly by six factors and one of which is the clothing insulation or clo-value. Clo-values are usually measured by a thermal mannequin, a specially-designed apparatus for the purpose. We apply human recognition techniques in thermal-depth images to efficiently measure clo-values, thereby enabling on-line assessment of thermal comfort. We evaluate the method and develop a mobile robot system for experimental testing. [ABSTRACT FROM AUTHOR]

In this study, the authors evaluated clothing insulation and changes in the metabolic rate of individuals in an office environment to determine thermal comfort. Clothing was evaluated using a questionnaire completed by 1306 workers in nine offices. The metabolic rates of 86 workers in three offices were measured using a physical activity meter. The distribution of the temperature at which a person in the room perceived a neutral thermal sensation was then calculated from the determined metabolic rates and clothing insulation values. The results demonstrate a noticeable difference between the average and most frequent values during the summer. Moreover, the required temperature distribution is not normal; rather, it is broad and skewed to the low-temperature side. Therefore, even if a thermally uniform environment is provided at the average required temperature by preventing temporal and spatial variations in the thermal environment, complaints of an unacceptably hot thermal environment are more likely to occur than complaints of an excessively cold thermal environment. [ABSTRACT FROM AUTHOR]

To accurately simulate human physiology and thermal comfort, certain human physiological and comfort models categorize the human body into multiple parts. Most of these body parts are normally clothed, which must be quantified in the simulation. However, existing databases of clothing evaporative resistance only characterize the evaporative resistance of the whole body and not those of individual body parts. This implies that each body part has the same level of clothing evaporative resistance. In this research, we measure the local clothing insulation and evaporative resistance. Here, we present the local thermal characteristic values as well as the values for the whole body. [ABSTRACT FROM AUTHOR]

The study of thermal comfort in buildings is required to maintain a stable and comfortable condition of the indoor environment. The climate chamber study used to determine thermal comfort is mathematically reproducible and robust, but exaggerative and hence is energy inefficient, whereas the adaptive model-based field survey method is exhaustive and bioclimatic specific. Although, several field survey-based thermal comfort studies have been reported from India, these studies were conducted mostly either in hot and humid or composite climatic condition, and very few research has been reported from cold climatic region, which lies mostly along the high altitudinal Himalayan region. In this paper, the results of field survey-based thermal comfort studies in residential houses of highly altitudinal Darjeeling Himalayan region in eastern India are presented. The study found that female subjects showed a lesser clothing cover but portrayed a higher discomfort with lower thermal sensation and higher comfort temperature. The comfort temperature as determined in this study did not comply with the ASHRAE standard 55 graphical method, and hence new comfort zone for regions with similar cold climate is proposed. [ABSTRACT FROM AUTHOR]

The metabolic rate (MET) is a fundamental parameter influencing thermal comfort, which further affects the well-being and productivity of the occupants. Here, the impacts of activity intensity, ambient temperature and clothing insulation on MET are studied through climate chamber experiments. The results indicate that MET is always positive to the activity intensity at various conditions of ambient temperature and clothing insulation. However, the impacts of ambient temperature and clothing insulation on MET are changing, and there are interactions between them. In addition, the measured MET and that calculated with the heart rate (HR) is compared, and the results reveal that the neutral ambient temperature range in ISO 8996–2021 can be extended from 9 to 24 °C with the human clothing regulation. The results not only provide data support for developing regional and global MET database, but also are significant in laying the groundwork for elucidating the relationship between MET and the thermal environment, clothing insulation as well as activity intensity. • The metabolic rate is measured by a portable metabolic device at various conditions. • The impacts of activity, temperature and clothing on the metabolic rate are studied. • The equation for the metabolic rate and walking speed is improved. • The measured metabolic rate and that calculated with the heart rate is compared. • Provide data support for developing regional and global the metabolic rate database. [ABSTRACT FROM AUTHOR]

Convective heat transfer coefficients for each part of the clothed human body were evaluated under airflow conditions and compared to those of nude body. This was done by measuring clothing surface temperatures on seated and standing manikin using an infrared-imaging radiometer. The convective heat transfer coefficients for the clothed manikin were larger than for the nude manikin. The difference could be 100 to 200% for some individual parts, and for the overall body the difference was 30 to 50%. These results were consistent for both standing and sitting postures, or for facing upwind and facing downstream, although slightly larger differences between clothed and nude could be seen when the manikin was sitting and facing upwind than in the other conditions. Clothing insulation for each part was also estimated. Some differences between standing and sitting were observed at the body part level. However for the whole body the difference was small. Regression models for convective heat transfer coefficients and clothing insulation for all body parts were presented for use in human thermal modeling.

The effects of air flow on clothing insulation and on the dry heat transfer coefficients were evaluated for each part of the clothed and nude human body. This was done by measuring clothing surface temperature using an infrared imaging radiometer. The results showed that increasing wind speed causes a decreased in clothing insulation and an increase in the dry heat transfer coefficients. The effects of air penetration on dry heat transfer coefficients could be determined by comparing the heat transfer coefficients of the clothed manikin to those of the nude manikin. Lastly, by comparing clothing insulation results obtained by the conventional indirect method of those of the direct method, in this study, one can demonstrated the limitation of the conventional method and the need for direct estimation.

The traditional houses are well adapted to the climate and socio-culture using local building materials and techniques. However, traditional practices are being replaced by the artificial materials, modern design and new technology. It requires strong policies to sustain the traditional architecture. The objectives of this study are to evaluate the thermal condition of traditional houses and to estimate the comfort temperature of residents. The thermal comfort survey was conducted during winter in the traditional houses. The thermal sensation votes were collected from 275 people in cold, temperate and sub-tropical climatic regions. This study was revealed that the mean indoor air temperature in cold climatic region is 12.3°C, which was 9.5K and 4.4K lower than sub-tropical and temperate climates. The comfort temperature of the residents in the cold climate was 13.9°C, which was 8.8K and 3.8K lower than sub-tropical and temperate climates. The mean clothing insulation in cold climate was 1.63 clo which was 0.48 clo and 0.31 clo higher than subtropical and temperate climates. It concludes that the people were well adapted to each climate with clothing adjustments and made themselves satisfied with the thermal condition of their houses. [ABSTRACT FROM AUTHOR]

Human local parts have different thermal responses to low temperature environment. The objective of this paper is to find out the most sensitive parts which are extremely discomforting in low temperature environments. Based on previous experimental data, the relationship among skin temperature, air temperature, and clothing insulation was fitted, and the neutral skin temperatures were obtained. The local skin temperatures at different parts of the human body were compared with neutral skin temperatures in different air temperatures and clothes. The results showed that the local parts of foot, hand, upper arm, and calf deviated far from the neutral condition and were selected as the principal parts to be warmed. The findings are significant to improve human local thermal discomfort. [ABSTRACT FROM AUTHOR]

This study focuses on clothing behavior of occupants regarding their 'neutral' thermal sensations inside buildings. Statistical analyses were performed with an aim to better understand how building occupants can achieve thermal comfort by adjusting their clothing insulation. The proposed neutral clothing insulation model can be used to determine whether clothing adjustment can sufficiently offset indoor temperatures in naturally ventilated building contexts. Thermal comfort parameters and diverse contextual variables recorded in the ASHRAE Global Thermal Comfort Database II were analyzed to define the key factors to be used in the estimation of clothing insulation values corresponding to neutral thermal sensations. The results of the analysis indicated that climate, season, building type (such as office, school, or residential), and indoor and outdoor temperature variations were the key contextual variables to be considered for understanding occupant clothing behavior. Different types of statistical models were also compared to derive the most useful model for predicting the ideal or optimal clo -values inside buildings. • Climate, season, building type were key categorical variables for neutral clothing. • Indoor and outdoor temperatures were key numerical variations for neutral clothing. • Clothing variation in multifamily was different from classroom and office building. • Female occupants more actively adjusted clothing than the males. • A linear mixed model was developed for 'neutral' clothing. [ABSTRACT FROM AUTHOR]

Air layers in multi-layer firefighter clothing ensembles resist heat transfer from the body to the environment. By reducing the volume of air between clothing layers, heat loss may be improved throughout the multi-layer firefighter turnout suit clothing system, potentially leading to reduced heat strain for the wearer. This research utilized a systems-level approach to the methodology in order to measure the effects of fabric properties and garment air gap dimensions on clothing system heat loss through specially configured turnout suit constructions. One experimental configuration incorporated a tight fitting stretchable moisture barrier garment. Another construction used thermal knit underwear to represent a closer fitting thermal liner. Air gap surface area, volume, and thickness were estimated using three-dimensional body scanning. This study showed the significant impact of fabric air permeability and clothing air gap volume on heat loss through structural firefighter suits. Tested individually, the tighter fitting moisture barrier construction permitted greater heat loss in comparison to the traditional fit moisture barrier. Heat loss differences associated with moisture barrier fit were not observed when the moisture barriers were configured in the three-layer turnout clothing system. This research showed that microclimate air gap volume is strongly correlated with total heat loss. It confirmed the significant impact of clothing air layers on heat loss through firefighter turnout systems. [ABSTRACT FROM AUTHOR]

• Sitting posture affected the thermal insulation of modern office chairs. • Leaning forwards reduced the chair insulation by 0.09 clo. • Facemasks provide small, but not insignificant thermal insulation of 0.05 clo. • The insulation of contemporary office chairs matched those of earlier studies. This study experimentally explored the variability in thermal insulation with different sitting postures and a contemporary selection of chair designs. Also, the insulating effect of three different types of facemasks was evaluated. Measurements were made with a thermal manikin seated in a well-controlled climate chamber at three different room temperatures: 20 ± 0.2 °C, 25 ± 0.2 °C and 30 ± 0.2 °C. Two sitting postures were investigated: back in contact with the chair backrest or not, i.e. leaning slightly forwards. The selected chairs had effective thermal insulation around 0.14–0.17 clo when the manikin was seated with the back in contact with the chair backrest, except the applied executive chair, which provided 0.26 clo. On average, leaning forwards reduced the clothing insulation by 0.09 clo. The tested facemasks all provided the same marginal insulation I clu of 0.05 clo. The measured chair insulation values were well aligned with those from earlier studies. The study confirms that chair insulation is a parameter that should be carefully evaluated and considered when assessing thermal comfort. [ABSTRACT FROM AUTHOR]

Development of multi-node thermoregulation models with local clothing insulation as an indispensable input parameter enables distinguishing the effects of spatial and temporal changes in the thermal environment around the human body. However, the current research on local clothing insulation lags compared with multi-node thermoregulation models, affecting model prediction accuracy. The effects of the determination methods and posture on the overall and local intrinsic clothing insulation remain unknown. Therefore, in this study, the overall and local intrinsic clothing insulation values for seven typical clothing ensembles in standing and sitting postures were determined using four different methods that included thermal manikin (TM) experiments and thermal comfort standards. The results showed that (1) the overall intrinsic clothing insulation I cl differed slightly across the methods, whereas the local clothing insulation I cl,i differed substantially across the methods; (2) the overall intrinsic clothing insulation I cl for the sitting posture was 15% lower than that of the standing posture, whereas the difference in the local intrinsic clothing insulation I cl,i for the standing and sitting postures was only statistically significant at the pelvis and thigh; and (3) the local intrinsic clothing insulation I cl,i differed significantly over different body segments, and the largest I cl,i was 2.7 and 3.2 times the smallest I cl,i for the standing and sitting postures, respectively. Therefore, methods employed along with the posture affected the results of both overall and local intrinsic clothing insulation. The findings are effective in modeling sensible heat loss through clothing and contribute to improving the prediction accuracy of multi-node thermoregulation models. • Supplemented database on overall and local clothing insulation in various postures. • Methods compared to determine overall and local intrinsic clothing insulations. • Overall intrinsic clothing insulation is 15% smaller when sitting than standing. • Local clothing insulation (thigh and pelvis) is smaller when sitting than standing. • Largest local insulation: 2.7 (standing) and 3.2 (sitting) times the smallest value. [ABSTRACT FROM AUTHOR]

Clothing influences the heat exchange between the human body and the environment, and the thermal resistance of clothing is typically unevenly distributed across different body parts. The determination of local clothing insulation values is critical for the operation of multi-segment human thermoregulation models to obtain accurate thermophysiological parameters. As current standards only consider overall clothing insulation for the entire body, estimating local clothing insulation in field studies and human experiments remains difficult. In this study, a method for estimating the local thermal insulation values of garments using their overall insulation values was proposed, and its practical application for determining local insulation of ensembles was further presented. Eight garment types (excluding female-specific garments such as skirts and bras) were classified according to the main covered area of the human body. Based on the thermal manikin test results of 75 garments, prediction models for local insulation at different body parts were developed for various types of garments using the overall insulation values. For practical applications, the estimation method was applied to typical garments in the ISO 7730 standard to obtain reference local insulation values. The local insulation of ensembles can finally be calculated by combining the regression models between the local insulation of the ensemble and the sum of the local insulation of the contained garments. This study can help determine standardized local clothing insulation, providing validated input parameters for heat transfer analysis of the human-clothing-environment system and local thermal comfort research. [Display omitted] • Method for estimating local insulation of garments was developed. • Garments were classified to eight types based on covered body parts. • Local insulation distribution was presented for each type of garments. • Reference local insulation for typical garments in standard was calculated. • Two-phase method for estimating local insulation of ensembles was developed. [ABSTRACT FROM AUTHOR]

A simplified algorithm using an artificial neural network (ANN, a feed-forward neural network) for the assessment of the predicted mean vote (PMV) index in summertime was developed, using solely three input variables (namely the indoor air temperature, relative humidity, and clothing insulation), whilst low air speed (

Many thermal comfort studies have been conducted in offices, classrooms and dwellings, but few in public buildings such as cathedrals, museums and markets. A recent thermal comfort study has been conducted in three naturally ventilated (NV) buildings, a cathedral, a museum and a market, in Jakarta, between March and April 2014. There is a curiosity as to whether people doing slightly different activities with slightly different clothing insulation values, in different building types, might have different comfort temperatures. Approximately the same number of subjects (respondents) participated in the study of each building. Using the same monitoring equipment, results of this study show that subjects’ comfort temperatures were found to be similar in all of the buildings; however, it was found that the spread of the subjects’ comfort range in the three buildings was significantly different.

The purpose of this research was to determine the impact of additional textile layer reinforcements on garment heat loss and the physiological comfort of the firefighter. Four structural firefighter turnouts with varying levels of 'bulk' were assessed. A base composite analysis was conducted and each suit was evaluated for thermal resistance, evaporative resistance, and overall total heat loss (THL) on a sweating thermal manikin. Raw resistance data were then modeled to predict the physiological responses of firefighters for each turnout suit. Base composite percentages were compared to the heat loss values and predicted physiological responses. The Light Weight suit along with the Control, demonstrated the greatest heat loss values and lowest rise in predicted core temperature. Overall, results depicted the harmful impact that bulky reinforcements may have on wearer physiological comfort as the Heavy Duty suit had significantly lower heat loss and a potentially fatal maximum predicted core temperature. [ABSTRACT FROM AUTHOR]

Thermal comfort standards are required to provide comfortable indoor condition which has a positive effect on the occupant. However, the Predicted Mean Vote – Percentage People Dissatisfied (PMV-PPD) model which is used to determine the indoor comfort in most of the international standards fails often, especially in naturally ventilated buildings. Several field studies were conducted elsewhere to determine the comfort condition, but very few are reported for the cold and cloudy type of climate and in hilly region. In this paper, the results of field studies conducted in 10 buildings of different types located in varying elevation are presented. A total of 2608 responses of thermal comfort were collected from 436 subjects between January and December 2015. The mean clothing insulation of the subjects were found to increase with the increase in the elevation of the location and this difference was statistically significant, t  = −94.05 (df = 2607, p  < 0.001). The yearly mean clothing insulation in S0135 was 0.640 clo, K1420 was 0.722 clo, M1640 was 0.947 clo, S1950 was 1.055 clo and T2565 was 0.907 clo, respectively. Whereas, the mean comfort temperature decreased with the elevation of the location and this difference was also statistically significant, t  = −92.34 (df = 2607, p  < 0.001). The yearly mean comfort temperature for the location S0135 was 28.37   °C, K1420 was 20.59   °C, M 1640 was 20.07   °C, S1950 was 19.72   °C and T2565 was 17.35   °C, respectively, where the digits in the locations (i.e. 0135 in S0135, 1420 in K1420, 1640 in M1640, 1950 in S1950 and 2565 in T2565) represents the elevation of the location under study in meters above mean sea level. A relation of the indoor comfort temperature with the outdoor environmental conditions and with the elevation of the location under study is obtained. [ABSTRACT FROM AUTHOR]

Although clothing is a critical factor in assessing human thermal comfort, gender differences exist in thermal responses. This paper presents research on gender differences in adult physiological and psychological responses to the thermal environment, using 12 different clothing ensembles. The experiment was conducted at four air temperatures: 10, 16, 22, and 28 °C, with three different series of clothing ensembles in each air temperature. The main conclusions are as follows: women are more sensitive to a colder thermal environment. Their measured overall skin temperatures were lower than those of their male counterparts and the predicted values for cold environments. This was particularly true in the case of hands, feet, and lower body parts, resulting in women feeling colder than men in the same cold environment. However, there were no significant differences in thermal sensations between the genders when their measured skin temperatures were the same. Different body parts showed different levels of thermal adaption to cold environments: the head, hands, and lower body had lower neutral skin temperatures in cold environments than those recorded in a previous study of a neutral environment, especially in the case of women. Due to these physiological and psychological differences of local body, more men than women preferred to add warmer or additional pants in cold environments. This article provides information to help researchers and designers take gender differences into consideration when designing indoor thermal environments, helping to improve both thermal comfort and system efficiency. [ABSTRACT FROM AUTHOR]