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Graphical abstract Highlights • A 3-layer phase change material configuration was proposed. • A method for temperature selection of phase change material was proposed. • Novel hybrid phase change material wallboards were fabricated and characterized. Abstract Phase change materials are smart, feasible latent heat storage materials and have been incorporated into building materials to reduce energy demand and improve the thermal comfort of buildings. This study proposes a method for improving energy efficiency and thermal comfort in buildings (during both summers and winters) by developing a novel hybrid phase change material wallboard and a method to select the temperature of phase change material for different seasons (29 °C for summer, 18 °C for midseason, and 12 °C for winter). This type of hybrid phase change materials wallboard consists of three types of phase change materials with different phase-change temperatures that can be utilized efficiently in different seasons. The thermal performances of the hybrid phase change material wallboards (two combination modes: Mode1 and Mode2) were evaluated by a guarded hot plate method. The effective thermal conductivity (λ) and apparent specific heat (C p) of these wallboards were investigated. The interior temperature variations of the two types of phase change materials wallboards were compared during heating and cooling, and it could be concluded that the Mode2 hybrid phase change materials wallboard (where phase change material was incorporated into different gypsum wallboard layers) was more suitable for real applications. The goal of this study is to investigate an appropriate method to fabricate a new hybrid phase change materials wallboard for building energy savings over different seasons. [ABSTRACT FROM AUTHOR]

Personal thermal preference information can help to create a building environment that satisfies all staff, instead of an environment that only satisfies most people, to enhance personal thermal comfort. Research has shown that thermal preference can be predicted using parameters that are based on various local body parts, but the selected body parts are often different. Using too many body parts for the measurements leads to high costs, while using too few body parts results in large errors. In this study, 19 adult subjects (8 females and 11 males) were recruited, their overall and local thermal preferences were surveyed, and the skin temperature of seven body parts were measured. A machine learning algorithm, random forest, was employed to analyse the contributions of different body parts. Three criteria (the best combination, fewest combination, and common combinations) were employed to select body parts to use to establish thermal preference models for individuals and groups. The results show that the prediction power of these combinations reached 0.91 ± 0.07 (accuracy), 0.75 ± 0.16 (Cohen's kappa), and 0.87 ± 0.09 (AUC) when using 2–8 body parts. The common combinations are recommended for their balance of their prediction power and the number of local body parts involved. This study offers a reference for efficient and economic measurements for thermal comfort research in building environments. [ABSTRACT FROM AUTHOR]

Clothing has a significant impact on the heat transfer between the human body and the environment, and clothing insulation is an important input parameter for many thermal comfort models. With the development of studies on non-uniform environment and human's local thermal comfort, the clothing local insulation is required in the multi-node human thermoregulation models and significantly affects the accuracy of simulation results. However, there lacks data on clothing local insulation values in standards. In this study, the local insulation of 57 typical garments and 62 ensembles with different layers (1–6 layers) were measured using a thermal manikin. The results show that the ranges of overall insulation for tested garments and ensembles were 0.01–0.56 clo and 0.27–2.17 clo, respectively. The local insulation values differed greatly from the overall insulation values, and varied greatly between different body parts. Further, the linear regression was performed between the ensembles' local insulation at different body parts and the sum of the garments' local insulation. Based on the prediction equations of local insulation, a new method for estimating the overall insulation of ensembles was proposed. Compared with the tradition method using the linear regression equations of overall insulation, the new method reduced the mean relative error from 12.6%–9.1% to 3.4%. This study provided basic data and prediction equations of local insulation for future researches of clothing insulation and local thermal comfort. • A clothing local insulation database including 57 typical garments and 62 ensembles was built. • Linear regression equations of local insulation at different body parts were proposed. • A new method for predicting overall insulation of ensembles using garments' local insulation was developed. • New method reduced the MAPE from 9.1% to 3.4% compared with the method using linear model of overall insulation. [ABSTRACT FROM AUTHOR]

Human thermoregulation models can predict human thermal responses to evaluate thermal comfort and help create a healthy environment, while their applicability to older people has not been sufficiently validated. This study aimed to evaluate the performance of the Stolwijk model and the Tanabe model for predicting older people's mean and local skin temperatures under thermal transient conditions. Eighteen healthy older people were recruited and exposed to transient environments including neutral (26 °C), low-temperature (23 and 21 °C), and high-temperature (29 and 32 °C) conditions. The local skin temperatures of the subjects were measured and compared to predictions of the Stolwijk model and the Tanabe model. The results revealed that the Stolwijk model and the Tanabe model could accurately predict the mean skin temperature of older people under neutral and high-temperature conditions, while their predictive accuracy declined under low-temperature conditions. Increased deviations were observed in the predictions of local skin temperatures for all conditions. This work attempted to provide an understanding of older people's thermal response characteristics under transient conditions and to inspire the improvement of thermoregulation models for older people. [ABSTRACT FROM AUTHOR]

Clothing plays an essential role in maintaining heat balance and thermal comfort for older people but varies with climate conditions and costume culture. The recommended clothing insulation in ISO 7730 and ASHRAE Standard 55 lack information on typical clothing ensemble and local insulation values for older people. To investigate the winter clothing characteristics of older people living in Shanghai, a field survey involving 342 healthy subjects from 12 aged-care homes and a lab study conducted with a 22-segment thermal manikin were performed. Subjects' typical clothing ensembles were summarized based on the survey. The local clothing insulation of 34 typical garments and 35 clothing ensembles were measured in the lab experiment. Results show that most older people in winter worn 7 pieces of clothes (excluding underpants, socks and shoes). The frequencies of typical upper and lower garments/ensembles were reported. Through manikin tests, the whole and local insulation of those typical garments and ensembles were presented. By comparison, the insulation values of garments in ISO 7730 were found to be inconsistent with tested garments' results for older people. Further, linear regression models were built to link relationships of the insulation of multiple garments and ensembles. Through running an older people-based thermoregulation model, it was found an incorrect estimation of typical winter clothing insulation for older people could lead around 1.3 °C deviation on predicted mean skin temperature or around 26% deviation on heat loss. • A field study of 342 elderly people was conducted in 12 aged-care homes in winter. • Local insulation of typical ensembles was tested using a 22-segment thermal manikin. • A winter local clothing insulation database for ederly people was built. • Linear regression models of local clothing insulation were established. • Effects of typical winter clothing for the elderly in predicting skin temperature have been discussed. [ABSTRACT FROM AUTHOR]