Comfortable outdoor environment benefits the health of citizens and reduces energy consumption and pollution. This study discusses different outdoor thermal sensation and comfort evaluation methods ...in severe cold area. The database was from a year-long outdoor thermal comfort survey conducted in Harbin, China. Thermal sensation evaluation was developed using meteorological parameters and three popular thermal comfort indices including Standard Effective Temperature (SET*), Physiologically Equivalent Temperature (PET) and Universal Thermal Climate Index (UTCI). Thermal comfort prediction was developed by the three thermal comfort indices and acceptability. Original thermal sensation scales of SET* and PET were less applicable to predict thermal sensation vote (TSV). Calibrated scales of the three indices were obtained based on linear regression results and probit analysis. The accuracies of calibrated scales of thermal sensation were all below 32.8%. The comfortable thermal sensation range in severe cold area varied from “slightly cool” to “hot”. This calibrated range improved accuracies of thermal comfort predicting by around 20%. The unacceptability appropriate to define comfortable range was 9% on the cold thermal sensation side and 26% on the hot side. Adaptation and local exposure also acted on thermal sensation and comfort apart from factors included in thermal comfort indices. Our results provide practical thermal sensation and thermal comfort scales for severe cold area. The discussions indicate the significance of considering adaptation and local exposure for further improving thermal sensation and comfort predicting.
Display omitted
•Original scale of UTCI is superior to SET* and PET in thermal sensation evaluation.•Performance of obtained thermal sensation prediction methods show minor difference.•Comfortable range for adults in severe cold area is from “slightly cool” to “hot”.•Unacceptability to define comfortable range is 9% (cold side) and 26% (hot side).•Adaptation and local exposure are vital for further improving comfort predicting.
Thermal comfort markedly impacts our health, well-being and work productivity. This article is a review of practices generally adopted to quantify human thermal comfort in buildings. The review ...indicates that there is significant variation in comfort requirements due to diversified socio-cultural set-up and local adaptive behaviour. Thus, the localised thermal comfort models need to be developed to identify the actual comfort requirements helpful in drafting new local comfort standards. The study justifying the relationship between thermal comfort and indoor air quality are scant and need to be explored as such relationships are greatly dependent on occupant's adaptive behaviour. Further, the interdisciplinary research on thermal comfort which not only helps in real-time assessment but also covers other critical aspects like building architecture and energy consumption is lacking in the literature. Moreover, this review paves way for research on thermal comfort in countries where high building stock is expected in future.
Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of ...humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub‐classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi‐channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.
Urban green and blue infrastructures (GBI) are considered an effective tool for mitigating urban heat stress and improving human thermal comfort. Many studies have investigated the thermal effects of ...main GBI types, including trees, green roofs, vertical greenings, and water bodies. Their physical characteristics, planting designs, and the surrounding urban-fabric traits may impact the resultant thermal effects. ENVI-met, a holistic three-dimensional modeling software which can simulate the outdoor microclimate in high resolution, has become a principal GBI research tool. Using this tool, the GBI studies follow a three-step research workflow, i.e., modeling, validation, and scenario simulation. For providing a systematic and synoptic evaluation of the extant research workflow, a comprehensive review was conducted on GBI-targeted studies enlisting ENVI-met as the primary tool. The findings of 79 peer-reviewed studies were analyzed and synthesised for their modeling, validation, and scenario simulation process. Special attention was paid to scrutinising their data sources, evaluating indicator selection, examining main analytical approaches, and distilling recommendations to improve the research workflow. This review provides researchers with an overview of the ENVI-met methodology and recommendations to refine research on GBI thermal effects.
People's outdoor thermal sensation varies from that indoors. The highly asymmetric solar radiation and transient wind environment are the main causes. The University of California-Berkeley developed ...a multi-nodal human body thermal regulation model (the UCB model) to predict human thermal sensation and comfort in asymmetric and transient indoor environments. However, few studies compared its predictions with the survey responses outdoors. In this study, subjects' thermal sensations outdoors were surveyed and compared with the UCB model predictions. Meteorological parameters were monitored using a microclimate station, and over a thousand human subjects were surveyed. Results point out that subjects were highly sensitive to the changes in wind speed, especially under low-radiation conditions. However, the UCB model failed to predict such a high sensitivity. Besides, subjects had a higher tolerance to high air temperatures in outdoor environments when the solar radiation was acceptable, but the UCB model over-predicted the TSV (thermal sensation vote) in such conditions. Both the on-site results and the predictions by UCB model showed that subjects were more sensitive to wind speed in hotter environments while they were least sensitive to solar radiation in neutral thermal conditions. This study helps to reveal the potential of a multi-nodal thermal regulation model to address the asymmetric and transient features of outdoor environments and indicates the need to further refine the model for better quantitative prediction of outdoor thermal sensations.
•Solar radiation and wind speed changed rapidly in the outdoor environments.•The acceptable range of operative temperature outdoors was wider than predicted.•The UC Berkeley model underestimated the cooling effect caused by wind.•The UC Berkeley model overpredicted TSV when solar radiation was acceptable.•People's sensitivity to wind speed and solar radiation was higher than predicted.
•A two layered control strategy integrating DP and fuzzy PID is built.•PPTC can accurately describe the thermal habit of passenger.•DP integrates the PPTC, VVP and WIR and achieves a low energy ...cost.•Fuzzy PID well responses the requirement of refrigeration capacity from DP.•Two layered strategy raises comfort and control precision and saves energy.
A two-layered control strategy is proposed for the air conditioning (AC) systems of electric vehicles. Unlike traditional rule-based controllers such as the on–off controller and proportion-integral-derivative (PID) controller, this strategy includes a decision layer and a control strategy. The core algorithm in the decision layer is the dynamic programming (DP), which integrates information from the thermal habit predictor of the passenger, vehicle velocity planner, and weather information receiver. The DP optimises the development of the cabin temperature to minimise the energy consumption of the AC system and sends the planned temperature to the control layer. The control layer uses a fuzzy PID algorithm to adjust the compressor speed based on the planned temperature profile, such that the real-world cabin temperature approaches the planned temperature. This two-layered control strategy is applied to a car whose AC-cabin system was verified by test data, and the results are compared with those obtained by the on–off controller and PID. When the target cabin temperature is not manually adjusted, the energy cost of the proposed strategy is 28.2% and 5.4% lower than those of the on–off controller and PID, respectively, at the ambient temperature profile of Environment 1 (described herein), and its maximum fluctuation of the cabin temperature is 92.8% and 68.2% smaller than those of the on–off controller and PID, respectively. At the ambient temperature of Environment 2 (described herein, lower than that of Environment 1), the energy cost of the proposed strategy is 37.1% and 5.9% lower, and the maximum fluctuation of the cabin temperature is 96.8% and 86.4% smaller, compared to the on–off controller and PID, respectively. When the target temperature is repeatedly set for the on–off controller and PID (first to 20 °C, then to 24.3 °C), the AC system consumes extra energy, leading to poor thermal comfort. Because the proposed strategy automatically sets the cabin temperature to the temperature preferred by the passenger, there is no extra adjustment of the target and the thermal environment inside the cabin is optimal for the passenger. Under this condition, the developed strategy can produce energy savings of 30.2% and 12.4%, compared to the on–off strategy and PID, respectively. Thus, the two-layered strategy can control the cabin temperature precisely, provide the passenger with a good thermal environment, and produce energy savings for the AC system.
•Reviewing thermal comfort models in different aspects.•Analyzing the advantages and disadvantages of all the models in the review.•Interpreting the importance of the models in different ...environments.•Suggesting some future developing directions of thermal comfort models.
In the past several years, thermal comfort, especially development and application of thermal comfort model, has been a research focus of building environment. Since the 1970s, a series of thermal comfort models based on people's thermal sensation to environment have been established, and gradually became an important part of the field of thermal comfort research. In this review, the existing thermal comfort models are summarized from various perspectives, such as models applied in different environments like sleeping environment and outdoor environment. Besides, models used for different groups people, such as elderly and different races are discussed. In the part, adaptive models are mentioned. In additions, data-driven models were reviewed. This paper introduced the advantages and disadvantages of each model. Based on the above review, future research work of thermal comfort model is proposed.
•The influence of social context on university students’ thermal comfort is studied.•2147 questionnaires were selected for analysis.•Votes were selected from similar thermal environments and personal ...characteristics.•There is no correlation between thermal sensation vote and socioeconomic context.
Classrooms are environments occupied by people with different thermal preferences and with different social and economic realities. This study aimed to evaluate the influence of the socioeconomic context on the thermal comfort of university students in classrooms. In this study, the socioeconomic context of the students was evaluated based on four categorical variables: per capita income range, paid work status, undergraduate course, and ethnicity. The study was conducted between October 2022 and July 2023 and had the participation of 2,034 students from two universities located in a humid subtropical climate in southern Brazil. During the field study, environmental variables were measured using a microclimatic station, while personal variables were obtained through student responses in electronic questionnaires. The analyses were performed for two modes of operation of the classrooms: natural ventilation and use of air-conditioning. In both cases, a statistically significant difference was observed when evaluating the thermal sensation for females and males, in which the mean thermal neutrality temperature of female students was higher than that of males. However, no statistically significant differences were observed between the students’ thermal sensation votes when considering different socioeconomic contexts.
In environments with similar physical parameters, thermal comfort and sensation feelings may differ indoors and outdoors. How indoor and outdoor thermal perception differ from each other remains ...unclear. This study compared and discussed 29,536 field survey data, including 19,191 sets of indoor data, and 10,345 sets of outdoor data, covering five Köppen climate zones during transitional seasons and summer. Indoor data points were collected from two databases: the ASHRAE Global Thermal Comfort II and the SCATs (Smart Controls and Thermal Comfort), while outdoor data points were collected from the RUROS database (Rediscovering the Urban Realm and Open Spaces) and five individual projects executed in Singapore, Hong Kong, Guangzhou, Changsha, and Tianjin. The concepts of neutral rate (NR) and comfort rate (CR) were developed to help categorize “neutral” and “comfort” across different studies. The results of this study show that people are less sensitive to changes in thermal environment outdoors than indoors. Moreover, thermal comfort cannot be simply treated as thermal neutral, particularly for outdoor spaces. Compared with MM (mixed-mode) and NV (naturally ventilated) spaces, outdoor space does not have the highest NR, but its CR is much higher, with a wide range of SET* (Standard Effective Temperature) corresponding to CR over 80 %, from 15.5 °C to 23.4 °C. In the Cfa (humid subtropical) climate zone, significantly higher CR are recorded for outdoor spaces, although the NR are similar or even lower than those of indoors. Natural thermal resources in the outdoor thermal environment may hold the key to extending indoor comfort ranges.
Display omitted
•People are less sensitive to changes in thermal environment outdoors than indoors.•Outdoor spaces have a lower neutral rate than mixed-mode and naturally-ventilated spaces.•Outdoors have a broader range of thermal parameters in the neutral zone than indoors.•Thermal comfort is easier to be achieved outdoors than indoors.
PDF
