aPMV Model Research Articles

Investigation of thermal comfort and preferred temperatures among rural elderly in Weihai, China: Considering metabolic rate effects

As the population ages, the thermal environment indoors for the elderly has garnered extensive attention. However, current research on thermal comfort for the elderly is not comprehensive, particularly for rural elderly individuals who experience unique thermal perceptions and adaptation behaviors due to physical changes. Moreover, metabolic rates, which are often overlooked in thermal comfort studies for the elderly, play a crucial role. A year-long survey of thermal comfort was conducted in the rural areas of Weihai, a coastal city in China's cold region, collecting 203 questionnaires. Three different values of metabolic rates (recommended values, estimated values, and values calculated using Basal Metabolic Rate and Physical Activity Ratio) were analyzed. The results demonstrate that the Basal Metabolic Rate and Physical Activity Ratio method provides predictions of thermal sensation that more closely align with actual thermal sensations. The adaptive coefficient of the aPMV model was found to be −0.38 in colder environments and 0.272 in warmer ones. Additionally, using PMV regression, TSV regression, and Griffiths' method, we calculated the local elderly's comfort temperatures to be 18.9 °C (15.43–22.57 °C), 19.3 °C (15.16–22.75 °C), and 21.63 °C (21.34–23.49 °C) respectively. This study introduces a straightforward method for calculating metabolic rates in elderly individuals, offering new insights for research on thermal comfort in the elderly and expanding the database for thermal comfort studies. It lays a foundation for future design and standardization of housing for rural elderly populations.

Adaptive thermal sensation evaluation model in tents for Western Sichuan Plateau of China: A field study

The Western Sichuan Plateau (WSP), which is located in the eastern margin of the Qinghai–Tibet Plateau, exhibits a unique climate featuring high altitude, thin air, low air temperature, and strong solar radiation. The local residents have developed a unique thermal sensation as a result of climatic adaptation, which cannot be accurately described using existing thermal sensation evaluation models. Therefore, we conducted a field study of the thermal sensation of the herdsmen living in tents in two typical areas located in the WSP. We measured the thermal environment parameters (air temperature, relative humidity, air speed, and black-globe temperature) on site and simultaneously conducted a questionnaire regarding the activity level, clothing insulation, and thermal sensation of the residents. A statistical regression analysis was performed, and the results showed a difference of 5.7 °C and 3.2 °C between the actual and predicted thermal neutral temperatures of the residents in the WSP during winter and summer, respectively. To improve the prediction accuracy, an adaptive predicted mean vote (aPMV) model incorporated with an adaptive coefficient was established for the WSP. The aPMV model can accurately predicted the thermal sensation levels of the local herdsmen living in tents.

Occupants’ Responses to Naturally Ventilated Buildings in Northern Guizhou, China

With the acceleration of urbanization, suggestions that are based on findings gathering from field studies on building refurbishment, new building design and building operation and maitenance are essential to achieve building energy saving and carbon emmision target. Therefore, a field investigation on thermal comfort and adaptive responses of occupants in naturally ventilated buildings were conducted during winer time in Zunyi. Without central heating system supply, the mean value of indoor air temperature is 14.86°C. But more than half of occupants (57.9%) who were satisfied with surrounding thermal environment. People are active to utilize various strategies to restore thermal comfort of their own. Adjusting clothing levels and using heating devices (e.g. fan heater, portable hand warmer, etc.) are the most popular adaptive behaviours helping them alleviate thermal discomfort caused by lower and humid thermal environment. The aPMV model is developed with adaptive coefficient of -0.33. The findings obtained from this investigation fill gaps in similar researches in northern Guizhou and provide guidelines on building indoor thermal environment improvement considering passive design strategies in this area.

Quantification of thermal environments and comfort expectations of residents in hostel dormitories during hot and humid days in Indian composite climate

ABSTRACT Improved quality of the thermal environment in hostel buildings will have a constructive role in the health, learning and overall productivity of student’s activities. We, therefore, conducted a thermal comfort field study in two mid-rise naturally ventilated (NV) hostel buildings during rainy days (August–September, 2018). The field study conducted for three consecutive weeks collecting 642 valid subjective responses (out of 679 sample) with objective information of thermal environments in 253 rooms at different floor levels. Statistical analysis of measured thermal variables was performed for assessing the effects on student’s thermal perception considering inter buildings effects, different weather conditions and different daytime duration, respectively. The study reported higher comfort bandwidth of 25.2–33.3°C for the studied group. Results of present study are compared with Predicted Mean Vote (PMV), Predicted Mean Vote with expectancy factor (PMVe) and adaptive Predicted Mean Vote (aPMV). aPMV is observed to be more reliable than PMV and PMVe to estimate the actual thermal sensation of occupants. Further, field study results are showing good agreement with the adaptive comfort models for NV buildings in India. Highlights Study quantifies thermal environments of two multi-storey NV hostel buildings. About 76% responses voted comfortable (±1 TS scale). Comfort bandwidth for occupant's ranges between 25.2–33.3°C for the study period. aPMV model of thermal comfort predicts TS more closely than PMV or PMVe model. Indian composite climate-specific adaptive models fit better with present data base.

Effect of inhabitant behavioral responses on adaptive thermal comfort under hot summer and cold winter climate in China

The hot summer and cold winter zone is an important area in China, accommodated with huge population and occupying a great amount of the lands. Due to the local climate and long-term economic conditions, the adaptive thermal sensation of local residents and the thermal regulation behaviors have unique characteristics. The thermal regulation behaviors involve complicated dynamic features and many influencing factors. However, due to the limited experimental testing conditions, it is greatly lack of relevant studies on the characteristics of different thermal regulation behaviors and their influences on both indoor thermal environment and the thermal comfort in this zone. Aiming at this, taking the residential buildings in Hangzhou city as the main object, a large-scale questionnaire surveys and measurements were conducted. The characteristics of various types of thermal regulation behaviors and the annual indoor thermal environment are analyzed. The effects of each regulation behavior on the indoor thermal environment and the adaptive thermal comfort are revealed. Rectified adaptive coefficients for the actual situation of Hangzhou residents are proposed and it is proved that the modified values can be used to evaluate the adaptive thermal sensation of the local residents more precise than the original ones used in the National Standard GB/T 50,785–2012. Incorporating the modified adaptive coefficient λ into the APMV model, the potential impact of summer ventilation on thermal comfort is quantified. The research results can provide theoretical support for the energy saving-oriented indoor thermal comfort research in the region.

Occupants’ thermal comfort and perceived air quality in natural ventilated classrooms during cold days

In north-west China, a number of university classrooms are natural ventilated during cold days when the prevailing mean outdoor air temperature is about 10 °C. This study investigated the students' thermal comfort and perceived air quality in natural ventilated university classrooms under such low outdoor temperature. 30 field-surveys were conducted in seven typical university classrooms during November 2017 in a sub-provincial city of Xi'an located in the north-west of China in the cold climate zone. A total of 992 responses from the university students ages between 17 and 22 years were received. The results showed that the thermal neutral temperature was 20.6 °C; the thermal comfort temperature range was from 19.5 to 21.8 °C; the occupants' preference temperature was 22.78 °C. The thermal dissatisfaction rate was lower than 10% when the indoor operative temperature ranges between 18.3 and 23.8 °C. The percentage of dissatisfied occupants for indoor air quality was higher than 20% in some cases and it was not related to CO2 concentration. Based on the survey results, it was found that the comfort temperature calculated by the aPMV model (China's thermal comfort model for free-running buildings) was higher than the experiment results. The occupant density affected the perceived air quality, but had no effect on thermal sensation. Moreover, the influence factors of perceived air quality including indoor temperature, enthalpy, thermal acceptability and thermal sensation were analyzed. Results showed that the occupants' acceptability of indoor air quality was mainly affected by thermal sensation.

Development Adaptive Predicted Mean Vote (aPMV) Model for Naturally Ventilated Buildings in Zunyi, China

Fanger’s predicted mean vote (PMV) model which is as a result of climate-chamber-based experiments is a good tool to evaluate indoor thermal comfort for air-conditioned buildings in global wide. However, PMV model has defect of predicting people’s real thermal sensation under non-air-conditioned conditions. It is reflected by the significant discrepancies between PMV values and Actual Mean Vote (AMV) values. The aim of this study is to develop an Adaptive Predicted Mean Vote (aPMV) Model on the basis of ‘black box’ theory considering occupants’ adaptations to improve prediction performance. A field study was carried out in naturally ventilated educational buildings in Zunyi, China. The developed aPMV model produces more reliable results and shows better prediction performance, comparing with values predicted by PMV model. It indicates that aPMV model is of great benefit to connect traditional PMV model and adaptive comfort model and consequently to provide guidance on building design, operation and maintenance, which contribute to achieve building energy conservation and emission reduction target.

Seasonal variation of thermal sensations in residential buildings in the Hot Summer and Cold Winter zone of China

Seasonal variation of thermal comfort demands directly affects the energy needs for heating or cooling purpose. In previous studies, the differences of neutral temperatures between summer and winter were revealed, but the studies on the difference of human thermal adaption in transitional seasons are insufficient. To clarify this, this paper presents a year-long survey which was carried out in 505 residential buildings in six cities located in the Hot Summer and Cold Winter (HSCW) zone of China involving 11,524 subjects. Results show a significant difference of adaptive responses in different seasons, and a lag of behavioral responses behind climate change in transitional seasons is observed. Occupants not only adjust clothing insulation according to air temperature in different seasons, but also actively control indoor air movement, including closing/opening windows and using fans. The seasonal, monthly and daily neutral temperatures are studied, implying that occupants’ thermal experience has significant effect on their thermal comfort by behavioral, physiological and psychological paths. According to the comparative study, the running mean air temperature method and aPMV model are recommended in free-running space. The findings provide scientific evidence to the concept that dynamic thermal comfort temperature range should be considered in evaluation of indoor thermal environment.

Thermal environment in the cotton textile workshop

Workers with years of work experience and students with rarely entering into the cotton textile workshop were chosen as subjects to investigate the thermal environment in the cotton textile workshop. Questionnaires have been applied to obtain actual thermal sensation and personal information. In this period, thermal comfort parameters were measured to derive the predicted mean vote (PMV). The adaptive predicted mean vote (aPMV) model and the extended predicted mean vote (ePMV) model were also introduced to compare with the actual mean vote (AMV) and the PMV. Compared with the PMV model and the ePMV model, the aPMV model is more suitable to describe the actual thermal environment in the cotton textile workshop. According to the actual thermal environment and thermal acceptability (TA) survey, the aPMV range for the worker in the cotton textile workshop was recommended to find the environment thermally acceptable to textile worker, which was applied to a graphic of acceptable zone for the cotton textile workshop. The acceptable zone is defined by the combinations of the key factors for thermal sensation, thermal adaptation and technological requirement, so it is suitable to be applied to the cotton textile workshop.

A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)

This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ( λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.