Data-driven adaptive GM(1,1) time series prediction model for thermal comfort.

In this paper, the future prediction of predicted mean vote (PMV) index of indoor environment is studied. PMV is the evaluation index used in this paper to represent the thermal comfort of human body. According to the literature, the main environmental factors affecting PMV index are temperature, humidity, black globe temperature, wind speed, average radiation temperature, and clothing surface temperature, and there is a complex nonlinear relationship between the six variables. Due to the coupling relationship between the six parameters, the PMV formula can be simplified under specific conditions, reducing the monitoring of variables that are difficult to observe. Then, the improved grey system prediction model GM(1,1) with optimized selection dimension is used to predict the future time of PMV. Due to the irregularity, uncertainty and fluctuation of PMV values in time series, based on the original GM(1,1) time series prediction, an adaptive GM(1,1) improved model is proposed, which can continuously change with time series and enhance its prediction accuracy. By contrast, the improved GM(1,1) model can be derived from the sliding window of the adaptive model through changes in the dataset and get better model grades. It lays a foundation for the future research on the predicted index of PMV, so as to set and control the air conditioning system in advance, to meet the intelligence of modern intelligent home and humanized function of sensing human comfort.

Fuzzy Logic Controlled Simulation in Regulating Thermal Comfort and Indoor Air Quality Using a Vehicle Heating, Ventilation, and Air-Conditioning System.

Conventional heating ventilation and air-conditioning (HVAC) controllers have been designed to mainly control the temperature of a confined compartment, such as a room or a cabin of a vehicle. Other important parameters related to the thermal comfort and indoor air quality (IAQ) of the confined compartment have often been ignored. In this project, IAQ in the vehicle cabin was represented by its carbon dioxide (CO2) concentration, and the occupants' thermal comfort levels were estimated with the predicted mean vote (PMV) index. A new fuzzy logic controller (FLC) was designed and developed using the MATLAB fuzzy logic toolbox and Simulink to provide a nonlinear mapping between the measured values, i.e., PMV, temperature, CO2, and control parameters (recirculation flaps, blower's speed, and refrigerant mass flow rate) of a vehicle HVAC system. The new FLC aimed to regulate both in-cabin PMV and CO2 values without significantly increasing overall energy consumption. To evaluate the effectiveness of the proposed FLC, a cabin simulator was used to mimic the effects of different HVAC variables and indoor/outdoor environmental settings, which represented the in-cabin PMV and IAQ readings. Results demonstrated that the new FLC was effective in regulating the in-cabin PMV level and CO2 concentration, at desirable levels, by adaptively controlling the opening and closing of the recirculation flap based on in-cabin temperature and CO2 readings, while maintaining an average-to-good energy consumption level. The proposed FLC could be applied to a large variety of HVAC systems by utilizing low-cost sensors, without the need to significantly modify the internal design of the HVAC system.

Modification and verification of the PMV model to improve thermal comfort prediction at low pressure.

The human body's thermal physiology changes due to atmospheric pressure, which significantly impacts the perception of thermal comfort. To quantify this effect, an improved version of the Predicted Mean Vote model (PMVp), was developed in this study to predict human thermal sensation under low atmospheric pressure conditions. The study employed environmental conditions of 0km/26°C, 3km/26°C, 4km/26°C, and 4km/21°C. Thirteen subjects were continuously monitored for exhaled CO2, inhaled O2, ambient temperature (ta), relative humidity (RH), air velocity (V), black globe temperature (tg), and altitude (H). The predictive performance of PMVp was evaluated by comparing the experimental results from this study with previous experiments. The findings demonstrate that PMVp exhibits lower root-mean-square errors (RMSE) than the original PMV model. Under the four experimental conditions, the RMSE values for PMVp were 0.311, 0.408, 0.123, and 0.375, while those for PMV were 1.251, 1.367, 1.106, and 1.716, respectively. Specifically, at a temperature range of 21∼27°C (altitude: 941m), the RMSE of PMVp (0.354) was smaller than PMV's. Furthermore, the study analyzed the sensitivity of PMVp to input parameters at an altitude of 4 km. PMVp exhibited considerable sensitivity to the metabolic rate (M) and thermal insulation of clothing (ICL). Consequently, a simple sensitivity scale was established: M>ICL>Ta≈V>Tr>H≈RH, indicating the relative importance of these parameters in influencing PMVp's response. The research findings provide comprehensive knowledge and a useful reference for developing a standard to design and evaluate indoor thermal environments in the plateau region.

[Evaluation of thermal environment and human thermal comfort in 8 types of public places from 2019 to 2021].

Objective: To evaluate the thermal environment of different types of public places and the thermal comfort of employees, so as to provide scientific basis for the establishment of microclimate standards and health supervision requirements. Methods: From June 2019 to December 2021, 50 public places (178 times) of 8 categories in Wuxi were selected, including hotels, swimming pools (gymnasiums), bathing places, shopping malls (supermarkets), barber shops, beauty shops, waiting rooms (bus station) and gyms. In summer and winter, microclimate indicators such as temperature and wind speed were measured in all kinds of places, combined with the work attire and physical activity of employees in the places. Fanger thermal comfort equation and center for the built environment (CBE) thermal comfort calculation tool were used to evaluate the predicted mean vote (PMV), predicted percent dissatisfied (PPD) and standard effective temperature (SET) according to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 55-2020. The modification effects of seasonal and temperature control conditions on thermal comfort were analyzed. The consistency of GB 37488-2019 "Hygienic Indicators and Limits in Public Places" and ASHRAE 55-2020 evaluation results on thermal environment was compared. Results: The thermal sensation of hotel, barber shop staff and the gym front-desk staff were moderate, while the thermal sensation of swimming place lifeguard, bathing place cleaning staff and gym trainer were slightly warm in summer and winter. Waiting room (bus station) cleaning and working staff, shopping mall staff felt slightly warm in summer and moderate in winter. Service staff in bathing places felt slightly warm in winter, while staff in beauty salons felt slightly cool in winter. The thermal comfort compliance of hotel cleaning staff and shopping mall staff in summer was lower than that in winter (χ(2)=7.01, 7.22, P=0.008, 0.007). The thermal comfort compliance of shopping mall staff in the condition of air conditioning off was higher than that in the condition of air conditioning on (χ(2)=7.01, P=0.008). The SET values of front-desk staff in hotels with different health supervision levels were significantly different (F=3.30, P=0.024). The PPD value and SET value of the front-desk staff, and the PPD value of cleaning staff of hotels above three stars were lower than those of hotels below three stars (P<0.05). The thermal comfort compliance of front-desk staff and cleaning staff in hotels above three stars was higher than that in hotels below three stars (χ(2)=8.33, 8.09, P=0.016, 0.018). The consistency of the two criteria was highest among waiting room (bus station) staff (100.0%, 1/1) and lowest among gym front-desk staff (0%, 0/2) and waiting room (bus station) cleaning staff (0%, 0/1) . Conclusion: There are different degrees of thermal discomfort in different seasons, under the condition of air conditioning and health supervision, and the microclimate indicators can not fully reflect the thermal comfort of human body. The health supervision of microclimate should be strengthened, the applicability of health standard limit value should be evaluated in many aspects, and the thermal comfort of occupational group should be improved.

Determination of thermal sensation levels for Koreans based on perceived temperature and climate chamber experiments with hot and humid settings.

People perceive thermal sensation differently despite the same temperature value of thermal comfort index depending on various factors such as climate, culture, and physiological characteristics. The use of the thermal comfort index without optimization may lead to biases in assessment of thermal stress and sensation. This study aims to derive the perceived temperature (PT) ranges of thermal sensation levels related to heat stress for Koreans. The experiments were designed using a controlled environmental chamber to derive the PT ranges and were performed with subjects who are residents of Seoul, South Korea. The experiments were carried out in the summers of 2017 and 2018, and the thermal sensation votes were surveyed from 19 subjects whose mean age, height, weight, and body mass index were 22.5 years, 171 cm, 72 kg, and 23 kg⋅m-2, respectively. The derived PT ranges for Koreans led to a better performance than the reference PT ranges for Germans based on the results of validation. The thresholds of 'Warm,' 'Hot,' and 'Very hot' thermal sensation classes for Koreans were 28 °C, 36 °C, and 43 °C, respectively: higher than those for Germans. The results indicate that Koreans may have higher heat resistance or lower heat sensitivity than Germans.

Investigation of the effects of face masks on thermal comfort in Guangzhou, China.

Wearing masks to study and work places has become a daily protective measure during the COVID-19 pandemic. In the summer of 2021, environmental parameters were monitored, and students in a university library in Guangzhou, China, were surveyed to analyze the possible symptoms of wearing masks for a long time, and to assess the sensitivity of various body parts to the environmental parameters. Concurrently, the preference of subjects wearing masks for various environmental parameters was also analyzed. Additionally, the relationship between thermal sensation and thermal index was analyzed to identify acceptable and comfortable temperature ranges. The expected duration of wearing masks was counted. Subjects wearing masks had greater requirements for environmental comfort, and reported increased thermal discomfort of the face and head, compared to those without masks. More than 70% of the subjects wearing masks reported that they experienced discomfort on their faces. Among the subjects who experienced discomfort, 62.7% reported that facial fever was the main symptom; while some reported symptoms of dyspnea (25.4%) and rapid heartbeat (9.1%). More than 75% of the subjects were expected to wear masks for 2.0 h or less. Evaluation of environmental thermal sensation, including overall, facial, and head thermal sensation, differed among subjects who wore and did not wear masks. The indexes of neutral Operative temperature/Standard Effective Temperature (T op /SET*) and preferred T op /SET* were lower among subjects with masks than among those without masks. The neutral T op /SET* deviation was 0.3 °C, and the preferred T op /SET* deviation was 0.5 °C. Additionally, the acceptable and comfortable temperature zones differed between the two cases. The subjects who wore masks preferred colder temperatures. These findings indicated that the environmental parameters should be adjusted to improve the thermal comfort of the human body while wearing masks in work or study places.

Adaptive-rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient.

Thermal adaptations, as feedbacks of occupants to physical stimuli, extend thermal comfort zone thereby reducing building energy consumption effectively. The rational approach models thermal comfort from the perspective of the body's heat balance, but is limited in explaining the thermal adaptations. The adaptive approach of modeling thermal comfort can fully account for the thermal adaptations, but ignores the body's heat balance. To improve thermal comfort prediction, this study proposes an adaptive-rational thermal comfort model, that is, an adaptive predicted mean vote with a variable adaptive coefficient (termed as arPMV). By linearly linking the negative feedback effects of the thermal adaptations to the ambient temperature according to the adaptive approach, the variable adaptive coefficient is linearly related to the reciprocal of the ambient temperature with two constants. The variable adaptive coefficient is determined by explicitly quantifying the two constants as the functions of the predicted mean vote, thermal sensation vote, and ambient temperature. The proposed arPMV is validated for naturally ventilated, air-conditioned, and mixed-mode buildings, with the mean absolute error and the robustness of the thermal sensation prediction reduced by 24.8%-83.5% and improved by 49.7%-83.4%, respectively.

IoT Based Architecture for Model Predictive Control of HVAC Systems in Smart Buildings.

The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closed-loop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to end-users. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related set-points of the system; while comfort and environmental indices are transferred via the Internet and displayed on the end-users' interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach.

Field Study on Indoor Thermal Environments of Monastic Houses and Thermal Comfort of Monks.

Monastic houses are an essential part of the Tibetan monastic system in China. In this study, the monastic houses of Labrang in the Tibetan region of Gannan were used as the research objects. Physical parameters such as indoor temperature, humidity, and radiation temperature of the monastic houses were measured. The measured results were compared with the standard values, while the air temperature was linearly fitted using TSV, PMV, and aPMV. The results show that the temperature inside and outside the monastic houses fluctuates considerably; the theoretical thermal neutral temperature of the tested monks in winter is 22.46 °C, which is higher than the measured thermal neutral temperature in winter of 16.43 °C. When analyzing the results, it was found that the local climate, dress code, and the monks' specific habits all impact the perception of thermal comfort, which creates a discrepancy between the accurate results and the standard values. The above findings provide a more comprehensive reference for the thermal comfort requirements of the monks in cold areas, which can be used as a guide for the improvement and evaluation of the monastic houses in cold areas.

A Physiological-Signal-Based Thermal Sensation Model for Indoor Environment Thermal Comfort Evaluation.

Traditional heating, ventilation, and air conditioning (HVAC) control systems rely mostly on static models, such as Fanger's predicted mean vote (PMV) to predict human thermal comfort in indoor environments. Such models consider environmental parameters, such as room temperature, humidity, etc., and indirect human factors, such as metabolic rate, clothing, etc., which do not necessarily reflect the actual human thermal comfort. Therefore, as electronic sensor devices have become widely used, we propose to develop a thermal sensation (TS) model that takes in humans' physiological signals for consideration in addition to the environment parameters. We conduct climate chamber experiments to collect physiological signals and personal TS under different environments. The collected physiological signals are ECG, EEG, EMG, GSR, and body temperatures. As a preliminary study, we conducted experiments on young subjects under static behaviors by controlling the room temperature, fan speed, and humidity. The results show that our physiological-signal-based TS model performs much better than the PMV model, with average RMSEs 0.75 vs. 1.07 (lower is better) and R2 0.77 vs. 0.43 (higher is better), respectively, meaning that our model prediction has higher accuracy and better explainability. The experiments also ranked the importance of physiological signals (as EMG, body temperature, ECG, and EEG, in descending order) so they can be selectively adopted according to the feasibility of signal collection in different application scenarios. This study demonstrates the usefulness of physiological signals in TS prediction and motivates further thorough research on wider scenarios, such as ages, health condition, static/motion/sports behaviors, etc.

Performance Evaluation of Particulate Matter and Indoor Microclimate Monitors in University Classrooms under COVID-19 Restrictions.

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 µg m-3 and PM10 ranged between 30 and 42 µg m-3. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10-4 mg/kg-day (CV = 14.3%) for the 20-40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.

A method for predicting the Actual Percentage of Dissatisfied (APD) through a simple proposition of thermal comfort zones in a working environment.

BACKGROUND: Over the last few decades, there has been a concern to improve the quality of indoor work environments and increase energy efficiency as people spend much of their time in such settings. OBJECTIVE: This study analyzed a group of women developing sedentary activities to determine the Actual Percentage of Dissatisfied (APD) in the environment, considering that all people who voted any value other than zero on the seven-point scale are deemed dissatisfied. METHODS: After this analysis, using the probit regression model, hot and cold air temperature curves were plotted so as to determine in which situation the number of people dissatisfied with the environment is minimal. RESULTS: The results showed an APD of 52.31%, which is different from the ADP recommended by ISO 7730 (2005) [-0.5 < PMV < + 0.5, PPD < 10% ]. The probit analysis using the cut of 10% as dissatisfied, according to category B of ISO 7730 (2005), showed a comfort temperature of 21.1°C, with a comfort temperature range from 19.61 to22.61°C. CONCLUSIONS: Using the fraction of people dissatisfied with the environment (52.31%) as the cutoff, when the air temperature is equivalent to 20.2°C, the lowest percentage dissatisfied by the cold and heat in the environment occurs simultaneously.

The effect of personal protective equipment on thermal stress: An experimental study on firefighters.

BACKGROUND: Various parameters can affect the performance of firefighters. Thermal stress in firefighters is one of the most important harmful factors, which causes impaired performance and subsequent occupational accidents. Therefore, this study aimed to evaluate the effect of personal protective equipment (PPE) on thermal stress in firefighters. MATERIALS AND METHODS: This descriptive-analytical cross-sectional study was performed on 30 firefighters. Heart rate, metabolism and temperature parameters were measured with and without using PPE in a simulated standard chamber. Then, the two indices of predicted mean vote (PMV) and predicted percentage dissatisfied (PPD) were calculated. Data analysis was performed using SPSS version 22.0. RESULTS: The results showed that PPE-induced weight directly increased heart rate and indirectly led to an increase in metabolism and temperature as well as significant changes in PMV and PPD indices (p < 0.001). In addition, our results showed that the effect of thermal resistance of clothing (Clo) on PMV and PPD indices was very high (p < 0.001). CONCLUSION: The findings of the study indicated that heat stress in firefighters is influenced by PPE weight and thermal resistance of clothing. Therefore, cooling vests can be used to reduce the thermal stress induced by temperature rise resulted from metabolism, PPE weight and thermal resistance of clothing. Reduced thermal stress will lead to the cooling of body temperature to acceptable levels of PMV and PPD.

Evaluation of thermal environment and human thermal comfort in 8 types of public places from 2019 to 2021 / 中华劳动卫生职业病杂志

Objective: To evaluate the thermal environment of different types of public places and the thermal comfort of employees, so as to provide scientific basis for the establishment of microclimate standards and health supervision requirements. Methods: From June 2019 to December 2021, 50 public places (178 times) of 8 categories in Wuxi were selected, including hotels, swimming pools (gymnasiums), bathing places, shopping malls (supermarkets), barber shops, beauty shops, waiting rooms (bus station) and gyms. In summer and winter, microclimate indicators such as temperature and wind speed were measured in all kinds of places, combined with the work attire and physical activity of employees in the places. Fanger thermal comfort equation and center for the built environment (CBE) thermal comfort calculation tool were used to evaluate the predicted mean vote (PMV), predicted percent dissatisfied (PPD) and standard effective temperature (SET) according to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 55-2020. The modification effects of seasonal and temperature control conditions on thermal comfort were analyzed. The consistency of GB 37488-2019 "Hygienic Indicators and Limits in Public Places" and ASHRAE 55-2020 evaluation results on thermal environment was compared. Results: The thermal sensation of hotel, barber shop staff and the gym front-desk staff were moderate, while the thermal sensation of swimming place lifeguard, bathing place cleaning staff and gym trainer were slightly warm in summer and winter. Waiting room (bus station) cleaning and working staff, shopping mall staff felt slightly warm in summer and moderate in winter. Service staff in bathing places felt slightly warm in winter, while staff in beauty salons felt slightly cool in winter. The thermal comfort compliance of hotel cleaning staff and shopping mall staff in summer was lower than that in winter (χ(2)=7.01, 7.22, P=0.008, 0.007). The thermal comfort compliance of shopping mall staff in the condition of air conditioning off was higher than that in the condition of air conditioning on (χ(2)=7.01, P=0.008). The SET values of front-desk staff in hotels with different health supervision levels were significantly different (F=3.30, P=0.024). The PPD value and SET value of the front-desk staff, and the PPD value of cleaning staff of hotels above three stars were lower than those of hotels below three stars (P<0.05). The thermal comfort compliance of front-desk staff and cleaning staff in hotels above three stars was higher than that in hotels below three stars (χ(2)=8.33, 8.09, P=0.016, 0.018). The consistency of the two criteria was highest among waiting room (bus station) staff (100.0%, 1/1) and lowest among gym front-desk staff (0%, 0/2) and waiting room (bus station) cleaning staff (0%, 0/1) . Conclusion: There are different degrees of thermal discomfort in different seasons, under the condition of air conditioning and health supervision, and the microclimate indicators can not fully reflect the thermal comfort of human body. The health supervision of microclimate should be strengthened, the applicability of health standard limit value should be evaluated in many aspects, and the thermal comfort of occupational group should be improved.

Associations between Thermal and Physiological Responses of Human Body during Exercise.

In this study, thermal behaviours of the athletes were investigated with respect to thermal comfort and exercise intensity. The relationship between an index for analysing thermal comfort (Predicted Mean Vote: PMV) and Rating of Perceived Exertion (RPE) which shows exercise intensity and exhaustion level was evaluated. Eleven moderately trained male athletes ( V ˙ O2max 54 ± 9.9 mL∙min-1∙kg-1) had volunteered for the study (age: 22.2 ± 3.7 years; body mass: 73.8 ± 6.9 kg; height: 181 ± 6.3 cm; Body surface area (BSA): 1.93 ± 0.1 m²; body fat: 12.6% ± 4.2%; V ˙ O2max: 54 ± 9.9 mL∙min-1∙kg-1). Experiments were carried out by using a cycle ergometer in an air-conditioned test chamber which provided fresh air and had the ability to control the temperature and relative humidity. The study cohort was divided into two groups according to maximal oxygen consumption levels of the participants. Statistical analyses were conducted with the whole study cohort as well as the two separated groups. There was a moderate correlation between PMV and RPE for whole cohort (r: -0.51). When the whole cohort divided as low and high aerobic power groups, an average correlation coefficient at high oxygen consumption cohort decreased to r: -0.21, while the average correlation coefficient at low oxygen consumption cohort increased to r: -0.77. In conclusion, PMV and RPE have a high correlation in less trained participants, but not in the more trained ones. The case may bring to mind that thermal distribution may be better in high aerobic power group in spite of high RPE and thus the relation between PMV and RPE is affected by exercise performance status.