Predicted Mean Vote Values Research Articles

Energy and exergy analyze of different air distributions in a residential building

To improve the living and sleeping quality for human beings, air conditioning is widely applied to maintain a comfortable indoor environment in bedrooms. However, most current air conditioning methods in bedrooms are based on mixing ventilation, which is low efficiency due to the uniform environment created by this ventilation method. In this study, stratum ventilation is introduced applied in a sleeping environment to improve ventilation performance. To better analyze the application potential of stratum ventilation, three ventilation methods are compared, including mixing ventilation, displacement ventilation and stratum ventilation. Based on computational fluid dynamics technology, the energy and exergy efficiency of the three air distribution methods are conducted and compared. The results show that stratum ventilation provides a nonuniform environment both in the vertical and horizontal directions in a typical sleeping environment with a higher energy and exergy efficiency than the mixing ventilation and displacement ventilation. When the predicted mean vote value in the occupied zone equals zero, energy consumption and exergy loss of stratum ventilation reduce 10% and 15.6% in comparison with mixing ventilation respectively. The energy consumption difference of stratum ventilation and displacement ventilation is not significant, but the exergy loss reduces 6.2%, with the predicted mean vote equals zero in the occupied zone. In addition, the energy utilization coefficients of stratum ventilation, displacement ventilation and mixing ventilation are 1.3, 1.03 and 0.89 respectively. The results show that stratum ventilation has a high potential for energy-saving in a sleeping environment.

Experimental investigation of the effect of clothing insulation on thermal comfort indices

Clothing insulation is one of the six parameters used to calculate the predicted mean vote (PMV) and the new standard effective temperature (SET*). Various studies have confirmed the effects of airspeed, wind direction, and posture on clothing insulation. However, there is a lack of clarity on how these factors affect the prediction of thermal comfort by impacting clothing insulation. This study presents the clothing insulation of eight sets of current typical clothing ensembles under various airspeeds and wind directions using a manikin experiment. Furthermore, the effects of airspeed, wind direction, and posture on the calculation of PMV and SET* were investigated. The results of the study highlight that (1) the clothing insulation for the standing posture was 10% higher than that of the sitting posture; The clothing insulation decreased with the increase in airspeed. (2) The PMV and SET* for the standing posture were higher than those of the sitting posture. The PMV value under the crosswind was, at the maximum, 0.23 larger than that under other wind directions. The SET* for the crosswind was, at a maximum, 0.85 °C higher than that under other wind directions. (3) The PMV and SET* values considering the reduction of clothing insulation due to airspeed had smaller values than those that do not consider the reduction of clothing insulation. Thus, it is essential to consider the conditions of wind direction, posture, and reduction of clothing insulation caused by airspeed to achieve reliable prediction of thermal comfort.

Experimental Study and Analysis of Thermal Comfort in a University Campus Building in Tropical Climate

This study presents the evaluation of the performance and acceptability of thermal comfort by students in the classrooms of a university building with minisplit-type air-conditioning systems, in a tropical climate. To carry out the study, temperature and humidity measurements were recorded, both outside and inside the selected classrooms, while the students were asked to complete thermal surveys on site. The survey model is based on the template proposed by Fanger and it was applied to a total number of 584 students. In each classroom, the Predicted Mean Vote (PMV) and the Predicted Percentage Dissatisfied (PPD) were estimated according to Fanger’s methodology, as well as the Thermal Sensation Vote (TSV) and the Actual Percentage Dissatisfied (APD), which were obtained from the measurements and the surveys. The results of this study showed that the PMV values, although they may vary with the insulation of the clothing, do not affect the TSV. Furthermore, comparing PMV vs. TSV scores, a 2 °C to 3 °C difference in operating temperature was found, whereby the thermal sensitivity for TSV was colder, so it could be assumed that the PMV model overestimates the thermal sensitivity of students in low-temperature conditions. In addition, an acceptability by 90% with thermal preferences between 23 °C and 24 °C were also found. These results indicate that it is possible to increase the temperature set point in minisplit-type air-conditioning system from 4 °C to 7 °C with respect to the currently set temperatures, without affecting the acceptability of the thermal environment to the students in the building.

Efficient PMV computation for public environments with transient populations

Thermal Comfort (TC) is an important environmental parameter strongly affecting human well-being. Nevertheless, it is not being routinely monitored in public environments (e.g., hospitals and shopping malls) characterized by high occupancy and transient populations. Furthermore, the unique computational demands of TC models for such environments are less studied. We establish large datasets representing such settings and corresponding Predicted Mean Vote (PMV) values as calculated by ISO7730 (Fanger’s model). We then demonstrate that PMV values can be reasonably estimated using linear regressions if the full PMV range is piecewise segmented. Support Vector Machine (SVM) regression provides certain accuracy improvement over linear that becomes marginal for sufficiently small segments. However, while SVM computation becomes orders of magnitude slower than ISO7730 algorithm for large datasets, linear computation becomes exponentially faster. Furthermore, the latter does not require unique expertise in mathematics/TC and constitutes an excellent first-step checkpoint to more accurate algorithms adapting the environment to transient populations. Spatial/temporal flexible segment resolution adds compliance with dynamic demands. To conclude, PMV piecewise linear regression can greatly expedite implementing TC and thus conserving energy in public environments, particularly those exposed to extreme climates. To this end, future TC models must consider computation efficiency besides accuracy.

Investigation of indoor air quality and thermal comfort condition in airport terminal buildings

PurposeThis paper aims to measure the thermal comfort conditions and indoor air quality parameters, through on-site measurements taken in the areas mostly occupied by the passengers and airport staff. Terminal buildings consist of areas with various functions. Heating, ventilation and air conditioning requirements vary from area to area, thus leading to challenges in the management of indoor environment quality. Therefore, the study focuses on investigating the indoor environment conditions in various areas of the terminal buildings.Design/methodology/approachIn this study, the thermal comfort and indoor air quality were evaluated based on the parameters [CO2 concentration, relative humidity, temperature, predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD)] collected for summer 2019 from different zones inside the International Dalaman Airport terminal building located in the southwest of Turkey. The measurements were performed in the areas mostly occupied by the airport staff and passengers (check-in area, security control areas, international departure lounge, domestic departure lounge and baggage claim hall).FindingsAs a result of the study, it was observed that the CO2 concentration was 480–965 ppm, the relative humidity was 51.9–75.8% and the temperature was in the range of 23.9°C–28.3°C inside the airport terminal. The PMV values were determined to be in the range of −0.23 to 0.67, and the PPD values 5–15%, which are used to measure the thermal comfort conditions.Originality/valueThere has been limited study on the determination of the indoor air quality in airport terminals and the investigation of the thermal comfort conditions. However, in this study, indoor air quality and thermal comfort conditions were determined by on-site measurements in the five mostly occupied areas by passengers and employees in the terminal building.

The virtual in-situ calibration of various physical sensors in air handling units

Systematic and random errors for working sensors in building systems can seriously affect the operation performance and have a significant negative impact on energy efficiency and indoor comfort. However, the traditional method for sensor calibration is very time-consuming and labor-intensive. Therefore, a virtual in-situ calibration (VIC) method was proposed based on Bayesian inference that can simultaneously correct systematic errors for multiple working and greatly reduce random errors. Using an actual system with reheating of the primary return air, we introduced the principle of the VIC method and its application. The robustness and applicability of the method were verified under six normal and four extreme operating conditions. The effects of sensor system errors on the energy consumption of the building system and on indoor thermal comfort were also studied. The results showed that under various working conditions, systematic and random errors for all the working sensors in the system were accurately identified. On average, the systematic and random error after calibration were reduced by approximately 95% and 60%, respectively. Compared to operating conditions with systematic errors, the average energy consumption after VIC was reduced by more than 50%, and predicted mean vote values after calibration were within the comfort zone.

Use of outdoor microclimate simulation maps for a planting design to improve thermal comfort

The availability of thermal comfort conditions outdoors is considered one of the necessities of being a livable city. There is a relationship between outdoor thermal comfort and microclimate regulation potential of tree species. This study aims to form a proposal planting design, which may enhance outdoor thermal comfort in a university campus. In this study, thermal comfort has been identified by Predicted Mean Vote (PMV) index and ASHRAE scale and the analysis has been performed with ENVI-met software. The study has been carried out in three stages: a) Evaluation of the campus master plan in terms of thermal comfort, b) Formation of planting design, where six tree species have been used to improve thermal comfort and evaluation of this offer in terms of thermal comfort c) Comparison of the findings obtained in the first two stages and manifestation of information, which may be used in the activities aimed at improving thermal comfort. According to the findings obtained in the study, with a planting design in which tree species are located according to their characteristics, PMV values increase by 0.50 on average in the coldest hours of winter and decrease by 1.75 on average in the hottest hours of summer.

Thermal performance analysis of a naturally ventilated system using PMV models for different roof inclinations in composite climatic conditions

Computational analysis has become a very useful tool for a detailed understanding of building physics before actual building constructions and for predicting such system behaviors where massive urbanizations are envisaged. The present study attempts to describe the efficacies of CFD as an “analysis led design” tool, where a computationally modeled cross-ventilation system with asymmetric positions of openings is analyzed to estimate the comfort zones according to the PMV (predicted mean vote) model for evaluating the influence due to roof inclinations, thereby providing opportunities in rectifying any anomalies pertaining to it, prior to the actual construction. A numerical analysis has been carried out to examine the effects of natural ventilation in a wind-driven system using the established extended PMV model (PMVe). The study focuses on thermal comfort and the effect of roof inclination angle over the three different weather conditions in Delhi—winter season (high humidity and low temperature), summer season (low humidity and high temperature) and monsoon season (high humidity and mild temperature). Appropriate roof inclination angles provide a better ventilation rate and air distribution pattern, which significantly affects comfort condition. Study shows that for winter season, the PMV values decrease as the roof inclination angle is increased and the ventilation rate for 30° inclined roof increases about 16% as compared to the flat roof case, while PMV values increase with roof inclination for summer season, signifying zone of discomfort. It also concludes that a moderate roof inclination is beneficial for monsoon season.

Analysis for determining the impact of air quality and thermal comfort in an enclosed cavity

Quality of the indoor environment has been in the focus of many researchers since decades. People spend about 80–90% of the total time within buildings which may be an office, house, gymnasium, etc. So, there is a need to check the environmental conditions on the basis of thermal comfort as well as the condition of indoor air. Although, condition of air and thermal comfort are considered to be interdependent, as if the quality of air is not good, it will result in uncomfortable dwelling conditions and vice-versa. Many researchers have tried to evaluate the thermal comfort and quality of indoor air theoretically with the help of the thermal sensation scale as per the Fanger model. Although, a limited simulation work is published describing the effect of airflow generated from the ceiling fan on the quality of indoor air in the building envelope. This communication is an attempt to examine the impact of indoor air quality by considering the influence of temperature, velocity and humidity level of air, inside an enclosed cavity for a specific location. This work involves the use of an SST k-ω based turbulence model in order to study the turbulent behavior of airflow generated by ceiling fan. The radiation model has been considered in order to study the temperature variation inside the cavity. It also incorporates the evaluation of relative humidity and PMV-PPD inside the enclosed cavity for attaining comfortable dwelling conditions. Investigation revealed the average predicted mean vote value to be −0.89, which can be considered as an ideal condition for comfortable dwelling.

Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

AbstractObjectivesThe aim of this study was to analyse the thermal discomfort of outdoor environments in two climates of Iran using physiological equivalent temperature (PET), predicted mean vote (PMV) indices and Universal Thermal Climate Index (UTCI).MethodsIn this study, the meteorological data recorded by the meteorological organisation in a 15‐year period, including temperature, air velocity, cloudiness, relative humidity and water vapour pressure, in two different climates of Iran were surveyed. According to classification of the Köppen, Arak as a representative of a semi‐arid and cold climate and Bandar Abbas as a representative of a hot and dry climate were used to calculate thermal indices. The PMV index was based on the ASHRAE 7‐point thermal sensation scale, and the values of PMV and PET indices were extracted using Rayman1.2 software. The values of the UTCI were calculated using BioKlima 2.6 software.ResultsThe results showed that the maximum and minimum temperatures in two climates were related to July and January, respectively. In Arak, the means of the UTCI, PET and PMV indices were 14.41 ± 11.5, 15.81 ± 1.23 and −0.77 ± 2.15, respectively. In Bandar Abbas as well, the mean of the UTCI, PET and PMV indices were 22.56 ± 9, 22.73 ± 7.7 and 0.73 ± 7.7, respectively. In Arak, there was moderate heat stress to moderate cold stress in this region, whereas in Bandar Abbas, the days had a strong heat stress to low cold stress. There are very strong correlations between the indices used for two different climates.ConclusionThe bioclimatic comfort indices used were able to demonstrate the comfort and discomfort of people during different months of the year in two surveyed climates, and despite trivial differences, they provided relatively uniform representations of climate comfort for surveyed cities. Using thermal comfort indices, high‐risk areas can be identified, and appropriate measures can be adopted to reduce the effects of the changes.

Thermal comfort and mortality in a dry region of Iran, Kerman; a 12-year time series analysis

This study was conducted in order to explore the effect of thermal comfort on all-cause mortality using three indices in different lag times, in a semi-arid to dry region of Iran. Three thermal comfort indices based on the energy balance of the human body including physiologically equivalent temperature (PET), predicted mean vote (PMV), and standard effective temperature (SET) were used to assess the effects of thermal comfort on mortality. Distributed lag non-linear models were used to assess the relation. The natural cubic spline was chosen as the basis function for the space of predictors and lags, with 4 degrees of freedom. All three indices showed the same pattern in general, but the relative risk for PMV values were more than the other indices in different lags. For all three indices, lag 0 had the highest relative risk of mortality in warm and hot indices. The relative risk for warm and hot values was more than cool and cold values in lag 0, and for the PMV index, it was larger than the two other indices. These results were different in lags 5 to 8, and the relative risks for cool and cold values were more than warm and hot values. This study showed that heat stress has a stronger and more immediate adverse effect on mortality than cold stress. Also, the elderly and females are more vulnerable than others. The most apparent effect was seen in lags 0–12.

Numerical evaluation of outdoor thermal comfort and weather parameters in summertime at Széchenyi square

Abstract Numerical research in the context of urban in a humid continental climate zone is still limited. The aim of modeling the case study is to assess the performance of outdoor thermal comfort parameters and investigate their capabilities in achieving the outdoor thermal comfort. A computer-based tool is used to quantitatively study the outdoor thermal comfort and its weather parameters. The parameters have been analyzed using ENVI-met tool and then compared against different comfort scales like relative humidity comfort scale, the predicted mean vote scale as well as other scales and standards. The results have shown that the average predicted mean vote value is +4 (very hot), the average air temperature is hot, the average wind speed is light breeze and the relative humidity falls within the comfort range. However, street orientation, shading, water bodies and plantation play a significant role in increasing and decreasing the outdoor thermal comfort.

A pilot study on thermal comfort in Indian Railway pantry car chefs

An Indian railway pantry car kitchen is a typical kitchen, where involves various kinds of thermal environment factors. Till now, the research related to pantry car kitchen is rarely reported. Therefore, this pilot study explores the thermal environmental factors and its impact on the chef’s comfort in two different pantry car kitchen (Non-AC and AC) using a subjective and physical measurement technique. The thermal comfort level was quantified by Predicted Mean Vote (PMV) Index and Predicted Percentage Dissatisfied (PPD) Index. The thermal sensation of non-air-conditioned pantry cars was hot with PMV and PPD values are 2.93 and 99% respectively. Whereas, air-conditioned pantry cars was a warm thermal sensation with PMV and PPD values are 2.17 and 84% respectively. Moreover, most of the chef (86%) are perceived thermal discomfort in both pantry car kitchens. The result concluded that both types of pantry car kitchens are having thermal sensation effect of hot and warm. A further detail study is necessary and a possible design intervention may require to enhance thermal comfort of chefs.

Thermal Comfort Evaluation of Rooms Installed with STPV Windows

Thermal comfort is an important aspect to take into consideration for the indoor environment of a building integrated with a semi-transparent Photovoltaics (STPV) system. The thermal comfort of units with photovoltaic windows and that of conventional windows, which is an ordinary without PV, were evaluated via on-site tests and questionnaires. Using the thermal comfort investigation of the test rig, the maximum difference in air temperature was found to be around 5 °C between test unit and comparison unit. The predicted mean vote (PMV)–predicted percentage dissatisfied (PPD) value of the test unit was better than that of the comparison unit. It was observed that on sunny days, the PMV value ranged from 0.2 (nature) to 1.3 (slightly warm) in the test unit, and that of the comparison unit was 0.7 (slightly warm) to 2.0 (warm), thereby providing better thermal comfort, especially during mornings. The maximum difference in PPD values was found to reach 27% between the two units at noon. On cloudy days, the difference was negligible, and the thermal sensation between the foot and the head were almost the same. Fifty respondents were asked to complete a carefully designed questionnaire. The thermal sensation of the test unit was better than that of comparison unit, which corresponded with the test results. Thermal, lighting, acoustic, and other environment comfort scores were combined, and the acceptance of the test unit with the STPV windows was found to be 73.8%. The thermal sensation difference between men and women was around 5%. Thus, during summer, STPV windows can improve the thermal comfort and potentially reduce the air-conditioning load.

Occupant Comfort Management Based on Energy Optimization Using an Environment Prediction Model in Smart Homes

Occupant comfort management is an important feature of a smart home, which requires achieving a high occupant comfort level as well as minimum energy consumption. Based on a large amount of data, learning models enable us to predict factors of a mathematical model for deriving the optimal result without expensive experiments. Comfort management supports high-level comfort to the occupant in the individual indoor environment, using the optimal power consumption to run home appliances. In this paper, we propose occupant comfort management based on energy optimization, using an environment prediction model. The proposed energy optimization model provides optimal power consumption based on the proposed objective function, which requires temperature and comfort index data as the input parameters. For the input requirement, temperature prediction model and humidity prediction model are presented based on a recurrent neural network with a pre-collected dataset, including indoor and outdoor temperature and humidity sensing data. Using the predicted temperature and humidity data, the comfort index model derives the predicted mean vote value to be used in the energy optimization model with the predicted temperature data. The experimental results present an 8.43% reduction of the optimized power consumption compared to the actual power consumption using mean absolute percentage error to calculate. Moreover, the emulation of an indoor environment using optimal energy consumption presents as approximately similar to the actual data.

Statistical significance of gender and age on thermal comfort: a case study in Turkey

Maintaining thermal comfort in buildings is essential since it affects users’ health and performance. Thermal comfort standards provide reference values for indoor environmental parameters; however, they cannot incorporate gender and age in their theories, in which the predicted mean vote (PMV) is used. The aim of this study was to investigate the effects of gender and age on thermal sensation, preference and acceptability as well as verifying the applicability of the PMV model. In order to obtain PMV and actual mean vote values, in situ measurements and surveys were carried out simultaneously in a religious building in Turkey. Statistical analyses, including the Shapiro–Wilk, Levene, Kruskal–Wallis and Games–Howell tests, were conducted to understand the statistical significance between females and males as well as four age groups. The results show that the PMV model is applicable for both females and males; however, it cannot be verified for all age groups except for the age group of 46–65 years. The relationship between thermal sensation and age group is stronger compared with that between thermal sensation and gender. Moreover, the effect of age group on thermal preference and thermal acceptability is statistically significant, whereas that of gender is not significant.

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.

Enhancement of thermal comfort in a large space building

Many large confined spaces in tropical countries employ a combination of natural ventilation and mechanical fans for space cooling purposes. However, due to low wind velocity and an inability of mechanical fans to remove warm air, this cooling method is not capable of providing a satisfactory thermal comfort to the occupants. This study aims to find out a simple strategy for improving the thermal comfort inside a mosque building in Malaysia. Field measurements were first carried out to acquire the airflow velocity, air temperature, relative humidity and mean radiant temperature inside the mosque, for a duration of one-year. These data were then used to calculate two thermal comfort indices namely predicted mean vote (PMV) and predicted the percentage of dissatisfied (PPD). A computational fluid dynamic (CFD) method was employed to predict airflow and temperature distributions and to examine the effects of installing exhaust fans on the thermal comfort condition inside the mosque. Parametric flow analyses were conducted to find out the arrangement of the exhaust fans that would produce highest improvement in the PMV and PPD thermal comfort indices. It was found that, under the present ventilation condition, both PMV and PPD values at the selected locations inside the mosque exceed the respective upper limits as recommended in the ASHRAE Standard-55, indicating that the thermal comfort inside the mosque is extremely hot. Results of parametric flow analyses show that installing ten exhaust fans with a 1-m diameter at the south-side wall, at the height of 6 m from the floor, has a potential of reducing the PMV index by 75–95% and the PPD index by 87–91%. This translates into a vast improvement in the thermal comfort inside the mosque building.

Evaluation of thermal comfort in an office building served by a liquid desiccant-assisted evaporative cooling air-conditioning system

The main purpose of this research is to evaluate the thermal-comfort environment in an office building served by a liquid-desiccant and indirect-and-direct evaporative-cooler-assisted 100% outdoor-air system (LD-IDECOAS). This research presents a method for evaluating the thermal environment via a series of energy simulations using the TRNSYS 17 program, integrated with an engineering equation-solver (EES) program. The supply air (SA) temperature is estimated according to the LD-IDECOAS seasonal operation modes proposed in previous research. The indoor-air conditions are estimated under the assumption that the relative humidity of room air was maintained at the set values by auxiliary humidification systems. Then, the predicted mean vote (PMV) values are estimated using the given indoor environment conditions. In this paper, the indoor-air conditions and PMV values for each LD-IDECOAS operation mode are represented. A detailed analysis of the impact of the indoor-air conditions on the PMV is provided in this paper. Furthermore, the simulation results for LD-IDECOAS were compared with those for a conventional variable-air-volume (VAV) system to evaluate the thermal environment in a building served by LD-IDECOAS. The PMV values with LD-IDECOAS showed that the thermal environment in a conditioned space is generally in compliance with ASHRAE Standard 55. Consequently, it is concluded that using LD-IDECOAS in an office building can produce energy savings with an acceptable level of thermal comfort.

Investigating Thermal Comfort for the Classroom Environment using IoT

<p>In this modern century where fine comfort is a necessity especially in buildings and occupied space, the study to satisfy one aspect of human comfort is a must. This study encompasses of exploring the physiological and environmental factors in achieving thermal comfort which specifically considering the clothing insulation and metabolic rate of students as well as the deployment of dry-bulb temperature, mean radiant temperature, humidity, and air movement in order to obtain the level of comfort students are experiencing in class. The level of comfort are detected by using ASHRAE 55 to determine the average thermal sensation response through the Predicted Mean Vote (PMV) value. An android application were developed to read input of recognizing clothing level (thickness of clothing) and capturing metabolic rate to cater the inputs for physiological factors, while radiant temperature, humidity and air movement are captured through static sensors set up in the classroom space. This paper analyses both the physiological and environmental factors in affecting students in class and further determine their comfort levels that is a major influencing factor of focus in learning. Through cross referencing collected data from IoT enabled nodes, it is found that both physiological and environmental factors, and the combination of them greatly influence in getting the most comfortable state with PMV value of 0.</p>