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Courtyard houses constructed recently with air-conditioning systems need to increase efficiency by simultaneously reducing thermal load and improving thermal comfort in all seasonal zones around the yard. The envelope design is one of the effective parameters in reducing energy consumption and increasing thermal comfort. Therefore, this study investigated the effect of some design parameters related to the envelope of the building on Predicted Mean Vote (PMV) and thermal loads. The design parameters were Wall Construction (WLC) and Window Construction (WID) with different U-values (thermal transmittance), Window to Wall Ratio (WWR), Depth of Shading (DSH), and the Number of Shading (NSH). This research proposed a parametric study process that can simultaneously help designers evaluate the PMV values and thermal loads of numerous design options in four seasonal zones around the courtyard and generate optimized design solutions. According to the results, the PMV of best design solution (BS) compared with the worst design solution (WS) increased by 8%, 9%, 8%, and 12% in different zones. The thermal load decreased by 21%, 26%, 22%, and 21%. According to the sensitivity analysis, PMV values for most zones were negatively affected (decreased) by WID. [ABSTRACT FROM AUTHOR]

This research focuses on schools due to their significant energy consumption. It explores the use of well-designed unshaded courtyards as a passive design strategy in hot climate regions, an area that has received limited attention. The research methodology combines a qualitative approach, case study, and computer simulations through ENVI-met and Integrated Environmental Solutions Virtual Environment (IESve) software. The case study involves an existing school building in the hot arid climate of the United Arab Emirates (UAE). The ENVI-met software evaluates changes in the school's microclimate and building temperature resulting from modifications to the courtyard's design, encompassing five phases. Moreover, the research employs the predicted mean vote (PMV) metric to assess outdoor thermal comfort within school courtyards, correlating with the five design phases. The IESve software assesses the reduction in cooling sensible load achieved through improved courtyard design in the case study. The simulation results demonstrate that the optimal courtyard design lowers the school building's temperature by 1.9°C and 1.7°C on September 21 and March 21, respectively, compared with the base case. Furthermore, it enhances PMV within the courtyard, providing students with a more comfortable outdoor environment during breaks, with maximum PMV reductions of 1.2 and 1.1 on September 21 and March 21. In addition, the optimal courtyard design achieves a significant reduction in cooling sensible load, showing a 19% decrease on September 21 and a 27% decrease on March 21, compared with the basic case. These findings underscore the potential of well-designed courtyards to enhance thermal comfort and energy efficiency in schools within hot arid climates, contributing to sustainable architectural practices. [ABSTRACT FROM AUTHOR]

In the period of coronavirus pandemic (COVID-19), wearing a mask was a mandatory measure to prevent the spread of the virus. After the pandemic, a large percentage of people answered that they would wear a mask to protect themselves and others. However, the mask would directly affect not only the thermal sensitivity of the face but also occupant's thermal sensation. In this context, this study aimed at clarifying the effect of mask on occupant's thermal comfort. The predicted mean vote (PMV), predicted percentage of dissatisfied (PPD) and thermal sensation vote (TSV) were evaluated in a chamber where the set temperature was maintained at 20°C, 22°C and 24°C with and without a mask. When wearing a mask, the TSV mostly exceeded the comfort range and showed a more sensitive variation than the PMV. In addition, the mask dead-space temperature showed a significant difference when the room temperature was increased from 22°C to 24°C. The room temperature that affects the individual thermal comfort with masks was 24°C or higher. Room and mask dead-space temperatures showed a 55% correlation with TSV. This study would provide basic data for determining the optimal room temperature for occupants with masks by identifying the room temperature that could significantly affect thermal comfort of occupants with masks. [ABSTRACT FROM AUTHOR]

The main aim of this study is the analysis of the impact that occupants' characteristics have on thermal comfort assessment, through establishing a novel PMVo model using an approximation method, based on the experimental data. The parameters which are chosen as model's inputs are the air temperature, mean radiant temperature, relative humidity, basic clothing insulation, air velocity and occupants characteristics – gender, age, height, and body mass, while the output is the PMVo, a novel thermal comfort index. Since existing standards concerning thermal comfort do not consider these occupants' characteristics, the main novelty of the introduced model is the inclusion of occupants' characteristics in the thermal comfort assessment. To ensure enhanced precision, the model is established using both linear regression and by training neural network. These two approximation methods are compared to determine which one is more applicable in the context of data approximation. Study shows that regardless of dataset based on which models are established and regardless of testing input values, neural network (R2 in the range of 99.87% to 99.96%) is a superior mathematical approximation algorithm compared to the linear regression (R2 in the range of 95.3% to 97.5%). Novel neural network based thermal comfort assessment model is used for investigation of occupants' characteristics impact on thermal comfort assessment. Analysis of the results showed that gender, age, height and body mass may significantly impact thermal comfort indices calculation, which implies the necessity of their inclusion in thermal comfort prediction and evaluation. Thus, the presented PMVo model may be highly beneficial to implement within existing thermal comfort standards, ensuring well-being and satisfaction with conditions of indoor environment for wider range of the occupants. [ABSTRACT FROM AUTHOR]

Mostadam is the Green Building Rating System in the Kingdom of Saudi Arabia. Indoor thermal comfort assessment is one of the key issues in Mostadam. Controlling the thermal characteristics of the building envelope is one of the main methods to achieve thermal comfort. In Mostadam, these characteristics should comply with the Saudi Building Code for energy conservation, where the required thermal resistance value (R-value) of the abovegrade walls for twelve thermal zones are unified despite their various climatic aspects. Taif city, for example, has a moderate temperature for most of the year in contrast to many Saudi cities that share the walls' R-value. The purpose of this paper is to highlight the importance of considering a comprehensive assessment of a building across all its life stages before judging any green practice. Therefore, a simulation methodology was used for a set of models through which the impact of R-value on the building's assessment to its different stages can be checked. Simulation results showed that half the value of the required Saudi code's R-value can give the same thermal target in Taif city. But the higher R-value means more materials and loads, which accordingly leads to more construction costs. To decide that a conservation method is appropriate, it should be judged over the whole life cycle of the building. Thus, it is not considered appropriate if a thermal solution gives the same energy consumption during the operational building stage but more cost during the construction and demolition stages. The manuscript results in that the suitable R-value that should be used within the Saudi codes and, therefore, Mostadam for the above-grade walls in Taif city is 1 (m² K)/W, as it maintained the targeted thermal comfort achievement with less building construction cost. It is recommended to evaluate the Saudi code values accordingly. [ABSTRACT FROM AUTHOR]

Indoor air quality and thermal comfort affect occupant comfort and productivity. Thermal comfort supports productivity, while indoor air quality maintains occupant health. However, occupants are the main source of CO2, which is the main index for indoor pollutants in educational buildings due to many occupants gathering in one room. This study investigates the performance of applying a total heat exchanger for diluting CO2. Besides, the thermal comfort of the occupants has been evaluated extensively as the total heat exchanger also reduces the fresh air temperature. An office area with 14 graduate students seated in a meeting was investigated. Questionnaires and field measurements were conducted simultaneously. Time-varying indoor air quality (CO2 concentration) was assessed using CFD. The numerical simulation program also contained user defined function based predicted mean vote algorithms to determine occupant thermal comfort. The results indicated that without using total heat exchanger, the CO2 concentration gradually rises until it reaches a maximum of 1400 ppm inside the room. This condition occurs because there is no air change between indoor and fresh air, mainly due to the lack of fresh air supply and reliance on split air conditioning for circulation. With total heat exchanger, the concentration could lower to below 1000 ppm. In addition, it also could make room temperature slightly lower, with the overall temperature average in this study being 24.5 °C without total heat exchanger and 24.1 °C when total heat exchanger is operated. [ABSTRACT FROM AUTHOR]

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Rapid urbanization and increased human activity have negatively impacted the microclimate of cities, leading to unfavorable conditions for human thermal comfort, particularly in outdoor spaces. Thermal comfort can be improved through various means, such as adjusting the height of urban buildings, the aspect ratio of road widths, and the placement of street trees. This study employed the ENVI-met software V5.5.1 to simulate the microclimate based on aspect ratio (H/W = 1.5) and street tree spacing (6 m) similar to actual conditions with different aspect ratios (H/W = 0.5, 1.0, and 2.0) and street tree spacing (2 m) in Seoul, Republic of Korea. Thermal comfort was assessed through a comprehensive predicted mean vote (PMV) evaluation, considering the gender (male and female) and age (8, 35, and 80 years) of residents in the target area, to determine the optimal urban canyon scenario. The results of the study indicated that the height of the building and the percentage of trees had a significant impact on the temperature and PMV results. When comparing PMV results, women have higher thermal vulnerability than men, and based on age, older adults have higher thermal vulnerability. The aspect ratio of 1.5 and tree spacing of 2 m resulted in the lowest temperature of 35.91 °C at 12:00 p.m. at 0° wind direction and 36.09 °C at 90° wind direction, lower than the actual input value of 36.9 °C. The PMV values were also under the same conditions, with an average PMV by gender of 3.87 at 0° and 4.21 at 90° and an average PMV by age of 3.86 at 0° and 4.19 at 90°. This finding is significant because it can inform the development of planned cities that prioritize urban thermal comfort during summer. This can be achieved through the strategic design of urban canyons and incorporation of street trees in both new and existing cities. [ABSTRACT FROM AUTHOR]

Abstract Air conditioner (AC) systems are important for maintaining indoor thermal comfort, but discrepancies can exist between setpoints and the actual room temperature. In the present study conducted in a typical Korean office during summer, we identified differences of up to 2.77 °C between the AC setpoint and the average room temperature. This variation may have originated from the oscillatory cooling pattern, leading to moments of discomfort even though the overall thermal balance was maintained. While consistent initial cooling rates were observed for various setpoints, oscillations at 20 °C lowered the efficiency of the AC system. A bi-exponential model applied to the cooling pattern confirmed a two-phase cooling process. Interestingly, the coefficient of performance was highest at the lowest temperature setpoint, even though this led to greater energy consumption and possible overcooling. The weather strongly affected AC performance, with rainy conditions requiring less power than sunny conditions at the same setpoint. Furthermore, our experiment comparing the predicted mean vote (PMV) with actual human comfort revealed that the PMV often recommends a cooler ambient temperature than what occupants actually prefer.

Air conditioner (AC) systems are important for maintaining indoor thermal comfort, but discrepancies can exist between setpoints and the actual room temperature. In the present study conducted in a typical Korean office during summer, we identified differences of up to 2.77 °C between the AC setpoint and the average room temperature. This variation may have originated from the oscillatory cooling pattern, leading to moments of discomfort even though the overall thermal balance was maintained. While consistent initial cooling rates were observed for various setpoints, oscillations at 20 °C lowered the efficiency of the AC system. A bi-exponential model applied to the cooling pattern confirmed a two-phase cooling process. Interestingly, the coefficient of performance was highest at the lowest temperature setpoint, even though this led to greater energy consumption and possible overcooling. The weather strongly affected AC performance, with rainy conditions requiring less power than sunny conditions at the same setpoint. Furthermore, our experiment comparing the predicted mean vote (PMV) with actual human comfort revealed that the PMV often recommends a cooler ambient temperature than what occupants actually prefer. [ABSTRACT FROM AUTHOR]

This article summarizes a study conducted in Guangzhou, China, comparing the thermal comfort in different types of office buildings. The study found that green office buildings outperformed conventional office buildings in terms of indoor temperature, air movement, and occupant satisfaction. The study suggests that employees in green office buildings are better adapted to their thermal environment and may have greater potential for energy savings. The findings have implications for the design and operation of green buildings to create a better indoor environment while ensuring thermal comfort. The article also discusses the importance of indoor environmental quality (IEQ) in promoting comfort, well-being, and productivity in indoor spaces. [Extracted from the article]

Rapid urbanization and increased human activity have negatively impacted the microclimate of cities, leading to unfavorable conditions for human thermal comfort, particularly in outdoor spaces. Thermal comfort can be improved through various means, such as adjusting the height of urban buildings, the aspect ratio of road widths, and the placement of street trees. This study employed the ENVI-met software V5.5.1 to simulate the microclimate based on aspect ratio (H/W = 1.5) and street tree spacing (6 m) similar to actual conditions with different aspect ratios (H/W = 0.5, 1.0, and 2.0) and street tree spacing (2 m) in Seoul, Republic of Korea. Thermal comfort was assessed through a comprehensive predicted mean vote (PMV) evaluation, considering the gender (male and female) and age (8, 35, and 80 years) of residents in the target area, to determine the optimal urban canyon scenario. The results of the study indicated that the height of the building and the percentage of trees had a significant impact on the temperature and PMV results. When comparing PMV results, women have higher thermal vulnerability than men, and based on age, older adults have higher thermal vulnerability. The aspect ratio of 1.5 and tree spacing of 2 m resulted in the lowest temperature of 35.91 °C at 12:00 p.m. at 0° wind direction and 36.09 °C at 90° wind direction, lower than the actual input value of 36.9 °C. The PMV values were also under the same conditions, with an average PMV by gender of 3.87 at 0° and 4.21 at 90° and an average PMV by age of 3.86 at 0° and 4.19 at 90°. This finding is significant because it can inform the development of planned cities that prioritize urban thermal comfort during summer. This can be achieved through the strategic design of urban canyons and incorporation of street trees in both new and existing cities.

Present work characterizes a spray tower-based desalination system, designed to simultaneously provide fresh water by condensation and supply dehumidified air to occupied spaces. Its configuration is open air-open water, with Celdek 7090 packing in the humidification section and water-cooled helical coils for dehumidification. The performance parameters calculated are: gained output ratio, recovery ratio, coefficient of performance, specific electrical energy consumption, mass ratio, humidification, and dehumidification efficiency. This performance is analyzed for varying air Reynold's number and water flow rate. The best results were obtained for the sea water flow rate tested of 18 liters per hour, and showed maximum humidification efficiency, dehumidification efficiency, COP, freshwater rate, gained output ratio and concentration factor equal to 87.14%, 94.56%, 3.34, 0.9 liters per hour and 1.05, respectively. Exit air meets the thermal comfort requirements which avoids the ventilation thermal loads in the space cooling. • A spray tower desalination unit with a venturi is designed. • The maximum COP of the system is found to be 3.34 which signifies energy efficiency. • Reynolds number of 50519 & water flow rate of 18 LPH yielded maximum fresh water of 0.9 LPM. • Air supply values PMV & PPD obtained are − 0.51 & 10.41 which are within the thermal comfort range. [ABSTRACT FROM AUTHOR]

We developed pythermalcomfort, a Python package that allows users to calculate the most common thermal comfort indices in compliance with the main thermal comfort standards. For example, pythermalcomfort can be used to calculate: whole body thermal comfort indices (e.g., Predicted Mean Vote, adaptive models, Standard Equivalent Temperature), local discomfort, clothing insulation, and psychrometric properties of air. All pythermalcomfort functions have been validated against the reference tables provided in the corresponding thermal comfort standards. We have developed documentation, examples and tutorial videos to guide users on how to use our package. pythermalcomfort allows researchers and professionals to accurately perform complex thermal comfort calculations without the need of re-writing the programming code. With Python being among the most widely utilized programming languages and pythermalcomfort being the only Python library which includes a comprehensive list of thermal comfort functions, we believe that pythermalcomfort will have a significant impact on both the research and industrial communities.

The Center for the Built Environment (CBE) Thermal Comfort Tool is a free online tool for thermal comfort calculations and visualizations that complies with the ASHRAE 55–2017, ISO 7730:2005 and EN 16798–1:2019 Standards. It incorporates the major thermal comfort models, including the Predicted Mean Vote (PMV), Standard Effective Temperature (SET), adaptive models, local discomfort models, SolarCal, and dynamic predictive clothing insulation. Our tool also provides dynamic and interactive visualizations of thermal comfort zones. The CBE Thermal Comfort Tool has several practical applications and each year is used by more than 49,000 users worldwide, including engineers, architects, researchers, educators, facility managers and policymakers.

The Center for the Built Environment (CBE) Thermal Comfort Tool is a free online tool for thermal comfort calculations and visualizations that complies with the ASHRAE 55–2017, ISO 7730:2005 and EN 16798–1:2019 Standards. It incorporates the major thermal comfort models, including the Predicted Mean Vote (PMV), Standard Effective Temperature (SET), adaptive models, local discomfort models, SolarCal, and dynamic predictive clothing insulation. Our tool also provides dynamic and interactive visualizations of thermal comfort zones. The CBE Thermal Comfort Tool has several practical applications and each year is used by more than 49,000 users worldwide, including engineers, architects, researchers, educators, facility managers and policymakers.

We developed pythermalcomfort, a Python package that allows users to calculate the most common thermal comfort indices in compliance with the main thermal comfort standards. For example, pythermalcomfort can be used to calculate: whole body thermal comfort indices (e.g., Predicted Mean Vote, adaptive models, Standard Equivalent Temperature), local discomfort, clothing insulation, and psychrometric properties of air. All pythermalcomfort functions have been validated against the reference tables provided in the corresponding thermal comfort standards. We have developed documentation, examples and tutorial videos to guide users on how to use our package. pythermalcomfort allows researchers and professionals to accurately perform complex thermal comfort calculations without the need of re-writing the programming code. With Python being among the most widely utilized programming languages and pythermalcomfort being the only Python library which includes a comprehensive list of thermal comfort functions, we believe that pythermalcomfort will have a significant impact on both the research and industrial communities.

The thermal comfort of passengers in the carriage cannot be ignored. Thus, this research aims to establish a prediction model for the thermal comfort of the internal environment of a subway car and find the optimal input combination in establishing the prediction model of the predicted mean vote (PMV) index. Data-driven modeling utilizes data from experiments and questionnaires conducted in Nanjing Metro. Support vector machine (SVM), decision tree (DT), random forest (RF), and logistic regression (LR) were used to build four models. This research aims to select the most appropriate input variables for the predictive model. All possible combinations of 11 input variables were used to determine the most accurate model, with variable selection for each model comprising 102 350 iterations. In the PMV prediction, the RF model was the best when using the correlation coefficients square (R2) as the evaluation indicator (R2: 0.7680, mean squared error (MSE): 0.2868). The variables include clothing temperature (CT), convective heat transfer coefficient between the surface of the human body and the environment (CHTC), black bulb temperature (BBT), and thermal resistance of clothes (TROC). The RF model with MSE as the evaluation index also had the highest accuracy (R2: 0.7676, MSE: 0.2836). The variables include clothing surface area coefficient (CSAC), CT, BBT, and air velocity (AV). The results show that the RF model can efficiently predict the PMV of the subway car environment.

The concern with the well-being of users in buildings has become increasingly essential, covering aspects related to health, energy efficiency, and productivity. The thermal environment evaluation in buildings has become more frequent due to the time people spend inside them. In this context, this study aimed to analyze thermal comfort in classrooms at a Brazilian University. During the autumn, 50 measurements were performed, resulting in 519 valid responses. The results of the linear regression analysis revealed that the thermal comfort range for females was 20.39–22.19 °C, while for males it was 19.47–22.56 °C. Through discriminant analysis, participants were classified based on their thermal sensation vote (TSV), predicted mean vote (PMV), and thermal preference votes (PREF), achieving a success rate of 76.1% for females and 81.6% for males in forming the groups, which demonstrates the effectiveness of discriminant functions in predicting thermal comfort for both groups. These results highlight the importance of considering gender differences in the search for thermal comfort conditions and providing guidelines that promote the well-being of occupants and the conscious use of energy. This implies adjusting the thermal conditions according to the specific needs of males and females in classrooms, always seeking to provide a suitable environment for activities, and considering energy efficiency and users' productivity. [ABSTRACT FROM AUTHOR]

This work proposes a data-driven decision-making approach to develop a smart avatar that allows for evaluating the thermal comfort experienced by a user in Chile. The ANSI/ASHRAE 55-2020 standard is the basis for the predicted mean vote (PMV) comfort index, which is calculated by a random forest (RF) regressor using temperature, humidity, airspeed, metabolic rate, and clothing as inputs. To generate data from four cities with different climates, a 3.0 m × 3.0 m × 2.4 m shoe box with two adiabatic walls was modeled in Rhino and evaluated using Grasshopper's ClimateStudio plugin based on Energy Plus+. Long short-term memory (LSTM) was used to forecast the PMV for the next hour and inform decisions. A rule-based decision-making algorithm was implemented to emulate user behavior, which included turning the air conditioner (AC) or heater ON/OFF, recommendations such as dressing/undressing, opening/closing the window, and doing nothing in the case of neutral thermal comfort. The RF regressor achieved a root mean square error (RMSE) of 0.54 and a mean absolute error (MAE) of 0.28, while the LSTM had an RMSE of 0.051 and an MAE of 0.025. The proposed system was successful in saving energy in Calama (31.2%), Valparaiso (69.2%), and the southern cities of Puerto Montt and Punta Arena (23.6%), despite the increased energy consumption needed to maintain thermal comfort. [ABSTRACT FROM AUTHOR]

Gaotai dwellings are the most important representative of dwellings in Xinjiang. It is an important evidence for studying the living customs and architectural features of ethnic minorities. The building enclosure type (BET) and building orientation (BO) are important factors that influence the indoor thermal comfort of the courtyard building. In this research, 20 test scenarios are simulated through field investigation and virtual simulation integrated in the software to grasp the influence of BET and BO on indoor thermal environment. The conclusions are as follows: 1. The higher the degree of building enclosure, the higher the number of comfort hours and the better the comfort. 2. Each BET has its suitable orientation. The best orientation of “T” type is east, the best orientation of “I” type and “L” type is north, and the best orientation of “C” type and “O” type is south. 3. When the optimal BET is combined with its corresponding optimal orientation of the main room, the indoor thermal comfort will be greatly increased (comfort hours in winter and summer will increase by 62.9% and 37.1%).The conclusion of this study can provide flexible design ideas for courtyard buildings to improve the thermal comfort in Kashi.

The paper examines outdoor thermal comfort in summer in the multi-family housing area Duvanište in the city of Niš, Serbia, combining objective and subjective evaluation assessments. Objective evaluation obtained field measurements of microclimatic parameters at selected sites and mean radiant temperature, predicted mean vote, and psychological equivalent temperature calculation using RayMan software. Subjective methodology assessment is performed using survey questionnaires based on thermal sensation vote and overall comfort vote. The paper aims to find the correlation between measured and calculated parameters on one side and Thermal Sensation Vote values. The results show that air temperature signifi- cantly correlates to human thermal sensation in the subject area. Obtained results also indicate high prediction accuracy of psychological equivalent temperature in the outdoor thermal comfort evaluation in summer. Finally, to feel comfortable, neither warm nor cold, in continental climate regions with hot summer conditions, the neutral psychological equivalent temperature should be between 15-24.3 °C. [ABSTRACT FROM AUTHOR]

The accurate prediction of thermal perception paves the way to create a thermal comfort environment. This study proposes a modified predicted mean vote (PMV) model for elderly people. Data from three age groups in two pensioners' buildings are collected and divided: 80 % for calculating key parameters (B and BT) via logistic function, establishing the mPMV model, and 20 % for validation data. The model is further validated by a subset of the ASHRAE Global Thermal Comfort Database II. The mPMV model demonstrated improved prediction quality over the original PMV model, reducing mean mean absolute error (MAE), standard deviation (SD), and coefficient of variation of root mean square error (CVRMSE) by 0.67, 0.36, and 1.26, respectively, in the experimental data. However, due to various scene classifications in the ASHRAE data, the prediction quality of the mPMV model remains basically unchanged compared with the PMV model, with minor increases in MAE and CVRMSE and a decrease in SD. With the elimination of the climate differences, the mean MAE, SD and CVRMSE of the mPMV model reduces by 0.19, 0.16 and 0.29 compared with the PMV model. In addition, the mPMV model outperforms the other three modified models across all three age groups of the experimental data, but this advantage is only observed in the younger elderly group of the ASHRAE data. This study can offer methodological assistance in predicting the thermal sensation for elderly people and contribute to creating a thermal environment accordant to their thermal preferences. • The prediction of the PMV guarantees thermal environment for human thermal comfort. • The logistic function is utilized as the modification frame of the new mPMV model. • The seven-scale TSV and age are consolidated into the modification frame. • The mean MAE, SD and CVRMSE of the mPMV model reduces by 0.67, 0.36 and 1.26. • The mPMV model excels other models on the younger elderly group of the ASHRAE data. [ABSTRACT FROM AUTHOR]

Heated glass can be applied to improve windows' condensation resistance and indoor thermal comfort in buildings. Although this applied technology has advantages, there are still some concerns in practical applications, such as additional energy consumption and control issues. This study evaluates the effectiveness of a heated window heating (HWH) system in terms of thermal comfort and heating energy performance (HEP). The simulation-based analysis is performed to evaluate the effectiveness of the HWH using a residential building model and to compare it with radiant floor heating (RFH) and hybrid heating (HH) systems (i.e., combined HWH and RFH). This study also investigates the peak and cumulative heating loads using HWH systems with various scenarios of control methods and setpoint temperature. The predicted mean vote (PMV) is used as an indoor thermal comfort index. The ratio of cumulative thermal comfort time to the entire heating period is calculated. The results show that HWH and HH can reduce the heating load by up to 65.60% and 50.95%, respectively, compared to RFH. In addition, the times of thermal comfort can be increased by 12.55% and 6.98% with HWH and HH, respectively. However, considering the social practices of South Korea, HH is more suitable than HWH. Further investigations for HH show that a surface setpoint of 26 °C is proper, considering both heating demands and thermal comfort. In addition, the setpoint temperature should be determined considering HEP and the thermal comfort for HWH, and the optimal setpoint temperature was suggested under specific conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study aimed to comprehensively investigate the thermal comfort and physiological and psychological effects according to tree density in forest environments during rest and during and after physical activities in the summer. Participants consisted of 18 male university students (average age: 24.0 ± 1.6 years old), and a within-subjects experimental design was used. Participants sat on a chair for 5 min to rest, performed a step-box exercise for 8 min, and then sat on the chair again, and rested for 10 min in a forest with high tree density (85.6%) and one with low tree density (12.2% as a control). Thermal comfort (predicted mean vote; PMV and percentage of dissatisfied; PPD) and physiological and psychological responses were measured. We investigated and analyzed the changes in "rest", "during exercise", and "after exercise". As a result, a forest with high tree density showed a statistically significant decrease in PMV and PPD values; an increase in parasympathetic nervous activity; a decrease in respiratory rate, systolic blood pressure, and pulse rate; an improvement in mood state; an increase in comfortable, relaxed, and natural feelings; and more of an increase in personal thermal sensation during the recovery period after physical activities than in a forest with low tree density. In conclusion, a forest with high tree density during recovery after physical activities in the summer has higher thermal comfort and physiological and psychological relaxation effects on humans, as compared to one with low tree density. [ABSTRACT FROM AUTHOR]

The precise building performance assessment of residential housings in subtropical regions is usually more difficult than that for the commercial premises due to the much more complicated behavior of the occupants with regard to the change in indoor temperature. The conventional use of a fixed schedule for window opening, clothing insulation and cooling equipment operation cannot reflect the real situation when the occupants respond to the change in thermal comfort, thus affecting the appropriateness of the assessment results. To rectify the situation, a new modeling strategy in which the modification of the various operation schedules was based on the calculated thermal comfort (TC), was developed in this study. With this new TC-based strategy, the realistic building performances under different cooling provision scenarios applied to a high-rise residential building under the near extreme weather conditions were investigated and compared. It was found that sole provision of ventilation fans could not meet the zone thermal comfort by over 68% of the time, and air-conditioning was essential. The optimal use of ventilation fans for cooling could only help reduce the total cooling energy demand by less than 12% at best which could only be realistically evaluated by adopting the present strategy. Parametric studies were conducted which revealed that some design factors could offer opportunities for reducing the total cooling energy under the near extreme weather conditions. [ABSTRACT FROM AUTHOR]

One of the crucial factors for the presence of more people outdoors is to create comfortable conditions. This issue is significant for the elderly due to the different physical conditions. The purpose of this study is to improve the micro-climatic condition around residential complexes considering the elderly in a linear type. For this purpose, two physical indicators, the ratio of the height of buildings to their distance from each other (H/D) and the orientation of them towards the street, were investigated. Regarding H/D, ratios of 0.5, 1, 1.5, and 2, and about the orientation factor, angles of 135° to 200° were examined. This study was conducted outdoors around residential complexes in Iran, Tabriz, with a cold semi-arid climate. Envi-met software model 4.4.5 was used for the simulation. The days June 22 and December 22, 2020 were selected as one of the hottest and coldest day of the year. Two indexes of the Predicted Mean Vote (PMV) and the Universal Thermal Climate Index (UTCI) were examined as essential thermal comfort indexes. Also, for validation, local and field data in six days (21, 22, 23 June in summer and 21, 22, 23 December in winter) were extracted and compared with the data of the software. The results display, the ratio of H/D=1.5 and the angles of 135° and 145° were the most suitable comfort conditions.

The ongoing climate change is manifesting itself through the increasing expansion of Urban Heat Island (UHI) effects. This paper evaluates the microclimate benefits due to cool road pavements, greenery, and photovoltaic canopies in a parking lot in Fondi (Italy), identifying the best strategy to counteract the negative effects of UHIs. The ENVI-met software allowed a microclimatic analysis of the examined area in July 2022 through the comparison of the thermal performances between the current asphalt pavement and ten alternative scenarios. The proposed layouts were investigated in terms of air temperature (AT), surface temperature (ST), mean radiant temperature (MRT), and predicted mean vote (PMV). The results showed that the existing asphalt pavement is the worst one, while the cool pavement integrated with vegetation provides appreciable benefits. Compared to the current layout, a new scenario characterized by light porous concrete for carriageable pavements and sidewalks, concrete grass grid pavers for parking stalls, a 2-m-high border hedge, and 15-m-high trees implies reductions of AT above 3 °C, ST above 30 °C, MRT above 20 °C, and a maximum PMV value equal to 2.2. [ABSTRACT FROM AUTHOR]

Ongoing climate change is manifesting in the expansion of the urban heat island (UHI) effect. This paper evaluates the microclimate benefits of cool pavements and green infrastructures in a historical square in Rome, Italy. The ENVI-Met software enabled us to conduct a microclimatic analysis of the examined square in July 2021, through a comparison of the thermal performances of the current asphalt and sampietrini pavement (AS) with three alternatives. The proposed options are to change the existing layout to include: light concrete slabs and green furniture consisting of 5 m high trees (LC+G1), a perimeter hedge with 5 m high trees (LC+G2), and a perimeter hedge with 15 m high trees (LC+G3). The effects of the road pavements as passive countermeasures to the UHI effect are investigated in terms of air temperature (AT), mean radiant temperature (MRT), and predicted mean vote (PMV). The results show that the existing asphalt pavement is the worst option, while the cool pavement integrated with vegetation is greatly beneficial to human thermal comfort. Compared to the current layout, LC+G3 is the best scenario, because it implies an AT reduction higher than 3 °C, a MRT reduction equal to 50%, and a maximum PMV value equal to 2.2. [ABSTRACT FROM AUTHOR]