Predicted Mean Vote Values Research Articles

Urban Canyon Design with Aspect Ratio and Street Tree Placement for Enhanced Thermal Comfort: A Comprehensive Thermal Comfort Assessment Accounting for Gender and Age in Seoul, Republic of Korea

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.

Evaluation of the air quality and the thermal comfort in the kitchen fume environment under the fresh air supplement

Kitchen cooking particles can severely deteriorate indoor environment, aggravating the risk of cardiovascular and cerebrovascular diseases, as well as respiratory diseases. In view of the severe hazard of cooking particles to human health, this paper numerically studies the trajectory and deposition of the cooking particles in the kitchen environment based on a numerical model. Also, quantitative evaluations for the air quality and thermal comfort are performed, hoping to provide a useful reference for the control of kitchen air pollution. Firstly, a kitchen environment simulation model is established based on Fluent. A post-processing UDF program for evaluating the effectiveness of fume absorption is developed. The reliability of the numerical model is verified by comparing the results of the fume concentration with those by the cooking experiments. Using this numerical model, the fume extraction effectiveness of the range hood under different velocities of the fresh air is analyzed comprehensively, including particle trajectory, air age, temperature, PMV (Predicted Mean Vote), and PPD (Predicted Percentage of Dissatisfied) indicators. Results have shown that high speed of the fresh air can cause a strong blowing sensation, deteriorating indoor air quality. The PMV and PPD values around the human body show a parabolic trend. Generally, the relatively low fresh air speed can achieve satisfactory air quality and thermal comfort while saving energy consumption.

Sustainable Urban Landscapes in Hot–Dry Regions: Climate-Adaptive Courtyards

In hot and arid environments, courtyards are essential architectural elements that significantly contribute to microclimate regulation and enhanced thermal comfort. Beyond providing protection against environmental severities, these spaces elevate the standards of livability and sustainability in urban design. The traditional landscape of Mardin, Turkey, exemplifying such challenges, takes center stage in this study, where courtyards hold a prominent role in architectural composition. Facilitated by the ENVI-met software, the evaluation process herein comprehensively analyzes four representative courtyard case studies in Mardin. Key parameters, including air temperature, humidity, predicted mean vote (PMV), and wind speed, are considered to gain a nuanced understanding of their thermal dynamics. The initial evaluation of existing conditions reveals varying thermal comfort levels, with higher PMV values indicating discomfort in the courtyards, underscoring the need for interventions to enhance their microclimate regulation and resilience to climate change challenges. This study aims to enhance our comprehension of the relationship between courtyards and microclimate regulation, particularly in hot–dry regions. By examining the design principles and passive strategies of courtyards, this research identifies effective approaches for optimizing courtyard design, aiming to create sustainable and comfortable living environments.

Winter indoor thermal environment and livability analysis of traditional residential houses in northeast Sichuan, China

With the rapid development of the national economy, increasing attention has been given to the living environment in rural areas, especially indoor thermal and wind environments. This study conducted on-site measurements and questionnaire surveys during winter in the indoor environment of five villages in northeastern Sichuan. Eighty-nine traditional residences were selected to investigate their fundamental characteristics, indoor thermal environment, humidity conditions, and comfort levels. Questionnaires and comparative experiments were also conducted with natives and locals. This combination of objective data and subjective feedback provides a comprehensive perspective for assessing the indoor thermal environment. The results showed that when expressed as neutral temperature and humidity, the temperature difference was 2.36 °C, with little humidity difference. Residents exhibited higher tolerance towards the local thermal and humidity environment than nonlocal volunteers, who showed greater sensitivity to it. In addition, residents had a Predicted Mean Vote (PMV) value of −0.69 and a heat acceptance value of −1.78, while non-local volunteers had a PMV value of −0.76 and a heat acceptance value of −1.32. A detailed evaluation and analysis of the relationship between the indoor thermal environment and human comfort of local residential houses was carried out, providing technical guidance for energy conservation and thermal insulation of local buildings.

Field test of machine-learning based mean radiant temperature estimation methods for thermal comfort-integrated air-conditioning control improvement and energy savings

Advanced control strategies for heating, ventilation, and air-conditioning (HVAC) systems aim to enhance both buildings' energy efficiency and occupant thermal comfort. Despite their potential, real-world demonstration studies on such advanced technologies are still lacking. This study presents a field demonstration of a real-time predicted mean vote (PMV)-based HVAC control strategy in a typical residential building under hot and dry climate conditions. This study introduces an advanced thermal comfort-based controller (TCC) for the PMV-based HVAC control. TCC continually assesses indoor and outdoor thermal conditions and adjusts the HVAC setpoint temperature to optimize real-time energy use while ensuring satisfactory indoor thermal comfort. Machine learning models for the PMV-based HVAC control system are employed to estimate a mean radiant temperature (MRT) point, which is one of the variables used to calculate real-time PMV values. Three machine learning models (i.e., linear regression, regression trees, and artificial neural network) are adopted in this study with non-stationary real-time input values, including times, pre-determined setpoints, and indoor and outdoor temperatures. The developed TCC is installed in a full-scale experimental house in Kuwait, which is under hot and dry climate conditions, to assess the house's indoor thermal comfort and AC energy efficiency performance. Results indicate that the TCC provides better thermal comfort performance compared to the non-TCC case, including up to a 60% improvement in PMV. The proposed TCC controlled by the machine learning methods demonstrates HVAC energy savings potential of over 20% while meeting the desired thermal comfort levels in the experimental building. These findings are expected to be valuable, as they can contribute to reducing cooling energy in residential buildings in hot and dry climate conditions.

The effects of different landscape strategies on outdoor thermal comfort in village squares: a case study in Dayuwan village in Wuhan City.

Appropriate landscape configurations significantly mitigate rural thermal degradation. However, limited research exists on seasonal thermal comfort and the interconnections among landscape elements. Using ENVI-met software and field measurements, this study analyzed the microclimate of Dayuwan Village Square in Wuhan City. Fifteen design scenarios, including tree planting, building greening, albedo adjustment, and expanded tree coverage, were quantitatively evaluated to assess their impact on outdoor thermal comfort. Additionally, synergistic interactions between mitigation strategies were explored. The study found that increasing evergreen tree coverage by 50% has minimal impact on comfort during winter and spring. However, it significantly reduces temperatures in summer and autumn, resulting in average predicted mean vote (PMV) decreases of 0.315 and 0.643, respectively. Additionally, this strategy optimizes PMV values at 18:00 on extreme days, with a 0.102 decrease in summer and a 0.002 increase in winter. This research offers practical and sustainable guidance to designers for enhancing mitigation effects through optimal landscape configuration, providing a technical framework for rural environmental improvements.

Advancing Sustainable Building Practices: Intelligent Methods for Enhancing Heating and Cooling Energy Efficiency

Our work is dedicated to enhancing sustainability through improved energy efficiency in buildings, with a specific focus on heating and cooling control and the optimization of thermal comfort of occupants. With an energy consumption of more than 60% in buildings, HVAC systems are the biggest energy users. By integrating advanced technology, data algorithms, and digital twins, our study aims to optimize energy performance effectively. We have developed a Neural Network-based Model Predictive Control (NNMPC) to achieve this goal. Leveraging technologies such as MQTT communication, Wi-Fi modules, and field-programmable gate arrays will enhance scalability and flexibility. Our findings demonstrate the efficacy of the NNMPC system deployed on the PYNQ board for reducing sensible thermal energy usage for both cooling and heating purposes. Compared to traditional On/Off control systems, the NNMPC achieved an impressive 40.8% reduction in heating energy consumption and a 37.8% decrease in cooling energy consumption in 2006. In comparison to the On/Off technique, the NNMPC demonstrated a 25.6% reduction in annual heating energy consumption and a 28.8% drop in annual cooling energy consumption in the simulated year of 2017. We observed that, across all strategies and platforms, there were no instances where the Predicted Mean Vote (PMV) fell below −0.5. However, a significant proportion of PMV values (ranging from 65% to 83%) were observed between −0.5 and 0.5, signifying a high level of occupant comfort. Additionally, for PMV values between 0.5 and 1.0, percentages ranged from 16% to 33% for both years. Importantly, the NNMPC exhibited notable efficiency in maintaining occupants’ comfort within this range, requiring less energy while ensuring highly satisfactory environments.

The effect of internal blinds on thermal comfort: An experimental analysis in an office room with radiant panels

This study investigated the impact of two types of internal blinds on the indoor thermal environment of a highly glazed office room in Istanbul during summer. The research examined four configurations: (i) no blinds, (ii) roller blinds, (iii) layered roller blinds in night mode and (iv) layered roller blinds in day mode. Measurements of air velocity, average radiation temperature, air temperature and relative humidity were conducted to assess thermal comfort. The findings revealed that internal blinds significantly influence thermal comfort in radiantly cooled office spaces during summer. Without blinds, the indoor environment only met ISO 7730 comfort category C, with average predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) values of 0.6 and 12.5%, respectively. However, with internal blinds, comfort categories A and B were achieved, resulting in improved thermal comfort levels, with average PMV and PPD values ranging from 0.2 to 0.3 and 6% to 7.5%, respectively. Roller blinds, in particular, proved highly effective in enhancing thermal comfort and reducing mean radiant and indoor air temperatures in highly glazed radiant cooling offices. This demonstrated their energy-efficient potential for improving indoor thermal comfort.

CFD-based multi-objective optimization of indoor air quality and thermal comfort in a classroom

Comfort conditions and air quality in educational buildings can affect students’ performance, achievement and productivity, but they can also threaten their health. In this study, a sample classroom in Trakya University, Edirne, which lacks a ventilation system, is discussed. Depending on the determined parameters, an optimization study was performed using computational fluid dynamics. Predicted mean vote (PMV) for general thermal comfort, draught rate (DR) for local thermal comfort and the carbon dioxide (CO2) level for indoor air quality are selected as target functions. Outdoor air temperature, heating/ventilation system, insulation thickness, number of people in the classroom and clothing factor were identified as parameters that could affect the target functions. According to the numerical results, the rank of importance of the parameters affecting the target functions was calculated using the Taguchi method. The effect percentages of the parameters were determined using the analysis of variance. Then, all target functions were optimized with the grey relational analysis. The best case obtained as a result of the optimization has PMV, CO2 and DR values of −0.12, 511 ppm and 5.37%, respectively. When the general results are evaluated, a comfortable and healthy environment is provided in the classroom with the underfloor air distribution system operating at 100% fresh air and a reduced number of occupants.

Numerical Study of Thermal Comfort Evaluation in Naturally Ventilated Classrooms

The classroom is one of the important facilities in teaching and learning activities. Just like any other room, ensuring thermal comfort becomes a vital aspect for its occupants. This study aims to evaluate environmental conditions and the thermal comfort experienced by classroom occupants through numerical methods. The evaluation involves the integration of the Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) equations into Computational Fluid Dynamics (CFD) simulations using a user-defined function. Furthermore, extensive field measurements and questionnaire surveys are also employed to support the simulation process. The results indicate that the air temperature tends to be high, reaching 30.91°C. Meanwhile, the air velocity within the room, particularly in the occupied areas, is significantly low, with an average value of 0.04 m/s. According to the ASHRAE Standard 55, the classroom is perceived as uncomfortable, as evidenced by a PMV value of 1.38 and a PPD of 44.94%. Therefore, efforts are required to enhance the thermal comfort in the space.

Mitigation of Climate Change Impact on Bioclimatic Conditions Using Different Green Space Scenarios: The Case of a Hospital in Gorgan Subtropical Climates

Urban development and its climatic consequences have caused urban decision-makers to establish strategies to mitigate climate change. The implementation of different green spaces is one of the main strategies to reduce the environmental and climatic consequences of urbanization. Therefore, the main objective of this research is to reveal the effect of different green space scenarios on micro-bioclimatic conditions of a hospital located in Gorgan city, Golestan province. Therefore, in order to determine the position of the hospital building relative to Gorgan’s urban heat island (UHI), the location and changes in UHI intensity of Gorgan were determined as evidence of urban expansion. Since 27 July was determined as the hottest day in Gorgan city based on historical data analysis, the climatic conditions during 27 July 2021 were measured using an AR847 data logger installed in the hospital environment. Additionally, four different conditions, including actual environmental conditions of the hospital (actual conditions), along with the application of cypress trees (scenario A), plane trees (scenario B), and Buxus shrubs (scenario C), have been used to analyze the impact of different vegetation species on the bioclimatic conditions of 5 Azar Hospital during two time intervals, including observational periods (1970–2020) and the decade of the 2040s. Finally, spatiotemporal patterns of the predicted mean vote (PMV) thermal index were calculated for the observational period and during the 2040s using the ENVI-met micro-scale model. Results showed that the study site is in the UHI, which can affect the micro-bioclimatic conditions and the patient’s thermal perception. For all designed scenarios, results indicate that the average PMV index will increase by the 2040s. However, implementing different green space scenarios showed that the minimum and maximum values of PMV were found in scenario B, of 2.7. The actual PMV conditions of the studied site increased by 3.5. The scenario introduction of green spaces during the 2040s indicates that the average PMV at the hospital site will be decreased by 0.9 compared to the actual conditions. The study proves that appropriate green space strategies can reduce thermal loads occurring due to global climate change and improve the thermal conditions in the study area.

Assessment of health hazards of greenhouse workers considering UV exposure and thermal comfort

Greenhouse (GH) indoor environments are usually manipulated to enhance plant growth and yield, but those environments might not be favorable for GH workers. This study aimed to investigate the health hazards of greenhouse workers from UV radiation exposure and analyze the heat stress and thermal comfort in air-conditioned greenhouses. Two GHs with different covering materials (glass greenhouse-GGH and polycarbonate greenhouse-PCGH) were selected for this study. The UV index of GGH varied from moderate to high (3 to 8) based on the season and deployment of the shade screen, whereas PCGH was always UV risk-free below and above the shade screen. Heat stress was evaluated in terms of wet bulb globe temperature (WBGT) and thermal comfort with the predicted mean vote (PMV) and predicted percent dissatisfied (PPD). The value of WBGT in GGH varied between 17.67 °C and 26.54 °C and between 18.25 °C and 25.97 °C in PCGH. The PMV values ranged from -2.57 to 1.15 for GGH and from -2.24 to 1.42 for PCGH, depending on airspeed, metabolic rate, and indoor conditions. The PPD values ranged between 5.0 to 94.6 % for GGH and 5.0 to 75.0 % for PCGH. As the optimal target range of the indoor environmental parameters (temperature and relative humidity) were maintained in the modern GHs throughout the year, the potential for heat stress and thermal discomfort was not severe. However, as a precaution, avoiding heavy activities around noon is recommended, even in perfectly conditioned greenhouses, which could be above the danger level in low-tech greenhouses.

Impact of building envelope parameters on occupants’ thermal comfort and energy use in courtyard houses

ABSTRACT 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.

CFD Investigation on Thermal Comfort in Open Spaces Library in Tropical Climate

Libraries consist of large indoor open spaces with comfortable environments for studying activities. Hence, library occupants are exposed to microclimatic conditions in the indoor environment of the library. This problem can lead to a series of thermal condition symptoms (cold or hot) and general discomfort. Therefore, this study aimed to develop computational fluid dynamic (CFD) model and validated the model with the field measurement data of the indoor open space located at the second floor of Universiti Tun Hussein Onn Malaysia (UTHM) library. Parameters validated inside the indoor open space library were air temperature, relative humidity, and mean radiant temperature measured at eight sampling points located 0.5 m height from the floor for first and second days (morning and afternoon session). Predicted Mean Vote (PMV) values and Thermal Sensation Vote (TSV) values were also validated. Then, the developed model was used to get the average comfort temperature that satisfied the PMV and TSV value between +0.5 and -0.5. The results showed that the relative errors between simulation and field measurement were less than 5.5% for air temperature, relative humidity, and mean radiant temperature. The relative error for PMV and TSV value between simulation and field measurement were less than 12.2% and 2.7% respectively. The experiment and the simulation value for all parameters investigated were in good agreement with acceptable relative error value. The study concluded that the average value of comfort temperature and relative humidity for thermal comfort value of PMV and TSV in the investigated open spaces in the library were 24˚C and 57% respectively

Toward Utilizing IoT Open Data Set to Identify the Room Thermal Comfort

Building sectors are responsible for 33% of global energy consumption and a one-third of CO2 emission as buildings are expected to experience high performance in order to mee occupnt requirments such as lightng, coling, heting, and ventiltion systm. Internet of Things (IoT) as one of the leading developments in digital technologies led to the establishment of devices for improving the living style of the occupants. To date, stdies on intgrating the mechnisms of IoT to identify room thrmal cmfort are very sarce. Therefore, this study discussed the room thermal comfort with respect to room temperature and relative humidity. Three activities i.e. read, write, and sit were adopted. The value of air sped, metablic rate, and clohing inslation was assumed constant. The anlysis was condcted according to Fanger method and ASHRAE standard 55. Center for the Built Environment (CBE) Thermal Comfort Tool was usd to calculate the Predicted Mean Vote (PMV) vales. Results showed the average PMV values of each activity were -2.3 (read), -2.0 (write), and -1.4 (sit). Compared to the room climate data set, sitting performed the closest thermal comfort scale to the neutral. It means light activities with lower metabolic rate should be conducted in the room with higher room temperature and relative humidity.

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.

Evaluation of energy-saving potential and cabin thermal comfort for automobile CO2 heat pump

Currently, the heat pump air conditioning system is extensively used in Electric Vehicle (EV). However, most previous simulation studies focused on one-dimensional (1D) system performance rather than three-dimensional (3D) cabin thermal comfort. This study proposed a novel control strategy for the operation of a one- and three-dimensional coupling transcritical CO2 heat pump air conditioning system based on the weighted Predicted Mean Vote (PMV) model. The mathematical characterizations of the multiple thermodynamic systems were achieved by one-dimensional calculation and the cabin thermal environment was described by three-dimensional simulation. The weighted predicted mean vote value was calculated by real-time interactive three-dimensional cabin thermal environment parameters while providing control signals for the one-dimensional refrigeration system. The simulation comparison revealed the influence of the weighted Predicted Mean Vote control strategy on the system’s thermodynamic parameters and energy-saving potential. Results showed that the compressor power consumption of the Predicted Mean Vote control strategy was reduced by 9.1%-33.7%, compared with the method of presetting specific temperatures. The proposed one- and three-dimensional coupling method of cabin thermal management establishes the structured correlation between heat pump air conditioning system and cabin thermal environment. The weighted Predicted Mean Vote control strategy reduces the system power consumption within the thermal comfort range of the passengers, and it provides a novel idea for cabin thermal management during practical engineering.

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.

Experimental study of air distribution and heating performances of deflection ventilation

Deflection ventilation uses a purposely-designed deflector to divert supply air jet into the occupied zone directly. A few numerical studies have shown good indoor air quality with deflection ventilation. However, there was a lack of research on thermal comfort, which is also important to ensure human wellbeing. This study conducted experimental measurements when deflection ventilation was operated for winter heating. Eleven cases with different supply air velocities, supply air temperatures and deflection angles were carried out in an office-layout experimental chamber. As a comparison, another case with mixing ventilation was also measured. The predicted mean vote (PMV), draft rate (DR), air diffusion performance index (ADPI) and energy utilization coefficient (EUC) were adopted to evaluate the heating performances. The results showed that the deflection angle played a decisive role on air distribution. An inclined deflector (deflection angle: 35° downward) could elevate air temperature in the lower occupied zone as compared with a horizontal deflector (deflection angle: 0°), which provided efficient air distribution for winter heating. The average PMV values were in the range of −0.7 – 0.5, and the values of DR and ADPI in the occupied zone were typically less than 20% and higher than 80%, respectively. According to ISO 7730 and ASHRAE 113, deflection ventilation achieved satisfactory indoor environment with regard to thermal comfort. The EUC was typically greater than unity, indicating high energy efficiency of deflection ventilation, especially for the cases with deflection angle of 35°. In comparison with mixing ventilation, deflection ventilation can provide better thermal comfort as well as energy efficiency.

Effects of different renovation strategies on the thermal comfort in urban parks based on bioclimatic design theory

Bioclimatic design can effectively affect the environmental thermal comfort level through changing the surface of the study area. Using Zhengzhou Beach Park as a case study, the impact of three different bioclimatic design methods (changing pavement only, changing design only and changing both pavement and design) on outdoor thermal comfort, temperature, relative humidity, and wind speed under the ENVI-met model is quantitatively analysed. The results show that the three bioclimatic design schemes significantly affect the predicted mean vote of the site. The overall decrease in predicted mean vote average after pavement renovation pavement renovation is about 0.03, the overall increase in predicted mean vote average after design renovation design renovation is about 0.01, and the overall predicted mean vote average decrease after combined renovation is about 0.02. The relation among different predicted mean vote values and occupied areas under different bioclimatic design backgrounds is quantified, and the difference-value of climate index change were visualized for the first time. This study firstly uses a series of figures to show different trends of predicted mean vote and their area changes under the background of different transformation modes, which can effectively promote the refinement of the research on biological climate design.