Thermal Environment Parameters Research Articles

Research on the thermal energy environment and process parameters of milling process in ceramic art design

In ceramic art design, milling technology is the key processing technology, which directly affects the quality and artistic expression of ceramic products. However, the thermal energy environment generated in the milling process has a significant impact on the material characteristics and machining results. This study aims to explore the influence of the thermal energy environment on the ceramic art design during the milling process, optimize the process parameters, and improve the processing efficiency and product quality. Experiments with different milling speed, feed rate and cutting depth were designed to compare and analyze the change of thermal environment by combining experiment and simulation. The influence of thermal energy on ceramic machining quality was evaluated by monitoring the temperature distribution in the cutting process with thermal imaging technology and combining with the experimental data of material properties. The experimental results show that the temperature increase in milling process is closely related to the cutting speed and feed rate, and proper control of the thermal energy environment can significantly reduce the crack generation rate and improve the surface finish of ceramic materials. The optimized process parameters make the temperature control in the milling process within the ideal range, thus realizing the processing of high quality ceramic products. Through reasonable optimization of process parameters, the heat energy in the processing process can be effectively controlled, which helps to improve the overall quality and artistic value of ceramic works.

Health risk assessment of residential overheating under the heat waves in Guangzhou

During extreme heatwave events, indoor overheating caused by power outages poses a significant threat to human health, especially for low-income groups exposed to hot and humid conditions for extended periods. However, currently, the definition and quantification standards for indoor overheating are not well-defined, and relying solely on thermal comfort indicators is insufficient to accurately assess the health risks associated with indoor overheating. This study proposes the use of maximum heat index (HImax) and heat index hazard hours when the heat index exceeds the caution level (HIHHCaution) to assess the health risk of indoor overheating. Taking various types of residential buildings in Guangzhou as examples, the study employs field surveys, simulation analysis, and statistical regression to analyze the impact of power outages during heatwaves on the indoor thermal environment and key human thermal physiological parameters, thereby establishing the basis for measuring indoor overheating and reference thresholds for assessing heat health risks. The results indicate that for young adults and the elderly, HIHHCaution exceeding 1174 °C·h and 850 °C·h respectively, or HImax nearing 55 °C, are likely to result in heat-related illnesses. In Guangzhou, most urban village housing with poor insulation cannot withstand the risk of power outages lasting more than a day during heatwaves, while old housing and commodity housing that meets the energy-efficiency standards of different periods still face varying degrees of indoor overheating risk. The findings enhance understanding of indoor overheating health risks and provide a scientific basis for strategies to improve living environments during heatwaves.

Thermal environment analysis and parameters optimization of a novel hot-air phase change heating bed

Maintaining indoor heating consumes significant energy; personalized heating can reduce this consumption. Existing bed-based heating devices have drawbacks in terms of temperature distribution and susceptibility to weather influences. In this paper, a hot-air phase change heating bed (HAPCHB) is proposed, which can heat the indoor thermal environment during the day and the bedding thermal environment at night. The theoretical analysis and simulation model of the new heating bed is established, and the experimental platform for analyzing the thermal environment building effect is built, which verifies the accuracy of the numerical simulation results. The experimental and simulation results show that the thermal inertia of the envelope has a great influence on the room temperature, but has little influence on the bed board temperature under the experimental conditions. Both indoor and bed board temperatures can keep the lower limit of thermal comfort for 12 h continuously. With the increase of phase change material (PCM), the thermal performance of the system is enhanced and attenuated, and the thermal performance of PCM-1.4 scheme is better. The rate of indoor temperature drop is similar under three heating times, but the performance of room temperature and bed board temperature is better at 6 h and 8 h respectively. The research results provide basis and guidance for improving indoor heating effect by HAPCHB.

A Study on Outdoor Thermal Comfort of College Students in the Outdoor Corridors of Teaching Buildings in Hot and Humid Regions

It is important to create a favorable environment for various student activities and interactions by improving the thermal comfort of semi-outdoor spaces in teaching buildings. However, there has been limited research focusing on the thermal comfort levels of college students in these areas, such as corridors (access ways connecting different buildings outdoors). This study aims to assess the thermal comfort levels of college students in the corridors of teaching buildings in hot and humid regions. Based on field measurements and questionnaire surveys, the study evaluated the thermal comfort levels of male and female college students. The findings indicate the following: (1) air temperature and air velocity are the primary thermal environmental parameters affecting college students in corridor spaces, regardless of gender; (2) physiological equivalent temperature (PET) and Universal Thermal Climate Index (UTCI) were used as indices to evaluate the thermal environment of outdoor corridor spaces. Males and females perceive the outdoor environment as hot when PET (UTCI) values reach 33.5 (34.5) °C and 33.3 (33.5) °C, respectively. When the PET (UTCI) values reach 39.0 °C (37.5 °C) for males and 37.7 °C (38.3 °C) for females, individuals in corridor spaces will face extreme heat stress; (3) females find it more challenging than males to tolerate hot outdoor environments. The unacceptable temperatures for males and females are 31.1 °C and 31.8 °C, respectively; and (4) in hot outdoor environments, females are more susceptible than males to experiencing fatigue and negative emotions. The results of this study provide valuable insights for the future design and renovation of teaching buildings on university campuses.

Numerical study on the thermal environment of the vertical greening system based on infrared thermal imaging

ABSTRACT Since the design and construction of the building envelope affects approximately 20–60% of the energy used to heat and cool the building, it is important to improve the energy efficiency of the building envelope. This study intends to obtain an optimal thermal environment model of vertical greening through software simulation in the later stage. For some countries and cities that are still relatively backward in green development, we can provide technical support and guidance. In this study, infrared imaging equipment was used to obtain the thermal environment parameters of vertical greening, and the corresponding thermal environment characteristics were analyzed to provide support for the construction of the thermal environment model of the vertical greening system. Secondly, a new microclimate numerical simulation software ENVI-met was used to establish a vertical greening system model, quantify the changes of thermal environment parameters under different conditions, and output the numerical simulation analysis results, including temperature and thermal comfort evaluation indicators, to evaluate the role relationship and influence mechanism under different conditions. It provides theoretical support for the development, application and prediction of vertical greening. This will improve the energy efficiency of buildings.

Field measurement study of indoor thermal environment of badminton halls in a hot summer and cold winter region in different seasons in China

The indoor thermal environment has a direct impact on human thermal comfort and health. In order to assess the status of the indoor thermal environment of typical sports buildings in hot summer and cold winter climate zones in China, 14 badminton halls in 10 cities in Hubei Province (including 5 venues in Wuhan) in this climate zone are chosen as research objects for field testing of indoor thermal environment parameters in 4 seasons. All the tested stadiums are naturally ventilated in non-event conditions. The results reveal that the average indoor temperature of badminton halls in summer is excessively high (i.e., 31.89 °C), which is higher than the regulation specified in JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in summer, (i.e., (26–28 °C) or (22–28 °C), respectively). The average indoor temperature of badminton halls in winter is too low (i.e., 12.95 °C), and it is lower than the recommendations of JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in winter (i.e., (16–18 °C) or (16–24 °C), respectively), relative humidity and air velocity are in the thermal comfort interval for all seasons, and the indoor thermal environment factors of badminton courts in spring and autumn meet the comfort requirements. The indoor and outdoor temperatures and the relative humidity of badminton courts are highly correlated. The indoor temperature and relative humidity vary according to changes in those factors outdoors, whereas the air velocity is not affected by outdoor changes. In the hot summer and cold winter climate zones, some discrepancies in the indoor temperature variation patterns of badminton halls at various altitudes are detectable. The results of this study aim to provide a solid basis for the development of indoor thermal-comfort standards for sports stadiums in China.

Field Investigation on Adaptive Thermal Comfort in Rural Dwellings: A Case Study in Linyi (China) during Summer

A large number of people in China still live in rural villages. The indoor environment of these rural dwellings directly affects the quality of life of the occupants. Nevertheless, constrained by the quality of dwelling construction, rural buildings have poorer indoor environments and, at the same time, have a higher operating energy consumption. However, inadequate attention has been given to the summer thermal environment in cold regions. This work has been carried out around the thermal environment of rural residences in cold regions during summer. Field measurements, questionnaires, and data analysis were used in this study. We recorded the indoor and outdoor thermal environment parameters on a typical summer day in the Linyi rural area. Moreover, the subjective sensations and thermal adaptive behaviors of the participants were recorded in detail with a questionnaire. Linear regression showed that the neutral temperature for residents in summer was 27.52 °C, with acceptable temperatures ranging from 25.14 °C to 29.9 °C. Age and gender differences were found to affect the occupants’ sensation of thermal comfort and humidity, as well as their thermal adaptive behavior. In addition, a thermal adaptive model has been constructed in the study, which will further enrich the thermal adaptive investigation and provide a scientifically sound reference for the renovation and development of the local rural areas.

Dual-phase prediction model of passenger thermal sensation using facial thermal imaging and environmental factors

The concept of passenger-centric design has become increasingly significant in the intelligent automotive industry. Enhancing in-cabin thermal comfort while maintaining energy efficiency is crucial, and to this end, we leverage real-time passenger thermal sensation as a basis for HVAC control strategies. This study introduces a non-invasive, dual-phase prediction model that evaluates passenger thermal comfort by utilizing facial thermal imaging and environmental factors. The proposed model employs a deep learning neural network to extract pertinent features from the facial thermal images for an initial prediction. Then this prediction is refined by integrating it with environmental data through a machine learning algorithm, facilitating real-time personal thermal comfort assessment. Data collection for the model was performed across two distinct seasons, with 22 participants in summer and 18 in winter, gathering facial thermal images, environmental parameters, and thermal sensation votes to construct a comprehensive dataset. Analysis revealed a set of critical environmental factors that correlate strongly with thermal sensation votes, which were used as auxiliary features in the model. The performance of the proposed dual-phase approach, combining deep learning and machine learning techniques, demonstrated robust effectiveness on both summer and winter datasets. This substantiates the method's practicality for real-world application within vehicle environments.

Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration

Heating, Ventilation, and Air Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet they frequently fail to ensure provide adequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensors have opened up new possibilities for real-time detection of occupant thermal comfort status and timely feedback to the HVAC system. However, since occupant thermal comfort is subjective and cannot be directly measured, it is generally inferred from thermal environment parameters or physiological signals of occupants within the HST compartment. This paper presents a field test conducted to assess the thermal comfort of occupants within HST compartments. Leveraging physiological signals, including skin temperature, galvanic skin reaction, heart rate, and ambient temperature, we propose a Predicted Thermal Comfort (PTC) model for HST cabin occupants and establish an intelligent regulation model for the HVAC system. Nine input factors, comprising physiological signals, individual physiological characteristics, compartment seating, and ambient temperature, were formulated for the PTS model. In order to obtain an efficient and accurate PTC prediction model for HST cabin occupants, we compared the accuracy of different subsets of features trained by Machine Learning (ML) models of Random Forest, Decision Tree, Vector Machine and K-neighbourhood. We divided all the predicted feature values into four subsets, and did hyperparameter optimisation for each ML model. The HST compartment occupant PTC prediction model trained by Random Forest model obtained 90.4% Accuracy (F1 macro = 0.889). Subsequent sensitivity analyses of the best predictive models were then performed using SHapley Additive explanation (SHAP) and data-based sensitivity analysis (DSA) methods. The development of a more accurate and operationally efficient thermal comfort prediction model for HST occupants allows for precise and detailed feedback to the HVAC system. Consequently, the HVAC system can make the most appropriate and effective air supply adjustments, leading to improved satisfaction rates for HST occupant thermal comfort and the avoidance of energy wastage caused by inaccurate and untimely predictive feedback.

Optimization of university timetables considering students’ thermal sensation in classrooms

In northern China, university classrooms are often densely populated, and students have limited means of thermal adaptation during lectures. Considering the significant differences in the thermal environment of the classroom throughout different periods, changing the patterns of classroom utilization is a feasible way to improve students’ thermal comfort during classes and ensure learning efficiency. A university teaching building in Xi'an is considered an example in this study. The indoor and outdoor thermal environment parameters of the teaching building were measured in the autumn semester, and the students’ thermal sensation was investigated. On this basis, a model for optimizing university timetables was developed to minimize students’ thermal discomfort in classrooms. The study results showed: 1) During non-heating seasons, students felt comfortable in all periods, except for the third class period (14:00–15:30), during which they felt slightly hot. During the heating season, students felt slightly cold in the first class period (8:30–10:00), slightly hot in the third class period, and comfortable in the second (10:30–12:00) and fourth (16:00–17:30) class periods. 2) Compared to the general schedule, the optimized timetable decreased first period classes by 14 and increased fourth period classes by 13, with minimal changes elsewhere. Adopting this approach, students’ thermal discomfort time during classes in the autumn semester was shortened by 6.16%. 3) The students’ thermal discomfort time reduction rate obtained by timetabling optimization during the non-heating season, heating season are 0.78%, 8.91%, respectively. The effect of reducing students’ thermal discomfort is more pronounced during the heating season.

Indoor Thermal Comfort Sector: A Review of Detection and Control Methods for Thermal Environment in Livestock Buildings

The thermal environment is crucial for livestock production. Accurately detecting thermal environmental conditions enables the implementation of appropriate methods to control the thermal environment in livestock buildings. This study reviewed a comprehensive survey of detection and control methods for thermal environments in livestock buildings. The results demonstrated that temperature, humidity, velocity, and radiation are major elements affecting the thermal comfort of animals. For single thermal environmental parameters, the commonly employed detection methods include field experiments, scale models in wind tunnels, computational fluid dynamics (CFD) simulation, and machine learning. Given that thermal comfort for livestock is influenced by multiple environmental parameters, the Effective Temperature (ET) index, which considers varying proportions of different environmental parameters on the thermal comfort of livestock, is a feasible detection method. Environmental control methods include inlet and outlet configuration, water-cooled floors, installation of a deflector and perforated air ducting (PAD) system, sprinkling, etc. Reasonable inlet configuration increased airflow uniformity by more than 10% and decreased ET by more than 9 °C. Proper outlet configuration improved airflow uniformity by 25%. Sprinkling decreased the temperature by 1.1 °C. This study aims to build a comprehensive dataset for the identification of detection and control methods in research of the thermal environment of livestock buildings.

Analysis of the correlation mechanism between geometric parameters and the thermal environment of Xi'an's summer outdoor commercial pedestrian streets.

Intensive urban development has resulted in the degradation of the urban thermal environment in most regions. There is a growing consensus on the need to enhance urban thermal comfort through well-designed forms, especially in open spaces like urban canyons. To address this, our study focuses on Xi'an's commercial pedestrian streets, employing K-means clustering analysis to create 32 representative models based on actual scenes, capturing their textural characteristics. Simultaneously, 11 geometric indicators (2D/3D) were chosen to quantify the canyon's geometric form. We assessed the spatial and temporal distribution differences in the thermal environment across these models using Envi-met simulation. Finally, Spearman correlation analysis was employed to examine the correlation and significance of the two sets of indicators, culminating in formulating an ideal model. The findings reveal that (1) wind conditions are predominantly influenced by the canyon's geometric form, followed by solar radiation and temperature, with the lowest relative humidity change amplitude among the assessed thermal parameters. (2) Among the 11 geometric form indicators, 3D indicators correlate more significantly with thermal environment parameters than 2D indicators. Specifically, street orientation significantly impacts the thermal environment, Build-To-Line Rat holds greater significance than interface density, and both building shape coefficient and block surface ratio are significantly correlated with air temperature and wind speed, with a weaker correlation to solar radiation. (3) In the Xi'an region, courtyards oriented north-south demonstrate a more favorable trend in the thermal environment.

Study on the dynamic effects of plateau hypoxic and cold environment on the thermal adaptation of short-term sojourners in Xizang

The plateau hypoxic environment can affect the thermoregulation process of the human body, and due to the different acclimatization ability to the hypoxic environment, the thermal requirements among the people who enter Xizang at different times may be different. Accordingly, this study aims to clarify how plateau hypoxic environments influence the physiological and subjective responses of people entering Xizang at different times. And field experiments were conducted in Xi'an and Lhasa, respectively, to compare the thermal responses and oxygen responses of the subjects under different temperature conditions on the plain, the first day of entering Xizang and the 15th day of entering Xizang. The results showed that under the hypoxic environment, the thermal sensation of the subjects decreased. With the extension of the time entering Xizang, the influence of the hypoxic environment on thermal comfort was gradually weakened, but under the low temperature environment, the effect of hypoxia on thermal response was not significantly reduced. The results of this study can help to reveal how plateau hypoxic environments affect human thermal comfort and provide a theoretical basis for the design of indoor thermal environment parameters suitable for sojourners entering Xizang at different times.

A novel interpolation-MLP coupled reconstruction method for turbulent natural convection thermal environment reconstruction of MW-class offshore wind turbine nacelles

Localized overheating in the nacelle due to heat loss in high-power offshore wind turbines of 10 MW or more, where localized overheating affects the operation of other components, it is particularly important to visualize the thermal environment in the nacelle accurately and in real time in order to control the start-up and shutdown of cooling methods. However, the complexity of the high turbulence intensity (Rayleigh number (Ra) > 109) thermal environment in the nacelle of high-power units leads to significant errors in existing visualization techniques. Therefore, this paper presents a novel coupled interpolation-MLP reconstruction technique based on a data-driven deep neural network. Based on the interpolation method as primary reconstruction, a secondary reconstruction neural network model is obtained by training the thermal environment parameters (static pressure P, tangential velocity U, normal velocity V and temperature T) of specific computing nodes in the nacelle. The model is used to predict the values of thermal environment parameters at each time point for computing nodes with large gradients. An improved PSO algorithm is used to arrange the positions of a defined number of sensors to save sensor resources during the measurement process and to and ensure computing stability. The above improvements to the traditional interpolation reconstruction algorithms have led to an increase in the accuracy of the thermal environment reconstruction.

Calibrating thermal sensation vote scales for different short-term thermal histories using ensemble learning

The urban heat island effect intensifies, leading to increased thermal exposure for city residents. Variations in thermal sensation are observed among individuals with different short-term thermal experiences, challenging the reliability of Thermal Sensation Vote (TSV) scales. This study investigates TSV disparities in Shanghai, China, between two groups: individuals with Short-Term Air Conditioning Usage Experience (STACUE) and those Lacking Short-Term Air Conditioning Usage Experience (LSTACUE). Through questionnaire surveys and environmental monitoring, the study evaluates the performances of various ensemble learning models for predicting TSV. The selected Random Forest Regressor is employed to calibrate TSV scales for Physiologically Equivalent Temperature, Standard Effective Temperature (SET*), Universal Thermal Climate Index, and Perceived Temperature. Using Shapley values from game theory, we reveal how environmental variables contribute to TSV differences among individuals with varying short-term thermal histories. Results indicate higher Thermal Unacceptable Vote and greater Environmental Expectation Vote for STACUE individuals versus LSTACUE ones. Calibrated TSV scales, particularly SET*, exhibit significant enhancements over original scales: a 35.04 % increase in prediction accuracy percentage and a 0.57 correlation increase. Explainable analysis underscores that air temperature (28.8%) has a stronger impact on TSV among STACUE individuals, whereas mean radiant temperature (32.2%) is the primary factor affecting TSV among LSTACUE. Furthermore, we found gender interacts with thermal environmental parameters concerning TSV. This study sheds light on how short-term thermal history influences TSV among residents, informing customized urban thermal management strategies.

Field study on pregnant women's thermal preference in different trimesters in winter

This study investigated the differences in the thermal preferences of pregnant women during various trimesters and the factors influencing these preferences. The survey was conducted in a hospital waiting room, encompassing the testing of thermal environmental parameters, and the distribution of questionnaires to pregnant women. These questionnaires encompassed various aspects, including basic information, thermal responses, pregnancy diseases, and more. In total, 1388 questionnaires were collected, distributed across the first trimester (225 participants), second trimester (498 participants), and third trimester (665 participants). The findings revealed a notable shift in the thermal preferences of pregnant women as their pregnancies progressed, transitioning from a preference for warmer conditions to a preference for cooler environments. Specifically, the mean thermal preference scores for the first, second, and third trimesters were 0.82, −0.27, and −1.76, respectively. These shifting preferences were associated with various factors, including pregnancy diseases, pre-pregnancy body mass index (PBMI), and exercise habits. Notably, hyperthyroidism, a higher PBMI, and regular exercise were correlated with a preference for cooler conditions, whereas hypothyroidism, anemia, a lower PBMI, and rare exercise were associated with a preference for warmer environments. Furthermore, it was observed that the actual neutral temperatures for pregnant women in the first, second, and third trimesters were 20.3 °C, 19.5 °C, and 19 °C, respectively. By contrast, the predicted neutral temperatures were 23.5 °C for the first and third trimesters and 23.4 °C for the second trimester. This indicated that the Predicted Mean Vote (PMV) model tended to underestimate the acceptability that pregnant women experienced in colder environments. Given the unique thermal preferences of pregnant women, further research is essential to refine thermal comfort parameters and the PMV model tailored specifically to this demographic.

Assessing the influence of neighborhood urban form on outdoor thermal conditions in the hot dry city of Biskra, Algeria

The quality of the thermal urban environment plays a vital role in outdoor human activities and the overall quality of life in residential neighborhoods. This study investigated the influence of two urban form variables, the height to width ratio (H/W) and sky view factor (SVF), on three outdoor thermal environmental parameters (OTEP), direct solar radiation (DSR), mean radiant temperature (MRT), and air temperature (AT) in three neighborhoods in the hot and dry city of Biskra, Algeria. The research followed a three-step process: Three neighborhoods with varying urban form variables were selected, and field measurements of thermal parameters were conducted at various locations during the hottest period of the year. Numerical modeling, simulation, and validation using Envi-met were then performed to gather the remaining outdoor thermal environmental parameters (OTEP; DSR and MRT). Statistical modeling and regression analysis were conducted to investigate the interaction between urban form variables and OTEP. The results showed that increasing the H/W ratio by 1 reduces MRT and AT by 11.79 °C and 1.49 °C, respectively, while decreasing the SVF by 0.1 reduces MRT and AT by 4.173 °C and 0.479 °C, respectively.

Evaluation method and experimental study of sleep thermal sensation based on heart rate

Accurate assessment of sleep thermal sensation is the premise of analyzing the thermal environment of bedroom. And human metabolic rate is one of the key parameters affecting thermal sensation. This study aims to explore the evaluation method of sleep thermal sensation. The sleep metabolic rate based on heart rate are studied. And the feasibility of the evaluation method is validated by the performance of the sleep thermal sensation prediction model. The experiment was carried out in the sleep climate chamber at 23, 26, and 29 °C in summer. The sleep thermal environment parameters, physiological parameters, and subjective evaluation of 14 subjects were monitored. The experimental results showed that the mean sleep metabolic rate was 39 W/m2. And this evaluation method based on heart rate can improve the prediction performance of sleep thermal sensation model. The metabolic rate during sleep presents the U-shaped curve with time. However, compared with falling asleep, the metabolic rate was lower when waking up. This resulted in a thermal neutral temperature of sleep being 26.7°C which was 1°C higher than pre-sleep. This study will provide a reference for the operation strategy of sleep air conditioning.

The influence of perceived control on outdoor thermal comfort: A case study in a hot summer and warm winter climate

Perceived control is a psychological state experienced by individuals in their environment and is considered a critical factor in adaptive thermal comfort models. A longitudinal study lasting two and a half years was conducted in Xiamen, China, to investigate the impact of perceived control on outdoor thermal comfort. The study, carried out in an outdoor living laboratory with 56 participants, explored conditions with and without perceived control. Subjective thermal perception and thermal environment parameters were collected. Differences in outdoor thermal comfort across summer, transition seasons, and winter between participants with and without perceived control were established, and conversion formulas for thermal sensation votes were obtained. The study results indicate that: (1) The neutral mPET of participants with perceived control were 26.4 °C, 24.9 °C, and 22.3 °C in summer, transition seasons, and winter respectively, while those without perceived control were 25.2 °C, 24.6 °C, and 22.8 °C respectively. (2) Participants without perceived control tend to prefer different thermal environment (either cooler or warmer). (3) Perceived control expanded the range of acceptable thermal environment for participants in all seasons. (4) Perceived control can reduce outdoor thermal sensitivity and make participants more likely to achieve a comfortable thermal experience, but the effect varies under different thermal conditions. (5) Regardless of perceived control, global radiation and air temperature are the most crucial environmental factors affecting thermal sensation, while the impact of clothing thermal resistance and duration of stay on thermal sensation is enhanced under conditions without perceived control.

Experimental and numerical study on thermal performance of phase-change-material cool roofs in summer

Cool roofs can reduce building energy consumption and improve indoor and outdoor thermal environments. A phase change material cool roof (PCMC roof) was proposed in order to reduce roof heat gain in the indoor thermal environment in summer. Indoor thermal and energy environmental parameters in three full-size rooms (ordinary room, PCM room, and PCMC room) were tested from July to September 2022. The heat transfer characteristics and energy saving effect of roofs were investigated by combining experimental analysis with numerical analysis. Compared with the ordinary roof, the PCMC roof decreased external and internal roof surface real-time temperatures up to 30.0 °C and 6.4 °C respectively, and reduced the roof inner surface heat flux of 33.3%-66.7%. Compared with the relevant roof studies, the energy saving and cooling effects are more significant. Then, based on the mathematical model of roof heat transfer, the correlation analysis between seven different elements was carried out to evaluate the energy-saving effect of PCMC roof. This study investigates the PCMC roof from the aspects of roof heat transfer characteristics, influence on indoor thermal environment, energy saving evaluation, etc., which provides a more complete and valuable reference for advancing building roofs.