Thermal Comfort Research Articles

A methodological framework for sustainable housing for displaced populations

AbstractThis research highlights the role of sustainability aspects focusing on socio-cultural parameters and environmental performance in designing more comfortable and sustainable shelters. Following a two-mixed method approach, on the one hand, a comparative analysis is presented of IKEA Better Shelter, Rwandan Mud-Brick, and Nepali shelters by examining the cultural integration into their design (traditional layouts and shared spaces), their adaptability, and their environmental performance. On the other hand, a qualitative survey determines the level of satisfaction regarding space, comfort, social interaction, and cultural fit among residents. The results show that traditional building methods with the use of local materials, offer high privacy levels, excellent thermal and acoustics comfort, good cultural appropriateness and minimal environmental impact.

A novel PCM-based foam concrete for heat transfer in buildings -Experimental developments and simulation modelling

Foam concrete is renowned for its lightweight and versatile properties, such as good thermal insulation, airborne sound absorption and adequate compressive strength. Phase change materials are recognized for their heat storage characteristics. The current study investigates the enhancement of building envelope thermal performance by integrating phase change materials in foam concrete composites. The phase change material (PCM) developed using exfoliated vermiculite impregnated with capric acid and absolute ethanol demonstrated optimal thermal stability. Among the various foam concrete mix composites, PCM in addition to the nano silica and coconut fibre (PNC) mix showed improved mechanical and thermal properties. Test results showed that optimum mix (PNC-5 %) possess a compressive strength of 7.96 MPa, with a thermal conductivity of 0.15 W/mK. The nano silica added in the PNC mix reacted with CH rapidly for the formation of C-S-H and filled the pores, which improved the bonding and reduced the brittleness of the samples, which is also evident from the SEM images. The PNC-5 % sample mixture exhibited a melting and freezing point of 31.42 °C and 21.08 °C respectively, with a latent thermal storage 9.72 J/g for freezing and 17.55 J/g melting. Scanning electron microscopy and thermogravimetric analysis confirmed the compatibility and high thermal resistance of PNC-5 %. TGA results confirmed that the mass loss corresponding to CH content was slightly lesser for the PNC-5 % mixture than for the PCM mixture, due to the inclusion of nano silica in the case of PNC-5 %. COMSOL Multiphysics ® software model analysis is implemented for validation of thermal characteristics of the developed PCM-impregnated foam concrete wall panel for insulation in buildings, emphasizing the potential for enhanced thermal comfort compared to that of noninsulated structures. This research proves the efficacy of PNC insulated foam concrete composites for sustainable and energy-efficient building solutions, paving the way for advancements in building applications.

Dashboard for interpreting future climate files used in the simulation of buildings – An outdoor thermal comfort approach

The Earth’s changing climate significantly affects the built environment, including thermal comfort and energy demand. This study introduces a code pipeline and a dashboard to create and interpret future climate files (EPW format) used in building simulations, focusing on outdoor thermal comfort. The code pipeline uses the Future Weather Generator (FWG) to generate city climate forecasts. It also integrates the climatic data with thermal comfort indices like the Universal Thermal Climate Index (UTCI) and Discomfort Index (DI). Then, a dashboard is used to assess the country’s outputs and provide a comprehensive tool for researchers, policymakers, and practitioners to assess and mitigate climate change impacts on buildings and cities, ensuring accurate inputs for thermal comfort and energy efficiency modelling. A case study was carried out in Brazil, simulating all 578 available EPW files. Predictions indicate an overall increase in dry bulb temperature and changes in the country’s relative humidity, radiation, and wind speed. Given the specific changes in different bioclimatic zones, a tailored tool is essential for understanding local conditions. The key benefit is the creation of up-to-date validated weather files crucial for climate-adaptive planning.

Thermal comfort evaluation of a Rammed Earth residential building: case study: Yazd city in Iran

ABSTRACT The main purpose of this research was to determine the thermal conductivity of Rammed Earth walls and assess thermal comfort in RE houses, particularly in the hot and dry climate of Yazd city. For this work a thermal conductivity test was performed on a Rammed Earth sample, and the wall's thermal resistance was calculated to evaluate thermal comfort conditions in a Rammed Earth building. Subsequently the building was simulated and were investigated using Fanger's comfort factors. (Fanger factors: Predicted Mean Vote [PMV] and Predicted Percentage of Dissatisfied [PPD]). Laboratory tests were performed, and a thermal resistance of 0.49 m2k/W was obtained for a 30 cm Rammed Earth wall. This lead to the consideration of a technical solution by Iran's national building regulations, Article 19. Based on this article, a three-layer wall with intermediate thermal insulation and a thickness of 10 cm for the external walls was designed. In this way, the wall's thermal resistance increased from 0.49 to 2.14 m2k/W, improving comfort conditions compared to walls without thermal insulation. It is recommended to increase the thermal insulation thickness from 10 to 15 cm to achieve fully comfortable conditions. Based on the results, the use of Rammed Earth is not recommended, and it appears that adobe material has historically been the best choice for the hot and dry climate of Iran.

Experimental and numerical study on thermal performance of energy storage interior wall with phase change materials

Phase change materials (PCM) and embedded tube radiant terminals demonstrate considerable advantages with respect to heat storage, energy savings, and the provision of comfort in buildings. This paper puts forth the concept of an energy storage interior wall (ESIW) with embedded pipe radiant technology, comprising PCM, and coupled with low-grade energy sources. Compared to traditional TABS, this system uses PCM energy storage to compensate for the instability of solar energy supply, which expands the application scenarios of clean energy. At the same time, it can greatly improve the thermal mass of the building and provide cooling and heating for multiple rooms. Experimental results demonstrate that the ESIW is capable of markedly enhancing the thermal comfort and indoor temperature, with an average increase of 9.9 °C relative to the outdoor. In the numerical study based on test data, sensitivity analysis was performed on 10 characteristic parameters of the ESIW structure: wall thickness, wall density, wall thermal conductivity, wall specific heat capacity, PCM phase change temperature, PCM pipe diameter, PCM enthalpy, PCM pipe length, pipe flow diameter, and number of rows of PCM pipes. The results show that the key parameters affecting the first objective (thermal storage capacity) are: pipe flow diameter, wall density, wall thickness, and PCM pipe diameter; and the key parameter affecting the second objective (investment cost) is the diameter of the PCM pipe. After multi-objective optimization for these two objectives, the thermal storage capacity of the ESIW was improved by 96.7 %, and the investment cost was reduced by 11.49 %.

A deep reinforcement learning control method for multi-zone precooling in commercial buildings

In commercial buildings, implementing precooling measures before office hours in summer can effectively meet the thermal comfort needs of employees. However, in multi-zone environments, differences in the cooling rates between regions often exacerbate the heat transfer interference between zones, increasing the complexity of the precooling system and leading to energy waste with limited cooling capacity. To overcome these challenges, we have developed a novel multi-zone precooling control method, which integrates deep reinforcement learning (DRL) to optimize the heat transfer process by adjusting the Air Handling Units (AHUs) valve openings, thus achieving uniform precooling across the building. Comparisons with traditional precooling control methods demonstrate the effectiveness of the proposed method. The results show that, under conventional conditions, compared with the rule-based control (RBC) and proportional integral derivative (PID) methods, the precooling time is reduced by 11.4% and 5.8%, respectively, the complexity of heat transfer is reduced by 77.6% and 64.1%, and energy consumption is reduced by 14.5% and 9.3%. In addition, the study analyzes the influence of environmental parameters on precooling optimization. The findings indicate that weather conditions have the most substantial impact on short-term precooling performance, followed by building thermal performance and cooling conditions.

Assessing the impact of adjacent urban morphology on street temperature: A multisource analysis using random forest and SHAP

Urbanization has significantly transformed land use patterns, intensifying environmental challenges such as the urban heat island (UHI) effect and increasing health risks in urban public spaces. Urban streets, as vital public spaces, frequently experience heat accumulation during summer due to various environmental factors. Existing research has focused primarily on microscale case studies, leaving the broader impact on adjacent areas unclear. Therefore, this study examines the influence of morphology features within street-adjacent buffers on street temperatures in Nanjing, China, utilizing multisource data and machine learning. The random forest algorithm, combined with the Shapley additive explanation (SHAP) interpretation, was applied to analyze the impact of adjacent street morphological features on the land surface temperature (LST) of streets. The results suggest that greenery, buildings, and surface morphology features within street-adjacent buffers are crucial in regulating street temperatures. Furthermore, this study explains the variations in the factors influencing the thermal environments of different typical street types via K-means clustering analysis. The findings offer insights for sustainable urban planning strategies aimed at mitigating extreme heat and enhancing thermal comfort in urban pedestrian spaces.

Development of a tailored questionnaire instrument to evaluate thermal sensation of elderly people in India

Purpose India’s growing elderly population necessitates ensuring indoor thermal comfort because of their vulnerability to temperature-related illnesses and reduced capacity to regulate body temperature. Currently, thermal sensation (TS) assessment scales, designed for those between 20 and 60 years of age, may not accurately capture the preferences of elderly adults. To address the gap, this study aims to identify appropriate scaling methods to help the elderly understand the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE-55) seven-point TS scale clearly. Design/methodology/approach Four scaling methods – color, emoji, landscape images and regional images scales – identified from literature were analyzed using quantitative approaches. The differences between two age groups (<60 years and = 60 years) were examined using frequency distribution differences and independent sample t-test methods. Findings Results indicated that both younger/middle-aged (<60 years) and elderly individuals (= 60 years) were adept at identifying color and regional images scale, while emoji and landscape images scale posed challenges for the elderly. Furthermore, a tailored questionnaire instrument was developed to enhance the comprehension of TS questions for the elderly. One sample t-test results indicated that the proposed questionnaire instrument is a better fit to support ASHRAE-55 seven-point TS scale, making it particularly effective for the elderly population. Originality/value This research presents a novel, tailored questionnaire instrument that significantly enhances the elderly population’s comprehension of TS questions, thereby improving the accuracy of thermal comfort assessments and contributing to the creation of better indoor thermal environments for the elderly people.

Solar-powered thermo-pneumatic actuators for passively controlled adaptive shading

Abstract The operational energy demand of buildings plays a significant role in global energy consumption. Especially, the energy required for cooling is predicted to rise due to climate change. Adaptive shading is a promising approach to save operational energy in buildings.
State-of-the-art adaptive shading systems employ both active and passive actuation as well as control strategies, to lower energy consumption while maintaining the thermal and visual comfort of building occupants. However, both approaches still must overcome challenges that hinder widespread adoption. Active systems need motors and pumps, dedicated power supplies, and control electronics. These components make the systems heavy and complex to maintain and repair. Passive systems work without dedicated power supplies and control electronics but can face limitations based on the active materials used, e.g., material degradation, toxicity, narrow response windows, and unknown performance in varying conditions. This work presents a solar-powered, thermo-pneumatic actuator for use in adaptive shading applications that works without specialized active materials, electronic actuation and controls. The actuator incorporates elastic bellows to transform the thermal expansion of air into motion and adapts to changes in irradiance. The actuator is built as a functional prototype and its performance in different irradiance scenarios is evaluated. The actuator is capable of considerable motion, moving a rotational mechanism close to 90° powered by an irradiance of 1000 W/m². The actuator response is sensitive enough to react to hourly changes in irradiance as well as to a simulated solar cycle. The paper concludes with the presentation of a shading device concept incorporating the actuator to highlight its potential for use in adaptive shading applications to reduce operational energy in buildings.

An analysis of outdoor thermal comfort impact on pedestrian walking patterns at sub-hour timescales with agent-based modelling

PurposeThis study aims to analyse the impact of outdoor climate, building configuration and locations of public amenities on pedestrians’ walking behaviour and their outdoor thermal comfort. As outdoor climate can rapidly change within minutes, this study maintains that outdoor thermal comfort should be analysed at the pedestrian scale and within a short period to understand people’s walking behaviour and how it may affect urban activities.Design/methodology/approachThis research analyses the thermal stresses experienced by pedestrians and their walking patterns within a sub-hour timeframe in Darling Square, Sydney. The simulation incorporates multiple outdoor climate analyses with agent-based modelling (ABM) simulation; it runs on a parametric modelling platform to predict walking patterns according to the agents’ innate properties, goals and environmental constraints as the weather fluctuates.FindingsThis study demonstrates that mapping outdoor thermal comfort within a shorter timescale could reveal emergent walking patterns that inform pedestrians’ preferences of their surrounding environment and their walking behaviour.Practical implicationsThe findings could inform planners and stakeholders on how outdoor climate and building configuration affect pedestrian walking patterns for improving outdoor space quality during the design process or post-occupancy evaluation.Originality/valueThis study integrates ABM that incorporates multiple agents’ goals and innate properties and a micro-climate analysis on diverse context geometries under sub-hour periods, compatible with the pedestrian walking speed and distances at the neighbourhood scale.

Investigating thermal comfort indices in relation to clothing insulation value: A survey of an outdoor space in Tehran, Iran

With the increasing impacts of climate change, there is a need for more accurate assessments of thermal comfort. This study addresses the limitations of current thermal indices in accommodating variations in clothing insulation, which is a critical behavioral adaptation influencing human thermal comfort. Many existing indices, such as Physiologically Equivalent Temperature (PET) and Standard Effective Temperature (SET*), rely on fixed clothing insulation values that may not accurately represent real-world conditions due to environmental, cultural, and behavioral variability. In contrast, some indices like the modified Physiologically Equivalent Temperature (mPET) and the Universal Thermal Climate Index (UTCI) allow for adjustable clothing insulation; however, UTCI's fixed values can be insufficient in regions with distinctive clothing practices, impacting its accuracy. This study evaluates the effectiveness of thermal comfort indices by conducting a field survey and questionnaire, collecting a total of 838 data sets. The analysis employs various methods, including sensitivity and specificity analysis, principal component analysis (PCA), alluvial diagrams, and polynomial charts. Findings highlight the limitations of fixed insulation values in indices such as PET and SET*, while emphasizing mPET's superior accuracy in predicting outdoor thermal comfort. PCA identified clothing insulation (Icl) as a significant personal factor affecting thermal comfort across diverse environments. This research reveals differing correlation coefficients at higher insulation levels (1.11-1.26 clo and 1.26-1.56 clo), with SET* exhibiting substantial variability (0.33) compared to mPET, which demonstrated the least variability (0.46). These results underscore the need to revise existing thermal comfort indices to incorporate more dynamic and context-sensitive insulation values for improved thermal predictions.

An indoor thermal comfort model for group thermal comfort prediction based on K-means++ algorithm

Predicting indoor thermal comfort plays an essential role in controlling energy consumption in buildings. Existing studies have used supervised machine learning to predict thermal comfort, which were more accurate than traditional models. However, these models required occupants’ subjective feedback for model training, which reduced the accuracy of the model. In this study, a prediction model that didn’t require feedback was proposed for the first time using the K-means++ algorithm based on the ASHRAE Global Thermal Comfort Database II. Firstly, the data quality was improved through feature selection, dimensional processing, and feature weighting. Then the influence of different outlier judgment methods, feature weight and data set size on model accuracy were compared. Finally, the K-means++ algorithm was applied for thermal comfort clustering analysis. The result showed that the model with an accuracy higher than 90 % could be constructed using only three factors (CLO, TA, RH), and the proposed model could predict indoor group thermal comfort reliably, and provide a foundation for the indoor thermal sensation evaluation.

Improving thermal comfort using personalized local conditioning: A large-scale retrospective questionnaire survey conducted during a heatwave in China

The increasingly frequent heatwaves caused by global warming indicate that more energy consumption is required to maintain individuals' thermal comfort and health. Understanding how to utilize local conditioning for optimizing conditioning devices and creating a comfortable environment is crucial. Due to variations in individuals' adaptability to their surroundings, people from different climatic zones exhibit different needs for environmental conditioning. Current research findings in built environments have not adequately explained how individuals in various climatic zones use local conditioning to meet these diverse thermal needs. Therefore, it is highly important to conduct quantitative research on individuals' willingness to use local conditioning and their preferences across different climatic zones. To address this issue, a retrospective survey of 2,247 participants across five climate zones in China was conducted over a two-month period. The results revealed that many participants chose to use local conditioning to further improve thermal comfort, even if they initially felt comfortable. Participants from the severe cold and cold zones preferred water-cooled fans and floor fans, whereas floor fans were the preferred choice in other zones. Price and convenience were the main factors considered when selecting local conditioning devices (average composite score > 7). Differences in the methods, duration, parameter settings, placement of local conditioning, and regulated body parts varied among participants from the five climate zones. These results aid in improving our understanding of thermal comfort and health in high-temperature environments during summer.

Optimal control strategy for a cutting-edge hybrid ventilation system in classrooms: Comparative analysis based on air pollution levels across cities

Natural ventilation has the potential to enhance indoor air quality in classrooms with elevated CO2 levels, although it may introduce outdoor pollutants. This study introduces a novel controller for automatic windows that simultaneously monitors outdoor air pollution and temperature, synchronizing window openings with mechanical ventilation system to create a comfortable, healthy, and energy-efficient indoor environment. The practicality of the proposed controller is assessed for a classroom in Delhi, Warsaw, and Stockholm, each with contrasting climates and outdoor pollution levels, specifically PM2.5 and NO2. The controller parameters are optimized for each city using a non-dominated sorting genetic algorithm (NSGA-II) to find the best trade-off between thermal comfort, CO2 levels, and energy consumption. The results show that the controller successfully met the indoor air quality standards in all cities; however, its operation was significantly influenced by the climate and pollution levels. While natural ventilation was utilized for 44% and 31% of the year in Warsaw and Stockholm, respectively, it was used for only 11% of the year in Delhi, the most polluted city. The optimization process significantly reduced energy use across all cities while also successfully reducing indoor CO2 concentrations. Although thermal comfort decreased slightly, it remained within acceptable thermal comfort conditions.

Comparative study on the correlation between human local and overall thermal sensations based on supervised machine learning

In heterogeneous indoor environments, significant perceptual discrepancies exist among different body parts concerning their environmental sensitivity. Understanding the relationship between Local Thermal Sensation (LTS) at various body sites and the Overall Thermal Sensation (OTS) is essential for both theoretical inquiry and practical application. Previous studies have predominantly occurred within artificially controlled climatic chambers, with relatively fewer investigations conducted in situ. This study investigates the relationship between LTS and OTS among university students of differing genders in both air-conditioned and non-air-conditioned classroom settings in colder regions. Various supervised machine learning (SML) algorithms were utilized to analyze the data, evaluating their efficacy in predicting the relationship between LTS and OTS and their respective influence weights. The findings demonstrate a significant nonlinear positive correlation between LTS and OTS across different air conditioning settings and genders. Additionally, the Random Forest (RF) algorithm achieved the highest accuracy in predicting LTS weights, with an accuracy exceeding 80%. The study also revealed differences in the influence weights of different body parts across genders and conditions; however, across all conditions, the head and neck region consistently exhibited the highest weight, while the feet displayed the lowest.

A comparison of heating and cooling systems having radiant and ventilation systems regarding thermal comfort

A comparison of heating and cooling systems having radiant and ventilation systems regarding thermal comfort

Behaviour pattern in the air-conditioner usage of the elderly living in a nursing home during winter nights - A case in Chongqing, China

The indoor thermal environment during winter nights significantly affects the elderly's sleep quality. In nursing homes in Chongqing, China, room air conditioners (RACs) are commonly used to regulate indoor temperatures and ensure a comfortable sleeping environment for elderly residents. Despite their widespread use, there is limited understanding of how elderly individuals utilize RACs and their specific thermal needs during winter nights. This study examines the RAC usage patterns and thermal environment preferences of elderly residents in a nursing home in Chongqing. The real-time RAC usage and indoor temperature conditions of sixteen elderly participants were monitored. The findings reveal notable differences in RAC usage between the pre-sleep and sleep stages. Specifically, the RAC was used 15 % more frequently and set to a temperature 2 °C warmer in the pre-sleep stage compared to during sleep. Additionally, varying thermal needs was observed throughout the night, leading to distinct RAC usage patterns categorized into low-demand and high-demand operations. Factors such as outdoor temperature, time of night, and the number of occupants were identified as key predictors of RAC usage among the elderly. This study provides valuable insights into the thermal comfort needs of elderly residents and highlights the importance of tailored RAC management for improving sleep quality in nursing homes.

Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm

Abstract. This study investigates the optimization of multilayer glass thickness to maximize solar heat gain in buildings located in cold northern climates, utilizing the Ant Colony Optimization (ACO) algorithm. The research focuses on enhancing thermal comfort and reducing energy consumption by optimizing the thickness of three glass layers, thereby improving solar energy transmission into indoor spaces. ACO, a metaheuristic inspired by the foraging behavior of ants, is employed due to its robustness in handling complex optimization problems. The study incorporates wavelength-specific considerations into the ACO framework to achieve a sophisticated optimization approach, resulting in improved solar energy transmission. The experimental results demonstrate that the optimized glass configuration significantly increases sunlight transmittance, especially within the target wavelength range, contributing to more energy-efficient and comfortable architectural designs. This research highlights the potential of ACO in optimizing building materials and suggests further refinement of the algorithm for enhanced performance in real-world applications.

Impact of Urban Surfaces on Microclimatic Conditions and Thermal Comfort in Burdur, Türkiye

Rapid urbanization worldwide offers numerous benefits but also introduces challenges, particularly concerning urban climate comfort, which affects the physical and social well-being in cities. This study examined the microclimatic characteristics of the Burç neighborhood in the historical core of Burdur city, using ENVI-Met models with temperature, relative humidity, wind and PET data collected over a 33,665 m2 area at 06:00, 09:00, 12:00, 15:00, 18:00 and 21:00 on 15 August 2023. The analysis revealed that thermal comfort decreases significantly from 09:00 onwards, especially on hard surfaces like asphalt, concrete and parquet, which lack vegetation and intensify heat retention. By contrast, green areas were found to enhance bioclimatic comfort by reducing perceived temperatures by up to 20% in shaded and vegetated zones. Based on these findings, it is recommended that urban areas reduce heat-absorbing materials, such as asphalt and concrete and prioritize green spaces in landscape planning to improve thermal comfort and create more sustainable urban environments.

Multi-objective optimization of office building envelopes properties and Venetian blinds using NSGA-II to save energy consumption and enhance thermal and visual comfort

Since the building industry has grown to be a significant energy user, offering practical solutions can aid in addressing this significant problem. Windows are among the most crucial architectural elements since they let in the majority of the natural light that enters the structure. On the one hand, improper window and associated component design causes the space to overheat and consume more energy; on the other hand, it compromises the inhabitants of the building's thermal and visual comfort. This research presents a novel method for multi-objective optimization of control parameters for smart shade curtains and architectural standards. By using this suggested method, building energy consumption is significantly reduced and thermal and visual comfort are improved. EnergyPlus software is used to run simulations about energy. Subsequently, JEPLUS software has considered 28 design aspects, such as hour groove angle, building cover requirements, material dimensions and specifications, control techniques and adjustment points, and shading position and direction. These simulations are run for nine cities with varying climates in four distinct geographic orientations throughout the year. The program JEPLUS + EA is utilized for data improvement. To extract the ideal points on the Pareto front, the data is optimized using the NSGA-II algorithm. The optimization findings indicate that the inner curtain outperforms the outside curtain. Additionally, the visual comfort improves with a narrower slat angle (SA), but the illumination requires more power. The multi-objective optimization of the controlled blind characteristics yielded results that, depending on the building's geographical orientation, reduced the building's overall energy consumption by 4–30 % annually while improving thermal and visual comfort, with ranges of 64–11 % and 60–81 %, respectively.