Adaptive Thermal Comfort Model Research Articles

Using setpoint temperatures based on adaptive thermal comfort models: The case of an Australian model considering climate change

It has recently become clear that using adaptive thermal comfort models to determine setpoint temperatures is a successful energy-saving method. Global models like ASHRAE 55 and EN16798-1 have been used in recent experiments using adaptive setpoint temperatures. This work, however, has taken a different route by concentrating on a region-specific Australian adaptive comfort model. The goal is to compare the energy implications of the use of setpoint temperatures based on the Australian local comfort model compared to the worldwide adaptive ASHRAE 55 model to highlight the significance of choosing the most fitting comfort model for making accurate predictions. All of Australia's climate zones are taken into account, as well as mixed-mode building operation scenarios, current and future scenarios, namely the years 2050 and 2100 for Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. It has been found that the Australian-model-based adaptive setpoint temperatures taking into account mixed-mode significantly lowers energy demand when compared to the ASHRAE 55 adaptive model (average energy-saving value of 63 %). Considering climate change, the Australian model has an average energy demand of 13–26 kW h/m2·year, and an average increase of 1–13 kW h/m2·year. In the case of ASHRAE 55 model, energy demand decreases in future scenarios and average values range between 3 and 11 kW h/m2·year. Therefore, setting setpoint temperatures in accordance with the Australian regional adaptive comfort model is a very efficient method for energy conservation. These differences raise awareness on the importance of the selection of the appropriate adaptive thermal comfort model.

Passive cooling and thermal comfort performance of Passive Downdraught Evaporative Cooling (PDEC) towers in a Saudi library: An on-site study

In the hot arid climate of Saudi Arabia, where air conditioning, primarily fueled by fossil fuels, accounts for a significant portion of energy consumption, the implementation of Passive Downdraught Evaporative Cooling (PDEC) towers presents a sustainable solution. This study conducts an extensive evaluation of PDEC towers in a public library, focusing on their effectiveness in reducing reliance on conventional cooling and enhancing thermal comfort. Through detailed field measurements, the study examines the influence of wind speed on the towers' cooling performance, correlating it with internal environmental conditions. The research extends to a comparative analysis of two prominent thermal comfort models: the Predicted Mean Vote (PMV) and the Adaptive Thermal Comfort (ATC) model. Findings indicate a notable interaction between wind speed and indoor air temperature, where increased wind speeds correspond to higher indoor temperatures. Despite this, the PDEC towers demonstrate a significant reduction in temperature, maintaining cooling effectiveness between 70 % and 75 %. The comparative study of thermal comfort models reveals that the ATC model provides a more relevant assessment of comfort levels in naturally ventilated spaces, with 71 % of the recorded temperatures falling within the comfortable range during the monitoring period. The research highlights the PDEC tower's potential in delivering effective passive cooling, adaptable to wind speed changes, and contributing to a sustainable and energy-efficient building environment in hot arid climates.

Seasonal field study on thermal comfort in university classrooms in Mediterranean climate

The assessment of indoor environmental conditions of educational buildings is not only essential to ensure the correct performance of heating, cooling and ventilation systems but it is also fundamental to guarantee a suitable environment. This study aims to analyse the thermal comfort of students in teaching–learning spaces in university buildings with natural ventilation. A field measurement campaign and a questionnaire survey were carried out from September 2021 to June 2022 in educational buildings in southern Spain. The collected data were analysed and the neutral temperature in each season was obtained, based on the thermal sensation votes of 1966. The neutral temperatures found in this study were 23.5°C, 23.1°C, 23.3°C and 23.9°C, for autumn, winter, spring and summer, respectively. The ranges obtained for 90% acceptability in the winter season (21.1°C–25.1°C) provided lower temperature limits than the ranges obtained in the summer months (22.6°C–25.3°C). The highest values for clothing insulation were found in the autumn (0.90 clo) and winter (0.75 clo) seasons, compared to the spring (0.5 clo) and summer (0.4 clo) seasons. An adaptive thermal comfort model was applied. These findings could be used to improve thermal comfort and to optimise energy consumption according to the students’ actual thermal perception.

Deriving thermal sensitivity across educational stages: Evidence-based definition of Griffiths' coefficient

Thermal sensitivity directly impacts occupants' comfort by influencing neutral temperatures and comfort models. The Griffiths method, commonly used to derive thermal sensitivity, often assumes a constant value of 0.5°C-1 for calculating occupants' neutral temperatures. However, it is important to note that thermal sensitivity can vary depending on factors such as building type, climatic conditions, operation mode (i.e., natural ventilation, mechanical ventilation, or mixed mode), and occupants' age. This study aims to define whether age-dependent differences in thermal sensitivity exist in schools, achieved through the formulation of specific Griffiths coefficients for each educational stage. A field study was conducted in naturally ventilated classrooms within the same climate zone, collecting 1548 subjective responses and objective measurements from students across different educational stages. The results demonstrate that the thermal sensitivity in schools is lower than the commonly assumed values, especially in primary schools (0.085°C-1), and it increases with students' age. This variation is reflected in the corresponding neutral temperatures, which also increase with age. Using a constant Griffiths coefficient can lead to significant estimation errors in neutral temperature, potentially up to 1 °C, impacting both comfort and energy consumption. This study emphasizes that there are different thermal comfort expectations related to students’ age. To improve the reliability of adaptive thermal comfort models and ensure accurate neutral temperatures estimations, it is essential for future research to consider the students' age when evaluating the thermal sensitivity.

Exploring thermal comfort in rural houses of Chhattisgarh state, India: A comprehensive survey and adaptive model analysis

Thermal comfort studies in India are very much at an emerging stage. According to Indian codes, in the summer, the comfortable temperature range for residential buildings is 23–26 °C. The recommended Indian residential comfort range does not consider the impact of India’s enormous cultural and geographical heterogeneity. Additionally, there seems to be very little effort to conduct a thermal comfort field survey in India’s rural regions. In recent years, houses in rural India have been converted from kutcha (mud houses) to pucca (concrete houses). This work is aimed at proposing an adaptive thermal comfort model for the premonsoon season in the rural area of Raipur, Chhattisgarh, India. The model was achieved using a field study survey conducted in 80 rural area houses in the months of June and July. Regression analysis, the Griffiths method, and the Fanger method have been adopted to analyze thermal comfort. Based on the regression analysis, the comfort band (voting −1 to +1) is established in the range of 28.39 °C to 32.31 °C, with 30.30 °C as the neutral temperature. The study has been carried out to assess the influence of gender, age, controls, and fan usage on thermal comfort perception in rural households.

Improved grey principal component analysis neural network based adaptive thermal comfort model: Application in the enclosed cabin with microclimatic conditions

Predicting the thermal comfort of operators in enclosed cabins under extreme operational conditions is crucial for the enhanced and optimal design of cabin air circulation systems. In this study, an improved supervised machine learning algorithm, namely a Grey Principal Component Analysis (G-PCA) was proposed to evaluate the operators’ thermal comfort. The comprehensive dataset was first attained and constructed from the proposed 32 indicators, which recorded each tested object’s EEG and physiological features, core body temperature, skin temperature, and subjective assessments. The accuracy of the proposed model was demonstrated by comparing it with the results predicted via existing indicator sets (PMV and 7-point skin temperature) and modelling algorithms (BP and PCA BP). The results showed that the prediction accuracy of the PMV model, 7-point skin temperature, the 32 indicators were found to be 79.4%, 82.8%, 96.1%, utilising the G-PCA WNN algorithm, and the prediction accuracy of BP, PCA BP, G-PCA WNN is 82.3%, 89.9%, 96.1%, based on the 32 indicators. A conclusion could be drawn that the proposed 32 indicators can incorporate a more comprehensive range of thermal comfort information, and the improved G-PCA WNN thermal comfort prediction model achieved the best prediction performance among the compared algorithms and models.

An investigation of indoor thermal environments and thermal comfort in naturally ventilated educational buildings

Indoor thermal conditions are essential in educational buildings. The health and well-being of students can be affected by a poor thermal environment, which also has a clear impact on building energy consumption. In this context, the indoor thermal environment in naturally ventilated university classrooms is explored in this study during a complete academic year. A monitoring campaign and a questionnaire survey were conducted simultaneously in higher education buildings in Spain. A total of 2115 sets of data were collected. Thermal sensation prediction indices (predicted mean vote, extended predicted mean vote and adaptive predicted mean vote) were applied to evaluate student’s thermal perception and their prediction accuracy was assessed. Additionally, two machine-learning models, based on Artificial neural network (ANN) and random forest (RF) algorithms, were formulated to predict occupants’ thermal sensation. The obtained results evidenced that the proposed ANN and RF models outperform traditional indices. Finally, it is also proposed an adaptive thermal comfort model. The results obtained suggest that students have a greater adaptive capacity to changes in environmental conditions than suggested by the ASHRAE-55 adaptive model and that they preferred an environment with lower temperatures than those suggested by the EN-16798 adaptive model.

A systematic approach for assessing buildings with natural materials in the Mediterranean climate

Natural building materials, including bioaggregates and biocomposites, have been making a comeback in recent years, in an attempt to minimize the Embodied and Operational Energy and Carbon (EE, OE, EC, OC) related to construction. This paper presents monitoring results of three buildings (two residential and one educational) built with such materials in the Mediterranean climate of western Crete. Temperature and relative humidity monitoring results show a very stable indoor environment behavior even when the buildings were unoccupied, thus not appropriately operated. Additional measurements undertaken and presented here include CO2 concentration in the occupied residential building with a combustion heater; and blow-door tests to better understand infiltration issues related with such construction. Results analysis shows that such materials are appropriate alternatives, definitely in bioclimatic building design for the specific climate. Indoor conditions analyzed vis-à-vis the adaptive thermal comfort model are shown to be within the thermal comfort zone, almost for all climatic conditions.

Thermal comfort in Indian naturally ventilated buildings: A comprehensive review

A significant amount of global energy is expended to meet the cooling requirements in buildings. There has been a huge shift from naturally ventilated buildings to air-conditioning with an annual shift of 15.75% considering an overall increase in extreme heat incidences in cities during summer. Studies show that reducing cooling energy consumption significantly is possible by applying passive approaches in buildings. In this study, thermal comfort in naturally ventilated buildings on a global scale, with a specific emphasis on India, has been examined through a review of existing studies. Bibliometric analysis, followed by comparative analysis, is used to identify and evaluate research on methods for assessing thermal comfort and developing adaptive models for occupants in diverse buildings and climates. It is observed that Griffith’s method is popularly used along with PMV-PPD to obtain thermal comfort interpretations in Indian naturally ventilated buildings. Moreover, the major contributors to thermal comfort studies are Europe and Southeast Asia. Further, Indian subcontinent has a wider comfort range than what international field studies have suggested. While the residents of naturally ventilated buildings in cold climates have a comfort range of 12.5–32 °C, for composite climates, the range is 15.3–33.8 °C, and for hot and humid climates, the range is 18.4–33.5 °C. Additionally, the variation in the thermal comfort range is also significantly influenced by local cultural factors. Therefore, a customized thermal comfort model that should not only reflect the unique climatic conditions but also include cultural factors of the Indian subcontinent can ensure that building occupants are provided with a comfortable and healthy indoor environment.

PENILAIAN JEJAK KARBON DAN KESELESAAN TERMAL DI BENGKEL WELDING DAN KONKRIT

Abstract: Global warming is the phenomenon of global temperature increase from year to year due to the greenhouse effect. Currently, carbon dioxide concentrations are estimated to be most dominant in the atmosphere. Therefore, this carbon footprint study will be conducted in the institutional area to determine the actual amount of CO2 present in Politeknik Kuching Sarawak institution. Research on ways to reduce carbon dioxide emissions will also be conducted indirectly. The objective of the study was to analyze carbon dioxide footprints in skill institutions that emit large amounts of gas emissions. Adaptive thermal comfort model is methods can be identified from previous readings to record or analyze data by using Air Quality Detector, Lux Meter and Anemometer. While to refer and compare the data obtained, we refer to the existing standards that are ASHRAE 55 standards and CIBSE Guide A. The result found is carbon footprint in concrete and welding laboratory in Politeknik Kuching Sarawak institution is still in the safe range but measures or proposals to reduce carbon emissions need to be initiated to maintain safety in terms of ventilation and environment in the institution.

Exploring the natural ventilation potential for supertall buildings considering vertical meteorology: A case study in Harbin, China

The natural ventilation strategy is gaining increasing attention from architects due to its advantages in reducing energy consumption and maintaining a healthy indoor environment. For supertall buildings, the vertical variation in outdoor meteorology has inspired us to explore the energy-saving potential by adopting natural ventilation strategy. This study investigates the impact of vertical variation in urban meteorology on the natural ventilation potential (NVP) of supertall buildings based on numerical simulation and field observation. Firstly, the Weather Research and Forecasting (WRF) model is used to simulate the urban meteorology of the study region by integrating the local climate zone (LCZ) map. Next, meteorological data from sounding experiments by unmanned aerial vehicle (UAV) and monitoring stations are used to validate the simulated result, and thereby to explore the vertical meteorology in urban area. Finally, the vertical NVP in supertall buildings is quantitatively assessed considering the impact of LCZ in urban areas based on thermal comfort models. The findings reveal that atmospheric temperature decreases approximately linearly with increasing altitude, with a maximum temperature gradient of up to −0.82 °C/100 m. Static models underestimated the annual natural ventilation hours (NVHs) by at least 348 h compared to the adaptive thermal comfort model. Compared to low-density building regions, the higher NVP is indicated in high-density building regions. This study aims to illustrate the importance of considering the vertical variations of urban meteorology, and is expected to assist architects and policy makers in quantifying the energy saving potential of natural ventilation in supertalls.

Holistic analysis to reduce energy poverty in social dwellings in southern Spain considering envelope, systems, operational pattern, and income levels

Energy renovations carried out in energy poor households should consider a holistic view in the short-, mid- and long-term, especially in warm areas such as Andalusia, in the south of Spain. This study addresses the existing knowledge gap on technological and economic interactions in the energy poverty of family units in warm areas of Spain. To do this, the study performs a parametric analysis. In this parametric analysis, a dataset of 36,230,400 instances was developed considering envelope, HVAC systems, an operational pattern (based on static and adaptive thermal comfort models), and family units’ income levels. Likewise, the energy poverty ratio was compared based on the high share of energy expenditure in income (2 M). The results showed that improving envelope and establishing adaptive operational patterns did not effectively reduce energy poverty cases in low-income families in the south of Spain. However, these strategies were appropriate in family units with greater incomes to remove energy poverty cases, regardless of the low reduction in energy consumption by improving the envelope. This study is a starting point to combine social aids, energy improvements and rational energy use through adaptive operational patterns.

Assessment of the energy implications adopting adaptive thermal comfort models during the cooling season: A case study for Mediterranean nursing homes

Assessment of the energy implications adopting adaptive thermal comfort models during the cooling season: A case study for Mediterranean nursing homes

Examining Occupant-Comfort Responses to Indoor Humidity Ratio in Conventional and Vernacular Dwellings: A Rural Indian Case Study

Optimum indoor humidity is often associated with comfort and overall well-being. Occupant comfort is often evaluated with a focus on “thermal comfort” using the PMV (predicted mean vote), PDD (predicted percentage of dissatisfied), and adaptive thermal comfort models. Humidity-determined comfort parameters, like skin and respiratory comfort, are well acknowledged in the scientific community, but strangely not considered for indoor comfort computations. This study proposes a new computational approach for describing and evaluating humidity-related skin comfort in buildings using skin temperature, evaporative loss, and skin wettedness as critical parameters. The Development and validation of the computational model was demonstrated through a case study in a rural Indian context. The case study involves real-time monitoring of indoor environmental parameters and humidity-determined occupant comfort votes recorded through a novel aggregated humidity comfort vote method. The simulation results were compared with the community comfort/health survey. It was observed that, even at neutral skin temperatures, an increase in skin wettedness increases the thermal sensation vote. Clothing varies according to gender, community, and personal preferences, influencing physiological parameters which determine comfort. The acceptable humidity ratio was found to be in the range of 17.4 to 22.6 g-wv/kg-da for Indian participants. Including humidity-related comfort parameters in building simulation tools would aid in selecting building materials for improved indoor comfort.

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.

Study on adaptive thermal comfort model and behavioral adaptation in naturally ventilated residential buildings, Jimma Town, Ethiopia

Ethiopia boasts abundant untapped energy resources, yet access to electricity remains limited (30%), with frequent and prolonged outages. Research on occupant thermal comfort in Ethiopia remains limited as well. This study aimed to investigate comfort temperature, adaptive models, and behavioral adaptations in naturally ventilated residential buildings in Jimma town, Ethiopia. Our thermal comfort field survey involved 870 occupants from 104 houses, generating 5220 datasets between February and September 2020. Indoor environments were simultaneously measured using handheld digital instruments. Notably, the subjects lacked electrical fans, space heaters, or air-conditioners, relying instead on charcoal and plant residue for cooking and heating.Overall, only 56.2% of subjects felt comfortable within the thermal sensation scale's defined band, while 70.9% preferred either warmer or cooler environments, and 63.4% accepted their environments. The mean comfort temperature was 23.3˚C ± 3.44 based on all data. Our adaptive model predicted a 1.82 K perturbation in outdoor running mean temperature, resulting in a unit change in indoor comfort temperature. Significant occupant behavioral adaptation through operable environmental controls, clothing choices, and activity levels was observed. Our model is essential for building simulation in Ethiopia, emphasizing the need for an Ethiopian adaptive standard. Given the limited modern energy sources, understanding low-energy thermal comfort and human adaptation becomes vital for sustainable living conditions.

A novel comfort temperature determination model based on psychology of the participants for educational buildings in a temperate climate zone

Maintaining thermal comfort in the educational buildings is vital due to the impacts on learning effectiveness of students. Therefore, development of a proper comfort temperature in educational buildings is a must. In naturally ventilated and mixed-mode buildings, the adaptive thermal comfort model, which considers additively psychological, and behavioural factors to the Fanger's PMV/PPD model, is commonly applied based on regression analyses. However, the psychological adjustments based on current mood state are very limited in these adaptive thermal comfort models. Therefore, this study focuses on the psychological adjustments in terms of Profile of Mood States in order to predict comfort temperature of students in a case building. The experiments are conducted in a university on a temperate climate zone for a long period-data including both heating and cooling seasons. In this study, the comfort temperatures for each student are determined via Griffith method for the case building. Moreover, the current mood states of students are assessed utilizing the Profile of Mood States survey, which are collected via a developed mobile application. As a conclusion, the relation between the current mood state of the students and comfort temperature are statistically investigated. The results show that a Griffith constant are found as 0.332/K and mean annual comfort temperature is found as 21.32 °C in the case building. Additionally, a significant difference is found in the comfort temperatures among the students who have more, or fewer concerns than typically reported. The novelty of the study is to present a comfort temperature determination model which considers human psychology as a starter study in the literature.

Impact of outdoor particulate matter 2.5 pollution on natural ventilation energy saving potential in office buildings in China

Natural ventilation improves building energy performance and indoor air quality, but its potential is hindered by outdoor pollution. This paper aims to evaluate the impact of outdoor Particulate Matter 2.5 (PM2.5) pollution on natural ventilation energy saving potential in office buildings in China. Firstly, a typical office building in five representative cities across all climatic regions was designed. Secondly, related weather data were obtained and preprocessed. Thirdly, a computer model was developed under the EnergyPlus environment with smart window ventilation control, space temperature reset using adaptive thermal comfort model, and a validated pollution transportation model that calculates the indoor PM2.5 concentration. The computer model was applied to three air-conditioning systems, i.e., constant air volume (CAV), variable air volume (VAV), and variable refrigerant flow (VRF) with three evaluation indices. The results show that the natural ventilation hours rate with/without considering the outdoor PM2.5 concentration level were 15%–55% and 28%–67%, respectively. Energy savings varied across regions, with mild regions having the highest potential and cold regions having the least. CAV demonstrates the highest energy savings, followed by VAV and VRF, except in Guangzhou where VAV performs the worst. This study contributes to understanding the impact of outdoor pollution on natural ventilation potential and provides practical insights for energy-saving strategies in office buildings. Its originality lies in the evaluation methodology, comprehensive approach, sophisticated computer model, comparative analysis of air-conditioning systems, and practical implications for energy-savings. The research outcomes can guide building facility engineers in implementing ventilation control strategies while maintaining indoor thermal comfort.

Dynamic comfort criteria – A possible solution to the conflict between heat balance and adaptive thermal comfort models

Physiologists typically assume that optimal thermal comfort can only be achieved by minimizing thermoregulatory efforts. People are thus believed to be thermally comfortable with a mean skin temperature of 33–34 °C and minimized sweating rate at a low metabolic rate. Many heat balance comfort models are established based on these fixed comfort criteria. However, occupants’ thermal requirements are found to be more flexible and dynamic because of physiological and psychological adaptions. In this study, dynamic comfort criteria (DCC) are proposed to consider the adaption in the PMV model. Occupants tend to accept a lower skin temperature in a cold climate and a slightly higher sweating rate in a hot climate. We provide two methods to infer DCC based on ASHRAE thermal comfort database II. One is to develop a generalized DCC that can be applied globally. Another is to use Bayesian calibration to develop a customized DCC that further localizes the thermal requirements. With DCC, the deficiency of the PMV and the adaptive model can be largely eliminated. Unlike PMV, the model with DCC performs consistently in different operation modes. DCC is conceptually different from actual physiological responses, although they can sometimes be close to each other in values. The study paves the road for unifying comfort theories and equipping traditional comfort models with the ability to re-learn.

Mejora del desempeño térmico de colegios en la Región Altoandina del Perú. El caso del “módulo prefabricado aula tipo heladas - PRONIED”

Faced with the qualitative and quantitative deficit of educational infrastructure in Peru’s rural high Andean areas, in recent years the Peruvian State has been investing in and supporting modular solutions, seeking efficiency in the construction processes. The specific proposal, with special emphasis on bioclimatic design, is the "Prefabricated Frost-type Modular Classroom". However, users have been expressing discomfort with these new facilities. This study shows the measurement process carried out on a built module, which allowed calibrating and validating the model using simulation software, to propose improvements in the design that may contribute to future constructions. Taking the adaptive thermal comfort model as a reference, it was confirmed that indoor temperatures were below thermal comfort limits in the early hours of the morning and well above them close to noon, by around 6 ºC and 7 ºC respectively. With the application of complementary bioclimatic strategies, it was possible to considerably improve indoor thermal conditions, although not enough to reach comfort early in the morning. This is because the night-time outdoor temperatures are very low, the building is uninhabited all night long, there is no thermal mass in the envelope, and there are no active solar systems or mechanical air conditioning.