Search Results (31)

This study employs a multi-method, high-precision research approach to evaluate the thermal comfort performance of a window-based direct evaporative cooling (DEC) air conditioning system installed in a university dormitory building (50 rooms) in Beijing. To compensate for the insufficiency of single-day test data, the study was conducted continuously for 30 days from 1 June to 30 June 2026 (00:00–23:59 daily). Eight calibrated sensor sets were deployed in each of the 50 rooms (that is, eight fixed sensor sets per room × 50 rooms = 400 synchronously logged spatial measurement points, each integrating a fixed SHT35 temperature/humidity sensor with a matched hot-wire anemometer probe; this unusually dense, building-scale simultaneous deployment is uncommon in previous dormitory studies), recording data simultaneously across all rooms throughout the test period with the DEC units continuously operating. The research integrates field physical measurement data, standardized subjective questionnaire surveys (200 within-person paired questionnaires, each pairing a student’s retrospective recall of the pre-DEC condition with an in situ vote collected during DEC operation), and advanced computational thermophysiological modeling results based on the frameworks of ISO 7730–2021 and ASHRAE Standard 55–2023. Environmental parameters, including dry-bulb temperature (Ta), relative humidity (RH), and air velocity (Va), were monitored at eight spatially distributed points per room with a 10 Hz sampling frequency and a one-hour median resolution. The mean radiant temperature (Tr) was approximated as equal to Ta due to the absence of globe temperature measurements, and this simplification is discussed as a limitation. Simultaneously, through a single-session questionnaire (June 24–30) compliant with ISO 10551 and the Appendix B requirements of ANSI/ASHRAE Standard 55, which paired each respondent’s retrospective recall of the early-June pre-DEC (non-cooled) condition with a concurrent vote collected during DEC operation—a recalled-pre/concurrent-post design rather than two separate real-time pre-/post-intervention surveys—data on clothing ensembles, activity levels, and subjective thermal sensation votes (TSV) were collected. The acquired data were input into a customized simulation platform developed in the Fortran language (which was debugged and cross-validated against the ISO 7730/ASHRAE Standard 55 reference implementation to within 0.01 PMV scale units), which employs the Fanger two-node thermoregulation model to accurately calculate and predict the predicted mean vote (PMV), predicted percentage of dissatisfied (PPD) occupants, new effective temperature (ET*), and standard effective temperature (SET*). The results indicate that the DEC unit achieved a stable outlet temperature reduction of Δt = 3.87 °C (inlet temperature 31.72 °C, outlet temperature 27.85 °C), with an average wet-bulb air temperature of 18.66 °C and an average outlet relative humidity of 58.3% (inlet RH: 42.1%), confirming the expected humidifying effect of direct evaporative cooling while maintaining an average indoor relative humidity of 42.07%—a result particularly relevant to Beijing’s dry-to-semi-humid summer environment, where evaporative cooling is thermodynamically favorable. Because no DEC-off baseline period was monitored, the measured indoor conditions are reported as observational associations with DEC operation rather than as effects attributable exclusively to the unit; the pre-DEC satisfaction level was recalled retrospectively within the same single session and is therefore subject to recall/contrast bias; and all energy-saving figures are theoretical nameplate estimates rather than metered energy consumption. Full article

Driven by the demand for high-quality housing, fourth-generation residential buildings—known internationally as “Vertical Forest” and in China as “Urban Forest Garden”—have developed rapidly. Initially built in mild southern regions, they have recently expanded to colder northern areas, with over 50 projects underway in provinces such as Shanxi, Hebei, Shaanxi, and Gansu. Several cities have introduced design standards and incentives, and the China Association for Standardization of Engineering Construction has issued the “Design Standards for Urban Forest Garden Housing.” However, in cold regions, where winters are long and cold and summers are short and hot, there is a lack of systematic quantitative research on how balcony design affects building carbon reduction, energy efficiency, and indoor thermal comfort. To address this research gap, this paper poses the following research questions: (1) In fourth-generation residential buildings in cold regions, how do different combinations of balcony orientations affect annual energy consumption and indoor thermal comfort? (2) Which balcony configurations offer the best balance between carbon reduction, energy efficiency, and thermal comfort? Based on statistical analysis of terrace configurations from more than 40 projects, 12 typical configuration models were identified. Using Ladybug and Honeybee tools on the Grasshopper platform, building energy consumption and indoor thermal comfort were simulated. Multi-objective trade-off analysis was performed using the Pareto front method. In this study, indoor thermal comfort was evaluated using the PMV (Predicted Mean Vote) index. PMV is an index proposed by Professor Fanger that comprehensively reflects human thermal sensation, taking into account air temperature, humidity, wind speed, mean radiant temperature, human metabolic rate, and clothing thermal resistance. Its typical range is −3 (cold) to +3 (hot); in this study, the comfort zone was defined as −1 ≤ PMV ≤ 1. Key findings: (1) The southwest + south terrace configuration shows the highest annual energy consumption, exceeding the lowest (northwest + west) by 2.7%, indicating that south-facing terraces are less favorable for carbon reduction. (2) The best thermal comfort is achieved with east, west, and south orientations. Compared to the least comfortable combination (southwest + northwest), the difference in PMV comfort percentage reaches 2.4%. (3) The Pareto front reveals that beyond a certain comfort level, energy consumption increases sharply. The west + south and east + south combinations yield the highest thermal comfort (49.4%) while maintaining relatively low energy consumption (17.98 kWh/m²). Therefore, in cold regions, fourth-generation residential designs should prioritize terrace combinations integrating south-facing and side-facing orientations and avoid pure corner configurations to balance winter solar gain and summer shading. Full article

Achieving adequate thermal comfort in classrooms in hot cities in southern Mexico is challenging. A heterogeneous distribution of air conditioning flow leads to thermal discomfort, affecting occupants’ academic performance and increasing energy consumption. This study evaluates the thermal comfort of occupants in an air conditioned classroom using computational fluid dynamics. We determined the effects of variations in air conditioning operating parameters (supply angle, velocity, and temperature) on PMV and modified PMV indices. An operating configuration of 60°, 3 m/s, and 22 °C ensures that thermal comfort remains within regulations while optimizing energy consumption, in contrast to the original PMV model. Using the modified PMV model, the values are 0.38 for students and 0.31 for the teacher, with percentages of dissatisfied individuals of 10% and 7.7%, respectively. This study demonstrates the importance of analyzing air conditioning operating parameters to enhance thermal comfort while reducing energy consumption. Full article

Non-contact measurement of human skin temperature is an important area of research. Infrared temperature devices have played a critical role in measuring skin temperature without physical contact. Thermal cameras have also been employed for non-contact skin temperature measurements. However, both infrared devices and thermal cameras have limitations that restrict their use in the building industry for assessing occupant thermal comfort. The building industry requires sophisticated equipment capable of measuring human temperature non-invasively and, through integration with building control systems, adjusting the environment to meet occupants’ thermal comfort needs. Unfortunately, standard thermal cameras and infrared temperature sensors are not designed with building applications in mind. This paper proposes an affordable and building-compatible thermal camera designed to measure occupant skin temperature via a non-contact method, enabling better integration with building control systems to support occupant comfort. Experimental results demonstrate that the proposed system can reliably capture facial skin temperature and establish a quantifiable relationship between facial and room temperatures. Moreover, this provides a foundation for future real-time thermal comfort and building-control applications. Full article

Due to global weather changes and pandemics, people are more likely to spend most of their time in indoor environments. In this regard, indoor environment quality is a very important aspect of occupant well-being, which is often ignored in modern building designs. Based on our research, thermal comfort is one of the essential items in building environments that can improve the mental stability and productivity of the occupants if the building’s indoor environment is created in a way that meets the occupants’ comfort requirements. Buildings nowadays operate on adaptive or stationary models to attain thermal comfort, which is based on Fanger’s model of the Predicted Mean Vote (PMV). Based on the literature review, limited work has been carried out to enhance the quality of the inside environment, and most research work has been devoted to building energy management. Moreover, there have been no definite solutions so far that have the capability to detect the thermal comfort requirements of multiple occupants in real time. Modern buildings tend to operate on predefined set point parameters to control the indoor environment based on the measured room temperature, which can be different from the thermal comfort requirements of the occupants. This paper discusses the limitations and assumptions that are associated with the existing thermal comfort solutions and emphasises the importance of having a real-time solution to address the thermal requirements of occupants. Full article

The building sector accounts for 30% to 40% of total energy consumption, and historic buildings play an important role in this proportion. Historical buildings that do not meet the required comfort conditions for the residents are adaptively reused, with various revisions. Recognizing the energy design of a historical building in its original condition and comparing the current situation can help create future solutions. This study examines the changes that a historic house in a hot climate zone in Türkiye experiences, from its original state up until the current situation. Energy analyses of the pre- and post-restoration situation are carried out, and the effect of adaptive reuse decisions on the energy performance of the building is investigated. A dynamic thermal simulation created with DesignBuilder was used to identify the energy use, carbon emissions, and thermal comfort. TM59 adaptive thermal comfort was used for the pre-restoration and the Fanger model for the post-restoration phase. This building, which was repurposed from a three-block residence, consists of a four-block hotel. Although the preservation of its original value is at the forefront, various structural changes were observed. The analysis demonstrates a higher occurrence of discomfort hours during summer compared to winter, consistent across both phases. Furthermore, energy consumption increased significantly, predominantly for heating, representing a doubling of energy use during the post-restoration phase. This is attributed to the building’s conversion into a hotel and the use of mechanical systems. Future research is required to develop strategies to reduce the energy consumption, carbon emissions, and discomfort hours while maintaining the value of the historic building and its materials. Full article

Massive construction systems have always characterized traditional architecture and are currently the most prevalent, straightforward, and cost-effective in many Mediterranean countries. However, in recent years, the construction industry has gradually shifted towards using lightweight, dry construction techniques. This study aims to assess the effects on energy consumption, comfort levels, and environmental sustainability resulting from the adoption of five high-performance construction systems in a multi-family residential building: (i) reinforced concrete structure with low-transmittance thermal block infill; (ii) reinforced concrete structure with light-clay bricks and outer thermal insulation; (iii) steel frame; (iv) cross-laminated timber (CLT); (v) timber-steel hybrid structure. To achieve this goal, a multidisciplinary approach was employed, including the analysis of thermal parameters, the evaluation of indoor comfort through the adaptive model and Fanger’s PMV, and the quantification of environmental and economic impacts through life cycle assessment and life cycle cost applied in a long-term analysis (ranging from 30 to 100 years). The results highlight that heavyweight construction systems are the most effective in terms of comfort, cost, and long-term environmental impact (100 years), while lightweight construction systems generally have higher construction costs, provide lower short-term environmental impacts (30 years), and offer intermediate comfort depending on the thermal mass. Full article

This paper considers microclimate to be one of the main contributors to thermal comfort in educational buildings. The influence of microclimate on well-being and productivity is considered. The role of microclimatic parameters is assessed from the perspective of building design, focusing on approaches to regulating these parameters. We also describe the formation of microclimate and the factors directly affecting it. The state of the microclimate of classrooms of an educational institution was analyzed, providing estimates of people’s real thermal sensations. The microclimate was assessed by the Fanger method. The PMV and PPD comfort indices were calculated for this purpose. The calculations were carried out thrice, i.e., based on the data obtained by using measuring equipment, based on the data from the survey and based on a SolidWorks model. Calculations in the program were carried out to validate the measured values and visualize the process of the distribution and localization of comfort indices. The results confirm that the indoor microclimate was generally favorable, and the PMV values obtained from the survey of people’s real sensations of thermal comfort were higher than the calculated PMV values. It was established that the PMV and PPD values corresponding to the largest deviations from the norm were as follows: −0.74/17% (PMV/PPD) for the calculation based on the real values of microclimatic parameters and 0.70/15.3% (PMV/PPD) for the calculation based on people’s thermal sensations. For applying the Fanger method for thermal comfort analysis in an educational institution in St. Petersburg, we upgraded the procedure, introducing a questionnaire survey. The mean PMV values calculated by the Fanger method were 0.16 lower than the PMV values obtained by the survey. Full article

With the growing interest in radiant heating and cooling systems, driven by their improved efficiency and enhanced thermal comfort compared to air systems, there is an increasing need to develop a more accessible method for designers to understand the implications of radiation heat exchange between the human body and radiant panels. To address this, a novel angle factor calculation model, named the HNU Angle Factor Model, was developed, taking into account the spatial arrangement and geometric relationship between the human body and radiant panels. The angle factors obtained using the HNU Angle Factor Model exhibited good agreement with the results obtained with Fanger diagrams and the contour integral method, with average relative differences of 8.1% and 10.0% for 140 cases, respectively. Furthermore, placing a radiant panel on the floor while maintaining its fixed size can contribute to the creation of an even and efficient thermal environment for individuals in both seated and standing positions. By implementing the HNU Angle Factor Model in practical engineering applications, more effective utilization of radiant systems can be achieved, as it provides an evaluation of the heat transfer between the human body and radiant panels. Full article

Heating, ventilation, and air conditioning (HVAC) system performance research has received much attention in recent years. Many researchers suggest a set of appropriate fuzzy inputs that can be used to design fuzzy rules-based smart thermostats or controllers that can respond to demand-controlled ventilation, which in turn optimizes HVAC energy usage and provides satisfactory indoor temperatures. Previous research has focused on limited input parameters, such as indoor occupancy status, ambient temperature, and humidity constraints, which cannot efficiently and precisely manage thermal comfort. Hence, this study proposes a novel fuzzy controller with additional input parameters to keep indoor thermal comfort consistent with the corresponding number of occupants. The process employs an automatic fuzzy rule generation method to simplify the task of generating rules in the fuzzy inference system (FIS) using Mamdani FIS. A design-builder is used for modeling the HVAC systems. Local weather data were used to conduct simulations via EnergyPlus. The thermal comfort analysis using the Fanger model for three different scenarios shows that the proposed FIS controller can successfully respond to the indoor comfort variation in all possible scenarios and ensure a satisfactory comfort level. The proposed method demonstrates up to 50% energy savings if occupants do not worry about comfort. Full article

Energy-efficient automated systems for thermal comfort control in buildings is an emerging research area that has the potential to be considered through a combination of smart solutions. This research aims to explore and optimize energy-efficient automated systems with regard to thermal comfort parameters, energy use, workloads, and their operation for thermal comfort control in indoor spaces. In this research, a systematic approach is deployed, and building information modeling (BIM) software and energy optimization algorithms are applied at first to thermal comfort parameters, such as natural ventilation, to derive the contextual information and compute the building performance of an indoor environment with Internet of Things (IoT) technologies installed. The open-source dataset from the experiment environment is also applied in training and testing unique black box models, which are examined through the users’ voting data acquired via the personal comfort systems (PCS), thus revealing the significance of Fanger’s approach and the relationship between people and their surroundings in developing the learning models. The contextual information obtained via BIM simulations, the IoT-based data, and the building performance evaluations indicated the critical levels of energy use and the capacities of the thermal comfort control systems. Machine learning models were found to be significant in optimizing the operation of the automated systems, and deep learning models were momentous in understanding and predicting user activities and thermal comfort levels for well-being; this can optimize energy use in smart buildings. Full article

Climate change is becoming a crucial factor to consider within human activities and the building sector is particularly influenced by aspects of internal comfort and energy. In Italy, great attention has been paid to the energy refurbishment of buildings. However, such interventions are mostly focused on reducing heating energy consumption, thus neglecting summer season performance. Moreover, climate change is barely considered during the design phase. This issue is addressed in this work which analyzes some of the most common refurbishment interventions applied to a social housing building in Trieste, while also considering internal comfort during the summer season. A dynamic analysis of the building-plant system is carried out using EnergyPlus. Fanger, UTCI and the adaptive comfort models were used to represent internal health, while three TRY data sets were generated using two GCM–RCM projections to evaluate the influence of climate change. The results show that both building insulation and climatic change affect heating consumption reaching a 70% reduction. However, building insulation does not greatly affect internal comfort, although different models show different behavior to protect against external temperatures. On the contrary, climatic change influences the percentage of hours of discomfort, with a 20% increase for all of the models. The final consideration is that people’s internal health should always be considered when carrying out refurbishment activities. Full article

Since P.O. Fanger proposed PMV, it has been the most widely used index to estimate thermal comfort. However, in some cases, it is challenging to measure all six parameters within indoor spaces, which are essential for PMV estimation; a couple of parameters, such as Clo or Met, tend to show a large deviation in accuracy. For these reasons, several studies have suggested methods to estimate PMV but their accuracies were significantly compromised. In this vein, this study proposed a way to reduce the dimensions of parameters for PMV prediction utilizing the machine learning method, in order to provide fast PMV calculations without compromising its prediction accuracy. Throughout this study, the most influential features for PMV were pinpointed using PCA, Best Subset, and the Gini Importance, with each model compared to the others. The results showed that PCA and ANN achieved the highest accuracy of 89.70%, and the combination of Best Subset and Random Forest showed the fastest prediction performance among all. Full article

The building sector greatly contributes to energy consumption and Greenhouse Gas emissions, relating to the whole building life cycle. Boasting a huge building heritage of historical and architectural value, Europe faces challenging retrofit perspectives, as the potential for high energy efficiency has to be exploited while preserving the buildings’ original characteristics. The present work aims to feature the influence of a passive strategy on a heritage building in a mild climate. As historical its façade cannot be modified, its large glazing areas involve multiple issues, such as an increase in the heating ($Q_H)$ and cooling ($Q_C$) energy demands and the risk of thermal discomfort. Thus, window replacement was proposed for retrofitting. A dynamic simulation model in TRNSYS was validated with experimental data collected by the continuous monitoring of walls of different thicknesses and orientations. Solutions from replacement with Double Glazing Units (DGUs) with improved thermal insulation, to internal shading activation were applied. All configurations were compared in terms of $Q_H$, $Q_C$, thermal performance of the building and user comfort (Fanger). Low-e DGU enabled the saving of up to 14% of the annual energy demand, and shading also offered good results in summer, reducing $Q_C$ by 19%. In summer, DGU involved a maximum PPD reduction of 10 units. Full article

Remote work can have many benefits when set up properly. Nevertheless, the preferences of home workers’ comfort havenot been profoundly studied yet. Therefore, this study aims to understand their accepted Indoor Environmental Quality values in winter based on self-reported comfort. In this regard, 26 households in Catalonia’s Mediterranean region were monitored and surveyed for separated periods of 15 days during from 22 November 2021 to 6 March 2022. Measurements including temperature, temperature, CO₂ and Relative Humidity levels were data logged in their most used workspace. Results show that most people work between 18 °C to 20 °C and find those temperatures acceptable. Common spaces used as homeoffices are on average 0.8 °C warmer and there are 470 ppm lower CO₂ concentrations. Families with children or teenagers and especially women tend to have a warmer mean operative temperature. The comparison between theoretical thermal comfort models (Fanger and Adaptive) to direct vote perception from a sample of spaces and conditions shows low correlation with real perception having the Adaptive model a better prediction of votes. In general, people report feeling more comfortable at the office, although a high number of participants feel indifferent or reckon that depends on other factors. Full article