Thermal Comfort Level Research Articles

Dynamic interdependence of comfortable thermal conditions and energy efficiency increase in a nursery school building for heating and cooling period

The paper studies the influence of building function and orientation, level of thermal insulation on energy efficiency and occupant thermal comfort dynamic interdependence. Energy state dynamic modelling of the typical preschool educational facility (Kyiv, Ukraine) was carried out with different levels of thermal comfort in each of the zones, taking into account occupants' activity, metabolism, clothing, etc. The research was conducted for the heating and cooling periods, taking into account the operational peculiarities of the building. Increasing the thermal resistance from the base version to the Swedish norms reduces energy consumption by 32% for the heating period, compared to the base version. The introduction of intermittent heating leads to a reduction of energy consumption by 14%, compared to the base version. Intermittent heating and ventilation and increased thermal protection to Swedish standards can reduce energy consumption by 42%. The investigation of comfort indicators revealed that during the transition period when the heating is turned off, electric heating of the premises is required to maintain the comfort conditions, which increases the heating energy consumption by 18%. Three different options for children's clothing in the summer period to avoid feeling cold were investigated.

Experimental Study of Indoor Air Distribution and Thermal Environment in a Ceiling Cooling Room with Mixing Ventilation, Underfloor Air Distribution and Stratum Ventilation

A ceiling cooling system integrated with a mechanical ventilation system has been widely used in modern buildings with large sensible cooling loads due to the high thermal comfort level and large energy efficiency. However, there is a lack of systematic research on the influence factors such as ceiling surface temperature and cooling load on the indoor air distribution and thermal environment, and the impact of ventilation system type in the ceiling cooling room is still unclear. Therefore, this paper presented an experimental study of indoor air distribution and thermal environment in a ceiling cooling (CC) room with mixing ventilation (MV), underfloor air distribution (UFAD) and stratum ventilation (SV); the ceiling surface temperature was 17 °C–26 °C and the internal or external cooling load was 41.5 W/m2–69.5 W/m2. The results showed that the vertical air temperature difference and contaminant removal effectiveness were 0.2 °C–0.4 °C and 0.53–0.85 with CC + MV, 0 °C–1.2 °C and 0.68–1.25 with CC + UFAD and 0.3 °C–0.9 °C and 0.50–0.83 with CC + SV, and the corresponding heat removal effectiveness and air diffusion performance index were 0.96–1.11 and 96–100%, 0.9–1.5 and 57–100% and 1.11–1.34 and 71–100%, respectively. Moreover, the difference between mean radiant temperature and air temperature and the predicted mean vote of thermal sensation were from 0 °C to 0.9 °C and between 0 and 0.26 with CC + MV, from −0.1 °C to 2.2 °C and between −0.1 and 0.42 with CC + UFAD and from −0.1 °C to 0.9 °C and between −0.2 and 0.13 with CC + SV. Hence, the ventilation system type clearly affected the indoor air distribution and thermal environment in the ceiling cooling room, and the experimental results would be beneficial for the design and control of a ceiling cooling system combined with a mechanical ventilation system in practice.

Comprehensive renovation and optimization design of balconies in old residential buildings in Beijing: A study

This study presents a comprehensive approach to renovating and optimizing balconies in old residential buildings in Beijing. Firstly, it explores residential balconies' evolution, characteristics, and development trends to identify various sample types and understand the associated problems and residents' needs related to balconies through investigation. Secondly, the Rhino/Grasshopper parametric platform is employed to simulate the performance and analyze data from standard balcony types, resulting in five qualitative and four quantitative renovation strategies and methods. Subsequently, these comprehensive renovation and optimization design strategies are implemented in the renovation process, and their performance is simulated. The daylight autonomy (DA), universal daylight indicator (UDI), and spatial daylight autonomy (sDA) metrics experienced significant increases of 16.56, 20.12, and 0.13, respectively, indicating improved light environment and functionality. Notably, the proposed strategies maintain consistent energy consumption and thermal comfort levels. Both PMV and PPD have improved, but the improvement is not significant, only by 0.01. The window-to-wall ratio has been increased by 0.1, and insulation has been added. The overall thermal comfort value is stable. These findings validate the practicality and effectiveness of the proposed approach and methods. This study provides valuable references for renovating and optimizing balconies in old residential buildings, contributing to problem-solving efforts and enhancing living quality.

Impervious Surface Area Patterns and Their Response to Land Surface Temperature Mechanism in Urban–Rural Regions of Qingdao, China

The expansion of impervious surface area (ISA) in megacities of China often leads to land surface temperature (LST) aggregation effects, which affect living environments by impacting thermal comfort levels, thus becoming an issue of public concern. However, from an urban–rural synchronous comparison perspective, the study of LST responses to ISA changes is still lacking in the central coastal megalopolises of China. To solve this issue, a collaborative methodology of artificial digitization—fully constrained least squares mixed pixel decomposition—split-window algorithm—PCACA model was established for Qingdao using land use dataset and remote sensing images. The conclusions are below. Long time series of land use monitoring indicated that the expansion ratios of urban and rural areas were 131.29% and 43.42% in the past 50 years (i.e., from 1970 to 2020). Within urban and rural areas, a synchronous ISA increase was observed, with ratios of +9.14% (140.55 km2) and +7.94% (28.04 km2), respectively. Higher ratios and area changes were found in the urban regions, and a similar ISA change pattern in both urban and rural regions was captured by the ISA horizontal epitaxial expansion and vertical density enhancement. Further, the horizontal gradient effect displayed that the mean LSTs were 28.75 °C, 29.77 °C and 31.91 °C in the urban areas and 28.73 °C, 29.66 °C and 31.65 °C in the rural areas in low-, medium-, and high-density ISAs. The vertical density effect showed that the LST change was 1.02 °C and 2.14 °C in the urban areas but 0.93 °C and 1.99 °C in the rural areas during the ISA-density transition from low- to medium- and from medium- to high-density, respectively. Potential surface thermal indicators were assessed, and the urban regions displayed higher sensible heat flux (280.13 W/m2) compared to the rural regions (i.e., 274.76 W/m2). The mechanism effect of the ISA changes on LST in the urban and rural regions was revealed. These findings form a new comparative perspective of the urban–rural synchronous change in the central coastal megalopolis of China and can provide a practical reference for relevant studies.

Investigating the effectiveness of the Building’s envelope materials in hot and arid climates to achieve indoor thermal comfort

Envelope Building materials play an important role in architecture by providing protectionnecessities, comfort, and technical performance while promoting an architectural language and an image.The building envelope represents all the surfaces of a space, which consist of opaque parts such as walls,floors and roofs and transparent parts such as windows and openings. The building envelope is thepartition between the external and internal environment of the building which influences the heat transferbetween the two environments so it has a direct impact on the thermal comfort sensation which alsoinfluences the energy consumptions. This research focuses on the opaque building materials of theenvelope and their contribution in the thermal comfort and the energy consumption; an investigation ofthe impact and the thermal behavior of different envelope configuration materials under the climaticconditions of Biskra was carried, Algeria a hot and arid climate. The thermal performance of differentmaterials was compared using in situ measurement using “Testo 480” a hygrothermal scale and byanalyzing the results of a different simulation using “DesignBuilder v5.5” to perform a thermal andenergy analysis. The results show that choosing a multilayered isolated envelope such as double red brickisolated wall will likely affect positively the level of the indoor thermal comfort.

The Effect of Lowering Indoor Air Temperature on the Reduction in Energy Consumption and CO2 Emission in Multifamily Buildings in Poland

This article analyzes the possibility of reducing the energy consumption from building heating as a result of lowering the indoor air temperature, which is recommended as a response to the energy crisis. Various values of the set-point temperature (16–22 °C), as well as different scenarios for their changes, were assumed for analysis. Changes in clothing that were determined to maintain the same level of thermal comfort after a temperature change were determined. The associated reduction in CO2 emissions emitted into the atmosphere was determined. The effect of reducing CO2 emissions was studied depending on the type of heating source. Simulation calculations were carried out for an exemplary multifamily building. The effect of different building insulations required in Poland over the years 1964–2022 was considered. Analyses were performed for the climatic conditions of cities located in different climatic zones of Poland: Koszalin, Wroclaw, Warsaw, Bialystok, Suwalki. Depending on the scenario, the insulation standard of the building, and the variant of location, the energy reduction achieved ranges from 6.6%/K to 13.2%/K. Taking into account the type of heating source, the reduction in CO2 emissions is from 0.7 to 7.5 kgCO2/(K·m2). The reduction in temperature by 1 or 2 K can be compensated for by wearing an additional sleeveless vest (0.12 clo) or sweater (0.28 clo).

Optimizing demand-controlled ventilation with thermal comfort and CO2 concentrations using long short-term memory and genetic algorithm

Heating, ventilation, and air conditioning systems are the largest consumers of energy in commercial and residential sectors. Minimizing their energy consumption without compromising indoor air quality and thermal comfort would result in environmental and financial benefits. However, most buildings still utilize constant air volume systems with on/off control to meet the thermal loads. Previous studies show that CO2-based demand-controlled ventilation is the most widely used strategy to determine the optimal level of supply air volume. Conventional CO2 mass balanced models, however, do not take the thermal comfort level into account. This paper aims to develop and implement a practical and efficient optimization framework to help office building designers and operators enhance thermal comfort and indoor air quality while minimizing energy costs for ventilation using demand-controlled ventilation. The objective function was constructed to consider thermal comfort indices, indoor air quality, and ventilation power demand. Long Short-Term Memory networks in conjunction with a generic algorithm optimization were utilized to generate the search spaces and solve the objective function. The proposed optimization strategy achieved near-optimal results within approximately 1 h of computation time. The findings indicate a reduction of the average ventilation power by 5.6% compared to the current on/off control approach and a slight increase of 0.25% in ventilation power when compared against the minimum ventilation rate recommended by ASHRAE. Additionally, the optimized approach leads to a saving of 26.9 kg per day of greenhouse gas emissions in terms of carbon dioxide equivalent.

Thermal Comfort Improvement Strategies for Outdoor Spaces in Traditional Villages Based on ENVI-Met: Shimengao Village in Chizhou City

The thermal comfort of outdoor spaces in traditional villages must be improved because high building density combined with complex and narrow spaces leads to a poor thermal environment. In traditional villages, outdoor spaces are the most frequently used places by local residents and tourists. In this study, the Shimengao Village in Tangxi Town, Chizhou City, a typical mountainous area in the southern Anhui Province, was selected as the research object, and Depthmap software was used to identify the most frequently used outdoor spaces. The spatial layout and three different outdoor spaces of the traditional village were measured and validated using ENVI-met software. In addition, the distribution of thermal comfort in the core area of the village and influencing factors were analyzed. Our results demonstrated that during summer, PET reached its highest value at 15:00, exhibiting a poor thermal environment in the core area of traditional village integration. From 15:00 to 21:00, PET values declined, resulting in improved thermal comfort levels. Open spaces had better thermal comfort ratings throughout the day. The thermal comfort distribution of three different types of outdoor space in traditional villages was also analyzed. The courtyard space had the worst thermal comfort, followed by the street space, whereas the square space had the best thermal comfort environment. This was correlated with the spatial layout of traditional villages, external facilities of buildings, microlandscapes (plants, water availability, etc.), and outdoor ground materials. Hence, we propose that optimizing the overall spatial layout of a traditional village, increasing the external facilities of buildings, creating “micro landscapes,” and optimizing the materials of outdoor spaces are important for improving the thermal comfort of the outdoor spaces of traditional villages.

Relationship between Visual and Thermal Comfort and Electrodermal Activity in Campus Blue–Green Spaces: A Case Study of Guangzhou, China

The rapid speed of urbanization in modern cities has led to various environmental challenges impacting human activities, livelihoods, and comfort. One of these effects is the urban heat island, which describes the increase in temperature in an urban area resulting from the replacement of natural surfaces with concrete, buildings, and other structures that absorb and retain heat. Variations in individual perception and adaptative ability present additional challenges when trying to ensure outdoor comfort and require advanced measuring instruments and simulation tools to accurately predict a broad range of related variables. In this study, we investigated three different types of blue–green spaces (six in total) on the campus of Guangzhou University, focusing on their distinct layouts. The aim was to evaluate these spaces’ microclimate and sunlight intensity conditions by quantifying several environmental factors. Subjective comfort assessments and objective physiological parameter measurements were conducted using questionnaires and biosensors, respectively. The results revealed the following: (1) Different types of blue–green spaces exhibit distinct microclimate and visual environment characteristics, and while similar patterns emerged, certain environmental parameters revealed important differences. (2) There is a significant association between individuals’ thermal and visual comfort in blue–green spaces and multiple environmental factors. (3) Linear regression analysis demonstrated the strong predictive capabilities of skin conductance indicators (Rsc, SCR, and nSCR) in assessing individuals’ outdoor visual–thermal comfort levels, with R2 exceeding 0.5, indicating high accuracy. These findings provide valuable insights and references for urban planners and designers seeking to enhance the visual and thermal aspects of sustainable landscapes on campuses as well as in other outdoor environments.

Data analysis and interpretable machine learning for HVAC predictive control: A case-study based implementation

Energy efficiency and thermal comfort levels are key attributes to be considered in the design and implementation of a Heating, Ventilation and Air Conditioning (HVAC) system. With the increased availability of Internet of Things (IoT) devices, it is now possible to continuously monitor multiple variables that influence a user’s thermal comfort and the system’s energy efficiency, thus acting preemptively to optimize these factors. To this end, this paper reports on a case study with a two-fold aim; first, to analyze the performance of a conventional HVAC system through data analytics; secondly, to explore the use of interpretable machine learning techniques for HVAC predictive control. A new Interpretable Machine Learning (IML) algorithm called Permutation Feature-based Frequency Response Analysis (PF-FRA) is also proposed. Results demonstrate that the proposed model can generate accurate forecasts of Room Temperature (RT) levels by taking into account historical RT information, as well as additional environmental and time-series features. Our proposed model achieves 0.4017 °C and 0.9417 °C of Mean Absolute Error (MAE) for 1-h and 8-h ahead RT prediction, respectively. Tools such as surrogate models and Shapley graphs are employed to interpret the model’s global and local behaviors with the aim of increasing trust in the model.

Performance analysis of transparent BIPV/T double skin façades integrated with the decision-making algorithm for mixed-mode building ventilation

ABSTRACT This study addresses building performance profiles of building-integrated photovoltaic/thermal double-skin façades (BIPV/T-DSF) integrated with the decision-making for the opening control algorithm in the mixed-mode building ventilation system. Three cases were generated and simulated in this study. The integrated case (a focused case) indicated its potential in comparison with two other fixed single-mode ventilated BIPV/T-DSF cases (non-ventilated cavity and cavity ventilated BIPV/T-DSF cases). The mixed-mode building ventilation algorithm was logically generated and implemented in the integrated case to maximize passive heating and cooling while reducing energy consumption, increasing the indoor thermal comfort level, and preventing the overheating of BIPV. The temperatures of spaces used as major criteria in the developed algorithm were identified through optimization analysis. Three cities were chosen to represent three different climates: hot summer continental and cold winter climate (Daejeon, South Korea), tropical savanna (Bangkok, Thailand), and continental subarctic (Tayshet, Russia). Multi-criteria simulation results showed that implementing the logically created mixed-mode building ventilation algorithm in a transparent BIPV/T-DSF has outstanding potential to improve thermal comfort, especially during moderate weather, and somewhat reduces energy consumption compared to the two other studied cases.

Research on Online Temperature Prediction Method for Office Building Interiors Based on Data Mining

Indoor environmental parameters are closely related to the energy consumption and indoor thermal comfort of office buildings. Predicting these parameters, especially indoor temperature, can contribute to the management of energy consumption and thermal comfort levels in office buildings. An accurate indoor temperature prediction model is the basis for implementing this process. To this end, this paper first discusses the input and output parameters of the model, and then it compares the prediction effects of mainstream prediction model algorithms based on data mining under the same data conditions. The superiority of the XGBoost integrated learning algorithm is verified, and a further XGBoost-based indoor temperature online prediction method is designed. The effectiveness of the method is validated using actual data from a commercial office building in Haidian District, Beijing. Finally, optimization methods for the prediction method are discussed with regard to the scheduler mechanism proposed in this paper. Overall, this work can assist building operators in optimizing HVAC equipment running strategies, thus improving the indoor thermal comfort and energy efficiency of the building.

Habitability Studies of a Replica Fremont-style Pithouse

A full-sized Fremont-style pithouse was reconstructed to explore habitability. The results are: (1) the pithouse dampens daily and seasonal temperature fluctuations; (2) a wood and leather access closure was thermally more effective than a stone slab; (3) computational fluid dynamics (CFD) modeling shows the superstructure affects interior ventilation; (4) a floor-level vent is necessary for adequate ventilation and CFD modeling indicates its position relative to prevailing wind is important; (5) once reached, the thermal comfort level of 16.5°C can be maintained by body heat alone. Ancillary information acquired during construction and subsequent destruction of the pithouse: (6) the estimated time required by a Fremont community to construct a pithouse is roughly 538 person-hours; (7) expediting the burning of the structure required an animal fat accelerant and ventilation holes cut into the superstructure; and (8) nearly a half-hour of burning occurred before there was an abrupt catastrophic roof collapse.

Numerical investigation of thermal-humidity environment in pedestrian area of ecological community with the porous pavement in arid areas

In this paper, the water evaporation from porous pavement is used to improve the thermal-humidity environment (THE) in pedestrian area of ecological community at the large wind and sand, and arid areas, such as Lanzhou in northwest China. A simulation model is established to analyze the THE of ecological community with the porous pavement in arid areas. And the water evaporation is considered from plant transpiration and porous pavement in this model. The simulation results are compared with the experimental results, the relative error was less than 13.5%. At the same time, the THE is also analyzed under different building layout, building spacing and building height. The results show that the average value of universal thermal climate index (UTCI) in pedestrian area increases with the building height, while the minimum value has little difference. This means that the local thermal discomfort would more likely occurs in ecological community with the building height increase. The local value of UTCI in pedestrian area decreases by about 8℃ when the building spacing is changed from 10 m to 40 m. The uniformity of UTCI is greatly improved when the building spacing rises to 25 m. The array building layout should be adopted in Lanzhou, the building spacing should be at least 25 m when the building height is 50 m. The above research results can provide theoretical guidance for improving the thermal comfort level of ecological community in Lanzhou.

Optimization Control Strategy for a Central Air Conditioning System Based on AFUCB-DQN

The central air conditioning system accounts for 50% of the building energy consumption, and the cold source system accounts for more than 60% of the total energy consumption of the central air conditioning system. Therefore, it is crucial to solve the optimal control strategy of the cold source system according to the cooling load demand, and adjust the operating parameters in time to achieve low energy consumption and high efficiency. Due to the complex and changeable characteristics of the central air conditioning system, it is often difficult to achieve ideal results using traditional control methods. In order to solve this problem, this study first coupled the building cooling load simulation environment and the cold source system simulation environment to build a central air conditioning system simulation environment. Secondly, noise interference was introduced to reduce the gap between the simulated environment and the actual environment, and improve the robustness of the environment. Finally, combined with deep reinforcement learning, an optimal control strategy for the central air conditioning system is proposed. Aiming at the simulation environment of the central air conditioning system, a new model-free algorithm is proposed, called the dominant function upper confidence bound deep Q-network (AFUCB-DQN). The algorithm combines the advantages of an advantage function and an upper confidence bound algorithm to balance the relationship between exploration and exploitation, so as to achieve a better control strategy search. Compared with the traditional deep Q-network (DQN) algorithm, double deep Q-network (DDQN) algorithm, and the distributed double deep Q-network (D3QN) algorithm, the AFUCB-DQN algorithm has more stable convergence, faster convergence speed, and higher reward. In this study, significant energy savings of 21.5%, 21.4%, and 22.3% were obtained by conducting experiments at indoor thermal comfort levels of 24 °C, 25 °C, and 26 °C in the summer.

Comparative Analysis of the Surface Urban Heat Island (SUHI) Effect Based on the Local Climate Zone (LCZ) Classification Scheme for Two Japanese Cities, Hiroshima, and Sapporo

The Local Climate Zone (LCZ) classification system is used in this study to analyze the impacts of urban morphology on a surface urban heat island (SUHI). Our study involved a comparative analysis of SUHI effects in two Japanese cities, Sapporo and Hiroshima, between 2000 to 2022. We used geographical-information-system (GIS) mapping techniques to measure temporal LST changes using Landsat 7 and 8 images during the summer’s hottest month (August) and classified the study area into LCZ classes using The World Urban Database and Access Portal Tools (WUDAPT) method with Google Earth Pro. The urban thermal field variance index (UTFVI) is used to examine each LCZ’s thermal comfort level, and the SUHI heat spots (HS) in each LCZ classes are identified. The research findings indicate that the mean LST in Sapporo only experienced a 0.5 °C increase over the time, while the mean LST increased by 1.8 °C in Hiroshima City between 2000 and 2022. In 2000, open low-rise (LCZ 6) areas in Sapporo were the hottest, but by 2022, heavy industry (LCZ 10) became the hottest. In Hiroshima, compact mid-rise (LCZ 2) areas were the hottest in 2000, but by 2022, heavy-industry areas took the lead. The study found that LCZ 10, LCZ 8, LCZ E, and LCZ 3 areas in both Dfa and Cfa climate classifications had unfavorable UTFVI conditions. This was attributed to factors such as a high concentration of heat-absorbing materials, impervious surfaces, and limited green spaces. The majority of the SUHI HS and areas with the highest surface temperatures were situated near industrial zones and large low-rise urban forms in both cities. The study offers valuable insights into the potential long-term effects of various urban forms on the SUHI phenomenon.

Assessing indoor thermal comfort of rock-cut architecture in Meymand world heritage site during winter and summer

Rock-cut architecture is among the unique types of ancient architecture in Iran, which creates human living space by excavating the stone mass in the rocks. The rock-cut architecture benefits from utilization of the temperature of the groundmass in cold and hot weather by penetrating its heart. The World Heritage Site of rock-cut architecture in Meymand with more than 360 architectural units is considered as an evolved and appropriate example of such architecture in the semi-hot and dry foothill climate of Iran. The present study aims to determine indoor thermal comfort level of some buildings in the site as mentioned earlier to measure their fitness to climatic conditions of the area without energy consumption. To this aim, Predicted Mean Vote (PMV) index was determined for four selected buildings through the indoor bioclimatic monitoring, as well as calculating the level of the above-mentioned index during December–February and June–August.​ Then, the ASHRAE standard questionnaire was prepared to evaluate and compare the comfort sensation feedback of the occupants in the aforementioned buildings with indoor PMV calculation results. The results indicated that the average indoor PMV during the winter and summer equaled -2.17 and -1.07 with a cold and cool sensation, respectively, which is in line with those of the questionnaire in which most occupants reported a neutral and cold sensation during the winter and a cool one during the summer. In addition, calculation of the percentage of proximity to the comfort zone for indoor environment of the above-mentioned buildings showed they are closer to comfort by 22% and 36%, during the winter and summer, respectively Finally, the results indicated the rock-cut architectural buildings had provided conditions by applying the high thickness of their architectural layers, low heat exchange coefficient of the walls, and temperature of the groundmass, which they are in the comfort zone without energy consumption in summer and provide living conditions with minimal energy consumption in winter.

Fast Human-in-the-Loop Control for HVAC Systems via Meta-Learning and Model-Based Offline Reinforcement Learning

Reinforcement learning (RL) methods can be used to develop a controller for the heating, ventilation, and air conditioning (HVAC) systems that both saves energy and ensures high occupants' thermal comfort levels. However, the existing works typically require on-policy data to train an RL agent, and the occupants' personalized thermal preferences are not considered, which is limited in the real-world scenarios. This paper designs a high-performance model-based offline RL algorithm for personalized HVAC systems. The proposed algorithm can quickly adapt to different occupants' thermal preferences with a few thermal feedbacks, guaranteeing the high occupants' personalized thermal comfort levels efficiently. Firstly, we use a meta-supervised learning algorithm to train an occupant's thermal preference model. Then, we train an ensemble neural network to predict the thermal states of the considered zone. In addition, the obtained ensemble networks can indicate the regions in the state and action spaces covered by the offline dataset. With the personalized thermal preference model updated via meta-testing, model-based RL is used to derive the optimal HVAC controller. Since the proposed algorithm only requires offline datasets and a few online thermal feedbacks for training, it contributes to a more practical deployment of the RL algorithm to HVAC systems. We use the ASHRAE database II to verify the effectiveness and advantage of the meta-learning algorithm for modeling different occupants' thermal preferences. Numerical simulations on the EnergPlus environment demonstrate that the proposed algorithm can guarantee personalized thermal preferences with a slight increase of power consumption of 1.91% compared with the model-based RL algorithm with on-policy data aggregation.

Holistic Approach to Ecological Design Parameters of Building and Landscape Design on Outdoor Thermal Comfort in Hot, Humid Climate

In this study, academic staff residential buildings were studied as part of a university campus located in a hot and humid climate zone in Türkiye. Within the scope of the study, the energy efficient architectural and landscape design decisions of the buildings built in 1976 were examined. The aim was to determine the energy performance of buildings built about 50 years ago and to quantify the effect of changing landscape conditions on thermal comfort. In this aim, the outdoor thermal comfort level was determined by creating microclimate simulations for the hottest day and time of the year. Microclimatic analyses were performed with ENVI-met software and thermal comfort was evaluated with two metrics, average PMV and ASHRAE scale. The energy performance of the buildings was determined using ecological design parameters. An approach to global environmental problems is the use of ecological design principles, including architectural and landscape design principles. It is important to consider both architectural design criteria and landscape design criteria when discussing ecological design in the built environment. Architectural and landscape design decisions for hot and humid climate regions together increased energy efficiency by 51.1% to 75.5%. It was found that although the plant design improves energy performance in buildings by that range value, it improved outdoor thermal comfort by 15% to 22%. As a result, the study evaluated climate-balanced plant design with building energy performance in order to improve outdoor thermal comfort.

Influence of cooling surface area on indoor air and surface heat transfer characteristics of a thermally activated building system in warm and humid zones: An Experimental study

Several alternatives have been introduced in recent years to enhance the thermal comfort levels within buildings. Thermally Activated Building Systems (TABS), one of the above alternatives, have gained interest because of the huge benefits this technology offers the building sector. This type of system consists of encapsulated pipes within the building structure to control the surface temperature. This study explores the thermal behavior of the cooling surface and fluctuations in indoor air temperature (IAT) of TABS under various cooling scenarios. Only limited number of investigations has been carried out to study the heat transfer behavior of TABS. Hence, the building indoor thermal properties such as air temperature, surface temperature and rate of heat transfer between the indoor air and inner surface of the TABS has been evaluated experimentally by enhancing the cooling surface area. Moreover the results were compared with the conventional building (no cooling provides). The thermal energy stored in the TABS is significantly removed by the increase in cooling surface area, resulting in a 2°C decrease in the average indoor air temperature. The average heat gain of all wall surfaces in the case of no cooling (WOC) ranges from −3 to 13 W/m2. The amount of heat gain on the walls was not significantly affected by only roof and floor cooling (R+F) activities. Moreover, it ranged from −2 to 24 W/m2 in all surface cooling (ASC) scenarios. As a result, there was additional surface cooling, which increased surface heat gain and indoor cooling capacity.