Comfortable Indoor Thermal Environment Research Articles

A simulation study on the indoor thermal environment of an office building with transparent radiative cooling (T-RC) film in Nanjing, China

The application of radiative cooling materials in buildings can effectively improve the indoor thermal environment in summer. This study used computational fluid dynamics (CFD) simulation to investigate the impact of transparent radiative cooling (T-RC) film on the indoor thermal environment of an office building in Nanjing, Jiangsu Province, China. The window-to-wall ratios (WWR) and orientations of the windows were also considered. The simulation results indicate that the best cooling effect of the T-RC film on indoor average air temperature is observed in the south room (1.91 °C), followed by the east room (1.59 °C) and then the west room (1.5 °C), while the cooling effect in the north room is limited (0.56 °C). The cooling effect of the T-RC film is best in the west room at WWR 50%, while in the east and south rooms at WWR 75%. The cooling effect of applying the T-RC film only to the south-facing windows is 61.4% and 57.9% of applying film to all windows for the west and east rooms, respectively. This study can provide a reference for the effects of applying the T-RC film to office buildings, inform the design or retrofit scheme of building windows, and provide helpful information for making a more comfortable indoor thermal environment.

Development of Virtual Sensor Based on LSTM-Autoencoder to Detect Faults in Supply Chilled Water Temperature Sensor

Supply chilled water temperature (SCWT) is an important variable for the efficient and stable operation of heating, ventilation, and air conditioning (HVAC) systems. A precisely measured value ensured by the continuous reliability of the temperature sensor is essential for optimal control of an HVAC system because temperature sensor faults can affect the chiller operation and waste energy. Therefore, temperature sensor fault-detection strategies are imperative for maintaining a comfortable indoor thermal environment and ensuring the efficient and stable operation of HVAC systems. This study proposes a fault-detection method for an SCWT sensor using a virtual sensor based on a long short-term memory-autoencoder. The fault-detection performance is evaluated considering a case study under various sensor fault scenarios to evaluate changes in indoor thermal comfort and energy consumption after correcting sensor faults detected by the virtual sensor. The results verify excellent fault-detection performance in various fault scenarios (F-1 scores ranging from 0.9350 to 1.000). After correcting the SCWT fault, indoor thermal comfort is steadily maintained without additional energy consumption (indoor set-point temperature unmet hour reduced by a maximum of 105.7 hours, and energy consumption decreased by up to 1.8%).

Prediction of thermal comfort indoors and cooling loads based on reasonable zoning using the improved HHO with multi-strategy fusion-FENN algorithm

A comfortable indoor thermal environment helps occupants work healthily and efficiently, and the air-conditioning system, as the most energy-consuming system in building operation, accurate energy modeling while balancing thermal comfort can provide effective control strategies for managers. Metaheuristic algorithms are widely optimized for various types of machine learning models for the study of data-driven. However, the majority of them currently use the default hyperparameter or random and grid search, which are prone to obtaining inaccurate prediction results. In this paper, a sizable commercial building in Shaanxi Province is used as a research sample. The regional per floor firstly is divided with business model distribution, the cross-validation of random forest and correlation analysis is used to extract features, and the input factors of the prediction model are decided, and then the fully elman neural network is optimized using a segmental fusion strategy combining Cauchy operator and reverse learning to promote harris hawks optimization algorithm, and the prediction model the IMFHHO-FENN (improved Harris Hawks Optimization with multi-strategy fusion-Fully Elman Neural Network) is trained and constructed, which is finally used for predicting thermal comfort and cooling load. According to verification results, it can be proved that the IMFHHO-FENN model has excellent performance compared to mainstream single and combined models and can provide accurate results of predicted models in the design phase of building energy efficiency and later operation management, reducing energy consumption waste while satisfying personnel thermal comfort as much as possible and supply marked theoretical and decision reference for building equipment management.

Detecting thermal anomalies in buildings using frequency and temporal domains analysis

Identifying and modifying areas in a building where thermal anomalies occur will help to maintain a comfortable indoor thermal environment while reducing energy waste. In this study, a Fourier transform-based method was developed to detect places with thermal anomalies by considering the periodic characteristics of the temperature time series. Results were compared with anomalies detected by a support vector regression-based method. Both methods were applied to six days of temperature data obtained from sensors placed in various locations in two office buildings, each building having 60 sensors placed within them during the test period. Results showed that both Fourier transform and support vector regression based methods are capable of identifying abnormal time series without prior knowledge of the series. This developed Fourier transform-based anomaly detection method can be used effectively for anomaly detection in time series with periodic characteristics, which will make it easier to identify poorly-performing areas within an internal building environment using non-permanent sensors.

Image Generation Technique of Indoor Temperature Distribution Using Transposed Convolutional Neural Network

It is important to maintain a comfortable indoor thermal environment because people spend most of their time in buildings. Computational fluid dynamics (CFD) applications can not only simulate the indoor environment under various boundary conditions but also visualize analysis results as contour plots to help humans understand them easily. However, calculations are required for each boundary condition, and a significant amount of time is required to obtain the results. In recent years, artificial intelligence has been utilized in various fields, including image processing technology. Generating temperature distribution images using artificial intelligence instead of CFD analysis is expected to reduce the number of CFD cases and time required for preliminary studies. In this study, a transposed convolutional neural network was used to generate a model for the fast prediction of indoor temperature distribution, and case studies were conducted using a combination of training data. Consequently, it was confirmed that by appropriately selecting 108 out of 300 data points arranged in a grid, a model that predicts temperature distribution with generally good accuracy was generated for the untrained data.

Adaptive thermal comfort for energy saving office building design- A literature review

Office building thermal environment quality is essential since thermal comfort and worker productivity are closely related. As thermally comfortable condition is determined by the climate, geography, and surroundings, it is vital to have thermal comfort standards to guide the building designers to create a comfortable indoor thermal environment. The current paper reviews studies on adaptive approach of thermal comfort carried out in offices across the world. It has analyzed many research papers through Scopus. This study reveals that indoor thermal condition is impacted by outdoor climates and the impact is higher in naturally ventilated building. Building with natural ventilation has 17.6°C to 31.2°C rage of comfortable temperature. Adaptive comfort models have also been proposed to predict the comfortable indoor temperature in different modes. According to several studies, lowering the set point and using natural ventilation may result in considerable energy savings. The importance of developing climate specific thermal comfort guidelines in order to create energy efficient designs is also emphasized in this study, as present comfort standards may not be suitable for all climates.

External envelope impact on thermal environment of heritage buildings from the colonial period in hot arid area

The present research aims to study the effectiveness of the envelope components of colonial dwellings in maintaining a comfortable indoor thermal environment. In hot and dry areas, extreme outdoor air temperatures compel designers to provide a better indoor thermal condition which remains a rather delicate task to achieve such as in the case of the city of Biskra. The heritage buildings were constructed in the colonial period in the Biskra region; the colonial district buildings are built with local materials such as mud bricks and stones that have a large thermal mass; these materials are the main component of the walls of the outer exterior skin. Onsite measurement campaigns were carried out to record air temperatures inside the inhabited area for 24 hours. Thereafter, the collected data were compared with the outdoor air temperatures to assess the effect of the envelope impact on the temperature variation. The important results remain in the envelope’s crucial effect to achieve thermal comfort using local materials with a high thermal mass.

The effect of normative-based feedback messaging on room air conditioner usage in university dormitory rooms in winter season

Reducing energy waste in building operation phases is a crucial approach to mitigating global warming. Maintaining a comfortable indoor thermal environment is considered one of the major contributors to the final building energy consumption, largely influenced by actual occupant behaviours. Normative-based feedback messaging containing social comparison-based energy feedback is able to impact energy behaviour at homes. However, its real-world effectiveness on usage of room air conditioners (RACs) and their energy consumption together with corresponding impact on occupants’ subjective thermal evaluation has been rarely investigated. This study reports results of a preliminary investigation into the effect of feedback messaging on occupants’ RAC usage and thermal evaluations in a real-world residential setting, the factors that influence the effectiveness of feedback messaging, and the attitudes towards feedback messaging. A three-week field investigation was conducted with 101 subjects from 32 university dormitory rooms. The results suggest that messaging may potentially reduce RAC energy consumption while thermal sensation votes were mostly remained within the acceptable range, though no significant difference was found in comparison to periods without messaging. Meanwhile, the effect of feedback messaging on RAC usage demand was potentially impacted by people’s emotional stability, but a further investigation is recommended to confirm this finding.

Evaluation of Indoor Thermal Comfort Conditions of Residential Traditional and Modern Buildings in a Warm-Humid Climate

Achieving optimal levels of indoor thermal comfort in a warm, humid climate continues to pose a challenge to building occupants in such climatic regions. Buildings are either being retrofitted or designed differently to cater to thermal comfort. As a result, a variety of tactics have been deployed to guarantee optimal thermal comfort for occupants. Some scholars have highlighted the salient contributions of various types of construction materials toward the delivery of different housing types which perform differently under a diverse range of climatic conditions. A plethora of studies suggesting better indoor thermal comfort performance of traditional buildings as compared to contemporary dwellings due to various reasons have been observed. However, limited studies have sought to investigate this suggestion within warm, humid climatic regions. As such, this study engages in an evaluation of indoor thermal comfort qualities of traditional and modern buildings during the dry season with the goal of developing design guidelines for a thermally pleasant environment in a town, Okigwe, which is situated in a warm, humid climatic region in Southeastern Nigeria. Data were collected utilizing a field measurement technique. Throughout the survey period, variables of the indoor environment such as relative humidity and air temperature were recorded concurrently in nine selected buildings, two traditional and seven modern buildings. The fluctuations and differences in relative humidity and air temperature between the two building types were investigated using Z-test statistical techniques. The study’s results revealed that the contemporary structures’ indoor air temperature (29.4 °C) was 0.6 °C higher than traditional buildings’ indoor air temperature (28.8 °C). Therefore, the study recommends that architects and planners should make concerted efforts to integrate methods of passive design into the provision of a comfortable indoor thermal environment rather than relying solely on active design strategies, which whilst lacking in traditional buildings, nonetheless did not prevent such buildings from recording lower air temperature readings compared to modern buildings.

Energy consumption optimization of building air conditioning system via combining the parallel temporal convolutional neural network and adaptive opposition-learning chimp algorithm

Heating, ventilation, and air-conditioning systems provide a comfortable indoor thermal environment, but high energy consumption is often necessary to achieve an adequate level of indoor thermal comfort. However, it is challenging to design an energy-efficient thermal comfort control strategy, mainly because the internal thermal environment is influenced by complicated factors and difficult to model accurately. To solve this problem, a control strategy incorporating the parallel temporal convolutional neural network (PTCN) and the improved chimp optimization algorithm (ICHOA) is proposed for thermal comfort control of buildings. Thermal comfort control is transformed into a cost-minimization problem by establishing an objective function for both the future thermal comfort of the occupants and energy consumption and optimizing multiple air-conditioning temperature set points for the coming day. First, to ensure the prediction performance, a PTCN model was developed to predict the energy consumption and thermal comfort under different factors. An opposition-learning-based adaptive chimp algorithm was then used to solve the objective function to output the optimal set temperature. Finally, the superiority of the PTCN-ICHOA optimization strategy was verified using an office building in Jinan as an example. In winter and summer experiments, the proposed PTCN model achieved the lowest prediction errors among the models compared in terms of energy and temperature prediction. Furthermore, the PTCN-ICHOA optimization model exhibited faster convergence than the other models for both experiments. Through the proposed optimization strategy, energy consumption savings of approximately 6.3%–8.1% can be achieved while maintaining indoor thermal comfort.

Life cycle assessment of traditional Saharan houses: Towards a sustainable building?

While traditional buildings have demonstrated their ability to provide a comfortable indoor thermal environment and to reduce their energy consumption, their ecological and human health performances are not widely known. This paper proposes a new approach to demonstrate and optimize the environmental performances of four traditional Saharan houses through Life Cycle Assessment (LCA), mainly by intervening on the roof, which is considered as an identifying element of this architecture type. This approach is based on a system of indicators, developing algorithmic equations for six impact categories, and combining environmental, morphological and climatic aspects. The results obtained demonstrated that the voutain allows very close environmental performances to those of ecological houses, that the ecological aspect of the cupola can only be revealed by coupling it with a very high thermal inertia and that it is recommended to use a large cupola roof rather than a multi and small cupola roof for better environmental performances. Morphological and technical parameters values were proposed as a support tool for ecological design, ensuring the sustainability of buildings in arid climates.

A Survey of the Influence of Air Distribution on Indoor Environment and Building Energy Efficiency

With society paying more and more attention to energy conservation, building energy conservation has become a problem that must be considered in the design phase. In addition, modern life makes people spend more time indoors every day. Reasonable indoor air distribution positively impacts a comfortable indoor thermal environment and reduces building energy consumption. This paper discusses the influence of air distribution on indoor thermal comfort and building energy saving. Reasonable air distribution in the air-conditioned room will create a comfortable indoor thermal environment, which is helpful for the physical and mental health of personnel and efficient work. Meanwhile, it can also effectively reduce the equipment's initial investment and operating energy consumption and realize building energy savings. The design of indoor air distribution cannot be a single, isolated project. A comprehensive analysis based on each station's environmental thermal comfort requirements in the work area must be carried out to reduce air-conditioning operation energy consumption and achieve building energy-saving goals. For existing buildings and large space buildings, the corresponding air distribution design scheme should be designed reasonably. This paper also suggests future research directions on indoor air distribution.

Thermal Performance of School Buildings: Impacts beyond Thermal Comfort.

Based on field study data regarding the winter indoor thermal environment of three classrooms with different building envelopes, this study compared and evaluated these environments, not only related to students’ thermal comfort but also to their health. The inadequacy of the conventional New Zealand school building for maintaining a comfortable and healthy winter indoor thermal environment has been identified. A classroom with thermal mass had 31%, 34% and 9% more time than a classroom without thermal mass when indoor temperatures met 16 °C 18 °C and 20 °C respectively and has 21.4% more time than the classroom without thermal mass when indoor relative humidity was in the optimal range of 40% to 60%, in a temperate climate with a mild and humid winter. Adding thermal mass to school building envelopes should be considered as a strategy to improve the winter indoor thermal environment in future school design and development. Adding thermal mass to a school building with sufficient insulation can not only increase winter indoor mean air temperature but can also reduce the fluctuation of indoor air temperatures. This can significantly reduce the incidence of very low indoor temperature and very high indoor relative humidity, and significantly improve the indoor thermal environment.

Heating performance of heating floor integrated with impinging jet ventilation system

Radiant floor heating systems provide comfortable indoor thermal environment. Primary air supply systems can be used to remove contaminants in the space heated by radiant floor. In this study, heating performance of integrated system of impinging jet ventilation (IJV) and heating floor was numerically investigated. The lowest floor heating capacity was 0 W/m2 and gradually increased to 50W/m2, and the primary air temperature supplied by IJV were 14, 16 and 18°C, respectively. In terms of contaminant removal efficiency, contaminant removal efficiency (CRE) was applied. The vertical dimensionless temperature distribution was used to analyse the heating performance of HF on supply air. The numerical results showed that the supply air layer of IJV could be heated by 60% to 80% under the heat effect of HF. The same is true for low supply air temperature 14 °C. The integrated system IJV/HF generated the weaken thermal stratification which is beneficial for energy saving. The CRE of IJV/HF system was influenced by the downward airflow of external wall. Sufficient supply air could overcome the downflow and effectively increase the CRE value (> 2).

Study on the impact of parallel jet spacing on the performance of multi-jet stratum ventilation

With the wide spread of novel coronavirus SARS-CoV-2 pandemic around the word, high quality indoor environment and more efficient mechanical ventilation become the new focus of scholars' attention. Stratum ventilation refers to the ventilation mode that the air supply port on the side wall slightly higher than the height of the working area directly sends fresh air into the working breathing area. As an efficient mechanical ventilation mode, it can create a more healthy and comfortable indoor environment. However, the impact caused by airflow characteristic under stratum ventilation on the thermal performance and indoor comfort is noteworthy due to its supply air outlets are close to the occupied zone. It is widely known that parallel turbulent jets are important for the flow structure and air distribution. Hence, an optimum parallel jet spacing (PJS) between two jet centerlines can obviously enhance the fluid interaction and indoor thermal comfort with low energy consumption. Therefore, this study aims to investigate the impact of the PJS on the performance of multi-jet stratum ventilation. A validated Computational Fluid Dynamics (CFD) model was used to conduct the year-round multivariate analysis. A total of eight PJSs, four inlet locations and five climate zones were discussed synthetically. Air distribution performance index (ADPI), ventilation effectiveness (Et) and economic comfort coefficient were employed as the evaluation indicators to assess the thermal comfort and energy efficiency in various scenarios. Research results indicated that the PJS showed different influences on the indoor thermal comfort and energy utilization efficiency as a result of cooperative effect including energy dissipation, air short-circuit probability, air distribution uniformity and airflow path. Combining with building energy simulation method, the optimum PJSs of stratum ventilation with different air inlet positions in five climate zones were obtained, which can help provide a comfortable indoor thermal environment and improve energy efficiency in a low-cost way. The data and conclusions presented in this study can supplement the theoretical basis for the actual applications of multiple-jet stratum ventilation used in an office.

Experimental studies on hot gas bypass defrosting control strategies for air source heat pumps

The air source heat pump (ASHP) is commonly used for improving indoor thermal comfort with its traditional defrosting strategy based on reverse circulation, leading to a widely fluctuating range of indoor air temperatures, which can drop dramatically when the defrosting is in operation and increase sharply after it stops. Based on a theoretical analysis of the characteristics of a hot gas bypass defrosting system, this study proposes a novel intelligent control strategy based on the maximum heating capacity of the ASHP system with appropriate start and end points for defrosting designed to operate accurately under different outdoor temperature ranges. This defrosting method was verified in a well-structured environmental laboratory and the performance was compared to the conventional system through experiments. The results show that the heating capacity of the hot gas bypass defrosting is 10.17% higher and the overall energy efficiency is 4.06% higher. The indoor air temperature fluctuates in the range of 1°C–1.6 °C, which is about 84% less than that under conventional defrosting conditions. Moreover, the temperature of the outlet air is decreased by about 7 °C, with the fluctuation range being 56% less than that of conventional defrosting. The maximum outlet temperature remains stable at 35.2 °C and the rising rates of indoor air temperature and outlet temperature are significantly improved, ensuring a comfortable indoor thermal environment. The proposed hot gas bypass control strategy enables a high energy efficiency for the ASHP for winter heating to be achieved whilst avoiding sharp fluctuations in the indoor air temperature during defrosting.

Thermal adaptive behavior and thermal comfort for occupants in multi-person offices with air-conditioning systems

A better understanding of the adaptive behavior of office users is very important for creating comfortable indoor thermal environment and working healthily and efficiently. This study considers a multi-person office with air conditioning systems in Guangzhou, China as a research object. The relationship between users' adaptive behaviors and thermal satisfaction and influences of environmental parameters and gender on the probabilities of adaptive behaviors were studied. The logical regression method was used to conduct a probabilistic prediction analysis of adaptive behaviors in cold and hot environment. The study shows that user only accepts an indoor temperature change of approximately 1 °C higher than the neutral temperature in hot environment. Under the same thermal sensation vote, the indoor temperature when the user's adaptive behaviors are generated is approximately 1 °C higher (in hot environment) or lower (in cold environment) than that when no action occurs. The indoor temperature and globe temperature significantly affect the occurrence probabilities of adaptive behaviors (P < 0.005). The overall regression accuracy is higher than 70%. The characteristic coefficients of the adaptive probabilistic prediction model of cold and hot behaviors (using indoor temperature data) are 26 °C and 28 °C, which are the critical temperatures of indoor thermal satisfaction and dissatisfaction, respectively. Men engage in hot adaptive behaviors when the indoor temperature is approximately 22 °C, which is around 3 °C lower than women.

Development of a back-propagation neural network and adaptive grey wolf optimizer algorithm for thermal comfort and energy consumption prediction and optimization

Heating ventilation and air conditioning (HVAC) systems provide a comfortable indoor thermal environment, but in the process of attaining appropriate indoor thermal comfort levels, they usually entail high energy consumptions. It is therefore imperative to balance thermal comfort value with energy consumption. However, such research currently faces two problems: one, it is difficult to obtain accurate parameters pertaining to the indoor environment of buildings, particularly near heat source areas; two, it is the diametrical nature of having to simultaneously maintain thermal comfort and keep energy consumption low. Therefore, this study aims to propose a rapid thermal comfort level prediction and optimization algorithm, as well as a method to minimize the energy consumption using only a computational fluid dynamic (CFD) database that is compact in size. Firstly, CFD is used to implement the database that stores data on indoor airflow and temperature distributions of different building structures and indoor conditions. Next, using the database as a basis, a back-propagation neural network (BPNN) is developed to predict the thermal comfort level. The adaptive grey wolf optimizer (GWO) algorithm is then applied to optimize the thermal comfort value, and the latest control methods: the artificial neural network (ANN)-genetic algorithm (GA) and ANN-particle swarm optimizer (PSO) algorithm are compared against the BPNN-based adaptive GWO method. The results show that the BPNN-based adaptive GWO algorithm can rapidly predict the thermal comfort level and have strong optimization ability. Meanwhile, 1.01% of energy savings are achieved.

A comparative case study of volcanic-rock vernacular dwelling and modern dwelling in terms of thermal performance and climate responsive design strategies in Hainan Island

ABSTRACT The volcanic-rock dwellings are a special kind of traditional vernacular architecture with high value of research, which located in the north of the Hainan Island in China. In order to clarify the thermal mechanism differences between volcanic-rock dwellings and modern dwellings in Haikou, the main factors affecting the thermal comfort of dwellings are analyzed through investigations of indoor thermal environment in the Yangshan lava area of Haikou. The results show that the volcanic-rock dwelling can achieve 10 h (from 23:30 to 9:30 the next day) with air temperature under 28.7°C in a comfortable thermal indoor environment without air-conditioning cooling equipment, while the rooms on the ground floor of modern dwelling can achieve 1 h around sunrise, and the room on the top floor is completely outside the thermal comfort zone. Temperature difference between exterior and interior of volcanic-rock wall and wooden window can reach a maximum of 6.7°C and 2.8°C respectively, which shows that the envelope of volcanic-rock dwelling has a good thermal insulation performance. It is necessary to inherit the space prototypes and climate-adaptive strategies of traditional residential buildings when designing a new building, which play a significant role on providing a comfortable indoor thermal environment.

Evaluation of Rural Dwellings’ Energy-Saving Retrofit with Adaptive Thermal Comfort Theory

The purpose of energy-saving retrofit of rural dwellings is to obtain a more comfortable indoor thermal environment with reasonable investment. The utilization rate of heating and air conditioning equipment for dwellings in poor rural areas is very low, and the buildings operate in natural ventilation mode all year round. Since the existing research on energy-saving retrofit is aimed at air-conditioned buildings, the research methods and results are not applicable to rural dwellings. This paper proposes a set of energy-saving retrofit evaluation methods suitable for natural ventilation buildings and applies it to the research on energy-saving retrofit of rural dwellings in cold climate regions of China. The specific process is as follows: First, this paper analyzed the current situation using field research and established a typical building model. Second, the DesignBuilder software was used to simulate all 725 schemes. Subsequently, the three main retrofit measures (replacing the external insulation windows, setting the external wall insulation layer and setting the roof insulation layer) were analyzed separately, and the optimal parameters of each retrofit measure were obtained. Finally, the entropy weight method was used to perform a multi-objective optimization analysis on all retrofit plans. The results show that 6+12A+6-mm insulating glass windows + 50-mm external wall insulation + 90-mm roof insulation is the optimal energy-saving reconstruction scheme. Compared with the benchmark building, the energy-saving rate of the optimal scheme is increased by 23.81%, and the annual adaptive thermal discomfort degree-hours are decreased by 13.17%.