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Thermal comfort preference in primary schools is quite crucial because of the difficulty of young students to show and reflect their actual status of comfort: they may come with a jacket early morning in winter, but they may not take it off later in the afternoon. Little research on thermal comfort has been done in educational buildings globally as compared to other types of buildings such as working places. This research was focused on the ultimate type of shading devices in relation to thermal energy performance such as indoor air temperature, solar heat gain, and day-lighting from one side and thermal comfort preference from the other. In this research, we used a variety of tools such as thermal imaging cameras, TAS EDSL software. There is a clear lack in economical perspective for the users in this region to try to adapt without heavy reliance on air-conditioning systems, one of the major contribution of this study is to provide alternatives for sustainable buildings. We observed that vertical shading systems were generally more preferable for efficient shading in hot regions.

Facade planting is an innovative idea to make use of plants in cooling the surrounding. Double Skin Green Facade is a type of green walls that offers psychological benefit in addition to its thermal performance. The aim of this research was to define the effect of Double Skin Green Facade on indoor thermal conditions. Orientation and cavity width were the parameters identified in this research in order to achieve maximum efficiency. A Double Skin Green Facade model was applied on an office building to investigate its thermal performance in Cairo, using Design Builder software. The simulation process was divided into three phases. The first phase aimed to define the day with extreme high temperature among the year to undergo further phases. The second phase intended to compare the performance of the green facade to that of the base case in south, east, and west orientations. Then the cavity width parameter was examined on third phase. Results showed improvement on indoor air temperature after applying Double Skin Green Facade. Moreover, the research recommended its application on the west orientation with 1.5 meters cavity width with respect to Cairo climatic conditions.

This work aims at answering the question–to what extent thermally compliant buildings are involved in ensuring the winter indoor thermal comfort of occupants in cold semi-arid climates in Morocco. Real-time monitoring of a new-built university building located in eastern Morocco was conducted. The good agreement between the measured and simulated temperatures of the case study building confirmed the accuracy of the developed model. Thereafter, the thermal performance of different external wall configurations was investigated. The results show that compliant buildings guarantee better comfort conditions in winter by passively increasing the indoor air temperature by up to 2 °C, resulting in a maximum percentage of dissatisfaction of less than 13%. The winter discomfort hours based on a temperature set point of 16 °C are reduced by 95% compared to typical buildings. Moreover, the thermal compliance of buildings significantly reduces the daily air temperature amplitude, leading to a periodic dynamic behaviour without peak loads, which could be effective for the building energy management. The efficacy of earthen walls in regulating indoor temperatures was also confirmed due to the excellent thermal inertia of earth. For optimum winter comfort (20 °C), the implementation of the Moroccan building energy code shows up to 72% of reduction in heating demand when applied to conventional buildings.

After massive earthquake 2015, thousands of Nepalese who lost their permanent houses by the hardest hits were forced to live in makeshift temporary shelters. The field measurement on indoor thermal environment in five shelters was conducted in one of the district hit by the earthquake, Lalitpur, in winter. The mean indoor and outdoor air temperatures during the measured nighttime were found to be 10.3 °C and 7.6 °C, respectively, and the nocturnal indoor air temperature remained below the lowest acceptable temperature of 11 °C. This result assured that these shelters are not good for winter and must create various problems. We therefore analyzed the thermal characteristics of those shelters based on the measured results in order to seek a possible improvement. The total heat loss coefficient estimated per floor area in five shelters ranged from 11.3 to 15.2 W/(m2·K); that is thermal insulation was very low. We made a simple numerical analysis on the variation of indoor air temperature with the assumption of improved thermal characteristics and thereby found that it needs to be reduced about 2∼7 W/(m2·K) to have the indoor air temperature higher than 11 °C for 70% of the whole nocturnal hours. Such reduction of heat loss was found to be realized by adding affordable materials, e.g., cellular polyethylene foam and clothes for respective walls and roof. Thus, the knowledge obtained from this study should hopefully be applied to actual improvement of indoor thermal environment in existing shelters and also to a development for the preparation against future disaster.

Simple Summary Hourly manure coverage proportion and area on the manure belt are key parameters for estimating ammonia emissions in poultry houses in order to provide environmental control suggestions and achieve the goals of precision poultry farming. In this study, experimental measurements were performed, and binary images were applied to provide new insights into the projected hourly manure coverage area on the manure belt at different layer hen ages. It was demonstrated that manure coverage proportion and area measured at different laying hen ages showed similar trends and values with four distinct stages within 48 h. In addition, statistical analyses found no significant correlation between the hourly increment of manure weight and the hourly increment of manure coverage proportion. The results from the present study are expected to serve as a fundamental input parameter for ammonia emission modeling to more accurately simulate the hourly indoor environment and provide effective mitigation strategies. Abstract The main advantage of having livestock, for example, the laying hens, in a controlled environment is that the optimum growth conditions can be achieved with accuracy. The indoor air temperature, humidity, gases concentration, etc., would significantly affect the animal performance, thus should be maintained within an acceptable range. In order to achieve the goals of precision poultry farming, various models have been developed by researchers all over the world to estimate the hourly indoor environmental parameters so as to provide decision suggestions. However, a key parameter of hourly manure area in the poultry house was missing in the literature to predict the ammonia emission using the recently developed mechanistic model. Therefore, in order to fill the gap of the understanding of hourly manure coverage proportion and area on the manure belt, experimental measurements were performed in the present study using laying hens from 10 weeks age to 30 weeks age. For each test, six polypropylene (pp) plates were applied to collect the manure dropped by the birds every hour, and photographs of the plates were taken at the same time using a pre-fixed camera. Binary images were then produced based on the color pictures to determine the object coverage proportion. It was demonstrated that for laying hens of stocking density around 14 birds/m2, the manure coverage proportion at the 24th hour after the most recent manure removal was about 60%, while the value was approximately 82% at the 48th hour. Meanwhile, for laying hens at different ages, the hourly increment of manure coverage proportion showed a similar pattern with four distinct stages within 48 h. The statistical analyses demonstrated no significant correlation between the hourly increment of manure weight and the hourly increment of manure coverage proportion. Finally, prediction models for estimating the hourly manure coverage proportion on the manure belt in typical laying hen houses were provided.

With the increase in the frequency and duration of heatwaves and extreme temperatures, global warming becomes one of the most critical environmental issues. Heatwaves pose significant threats to human health, including related diseases and deaths, especially for vulnerable groups. Such as the one during the 2018 summer in Montreal, Canada, caused up to 53 deaths, with most lived in buildings without access to air-conditioning. Unlike building energy models that mainly focus on energy performance, building thermal models emphasizes indoor thermal performance without a mechanical system. It is required an understanding of the complex dynamic building thermal physics in which detailed building parameters need to be specified but challenging to be determined in real life. The uncertainty assessment of the parameters estimates can make the results more reliable. Therefore, in this paper, a Bayesian-based calibration procedure was presented and applied to an educational building. First, the building was modeled in EnergyPlus based on an in-site visit and related information collection. Second, a sensitivity analysis was performed to identify significant parameters affecting the errors between simulated and monitored indoor air temperatures. Then, a Meta-model was developed and used during the calibration process instead of the original EnergyPlus model to decrease the requirement of computing load and time. Subsequently, the Bayesian inference theory was employed to calibrate the model on hourly indoor air temperatures in summer. Finally, the model was validated. It is shown that the Bayesian calibration procedure not only can calibrate the model within the performance tolerance required by international building standards/codes but also predict future thermal performance with a confidence interval, which makes it more reliable.

Indoor air temperature (IAT) and indoor relative humidity (IRH) are the prominent microclimatic variables, still, potential contributors that influence the homeostasis of livestock animals reared in closed barns. Further, predicting IAT and IRH encourages farmers to think ahead actively and to prepare the optimum solutions. Therefore, the primary objective of the current literature is to build and investigate extensive performance analysis between popular ML models in practice used for IAT and IRH predictions. Meanwhile, multiple linear regression (MLR), multilayered perceptron (MLP), random forest regression (RFR), decision tree regression (DTR), and support vector regression (SVR) models were utilized for the prediction. This study used accessible factors such as external environmental data to simulate the models. In addition, three different input datasets named S1, S2, and S3 were used to assess the models. From the results, RFR models performed better results in both IAT (R2 = 0.9913, RMSE = 0.476, MAE = 0.3535) and IRH (R2 = 0.9594, RMSE = 2.429, MAE = 1.47) prediction among other models particularly with S3 input datasets. In addition, it has been proven that selecting the right features from the given input data builds supportive conditions under which the expected results are available. Overall, the current study demonstrates a better model among other models to predict IAT and IRH of a naturally ventilated swine building containing animals with fewer input attributes.

In this paper, a newly formulated model for simulation of indoor air temperature is presented. The model combines diffusion model for description of heat and mass transfer through the wall assembly and the indoor air temperature model. Both models are interconnected and exchange data during the simulation. The model capability is demonstrated on a simple case study, in which a historical masonry made of sandstone is analyzed before and after thermal retrofitting. The result showed good performance of the model as well as possible ways for model extension and utilization.

In recent years around Europe several investigations, measurements were carried out in order to reduce the buildings energy need, but the energy need for cooling, still shows a growing curve. In relation to residential buildings different standards has distinct requirements for internal/operative temperature. To assure the required air temperature and comfort different types of air conditioning systems are installed in buildings. Therefore, in many countries especially in summer period the power networks are strongly overloaded. The internal air temperature in a residential building through two different summer periods was measured. In the first period the internal air temperature was measured without residential ventilation and air conditioning system. In the next summer period measurements were accomplished with residential ventilation and air conditioning system. The indoor air temperature variation was calculated using the EN ISO 13790 standard's methodology, values obtained from the measurements were compared with the analytical values. The theoretical values were used in the case of summer, hot and torrid days for heavy construction buildings. Certainly, the indoor air temperature variation and the energy need for cooling was analysed for one residential building.

Our global climate is changing and the problem got so serious that the European Commission is calling for a climate-neutral Europe by 2050. To reach such an ambitious and urgent goal, an energy efficient renovation of the existing building stock is needed. Nonetheless, some buildings must be treated with special attention because of their historical value. Thus, it is advisable to evaluate their retrofit with the aid of calibrated hygrothermal simulation models, whose calibration can be complex and time demanding. This work shows the strategy adopted for obtaining a calibrated model for a XVI-century construction located northern Italy, by means of indoor air temperature and relative humidity monitoring, plus CO2 measurements and in situ inspection. This study accounts for the first 9 months of measurements performed on the case study and it adopts HAMBase as a simulation tool because of its ability to combine heat and moisture calculations in monumental buildings with HVAC systems. This paper aims at showing the main problems found in developing and calibrating the simulation model while defining a procedure to overcome them. The major outcome of the study is that the stratification of temperature detected in the main monumental room could be successfully modelled via dividing this space into different zones, vertically, by introducing fictitious interzonal surfaces made of a material with high thermal conductivity and vapour permeability. All in all, the strategy adopted in this work can be used by other researchers and professionals to overcome problems that can be commonly met when modelling similar historic constructions.

Earth-to-air heat exchanger (EAHE) is a promising energy-efficient technology for indoor thermal environment regulation; however, it should adapt to both building and climatic conditions. This paper proposes a new inverse approach to determine the parameters of EAHE integrating into buildings and to achieve a prescribed indoor thermal comfort objective. First, the criterion for achieving year-round thermally comfortable indoor air temperatures is formulated. According to the objective, the required combined parameters characterizing the dynamic behavior of the earth-to-air heat exchanger outlet-air temperature are inversely calculated. Then, the earth-to-air heat exchanger parameters, such as length, radius, burial depth and flow rate, satisfying the proposed objective are determined. The results demonstrate that decreasing the phase shift of the anticipated indoor air temperature profile helps to reduce the requirements on earth-to-air heat exchanger parameters. A Computational Fluid Dynamics simulation incorporated with real meteorological date is implemented according to the EAHE parameters obtained from the proposed approach. It is demonstrated the proposed inverse approach is effective and the year-round indoor thermal comfort is achievable.

Formaldehyde emissions of building materials are greatly influenced by the indoor air temperature. An accurate evaluation of the influence of formaldehyde emissions on indoor air quality requires an investigation of the emission characteristic parameters at different temperatures. Based on the adsorption potential theory, this paper derived the correlation between the initial emittable concentration (C0) and the partition coefficient (K) of formaldehyde emissions from building materials. On account of the characteristics of a high equilibrium concentration of formaldehyde emissions under high temperatures in an airtight environment, a step temperature rising emission (STRE) method to simultaneously determine the characteristic parameters of formaldehyde emissions at multiple temperatures was proposed. This innovative method was validated by theoretical models in the literature and via independent experiments. In addition, an optimization method for determining the appropriate volumetric air/material phase ratio was discussed and analyzed to improve the accuracy and reliability of the STRE method. This method aims to improve the measurement efficiency of the emission characteristic parameters and provides inspiration for evaluating the hazard posed by formaldehyde emissions from furniture and building materials.

The evacuated tube solar collector with auxiliary electric heater (ETCAEH) was presented for rural heating in this study. The examined building heating system with evacuated tube solar collector was designed and constructed in Jinan city, china. The aim of this study is to analyze the feasibility of building heating system presented. Thermal performance and economic analysis of ETCAEH for rural heating were investigated. The results show that the heating room indoor air temperature can meet heating demand by adopting ETCAEH. Furthermore, ETCAEH used in rural area has applicative enough for their advantages in economy by comparing with coal-fired boiler and air conditioning. It is said that this study will provide guidance for designing and economic feasibility of ETCAEH used in building heating.

Buildings consume huge amounts of electrical energy in the Kingdom of Saudi Arabia, particularly during the summer months, due to the enormous air conditioning demands created by very hot outdoor temperatures. Residential buildings consume more than half of the electricity used in Saudi Arabia, with the air conditioning load making up 70% of this use. The main aim of this study is to evaluate the thermal performance of two mid-rise residential buildings in Makkah, Saudi Arabia. These buildings are five floors in height and have the same orientation, but the first building is thermally insulated, while the second building is not. To investigate the indoor thermal performance of the two buildings, physical measurements were taken during May 2019. The data gathered included indoor air temperature values as recorded every fifteen minutes for a period of sixty-eight hours in two equivalent rooms in each building. Analysis of site monitoring data was conducted, and the results obtained offer a better idea of the effectiveness of the existing building fabric characteristics, in particular external walls and rooves, in relation to indoor thermal performance. These data were calibrated with simulated results taken from thermal analysis software (TAS) to validate them and to thus quantify the cooling load in the case study buildings. The outcomes illustrate the similarity between the measured and simulated results and as well as indicating that thermal insulation can decrease cooling loads by to up to 50%.

This study presents a case study of public buildings using a novel deep learning method to forecast indoor air temperature. The aim is to explore the potential of long short-term memory (LSTM) model in forecasting indoor temperature, and a novel LSTM model modified by error correction model is established. The performance of the two models is compared with popular prediction methods in the building field. Results show that the proposed novel LSTM model has slight advantages in level indoor temperature prediction performance comparing with other common machine learning methods. However, it outperforms other models including original LSTM in terms of directional prediction accuracy, and accurately predicts the indoor temperature variation trend. This work is enlightening and may have a further reference to the feasibility study of indoor air temperature prediction model.

Double layers shape-stabilized phase change material (SSPCM) wallboard could improve building indoor thermal comfort both in summer and winter. The exterior and interior layer was active in summer and winter, respectively. In order to study thermal performance of building integrated with double layers SSPCM wallboards in real weather conditions without air conditioner, two simplified experimental rooms were developed in Wuhan city. The envelope construction properties of the two rooms were the same except the PCM room had double SSPCM layers on south wall. The summer experiment was conducted from 10th July to 3rd September in 2017. The winter experiment was conducted from 20th November, 2017 to 19th January, 2018. According to the continuous measurement data in summer and winter, indoor air temperature, interface temperature and heat flow of wall surface were collected. The indoor air temperature in PCM room was 1.9 °C lower in maximal and 0.6 °C lower in average than that in reference room in summer. The indoor air temperature in PCM room was 1.3 °C lower in maximal and 0.1 °C higher in average than that in reference room in winter. The experiment results showed that PCM room could prevent overheating in summer and undercooling in winter compared with reference room.

Cooling load estimation is the base for the design and control of the air conditioning system. The indoor air temperature stratification of stratum ventilation and displacement ventilation contributes to the energy saving, but challenges the cooling load estimation. The existing building simulation tools are generally equipped with only the fully mixed air model and ignore the indoor air temperature stratification. This study proposes an equivalent room air temperature based cooling load estimation method to enable the fully mixed air model to accurately estimate the cooling load of stratum ventilation and displacement ventilation. The equivalent room air temperature is the air temperature with which the fully mixed air model can produce the same cooling load as that of stratum ventilation/displacement ventilation. The equivalent room air temperature is modelled as a function of the supply air temperature, supply airflow rate and room air temperature of stratum ventilation/displacement ventilation using response surface methodology. Case studies using the experimentally validated multi-node models are conducted to demonstrate the effectiveness of the proposed method. The mean absolute errors in the cooling load estimation by the proposed method for the constant-air-volume system and the variable-air-volume system are 0.02% and 5.78% respectively under stratum ventilation, and 0.07% and 4.78% respectively under displacement ventilation. Compared with the conventional method, the proposed method improves the accuracy in the cooling load estimation by 70.92%–99.94%.

During disaster relief reconstructions, prefabricated temporary houses (PTHs) have been extensively used for resettling disaster victims. However, due to the nature of disaster relief, PTHs are normally light-weighted, without an electrical thermal environmental control systems installed. Hence, the thermal environments inside these PTHs can become intolerably hot in summer. Therefore, simple and low cost measures should be applied to disaster-relief PTHs for improving their indoor thermal environments. In this paper, an experimental study on applying PCMs to disaster-relief PTHs is reported. Two different designs of applying PCMs were examined. In Design 1, PCMs were fixed to the internal surfaces of a model PTH and the related experimental results demonstrated that both indoor air temperature and internal surface temperature of the model PTH can be reduced at daytime. However, in Design 2, a movable PCM based energy storage system (PESS) was used and the related experimental results suggested the use of the mobile PESS with a total charge of 148.8 kg PCM helped reduce the average indoor air temperature by 3.2–3.6 °C. The experimental results from both Designs suggested that, due to the nature of disaster relief and since outdoor air at a lower temperature may be the only cooling energy source for charging the PCM, a movable PESS system was preferred, so that it can be moved to outdoor at nighttime for being charged with more cooling energy using lower temperature outdoor air not adversely increasing the air temperature inside PTHs.

We conducted a series of survey on occupants’ behaviors for adaptive thermal comfort together with indoor air temperature measurement in a condominium equipped with Home Energy Management System (HEMS), from November 2015 to October 2016, in which 17,026 votes were collected. The data was categorized into Free Running (FR), Cooling (CL) and Heating (HT) mode and were analyzed thoroughly. The results showed that the indoor air temperature was highly correlated with outdoor air temperature in FR mode. In CL mode, the mean indoor air temperature was 27.3 °C, which was close to the recommended air temperature for summer in Japan equal to 28 °C. In HT mode it was found that indoor air temperature was maintained around 20 °C. Similar indoor air temperature was also observed in FR mode during winter. The occupants’ thermal sensation votes were most likely to be neutral. The mean clothing insulation was 0.43 clo in summer and 0.89 clo in winter. The occupants’ behaviors in this condominium for clothing insulation adjustment were found to be quite similar to those in detached houses found in previous studies. The occupants seemed adapting to the indoor thermal environment by window-opening behaviors to adjust thermal comfort during summer. The use of fan was found to increase as the indoor air temperature increased. The occupants were found to take these passive means along with the use of air conditioning unit for cooling. Mechanical heating was used only for a limited period for the condition of outdoor air temperature being low.

Improving energy efficiency in the UK housing stock has been emphasised for a long time leading to use of various energy efficiency measures in the houses. Eco houses with the integration of low carbon, highly energy efficient and renewable energy technologies aim to achieve desired user comfort and energy saving. Noteworthy that occupant's behaviours are also significant to real life performance of the Eco houses. Present study investigates the occupant's awareness and satisfaction living in the Eco houses. Factors such as indoor air temperature and quality, acoustic, lighting and the control over indoor environment have been investigated. Three main issues have been raised by households: overheating in summer; poor sound privacy; and low quality construction materials. Research has found out that there is strong demand for appropriate lighting and ventilation control, poor usability and awareness of the indoor environment control devices. A gear process is presented to act as a conceptual guidance in improving Eco house performance with the end user's priorities and awareness as well as the embedded technologies.

The present paper aims to evaluate the performance characteristics of a split air conditioner working with R-417A under different indoor and outdoor operating conditions. A test facility was constructed and experiments were carried out to achieve the research objectives. The indoor conditions were varied in a wide range of air temperature (21–31.4 °C), air relative humidity (40.3%–61.9%) and air velocity (2.8–4.7 m s−1) while the outdoor conditions were changed in range of air temperature (35–51.2 °C) and air relative humidity (40.8%–81.2%). Experimental results showed that the increase in the indoor air temperature causes an enhancement in the system coefficient of performance by about 59.7%, while increasing the outdoor air temperature decreases the system coefficient of performance by about 51.6%. The system cooling capacity using R-417A was lower than that of R-22 by about 33.2% at indoor air temperature of 24.5 °C.

The huge heat loss/gain through windows is the cause of great energy consumption in buildings. In addition, the traditional fabrication method for glass causes many environmental problems. Recently, transparent wood has emerged as a promising alternative to traditional glass because of its high transmittance, strong mechanical properties, excellent thermal insulation ability and sustainability. In this study, inspired by jellyfish, a thermochromic transparent hydrogel wood that can smartly regulate solar irradiation is proposed as a smart window material by impregnating Poly(N-isopropylacrylamide)-polyacrylamide hydrogel into delignified wood. The novel thermochromic transparent hydrogel wood inherits the excellent thermochromic properties of PNIPAM and strong mechanical properties of wood, showing advanced optical regulation ability (i.e. Tlum = 82.7% and 39.8% at the cold and hot states & ΔTsol = 38.1%), low transition temperature (i.e. Tc = 22.9 °C), mechanically robust (i.e. σ = 11.6 MPa along the axial direction) and low thermal conductivity (i.e. K = 0.37 W m−1 K−1 along the perpendicular direction of the wood growth). A field test conducted in October in Hong Kong shows that thermochromic transparent hydrogel wood can reduce the indoor air temperature by 4.3 °C. Furthermore, a computational simulation for an office building proves that 2.6–10.2% energy could be saved by thermochromic transparent hydrogel wood in four different climate-zone cities. Besides, thanks to the flexibility, thermochromic transparent hydrogel wood can be easily fitted on existing windows, demonstrating the great potential for use in energy-efficient buildings.

This paper proposes a novel passive cooling method utilizing the heat capacity of the ground under an uninsulated floor slab in the summer to cool the inside air. The calculation results and measurements of the indoor air temperature inside two full-scale laboratory rooms located in western Poland were validated with simultaneous statistical analysis. The similar, terraced rooms differed from each other only in the presence or absence of thermal insulation over the whole floor slab area. Experimental research fully confirmed the simulation results. Omitting the ground floor thermal insulation decreased the indoor air temperature in the room during a 2 week heat wave by almost 4 K; thus, the cooling potential of the uninsulated floor is approximately 0.2 MJ/m 2 day. Moreover, the cooling effect remained stable independent of the heat wave duration. The differences in the average floor surface temperature did not exceed 0.5 K; therefore, the “cold floor” effect was negligible. The energy demand for the two rooms was significantly different but can be easily offset by alternative energy sources, e.g., solar energy.

Classrooms in Southern Europe are traditionally ventilated with manual opening of windows. This is an energy-sparing and perfectly appropriate way of ventilating classrooms when weather conditions are warm, however, as outdoor air temperatures drop, teaching staff and students tend to leave windows closed and, as a consequence, ventilation rates fall leading to poor indoor air quality. To safeguard classrooms' indoor air quality and promote energy conservation, understanding the conditions for which manual window-airing is appropriate is of great relevance. Yet, given the stochastic nature of window-airing, it is difficult to get hold of this understanding. The main objective of this paper is to find out when manual window-airing of classrooms is appropriate. To achieve this objective, four free-running classrooms of a Portuguese public secondary school were monitored during a two-year period. Ventilation rates were determined and it is concluded that manual opening of windows provides appropriate ventilation for outdoor running mean temperatures larger than 19 °C. When outdoor running mean temperatures are lower than 16 °C, manual window-airing becomes inappropriate and, for outdoor running mean temperatures between 16 and 19 °C, appropriate manual window-airing depends on the indoor air temperature. For the studied classrooms, these results translate into appropriate ventilation for approximately a quarter of the academic year. Because of the significance of this finding, the paper concludes with a review of the ventilation strategy used in the studied classrooms.

This paper reviews the most used thermal comfort models and indicators with their variants, discussing their usage in control problems referring to energy management in indoor applications. The first part addresses the recent literature referring to the thermal comfort concepts, models of human thermal comfort, thermal comfort models and indicators, thermal comfort standards, control systems, optimisation methods, and practical assessments. Then, the ambient and personal parameters used to represent thermal comfort and thermal sensation are recalled. The following part reviews the definitions and usage of a number of thermal comfort indices, mainly related to the Predicted Mean Vote ( PMV ), the Actual Mean Vote ( AMV ), and the Predicted Percentage Dissatisfied ( PPD ), with their modifications and variants, indicating a number of applications to different situations in indoor environments. The last part reviews the thermal comfort models used to define control strategies in indoor applications, discussing the characteristics and parameters of models based on artificial neural networks, autoregressive variants, fuzzy control, and hybrid models combining different approaches. The characteristics of these models and their usage to predict the indoor air temperature and the PMV index are discussed with reference to the identification of the several inputs used in relevant literature contributions.

In Southeast Asia with tropical climates, Chinese Shophouse (CSH) as a type of vernacular architecture is usually equipped with small intermediate air-well type courtyards, also known as ‘Tianjin’, to moderate the indoor thermal environment. This paper investigates the effectiveness of air-well type courtyards as passive design strategies on moderating indoor thermal environments in two CSHs located in Malacca, Malaysia. The study used a field survey and a CFD simulation. Statistical analyses of indoor air temperature and heat index (HI) measured at different locations of the CSHs show that intermediate spaces next to the air-wells had significantly lower air temperature and HI. Cross ventilation through the openings on the walls and air-wells resulted in a significantly lower normalized mean age of air and higher air velocity. The air-well is a suitable passive design strategy to reduce overheating during daytime and to increase cooling of building structure during night-time. The air-well courty...

9th Mediterranean Conference of HVAC: Historical Buildings Retrofit in the Mediterranean Area, Climamed 2017; Matera; Italy; 12 May 2017 through 13 May 2017, Mosques differ from other types of buildings by having an intermittent operation schedule. Due to five prayer times per day throughout the year, mosques are fully or partially, yet periodically, occupied. This paper examines the potential of using an underfloor heating system for improvement of indoor thermal comfort in a historic mosque, which is naturally ventilated, heated and cooled, based on adaptive thermal comfort method. The selected Salepçioǧlu Mosque, housing valuable wall paintings, was built in 1905 in KemeraltI, Izmir, Turkey. It requires specific attention with its cultural heritage value. Firstly, indoor microclimate of the Mosque was monitored for one-year period of 2014-15. Then, dynamic simulation modelling tool, DesignBuilder v.4.2 was used to create the physical model of the Mosque. The ASHRAE Guideline 14 indices were utilized to calibrate the model, by comparing simulated and measured indoor air temperature to achieve hourly errors within defined ranges. The results of calibrated baseline model indicate that the Mosque does not satisfy acceptable thermal comfort levels for winter months that provided by the adaptive method. Then, the effect of underfloor heating was examined in the second model by the.

Addressing thermal comfort is an important aspect of applying economic model predictive control (E-MPC) schemes with the objective to perform demand response (DR), e.g. minimize operational cost. This paper compares the performance of four E-MPC schemes using both single-objective and multi-objective formulations to address thermal comfort. It is difficult to proclaim the superior formulation as the notion of thermal comfort is a subjective matter. However, the single-objective problem formulation proposed in this paper contains a parameter, e max , which describes the maximum acceptable deviations from the preferred indoor air temperature. This parameter can be regarded as a user-defined indicator of the acceptable deviations from the preferred temperature or, in other words, their ‘DR willingness’.

To meet the heating demand in north China and reduce the pollution of traditional Chinese kang, a novel combined heating system consists of solar kang system and solar air heating system is proposed. The solar air system is built for the residents’ daily heating demand. The solar kang system can store the solar energy collected in the daytime and provide a good sleeping environment at night. In this study, demonstration buildings are built in Huzhu, Qinghai province and one of them is chosen to test its thermal performance. Three different operation modes: only the solar air system works, only the solar kang system works and the whole combined system works are tested. A mathematic model of the room and combined system is built based on the demonstrating building. Output simulation results are compared with experiment data. The result shows the combined system can rise the indoor air temperature significantly and the simulation result can fit the experiment well. The indoor air temperature can keep about 18 °C when the ambient average temperature is 5 °C. Kang surface temperature can keep above 26 °C during the night at the same condition. The study proves the excellent heating performance of the combined system.

A simulation study to improve energy and indoor environmental performance of a rural house by retrofitting in Beijing of China is presented in this paper. This dwelling was retrofitted using passive energy saving methods and it aims to reduce the annual energy consumption, especially the energy used for household heating demands and to improve the indoor air temperature during the winter. Two main retrofitting methods were used for this case study: insulation was added to the envelope of the house, and the single glazing windows had been replaced by double glazing. The model of this rural house simulated by DesignBuilder software is validated by the actual energy consumption. The validated model is then used to evaluate and predict the future performance of this house. The findings of this study indicate the advantages of retrofitting a rural house by using passive methods: annual energy saving for heating is about 60% and the indoor temperature of the house can be improved dramatically compared to its original status. Moreover, the environmental impacts cause by the heating fuel source has been mitigated. The results showed the potential for rural house retrofitting using passive energy saving methods in northern China.

Living in cold conditions poses a risk to health, in particular to low-income, fuel-poor households. Improving the energy efficiency of the housing stock may bring multiple positive health gains through improved indoor temperatures and reduced fuel consumption. This study used a multilevel interrupted time-series approach to evaluate a policy-led energy-performance investment programme. Long-term monitoring data were collected for intervention and control households at baseline (n = 99) and follow-up (n = 88), creating a dataset with 15,771 data points for a series of daily-averaged hydrothermal outcome variables. The study found that the intervention raised indoor air temperature by on average 0.84 K as compared with control households, thereby bringing the majority of indoor temperature measurements within the ‘healthy’ comfort zone of 18–24°C, while average daily gas usage dropped by 37%. External wall insulation was the most effective measure to increase indoor air temperature. The greatest increases were found in the evening and at night, in the bedroom, and in British steel-framed buildings. No evidence was found that the intervention substantially increased indoor relative humidity levels when accompanied by mechanical ventilation. The study concludes that the multilevel interrupted time-series approach offers a useful model for evaluating housing improvement programmes.

Due to the low thermal inertia and poor thermal insulation of ultrathin envelope in tents, its indoor temperature environment is extremely bad and its occupants are tormented. Especially under the high solar radiation, both indoor air temperature and inner surface radiation temperature increase rapidly. And thereby, decreasing radiation heat gain in summer is necessary to refine indoor temperature environment in tents. Retro-reflective materials make it a reasonable choice due to their high reflectivity for solar radiation. To reveal the temperature environment improvement of tents by integrating with retro-reflective materials, a comparative experiment is carried out under the summer climatic conditions of Chengdu city, China. Experimental results show that due to integrating with retro-reflective materials, indoor air peak temperature in the tent can be reduced by more than 7.7 °C, while inner surface radiant temperature can be lowered up to 4.8 °C in the day time. It shows retro-reflective materials could refine indoor temperature environment in tents. Through a comparison of the walls in different orientations, on which retro-reflective materials are covered, the top, east and north walls are found to be better choices, while the north wall is the worst one for retro-reflective materials.

Vertical Greenery Systems (VGS) are upcoming facade cladding fixtures which restore the connection between the city and nature. They are capable of providing thermal benefits to the building. The objective of this study is to explore the impact of VGS on building energy performance. This study simulates thermal effect of VGS using a mathematical model based on heat balance principle of the foliage layer and soil later, which is then integrated into one of the widely accepted building simulation program, EnergyPlus. The integrated VGS model is validated against two reported experimental studies, and show good agreement. Validation results show that integrated VGS model satisfactorily predict the effect of VGS on indoor air temperature and exterior and interior surface temperature of facades with VGS. The integrated VGS model is then used to assess the impact of VGS on building energy performance in warm temperature climates. Simulations have shown that in hot summer days, VGS leads to reduce exterior surface temperature of building facades, maximum of 26 °C. The annual cooling energy consumption is reduced by 3% for warm temperature climates. However, during the winter season insulation effect of VGS cause increase in heating demand of the building. Simulations suggest that, passive energy benefits of VGS are promising during summer periods, whereas it may disadvantageous during winter periods. However, in warm temperature climates, VGS still able to provide net passive energy benefits to the building.

In this paper the thermal performance of synthetic and natural insulation materials under real applications are investigated through an experimental activity as well as numerical simulations. During the refurbishment of two houses in Turin (north western Italy) one roof was insulated with a natural material (wood fiber panels) and the other one with a business as usual synthetic material (XPS and polyurethane). An experimental activity was carried out, both during summer and winter seasons, and the results were used to validate a simplified model. During winter, as expected, the strongest influence on the global performance is related to the insulation thickness. As far as the summer season performance is regarded, for smaller roof surfaces, as for the analysed case study, no particular difference was noticed between the two solutions. A better control of the indoor air temperature was evaluated for the wood fiber insulation when applied on a large surface of the roof. In order to define the best cost-benefit retrofit solutions, ad-hoc evaluations need to be performed.

The aim of the study is to simulate the functionality of a HVAC system in different situations, summer and winter time, using specialized software ANSYS-Fluent. A 2D building model was realized and simulating the internal conditions represented the main elements of the study. There are studied the indoor air temperature and air velocity in different conditions. The results are presented as graphs/plots and spectra of interest parameters. HVAC system functionality simulation using ANSYS-Fluent is providing important results for the studied scenario.

HVAC systems are often used to reach thermal comfort in buildings. It is then necessary to understand the resulting indoor airflow and thermal conditions to optimize the systems. Therefore, this paper presents detailed measurements of axisymmetric and anisothermal jets developing near the ceiling of a thermally controlled room called MINIBAT. Air temperature, velocity and turbulent quantities over five vertical plans on the room were measured using adequate materials such as Pt100 probes and a hot-wire anemometer. These data are to be used for the analysis of indoor air mixing processes and CFD validation. The detailed experimental process and measurements as well as CFD results are exposed in [1]. Keywords: Building physics, HVAC, Axisymmetric anisothermal jet, Indoor air temperature, Turbulent flow, CFD validation data

The main purpose of Heating, Ventilating and Air-Conditioning (HVAC) systems is to satisfy thermal comfort for the occupants. Conventionally, HVAC systems adjust set-temperature to achieve thermal comfort by continuously measuring indoor air temperature of the environment. However, ASHRAE 55, a standard of acceptable thermal environments, offers to use acceptable ranges of operative temperatures in air-conditioned buildings. Considering operative temperature is a function of indoor air temperature and mean radiant temperature, set-temperature of HVAC system can be controlled by using operative temperature to satisfy neutral thermal comfort for the occupants. This study compares thermal comfort and energy consumption of two exactly same HVAC systems which are operated based on indoor air temperature and operative temperature, respectively. Two office rooms with same architectural configurations -which are located in a university-Ankara-Turkey- were selected as a case study. The HVAC systems were operated based on indoor air temperature and operative temperature, respectively, at the same time and occupancy schedules. The results showed that operative temperature driven controlled HVAC system achieves better thermal comfort while slightly increasing energy consumption. The main findings of this study would be useful not only to design energy-efficient HVAC systems but also create more comfortable environments.

[EN] A Mobile Monitoring System (MMS) has been designed tak- ing into account the use of technology with high sensor ac- curacy and the ability to be installed easily and quickly in different cardinal locations, distribution spaces, volumes and at different heights of a tertiary in-use building located in Leioa (Bilbao). Two types of MMS have been designed with the objective of carrying out two types of analysis; one in- tended to do a global indoor air temperature uncertainty analysis and the other focused on doing a global outdoor air temperature uncertainty analysis. Eight tripods make up the interior MMS with twenty sen- sors at different heights, which have been installed in differ- ent offices in the building to collect indoor air temperature measurements at different heights and locations. In addition, eight sensors make up the exterior MMS to collect data from outdoor air temperature measurements around the building envelope. Both MMS have been integrated into the existing Building Automation System (BAS) of the tertiary building; some other data collected by the BAS has also been taken into account for the uncertainty analysis of indoor and out- door air temperature. The interior and exterior MMS datasets have been compiled based on a rigorous data collection process, with the po- tential to use the data to study the spatial air temperature behavior, taking into account the impact of solar radiation, the heating system and the electrical energy consumption. Furthermore, it enables the global uncertainty of indoor and outdoor air temperature measurements on an in-use build- ing to be estimated and to break it down into the differ- ent uncertainty sources, such as the sensor accuracy, vertical and horizontal temperature variability, solar radiation, occu- pancy and heating system effects. Finally, it enables the opti- mization of monitoring and control systems for BAS, heating and HVAC systems, as well as any monitoring system imple- mented in research tests using indoor and/or outdoor tem- perature measurements as key variables.

Previous research has shown that under-ventilation of classrooms is common and negatively impacts student health and learning. To advance understanding of contributing factors, this study visited 104 classrooms from 11 schools that had recently been retrofitted with new heating, ventilation, and air-conditioning (HVAC) units. CO2 concentration, room and supply air temperature and relative humidity, and door opening were measured for four weeks in each classroom. Field inspections identified HVAC equipment, fan control, and/or filter maintenance problems in 51% of the studied classrooms. Across 94 classrooms with valid data, average CO2 concentrations measured during school hours had a mean of 895 ppm and a standard deviation (SD) of 263 ppm. Ventilation rates (VRs), estimated using the daily maximum 15-min CO2 in each classroom, had a mean of 5.2 L/s-person and a SD of 2.0 L/s-person across 94 classrooms. Classrooms with economizers, with or without demand control ventilation (DCV), tended to have lower mean CO2. Improperly selected equipment, lack of commissioning, incorrect fan control settings and maintenance issues (heavily loaded filters) were all associated with under-ventilation in classrooms. Many classrooms in this sample were frequently too warm to support learning. There were 23 out of 103 classrooms that had indoor air temperature above 25.6 °C for more than 20% of the school hours. Better oversight on HVAC system installation and commissioning are needed to ensure adequate classroom ventilation. Periodic testing of ventilation systems and/or continuous real-time CO2 monitoring (either as stand-alone monitors or incorporated into thermostats) is recommended to detect and correct ventilation problems.

This study examined indoor air pollutants and their health effects on allergic rhinitis in 3194 employees of 226 bus station halls and then constructed a nomogram model to predict allergic rhinitis risk in those employees. Indoor air temperature, relative humidity, PM10 , PM2.5 , total bacteria, and total fungi were measured, and questionnaires were used to collect basic station information and employee health information. The results revealed that the over-standard rates of PM10 , PM2.5 , total bacteria, and total fungi were 18.16%, 31.13%, 2.22%, and 55.89%, respectively. Seasonal variations were found in temperature, relative humidity, and PM2.5 . Passenger flow could affect temperature, and total bacteria. Central air conditioning could affect total bacteria. A total of 15.90% of the employees were diagnosed as allergic rhinitis by physicians. Relative humidity, fungi, self-reported allergic rhinitis symptoms, and exposure to smoking were the influencing factors for allergic rhinitis. These four variables were incorporated to construct a nomogram. The concordance index of the nomogram was 0.775 (95% CI: 0.745-0.806) and 0.749 (95% CI: 0.715-0.783) for the training cohort and test cohort, respectively. The calibration plot revealed that the nomogram model exhibited good discrimination and consistency. This nomogram model may help predict the occurrence of allergic rhinitis.

Traditional air conditioners are designed to maintain the indoor temperature and humidity at a desired level. They were not designed to monitor room occupants comfort and because of controlling the indoor air temperature they consume extra energy. The purpose of this project was to improve building occupants’ thermal comfort and optimize the energy consumption by air conditioners. This was achieved by relating building occupant blood pressure to the temperature fed by air-conditioner. From the results of this study, it was noticed an inverse relationship between the blood pressure and Temperature. The project is relevant for improving the comfort of the people subjected to air-conditioned environment and helps to optimize the energy consumption by the air conditioners

Currently, in order to achieve the optimal thermal comfort for a given occupant, the optimal indoor air temperature should be set by the occupant himself/herself and then the air conditioning is used to control the actual indoor air temperature to converge to the optimal temperature. In this paper, we develop a method to determine the optimal indoor air temperature with which the air conditioning can be adjusted automatically without the involvement of the occupant. We first borrow the predicted mean vote(PMV) model to describe the relationship between the indoor air temperature and the occupant’s thermal comfort. We then adopt the deep learning method to obtain a classification deep neural network model which is used to capture the relationship between the indoor air temperature and the occupant’s thermal comfort. We test the model and the result shows that its mean average error is about 0.1°C, which satisfies the accuracy requirements of practical systems.

The thermal environment in bedrooms is important for high-quality sleep. Studies confirm that, even during sleep, the human body remains sensitive to the ambient air temperature. This study assesses how changing indoor air temperatures at different sleep stages affects the subjective evaluation of sleep quality. We compare reports from two identical sleeping environments with different thermal control systems: an IoT-based control system that adjusts the indoor air temperature according to the sleep stage and a fixed control system that maintains a constant temperature throughout the night. Ten subjects participated in the experiments and completed a questionnaire about their sleep quality. Our results show that, overall, the subjects experienced better sleep in the room with the IoT-based control system than in the one with a fixed thermal control. The mean differences in sleep satisfaction levels between the two sleeping environments were generally statistically significant in favor of the room with the IoT-based thermal control. Our results thus illustrate the suitability of using the IoT to control the air conditioning in bedrooms to provide improved sleep quality.

Cooling radiant ceiling panel (CRCP) have been dramatically applied in modern buildings. Therefore, the key aim of this article is to recommend a new multi-segmented mini-channel-based CRCP with four distinct designs to compete with the traditional flat sheet-and-tube CRCP. In these designs, the panel is divided into multi-strips wide mini-channel. These segments are integrated into the room with a different inclination angles. This permits the designers to enlarge the number of segments or the panel area for the same constrained ceiling area. Two different 3D CFD models are developed and validated. The first model is a conjugate heat transfer model used to compare the thermo-hydraulic performance of the sheet and tube CRCP with the new proposed mini-channel-based CRCP. The second model is utilized to integrate the new mini-channel with different designs for the standard testing methods. The findings demonstrate that the mini-channel CRCR accomplish high panel temperature uniformity, higher cooling capacity, and lower power consumption in comparison with the traditional sheet and tube panels. Furthermore, the multi-segmented mini-channel CRCP inclined with ± 45°, V- shape, with 83% increased area accomplish a 51% boost in the cooling capacity at the same indoor temperature. Also, it is worth declaring that this design can be conducted at a panel temperature of 18.8 °C to accomplish the same cooling capacity and the identical indoor air temperature obtained by a flat CRCP with panel temperature of 15.8 °C.

The integration of phase change material (PCM) into Trombe wall in a passive solar building is a potential way for the heating performance improvement of Trombe wall and effective utilization of solar energy. This work aims to explore the optimal combination of melting temperature and PCM layer thickness in the PCM Trombe wall in Beijing, Jiuquan, and Shenyang, which are located in three solar energy distribution zones of China, respectively. The state space model of a solar passive building with an integrated PCM Trombe wall is developed considering the two-dimensional heat transfer of PCM layer. The state space model is validated by the experimental results. The experimental and numerical results show that the heating capacity of Trombe wall has a remarkable influence on indoor air temperature. Based on the daily accumulative deviation of indoor air temperature and the heating capacity of Trombe wall, it is found from the simulated results that the optimum combination of PCM melting temperature and layer thickness are 23 °C and 5 cm for Beijing and Jiuquan, 21 °C and 5 cm for Shenyang. Besides, this study also obtains that the effective thicknesses of PCM layer corresponding to different melting temperatures of PCM are equal to or less than the PCM layer thickness.

This paper is an updated, but totally new, version of “A review on phase change materials (PCMs) integrated in building walls”, an article published in 2011 in Renewable and Sustainable Energy Reviews. Both numerical and experimental studies on building walls containing PCMs during the last ten years (2011–2020) are reviewed. The paper also summarizes the main PCMs used in this application and the recent progress in the integration techniques of PCMs in building construction elements. Most of the proposed studies (about 66%) are focused on PCM in walls. In addition, more than half of these studies are numerical where several assumptions are made such as the neglected of both the occupant presence in the building and its behaviour. Based on this review, it is concluded that the used PCMs in building walls showed good potential for reducing both indoor air temperature fluctuations and energy consumption. However, further numerical and experimental studies are needed that take other aspects into consideration, such as the real use of buildings with the occupant behaviour, the economic viability and the environmental impact. This review paper will help scientific researchers and engineers to update the integration techniques of PCM in building walls and to define potential future research works.

As the number of installed meters in buildings increases, there is a growing number of data time-series that could be used to develop data-driven models to support and optimize building operation. However, building data sets are often characterized by errors and missing values, which are considered, by the recent research, among the main limiting factors on the performance of the proposed models. Motivated by the need to address the problem of missing data in building operation, this work presents a data-driven approach to fill these gaps. In this study, three different autoencoder neural networks are trained to reconstruct missing short-term indoor environment data time-series in a data set collected in an office building in Aachen, Germany. This consisted of a four year-long monitoring campaign in and between the years 2014 and 2017, of 84 different rooms. The models are applicable for different time-series obtained from room automation, such as indoor air temperature, relative humidity and $CO_{2}$ data streams. The results prove that the proposed methods outperform classic numerical approaches and they result in reconstructing the corresponding variables with average RMSEs of 0.42 {\deg}C, 1.30 % and 78.41 ppm, respectively., Comment: Accepted in Building and Environment

This article describes a methodological approach to defining indoor air temperature in buildings heated by a power supply unit consisting of a boiler house and a wind-driven power plant (WDPP). We discuss a heating option for a residential building in the windy conditions of Murmansk city. We proved that, during the periods of strong wind, a WDPP can partially or fully satisfy the heat demand and sometimes even create a surplus of energy. During low wind weather, almost all loads are handled by the boiler house. We considered a possibility to accumulate the surplus energy obtained from a WDPP during strong wind by increasing the temperature in the whole building up to 25°C and further using the accumulated heat during the lowwind period when indoor air temperature may fall below 20°C. This allows saving organic fuel in the boiler house. We demonstrated how indoor air temperature in the building may change throughout the year when using the surplus energy from the WDPP due to thermal storage capacitance of the building. We also provided the results of study, showing favorable energy-related effects of using a WDPP along with the boiler house. It was determined that engaging a WDPP in fulfilling the diagram of heating loads promotes the decrease in the boiler house’s contribution to heat supply by 30 to 50%, and using the surplus energy from the WDPP and thermal storage capacitance of the building allows reducing the contribution of the boiler house by 5–15% more in certain months.

In office buildings, dividing outer and inner space reasonably is the key issue to achieve the symmetrical indoor air temperature. This paper aims to analysis the classified methods of outer and inner space and obtain the air conditioning systems with different orientations based on TRNSYS. Studies indicate that: i) the outer area load vary with the season, but inner space’s load is cold load throughout the year; ii) the temperature of outer zone’s south room is higher than other orientations and air conditioning system shall be installed separately.

A novel weights based fuzzy logic control algorithm (WBFLCA) has been previously developed. The control algorithm is able to control indoor temperature and humidity simultaneously using direct expansion (DX) air-conditioning (A/C) system. However, linguistic variables and weights of WBFLCA must be carefully chosen, otherwise hunting of control parameters may happen. This paper evaluates control performance of WBFLCA under 16 combinations of weights setting rules (4 kinds of rules for temperature and humidity respectively) to find out optimal setting rules. The simulation model is comprised of a DX A/C system model, a room thermal model and a WBFLCA controller. Indoor temperature and humidity are control parameters, while fan speed and compressor speed of A/C system are modulated variables in DX A/C system. Details of simulation results are discussed. An optimal setting rule for WBFLCA is established. PID control is also implemented to compare decoupling performance of the two control algorithms.