This study focuses on the optimum cooling effect of trees with ground materials modification in mitigating the urban heat island (UHI) and the benefits towards building energy performance in tropical ...climate. The modification focused on both physical properties – i.e. tree canopy density and quantity; and the albedo values of ground materials. Two phases of methodology were developed and applied using field measurement and computer simulation. This study measured the average monthly UHI intensity found to be +2.6 °C. In mitigating its impact, higher levels of tree canopy density (LAI 9.7) coupled with “cool” materials (albedo of 0.8) produced the largest urban air temperature reduction. Simulations predicted an average air temperature reduction of 2.7 °C when compared with the current condition. Further, both modifications were found to produce a potential building cooling load reduction of up to 29%. In fact, the optimum improvement of both outdoor and indoor environment was influenced by three major physical factors, namely, larger tree quantity, higher canopy density and cool materials. Thus, it is suggested that appropriate guidelines, influencing implementation of these improvements could be implemented in order to mitigate the UHI effect in tropical climate.
► The cooling effect potential of trees and ground material properties modification. ► Larger quantity of high density tree and cool material improved urban air temperature. ► Improved UHI intensity up to 2.7 °C. ► The combined effect could reduce total building cooling load up to 29%.
People spend about one third of their lives sleeping. Sleep is essential for the recovery of the body from both physical and psychological fatigue suffered throughout the day, the refreshment of ...mind, and the restoration of energy for maintenance of bodily functions. Current thermal comfort theories and standards are mainly concerned with people in waking state. However, many problems regarding thermal environment are found within a few field surveys in bedrooms, pushing out the need to investigate thermal environment and thermal comfort for sleeping people. In this paper, the questions concerning the measurement and evaluation of human sleep quality, the correlation between thermal regulation system and sleep regulation, and the characteristics of night-time space cooling load etc. are answered. The evidences illustrating the effects of thermal parameters on human sleep quality are also provided, in an attempt to shed light on the thermal comfort requirements of sleeping people.
•Human sleep quality can be objectively evaluated with the recordings of eye movement, chin muscle tension, and brain wave.•People prefer a warmer environment in sleep compared to the pre-sleep waking state.•Air flow could be used to improve thermal comfort for sleeping people while achieving energy saving.
•Case study for testing mock target IR Thermography technique under transient conditions.•Mock target IR Thermography was proven in concept for non intrusive measurement of stratification.•Results ...reveal good reponse of the technique under transient conditions with average time lag of 15 min.•Results confirmed with validated numerical model, and extend the scope of the assessment under diverse conditions.
Mock Target IR Thermography for indoor air temperature measurement has been proven as an effective methodology for steady-state conditions. This method uses vertical poles of known emissivity placed in a space to measure air temperature by employing IR thermography. Compared to thermocouple / point-by-point measurement, this technique allows obtaining air temperature values in a continuous line. Several poles can be installed in a space ensuring the collection of a large amount of air temperature data entries by taking a single IR image, whereas measurements in large spaces with hundreds of thermocouples would require complicated wiring and data collection hardware. However, for this approach to be more widely considered, such measurement techniques should be adaptable for transient conditions as well, as air temperature can fluctuate and change due to external climatic conditions, occupancy or faults in HVAC equipment. This work aims to investigate if IR Thermography which was only tested in steady-state conditions can be applied to conditions of transient variation of indoor air temperature. For this purpose, measurements under lab conditions and numerical analysis with the use of finite element modelling (FEM) were performed. Specifically, measurements were carried out by using both Mock Target IR thermography and thermocouples, to investigate the precision of IR-obtained transient data. The experiments were conducted in the environmental chamber under controlled conditions. Three types of heating systems (underfloor heating, radiator heating, and ventilation heating) were investigated to ensure that the method is tested under conditions of different heat-emitting devices, as well as different convection and radiation ratios. Validated numerical models were developed using the FEM Multiphysics approach, to extend the scope of the assessment under various conditions and to observe the difference between the mock target pole temperature and air temperature. It was concluded that the mock target IR Thermography performance was accurate for the case of transient air temperature, as well as for different rates of temperature change, with an average temperature deviation of 0.4 % according to the experimental measurements and 1.74 % based on the numerical simulations.
Indoor thermal environment is usually non-uniform in buildings with passive or active radiant surfaces, and strict constraints for thermal homogeneity would increase the difficulty of system design ...and cause unnecessary energy consumption. In order to explore the thermal comfort response characteristics in non-uniform environments, 20 subjects were recruited in this study to participate in a thermal comfort experiment in two types of non-uniform environments. The two non-uniform environments were created by different combinations of indoor air temperature and radiant temperature. In the first non-uniform environment, all the interior surface temperatures were equal, but the radiant temperature and air temperature were not equal (ANUE). The other type was a single surface non-uniform environment where the surface temperature of one interior surface and the air temperature were not equal (SNUE). Subjects’ physiological parameters were measured and subjective evaluations were obtained by questionnaires. The results showed that in thermal neutral condition, the mean skin temperature was 33.6 °C under ANUE environment, while it was 33.8°C–33.9 °C under SNUE environment. Based on the experimental results, thermal dissatisfied percentage (TDP) models for the two environments were proposed and evaluated by determination coefficient and Bayesian information criterion (BIC). According to the five different TDP levels (5%, 10%, 15%, 20%, 25%), coupling thermal comfort zone of indoor air temperature and surface temperature was classified into five hierarchies. The study has implications for the proper design of comfortable and energy saving non-uniform environments.
•Non-uniform thermal environment was created by indoor air and surface temperature.•Physiological and comfort characteristics in non-uniform environment were explored.•tmst for thermoneutrality under non-uniform thermal environment was obtained.•TDP models were established for two types of non-uniform thermal environments.
•A new building envelope with variable thermal performance under step control operation strategy was proposed;•Field test results were in good agreement with model simulation results;•Trade-off ...between solar heat gain coefficient and thermal resistance was well coordinated;•Indoor thermal environment was improved with the new building envelope.
The integration of passive solar heating strategies into the existing buildings has been considered as an innovative and effective approach to mitigate energy and environmental issues. To balance the trade-off between solar heat gain and thermal insulation in traditional passive solar systems, this paper presented an innovative envelope with variable thermal performance for passive solar buildings. Field measurement was carried out to validate the feasibility of the transparent building envelope under step control operation strategy to building comfortable indoor environment especially in cold plateau areas. The experimental results show that, even under harsh climate conditions, the application of the proposed building envelope effectively increases the heat gain and maintains indoor temperature at a relatively comfortable level in the studied case. The average indoor air temperature of the studied rooms is at 13.0–14.0 °C, with the highest temperature up to 21 °C. Numerical simulation by DesignBuilder software was further developed to exploit the efficiency of the proposed building envelope under the step control operation strategy for increasing the indoor temperature. The simulation results show the same tendency with the filed measurement results. The operation strategy of opening indoor window at 10:00 am and closing at 5:00 pm can achieve the maximization of solar gain, significantly increasing the indoor temperature. Attributed to good balance between solar heat gain coefficient and thermal resistance, the average temperature of the room with the proposed envelope mode is 2.0 °C (sunny day) and 1.5 °C (cloudy day) higher than that of another three passive solar envelope operation modes, respectively. In general, the proposed building envelope with variable thermal performance has high potential to improve the indoor thermal environment in cold plateau areas at low cost.
This paper presents an experimental study on the indoor air temperature near residential facades in naturally ventilated buildings in tropical climate of Singapore. Four residential sites (Site A-D) ...with different design features were selected for investigation. Indoor measurements were conducted at locations 30-cm away from the façades.
Field measurement results showed that windows are of great significance to indoor thermal environment. In vacant units, the peak indoor air temperature reached 44 °C near a large west-facing window at Site A on sunny afternoon, when windows were kept closed and window-to-wall ratio (WWR) was 0.9. Air temperature near the closed window was lowered by 4.1 °C in the afternoon when WWR was reduced from 0.9 to 0.6. Moreover, window openings can effectively lower the indoor air temperature. At Site B, indoor air near a closed window was 7.6 °C hotter than that near an open window with the same orientation and window, and the average temperature difference reached 3.2 °C during daytime (7:00–19:00). In occupied units, air temperature near the north-facing façade was found 4.7 °C higher than that near the east-facing façade in July at Site D, due the sun path in Singapore. The percentages of time with indoor comfortable conditions were evaluated using the criterion for Asian residential buildings in summer. It was found that the acceptable time percentages were no less than 80% for indoor locations with daytime or occasional window ventilation. Façade design recommendations were proposed to reduce indoor air temperature and improve indoor thermal comfort in tropical climate.
•Both vacant and occupied residential buildings in tropics were studied.•Indoor air temperature near different residential facades were measured.•The impact of façade orientation, WWR, external shading, and openings was evaluated.•Residential façade design recommendations are provided for indoor thermal comfort.
Understanding the associations of indoor air temperature with building physical characteristics is essential for human comfort and energy saving. While traditional studies depended heavily on ...simulation tools, statistical approaches have recently provided higher flexibility and efficiency to explore factors associated with indoor air temperature. Under such background, this study systematically constructed building spatial design and occupancy features for 53 university classrooms in 4 teaching buildings in Beijing, China, and used statistical models to quantify their impacts on indoor air temperature. Both multiple linear regression (MLR) and random forest regression (RFR) were conducted for different time periods in a day, and the MLR coefficients and RFR feature importance were examined. 16 spatial design features and 5 occupancy features were identified as significant. Among spatial design features, floor number of the classroom had the most notable positive impacts throughout a day. Window-to-wall ratios from different orientations had distinctive influences and added up to make a huge difference. Impacts from classroom size and position, parent building's forms and envelopes were certain but less important. Among occupancy features, it was found for teaching buildings that the whole-buildings’ occupancy had stronger impacts over the classrooms' one, and daily occupancy over temporal one, with building daily occupancy rate being the most influential. The results highlight the potential to adjust thermal environment through proper organization of spatial design and occupancy features addressing their rankings. The RFR models obtained adjusted R2 of above 98%, testifying the effectiveness of predicting indoor air temperature with well-selected building features.
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•16 spatial design and 5 occupancy features were related to indoor air temperature.•Impacts of these features were quantified and ranked using statistical models.•Floor number of the classroom was the most influential spatial design feature.•Building daily occupancy rate was the most influential occupancy feature.•The random forest regression models obtained notable performance.
•Demand-controlled ventilation for energy-efficient mechanical ventilation in pigsty.•Indoor temperature and CO2 concentration prediction model was developed.•Changes in pig weights affected ...prediction performance.•15-minute time step DCV control achieved smaller change in indoor temperature.
The distribution of agricultural and livestock products has been limited owing to the recent rapid population growth and the COVID-19 pandemic; this has led to an increase in the demand for food security. The livestock industry is interested in increasing the growth performance of livestock that has resulted in the need for a mechanical ventilation system that can create a comfortable indoor environment. In this study, the applicability of demand-controlled ventilation (DCV) to energy-efficient mechanical ventilation control in a pigsty was analyzed. To this end, an indoor temperature and CO2 concentration prediction model was developed, and the indoor environment and energy consumption behavior based on the application of DCV control were analyzed. As a result, when DCV control was applied, the energy consumption was smaller than that of the existing control method; however, when it was controlled in an hourly time step, the increase in indoor temperature was large, and several sections exceeded the maximum temperature. In addition, when it was controlled in 15-min time steps, the increase in indoor temperature and energy consumption decreased; however, it was not energy efficient on days with high-outdoor temperature and pig heat.
Although smart thermostats have increasingly provided homeowners with abundant operational data related to advanced HVAC control and energy usage management in homes, there is a lack of systematic ...frameworks that can utilize such data to generate actionable information for advanced home comfort system diagnosis and control. Recognizing that a home thermal model, which is capable of connecting weather and HVAC operational data, is crucial to this framework, this paper introduces a home thermal model that is built upon the standard RC (Resistor–Capacitor) approach and the one virtual envelope assumption to describe the thermal dynamics of a home. A parameter estimation scheme is also developed that enables automatic, sequential, and optimal estimation of the model parameters, i.e., the thermal properties, of a home. Finally, the home thermal model and its parameter estimation scheme are tested using data collected over 63 consecutive days from a test home. In the test, the length of data that can provide enough robustness for parameter estimation is investigated. It is found that 10 days of data are enough, although 20 or more days of data can provide more robust results. In addition, when the model is used to make 12-hour-ahead predictions of indoor temperature, the resulting mean, maximum, and 95%-confidence-interval absolute are 0.31 °C, 1.72 °C, and 0.90 °C, respectively, if the model is trained using 10 consecutive days of data, and 0.27 °C, 1.19 °C, and 0.72 °C, respectively, if 20 consecutive days are used. Therefore, the proposed home thermal model requires only a modest amount of training data to yield fairly accurate prediction and is able to perform better with more data.
We are considering the problem of reconstructing indoor temperature distributions using the Acoustic travel-time TOMography (ATOM) technique. Motivated by the benefits of acoustic rooms, we ...reconstruct the field from the estimated time-of-flight (TOF) of the early reflections, considering the first, second, and third orders. Here, TOF collected from early reflections is used as an input dataset to reconstruct indoor air temperature using the simultaneous iterative reconstruction technique (SIRT). Results showed that even with only one loudspeaker and one microphone, we obtain promising reconstruction fields. However, in order to control the semiconvergence of the SIRT algorithm, several examples of reconstructed fields are provided to highlight the effects of linkage between voxels (so-called weighting factor <inline-formula> <tex-math notation="LaTeX">w </tex-math></inline-formula>), relaxation parameter (<inline-formula> <tex-math notation="LaTeX">\lambda </tex-math></inline-formula>), and the number of iterations (<inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula>). Based on the findings, we suggest the optimal values of <inline-formula> <tex-math notation="LaTeX">w </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\lambda </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula>, which assist in improving the quality of the reconstructed field. On the other hand, obtaining high-quality indoor field measurements is deeply related to the coordinates of the transceiver, highlighting the need for an optimal position choice. In this context, we propose an improved version of an existing numerical method for predicting the optimal coordinates and reconstructing a highly accurate temperature within an echoic box (<inline-formula> <tex-math notation="LaTeX">1.33\times 1.0\times1.27 </tex-math></inline-formula> m). We show that the predicted optimal position successfully recovers a highly accurate field, satisfying the negative temperature coefficient (NTC)-thermistors measurement.
