To enhance the productivity of livestock facilities, maintaining a comfortable indoor environment is necessary, as livestock are sensitive to indoor temperature and livestock excrement generates ...numerous pollutants. In most livestock facilities, the ventilation system represents a large proportion of the indoor environment. Therefore, an energy-efficient ventilation control system, which considers the performance of the ventilation fan and outdoor air conditions, is increasingly in demand. In this study, we developed a building energy simulation model for ventilation control system in a livestock facility. In addition, a polynomial equation for the part-load-factor according to the part-load-ratio was developed to calibrate the fan energy consumption. The indoor temperature prediction performance was calibrated by optimising the infiltration rate and equipment load variables. The proposed building energy simulation model is expected to contribute to energy reduction and productivity improvement of the livestock by determining the optimum fan operation schedule through simulation analysis of various factors.
•A whole-building energy model for livestock facility was developed.•PLF model was applied in the energy model and showed high prediction performance.•High prediction performance for air temperature was secured by input optimization.•Daily model update better represents trend of indoor air temperature than weekly update.
•Experimental test of the PCM room and ordinary room was carried out in summer and winter.•The thermal behavior simulation platform of the PCM room was built.•Several indexes were used to evaluate ...the thermal behavior of the two rooms.•Composite PCM room performed a better thermal behavior in both summer and winter.
The thermal behavior of the PCM in one season has been studied by many researchers. However, more and more attention was paid to the thermal behavior of new types of PCM room in several seasons. In this paper, the concept of composite PCM room was proposed, that is to place two PCMs of different melting temperature in one room. A composite PCM room and an ordinary room (room without PCM) were built. The indoor air temperature, thermal load leveling, standard deviation of the inner surface temperatures were tested and analyzed for both summer and winter. The thermal behavior simulation platform of the PCM wall was established by sensible heat capacity method together with TRNSYS. On this basis, the influence of melting temperature and thickness of the PCM layer to the heat absorbing/releasing performance were simulated. Results showed that (1) In summer, as compared to ordinary room, the PCM room can bring a temperature drop of about 4.28–7.7°C during the day and reduce the indoor air temperature fluctuation by up to 28.8–67.8% during sunny days. The combined PCM room can significantly increase the heat absorbed from the room and decrease the heat released to the room. (2) In winter, the temperature rise was 6.93–9.48°C for PCM room at winter night. The indoor air temperature fluctuation decreased 17.7–25.4% during sunny days. The combined PCM room can significantly increase the heat released to the room and decrease the heat absorbed from the room. In conclusion, the composite PCM room performed a better thermal behavior in both summer and winter.
Buildings are expected to be energy efficient but also to provide a comfortable environment to their occupants as well as to be durable. Indoor relative humidity influences the energy consumption, ...structure and the occupants’ comfort and health. Therefore, it is necessary to control and predict indoor environmental conditions. This work aims to simulate indoor temperatures and relative humidity in a multi-zone building model under realistic conditions, such as occupancy and moisture gains, operation of windows and doors and mechanical ventilation. The combined multi-zone air flow model is developed with TRNSYS and TRNFLOW and it is applied to a phase of the Twin Houses extended experiment of the international energy agency, energy in buildings and communities (IEA EBC) Annex 71. The main novelty of this work is to determine the masses of surface and deep moisture buffer storage by performing a multi-objective calibration of indoor temperatures and relative humidity. Results prove that building energy simulations need to model the moisture buffering of internal materials to accurately predict indoor humidity. The error in simulating relative humidity is reduced by 69% in the house with moisture gains after calibration of the masses of buffering materials. Moreover, the calibrated multi-zone building model shows a great agreement between simulated and measured data with an average root mean square error (RMSE) among thermal zones of 0.51 °C and 0.48 °C in indoor temperatures and 3.58% and 2.21% in relative humidity for the two houses in the validation period.
•Indoor environment simulation of the Twin Houses considering occupancy effect.•The use of a buffer storage humidity model is investigated.•Multi-objective calibration determines the masses of moisture buffering materials.•The error in relative humidity is reduced by 69% in the house with moisture gains.•Validation of air temperature and relative humidity is performed for each thermal zone.
Control strategies for variable air volume (VAV) air-conditioning systems play a pivotal role in ensuring indoor environmental quality and energy efficiency. However, conventional approaches, such as ...static pressure reset (SPR) control, focus on managing indoor air temperature without considering the room pressure, which can lead to unbalanced room pressure and undesirable air leakage. Moreover, with the application of prevalent building pressure control strategies, such as airflow tracking control, to multizone VAV systems, neutralization of the room pressure is difficult across multiple zones in VAV systems. Therefore, this study introduces a model-based optimal control strategy for multizone VAV air-conditioning systems. The proposed strategy uses a multiobjective optimization framework to regulate fan frequencies and damper openings on both the supply and return sides. This holistic approach facilitates the simultaneous control of the indoor air temperature and room pressure while minimizing fan energy consumption. To assess the effectiveness of the proposed strategy, four control strategies were tested using a Python-based simulation testbed. The results demonstrate that the proposed strategy effectively maintains the indoor air temperature, neutralizes room pressure, and reduces fan energy consumption, thereby contributing to the overall efficiency of the VAV system. Moreover, the results highlight the limitations associated with combining airflow tracking control with SPR control for room pressure regulation in multizone VAV systems. This highlights the importance of adopting a model-based approach to address the complexities of concurrent room pressure and indoor air temperature control.
•A multi-objective optimal control strategy is proposed for multi- zone VAV systems.•Optimal combinations of fan frequencies and damper openings can be determined.•This strategy can control indoor air temperature and room pressure simultaneously.•It can reduce fan energy use by maintaining dampers within the optimal opening range.
Several relationships between air temperature and work performance have been published. We reanalysed the one developed in 2006 by Seppänen et al.; which is probably the best known. We found that ...even when significant, its prediction accuracy is very low (R2 = 0.05, MAE = 1.9%, RMSE = 3.1%). We consequently reviewed the literature and found 35 studies on the effects of temperature on office work performance. We used Seppänen et al.’s approach to normalise the data reported in these studies and explored the feasibility to develop a new relationship using regression models, models based on the Maximal Adaptability framework, and machine learning. We could not find a relationship between temperature and office work performance neither for the range of temperatures measured in most of the office buildings (20 °C–30 °C) or a wider range (18 °C–34 °C). Plausible reasons are discussed including the variety of methods used to assess performance, the multiple uncontrolled confounders, and the fact that temperature alone may not fully describe how the thermal environment affects building occupants. We do not recommend the use in practice of any of the models relating temperature to office work performance examined in the present study. The lack of relationships does not necessarily refute that temperature affects the performance of office work. Coordinated research predicated on a shared protocol enabling integrated analysis in the modelling of the relationships between the indoor thermal environment and office work performance is proposed to be carried out before using them in practice. We made the database open-source and developed an application for data exploring.
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•We made an open-source database containing 358 normalised data points from 35 studies.•We could not find a relationship between temperature and work performance.•Effects of task complexity, speed/accuracy, and climate were no significant.
Indoor thermal environment is a critical factor for animal health and production in confined livestock facilities. In order to improve indoor thermal environment control and save energy, a novel ...dynamic thermal exchange model was developed using the energy balance equation (EBE) and 87 days of data collected in three different seasons in a pig building to simulate the heat transfer and energy consumption in the building. To evaluate the performances of the EBE model, a comparison was made using adaptive neuro fuzzy inferring system (ANFIS) for indoor air temperature prediction. Also, the EBE model was evaluated comparing its outputs of indoor temperature with the dataset of six days, under three different ventilation modes (Min-vent, Low-vent, and High-vent) that represent for the cold, warm and hot weather, obtained through a monitoring period in pig buildings during the production. The results showed that, under three different ventilations modes, the maximum errors between the EBE model simulated and measured data were 1.5 °C compared with 2.6 °C of the ANFIS model; and the averaged coefficients of determination R2 were 0.945 and 0.743, respectively, for the EBE and ANFIS models. Compared with the present ventilation operation, there was 358.301 kW h power saved with the EBE model in a pig room during the whole research period of 87 days. Therefore, this research has several practical applications: the model can be used in developing strategies of indoor thermal environmental control, it can also increase the knowledge about energy consumption in the livestock house.
•A dynamic thermal model for indoor air temperature prediction and energy saving was developed.•Data measured for 87 days in three different seasons from a swine room were used.•Model parameters can be determined with multiple non-linear regression method.•The model contributes to heat exchange and animal building environment control strategies.
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%.
Obtaining neural information about salivary secretory immunoglobulin E (S-IgE) is a starting point for investigating the mechanism of thermal environment regulation affecting human respiratory ...mucosal immunity. However, there is a scarcity of human-subjects research. To fill this void, we designed seven temperature conditions (15, 18, 21, 24, 27, 30, and 33 °C), collected electroencephalogram (EEG) and saliva from subjects, obtained thermal sensation and comfort votes, and detected S-IgE concentrations in saliva. Our results showed that the mean thermal sensation vote decreased by 2.31 units in the cold condition but increased by 2.25 units in the hot condition as compared to the thermal neutral condition (24 °C). Similarly, the absolute power of most channels in different frequency bands was the lowest at 24 °C within the thermally acceptable temperature range, including F8, F4, AF4, and T8 in α and β bands; at this temperature, the S-IgE concentration was the highest, increasing by 49.4 and 54.4%, respectively, compared to 21 and 27 °C. Furthermore, higher S-IgE concentration was associated with an increase in absolute power in the AF3 channel from the alpha band and the T8 channel from the theta band but a decrease in absolute power in the F7, T8, FC6, and F8 channels from the beta band (p < 0.05). Our findings suggest that EEG can be used to collect EEG signals associated to S-IgE concentration. Future research will concentrate on the effects of long-term temperature exposure on EEG signal and S-IgE concentration, as well as the link between them.
•Electroencephalogram (EEG) and secretory immunoglobulin E (S-IgE) were obtained.•EEG power and S-IgE level were significantly affected by indoor air temperature.•There were relationships between S-IgE concentration and EEG power.•EEG was a new way obtaining neural signal related to respiratory mucosal immunity.•"Like" and "relaxed" environments may improve respiratory mucosal immunity.
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