Search Results (9)

Climate change poses significant challenges to energy efficiency and occupant comfort in residential buildings. This study introduces a simulation-based multi-objective optimization approach for architectural design, aimed at addressing these challenges and enhancing environmental sustainability. Utilizing EnergyPlus for energy simulations and jEPlus to identify objective functions and design parameters, the research employed the NSGA-II algorithm through jEPlus + EA for multi-objective optimization. A Morris sensitivity analysis assessed the impact of 25 design variables—including heating and cooling setpoints, air infiltration rates, insulation types, window selections, airflow rates, and HVAC systems—on key objective functions. Applied to a residential building in Sari, Iran, the study analyzed various climate change scenarios to minimize five main objectives: primary energy consumption, greenhouse gas emissions, indoor air quality, predicted percentage of dissatisfied, and visual discomfort hours. The weighted sum method was used to select optimal solutions from the Pareto front. Results demonstrated that the recommended energy retrofit strategies could reduce primary energy consumption by up to 60%, greenhouse gas emissions by 60%, predicted thermal dissatisfaction by 65%, and visual discomfort hours by 83%, while also achieving indoor air quality levels that meet ASHRAE recommended standards. However, the implementation of these energy-efficient solutions may require careful consideration of trade-offs in design decisions when addressing climate change challenges. Full article

Thermal comfort is increasingly recognized as vital in healthcare facilities, where patients spend 80–90% of their time indoors. Sensing, controlling, and predicting indoor air quality should be monitored for thermal comfort. This study examines the effects of ventilation design on thermal comfort in hospital rooms, proposing four distinct ventilation configurations, each with three airflow rates of 9, 12, and 15 Air Changes per Hour (ACH). The study conducted various ventilation simulation scenarios for a hospital room. The objective is to determine the effect of airflow and the diffuser location distribution on thermal comfort. The Reynolds-Averaged Navier–Stokes (RANS) equations, along with the k–ε turbulence model, were used as the underlying mathematical representation for the airflow. The boundary conditions for the simulations were derived from the ventilation standards set by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) and insights from previous studies. Thermal comfort and temperature distribution were assessed using indices like Predicted Percentage Dissatisfaction (PPD), Predicted Mean Vote (PMV), and Air Diffusion Performance Index (ADPI). Although most of the twelve scenarios failed to attain thermal comfort, two of those instances were optimal in this simulation. Those instances involved the return diffuser behind the patient and airflow of 9 ACH, the minimum recommended by previous studies. It should be noted that the ADPI remained unmet in these cases, revealing complexities in achieving ideal thermal conditions in healthcare environments. This study extends the insights from our prior research, advancing our understanding of ventilation impacts on thermal comfort in healthcare facilities. It underscores the need for comprehensive approaches to environmental control, setting the stage for future research to refine these findings further. Full article

Effective indoor thermal controls can have quantifiable advantages of improving energy efficiency and indoor environmental quality, which can also lead to additional benefits such as better workability, productivity, and economy in buildings. However, in the case of factory buildings whose main usage is to produce and process goods, securing thermal comfort for their workers has been regarded as a secondary problem. This study aims to explore the method for cooling and heating air supply controls to improve the thermal comfort of factory buildings by use of a data-driven adaptive model. The genetic algorithm using the idea of occupancy rate helps the model to effectively analyze the indoor environment to determine the optimized conditions for energy use and thermal comfort. As a result, the proposed model successfully shows better performance, which confirms that there is a 2.81% saving in energy consumption and a 16–32% reduction in indoor thermal dissatisfaction. In particular, the significance of this study is that energy use and thermal dissatisfaction can be reduced simultaneously despite precise air-supply controls that are performed in response to the conditions of the building, weather, and occupancy rate. Full article

Thermal discomfort body language has been shown to be a psychological representation of personnel’s particular thermal comfort. Individual thermal comfort differences are ignored in public building settings with random personnel flow. To solve this issue, we suggested a Bayesian group thermal dissatisfaction rate prediction model based on thermal discomfort body language expression and subsequently implemented intelligent indoor temperature and humidity control. The PMV-PPD model was utilized to represent the group’s overall thermal comfort and to create a prior distribution of thermal dissatisfaction rate. To acquire the dynamic distribution of temperature discomfort body language, data on thermal discomfort body language expression were collected in a real-world office setting experiment. Based on Bayesian theory, we used personalized thermal discomfort body language expressions to modify the group’s universal thermal comfort and realized the assessment of the thermal dissatisfaction rate by combining commonality and personalization. Finally, a deep reinforcement learning system was employed to achieve intelligent indoor temperature and humidity control. The results show that when commonality and personalized thermal comfort differences are combined, real-time prediction of thermal dissatisfaction rate has high prediction accuracy and good model performance, and the prediction model provides a reference basis for reasonable indoor temperature and humidity settings. Full article

Forced ventilation is applied in clean rooms, specifically operating rooms, to ensure the health of both the patient and the medical staff. Ventilation reduces the risk of patient contamination, and its parameters are legally prescribed. In addition to preventing contamination, the ventilation system also ensures the creation of a comfortable environment for personnel who spend a large amount of working time in the operating room. This research focuses on the appropriate design of the air flow rate from the distribution element to the operating room. The PMV and PPD indexes were used to evaluate thermal comfort for human beings. The measurements of parameters determining thermal comfort took place in a laboratory with an accurate model of the operating room, including equipment and HVAC system, during the summer months, in cooling mode. Discharge speeds in the range of 0.15–0.175 m/s were evaluated as the most comfortable, with the PPD index ranging up to 22%. There was a significant increase in user dissatisfaction up to the limit of 70% at higher discharge speeds. Full article

The current +−0.5 PMV (Predicted Mean Vote) targets adopted by NABERS (National Australian Built Environment Rating System) is the practical range deemed acceptable for 90% acceptability for commercial buildings in Australia, however thermal comfort satisfaction scores measured in office buildings still show high percentages of dissatisfied occupants. This paper aims to demonstrate the potential of curbing energy consumption from commercial buildings in Australia by increasing summer temperature set-points. A 10-year NABERS dataset, along with objective and subjective thermal comfort and air quality data from NABERS-certified offices are investigated in this study. Furthermore, different simulation scenarios are tested to investigate the discomfort hours and energy consumption for various summer temperature setpoints. Result analysis shows that occupants’ satisfaction in NABERS-certified buildings was not within the 90% satisfaction, with being too cold/hot as the main source of dissatisfaction. Objective measurements also showed temperature was out of recommended range for several datapoints. Simulation results indicate that, within the average range of 21–24.9 °C, there is not a significant difference in discomfort hours that could drive the selection of one temperature set-point over the other. Challenging the current practices, results suggest that a cooling set point temperature on the upper limit of the range indicated by the Australian standard AS 1837–1976 may minimize the energy consumption without significantly increasing discomfort, or even increasing the perceived satisfaction with the indoor environment. Full article

Patients are different regarding their health conditions, illnesses and ailments, and mobility. These and other factors could affect their specific feelings about the thermal environment. Current methods of predicting thermal sensations were developed based on research on a group of healthy people. Therefore, the use of these methods with patients should be verified. This paper aimed to verify selected thermal comfort models in terms of their reliability to predict the average assessment of thermal conditions in the patient rooms and the percentage of dissatisfied patients. Thermal condition analyses were based on microclimate parameter measurements and extensive questionnaires among patients, done in parallel in the hospital’s patient rooms. The research was carried out in 23 hospitals located in the following provinces in Poland: (Warmińsko-Mazurskie, Kujawsko-Pomorskie, Mazowieckie, Wielkopolskie, Łódzkie, Świętokrzyskie, Lubelskie and Dolnośląskie). Overall, 890 patients from 14 different specialities participated in the research. Actual thermal sensations of patients differed from predictions obtained from selected thermal comfort models. A comparison of the actual thermal sensations with the PMV model indicates the shift of the comfort curve towards cooler rather than neutral conditions. A comparison of the same to the adaptive model predictions indicates that patients had a higher dissatisfaction rate and preferred cooler thermal conditions than predicted. Research findings show that normative models are not fully reliable in predicting patients’ thermal sensations. Full article

The quality of the indoor environment has become a vital component for buildings due to the time spent indoors. To this extent, the performance of the indoor environment is considered as part of the greenery criteria by green rating schemes such as the Green Building Index in Malaysia. This study aims to investigate and assess the quality of the indoor environment of Platinum-certified office buildings in a tropical climate. This research applied a case study approach over two Platinum-certified office buildings. Post-occupancy evaluation is employed integrating full-scale measurement with an occupants’ survey. The measurement was carried out from May to August, and 112 questionnaires were retrieved to evaluate occupants’ satisfaction with aspects of the indoor environment. Thermal comfort, indoor air quality, acoustic, lighting, furniture, and cleanliness are considered as the main study variables. The findings of full-scale measurement indicated high relative humidity, and low air velocity and illuminance. While occupants reported overall indoor environment quality (IEQ) comfort, a significant correlation of variables was observed. The main sources of dissatisfaction were identified as overcooling around 24 °C, high relative humidity (RH), around 70% RH, glare, and background noise around 51.9 dB. Statistically, a significant difference between occupants’ responses to IEQ of two cases was identified, although both buildings are labelled with a Platinum certificate. Full article

The influence of different control strategies on the user’s satisfaction in cell offices was studied in a full-scale facility in Trondheim, Norway. Eleven participants used two test cells as a workspace and answered a computer-based questionnaire for reporting their perceived thermal and visual comfort, and any desired changes in the cell environment. Concurrently, the indoor operative temperature and illuminance were registered. Two different strategies for controlling the indoor environment were used in the case study. In Cell A, the ceiling-mounted lights, the window blind, and a water-based radiator were controlled by the main acquisition and control system, whereas in Cell B, these were manually controlled by the users. In both cells, the window opening was user-controlled, except for a small motorised window, which was automated in Cell A, and user-controlled in Cell B. The results show that the occupants of Cell B first tended to open the window, then to adjust their clothing level, and finally to lower the blind when the operative temperature increased. The recorded Thermal Sensation Votes (TSVs) and Illuminance Ratings (IRs) show that the limitation of control opportunities in Cell A increases the level of thermal and visual dissatisfaction. Full article