An innovative method of simulating close-to-nature-dynamic air movement through dynamically controlling electric fans. (January 2022) - Yu, Wei
Abstract: The electric fan is widely employed in buildings by occupants to relieve dependences on air conditioning and extend the acceptable temperature limits in summer. While dynamic airflow is known to effectively improve the thermal comfort of human, a convenient method of creating a comfortable and close-to-nature airflow is currently unavailable. This study simulated a dynamic air movement through referring to the physical parameters of natural airflow, based on an commonly used electric fan and analysed the flow characteristics and comfort perceptions through experiments. The results of flow field characteristic showed that natural airflow had a skewness of higher than 0 (i.e., features a right-skewed distribution) and a β value distributing in a range of 1.2–1.6. Two typical airflow patterns of sine and random were then simulated through regulating the motor speed cycles of fan. The acceptable air velocities and change periods for dynamic airflow were determined through a human exposure experiment, responding to different temperatures (28 °C, 30 °C, 32 °C) and relative humidities (50%, 70%, 90%). An evaluating metrics including comfort indices and flow parameters was proposed to identify the comfort airflow. According to the principle that β>1.1 is close to natural wind, the best airflow movement form under different dynamic airflows is obtained. The outcomes based on cluster analysis indicated that the field parameters of sinusoidal airflow were much close to that of natural airflow. The proposed method of simulating close-to-nature airflow provides a technical guidance and data support for creating dynamic air movement and improving thermal comfort for people exposing to air movement. The work is expected to promote the fan utilization efficiently in warm environments and benefit to energy savings in buildings. Highlights: Tested the characteristic parameters of natural wind flow field. Based on human thermal comfort, the comfortable wind speed range is determined. Two types of airflow, sine and random, were simulated and field characteristics was analysed. Cluster analysis was adopted to identify parameters and airflow types close to natural wind.