Objective: develop new ADPI design guidelines for both cooling and heating conditions. The current guideline of diffuser/ outlet selection for all-air HVAC (heating, ventilating and air conditioning) systems was developed back in 1970s only for cooling operation. The guideline correlates indoor air distribution with diffuser/ outlet performance to distribute supply air, by using ADPI (Air Diffusion/ Distribution Performance Index) method. As of when the method was developed, however, new types of diffusers/ outlets have been emerging and the use of all-air HVAC system for heating purpose is prevalent.
Epidemic diseases are believed to be related to respiratory airborne transmission, and human coughing promotes the spread of human released particles. By discharging a large quantity of airborne particles with a high discharge velocity, coughing releases particles with a higher concentration than breathing or talking. This project investigated the transport of coughed particles between two people standing in a talking distance. We used three particle sizes (0.77, 2.5 and 7 µm) in the experiments. The second part of this project examines the protection effectiveness of a new ventilation system--protected occupied zone (POV) ventilation.
Draft is unwanted local cooling caused by air movement. Draft at ankles is often an issue or concern for displacement ventilation (DV) and underfloor air distribution (UFAD) systems that provide conditioned air at the floor level. Moreover, downward cold air along external envelope in the heating season could cause draft and cold feet to occupants sitting around. The project evaluated draft risk at ankles with 110 college students in a controlled climate chamber. We assessed the effect on ankle draft of various combinations of air speed, temperature, turbulence intensity (at ankles), sex, and clothing insulation.
Indoor climate monitoring is a critical task in building operation, maintenance, and diagnosis. Current approach based on static sensor network is not scalable for typical tasks like indoor air quality (IAQ) assessment relying on costly sensing instruments. The study proposes to leverage autonomous mobility to reduce sensing infrastructure cost and enable real-time high-granularity monitoring that can be otherwise inhibitively laborious. Unique to the autonomous mobile sensing methodology, the collected samples are highly sparse in both spatial and temporal domains. The study develops spatio-temporal (ST) interpolation methods based on ST binning, global trend extraction, and local variation estimation, which efficiently use the data to construct accurate depiction of the indoor environment evolution. The method is evaluated in a standard ventilation experiment against a dense sensor network, where the estimation is shown to be highly correlated with the ground truth, and reveals the true ventilation conditions.