Principal Investigator Leon Glicksman
In the United States and most developed countries buildings consume roughly 40% of the nation’s primary energy, a number that is steadily growing. For all US buildings, space cooling and ventilation consume 16% of building energy use. However, in cooling-dominated climates, this percentage is significantly higher. One strategy for decreasing this energy consumption is to use natural ventilation (NV), a passive cooling and ventilating technique that utilizes natural forces like wind or buoyancy differences to bring outside air into the building.
A fundamental limitation of NV is the required climate. No building owner will naturally ventilate his building if outside air temperature or humidity levels are unacceptable for indoor comfort conditions. Thus, a rare few climates allow for a purely naturally ventilated building. This limitation in NV has lead to hybrid ventilation (HV) -- a mix of NV and more traditional mechanical heating, ventilation, and air conditioning (HVAC) methods. While HV systems predictably require a larger capital investment than either a NV or mechanical HVAC system, the cost savings of an HV system over its lifetime could conceivably more than pay back the initial investment.
A major gap currently exists in our ability to predict the performance of an HV system -- thus its energy and cost savings – when buoyancy-driven flow is present. Airflow network tools exist that predict airflow driven both by wind and buoyancy effects, however the assumptions used to model buoyancy-driven flow are often unrealistic. Such assumptions include a uniform temperature distribution in the ventilation duct, when actually the distribution is highly stratified especially near the duct entrance, or uni-directional flow in the duct, when bi-directional flow is likely due to the presence of large eddies in the flow.
The aim of this research is to deepen the understanding of NV to allow for better modeling in airflow network tools used in building energy modeling software to more confidently predict the energy and cost savings of a hybrid ventilation system.