@article{34463,
  keywords = {Natural ventilation, Energy Plus, California office},
  author = {Annamaria Belleri and Roberto Lollini and Spencer M Dutton},
  title = {Natural ventilation design: An analysis of predicted and measured performance},
  abstract = {<p>We present a study of natural ventilation design during the early (conceptual) stage of a building's design, based on a field study in a naturally ventilated office in California where we collected data on occupants' window use, local weather conditions, indoor environmental conditions, and air change rates based on tracer-gas decay. We performed uncertainty and sensitivity analyses to determine which design parameters have most impact on the uncertainty associated with ventilation performance predictions. Using the results of the field study along with wind-tunnel measurements and other detailed analysis, we incrementally improved our early-design-stage model. The improved model's natural ventilation performance predictions were significantly more accurate than those of the first draft early-stage-design model that employed model assumptions typical during initial design. This process highlighted significant limitations in the EnergyPlus software's models of occupant-driven window control. We conclude with recommendations on key design parameters including window control, wind pressure coefficients and weather data resolution to help improve early-design-stage predictions of natural ventilation performance using EnergyPlus.</p>},
  year = {2014},
  journal = {Building and Environment},
  month = {11/2014},
  url = {https://www.sciencedirect.com/science/article/abs/pii/S0360132314001954},
  doi = {https://doi.org/10.1016/j.buildenv.2014.06.009},
  language = {eng},
}