- 1. Building Airflow and Thermal Management
- CityFFD - City Fast Fluid Dynamics
- CityBEM - City Building Energy Model and Whole-building energy analysis
- Built Environment Scaling and Similarity with 3D Printing Applications
- Natural Ventilation Potential Map
- Forecasting Built Environment by Numerical Weather Prediction Models
- Smart Air Curtains
- Sub-Scale Model Experiment and Dimensionless Design
- Modular Growing Bed Ventilation System Design With SLA(Stereolithography Apparatus) 3D Printing Technology
- 2. Building Fire Protection and Smoke Management
- People
Forecasting Simulations in Built Environment by Ensemble Kalman Filter (EnKF) (Data Assimilation)
Student: Danlin Hou, Ph.D. Candidate and Cheng-Chun Lin, Ph.D.
Sponsor: Natural Science and Engineering Research Council of Canada (NSERC) Discovery Grants
C. Lin and L. Wang. 2013. Forecasting simulations of indoor environment using data assimilation via an Ensemble Kalman Filter. Building and Environment. Volume 64, pp. 169-176.
C. Lin and L. Wang. 2014. Applications of Data Assimilation to Forecasting Indoor Environment. 2014 IEEE International Conference on Automation Science and Engineering (CASE). Taipei, Taiwan, August 18-22, 2014.
D. Hou, C. Lin, A. Katal and L. Wang. 2019. Forecasting Cooling Load and Energy Saving Potential by Ensemble Kalman Filter for an Institutional High-Rise Building with Hybrid Ventilation. Submitted to ISHVAC 2019. Harbin, China, 8 pages.
Research Highlights:
- Use CFD software, FLUENT, to generate detailed data as numerical experimental data
- Use CONTAM in the data assimilation toolbox: OpenDA
- Forecasts are made in the time frame of days in terms of airflow infiltrations and indoor contaminant levels
- Different data assimilation methods will be tested within OpenDA
