Physics-Informed AI and Digital Twins for Environmental Control

Buildings, underground environments, data centres and controlled facilities depend on ventilation and HVAC systems to maintain safe air quality, temperature and humidity. Conventional fixed-setting control can respond slowly to changing occupancy, weather, heat load, dust or gas release. Physics-informed AI can combine CFD, experiments and sensor data to predict how air, heat, moisture and contaminants move through real geometries, enabling proactive and energy-efficient control

Project Team and Collaborators

Dr. Mehdi Khatamifar, Pedram Alamdari and Ashutosh Sharma