As part of the AI for Net Zero webinar series Dr Georgios Rigas presented a summary of his research theme focusing on real-time digital optimization and decision-making for fluid-based energy and transport systems.
Dr Rigas is an expert in the fields of aerodynamics and artificial intelligence (AI). Having studied both topics separately he found that AI was exactly the tool he needed to answer problems he found in his aerodynamic studies. This research project truly bridges the gap between fluid-based energy and transport systems and real-time digital optimization (RL), also known as decision-making tools.
The webinar goes into the details of how algorithm learnings can increase the aerodynamic efficiencies of heavy goods vehicles, how it can increase energy production of wind farms, and the role it’s playing in effective hydrogen combustion.
The research is steaming ahead, and Dr Rigas reported that the next most important steps are to reinforce algorithm learnings, especially for windfarms, by setting up pilot test sites to see how the theoretical situations perform in real environments.
Dr Rigas wrapped up his presentation by inviting us to get in touch with advice about standardising guidelines for scientific machine learning, a piece of work that he is currently putting together. He also tells us to watch out for a specialised training workshop on machine learning and RL for physical systems, that should be happening later this year.
The audience was rather active, asking questions about real-life fuel savings, developments in physics, and improvements in parameterization.
Dr Rigas’ webinar can be rewatched the AI for NetZero YouTube channel along with the entire series.