High Performance Computing and Machine Learning for the Energy Challenge

Abstract:

Climate change is one of the most important challenges that we face today. Technological barriers hinder a sustainable and carbon-free generation of energy, for which fluid mechanics play a central role. I highlight recent research of my group, where  we combine machine learning methods and high-fidelity numerical simulations to develop reduced-order models that predict future flow states with high accuracy. Importantly, I will present a large range of scientific questions including canonical and industrial problems at scale.