Phi-ML meets Engineering - Physics-informed discovery of non-smooth…

This bi-monthly seminar series explores real-world applications of physics-informed machine learning (Φ-ML) methods to the engineering practice. They cover a wide range of topics, offering a cross-sectional view of the state of the art on Φ-ML research, worldwide.  Speaker: Davide MurariMany dynamical systems exhibit non-smooth dynamics, including friction, contact, impacts, saturation, and switching. Standard machine-learning approaches for system identification often assume smooth vector field