Data Learning of Fluid Dynamics for Physically Informed Digital Twins

Abstract

We present a novel realtime digital twin based on artificial intelligence to emulate physically sound fluid dynamics, and classify and recognise liquids, with information from video streamings. Results are presented with augmented reality techniques not only for friendly user interaction, but also to provide augmented information in manipulation tasks.