(video) Reduced Order Modeling

In this episode, we sit down with Lucas Boucinha to explore the role of Reduced Order Modeling (ROM) in the context of digital twins. Lucas explained that behind every physical principle lies a set of complex mathematical equations, too intricate to solve by hand, except in the simplest cases of behavior and geometry. Finally, he shared insights on how ROMs address this challenge by reducing the computational complexity of high-fidelity models while preserving accuracy.

00:00 Introduction
01:11 Reduced Order Modeling definitions
02:30 High-fidelity models use of physics and mathematical equations
04:30 Model reduction techniques to solve high fidelity models
05:18 Why ROMs technology works so well
06:31 Intrusive and non-intrusive model reduction techniques 
08:26 The power behind non-intrusive ROMs
09:06 Level of maturity of Reduced Order Modeling technology
10:22 Business opportunities enabled by ROMs
12:34 Delivering the traditional values of simulation software faster than ever
15:10 ROMs in the Gartner hype cycle
16:11 Digital Twin challenges that ROMs are taking up