The American Institute of Aeronautics and Astronautics (AIAA) has shared a presentation that explains how incorporating physics into AI models for simulation will help rewrite how to design aerospace systems.

The presentation is by Juan Alonso, cofounder of Luminary Cloud and chair of the Department of Aeronautics and Astronautics at Stanford University, who shared his insights during the recent AIAA Aerospace Perspective Series webinar.

“Physics-based AI provides valuable information: it embeds symmetries, invariants, and conservation laws directly into machine-learning architectures,” AIAA reports. “That means less training data is required to reach a given accuracy, more accurate predictions are possible, and the resulting model generalizes far better on designs it hasn’t seen before.” Such models predict full surface and volume fields — pressure, shear stress, and velocity — so that detailed flow physics can be constructed in milliseconds instead of hours or days, Alonso emphasized.

Read more and access the full presentation on AIAA’s website.