Blueprint for Interactive Virtual Wind Tunnels Enables Unprecedented Computer-Aided Engineering Exploration for Altair, Ansys, Cadence, Siemens and More
eejournal.com, Nov. 18, 2024 –
NVIDIA today announced an NVIDIA Omniverse™ Blueprint that enables industry software developers to help their computer-aided engineering (CAE) customers in aerospace, automotive, manufacturing, energy and other industries create digital twins with real-time interactivity.
Software developers such as Altair, Ansys, Cadence and Siemens can use the NVIDIA Omniverse Blueprint for real-time computer-aided engineering digital twins to help their customers drive down development costs and energy usage while getting to market faster. The blueprint is a reference workflow that includes NVIDIA acceleration libraries, physics-AI frameworks and interactive physically based rendering to achieve 1,200x faster simulations and real-time visualization.
"We built Omniverse so that everything can have a digital twin," said Jensen Huang, founder and CEO of NVIDIA. "Omniverse Blueprints are reference pipelines that connect NVIDIA Omniverse with AI technologies, enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries."
One of the first applications of the blueprint is computational fluid dynamics (CFD) simulations, a critical step to virtually explore, test and refine the designs of cars, airplanes, ships and many other products. Traditional engineering workflows – from physics simulation to visualization and design optimization – can take weeks or even months to complete.
In an industry first, NVIDIA and Luminary Cloud are demonstrating at SC24 a virtual wind tunnel that allows users to simulate and visualize fluid dynamics at real-time, interactive speeds, even when changing the vehicle model inside the tunnel.
Unifying Three Pillars of NVIDIA Technology for Developers
Building a real-time physics digital twin requires two fundamental capabilities: real-time physics solver performance and real-time visualization of large-scale datasets.