Luminary Cloud and nTop have collaborated with Nvidia to integrate with Nvidia PhysicsNeMo in a move to reduce physics-based AI design optimisation from weeks to hours.
The move connects nTop’s parametric geometry generation, Luminary’s GPU-native simulation and simulation management platform and NVIDIA’s PhysicsNeMo via APIs, allowing engineers to create and analyse hundreds of design variations in a single day—a process that previously took weeks to months of manual effort across disconnected systems.
The companies are calling this the first automated pipeline for physics AI-driven engineering design optimisation.
Users can now define design parameters, automatically generate and simulate hundreds of variations, and leverage AI to predict optimal configurations, all in an integrated workflow without manual file transfers or specialised expertise.
The system shows potential for performance improvements across aerospace, automotive, and consumer product applications. The first joint demonstration between nTop and Luminary in particular shows the optimisation of lift and drag characteristics of flying wing configurations.
“The use of cloud-native platforms and modern APIs from nTop and Luminary enable the generation of ensembles of simulations and vast amounts of data that are easy to curate, store, and consume for physics AI model training in less than a day,” said Luminary Cloud CTO Juan J. Alonso.
“Without the ability to seamlessly manage the data we rely on, even the most sophisticated companies today are unable to deploy Physics AI models as quickly as required.”
The collaboration marks Luminary’s first native, API-based integration with a geometry engine to ingest and simulate many design iterations and represents a fundamental shift in the development of AI models for design optimisation, democratising both access to Physics AI for engineering teams of all sizes and the way simulation-based design is conducted.
nTop CEO Brad Rothenberg said that physics simulation has long been a critical bottleneck in real-time design optimisation. “The integration between Luminary and nTop, powered by Nvidia hardware, brings us significantly closer to solving this challenge. Through Luminary’s API, we can seamlessly push nTop geometries to Luminary for physics calculations and automatically return results to nTop in a robust, continuous loop,” said Rothenberg.
“This makes it now possible, and actually easy, to train up physics-based AI models used to accelerate performance predictions – we’re now closer than ever to real-time design optimization.”
The set-up has been designed to be as easy as possible, using the robust and flexible APIs from nTop, Luminary, and Nvidia to allow for bi-directional connections between geometry iteration, engineering simulation, and Physics AI model training within a single workflow.
