Research That’s Shaping the Industry
Published breakthroughs pushing the state of the art
AB-UPT for Automotive and Aerospace Applications
In this technical report, we add two new datasets to the body of empirically evaluated use-cases of AB-UPT, combining high-quality data generation with state-of-the-art neural surrogates.
PAINT: Parallel-in-time Neural Twins for Dynamical System Reconstruction
Neural surrogates have shown great potential in simulating dynamical systems, while offering real-time capabilities. We envision Neural Twins as a progression of neural surrogates, aiming to create digital replicas of real systems.
GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations
Nuclear fusion plays a pivotal role in the quest for reliable and sustainable energy production. A major roadblock to viable fusion power is understanding plasma turbulence, which significantly impairs plasma confinement, and is vital for next-generation reactor design.
Einstein Fields: A Neural Perspective To Computational General Relativity
We introduce Einstein Fields, a neural representation that is designed to compress computationally intensive four-dimensional numerical relativity simulations into compact implicit neural network weights.
AB-UPT
Anchored-Branched Universal Physics Transformer (AB-UPT) for aerodynamics CFD. Handles raw geometry without remeshing at 9M surface and 140M volume cells on a single GPU.
NeuralDEM
First end-to-end deep learning surrogate for large-scale multi-physics processes. Enables real-time simulation of industrial processes like fluidised bed reactors.
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