Unfolding Time: Generative Modeling for Turbulent Flows in 4D

arXiv:2406.11390v1 Announce Type: cross
Abstract: A recent study in turbulent flow simulation demonstrated the potential of generative diffusion models for fast 3D surrogate modeling. This approach eliminates the need for specifying initial states or performing lengthy simulations, significantly accelerating the process. While adept at sampling individual frames from the learned manifold of turbulent flow states, the previous model lacks the capability to generate sequences, hindering analysis of dynamic phenomena. This work addresses this limitation by introducing a 4D generative diffusion …

abstract adept arxiv cs.lg diffusion diffusion models flow generative generative modeling manifold modeling physics.flu-dyn potential process sampling simulation simulations study type while