2 citations · 5 across the 3 of their papers we have counts for
3 papers
JAX-based differentiable fluid dynamics on GPU and end-to-end optimization
Wenkang Wang, Xuanwei Zhang, Deniz Bezgin +3
This project aims to advance differentiable fluid dynamics for hypersonic coupled flow over porous media, demonstrating the potential of automatic differentiation (AD)-based optimi…
JAX-Fluids 2.0: Towards HPC for Differentiable CFD of Compressible Two-phase Flows
Deniz A. Bezgin, Aaron B. Buhendwa, Nikolaus A. Adams
In our effort to facilitate machine learning-assisted computational fluid dynamics (CFD), we introduce the second iteration of JAX-Fluids. JAX-Fluids is a Python-based fully-differ…
A fully-differentiable compressible high-order computational fluid dynamics solver
Deniz A. Bezgin, Aaron B. Buhendwa, Nikolaus A. Adams
Fluid flows are omnipresent in nature and engineering disciplines. The reliable computation of fluids has been a long-lasting challenge due to nonlinear interactions over multiple…