JAX-FLUIDS: A fully-differentiable high-order computational fluid dynamics solver for compressible two-phase flows. (arXiv:2203.13760v1 [physics.flu-dyn])

Physical systems are governed by partial differential equations (PDEs). The
Navier-Stokes equations describe fluid flows and are representative of
nonlinear physical systems with complex spatio-temporal interactions. Fluid
flows are omnipresent in nature and engineering applications, and their
accurate simulation is essential for providing insights into these processes.
While PDEs are typically solved with numerical methods, the recent success of
machine learning (ML) has shown that ML methods can provide novel avenues of
finding solutions to PDEs. ML is becoming more …

arxiv computational fluid dynamics physics