Super-resolution of turbulence with dynamics in the loss
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Publication:6669442
DOI10.1017/JFM.2024.1202MaRDI QIDQ6669442
Publication date: 22 January 2025
Published in: Journal of Fluid Mechanics (Search for Journal in Brave)
Cites Work
- Discrete adjoint of fractional-step incompressible Navier-Stokes solver in curvilinear coordinates and application to data assimilation
- Machine Learning for Fluid Mechanics
- A data-assimilation method for Reynolds-averaged Navier–Stokes-driven mean flow reconstruction
- State estimation in turbulent channel flow from limited observations
- Learned turbulence modelling with differentiable fluid solvers: physics-based loss functions and optimisation horizons
- Machine-learning-based spatio-temporal super resolution reconstruction of turbulent flows
- Invariant recurrent solutions embedded in a turbulent two-dimensional Kolmogorov flow
- Synchronization of turbulence in channel flow
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