--- license: mit task_categories: - image-to-3d tags: - mathematics - partial-differential-equations - computational fluid dynamics - physics - neural operator size_categories: - 1K The dataset for tensor-to-tensor or trajectory-to-trajectory neural operators, generated from Navier-Stokes equations to model the isotropic turbulence [1] such that the spectra satisfy the inverse cascade discovered by A.N. Kolmogorov [2]. [1]: McWilliams, J. C. (1984). The emergence of isolated coherent vortices in turbulent flow. *Journal of Fluid Mechanics*, 146, 21-43. [2]: Kolmogorov, A. N. (1941). The local structure of turbulence in incompressible viscous fluid for very large Reynolds Numbers. *Dokl. Akad. Nauk SSSR*, 30, 301. ## Dataset Details ### Dataset Description The dataset contains several cases of isotropic turbulence modeled by Navier-Stokes equations. The data are generated either by a pseudo-spectral solver with 4th-order Runge-Kutta for the convection term, or a higher order Finite Volume IMEX methods. The different initial conditions have different peak wavenumbers of O(1), and eventually their spectra all converge to the Kolmogorov inverse cascade. - **Curated by:** S. Cao - **Funded by National Science Foundation:** NSF award DMS-2309778 - **License:** MIT license ### Dataset Sources [optional] - **Repository:** [https://github.com/scaomath/torch-cfd](https://github.com/scaomath/torch-cfd) - **Paper:** [More Information Needed] - **Demo:** - [The classical Kolmogorov inverse cascade with a solenoidal forcing and small drag.](https://github.com/scaomath/torch-cfd/blob/main/examples/Kolmogrov2d_rk4_cn_forced_turbulence.ipynb) - [The fast training using the data with a small number of vortices.](https://github.com/scaomath/torch-cfd/blob/main/examples/ex2_SFNO_train_fnodata.ipynb) - [The fast converging to the inverse cascade.](https://github.com/scaomath/torch-cfd/blob/main/examples/ex2_SFNO_5ep_spectra.ipynb) ## Dataset Structure Each individual chunk of data is pickled in single-file format. ## Dataset Creation ### TO-DO ## Citation ```bibtex @article{2024SpectralRefiner, title={Spectral-Refiner: Fine-Tuning of Accurate Spatiotemporal Neural Operator for Turbulent Flows}, author={Shuhao Cao and Francesco Brarda and Ruipeng Li and Yuanzhe Xi}, journal={arXiv preprint arXiv:2405.17211}, year={2024}, primaryClass={cs.LG} } ```