Datasets:

ydai17
/

TIDE-helical_re86_retune2_256_fp64

license: cc-by-4.0
tags:
  - turbulence
  - computational-fluid-dynamics
  - direct-numerical-simulation
  - navier-stokes
  - scientific-machine-learning
pretty_name: TIDE - helical_re86_retune2_256_fp64

TIDE - `helical_re86_retune2_256_fp64`

One configuration of TIDE (Turbulent Incompressible DNS Ensembles): a 256^3 fp64 direct numerical simulation of the incompressible Navier-Stokes equations, shipped as independent realizations and released only after passing a fixed acceptance standard of statistical gates and equation-level residual checks.

Index of all configurations: https://huggingface.co/datasets/ydai17/TIDE
Code: https://github.com/Dyloong1/TIDE-dataset-benchmark
DOI record: https://doi.org/10.5281/zenodo.21589489

huggingface-cli download ydai17/TIDE-helical_re86_retune2_256_fp64 --repo-type dataset \
    --local-dir ./tide-data/corpus/helical_re86_retune2_256_fp64.zarr

import zarr
z = zarr.open("./tide-data/corpus/helical_re86_retune2_256_fp64.zarr", mode="r")
u = z["u"][0]   # (3, 256, 256, 256) velocity of the first frame

Each store holds velocity [N,3,256^3], pressure [N,256^3], the optional scalar/buoyancy channel, and per-frame t, k_max_eta, seed. Fields are computed in fp64 and stored in fp32; frames are exported every 0.05 T_L. Data under CC-BY-4.0.