--- license: other license_name: mixed-cc-by-4.0-and-cc-by-nc-sa-4.0 license_link: LICENSE task_categories: - other language: - en tags: - turbulence - rans - cfd - dns - les - benchmark - machine-learning-for-physics pretty_name: "Closure Challenge v2 — extended ML-RANS turbulence benchmark" size_categories: - 100K **Heavy CFD assets** (full OpenFOAM cases, VTK volumes): [`anon-closure-challenge-v2/closure-challenge-v2-cfd-cases`](https://huggingface.co/datasets/anon-closure-challenge-v2/closure-challenge-v2-cfd-cases) ## What's in the test set 8 inherited v1 cases: - 4 parametric periodic-hill geometries at Re=5600 - 3 square / rectangular duct configurations (AR=1, 3, 14.4 at Re_τ=180/360) - NASA wall-mounted hump 6 new v2 cases: | Case | Reference type | Quantities of interest | |------|-----------------|--------------------------| | `NASA_2DZP` | NASA TMR theory | C_f(x), u⁺(log y⁺) | | `NASA_2DN00` | Ladson NASA TM 4074 + Gregory NPL R&M 3726 | C_L(α), C_D(α), C_p(x/c), C_f(x/c) | | `NASA_ASJ` | Bridges-Wernet ARN consensus PIV | U/U_jet centerline + 5 stations, ⟨u'v'⟩/U_jet² at 5 stations | | `ERCOFTAC_AhmedBody25` | LDA wake + pressure taps (case082) | rear-surface C_p, integrated C_D vs canonical 0.285 | | `NASA_FaithHill` | PIV centerline + PSP + FISF | mean velocity, TKE, surface C_p, surface C_f | | `ERCOFTAC_WingBodyJunction` | DNS 1-6 | symmetry-plane velocity / TKE / R_xx + bottom-wall and wing-root C_p | ## Layout ``` data/ ├── alpha_15_13929_4048/ v1 PHLL ├── alpha_15_13929_2024/ ├── alpha_05_4071_4048/ ├── alpha_05_4071_2024/ ├── AR_1_Ret_360/ v1 DUCT ├── AR_3_Ret_360/ ├── AR_14_Ret_180/ ├── NASA_2DWMH/ v1 hump ├── NASA_2DZP/ v2 new ├── NASA_2DN00/ ├── NASA_ASJ/ ├── ERCOFTAC_AhmedBody25/ ├── NASA_FaithHill/ ├── ERCOFTAC_WingBodyJunction/ └── evaluation_points/ v1 case grids ``` All 14 are **held-out test cases**. This dataset contains no training data. The standardized training and validation sets (27 and 5 cases) are published in the companion heavy dataset under `data/train/` and `data/validation/`: [`anon-closure-challenge-v2/closure-challenge-v2-cfd-cases`](https://huggingface.co/datasets/anon-closure-challenge-v2/closure-challenge-v2-cfd-cases). For each v2-new case: ``` / ├── baseline_komegasst/ k-ω SST baseline (.dat + .csv pairs) ├── highfidelity/ Reference data (.dat + .csv pairs) └── plots/ Pre-rendered comparison figures ``` ### Reading the periodic-hill case names The digits in `alpha___` are **domain dimensions, not Reynolds numbers**. `alpha_05_4071_2024` has streamwise extent x = 0 .. 4.071 and wall-normal extent y = 0 .. 2.024; `alpha_15_13929_4048` spans x = 0 .. 13.929 and y = 0 .. 4.048. The leading `alpha` value is the hill-slope parameter. ## Quick start ```python import pandas as pd df = pd.read_csv("data/NASA_2DZP/highfidelity/cf_as_function_of_x.csv") print(df.columns.tolist()) # ['zone', 'x', 'skinfr', '5percenterror'] ``` For end-to-end scoring, use the `closure-challenge-v2` Python package and the `notebooks/sample_eval.ipynb` example, both available in the [code repository](https://anonymous.4open.science/r/closure-challenge-v2). ## License This dataset aggregates material under two different licenses. See the `LICENSE` file at the repository root for the authoritative statement. - **CC-BY-4.0**: the 12 non-ERCOFTAC cases (`alpha_*`, `AR_*`, `NASA_*`) and `evaluation_points`, derived from public-domain or CC-BY upstream sources (NASA Turbulence Modeling Resource, Vinuesa duct database, Xiao parametric periodic-hill database). - **CC-BY-NC-SA-4.0**: `ERCOFTAC_AhmedBody25` and `ERCOFTAC_WingBodyJunction`, curated extracts of ERCOFTAC kbwiki material (Classic Collection case082; DNS 1-6), inheriting the upstream non-commercial and share-alike conditions. - **Code**: MIT (see `LICENSE-CODE` in the [code repository](https://anonymous.4open.science/r/closure-challenge-v2)). Hugging Face has no per-directory license field, so this repository declares `license: other` and records the split in `LICENSE`. The `configs` block above groups the two license scopes for readers and machine consumers; it does not itself carry licensing force. Per-case attribution is in [`SOURCES.md`](https://anonymous.4open.science/r/closure-challenge-v2/SOURCES.md) of the code repository. ## Citation ```bibtex @inproceedings{closure_challenge_v2_neurips26, title={The Closure Challenge: A Benchmark Task for Machine Learning in Turbulence Modeling}, author={Anonymous}, booktitle={NeurIPS Datasets and Benchmarks Track (under review)}, year={2026} } ``` ## Croissant metadata A Croissant 1.0 + RAI metadata file is provided as `croissant.json` in this repository, suitable for the JoaquinVanschoren/croissant-checker validator.