| --- |
| license: cc-by-4.0 |
| 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<n<1M |
| viewer: false |
| --- |
| |
| # Closure Challenge v2 |
|
|
| Extended ML-RANS turbulence-modelling benchmark with composite scoring across 14 test cases. |
|
|
| This dataset is the **lightweight integral-profile portion** used by the scoring protocol — CSV reference data and k-ω SST baseline predictions sampled at the canonical evaluation points for each case. The full OpenFOAM cases (mesh, fields, run scripts) and DNS-native partitioned VTUs are hosted on a separate Hugging Face dataset linked from the paper. |
|
|
| NeurIPS 2026 Evaluations & Datasets track submission. Authors anonymised for double-blind review. |
|
|
| ## 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 |
| ``` |
|
|
| For each v2-new case: |
|
|
| ``` |
| <case>/ |
| ├── baseline_komegasst/ k-ω SST baseline (.dat + .csv pairs) |
| ├── highfidelity/ Reference data (.dat + .csv pairs) |
| └── plots/ Pre-rendered comparison figures |
| ``` |
|
|
| ## 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 linked code repository. |
|
|
| ## License |
|
|
| - **Code**: MIT (see `LICENSE-CODE` in the code repository) |
| - **Curated data**: CC-BY-4.0 for all cases derived from public-domain or CC-BY upstream sources (NASA TMR, Vinuesa duct database, Xiao parametric PHLL, NASA wall-mounted hump, Faith Hill, NACA 0012) |
| - **ERCOFTAC kbwiki extracts**: CC-BY-NC-SA-4.0 (Ahmed body case082, wing-body junction DNS 1-6) — inherited from upstream |
|
|
| Per-case attribution is in `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. |
|
|
