Datasets:

anon-closure-challenge-v2
/

closure-challenge-v2-cfd-cases

	{
	"@context": {
	"@language": "en",
	"@vocab": "https://schema.org/",
	"citeAs": "cr:citeAs",
	"column": "cr:column",
	"conformsTo": "dct:conformsTo",
	"cr": "http://mlcommons.org/croissant/",
	"rai": "http://mlcommons.org/croissant/RAI/",
	"data": {
	"@id": "cr:data",
	"@type": "@json"
	},
	"dataType": {
	"@id": "cr:dataType",
	"@type": "@vocab"
	},
	"dct": "http://purl.org/dc/terms/",
	"examples": {
	"@id": "cr:examples",
	"@type": "@json"
	},
	"extract": "cr:extract",
	"field": "cr:field",
	"fileProperty": "cr:fileProperty",
	"fileObject": "cr:fileObject",
	"fileSet": "cr:fileSet",
	"format": "cr:format",
	"includes": "cr:includes",
	"isLiveDataset": "cr:isLiveDataset",
	"jsonPath": "cr:jsonPath",
	"key": "cr:key",
	"md5": "cr:md5",
	"parentField": "cr:parentField",
	"path": "cr:path",
	"recordSet": "cr:recordSet",
	"references": "cr:references",
	"regex": "cr:regex",
	"repeated": "cr:repeated",
	"replace": "cr:replace",
	"sc": "https://schema.org/",
	"separator": "cr:separator",
	"source": "cr:source",
	"subField": "cr:subField",
	"transform": "cr:transform"
	},
	"@type": "sc:Dataset",
	"name": "closure-challenge-v2-cfd-cases",
	"description": "Closure Challenge v2 — heavy CFD case files. Full OpenFOAM cases (polyMesh, initial and converged time directories, system and constant dictionaries, postProcessing output), VTK volume snapshots, and raw upstream high-fidelity reference archives for the 14 test cases of the Closure Challenge v2 benchmark. This is the companion to the lightweight integral-profile dataset, which holds the CSV reference data and k-omega SST baseline predictions used by the scoring protocol. Most consumers need only the lightweight dataset; this repository is required for re-running the CFD simulations from scratch or for extended analyses.",
	"conformsTo": "http://mlcommons.org/croissant/1.0",
	"license": "https://huggingface.co/datasets/anon-closure-challenge-v2/closure-challenge-v2-cfd-cases/blob/main/LICENSE",
	"url": "https://huggingface.co/datasets/anon-closure-challenge-v2/closure-challenge-v2-cfd-cases",
	"version": "0.4.0",
	"citeAs": "@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}}",
	"datePublished": "2026-05-04",
	"keywords": [
	"turbulence modeling",
	"RANS",
	"computational fluid dynamics",
	"OpenFOAM",
	"machine learning benchmark",
	"DNS",
	"LES",
	"k-omega SST",
	"NASA TMR",
	"ERCOFTAC"
	],
	"creator": {
	"@type": "Organization",
	"name": "Anonymous (under double-blind review)"
	},
	"isLiveDataset": false,

	"rai:dataCollection": "Original OpenFOAM k-omega SST baseline runs for the 14 benchmark cases, together with the meshes they were computed on, and the raw upstream high-fidelity reference archives (NASA Turbulence Modeling Resource, ERCOFTAC kbwiki Classic Collection, Vinuesa-lab duct database, Xiao et al. parametric periodic-hill database) from which the lightweight dataset's curated CSVs were derived.",
	"rai:dataPreprocessingProtocol": "OpenFOAM cases are shipped as run, with initial and converged time directories retained and intermediate checkpoints removed. Solver log headers have been normalised to remove machine-specific execution paths, hostnames, and process identifiers; residual and convergence history is preserved verbatim. Run scripts have been generalised to remove site-specific scheduler and module configuration. Raw upstream reference archives are byte-identical to their sources.",
	"rai:dataUseCases": "Re-running or extending the Closure Challenge v2 baseline simulations. Validation of CFD solver implementations against a fixed mesh and configuration. Development of mesh-aware or field-based machine-learning turbulence closures that require volume data rather than sampled profiles. Educational resource for CFD validation methodology.",
	"rai:dataLimitations": "(1) The 14 test cases focus on incompressible to low-Mach steady-state RANS-relevant flows; not applicable to transonic, hypersonic, or strongly unsteady regimes without re-curation. (2) Meshes are those used for the published baselines and have not been subjected to a formal grid-convergence study within this release. (3) DNS/LES references have finite statistical and numerical accuracy; the scoring protocol does not weight cases by reference uncertainty. (4) The ERCOFTAC wing-body junction volume DNS fields are not redistributed here because of their size; the curated profile and surface extracts in the lightweight dataset are the intended reference.",
	"rai:dataSocialImpact": "Provides the full computational provenance behind a community-standardised turbulence-closure benchmark, enabling independent reproduction of the baseline results rather than reliance on published summary profiles alone.",
	"rai:dataReleaseMaintenancePlan": "Versioned releases on Hugging Face, tracking the lightweight companion dataset's version. Errata tracked via GitHub issues on the public release repository. Significant corrections trigger a new patch version; new test cases or scoring-protocol changes trigger a new minor or major version. Old versions remain accessible to preserve leaderboard reproducibility.",
	"rai:dataBiases": "The benchmark deliberately selects canonical research geometries (parametric periodic hills, square and rectangular ducts, NASA TMR validation cases, simplified automotive bluff bodies, axisymmetric subsonic jet, smooth-body separation, wing-body junction). It is therefore biased toward research-grade flow configurations rather than industrial-scale geometries, and toward incompressible to low-Mach steady-state regimes rather than transonic, hypersonic, or strongly unsteady flows. The cases are also intentionally chosen to be challenging for the k-omega SST baseline, which biases the difficulty distribution toward separated and adverse-pressure-gradient flows. No human-subject, demographic, or socioeconomic bias is present because the dataset contains only fluid-mechanics measurements and simulation output.",
	"rai:personalSensitiveInformation": "None. The dataset contains computational fluid dynamics simulation outputs, meshes, solver configuration, and laboratory experimental measurements (PIV, LDA, pressure-sensitive paint, fringe-imaging skin friction). No human subjects, no personally identifiable information, no health data, no sensitive personal categories. Solver logs have been scrubbed of machine and account identifiers.",
	"rai:hasSyntheticData": "Partially. The OpenFOAM baseline cases are simulation outputs, and the high-fidelity references include both physics-based numerical simulations (DNS and LES, which are algorithm-generated and therefore synthetic in the RAI sense) and real-world laboratory measurements (PIV, LDA, PSP, FISF, hot-wire, surface pressure taps). No data is generated by machine-learning models or generative AI; all simulation outputs come from numerical integration of the Navier-Stokes equations in established CFD solvers.",

	"distribution": [
	{
	"@type": "cr:FileObject",
	"@id": "repo",
	"name": "repo",
	"description": "Hugging Face dataset repository hosting the full OpenFOAM cases, VTK snapshots, and raw upstream reference archives.",
	"contentUrl": "https://huggingface.co/datasets/anon-closure-challenge-v2/closure-challenge-v2-cfd-cases",
	"encodingFormat": "git+https",
	"sha256": "main"
	},
	{
	"@type": "cr:FileSet",
	"@id": "openfoam-mesh",
	"name": "openfoam-mesh",
	"description": "OpenFOAM polyMesh definitions (points, faces, owner, neighbour, boundary) for each test case.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "application/x-openfoam",
	"includes": "data//constant/polyMesh/"
	},
	{
	"@type": "cr:FileSet",
	"@id": "openfoam-system",
	"name": "openfoam-system",
	"description": "OpenFOAM case dictionaries: controlDict, fvSchemes, fvSolution, decomposeParDict, and post-processing function objects.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "application/x-openfoam",
	"includes": "data//system/"
	},
	{
	"@type": "cr:FileSet",
	"@id": "openfoam-fields",
	"name": "openfoam-fields",
	"description": "Converged k-omega SST solution fields and diagnostic quantities per test case.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "application/x-openfoam",
	"includes": "data///[Upk]*"
	},
	{
	"@type": "cr:FileSet",
	"@id": "vtk-snapshots",
	"name": "vtk-snapshots",
	"description": "VTK volume and surface snapshots for direct inspection in ParaView.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "application/x-vtk",
	"includes": "data//VTK/*"
	},
	{
	"@type": "cr:FileSet",
	"@id": "baseline-csv",
	"name": "baseline-csv",
	"description": "k-omega SST RANS baseline predictions sampled at the high-fidelity reference points, matching the lightweight companion dataset.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "text/csv",
	"includes": "data//baseline_komegasst/.csv"
	},
	{
	"@type": "cr:FileSet",
	"@id": "highfidelity-csv",
	"name": "highfidelity-csv",
	"description": "High-fidelity reference data per test case (DNS, LES, experimental PIV/LDA/PSP/FISF).",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "text/csv",
	"includes": "data//highfidelity/.csv"
	},
	{
	"@type": "cr:FileSet",
	"@id": "raw-reference-archives",
	"name": "raw-reference-archives",
	"description": "Raw upstream high-fidelity reference archives as distributed by NASA TMR and ERCOFTAC kbwiki, retained unmodified for provenance.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "application/gzip",
	"includes": "data/high_fidelity_data/**"
	},
	{
	"@type": "cr:FileSet",
	"@id": "extraction-tools",
	"name": "extraction-tools",
	"description": "Python utilities used to derive the lightweight dataset's curated CSVs from these cases and archives.",
	"containedIn": {"@id": "repo"},
	"encodingFormat": "text/x-python",
	"includes": "data/*.py"
	}
	]
	}