{ "@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" } ] }