data/NASA_ASJ/README.md

NASA ASJ — Axisymmetric Subsonic Jet

Validation case from the NASA TMR Collaborative Testing Challenge 2022 (turb-prs2022). Acoustic reference Mach M_jet ≈ 0.5.

Required metrics

1. u/U_jet vs. x/D_jet — centerline velocity decay
2. u/U_jet vs. y/D_jet at 5 specified stations — radial velocity profiles
3. u'v'/U_jet² vs. y/D_jet at 5 specified stations — Reynolds-stress profiles

Compared with the Bridges & Wernet ARN (Acoustic Reference Nozzle) consensus PIV dataset.

Folder layout

NASA_ASJ/
├── baseline_komegasst/   k-ω SST integral profiles (.dat + .csv)
├── highfidelity/         ARN PIV experiment + NASA WIND SSTV CFD reference
└── plots/                Pre-rendered comparison figures + plot_profiles.py

The full transient OpenFOAM case (mesh, time-averaged fields, post-processing) is hosted separately on the heavy CFD-asset Hugging Face dataset linked in the paper.

Solver / setup

• Solver: rhoPimpleFoam (compressible transient, with fieldAverage to produce mean fields)
• Turbulence model: kOmegaSST (baseline, no augmentation)
• Time-averaging window: last half of run, captured in *Mean fields
• Mach: M_jet = 0.5
• Why transient: the jet shear layer is convectively unstable; a steady SIMPLE iteration does not converge cleanly. Time-stepping with field averaging is the equivalent of a converged steady RANS solution here.

Submission format

Three files matching the columns of the bundled baseline:

• ASJ_u_vs_x.csv — zone, x/Dj, u/Uj (single zone, centerline)
• ASJ_u_at5stations.csv — zone, u/Uj, y/Dj (one zone per station: x/Djet=2, 5, 10, 15, 20)
• ASJ_uv_at5stations.csv — zone, u'v'/Uj^2, y/Dj (same zone structure)

Then python plots/plot_profiles.py overlays the baseline + reference + your model.