Turbulence Model Selection

OpenFOAM Case Generator y+ Calculator ◈ Portfolio

Flow & Geometry

Reynolds Number Re

Mach Number Ma

Geometry

Wall Treatment

Simulation Goals

Primary Goal

Unsteadiness

Compute Budget

Configure inputs and press ▶ RUN SELECTOR.

Y-Axis Grouping

Highlight Type

Cursor Inspector (Click map to pin)

Hover map to see models at Re. Click to pin.

Regime Boundaries

Pipe laminar→turbulentRe ≈ 2300

Flat plate transition onsetRe_x ≈ 3×10⁵

Flat plate fully turbulentRe_x ≈ 5×10⁵

Cylinder drag crisisRe ≈ 2–5×10⁵

LES affordable (research)Re_L ≲ 10⁵

LES requires HPCRe_L ~ 10⁶

WMLES required (wall BL)Re_L ≳ 5×10⁶

DDES preferred range10⁵–10⁸

Click any model card to expand full profile. Includes exact equations, failure modes, validation history, and OpenFOAM tips.

Model	Re	Ma/Compress.	APG	Rotation	Tu	Mesh	Notes

How to Read

Sensitivity Scale

0 — NoneModel is insensitive to this parameter

1 — LowMinor effect, manageable

2 — ModerateNoticeable; review setup

3 — HighSignificant; requires care

4 — CriticalDominant; results strongly affected

Abbreviations & Full Forms

ReReynolds Number (ρUL/μ)

MaMach Number (U/c)

APGAdverse Pressure Gradient

FPGFavourable Pressure Grad.

ZPGZero Pressure Gradient

TuTurbulence Intensity (%)

y⁺Wall distance (u_τ·Δy/ν)

BLBoundary Layer

TKE / kTurbulent Kinetic Energy

ωSpecific dissipation rate

εTurbulent dissipation rate

RANSReynolds-Averaged N-S

LESLarge Eddy Simulation

DESDetached Eddy Simulation

DDESDelayed DES

IDDESImproved DDES

RSMReynolds Stress Model

SGSSubgrid-Scale (model)

SASScale Adaptive Simulation

SASpalart-Allmaras

SSTShear Stress Transport

WMLESWall-Modelled LES

Model	Type	Cost	Separation	Heat Xfr	Transition	Acoustics	Rotating	y⁺ Range	Anisotropy	Comp. Ready	Min Cells (Est.)	OF Class

Head-to-Head: k-ω SST vs Competitors

Canonical Flow	SST Result Quality	Competitor Model & Quality	Winner	Engineering Note
Flat Plate (ZPG)	Excellent (captures log-law perfectly)	SA: Excellent (designed for it)	Tie	SA is 20% cheaper computationally.
RAE2822 Airfoil (Transonic APG)	Excellent (predicts shock location well)	k-ε: Poor (shock too far aft, no sep)	SST	SST limits shear stress in APG via Bradshaw's assumption.
Backward Facing Step (Sep.)	Good (reattachment slightly late)	v2f / LRR: Excellent (exact reattachment)	RSM / v2f	SST overpredicts TKE in shear layer. RSM handles anisotropy.
Pipe Flow (Internal ZPG)	Good (requires fine mesh near wall)	k-ε Realizable: Excellent + cheap	k-ε Real.	k-ε with wall functions is vastly cheaper for bulk pipe flows.
Tandem Cylinder (Acoustics)	Poor (Steady RANS damps shedding)	SST-DDES: Excellent (resolves wake)	DDES	RANS cannot resolve broadband noise. Scale-resolving required.
Turbine Cascade (Curvature)	Moderate (blind to streamline curvature)	SARC / SSG: Good (captures curvature)	SARC / RSM	Standard eddy viscosity assumes turbulence is blind to rotation.

1. RANS Closure & Boussinesq

Boussinesq Approximation

τ_ij = 2μ_t S_ij − (2/3)ρk δ_ij S_ij = 0.5·(∂U_i/∂x_j + ∂U_j/∂x_i)

k-ω SST Exact Transport Equations

∂(ρk)/∂t + ∂(ρU_j k)/∂x_j = P_k - β*ρkω + ∂/∂x_j[(μ + σ_k μ_t) ∂k/∂x_j] ∂(ρω)/∂t + ∂(ρU_j ω)/∂x_j = (γ/ν_t)P_k - βρω² + ∂/∂x_j[(μ + σ_ω μ_t) ∂ω/∂x_j] + 2(1-F1)ρσ_{ω2}(1/ω) ∂k/∂x_j ∂ω/∂x_j

RSM (Reynolds Stress Model)

∂(ρR_ij)/∂t + C_ij = P_ij + D_ij + Φ_ij - ε_ij

Φ_ij (Pressure-Strain) is the critical closure. LRR uses a linear model; SSG uses a quadratic model (better for swirl). Realizability (Lumley triangle) ensures physical positive-definite turbulent normal stresses.

2. DES / DDES Formulation

DES Length Scale

d̃ = min(d_wall, C_DES · Δ) Δ = max(Δx, Δy, Δz)

DDES Shielding Function

d̃ = d_wall − F_d · max(0, d_wall − C_DES·Δ) F_d = 1 − tanh((8·r_d)³) r_d = (ν_t + ν) / (κ² · d_wall² · √|S_ij|²)

IDDES & SAS & WMLES

IDDES: Blends DDES shielding with WMLES formulation. Introduces elevating function to fix log-layer mismatch.
SAS-SST: Uses von Kármán length scale L_vK = κS / |∇²U|. Break RANS into LES structures without explicit grid dependence.
WMLES: Algebraic wall model imposes wall shear stress τ_w as a BC for the resolved outer layer.

3. Wall Treatment & y⁺ Physics

Spalding Unified Wall Law

y⁺ = u⁺ + e^{-κB} [ e^{κu⁺} - 1 - κu⁺ - 0.5(κu⁺)² - (1/6)(κu⁺)³ ]

Valid from y⁺=0 to y⁺=300 continuously. Used in OpenFOAM's nutUSpaldingWallFunction.

OpenFOAM Wall Function Mapping

Model	y+ < 1	y+ > 30
k-ε	nutLowReWallFn	nutkWallFunction
k-ω SST	nutLowReWallFn	nutkWallFunction
SA	nutLowReWallFn	nutUSpalding...

y⁺ Physics

y⁺ = u_τ·Δy / ν. First cell centroid dictates valid assumptions. Buffer layer (y⁺ 5–30) violates both viscous and log-law assumptions.

4. LES Cost & Scales

Cost Scaling vs Re

Model	Grid (N)	Timesteps	Total Cost
RANS	Re^0	Re^0 (steady)	O(1)
WMLES	Re^1.0	Re^0.5	O(Re^1.5)
WRLES	Re^1.8	Re^0.6	O(Re^2.4)
DNS	Re^2.25	Re^0.75	O(Re^3.0)

Turbulence Scales

Integral (L): Macro scale, contains most energy.
Taylor (λ): Inertial subrange. λ/L ~ Re_L^(-1/2)
Kolmogorov (η): Dissipation scale. η = (ν³/ε)^(1/4). η/L ~ Re_L^(-3/4). Resolved by DNS.

5. Transition Physics

Transition Mechanisms

Natural: TS waves → secondary instability → breakdown. Needs very low freestream Tu (< 0.1%).
Bypass: High freestream Tu (> 1%) penetrates BL, bypassing TS waves. Typical in turbomachinery.
Separation-induced: Laminar BL separates in APG, transitions in shear layer, reattaches as turbulent (LSB).

γ-Reθ Formulation

Uses empirical correlations (e.g. Mayle) linking local Tu to transition onset Re_θt. γ (intermittency) equation multiplies TKE production, switching it on smoothly.

6. Compressible Turbulence

Favre Averaging

ũ_i = \bar{ρ u_i} / \bar{ρ} u_i = ũ_i + u_i''

Density-weighted averaging eliminates complex density fluctuation terms in N-S equations.

Dilatation Dissipation (Sarkar)

ε_c = α M_t² ε_s M_t = √(2k) / c

As Mach increases, compressibility drains energy via shocks/dilatation. Reduces spreading rate of supersonic jets (comp. shear layer anomaly). Corrected via Sarkar/Wilcox modifiers.

Curated validation resources with direct links to databases, landmark papers (DOI), benchmark datasets, and experimental data. Each canonical flow maps to specific model recommendations.

🗄 Official Validation Databases

NASA Turbulence Modeling Resource (TMR)

The single most authoritative public database for RANS model verification. Contains grid-convergence studies, structured solution files, and experimental comparisons for: Flat Plate (ZPG), Backward Facing Step, RAE2822 Airfoil, NACA 0012, 2D Bump, CRM Wing-Body, Axisymmetric Bump, Juncture Flow, and more.
turbmodels.larc.nasa.gov — free access, updated actively.

ERCOFTAC Classic Database (SIG15)

European Research Community on Flow, Turbulence And Combustion. 100+ experimental datasets covering: pipe flow, channel flow, backward-facing step, bluff body wakes, free jets, swirling flows, impinging jets, flow over hills (ERCOFTAC SPH11). Each case has structured data files for direct comparison.
cfd.mace.manchester.ac.uk/ercoftac

NPRAC Alliance V&V (NASA GRC)

Structured Verification and Validation test cases for the WIND-US solver; applicable to any CFD code. Includes flat plate, RAE2822, axisymmetric bump, and more.
www.grc.nasa.gov/www/wind/valid

Johns Hopkins Turbulence Databases (JHTDB)

Direct access to DNS datasets (channel flow Re_τ=1000, 5200; isotropic turbulence; MHD; rotating stratified). Petascale data, query-able via API or Python client. Invaluable for SGS model calibration.
turbulence.idies.jhu.edu

OpenTurbulence (KTH)

Open repository of spectral DNS channel flow data at Re_τ = 180–5200. Fully resolved statistics available: mean profiles, Reynolds stresses, spectra, budgets.
KTH DNS Database

AGARD Advisory Reports

AGARD AR-345 (1998) — "A Selection of Test Cases for the Validation of Large-Eddy Simulations of Turbulent Flows". AGARD AR-291 — Turbulent Shear Flows. Both available via DTIC (US Department of Defense Technical Information Center).
apps.dtic.mil/sti/

📄 Canonical Test Cases — Model Map

Flat Plate — ZPG Boundary Layer

ExperimentWieghardt (1951), Klebanoff (1955)

Best RANSk-ω SST, SA

Data sourceNASA TMR Flat Plate

Backward Facing Step (BFS)

ExperimentDriver & Seegmiller (1985), Re_h=37,400

Best RANSv2f, SST (reattachment ±5%)

Data sourceNASA TMR BFS

RAE 2822 Airfoil (Transonic)

ExperimentCook, McDonald & Firmin (1979), ARC R&M 3744

Best RANSk-ω SST (Case 9: Ma=0.73)

Data sourceNASA TMR RAE2822

2D NACA 0012 Airfoil

ExperimentGregory & O'Reilly (1970)

Best RANSSA, SST (pre-stall)

Data sourceNASA TMR NACA0012

Periodic Hill (Wavy Channel)

LES referenceBreuer et al. (2009), Re_b=10595

Best approachDDES, LES (SST overestimates sep)

Data sourceERCOFTAC C69

ERCOFTAC T3 Series — Transition

ExperimentRoach & Brierley (1992)

Best RANSγ-Reθ, γ SST

Data sourceERCOFTAC T3A–T3C

NASA Common Research Model (CRM)

ExperimentVassberg et al. (2008), AIAA 2008-6919

Best RANSk-ω SST, SA-RC

Data sourceAIAA Drag Prediction Workshop

📚 Landmark Papers — Full DOI References

Foundational Model Papers

Launder & Spalding (1974) — "The numerical computation of turbulent flows." Computer Methods in Applied Mechanics and Engineering, 3(2), 269–289. DOI:10.1016/0045-7825 — The original k-ε model.
Wilcox (1988) — "Multiscale model for turbulent flows." AIAA Journal, 26(11), 1311–1320. DOI:10.2514/3.10042 — Original k-ω model.
Menter (1994) — "Two-equation eddy-viscosity turbulence models for engineering applications." AIAA Journal, 32(8), 1598–1605. DOI:10.2514/3.12149 — The seminal SST paper.
Spalart & Allmaras (1992) — "A one-equation turbulence model for aerodynamic flows." AIAA Paper 92-0439. DOI:10.2514/6.1992-439
Shih et al. (1995) — "A new k-ε eddy viscosity model for high Reynolds number turbulent flows." Computers & Fluids, 24(3), 227–238. DOI:10.1016/0045-7930 — Realizable k-ε.
Yakhot & Orszag (1986) — "Renormalization group analysis of turbulence." J. Scientific Computing, 1(1), 3–51. DOI:10.1007/BF01061452 — RNG k-ε.
Launder, Reece & Rodi (1975) — "Progress in the development of a Reynolds-stress turbulence closure." JFM, 68(3), 537–566. Semantic Scholar — Original LRR RSM.
Speziale, Sarkar & Gatski (1991) — "Modeling the pressure-strain correlation of turbulence." JFM, 227, 245–272. DOI:10.1017/S0022112091000101 — SSG RSM.
Durbin (1991) — "Near-wall turbulence closure modeling without damping functions." Theoretical and Computational Fluid Dynamics, 3(1), 1–13. DOI:10.1007/BF00271513 — v2f model.

Hybrid / DES / LES Papers

Spalart et al. (1997) — "Comments on the Feasibility of LES for Wings, and on a Hybrid RANS/LES Approach." Advances in DNS/LES, 137–147. — Original DES concept.
Spalart et al. (2006) — "A New Version of Detached-eddy Simulation, Resistant to Ambiguous Grid Densities." Theoretical and Computational Fluid Dynamics, 20(3), 181–195. DOI:10.1007/s00162-006-0015-0 — DDES.
Shur et al. (2008) — "A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities." Int. J. Heat and Fluid Flow, 29(6), 1638–1649. DOI:10.1016/j.ijheatfluidflow.2008.07.001 — IDDES.
Menter & Egorov (2010) — "The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions." Flow Turbulence Combustion, 85(1), 113–138. DOI:10.1007/s10494-010-9264-5 — SAS-SST.
Smagorinsky (1963) — "General circulation experiments with the primitive equations." Monthly Weather Review, 91(3), 99–164. DOI link — Smagorinsky LES SGS.
Nicoud & Ducros (1999) — "Subgrid-scale stress modelling based on the square of the velocity gradient tensor." Flow Turbulence Combustion, 62(3), 183–200. DOI:10.1023/A:1009995426001 — WALE SGS.
Nicoud et al. (2011) — "Using singular values of the velocity gradient tensor as subgrid scale model." Flow Turbulence Combustion, 86(3–4), 529–546. DOI:10.1007/s10494-011-9354-2 — Sigma model.

Transition Modeling Papers

Langtry & Menter (2009) — "Correlation-Based Transition Modeling for Unstructured Parallelized CFD Codes." AIAA Journal, 47(12), 2894–2906. DOI:10.2514/1.42362 — γ-Reθ transition model.
Menter et al. (2015) — "A One-Equation Local Correlation-Based Transition Model." Flow Turbulence Combustion, 95(4), 583–619. DOI:10.1007/s10494-015-9622-4 — γ SST (one-eq).

📖 Textbooks & Review Articles

Essential Textbooks

Wilcox, D.C. (2006). Turbulence Modeling for CFD, 3rd ed. DCW Industries. ISBN: 978-1-928729-08-2. — The most complete model-by-model derivation reference. Covers SA, k-ω, k-ε, RSM with worked examples and validation data.
Pope, S.B. (2000). Turbulent Flows. Cambridge University Press. ISBN: 0-521-59886-9. — Rigorous statistical theory. Best reference for turbulence physics fundamentals, energy spectra, Kolmogorov scales, RANS derivation.
Sagaut, P. (2006). Large Eddy Simulation for Incompressible Flows, 3rd ed. Springer. ISBN: 978-3-540-26344-9. — Definitive LES reference: SGS models, filtering, wall models, numerical constraints.
Durbin, P.A. & Pettersson Reif, B.A. (2010). Statistical Theory and Modeling for Turbulent Flows, 2nd ed. Wiley. — Bridges mathematical theory and engineering models. Excellent v2f and RSM treatment.
Ferziger, J.H., Perić, M. & Street, R.L. (2020). Computational Methods for Fluid Dynamics, 4th ed. Springer. — Numerical methods foundation for CFD practitioners.
Blazek, J. (2015). Computational Fluid Dynamics: Principles and Applications, 3rd ed. Butterworth-Heinemann. — Practical discretization, boundary conditions, compressible turbulence.
Lesieur, M., Métais, O. & Comte, P. (2005). Large-Eddy Simulations of Turbulence. Cambridge University Press. — Advanced SGS physics.

Key Review Articles (Free Access)

Spalart (2009) — "Detached-Eddy Simulation." Annual Review of Fluid Mechanics, 41, 181–202. DOI link — Comprehensive DES state-of-the-art review.
Georgiadis, Rizzetta & Fureby (2010) — "Large-Eddy Simulation: Current Capabilities, Recommended Practices, and Future Research." AIAA Journal, 48(8). DOI link
Durbin (2018) — "Some Recent Developments in Turbulence Closure Modeling." Annual Review of Fluid Mechanics, 50, 77–103. DOI link
Piomelli (1999) — "Large-eddy simulation: achievements and challenges." Progress in Aerospace Sciences, 35(4), 335–362. DOI link
Menter (2011) — "Turbulence Modeling for Engineering Flows." Ansys Technical Report. Ansys Resource Library

Free PDF Resources

NASA TMR Model Equations (PDF) — Complete equations, coefficients, and implementation notes for all major RANS models.
CFD-Online Wiki: RANS Equations — Community-maintained reference.
OpenFOAM User Guide — Turbulence Modeling — Official OpenFOAM turbulence model documentation.
arXiv:2109.01165 — ML for Turbulence Modeling (Review) — Machine learning approaches review (2021).

✅ Per-Model Validation Evidence Summary

Model	Best Validated Case	Error vs Experiment	Reference Experiment	Known Failure Flow	Peer-Reviewed Source
k-ω SST	RAE2822 Case 9 (transonic)	Cp within 5%, skin friction ±8%	Cook et al. 1979, ARC R&M 3744	Massive post-stall separation	Menter (1994)
k-ε Standard	Plane mixing layer, pipe flow	Velocity profile ±3%	Rodi (1972) mixing layer	Round jet (15% error in spreading rate)	Launder & Spalding (1974)
k-ε Realizable	Round jet, swirling flow	Spreading rate correct	Wygnanski & Fiedler (1969)	APG separation onset	Shih et al. (1995)
Spalart-Allmaras	NACA 0012, flat plate BL	Cf within 2% (ZPG)	Gregory & O'Reilly (1970)	Separated free shear, heat transfer	Spalart & Allmaras (1992)
v2f	Impinging jet heat transfer	Nu distribution ±5%	Baughn & Shimizu (1989)	Elliptic f solver divergence on coarse mesh	Durbin (1991)
γ-Reθ SST	T3A/T3B/T3C flat plates	Transition location ±5–10%	Roach & Brierley (1992), ERCOFTAC	Tu decay between inlet and LE	Langtry & Menter (2009)
LRR RSM	Square duct secondary flow	Velocity components ±8%	Gessner & Jones (1965)	Divergence from poor initialisation	Launder et al. (1975)
SST-DDES	Tandem cylinder	CL frequency ±3%, PSD shape	Jenkins et al. (2005) NASA TM-2005-213649	Grey area MSD in thin BL	Spalart et al. (2006)
WALE LES	Channel flow Re_τ=395	u+ within 1%, TKE ±5%	Moser, Kim & Mansour (1999) DNS	HPC required for Re_τ>1000	Nicoud & Ducros (1999)
Smagorinsky LES	Decaying isotropic turbulence	E(k) spectrum shape matches	Comte-Bellot & Corrsin (1971)	Over-dissipative in laminar near-wall regions	Smagorinsky (1963)
IDDES	Channel flow Re_τ=395, 2000	Log-layer mismatch <5%	DNS Moser et al. (1999)	Highly mesh-design dependent	Shur et al. (2008)

📐 Grid Independence & V&V Best Practice

Richardson Extrapolation (Roache GCI)

The Grid Convergence Index (GCI) is the AIAA/ASME standard for reporting discretization error:

GCI = Fs × |ε| / (r^p - 1) ε = (f_2 - f_1) / f_1 (relative change) r = h_coarse / h_fine (refinement ratio ≥ 1.3) p = ln(|ε_32/ε_21|) / ln(r) (observed order) Fs = 1.25 (safety factor) Target: GCI_fine < 5% for engineering, <1% for research.

AIAA standardRoache (1998) GCI Paper

NASA standardNASA Spatial Convergence Tutorial

Three-Mesh GCI Protocol

Coarse: baseline (~100k cells for 3D RANS)
Medium: ×2–3 refinement by volume
Fine: ×2–3 additional refinement
Report GCI for key QoI (Cd, Nu, Cp)
For LES: report SGS contribution fraction <20%

y+ Verification

Post-run: check y+ histogram in ParaView / CFD-Post
For wall-resolved: 95% cells must have y+ < 1
For wall functions: 70% cells must have 30 < y+ < 300
Buffer layer contamination (5 < y+ < 30) invalidates both approaches

⚠ Common Validation Pitfalls

Inlet Condition Mismatch

If freestream turbulence intensity (Tu) and length scale (L) at the leading edge do not match the experimental conditions, all transition and separation predictions will be systematically off. The k and ω fields decay with distance — run a separate decay study to match Tu at the measurement plane, not just at the inlet boundary.

Reference Area / Length Confusion

Force coefficients (Cd, Cl) are non-dimensionalised by a reference area and dynamic pressure. Validate that your reference area, reference velocity, and density match the experimental setup exactly. A 5% mismatch in reference chord length = 5% systematic error in all force coefficients.

Incorrect Experimental Re

Many classic experiments (e.g. RAE2822) were conducted at fixed chord Reynolds number, not a body Reynolds number. Ensure your CFD inlet conditions reproduce the same Re_c, including the correct viscosity at the experimental temperature.

Statistical Convergence for URANS/LES

LES and DDES require sufficient flow-through times before statistics are sampled. Minimum: 5–10 flow-through times for wash-out, then sample for at least 5 additional flow-through times. For turbomachinery: minimum 10 blade passages. Insufficient averaging produces spurious results.

Compressibility Mismatch

At Ma > 0.3, use a compressible solver (rhoPimpleFoam, rhoCentralFoam). Incompressible simulations at Ma = 0.5 introduce >10% error in pressure coefficient even before shocks appear.

Wall Function Buffer Zone

The buffer layer (5 < y+ < 30) is in-between the viscous sublayer and log-law. Both wall function assumptions fail here. If y+ values cluster in this range, the result is neither resolved nor accurately modelled. Avoid by design: target y+ < 1 or y+ > 30, not both on the same mesh.

Disclaimer

This tool compiles information from the above peer-reviewed sources and publicly available databases. All recommendations should be validated against case-specific benchmark data before production use. Turbulence model selection is inherently problem-dependent — no single model is universally optimal. The author assumes no liability for engineering decisions made solely on the basis of this tool.

Curated YouTube lectures, CFD blog posts, open-source tutorials, and community tools for turbulence modeling practitioners.

▶ YouTube — Lectures & Tutorials

Full Lecture Series

NPTEL — Turbulence (IIT Madras) — 40-lecture series covering Reynolds averaging, k-ε, k-ω, LES from first principles. Free, with subtitles.
Fluid Mechanics 101 (Dr. Andrew Coughtrie) — Clear, concise explanations of turbulence models: wall functions, y+, mesh sensitivity. Highly recommended for beginners.
JÃ³zsef Nagy (OpenFOAM Tutorials) — OpenFOAM turbulence model walkthroughs including SST, DDES, LES setups.
Wolf Dynamics (OpenFOAM) — Practical RANS tutorials in Fluent and OpenFOAM with mesh generation and post-processing.

Key Individual Videos

Turbulence — It's Worse Than You Think (Veritasium) — Excellent physics intuition on turbulence. 15M views.
k-omega SST Explained (SimScale Academy) — Visual explanation of SST model blending, near-wall treatment.
DES vs RANS vs LES (Dr. Thibault Pringuey) — Side-by-side comparison with flow visualisations.
Wall y+ in CFD — Explained (LEAP CFD) — y+ target selection, mesh design for wall functions vs resolved.
What is LES? (SimFlow Tutorial) — Conceptual LES introduction with filter width and SGS models.
OpenFOAM k-omega SST Setup (TU Delft) — Step-by-step tutorial including turbulenceProperties, boundary conditions.
Turbulence Intensity & Length Scale (CFD-Online) — Inlet boundary condition specification.

Graduate Level / Research

MIT OCW — Turbulent Flows (Lecture Series)
Stanford Engineering — Parviz Moin LES Lectures — Advanced LES from one of the field's pioneers.
Spalart on DES — AIAA Talk (2021) — Phil Spalart explains 25 years of DES development.

📝 Blogs, Forums & Online Resources

Premier CFD Blogs

CFD-Online.com — The largest CFD community forum. Turbulence model forum has 20+ years of practitioner Q&A. Wiki has excellent model summaries.
SimScale — Turbulence Model Guide — Visual, engineering-focused guide with selection flowchart and example simulations.
CFD-Online Wiki — Turbulence Modeling — Community wiki with equations, derivations, and implementation notes for every major model.
OpenFOAM Official Turbulence Guide — Complete list of available models, dict entries, and boundary conditions in OpenFOAM.
LEAP Australia CFD Blog — Practical guides on y+, wall functions, solver selection. Very practitioner-focused.

Ansys / Commercial Solver Resources

Ansys Fluent — Turbulence Models Chapter — Complete Fluent documentation including model formulation and recommended practices.
Ansys White Paper — Best Practices for Turbulent Flow (free download after registration)
Siemens Simcenter STAR-CCM+ (CFD)

Research Groups & Portals

NASA Langley Turbulence Modeling Resource — Active resource by the CFD validation group; most authoritative RANS data.
AIAA Drag Prediction Workshop (DPW) — DPW 1–7 results compare all major RANS codes on CRM geometry. Excellent model accuracy data.
ERCOFTAC.org — European body for CFD research; SIG15 manages turbulence model validation database.
NASA WIND-US V&V Test Cases — Structured validation study methodology reference.

Specialised OpenFOAM Resources

OpenFOAM Tutorial Guide — Official tutorials including turbulent pipe flow, backward-facing step, bluff body DES.
OpenFOAM Wiki (Community) — Tips on turbulence model setup, wall function selection, debugging divergence.
OpenFOAM Forum @ CFD-Online — 500k+ posts on OpenFOAM turbulence model setups.

🔧 Tools & Calculators

Online Calculators

y+ Calculator (this site) — Compute first-cell height Δy for target y+, with Cf correlations.
OpenFOAM Case Generator (this site) — Full case directory generation with turbulence model settings.
Boundary Condition Calculator (this site) — Compute k, ε, ω, ν_t from Tu and L_mix.
CFD-Online Turbulence Calculator — k, ε, ω, ν_t from Tu and I.

Open-Source CFD Solvers

OpenFOAM — Leading open-source CFD solver. All major turbulence models included. pisoFoam (LES), simpleFoam (RANS), rhoPimpleFoam (compressible).
SU2 — Open-source multi-physics solver from Stanford. SA and SST built in, adjoint optimization capable.
OpenFOAM Foundation — Official OpenFOAM.org branch with latest turbulence model updates.

Post-Processing & Visualisation

ParaView — Industry-standard CFD post-processing. y+ field inspection, Q-criterion iso-surfaces, line probes against experimental data.
fluidfoam (Python) — Read OpenFOAM results in Python for automated validation against experimental data files.

📊 Decision Framework — Quick Reference

Model Selection Flowchart (Text)

Attached BL, external aero, cruise: → Spalart-Allmaras or k-ω SST. If Ma > 0.3, enable compressibility correction.
Mild separation, APG, force coefficient: → k-ω SST. If transition important → γ-Reθ SST.
Pipe flow, HVAC, internal duct: → k-ε Realizable with wall functions (y+ 30–100).
Swirling flow, cyclone, combustion: → k-ε RNG or RSM (LRR/SSG).
Heat transfer, conjugate: → Low-Re k-ε LS, v2f, or k-ω SST with y+ < 1.
Laminar–turbulent transition: → γ-Reθ SST (4-eq) or γ SST (3-eq, local).
Bluff body, massive separation, shedding: → SST-DDES (transient). Budget permitting: SST-IDDES.
Aeroacoustics: → IDDES or WMLES + FW-H acoustic analogy.
Rotating machinery, turbomachinery: → k-ω SST + MRF (steady) or sliding mesh (unsteady). For curvature: SA-RC.
Fundamental research / benchmark data: → WALE or Sigma LES. DNS for Re < 10⁵.

Key OpenFOAM Solver-Model Compatibility

Solver	Regime	Compatible Models
simpleFoam	Incompressible RANS steady	SA, k-ε, k-ω SST, RSM
pimpleFoam	Incompressible RANS/DDES transient	SST, DDES, SAS, IDDES
pisoFoam	Incompressible LES	Smag, WALE, dyn-k, Sigma, Vreman
rhoPimpleFoam	Compressible transient	k-ω SST, SA, DDES
rhoSimpleFoam	Compressible steady	k-ω SST, k-ε, SA
rhoCentralFoam	Supersonic/hypersonic	k-ω SST + Wilcox compressibility
buoyantSimpleFoam	Buoyant RANS steady	k-ε, k-ω SST (add buoyancy source)