What information do Reynolds-averaged models lack to predict smooth-surface separation? · revision history

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Title

What information do Reynolds-averaged models lack to predict smooth-surface separation?

Plain

Engineering simulations cannot afford to resolve every eddy, so they use approximate models of turbulence. These models still fail to predict reliably where a turbulent flow detaches from a smooth curved surface, which governs stall and drag, and it is not known what information they are missing.

Precise

For turbulent boundary layers separating under an adverse pressure gradient from a smooth surface (benchmarks such as $2\mathrm{D}\ \text{and}\ 3\mathrm{D}$ smooth bumps at $\mathrm{Re}_L \sim 10^6\ \text{to}\ 10^7$), identify which non-local or history information absent from single-point Reynolds-averaged equations (for example upstream pressure-gradient history, transport of Reynolds-stress anisotropy, or large-scale unsteadiness) is needed to predict separation and reattachment locations within experimental uncertainty. Answer: the minimal added information, demonstrated by a model that uses it and predicts an unseen geometry blind.

Settled by

Blind predictions of separation and reattachment on a new benchmark geometry agreeing with experiment within stated uncertainty, by a model whose added inputs are stated.

Kind

phenomenon

Answer type

identification

References

(empty)

Literature status

open

Status note

Data-driven closures improve agreement on training cases but have not shown reliable transfer to unseen geometries as of 2026.

Posed since

(empty)