# An assessment of the two-layer quasi-laminar theory of relaminarization through recent high-Re accelerated TBL experiments

## TL;DR

This paper evaluates the two-layer quasi-laminar theory's effectiveness in predicting high-Re relaminarizing boundary layer flows, demonstrating its superior accuracy over standard turbulence models through recent experimental data.

## Contribution

The study revisits and improves the quasi-laminar theory, validating its applicability at high Reynolds numbers with exact inner-layer solutions and experimental comparisons.

## Key findings

- QLT matches high-Re experimental data better than standard models
- Inner-layer equations solved exactly improve prediction accuracy
- Supports using QLT in RANS simulations for relaminarizing flows

## Abstract

The phenomenon of relaminarization is observed in many flow situations, including that of an initially turbulent boundary layer subjected to strong favourable pressure gradients. Available turbulence models have hitherto been unsuccessful in correctly predicting boundary layer parameters for such flows. Narasimha and Sreenivasan \cite{narasimha1973relaminarization} proposed a quasi-laminar theory (QLT) based on a two-layer model to explain the later stages of relaminarization. This theory showed good agreement with the experimental data available, which at the time was at relatively low $Re$. QLT, therefore, could not be validated at high $Re$. Some of the more recent experiments report for the first time comprehensive studies of a relaminarizing flow at relatively high Reynolds numbers (of order $5\times 10^3$ in momentum thickness), where all the boundary layer quantities of interest are measured. In the present work, the two-layer model is revisited for these relaminarizing flows with an improved code in which the inner-layer equations for quasi-laminar theory have been solved exactly. It is shown that even for high-$Re$ flows with high acceleration, QLT provides a much superior match with the experimental results than the standard turbulent boundary layer codes. This agreement can be seen as strong support for QLT, which therefore has the potential to be used in RANS simulations along with turbulence models.