Development of transitional Reynolds number correlation and assessment of RANS for predictions of bypass transition

TL;DR

This paper develops a new correlation for predicting bypass transition Reynolds number using DNS data and assesses the performance of RANS models in transitional flow predictions, highlighting their sensitivities.

Contribution

It introduces a novel intermittency-based transition correlation and evaluates RANS model accuracy during bypass transition.

Findings

The new intermittency correlation predicts transition Reynolds number within 10.8% error.

RANS simulations are sensitive to inlet turbulence length scale.

RANS overpredicts or underpredicts flow scale growth depending on turbulence levels.

Abstract

We present direct numerical simulations (DNSs) of bypass transition over a flat plate with inlet freestream turbulence intensity levels of 0.75%, 1.5%, 2.25%, 3.0%, and 6.0%, respectively. A new definition of the transition intermittency is proposed based on the mean skin friction. Based on these, we develop an intermittency correlation to predict flow transition. The proposed model is consistent with the classical correlation of Abu-Ghannam and Shaw and reasonably predicts transition Reynolds number (within 10.8% error) for the experiments of Fransson & Shahinfar (2020). Accompanying Reynolds-averaged Navier-Stokes (RANS) simulations for our DNS cases simulations are performed. The RANS results are sensitive to the specification of the inlet turbulence length scale and overpredict (underpredict) the growth of the integral flow scales across the boundary layer during transitional stages when the inlet freestream turbulence is low (high), respectively.