Yang, X and Tucker, PG (2016) *Assessment of turbulence model performance: Severe acceleration with large integral length scales.* Computers and Fluids, 126. pp. 181-191. ISSN 0045-7930

## Abstract

© 2015 The Authors. Turbulence is substantially laminarised, when the mean flow experiences streamwise acceleration above a certain critical acceleration parameter. Recently, to essentially reveal aero engine intake acceleration scenarios, Direct Numerical Simulations (DNS) have been performed for turbulent flow through a rapidly contracting channel. On average, the streamwise acceleration parameter K s is of the magnitude of 1×10 -5 . Converged statistics show that it is the streamwise acceleration that causes the first term of the production rate for u'u' to be negative. This initiates the degeneration towards laminar flow and also closes the usual wall turbulence self-sustaining mechanism. Further downstream, the progressive turbulence recovery is largely streamwise dominant. Importantly, the laminarisation effects are lagging to the rate of contraction. To assess the corresponding turbulence model performance and for better modelling, for the same flow configurations, Reynolds-averaged Navier-Stokes (RANS) predictions are compared, using some available Reynolds-stress (RSM) and eddy-viscosity models. These are the second-order closure with the strain-ω formulation, the standard k-ω and the Menter's shear-stress transport (SST) models, the standard Spalart-Allmaras (S-A) model, and that with the strain-vorticity correction. As will be shown, through the contraction, all the benchmarked models are able to predict the essential characteristics of the laminarisation; whereas, further downstream, the eddy-viscosity models tend to return the flow immediately back to the fully developed turbulence. In contrast, the RSM predicts the gradually recovery process, in spite of the lower growth rate, relative to that of the DNS. The S-A model has been modified for the lagging mechanism caused by severe acceleration. The corresponding modified predictions better match the mean flow characteristics. Moreover, all models would also benefit from sensitisation to the impact of the large integral length scales.

Item Type: | Article |
---|---|

Subjects: | UNSPECIFIED |

Divisions: | Div A > Fluid Mechanics |

Depositing User: | Cron Job |

Date Deposited: | 17 Jul 2017 19:29 |

Last Modified: | 19 Jun 2018 02:02 |

DOI: |