227
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

Use of DES in mildly separated internal flow: dimples in a turbulent channel

, &
Pages 1180-1203 | Received 13 Mar 2017, Accepted 11 Aug 2017, Published online: 07 Sep 2017
 

ABSTRACT

Detached eddy simulation (DES) is investigated as a means to study an array of shallow dimples with depth to diameter ratios of 1.5% and 5% in a turbulent channel. The DES captures large-scale flow features relatively well, but is unable to predict skin friction accurately due to flow modelling near the wall. The current work instead relies on the accuracy of DES to predict large-scale flow features, as well as its well-documented reliability in predicting flow separation regions to support the proposed mechanism that dimples reduce drag by introducing spanwise flow components near the wall through the addition of streamwise vorticity. Profiles of the turbulent energy budget show the stabilising effect of the dimples on the flow. The presence of flow separation however modulates the net drag reduction. Increasing the Reynolds number can reduce the size of the separated region and experiments show that this increases the overall drag reduction.

Acknowledgment

This work has been gratefully supported by a research contract from Airbus Operations Ltd.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Airbus Operations Ltd.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 146.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.