Comparison of drag prediction using RANS models and DDES for the DLR-F6 configuration using high order schemes

Jiaye Gan, Yiqing Shen, GeCheng Zha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper compares the accuracy and robustness of steady state RANS, unsteady RANS, and DDES turbulence models with high order schemes for predicting the drag of the DLR-F6 configuration. The implicit time marching method with unfactored Gauss-Seidel line relaxation is used with a 5th order WENO finite difference scheme for Navier-Stokes equations. The viscous terms are discretized using a 4th order conservative central differencing. The effect of grid size on the accuracy of drag prediction by using the different turbulent models are conducted on the coarse, medium and fine mesh models at the same angle of attack. The coarse mesh has about 10 drag counts deviation from the experiment, the medium mesh has 28 counts, and the fine mesh has about 15 counts difference. The RANS method achieves almost the same results as URANS and DDES at angle of attack of 0.49◦. The DDES have the least deviation from the experimental drag result and the closest pressure distribution to the experiment in the trailing edge separation zone. However, since the DDES uses the same mesh as the RANS model in this paper, the DDES results should not be considered as conclusive. A more rigorous mesh refinement study for the DDES is in progress.

Original languageEnglish (US)
Title of host publication54th AIAA Aerospace Sciences Meeting
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624103933
StatePublished - 2016
Event54th AIAA Aerospace Sciences Meeting, 2016 - San Diego, United States
Duration: Jan 4 2016Jan 8 2016

Other

Other54th AIAA Aerospace Sciences Meeting, 2016
CountryUnited States
CitySan Diego
Period1/4/161/8/16

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ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Gan, J., Shen, Y., & Zha, G. (2016). Comparison of drag prediction using RANS models and DDES for the DLR-F6 configuration using high order schemes. In 54th AIAA Aerospace Sciences Meeting American Institute of Aeronautics and Astronautics Inc, AIAA.