The Grey-Area Improved \(\sigma \)-DDES Approach: Formulation Review and Application to Complex Test Cases

  • Marian FuchsEmail author
  • Charles Mockett
  • Jörn Sesterhenn
  • Frank Thiele
Conference paper
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 143)


The paper presents a formulation review and recent results for a non-zonal enhanced DES variant called \(\sigma \)-DDES [9], which seeks to address the issue of delayed transition from RANS to LES in free shear layers (also known as the grey-area problem) frequently experienced for standard delayed DES [13]. The two-part approach is based on modifying the LES behaviour of DES (the new model now behaves similar to the \(\sigma \) LES model of Nicoud et al. [10]) as well as using a more elaborate LES filter width formulation. Combining both means delivers an enhanced behaviour in the crucial early shear layer region. First, the derivation of the approach based on two popular RANS models (i.e. Spalart-Allmaras and Menter SST) is discussed. Subsequently, recent OpenFOAM results from different test cases are presented, such as pressure-induced separation from a 2D hump, a generic car flow and aeroacoustic results for a rudimentary landing gear (RLG). The \(\sigma \)-DDES variant is seen to deliver a more consistent flow prediction with varying grid resolution and topology independent of the applied RANS background model, and could also be established as a viable turbulence modelling approach for aeroacoustics prediction at low Mach numbers.


DES Grey-area problem Complex applications 



The development of the \(\sigma \)-DDES model was partially funded by the EU FP7 project “Go4Hybrid” (ACP3-GA-2013-60536-Go4Hybrid). The contributions of the two TU-Berlin students Denes Fischer (simulation of RLG on structured/polyhedral grids) and Louis Fliessbach (simulation of RLG on hex-dominant grid) are gratefully acknowledged. The structured grid for the 2D hump test case was generated by NTS (New Technologies and Services, St. Petersburg/Russia).


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Marian Fuchs
    • 1
    Email author
  • Charles Mockett
    • 2
  • Jörn Sesterhenn
    • 1
  • Frank Thiele
    • 1
  1. 1.Department of Computational Fluid DynamicsTechnische Universität Berlin, ISTABerlinGermany
  2. 2.Upstream CFD GmbHBerlinGermany

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