4.7 Article

Eddy resolving simulations in aerospace - Invited paper (Numerical Fluid 2014)

Journal

APPLIED MATHEMATICS AND COMPUTATION
Volume 272, Issue -, Pages 582-592

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2015.02.018

Keywords

LES; DES; Turbulence; Aerospace; Numerical methods

Funding

  1. Rolls-Rolls plc
  2. UK Engineering and Physical Sciences Research Council (EPSRC)
  3. EPSRC [EP/L000261/1, EP/I017771/1, EP/I010440/1, EP/I017747/1, EP/H001395/1, EP/G027632/]
  4. Engineering and Physical Sciences Research Council [EP/L000261/1, EP/H001395/1, EP/I017771/1, EP/I017747/1, EP/I010440/1] Funding Source: researchfish

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The future use of eddy resolving simulations (ERS) such as Large Eddy Simulation (LES), Direct Numerical Simulation (DNS) and related approaches in aerospace is explored. The turbulence modeling requirements with respect to aeroengines and aircraft is contrasted. For the latter, higher Reynolds numbers are more prevalent and this especially gives rise to the need for the hybridization of ERS methods with Reynolds Averaged Navier-Stokes (RANS) approaches. Zones where future use of pure ERS methods is now possible and those where hybridizations with RANS will be needed is outlined. The major focus is the aeroengine for which the component scales are much smaller. This gives rise to generally more benign Reynolds numbers. The use of eddy resolving methods in a wide range of zones in an aeroengine is discussed and the potential benefits and also cost drawbacks with such approaches noted. The tension when using such computationally intensive calculations in an area where the coupling of components and even the airframe and engine is becoming increasingly important is explored. Also, the numerical methods and meshing requirements are considered and the implications of ERS methods for future numerical algorithms. It is postulated that such simulations are ready now for niche uses in industry. However, to perform the scale of simulations that industry requires, to meet pressing environmental needs, challenges remain. For example, there is the need to develop optimal numerical methods that both map to the accuracy requirements for ERS and also future computer architectures. (C) 2015 The Authors. Published by Elsevier Inc.

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