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Predictive LES of aircraft icing aerodynamics

ORAL

Abstract

Predicting the aerodynamic performance of an aircraft in icing conditions is critical as failures in an aircraft’s ice protection system can compromise flight safety. Aerodynamic effects of icing have typically relied on RANS modeling, which usually struggles to predict stall behavior, including those induced by surface roughness. Encouraged by recent studies using LES that demonstrate the ability to predict stall characteristics on full aircraft with smooth wings at an affordable cost (Goc et al. FLOW, 2021), this study seeks to apply this methodology to icing conditions. Measurements of lift, drag, and pitching moments of a NACA23012 airfoil under clean and iced conditions are collected at Re = 1.8M. Preliminary results for the clean airfoil are completed and predict the correct stall angle and max lift coefficient. Using laser scanned, detailed representations of the icing geometries, LES calculations are conducted to compare integrated loads against experimental measurements in both clean and iced conditions at various angles of attack through the onset of stall (Broeren et al., Journal of Aircraft 2018).

Presenters

  • Brett Bornhoft

    Center for Turbulence Research, Stanford University

Authors

  • Brett Bornhoft

    Center for Turbulence Research, Stanford University

  • Suhas S Jain

    Center for Turbulence Research, Stanford University, Center for Turbulence Research, Center for Turbulence Research, Stanford University, CA, USA

  • Konrad Goc

    Stanford University, Center for Turbulence Research, Stanford University

  • Sanjeeb T Bose

    Stanford University, Cascade Technologies, Center for Turbulence Research, Stanford University, Stanford University

  • Parviz Moin

    Center for Turbulence Research, Stanford University, Stanford University, Stanford Univ