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Development of advanced models for transition to turbulence in hypersonic flows and prediction of transition under uncertainties

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Keywords
  • Engineering
  • Computing & Technology :: Aerospace & Aeronautics Engineering [C01]
  • Ingénierie
  • Informatique & Technologie :: Ingénierie Aérospatiale [C01]
Disciplines
  • Design
  • Mathematics

Abstract

Fluid Research Group Development of advanced models for transition to turbulence in hypersonic flows – Prediction of transition under uncertainties Meeting, 25th October 2010 4th SYMPOSIUM OF VKI PHD RESEARCH Development of advanced models for transition to turbulence in hypersonic flows Prediction of transition under uncertainties March 5th , 2013 Gennaro Serino Aeronautics and Aerospace Department Supervisors : Thierry E. Magin & Patrick Rambaud Promoter : Vincent Terrapon University of Liége Aeronautics and Aerospace Department Atmospheric reentry high speed & potential energy converted into heat Space vehicles need heat shields (TPS) Turbulent heat rates several times higher than in the laminar regime Safety margins are necessary for the design of the TPS Quantify the margins for a less conservative design MSL CFD in reentry conditionsMars Exploration Rover (MER) MSL Mach 10, α = 16-deg Data and Comparisons from AEDC Tunnel 9 Steven P. Schneider. Hypersonic laminar- turbulent transition on circular cones and scramjet forebodies., 2004. Transition prediction – The State of the Art • Experiments : empirical criteria and correlation (Shuttle, Van Driest) – Good : successfully used (Apollo, Shuttle); – Bad : expensive, limited in time and no real operating conditions (Re, Ma); • CFD : Transition models ( Menter, Goldberg, R-γ ) – Good : fast , design; – Bad : simplified physics, very sensitive to free stream conditions (Re, Ma, Tu); NUM EXP Footprint of the wakeRoughness G.Serino, F.Pinna, P.Rambaud, “ Numerical computations of hypersonic boundary layer roughness induced transition on a flat plate ”, 2012 Flow direction Flat plate Transition Transition prediction – What we propose • Introduce Uncertainty Quantification (UQ) in deterministic simulations for transition prediction to : – Take into account the physical variability of the system to simulate – Transition is a stochastic process – Impr

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