Assessment of Uncertainties in Modeling of Laminar to Turbulent Transition for Transonic Flows

• Published in: Flow, turbulence and combustion turbulence and combustion, 2013-07, Vol.91 (1), p.41-61
• Main Authors: Pecnik, Rene, Witteveen, Jeroen A. S., Iaccarino, Gianluca
• Format: Article
• Language: English
• Subjects: Applied fluid mechanics; Automotive Engineering; Computational fluid dynamics; Engineering; Engineering Fluid Dynamics; Engineering Thermodynamics; Exact sciences and technology; Fluid dynamics; Fluid flow; Fluid- and Aerodynamics; Fundamental areas of phenomenology (including applications); Heat and Mass Transfer; Hydraulic and pneumatic machinery; Mathematical models; Physics; Stochasticity; Transition to turbulence; Transonic flow; Turbulence; Turbulent flow; Turbulent flows, convection, and heat transfer; Uncertainty
• ISSN: 1386-6184; 1573-1987
• DOI: 10.1007/s10494-013-9453-0

The effect of physical variability and uncertainty in model correlations on laminar-turbulent transition in transonic flows is computed using two different Stochastic Collocation methods. Physical variability in the boundary conditions is first investigated for a flow over a flat plate with and without pressure gradient to quantify the uncertainties on the skin friction distribution along the plate surface. Since the laboratory conditions for the flat plate test cases are well defined and the applied transition model has been tuned for these cases, good agreement with experiments is achieved and the variability in the output is low. The second investigated cases exhibit boundary layer transition on the surface of a highly loaded turbine guide vane under transonic flow conditions. Comparisons between the predicted and measured wall heat transfer are used to quantify uncertainties in the free stream turbulence and the model correlations that accounts for compressibility effects on the onset and extension of the bypass transition. The computational results show that the uncertainties have a significant impact on the transition location for the turbine guide vane simulations and, consequently, on the reliability of the predictions for compressible flows. The output uncertainty accounts to a large extent for the difference between the deterministic simulation and the experiments. The results from the Simplex Stochastic Collocation method are computationally more efficient than those of the Stochastic Collocation based on Clenshaw–Curtis quadrature.