Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Julian Quick, Ryan King, Marc Henry de Frahan, Shreyas Ananthan, Michael Sprague, Peter Hamlington

Research output: Contribution to journalArticlepeer-review


Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. The analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 angle of attack and a Reynolds number of 1.5 × 106. We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

Original languageAmerican English
Pages (from-to)85-106
Number of pages22
JournalInternational Journal for Uncertainty Quantification
Issue number1
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 by Begell House, Inc.

NREL Publication Number

  • NREL/JA-2C00-80359


  • Active subspace
  • Sensitivity analysis
  • Turbulence modeling
  • Wind energy


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