This paper presents the multi-objective optimisation of the MH114 high-lift airfoil. We seek the set of Pareto optimal solutions that maximise the airfoil lift and minimise the drag. The lift and drag forces are considered uncertain due to geometrical uncertainties. The uncertainty quantification of the probabilistic aerodynamic force values requires a large number of samples. However, the prediction of the aerodynamic forces is expensive due to the numerical solution of the Navier–Stokes equations. Therefore, a multi-fidelity surrogate assisted approach is employed to combine expensive RANS simulations with cheap potential flow calculations. The multi-fidelity surrogate-based approach allows us to economically optimise the aerodynamic design of the airfoil under uncertainty.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-Objective Design Optimisation of an Airfoil with Geometrical Uncertainties Leveraging Multi-Fidelity Gaussian Process Regression


    Additional title:

    Space Technol.Proceedings



    Conference:

    International Conference on Uncertainty Quantification & Optimisation ; 2020 ; Brussels, Belgium November 17, 2020 - November 20, 2020



    Publication date :

    2021-07-16


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    Gaussian Process Regression for Bayesian Fusion of Multi-Fidelity Information Sources

    Ghoreishi, Seyede Fatemeh / Allaire, Douglas L. | AIAA | 2018


    Multi-objective Optimal Airfoil Design

    Sun, Jian-Qiao / Xiong, Fu-Rui / Schütze, Oliver et al. | Springer Verlag | 2018


    Interactive Visualisation of Multi-Fidelity Design Optimisation

    Pullan, Graham / Kotnik, Aljaz / Meyer, Marcus | TIBKAT | 2023


    Interactive Visualisation of Multi-Fidelity Design Optimisation

    Pullan, Graham / Kotnik, Aljaz / Meyer, Marcus | AIAA | 2023