Multi-fidelity surrogate model-based airfoil optimization at a transitional low Reynolds number

The aerodynamic design optimization of an airfoil is carried out at a transitional low Reynolds number in the framework of multi-fidelity surrogate modeling. Two multi-fidelity surrogate-based optimization methodologies are proposed. The first method involves the co-Kriging surrogate model with prediction-based high-fidelity model update strategy. The second method uses the Kriging model of the low-fidelity function, and subsequent co-Kriging modeling with high-fidelity infills done using the gradient-free trust-region approach. The high-fidelity solutions are obtained by solving the Reynolds-averaged Navier-Stokes equations with the flow transition modeled by the gamma-Re-theta model. The low-fidelity solutions are obtained by a panel code in conjunction with the e(N) method. The proposed optimization methodologies are applied to two different objective functions in the transitional low Reynolds number regime, namely, (i) maximization of lift coefficient, and (ii) maximization of endurance factor. Significant improvements in each of the objective functions are obtained using both these methodologies.