This contribution presents the implementation and results of a Gaussian Process regression based surrogate model for prediction of the aerodynamic drag coefficient CD of a transonic transport aircraft wing. The wing contains a hybrid laminar flow control system, alongside variable camber integration via an Adaptive Dropped Hinge Flap. The latter enters the envisaged input parameter space of the surrogate through specification of its deflection angle, alongside variations in cruise lift coefficient and altitude. The model builds upon high-fidelity computational fluid dynamics (CFD) results and aims at incorporating them into an overall aircraft design workflow. The predicted drag coefficients agree well when compared to CFD validation data, showing the model being suitable for the present application case. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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This contribution presents the implementation and results of a Gaussian Process regression based surrogate model for prediction of the aerodynamic drag coefficient CD of a transonic transport aircraft wing. The wing contains a hybrid laminar flow control system, alongside variable camber integration via an Adaptive Dropped Hinge Flap. The latter enters the envisaged input parameter space of the surrogate through specification of its deflection angle, alongside variations in cruise lift coefficie...
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