A discrete adjoint full potential formulation for fast aerostructural optimization in preliminary aircraft design

Abstract

Preliminary aircraft design is often carried out with the help of multidisciplinary optimization processes. Because there is a strong coupling between the flow and the structure of the aircraft, and because new composite materials have a unique capability of being designed for anisotropic directional stiffness and strength, these processes must model the aeroelastic behavior of the aircraft in order to be effective. Since many design variables are involved during the preliminary design stage, the optimization problems, formulated using high or medium fidelity models, can be solved using the adjoint method. Moreover, the level of fidelity of the fluid model and the associated simulation technique must also be selected with care, as they tend to be the main contributors to the computational cost. The novel contribution of the present work is twofold. Firstly, the discretized gradients of the full potential flow equation, which is a medium-fidelity model, are derived analytically so that they can be used in adjoint optimization problems. Moreover, the full potential flow solution and the computation of the gradients are implemented in an open-source and readily available finite element code. Secondly, aerodynamic shape and aerostructural optimization calculations are carried out on example wings to demonstrate the effectiveness and the computational efficiency of the proposed method. Overall, the results show that the newly implemented discrete adjoint nonlinear potential flow formulation is able to quickly optimize both the shape and the structural parameters of a typical wing. More specifically, the twist distribution along the wingspan is adapted to reduce the induced drag, the airfoils become more supercritical so that the shock strength and the associated wave drag are reduced, and the thickness of the structural elements is tailored to the loads to reduce the internal stresses. The present methodology is therefore able to deliver results at a low computational cost which are sufficiently accurate for the early design stages. Furthermore, the results obtained using the proposed methodology could be used as a starting point for the optimization calculations performed in later design stages.