Conference Paper

Large-scale Multifidelity Aerostructural Optimization of a Transport Aircraft


N. Wu, C. Mader, and J. R. R. A. Martins


33rd Congress of the International Council of the Aeronautical Sciences, 2022

High-fidelity aerostructural aircraft optimizations have become more widespread in recent years, especially when combined with the efficiencies offered by the adjoint method and gradient-based optimizers. However, it is still computationally expensive to perform such optimizations with hundreds of design variables and multiple flight conditions. In this work, we address some practical issues with large-scale aerostructural optimizations using a multifidelity approach. We perform an optimization of a notional transport aircraft analyzed over ten flight conditions, including close to 1000 design variables and 1000 constraints. We compare the result against a reference single-fidelity optimization, and show that by leveraging multiple lower-fidelity models, we can reduce the computational cost by 14%.