This work considers the aeroelastic optimization of transport wingbox structures under three different types of design variables: sizing (for example, skin thickness), shape (planform and airfoil twist/thickness), and topology/layout (rib and stringer placement). The numerical optimization is conducted with a nested bilevel method: with a nongradient-based global optimizer at the outer level (a Bayesian infill method), and a gradient-based optimizer at the inner level. Design variables are divided among the two groups based on the availability of adjoint derivatives. Results are provided in terms of a tradeoff between fuel burn reduction and structural weight reduction, with a focus on demonstrating the importance of including topology/layout variables in the optimization process. These layout variables have historically presented substantial numerical difficulties owing to their nongradient-based nature, and the results shown here are able to quantify the performance degradation (fuel burn, weight) when these layout variables are frozen.

这项工作考虑了在三种不同类型的设计变量下运输翼盒结构的气动弹性优化：尺寸（例如，蒙皮厚度）、形状（平面和翼型扭曲/厚度）和拓扑/布局（肋骨和纵梁放置）。数值优化使用嵌套双层方法进行：在外层使用基于非梯度的全局优化器（贝叶斯填充方法），在内层使用基于梯度的优化器。设计变量根据伴随导数的可用性分为两组。结果是根据减少燃料消耗和减少结构重量之间的权衡提供的，重点是证明在优化过程中包含拓扑/布局变量的重要性。