This work proposes a new topology optimization formulation to subsonic compressible flows. Compressible flows can be seen in many aerodynamic problems and optimization techniques can be used to improve designs of wings, diffusers, and other applications. In this work, the compressible Navier-Stokes equations are used coupled with a density-based material model. The effects of the material model are shown for both the momentum and energy equations. Two objective functions are considered, the entropy variation in a control volume and the entropy generation. The algorithm is implemented by a finite element model to solve the state equations. The pyadjoint libraries are used to perform the automatic sensitivity derivation and an internal point optimizer is used to update the design variable. The algorithm is evaluated by performing the optimization of 2D domains and a 3D diffuser. The results show optimized designs with reduced entropy generation.

这项工作为亚音速可压缩流动提出了一种新的拓扑优化公式。在许多空气动力学问题中都可以看到可压缩流动，优化技术可用于改进机翼、扩散器和其他应用的设计。在这项工作中，可压缩 Navier-Stokes 方程与基于密度的材料模型结合使用。材料模型对动量和能量方程的影响均显示出来。考虑了两个目标函数，控制体积中的熵变化和熵生成。该算法是通过有限元模型实现的，以求解状态方程。pyadjoint 库用于执行自动灵敏度推导，内部点优化器用于更新设计变量。该算法通过执行 2D 域和 3D 漫射器的优化来评估。结果显示了熵生成减少的优化设计。