Geometry parameterization is a key challenge in shape optimization. Parameterizations must accurately capture the design intent and perform well in optimization. In multidisciplinary design optimization (MDO), the parameterization must additionally represent the shape consistently across each discipline. pyGeo is a geometry package for three-dimensional shape manipulation tailored for aerodynamic and multidisciplinary design optimization. It provides several methods for geometry parameterization, geometric constraints, and utility functions for geometry manipulation. pyGeo computes derivatives for all parameterization methods and constraints, facilitating efficient gradient-based optimization.

Electrified aircraft propulsion enables new aircraft designs with fewer emissions. One challenge of electrified architectures is handling the electrical components’ waste heat. This is because batteries and other electrical components are sensitive to high temperatures and accumulate heat within their structure. In this work, we investigate using a thermoacoustic refrigerator to cool the battery of a parallel hybrid single-aisle commercial transport aircraft. This thermoacoustic refrigeration system is powered by waste heat from the turbofan engine core, whereas a conventional refrigerator consumes electricity from the battery or shaft power offtakes. Compared to a conventional vapor cycle refrigerator, the thermoacoustic refrigeration system results in greater mission fuel burn because of pressure losses attributable to the extraction of heat from the turbofan to drive the thermoacoustic refrigerator. Heat exchangers with very low pressure losses may render the thermoacoustic refrigeration system beneficial compared to conventional refrigeration in certain use cases, such as low-altitude missions.

Aircraft are multidisciplinary systems that are challenging to design due to interactions between the subsystems. The relevant disciplines, such as aerodynamic, thermal, and propulsion systems, must be considered simultaneously using a path-dependent formulation to assess aircraft performance accurately. In this paper, we construct a coupled aero-thermal-propulsive-mission multidisciplinary model to optimize supersonic aircraft considering their path-dependent performance. This large-scale optimization problem captures non-intuitive design trades that single disciplinary models and path-independent methods cannot resolve. We present optimal flight profiles for a supersonic aircraft with and without thermal constraints. We find that the optimal flight trajectory depends on thermal system performance, showing the need to optimize considering the path-dependent multidisciplinary interactions.