Amir MITTELMAN, Kieran MACKLE, Ingo JAHN, Rowan GOLLAN
DOI Number: 10.60853/bpzq-f253
Conference number: HiSST-2024-00323
Scramjet-propelled hypersonic vehicles hold vast promise in improving operational flexibility while reducing the cost of access to space launch systems. However, the design and optimization process of such vehicles suffers from the highly coupled nature of their components. To address such cross-coupled design problems and to efficiently explore the design space, a co-design gradient-based Multi-Disciplinary Analysis and Optimization (MDAO) framework is suggested. The co-design architecture enables nested optimization loops to control vehicle and trajectory design variables, and a gradient-based approach ensures computational tractability. The key components of the framework are the HyperVehicle package for geometrical representation, PySAGAS for aerodynamics, and an Optimal Control Problem (OCP) solver using CasADi for sensitivity analysis. Initial ongoing research demonstrated the successful integration of the above-mentioned design tools for an unpowered hypersonic vehicle, paving the way for the proposed research which will focus on the design and optimization methods of a scramjet-propelled hypersonic accelerator. A quasi-1D cycle analysis tool for scramjet engine characteristics will be integrated into the existing framework, as well as changes in the geometrical and aerodynamic analysis tools necessary for the inclusion of the engine. Expected results will include demonstrating the feasibility of solving a large-scale (large number of design variables) design optimization problem for a scramjet-propelled hypersonic vehicle. Additionally, the scope of the optimization problem that needs to be solved will be investigated, i.e., physical (vehicle) and combined (vehicle and trajectory) class optimizations, and the importance of including trajectory planning in the optimization sequence will be presented.