Amir Mittelman, Ingo Jahn, Rowan Gollan
DOI Number: N/A
Conference number: HiSST-2025-159
Hypersonic scramjet-powered vehicles offer the potential for increasing operational flexibility while reducing launch costs. However, the marginal design space stemming from the extreme hypersonic flight conditions results in a highly coupled and constrained vehicle design space. A gradient-based MDAO framework is suggested to address such cross-coupled design problems and efficiently explore the design space. Prior research demonstrated the successful integration of several Python packages, for geometrical representation, aerodynamics evaluation, and an optimal control solver, into an optimization framework that can perform simultaneous shape and trajectory optimizations for an unpowered hypersonic vehicle (i.e., hypersonic glider). In the current work, a scramjet performance analysis package was developed and successfully integrated with the above-mentioned design tools. The research focuses on developing computationally tractable design and optimization methods for scramjet-powered hypersonic accelerators. Expected results will include demonstrating the feasibility of solving a large-scale (large number of design variables) design optimization problem for such configurations. Additionally, the scope of the optimization problem that needs to be solved will be investigated, i.e., single-point (vehicle) and system-level (vehicle and trajectory) optimizations, and the importance of including trajectory simulation in the optimization sequence will be presented.