Efficient and Flexible Methodology for the Aerodynamic Shape Optimization of Hypersonic Vehicle Concepts in a High-Dimensional Design Space
Paper
Mackle, Kieran and Jahn, Ingo. 2024. "Efficient and Flexible Methodology for the Aerodynamic Shape Optimization of Hypersonic Vehicle Concepts in a High-Dimensional Design Space." AIAA SciTech Forum 2024. Orlando, FL, United States 08 - 12 Jan 2024 United States. https://doi.org/10.2514/6.2024-2838
| Paper/Presentation Title | Efficient and Flexible Methodology for the Aerodynamic Shape Optimization of Hypersonic Vehicle Concepts in a High-Dimensional Design Space |
|---|---|
| Presentation Type | Paper |
| Authors | Mackle, Kieran and Jahn, Ingo |
| Journal or Proceedings Title | Proceedings of AIAA SciTech Forum (2024) |
| Year | 2024 |
| Place of Publication | United States |
| Digital Object Identifier (DOI) | https://doi.org/10.2514/6.2024-2838 |
| Web Address (URL) of Paper | https://arc.aiaa.org/doi/10.2514/6.2024-2838 |
| Web Address (URL) of Conference Proceedings | https://arc.aiaa.org/doi/book/10.2514/MSCITECH24 |
| Conference/Event | AIAA SciTech Forum 2024 |
| Event Details | AIAA SciTech Forum 2024 Event Date 08 to end of 12 Jan 2024 Event Location Orlando, FL, United States |
| Abstract | Aerodynamic shape of optimization of hypersonic vehicles parameterized by a large number of design variables (e.g. more than 10) is challenging due to the high computational cost of CFD evaluations. Gradient-based optimization methods are commonly used for this reason, along with the adjoint method applied to the governing equations of the flow to provide the optimizer with a search direction. Downsides of this approach include that it requires specialized CFD solvers, highly converged CFD simulations, and it can still be costly when optimizing against multiple performance objectives. Exploration studies in a high-dimensional design space are particularly beneficial during the conceptual design phases, and thus an optimization approach that is easy to implement, flexible, and quick to run is essential. In this paper, we develop an alternative approach to obtain the search direction for gradient-based aerodynamic shape optimization. The proposed approach is efficient, scalable, and CFD solver-agnostic. An approximate Jacobian is obtained by applying lower order aerodynamic models (such as Piston theory or Van Dyke’s second order theory) locally, thus allowing pressure sensitivities to design parameters to be calculated without the need for further costly CFD simulations. The accuracy of this approach is demonstrated by estimating pressure sensitivities for a canonical shape, and the results are verified by comparison to finite difference of CFD solutions. We then demonstrate the approach as a suitable means for shape optimization by optimizing a generic hypersonic waverider for maximum Lift-to-Drag ratio (L/D), whilst also respecting an internal volume constraint. Using an 8 CPU workstation, the optimized configuration (parameterized by 16 design variables) is obtained in little over 4 hours, with a 33% increase in L/D. |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 400107. Satellite, space vehicle and missile design and testing |
| Public Notes | There are no files associated with this item. |
| Byline Affiliations | University of Queensland |
| University of Southern Queensland |
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https://research.usq.edu.au/item/z8619/efficient-and-flexible-methodology-for-the-aerodynamic-shape-optimization-of-hypersonic-vehicle-concepts-in-a-high-dimensional-design-space
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