Surrogate-based design optimization for a supersonic diverterless intake

Date

2024-4-16

Author

Çalış Geboloğlu, Sanem

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The diverterless intake has been one of the latest concept due to its favorable simplicity, stealth and efficiency characteristics. This creative design replaces the diverters with a bump which eliminates the need for complex mechanical systems to manage upstream airflow. Through the use of the bump surface and cowl, the boundary layer is effectively redirected and air is compressed for the propulsion system. The diverterless intake offers significant weight saving and reduced radar cross-section (RCS), contributing to improved aerodynamic performance. In the thesis, design and optimization approach of a forebody integrated diverterless intake for a supersonic fighter aircraft is provided. Numerical methodology is validated using wind tunnel test data of the NASA aircraft X-59. Then, a baseline geometry is modelled with a bump, featuring a forward-swept asymmetrical cowling and a straight duct. Latin Hypercube sampling is used to identify different design parameters for the bump compression surface. Surrogate model is carried out by both Response Surface and Kriging model to evaluate the prediction performance with the same training and validation data. Besides, multiobjective constrained optimization is performed using Genetic Algorithm. In the optimization, intake pressure recoveries for Mach numbers of 1.5 and 1.8 are taken as objectives by keeping capture area as a constraint. At the end, the performance of the optimum design is compared with baseline under design and off design conditions. The approach aims to serve as a tool for the design of a bump compression surface and the improvement of an existent diverterless intake geometry.

Subject Keywords

Diverterless supersonic intake, Low observability, Fighter aircraft, OpenMDAO, Machine learning

URI

https://hdl.handle.net/11511/109488

Collections

Graduate School of Natural and Applied Sciences, Thesis