Publication Date


Document Type


Committee Members

Dean Eklund (Committee Member), Mark Hagenmaier (Other), Scott Thomas (Committee Member), Mitch Wolff (Advisor)

Degree Name

Master of Science in Mechanical Engineering (MSME)


Various aspects of hypersonic vehicles are being rapidly explored for improved functionality. One of the main areas of consideration is the fueling of a Supersonic Combusting Ramjet (scramjet) engine. Using Computational Fluid Dynamics (CFD), computer simulations can be performed to analyze the flow physics of a scramjet. In this research, an optimization code, Dakota, is integrated with the CFD to optimize a set of parameters to maximum thrust. In this study, the fuel injection and combustion is replaced with heat sources. This simplification greatly reduces the computational requirements. Additionally, the 3D geometry is reduced to an axisymmetric 2D geometry because three dimension effects like mixing and combustion are not being modeled. With this simplified model, the optimization and CFD algorithm is executed to find the heat addition for maximum thrust. Different optimization methods have been explored to reduce computational times. A genetic algorithm was selected because of its robust abilities. Additionally, a sampling algorithm was selected because of its abilities to explore the whole design space. Furthermore, the sampling method enables additional studies, such as sensitivity studies, to be completed. In addition to optimization studies, calibration studies are performed to obtain the heat source values that correspond to a given experimental wall pressure distribution. Knowledge of the optimized heat distribution will assist in the optimization of fueling splits and injector locations for a more detailed combustion investigation in which similar optimization techniques can be applied.

Page Count


Department or Program

Department of Mechanical and Materials Engineering

Year Degree Awarded


Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.