Multi-Fidelity Predictions for Control Allocation on the NASA Ikhana Research Aircraft to Minimize Drag
Date of Award:
Master of Science (MS)
Mechanical and Aerospace Engineering
Douglas F. Hunsaker
Douglas F. Hunsaker
Stephen A. Whitmore
Optimal control settings (camber scheduling) can be used by aircraft to minimize drag at various operating conditions during flight. In this work, camber schedules for minimum drag on the NASA Ikhana are obtained over a range of lift coefficients. A modern numerical lifting-line algorithm is used to predict the lift and drag of the aircraft as a function of operating condition and wing section shape (airfoil camber). The SLSQP optimization algorithm is used to solve for the camber schedule that minimizes drag for a given operating condition. The process is repeated, varying the number of control sections to evaluate the benefit of additional control sections in minimizing drag on the aircraft. Results show that there are diminishing returns with increased numbers of control sections. For the NASA Ikhana, the limit on the number of control sections added before diminishing results were obtained was found to be 2 control sections. With 2 control sections the NASA Ikhana achieved between a 4.5% and 26.3% reduction in drag for lift coefficients between 0.1−0.9 when compared to the baseline Ikhana with no control sections. Adding an additional 2 control sections reduced the drag by less than 0.75%. Results from the optimization can be used in flight algorithms to schedule camber during flight such that drag and fuel burn are minimized. Results can also be used to inform the design of future aircraft with distributed control surfaces, especially in the growing small unmanned aerial vehicle (UAV) market where many designs are aerodynamically less efficient than commercial and research aircraft, such as the NASA Ikhana.
Schoenfeld, Justice T., "Multi-Fidelity Predictions for Control Allocation on the NASA Ikhana Research Aircraft to Minimize Drag" (2022). All Graduate Theses and Dissertations. 8662.
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