Bayesian design optimization of a BLI propulsion fan with regenerative air brake for electric passenger aircraft

In our previous work, we conducted an optimal design of a propulsion fan considering regenerative air braking and found that high-efficiency performance tends to be obtained when both regenerative and propulsion are in the high tip speed ratio. An effective means of achieving a high tip speed ratio is the use of Boundary Layer Injection (BLI), in which the slow velocity boundary layer is directly sucked in by the fan. Therefore, this study focuses on a regenerative airbrake using a BLI propulsion fan with a non-variable angle of attack for electric aircraft. The objective is to realize a fan shape with high efficiency during propulsion and regeneration with BLI at different rotation speeds and to find its characteristics. To realize the fan shape, it is necessary to conduct a global exploration of multivariable problems. But it is not realistic to conduct many costly evaluations, such as CFD. Therefore, Bayesian optimization is used as an efficient and global optimization method using approximate functions, and an attempt is made to find a fan shape with high performance in both efficiencies. The relationship between each efficiency and fan shape is then visually analyzed using self-organizing maps. As a result, we will find a fan shape that exhibits positive efficiency in both cases and shows aerodynamically appropriate shape characteristics for a BLI propulsion fan with regenerative air brake function. The results will lead to a reduction in total power consumption per flight in the future as electric fan engines.