A single-stage launch vehicle with hybrid rocket engine, which uses solid fuel and liquid oxidizer, has been being studied and developed as a next-generation rocket for scientific observation due to the advantages as low cost, safety, re-ignition, and reduced pollution. Therefore, the knowledge regarding hybrid rocket system has been being gained through the forepart of the conceptual design using design informatics. In the present study, the practical problem defined by using three objective functions and seven design variables for aurora observation is treated so as to contribute the real world using evolutionary computation and data mining for the field of aerospace engineering. The primary objective of the design in the present study is that the down range and the duration time in the lower thermosphere are sufficiently obtained for the aurora scientific observation, whereas the initial gross weight is held down. Investigated solid fuels are five, while liquid oxidizer is considered as liquid oxygen. The condition of single-time ignition is assumed in flight sequence in order to quantitatively investigate the ascendancy of multi-time ignition. A hybrid evolutionary computation between the differential evolution and the genetic algorithm is employed for the multidisciplinary design optimization. A self-organizing map is used for the data mining technique in order to extract global design information. Consequently, the design information regarding the tradeoffs among the objective functions, the behaviors of the design variables in the design space to become the nondominated solutions, and the implication of the design variables for the objective functions have been obtained in order to quantitatively differentiate the advantage of hybrid rocket engine in view of the five fuels. Moreover, the next assignments were also revealed.
