Multi-disciplinary Optimization of Single-stage Hybrid Rocket with Swirl Injection for Lunar Ascent

This paper investigates the use of swirl injection in hybrid rocket engines as a means to improve the overall design of the propulsion system. To this aim, a multi-disciplinary optimization problem is formulated, with the objective to determine the optimal single-stage hybrid rocket design and ascent trajectory for a lunar ascent mission, with the objective to reach a 100 km circular orbit on the Moon equatorial plane. A zero-dimensional internal ballistics model is used to estimate the thrust, mass flow rate, and gross mass of the hybrid rocket, while a three-degree of freedom dynamical model is employed for the ascent trajectory. Lastly, an in-house heuristic algorithm that merges the commonly known particle swarm and genetic algorithms is used to solve the resulting integrated optimization problem. After a preliminary analysis on the solution’s sensitivity to the optimizer particle count, results for both axial and swirl injection configurations are presented and compared.