Multi-Phase Trajectory Optimisation for Access-to-Space with RBCC-Powered TSTO via Surrogated-Assisted Hybrid Evolutionary Algorithms Incorporating Pseudo-Spectral Methods

A multi-objective design optimization study has been conducted for two-stage to orbit (TSTO) system with a rocket-based combined cycle (RBCC) comprising airbreathing components besides rocket engines, aiming to examine its feasibility to achieve efficient access to space, particularly to the International Space Station. The optimization has been performed by coupling evolutionary algorithms and trajectory optimization via pseudo-spectral methods with respect to three important design criteria, that is, the maximization of the velocity, altitude, and mass at the terminus of the orbiter trajectory under certain constraints. The results highlight complex interactions of numerous design parameters and a counteractive trend between the final velocity and mass has been revealed. Detailed investigation and sensitivity analysis have identified key design parameters and intricate behavior of the vehicle performance and trajectories due to highly nonlinear aerodynamic and thrust characteristics. Overall this research provides useful insights into the technological requirements to fulfill the desired mission with the vehicle and propulsion configurations considered here.