Support Vector Regression-driven Multidisciplinary Design Optimization for Multi-Stage Space Launch Vehicle Considering Throttling Effect

Abstract

The design of new Space Launch Vehicle (SLV) involves a full set of disciplines – propulsion, structural sizing, aerodynamics, mission analysis, flight control, stages layout – with strong interaction between each other. The optimal design of launch vehicles based on liquid rocket engines is critically dependent on ascent trajectories and thrust throttling. Recently many authors have incorporated trajectory optimization at conceptual design level but still have not gauged the potential of using thrust throttling at conceptual design phase. Since multidisciplinary design optimization of multistage launch vehicles is a complex and computationally expensive, an efficient Least Square Support Vector Regression (LS-SVR) technique is used to approximate the current problem. In this study we proposed not only the trajectory optimization but also the thrust throttling at the conceptual design phase. The whole problem with 26 parameters, linked to, the architecture and the command (trajectory optimization), 8 constraints - is solved using well known population based Genetic Algorithm as optimizer. The objective is to find minimum gross take-off mass, optimal trajectory and thrust throttling profile for liquid fueled space launch vehicle (SLV). The improvement in system design using thrust throttling with metamodeling for Space Launch Vehicle is studied in detail.