Optimal two-stage parachute and retro motor sizing for launch vehicle stage recovery

• Published in: Sadhana (Bangalore) Vol. 45; no. 1
• Main Authors: Priyadarshi, Pankaj, Joseph, Leya, Saroha, Kamal
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.12.2020; Springer Nature B.V
• Subjects: Clusters; Deceleration; Degrees of freedom; Design optimization; Engineering; Evolutionary algorithms; Grain design; High thrust; Initial conditions; Launch vehicles; Multidisciplinary design optimization; Multiple objective analysis; Parachutes; Pareto optimization; Pareto optimum; Recovery; Rockets; Spacecraft components; Thrusters; A; parachute cluster; Multidisciplinary design optimization (MDO); multi-objective evolutionary algorithm (MOEA); MOEA; DO; stage recovery; solid motor grain design; multiobjective multidisciplinary design optimization (M; three degrees of freedom (3-DOF) trajectory simulations
• ISSN: 0256-2499; 0973-7677
• DOI: 10.1007/s12046-020-01420-3

A deceleration system consisting of staged parachute clusters and retro thrusters is optimized for the recovery of the first stage of a launch vehicle on sea. Optimal mass as well as reduction in speed by each parachute cluster and the retro thrusters is essential to minimize the inherent payload loss due to inclusion of additional systems. Three disciplines are involved in the study, namely parachute design, grain design and Three Degrees of Freedom (3-DOF) trajectory simulations. Parachute components are sized and their masses are estimated using a parachute design code. It computes the number of parachutes in the cluster, their sizes and opening loads for multiple reefing stages. Solid motor grain design is carried out, using high burn rate propellant, to provide high thrust to decelerate the launch vehicle stage to a near-zero descent rate at touchdown. A Multiobjective Multidisciplinary Design Optimization ( M 2 DO) problem has been formulated to minimize the mass of the deceleration system and minimize the touchdown speed of the recovered stage, subject to constraints on Maximum Expected Operating Pressure (MEOP), feasibility, etc. The optimization is carried out and the Pareto optimal front is obtained using an in-house multi-objective optimization algorithm, Attractor Anchored Multi-objective Evolutionary Algorithm (A 2 -MOEA). A total of twenty-five design variables are considered including initial conditions for each deceleration stage, size of parachute cluster components for both drogue and main parachutes, and the size and shape of the solid motor grain for retro rockets. It is seen that the two objectives are conflicting. The Pareto optimal designs are discussed and the variation of design variables is presented.