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      https://www.ias.ac.in/article/fulltext/sadh/045/0241

    • Keywords

       

      Multidisciplinary design optimization (MDO); multiobjective multidisciplinary design optimization (M2DO); stage recovery; parachute cluster; solid motor grain design; three degrees of freedom (3- DOF) trajectory simulations; multi-objective evolutionary algorithm (MOEA); A2-MOEA.

    • Abstract

       

      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 highthrust to decelerate the launch vehicle stage to a near-zero descent rate at touchdown. A Multiobjective Multidisciplinary Design Optimization (M2DO) problem has been formulated to minimize the mass of the decelerationsystem 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-objectiveEvolutionary Algorithm (A2-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

    • Author Affiliations

       

      PANKAJ PRIYADARSHI1 LEYA JOSEPH KAMAL SAROHA

      1. Vikram Sarabhai Space Centre, Trivandrum 695022, India
    • Dates

       
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