Optimization of the reefed parachute using genetic algorithm

Abstract

Purpose The purpose of this paper is to find optimal reef parameters to minimize the maximum instantaneous opening load for a reefed parachute with geometry and environmental parameters given in the model. Design/methodology/approach The dynamic model Drop Test Vehicle Simulation (DTVSim) is used to model the inflation and descent of the reefed parachute system. It is solved by the fourth-order Runge–Kutta method, and the opening load values are thereby obtained. A parallel genetic algorithm (GA) code is developed to optimize the reefed parachute. A penalty scheme is used to have the maximum dynamic pressure restricted within a certain range. Findings The simulation results from DTVSim fit well with experimental data from drop tests, showing that the simulator has high accuracy. The one-stage and two-stage reefed parachute systems are optimized by GA and their maximum opening loads are decreased by 43 and 25 per cent, respectively. With the optimal reef parameters, two of the peaks in the opening load curve are almost equal. The velocity, loiter time and flight path angle of the parachute system all change, but these changes have no negative effect on the parachute’s operational performance. Originality/value An optimization method for reefed parachute design is proposed for the first time. This methodology can be used in the preliminary design phase for a reefed parachute system and significantly improve design efficiency.

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“…Therefore, Equation (17) can be represented as Equation (18) after considering the values of data in this study. Next, the linear equality is set for weightage ratio between investment of asset A, B and C. Therefore, linear equality is represented by using Equation (19). The total of investment in all of three assets is represented as 1. the weightage of investment ratio for each asset can take value from 0 until 1.…”

“…………..…………………..…… (19). Then, the lower bound and upper bound is set for weightage ratio between investments of asset A, B and C. Lower bound of assets…”

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