Optimization of the reefed parachute using genetic algorithm. Issue 6 (7th August 2017)

• Record Type: Journal Article
• Authors: Yang, Xue; Yu, Li; Zhao, Xiao-Shun
• Is Part Of: Engineering computations. Volume 34:Issue 6(2017)
• Page Start: 1923
• Page End: 1938
• Publication Date: 2017-08-07
• Subjects: Optimization -- Genetic algorithm -- Inflation process -- Maximum opening load -- Reefed parachute system; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-05-2016-0163
• Languages: English
• ISSNs: 0264-4401

Abstract

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.