Multiobjective Optimization of Stress-Release Boot of Solid Rocket Motor under Vertical Storage Based on RBF Model. (21st July 2022)

• Record Type: Journal Article
• Authors: Miao, Qiuwen; Zhang, Huihui; Shen, Zhibin; Zhou, Weiyong
• Other Names: Li Jun-Wei Academic Editor.
• Is Part Of: International journal of aerospace engineering. Volume 2022(2022)
• Publication Date: 2022-07-21
• Subjects: Aerospace engineering -- Periodicals; 629.105
• DOI: 10.1155/2022/8475281
• Languages: English
• ISSNs: 1687-5966

Abstract

Abstract : Stress-release boot can effectively improve the structural integrity of SRM (solid rocket motor), but it will also influence the loading fraction and interior ballistic performance, so the purpose of this paper is to propose a multiobjective optimization method for stress-release boot. The design variables are the front and rear depth of the stress-release boot, and four optimization variables were determined according to the analysis of SRM performance. To optimize a SRM with star and finocyl grain, the RBF (radial basis functions) model that satisfies the accuracy requirements was established based on parametric modeling technology and the OPLHS (Optimal Latin Hypercube Sampling) method. Subsequently, the Pareto front was obtained based on the NCGA-II algorithm. And an optimal solution was obtained based on the evolutionary algorithm and weighted method. Compared with the initial SRM, the maximum Von Mises strain of the grain, the maximum principal stress of the insulator/cladding interface, the maximum axial displacement, and the volume increment decreased by 19.92%, 35.33%, 4.80%, and 4.42%, respectively. The optimization design method proposed in this paper has significant advantages in computational efficiency for the optimization of SRM and can take into account various performances of SRM, which not only is suitable for the optimization design of stress-release boot but also provides guidance for the optimization design of other shape parameters of SRM.