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Robust performance optimization of dual thrust rocket motor

机译:双推力火箭发动机的鲁棒性能优化

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Purpose - During any design phase; the associated process variations and uncertainties can cause the design to deviate from its expected performance. The purpose of this paper is to propose a robust design optimization (RDO) strategy for the 3D grain design of a dual thrust solid rocket motor (DTRM) under uncertainties in design parameters. Design/methodology/approach - The methodology consists of design of 3D complex grain geometry and hybrid optimization approach through genetic algorithm; globally and simulated annealing; locally considering the uncertainties in design parameters. The robustness of optimized data is measured for a worst case parameter deviation using sensitivity analysis through stochastic Monte Carlo simulation considering variance of design parameters mean. Findings - The important achievement that can be associated with this methodology is its ability also to evaluate and optimize the propulsion system performance in a complex scenario of intricate 3D geometry under uncertainty. The study shows the objective function to maximize the average thrust in dual levels could be achieved by the proposed optimization technique while satisfying constraints conditions. Also; this technique proved to be a great help in reducing the design space for optimization and increasing the computational quality. Originality/value - This is the first paper to address the dual thrust solid rocket motor grain design under uncertainties using robust design and hybrid optimization approach.
机译:目的-在任何设计阶段;相关的过程变化和不确定性可能导致设计偏离其预期性能。本文的目的是为设计参数不确定的双推力固体火箭发动机(DTRM)的3D颗粒设计提出一种鲁棒的设计优化(RDO)策略。设计/方法/方法-该方法包括3D复杂晶粒几何设计和通过遗传算法的混合优化方法;全局和模拟退火;在本地考虑设计参数的不确定性。通过考虑设计参数均值的随机蒙特卡洛模拟的敏感性分析,可以对最坏情况下的参数偏差进行测量,从而获得优化数据的鲁棒性。研究结果-这种方法可以取得的重要成就是,在复杂的3D几何形状复杂且不确定的情况下,它还能够评估和优化推进系统的性能。研究表明,在满足约束条件的情况下,通过所提出的优化技术可以实现使双水平平均推力最大化的目标函数。也;事实证明,这项技术对减少优化设计空间和提高计算质量有很大帮助。原创性/价值-这是第一篇使用稳健设计和混合优化方法解决不确定性下双推力固体火箭发动机颗粒设计的论文。

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