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Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight 被引量:4

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight
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摘要 Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO) and uncertainty-based design optimization (UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS) and Kriging-based Taylor series approximation (KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles. Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO) and uncertainty-based design optimization (UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS) and Kriging-based Taylor series approximation (KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.
出处 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2015年第3期676-686,共11页 中国航空学报(英文版)
基金 supported by the National Natural Science Foundation of China(No.51305014) China Postdoctoral Science Foundation(No.2013M540842)
关键词 Design optimization Hybrid rocket motor Kriging model Uncertainty analysis Uncertainty-based designoptimization Design optimization Hybrid rocket motor Kriging model Uncertainty analysis Uncertainty-based designoptimization
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  • 1王晓锋,席光.基于Kriging模型的翼型气动性能优化设计[J].航空学报,2005,26(5):545-549. 被引量:39
  • 2吴亮红,王耀南,袁小芳,周少武.自适应二次变异差分进化算法[J].控制与决策,2006,21(8):898-902. 被引量:81
  • 3韩永志,高行山,李立州,岳珠峰.基于Kriging模型的涡轮叶片多学科设计优化[J].航空动力学报,2007,22(7):1055-1059. 被引量:38
  • 4Storn R,Price K V.Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J].Journal of Global Optimization,1997,11:341-359.
  • 5Nasimul Noman,Hitoshi Iba,Accelerating differential evolution using an adaptive local search[J].IEEE Transactions on Evolutionary Computation,2008(2):107-125.
  • 6Swagatam Das,Amit Konar,Uday K.Chakraborty,Two improved differential evolution schemes for fatser global search[C].GECCO'05,Washington,2005:991-998.
  • 7Fan H Y,Lampinen J.A trigonometric mutation operation to differential evolution[J].Journal of Global Optimization,2003,27(1):105-129.
  • 8Feoktistov V,Janaqi S.Generalization of the Strategies in differential evolution[C].Proceedings of 18th International Parallel and Distributed Processing Symposium,2004(7):165-170.
  • 9Yao X,Liu Y,Lin G.Evolutionary programming made faster[J].IEEE Transactions on Evolutionary Computation,1999,3(2):82-102.
  • 10方开泰,1994年

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