基于MOEA/D的三锥体拦截器气动外形优化设计
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摘要
针对由临近空间拦截器飞行环境变化剧烈导致的热流密度过高等问题,提出一种多目标外形优化设计方法,并针对一种新型三锥体临近空间拦截器外形进行优化设计。首先,建立飞行器的气动、弹道、气动热等多学科分析模型,利用高斯-伪谱法计算拦截弹道,利用桥函数法建立气动模型,并利用Fay-Riddle方法估计气动热流密度。然后,以飞行器航程、总热流量和飞行时间为优化目标,采用基于分解的多目标进化算法(MOEA/D)与伪谱法将该问题转化为一组单目标优化子问题,得到Pareto前沿并进行相关分析。最后,给出一个优于基准值,同时满足性能指标要求的新型外形。结果表明:该优化方法具有可实现性,为未来的飞行器设计提供了新思路。
To solve the problem of high heat flux density caused by the dramatic change of flight environment of near space interceptors, a new multi-objective shape optimization design method is proposed, and the shape of a new triple-cone near space interceptor is optimized. Firstly, a multi-disciplinary analysis model of aerodynamics, trajectories and aerodynamics of the aircraft is established. The Gaussian-pseudo-spectral method is used to calculate the intercepting trajectory. The aerodynamic model is established by the bridge function method, and the aerodynamic heat flux density is estimated by the Fay-Riddle method. Then, based on flight range, total heat flow and flight time, the decomposition-based multi-objective evolutionary algorithm(MOEA/D) and the pseudo-spectral method are used to transform the problem into a set of single-objective optimization sub-problems, and the Pareto frontier is obtained. Finally, this paper provides a new shape which is better than the benchmark and meets the performance requirements. The results show that the optimization method is achievable, providing a new idea for future aircraft design.
To solve the problem of high heat flux density caused by the dramatic change of flight environment of near space interceptors, a new multi-objective shape optimization design method is proposed, and the shape of a new triple-cone near space interceptor is optimized. Firstly, a multi-disciplinary analysis model of aerodynamics, trajectories and aerodynamics of the aircraft is established. The Gaussian-pseudo-spectral method is used to calculate the intercepting trajectory. The aerodynamic model is established by the bridge function method, and the aerodynamic heat flux density is estimated by the Fay-Riddle method. Then, based on flight range, total heat flow and flight time, the decomposition-based multi-objective evolutionary algorithm(MOEA/D) and the pseudo-spectral method are used to transform the problem into a set of single-objective optimization sub-problems, and the Pareto frontier is obtained. Finally, this paper provides a new shape which is better than the benchmark and meets the performance requirements. The results show that the optimization method is achievable, providing a new idea for future aircraft design.
引文
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[2] 丰志伟. 多目标进化算法研究及在飞行器动力学系统中的应用[D]. 长沙: 国防科学技术大学, 2014.
[3] 刘传振, 白鹏, 陈冰雁, 等. 三维流场乘波体快速设计方法及多目标优化[J]. 宇航学报, 2016, 37(5): 535-543.
[4] ZHANG Q, LI H. MOEA/D: a multi-objective evolutionary algorithm based on decomposition[J]. Transactions on Evolutionary Computation, 2007, 11(6): 712-731.
[5] PALAR P S, TSUCHIYA T, PARKS G. Decomposition-based evolutionary aerodynamic robust optimization with multi-fidelity point collocation non-intrusive polynomial chaos[C]//17th AIAA Non-Deterministic Approaches Conference. [S.l.]: AIAA, 2015: 1-17.
[6] REXIUS S L, REXIUS T, JORRIS T R, et al. Advances in highly constrained multi-phase trajectory generation using the general pseudospectral optimization software (GPOPS)[R].AD, AFRL-RQ-ED-TP-2013-182, 2013.
[7] WANG Y L, TANG W, ZHANG Y, et al. Aerodynamic configuration optimization of a common aero vehicle[J]. Journal of Astronautics, 2006, 27(4):709-718.
[8] CHE J, TANG S. Engineering calculation of aerodynamics for quasi-waverider vehicle[J]. Acta Aerodynamica Sinica, 2007, 25(3): 381-385.
[9] MOSS J N, BIRD G A, MARKELOV G N. DSMC simulations of hypersonic flows and comparison with experiments[C]//24th International Symposium on Rarefied Gas Dynamics. Hampton, VA: American Institute of Physics, 2005: 547-552.
[10] 水尊师, 周军, 葛致磊. 基于高斯伪谱方法的再入飞行器预测校正制导方法研究[J]. 宇航学报, 2011, 32(6): 1249-1255.
[11] FAY J A. Theory of stagnation point heat transfer in dissociated air[J]. Journal of the Aerospace Sciences, 1958, 25(2): 73-85.
[12] 丰志伟, 张青斌, 高兴龙, 等. 火星探测器气动外形/弹道一体化多目标优化[J]. 航空学报, 2014, 35(9): 2461-2471.
[2] 丰志伟. 多目标进化算法研究及在飞行器动力学系统中的应用[D]. 长沙: 国防科学技术大学, 2014.
[3] 刘传振, 白鹏, 陈冰雁, 等. 三维流场乘波体快速设计方法及多目标优化[J]. 宇航学报, 2016, 37(5): 535-543.
[4] ZHANG Q, LI H. MOEA/D: a multi-objective evolutionary algorithm based on decomposition[J]. Transactions on Evolutionary Computation, 2007, 11(6): 712-731.
[5] PALAR P S, TSUCHIYA T, PARKS G. Decomposition-based evolutionary aerodynamic robust optimization with multi-fidelity point collocation non-intrusive polynomial chaos[C]//17th AIAA Non-Deterministic Approaches Conference. [S.l.]: AIAA, 2015: 1-17.
[6] REXIUS S L, REXIUS T, JORRIS T R, et al. Advances in highly constrained multi-phase trajectory generation using the general pseudospectral optimization software (GPOPS)[R].AD, AFRL-RQ-ED-TP-2013-182, 2013.
[7] WANG Y L, TANG W, ZHANG Y, et al. Aerodynamic configuration optimization of a common aero vehicle[J]. Journal of Astronautics, 2006, 27(4):709-718.
[8] CHE J, TANG S. Engineering calculation of aerodynamics for quasi-waverider vehicle[J]. Acta Aerodynamica Sinica, 2007, 25(3): 381-385.
[9] MOSS J N, BIRD G A, MARKELOV G N. DSMC simulations of hypersonic flows and comparison with experiments[C]//24th International Symposium on Rarefied Gas Dynamics. Hampton, VA: American Institute of Physics, 2005: 547-552.
[10] 水尊师, 周军, 葛致磊. 基于高斯伪谱方法的再入飞行器预测校正制导方法研究[J]. 宇航学报, 2011, 32(6): 1249-1255.
[11] FAY J A. Theory of stagnation point heat transfer in dissociated air[J]. Journal of the Aerospace Sciences, 1958, 25(2): 73-85.
[12] 丰志伟, 张青斌, 高兴龙, 等. 火星探测器气动外形/弹道一体化多目标优化[J]. 航空学报, 2014, 35(9): 2461-2471.