基于组合算法的碟形水下滑翔机结构稳健优化
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摘要
为提高圆碟形水下滑翔机耐压结构优化设计方案的可靠性,引入稳健性设计方法进行优化设计.首先,采用拉丁超立方方法进行试验设计,建立了预测圆碟形耐压结构性能的径向基神经网络模型;采用存档微遗传算法(AMGA)和Hooke-jeeves组合优化算法,给出了耐压壳体结构多目标优化方案;然后,应用蒙特卡罗描述性抽样方法对确定性优化结果进行了可靠性分析;在此基础上,考虑工业制造过程中不确定性因素,进行耐压结构稳健性优化求解.优化结果表明:结构质量减少了20.03%,轻量化效果明显;各设计变量和优化目标的可靠度均达到100%,优化结果具有较好的稳健性.
To improve the optimized design's reliability for the pressure shell structure of the dish-shaped underwater glider,the robust design method was introduced to optimize the pressure shell structure.The sample points in the design space were selected by using latin hypercube sampling experiment design method.And the Radial basis function neural network model of the glider structure optimization was established by using the sample points data.The archive-based micro genetic algorithm(AMGA) and Hooke-jeeves combined optimization algorithm were designed to optimize the pressure shell structure of the dish-shaped underwater glider,and a multi-objective optimization scheme was established.The reliability analysis of deterministic optimization results was done by using Monte Carlo descriptive sampling method.On this basis,the robust optimization of the pressure structure was carried out,considering the uncertainties in industrial manufacturing process.The optimization results show that,the structural mass is reduced by 20.03%,and the effect of lightweight is obvious.The reliability of each design variable and optimization target is 100%,and the optimization result is very robust.
To improve the optimized design's reliability for the pressure shell structure of the dish-shaped underwater glider,the robust design method was introduced to optimize the pressure shell structure.The sample points in the design space were selected by using latin hypercube sampling experiment design method.And the Radial basis function neural network model of the glider structure optimization was established by using the sample points data.The archive-based micro genetic algorithm(AMGA) and Hooke-jeeves combined optimization algorithm were designed to optimize the pressure shell structure of the dish-shaped underwater glider,and a multi-objective optimization scheme was established.The reliability analysis of deterministic optimization results was done by using Monte Carlo descriptive sampling method.On this basis,the robust optimization of the pressure structure was carried out,considering the uncertainties in industrial manufacturing process.The optimization results show that,the structural mass is reduced by 20.03%,and the effect of lightweight is obvious.The reliability of each design variable and optimization target is 100%,and the optimization result is very robust.
引文
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[2]NAKAMURA M,KOTERAYAMA W,INADA M,et al.Disk-type underwater glider for virtual mooring and field experiment[J].International Journal of Offshore and Polar Engineering,2009,19(1):66-70.
[3]周晗,王天霖,于鹏垚.圆碟形水下滑翔机运动特性研究[J].华中科技大学学报:自然科学版,2018,46(9):112-118.
[4]HE Y R,SONG B W,DONG H C.Multi-objective optimization design for the multi-bubble pressure cabin in BWB underwater glider[J].International Journal of Naval Architecture and Ocean Engineering,2018,10(4):439-449.
[5]刘峰,王力丰,韩端锋,等.载人潜器耐压球壳参数化设计与稳定性分析[J].海洋技术学报,2015,34(1):32-37
[6]何雪浤,刘新猛.基于正交试验的潜水器耐压壳体的结构优化设计[J].机械科学与技术,2015,34(1):8-13.
[7]甄春博,刘兆瑞,王天霖,等.基于遗传算法的碟型水下滑翔机结构优化[J].海洋技术学报,2017,36(2):10-15.
[8]程妍雪,庞永杰,杨卓懿,等.基于径向基神经网络模型的耐压壳6σ设计[J].上海交通大学学报,2014,48(4):493-497.
[9]SUN G Y,LI G Y,ZHOU S W,et al.Crashworthiness design of vehicle by using multiobjective robust optimization[J].Structural and Multidisciplinary Optimization,2011,44(1):99-110.
[10]刘峰,韩端峰,姚军.有开孔加强结构耐压球壳稳健性优化[J].哈尔滨工程大学学报,2016,37(12):1613-1618.
[11]CHANG H C,CHENG X D,LIU Z Y,et al.Sample selection method for ship resistance performance optimization based on approximated model[J].Journal of Ship Research,2016,60(1):1-13.