遗传算法的超大跨度充气结构设计优化
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(北京航空航天大学 航空科学与工程学院, 100191 北京)

作者简介:

杨永强(1988—),男,博士后.

通讯作者:

马云鹏, myp@buaa.edu.cn.

中图分类号:

V219

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An optimizing design method of large span inflatable structure based on genetic algorithm
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(School of Aeronautic Science and Engineering, Beihang University, 100191 Beijing,China)

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    摘要:

    为了提高超大跨度充气结构设计水平和研发效率,用遗传算法和有限元分析相结合的优化方法进行了超大跨度充气结构设计优化.应用ABAQUS有限元分析软件建立了充气结构有限元模型并进行计算分析,采用遗传算法进行优化,经繁殖和进化后获得最优解.分析结果可知,最优解蒙皮材料应力分布基本均匀,结构各附件平均应力水平较高,具有较高的材料利用率,结构整体质量为3 928 kg.根据最优解进行了样件加工测试,在所有工况下充气结构均可安全工作,旋翼翼梢处最小水平安全距离1.09 m,最小垂直安全距离1.67 m,与有限元分析结果基本一致.测试结果与分析结果基本一致,优化方案能够满足运用要求,验证了该优化方法是有效的.

    Abstract:

    To improve the design level and R&D efficiency of large-span inflatable structure, an optimization method combining FEM with genetic algorithms is applied to design optimization of large span inflatable structure. A FEM model of the inflatable structure is established, calculated and analyzed with the FEM software ABAQUS, then the model is optimized with genetic algorithms and the optimal solution is obtained after breeding and evolution. From the analysis results, there are uniform stress distribution on skin material, higher average stress levels on each accessory structure, a high material utilization and the weight 3 928 kg of whole structure in the optimal solution. According to the optimal solution, the sample is processed and tested, and it can safely work under all conditions. The minimum safety distance of rotor wingtip is 1.09 m, and the minimum vertical safety distance is 1.67 m, which are consistent with the results of FEM. The test results are almost consistent with the analysis, and the optimization program meets the practical requirements well.

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杨永强,马云鹏,林康,武哲.遗传算法的超大跨度充气结构设计优化[J].哈尔滨工业大学学报,2014,46(9):86. DOI:10.11918/j. issn.0367-6234.2014.09.015

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  • 收稿日期:2013-08-20
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  • 在线发布日期: 2014-09-30
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