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Aircraft Design Optimization with Uncertainty Based on Fuzzy Clustering Analysis

机译：基于模糊聚类分析的不确定性飞机设计优化

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摘要

Uncertainty always exists in any design problems; conventional aircraft design with deterministic optimization may achieve underdesign or overdesign. Therefore, it is necessary to consider uncertainty analysis in aircraft concept design. Traditional uncertainty analyses need many sampling points to simulate the uncertain models. These methods include a large number of calculations to achieve the required accuracy. To increase the efficiency of uncertainty analysis and reduce the effect of error propagation on uncertainty models, a method with dynamic surrogate models based on fuzzy clustering analysis is proposed in this paper. Among the design spaces, the sampling points with little influence on response surface are abandoned by dynamic screening until the surrogate model reaches the expected level of accuracy. This method is applied to the optimization of a hypothetical aircraft concept design, which shows that the calculated amount of uncertainty analysis can be reduced effectively while the optimized performance can satisfy the reliability and robustness. (C) 2015 American Society of Civil Engineers.
机译：不确定性总是存在于任何设计问题中。具有确定性优化的传统飞机设计可能会设计不足或过度设计。因此，有必要在飞机概念设计中考虑不确定性分析。传统的不确定性分析需要许多采样点来模拟不确定性模型。这些方法包括大量计算以达到所需的精度。为了提高不确定性分析的效率，减少误差传播对不确定性模型的影响，提出了一种基于模糊聚类分析的动态替代模型方法。在设计空间中，对响应表面影响很小的采样点被动态筛选放弃，直到替代模型达到预期的精度水平。该方法应用于假设飞机概念设计的优化，表明可以有效减少不确定性分析的计算量，同时优化的性能可以满足可靠性和鲁棒性。 （C）2015年美国土木工程师学会。

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  • 来源
    《Journal of aerospace engineering》 |2016年第1期|04015032.1-04015032.9|共9页
  • 作者

    Du Shengchao; Wang Lifeng;

  • 作者单位

    Beijing Univ Aeronaut & Astronaut, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China;

    Beijing Univ Aeronaut & Astronaut, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China;

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