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考虑尾流遭遇情形下的不确定性与随机性因素,利用蒙特卡洛法对三维空间内的每个尾流遭遇点进行大数据量的仿真实验,提取了尾流遭遇情形下的三维极值参数,验证了一维的极值参数符合广义极值(GEV)分布;提出了三维极值参数的四参数变权重Copula(FPAVW Copula)模型,拟合优度检验的结果表明FPAVW Copula具有比其他Copula更高的精度;利用FPAVW Copula对尾流场内每个网格采样点上的三维极值参数进行了辨识,计算出了尾流空间的风险概率指标分布情况;在此基础上对尾流风险概率拓扑在不同发展阶段的结构特征进行了分析,构建了可视化的二维及三维风险概率结构图,可用来研究尾流场内的风险规避策略及算法.所提方法及思路亦可对其他内外部环境因素影响下的飞行风险概率评估及拓扑结构可视化等热点研究方向提供参考.
Considering the uncertainty and randomness of wake encountering condition, the Monte Carlo method is used to simulate the large data amount of each wake encounter point in three-dimensional space. The three-dimensional extreme value Parameters, the one-dimensional extremum parameters are verified to meet the generalized extreme value (GEV) distribution. A four-parameter variable-weight copula (FPAVW Copula) model with three-dimensional extremum parameters is proposed. The results of the goodness-of- fit test show that the FPAVW Copula has a better performance than the other Copula. The FPAVW Copula is used to identify the three-dimensional extremum parameters of each grid sampling point in the wake field, and the distribution of the risk probability index of the wake space is calculated. Based on this, The structural features of risk probability topologies in different stages of development are analyzed, and a visual two-dimensional and three-dimensional risk probability structure diagram is constructed, which can be used to study risk evasion strategies and algorithms in wake field. The proposed methods and ideas can also be applied to other Provide a reference for the research of hot spots such as evaluation of flight risk under the influence of internal and external environment factors and topological structure visualization.