机场飞行区多层异质链序风险传播模型研究

吴维; 吴泽萱; 王兴隆

doi:10.13700/j.bh.1001-5965.2023.0203

机场飞行区多层异质链序风险传播模型研究

doi: 10.13700/j.bh.1001-5965.2023.0203

吴维^{1, 2, ,},
吴泽萱¹,
王兴隆¹

1.
中国民航大学空中交通管理学院，天津 300300
2.
北京交通大学交通运输学院，北京 100044

基金项目: 天津市应用基础多元投入基金面上项目(21JCYBJC00700)；中央高校基本科研业务费项目中国民航大学专项(3122025098)

详细信息

通讯作者:
E-mail：wwu@cauc.edu.cn

中图分类号: U8；V355.2
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- 被引次数: 0
出版历程
- 收稿日期: 2023-04-24
- 录用日期: 2023-06-16
- 网络出版日期: 2023-07-04
- 整期出版日期: 2024-07-18

Research on multi-layer heterogeneous chain sequence risk propagation model in airport movement area

WU Wei^{1, 2
, ,},
WU Zexuan¹,
WANG Xinglong¹

1.
College of Air Traffic Management，Civil Aviation University of China，Tianjin 300300，China
2.
School of Traffic and Transportation，Beijing Jiaotong University，Beijing 100044，China

Funds: Natural Science Key project of Tianjin Municipal Education Commission (21JCYBJC00700)；The Fundamental Research Funds for the Central Universities Civil Aviation University of China Special Project (3122025098)

More Information

Corresponding author: E-mail：wwu@cauc.edu.cn

摘要

摘要:
为探究机场飞行区风险发生机制及风险传播特性，增强机场飞行区安全管控能力，采用复杂网络理论，依据风险致因间的因果链序关系，构建多层异质网络风险传播模型。采用多层次因果图(AcciMap)理论分析机场飞行区运行风险传播的致因链；基于风险致因特征构建3层异质风险传播网络并根据网络特征设计概率-触发传播模型、容量-阻抗传播模型、容量-负荷传播模型；利用复杂网络理论设计风险传播评价指标，对风险网络传播特征进行分析。结果表明：多层风险网络中节点风险传播能力与节点度弱相关，节点风险灵敏指数可提升风险节点排序准确性；对风险灵敏度指数排序前15%的节点进行风险控制，可有效降低风险扩散近32%；网络风险传播结构存在高连通和松散状态，对风险扩散指数排序前15%的节点进行控制，可以有效降低网络结构鲁棒性指数使风险网络结构由高连通进入到松散状态；所建模型可有效识别风险扩散过程并进行精准控制，以提升机场飞行区风险控制水平。
- 航空运输 /
- 机场运行 /
- 复杂网络 /
- 风险传播 /
- 控制策略
Abstract:
A multi-layer heterogeneous network risk propagation model was built using complex network theory and the causal chain relationship between risk factors in order to better characterize the characteristics of operational risks' propagation in flight areas and improve the safety management capabilities of airport flight areas. The accident analysis mapping（AcciMap） theory was employed to analyze the causal chain of risk propagation. A three-layer heterogeneous risk propagation network was built. Evaluation indicators were designed using complex network theory to analyze the characteristics of risk network propagation. The results demonstrate that the node's risk propagation capability exhibits a weak correlation with the node degree, and the node's risk sensitivity index can enhance the accuracy of risk node ranking. Implementing risk control measures on the top 15% of nodes ranked by the risk sensitivity index can effectively reduce risk diffusion by approximately 32%. It is possible to reduce the robustness index of the network structure and move the risk network structure from a highly connected state to a loose state by controlling the top 15% of nodes ranked by the risk diffusion index. The built model enables the identification and precise control of risk diffusion processes, thereby enhancing the level of risk control in airport flight areas.
- air transportation /
- airport operations /
- complex network /
- risk propagation /
- control strategy

HTML全文

图 1 机场飞行区风险事件AcciMap结构模型

Figure 1. AcciMap structural model for analyzing risk events in airport movement area

下载: 全尺寸图片幻灯片

图 2 多层链序风险传播网络

Figure 2. Multilayered network for cascade risk propagation

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图 3 节点风险灵敏指数

Figure 3. Node risk sensitivity index

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图 4 网络风险扩散指数

Figure 4. Network risk diffusion index

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图 5 网络结构鲁棒性指数

Figure 5. Network structural robustness index

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图 6 不同控制策略风险扩散指数

Figure 6. Risk diffusion index under different control strategies

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图 7 不同控制策略网络结构鲁棒性指数

Figure 7. Network structure robustness index under different control strategies

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表 1 阻抗节点参数

Table 1. Impedance node parameters

工作年限/a	$ {\kappa _{j1}} $	工作负荷	$ {\kappa _{j2}} $	工作时长/h	$ {\kappa _{j3}} $
0~6	0.15	0~0.3	0.25	1~2	0.25
6~15	0.25	0.3~0.7	0	3~4	0
15~30	0.4	0.7~1	−0.2	5~6	−0.1
注：${\kappa _{j1}} $、${\kappa _{j2}} $、${\kappa _{j3}} $为工作年限、工作负荷、工作时长的修正参数。

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