Propagation Mechanism of Safety Risk During Take-off and Landing of Amphibious Seaplanes Based on D-SEIRS Model
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摘要: 两栖水上飞机起降阶段事故频发，研究其安全风险具有重要意义。为了探究两栖水上飞机起降安全风险传播机理，基于疾病传染SEIRS模型，考虑两栖水上飞机起降安全风险的传播效应和延迟效应，构建了无标度网络上的两栖水上飞机起降安全风险传播延迟（D-SEIRS）模型，利用Routh-Hurwitz判据推导分析了模型平衡点的稳定性，求解了模型的稳态密度及基本再生数。运用MATLAB软件对模型进行数值仿真，揭示了两栖水上飞机起降安全风险的动态传播规律。结果表明：网络中感染类节点的稳态密度随有效传播率和传播延迟时间的增加而增加；传播延迟会减小网络中风险传播阈值，加快风险爆发平衡状态的出现；潜伏类节点的传播率和感染类节点的传播率均会导致感染节点和潜伏节点稳态密度的增加，且潜伏节点的有效传播率对网络中的风险传播影响更大。Abstract: It is of great importance to study the safety risk of amphibious seaplanes during their take-off and landing, since accidents occur frequently in these two phases. Based on the SEIRS model for disease transmission, considering the propagation and delay mechanism on safety risk of amphibious seaplane during take-off and landing, a risk propagation delay(D-SEIRS)model based on a scale-free network is developed to study the propagation mechanism of safety risk during the take-off and landing of amphibious seaplanes. The Routh-Hurwitz Criterion is used to analyze the stability of the equilibrium in the proposed model and solve for the steady-state density(SSD)and basic regeneration number of the proposed model. A numeric simulation based on the MATLAB software is performed using the proposed model, which discloses the dynamic propagation law of the safety risk during the take-off and landing of amphibious seaplanes. Study results show that both the effective propagation rate(EPR) and the propagation delay time(PDT)can lead to the increase of the steady-state density of the infected nodes of the network; the propagation delay can reduce the risk propagation threshold in the network and accelerate the emerging of risk outbreak state; the propagation rates of both latent nodes and infected nodes will lead to an increase in the steady-state density of infected nodes and latent nodes, and the effective propagation rate of latent nodes has a more prominent impact on risk propagation over the network than that of the infected nodes.
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Key words:
- traffic safety /
- amphibious seaplane /
- risk propagation /
- scale-free network /
- D-SEIRS /
- delay effect /
- numerical simulation
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图 1 水上飞机起降安全风险无标度网络拓扑结构图
Figure 1. Topological structure diagram of scale-free network for seaplane take-off and landing safety risk
图 4 传播率ρ1，ρ2对节点稳态密度的影响
Figure 4. The influence of the infection rate ρ1, ρ2 on the steady-state density of nodes
图 5 固定ρ1=0.01，ρ2对感染节点和潜伏节点稳态密的影响
Figure 5. The effect of ρ2 on the steady-state density of infected nodes and latent nodes when ρ1=0.01
图 6 固定ρ2=0.02，ρ1对感染节点和潜伏节点稳态密的影响
Figure 6. The effect of ρ1 on the steady-state density of infected nodes and latent nodes when ρ2=0.02
表 1 水上飞机起降安全风险网络节点定义
Table 1. Definition of network nodes for seaplane takeoff and landing safety risk
编号 事件名称 编号 事件名称 编号 事件名称 x1 飞行员技能不足 x14 管制员工作疏忽 x27 水文条件 x2 飞行员决策失误 x15 地面保障人员失误 x28 培训不足 x3 飞行员身体素质不佳 x16 地面保障人员工作环境恶劣 x29 日常监管机制不完善 x4 飞行员心理素质不佳 x17 航空器故障 x30 水上机场管理不到位 x5 飞行员经验不足 x18 飞机结构设计不合理 x31 应急监管机制不完善 x6 飞行员安全意识薄弱 x19 飞机配载失衡 x32 飞行前准备不足 x7 飞行员情景意识差 x20 飞机失控 x33 团队沟通缺失 x8 机组资源管理不到位 x21 空管设备失灵 x34 人员风险 x9 飞行员失能 x22 飞机装备配备不足 x35 设备设施风险 x10 飞行员疲劳 x23 跑道状况不佳 x36 环境风险 x11 飞行员违规 x24 障碍物 x37 管理风险 x12 飞行员视觉差 x25 起降场环境复杂 x38 起降安全风险 x13 管制员工作负荷大 x26 气象环境 
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