-
摘要:
提高航站楼运行韧性是减少偶然事件下人员财产损失、减轻破坏程度、尽快恢复功能的最佳办法。目前，对航站楼缺乏基于运行性能指标时变过程的韧性定量分析理论与技术。基于此，提出综合体现鲁棒性、快速性与系统性能损失的航站楼系统综合韧性指标的航站楼运行韧性理论框架，基于离散事件模拟，得出航站楼运行系统在设备损坏、人员缺席2种扰动情景及不同扰动时间、旅客到达率下的韧性变化规律，并提出提高安检效率及设备冗余率2种韧性提升策略。结果表明：系统鲁棒性指标、性能损失指标均与扰动时间及旅客到达率呈负相关；对于设备损坏和人员缺席2种情景，提升安检效率使系统综合韧性水平分别从原有的0.325、0.054提升至0.834、0.913，提升设备冗余率使系统综合韧性水平从0.22提升至0.638。
Abstract:Improving the operation resilience of the terminal is the best way to reduce the loss of people and property in an accident, mitigate the damage, and restore its function as soon as possible. At present, there is a lack of theories and techniques for quantitatively analyzing the resilience of the terminal based on the time-varying process of operation performance indicators. First, a theoretical framework of terminal operation resilience was proposed, with a comprehensive resilience index of the terminal system, which comprehensively reflected the robustness, rapidity, and system performance loss. Then, based on discrete event simulation, the resilience variation law of the terminal operation system under two disturbance scenarios of equipment damage and personnel absence, different disturbance time, and passenger arrival rates was obtained. In addition, two resilience improvement strategies were put forward to improve security check efficiency and equipment redundancy rate. The results show that the system robustness index and performance loss index are negatively correlated with disturbance time and passenger arrival rate. For the two scenarios of equipment damage and personnel absence, improving the security check efficiency increases the comprehensive resilience level of the system from the original 0.325 and 0.054 to 0.834 and 0.913, respectively, and improving the equipment redundancy rate increases the comprehensive resilience level of the system from 0.22 to 0.638.
-
图 10 人员缺席情景下旅客系统时间曲线
Figure 10. Curves of passenger system time during personnel absence
图 16 提升安检效率后系统韧性指标变化
Figure 16. Variation of system resilience index after improving security check efficiency
表 1 仿真区域相关参数
Table 1. Relevant parameters of simulation area
参数 数值 航站楼入口/个 5 自助值机设备/台 28 人工值机设备/台 72 安检通道/条 20 行李安检仪/台 40 仿真区域宽度/m 150 仿真区域长度/m 318 
下载: 导出CSV
表 2 旅客行为相关参数
Table 2. Relevant parameters of passenger behavior
服务流程 参数名称 服务时间/s 产生比例/% 入口检测 航站楼入口
爆炸物检测uniform(2,3) 咨询服务 咨询时间 uniform(30,90) 5 值机服务 是否自助值机 是，20；否，80 自助值机时间 triangular(30,75,40) 值机核验时间 uniform(15,20) 行李是否托运 是，70；否，30 等待取票时间 uniform(10,15) 办理行李托运及取票 uniform(30,40) 行李是否超重或违禁 是，20；否，80 超重或违禁行李处理 triangular(25,45,30) 安检服务 核验登机牌及证件 uniform(10,15) 旅客准备 uniform(10,15) 人员安检 uniform(30,55) 行李是否合规 是，85；否，15 违规行李检查 triangular(25,45,35) 提取行李 uniform(20,45)
下载: 导出CSV
-
[1] BRUNEAU M, CHANG S E, EGUCHI R T, et al. A framework to quantitatively assess and enhance the seismic resilience of communities[J]. Earthquake Spectra, 2003, 19(4): 733-752. doi: 10.1193/1.1623497 [2] CLARK K L, BHATIA U, KODRA E A, et al. Resilience of the U. S. national airspace system airport network[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 19(12): 3785-3794. doi: 10.1109/TITS.2017.2784391 [3] 王兴隆, 刘洋. 航空多层网络弹性测度与分析[J]. 复杂系统与复杂性科学, 2020, 17(2): 31-38.WANG X L, LIU Y. Resilience measurement and analysis of aviation multi-layer network[J]. Complex Systems and Complexity Science, 2020, 17(2): 31-38(in Chinese). [4] 郭九霞. 新一代民航运输系统安全韧性理论与方法研究[D]. 成都: 电子科技大学, 2021.GUO J X. Research on safety resilience theory and method for next generation air transportation system[D]. Chengdu: University of Electronic Science and Technology of China, 2021(in Chinese). [5] HUANG C N, LIOU J J H, LO H W, et al. Building an assessment model for measuring airport resilience[J]. Journal of Air Transport Management, 2021, 95: 102101. doi: 10.1016/j.jairtraman.2021.102101 [6] BAO D W, ZHANG X L. Measurement methods and influencing mechanisms for the resilience of large airports under emergency events[J]. Transportmetrica A: Transport Science, 2018, 14(10): 855-880. doi: 10.1080/23249935.2018.1448016 [7] 黄润建. 基于风险交互分析的4F机场灾害韧性评价研究[D]. 广州: 暨南大学, 2020.HUANG R J. Research on 4F airport disaster resilience evaluation based on risk interaction analysis[D]. Guangzhou: Jinan University, 2020(in Chinese). [8] 胡明伟, 黄文柯. 行人交通仿真方法与技术[M]. 北京: 清华大学出版社, 2016: 75-79.HU M W, HUANG W K. Pedestrian traffic simulation method and technology[M]. Beijing: Tsinghua University Press, 2016: 75-79(in Chinese). [9] HOLLING C S. Resilience and stability of ecological systems[J]. Annual Review of Ecology and Systematics, 1973, 4: 1-23. doi: 10.1146/annurev.es.04.110173.000245 [10] 欧阳虹彬, 叶强. 弹性城市理论演化述评: 概念、脉络与趋势[J]. 城市规划, 2016, 40(3): 34-42. doi: 10.11819/cpr20160306aOUYANG H B, YE Q. A review on the evolution of resilient city theory: Concept, context and tendency[J]. City Planning Review, 2016, 40(3): 34-42(in Chinese). doi: 10.11819/cpr20160306a [11] 李明捷. 机场规划与设计[M]. 北京: 中国民航出版社, 2015: 280-282.LI M J. Airport planning and design[M]. Beijing: China Civil Aviaiton Press, 2015: 280-282(in Chinese). [12] 王加冕, 陶翼飞, 罗俊斌, 等. 基于蒙特卡洛仿真的机场值机系统优化研究[J]. 软件导刊, 2021, 20(8): 82-86. doi: 10.11907/rjdk.202377WANG J M, TAO Y F, LUO J B, et al. Optimization of airport check-in system based on Monte Carlo simulation[J]. Software Guide, 2021, 20(8): 82-86(in Chinese). doi: 10.11907/rjdk.202377 [13] 吴忠君. 航站楼旅客离港服务流程建模与仿真[D]. 哈尔滨: 哈尔滨工业大学, 2013: 61-63.WU Z J. The departing service processes in terminal modeling and simulation[D]. Harbin: Harbin Institute of Technology, 2013: 61-63(in Chinese). [14] 张浩. 航站楼离港旅客流程仿真及优化研究[D]. 广汉: 中国民用航空飞行学院, 2018: 34-36.ZHANG H. Simulation and optimization of passenger flow in terminal building[D]. Guanghan: Civil Aviation Flight University of China, 2018: 34-36(in Chinese). [15] 赵振武, 李新源. 基于Anylogic的机场旅客安检流程仿真与优化[J]. 中国民航大学学报, 2018, 36(5): 52-55. doi: 10.3969/j.issn.1674-5590.2018.05.011ZHAO Z W, LI X Y. Simulation and optimization of airport passenger security screening process based on Anylogic[J]. Journal of Civil Aviation University of China, 2018, 36(5): 52-55(in Chinese). doi: 10.3969/j.issn.1674-5590.2018.05.011 [16] COMES T, WARNIER M, FEIL W, et al. Critical airport infrastructure disaster resilience: A framework and simulation model for rapid adaptation[J]. Journal of Management in Engineering, 2020, 36(5): 04020059. doi: 10.1061/(ASCE)ME.1943-5479.0000798 -
下载:
点击查看大图
计量
- 文章访问数: 198
- HTML全文浏览量: 70
- PDF下载量: 6
- 被引次数: 0
