| Citation: | WANG X L，ZHAO J N，WANG J. Resilience assessment and recovery of airport departure flights under severe weather[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（1）：110-121 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0193
|
In order to ensure the overall performance of the airport under severe weather, scientifically evaluate the resilience of the airport's flight operations, improve flight recovery capabilities, and alleviate the impact of severe weather effectively. This article first gives the definition of airport departure flight operation. Starting from the performance of the airport departure flight operation system, it analyzes flight departure delay time, total departure delay time, departure flight normality rate and airport departure flight operation system comprehensive resilience index four indicators to evaluate the resilience changes of the system under severe weather conditions.It is important to present airport departure flight operating system's performance recovery method, to employ a genetic algorithm to optimize the order of the delayed departure flights. Finally, this article takes the “721” heavy rain event in Beijing Capital International Airport in 2012 as an example to analyze the data, obtains the performance index and resilience index of the Capital Airport under the influence of heavy rain, and compare and analyze the changes in airport departure flight operating system performance and resilience level. The results indicate that under the influence of heavy rain, the comprehensive resilience index of the airport departure flight operation system decreased from 0.4573 to 0.0628, and increased to 0.2223 after the rainstorm decreased. The delay time is reduced by 24.85%, the airport performance recovery speed is increased by 13.89% after optimization, and the minimum resilience index of the optimized airport departure flight operation system is increased by 13.38%, the system performance is given priority to restore to the initial state, indicating the effectiveness of the proposed recovery strategy.
| [1] |
MURRAY-TUITE P M. A comparison of transportation network resilience under simulated system optimum and user equilibrium conditions[C]// Proceedings of the 2006 Winter Simulation Conference. Piscataway: IEEE Press, 2007: 1398-1405.
|
| [2] |
GAO J X, BARZEL B, BARABÁSI A L. Universal resilience patterns in complex networks[J]. Nature, 2016, 530(7590): 307-312. doi: 10.1038/nature16948
|
| [3] |
IP W H, WANG D W. Resilience and friability of transportation networks: Evaluation, analysis and optimization[J]. IEEE Systems Journal, 2011, 5(2): 189-198. doi: 10.1109/JSYST.2010.2096670
|
| [4] |
LORDAN O, SALLAN J M, SIMO P, et al. Robustness of the air transport network[J]. Transportation Research Part E, 2014, 68: 155-163. doi: 10.1016/j.tre.2014.05.011
|
| [5] |
王德龙, 王超峰. 基于蓄意攻击下的民用机场网络级联失效抗毁性分析[J]. 交通运输工程与信息学报, 2020, 18(3): 172-178. doi: 10.3969/j.issn.1672-4747.2020.03.020
WANG D L, WANG C F. Analysis of cascading failure and resistance of network in civil airports based on deliberate attacks[J]. Journal of Traffic and Transportation Engineering and Information, 2020, 18(3): 172-178(in Chinese). doi: 10.3969/j.issn.1672-4747.2020.03.020
|
| [6] |
D’LIMA M, MEDDA F. A new measure of resilience: An application to the London Underground[J]. Transportation Research Part A:Policy and Practice, 2015, 81: 35-46. doi: 10.1016/j.tra.2015.05.017
|
| [7] |
SUN W M, ZENG A. Target recovery in complex networks[J]. The European Physical Journal B, 2017, 90(1): 10. doi: 10.1140/epjb/e2016-70618-0
|
| [8] |
NAN C , SANSAVINI G. A quantitative method for assessing resilience of interdependent infrastructures[J]. Reliability Engineering & System Safety, 2017, 157: 35-53
|
| [9] |
王兴隆, 苗尚飞. 空域扇区网络结构特性分析及韧性评估[J]. 北京航空航天大学学报, 2021, 47(5): 904-911. doi: 10.13700/j.bh.1001-5965.2020.0084
WANG X L, MIAO S F. Structural characteristics analysis and resilience assessment of airspace sector network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(5): 904-911(in Chinese). doi: 10.13700/j.bh.1001-5965.2020.0084
|
| [10] |
JANIĆ M. Modelling the resilience, friability and costs of an air transport network affected by a large-scale disruptive event[J]. Transportation Research Part A:Policy and Practice, 2015, 71: 1-16. doi: 10.1016/j.tra.2014.10.023
|
| [11] |
潘维煌. 基于相依网络理论的空中交通系统脆弱性研究[D]. 天津: 中国民航大学, 2019.
PAN W H. Research on the vulnerability of air traffic system based on interdependent network theory [D]. Tianjin: Civil Aviation University of China, 2019(in Chinese).
|
| [12] |
周语, 邵荃. 基于不确定因素扰动的机场大面积航班恢复规划[J]. 科学技术与工程, 2018, 18(16): 300-305. doi: 10.3969/j.issn.1671-1815.2018.16.048
ZHOU Y, SHAO Q. Airport large-scale flight recovery planning based on uncertainty disturbance[J]. Science Technology and Engineering, 2018, 18(16): 300-305(in Chinese). doi: 10.3969/j.issn.1671-1815.2018.16.048
|
| [13] |
张启钱, 胡明华, 施赛锋, 等. 多跑道航班起降调度优化算法[J]. 交通运输工程学报, 2012, 12(6): 63-68. doi: 10.3969/j.issn.1671-1637.2012.06.010
ZHANG Q Q, HU M H, SHI S F, et al. Optimization algorithm of flight takeoff and landing on multi-runways[J]. Journal of Traffic and Transportation Engineering, 2012, 12(6): 63-68(in Chinese). doi: 10.3969/j.issn.1671-1637.2012.06.010
|
| [14] |
INNISS T R, BALL M O. Estimating one-parameter airport arrival capacity distributions for air traffic flow management[J]. Air Traffic Control Quarterly, 2004, 12(3): 223-251. doi: 10.2514/atcq.12.3.223
|
| [15] |
KLEIN A, CRAUN C, LEE R S. Airport delay prediction using weather-impacted traffic index (WITI) model[C]// 29th Digital Avionics Systems Conference. Piscataway: IEEE Press, 2010: 1-13.
|
| [16] |
KICINGER R, SABHNANI G, KRISHNA S, et al. Comparison of the impacts of airport terminal/surface weather hazards[C]// Proceedings of the AIAA Guidance, Navigation, and Control Conference. Reston: AIAA, 2011: 6385.
|
| [17] |
王时敏. 恶劣天气对航班延误影响的初步量化研究[D]. 南京: 南京航空航天大学, 2017.
WANG S M. Research on the impact of severe weather on flight delay[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017(in Chinese).
|
| [18] |
尉炜, 邵荃, 向红奕, 等. 基于复杂网络的恶劣天气对航班延误影响的研究[J]. 航空计算技术, 2018, 48(2): 48-51. doi: 10.3969/j.issn.1671-654X.2018.02.012
WEI W, SHAO Q, XIANG H Y, et al. Research on impact of bad weather based on complex network on flight delay[J]. Aeronautical Computing Technique, 2018, 48(2): 48-51(in Chinese). doi: 10.3969/j.issn.1671-654X.2018.02.012
|
| [19] |
WANG Y J, ZHAN J M, XU X H, et al. Measuring the resilience of an airport network[J]. Chinese Journal of Aeronautics, 2019, 32(12): 2694-2705. doi: 10.1016/j.cja.2019.08.023
|
| [20] |
HENRY D, EMMANUEL RAMIREZ-MARQUEZ J. Generic metrics and quantitative approaches for system resilience as a function of time[J]. Reliability Engineering & System Safety, 2012, 99: 114-122.
|
| [21] |
王楠, 戴福青, 齐雁楠. 基于-跑道容量的航班恢复优化模型[J]. 科学技术与工程, 2020, 20(15): 6279-6285. doi: 10.3969/j.issn.1671-1815.2020.15.056
WANG N, DAI F Q, QI Y N. Flight recovery optimization model based on runway capacity[J]. Science Technology and Engineering, 2020, 20(15): 6279-6285(in Chinese). doi: 10.3969/j.issn.1671-1815.2020.15.056
|
| [22] |
段伯隆, 张文龙, 刘海文, 等. 北京“7.21”特大暴雨过程暖区降水和锋面降水的时空分布特征[J]. 暴雨灾害, 2017, 36(2): 108-117. doi: 10.3969/j.issn.1004-9045.2017.02.002
DUAN B L, ZHANG W L, LIU H W, et al. The spatial and temporal distributions of warm sector rainfall and frontal rainfall for the torrential rain event in Beijing on 21 July 2012[J]. Torrential Rain and Disasters, 2017, 36(2): 108-117(in Chinese). doi: 10.3969/j.issn.1004-9045.2017.02.002
|
Figures(14) / Tables(4)
Copyright © Journal of Beijing University of Aeronautics and Astronautics
Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn
Supported by:
Beijing Renhe Information Technology Co., Ltd.
DownLoad:
