| 引用本文: | 宿爱静,杨文东,张冲,孔明星.航班运行系统仿真建模分析[J].哈尔滨工业大学学报,2019,51(9):49.DOI:10.11918/j.issn.0367-6234.201803050 |
| SU Aijing,YANG Wendong,ZHANG Chong,KONG Mingxing.Analysis on simulation and modeling of flight operation system[J].Journal of Harbin Institute of Technology,2019,51(9):49.DOI:10.11918/j.issn.0367-6234.201803050 |
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| 摘要: |
| 为研究航班计划的运行效率及其在突发扰动下的鲁棒性,将计算机仿真技术应用于航空运输系统,结合分类与航班过站时间的Logistic分布拟合等,通过模拟飞机起飞/降落、滑入/滑出、过站保障和航段飞行等运行过程,建立了含有118个国内主要机场的航班运行仿真模型,在Flexsim平台上实现了大型航空公司航班计划运行仿真. 此模型可以模拟正常和流控等不正常情况下的航班运行,并输出延误时间、正常率、飞机利用率、缓冲时隙等评估指标. 案例分析结果表明:模型较准确地模拟了航空公司航班的实际运行情况. 在正常情况下,对输出指标分析可以确定航班计划中导致延误的重点环节；在流控情况下,可以发现航班延误的范围呈扩散趋势,传播方向沿航班串向下,且延误时间逐渐减少,受直接影响航班过站时间大幅增加,受牵连影响航班过站时间减少. |
| 关键词: 航空运输 航班运行系统 仿真 航班计划 Flexsim 流控 |
| DOI：10.11918/j.issn.0367-6234.201803050 |
| 分类号:U8 |
| 文献标识码:A |
| 基金项目:青年科技创新基金(NS2016063)；南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20170714,kfjj20170702) |
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| Analysis on simulation and modeling of flight operation system |
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SU Aijing,YANG Wendong,ZHANG Chong,KONG Mingxing
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(College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)
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| Abstract: |
| In order to analyze the operational efficiency and the robustness of flight scheduling, computer simulation technology was applied to air transport system in this paper, and a flight operation system model which contains 118 major domestic airports was constructed based on Flexsim simulation software. The model implemented the flight scheduling operation of a large-scale airline by simulating the aircraft operation processes of take-off/landing, taxiing in/out, flight turnaround ground service, and segment flying. Parameters of several aircraft operation time were set by combining the classification method and different fitting distributions, such as fitting flight turnaround time with Logistic distribution. This system model could simulate flight operation under normal condition and abnormal condition (e.g., flow control), as well as export evaluation indexes, such as delay time, punctuality rate, aircraft utilization rate, and buffer time gap. Case analysis was validated to demonstrate the performance of the model and it showed that the model could accurately simulate the actual operation of airlines’ flight. Under normal condition, the key points of flight delays could be determined with the analysis of output indexes, whereas under flow control the transmission mode of delays were found to be passing down along the flight string as the delay time reduced gradually, and the turnaround time of directly affected flights was increased, while that of indirectly affected flights was reduced at the same time. |
| Key words: air transport flight operation system simulation flight scheduling Flexsim flow control |
