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基于飞机滑跑动力学模型的侧风湿跑道着陆状态分析及预测模型

蔡靖 李建平 牛玉发 李岳 戴轩

交通信息与安全2025,Vol.43Issue(6):54-66,75,14.
交通信息与安全2025,Vol.43Issue(6):54-66,75,14.DOI:10.3963/j.jssn.1674-4861.2025.06.006

基于飞机滑跑动力学模型的侧风湿跑道着陆状态分析及预测模型

An Analysis and Prediction Model of Aircraft Landing States on Wet Runways with Crosswind Based on Taxiing Dynamics Model

蔡靖 1李建平 2牛玉发 2李岳 2戴轩2

作者信息

  • 1. 中国民航大学交通科学与工程学院 天津 300300||民航机场智能建造与工业化工程技术研究中心 天津 300300
  • 2. 中国民航大学交通科学与工程学院 天津 300300
  • 折叠

摘要

Abstract

To address the frequent occurrence of runway excursion accidents in aviation safety,this study conducts a quantitative analysis of the factors influencing aircraft landing taxiing states and establishes a corresponding predic-tion model.A human-aircraft-environment coupled dynamics model for aircraft landing taxiing is developed in Simulink,focusing on the Airbus A320-214.This model incorporates a dynamic engine thrust module and integrates pilot operations,aircraft dynamics,crosswind,and wet runway surface conditions.Closed-loop simulations yield 3,191 sets of data for analysis.The influence of various factors,such as water film thickness,pilot reaction speed,and touchdown ground speed,on runway excursions is quantified using multiple linear regression.The mechanism of thrust reverser imbalance affecting deviation distance is analyzed,leading to the establishment of predictive models for landing taxiing distance and deviation distance.The findings indicate that during landing taxiing,touchdown ground speed has a greater impact on taxiing distance than on deviation distance.Environmental factors like water film thickness,friction imbalance,and crosswind velocity are more likely to cause runway deviations.Among these,friction imbalance has the most pronounced effect on yaw direction,exceeding the impact of thrust reverser imbal-ance by a factor of 14.5,which ranks as the second most influential factor.Under specified conditions,a thrust re-verser imbalance exceeding 0.4 pushes the deviation distance close to the safety threshold,representing a substantial risk.The multiple linear regression model for taxiing distance prediction demonstrates a coefficient of determination(R²)of 0.88,a mean absolute error(MAE)of 48.32 m,and a mean absolute percentage error(MAPE)of 7.75%.Pre-diction deviations for actual cases remain within 5%,indicating superior accuracy of the model for predicting air-craft landing taxiing distance.

关键词

航空运输安全/湿滑道面/侧风/着陆距离/偏出距离

Key words

aviation safety/wet runway pavement/crosswind/landing distance/offset distance

分类

交通工程

引用本文复制引用

蔡靖,李建平,牛玉发,李岳,戴轩..基于飞机滑跑动力学模型的侧风湿跑道着陆状态分析及预测模型[J].交通信息与安全,2025,43(6):54-66,75,14.

基金项目

国家自然科学基金项目(52472369)、天津市技术术创新引导专项(基金)-企业科技特派员项目(25YDTPJC00370)、民航机场智能建筑与工业化工程技术研究中心开放课题(MHJGKFKT-04)资助 (52472369)

交通信息与安全

OACSCD

1674-4861

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