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OACSCD
An Analysis and Prediction Model of Aircraft Landing States on Wet Runways with Crosswind Based on Taxiing Dynamics Model
针对航空运输安全领域飞机冲偏出跑道事故频发问题,进行了飞机着陆滑跑状态影响因素量化分析,建立了冲偏出跑道预测模型.基于Simulink软件以空客A320-214机型为研究对象,新增发动机推力动态模块,构建了包含驾驶员、飞机机体、侧风与湿滑道面的飞机着陆滑跑人-机-环境耦合动力学模型,进行飞机着陆滑跑状态人机闭环仿真,获得3191组仿真数据.采用多元线性回归分析方法量化分析水膜厚度、驾驶员反应速度、着陆接地时刻地速等影响因素对飞机冲偏出跑道的影响,分析反推不平衡度影响偏出距离的影响机制,建立多元线性回归飞机着陆滑跑预测模型.得到以下结论:飞机在着陆滑跑时,着陆接地时刻地速对滑跑距离的影响要比对偏出距离影响更大,而水膜厚度、摩阻不平衡度以及侧风风速等环境因素更容易导致飞机偏出跑道;其中,摩阻不平衡度对偏航方向的影响最为突出,其影响程度达到反推不平衡度的14.5倍,而反推不平衡度的影响居于第2位;当反推不平衡度达到0.4时,偏出距离已逼近安全阈值,具有实质偏出风险;多元线性回归滑跑距离预测模型的决定系数(R2)为0.88、平均绝对误差(mean absolute error,MAE)为48.32 m、平均绝对百分比误差(mean absolute percentage error,MAPE)为7.75%,对实际案例的预测偏差均在5%以内,体现出该模型对飞机着陆滑跑距离预测具有较为优越的准确性.
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.
蔡靖;李建平;牛玉发;李岳;戴轩
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中国民航大学交通科学与工程学院 天津 300300中国民航大学交通科学与工程学院 天津 300300中国民航大学交通科学与工程学院 天津 300300中国民航大学交通科学与工程学院 天津 300300
交通工程
航空运输安全湿滑道面侧风着陆距离偏出距离
aviation safetywet runway pavementcrosswindlanding distanceoffset distance
《交通信息与安全》 2025 (6)
54-66,75,14
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
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