Calculation of maximum failure speed of military aircraft

Abstract

Abstract: According to the calculation principle of failure speed, the aircraft motion simulation model is established. The key point is to combine the brake model, pneumatic model, engine model and landing gear system model, and to compile the calculation program to simulate the aircraft‘s acceleration run -off section and brake stop section. Taking one military aircraft as an example, a high-precision model solver based on the fourth-order Runge Kutta method is established, and the calculation method of the maximum failure speed of military aircraft is given. Calculation result of the algorithm can well fit the actual test flight data, providing reference for the actual training of troops.

Key words: , maximum failure speed, simulation model, actual flight test

CLC Number:

V212.1

ZHENG Fengmin, AN Y an. Calculation of maximum failure speed of military aircraft [J]. Journal of Civil Aviation University of China, 2021, 39(2): 7-11.

References 18

[1]	LI S M, XU X H, MENG L H. Flight conflict forecasting based on chaotictimeseries[J]. Transaction of Nanjing University of Aeronautics &Astronautics, 2012, 29(4): 388-394.
[2]	CONGW, HUM H. Chaotic characteristics analysis of air traffic system[J].Transaction of Nanjing University of Aeronautics & Astronautics, 2014,31(6): 636-642.
[3]	郑旭芳. 空中交通流非线性特征研究[D]. 天津: 中国民航大学, 2016.
[4]	王超, 郑旭芳, 王蕾. 交汇航路空中交通流的非线性特研究[J].西南交通大学学报, 2017, 52(1): 171-178. [5] 王飞. 空中交通流非线性分形特征研究[J]. 西南交通大学学报, 2019, 54(6): 1147-1154. [6] 王飞. 基于 Hurst 指数的空中交通流长相关性实证分析[J]. 中国民航大学学报, 2019, 37(2): 1-4.
[7]	于寄语. 时间序列的结构变化和单位根检验[D]. 武汉: 华中科技大学, 2017.
[8]	吴国清, 莫则尧, 陈虹. 基于信息理论的时间序列非线性检测方法[J].计算机工程与科学, 2010(7): 83-85.
[9]	THEILER J, EUBANK S, LONGTIIN A, et al. Testing for nonlinearityin time series: the method of surrogate data[J]. Physica D:NonlinearPhenomena, 1992, 58: 77-94.
[10]	THEILER J, DEAN P. Constrained-realization Monte-Carlo method forhypothesis testing[J]. Physica D, 1996, 94(4): 221-235.
[11]	THEILER J, SCHMITZ A. Surrogate time series[J]. Physica D: NonlinearPhenomena, 2000, 54(1): 136-143.
[12]	雷敏, 王志中. 非线性时间序列的替代数据检验方法研究[J]. 电子与信息学报, 2001, 23(3): 248-254.
[13]	陈震. 五体船运动非线性特性检验方法[J]. 上海交通大学学报(自然版), 2012, 46(03): 417-422.
[14]	眭烨. 替代数据及其应用[D]. 上海: 华东师范大学, 2011.
[15]	石鑫, 周勇, 甘新年, 等. 机载多源飞行数据资料的非线性检验[J].计算机与数字工程, 2013(5): 729-732.
[16]	卢山, 王海燕. 证券市场的非线性和确定性检验[J]. 系统管理学报, 2005, 14(3): 235-238.
[17]	李聪改, 曹锐, 武政, 等. 基于样本熵的时间序列非线性检测方法研究[J]. 计算机工程与设计, 2014, 35(11): 4017-4020, 4048.
[18]	张勇. 交通流的非线性分析、预测和控制[D]. 北京: 北京交通大学, 2011.