符合适航认证要求的燃油温度计算方法

张瑞华; 刘卫华; 刘文怡

doi:10.13224/j.cnki.jasp.20210008

符合适航认证要求的燃油温度计算方法

doi: 10.13224/j.cnki.jasp.20210008

1.
南京航空航天大学航空学院飞行器环境控制与生命保障工业和信息化部重点实验室，南京 210016
2.
中国航空工业集团有限公司金城南京机电液压工程研究中心，南京 211106

基金项目: 国家自然科学基金民航联合基金（U1933121）；获江苏省科研与实践创新计划（KYCX19_0198）；中央高校基本科研业务费专项资金（NC2020001）；江苏高校优势学科建设工程；

详细信息

作者简介:
张瑞华（1997-），女，博士生，主要从事运输类飞机适航技术研究。

通讯作者:
刘卫华（1965-），男，教授，博士，主要从事飞行器环境与生命保障工程、飞行器燃油系统研究。E-mail：lwh@nuaa.edu.cn

中图分类号: V228
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出版历程
- 收稿日期: 2021-01-08
- 刊出日期: 2022-02-28

Calculation method of fuel temperature conforming to requirements of airworthiness certification

1.
Key Laboratory of Aircraft Environmental Control and Life Support of Ministry of Industry and Information Technology，College of Aerospace Engineering，Nanjing University of Aeronautics and Astronautics，Nanjing 210016，China
2.
Jincheng Nanjing Engineering Institute of Aircraft System，Aviation Industry Corporation of China Limited，Nanjing 211106，China

摘要

摘要: 基于适航认证需要，以某型飞机中央翼油箱隔舱在规定工况下实测的燃油温度变化曲线为输入条件，借助于MATLAB多项式分段拟合功能，获取了各个阶段燃油温度变化规律的高阶函数表达式；采用Monte Carlo评估模型中规定的指数衰减方程来表征燃油温度变化规律，其中环境总温（TAT）由评估模型中所指定方法获取，平衡温差和时间常数由改进后的遗传算法反演得出；将反演得到的平衡温差和时间常数输入Monte Carlo评估模型并开展计算，比较了计算所获的温度数据与实测的多项式拟合数据，结果表明：两者变化趋势完全一致，各时刻的温差均不超过1.67 K，整个航段燃油温度的计算值和实测值平均差约为0.050 1 K；且在误差值较大的阶段，程序计算值均高于飞行实测值，满足适航标准的相关要求。所提出的时间常数和平衡温差反演方法科学可信，它较好地解决了当前适航认证中的瓶颈问题，可有力地支撑大飞机适航认证工作的顺利开展。
- Monte Carlo评估模型 /
- 燃油温度 /
- 平衡温差 /
- 时间常数 /
- 遗传算法
Abstract: Based on the requirements of airworthiness certification，the measured fuel temperature change curve of the central wing fuel tank compartment of a certain aircraft under specified working conditions was taken as the input，and the high-order functional expression of the fuel temperature change rule in each stage was obtained by means of MATLAB polynomial piecewise fitting function.The exponential attenuation equation stipulated in the Monte Carlo evaluation model was used to characterize the change law of fuel temperature.The total ambient temperature （TAT） was obtained by the method specified in the evaluation model，and the equilibrium temperature difference and time constant were obtained by the improved genetic algorithm.The equilibrium temperature difference and time constant obtained by the inversion were then input into Monte Carlo evaluation model for calculation，the calculated temperature data and the measured polynomial data were compared.The results showed that both trends were exactly the same，the temperature difference between each moment did not exceed 1.67 K，the mean difference between the calculated value and the measured value of fuel temperature during the entire flight segment was about 0.050 1 K; in the stage with large error value，the value calculated by program was higher than the value measured by flight，which met the relevant requirements of airworthiness standards.The inversion method of time constant and equilibrium temperature difference is scientific and reliable，which can solve the bottleneck problem in airworthiness certification process and can effectively support the smooth development of airworthiness certification of large aircraft.
- Monte Carlo evaluation model /
- fuel temperature /
- equilibrium temperature difference /
- time constant /
- genetic algorithm

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参考文献(18)

[1]	EVOSEVICH B J,JOJIC I.Aircraft fuel tank flammability reduction method and system: CA2873226C[P].2017-12-19.
[2]	MICHAEL B,WILLIAM M C.Inerting of a vented aircraft fuel tank test article with nitrogen-enriched air[R].DOT/FAA/AR-01/6,2001.
[3]	LANGTON R,CLARK C,HEWITT M,et al.Aircraft fuel system[M].New York:John Wiley & Sons,2010:225-237.
[4]	MARTINOV N P.Aircraft fuel tank explosion reduction safety method: US6343465[P].2002-02-05.
[5]	EVOSEVICH B J,JOJIC I.Aircraft fuel tank flammability reduction method and system: US10000294[P].2018-06-19.
[6]	Federal Aviation Administration.Fuel tank flammability reduction means[R].FAA 25.981-2A,2008.
[7]	PAUL M D,SURAWSKI E.Temperature control system for fuel tank inerting system: US15208139[P].2018-01-18.
[8]	杨世铭,陶文铨.传热学[M].4版.上海：教育出版社,2006:398-399.
[9]	PASION A J.Inflight fuel tank temperature survey data [R].NASA CR-159569,1979.
[10]	LAWSON J C.Method for collecting liquid temperature data from a fuel tank: US5613778[P].1997-03-25.
[11]	康振烨，刘振侠，任国哲，等.基于MATLAB/Simulink的飞机燃油箱内燃油温度仿真计算[J].推进技术,2014,35（1）:62-69.
[12]	张兴娟,张作琦,高峰.先进战斗机超声速巡航过程中的燃油温度变化特性分析[J].航空动力学报,2010,25（2）:258-263.
[13]	WANG Ri,DONG Sujun,MENG Fanchao,et al.A shortcut method for solving long-term thermal dynamic analysis of aircraft fuel tank by thermal node network analysis and OpenFOAM software[J].Advances in Mechanical Engineering,2018,10（11）:16-19.
[14]	MAULIK U,BANDYOPADHYAY S.Genetic algorithm-based clustering technique[J].Pattern Recognition,2000,33（9）:1455-1465.
[15]	SIVARAM M,BATRI K,MOHAMMED A S,et al.Exploiting the local optima in genetic algorithm using tabu search[J].Indian Journal of Science and Technology,2019,12（1）:9-13.
[16]	ARMAGHANI D J,HASANIPANAH M,MAHDIYAR A,et al.Airblast prediction through a hybrid genetic algorithm-ANN model[J].Neural Computing and Applications,2018,29（9）:619-629.
[17]	CHATTERJEE S,SARKAR S,DEY N,et al.Hybrid non-dominated sorting genetic algorithm:Ⅱ neural network approach[M].Hershey,US:IGI Global,2018:264-286.
[18]	刘卫华，刘春阳，薛勇.油箱可燃性与适航符合性方法[M].北京：科学出版社，2017:118-121.