内埋式舱门机构的混合时变可靠性分析

doi:10.7527/S1000-6893.2025.32310

Abstract

Abstract:

As a key component of fighter aircraft， the embedded cabin door mechanism has a significant impact on the stealth performance of the fighter’s cabin door. In order to solve the problem of the step difference that may occur in the movement stage of the embedded cabin door mechanism with pre-deformed cabin door in advanced fighter aircraft， this paper analyzes the contact force and aerodynamic load of the embedded cabin door mechanism based on the established rigid-flexible coupling model of the embedded cabin door. On this basis， in order to solve the problem of accuracy reliability analysis of the cabin door mechanism， a time-dependent reliability analysis method based on symbolic misjudgment probability under hybrid uncertainty is proposed， which further improved the reliability analysis efficiency of the cabin door mechanism. First， the formula of the symbolic misjudgment probability is derived. Then， a symbolic misjudgment probability function is established as a learning function to simultaneously update random samples， interval samples， and time nodes. The accuracy and efficiency of the method are verified through a numerical example. Finally， the upper and lower bounds of the time-dependent failure probability of the embedded cabin door mechanism throughout the movement process are calculated using this method， providing a quantitative basis for the safety margin assessment and reliability design optimization of the embedded cabin door mechanism.

Key words: embedded cabin door mechanism, rigid-flexible coupling, symbolic misjudgment, hybrid uncertainties, time-dependent reliability

CLC Number:

V215.7

Yi CHEN, Pan WANG, Guijie LI, Fukang XIN. Hybrid time-dependent reliability analysis of embedded cabin door mechanism[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(3): 232310.

Figures/Tables 25

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Table 1

Calculation results of numerical examples

方法	$P f m i n$	$P f m a x$	$N c a l l$	$ε r m a x$
MCS	0.018 21	0.113 17	10⁵ $×$ 101
MCSO	0.017 00	0.114 00	10⁵ $×$ 200
SLK-HTRA	0.014 00	0.112 00	11+35	0.046 73
所提方法	0.018 10	0.113 00	11+9	0.047 34

Table 1

Fig.16

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Table 2

Parameter distribution of input variable

变量	含义	分布类型	均值/下界	标准差/上界
$X 1$	销轴A半径	正态分布	2.4	0.1
$X 2$	销轴B半径	正态分布	2.4	0.1
$X 3$	C处气动载荷	正态分布	15	1
$Y 1$	销轴A摩擦系数	区间分布	0.01	0.15
$Y 2$	销轴B摩擦系数	区间分布	0.01	0.15

Table 2

Table 3

Reliability analysis results of embedded cabin door mechanism

方法	$P f m i n$	$P f m a x$	$N c a l l$	$ε r m a x$
SLK-HTRA	0.000 2	0.012 3	30+26	0.043 0
所提方法	0.000 2	0.011 0	30+15	0.041 6

Table 3

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References 40

[1]	张立新，钟顺录，刘小冬，等. 先进战斗机强度设计技术发展与实践［J］. 航空学报， 2020， 41（6）： 623480.
	ZHANG L X， ZHONG S L， LIU X D， et al. Development and practice of strength design technology for advanced fighters［J］. Acta Aeronautica et Astronautica Sinica， 2020， 41（6）： 623480 （in Chinese）.
[2]	吴继飞，罗新福，范召林. 内埋式弹舱流场特性及武器分离特性改进措施［J］. 航空学报， 2009， 30（10）： 1840-1845.
	WU J F， LUO X F， FAN Z L. Flow control method to improve cavity flow and store separation characteristics［J］. Acta Aeronautica et Astronautica Sinica， 2009， 30（10）： 1840-1845 （in Chinese）.
[3]	张群峰，闫盼盼，黎军. 内埋式弹舱与弹体相互影响的精细模拟［J］. 兵工学报， 2016， 37（12）： 2366-2376.
	ZHANG Q F， YAN P P， LI J. Elaborate simulation of interaction effect between internal weapon bay and missile［J］. Acta Armamentarii， 2016， 37（12）： 2366-2376 （in Chinese）.
[4]	周长聪，赵浩东，常琦，等. 飞机舱门泄压阀机构磨损可靠性与灵敏度分析［J］. 北京航空航天大学学报， 2021， 47（4）： 690-697.
	ZHOU C C， ZHAO H D， CHANG Q， et al. Reliability and sensitivity analysis of relief valve mechanism of aircraft door considering wear［J］. Journal of Beijing University of Aeronautics and Astronautics， 2021， 47（4）： 690-697 （in Chinese）.
[5]	刘敬一，张玉刚，庄新臣，等. 考虑间歇期的飞机连杆式舱门收放机构竞争失效分析［J］. 西北工业大学学报， 2021， 39（5）： 1105-1113.
	LIU J Y， ZHANG Y G， ZHUANG X C， et al. Competing failure analysis of aircraft connecting-rod-type cabin door retraction mechanism with intermission considered［J］. Journal of Northwestern Polytechnical University， 2021， 39（5）： 1105-1113 （in Chinese）.
[6]	NIE B P， HU X L， LI Z F. Effects of doors on an open cavity flow at Mach number 6［J］. Chinese Journal of Aeronautics， 2025， 38（2）： 103204.
[7]	WU M C， XIAHOU T， CHEN J T， et al. Differentiating effects of input aleatory and epistemic uncertainties on system output： A separating sensitivity analysis approach［J］. Mechanical Systems and Signal Processing， 2022， 181： 109421.
[8]	ZHANG J H， XIAO M， GAO L， et al. A novel projection outline based active learning method and its combination with Kriging metamodel for hybrid reliability analysis with random and interval variables［J］. Computer Methods in Applied Mechanics and Engineering， 2018， 341： 32-52.
[9]	LÜ H， SHANGGUAN W B， YU D J. An imprecise probability approach for squeal instability analysis based on evidence theory［J］. Journal of Sound and Vibration， 2017， 387： 96-113.
[10]	WANG C， ZHANG H， BEER M. Computing tight bounds of structural reliability under imprecise probabilistic information［J］. Computers & Structures， 2018， 208： 92-104.
[11]	WANG L， XIONG C， YANG Y W. A novel methodology of reliability-based multidisciplinary design optimization under hybrid interval and fuzzy uncertainties［J］. Computer Methods in Applied Mechanics and Engineering， 2018， 337： 439-457.
[12]	WANG C， QIANG X， XU M H， et al. Recent advances in surrogate modeling methods for uncertainty quantification and propagation［J］. Symmetry， 2022， 14（6）： 1219.
[13]	FAN H R， WANG C， LI S H. Novel method for reliability optimization design based on rough set theory and hybrid surrogate model［J］. Computer Methods in Applied Mechanics and Engineering， 2024， 429： 117170.
[14]	DONG B F， LU Z Z. Efficient adaptive Kriging for system reliability analysis with multiple failure modes under random and interval hybrid uncertainty［J］. Chinese Journal of Aeronautics， 2022， 35（5）： 333-346.
[15]	XIN F K， WANG P， HU H H， et al. An efficient system reliability analysis method for flap mechanism under random-interval hybrid uncertainties［J］. Structural and Multidisciplinary Optimization， 2024， 67（8）： 135.
[16]	XIE H C， LIAO D H. A time-dependent reliability analysis method based on multi-level meta-models for problems involving interval variables［J］. Probabilistic Engineering Mechanics， 2022， 70： 103369.
[17]	GONZALEZ-FERNANDEZ R A， LEITE DA SILVA A M. Reliability assessment of time-dependent systems via sequential cross-entropy Monte Carlo simulation［J］. IEEE Transactions on Power Systems， 2011， 26（4）： 2381-2389.
[18]	DU W Q， LUO Y X， WANG Y Q. Time-variant reliability analysis using the parallel subset simulation［J］. Reliability Engineering & System Safety， 2019， 182： 250-257.
[19]	LING C Y， LU Z Z. Adaptive Kriging coupled with importance sampling strategies for time-variant hybrid reliability analysis［J］. Applied Mathematical Modelling， 2020， 77： 1820-1841.
[20]	JIANG C， WEI X P， HUANG Z L， et al. An outcrossing rate model and its efficient calculation for time-dependent system reliability analysis［J］. Journal of Mechanical Design， 2017， 139（4）： 041402.
[21]	HU Z， DU X P. A sampling approach to extreme value distribution for time-dependent reliability analysis［J］. Journal of Mechanical Design， 2013， 135（7）： 071003.
[22]	DU X P. Time-dependent mechanism reliability analysis with envelope functions and first-order approximation［J］. Journal of Mechanical Design， 2014， 136（8）： 081010.
[23]	WANG Y， ZENG S K， GUO J B. Time-dependent reliability-based design optimization utilizing nonintrusive polynomial chaos［J］. Journal of Applied Mathematics， 2013， 2013（1）： 513261.
[24]	QIAN H M， HUANG H Z， LI Y F. A novel single-loop procedure for time-variant reliability analysis based on Kriging model［J］. Applied Mathematical Modelling， 2019， 75： 735-748.
[25]	LI M Y， WANG Z Q. LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems［J］. Reliability Engineering & System Safety， 2022， 217： 108014.
[26]	HU Z， MAHADEVAN S. A single-loop Kriging surrogate modeling for time-dependent reliability analysis［J］. Journal of Mechanical Design， 2016， 138（6）： 061406.
[27]	WANG Z Q， WANG P F. A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis［J］. Reliability Engineering & System Safety， 2015， 142： 346-356.
[28]	LI F Y， LIU J， YAN Y F， et al. A time-variant reliability analysis method for non-linear limit-state functions with the mixture of random and interval variables［J］. Engineering Structures， 2020， 213： 110588.
[29]	XIE S J， PAN B S， DU X P. High dimensional model representation for hybrid reliability analysis with dependent interval variables constrained within ellipsoids［J］. Structural and Multidisciplinary Optimization， 2017， 56（6）： 1493-1505.
[30]	WANG L， LIANG J X， YANG Y W， et al. Time-dependent reliability assessment of fatigue crack growth modeling based on perturbation series expansions and interval mathematics［J］. Theoretical and Applied Fracture Mechanics， 2018， 95： 104-118.
[31]	CHANG Q， ZHOU C C， WEI P F， et al. A new non-probabilistic time-dependent reliability model for mechanisms with interval uncertainties［J］. Reliability Engineering & System Safety， 2021， 215： 107771.
[32]	ZHAO Q Q， DUAN J Y， WU T F， et al. Time-dependent reliability analysis under random and interval uncertainties based on Kriging modeling and saddlepoint approximation［J］. Computers & Industrial Engineering， 2023， 182： 109391.
[33]	柏长青，左彦飞，耿斌斌，等. 基于多体接触瞬态动力学支承不同心模拟分析方法［J］. 振动与冲击， 2021， 40（10）： 81-88.
	BAI C Q， ZUO Y F， GENG B B， et al. Bearing misalignment simulation and analysis method based on multi-body transient contact dynamics［J］. Journal of Vibration and Shock， 2021， 40（10）： 81-88 （in Chinese）.
[34]	ZHOU C C， GAO S J， CHANG Q， et al. Hybrid time-dependent reliability analysis under a mixture of random and interval uncertainties［J］. International Journal for Numerical Methods in Engineering， 2023， 124（11）： 2529-2551.
[35]	LU Y X， LU Z Z， FENG K X. A novel training point selection strategy guided by the maximum reduction of structural state misclassification probability for time-dependent reliability analysis［J］. Aerospace Science and Technology， 2023， 140： 108493.
[36]	YANG X F， LIU Y S， MI C Y， et al. System reliability analysis through active learning Kriging model with truncated candidate region［J］. Reliability Engineering & System Safety， 2018， 169： 235-241.
[37]	CORNELL C A. Bounds on the reliability of structural systems［J］. Journal of the Structural Division， 1967， 93（1）： 171-200.
[38]	XIN F K， WANG P， CHEN Y， et al. A new uncertainty reduction-guided single-loop Kriging coupled with subset simulation for time-dependent reliability analysis［J］. Reliability Engineering & System Safety， 2025， 261： 111065.
[39]	ZHAO Q Q， WU T F， HONG J. An envelope-function-based algorithm for time-dependent reliability analysis of structures with hybrid uncertainties［J］. Applied Mathematical Modelling， 2022， 110： 493-512.
[40]	YANG X F， LIU Y S， GAO Y， et al. An active learning Kriging model for hybrid reliability analysis with both random and interval variables［J］. Structural and Multidisciplinary Optimization， 2015， 51（5）： 1003-1016.

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