Abstract

Due to the extremely rough working environment, aero-hydraulic pipes face serious dynamic failure problems in applications for practical engineering. This paper proposes a dynamic reliability and moment-independent global sensitivity analysis (GSA) method to evaluate the dynamic reliability and the effects of random input variables on the dynamic reliability of aero-hydraulic pipes. Based on the Miner criterion for the cumulative damage of structural fatigue, this paper establishes the dynamic reliability analysis method under the condition of double random vibration. In order to further analyze the influence of the uncertainty of each random variable of pipe on its dynamic reliability, a moment-independent global sensitivity index for dynamic reliability based on cumulative distribution function is proposed in this paper. The index can reflect the effects of random variables on dynamic reliability quantitatively. Based on the proposed GSA method of dynamic reliability, a sparse grid integral (SGI) method is introduced to solve the dynamic reliability and moment-independent global sensitivity index, with high computational efficiency. Finally, the effects of clamp supports, diameters, and curvature of curved pipe on the dynamic reliability and GSA are analyzed through a hydraulic piping example.

References

1.
Liu
,
Y. S.
,
He
,
X. D.
,
Zou
,
Y. H.
, and
Yue
,
Z. F.
,
2011
, “
Dynamical Strength and Design Optimization of Pipe-Joint System Under Pressure Impact Load
,”
Proc. Inst. Mech. Eng. G
,
8
(
226
), pp.
1029
1040
.10.1177/0954410011416177
2.
Tricarico
,
C.
,
Gargano
,
R.
,
Kapelan
,
Z.
,
Savic
,
D.
, and
de Marinis
,
G.
,
2006
, “
Economic Level of Reliability for the Rehabilitation of Hydraulic Networks
,”
Civ. Eng. Environ. Syst.
,
23
(
3
), pp.
191
207
.10.1080/10286600600789383
3.
Higo
,
H.
,
Yamamoto
,
K.
,
Tanaka
,
K.
,
Sakurai
,
Y.
, and
Nakada
,
T.
,
2000
, “
Bondgraph Analysis on Pressure Fluctuation in Hydraulic Pipes
,”
26th Annual Conference of the IEEE Industrial Electronics Society, International Conference on Industrial Electronics, Control and Instrumentation
(
IECON
),
Tokyo, Japan
,
Oct. 22–28
, pp.
1556
1561
.10.1109/IECON.2000.972506
4.
Zhang
,
S. W.
, and
Zhou
,
W. X.
,
2014
, “
An Efficient Methodology for the Reliability Analysis of Corroding Pipelines
,”
ASME J. Pressure Vessel Technol.
,
136
(
4
), p.
041701
.10.1115/1.4026797
5.
Rastogi
,
R.
,
Ghosh
,
S.
,
Ghosh
,
A. K.
, and
Vaze
,
K. K.
,
2017
, “
Reliability Assessment of Failure Assessment Diagram Based Fitness for Service Procedure Including the Effect of Bias in Modeling
,”
ASME J. Pressure Vessel Technol.
,
139
(
5
), p.
051602
.10.1115/1.4037264
6.
Liu
,
W.
,
Liu
,
Y. S.
, and
Yue
,
Z. F.
,
2010
, “
Dynamic Reliability of Aircraft Hydraulic Pipelines Under Random Pressure Pulsation and Vibration
,”
Multidiscip. Model. Mater. Struct.
,
4
(
6
), pp.
493
507
.10.1108/15736101011095154
7.
Han
,
Y. B.
,
Bai
,
G. C.
, and
Li
,
X. Y.
,
2010
, “
Reliability Analysis of Certain Aircraft's Hydraulic Pipe
,”
International Conference on Educational and Network Technology
, Qinhuangdao, China, June 25–27, pp.
377
380
.
8.
Zhang
,
T.
, and
Zhang
,
Y.
,
2014
, “
Reliability of Hydraulic Pressure Pipeline Made by Different Materials Under Impact Vibration With Finite Probability Information
,”
Mater. Res. Innovations
,
18
, pp.
66
68
.10.1179/1432891714Z.000000000914
9.
Cabrera-Miranda
,
J. M.
, and
Paik
,
J. K.
,
2018
, “
Long-Term Stochastic Heave-Induced Dynamic Buckling of a Top-Tensioned Riser and Its Influence on the Ultimate Limit State Reliability
,”
Ocean Eng.
,
149
, pp.
156
169
.10.1016/j.oceaneng.2017.12.012
10.
Guo
,
Q.
,
Liu
,
Y. S.
,
Zhao
,
Y. Z.
,
Li
,
B. H.
, and
Yao
,
Q.
,
2019
, “
Improved Resonance Reliability and Global Sensitivity Analysis of Multi-Span Pipes Conveying Fluid Based on Active Learning Kriging Model
,”
Int. J. Pressure Vessels Piping
,
170
(
2019
), pp.
92
101
.10.1016/j.ijpvp.2019.01.016
11.
Rice
,
S. O.
,
1945
, “
Mathematical Analysis of Random Noise
,”
Bell Syst. Tech. J.
,
24
(
1
), pp.
46
156
.10.1002/j.1538-7305.1945.tb00453.x
12.
Miles
,
J. W.
,
1957
, “
On Structural Fatigue Under Random Loading
,”
J. Acoust. Soc. Am.
,
1
(
29
), p.
176
.10.1121/1.1918447
13.
Jiang
,
X. M.
, and
Mahadevan
,
S.
,
2008
, “
Bayesian Wavelet Method for Multivariate Model Assessment of Dynamic Systems
,”
J. Sound Vib.
,
312
(
4–5
), pp.
694
712
.10.1016/j.jsv.2007.11.025
14.
Zhai
,
H. B.
,
Wu
,
Z. Y.
,
Liu
,
Y. S.
, and
Yue
,
Z. F.
,
2013
, “
The Dynamic Reliability Analysis of Pipe Conveying Fluid Based on a Refined Response Surface Method
,”
J. Vib. Control
,
4
(
21
), pp.
790
800
.10.1177/1077546313491443
15.
Shi
,
Y.
,
Lu
,
Z. Z.
,
Cheng
,
K.
, and
Zhou
,
Y. C.
,
2017
, “
Temporal and Spatial Multi-Parameter Dynamic Reliability and Global Reliability Sensitivity Analysis Based on the Extreme Value Moments
,”
Struct. Multidiscip. Optim.
,
2017
(
56
), pp.
117
29
.10.1007/s00158-017-1651-2
16.
Lu
,
C.
,
Feng
,
Y. W.
,
Liem
,
R. P.
, and
Fei
,
C. W.
,
2018
, “
Improved Kriging With Extremum Response Surface Method for Structural Dynamic Reliability and Sensitivity Analyses
,”
Aerosp. Sci. Technol.
,
76
, pp.
164
75
.10.1016/j.ast.2018.02.012
17.
Heiss
,
F.
, and
Winschel
,
V.
,
2008
, “
Likelihood Approximation by Numerical Integration on Sparse Grids
,”
J. Econometrics
,
144
(
1
), pp.
62
80
.10.1016/j.jeconom.2007.12.004
18.
Lu
,
Z. Z.
,
Song
,
J.
,
Song
,
S. F.
,
Yue
,
Z. F.
, and
Wang
,
J.
,
2010
, “
Reliability Sensitivity by Method of Moments
,”
Appl. Math. Model.
,
34
(
10
), pp.
2860
2871
.10.1016/j.apm.2009.12.020
19.
Zhao
,
Y. G.
, and
Ono
,
T.
,
2001
, “
Moment Methods for Structural Reliability
,”
Struct. Saf.
,
23
(
1
), pp.
47
75
.10.1016/S0167-4730(00)00027-8
20.
Zivanovic
,
R.
,
2012
, “
Global Sensitivity Analysis of Transmission Line Fault-Locating Algorithms Using Sparse Grid Regression
,”
Reliab. Eng. Syst. Saf.
,
107
, pp.
132
138
.10.1016/j.ress.2011.12.005
21.
Zhou
,
C. C.
,
Lu
,
Z. Z.
, and
Li
,
W.
,
2015
, “
Sparse Grid Integration Based Solutions for Moment-Independent Importance Measures
,”
Probab. Eng. Mech.
,
39
, pp.
46
55
.10.1016/j.probengmech.2014.12.002
22.
Borgonovo
,
E.
,
2007
, “
A New Uncertainty Importance Measure
,”
Reliab. Eng. Syst. Saf.
,
92
, pp.
771
784
.10.1016/j.ress.2006.04.015
23.
Borgonovo
,
E.
,
Castaings
,
W.
, and
Tarantola
,
S.
,
2011
, “
Moment Independent Importance Measures: New Results and Analytical Test Cases
,”
Risk Anal.
,
3
(
31
), pp.
404
428
.10.1111/j.1539-6924.2010.01519.x
24.
Liu
,
Q.
, and
Homma
,
T.
,
2009
, “
A New Computational Method of a Moment-Independent Uncertainty Importance Measure
,”
Reliab. Eng. Syst. Saf.
,
94
(
7
), pp.
1205
1211
.10.1016/j.ress.2008.10.005
25.
Li
,
Y.
,
Barkey
,
L. M. E.
, and
Kang
,
H. T.
,
2011
,
Metal Fatigue Analysis Handbook: Practical Problem-Solving Techniques for Computer-Aided Engineering
,
Elsevier
, Butterworth-Heinemann, Oxford, UK.
26.
Zhao
,
Y. G.
,
Ono
,
T.
, and
Idota
,
H.
,
1999
, “
Response Uncertainty and Time-Variant Reliability Analysis for Hysteretic MDF Structures
,”
Earthq. Eng. Struct. D
,
28
(
10
), pp.
1187
1213
.10.1002/(SICI)1096-9845(199910)28:10<1187::AID-EQE863>3.0.CO;2-E
27.
Kieslich
,
C. A.
,
Boukouvala
,
F.
, and
Floudas
,
C. A.
,
2018
, “
Optimization of Black-Box Problems Using Smolyak Grids and Polynomial Approximations
,”
J. Global Optim.
,
71
(
4
), pp.
845
869
.10.1007/s10898-018-0643-0
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