Abstract

System reliability is quantified by the probability that a system performs its intended function in a period of time without failures. System reliability can be predicted if all the limit-state functions of the components of the system are available, and such a prediction is usually time consuming. This work develops a time-dependent system reliability method that is extended from the component time-dependent reliability method using the envelope method and second-order reliability method. The proposed method is efficient and is intended for series systems with limit-state functions whose input variables include random variables and time. The component reliability is estimated by the second-order component reliability method with an improve envelope approach, which produces a component reliability index. The covariance between component responses is estimated with the first-order approximations, which are available from the second-order approximations of the component reliability analysis. Then, the joint distribution of all the component responses is approximated by a multivariate normal distribution with its mean vector being component reliability indexes and covariance being those between component responses. The proposed method is demonstrated and evaluated by three examples.

References

1.
Rausand
,
M.
, and
Høyland
,
A.
,
2003
,
System Reliability Theory: Models, Statistical Methods, and Applications
,
John Wiley & Sons
,
New York
.
2.
Hu
,
Z.
, and
Du
,
X.
,
2014
, “
Lifetime Cost Optimization With Time-Dependent Reliability
,”
Eng. Optim.
,
46
(
10
), pp.
1389
1410
. 10.1080/0305215X.2013.841905
3.
Singh
,
A.
,
Mourelatos
,
Z. P.
, and
Li
,
J.
,
2010
, “
Design for Lifecycle Cost Using Time-Dependent Reliability
,”
ASME J. Mech. Des.
,
132
(
9
), p.
091008
. 10.1115/1.4002200
4.
Wu
,
H.
,
Zhu
,
Z.
, and
Du
,
X.
,
2020
, “
System Reliability Analysis With Autocorrelated Kriging Predictions
,”
ASME J. Mech. Des.
,
142
(
10
), p.
101702
. 10.1115/1.4046648
5.
Zhang
,
J.
, and
Du
,
X.
,
2011
, “
Time-Dependent Reliability Analysis for Function Generator Mechanisms
,”
ASME J. Mech. Des.
,
133
(
3
), p.
031005
. 10.1115/1.4003539
6.
Caprani
,
C. C.
, and
OBrien
,
E. J.
,
2010
, “
The Use of Predictive Likelihood to Estimate the Distribution of Extreme Bridge Traffic Load Effect
,”
Struct. Safety
,
32
(
2
), pp.
138
144
. 10.1016/j.strusafe.2009.09.001
7.
Hu
,
Z.
, and
Du
,
X.
,
2012
, “
Reliability Analysis for Hydrokinetic Turbine Blades
,”
Renewable Energy
,
48
, pp.
251
262
. 10.1016/j.renene.2012.05.002
8.
Andrieu-Renaud
,
C.
,
Sudret
,
B.
, and
Lemaire
,
M.
,
2004
, “
The PHI2 Method: A Way to Compute Time-Variant Reliability
,”
Reliab. Eng. Syst. Safety
,
84
(
1
), pp.
75
86
. 10.1016/j.ress.2003.10.005
9.
Hu
,
Z.
, and
Du
,
X.
,
2013
, “
Time-Dependent Reliability Analysis With Joint Upcrossing Rates
,”
Structural Multidisciplinary Optim.
,
48
(
5
), pp.
893
907
. 10.1007/s00158-013-0937-2
10.
Jiang
,
C.
,
Wei
,
X. P.
,
Huang
,
Z. L.
, and
Liu
,
J.
,
2017
, “
An Outcrossing Rate Model and Its Efficient Calculation for Time-Dependent System Reliability Analysis
,”
ASME J. Mech. Des.
,
139
(
4
), p.
041402
. 10.1115/1.4035792
11.
Hu
,
Z.
,
Li
,
H.
,
Du
,
X.
, and
Chandrashekhara
,
K.
,
2013
, “
Simulation-Based Time-Dependent Reliability Analysis for Composite Hydrokinetic Turbine Blades
,”
Struct. Multidiscip. Optim.
,
47
(
5
), pp.
765
781
. 10.1007/s00158-012-0839-8
12.
Hu
,
Z.
, and
Mahadevan
,
S.
,
2016
, “
A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis
,”
ASME J. Mech. Des.
,
138
(
6
), p.
061406
. 10.1115/1.4033428
13.
Hu
,
Z.
, and
Du
,
X.
,
2015
, “
Mixed Efficient Global Optimization for Time-Dependent Reliability Analysis
,”
ASME J. Mech. Des.
,
137
(
5
), p.
051401
. 10.1115/1.4029520
14.
Wang
,
Z.
, and
Wang
,
P.
,
2013
, “
A New Approach for Reliability Analysis With Time-Variant Performance Characteristics
,”
Reliab. Eng. Syst. Safety
,
115
, pp.
70
81
. 10.1016/j.ress.2013.02.017
15.
Rice
,
S. O.
,
1944
, “
Mathematical Analysis of Random Noise
,”
Bell Syst. Tech. J.
,
23
(
3
), pp.
282
332
. 10.1002/j.1538-7305.1944.tb00874.x
16.
Du
,
X.
,
2014
, “
Time-dependent Mechanism Reliability Analysis With Envelope Functions and First-Order Approximation
,”
ASME J. Mech. Des.
,
136
(
8
), p.
081080
. 10.1115/1.4027636
17.
Li
,
J.
,
Chen
,
J.-b.
, and
Fan
,
W.-l.
,
2007
, “
The Equivalent Extreme-Value Event and Evaluation of the Structural System Reliability
,”
Struct. Safety
,
29
(
2
), pp.
112
131
. 10.1016/j.strusafe.2006.03.002
18.
Singh
,
A.
, and
Mourelatos
,
Z. P.
,
2010
, “
On the Time-Dependent Reliability of Non-Monotonic, Non-Repairable Systems
,”
SAE Int. J. Mater. Manuf.
,
3
(
1
), pp.
425
444
. 10.4271/2010-01-0696
19.
Hu
,
Z.
, and
Du
,
X.
, “
Second Order Reliability Method for Time-Dependent Reliability Analysis Using Sequential Efficient Global Optimization
,”
Proceedings of the ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2B: 45th Design Automation Conference
,
Anaheim, CA
,
Aug. 18–21
,
American Society of Mechanical Engineers Digital Collection
, p. V02BT03A038. https://doi.org/10.1115/DETC2019-97541
20.
Song
,
J.
, and
Der Kiureghian
,
A.
,
2006
, “
Joint First-Passage Probability and Reliability of Systems Under Stochastic Excitation
,”
J. Eng. Mech.
,
132
(
1
), pp.
65
77
. 10.1061/(asce)0733-9399(2006)132:1(65)
21.
Radhika
,
B.
,
Panda
,
S.
, and
Manohar
,
C.
,
2008
, “
Time Variant Reliability Analysis of Nonlinear Structural Dynamical Systems Using Combined Monte Carlo Simulations and Asymptotic Extreme Value Theory
,”
Comput. Modeling Eng. Sci.
,
27
(
1/2
), p.
79
.
22.
Yu
,
S.
,
Wang
,
Z.
, and
Meng
,
D.
,
2018
, “
Time-Variant Reliability Assessment for Multiple Failure Modes and Temporal Parameters
,”
Struct. Multidiscip. Optim.
,
58
(
4
), pp.
1705
1717
. 10.1007/s00158-018-1993-4
23.
Gong
,
C.
, and
Frangopol
,
D. M.
,
2019
, “
An Efficient Time-Dependent Reliability Method
,”
Struct. Safety
,
81
, p.
101864
. 10.1016/j.strusafe.2019.05.001
24.
Hu
,
Z.
, and
Mahadevan
,
S.
,
2015
, “
Time-Dependent System Reliability Analysis Using Random Field Discretization
,”
ASME J. Mech. Des.
,
137
(
10
), p.
101404
. 10.1115/1.4031337
25.
Jiang
,
C.
,
Wei
,
X.
,
Wu
,
B.
, and
Huang
,
Z.
,
2018
, “
An Improved TRPD Method for Time-Variant Reliability Analysis
,”
Struct. Multidiscip. Optim.
,
58
(
5
), pp.
1935
1946
. 10.1007/s00158-018-2002-7
26.
Hohenbichler
,
M.
, and
Rackwitz
,
R.
,
1982
, “
First-Order Concepts in System Reliability
,”
Struct. Safety
,
1
(
3
), pp.
177
188
. 10.1016/0167-4730(82)90024-8
27.
Wu
,
H.
, and
Du
,
X.
,
2020
, “
System Reliability Analysis With Second-Order Saddlepoint Approximation
,”
ASME J. Risk Uncert. Eng. Sys. Part B Mech. Eng.
,
6
(
4
), p.
041001
. 10.1115/1.4047217
28.
Jones
,
D. R.
,
Schonlau
,
M.
, and
Welch
,
W. J.
,
1998
, “
Efficient Global Optimization of Expensive Black-Box Functions
,”
J. Global Optim.
,
13
(
4
), pp.
455
492
. 10.1023/A:1008306431147
29.
Wang
,
Z.
, and
Wang
,
P.
,
2012
, “
A Nested Extreme Response Surface Approach for Time-Dependent Reliability-Based Design Optimization
,”
ASME J. Mech. Des.
,
134
(
12
), p.
121007
. 10.1115/1.4007931
30.
Goutis
,
C.
, and
Casella
,
G. J. A. S.
,
1999
, “
Explaining the Saddlepoint Approximation
,”
Am. Stat.
,
53
(
3
), pp.
216
224
. 10.1080/00031305.1999.10474463
31.
Hu
,
Z.
, and
Du
,
X.
,
2018
, “
Saddlepoint Approximation Reliability Method for Quadratic Functions in Normal Variables
,”
Struct. Safety
,
71
, pp.
24
32
. 10.1016/j.strusafe.2017.11.001
32.
Zeng
,
P.
,
Jimenez
,
R.
,
Li
,
T.
,
Chen
,
Y.
, and
Feng
,
X.
,
2017
, “
Application of Quasi-Newton Approximation-Based SORM for System Reliability Analysis of a Layered Soil Slope
,”
Geo-Risk
,
2017
, pp.
111
119
. 10.1061/9780784480700.011
33.
Gollwitzer
,
S.
, and
Rackwitz
,
R.
,
1988
, “
An Efficient Numerical Solution to the Multinormal Integral
,”
Probab. Eng. Mech.
,
3
(
2
), pp.
98
101
. 10.1016/0266-8920(88)90021-5
34.
Genz
,
A.
,
1992
, “
Numerical Computation of Multivariate Normal Probabilities
,”
J. Comput. Graphical Stat.
,
1
(
2
), pp.
141
149
.
35.
Genz
,
A.
,
2004
, “
Numerical Computation of Rectangular Bivariate and Trivariate Normal and t Probabilities
,”
Stat. Comput.
,
14
(
3
), pp.
251
260
. 10.1023/B:STCO.0000035304.20635.31
36.
Genz
,
A.
, and
Bretz
,
F.
,
2009
,
Computation of Multivariate Normal and t Probabilities
,
Springer Science & Business Media
,
New York
.
37.
Li
,
C.-C.
, and
Der Kiureghian
,
A.
,
1993
, “
Optimal Discretization of Random Fields
,”
J. Eng. Mech.
,
119
(
6
), pp.
1136
1154
. 10.1061/(ASCE)0733-9399(1993)119:6(1136)
38.
Wei
,
P.
,
Liu
,
F.
, and
Tang
,
C.
,
2018
, “
Reliability and Reliability-Based Importance Analysis of Structural Systems Using Multiple Response Gaussian Process Model
,”
Reliab. Eng. Syst. Safety
,
175
, pp.
183
195
. 10.1016/j.ress.2018.03.013
39.
Hu
,
Z.
,
Zhu
,
Z.
, and
Du
,
X.
,
2017
, “
Time-Dependent System Reliability Analysis for Bivariate Responses
,”
ASME J. Risk Uncert Eng. Sys. Part B Mech. Eng.
,
4
(
3
), p.
031002
. 10.1115/1.4038318
You do not currently have access to this content.