Technical Papers
Sep 18, 2020

Improved Model for Computing Time-Variant Reliability Based on Outcrossing Rate

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Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 4

Abstract

Time-variant reliability problems have been studied widely by scholars recently, and they usually are solved on the basis of the outcrossing rate. The common method to calculate the outcrossing rate involves a static parallel system reliability problem of two components, and sequentially the time-variant reliability can be computed by Rice’s formula. This formula, however, is not ideal because of its assumptions of Poisson distribution and independence for outcrossings, and thus a significant error may be generated. Therefore, the formula for computing time-variant reliability was rederived and modified in this paper. Time-variant reliability first was derived based on the failure rate, and then the approximate relationship between the outcrossing rate and failure rate was provided. Consequently, Rice’s formula for calculating time-variant reliability based on outcrossing rate can be modified from the perspective of failure rate, which can remove the drawbacks of the assumptions of Rice’s formula. Several examples were provided to validate the efficiency and accuracy of the proposed method.

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Data Availability Statements

All data, models, and code used during the study appear in the published article.

Acknowledgments

This research was supported by the National Natural Science Foundation of China under Contract number No. 51775090.

References

Andrieu-Renaud, C., B. Sudret, and M. Lemaire. 2004. “The PHI2 method: a way to compute time-variant reliability.” Reliab. Eng. Syst. Saf. 84 (1): 75–86. https://doi.org/10.1016/j.ress.2003.10.005.
Beck, A. T., and R. E. Melchers. 2004. “On the ensemble crossing rate approach to time variant reliability analysis of uncertain structures.” Probab. Eng. Mech. 19 (1–2): 9–19. https://doi.org/10.1016/j.probengmech.2003.11.018.
Chen, J.-B., and J. Li. 2007. “The extreme value distribution and dynamic reliability analysis of nonlinear structures with uncertain parameters.” Struct. Saf. 29 (2): 77–93. https://doi.org/10.1016/j.strusafe.2006.02.002.
Gnedenko, B. V., Y. K. Belyayev, and A. D. Solovyev. 2014. Mathematical methods of reliability theory. New York: Academic Press.
Hu, Z., and X. Du. 2013. “Time-dependent reliability analysis with joint upcrossing rates.” Struct. Multidiscip. Optim. 48 (5): 893–907. https://doi.org/10.1007/s00158-013-0937-2.
Hu, Z., and X. Du. 2015a. “First order reliability method for time-variant problems using series expansions.” Struct. Multidiscip. Optim. 51 (1): 1–21. https://doi.org/10.1007/s00158-014-1132-9.
Hu, Z., and X. Du. 2015b. “Mixed efficient global optimization for time-dependent reliability analysis.” J. Mech. Des. 137 (5): 051401. https://doi.org/10.1115/1.4029520.
Hu, Z., and S. Mahadevan. 2016. “A single-loop kriging surrogate modeling for time-dependent reliability analysis.” J. Mech. Des. 138 (6): 061406. https://doi.org/10.1115/1.4033428.
Huang, S., S. Mahadevan, and R. Rebba. 2007. “Collocation-based stochastic finite element analysis for random field problems.” Probab. Eng. Mech. 22 (2): 194–205. https://doi.org/10.1016/j.probengmech.2006.11.004.
Jiang, C., X. P. Wei, Z. L. Huang, and J. Liu. 2017. “An outcrossing rate model and its efficient calculation for time-dependent system reliability analysis.” J. Mech. Des. 139 (4): 041402. https://doi.org/10.1115/1.4035792.
Kaminski, M. 2013. The stochastic perturbation method for computational mechanics. Hoboken, NJ: Wiley.
Li, H., H.-Z. Huang, Y.-F. Li, J. Zhou, and J. Mi. 2018a. “Physics of failure-based reliability prediction of turbine blades using multi-source information fusion.” Appl. Soft Comput. 72 (Nov): 624–635. https://doi.org/10.1016/j.asoc.2018.05.015.
Li, X.-Y., Y.-F. Li, H.-Z. Huang, and E. Zio. 2018b. “Reliability assessment of phased-mission systems under random shocks.” Reliab. Eng. Syst. Saf. 180 (Dec): 352–361. https://doi.org/10.1016/j.ress.2018.08.002.
Li, Y.-F., H.-Z. Huang, J. Mi, W. Peng, and X. Han. 2019. “Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability.” Ann. Oper. Res. 1–15. https://doi.org/10.1007/s10479-019-03247-6.
Majcher, M., Z. Mourelatos, and V. Tsianika. 2017. “Time-dependent reliability analysis using a modified composite limit state approach.” SAE Int. J. Commer. Veh. 10 (1): 66–72. https://doi.org/10.4271/2017-01-0206.
Mejri, M., M. Cazuguel, and J. Y. Cognard. 2011. “A time-variant reliability approach for ageing marine structures with non-linear behaviour.” Comput. Struct. 89 (19–20): 1743–1753. https://doi.org/10.1016/j.compstruc.2010.10.007.
Mi, J., Y. Cheng, Y. Song, L. Bai, and K. Chen. 2019. “Application of dynamic evidential networks in reliability analysis of complex systems with epistemic uncertainty and multiple life distributions.” Ann. Oper. Res. 1–23. https://doi.org/10.1007/s10479-019-03211-4.
Mi, J., Y.-F. Li, W. Peng, and H.-Z. Huang. 2018. “Reliability analysis of complex multi-state system with common cause failure based on evidential networks.” Reliab. Eng. Syst. Saf. 174 (Jun): 71–81. https://doi.org/10.1016/j.ress.2018.02.021.
Mi, J., Y.-F. Li, Y.-J. Yang, W. Peng, and H.-Z. Huang. 2016. “Reliability assessment of complex electromechanical systems under epistemic uncertainty.” Reliab. Eng. Syst. Saf. 152 (Aug): 1–15. https://doi.org/10.1016/j.ress.2016.02.003.
Moarefzadeh, M. R., and B. Sudret. 2018. “Implementation of directional simulation to estimate outcrossing rates in time-variant reliability analysis of structures.” Qual. Reliab. Eng. Int. 34 (8): 1818–1827. https://doi.org/10.1002/qre.2374.
Mourelatos, Z. P., M. Majcher, V. Pandey, and L. Baseski. 2015. “Time-dependent reliability analysis using the total probability theorem.” J. Mech. Des. 137 (3): 031405. https://doi.org/10.1115/1.4029326.
Qian, H. M., H. Z. Huang, and Y. F. Li. 2019. “A novel single-loop procedure for time-variant reliability analysis based on Kriging model.” Appl. Math. Modell. 75 (Nov): 735–748. https://doi.org/10.1016/j.apm.2019.07.006.
Qian, H. M., Y. F. Li, and H. Z. Huang. 2020. “Time-variant reliability analysis for industrial robot RV reducer under multiple failure modes using Kriging model.” Reliab. Eng. Syst. Saf. 199 (Jul): 106936. https://doi.org/10.1016/j.ress.2020.106936.
Rackwitz, R. 2001. “Reliability analysis—A review and some perspectives.” Struct. Saf. 23 (4): 365–395. https://doi.org/10.1016/S0167-4730(02)00009-7.
Rice, S. O. 1944. “Mathematical analysis of random noise.” Bell Syst. Tech. J. 23 (3): 282–332. https://doi.org/10.1002/j.1538-7305.1944.tb00874.x.
Singh, A., Z. Mourelatos, and E. Nikolaidis. 2011. “Time-dependent reliability of random dynamic systems using time-series modeling and importance sampling.” SAE Int. J. Mater. Manuf. 4 (1): 929–946. https://doi.org/10.4271/2011-01-0728.
Singh, A., Z. P. Mourelatos, and J. Li. 2010. “Design for lifecycle cost using time-dependent reliability.” J. Mech. Des. 132 (9): 091008. https://doi.org/10.1115/1.4002200.
Sudret, B. 2008. “Analytical derivation of the outcrossing rate in time-variant reliability problems.” Struct. Infrastruct. Eng. 4 (5): 353–362. https://doi.org/10.1080/15732470701270058.
Sudret, B., and A. Der Kiureghian. 2000. Stochastic finite element methods and reliability: A state-of-the-art report. Berkeley, CA: Dept. of Civil and Environmental Engineering, Univ. of California.
Vanmarcke, E. 2010. Random fields: Analysis and synthesis (revised and expanded new edition). Singapore: World Scientific.
Vanmarcke, E. H. 1975. “On the distribution of the first passage time for normal stationary processes.” J. Appl. Mech. 42 (1): 215–220. https://doi.org/10.1115/1.3423521.
van Noortwijk, J. M., J. A. van der Weide, M. J. Kallen, and M. D. Pandey. 2007. “Gamma processes and peaks-over-threshold distributions for time-dependent reliability.” Reliab. Eng. Syst. Saf. 92 (12): 1651–1658. https://doi.org/10.1016/j.ress.2006.11.003.
Wang, Z., and W. Chen. 2017. “Confidence-based adaptive extreme response surface for time-variant reliability analysis under random excitation.” Struct. Saf. 64 (Jan): 76–86. https://doi.org/10.1016/j.strusafe.2016.10.001.
Wang, Z., H.-Z. Huang, and X. Du. 2010a. “Optimal design accounting for reliability, maintenance, and warranty.” J. Mech. Des. 132 (1): 011007. https://doi.org/10.1115/1.4000638.
Wang, Z., H.-Z. Huang, and Y. Liu. 2010b. “A unified framework for integrated optimization under uncertainty.” J. Mech. Des. 132 (5): 051008. https://doi.org/10.1115/1.4001526.
Wang, Z., and P. Wang. 2012. “A nested extreme response surface approach for time-dependent reliability-based design optimization.” J. Mech. Des. 134 (12): 121007. https://doi.org/10.1115/1.4007931.
Wang, Z., and P. Wang. 2013. “A new approach for reliability analysis with time-variant performance characteristics.” Reliab. Eng. Syst. Saf. 115 (Jul): 70–81. https://doi.org/10.1016/j.ress.2013.02.017.
Wang, Z., X. Zhang, H.-Z. Huang, and Z. P. Mourelatos. 2016. “A simulation method to estimate two types of time-varying failure rate of dynamic systems.” J. Mech. Des. 138 (12): 121404. https://doi.org/10.1115/1.4034300.
Xiao, N.-C., K. Yuan, and C. Zhou. 2020. “Adaptive kriging-based efficient reliability method for structural systems with multiple failure modes and mixed variables.” Comput. Methods Appl. Mech. Eng. 359 (Feb): 112649. https://doi.org/10.1016/j.cma.2019.112649.
Xiao, N.-C., M. J. Zuo, and C. Zhou. 2018. “A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis.” Reliab. Eng. Syst. Saf. 169 (Jan): 330–338. https://doi.org/10.1016/j.ress.2017.09.008.
Yu, S., and Z. Wang. 2018. “A novel time-variant reliability analysis method based on failure processes decomposition for dynamic uncertain structures.” J. Mech. Des. 140 (5): 051401. https://doi.org/10.1115/1.4039387.
Zhang, J., and X. Du. 2011. “Time-dependent reliability analysis for function generator mechanisms.” J. Mech. Des. 133 (3): 031005. https://doi.org/10.1115/1.4003539.
Zhang, Y., B. Wen, and Q. Liu. 1998. “First passage of uncertain single degree-of-freedom nonlinear oscillators.” Comput. Methods Appl. Mech. Eng. 165 (1–4): 223–231. https://doi.org/10.1016/S0045-7825(98)00042-5.
Zhao, Y.-G., and T. Ono. 2001. “Moment methods for structural reliability.” Struct. Saf. 23 (1): 47–75. https://doi.org/10.1016/S0167-4730(00)00027-8.
Zhou, X.-Y., P. D. Gosling, Z. Ullah, and C. J. Pearce. 2016. “Exploiting the benefits of multi-scale analysis in reliability analysis for composite structures.” Compos. Struct. 155 (Nov): 197–212. https://doi.org/10.1016/j.compstruct.2016.08.015.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6Issue 4December 2020

History

Received: Dec 26, 2019
Accepted: Jun 22, 2020
Published online: Sep 18, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 18, 2021

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Hua-Ming Qian
Ph.D. Candidate, School of Mechanical and Electrical Engineering, Center for System Reliability and Safety, Univ. of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.
Yan-Feng Li [email protected]
Associate Professor, School of Mechanical and Electrical Engineering, Center for System Reliability and Safety, Univ. of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China. Email: [email protected]
Hong-Zhong Huang [email protected]
Professor, School of Mechanical and Electrical Engineering, Center for System Reliability and Safety, Univ. of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China (corresponding author). Email: [email protected]

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