Journal of Northeastern University(Natural Science) ›› 2021, Vol. 42 ›› Issue (5): 658-664.DOI: 10.12068/j.issn.1005-3026.2021.05.008

• Mechanical Engineering • Previous Articles     Next Articles

Time-Dependent Reliability Algorithm Based on Kriging and Monte Carlo

CAO Ru-nan, SUN Zhi-li, GUO Fan-yi, WANG Jian   

  1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China.
  • Revised:2020-07-06 Accepted:2020-07-06 Published:2021-05-20
  • Contact: CAO Ru-nan
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Abstract: The first outcrossing method can get the change of failure probability with time, but the calculation is complex and may call for more cost. The quasi-static method requires a smaller amount of calculation, but it can only get the failure probability value corresponding to a given period of time, and cannot obtain its change trend.In view of the above problems, AK-MCS-T, a time-dependent reliability analysis method is proposed by combining the Kriging model and the Monte Carlo method. It not only has the advantage of small calculation amount of the quasi-static method, but also can give the change of failure probability with time. AK-MCS-T proposes a new selection criterion for the Kriging model which not only considers the probability of wrong judgment of response evaluation value based on the Kriging model at a sample point, but also considers the probability density corresponding to this sample point. At the same time, a new learning stopping condition is proposed to ensure the accuracy of AK-MCS-T. Finally, the effectiveness and accuracy of the new method are proved by two examples: acorroded beam structure and a cantilever tube structure.

Key words: Monte Carlo method; Kriging model; selection criterion; learning stopping condition; time-dependent reliability analysis

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