期刊
JOURNAL OF MECHANICAL DESIGN
卷 137, 期 5, 页码 -出版社
ASME
DOI: 10.1115/1.4029520
关键词
Kriging; reliability analysis; mixed EGO; time-dependent
资金
- National Science Foundation [CMMI 1234855]
- Intelligent Systems Center (ISC) at the Missouri University of Science and Technology
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1234855] Funding Source: National Science Foundation
Time-dependent reliability analysis requires the use of the extreme value of a response. The extreme value function is usually highly nonlinear, and traditional reliability methods, such as the first order reliability method (FORM), may produce large errors. The solution to this problem is using a surrogate model of the extreme response. The objective of this work is to improve the efficiency of building such a surrogate model. A mixed efficient global optimization (m-EGO) method is proposed. Different from the current EGO method, which draws samples of random variables and time independently, the m-EGO method draws samples for the two types of samples simultaneously. The m-EGO method employs the adaptive Kriging-Monte Carlo simulation (AK-MCS) so that high accuracy is also achieved. Then, Monte Carlo simulation (MCS) is applied to calculate the time-dependent reliability based on the surrogate model. Good accuracy and efficiency of the m-EGO method are demonstrated by three examples.
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