scholarly journals Kriging Model for Time-Dependent Reliability: Accuracy Measure and Efficient Time-Dependent Reliability Analysis Method

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 172362-172378 ◽  
Author(s):  
Yutao Yan ◽  
Jian Wang ◽  
Yibo Zhang ◽  
Zhili Sun
Keyword(s):  
Reliability Analysis ◽  
Kriging Model ◽  
Time Dependent ◽  
Analysis Method ◽  
Accuracy Measure

RCA-PCK: A new structural reliability analysis method based on PC-Kriging and radial centralized adaptive sampling strategy

2020 ◽  
pp. 095440622095771
Author(s):  
Zhenliang Yu ◽  
Zhili Sun ◽  
Runan Cao ◽  
Jian Wang ◽  
Yutao Yan
Keyword(s):  
Reliability Analysis ◽  
Failure Probability ◽  
Adaptive Sampling ◽  
Structural Reliability ◽  
Sampling Strategy ◽  
Kriging Model ◽  
Strong Nonlinearity ◽  
Analysis Method ◽  
Structural Reliability Analysis ◽  
Training Samples

To improve the efficiency and accuracy of reliability assessment for structures with small failure probability and time-consuming simulation, a new structural reliability analysis method (RCA-PCK) is proposed, which combines PC-Kriging model and radial centralized adaptive sampling strategy. Firstly, the PC-Kriging model is constructed by improving the basis function of Kriging model with sparse polynomials. Then, the sampling region which contributes a great impact on the failure probability is constructed by combining the radial concentration and important sampling technology. Subsequently, the k-means++ clustering technology and learning function LIF are adopted to select new training samples from each subdomains in each iteration. To avoid the sampling distance in one subdomain or the distance between the new training samples in two subdomains being too small, we construct a screening mechanism to ensure that the selected new training samples are evenly distributed in the limit state. In addition, a new convergence criterion is derived based on the relative error estimation of failure probability. Four benchmark examples are given to illustrate the convergence process, accuracy and stability of the proposed method. Finally, the transmission error reliability analysis of thermal-elastic coupled gears is carried out to prove the applicability of the proposed method RCA-PCK to the structures with strong nonlinearity and time-consuming simulation.

A time-dependent reliability analysis method for bearing lubrication

2019 ◽  
Vol 61 (5) ◽  
pp. 2125-2134
Author(s):  
YouRui Tao ◽  
BoWen Liang ◽  
Jianhua Zhang
Keyword(s):  
Reliability Analysis ◽  
Time Dependent ◽  
Analysis Method

Time-Dependent Reliability Analysis for Bivariate Responses

2015 ◽  
Author(s):  
Zhen Hu ◽  
Zhifu Zhu ◽  
Xiaoping Du
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
General System ◽  
Time Dependent ◽  
Series System ◽  
Analysis Method ◽  
First Order ◽  
Reliability Method ◽  
General Systems ◽  
Bivariate Responses

Time-dependent system reliability is measured by the probability that the responses of a system do not exceed prescribed failure thresholds over a period of time. In this work, an efficient time-dependent reliability analysis method is developed for bivariate responses that are general functions of random variables and stochastic processes. The proposed method is based on single and joint upcrossing rates, which are calculated by the First Order Reliability Method (FORM). The method can efficiently produce accurate upcrossing rates for the systems with two responses. The upcrossing rates can then be used for system reliability predictions with two responses. As the general system reliability may be approximated with the results from reliability analyses for individual responses and bivariate responses, the proposed method can be extended to reliability analysis for general systems with more than two responses. Two examples, including a parallel system and a series system, are presented.

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