scholarly journals A novel method for importance measure analysis in the presence of epistemic and aleatory uncertainties

2014 ◽  
Vol 27 (3) ◽  
pp. 568-576
Author(s):  
Bo Ren ◽  
Zhenzhou Lu ◽  
Changcong Zhou
2018 ◽  
Vol 10 (9) ◽  
pp. 3207 ◽  
Author(s):  
Xing Pan ◽  
Lunhu Hu ◽  
Ziling Xin ◽  
Shenghan Zhou ◽  
Yanmei Lin ◽  
...  

A risk scenario is a combination of risk events that may result in system failure. Risk scenario analysis is an important part of system risk assessment and avoidance. In engineering activity-based systems, important risk scenarios are related to important events. Critical activities, meanwhile, mean risk events that may result in system failure. This article proposes these definitions of risk event and risk scenario based on the characteristics of risk in engineering activity-based systems. Under the proposed definitions, a risk scenario framework generated based on importance measure analysis is given, in which critical activities analysis, risk event identification, and risk scenario generation are the three main parts. Important risk events are identified according to activities’ uncertain importance measure and important risk scenarios are generated on the basis of a system’s critical activities analysis. In the risk scenario generation process based on importance analysis, the importance degrees of network activities are ranked to identify the subject of risk events, so that risk scenarios can be combined and generated by risk events and the importance of scenarios is analyzed. Critical activities are analyzed by Taguchi tolerance design, mathematical analysis, and Monte Carlo simulation methods. Then the degrees of uncertain importance measure of activities are solved by the three methods and these results are compared. The comparison results in the example show that the proposed method of uncertain importance measure is very effective for distinguishing the importance level of activities in systems. The calculation and simulation results also verify that the risk events composed of critical activities can generate risk scenarios.


2011 ◽  
Vol 48 (5) ◽  
pp. 1733-1740 ◽  
Author(s):  
Pengfei Wei ◽  
Zhenzhou Lu ◽  
Wenrui Hao

2012 ◽  
Vol 38 ◽  
pp. 56-63 ◽  
Author(s):  
Wenrui Hao ◽  
Zhenzhou Lu ◽  
Pengfei Wei ◽  
Jun Feng ◽  
Bintuan Wang

Author(s):  
Nan WU ◽  
Qing GUO ◽  
Guojun TONG ◽  
Yongshou LIU

Pipe system conveying fluid faces the problem of multi-order resonance failure caused by broadband excitation. For solving above problem, the dynamic stiffness method is employed to solve the dynamic equations of multi-span pipes considering the temperature effect. Combining the obtained natural frequency and the rule of resonance failure of pipe system, a multi-order anti-resonance system reliability model is established in this paper. To analyze the effect of input variable uncertainty on the probability of system resonance failure, the variance-based importance measurement index is further established. By introducing the active learning Kriging (ALK) model, the resonance failure probability and importance measurement index can be calculated efficiently. The effects of fluid flow velocity, pressure and temperature on the probability of pipe resonance failure are analyzed in detail, which has significant guidance for the anti-resonance optimization design of pipes.


Author(s):  
Yicheng Zhou ◽  
Zhenzhou Lu ◽  
Yan Shi ◽  
Kai Cheng

The moment-independent importance measure technique for exploring how uncertainty allocates from output to inputs has been widely used to help engineers estimate the degree of confidence of decision results and assess risks. Solving the Borgonovo moment-independent importance measure in the presence of the multivariate output is still a challenging problem due to “curse of dimensionality,” and it is investigated in this contribution. For easily estimating the moment-independent importance measure, a novel method based on the vine copula is proposed. In the proposed method for estimating moment-independent importance measure, three steps are included. First, the moment-independent importance measure is expressed as a product of bivariate copula density functions through the vine copula trees. Second, the marginal probability density functions are obtained by the maximum entropy under the constraint of the fractional moments. Finally, the post-processed is executed to directly estimate the moment-independent importance measure by estimated copula density functions. The proposed method can handle multivariate output easily. The results of several examples indicate the validity and benefits of the proposed method.


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