Time-Dependent Reliability Modeling and Analysis Method for Mechanics Based on Convex Process

The objective of the present study is to evaluate the time-dependent reliability for dynamic mechanics with insufficient time-varying uncertainty information. In this paper, the nonprobabilistic convex process model, which contains autocorrelation and cross-correlation, is firstly employed for the q...

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Bibliographic Details
Published in:Mathematical problems in engineering 2015-01, Vol.2015 (2015), p.1-16
Main Authors: Chen, Xiao, Wang, Ruixing, Wang, Xiaojun, Wang, Lei
Format: Article
Language:English
Subjects:
Assessments
Autocorrelation
Computer simulation
Cross correlation
Engineering
Life cycle assessment
Life cycle engineering
Limit states
Mathematical analysis
Mathematical models
Mechanics
Mechanics (physics)
Monte Carlo methods
Monte Carlo simulation
Product safety
Random processes
Random variables
Regularization
Reliability analysis
Simulation
Structural safety
Time dependence
Time measurement
Uncertainty
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Summary:The objective of the present study is to evaluate the time-dependent reliability for dynamic mechanics with insufficient time-varying uncertainty information. In this paper, the nonprobabilistic convex process model, which contains autocorrelation and cross-correlation, is firstly employed for the quantitative assessment of the time-variant uncertainty in structural performance characteristics. By combination of the set-theory method and the regularization treatment, the time-varying properties of structural limit state are determined and a standard convex process with autocorrelation for describing the limit state is formulated. By virtue of the classical first-passage method in random process theory, a new nonprobabilistic measure index of time-dependent reliability is proposed and its solution strategy is mathematically conducted. Furthermore, the Monte-Carlo simulation method is also discussed to illustrate the feasibility and accuracy of the developed approach. Three engineering cases clearly demonstrate that the proposed method may provide a reasonable and more efficient way to estimate structural safety than Monte-Carlo simulations throughout a product life-cycle.
ISSN:1024-123X
1563-5147
DOI:10.1155/2015/914893