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中文核心期刊
Liu Haibo, Jiang Chao, Zheng Jing, Wei Xinpeng, Huang Zhiliang. A SYSTEM RELIABILITY ANALYSIS METHOD FOR STRUCTURES WITH PROBABILITY AND INTERVAL MIXED UNCERTAINTY[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 456-466. DOI: 10.6052/0459-1879-16-294
Citation: Liu Haibo, Jiang Chao, Zheng Jing, Wei Xinpeng, Huang Zhiliang. A SYSTEM RELIABILITY ANALYSIS METHOD FOR STRUCTURES WITH PROBABILITY AND INTERVAL MIXED UNCERTAINTY[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 456-466. DOI: 10.6052/0459-1879-16-294

A SYSTEM RELIABILITY ANALYSIS METHOD FOR STRUCTURES WITH PROBABILITY AND INTERVAL MIXED UNCERTAINTY

  • There are a large number of inherently uncertain parameters in the problem of system reliability. Traditional system reliability analysis methods are usually based on the probability model assumption. Probability distribution function of uncertain parameters can be easily obtained with sufficient samples, but in practical engineering problems, it is often difficult to get the precise probability distribution function with limited data or test conditions. In this paper, the uncertain variables of the system based on sufficient information are taken as the random variables, while others with limited information can only be given variation intervals. This paper proposes a new system reliability analysis method for structures with probability and interval mixed uncertainty. Firstly, the minimum reliability index of each failure mode is obtained based on an efficient solution method. Then the system reliability model under multiple failure modes with probability and interval mixed uncertainty is provided. Considering the dependence between different failure modes of systems, a correlation coefficient matrix is obtained by the linear correlation calculated method. Finally, the maximum failure probabilities are calculated for series and parallel system. Three numerical examples show that the present method can effectively deal with the system reliability problems of multiple nonlinear failure modes with probability and interval mixed uncertainty. Compared to the traditional probabilistic reliability analysis method, the presented method can ensure the security of system well and it only needs less uncertain information, and hence it seems suitable for reliability analysis and design of many complex engineering structures or systems.
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