考 虑 状 态 模 糊 性 的 结 构 非 概 率 可 靠 性 分 析

In practical engineering，it is sometimes difficult to clearly determine the output state of a structure. The non-probabilistic reliability analysis with the binary state ignores the fuzzy output state，which is too ideal. To solve this problem，we conduct the non-probabilistic reliability analysis with fuzzy failure and safe states by introducing the fuzzy state assumption，with the input uncertainties quantified by the ellipsoidal model. According to the fuzzy state assump⁃ tion，the states of structures are described by fuzziness，and then combined with the principle of indifference. The non-probabilistic fuzzy reliability degree is developed as a measure of the non-probabilistic reliability of the structure，fol⁃ lowed by the corresponding Monte Carlo simulation method for the non-probabilistic fuzzy reliability. To overcome the inefficiency associated with the Monte Carlo simulation method，a novel active learning Kriging method is proposed. Finally，an efficient non-probabilistic reliability analysis method with fuzzy states is established. Examples are used to illustrate the engineering practicality of the proposed non-probabilistic reliability analysis method.