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Cross-entropy-based adaptive importance sampling for time-dependent reliability analysis of deteriorating structures

机译:基于交叉熵的自适应重要性抽样,用于时变结构的时变可靠性分析

摘要

Time-dependent reliability analysis of deteriorating structures is important in their performance evaluation and maintenance. Various definitions and methods have been used by researchers to predict the time-dependent reliability of structures. In the present study, these methods are first critically reviewed and examined. Among these methods, the stochastic-process-based method is theoretically the most rigorous but also computationally the most expensive. To facilitate the wide application of the stochastic-process-based method in complex problems, an efficient importance sampling method is then proposed in this paper. The proposed method includes a number of improvements formulated to enhance the efficiency and robustness of an existing method proposed by Kurtz and Song, leading to more efficient solutions of time-dependent reliability problems of structural systems with multiple important regions. The validity and efficiency of the new method is demonstrated through three numerical examples.
机译:时变结构的时变可靠性分析在其性能评估和维护中很重要。研究人员已使用各种定义和方法来预测结构随时间的可靠性。在本研究中,首先对这些方法进行了严格的审查和检查。在这些方法中,基于随机过程的方法在理论上是最严格的,但在计算上也是最昂贵的。为了促进基于随机过程的方法在复杂问题中的广泛应用,提出了一种有效的重要性抽样方法。所提出的方法包括许多改进,旨在提高Kurtz和Song提出的现有方法的效率和鲁棒性,从而导致对具有多个重要区域的结构系统的时变可靠性问题进行更有效的解决。通过三个数值例子验证了该方法的有效性和有效性。

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