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• W2889202456 abstract "Systems with random variables and random excitations exist widely in various engineering problems. Extending the traditional global reliability sensitivity to this double-stochastic system has important guiding significance for its design optimization. However, because there is a certain coupling between the randomness of variables and the randomness of excitation, this coupling mechanism is difficult to determine in practical projects. Therefore, it is difficult to extend the traditional reliability sensitivity analysis method to this double-stochastic system. In this research, it is assumed that there is no correlation between variables and excitations. Then, combining the first-passage method–based dynamic strength formula and the variance-based sensitivity analysis method, an approximate global reliability sensitivity analysis method for this double-stochastic system is proposed. In order to improve the computational efficiency, a nested loop method based on seven-point estimation is proposed for reliability sensitivity analysis. In order to verify the accuracy and efficiency of the proposed method, a Monte Carlo simulation is given as a reference. Three examples are studied and discussed to illustrate the practicality and feasibility of the proposed method." @default.
• W2889202456 created "2018-09-07" @default.
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• W2889202456 date "2018-08-28" @default.
• W2889202456 modified "2023-09-26" @default.
• W2889202456 title "Extending the global reliability sensitivity analysis to the systems under double-stochastic uncertainty" @default.
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• W2889202456 doi "https://doi.org/10.1177/1369433218795570" @default.
• W2889202456 hasPublicationYear "2018" @default.
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