Variance-based global sensitivity analysis for fuzzy random structural systems

There have been increasing advances in the sophisticated approaches like fuzzy randomness to handle different uncertainties in civil engineering; however, less attention has been paid to the formulation of a sensitivity analysis for fuzzy random structural systems. In this study, the main objective is to present the formulation of fuzzy Sobol sensitivity indices to quantify the influence of fuzzy random structural parameters. Meanwhile, uncertainty in derivation of limit states and acceptance criteria in collapse analysis is addressed briefly and treated using fuzzy model parameters. To show the application of the established sensitivity test, the collapse behavior of a steel moment frame subjected to sudden column removal is evaluated thoroughly. The proposed fuzzy sensitivity indices are determined for the problem and the overall influence of fuzzy acceptance criteria on the collapse assessment is shown using fragility analysis. The results show that the presented fuzzy sensitivity analysis can give detailed insight into the characteristics of fuzzy random systems, and the epistemic uncertainty in derivation of limit states can have significant effects on the reliability-based collapse analysis. It is worth mentioning that to alleviate high computational demands in fuzzy probabilistic collapse analysis, a neural network metamodel is applied in conjunction with the genetic algorithm which is also of practical value to engineers and researchers.