The present study focuses on reliability analysis of linear discretized structures with uncertain mass and stiffness parameters subjected to stationary Gaussian multi-correlated random excitation. Under the assumption that available information on the uncertain parameters is poor or incomplete, the interval model of uncertainty is adopted. The reliability function for the extreme value stress process is evaluated in the framework of the first-passage theory. Such a function turns out to have an interval nature due to the uncertainty affecting structural parameters. The aim of the analysis is the evaluation of the bounds of the interval reliability function which provide a range of structural performance useful for design purposes. To limit detrimental overestimation caused by the dependency phenomenon, a sensitivity-based procedure is applied. The main advantage of this approach is the capability of providing appropriate combinations of the endpoints of the uncertain parameters which yield accurate estimates of the bounds of the interval reliability function for the extreme value stress process as long as monotonic problems are dealt with. Two case studies are analyzed to demonstrate the accuracy and efficiency of the presented method.
- Interval analysis
- Interval reliability function
- Random excitation
- Sensitivity analysis
- Uncertain parameters