| description abstract | A major challenge in a time-dependent reliability analysis is to find a good balance between computational effort, accuracy, and comprehension of the analysis. In this contribution, computational efforts are reduced, and comprehension is increased by changing the perspective from a classical time-dependent probabilistic model to an equivalent parameter state model. The model maps all time-dependent information to one stochastic variable, allowing one to analyze the original problem by analyzing changes in the distribution of this single variable. This clear-cut structure allows for analyzing and visualizing dependencies in detail as well as a novel perspective on reliability estimation, even in complex settings. Furthermore, it just needs computational effort as low as that for a static reliability estimation in many cases. Our approach utilizes, but is not restricted to, Subset Simulation and is therefore especially designed for complex engineering structures of high dimension. To illustrate the model and its computational efficiency, an illustrative example in the time-dependent reliability analysis of concrete structures is presented, and it is shown how to analyze complex networks potentially. | |
