Application of state‐space models with frequency‐dependent uncertainty for efficient reliability analysis of complex structures

Abstract

AbstractIn this work, we introduce a commonly used framework to model uncertain dynamical systems and adapt it to propagate both parameters uncertainty and model mismatches through a dynamically excited railway bridge system. The approach considers the system inherent uncertainties in the frequency domain and leads to a significant reduction of the computational effort when performing an uncertainty quantification tasks. In an application example the proposed approach is utilized for efficient reliability analysis of the uncertain railway bridge system. The utilized technique allows for an efficient generation of structural responses, and thus enables a fast evaluation of failure probabilities by crude Monte Carlo sampling. Accuracy of the uncertain prediction model is ensured by comparing the failure probabilities with failure probability simulations based on a semi‐analytical Euler‐Bernoulli bridge beam model.