Deterministic and probabilistic-based model updating of aging steel bridges

Numerical modeling is a very useful tool in different fields of bridge engineering, such as load-carrying capacity assessment or structural health monitoring. Developing reliable computational model that accurately represents the actual mechanical behavior entails advanced FEM-based complemented by comprehensive experimental campaign provides necessary supporting information and allows validating simulation outcomes. This paper proposes unified approach aimed at characterization FE updating aging steel bridges. It first involves realization an extensive bridge's geometrical, material, dynamic characterization. Then, calibration framework developed, where deterministic (optimization) probabilistic (Bayesian inference) approaches are employed, techniques global variance-based sensitivity analysis Kriging-based surrogate further implemented order to enhance identification process reduce overall burden. The methodology has been validated historical riveted O Barqueiro, north Galicia, Spain. results show good agreement identified parameter values noticeable correlation between numerical modal properties, with average relative error frequencies 0.34% 0.44% for MAC (Modal Assurance Criterion) ratio 0.96.