Impact of component damage correlations on seismic fragility and risk assessment of multi-component bridge systems

• A framework to quantify demand and capacity correlations among bridge components. • The model extends the existing component-based bridge seismic fragility approach. • Compared with other models to assess collapse fragility, repair costs, and recovery time. • Neglecting or oversimplifying damage correlations can lead to biased risk estimates. Seismic fragility modeling of bridges has evolved from simplified system-level assessments to high-fidelity, component-based methodologies. However, a key challenge remains in accurately incorporating damage dependency among bridge components, which might influence high-resolution seismic risk estimates that rely upon damage simulations of each bridge component. While previous studies have explored demand and capacity correlations in various structures, a comprehensive framework integrating these dependencies within the component-based bridge fragility modeling approach remains absent. This study addresses this gap by introducing a refined methodology for modeling seismic damage correlations across bridge components and damage states. A correlation-based fragility modeling framework is proposed, leveraging joint probabilistic seismic demand models and a hierarchical capacity correlation structure. The framework is systematically compared against other correlation models, including fully independent, fully correlated, and partially correlated approaches. Using a four-span, multi-column reinforced concrete bridge as a benchmark, the influence of correlation modeling on key seismic risk metrics, such as bridge collapse fragility, repair costs, and recovery durations, is assessed. Results demonstrate that neglecting damage correlation, or treating it perfectly correlated, sometimes would lead to significant biases in risk estimations. The proposed framework provides a practical extension of the existing component-level seismic fragility modeling approach for seamlessly integrating correlation effects, improving its effectiveness and applicability for downstream risk and resilience assessment of bridge systems.