Time-Dependent Seismic Reliability Analysis through Equivalent Stochastic Process Transformation and Real-Time Hybrid Simulation

Real-time hybrid simulation (RTHS) is widely used to evaluate the seismic performance of structures with significant local nonlinearities or those that are challenging to model at reduced scales. Traditional RTHS, however, often neglects both time-dependent and time-independent structural uncertainties, limiting its applicability in dynamic reliability analyses. This study addresses this limitation by integrating adaptive sampling with RTHS to evaluate global seismic reliability while accounting for time-dependent uncertainties. A novel two-stage adaptive sampling approach is proposed: the first stage identifies samples representing highly uncertain scenarios to improve prediction accuracy, while the second stage couples time-dependent and time-independent uncertainties across time intervals to estimate structural responses. By iteratively applying adaptive sampling to select new sample points and conducting corresponding RTHS experiments to obtain structural responses, a metamodel is developed to evaluate global structural performance throughout the life cycle. Validation results demonstrate the method’s accuracy in representing uncertainties and its effectiveness in conducting time-dependent reliability analysis with multiple failure criteria. This approach significantly reduces experimental costs while maintaining high precision.