Kriging metamodeling-based Monte Carlo Simulation for improved seismic fragility analysis of structures

The polynomial response surface method (RSM) is mostly adopted to overcome computational challenge of Monte Carlo Simulation (MCS)-based seismic fragility analysis (SFA) of structure. However, such SFA approach is primarily based on dual RSM involving lognormal assumption which lacks desired accuracy. The present study explores the advantage of adaptive nature of Kriging approach for improved SFA by random selection of metamodel to implicitly consider record to record variations of earthquakes. Without additional computational burden, the approach avoids a prior distribution assumption unlike dual RSM. The effectiveness of the approach over the usual polynomial RSM for SFA is elucidated numerically.