Seismic Risk Evaluation by Fragility Curves Using Metamodel Methods

Abstract

This study proposed an efficient and reliable fragility estimation by metamodel methods. To evaluate seismic risk, it is important to account for ground motions and structural parameter uncertainties. Nevertheless, seismic fragility analysis with uncertainties is impractical since it requires many time-consuming nonlinear dynamic simulations. To this end, an efficient approach based on metamodel in conjunction with Monte Carlo simulation is proposed to develop fragility curves. Several metamodel methods such as kriging, response surface method (RSM), and radial basis function (RBF) are investigated for this purpose. Optimum Latin hypercube design is used to generate “space filling” samples for nonlinear dynamic analysis under seismic excitations. A metamodel is constructed based on these design of experiment samples which include the input parameters and output fragility results. Kriging and RBF are better than the RSM metamodel. The fragility curves can be generated based on metamodel by considering the randomness of earthquake ground motions and uncertainties in material properties. Finally, seismic risk is evaluated by fragility curves. The computation time is significantly reduced by applying the metamodel method with acceptable accuracy. The proposed methodology also avoids nonlinear dynamic non-convergent problems. Kriging and RBF methods complement each other and are able to accurately evaluate fragility curves.