A PDEM-based non-parametric seismic fragility assessment method for RC structures under non-stationary ground motions

To alleviate the consequential influences of earthquakes, many seismic performance evaluation methods have been developed over the past century. Fragility assessment is an effective approach to evaluate the structural response under earthquake excitation, among which the classic parametric linear regression method (LRM) is one of the most popular ones. However, the classic parametric LRM method adopts a lognormal distribution assumption, and the assumption may not be satisfied under highly nonlinear scenario thus leading to inaccurate fragility curves. To overcome this issue, a PDEM-based non-parametric seismic fragility assessment framework without pre-defined distribution of the structural demand and performance is proposed in this paper. Non-stationary ground motions generated by the spectral representation method are employed for deeper representation of the earthquake excitation uncertainty, and two RC frames are designed to exhibit the performance of the proposed assessment framework. The results indicate that the proposed framework can conduct the fragility assessment effectively and perform a better accuracy than the classic parametric LRM method under the same number of dynamic calculations. Additionally, the PDEM-based framework requires much fewer samples compared to the benchmark Monte Carlo simulation (MCS), thus resulting in a less calculation burden. • Propose a novel non-parametric seismic fragility analysis framework via PDEM, which avoid the pre-defined lognormal assumption in classic parametric approach. • Introduce a non-stationary stochastic ground motion model for earthquake input, which is generated by spectral representation method. • Combine a non-conditional stable explicit KR- α algorithm with deterministic modeling method, without convergency issues even under huge excitation. • Compare the results with classical linear regression method and benchmark Monte Carlo Simulation, and proves the efficiency and accuracy with satisfaction.