Development of Frequency-Content Based Framework to Extract Fragility Curves Using Real Ground Motion Records

A new non-parametric procedure is presented for extracting seismic fragility curves by considering frequency content of real ground motion records. The implemented non-parametric method is based on parametric methods averaging and clustering the input data based on an intensity measure (IM) using K-means clustering method. As an advantage, it can considerably decrease the number of analyses via an optimization process and using Monte Carlo procedure. The proposed method's accuracy is evaluated for real ground motion records. Results show that although the random selection of records among different clusters can be effective for synthetic records, but it’s not suitable for selecting the real ones and can lead to large errors in estimations. Therefore, a classification procedure based on frequency content of the records is used in this study to select an appropriate set of real ground motion records for providing the required IM observations in the method. Then, a set of 472 real ground motion records corresponding to 60 earthquakes is chosen as input data for extracting the fragility curves of the case study structure for evaluating the accuracy and applicability of the non-parametric method. Mean period ( $$T_{m}$$ ) of the ground motions is considered as a suitable frequency content measure to classify the real ground motion records while this classification can lead to better and more accurate results rather than the Monte Carlo procedure. According to the results, with using the classification procedure, the optimized non-parametric method may require less than 70 nonlinear analyses to extract the fragility curves.