Large‐amplitude and long‐period pulses are observed in velocity time histories of near‐fault ground‐motion records. The pulses in these records have significant damage effect on flexible structures due to their long‐period property; therefore, more attention should be paid to the frequency components in the ground motion. Based on the identification of frequency components in the original record, a new method based on the Hilbert–Huang transform (HHT) is proposed here. A ground‐motion record can be decomposed into several intrinsic mode functions (IMFs) that carry different frequency components by the HHT without contamination from any a prior function. Only two fixed parameters, the peak ground velocity (PGV)/peak ground acceleration (PGA) ratio and the energy change of every IMF, are used to classify pulse‐like ground‐motion records. The inherent pulses of these records can also be extracted, based on the selection of IMFs for which PGV/PGA ratios are larger than 0.12 and energy changes that are greater than 0.1. For multipulse cases, all the pulses can be captured after extracting once, and the time course of inherent pulses can also be obtained. Then, pulse periods are calculated based on the solutions of instantaneous frequency of the peak for the extracted pulses. All the periods obtained using the HHT method can be verified by the results obtained from Baker’s wavelet method. The 24 controversial records that are discussed in previous studies are examined here as well. The HHT method is a complete procedure that includes the classification of pulse‐like ground motions, the extraction of velocity pulses, and the solution of pulse periods. It works well for multipulse records, especially because it can provide the exact timing of all the inherent pulses.

The aim of this research is to develop a probability method that can identify the flexure, shear or flexural-shear failure of RC columns. A total of 336 columns of cyclic load test results were collected, and a probabilistic model was constructed using the Bayesian procedure. Then, the model was simplified by Bayesian updating. The boundaries for each failure mode were selected through an internal search optimization. The results show that the Bayesian methodology can accurately predict the seismic failure modes of RC columns and the comparison of the identification with other methods underscore the validity of Bayesian method.

Coastal bridges are continually attacked by chloride ions during their lifetime, making the structures vulnerable. Piers, which are the main components of bridge structures to resist lateral forces, are supposed to have adequate deformation capacity to protect the structures from collapse. This paper studies the performance of coastal bridge piers that deteriorate nonuniformly along the height due to varying corrosion characteristics. A prediction method is proposed to estimate the ultimate lateral displacement of coastal bridge piers, and the results of cyclic tests are used to verify the prediction accuracy. Next, the failure mechanism of coastal bridge piers is investigated, taking into account the combined influence of corrosion level and varying performance deteriorations along the height. The analytical results indicate that the sections along the pier height behave differently due to varying corrosion levels when the service time increases, and the maximum damaged position may transfer from the pier bottom to the zone where the performance deteriorates most significantly. In addition, the length proportions between different zones along the pier height strongly affect the seismic failure of coastal bridge piers.