Rui Zhang

Serious damage to near-fault structures is caused mainly by velocity pulses in a ground motion, hence, the necessity to develop a pulse-related definition of strong-motion duration to adequately describe the intensity of near-fault ground motion. For a multipulse record, an ideal-pulse-based strong-motion duration, which is defined as the time interval between the beginning of the first pulse and the end of the last pulse in an ideal-pulse signal, is proposed. This strong-motion duration corresponds with the time interval of the occurrence of strong vibrations and energy accumulations in the original record. For near-fault records, pulselike characteristics can be completely presented within this duration. Meanwhile, the ideal-pulse-based strong-motion duration shows good performance in the estimation of structural responses. The elastic and inelastic displacement spectra of the original records agree well with those of the records shortened according to the proposed duration. The validity of applying the proposed duration to structural analysis is further verified by the nonlinear time history analyses of 3-, 9-, and 20-story steel moment-resisting frame structures. The proposed strong-motion duration accurately estimates nonlinear structural responses. It is proven that the ideal-pulse-based strong-motion duration can adequately describe the intensity of near-fault ground motions, both from the perspective of the energy accumulation process in a ground-motion record and that of the structural analyses subjected to these ground motions.

Structural health inspection systems are widely used to manage and maintain infrastructure that involves massive sensor devices. However, these sensors receive the natural environment or external factors in the long-term exposure to the outdoor environment, resulting in the failure of the sensors, which causes multiple categories of abnormal data in the collected data. The data often is unbalanced due to the random nature of failures. This unbalanced anomaly data poses a major challenge to existing anomaly detection methods and will affect the effectiveness of the information provided by the structural health monitoring system. In the paper, a data migration method is proposed to migrate bridge data to the target bridge dataset for expansion so that the number of images of different categories in the target bridge dataset increases. This method can be divided into three steps: firstly, to classify the data; secondly, to determine the suitability of the data and to construct the dataset; and finally, to train the data. The comparative validation is used to compare the training performance of the dataset using data migration with the dataset only using the target bridge to analyze the abnormal data identification in each category. In the experiment, the recall of some categories of data reached a significant increase of more than 30%, achieving better identification of various categories of abnormal data. Adopting the method of data migration between different bridges can solve the impact of imbalanced data and improve the recognition performance of categories with fewer images.

Hollow slab bridges are the most widely used form of small- and medium-span bridges. The existing research on the dynamic characteristics of hollow slab bridges is mostly based on numerical models, but there is a lack of theoretical analyses of their dynamic characteristics. In this paper, the relationship between the dynamic characteristic parameters and structural parameters of a hollow slab bridge is explored theoretically. Firstly, the solid model of a hollow slab bridge was established, and a modal analysis was carried out on it as a reference. Then, an orthotropic plate was used as an equivalent dynamic analysis model, and the analytical form of the transverse modal shape was deduced based on Kirchhoff thin plate theory. Furthermore, one hinge joint was considered as being equivalent to the elastic support boundary, and the local structure and the equivalent elastic support boundary were used to reflect the transverse modal shape of the original structure. The analysis shows that the influence of hinge joints on the transverse modal shape is mainly reflected in the transmission of bending deformation. Through comparison and verification, the results show that the analytical expression of the transverse modal shape can well describe the low-order transverse modal shape of a hollow slab bridge.

This paper presents a comparison of P-Delta effects on the nonlinear seismic behavior of the steel moment-resisting frame structures (MRFs) subjected to near-fault and far-fault ground motions. The 3-, 9- and 20-story MRFs designed for the American SAC Phase II Steel Project are used as benchmark models. The 40 near-fault ground motions with large velocity pulses, as well as ten typical far-fault ground motions, are selected and scaled for the nonlinear time-history analysis. The P-Delta effect is quantified based on peak inter-story drift ratio (PIDR) demands. The displacement demands of the whole structure and the distortion of the structural components are compared and analyzed. It was found that, at each floor, the P-Delta effect under near-fault ground motions is more significant than that under the far-fault ground motions. The P-Delta effect under near-fault ground motions also increases more rapidly with decreasing structure height even for low-rise structures or low earthquake intensity. It was also found that the P-Delta effect cause the PIDR demands to increase by 10% for all three structures subjected to far-fault ground motions. In contrast, considering the P-Delta effect, the PIDR demands rapidly increase by 45% for the high-rise building subjected to near-fault ground motions. Note that the increasing PIDR demands occur at the weakest floor and with the stronger earthquake intensity. However, the P-Delta effect does not change the location of the weakest floor and the yield sequence of components. The seismic behaviors under far-fault and near-fault ground motions are significantly different, because near-fault ground motions not only have velocity pulse but also possibly trigger structural higher vibration modes. In addition, the P-Delta effect may change the distortion direction of the components so that the prediction of the structural collapse direction may be affected. In addition, it was found that if the structure’s period is near the pulse period, the P-Delta effect becomes more significant with the increase of earthquake intensity, and accordingly, it should not be ignored. Moreover, the P-Delta effect cannot be neglected either for the structures susceptible to near-fault ground motions, even if those structures are not tall or the earthquake intensity is not strong.

A weighted scaling method (WSM) is developed for the selection and modification of structure-specific earthquake records in time-history analysis. The matching errors and scaling factors are calculated by weighted least-squares method to match with target spectrum. The weight factors are determined by the modal-mass participation factors. The 3-, 9-, and 20-story steel moment-resisting frame structures are used as examples. Their mean structural responses were calculated by the WSM and the unweighted scaling method (USM). WSM is as accurate as USM for estimating mean structural responses, but WSM has a better capacity for reducing the variability of structural responses.

In recent studies, spectral matching is the most commonly proposed method for selecting earthquake records for time-history analysis of structures. However, until now, there have been no serious investigations of the effects of coordinate values on the scaling of ground motions. This paper investigated the influence of using arithmetic and logarithmic values of response spectra in spectral matching procedures (i.e., ASM and LSM methods) on the results of nonlinear structural time-history analysis. Steel moment resisting frame structures of the 3-, 9-, and 20-stories, which represent low-, medium-, and high-rise buildings, respectively, were used as examples. Structural benchmark responses were determined by calculating the arithmetic mean and median of peak interstory drift ratio (PIDR) demands based on the three record sets developed by the American SAC Steel Project. The three record sets represent seismic hazard levels with 50%, 10%, and 2% probabilities exceeded in 50 years, and their average acceleration spectra were also taken as the target spectrum. Moreover, another 40 record components for selection were scaled both by ASM and LSM methods. The seven components whose spectra were best compatible with the target spectra were selected for the structural time-history analysis. The scale factors obtained by the LSM method are nearly larger than that of the ASM method, and their ranking and selection of records are different. The estimation accuracies of structural mean (median) responses by both methods can be controlled within an engineering acceptable range (±20%), but the LSM method may cause larger structural responses than the ASM method. The LSM method has a better capacity for reducing the variability of structural responses than the ASM method, and this advantage is more significant for longer-period structures (e.g., 20-story structure) with more severe nonlinear responses.

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.