Past reconnaissance studies revealed that bridges close to active faults are more susceptible to damage, and more than 60% of the bridges in California are skewed. To assess the combined effect of near-fault (NF) ground motions and skewness, this paper evaluates the seismic vulnerability of skewed concrete box-girder bridges in California subjected to NF and far-field (FF) ground motions. The relative risk of skewness and fault-location on the bridges is evaluated by developing fragility curves of bridge components and system accounting for the material, geometric, and structural uncertainties. The skewness and a bridge site close to active faults make bridges more vulnerable, and the existing modification factor in Hazus cannot capture the variation in the median value of the fragilities appropriately. A new set of fragility adjustment factors for skewness coupled with the effect of fault location is suggested in this paper.

Under the trend of the rapid development of the internet of things (IoT), sensing for dynamic behaviors is widely needed in many fields such as traffic management, industrial production, medical treatment, building health monitoring, etc. Due to the feature of power supply independence and excellent working performance under a low-frequency environment, triboelectric nanogenerators (TENGs) as sensors are attracting more and more attention. In this paper, a comprehensive review focusing on the recent advance of TENGs as sensors for dynamic behaviors is conducted. The structure and material are two major factors affecting the performance of sensors. Different structure designs are proposed to make the sensor suitable for different sensing occasions and improve the working performance of the sensors. As for materials, new materials with stronger abilities to gain or lose electrons are fabricated to obtain higher surface charge density. Improving the surface roughness of material by surface engineering techniques is another strategy to improve the output performance of TENG. Based on the advancement of TENG structures and materials, plenty of applications of TENG-based sensors have been developed such as city traffic management, human–computer interaction, health monitoring of infrastructure, etc. It is believed that TENG-based sensors will be gradually commercialized and become the mainstream sensors for dynamic sensing.

The timely identification of differential settlement of track foundations is of great significance for the safety of train operation and the maintenance of track structures. However, traditional monitoring techniques cannot meet the requirements of efficient, real-time, and automatic monitoring of track foundation settlement. In order to solve these problems, a real-time identification method based on a gated recurrent unit (GRU) neural network is proposed for the differential settlement of track foundations monitoring. According to parameter sensitivity analysis, the vertical acceleration of the vehicle is selected as the known data fed into the GRU network for differential settlement identification. Then the GRU network is employed to establish the nonlinear relationship between the vertical acceleration of the vehicle and the differential settlement of the track foundation. The results indicate that the longitudinal continuous differential settlement distribution curve of track foundations could be accurately identified with GRU neural network through the real-time vibration response of the vehicle–track. The current method may provide a new means for the real-time and efficient identification of the differential settlement of track foundations.

Structural-response reconstruction is of great importance to enrich monitoring data for better understanding of the structural operation status. In this paper, a data-driven based structural-response reconstruction approach by generating response data via a convolutional process is proposed. A conditional generative adversarial network (cGAN) is employed to establish the spatial relationship between the global and local response in the form of a response nephogram. In this way, the reconstruction process will be independent of the physical modeling of the engineering problem. The validation via experiment of a steel frame in the lab and an in situ bridge test reveals that the reconstructed responses are of high accuracy. Theoretical analysis shows that as the sensor quantity increases, reconstruction accuracy rises and remains when the optimal sensor arrangement is reached.

In order to improve the construction efficiency of piers and reduce the local damage of piers, concrete-filled steel tubes (CFST) are used to precast pier segments. Aiming at the problems of the poor integrity and insufficient energy dissipation capacity of dry joint segmental assembled piers, segmental assembled concrete-filled steel tubular piers with external replaceable energy dissipators are being developed. Based on the low cyclic test of a segmental assembled CFST pier, the finite element numerical simulation model of a CFST pier is established based on ABAQUS software, and the validity of the numerical model is verified by the experimental results. The effects of the section ratio, axial compression ratio, and initial prestress on the seismic performance of piers are studied through a pseudostatic analysis. The results show that an increase in the section ratio can improve the lateral bearing capacity and energy dissipation capacity of the pier. When the section ratio is increased to 4%, the energy dissipation capacity of a CFST pier is increased by 77.8% and the lateral bearing capacity is increased by 33.9% compared with a section ratio of 2%, but the residual displacement of the pier top also increases. With an increase in the axial compression ratio, the energy dissipation capacity of the pier is significantly improved; when the axial compression ratio is increased to 0.30, the energy dissipation capacity of CFST piers is increased by 27.5% compared with a section ratio of 0.05, the residual displacement of the pier top is reduced, and the self-resetting effect of the pier is improved. A change in the initial prestress has no effect on the energy dissipation capacity of piers. Finally, based on an analysis of mechanical theory, a formula of bending capacity suitable for this type of pier is proposed, and the error is within 10%.

Water leakage and debris accumulation caused by the expansion joints in a bridge superstructure reduce the service life of the bridge and increase the maintenance costs. A link slab is an effective means to eliminate the expansion joints, providing a continuous deck system. However, the load-caused concrete cracking of the link slab also leads to problems associated with water leakage and rebar corrosion. In order to solve these problems, a new type of steel–concrete composite link slab (SCC-LS) was designed to continuously subject the bridge deck to a positive bending moment and surface concrete compression, which reduced the cracking damage in the link slab. This paper presents the mechanical performance results of the SCC-LS obtained using full-scale model tests. Furthermore, theoretical calculations and finite element (FE) models of the jointless bridge validated the performance based on the experimental results. The results of this study show that the SCC-LS can effectively solve the problem of concrete cracking on the surface of the bridge deck, which has theoretical reference significance and engineering application value for the structural design, maintenance and transformation of continuous simply supported bridge decks and the promotion of seamless bridges.