Narrow Results

In this paper, an innovative two-level damage detection method applicable to real-world online structural health monitoring (SHM) systems is proposed for in-service large steel arch bridges. The method consists of Level 1 damage detection practice that includes strain data acquisition and damage location using the damage index based on the fractal theory, and Level 2 damage detection practice that includes acceleration sample acquisitions and dynamic model updating to quantify the damage. A numerical case study of the Yingzhou bridge based on various damage cases demonstrated the effectiveness of the proposed damage detection method. It is revealed that Level 1 damage detection is sufficiently robust against the standard measurement noise and normal temperature variations. The study results also indicated that the accuracy of Level 2 damage detection largely depends on whether the initial structure imperfections are taken into account, and whether the utilized model updating method is effective under model errors.

Instability is one of the major failure modes of long span arch bridges, and its possibility of occurrence will be increased as triggered by earthquake excitations. However, the randomness of each ground motion causes the difficulty in achieving a reliable assessment of the safety of the bridges in regard to its stability issue based on certain time history analysis. Therefore, a failure probability-based instability evaluation method and corresponding instability damage index are proposed in this study to solve this problem, converting the deterministic analysis of a ground motion into a probability analysis of a group of random ground motions. The results find that the input direction, the velocity pulse and the pulse period of the ground motion have a significant impact on the stability of the bridge, while seismic moment and PGV/PGA ratio do not. The fragility curves show that the bridge has more than 60% probability of slight instability when input PGA reaches 0.2 g, 50% probability of moderate instability when input PGA reaches 0.6 g, and 20% probability of collapse when input PGA reaches 1.0 g. Moreover, when the PGA approaches 1.0 g, it is discovered that the velocity pulse and the pulse period can increase the chance of the occurrence of bridge instability by 20%–30%.

A steel arch bridge originally designed against moderate earthquakes is retrofitted by installation of buckling-restrained braces (BRBs) to sustain severe earthquakes. Two retrofitting methods are considered to obtain good seismic performance of this arch bridge. The original model and retrofitted models subjected to the major earthquakes are investigated by dynamic analyses using 12 patterns of severe (level 2) earthquakes as input ground motions. It is found that the retrofitted models using BRBs can greatly improve seismic performance (displacement, section force, strain, reaction force, etc.) of the steel arch bridge. In addition, to investigate the influence of repeated earthquakes on the seismic responses of the main structure and the demands of BRBs, 12 patterns of earthquake ground motions are repeated by three times. Based on the analytical results, the seismic demands of BRBs against repeated earthquakes are obtained, and the required capacity of BRBs is recommended using a safety factor concluded by comparing the demands under the earthquake applied one and three times. Finally, the influence of the different yield stress on the demand of BRBs is examined by changing the steel grade of BRBs.