Kang Yang

The damage to structures caused by the velocity pulse effect of near-fault earthquake waves cannot be ignored, yet there are few studies on the risk assessment of seismic performance for precast concrete frame under near-fault earthquake waves. A novel self-centering precast concrete (SCPC) frame with hysteretic dampers is proposed to obtain great self-recovering and energy consumption characteristics. To accurately assess the seismic behaviors of the novel SCPC frame under the near-fault earthquake waves, a prototype structure is modelled and elastoplastic dynamic analysis is conducted at the design basis earthquake (DBE) and the maximum considered earthquake (MCE) seismic levels. Incremental dynamic analysis and the vulnerability analysis are performed. Annual and 50-year exceeding probabilities of the novel SCPC frame are calculated afterwards. In addition, the reinforced concrete (RC)frame and the traditional SCPC frame are also modelled, whose section sizes, reinforcements arrangement and seismic intensity are consistent with the novel SCPC frame. The dynamic time-history analysis at the two seismic levels are also carried out for two types of frames. The analysis results demonstrate that the novel SCPC frame has great seismic performance and low seismic risk possibility under the near-fault earthquakes loading.

It is common to assume the relationship between temperature and temperature response is instantaneous in bridge health monitoring systems. However, a time-lag effect between temperature and thermal strain response has been documented by the analysis of monitored field data of concrete box-girder s. This effect is clearly reflected by the ring feature in the temperature-strain correlation curve. Inevitably, the time-lag effect has an adverse impact on the accuracy and reliability of state assessment and real-time warning for structural health monitoring (SHM) systems. To mitigate the influence of the time-lag effect, a phase-shifting method is proposed based on the Fourier series expansion fitting method. The time-domain signal is firstly converted into the frequency domain signal to compute the phase difference between temperature data and response strain data at each decomposed order. Subsequently, the total phase difference can be obtained by weighted summation. The signal processing effectively reduces the hysteresis loop area and enhances the correlation between the structural response data and the temperature data. When processing the daily data in different seasons, it is found that after subtraction by the proposed method, the linear feature becomes dominant in the relationship between temperature and the strain during long-term observation.