Structural Health Monitoring in Performance Based Design of Bridges

点击翻译按钮获取中文摘要

The goal of this research is to incorporate Structural Health Monitoring (SHM) procedures into the Performance-based Design (PBD) of bridges. This will help bridge designers ensure that any bridge designed according to the provisions of the Canadian Highway Bridge Design Code (CHBDC) meets the specified performance criteria in the code. The 2014 edition of the CHBDC mandates performance based seismic design (PBD) for design of lifeline and major route bridges in seismic zones. This design approach is a more promising substitute to the traditional force based design approach permitted in the previous editions of the code. The basic premise of the PBD is to achieve multiple performance objectives defined in terms of serviceability conditions and structural damage at multiple hazard levels. Bridges must meet certain performance objectives defined in terms of tolerated structural damage and serviceability objectives, at three hazard levels of 10%, 5%, and 2% in 50 years' probabilities of exceedance. Nonlinear time history analysis is recommended by the code to assess the damage performance objectives. While the design approach is already required by the code, several challenges still exist for successful implementation of the envisioned requirements. There is clearly a need to facilitate the implementation of the CHBDC performance based design approach, and there are many ways to achieve this. One of these is to incorporate the knowledge of past performance of bridges, mainly from monitoring programs and lessons learned from extreme events, as part of the design procedure and help reduce the uncertainty associated with nonlinear time history analysis to predict the extent of damage, and how this damage could affect the safety of the structure. SHM procedures can be implemented as soon as a bridge has been built to verify that the bridge is performing as was expected when it was designed. It is proposed to implement in the SHM procedures Data Science methods using recorded past performance of bridges. This will help predict with higher confidence the expected performance of a bridge under extreme loads and to determine if the expected damage is within the accepted PBD criteria. To accurately determine the reliability of a structure based on diagnostic results, it is important to determine the probability of underestimating the severity of damage which causes structural failure. Methods for determining the probability distribution of occurrence of true damage need to be developed. It is also envisioned that these procedures could be used to address the issues of damage quantification and damage prognosis. The results of this research will contribute to make SHM a reliable and efficient tool for assessing the safety of structures subjected to strong ground shaking and for ensuring that a bridge designed using PBD can meet the expected performance objectives specified in the CHBDC.