Structural temperature gradient evaluation based on bridge monitoring data extended by historical meteorological data

Abstract

The structural temperature gradient (STG) is one of the most key factors causing cracking and even damage to bridge structures. However, its real effects on bridge structures are often over- or underestimated in practice. For most operating bridges, the structural health monitoring systems have just been put into use recently, and the monitoring structural temperature data are limited, which always leads to unreasonable STG representative value for a long return period based on such short-term structural temperature data. To solve the problems, this article proposes an STG determination method based on the long-term historical meteorological parameters at bridge sites. First, the main meteorological parameters affecting the STG were determined by correlation analysis. Second, considering the different influence mechanisms of various meteorological conditions on STG, a training sample set construction method is proposed by clustering the meteorological parameters and STG monitoring data. Based on such training data, a correlation model between STG and meteorological parameters can be established to extend the STG dataset based on the historical meteorological data. Finally, the peak over threshold method is applied to analyze the obtained extended STG data and to estimate its representative value. The proposed method was verified through a long-span cable-stayed bridge. The results show that the monitoring dataset of the STG can be effectively extended through the established correlation model. Compared with the short-term monitoring data, more reasonable representative values of the STG can be obtained through the extended dataset of monitoring STG.