Experimental analysis of temperature field test based on long-term monitoring data of cold region concrete continuous box girder

Purpose To investigate the temperature stress characteristics of concrete box girders in cold regions, this study focuses on an operational continuous concrete box girder bridge in Qiqihar. The research aims to analyze the annual temperature distribution patterns of the bridge and establish a probabilistic model for temperature differences at different structural positions. Design/methodology/approach Temperature data were collected over one year from the bridge. Statistical methods were employed to analyze the annual temperature distribution trends. The temperature variation patterns at different locations on the mid-span section were examined, and a probability density distribution model was developed using weighted Weibull distributions. Findings The annual temperature variation trend and the annual temperature difference trend both exhibit clear seasonal variations and geometric symmetry. Additionally, there are certain lateral temperature differences between the top slabs and between the bottom slabs, while vertical temperature differences exist between the top and bottom slabs. The positive and negative temperature differences of this cold-region concrete box girder were effectively fitted using a weighted sum of two Weibull distributions, and the parameters of the temperature difference probability density distribution functions between different measurement points were determined. Originality/value This study provides a novel approach to modeling temperature differences in concrete box girders in cold regions using weighted Weibull distributions. This study employs statistical methods to analyze the annual temperature distribution patterns in concrete box-girder bridges located in cold regions. Based on one year of temperature monitoring data, weighted Weibull distributions are adopted to model the temperature differences in concrete box girders under cold climate conditions. The findings contribute to a better understanding of temperature-induced stress patterns in bridge structures, offering valuable insights for the design and maintenance of similar bridges in extreme climate conditions. The established probability density model enhances the accuracy of temperature stress predictions, supporting more reliable structural assessments.