Local Calibration of EICM Using Measured Temperature Gradients and Numerical Analysis

Due to the daily and seasonal fluctuation of temperature gradients, accurate temperature gradients under local climatic conditions are imperative to correctly predict the performance of portland cement concrete (PCC) pavements. In this study, temperature sensors were installed at various depths (0-, 6.4-, 12.8-, 19.2-, and 25.6-cm) in a PCC pavement section to monitor temperature gradients. Based on the measured daily and seasonal temperature data, correlations between air temperature and surface temperature, as well as surface temperature and slab temperature difference, were developed. A finite element analysis was performed to simulate the temperature variation in a PCC pavement, and the analysis results were compared to the field measurement. A local calibration of the enhanced integrated climatic model (EICM) was conducted by comparing the field-measurements with the EICM-predicted temperature gradients. The conclusion demonstrated that surface temperature, rather than air temperature, would better predict temperature gradient in PCC pavements for the input data in EICM.


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  • Accession Number: 01575057
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 18 2015 11:15AM