Simple Empirical Temperature Gradient Prediction Model for Jointed Plain Concrete Pavements: Development and Validation

The aim of this paper is to propose a simple empirical prediction model for temperature gradients within concrete slabs of jointed plain concrete pavements (JPCPs) based on data collected by the Pavement Conditions Monitoring System at Shanghai Pudong International Airport. Temperature data (7,056 data sets) were obtained at the center and corner of the concrete slab and evaluated via statistical analysis. Equivalent linear temperature gradients were employed to quantify the nonlinear temperature profiles throughout the depth of the concrete slab. The surface temperature was obtained via the regressed quadratic function of the temperature profile. For simplicity and effectiveness, concrete slab thickness, surface temperature, air temperature, and time were selected as the input variables. A simple empirical model for predicting the temperature gradient in the concrete slab was developed using multiple regression analysis and validated by field temperature data. The results show no significant difference between the temperatures measured at the center and corner of the concrete slab. Hence, measurement location appears to have little effect on the monitoring of temperature in JPCPs. The results also show that the calculated surface temperature is valid for establishing the empirical model. Moreover, the statistical analysis results indicate that the empirical model fits the data well and all the coefficients in the model are significant at 5% significance. The final results of the model validation demonstrate that the proposed empirical model is reliable and can be conveniently used to predict the temperature gradients within concrete slabs of JPCPs. (C) 2020 American Society of Civil Engineers.