Induction heating technology has been widely applied in asphalt pavements, and previous studies indicated that the functions of the inductive heating asphalt pavement (IHAP) mainly depends on its temperature distribution under dispersed inductive material. To figure out this characteristic of temperature distribution and get close to the actual heating situation of the IHAP, waste steel shavings was selected as dispersed inductive material, and a novel two-dimensional finite element model was proposed which have been verified by the induction heating experiments. In this model, the 2-D random distribution mesoscopic structures, which were achieved by the modified random aggregate algorithm, were employed to characterize the dispersed conditions of the material composition in IHAP. Based on the above random distribution characteristics, the induction heating simulations of IHAP were conducted. The maximal temperature (Tmax) and the average temperature (Tave) of the pavement surface were used as the prediction targets, and the influences of the operational parameters, material composition and the environmental factors on the above targets were discussed. Moreover, the prediction models between the above influencing factors and the targets were established by response surface methodology. The prediction models and its suggestions for acquiring reasonable targets could provide scientific guidance for applications of the IHAP.

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