Multi-Factor Comprehensive Fatigue Test and its Fatigue Prediction Model for Rap

Abstract

The research on the fatigue performance of reclaimed asphalt mixture and the establishment of its fatigue life prediction model is the key to its large-scale engineering application. The multi-factor comprehensive four-point bending fatigue tests of the fresh and recycled asphalt mixtures under the strain control of cyclic loading were conducted to investigate influencing factors on their fatigue performance and establish a new fatigue prediction model for RAP. The hot recycled asphalt mixture samples of AC-16C were prepared by a uniform test design method, with the RAP content of 0%, 20%, 30%, and 40%. Through the fatigue test data of 20 groups of fresh asphalt mixture with 0% RAP and 40 groups of recycled asphalt mixtures with the content of 20%, 30%, and 40% RAP, the simplified applicability of the JTG fatigue model and its parameters modification were studied, thereby a comprehensive fatigue prediction model of recycled asphalt mixture is established on consideration of strain level, asphalt content, void ratio, and RAP mixing amount. This fatigue prediction model of recycled asphalt mixture is proposed by modifying the parameters of the fatigue formula of the new asphalt mixture in the specification and comparing the fatigue test data of the recycled asphalt mixture. The research results show that: (1) The simplified JTG fatigue prediction model can effectively predict the fatigue life of fresh asphalt mixture with the content of 0% RAP, and the model parameter a is a constant of the order of 10 16 ; (2) The correction coefficients α and β of the initial bending stiffness modulus S 0 and the Voids Filled with Asphalt ( VFA ) in the improved JTG model of the hot recycled asphalt mixture considering the RAP content are 0.006 and 0.0136, respectively; (3) The model can accurately predict the fatigue life of recycled asphalt mixtures with the range of RAP content of 0-40%, with an average deviation of only 0.106, and has higher prediction accuracy for fatigue life measured close to or higher than 10 6 times.

Keywords: Hot recycled asphalt mixture, Bending fatigue test, Fatigue prediction model, Uniform test design, Model parameter correction.