Increasing dynamic shear modulus of asphalt binder is one effective measure of improving modulus of asphalt mixture at high temperature. Dynamic shear modulus of asphalt binder may improve through modifying asphalt with polymer or decreasing asphalt grade. In this study, the solvent deasphalting art of producing the hard-grade asphalt demanded crude oil of high quality and decreased the performance of asphalt at low temperature, adopting the technology of blending the hard modifier with the high-grade asphalt reached the criteria of defining the hard-grade asphalt, i.e., dynamic shear modulus is over 10 kPa at the temperature of $60°\text{C}$ (10 rad/s), phase angle is less than 70°, and performance grade achieves 76-22. The results of mix performance tests indicated that the dynamic modulus of the mixture with the hard-grade asphalt at high temperature increased significantly, the antirutting ability also improved notably, while the bending resistant ability at low temperature and the antifatigue ability were slightly inferior to those mixes with the styrene butadiene styrene modified asphalt (PG70-28).

Aiming to evaluate the applicability of Fiber Bragg Grating (FBG) strain sensors for semirigid pavement monitoring, beam and cylinder specimens with three types of FBG strain sensors embedded in two kinds of classic semirigid pavement materials, asphalt mixture (AC‐25) and cement‐stabilized crushed stones (CSCS), were prepared in the laboratory. Four‐point bending tests and uniaxial‐compression tests were carried out under different loading frequencies and temperatures to evaluate the working properties of these sensors and then obtain the corresponding real sensitivity coefficients (SCs). The experimental results showed that the synchronism, repeatability, and linearity of all these sensors were prominent. However, the real SC results were significantly different from the recommended and dependent on many factors including temperature, the loading frequencies, the stress state, and the type of embedded material to different degrees. The SCs remained stable when the moduli of the embedded materials were high enough; otherwise, the SCs varied. Two SC prediction models that used the modulus of the embedded material as the only independent variable were developed to deal with the problem of instability. The modulus difference level between the sensors and the embedded material could integrate the factors roughly, except for the stress state. It is recommended that the factors above should be considered when using FBG strain sensors in practice, and it is still necessary to perform laboratory calibration in advance.

The dynamic modulus of asphalt mixture is an important factor in the design of asphalt pavement, and many scholars have proposed different models for estimating the dynamic modulus of asphalt mixture, but there are almost no studies on the prediction of the dynamic modulus of semi-flexible materials. In order to analyze and estimate the dynamic modulus of semi-flexible materials, we set up a high-performance cementitious paste (HPCP) semi-flexible material and a reference group Stone Mastic Asphalt (SMA-16) under multiple conditions, first measured its dynamic modulus in the laboratory, and analyzed the dynamic modulus characteristics of the material, and then used the equation the estimation equation proposed by Witczak et al. (Witczak1-37A) as a benchmark to introduce a new parameter, grouting mass ratio (Pb) to develop a Witczak-G prediction model to compare and validate the predicted dynamic modulus with the measured values. The results show that compared with SMA-16, HPCP semi-flexible material exhibits higher dynamic modulus and lower phase angle, and its temperature sensitivity and deformation resistance are significantly better than those of SMA-16. Under the influence of porosity and Pb factor, the dynamic modulus is positively correlated with both factors, and the phase angle increases first and then decreases, showing strong elastic properties. In this paper, we propose a dynamic modulus prediction model based on viscosity and Pb, Witczak-G, which predicts the highest coefficient of determination (R2) of the predicted dynamic modulus as high as 0.99 after initial fitting and validation, which indicates that the Witczak-G model is suitable for predicting the dynamic modulus of semi-flexible materials injected with HPCP.

This research focuses on the equivalent relationship between cold central plant recycling mixture and hot mix asphalt. In this paper, the pavement surface condition index (PCI) was calculated by the road surface conditions investigating, which was used as the evaluation standard. The unreasonable data were removed by SPSS software. The existing decay equation of pavement performance was simplified by MATLAB, and optimized by the Marquardt and global optimization methods. The survey data were fitted nonlinearly by 1stOpt software. Ultimately, the multivariate nonlinear regression optimization equation of the equivalent thickness coefficient was established. The results show that the cold central plant recycling with the emulsified asphalt (CREA) pavement equivalent thickness coefficient is 0.587. The cold central plant recycling with the foamed asphalt (CRFA) pavement equivalent thickness coefficient is 0.632. In addition, the performance of 10 cm cold central plant recycling pavement is equivalent to 6 cm the traditional hot mix asphalt pavement. The dispersion of the CREA is greater than that of the CRFA significantly.