Performance Characterization of Biorecycled Asphalt and Gray Correlation Analysis between Its Components and Macroproperties

Abstract

To explore the macroproperties of biorecycled asphalt and the correlation between its components and macroproperties, the cooking-aged waste soybean oil was used as the base oil, along with mixing additives, to prepare the biorejuvenator, and a total of six biorejuvenators with different component ratios were first developed. Then, using these rejuvenators, six biorecycled asphalts were prepared and their chemical components and viscosity and a series of pavement properties were measured and evaluated. Finally, using the gray correlation theory, gray correlation analysis between macroproperties and four components was conducted for recycled asphalts. Results show that the addition of biorejuvenator can adjust the component distribution in the aged asphalt, and the components in the aged asphalt can be gradually restored to the original level, thus achieving the regeneration of aged asphalt. Biorejuvenator can restore the penetration, softening point, ductility, and viscosity of aged asphalt to the same level as original asphalt. Further, the biorejuvenator with appropriate composition can restore the rheological parameters such as G*, δ, Jnr, Nf, S, and m of aged asphalt to the level consistent with that of original asphalt. And it can significantly improve the low-temperature and fatigue properties of aged asphalt, while ensuring that the high-temperature performance of regenerated asphalt meets the specification requirements. Overall, the regeneration effects of R5 [base oil: dibutyl phthalate (DBP): antiaging agent: stabilizer=88∶10∶1∶1] and R6 (base oil: DBP: antiaging agent: stabilizer=90∶8∶1∶1) are optimal, which can guarantee that the pavement performance of recycled asphalt basically meets the requirements of original asphalt. The gray correlation analysis shows that the change of the four components of biorecycled asphalt will significantly affect its viscosity, high- and low-temperature performance, and fatigue behavior. The seven indexes of δ, softening point, penetration, m, viscosity, S, and Nf2.5 demonstrate a higher gray correlation with the four components of asphalt (all exceed 0.6), followed by ductility, Jnr0.1, and Jnr3.2. However, G* correlates poorly with the four components of asphalt, whose gray correlation degree is not more than 0.4.