Strength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research. Based on the proposed experiments, the change law of rubber asphalt mixture strength with different temperatures and loading rates was revealed. The phenomenological fatigue equation of rubber asphalt mixture was established. The genetic algorithm optimized backpropagation neural network (GA-BPNN) is highly reliable for optimizing production processes in civil engineering, and it has a remarkable application effect. A GA-BPNN strength and fatigue life prediction model was created in this study. The reliability of the prediction model was verified through experiments. The results showed that the rubber asphalt mixture strength decreases and increases with the increase of temperature and loading rate, respectively. The goodness of fit of the rubber asphalt mixture strength and fatigue life prediction model based on the GA-BPNN could reach 0.989 and 0.998, respectively. The indicators of the fatigue life prediction model are superior to the conventional phenomenological fatigue equation model. The GA-BPNN provides an effective method for predicting the rubber asphalt mixture strength and fatigue life, which significantly improves the accuracy of the resistance design of the rubber asphalt pavement structure.

As an important ecofriendly material in pavement engineering, bioasphalt has received more and more attention recently. However, the negative high-temperature behavior of bioasphalt limits its extensive application. With the purpose of enhancing the bioasphalt high-temperature behavior, polyphosphoric acid (PPA) was used to modify bioasphalt. The PPA/bio-oil composite–modified asphalt’s high-temperature behavior was investigated by the dynamic shear rheometer (DSR) test. The low-temperature behavior was evaluated by using the bending beam rheometer (BBR) test. Finally, the modification mechanism of modified asphalt was analyzed by carrying out a Fourier-transform infrared reflection (FTIR) test. The results indicated that compared with the neat asphalt, the rutting index of PPA/bio-oil composite–modified asphalt was significantly improved. Also, it had excellent low-temperature crack resistance. As the bio-oil and PPA contents in respect to the weight of neat asphalt were 15% and 5%, respectively, PPA/bio-oil composite–modified asphalt performance was optimal. Shear time and shear rate did not have a remarkable effect on PPA/bio-oil composite–modified asphalt performance. Moreover, bio-oil did not affect the chemical structure of the neat asphalt. But, PPA generated new chemical functional groups with neat asphalt and produced chemical modification. This research makes pavement engineering greener, more economical, and environmentally friendly.

A full understanding of bitumen fatigue cracking behavior is extremely important as this phenomenon has a considerable influence on bituminous pavement performance. The current framework for assessing this asphalt binder property is inconsistent in ranking bitumen fatigue performance in terms of the failure definition and damage characteristic curve (DCC) analysis. This study used four different types of asphalt binders: neat asphalt (NA), self-healing thermoplastic polyurethane (STP)-modified bitumen, self-healing poly (dimethyl siloxane) crosslinked with urea bond (IPA1w)-modified bitumen, and styrene–butadiene–styrene (SBS)-modified bitumen (SBSB). All the bitumens were subjected to short-term and long-term aging, and they were also tested by utilizing the linear amplitude sweep (LAS) test and the simplified viscoelastic continuum damage (S-VECD) model. LAS and S-VECD procedures were used to apply the newly proposed and current frameworks in order to analyze bitumen performance. The current framework showed that the bitumens that used a higher number of loading cycles (N) to reach their failure points ($N_f$) failed to exhibit greater fatigue performances in terms of DCC analysis. The developed framework (mainly based on the damage intensity [S] instead of N) was used to solve the inconsistency between the failure definition and DCC assessment in ranking bitumen performance. Additionally, the current framework (failure criterion) presented two R² values below 0.1, but the developed framework (failure criterion) showed that all R² values were greater than 0.9. The developed framework represents a turning point because, for the first time, this type of procedure is mainly being based on S instead of N. Although further tests are needed to confirm its efficiency, it eliminates the inconsistency between the failure definition and DCC assessment.