Dynamic shear modulus of an asphalt mastic has a remarkable effect on the mechanical performance of an asphalt pavement, and particulate composite micromechanical models are proven to be suitable for the prediction of modulus of asphalt mastics. However, the prediction accuracy of the current micromechanical models decreases sharply at a high filler concentration and high temperature (or low frequency). This study aims to develop a modified micromechanical model that can be applied to predict modulus of asphalt mastics at a wide range of frequencies and filler concentrations. Dynamic shear rheometer (DSR) tests are performed using asphalt mastics with four filler concentrations, and three-dimensional discrete-element method (DEM) is implemented to validate the DSR tests and obtain additional master curves of asphalt mastics with different filler concentrations. The reinforcement mechanisms are introduced into the micromechanical models to predict the laboratory test results with an increase of the prediction accuracy. The numerical results show that the test data is repeated by the DEM simulation, which is believed to be a promising tool to present the rheological behavior of asphalt matrix and asphalt mastics. The modified micromechanical viscoelastic model can predict the dynamic shear modulus of asphalt mastics successfully at high filler concentration and low frequency.

This study aims to adopt the acoustic emission (AE) technique to evaluate the reinforcing effect of basalt and steel fibers on the fracture resistance of asphalt concrete (AC) under indirect tension (IDT) testing at low temperature. Control asphalt concrete (CAC) with no fibers was also tested for comparison. The AE counts and durations were recorded and analyzed to characterize the fracture processes of basalt fiber reinforced asphalt concretes (BFRAC) and steel fiber reinforced asphalt concretes (SFRAC), which were compared with the results from static displacement and strain data obtained through digital image correlation (DIC). The results revealed that the low-temperature fracture processes of BFRAC and SFRAC could be effectively divided into four stages according to the evolutions of AE parameters and corresponding cumulative AE parameters. AE properties could effectively evaluate the reinforcing effects of basalt and steel fibers on the low-temperature fracture resistance of AC, whereas static displacement and strain failed to identify the effects. BFRAC with a fiber length of 12 mm (BFRAC-12) had favorable ductile property at the final failure stage, whereas BFRAC with a fiber length of 6 mm (BFRAC-6), SFRAC with a fiber length of 6 mm (SFRAC-6), and SFRAC with a fiber length of 12 mm (SFRAC-12) exhibited brittle characteristics based on variations of AE parameters. Good correlations between the curve characteristics of AE parameters and the failure loads of AC specimens can be observed. The AE technique demonstrated great potential for the damage fracture characterization of asphalt materials.

To choose the maximum dividing sieve sizes for multiscale analysis, a mechanistic classification principle of sieve sizes is developed to characterize the size ranges of four inner structures in an aggregate’s gradation. A theoretical model of interlock check and stress evaluation is also established to evaluate the contact and interactive-filling status between the identified structures. Then, a discrete element (DE) simulation of triaxial compression tests of graded aggregates is built to validate the mechanistic classification principle. The contact force is extracted to calculate the contribution of each sieve size to bear the load and stabilize the structure. The size ranges of inner structures can be determined by the combined analysis of force occupation curves and mechanistic classification principle. The results show that the dividing sieve sizes for four gradations in the main classification system are different, but they are the same in the subclassification system. The sieve-size classification principle along with DE simulation can provide a basis of choosing appropriate sieve sizes to conduct multiscale analysis of asphalt mixtures and asphalt pavements.

Since rutting is a major distress in flexible pavements at intermediate and high temperatures, rutting models with concise expressions and satisfying accuracy can have considerable contributions to the pavement design, maintenance and rehabilitation. In this circumstance, two mechanistic-empirical rutting models were proposed in this study. The models were adapted from traditional rutting models and involve advanced mechanical aspects such as strains and stress invariants under moving loads and a yield criterion for asphalt mixtures. This paper includes detailed explanations of model expressions, qualitative comparisons with current models and model applications in an innovative laboratory test. The laboratory test and finite element simulation of asphalt mixtures under moving loads were used to calibrate, validate and check the sensitivity of the proposed models. The results showed the proposed models successfully captured rutting development in asphalt mixtures; they also reasonably predicted rutting behaviors of layered structures under different loading and environmental conditions. In model applications, effects of different factors on material properties, structural strain and stress responses and rutting development were evaluated. Finally, the determination of model parameters in the proposed models was discussed and recommended for further research.