## 1 Introduction
[21], have demonstrated the feasibility of using WAXD to characterize the crystalline structure and its changes under different conditions, suggesting that WAXD could be a valuable tool for measuring the adsorbed asphalt film thickness. [PERSON] et al. utilized toluene to sequentially elute and separate free asphalt from structural asphalt, subsequently calculating the adsorbed asphalt film thickness, which was approximately 1 \(\upmu\)m. However, the accuracy of these results may be influenced by the complexity of the elution experiments and measurement errors [22; 23]. Therefore, precise determination of the adsorbed asphalt film thickness necessitates further in-depth research. The road performance of asphalt mixtures is primarily influenced by the properties of the asphalt mastic, which result from the interactions between the asphalt and the mineral filler. However, the interactions between asphalt and mineral filler within the mastic, as well as the reinforcement mechanisms of the mineral filler, remain subjects that require further investigation. The micromechanics of composite materials provides an effective approach for studying the interaction mechanisms among the various components of asphalt mastic [24; 25]. Numerous scholars have extensively studied micromechanics models, including the Hashin model [26], the Mori-Tanaka (MT) model [27], the Generalized Self-Consistent (GSC) model [28], the Differential Scheme (DS) model [29], and the Periodic Structure (PS) model [30]. Among these, the Hashin model, the Mori-Tanaka (MT) model, and the generalized self-consistent (GSC) model are the most widely applied and foundational. The Hashin model is primarily designed for two-phase and multiphase heterogeneous materials [31], assuming that spherical inclusions are uniformly distributed in an isotropic homogeneous matrix, with no interaction between inclusion particles. It uses linear elastic variational principles to derive expressions for the elastic modulus, offering a concise formula with clear physical significance. The Mori-Tanaka model assumes that ellipsoidal inclusions of varying sizes are randomly distributed in the matrix and calculates the average stress within the matrix. This model effectively addresses the key theoretical challenges associated with applying [PERSON]'s equivalent inclusion principle under finite volume fraction conditions [32]. The generalized self-consistent model assumes spherical inclusions surrounded by a matrix shell embedded in an effectively infinite medium. In this model, the volume fraction of inclusions in the composite material is defined as the ratio of the inclusion to the matrix shell. [PERSON] and [PERSON] proposed a three-phase generalized self-consistent inclusion model [28], and [PERSON] and [PERSON] simplified the complex equations of the generalized self-consistent model through data analysis, providing a theoretical foundation for the use of micromechanics models in predicting the properties of asphalt mastic [31]. The reinforcement mechanisms of mineral filler in asphalt mastic mainly include volumetric filling reinforcement, physicochemical interaction reinforcement, and interparticle interaction reinforcement. [PERSON] et al. proposed that micromechanics models can be employed to distinguish these three reinforcement mechanisms in asphalt mastic [33]. [PERSON] and [PERSON] investigated the capability of the generalized self-consistent (GSC) model in predicting the dynamic mechanical behavior of asphalt mastic with mineral filler volume fractions of up to 31% [31]. The study found that the GSC model underestimates the effective shear modulus, primarily due to its incomplete representation of the volumetric reinforcement effect of mineral filler. [PERSON] et al. used BBR (Bending Beam Rheometer) and DSR (Dynamic Shear Rheometer) tests to determine the viscoelastic properties of asphalt. They proposed a multiscale model based on the Mori-Tanaka model to predict the viscoelastic behavior of asphalt mastic and examined the effects of voids and aggregates [33].