**4. Conclusions**

Crack prevention and control is a long-term research field of road engineering. A correct understanding of the internal crack propagation mechanism of asphalt pavement will help road workers to evaluate road working conditions more comprehensively, and make better decisions in design, construction, and maintenance. In this study, the FEM software ABAQUS was used to establish a three-dimensional asphalt pavement layered model. Fracture mechanics theory and the extended finite element method were used to investigate the expansion behavior of preset cracks in the pavement base layer, and the following conclusions were obtained.


• The entropy method was used to analyze the primary and secondary effects of various indicators in the process of reflecting crack propagation in asphalt pavement. The most important factor is the modulus of each layer, and the modulus of the bottom surface layer is the largest, followed by vehicle load. This shows that it is feasible to increase the modulus of each layer, especially the modulus of the bottom surface layer, to suppress the development of reflection cracks, but the impact of increasing the modulus on other road performance should not be ignored.

**Author Contributions:** Conceptualization, J.Y., Y.W., H.W. (Haopeng Wang) and H.W. (Houzhi Wang); methodology, J.Y., Y.W., H.W. (Haopeng Wang) and H.W. (Houzhi Wang); validation, Y.W. and H.W. (Houzhi Wang); formal analysis, Y.W. and H.W. (Houzhi Wang); investigation, Y.W. and H.W. (Houzhi Wang); data curation, Y.W. and H.W. (Houzhi Wang).; writing—original draft preparation, Y.W. and H.W. (Houzhi Wang); writing—review and editing, J.Y., Y.W., H.W. (Haopeng Wang) and H.W. (Houzhi Wang); visualization, Y.W. and H.W. (Houzhi Wang); supervision, J.Y. and H.W. (Houzhi Wang); project administration, J.Y. and H.W. (Houzhi Wang); funding acquisition, J.Y. and H.W. (Houzhi Wang). All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Natural Science Foundation of China (No. 51778140, No. 52078130), Technology Research and Development Program of China State Railway Group Co., Ltd. (P2019G030), Postdoctoral Research Fund Program at Southeast University (1121002107).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
