Low-Temperature Performance of Open-Grade Friction Course Based on Computed Tomography Image Reconstruction Technology

Open-grade friction course (OGFC) asphalt mixtures exhibit significant brittleness at low temperatures owing to their porous structure, rendering road surfaces vulnerable to damage under dynamic vehicle loads. This study combines industrial computed tomography (CT) scanning and discrete element modeling techniques to propose a macro–meso cross-scale analysis method, which effectively avoids result discreteness caused by individual differences of nonhomogeneous specimens in traditional tests, significantly improves the accuracy and reliability of test data, and provides a scientific analysis for the evaluation of a low-temperature performance. Brazilian disc specimens of the OGFC asphalt mixture were prepared, and industrial CT scanning was employed to obtain layer-by-layer distribution images of the asphalt mortar, aggregates, and voids inside the specimens. Subsequently, Python toolkits were utilized for image processing, and a pixel-based discrete element model based on the PFC3D software and Fish language was built. The results show that although low temperature exacerbates the brittleness of the material, the failure displacement value of the specimen at −15°C is significantly lower than that at −10°C and −5°C; furthermore, the dynamic-load state significantly impacts the tensile strength. Increasing the loading rate from 0.1×2 r to 10×2 r ms−1 increases the tensile strength by 58.6%, whereas decreasing the porosity from 24 to 18% increases the dynamic strength by 16.2%, indicating that controlling the porosity range improves the strength. In summary, this study reveals the strength attenuation mechanism of OGFC under the coupling action of low temperatures and dynamic loads, and the proposed cross-scale analysis method provides a generalizable modeling paradigm for the numerical simulation of permeable surface layer materials.