Abstract
This study evaluates the microstructural characteristics and mechanical behavior of cold recycled asphalt mixtures (CRAM) stabilized with asphalt emulsion throughout their curing period. A multi-scale experimental framework was employed, combining high-resolution X-ray micro-computed tomography with in-situ falling weight deflectometer (FWD) testing. Field-extracted specimens from four full-depth reclaimed pavement sections were scanned at multiple depths and curing ages to quantify air void (AV) morphology, distribution, and connectivity using deep learning-based digital image processing. Complementary FWD testing, conducted over a 263-day period, enabled the backcalculation of elastic moduli to monitor the progressive stiffness gain of the CRAM layers under field conditions. Results revealed significant heterogeneity in AV distribution, particularly in interface and base zones, which exhibited higher void counts and volumes compared with other layers. Deflection and modulus trends followed a three-phase trajectory: initial low stiffness, intermediate stabilization, and advanced structural gain, with moduli increasing from 300–700 MPa to over 3,000 MPa. The integration of microstructural and mechanical data revealed a strong correlation between AV network refinement and structural performance over time. These findings underscore the importance of curing protocols, compaction quality, and layer interaction in recycled pavement systems. The study demonstrates the value of combining advanced imaging with field testing to support performance-based design, quality control, and long-term durability of cold-recycled asphalt technologies.
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