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Discrete element modelling of foamed asphalt cold recycled mixture for characterizing realistic meso-scale failure behaviour

delete2026-06-30
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PRE
AI
X
Xiujun Li
L
Lijun Wang
X
Xin Xiao *
Y
Yang Kuang
Y
Ying Yang
M
Mingmin Li
DOI:10.1080/10298436.2026.2696972delete
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Abstract

Abstract

En 中文
Foamed asphalt cold recycled mixture (FACRM) is a complex multiphase material, and accurate numerical simulation of its mesoscopic failure behaviour remains challenging, as conventional models oversimplify coarse aggregates as rigid clumps and fail to fully capture its strength and failure evolution. This study proposes a crushable coarse aggregate discrete element method (DEM) model by integrating 3D blue-light scanning and particle flow code (PFC) for FACRM mesostructural reconstruction. A coarse aggregate shape template library is constructed from scanned morphological data. Virgin aggregates are reconstructed with low-overlapping multi-sized spherical sub-particles, and reclaimed asphalt pavement (RAP) particles are classified and reconstructed with targeted modelling strategies for mineral skeletons and aged asphalt binder distribution. A non-overlapping particle system matching actual gradation is generated and compacted to standard Marshall specimen dimensions. After model equilibrium, rigid aggregate clumps are converted into cemented crushable assemblies. Virtual Marshall stability test results well match laboratory data, reliably reproducing the stress-strain response and mesoscopic failure characteristics of FACRM. These findings validate the efficiency and cost-effectiveness of the established FACRM modelling framework.
Keywords:
Foamed asphalt cold recycled mixture (FACRM)
discrete element modeling (DEM)
meso-scale reconstruction
coarse aggregate with crush potential
reclaimed asphalt pavement (RAP)

Journal

International Journal of Pavement Engineering cover
International Journal of Pavement Engineering
IF:
3.3
Papers:
2.8K
Citations:
8.0K

Organization

B
b fuling district highway affairs center
Scholars:
2
Papers: 1
Citations: 0
U
university of shanghai for science and technology
Scholars:
5.1K
Papers: 2.1K
Citations: 4
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