Predictive quantitative model for assessing the asphalt-aggregate adhesion quality based on aggregate chemistry
Source abstract
Abstract
Asphalt-aggregate adhesion quality is a key factor in the mechanical performance of asphalt pavements. This work presents a predictive model of moisture damage in asphalt-aggregate systems based on aggregate chemistry. The study included seven siliceous aggregates and two calcareous aggregates, and one source of asphalt binder. Specimens composed of an aggregate core, a 20 μm thick asphalt film and a metallic stub were tested via a pull-off debonding experimental setup after multiple water conditioning processes. The experimental results i.e. maximum load at failure, Fmax, work of fracture, Wf, and adhesive failure area at the surface of the aggregate, A% show that for siliceous aggregates, the SiO2 content increases moisture susceptibility while the opposite is seen for Fe2O3 and CaO, and that for calcareous aggregates, moisture susceptibility increases with their SiO2 content. These results were used to propose, for the first time, an empirical moisture damage predictive model for siliceous aggregates based on aggregate chemistry.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Concrete Corrosion and Durability
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil and Environmental Engineering, Universidad de los Andes, Bogotá, Colombia
Funding
Office of the Vice-presidency of Research of Universidad de los Andes
References (31)
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