journal article·2017-05

Evaluating fatigue performance of fine aggregate matrix of asphalt mix containing recycled asphalt shingles

Jingwen Zhu, Mohammad Zia Alavi, John Harvey, Lijun Sun, Yuan He

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Abstract

Abstract The use of recycled asphalt shingles (RAS) has been increasing rapidly due to potential environmental and cost-saving benefits. RAS contains 20–30% aged asphalt binder that can replace a considerable portion of binder required in a mix. However, shingle binders are different than typical paving grade binders due to their advanced aging condition taking place during production and after years of service as roofing. This can influence mix properties upon interaction and blending with virgin binder. Asphalt mix fatigue performance is highly dominated by the properties of its fine aggregate matrix (FAM). The properties of FAM containing blends of RAS, virgin asphalt binders, from different sources and with different grades, and rejuvenating agent were evaluated in this study using the conventional time sweep test and a proposed strain sweep test. The tests were performed on small FAM cylindrical bars using a torsion bar fixture in a dynamic shear rheometer (DSR). Based on the results of the preliminary tests, it was observed that the strain sweep test and the time sweep test can similarly predict the fatigue life of the mix. The strain sweep has therefore been recommended due to its time-saving benefits. The fatigue performance of FAM mixes was found to be adversely affected by adding RAS. However, rejuvenating agent could improve the fatigue performance to some extent. The fatigue performance of FAM mixes evaluated was found to be the similar for mixes containing binders with similar grades, but from different sources.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Geotechnical Engineering and Underground Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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