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Construction & building materials, 2017-11, Vol.154, p.1216-1225
2017
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Autor(en) / Beteiligte
Titel
Assessment of the density and moisture content of asphalt mixtures of road pavements
Ist Teil von
  • Construction & building materials, 2017-11, Vol.154, p.1216-1225
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2017
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • •GPR surveys in HMA pavements carried out with a HF antenna to estimate density and moisture content.•The density of the asphalt mixes can be well predicted by the Complex Refractive Index Model.•Water is not easy to assess due to the connectivity pattern of air-voids inside the asphalt mixes. Distresses on asphalt pavements are associated to the traffic and moisture both in asphalt and granular layers. The traffic on road pavements is responsible by the occurrence of cracks that promote the pavement failure. The quality of the asphalt mixes, measured by its density, is an important factor to ensure the integrity of the pavements. The water in pavement surface decreases the driving comfort and reduces the asphalt-aggregate bond leading to the degradation of the asphalt materials. Thus, this paper uses Ground Penetrating Radar (GPR) tests to assess density and moisture content on asphalt mix slabs. Six asphalt mixes were produced in laboratory with the same aggregate gradation and asphalt type, varying the binder content (4.0, 5.0 and 6.0%) and the air-void content (from 3.7% up to 16.9%). For the assessment of the moisture content, each mix was tested with 5, 10, 20 and 40% of the air-void volume filled with water. The effect of the water on GPR results was performed after the sprinkling of the water and 24h after the water application. Results show that the density of the asphalt mixes can be well predicted by the Complex Refractive Index Model while the presence of water is not easy to identify due to the connectivity of the air-voids inside the asphalt mixes.
Sprache
Englisch
Identifikatoren
ISSN: 0950-0618
eISSN: 1879-0526
DOI: 10.1016/j.conbuildmat.2017.06.119
Titel-ID: cdi_gale_infotracmisc_A513926789

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