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An investigation into Dynamic Modulus of Western Australia Hot Mix Asphalt

Authors :
Y. Richard Kim
Kumlai, S.
Jitsangiam, Peerapong
Nikraz, Hamid
Y. Richard Kim
Kumlai, S.
Jitsangiam, Peerapong
Nikraz, Hamid
Publication Year :
2014

Abstract

Most road networks in Western Australia (WA) are made of flexible pavement with a relatively thin asphalt wearing course and Dense Graded Asphalt (DGA), a commonly used asphalt mix with a continuous size distribution and a low design air-void of around 3% to 7%. Currently, the input parameters for asphalt material for pavement design in Australia still rely entirely on the resilient modulus which cannot incorporate the visco-elastic behaviour of such material into pavement analysis and design. Unlike the resilient modulus, the recently introduced parameter of the dynamic modulus can express the intrinsic behaviour of the visco-elasticity of an asphalt material. The dynamic modulus can describe the stress-strain relationship of viscoelastic material across a wide range of temperatures and frequencies in the form of the Master Curve. The Master Curve is constructed from a sigmoidal function and the Time-Temperature Superposition principle (TTS) with a second-order polynomial shift factor function, according to AASHTO PP62-09. This study aims to investigate the dynamic modulus of Western Australian asphalt mixes, considering three different mixes with varying maximum aggregate sizes of 7 mm, 10 mm, and 14 mm. For this study, all test specimens were controlled to reach a 5% air-void with a Survopac gyratory compactor. Specimens were then tested with an Asphalt Mixture Performance Tester (AMPT) with a testing range of four temperatures: 4°C, 21°C, 37°C and 54°C, and six frequencies; 0.1 Hz, 0.5 Hz, 1 Hz, 5 Hz, 10 Hz, and 25 Hz, according to AASHTO TP62-07. Moreover, the dynamic modulus predictive equation proposed by NCHRP 1-37A MEPDG was modified and introduced to suit WA asphalt mixes.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1033982267
Document Type :
Electronic Resource