Development of mechanistic-empirical distress prediction model for the perfomance of superpave designed asphalt pavement using simplified dynamic modulus analysis method / Nuryantizpura Mohamad Rais
The permanent deformation becomes a major problem as axle loading increase where it normally happens on highly stressed roads. Permanent deformation always is a potential major distress where the ruts trap water and cause hydroplaning. Therefore, it is important to make efforts to minimize permanent...
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| Format: | Book Section |
| Language: | English |
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Institute of Graduate Studies, UiTM
2016
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| Online Access: | http://ir.uitm.edu.my/id/eprint/20061/ http://ir.uitm.edu.my/id/eprint/20061/1/ABS_NURYANTIZPURA%20MOHAMAD%20RAIS%20TDRA%20VOL%2010%20IGS%2016.pdf |
| Summary: | The permanent deformation becomes a major problem as axle loading increase where it normally happens on highly stressed roads. Permanent deformation always is a potential major distress where the ruts trap water and cause hydroplaning. Therefore, it is important to make efforts to minimize permanent deformation and the same time it is necessary to develop a model to predict the potential permanent deformation development when designing an asphalt pavement overlay. Thus, it is necessary to predict the distress prediction models using Superpave mixes other than conventional mixes in order to be efficient in assessing and controlling permanent deformation of asphalt pavements. In relation, there is absence of Mechanistic-Empirical pavement distress prediction models developed to predict the Superpave mixes permanent deformation under Malaysian environmental conditions. In order to take this gap into consideration, this study was conducted to investigate the use of dynamic modulus in the development of permanent deformation distress prediction model. The following procedure was used: The simplified dynamic modulus analysis method established in this research can be good indicators to describe how a master curve’s shape varies with asphalt, nominal aggregate size, aging and confinement level. The authors have developed the simplified master curve model which can predict dynamic modulus beyond the measure data set… |
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