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Rut Depth Prediction Modeling Using LCPC Tester Of Hot Mix Asphalt


Rut Depth Prediction Modeling Using LCPC Tester Of Hot Mix Asphalt

Asaad, Haitham (2008) Rut Depth Prediction Modeling Using LCPC Tester Of Hot Mix Asphalt. Masters thesis, Concordia University.

Text (application/pdf)
Asaad_MASc_S2016.pdf - Accepted Version


Rut Depth Prediction Modeling Using LCPC Tester of Hot Mix Asphalt

Rutting is considered as one of the major modes of deterioration to flexible pavements. The goal of this study is to contribute to the understating of this phenomenon, and to establish a simple tool predict the resistance to rutting of asphalt pavements based on the experimentation and modeling. Several asphalt mixes will be considered in this study (EG-10, EGA-10, EGS-10, and EG-20, EC-10, SMA). The majority of these mixes are commonly used in Quebec for road construction. Only the SMA (Stone Mastic Asphalt) is less common currently but it popularity is in continuous increase as high-performance mix.

The adopted laboratory test for this study is the LCPC French rutting tester. All mixes will be designed according to the LC Method for bituminous mix design. Influence of the following mix design parameters will be investigated in this research: Binder content (Pb). Air voids (V %). PG is performance grade of the binder (unmodified and modified binders). Voids filled with asphalt (VFA). NMAS is nominal maximum aggregate size represented by D60/D10 of particles in the mix. Percentage of filler.
In the modeling part of this thesis, a detailed analysis will be conducted on the experimental results to obtain a correlation between rutting performance and the different mix design parameters. The modeling would allow the development of computer software for the prediction of pavement resistance to rutting, for different bituminous mixes.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Asaad, Haitham
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Civil Engineering
Date:June 2008
Thesis Supervisor(s):Baaj, Hassan and Bagchi, A.B. and Alecsandru, C.A. and Ganesa, R.G. and Alkass, S.A.
ID Code:981222
Deposited On:15 Jun 2016 13:31
Last Modified:18 Jan 2018 17:52
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