Abstract:
The Mechanistic-Empirical Pavement Design Method through AASHTOWare Pavement-ME software is a tool that helps make pavement design tailored to the specific material, climatic and loading conditions of the road, giving it a great advantage over its predecessor, AASHTO 1993 method. Despite the great implications of utilizing Pavement-ME on the performance and lifetime of the pavement, highway agencies around the world are shying away from implementing it due to the lack of expertise, technologies and data needed. In order for Pavement-ME to predict the performance of the pavement in real time conditions, it employs detailed input parameters on truck traffic and climate, and the proper experimental characterization of materials. In addition, it requires empirical distress prediction functions that are able to translate strains and deformations into quantified distresses. Considering the countries of the Middle East, namely Kingdom of Saudi Arabia, United Arab Emirates and Qatar, their economies are witnessing fast growth accompanied by an expansion of their road infrastructure. The desert nature of this region alongside the very hot temperatures and the expected high truck volumes, are supporting reasons for a transfer towards Pavement-ME in pavement design. Very few attempts to implement Pavement-ME were taken outside the United States of America and none of those attempts resulted in a full implementation of the software. Since limited data is available for local highway agencies, there is great need to present a specific implementation roadmap that utilizes available easily collected data. This research addresses the above need by utilizing Pavement-ME runs to perform sensitivity analysis on important software input parameters. This analysis will result in recommending the level of accuracy needed for certain input parameters, and catalogue values, specific for the region, for other input parameters. The research utilizes a case study from Iraq to assess the need for a local calibration of the above mentioned em
Description:
Thesis. M.E. American University of Beirut. Department of Civil and Environmental Engineering, 2018. ET:6871.
Advisor : Dr. Ghassan Chehab, Associate Professor, Civil and Environmental Engineering ; Members of Committee : Dr. Mohamed-Asem Abdul Malak, Professor, Civil and Environmental Engineering ; Dr. Ibrahim Alameddine, Assistant Professor, Civil and Environmental Engineering.
Includes bibliographical references (leaf 109-113)