Implementation Of A Mechanistic- Empirical Pavement Design Method For Uruguayan Roadways

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Virginia Tech

Mechanistic-Empirical (M-E) methods are the cornerstone of current pavement engineering practice because of their enhanced predicting capabilities. Such predicting power demands richer input data, computational power, and calibration of the empirical components against distress measurements in the field.

In an effort to spearhead the transition to M-E design in Uruguay, the aim of this Project is twofold: (1) develop an open-source, MEPDG-based, simplified M-E tool for Uruguayan flexible pavements [Product-One], and (2) compile a library of Uruguayan input data for design [Product-Two].

A functional, Matlab-based beta version of Product-One with default calibration parameters and a first collection of Uruguayan input data are presented herein. The Product-One beta is capable of designing hot-mix asphalt (HMA) structures over granular bases on top of the subgrade. Product-Two features climate information from the INIA weather station network, traffic distribution patterns for select Uruguayan highways, standard-based (Level-3) HMA properties, and Level-3 and Level-2 unbound materials' parameters. Product-One's outcomes were against other available M-E software, as a means to test the code's performance: Product-One reported a distress growth similar to CR-ME (MEPDG-based) on default calibration parameters but different to MeDiNa (calibrated core).

In conclusion, Product-One managed to perform like another MEPDG-based software under the same design inputs and constraints, accomplishing one of this Thesis' objectives. However, Product-Two could not be created to the initially-desired extent. Nevertheless, the author remains confident that significant leaps forward can be made with little extra effort and further research on M-E design can be encouraged from this project.

pavement, Design, mechanistic, empirical, MEPDG