All published articles of this journal are available on ScienceDirect.
Implementation of Mechanistic-Empirical Pavement Design Guide against Indonesian Conditions using Arizona Calibration
Abstract
Background:
As a transportation infrastructure that connects one area to another, roads have an essential role in economic and social growth, together with establishing a location that may improve the quality of life in the surrounding community. For this reason, it is necessary to perform road maintenance when the structural or functional capacity of the road is inadequate, one of which is by overlaying the road.
Objective:
The main objective of this research is to determine the thickness of the flexible pavement overlay and subsequently examine the damage model produced by the 2015 MEPDG method with Arizona calibration. This study also proposes recommendations for implementing the 2015 MEPDG procedures in Indonesian settings.
Methods:
The thickness of the road overlay can be designed through a mechanistic-empirical approach, which is commonly referred to as the Mechanistic-Empirical Pavement Design Guide (MEPDG). The back calculation on the BAKFAA program was utilized to examine the existing situation. At the same time, a stress-strain analysis was performed using the KENPAVE software to calculate the response of the pavement structure.
Results:
The 2015 MEPDG with Arizona calibration by controlling fatigue cracking has resulted in an overlay thickness of 180 mm. In addition, the damage model was obtained for each type of road failure and can be beneficial in estimating the future IRI value.
Conclusion:
The damage model generated from the 2015 MEPDG procedure is specific to the types of road damage, which can eventually be utilized to predict the future IRI value. It also encompasses local and global calibration variables, such as adjustment factors for its implementation in road pavement conditions in Indonesia. The MEPDG application can be simplified by shortening the mechanistic analysis process, along with reducing traffic variations and the level of detail in the daily climate analysis.