Abstract

The objective of this study was to develop an approach for incorporating techniques used to interpret and evaluate deflection data for network-level pavement management system applications. A national pavement management system is being developed in Iran and the use of falling weight deflectometers (FWDs) at the network level was deemed necessary to compensate for the lack of vital construction history data in the pavement inventory. Because FWD measurements disrupt traffic flow and are a potential safety hazard, it is imperative to increase the interval between FWD testing points as much as possible to allow scanning of the entire 51,000 km network of freeways, highways, and major roads in a reasonable time span with the least traffic disruption. A project-level dataset at 0.2 km intervals in different environments and diverse traffic categories was selected for analysis. In addition, data from continuous ground-penetrating radar was collected concurrently and compared with a limited number of cores. The overall analysis included evaluation of interval variation, segmentation, the structural condition index (SCI), and layer moduli calculated using the AASHTO and ELMOD methods. The analysis was done to determine the optimum interval between test points. Analysis showed that the collection intervals could be increased from 0.2 to 0.6 km. Subsequently, the applicability and time efficiency of the network-level intervals were verified by calculating overlay thickness and time required.

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