Development of a Mechanistic Framework to Predict Pavement Service Life Using Axle Load Spectra from Texas Overload Corridors
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Authors
Morovatdar, Ali
Ashtiani, Reza S.
Licon Jr., Carlos
Issue Date
2020-08
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Other
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en_US
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Abstract
In the past decade, Texas has experienced an alarming increase in the Over-Weight (OW) truck operations associated with the energy development activities, resulting in expedited deterioration of ride quality and loss of pavements serviceability in the impacted zones. This was the motivation to devise a framework for the mechanistic characterization of the remaining service life (RSL) of the pavements affected by OW truck traffic. To achieve this objective, initially, the authors collected the traffic information by deploying Portable Weight-in-Motion (P-WIM) devices to ten representative energy corridors in the Eagle Ford Shale region. Subsequently, an algorithm was developed to retrace the traffic characteristics to the reconstruction year. Converted P-WIM traffic data, back-calculated layer moduli, and layer configurations from the field Non-Destructive Testing (NDT), as well as the climate information, were then incorporated in the RSL analysis protocol to estimate the service life of the pavements. The analysis results indicated that the majority of the studied Farm-to-Market (FM) roads, with less robust pavement structural capacity, either closely approaching their expected service life or exceeded the predefined distress limits. Further comparison of the post-processed results with the field distress measurements revealed that the proposed framework has the potential to realistically simulate the incremental progression of the distresses imparted during the service life of pavements.
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Morovatdar, Ali & Ashtiani, Reza & Licon, Carlos. (2020). Development of a Mechanistic Framework to Predict Pavement Service Life Using Axle Load Spectra from Texas Overload Corridors. 114-126. 10.1061/9780784483183.012.
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DOI:10.1061/9780784483183.012