A framework for incorporating dynamic loading in pavement design is introduced. The framework is composed of five main steps. Firstly, input parameters, such as traffic characteristics, material properties, and the pavement configuration, are determined. Both primary and secondary data were obtained from the literature in this step. Secondly, a database of critical pavement responses, used by AASHTOWare software’s transfer functions to calculate pavement damage, was built using advanced pavement finite element models after the loading input was defined. The database includes various pavement configurations, axle configurations (single and tandem), pavement material properties, temperatures, loading conditions, and tire types (single steering, dual, and wide-base). AASHTOWare’s transfer function predicts pavement damage from pavement responses and is used to calculate the international roughness index (IRI) in the third and fourth steps, respectively. Finally, the load spectrum is adjusted to incorporate roughness-induced dynamic loading once the IRI exceeds 95 in./mi. A simple analytical dynamic-loading model was developed, based on mechanistic truck–trailer results. The model is a function of the tire configuration, speed, and IRI. Multiple case studies were performed, considering various pavement configurations, material properties, average annual daily traffic values, and dynamic-loading percentiles. Results showed that dynamic loading had the most significant impact on fatigue life, followed by rutting potential. The AASHTOWare’s transfer functions were found to be insensitive to an increase in loading when considering thick-pavement structures. The outcome of this effort was validated using the measured and predicted IRI from the Specific Pavement Study sections, which are part of the Long-Term Pavement Performance program.


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    Title :

    Incorporation of Pavement Dynamic Loading in Mechanistic–Empirical Design Frameworks


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2023-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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