The development of prediction methods for the remaining life of flexible pavements using falling-weight deflectometer (FWD) multiload-level deflections is presented. Pavement response models and pavement performance models were used in developing this procedure. The pavement response models were designed to predict critical pavement responses from surface deflections and deflection basin parameters. The pavement performance models were used to develop the relationships between critical pavement responses obtained from pavement response models and actual pavement performance. Pavement distress data and FWD multiload-level deflection data obtained from the Long-Term Pavement Performance database were used to verify the performance prediction procedure. It was found that the performance of fatigue cracking can be predicted using the proposed procedure except for pavements with high and rapidly increasing cracking in wet-freeze regions. Such trends may be due to environment-induced distresses such as low-temperature cracking, permanent deformation of unbound layers, or both, during the spring thaw period. Predicted rut depths using both single-load and multiload-level deflections show good agreement with measured rut depths over a wide range of rutting potentials. However, the procedure using single–load-level deflections consistently underpredicts the rut depths. This observation demonstrates that the rutting prediction procedure using multiload-level deflections can estimate an excessive level of rutting quite well and thus improve the prediction quality of rutting potential in flexible pavements.


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    Titel :

    Prediction of Remaining Life of Asphalt Pavement with Falling-Weight Deflectometer Multiload-Level Deflections


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Park, Hee Mun (Autor:in) / Kim, Y. Richard (Autor:in)


    Erscheinungsdatum :

    01.01.2003




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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