Distress prediction models, or transfer functions, are key components of the Pavement ME Design and relevant analysis. The accuracy of such models depends on a successful process of calibration and subsequent validation of model coefficients in the transfer functions with independent data sets. In this paper, data needs for distress models in Pavement ME Design are investigated for the state of Oklahoma. Based on past research work at Oklahoma Department of Transportation (ODOT), various Pavement ME Design inputs, historical cracking, rutting, and roughness data are gathered for selected ODOT segments and Long Term Pavement Performance (LTPP) sites. Pavement ME Design test runs are performed, and precision and bias levels of rutting, cracking, and roughness data sets in the historical ODOT databases are studied. Finally a workflow for Pavement ME Design prediction model calibration in Oklahoma is recommended to assist ODOT in implementing Pavement ME in the coming years in a production environment.


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    Titel :

    Pavement ME Design Distress Modeling for Oklahoma


    Beteiligte:
    Wang, Kelvin C. P. (Autor:in) / Li, Qiang Joshua (Autor:in) / Cross, Stephen A. (Autor:in) / Dean, Jeff (Autor:in)

    Kongress:

    Second Transportation & Development Congress 2014 ; 2014 ; Orlando, Florida


    Erschienen in:

    Erscheinungsdatum :

    2014-05-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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