Pavement smoothness is one of the performance measures utilized for pavement maintenance and rehabilitation strategies. The International Roughness Index (IRI), a widely used indicator of pavement smoothness, is required for the Federal Highway Administration’s (FHWA’s) Highway Performance Monitoring System (HPMS). It has also been adapted as a functional performance characteristic in Mechanistic-Empirical Pavement Design Guide (MEPDG), now rebranded as the AASHTOWare Pavement ME Design. The local calibration of IRI prediction model for jointed plain concrete pavements (JPCP) in AASHTOWare Pavement ME Design software requires actual cracking, faulting and spalling measurements, which are not always collected or available with the state highway agencies (SHAs). The primary objective of this study is to examine if the JPCP IRI model can be locally calibrated without doing a local calibration of the primary distress prediction models associated with the IRI model. In this study, the local calibration of IRI model for JPCP pavement systems is performed using two approaches: the coefficients of IRI model are calibrated using (1) locally-calibrated and (2) nationally-calibrated faulting and transverse cracking model predictions. The accuracy of IRI model predictions using both approaches is evaluated and discussed with a focus on achieving reliable smoothness predictions in a cost-effective manner. Comparable accuracy improvement was achieved when Approach 1 was employed in the local calibration of IRI model compared to Approach 2.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Alternative Approaches to the Local Calibration of AASHTOWare Pavement ME Design Jointed Plain Concrete Pavement (JPCP) Smoothness Models


    Beteiligte:

    Kongress:

    Geotechnical and Structural Engineering Congress 2016 ; 2016 ; Phoenix, Arizona



    Erscheinungsdatum :

    2016-02-08




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch