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    Applicability of the International Roughness Index as a Predictor of Asphalt Pavement Condition1

    Source: Journal of Transportation Engineering, Part A: Systems:;2007:;Volume ( 133 ):;issue: 012
    Author:
    Kyungwon Park
    ,
    Natacha E. Thomas
    ,
    K. Wayne Lee
    DOI: 10.1061/(ASCE)0733-947X(2007)133:12(706)
    Publisher: American Society of Civil Engineers
    Abstract: This note establishes the relationship between the surface distress of an asphalt pavement and its roughness, as conveyed respectively by the pavement condition index (PCI) and the international roughness index (IRI). The DataPave software provides the roughness of varied roadway pavement sections from the North Atlantic region that were investigated under the long term pavement performance (LTPP) study. The MicroPAVER1 software system computes the condition of the same sections using cross-referenced distress data from DataPave. A transformed linear regression model predicts pavement condition given roughness. It confirms the acceptability of the IRI as a, albeit not the sole, predictor variable of the PCI whereby the former accounts for the majority, close to 59%, of the variations in the latter. Further, an analysis of variance confirms the existence of a strong relationship between both variables.
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      Applicability of the International Roughness Index as a Predictor of Asphalt Pavement Condition1

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    http://yetl.yabesh.ir/yetl1/handle/yetl/37955
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    contributor authorKyungwon Park
    contributor authorNatacha E. Thomas
    contributor authorK. Wayne Lee
    date accessioned2017-05-08T21:04:56Z
    date available2017-05-08T21:04:56Z
    date copyrightDecember 2007
    date issued2007
    identifier other%28asce%290733-947x%282007%29133%3A12%28706%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/37955
    description abstractThis note establishes the relationship between the surface distress of an asphalt pavement and its roughness, as conveyed respectively by the pavement condition index (PCI) and the international roughness index (IRI). The DataPave software provides the roughness of varied roadway pavement sections from the North Atlantic region that were investigated under the long term pavement performance (LTPP) study. The MicroPAVER1 software system computes the condition of the same sections using cross-referenced distress data from DataPave. A transformed linear regression model predicts pavement condition given roughness. It confirms the acceptability of the IRI as a, albeit not the sole, predictor variable of the PCI whereby the former accounts for the majority, close to 59%, of the variations in the latter. Further, an analysis of variance confirms the existence of a strong relationship between both variables.
    publisherAmerican Society of Civil Engineers
    titleApplicability of the International Roughness Index as a Predictor of Asphalt Pavement Condition1
    typeJournal Paper
    journal volume133
    journal issue12
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)0733-947X(2007)133:12(706)
    treeJournal of Transportation Engineering, Part A: Systems:;2007:;Volume ( 133 ):;issue: 012
    contenttypeFulltext
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    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian