TexasScholarWorks
    • Login
    • Submit
    View Item 
    •   Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    • Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A GIS-based early warning tool for pavement deterioration due to unusually heavy truck loads

    Thumbnail
    View/Open
    LI-THESIS-2017.pdf (5.039Mb)
    Date
    2018-01-25
    Author
    Li, Tianxin, M.S. in Engineering
    Share
     Facebook
     Twitter
     LinkedIn
    Metadata
    Show full item record
    Abstract
    Budget from transportation agencies cannot meet the increasing requirements of pavement maintenance. Preventative pavement maintenance is accepted as a more cost-effective way to keep pavement in an acceptable level with less investment, compared to the reactive pavement maintenance. Traffic information, especially that about heavy truck trips, can help agencies to determine when and how to take preventative pavement maintenance. Two types of unusually heavy truck trips, associated with energy extraction (oil and gas) and urban development activities, were analyzed in this study. Their equivalent single axile loads (ESALs) were then mapped to the network. In addition, existing pavement condition, measuring by ride score, one of the common indexes of Pavement Serviceability, was considered into the model. A new index, ESALs divided by ride score, was introduced to reflect the priority of pavement maintenance of the network influenced by the unusually heavy truck trips. A GIS-Based model, automating the process of analysis by employing the Python Toolbox and online ArcGIS Add-in, was developed. Results include the maps and Excel tables to help agencies understand the priority of pavement maintenance of the network in terms of ESALs and current pavement condition.
    Department
    Civil, Architectural, and Environmental Engineering
    Subject
    GIS
    ESALs
    Equivalent single axile loads
    Pavement
    Heavy trucks
    Pavement deterioration
    GIS-based tools
    URI
    http://hdl.handle.net/2152/63562
    Collections
    • UT Electronic Theses and Dissertations

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin

     

     

    Browse

    Entire RepositoryCommunities & CollectionsDate IssuedAuthorsTitlesSubjectsDepartmentsThis CollectionDate IssuedAuthorsTitlesSubjectsDepartments

    My Account

    Login

    Statistics

    View Usage Statistics

    Information

    About Contact Policies Getting Started Glossary Help FAQs

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin