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    A spatial and temporal 3D slab-based methodology for optimized concrete pavement asset management

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    GEARY-DISSERTATION-2019.pdf (15.10Mb)
    Date
    2019-11-12
    Author
    Geary, Georgene Malone
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    Abstract
    Management of cracking in jointed plain concrete (JPC) pavement assets is currently monitored at the Federal level using a value of percent transverse cracked slabs per 0.1 mile. This indicator does not provide sufficient information related to the asset to make informed decisions on the remaining life and subsequent investment needed to maintain JPC pavements. With over 20 State DOTs now collecting 3D pavement data using 3D laser technology, the opportunity exists to develop a more robust method to manage and evaluate JPC pavements using this relatively new technology. This dissertation presents a novel 3D Slab-Based Methodology, using 3D pavement data for improved management of cracking in JPC pavements. The proposed methodology consists of four modules: 1) slab severity states module at the individual slab scale with high granularity and finer severity classification that enables us to make more accurate and reliable Maintenance, Rehabilitation and Reconstruction (MR&R) decisions that could not be achieved previously, 2) a fundamental spatial-temporal analysis module which also incorporates the importance of cracking orientation patterns, 3) Kernel Density (KD) smoothing-based crack patterns to visualize and spatially analyze crack severity patterns in multiple scales (e.g. 0.1 mile or 1 miles), and 4) Remaining Service Life (RSL)-based cracking behavior to predict the remaining pavement life more reliably. The methodology is validated using case studies of three different categories (different ages and pavement designs) of Georgia JPC pavements. The validation shows that the methodology provides a valuable means to study the insight of crack deterioration behavior for making informed MR&R decisions by leveraging the 3D pavement data that has become widely available. The 3D Slab-Based Methodology is a more robust condition assessment tool that provides an immense amount of information as compared to the existing evaluation method.
    URI
    http://hdl.handle.net/1853/64055
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Civil and Environmental Engineering Theses and Dissertations [1755]

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