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Instrumentation, digital image correlation, and modeling to monitor bridge behavior and condition assessment.

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English


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  • Abstract:
    Bridge managers have historically relied on visual inspection reports and field observation, including

    photographs, to assess bridge health. The inclusion of instrumentation, including strain gauges, along

    with a structural model can enhance bridge management. This combination of instrumentation and

    modeling is commonly classified as Structural Health Monitoring (SHM). Traditional SHM measurements

    are reference-independent, such as strain gauges. These sensors can be easily installed and provided

    valuable information for bridge condition assessment, including neutral axis location. The collection of

    global deflection of a bridge, a reference-dependent measurement, is more difficult to collect as the

    connection between the bridge structure and a fixed reference is geometrically challenging. A

    measurement technique that alleviates this issue is digital image correlation. Through recent advances

    in digital photography and the computational capability of personal computers, Digital Image Correlation

    (DIC) is a non-contact measurement technique that can be cost-effectively deployed to collect global

    deflection measurements of a bridge structure. DIC uses multiple digital cameras to photograph a target

    object to provide structural response information. This project incorporates a DIC system into the bridge

    instrumentation and testing program for a concrete deck-steel girder composite bridge, Bagdad Road

    over US Route 4, in Durham, New Hampshire. This report presents the instrumentation selection,

    sensors location planning and deployment, structural testing, DIC measurement for displacement, and

    strain measurements in both laboratory and field experiments. This report also includes a detailed

    structural model that is calibrated with collected field structural response data for bridge decision-making

    and management.

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    urn:sha256:dd3c8ce8f807c134c44f97babd7fcd651d540ccc2bace0ac8afb847011714546
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    Filetype[PDF - 7.41 MB ]
File Language:
English
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