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Evaluation of Two-Dimensional (2D) Hydraulic Models to Improve Scour Predictions and Countermeasures

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English


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    August 1, 2019 – October 31, 2022
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  • Abstract:
    The overall goal of this research project was to examine the capabilities of FO-DTS and 2D hydraulic models for improving the prediction of scour depths at bridge foundations. To accomplish this goal, the following specific objectives were addressed: (1) to develop, test, and deploy scour monitoring devices based on FO-DTS capable of tracking changes in the sediment-water interface at high spatial and temporal resolutions during floods; (2) to compare the relative performance of 1D and 2D hydraulics models when resolving needed hydraulic variables and predicting maximum scour depths at bridge crossings; and (3) to develop recommendations for predicting scour depths around bridge foundations using 2D hydraulics models in the context of current procedures that are established by the FHWA for design purposes. A novel FO-DTS scour-monitoring device was developed, addressing many of the limitations of the existing scour-monitoring systems. The testing of the FO-DTS scour monitoring device demonstrated that the device can effectively detect the Sediment-Water and Water-Air interfaces under different flow conditions with high accuracy. Application of 1D and 2D hydraulics models indicated that the maximum values of predicted hydraulics variables by SHR-2D tend to be larger than the corresponding HEC-RAS 1D values. Alternatively, at the pier locations, results suggested an opposite trend in which the values predicted by SHR-2D are smaller than those predicted by HEC-RAS 1D. It should be noted, however, that the relative performance between the models varies with bridge crossing and simulated event. More importantly, the normalized flow field characterization indicated that 2D modeling captured spatial variability of flow variables along the channel, which in turn has implications for predicting maximum sour depths.
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    urn:sha-512:f8233a92c99b8a23161f92fefd42d17cb3a5bc44f538d5e65236f5b066983adbf45235a8797720713a8cf447c0734cf6ebd946474882f0874e7635799029e251
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English
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