Predicting Critical Shear Stress of Fine-Grained Soils in Kansas
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Predicting Critical Shear Stress of Fine-Grained Soils in Kansas

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English

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    Final Report, August 2017–May 2020
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    Critical shear stress is the stress exerted by flowing water that initiates soil erosion. It is a required parameter for estimating scour around structures. The current state of practice for estimating critical shear stress in cohesive soils is to assume a minimum value based on experiments with cohesionless, coarse-grained soils. The most accurate method for determining the critical shear stress is to directly measure it with a laboratory or in situ erosion device. Unfortunately, erosion testing requires highly specialized equipment not available to many Departments of Transportation. Therefore, the objective of this study was to develop an empirical equation for estimating the critical shear stress in cohesive soils with commonly measured geotechnical properties. This study is unique because electrical resistivity, a common near surface geophysical method that was previously correlated with soil erodibility, was used as a geotechnical property. A total of 26 scour critical bridges with cohesive soils were selected for this study; five soil samples were collected at 12 of the sites in K-TRAN: KSU-15-4. At least one soil sample was collected from the remaining 15 sites to broaden the soil erosion characteristics for model development. Erosion testing was performed in an Erosion Function Apparatus and 13 independent variables (geotechnical properties) were measured. Multiple variable screening criteria identified the percent passing the No. 200 sieve, liquid limit, and electrical resistivity as the statistically significant variables to predict critical shear stress. A probabilistic analysis was used to develop design factors selected by the engineer for implementing the model to predict abutment scour. Finally, the critical shear stress model was validated in a blind study using a bridge site selected by KDOT. This report presents the model development, design factors, study recommendations, and two examples for implementation.
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