Development of Physics-Based Deterioration Models for Reinforced Soil Retaining Structures
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2025-01-01
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Corporate Contributors:State of California SB1 2017/2018, Trustees of the California State University Sponsored Programs Administration ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
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Abstract:Reinforced soil walls are key earth retention features in the transportation infrastructure. They are used to support and retain soil in a wide variety of crucial structures, such as highways, bridges, and railways, to ensure stability. They also provide solutions for constructing embankments and slopes in constrained spaces, allowing for efficient land use and improved infrastructure planning. This study used advanced numerical modeling to improve the understanding of the behavior and long-term performance of the aging reinforced soil walls from the 1970s for asset management purposes. An asset-scale model was created to simulate the effects of weather on these walls. The model included a system to track how moisture-driven corrosion affects wall stability and performance over time. The model outputs provide implications on the wall progressive deterioration over time and estimates for the wall remaining service life. Unlike newer wall generations constructed with strict specifications that limit fill corrosivity, early wall generations may maintain high levels of moisture for prolonged periods that can significantly increase corrosion rates. Accordingly, it is recommended that fill moisture monitoring be added to asset management measures for early generation walls that could have been constructed with highly corrosive or poorly drainable fills. The results of this study indicate that even though corrosion rates vary with changes in fill moisture, the overall loss in reinforcement thickness happens at a steady rate, showing a linear relationship between cumulative corrosion and time. The results also indicate that 25% fluctuation in fill moisture has no to little effect on the cumulative corrosion, and that the average fill moisture can be used to predict an approximate long-term cumulative corrosion. Thus, it is recommended to use one year of seasonal climate data for a specific location to estimate the annual variation in fill moisture. This can predict the yearly corrosion of reinforcements, which can then be multiplied by the number of service years to estimate long-term cumulative corrosion. Finally, an asset-scale performance model based on performance-requirement failure framework was developed using the outputs of the asset-scale numerical model. These performance models can inform decisions about critical transportation infrastructure maintenance, repair, or replacement strategies, and optimizing resource allocation.
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