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    Failure Prediction of Clay Embankments Subject to Weather-Driven Deterioration

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2024:;Volume ( 150 ):;issue: 012::page 04024128-1
    Author:
    Amr M. Morsy
    ,
    Peter R. Helm
    DOI: 10.1061/JGGEFK.GTENG-12842
    Publisher: American Society of Civil Engineers
    Abstract: Embankments have been widely used in the construction of transportation and flood defense infrastructure. Embankments constructed from clays experience a suite of weather-driven deterioration processes that lead to a progressive loss of hydromechanical performance and eventually to failures whose consequences can be severe and costly. This study aimed to predict the time to failure of aging, deteriorating clay embankments supporting transportation infrastructure. A multiphase numerical modeling approach developed to simulate the long-term weather-driven hydromechanical behavior of clay embankments was used to model and simulate the behavior of a number of well-documented embankment failure case histories with known service life and available information to derive the necessary soil properties and climate records. Numerical models were developed for a total of 34 case studies, and numerical simulations were performed to predict the time to failure of the embankments due to progressive, long-term, weather-driven deterioration. Predictions compared well with actual times to failure reported for the simulated case studies. Further, geometries of modeled slides compared well with those measured for actual slides. The models offered insights into the conditions associated with failure, such as displacement patterns and pore pressure conditions. It was observed that as near-surface soil experiences cycles of wetting and drying, and accompanying cycles of swelling and shrinkage, irrecoverable swelling accumulates with time, causing swelling-induced slides. Overall, the numerical modeling approach was proven effective in producing data necessary to develop deterioration models that could improve infrastructure asset management. This study underscores the importance of understanding and predicting the long-term performance of clay embankments in civil engineering infrastructure. Through the use of long-term numerical modeling, this study could predict the time of weather-driven shallow slides in clay embankments. The ability to predict failures of embankments can offer significant improvements in infrastructure asset management. Predictive models can offer early warning to potential imminent failures, allowing for timely intervention to minimize the risk of sudden, unexpected failures, especially where consequences can be severe and costly.
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      Failure Prediction of Clay Embankments Subject to Weather-Driven Deterioration

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4304623
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    • Journal of Geotechnical and Geoenvironmental Engineering

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    contributor authorAmr M. Morsy
    contributor authorPeter R. Helm
    date accessioned2025-04-20T10:23:19Z
    date available2025-04-20T10:23:19Z
    date copyright10/10/2024 12:00:00 AM
    date issued2024
    identifier otherJGGEFK.GTENG-12842.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304623
    description abstractEmbankments have been widely used in the construction of transportation and flood defense infrastructure. Embankments constructed from clays experience a suite of weather-driven deterioration processes that lead to a progressive loss of hydromechanical performance and eventually to failures whose consequences can be severe and costly. This study aimed to predict the time to failure of aging, deteriorating clay embankments supporting transportation infrastructure. A multiphase numerical modeling approach developed to simulate the long-term weather-driven hydromechanical behavior of clay embankments was used to model and simulate the behavior of a number of well-documented embankment failure case histories with known service life and available information to derive the necessary soil properties and climate records. Numerical models were developed for a total of 34 case studies, and numerical simulations were performed to predict the time to failure of the embankments due to progressive, long-term, weather-driven deterioration. Predictions compared well with actual times to failure reported for the simulated case studies. Further, geometries of modeled slides compared well with those measured for actual slides. The models offered insights into the conditions associated with failure, such as displacement patterns and pore pressure conditions. It was observed that as near-surface soil experiences cycles of wetting and drying, and accompanying cycles of swelling and shrinkage, irrecoverable swelling accumulates with time, causing swelling-induced slides. Overall, the numerical modeling approach was proven effective in producing data necessary to develop deterioration models that could improve infrastructure asset management. This study underscores the importance of understanding and predicting the long-term performance of clay embankments in civil engineering infrastructure. Through the use of long-term numerical modeling, this study could predict the time of weather-driven shallow slides in clay embankments. The ability to predict failures of embankments can offer significant improvements in infrastructure asset management. Predictive models can offer early warning to potential imminent failures, allowing for timely intervention to minimize the risk of sudden, unexpected failures, especially where consequences can be severe and costly.
    publisherAmerican Society of Civil Engineers
    titleFailure Prediction of Clay Embankments Subject to Weather-Driven Deterioration
    typeJournal Article
    journal volume150
    journal issue12
    journal titleJournal of Geotechnical and Geoenvironmental Engineering
    identifier doi10.1061/JGGEFK.GTENG-12842
    journal fristpage04024128-1
    journal lastpage04024128-23
    page23
    treeJournal of Geotechnical and Geoenvironmental Engineering:;2024:;Volume ( 150 ):;issue: 012
    contenttypeFulltext
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