Technical Papers
Oct 10, 2024

Failure Prediction of Clay Embankments Subject to Weather-Driven Deterioration

Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 150, Issue 12

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.

Practical Applications

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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Data Availability Statement

Data presented in this paper are accessible through the data set of Morsy and Helm (2024). Some or all models or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

Amr Morsy acknowledges the support of the California State University Transportation Consortium (CSUTC) through Project Nos. 2326, 2438, and 2457 funded by Senate Bill 1 (SB1) the Road Repair and Accountability Act. Peter Helm acknowledges the support of the Research Hub for Decarbonised Adaptable and Resilient Transport Infrastructures (DARe) funded by the UK Engineering and Physical Sciences Research Council (EPSRC) and the UK Department for Transport (EP/Y024257/1). The authors acknowledge the support of the Assessment, Costing and Enhancement of Long-Life, Long-Linear Assets (ACHILLES) program Grant (EP/R034575/1), funded by EPSRC, during the early stages of this work. The opinions presented in this paper are those of the authors and are not necessarily those of any of the supporting entities.

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Journal of Geotechnical and Geoenvironmental Engineering
Volume 150Issue 12December 2024

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Received: Mar 22, 2024
Accepted: Jul 19, 2024
Published online: Oct 10, 2024
Published in print: Dec 1, 2024
Discussion open until: Mar 10, 2025

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Assistant Professor, Dept. of Civil Engineering and Construction Engineering Management, California State Univ., Long Beach, CA 90840 (corresponding author). ORCID: https://orcid.org/0000-0002-9335-7847. Email: [email protected]
Research Associate, School of Engineering, Newcastle Univ., Newcastle upon Tyne NE1 7RU, UK. ORCID: https://orcid.org/0000-0001-6866-5568

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