Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand

Seabed foundations consisting of interbedded layers of saturated soft clay and sand deposited during the Quaternary period are widely distributed in the coastal areas of Southeastern China. These soil foundations are prone to significant settlement under seismic loading. The study of the seismic dynamic response characteristics of saturated foundations with interbedded soft clay–sand and the development of rapid prediction models are essential for controlling settlement and ensuring the service safety of marine structures. A total of 4000 sets of seabed foundation models are randomly generated, with layers of saturated soft clay and sand and with a random distribution of layer thickness and burial depth. The mechanical behavior of saturated soft clay is described using the Soft Clay model based on the boundary surface theory, and the generalized elastoplastic constitutive model PZIII is used to characterize the mechanical behavior of sandy soil. The finite element platform FssiCAS is employed for a computational analysis to study the characteristics of seismic subsidence in saturated seabed foundations with interbedded soft clay–sand. A machine learning model is implemented based on the Random Forest algorithm, in which 3200 sets of numerical simulation results are used for model training, and 800 sets are used for validating the model’s reliability. The results show that under seismic excitation, the pore water pressure within the saturated seabed foundation with interbedded soft clay–sand accumulates, effective stress decreases, and the seabed foundation softens, to a certain extent. During the post-seismic consolidation phase, significant settlement of the seabed foundation occurs. The fast prediction model based on the Random Forest algorithm could reliably predict the settlement characteristics of submarine foundations. This research provides a new technological avenue for the rapid prediction of the seismic settlement of submarine foundations, which could be of use in engineering design, assessment, and prediction.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-03-13
DOI
https://doi.org/10.3390/jmse13030559
Citations
1
Primary Topic
Geotechnical Engineering and Soil Stabilization
Type
article
Field-Weighted Citation Impact
0.95

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article

Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand

Fan Yang, Jianhong Ye, Miaojun Sun, Liuyuan Zhao et al.
1 citations
Journal of Marine Science and Engineering
Geotechnical Engineering and Soil Stabilization
0.95
article

Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand

Fan Yang, Jianhong Ye, Miaojun Sun, Liuyuan Zhao, Kunpeng He
article en
1 citations

Abstract

Seabed foundations consisting of interbedded layers of saturated soft clay and sand deposited during the Quaternary period are widely distributed in the coastal areas of Southeastern China. These soil foundations are prone to significant settlement under seismic loading. The study of the seismic dynamic response characteristics of saturated foundations with interbedded soft clay–sand and the development of rapid prediction models are essential for controlling settlement and ensuring the service safety of marine structures. A total of 4000 sets of seabed foundation models are randomly generated, with layers of saturated soft clay and sand and with a random distribution of layer thickness and burial depth. The mechanical behavior of saturated soft clay is described using the Soft Clay model based on the boundary surface theory, and the generalized elastoplastic constitutive model PZIII is used to characterize the mechanical behavior of sandy soil. The finite element platform FssiCAS is employed for a computational analysis to study the characteristics of seismic subsidence in saturated seabed foundations with interbedded soft clay–sand. A machine learning model is implemented based on the Random Forest algorithm, in which 3200 sets of numerical simulation results are used for model training, and 800 sets are used for validating the model’s reliability. The results show that under seismic excitation, the pore water pressure within the saturated seabed foundation with interbedded soft clay–sand accumulates, effective stress decreases, and the seabed foundation softens, to a certain extent. During the post-seismic consolidation phase, significant settlement of the seabed foundation occurs. The fast prediction model based on the Random Forest algorithm could reliably predict the settlement characteristics of submarine foundations. This research provides a new technological avenue for the rapid prediction of the seismic settlement of submarine foundations, which could be of use in engineering design, assessment, and prediction.

Journal of Marine Science and EngineeringVol. 13(3)
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), PowerChina (China) (CN), Institute of Rock and Soil Mechanics (CN), Powerchina Huadong Engineering Corporation (China) (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 28%
Geotechnical Engineering and Soil Stabilization
0.95
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