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 dyn...
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MDPI AG
2025-03-01
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| Series: | Journal of Marine Science and Engineering |
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| author | Liuyuan Zhao Miaojun Sun Jianhong Ye Fuqin Yang Kunpeng He |
| author_facet | Liuyuan Zhao Miaojun Sun Jianhong Ye Fuqin Yang Kunpeng He |
| author_sort | Liuyuan Zhao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a67319018bfe48e0904aebe9659e85ee |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-a67319018bfe48e0904aebe9659e85ee2025-08-20T01:48:56ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-03-0113355910.3390/jmse13030559Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–SandLiuyuan Zhao0Miaojun Sun1Jianhong Ye2Fuqin Yang3Kunpeng He4Zhejiang Huadong Geotechnical Investigation & Design Institute Corporation Limited, Hangzhou 310004, ChinaZhejiang Huadong Geotechnical Investigation & Design Institute Corporation Limited, Hangzhou 310004, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, ChinaState Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, ChinaSeabed 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.https://www.mdpi.com/2077-1312/13/3/559seabed foundation with interbedded soft clay–sandseismic dynamicsmachine learningrapid prediction of seismic subsidence |
| spellingShingle | Liuyuan Zhao Miaojun Sun Jianhong Ye Fuqin Yang Kunpeng He Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand Journal of Marine Science and Engineering seabed foundation with interbedded soft clay–sand seismic dynamics machine learning rapid prediction of seismic subsidence |
| title | Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand |
| title_full | Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand |
| title_fullStr | Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand |
| title_full_unstemmed | Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand |
| title_short | Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand |
| title_sort | characteristics and rapid prediction of seismic subsidence of saturated seabed foundation with interbedded soft clay sand |
| topic | seabed foundation with interbedded soft clay–sand seismic dynamics machine learning rapid prediction of seismic subsidence |
| url | https://www.mdpi.com/2077-1312/13/3/559 |
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