Shear Wave Speed of Shallow Seafloor Sediments in the Northern South China Sea and Their Correlations With Physical Parameters

Kan, Guangming; Cao, Guolin; Wang, Jingqiang; Li, Guanbao; Liu, Baohua; Meng, Xianwei; Meng, Qing-Hao

doi:10.1029/2019ea000950

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Lu and Liang (1991) established the dual-parameter regression equations between the shear wave speed and the dual-parameter pair of unconfined compression strength and strength sensitivity of sediments and pointed out that the dual-parameter equations have higher correlation coefficients than the single-parameter equations. Kan et al (2020) established dual-parameter regression empirical equations of shear wave speed with porosity and average grain size at different frequencies based on data from the northern part of the South China Sea, and the correlation coefficient was significantly improved compared to the single-parameter empirical equation.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Meng,

Wang

et al. 2024

Front. Mar. Sci.

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Based on data on the shear wave speed and physical properties of the shallow sediment samples collected in the northwest South China Sea, the hyperparameter selection and contribution of the characteristic factors of the machine learning model for predicting the shear wave speed of seafloor sediments were studied using the eXtreme Gradient Boosting (XGBoost) algorithm. An XGBoost model for predicting the shear wave speed of seafloor sediments was established based on four physical parameters of the sediments: porosity (n), water content (w), density (ρ), and average grain size (MZ). The result reveals that: (1) The shear wave speed has a good correlation with n, w, ρ, and MZ, and their Pearson correlation coefficients are all above 0.75, indicating that they can be used as the suitable characteristic parameters for predicting the shear wave speed based on the XGBoost model; (2) When the number of weak learners (n_estimators) is 115 and the maximum depth of the tree (max_depth) is 6, the XGBoost model has a very high goodness of fit (R2) of the validation data of 0.914, the very low mean absolute error (MAE) and mean absolute percentage error (MAPE) of the predicted shear wave speed are 3.366 m/s and 9.90%, respectively; (3) Compared with grain-shearing (GS) model and single- and dual-parameter regression equation prediction models, the XGBoost model for the shear wave speed of seafloor sediments has higher fitting goodness and lower prediction error.

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Section: Introductionmentioning

confidence: 99%

Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Meng,

Wang

et al. 2024

Front. Mar. Sci.

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“…Li et al (2005) provided a more detailed understanding of the physical and mechanical properties of submarine soils by exploring the properties of clay soils in the South Yellow Sea resource area as well as the size and characteristics of particles. On the basis of measured data on the shear wave velocity of submarine soil in the Yellow Sea, Kan et al (2014) found some correlation between soil shear wave velocity and physical and mechanical parameters. In addition, in situ testing on the mechanical properties of submarine soils has been widely carried out (Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Physical and mechanical properties and microstructures of submarine soils in the Yellow Sea

Tian,

Chang,

Chen

et al. 2023

Deep Underground Science and Engineering

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In recent years, the exploration of seabed has been intensified, but the submarine soils of silt and sand in the Yellow Sea area have not been well investigated so far. In this study, the physical and mechanical properties of silt and sand from the Yellow Sea were measured using a direct shear apparatus and their microstructures were observed using a scanning electron microscope. The test results suggest that the shear strength of silt and sand increases linearly with the increase of normal stress. Based on the direct shear test, the scanning electron microscope was used to observe the section surface of sand. It is observed that the section surface becomes rough, with many “V”‐shaped cracks. Many particles appear on the surface of the silt structure and tend to be disintegrated. The X‐ray diffraction experiment reveals that the sand and silt have different compositions. The shear strength of sand is slightly greater than that of silt under high stress, which is related to the shape of soil particles and the mineral composition. These results can be a reference for further study of other soils in the Yellow Sea; meanwhile, they can serve as soil parameters for the stability and durability analyses of offshore infrastructure construction.

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Correlation between acoustic velocity and physical parameters of sea floor sediments: a case study of the northern South China Sea

Zhang,

Xing,

Zhou

et al. 2024

Front. Mar. Sci.

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As the interface between seawater and the seabed, superficial sediments on the seabed are an important part of the marine acoustic field environment and are indispensable for marine resource investigations. Studying sediments several meters to hundreds of meters below the seafloor is highly valuable and important. This study processes and analyses the water depth, topography and bottom data and obtains the shallow bottom profile and topographic map of the northern continental slope of the South China Sea (SCS). The study analyzes the influence of physical parameter (including density, porosity, and grain size) on the acoustic velocity in sediments. Single-parameter and dual-parameter models are established to further examine this influence. The results show that porosity and density have greater influences on the acoustic velocity of sediments than does grain size. Finally, the acoustic properties of several typical stations with water depths are tested to analyze the variations in the acoustic properties of the shallow sediments in the northern SCS. The results show that the influence of each parameter on the prediction of the acoustic velocity of the sediment is in the following order: porosity>density>grain size. This study analyses and reveals the reason why the seafloor sediments in the local area cause the acoustic properties to change greatly. It may be caused by changes in the sediment type, lithology along with the depth. And the other reason is the development of interlayer in the land slope of the northern SCS.

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Shear Wave Speed of Shallow Seafloor Sediments in the Northern South China Sea and Their Correlations With Physical Parameters

Cited by 3 publications

References 6 publications

Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Physical and mechanical properties and microstructures of submarine soils in the Yellow Sea

Correlation between acoustic velocity and physical parameters of sea floor sediments: a case study of the northern South China Sea

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