A Preliminary Study of Shear Wave in Seafloor Surface Sediments

Lu, Bo; Li, Ganxian; Huang, Shaobo

doi:10.1080/10641190600559440

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The geoacoustic properties of shallow sediments from several meters to tens of meters below the seafloor are closely related to the geological environment of the seafloor, and the relationship between their acoustic and physical properties has been a focus of research (Hou, 2016). For the research of marine acoustics, the characteristics of shear waves in seafloor sediments are of great significance for the interpretation of experimental results of marine acoustic propagation and the accurate prediction of sound fields (Lu et al, 2004). In the field of marine engineering investigation, measurements of sediment shear wave speed and shear modulus are widely used in the study of foundation-bearing capacity, sand liquefaction caused by earthquakes, and consolidation behavior (Jackson and Richardson, 2007;Guo et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

“…Richardson and Briggs (1996) studied the difference in shear wave speed between muddy and sandy sediments but did not build the corresponding empirical equations of the correlation between shear wave speed and the physical parameters of seafloor sediments. Lu et al (2004) analyzed a small number of shallow seafloor sediment samples from the Yellow Sea, East China Sea, and South China Sea and established single-parameter regression empirical equations for shear wave speed, sediment density, and liquid limit, respectively. Pan et al (2006) measured the shear wave speed of 10 seafloor sediment samples collected at seven stations located in different marine areas and established single-parameter regression equations between the shear wave speed and water content, density, porosity, plastic limit, and liquid limit, respectively.…”

Section: Introductionmentioning

confidence: 99%

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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%

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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“…Shear wave speed is one of the critical parameters of the acoustic properties of seabed sediments, which has been extensively employed in various fields. For instance, shear wave speed is an essential input parameter for the acoustic models of the seabed, which is of great significance for accurate interpretation of seabed acoustic surveying data and precise prediction of the acoustic field of oceans (Buckingham, 2005;Lu et al, 2004). Besides, shear wave speed has fundamental applications in the evaluation and prediction of stability with regard to engineering geology, as well as other applications such as bearing capacity of foundation in seabed, shear strength of marine soil, and liquefaction of sand caused by an earthquake (Jackson & Richardson, 2007;Liu & Zhang, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

Kan

Cao

Wang

et al. 2020

Earth and Space Science

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In this study, shear wave speed and related physical properties were measured for 21 seafloor sediment cores collected in the northern South China Sea. Results reveal that the shear wave speed in this study area ranges between 15.57 and 75.55 m/s and demonstrates a pattern of regional distribution. The sediment in the continental shelf area shows characteristics of high shear wave speed, high wet bulk density, low porosity, and large grain size. Contrarily, the sediment in the continental slope area exhibits characteristics of low shear wave speed, low wet bulk density, high porosity, and fine particles. Accordingly, the correlation between shear wave speed and physical properties such as porosity, wet bulk density, water content, and average grain size was studied. Prediction formulas of shear wave speed of sediments in this study area containing single and double physical parameters were established via regression analysis. The comparison between single‐parameter and double‐parameter prediction formulas indicates that the determined coefficient of the double‐parameter prediction formulas based on porosity and average grain size is higher than that of single‐parameter prediction formulas. It indicates that the double‐parameter prediction formulas based on porosity and average grain size have better prediction performance. Moreover, the prediction formulas established in this study were further compared with those of other study areas, and their differences were analyzed accordingly.

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Sea Floor Sediment and Its Acouso-Physical Properties in the Southeast Open Sea Area of Hainan Island in China

Liu

et al. 2008

Marine Georesources & Geotechnology

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A Preliminary Study of Shear Wave in Seafloor Surface Sediments

Cited by 4 publications

References 8 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

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

Sea Floor Sediment and Its Acouso-Physical Properties in the Southeast Open Sea Area of Hainan Island in China

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