Experimental Study on the Gmax Characteristics of the Sand-Silt Mixed Soil Materials Using Bender Element Testing

Bian, Jiang; Wu, Hao; Xing, Xiao; Wu, Qi; Zhenglong, Zhou

doi:10.3390/ma15186200

Cited by 4 publications

(2 citation statements)

References 38 publications

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“…The data from previous studies [26][27][28][29][30][31] were used to create a comprehensive dataset covering different types of granular soil. All the tests were performed on reconstituted specimens prepared using different SP methods.…”

Section: Dataset Collection and Processingmentioning

confidence: 99%

Machine Learning Models for Predicting Shear Wave Velocity of Soils

Mousavi,

Bayat,

Feng

2024

IOP Conf. Ser.: Earth Environ. Sci.

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As regards regions prone to seismic activity, shear wave velocity (Vs) is a design parameter for geotechnical systems exposed to dynamic loads. Evaluating Vs for geomaterials involves on-site and laboratory assessments; however, its availability is often limited in projects owing to resource and time constraints. Various mathematical and empirical models have been proposed to predict Vs for cohesive or granular soils; however, a majority of these models are specific to certain soil types and loading conditions. In this study, machine learning techniques were used for Vs prediction. These models encompass factors such as grading attributes, void ratio (e), mean effective confining pressure (σ’m), consolidation stress ratio (KC), and specimen preparation methods. To achieve this, a series of bender element tests was performed on various sand and gravel mixtures supplemented with culled data from earlier investigations. This study facilitated the development of three machine learning models aimed at predicting the Vs for granular soils: artificial neural networks (ANN), support vector regression (SVR), and gradient boosting regression (GBR), aimed at predicting Vs for granular soils. The findings of the study demonstrated that the ANN model exhibited enhanced precision and reduced error compared with the other models.

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Section: Dataset Collection and Processingmentioning

confidence: 99%

Machine Learning Models for Predicting Shear Wave Velocity of Soils

Mousavi,

Bayat,

Feng

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Generally, solidified sludge is a kind of ecological environmental material, which can be used in engineering filling, ecological slope stabilization and other areas. It has the advantages of rich resources, simple preparation, recycling and so on [ 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Study on Modification and Mechanism of Construction Waste to Solidified Silt

Yannan

Weng

et al. 2023

Materials

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A large amount of silt may be produced in river and lake regulation. It not only occupies land but also pollutes the environment. Therefore, it is urgent to seek effective disposal and utilization methods. Based on the problems of poor stability of stabilized soil and its tendency to soften easily in water, as well as its low strength with low curing agent dosage, this paper proposes a method to improve stabilized soil’s solidification effect by adding materials such as cement, lime, fly ash, triethanolamine, sodium hydroxide, sodium silicate, etc., while mixing different grain diameters and quantities of building waste materials and ordinary sand. Using construction waste and ordinary sand as a comparative test, the curing mechanism of construction waste debris on the mechanical properties, permeability, and microstructure of solidified sludge was studied through unconfined compression tests, dry and wet cycle tests, permeability tests, and micro-structure tests such as XRD, MIP, and SEM. The test results show that the strength increases 8.5%~72.1% by adding building waste materials, and it grew with the increase in particle size and amount. It reduced the content of large pore size of solidified sediment and optimized the internal pore structure. At the same time, it formed a new structure filled by rigid skeleton material. Thus, it improved its unit section stress, built up the curing effect and water stability. The findings of this study can be used to modify solidified silt to improve stability and compaction characteristics.

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