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34 results on '"Chao, Zhiming"'

4. Physical performance of clayey soil geocomposite drainage layer interfaces subjected to environmental loadings

Author

Chao, Zhiming

Subjects
S Agriculture (General), TA Engineering (General). Civil engineering (General), TC Hydraulic engineering. Ocean engineering, TD Environmental technology. Sanitary engineering
Abstract

Geocomposite Drainage Layers (GDL) are applied in a broad range of geotechnical and geo-environmental applications, including mining facilities, embankments, landfills, etc., which can substitute traditional methods of placing layers of gravel and graded sand to drain excess water effectively and decrease pore water pressure, improving the stability of engineering projects. For the applications with GDLs installed, their stability is mainly controlled by the mechanical characteristics of GDL-cover soil interfaces. Therefore, the correct evaluation of the mechanical behaviour for GDL-cover soil interfaces is crucial. Additionally, during the service life, the GDL cover systems can experience climatic variations, such as the increase in ambient temperature, consecutive rainfall and drought, etc. to result in obviously elevated temperature, drying-wetting cycles, and thermal cycles on cover soil-GDL interfaces to affect their mechanical properties, which may impact the stability of GDL cover systems. This thesis quantifies the mechanical behaviour of cover soil-GDL interfaces subjected to environmental factors. In this thesis, a stress and temperature-controlled large direct shear apparatus was established. With use of the apparatus, the impacts of environmental factors, including drying-wetting cycles, thermal cycles, and elevated temperature, on the short-term and creep mechanical characteristics of cover clayey soil-GDL interfaces were quantified.

Published
2021

20. The Application of Machine Learning Techniques in Geotechnical Engineering: A Review and Comparison.

Author

Shao, Wei, Yue, Wenhan, Zhang, Ye, Zhou, Tianxing, Zhang, Yutong, Dang, Yabin, Wang, Haoyu, Feng, Xianhui, and Chao, Zhiming

Subjects
GEOTECHNICAL engineering, MACHINE learning, SUPPORT vector machines, ROCK deformation, SOIL classification, ARTIFICIAL neural networks
Abstract

With the development of data collection and storage capabilities in recent decades, abundant data have been accumulated in geotechnical engineering fields, providing opportunities for the usage of machine learning approaches. Thus, a rising number of scholars are adopting machine learning techniques to settle geotechnical issues. In this paper, the application of three popular machine learning algorithms, support vector machine (SVM), artificial neural network (ANN), and decision tree (DT), as well as other representative algorithms in geotechnical engineering, is reviewed. Meanwhile, the applicability of diverse machine learning algorithms in settling specific geotechnical engineering issues is compared. The main findings are as follows: ANN, SVM, and DT have been widely adopted to solve a variety of geotechnical engineering issues, such as the classification of soil and rock types, predicting the properties of geotechnical materials, etc. Based on the collected relevant research, the performance of random forest (RF) in sorting soil types and assessing landslide susceptibility is satisfying; SVM has high precision in classifying rock types and forecasting rock deformation; and backpropagation ANNs and Hopfield ANNs are recommended to forecast rock compressive strength and soil settlement, respectively. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Dependency of hydromechanical properties of monzonitic granite on confining pressure and fluid pressure under compression

Author

Weiya Xu, Qingxiang Meng, Huanling Wang, Chao Zhiming, and Zaobao Lui

Subjects
Materials science, 010504 meteorology & atmospheric sciences, Scanning electron microscope, Stress–strain curve, 0211 other engineering and technologies, Compaction, Statistical and Nonlinear Physics, Fracture mechanics, 02 engineering and technology, Condensed Matter Physics, Overburden pressure, Microstructure, 01 natural sciences, Permeability (earth sciences), Composite material, Porosity, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences
Abstract

Monzonitic granite is a low-permeability rock. Monzonitic granite formations are ideal for underground storage of oil due to their low permeability and high mechanical strength. In this study, a series of coupled hydromechanical triaxial tests are carried out using monzonitic granite specimens. The influence of confining and fluid pressures on stress, strain, and permeability is investigated. Failure characteristics under different confining and fluid pressures are discussed based on the analysis of macro fracture planes and micro scanning electron microscopy (SEM). The test results show that the change of permeability with stress and strain reflects the deformation stages of compaction, compression, crack propagation, coalesce, and failure of cracks. Due to the low porosity, the change of permeability is small in the initial phases of compaction and compression, whereas there is a significant increase in permeability when new cracks start to develop and coalesce. Confining pressures have a significant impact on the strength and permeability, particularly the crack damage stress of the rock. Compared with confining pressure, the effect of fluid pressure on rock strength and crack damage stress is small. For the monzonitic granite specimens tested, changing the confining pressure results in different failure modes, whereas the fluid pressure has a relatively small effect on the failure modes.

Published
2016

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