This study proposes an approach that considers mitigation strategies in predicting landslide susceptibility through machine learning (ML) and geographic information system (GIS) techniques. ML models, such as random forest (RF), logistic regression (LR), and support vector classification (SVC) are incorporated into GIS to predict landslide susceptibilities in Hong Kong. To consider the effect of mitigation strategies on landslide susceptibility, non-landslide samples were produced in the upgraded area and added to randomly created samples to serve as ML models in training datasets. Two scenarios were created to compare and demonstrate the efficiency of the proposed approach; Scenario I does not considering landslide control while Scenario II considers mitigation strategies for landslide control. The largest landslide susceptibilities are 0.967 (from RF), followed by 0.936 (from LR) and 0.902 (from SVC) in Scenario II; in Scenario I, they are 0.986 (from RF), 0.955 (from LR) and 0.947 (from SVC). This proves that the ML models considering mitigation strategies can decrease the current landslide susceptibilities. The comparison between the different ML models shows that RF performed better than LR and SVC, and provides the best prediction of the spatial distribution of landslide susceptibilities.
Summary This paper presents the development of a three‐dimensional discrete element model using flat‐joint and smooth‐joint contact models to investigate the effect of anisotropy on the tensile behaviour of slate, a transversely isotropic rock, under Brazilian testing from both macro and microscales. The effect of anisotropy is further realised by exploring the influence of foliation orientations ( β and ψ ) on the tensile strength, fracture pattern, microcracking and stress distribution of the transversely isotropic rock. The variation of tensile strength with foliation orientation is presented. The cross‐weak‐plane fracture growth observed in laboratory is reproduced, and the criterion for which to form is also given from the aspect of foliation orientation. Furthermore, the proportional variations of microcracks well account for the effects of foliation orientation on the tensile strength and failure pattern. Finally, it is found that the existence of weak planes increases both the heterogeneity and the anisotropy of stress distributions within the transversely isotropic rock, with the degree of influence varying with the foliation orientation.
This paper attempts to formulate a coupled practical model in the framework of continuum mechanics to evaluate the phenomenon of internal erosion and its consequences on the mechanical behavior of soils. For this purpose, a four-constituent numerical approach has been developed to describe the internal erosion process. The detachment and transport of the fine particles have been described by a mass exchange formulation between the solid and fluid phases. The stress–strain relationship of the soil is represented by a nonlinear incremental model. Based on experimental data, this constitutive model has been enhanced by the introduction of a fines content–dependent critical state, which allows accounting for the influence of fines on soil deformation and strength. The applicability of the practical approach to capture the main features of the internal erosion process and its impact on the mechanical behavior of the eroded soil have been validated by comparing numerical and experimental results of internal erosion tests on Hong Kong completely decomposed granite (HK-CDG) mixtures, which demonstrated that the practical model was able to reproduce, with reasonable success, the experimental data. Furthermore, the influence of the stress state, the initial soil density, and the initial fraction of fines have been analyzed through numerical simulations using the proposed model.
This paper presents a numerical investigation into the leakage behavior of cut-off walls in gravel strata due to dewatering in a deep excavation pit. The calculated values of the groundwater head and surface settlement using a model agree well with the measured values. Values of the hydraulic conductivity (k) and storage coefficient (S s ) of each soil layer are obtained from the test results when the cut-off wall is 43 m deep. The leakage through the cut-off wall in gravel is analyzed by considering a variation in hydraulic conductivity in different sections of the cut-off wall. The simulated results show that a significant leakage occurred in the 54 m deep cut-off wall. Although leakage did occur in the full cut-off wall in the confined aquifer, the full cut-off wall is still more efficient in preventing groundwater seepage than the partial cut-off wall. The relative depths of the cut-off wall and of the wells have a significant effect on ground surface settlement during the withdrawal of groundwater. Therefore, the appropriate selection of relative depth of both cut-off wall and pumping well is an effective way of controlling surface settlement outside the pit.
In this study, a novel, interdisciplinary method is introduced that merges fundamental geomechanics with computer vision to develop an advanced hybrid feature-aided digital volume correlation (DVC) technique. This technique is specifically engineered to measure and compute the full-field strain distribution in fine-grained soil mixtures. A clay–sand mixture specimen composed of quartz sand particles and kaolinite was created. Its mechanical properties and deformation behaviour were then tested using a mini-triaxial apparatus, combined with micro-focus X-ray computed tomography (μCT). The CT slices underwent image processing for denoising, segmentation of distinct phases, reconstruction of sand particles and feature extraction within the soil specimen. The proposed approach incorporated a two-step particle tracking method, which initially uses particle volume and surface area features to establish a preliminary matching list for a reference particle and then use the iterative closest point method for precise target particle matching. The soil specimen's initial displacement field was then mapped onto the DVC method's grid, and further refined through sub-voxel registration by way of a three-dimensional inverse compositional Gauss–Newton algorithm. The proposed method's effectiveness and efficiency were validated by accurately calculating the displacement and strain fields of the soil mixture sample, and comparing the results with those from a traditional DVC method. Given the soil's compositional and microstructural characteristics, these image-matching techniques can be integrated to create a versatile, efficient, and robust DVC system, suitable for a variety of soil mixture types.
This study presents an experimental investigation of the effect of sand particle size on the shear behaviour of bio-cemented sand-steel structure interface, with sand treated by microbially induced calcite precipitation (MICP). Five sand groups were involved with different median particle sizes. The MICP treatment followed the surface percolation method featuring bacterial suspensions with a fixed optical density (linearly related to active cell concentration or urease activity). Scanning electron microscopy was used to identify the microstructure of the samples, while interface shear test was performed to observe the macroscale mechanical behaviour. The testing results indicated that smaller sand particle size was associated with a relatively larger effective calcium carbonate bonding area, providing a more significant bonding effect. Thus, smaller sand particle sizes in the treated samples were associated with higher values for the interface cohesion and a more pronounced increase in the interface friction angle at the peak state (compared to the corresponding untreated samples). By contrast, because the bonding effect broke close to the interface during shearing, the bottom of the treated samples became planar and smooth. Hence, a lower interface friction angle at the ultimate state was identified for a treated sample, compared to the corresponding untreated one.
Two recently proposed anisotropic rate-dependent models are used to simulate the consolidation behavior of two soft natural clays: Murro clay and Haarajoki clay. The rate-dependent constitutive models include the EVP-SCLAY1 model and the anisotropic creep model (ACM). The two models are identical in the way the initial anisotropy and the evolution of anisotropy are simulated, but differ in the way the rate effects are taken into consideration. The models are compared first at the element level against laboratory data and then at the boundary value level against measured field data from instrumented embankments on Murro and Haarajoki clays. The numerical simulations suggest that at the element level, the EVP-SCLAY1 model is able to give a better representation of the clay response under oedometric loading than ACM, when the input parameters are defined objectively. However, at the boundary value level, the issue is not as straightforward, and the appropriateness of the constitutive model may depend heavily on the in situ overconsolidation ratio (OCR).
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