• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.257-264
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• 2001

This study presents the slope stability analysis results for the model slope test. The model slope was made of the soil reinforced by FPF(Fibrillated Polyprophylene Fiber). The shear strength properties of the soil reinforced by FPF fibers were evaluated through the direct shear tests. The model slope 1:1 and 1:1.5 were made and the load tests were performed. Back analysis using limit equilibrium method was carried out to evaluate the shear strength increase on the FPF reinforced slope. The factor of safety of the FPF reinforce slope increased about 23% over unreinforced slope.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.165-175
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• 2006

To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.209-219
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• 2022

To experimentally investigate the variation of soil characteristics in slope during rainfall and the shape of slope failure, the model test was performed using soil box and artificial rainfall simulator. The model test of slope formed by the homogenous sand was performed, and the saturation pattern in the model slope due to rainfall infiltration was observed. The slope model with the inclination of 35° was set up on the slope of 30°, and the rainfall intensity of 50 mm/hr was applied in the test. The soil depth of 35 cm was selected by considering the size of soil box, and the TDR (time domain reflectometry) sensors were installed at various depths to investigate the change of soil characteristics with time. As the result of model test, the slope model during rainfall was saturated from the soil surface to the subsurface, and from the toe part to the crest part due to rainfall infiltration. That is, the toe part of slope was firstly saturated by rainfall infiltration, and then due to continuous rainfall the saturation range was enlarged from the toe part to the crest part in the slope model. The failure of slope model was started at the toe part of slope and then enlarged to the crest part, which is called as the retrogressive failure. At the end of slope failure, the collapsed area increased rapidly. Also, the mode of slope failure was rotational. Meanwhile, the slope failure was occurred when the matric suction in the slope was reached to the air entry value (AEV) estimated in soil-water characteristic curve (SWCC).

• Computers and Concrete
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• v.19 no.5
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• pp.527-535
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• 2017

In this study, an aging deformation statistical model for a unique high and steep rock slope was proposed, and the aging characteristic of the slope deformation was better reflected. The slope displacement was affected by multiple-environmental factors in multiple scales and displayed the same tendency with a rising water level. The statistical model of the high and steep rock including non-aging factors was set up based on previous analyses and the study of the deformation and residual tendency. The rule and importance of the water level factor as a non-aging unit was analyzed. A partitioned statistical model and mutation model were established for the comprehensive cumulative displacement velocity with the monitoring study under multiple factors and multiple parameters. A spatial model was also developed to reflect and predict the whole and sectional deformation character by combining aging, deformation and space coordinates. A neural network model was built to fit and predict the deformation with a high degree of precision by mastering its feature of complexity and randomness. A three-dimensional finite element model of the slope was applied to approach the structure character using numerical simulations. Further, a three-dimensional finite element model of the slope and dam was developed, and the whole deformation state was analyzed. This study is expected to provide a powerful and systematic method to analyze very high, important and dangerous slopes.

• Journal of Ocean Engineering and Technology
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• v.20 no.5 s.72
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• pp.49-56
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• 2006

In this thesis, centrifuge model experiments and numerical analyses were carried out to investigate the behavior of an excavated slope in soft clay ground. Centrifuge model tests were performed with various slopes for the excavated ground, such as 1:1.5 and 1:2. Pore pressuresthe model ground were measured to find their effects on the stability of the excavated slope. These experiments showed that the model with 1:2.5 maintained its stability within a short period of time and failed gradually. Therefore, anexcavated slope of soft soil with this slope might maintain stable conditions within a certain time. The mode1 with a 1:3 slope was observed to maintain a very stable condition, showing insignificant deformation in the ground after being excavated. Numerical analyses with PLAXIS, a commerciallyavailable software implemented with the finite element numerical technique, were performed to find the pore pressure distribution within the ground mass and the deformation of the soil. From the results of numerical analysis, a negative pore pressure was developed after the excavation and thus the stability of the slope was maintained. The safety factor for slope failure was found to decrease with time because of the dissipation of negative pore pressure with time.

• Geomechanics and Engineering
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• v.31 no.1
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• pp.15-30
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• 2022

Slope stability during the excavation of twin road tunnels is considered crucial in terms of safety. In this research, physical model testing and numerical analysis were used to investigate the characteristics of the settlement (uz) and vertical stresses (σz) along the two tunnel sections. First, two model tests for a (fill-rock) slope were conducted to study the settlement and stresses in presence and absence of slope support (plate support system). The law and value of the result were then validated by using a numerical model (FEM) based on the physical model. In addition, a finite element model with a slope supported by piles (equivalent to the plate) was used for comparison purposes. In the physical model, several rows of plates have been added to demonstrate the capacity of these plates to sustain the slope by comparing excavating twin tunnels in supported and unsupported slope, the results show that this support was effective in the upper part of the slope, while in the middle and lower part the support was limited. Additionally, the plates appear to induce less settlement in several areas of the slope with differing settlement and stress distribution as compared to piles. Furthermore, as a results of the previous mentioned investigation, there are many factors influence the stress and settlement distribution, such as the slope's cover depth, movement during excavation, buried structures such as the tunnel lining, plates or piles, and the interaction between all of these components.

• Smart Structures and Systems
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• v.7 no.4
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• pp.263-274
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• 2011

A reliability-based slope stability assessment method considering fluctuations in the monitored matric suction was proposed for real-time identification of slope risk. The assessment model was based on the limit equilibrium model for infinite slope failure. The first-order reliability method (FORM) was adopted to calculate the probability of slope failure, and results of the model were compared with Monte-Carlo Simulation (MCS) results to validate the accuracy and efficiency of the model. The analysis shows that a model based on Advanced First-Order Reliability Method (AFORM) generates results that are in relatively good agreement with those of the MCS, using a relatively small number of function calls. The contribution of random variables to the slope reliability index was also examined using sensitivity analysis. The results of sensitivity analysis indicate that the effective cohesion c' is a significant variable at low values of mean matric suction, whereas matric suction ($u_a-u_w$) is the most influential factor at high mean suction values. Finally, the reliability indices of an unsaturated model soil slope, which was monitored by a wireless matric suction measurement system, were illustrated as 2D images using the suggested probabilistic model.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.233-242
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• 2009

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in crystalline rocks like gneiss, granite, and so on, a prediction model was developed by the use of a decision tree model. The classification standard of the selected prediction model is composed of the slope angle, the coefficient of permeability and the void ratio in the order. The computer program, SHAPP ver. 1.0 for prediction of slope hazards around an important national facilities using GIS technique and the developed model. To prove the developed prediction model and the computer program, the field data surveyed from Jumunjin, Gangneung city were compared with the prediction result in the same site. As the result of comparison, the real occurrence location of slope hazards was similar to the predicted section. Through the continuous study, the accuracy about prediction result of slope hazards will be upgraded and the computer program will be commonly used in practical.

• Economic and Environmental Geology
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• v.36 no.4
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• pp.313-320
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• 2003

Slope disaster is one of the repeated occurring geological disasters in rainy season resulting in about 23 human losses in Korea every year. The slope disaster, however, mainly depends on the spatial and climate properties. such as geology, geomorphology, and heavy rainfall, and, hence, the prediction or hazard analysis of the slope disaster is a difficult task. Therefore, GIS and various statistical methods are implemented for slope disaster analysis. In particular, GIS technique is widely used for the analysis because it effectively handles large amount of spatial data. The GIS technique. however, only considers the statistics between slope disaster occurrence and related factors, not the mechanism. Accordingly. an infinite slope model that mechanically considers the balance of forces applied to the slope is suggested here with GIS for slope disaster analysis. According to the research results, the infinite slope model has a possibility that can be utilized for landslide prediction and hazard evaluation since 87.5％ of landslide occurrence areas have been predicted by this technique.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1365-1371
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model. The slope hazards data of Seoul and Kyonggi Province were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. The statistical analyses using the decision tree model were applied to the entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320m, respectively.