• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.265-272
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• 2003

In this study, the rock mass classification results from the face mapping and the resistivity inversion data are compared and analyzed for the reliability investigation of the determination of the rock support type based on the surface electrical survey. To get the quantitative correlation, rock engineering indices such as RCR(rock condition rating), N(Rock mass number), Q-system based on RMR(rock mass rating) are calculated. Kriging method as a post processing technique for global optimization is used to improve its resolution. The result of correlation analysis shows that the geological condition estimated from 2D electrical resistivity survey is coincident globally with the trend of rock type except for a few local areas. The correlation between the results of 3D electrical resistivity survey and the rock mass classification turns out to be very high. It can be concluded that 3D electrical resistivity survey is powerful to set up the reliable rock support type.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1445-1456
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• 2003

The ASTER TIR (thermal infrared radiometer) sensor has 5 spectral bands over 8 to 12 ${\mu}$m region. Rock type classification using the ASTER TIR nighttime data was performed in the Erta Ale range of the Ethiopian Rift Valley. Erta Ale range is the most important axial volcanic chain of the Afar region. The petrographic diversity of lava erupted in this area is very important, ranging from magnesian transitional basalt to rhyolites. We tried to classify the rock types based on the spectral behavior of each volcanic rock types in thermal infrared range and estimated SiO$_{2}$ content with emission data by the ASTER TIR.

• Tunnel and Underground Space
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• v.13 no.4
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• pp.279-286
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• 2003

Many trials to set up the correlation between the rock mass classification and the earth resistivity have been carried out to design tunnel support type based on the interpreted electrical resistivity acquired by surface electrical survey. But it is hard to find reports on the comparison of the real rock support type determined during the excavation with the electrical resistivity by the inversion of the survey data acquired before the tunneling. In this study, the rock mass classification based on the face mapping data and the resistivity inversion data are investigated to see if it is possible to design reliably the rock support type based on the surface electrical survey. To get the quantitative correlation, rock engineering indices such as RCR(rock condition rating), N(Rock mass number), Q-system and RMR(rock mass rating) are calculated. Since resistivity data has low resolution, Kriging method as a post processing technique which minimizes the estimated variance is used to improve resolution. The result of correlation analysis shows that the 2D electrical resistivity survey is appropriate to see the general trend of the geology in the sense of rock type, though there might be some local area where these two factors do not coincide. But the correlation between the result of 3D survey and the rock mass classification turns out to be very high, and then 3D electrical resistivity survey can make it possible to set up more reliable rock support type.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.5 no.5
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• pp.22-29
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• 2002

This study was conducted to suggest develop revegetation methods and to classification of cutting-rock slopes revegetation type. The data was collected from pre-experienced data, reports and journal. Also research result was reflected from field research for the conditions of construction, vegetation types and field conditions. As the result of analyze, the factors affecting the plant coverage rates of cutting-rock slopes were period of construction, revegetation methods, slope gradient and slope length. Classification of cutting-rock slopes revegetation type was fourth from material of revegetation measures and spray type. It is recommended to adjust the proposed factor as environment, field condition and characteristic related with revegetation measures on slopes for the presentation of revegetation standard.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• The Journal of Engineering Geology
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• v.26 no.4
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• pp.593-600
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• 2016

To understand the mechanical properties of rock masses and intact rock in Korea, data from 4,280 in situ and laboratory tests from 107 tunnels on general national roads were analyzed. The mechanical properties (unit weight, cohesion, friction angle, modulus of deformation, Young's modulus, Poisson's ratio, uniaxial compressive strength, tensile strength, coefficient of permeability, and specific gravity) were analyzed by rock types and strength of rock in each rock type. The results of analysis, the mean specific gravity was highest in gneiss. The coefficient of permeability and Poisson's ratio show the highest mean values in granite and metamorphic rock, respectively. In addition, the unit weight, cohesion and friction angle in sedimentary rock, modulus of deformation, Young's modulus, uniaxial compressive strength and tensile strength in volcanic rock have the highest mean values. The values for each mechanical property showed wide ranges by the heterogeneity and anisotropy of rock masses in spite of detailed analysis by rock type and classification of rocks according to the strength.

• Tunnel and Underground Space
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• v.15 no.6 s.59
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• pp.425-431
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• 2005

A series of geotechnical surveys and in-situ tests were carried out to evaluate the stability of underground mine cave in an abandoned coal mine. After the closure of the mine, the underground mine drifts have been utilized for a tourist route since 1999. The dimension of the main cave is 5m width, 3m height and 230m length. The surrounding rock mass of the cave is consist of black shale, coal and limestone. Also, the main cave is intersected by two fault zone. Detailed field investigations including Rock Mass Rating(RMR), Geological Strength Index(GSI) and Q classification were performed to evaluate the stability of the main cave and to examine the necessity of reinforcement. Based on the results of rock mass classification and numerical analysis, suitable support design was recommended for the main cave. RMR and Q values of the rock masses were classified in the range of fair to good. According to the support categories proposed by Grimstad & Barton(1993), these classes fall in the reinforcement category of the Type 3 to Type 1. A Type 3 reinforcement category signifies systematic bolting and no support is necessary for the Type 1 case. From the result of numerical analysis, it was inferred that additional support on the several unstable blocks is required to ensure stability of the cave.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.610-614
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• 2005

Rock mass classification by using electrical resistivity tomography(ERT) method is widely performed for the determination of rock support type in tunnel design. In the region of high electrical noise level, however, the result of the ERT will have many erroneous features. In this study, the back ground electrical noise had been measured to find out the reason why the results of ERT in this area did not agree to the expected geology confirmed by boreholes. In order to overcome this limitation of ERT, a hybrid surface-borehole array seismic refraction tomography had been followed. Using this technique, we could get P-wave velocity section including the depth level of tunnel. The comparison of the P-wave velocity and RMR shows fairly good statistical relationship to make it possible to set up the rock mass classification for the entire tunnel line.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.655-666
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• 2013

A number of highway projects are in progress in Korea to accommodate increasing transportation demands. As the highway route becomes more complex, some projects include tunneling through unconsolidated sedimentary rock. Since an unconsolidated sedimentary rock mainly consists of rock and ground mass, the behavior and characteristics in unconsolidated sedimentary rock tunnel are quite different from typical rock tunnel. However, construction case histories and rock classifications method on unconsolidated sedimentary rock tunnel had not been developed or studied domestically. Consequently the case studies and rock classification system for unconsolidated sedimentary rock are required to better understand its behavior for tunneling. In this study, rock mass classification method is proposed to identify unconsolidated sedimentary rock based on point load and slake durability tests. Based on this, the proposed method of unconsolidated sedimentary rock can be applied well through comparisons with the results of convergence measurement.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.476-479
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• 2007

The selection of the support system is an important design parameter in design and construction of the tunnel using the new Australian tunnel method. It is a common practice to select the support based on the rock mass grade, in which the rock mass is classified into five rock groups. The method is applicable if the characteristics of the rock mass are uniform in the vertical direction. However, such case is seldom encountered in practice and not applicable when the properties vary along the vertical direction. This study performs comprehensive three dimensional finite difference analyses to investigate the ground deformation pattern for cases in which the rock mass properties change in the vertical direction of the tunnel axis. The numerically calculated displacements at the tunnel crown show that the displacement is highly dependent on the stiffness contrast of the rock masses. The results strongly indicate the need to select the support type $0.5{\sim}1.0D$(vertical direction) on the rock mass boundary. The paper proposes a new guideline for selecting the support type based the results of the analyses.