• Tunnel and Underground Space
• /
• v.31 no.6
• /
• pp.494-507
• /
• 2021

With the increasing use of TBM, research has recently been conducted in Korea to analyze TBM data with machine learning techniques to predict the ground in front of TBM, predict the exchange cycle of disk cutters, and predict the advance rate of TBM. In this study, classification prediction of rock characteristics of slurry shield TBM sites was made by combining traditional rock classification techniques and machine learning techniques widely used in various fields with machine data during TBM excavation. The items of rock characteristic classification criteria were set as RQD, uniaxial compression strength, and elastic wave speed, and the rock conditions for each item were classified into three classes: class 0 (good), 1 (normal), and 2 (poor), and machine learning was performed on six class algorithms. As a result, the ensemble model showed good performance, and the LigthtGBM model, which showed excellent results in learning speed as well as learning performance, was found to be optimal in the target site ground. Using the classification model for the three rock characteristics set in this study, it is believed that it will be possible to provide rock conditions for sections where ground information is not provided, which will help during excavation work.

• Economic and Environmental Geology
• /
• v.17 no.1
• /
• pp.57-78
• /
• 1984

The object of this study is to offer the standarized data for the design and calculating engineering cost of the rock excavation an the construction of the 3rd and 4th Seoul Subway lines From Jnauary to March in 1983, this study was carried out by the both methods of the field and laboratary studies. In the field, the geological survey in the entire area of Seoul City and sites on the subway lines were carried out and also a site measure of uniaxial compressional strength of rock masses by using Schmidt hammer was done. The labartory studies were carsied out by a study of preuions surveyes, microscopic studies of the mineral composition and degree of weathering of rocks, and measure of uniaxial compressional strengths Finally an engineering classification of each rock masses of South Africa council for Scientific and Industrial Research, CSIR, after Bieniawski, 1974. was done. In this method of classification 6 parameters such as strength of intact rock material, rock quality designation, spacing of fractures, condition of fractures, groundwater conditions, and the effect of fracture strike and dip orientation in tunnelling were used to evaluate rating of each rock mass.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2003.06b
• /
• pp.119-137
• /
• 2003

Electrical resistivity is one of physical property of the earth and measured by electrical resistivity survey, electrical resistivity logging and laboratory test. Recently, electrical resistivity Is widely used In determination of rock quality in road and railway tunnel design. To get more reliable rock quality data from electrical resistivity, it needs a lot of test and study on correlation of resistivity and rock quality. Firstly, we did rock property test In laboratory, such as uniaxial compressive strength(UCS), P wave velocity, Young's modulus and electrical resistivity. We correlate each test results and we found out that electrical resistivity has exponentially related to UCS and P wave velocity and linearly related to Young's modulus. And we accomplished electrical resistivity survey in field site and carried out electrical resistivity togging at In-situ area. Also we performed rock classification, such as RQD, RMR and Q-system and we correlate electrical resistivity to rock classification results. We found out that electrical resistivity logging data are highly correlate to RQD, Q and RMR. Also we found out that electrical resistivity survey data are lower than electrical resistivity logging data when there are faults or fractures. And it cause electrical resistivity survey data to lowly correlate to RQD, Q and RMR.

• Proceedings of the Korean Society for Rock Mechanics Conference
• /
• 2004.04a
• /
• pp.219-229
• /
• 2004

In this article a comprehensive review of the Rock Mass Rating and Q-rockmass classification systems is made with reference to their scope with in the constraints of underground mining operations. The modifications suggested by KIGAM for both the RMR and Q for the calculation of a safe unsupported span were tested for Daesung and Pyunghae underground limestone mines. Even though the suggested modifications were site specific, the additional parameters considered in the above classification systems are very significant for a design of stable underground openings, considering any general mining conditions.

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

• Journal of the Korean Geotechnical Society
• /
• v.21 no.3
• /
• pp.19-25
• /
• 2005

A tunnel that uses the RMR method or the Q-system is called a 'modem tunnel' because the New Austrian Tunneling Method (NATM) is not employed, even though shotcrete and rock bolts are used as support. It is known that the modem tunnel, which is supported by shotcrete, is basically different from the conventional tunnel, which is supported by steel ribs. In order to preserve the load-carrying capacity of the rock mass, loosening and excessive rock deformations must be minimized. Although it is known that this can be achieved by applying shotcrete in the case of the modem tunnel, this has not been clearly demonstrated. In order to inspect the distinctions between the conventional tunnel and the modern tunnel, their support characteristics and the rock loads of the rock mass classifications are compared. Terzaghi's rock load classification was used as the conventional tunnel's representative rock mass classification. The RMR method and the Q-system were adopted as the modem tunnel's representative rock mass classification. The study's results show that the load-carrying capacity of shotcrete, when used as the main support in the modern tunnel, is greater than the load-capacity of the steel ribs used in the conventional tunnel. Because it has been verified that the rock loads of their rock mass classifications are not different, then, according to the rock mass classifications, the load-carrying capacity of the rock mass of the modern tunnel, which uses shotcrete, is not greater than that of the conventional tunnel.

• Tunnel and Underground Space
• /
• v.21 no.6
• /
• pp.439-449
• /
• 2011

The characteristics of rock fractures for engineering rock classification are investigated by analyzing three dimensional point cloud generated from adjusted digital images of a tunnel face during construction and the tunnel is reinforced based on the supporting pattern suggested by the RMR and the Q system using parameters extracted from those images. As results, it is possible saving time required from face mapping to tunnel reinforcing work, enhancing safety during face mapping work in tunnels and reliability of both the mapping information and selecting supporting pattern by storing the files of digital images and related information which can be checked again, if necessary sometime in the future.

• Geomechanics and Engineering
• /
• v.20 no.2
• /
• pp.113-120
• /
• 2020

Rock damage is the main cause of accidents in underground engineering. It is difficult to predict rock damage accurately by using only one parameter. In this study, a rock failure prediction model was established by using stress, energy, and damage. The prediction level was divided into three levels according to the ratio of the damage threshold stress to the peak stress. A classification predicting model was established, including the stress, energy, damage and AE impact rate using Bayesian method. Results show that the model is good practicability and effectiveness in predicting the degree of rock failure. On the basis of this, a multi-parameter classification predicting deterioration model of rock failure was established. The results provide a new idea for classifying and predicting rockburst.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.5 no.3
• /
• pp.291-299
• /
• 2003

Electrical resistivity prospecting has been recently increased in the application to tunnel, landslide and other investigations in the civil engineering field. Therefore, it is essential to establish the rock mass classification technique using electrical resistivity data. In this paper, the authors, try to propose a technique which can classify tunnel rock mass using seismic wave velocities derived from electrical resistivity data. In addition, the applicability of the proposed tunnel rock mass classification technique is discussed, by comparing estimated support patterns with actually performed ones.

• Tunnel and Underground Space
• /
• v.21 no.3
• /
• pp.205-215
• /
• 2011

In this study, we analyzed physical properties of granites and their correlation with rock mass classification methods. The granite samples were obtained from field survey, in-situ borehole tests and laboratory tests for a design phase of various roads, railways and other civil engineering works in Korea. Among the measured physical properties, the results of unit weight, compressive strength, tensile strength, seismic velocity, cohesion, friction angle, elastic modulus and deformation modulus were introduced. We also correlated these properties with the compressive strength. The results of different rock classification method of RQD, RMR, and Q-system against the granites in Korea were compared with each other, and the correlation equations were proposed in a more simplified form. We also derived RMR values using the compressive strength as well as the RQD values of in-situ drilled cores, and estimated the deformation modulus of in-situ rock mass in terms of the RMR values.