• Journal of Korean Tunnelling and Underground Space Association
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• v.7 no.1
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• pp.73-88
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• 2005

Three approaches presently used for the design of underground structures in rock mass are quantitative rock mass classification system, classification systems based on the behavior of the rock mass during excavation and general qualitative procedures for the design process. In this study their characteristics and shortcomings are discussed, and Austrian guideline for tunnel design/construction, that was proposed to solve the problems with these methods, are introduced and compared. For technically sound and economic tunnel construction, a flexible design and construction procedure is needed to cope with uncertain ground and boundary condition, and also actual ground condition should be predicted through feedback of geotechnical information obtained during construction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.6
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• pp.617-635
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• 2012

In this study, correlations between the rock mass permeability before and after grouting & injection volume and the parameters of Q system were investigated on a grouted rock mass tunnel corresponding to rock class 4 and 5 in terms of Q classification system. As a result, it appears that the lower the Q value is, the higher the before-grouting permeability becomes and the smaller the injection volume of grouting becomes. Also RQD and Jn are the most influencing factors to the permeability of rock mass and the injection volume of grouting. In addition, it turned out that it was very difficult to lower the permeability of rock mass smaller than $1.0{\times}10^{-8}$ m/sec with the ordinary portland cement grout.

• Journal of the Korean Geotechnical Society
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• v.17 no.4
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• pp.127-134
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• 2001

본 논문에서는 국내 여러 지역에서 수행된 도로, 철도 및 기타 토목공사를 위한 설계과정에서 조사가 이루어진 현지조사와 시추코아 및 시추공을 대상으로 암반평가가 이루어진 자료들을 대상으로 암반분류방법간의 상관관계에 대해 조사하였다. 상관관계에 대한 해석은 암반분류에서 많이 사용되고 있는 RMR과 Q분류법간의 상관관계 그리고 RQD와 두 암반평가방법간의 관계에 대하여 암석성인별 분류 즉 화성암, 퇴적암 및 변성암별로 검토를 실시하였다. 전체적으로 분류방법의 상관관계는 좋게 나타나고 있다. 그리고 음파검층에 의한 탄성파 P파 속도와 RMR의 상관관계를 고찰하였는데, 이 두 요소간의 상관성은 비교적 양호하였으며 보다 신뢰성 있는 관계식을 유도하기 위한 노력이 필요하다.

• Tunnel and Underground Space
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• v.3 no.1
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• pp.63-79
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• 1993

The design of tunnels in rock masses often demands more informations on geologic features and rock mass properties than acquired by usual field survey and laboratory testings. In practice, the situation that a perfect set of geological and mechanical input data is given to geomechanics design engineer is rare, while the engineers are asked to achieve a high level of reliability in their design products. This study presents an artificial neural network which is developed to resolve the difficulties encountered in conventional design techniques, particulary the problem of deteriorating the confidence of existing numerical techniques such as the finite element, boundary element and distinct element methods due to the incomplete adn vague input data. The neural network has inferring capabilities to identify the possible failure modes, support requirements and its timing for underground openings, from previous case histories. Use of the neural network has resulted in a better estimate of the correlation between systems of rock mass classifications such as the RMR and Q systems. A back propagation learning algorithm together with a multi-layer network structure is adopted to enhance the inferential accuracy and efficiency of the neural network. A series of experiments comparing the results of the neural network with the actual field observations are performed to demonstrate the abilities of the artificial neural network as a new tunnel design assistance system.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.63-70
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• 2019

These days, as Interest in Image recognition with deep learning is increasing, there has been a lot of research in image recognition using deep learning. In this study, we propose a system for classifying rocks through rock images of 18 types of rock(6 types of igneous, 6 types of metamorphic, 6 types of sedimentary rock) which are addressed in the high school curriculum, using CNN model based on Tensorflow, deep learning open source framework. As a result, we developed a classifier to distinguish rocks by learning the images of rocks and confirmed the classification performance of rock classifier. Finally, through the mobile application implemented, students can use the application as a learning tool in classroom or on-site experience.

• Explosives and Blasting
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• v.35 no.4
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• pp.27-35
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• 2017

A total of 22 sites around openings of limestone mine are chosen to assess rock mass classification schemes such as RMR, Q-system, and GSI. RMR and Q are modified to estimate the relationship with GSI. Q' is the modified Q with SRF=1.0 and $J_w=1.0$. Rock mass is assumed to be completely dry and very favorable discontinuity orientations are assumed to estimate ${RMR_{89}}^{\prime}$. Relationships of Q-Basic RMR, Q-Total RMR, ${GSI-RMR_{89}}^{\prime}$, and GSI-Q' are analyzed, in which a correlation of ${GSI-RMR_{89}}^{\prime}$ is found to be the highest. Failure strains are calculated using the modulus ratios and most measuring sites appear to be stable with low failure strain class.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.3
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• pp.275-286
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• 2007

In construction of a structure in underground space, in-situ stress in rock mass has great effect on the stability of the structure. Especially, the direction and magnitude of rock stress have influence on the excavation method, the choice of support and reinforcement method for establishing the stability of tunnel. Therefore, it is very important to consider the characteristics of in-situ stress in rock mass for tunnel stability analysis. In this study, a reasonable design method for underground structure was reviewed through the case study for tunnel design considering in-situ rock stress. For this purpose, the estimation for SRF (Stress Reduction Factor) as input parameter in rock classification using Q-System and the assesment for tunnel support were studied. Also, considering the characteristics of in-situ rock stress such as the magnitude of K and the direction of principal stress, the parameter studies for tunnel stability analysis were carried out. An improved method was proposed for obtaining the better results in the tunnel stability analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.271-278
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• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital sign processing approach. From the 20 seconds query audio file, the audio signal is segmented into 23ms frame with non-overlapped hamming window and 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS(Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we can verify the superior performance of the proposed method that provides near 90% success rate for the genre classification which means 10%∼20% improvements over the previous methods. For the case of actual user system environment, feature vector is extracted from the random interval of the query audio and it shows overall 80% success rate except extreme cases of beginning and ending portion of the query audio file.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.23-37
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• 2002

Failure of the cut slope is triggered by combination of internal and extemal failure factors. Internal failure factors are related to geological and geometrical conditions of slope itself, and natural and/or artificial loadings on slope can be the external failure factors. Influences of these failure factors show different intensity according to the ground condition and are controlled by behavior characters of the slope. In this study, the soil depth ratio(SR), block size ratio(BR) and rock strength are used as the criteria to divide ground condition based on behavior characteristics. Ground condition of the slope is divided into discontinuous jointed rock mass and continuos soil-like mass, highly fractured rock mass and massive rock mass by the criteria(SR and BR). The SFi-system is a rating system to determine the slope failure index(SFi) by analyzing internal and external factors based on classification of the ground condition. The results of the SFi-system application to the real cut slopes show close relationship between the SFi value and potential or dimension of the failure. Therefore, the SFi-system can be used as a useful tool to predict and analyze the characteristic of the slope failure.

• Tunnel and Underground Space
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• v.21 no.5
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• pp.333-340
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• 2011

RMR is most strongly adopted rock classification method to scheme support system in domestic tunnel. However the RMR, which is based on geological survey during design stage of tunnel, can't present the real ground accurately. In this study, authors suggested Weighted-RMR (W-RMR) which is considered weighted value of risk factors of collapse due to prevent collapse and roof falls during tunneling. According to the application of W-RMR to Bye-Gye tunnel, we could change support type flexibly by the risk factors on a face of tunnel.