• Tunnel and Underground Space
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• v.29 no.1
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• pp.30-37
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• 2019

Some leading countries in mining have a very quantitative guideline for underground mine opening design which is useful to minimize mine hazards such as rockfall and collapse. Those hazards sometimes can cause a huge damage on human life and property in the mines. Construction guidelines of underground mines in Korea consist of qualitative and general expressions although the workers' safety rules and guides are well provided. Recently, mining operations in Korea are going underground due to the environmental regulations and resource depletion at shallow depth, and therefore there is a growing demand on a specialized and systematic guideline for mine opening design securing the underground stability. In this paper, current status of mining industry, research trends, and mining guidelines in Korea and overseas have been reviewed to give an insight into developing a new Korean guideline for underground mine design.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.107-121
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• 2022

Coal pillar assessment is of broad importance to underground engineering structure, as the pillar failure can lead to enormous disasters. Because of the highly non-linear correlation between the pillar failure and its influential attributes, conventional forecasting techniques cannot generate accurate outcomes. To approximate the complex behavior of coal pillar, this paper elucidates a new idea to forecast the underground coal pillar stability using combined unsupervised-supervised learning. In order to build a database of the study, a total of 90 patterns of pillar cases were collected from authentic engineering structures. A state-of-the art feature depletion method, t-distribution symmetric neighbor embedding (t-SNE) has been employed to reduce significance of actual data features. Consequently, an unsupervised machine learning technique K-mean clustering was followed to reassign the t-SNE dimensionality reduced data in order to compute the relative class of coal pillar cases. Following that, the reassign dataset was divided into two parts: 70 percent for training dataset and 30 percent for testing dataset, respectively. The accuracy of the predicted data was then examined using support vector classifier (SVC) model performance measures such as precision, recall, and f₁-score. As a result, the proposed model can be employed for properly predicting the pillar failure class in a variety of underground rock engineering projects.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.2
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• pp.167-174
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• 2002

In this study, a numerical stability analysis was performed for a large tunnel considering excavation sequence. In most cases, stability of a tunnel is analyzed based on the stability of the final excavation stage only. In this study, stability analysis of a tunnel was performed at each excavation stage. In summary, it can be inferred that there is no problem in stability of the tunnel. However, thorough and careful measurements are recommended. Also, it is found that the stability of the tunnel at the 5th excavation stage when the right half of the main tunnel is excavated is rather lower than that of the tunnel at the final excavation stage.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.417-426
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• 2024

Shield tunneling method is widely used to build tunnels in complex geological environment. Stability control of tunnel face is the key to the safety of projects. To improve the excavation efficiency or perform equipment maintenance, the excavation chamber sometimes is not fully filled with support medium, which can reduce the load and increase tunneling speed while easily lead to ground collapse. Due to the high risk of the face failure under non-fully support mode, the tunnel face stability should be carefully evaluated. Whether compressive air is required for compensation and how much air pressure should be provided need to be determined accurately. Based on the upper bound theorem of limit analysis, a non-fully support rotational failure model is developed in this study. The failure mechanism of the model is verified by numerical simulation. It shows that increasing the density of supporting medium could significantly improve the stability of tunnel face while the increase of tunnel diameter would be unfavorable for the face stability. The critical support ratio is used to evaluate the face failure under the nonfully support mode, which could be an important index to determine whether the specific unsupported height could be allowed during shield tunneling. To avoid of face failure under the non-fully support mode, several charts are provided for the assessment of compressed air pressure, which could help engineers to determine the required air pressure for face stability.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.5
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• pp.487-495
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• 2014

In this study, in order to suggest the design method for supports in the room-and-pillar underground structure, the case study was carried out. In the case study, shape of rock pillar and room was mainly considered. From the analysis, a displacement at the roof, the maximum principle stress and plastic state were examined. To optimize variables in the case study, cases from the Seoul metro station were analyzed, then a target depth of the underground structure and ground conditions were determined. And the height of rock pillar and room were chosen from the assumed purpose of underground space, i.e. living/office and warehouse. Total cases of analysis was 180 cases including 3 types of ground condition, 5 types of rock pillar and 6 types of roof span. It is expected that results from analysis can be used to determine the installation of support in room-and-pillar underground structure with stability, utilization efficiency of underground space and applicability of vehicles.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.5
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• pp.389-397
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• 2010

This paper presents the effects of the tunnel stability using rebar steel pipe which is the steel pipe reinforced by rebar. In order to carry out this research, not only the theoretical and experimental study for bending stiffness of normal steel pipes and rebar steel pipes but also numerical analysis of tunnel stability are performed. It is clearly found from the results that 65% of bending stiffness of the rebar steel pipe is larger than that of the normal steel pipe. The results obtained from the numerical analysis of tunnel stability show that about 10% of tunnel stability is increased in case of the rebar steel pipe. The rebar steel pipe, therefore, may be very useful to develope the tunnel stability economically.

• Explosives and Blasting
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• v.38 no.4
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• pp.1-15
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• 2020

With the increase of the utilization of underground space in Korea, explosion accidents at the underground facilities such as gas pipes have occurred frequently. In urban area with high population density, individual explosion accidents are likely to spread into large complex accidents. It is necessary to investigate the effect of explosion on the stability of underground structures in urban area. In this study, a sensitivity analysis was carried out to investigate the possible influence of nearby explosion on the stability of underground structure with 8 parameters including explosion conditions and rock properties. From the sensitivity analysis using AUTODYN, the main and interaction effects of each parameters could be determined. From the analysis, it was found that the distance between explosion point and tunnel, charge weight, and Young's modulus are the most important parameters on the stress components around a tunnel.

• Tunnel and Underground Space
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• v.8 no.4
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• pp.351-358
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• 1998

A statistical method for assessing the joint persistence based on the in-situ measurement of joint trace length has been derived. This method utilizes the probability density distribution of either the joint trace length or the diameter of hypothetically circular joint diameter depending on the relative size of joint surface to that of the potential keyblock. The stability of potential keyblock with different sizes and joint persistences has been also calculated to illustrate the applicability of the developed method to the design and the safe excavation of large scale underground openings.

• Economic and Environmental Geology
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• v.48 no.2
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• pp.131-145
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• 2015

Thermodynamic prediction of weathering products from primary aquifer minerals around underground disposal sites was investigated. The distribution of solubility quotients for kaolinite-smectite reactions showed the trend of reaching at equilibrium with Ca-, Mg-, and Na-smectite for deep groundwaters in granitic aquifers. The values of $10^{-14.56}$, $10^{-15.73}$, and $10^{-7.76}$ were proposed as equilibrium constants between kaolinite and Ca-, Mg-, and Na-smectite end members, respectively. On stability diagrams, most of deep groundwaters were located at equilibrium boundaries between stability fields of kaolinite and smectites or on stability fields of smectites and illite. Shallow groundwaters in basic rock aquifer were plotted at the same stability areas of deep granitic groundwaters on stability diagrams. The results indicated that the primiary mineralogical composition may be important to predict weathering products in deep aquifers.