• Tunnel and Underground Space
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• v.22 no.2
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• pp.77-85
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• 2012

In a material, micro-cracks can be progressively occurred, propagated and finally lead to failure when it is subjected to cyclic or periodic loading less than its ultimate strength. This phenomenon, fatigue, is usually considered in a metal, alloy and structures under repeated loading conditions. In underground structures, a static creep behavior rather than a dynamic fatigue behavior is mostly considered. However, when compressed air is stored in a rock cavern, an inner pressure is periodically changed due to repeated in- and-out process of compressed air. Therefore mechanical properties of surrounding rock mass and an inner lining system under cyclic loading/unloading conditions should be investigated. In this study, considering an underground lined rock cavern for compressed air energy storage (CAES), the mechanical properties of a lining system, that is, concrete lining and plug under periodic loading/unloading conditions were characterized through cyclic bending tests and shear tests. From these tests, the stability of the plug was evaluated and the S-N line of the concrete lining was obtained.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.1
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• pp.25-36
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• 2008

When constructing subsea underground structures, the influence of high water and seepage pressure acting on the structures can not be neglected. Thus hydro-mechanical coupled analysis should be performed to estimate the behavior of the structures precisely In practice, relaxed rock load is generally used for the design of tunnel concrete lining. A method based on the distribution of local safety factor around a tunnel was proposed for the estimation of a height of relaxed rock mass ($H_{relaxed}$). In this study, the validation of the suggested method is investigated in the framework of hydro-mechanical coupled analyses. It was suggested that inducing inflow by pumping through a drainage well gave more reliable results than inducing inflow with shotcrete hydraulic characteristics in case of rock condition of Class III. In this study, therefore, inducing inflow by pumping through a drainage well are adopted in estimating $H_{relaxed}$ due to a tunnel excavation with the rock condition of Class I, III, and V. Also the estimated $H_{relaxed}$ results are compared with those of the existing suggested methods. As the result of this study, it is confirmed that estimating $H_{relaxed}$ based on the distribution of local safety factor around a tunnel can be effectively used even for the case of hydro-mechanical coupled analysis. It is also found that inducing inflow pumping through a drainage well gives more precise and consistent Hrelaxed of a subsea structure.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2009.04a
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• pp.487-492
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• 2009

This study was performed FE numerical analysis under 120-minute fire conditions, using the ABAQUS, a wide use software, on the basis of the test results by concrete tunnel lining fire strengths (ISO, RWS, and MHC). The concrete material test was to secure the material properties of concrete linings, which were numerical analysis input conditions. And then built the material properties, such as specific heat, heat transfer rate, heat expansion rate, density, elasticity coefficient and compression strength under high temperature conditions, as database at 20 $^{\circ}C$ to 800 $^{\circ}C$, applying them to analysis as input values. As a result, the tunnel linings under RWS fire conditions saw fire temperature rose to maximum 1119 $^{\circ}C$at the location of 5 mm above a thermal surface, and saw surface temperature amount to 1214 $^{\circ}C$ in the middle part.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.513-524
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• 2022

Recently, detecting damages of civil infrastructures from digital images using deep learning technology became a very popular research topic. In order to adapt those methodologies to the field, it is essential to explain robustness of deep learning models. Our research points out that the existing pixel-based deep learning model evaluation metrics are not sufficient for detecting cracks since cracks have linear appearance, and proposes a new evaluation methodology to explain crack segmentation deep learning model more rationally. Specifically, we design, implement and validate a methodology to generate tolerance buffer alongside skeletonized ground truth data and prediction results to consider overall similarity of topology of the ground truth and the prediction rather than pixel-wise accuracy. We could overcome over-estimation or under-estimation problem of crack segmentation model evaluation through using our methodology, and we expect that our methodology can explain crack segmentation deep learning models better.

• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.879-884
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• 2005

The setting time is a very important factor affecting the quality of tunnel lining and reinforcement of inclined slope etc. Currently, however, the quality criteria of accelerating admixture to improve it is not established well. In this study, evaluation on setting time measuring methods of cement mixed a accelerating admixture (AA) was performed using Gillmore and Vicat needle test methods. For both test methods, the setting time for addition at a time was better than post addition regardless of initial setting and final setting. For Gillmore needle test method, two types of measuring methods were selected and it is noted that setting time with cement type under the same accelerating admixture can be different. Accordingly, manufacturing company shall develop a less sensitive accelerating admixture to cement type. For Vicat needle test method, six types of measuring methods were used and a proper measuring method of the admixture were proposed as follows: (1) the temperature of materials used shall be controlled exactly and (2) to evaluate its properties, an admixture usage of $5\%$ (ratio of cement weight) is recommended.

• Journal of the Korean Geotechnical Society
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• v.15 no.3
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• pp.161-176
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• 1999

A powerful numerical method that can be used for modeling rock-structure interaction is the Discontinuous Deformation Analysis (D D A) method developed by Shi in 1988. In this method, rock masses are treated as systems of finite and deformable blocks. Large rock mass deformations and block movements are allowed. Although various extensions of the D D A method have been proposed in the literature, the method is not capable of modeling water-block interaction, sequential loading or unloading and rock reinforcement; three features that are needed when modeling surface or underground excavation in fractured rock. This paper presents three new extensions to the D D A method. The extensions consist of hydro-mechanical coupling between rock blocks and steady water flow in fractures, sequential loading or unloading, and rock reinforcement by rockbolts, shotcrete or concrete lining. Examples of application of the D D A method with the new extensions are presented. Simulations of the underground excavation of the \ulcornerUnju Tunnel\ulcorner in Korea were carried out to evaluate the influence of fracture flow, excavation sequence and reinforcement on the tunnel stability. The results of the present study indicate that fracture flow and improper selection of excavation sequence could have a destabilizing effect on the tunnel stability. On the other hand, reinforcement by rockbolts and shotcrete can stabilize the tunnel. It is found that, in general, the D D A program with the three new extensions can now be used as a practical tool in the design of underground structures. In particular, phases of construction (excavation, reinforcement) can now be simulated more realistically.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.283-299
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• 2017

The leakage of tunnel causes the long-term durability of the structures such as concrete lining to deteriorate. The cause of durability degradation can be various substances contained in groundwater such as chloride, sulphate, water, and gas. In this study, a series of test were carried out to determine the watertightness performance and the resistance to salt water of the spray-applied membrane used as non-structural rock support or as a waterproof material for tunnels. As a result, it was found that the penetration of water could occur in a specimen, and the reason was that the internal pores generated by the mixing of the liquid polymer and the powder material and the internal pores were connected by the water pressure. The tensile strength of the test specimens immersed in distilled water and saline water was found to be reduced to less than half of the tensile strength in normal condition. In addition, The elongation was measured to be higher in distilled water than in salt water. However, this result will require further investigation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.174-179
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• 1999

Shear wave velocity, one of major elastic constants in the dynamic design for civil structures, is conventionally measured from downhole, crosshole or sonic logging tests. SASW (Spectral Analysis of Surface Waves) method, which overcomes the disadvantage of the in-hole tests, can evaluate subsurface stiffness nondestructively and nonintrusively through measuring surface waves on surface. In this paper, principles of the SASW method are briefly described and the results of various field tests, conducted to investigate the applicability of the method, are summarized. The SASW method was successfully applied in evaluating the effects of dynamic compaction at Inchon international airport site, applied in evaluating the integrity of the lining and sidewall at a testing tunnel located in Mabukri, and applied in detecting thickness of a concrete retaining wall. The results of field tests and the nondestructive and economical characteristics of the method show the promising future of the SASW method in civil engineering projects.