• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.543-547
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• 2003

We applied the modified invasion percolation (MIP) model to the migration of DNAPL within a two-dimensional random fracture network. The MIP model was verified against laboratory experiments, which was conducted using a two-dimensional random fracture network model. The results showed that the MIP needs modification. To remove TCE trapped in a random fracture network, the density-surfactant-motivated removal method was applied and found very effective to remove TCE from dead-end fractures.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.105-111
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• 1996

This paper suggests the scheme to simultaneously accomplish prediction of fracture initiation and geomeytical configuration of deformation in metal forming processes using the artificial neural network. A three-layer neural network is used and a back propagation algorithm is adapted to train the network. The Cookcroft-Lathjam criterion is used to estimate whether fracture occurs during the deformation process. The geometrical configuration and the value of ductile fracture are measured by finite element method. The predictions of neural network and numerical results of simple upsetting are compared. The proposed scheme has successfully predicted the geometrical configuration and fracture initiation.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.639-652
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• 2012

A three-dimensional discrete fracture network model was developed in order to simulate the hydraulic characteristics of a granitic rock mass at Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The model used a three-dimensional discrete fracture network (DFN), assuming a correlation between the length and aperture of the fractures, and a trapezoid flow path in the fractures. These assumptions that previous studies have not considered could make the developed model more practical and reasonable. The geologic and hydraulic data of the fractures were obtained in the rock mass at the KURT. Then, these data were applied to the developed fracture discrete network model. The model was applied in estimating the representative elementary volume (REV), the equivalent hydraulic conductivity tensors, and the amount of groundwater inflow into the tunnel. The developed discrete fracture network model can determine the REV size for the rock mass with respect to the hydraulic behavior and estimate the groundwater flow into the tunnel at the KURT. Therefore, the assumptions that the fracture length is correlated to the fracture aperture and the flow in a fracture occurs in a trapezoid shape appear to be effective in the DFN analysis used to estimate the hydraulic behavior of the fractured rock mass.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.129-137
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• 2000

This paper presents groundwater flow characteristics in discontinuous rock mass using fracture network program(NAPSAC) by statistical approach. Equivalent permeability coefficients are estimated from borehole data around Mabuk test tunnel site and fracture map on the arch of the tunnel. The reliability of fracture network model is obtained from determination of input data for statistical fracture network analysis from the real data(data of fracture network, data of hydraulic tests). The variation of permeability and mean anisotropic permeability coefficients are calculated from the realized model by increasing the size. As a result of analysis, a strong anisotropy of permeability is observed according to the direction of the fracture sets around the test tunnel.

• Tunnel and Underground Space
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• v.10 no.3
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• pp.378-386
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• 2000

This paper presents groundwater flow characteristics in discontinuous rock mass using fracture network program(NAPSAC) by statistical approach. Equivalent permeability coefficients are estimated from borehole data around Mabuk test tunnel site and fracture map on the arch of the tunnel. The reliability of fracture network model is obtained from determination of input data for statistical fracture network analysis from the real data(data of fracture network, data of hydraulic tests). The variation of permeability and mean anisotropic permeability coefficients are calculated from the realized model by increasing the size. As a result of analysis, a strong anisotropy of permeability is observed according to the direction of the fracture sets around the test tunnel.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.201-205
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• 1996

This paper suggests the scheme to simultaneously accomplish prediction of fracture initation and geometrical configuration of deformation in metal forming processes using the artificial neural network. A three-layer neural network is used and a back propagation algorithm is adapted to train the network. The Cockcroft-Latham criterion is used to estimate whether fracture occurs during the deformation process. The geometrical configuration and the value of ductile fracture are measured by finite element method. The prediction of network and numerical results of simple upsetting are compared. The proposed scheme has successfully predicted the geometrical configuration and fracture initiation.

• Geomechanics and Engineering
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• v.22 no.2
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• pp.133-142
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• 2020

The evolution of the mining-induced fracture network formed during longwall top coal caving (LTCC) has a great influence on the gas drainage, roof control, top coal recovery ratio and engineering safety of aquifers. To reveal the evolution of the mining-induced stress and fracture network formed during LTCC, the fracture network in front of the working face was observed by borehole video experiments. A discrete element model was established by the universal discrete element code (UDEC) to explore the local stress distribution. The regression relationship between the fractal dimension of the fracture network and mining stress was established. The results revealed the following: (1) The mining disturbance had the most severe impact on the borehole depth range between approximately 10 m and 25 m. (2) The distribution of fractures was related to the lithology and its integrity. The coal seam was mainly microfractures, which formed a complex fracture network. The hard rock stratum was mainly included longitudinal cracks and separated fissures. (3) Through a numerical simulation, the stress distribution in front of the mining face and the development of the fracturing of the overlying rock were obtained. There was a quadratic relationship between the fractal dimension of the fractures and the mining stress. The results obtained herein will provide a reference for engineering projects under similar geological conditions.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.04a
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• pp.106-109
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• 2002

In order to delineate the flow system of fractured hard rock aquifer, numerical experiments are conducted and the results are analyzed with Mote Carlo simulation. The results show that the percolation threshold and the effective conductivity of a fracture network can be estimated with power law exponent (a) and fracture intensity. But the dependability of the estimated value relies on the percolation threshold, the system scale, and the characterization level.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.43-46
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• 2003

We consider influences of the aperture variation and the ambient groundwater flow on the migration of DNAPL within a fracture network. In context of a modified invasion percolation (MIP) growth algorithm, we formulate a mechanistic model that includes capillary and gravity forces as well as viscous forces within the DNAPL and the ambient groundwater. The MIP model is verified against laboratory experiments, which is conducted using a two-dimensional random fracture network model. The results show that the aperture variation and ambient groundwater flow can be significant factors controlling DNAPL migration path within fracture networks.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2009.06a
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• pp.186-186
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• 2009

The characterization strategy of fracture networks are classified into a deterministic or statistical characterization according to the type of required information. A deterministic characterization is most efficient for a sparsely fractured system, while the statistics are sufficient for densely fractured rock. In this study, the ensemble mean and variability of the effective connectivity is systematically analyzed with various density values for different network structures of a power law size distribution. The results of high resolution Monte Carlo analyses show that statistical characteristics can be a necessary information to determine the transport properties of a fracture system when fracture density is greater than a percolation threshold. When the percolation probability (II) approaches unity with increasing fracture density, the effective connectivity of the network can be safely estimated using statistics only (sufficient condition). It is inferred from conditional simulations that deterministic information for main pathways can reduce the uncertainty in estimation of system properties when the network becomes denser. Overall results imply that most pathways need to be identified when II < 0.5 statistics are sufficient when II $\rightarrow$ 1 and statistics are necessary and the identification of main pathways can significantly reduce the uncertainty in estimation of transport properties when 0.5$\ll$1. It is suggested that the proper estimation of the percolation probability of a fracture network is a prerequisite for an appropriate conceptualization and further characterization.