• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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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.

• 한국정밀공학회지
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• 제13권10호
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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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• 제44권6호
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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.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2000년도 암반공학문제의 수치해석(Numerical Analysis in Rock Engineering Problems)
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• pp.129-137
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• 2000

본 논문은 통계적 기법에 의한 균열망 해석 프로그램(NAPSAC)을 사용하여 암반의 수리특성을 평가하기 위해 시도되었다. 암반내 존재하는 절리의 방향성을 고려한 투수계수를 산정하기 위해 마북리 시험터널 주위의 시추자료와 막장 자료로부터 얻어진 균열에 대한 정보로부터 대상지역의 등가 투수계수를 추정하였다. 대상지역의 관찰자료(균열망에 대한 자료, 수리지질학적 자료)로부터 통계적 균열망 해석을 위한 입력자료를 결정하여 해석모델의 신뢰성을 확보하였다. 구현된 모델로부터 모델의 크기를증가함에 따라서 이방성 투수계수 및 투수계수의 변화를계산하였다. 해석결과대상지역의 투수성은 균열군의 방향성에 의해 강한 이방성을 보였다.

• 터널과지하공간
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• 제10권3호
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• pp.378-386
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• 2000

본 논문은 통계적 기법에 의한 균열망 해석 프로그램 (NAPSAC)을 사용하여 암반의 수리특성을 평가하기 위해 시도되었다. 암반내 존재하는 절리의 방향성을 고려한 투수계수를 산정하기 위해 마북리 시험터널 주위의 시추자료와 막장 자료로부터 얻어진 균열에 대한 정보로부터 대상지역의 등가 투수계수를 추정하였다. 대상지역의 관찰자료 (균열망에 대한 자료, 수리지질학적 자료 )로부터 통계적 균열망 해석을 위한 입력자료를 결정하여 해석모델의 신뢰성을 확보하였다. 구현된 모델로부터 모델의 크기를 증가함에 따라서 이방성 투수계수 및 투수계수의 변화를 계산하였다. 해석결과 대상지역의 투수성은 균열군의 방향성에 의해 강한 이방성을 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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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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• 제22권2호
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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.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2002년도 총회 및 춘계학술발표회
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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.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
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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.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2009년도 학술논문요약집
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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.