• Tunnel and Underground Space
• /
• v.11 no.2
• /
• pp.156-166
• /
• 2001

A stochastic continuum(SC) modeling technique was developed to simulate the groundwater flow pathway in fractured rocks. This model was developed to overcome the disadvantageous points of discrete fracture network(DFN) modes which has the limitation of fracture numbers. Besides, SC model is able to perform probabilistic analysis and to simulate the conductive groundwater pathway as discrete fracture network model. The SC model was formulated based on the discrete fracture network(DFN) model. The spatial distribution of permeability in the stochastic continuum model was defined by the probability distribution and variogram functions defined from the permeabilities of subdivided smaller blocks of the DFN model. The analysis of groundwater travel time was performed to show the consistency between DFN and SC models by the numerical experiment. It was found that the stochastic continuum modes was an appropriate way to provide the probability density distribution of groundwater velocity which is required for the probabilistic safety assessment of a radioactive waste disposal facility.

• Proceedings of the KSEEG Conference
• /
• 2002.04a
• /
• pp.258-261
• /
• 2002

• Proceedings of the KSEEG Conference
• /
• 1999.04a
• /
• pp.251-253
• /
• 1999

• Journal of Aerospace System Engineering
• /
• v.17 no.4
• /
• pp.28-33
• /
• 2023

In this study, computational fluid dynamics was used to analyze the flow bias generated as air supplied by a fan passes through ducts, piping, and a coal separation screen. The flow bias of the air flow is mostly caused by the spatial characteristics of the fan volute and duct, and the internal baffle and the coal separation screen at the outlet cause strong pressure losses that dampen the flow bias. ANSYS CFX was used for computational fluid dynamics, and since the baffle and the coal separation screen are shaped like perforated plates with many small holes uniformly distributed, actual modeling for analysis was not possible. Therefore, the Porous Loss Model was applied. The evaluation of the flow bias was analyzed based on the velocity distribution of the Porous Loss Model at the outlet surface of the coal separation screen obtained from the computational fluid dynamics results.

• Journal of the Economic Geographical Society of Korea
• /
• v.12 no.4
• /
• pp.540-556
• /
• 2009

The hub and spoke network is a critical network-based infrastructure that is widely applied in current transportation and telecommunications systems, including Internets, air transportation networks and highway systems. This main idea of hub location models is to construct a network system which achieves the economy of scale of flows. The main purpose of this study is to introduce new hub location problems that take into account network reliability. Two standard models based on assignment schemes are proposed, and a minimum threshold model is provided as an extension in terms of hub network design. The reliability and interaction potentials of 15 nodes in the U.S. are used to examine model behaviors. According to the type of models and reliability, hubs, and minimum threshold levels, relationships among the flow economy of scale, network costs, and network resiliency are analyzed.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.7
• /
• pp.65-76
• /
• 2007

Recently, there have been many construction projects on soft ground with growth of industry and various construction problems concerning soft soil behavior also have been reported. Especially, foundation piles of abutments and (or) buildings which were constructed on the soft ground have been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches for this phenomena have been carried out, it is still difficult to assess the mechanism of lateral flow on soft ground quantitatively. And reliable design method for judgement of lateral flow occurrence is not established yet. In this study, PNN (probabilistic neural network) and CNN (committee neural network) theories were applied for judgment of lateral flow occurrence based on eat data compiled from Korea and Japan. Predictions of PNN and CNN models for new data which were not used during model development are compared with those predicted by conventional empirical methods. It was found that the developed PNN and CNN models can predict more precise and reliable judgment of lateral flow occurrence than conventional empirical methods.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.458-461
• /
• 2021

유동인구 예측은 상권의 특성에 따른 점포의 입지 선정 및 고객 맞춤형 마케팅 등 민간 분야에서부터 교통망 등 사회 간접 자본 설계를 위한 공공 분야에 이르기까지 다양한 목적으로 연구되어 왔으며, 최근에는 Covid-19 의 확산에 따라 그 중요도가 더욱 높아지고 있다. 보다 정교한 예측을 위해서는 전체적인 유동 인구 뿐만 아니라 특성 별로 세분화된 하위 그룹에 대해서도 정확한 예측이 요구되나, 기존의 예측 모델들은 이러한 데이터의 계층 구조를 고려하지 않았다. 본 연구에서는 세분화된 하위 그룹 별 유동인구의 예측 정확도를 높이기 위해 전체 유동인구의 패턴을 동시에 활용하는 Global-Local 구조 기반의 Deep Learning 유동인구 분석 모델을 제안한다. 실험 결과 단일 시계열 데이터만을 사용하는 경우 대비 5.4%~52.6%의 예측 오류 감소 효과가 있음을 확인하였다.

• 한국가스학회:학술대회논문집
• /
• 1997.09a
• /
• pp.284-291
• /
• 1997

배관망의 해석은 유체역학을 필요로 하며 관내의 유체의 거동과 운전 상태에 따른 유동해석을 위해 여러 식들이 사용되어왔다. 본 연구에서는 정상상태의 유량방정식을 사용해 경인지역가스 배관망에 대한 수학적 모델을 만들고 모사 및 분석을 수행하였다. 개발된 수학적 모델에서 얻어진 데이터에 통계학적인 방법을 도입해 통계학적 모델을 만듦으로써 통계학적 모델을 이용한 배관망 해석의 가능성에 대해 검토하였다.

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2005.06a
• /
• pp.231-238
• /
• 2005

On the basis of flow resistance theory the conceptual model and related mathematical descriptions is proposed for resistance modeling of groundwater flow in CPM(continuum Porous medium), DFN(discrete fracture network) and fractured-porous medium. The proposed model is developed on the basis of finite volume method assuming steady-state, constant density groundwater flow. The basic approach of the method is to evaluate inter-block flow resistance values for a staggered grid arrangement, i.e. fluxes are stored at cell walls and scalars at cell centers. The balance of forces, i.e. the Darcy law, is utilized for each control volume centered around the point where the velocity component is stored. The transmissivity (or permeability) at the interface is assumed to be the harmonic average of neighboring blocks. Flow resistance theory was utilized to relate the fluxes between the grid blocks with residual pressures. The flow within porous medium is described by three dimensional equations and that within an individual fracture is described by a two dimensional equivalent of the flow equations for a porous medium. Newly proposed models would contribute to develop flow simulation techniques with various matrix characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1C
• /
• pp.1-8
• /
• 2008

Recently, there have been many construction projects on soft ground with growth of industry and economy. Therefore foundation piles of abutments and(or) buildings had been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches about lateral flow have been carried out, it is still difficult to assess the mechanism of lateral flow in soft ground quantitatively. And reasonable design method for judgement of lateral flow occurrence in soft ground is not established yet. In this study, six PNN (Probabilistic Neural Network) models were developed according to input variables and database compiled from Korea and Japan for the judgment of lateral flow occurrence. PNN models were compared with present empirical methods. It was found that the developed PNN models can give more precise and reliable judgment of lateral flow occurrence than empirical methods.