• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 12th Asian Congress of Fluid Mechanics
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• pp.67.1-67.1
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• 2008

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 12th Asian Congress of Fluid Mechanics
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• pp.34.3-34.3
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• 2008

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2010년 춘계학술대회논문집
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• pp.517-523
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• 2010

Recently, the rapid evolution of computational fluid dynamics (CFD) has enabled its key role in industries and predictive sciences. From diverse research disciplines, however, are there strong needs for integrated analytical tools for multi-phenomena beyond simple flow simulation. Based on the concurrent simulation of multi-dynamics, multi-phenomena beyond simple flow simulation. Based on the concurrent simulation of multi-dynamics, multi-physics and multi-scale phenomena, the multi-phenomena CFD technology enables us to perform the flow simulation for integrated and complex systems. From the multi-phenomena CFD analysis, the high-precision analytical and predictive capacity can enhance the fast development of industrial technologies. It is also expected to further enhance the applicability of the simulation technique to medical and bio technology, new and renewable energy, nanotechnology, and scientific computing, among others.

• 반도체디스플레이기술학회지
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• 제22권1호
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• pp.134-138
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• 2023

This study focuses on the analysis of the results of computational fluid dynamics simulations of mist-chemical vapor deposition for the growth of an epitaxial wafer in power semiconductor technology using artificial intelligence techniques. The conventional approach of predicting the uniformity of the deposited layer using computational fluid dynamics and design of experimental takes considerable time. To overcome this, artificial intelligence method, which is widely used for optimization, automation, and prediction in various fields, was utilized to analyze the computational fluid dynamics simulation results. The computational fluid dynamics simulation results were analyzed using a supervised deep neural network model for regression analysis. The predicted results were evaluated quantitatively using Euclidean distance calculations. And the Bayesian optimization was used to derive the optimal condition, which results obtained through deep neural network training showed a discrepancy of approximately 4% when compared to the results obtained through computational fluid dynamics analysis. resulted in an increase of 146.2% compared to the previous computational fluid dynamics simulation results. These results are expected to have practical applications in various fields.

• 한국안전학회지
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• 제28권1호
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• pp.57-62
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• 2013

Aerodynamic characteristics of cross section shape is an important parameter for the wind response and structural stability of long span bridges. Numerical simulation methods have been introduced to estimate the aerodynamic characteristics for more detailed flow analysis and cost saving in place of existing wind tunnel experiment. In this study, the computational fluid dynamics(CFD) simulation and large eddy simulation( LES) technique were used to estimate lift, drag and moment coefficients of four cross sections. The Strouhal numbers were also determined by the fast Fourier transform of time series of the lift coefficient. The values from simulations and references were in a good agreement with average difference of 16.7% in coefficients and 8.5% in the Strouhal numbers. The success of the simulations is expected to attribute to the practical use of numerical estimation in construction engineering and wind load analysis.

• Environmental Engineering Research
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• 제19권2호
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• pp.165-174
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• 2014

A model combining multi-dimensional discretized population balance equations with a computational fluid dynamics simulation (CFD-DPBE model) was developed and applied to simulate turbulent flocculation and sedimentation processes in sediment retention basins. Computation fluid dynamics and the discretized population balance equations were solved to generate steady state flow field data and simulate flocculation and sedimentation processes in a sequential manner. Up-to-date numerical algorithms, such as operator splitting and LeVeque flux-corrected upwind schemes, were applied to cope with the computational demands caused by complexity and nonlinearity of the population balance equations and the instability caused by advection-dominated transport. In a modeling and simulation study with a two-dimensional simplified pond system, applicability of the CFD-DPBE model was demonstrated by tracking mass balances and floc size evolutions and by examining particle/floc size and solid concentration distributions. Thus, the CFD-DPBE model may be used as a valuable simulation tool for natural and engineered flocculation and sedimentation systems as well as for flocculant-aided sediment retention ponds.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 PARALLEL CFD 2006
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• pp.139-142
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• 2006

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권2호
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• pp.1089-1104
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• 2017

We have developed an information management tool for the EDISON (EDucation-research Integration through Simulation On the Net) open platform. EDISON is, at present, a web-based simulation service for education and research in five computational areas, namely, nanophysics, fluid dynamics, chemistry, structural dynamics, and computer aided optimal design. The EDISON open platform consists of three tiers: EDISON application framework, EDISON middleware, and EDISON infra-resources. The platform provides web portals for education and research in areas such as computational fluid dynamics, computational chemistry, computational nanophysics, computational structural dynamics, and computer aided optimal design along with user service. The main purpose of this research is to test the behavior of the release version of the EDISON Open-Platform under normal operating conditions. This management tool has been implemented using the RESTful API designed in EDISON middleware. The intention is to check co-operation between the middleware and the infrastructure. Suggested tools include User management, Simulation and Job management, and Simulation software (i.e., solver) testing. Finally, it is considered meaningful to develop a management tool that is not supported in other web-based online simulation services.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1310-1317
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• 2017

GASFLOW-MPI is a widely used scalable computational fluid dynamics numerical tool to simulate the fluid turbulence behavior, combustion dynamics, and other related thermal-hydraulic phenomena in nuclear power plant containment. An efficient scalable linear solver for the large-scale pressure equation is one of the key issues to ensure the computational efficiency of GASFLOW-MPI. Several advanced Krylov subspace methods and scalable preconditioning methods are compared and analyzed to improve the computational performance. With the help of the powerful computational capability, the large eddy simulation turbulent model is used to resolve more detailed turbulent behaviors. A backward-facing step flow is performed to study the free shear layer, the recirculation region, and the boundary layer, which is widespread in many scientific and engineering applications. Numerical results are compared with the experimental data in the literature and the direct numerical simulation results by GASFLOW-MPI. Both time-averaged velocity profile and turbulent intensity are well consistent with the experimental data and direct numerical simulation result. Furthermore, the frequency spectrum is presented and a -5/3 energy decay is observed for a wide range of frequencies, satisfying the turbulent energy spectrum theory. Parallel scaling tests are also implemented on the KIT/IKET cluster and a linear scaling is realized for GASFLOW-MPI.

• 한국산학기술학회논문지
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• 제12권8호
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• pp.3492-3496
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• 2011

우리나라의 국방 분야에서 모델링 및 시뮬레이션의 수준은 외국에 비해 상당히 저조하며, 무기체계의 연구 개발과 획득에서 신뢰성 부분을 해결하지 못하고 있는 실정이다. 따라서 본 연구에서는 전산유체역학을 이용하여 M&S를 공학적인 차원에서 모델링과 시뮬레이션의 적용 가능성을 제시하고, 향후 효과적인 무기체계의 연구개발과 획득에 적극 활용하고자 한다.