• 한국전산유체공학회:학술대회논문집
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• 2006.10a
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• pp.18-21
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• 2006

This paper investigates LES of turbulent combustion flow based on 2-scalar flamelet approach, where a G-equation and a conserved scalar equation simulate a propagation of premixed flame and a diffusion combustion process, respectively. The turbulent SGS modeling on these flamelet combustion approach is also researched. These LES models are applied to an industrial flows in a full scale gasturbine combustor with premixed and non-premixed flames. The numerical results predict the characteristics of experiment temperature profiles. Unsteady features of complex flames in combustor are also visualized.

• Structural Engineering and Mechanics
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• v.9 no.2
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• pp.141-152
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• 2000

Based on the discussion about some empirical coherency models resulted from earthquake-induced ground motion recordings at the SMART-1 array in Taiwan, and a heuristic model of the coherency function from elementary notions of stationary random process theory and a few simplifying assumptions regarding the propagation of seismic waves, a practical coherency model for spatially varying ground motions, which can be applied in aseismic analysis and design, is proposed, and the regressive coefficients are obtained using least-square fitting technique from the above recordings.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.293-296
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• 2001

In this paper, we investigate two soft handover algorithms used in the different mobile communication system. These different systems are IS-95 system and 3GPP system. The performances of two different soft handover are compared under similar conditions in terms of propagation, environment and mobility behavior. For performance comparison of soft handover, we model cell environment, radio channel and mobility. With these models the computer simulation are performed and the result of computer simulation are reported.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.758-763
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• 1994

The work discusses the problems of modelling of the process of acoustic signal generation in machines. We have pointed out that in the task of minimizing of both moise and vibration, the key problem is identification of sources and paths of propagation, both in terms of their location and of definition of their characteristic features. Properly conducted identification makes possible the use of relatively simple mathematical models and this fact is particularly important for a broad application of the proposed methods in practice.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.2
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• pp.87-94
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• 2014

In solid mechanics, the peridynamics theory has provided a suitable framework for material failure and damage propagation simulation. Peridynamics is computationally expensive since it is required to solve enormous nonlocal interactions based upon integro-differential equations. Thus, multiscale coupling methods with other local models are of interest for efficient and accurate implementations of peridynamics. In this study, peridynamic models are restricted to regions where discontinuities or stress concentrations are present. In the domains characterized by smooth displacements, classical local models can be employed. We introduce a recently developed blending scheme to concurrently couple bond-based peridynamic models and the Navier equation of classical elasticity. We demonstrate numerically that the proposed blended model is suitable for point loads and static fracture, suggesting an alternative framework for cases where peridynamic models are too expensive, while classical local models are not accurate enough.

• Geomechanics and Engineering
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• v.9 no.4
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• pp.465-481
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• 2015

Three-dimensional simulation of flow through dam foundation is performed using finite element (Seep3D model) and artificial neural network (ANN) models. The governing and discretized equation for seepage is obtained using the Galerkin method in heterogeneous and anisotropic porous media. The ANN is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning, using the water level elevations of the upstream and downstream of the dam, as input variables and the piezometric heads as the target outputs. The obtained results are compared with the piezometric data of Shahid Abbaspour's Dam. Both calculated data show a good agreement with available measurements that demonstrate the effectiveness and accuracy of purposed methods.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.203-206
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• 2007

In urban flood model, the features like roads, buildings, and river's banks have great effect on flow dynamics and flood propagation and it must be accounted for model set-up. Two-dimensional hydraulic models in high-density building areas are at the forefront of current research into flood inundation mechanisms, but they are however constrained by inadequate parameters of topography and friction due to insufficient and inaccurate data. This paper describes the development of urban flooding with the extraction of building areas and estimates the its influence on flood inundation extent, and present initial results of flood simulation varying grid size.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.154-157
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• 2003

In order for testing faults of combinatorial logic circuit, the authors have developed a new diagnosis method: "Neural Network (NN) fault diagnosis", based on fm error back propagation functions. This method has proved the capability to test gate faults of wider range including so called SSA (single stuck-at) faults, without assuming neither any set of test data nor diagnosis dictionaries. In this paper, it is further shown that what kind of fault models can be detected in the NN fault diagnosis, and the simply modified one can extend to test delay faults, e.g. logic hazard as long as the delays are confined to those due to gates, not to signal lines.

• Journal of electromagnetic engineering and science
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• v.5 no.4
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• pp.189-192
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• 2005

The measurement of unique rainfall phenomenon and rain attenuation on 38 GHz terrestrial links at South Korea in 1998 is presented. It was one of the most severe rainfall years at the measured region due to increased EI Nino signal. The rainfall rate exceeded at $0.01\%$ was 97.4 mm/h during a worst month and annual rate was 63.5 mm/h. Experimentally measured results have been compared with some models and found that the rain attenuation by system level was underestimated by the existing prediction models. As it was measured only three months, further study and measurement of rainfall and rain attenuation in this region are needed for stable millimeter-wave system operation at all times.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.6
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• pp.54-66
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• 1997

The objectives of this study is to introduce and apply neural network theory to real hydrologic systems for stochastic nonlinear predicting of daily runoff discharge in the river catchment. Back propagation algorithm of neural network model is applied for the estimation of daily stochastic runoff discharge using historical daily rainfall and observed runoff discharge. For the fitness and efficiency analysis of models, the statistical analysis is carried out between observed discharge and predicted discharge in the chosen runoff periods. As the result of statistical analysis, method 3 which has much processing elements of input layer is more prominent model than other models(method 1, method 2) in this study.Therefore, on the basis of this study, further research activities are needed for the development of neural network algorithm for the flood prediction including real-time forecasting and for the optimal operation system of dams and so forth.