• Structural Engineering and Mechanics
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• v.16 no.3
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• pp.259-274
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• 2003

In this paper, a novel numerical solution technique, the differential cubature method is employed to study the buckling problems of thick plates with arbitrary quadrilateral planforms and non-uniform boundary constraints based on the first order shear deformation theory. By using this method, the governing differential equations at each discrete point are transformed into sets of linear homogeneous algebraic equations. Boundary conditions are implemented through discrete grid points by constraining displacements, bending moments and rotations of the plate. Detailed formulation and implementation of this method are presented. The buckling parameters are calculated through solving a standard eigenvalue problem by subspace iterative method. Convergence and comparison studies are carried out to verify the reliability and accuracy of the numerical solutions. The applicability, efficiency, and simplicity of the present method are demonstrated through solving several sample plate buckling problems with various mixed boundary constraints. It is shown that the differential cubature method yields comparable numerical solutions with 2.77-times less degrees of freedom than the differential quadrature element method and 2-times less degrees of freedom than the energy method. Due to the lack of published solutions for buckling of thick rectangular plates with mixed edge conditions, the present solutions may serve as benchmark values for further studies in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1001-1009
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• 2015

In Smart Grid, smart meter sends our electric signal data to the main server of power supply in real-time. However, the more efficient the management of power loads become, the more likely the user's pattern of usage leaks. This paper points out the threat of privacy and the need of security measures in smart device environment by showing that it's possible to identify the appliances and the specific usage patterns of users from the smart meter's data. Learning algorithm PCA is used to reduce the dimension of the feature space and k-NN Classifier to infer appliances and states of them. Accuracy is validated with 10-fold Cross Validation.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.239-244
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• 2009

The gridless (or meshfree) methods, such as MPS, SPH, FPM an so forth, are feasible and robust for the problems with moving boundary and/or complicated boundary shapes, because these methods do not need to generate a grid system. In this study, a gridless solver, which is based on the combination of moving least square interpolations on a cloud of points with point collocation for evaluating the derivatives of governing equations, is presented for two-dimensional unsteady incompressible Navier-Stokes problem in the low Reynolds number. A MAC-type algorithm was adopted and the Poission equation for the pressure was solved by successively in the moving least square sense. Some weighing functions were tested in order to investigate the up-winding effect for the convection term. Some typical problems were solved by the presented solver for the validation and the results obtained were compared with analytic solutions and the numerical results by conventional CFD methods, such as FVM.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.152-157
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• 2002

A cross-flow fan is widely used on many industrial fields: a blower for the general industry, mining industry, automobile and home appliances. The design point of the cross-flow fan is generally chosen by based on the region within low static pressure and high flow rate. It relatively makes high dynamic pressure at low speed because a working fluid passes through an impeller blade twice. However, it has low static pressure efficiency between $30\%$ and $40\%$ because of relative high impact loss. Recently, in the air-conditioning systems, the operating behaviors at the off-design points are highly regarded to broaden the application area for various air-cooling loads. Especially, at the low flow rate, there exists a rapid pressure head reduction, a noise increase and an irregular flow against a rearguider as a scroll of centrifugal fan. Numerical analyses are carried out for cross-flow fan including the impeller, the rearguider and the stabilizer. Numerical domains are discretized by hexahedral cells. Three-dimensional, unsteady governing equations are solved using FVM, SIMPLE algorithm, sliding grid system and standard k-$\epsilon$ turbulence model.

• Journal of computational fluids engineering
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• v.19 no.4
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• pp.61-67
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• 2014

Since the most of the existing non-Newtonian models are not adequate to apply to the lattmce Boltzmann method, it is a challenging task from both the theoretical and the numerical points of view. In this research the hydro-kinetic model was modified and applied to the 3-D moving sphere in the circular channel flow and the characteristics of the shear thinning effect by the HK-model was evaluated and the condition of ${\Gamma}$ in the model was suggested for the stable simulation to generate non-trivial prediction in three dimension strong shear flows. On the wall boundaries of circular channel the curved wall surface treatment with constant velocity condition was applied and the bounceback condition was applied on the sphere wall to simulate the relative motion of the sphere. The condition is adequate at the less blockage than 0.7 but It may need to apply a multi-scale concept of grid refinement at the narrow flow region. to obtain the stable numerical results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1354-1359
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• 2007

This paper discusses the acoustic performance of simple expansion chamber using computational fluid dynamics(CFD). The CFD model consists of an axisymmetric grid with a single period sinusoid of acceptable amplitude and duration imposed at the inlet boundary condition. The time history of the static pressure is recorded at two points, one in the inlet pipe and one point in outlet pipe. The time history of the static pressure is converted to the frequency domain using Fourier Transform and the transmission loss (TL) of the muffler is obtained from the ratio of the static pressure at the inlet and outlet pipe. The transmission loss of CFD result is compared with that of the computational acoustic analysis using the boundary element method (BEM). There are some differences in two results due to the pressure drop according to the inlet and outlet pipe length. Therefore, the effects of the pressure drop to the transmission loss have to be considered.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.112-115
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as support vector machine neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the monthly precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 2 grid points including $127.5^{\circ}E/35^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, which produced the best results from the previous study. The output node of neural networks models consist of the monthly precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of SVM-NNM and MLP-NNM performances for the downscaling of the monthly precipitation data. We should, therefore, construct the credible monthly precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.125-128
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the daily precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 4 grid points including $127.5^{\circ}E/37.5^{\circ}N$, $127.5^{\circ}E/35^{\circ}N$, $125^{\circ}E/37.5^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, respectively. The output node of neural networks models consist of the daily precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM performances for the downscaling of the daily precipitation data. We should, therefore, construct the credible daily precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• Journal of Power Electronics
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• v.11 no.2
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• pp.202-210
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• 2011

Polymer electrolyte membrane (PEM) fuel cell is one of the popular renewable energy sources and widely used in commercial medium power areas from portable electronic devices to electric vehicles. In addition, the increased integration of the PEM fuel cell with power electronics, dynamic loads, and control systems requires accurate electrical models and simulation methods to emulate their electrical behaviors. Advancement in parallel computation techniques, various real-time simulation tools, and smart power hardware have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds up advancements of optimized model constructions for a fuel cell stack system on a real-time simulator in the view points of improving dynamic model accuracy and boosting computation speed. In addition, several considerations for a power hardware-in-the-loop (PHIL) simulation are provided to electrically emulate the PEM fuel cell stack system with power facilities. The effectiveness of the proposed PHIL simulation method developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator and a programmable power supply is verified using experimental results of the proposed PHIL simulation system with a Ballard Nexa fuel cell stack.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.776-785
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• 2011

Since the Internet-based real-time Global Positioning System(GPS) synchronized widearea power system frequency monitoring network (FNET) was proposed in 2001, it has been monitoring the power system frequency in interconnected United States power systems and numerous interesting behaviors have been observed, including frequency excursion propagation. We address the consistency of a frequency excursion detection order of frequency disturbance recorders in FNET in relation to the same generation trip, as well as the ability to recreate by power systems dynamic simulation. We also propose a new method, as an application of FNET measurement, to locate a tripped generator using power systems dynamic simulation and wide-area frequency measurement. The simulation database of all the possible trips of generators in the interconnected power systems is created using the off-line power systems dynamic simulation. When FNET detects a sudden drop in the monitoring frequency, which is most likely due to a generation trip in power systems, the proposed algorithm locates a tripped generator by finding the best matching case of the measured frequency excursion in the simulation database in terms of the frequency drop detection order and the time of monitoring points.