• Atmosphere
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• v.20 no.3
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• pp.319-332
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• 2010

Sensitivity experiments of WRF model using different planetary boundary layer (PBL) and land surface model (LSM) parameterizations are evaluated for prediction of wind fields within the surface layer. The experiments were performed with three PBL schemes (YSU, Pleim, MYJ) in combination with three land surface models (Noah, RUC, Pleim). The WRF model was conducted on a nested grid from 27-km to 1-km horizontal resolution. The simulations validated wind speed and direction at 10 m and 80 m above ground level at a 1-km spatial resolution over the South Korea. Statistical verification results indicate that Pleim and YSU PBL schemes are in good agreement with observations at 10 m above ground level, while the MYJ scheme produced predictions similar to the observed wind speed at 80 m above ground level. LSM comparisons indicate that the RUC model performs best in predicting 10-m and 80-m wind speed. It is found that MYJ (PBL) - RUC (LSM) simulations yielded the best results for wind field in the surface layer. The choice of PBL and LSM parameterization will contribute to more accurate wind predictions for air quality studies and wind power using WRF.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.7-13
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• 2006

The advent of Semantic Web has generated several methods that can access the data on the web. Thus, it is necessary to handle the data by accessing the current web ontology as well as the existing knowledge base system. Web ontology languages are RDF(Resource Description Framework), DAML-OIL, OWL(Web Ontology Language), and so on. This paper presents the creation and the method of the ontology object model that can access, represent, and process the web ontology and the existing knowledge base. Unlike the existing access approach of web ontology using the model on memory constructed by each parser, we divide the model of web ontology into three layers such as frame-based ontology layer, generic ontology layer, and functional ontology layer. Generic ontology layer represents the common vocabulary among several domains and functional ontology layer contains the dependent vocabulary to each ontology respectively. Our model gets rid of the redundancy of the representation and enhances the reusability. Moreover, it can provide the easy representation of knowledge and the fast access of the model in the application.

• Structural Engineering and Mechanics
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• v.48 no.1
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• pp.57-75
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• 2013

It is still inadequate for investigating the highly nonlinear and complex mechanical behaviors of single-layer latticed domes by only performing a force-based demand-capacity analysis. The energy-based balance method has been largely accepted for assessing the seismic performance of a structure in recent years. The various factors, such as span-to-rise ratio, joint rigidity and damping model, have a remarkable effect on the load-carrying capacity of a single-layer latticed dome. Therefore, it is necessary to determine the maximum load-carrying capacity of a dome under extreme loading conditions. In this paper, a mechanical model for members of the semi-rigidly jointed single-layer latticed domes, which combines fiber section model with semi-rigid connections, is proposed. The static load-carrying capacity and seismic performance on the single-layer latticed domes are evaluated by means of the mechanical model. In these analyses, different geometric parameters, joint rigidities and roof loads are discussed. The buckling behaviors of members and damage distribution of the structure are presented in detail. The sensitivity of dynamic demand parameters of the structures subjected to strong earthquakes to the damping is analyzed. The results are helpful to have a better understanding of the seismic performance of the single-layer latticed domes.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.4
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• pp.374-380
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• 2015

In this paper, a dynamic model describing the 2 phase effect on the gas diffusion layer depending on load change of a fuel cell stack was developed to examine the effects of liquid water in fuel cell cathode gas diffusion layer on the fuel cell performance. For the developed model, 2 phase effect on the performance of a fuel cell stack depending on the load changes, concentration distribution of water vapor and oxygen inside a gas diffusion layer, the effect of the thickness and porosity of the gas diffusion layer on the fuel cell stack voltage were examined. As a result, a fuel cell stack voltage for the 2 phase model within the scope of the research become lower than that for the 1 phase model regardless of the load. Although oxygen molar concentration for the gas diffusion layer adjacent to the catalyst layer was the lowest, water vapor concentration is the highest. In addition, as thickness and porosity of the gas diffusion layer increased and decreased, respectively, the fuel cell stack voltage decreased.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.33-42
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• 1994

The radiative heat transfer analysis in the fluidized particles layer has important application in many technological areas such as combustion chambers at high pressure and temperature, plasma generators for nuclear fusion, MHD generator using pulverized coal and the liquid droplet radiator used to reject wasted heat from a power plant operating in space. To accurately model the radiation properties of the fluidized particles layer, it is necessary to know the radiation interchange factors of particles in each layer. But the solutions are usually not possible for the equations of radiative heat transfer because it has an inherent difficulty in treating the governing intergo- differential equations, which are derived from the remote effects of radiative heat transfer. In this study, the analysis uses the Monte Carlo simulation method with optical depth model to calculate the radiation interchange factors of particles in each layer with wall and with each other.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.2
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• pp.96-111
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• 2012

Hull Mounted Sonar (HMS) is a long range submerged vehicle's hull-mounted passive sonar system which detects low-frequency noise caused by machineries of enemy ships or submerged vehicles. The HMS needs a sound absorption /insulation multi-layer structure to shut out the self-noise from own machineries and to amplify signals from outside. Therefore, acoustic analysis of the multi-layer system should be performed when the HMS is designed. This paper simplified the HMS multi-layer system to be an infinite planar multi-layer model. Also, main excitations that influence the HMS were classified into mechanical, plane wave and turbulent flow excitation, and the investigations for each excitation were performed for various models. Stiffened multi-layer analysis for mechanical excitation and general multi-layer analysis for turbulent flow excitation were developed. The infinite planar multi-layer analysis was expected to be more useful for preliminary design stage of HMS system than the infinite cylindrical model because of short analysis time and easiness of parameter study.

• Journal of the korean society of oceanography
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• v.31 no.2
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• pp.75-88
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• 1996

The analytic and numerical solution of the 1$\frac{1}{2}$-layer and 2$\frac{1}{2}$-layer models are derived. The large coastal-sea level drop and the fast westward speed of the anticyclonic gyre due to strong offshore winds using two ocean models are investigated. The models are forced by wind stress fields similar in structure to the intense mountain-pass jets(${\sim}$20 dyne/$cm^{2}$) that appear in the Gulfs of Tehuantepec and Papagayo in the Central America for periods of 3${\sim}$7 days. Analytic and numerical solutions compare favorably with observations, the large sea-level drop (${\sim}$30 cm) at the coast and the fast westward propagation speeds (${\sim}$13 km/day) of the gyres. The coastal sea-level drop is enhanced by several factors: horizontal mixing, enhanced forcing, coastal geometry, and the existence of a second active layer in the 2$\frac{1}{2}$-layer model. Horizontal mixing enhances the sea-level drop because the coastal boundary layer is actually narrower with mixing. The forcing ${\tau}$/h is enhanced near the coast where h is thin. Especially, in analytic solutions to the 2$\frac{1}{2}$-layer model the presence of two baroclinic modes increases the sea-level drop to some degree. Of theses factors the strengthened forcing ${\tau}$/h has the largest effect on the magnitude of the drop, and when all of them are included the resulting maximum drop is -30.0 cm, close to observed values. To investigate the processes that influence the propagation speeds of anticyclonic gyre, several test wind-forced calculations were carried out. Solutions to dynamically simpler versions of the 1$\frac{1}{2}$-layer model show that the speed is increased both by ${\beta}$-induced self-advection and by larger h at the center ofthe gyres. Solutions to the 2$\frac{1}{2}$-layer model indicate that the lower-layer flow field advects the gyre westward and southward, significantly increasing their propagation speed. The Papagayo gyre propagates westward at a speed of 12.8 km/day, close to observed speeds.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.771-780
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• 2004

The purpose of this study is to test a development of system for flood runoff forecasting using neural network model. As the forecasting models for flood runoff the neural network model was tested with the observed flood data at Gongju and Buyeo stations. The neural network model consists of input layer, hidden layer, and output layer. For the flood events tested rainfall and runoff data were the input to the input layer and the flood runoff data were used in the output layer. To make a choice the forecasting model which would make up of runoff forecasting system properly, real-time runoff of river when flood periods were forecasted by using neural network model and state-space model. A comparison of the results obtained by the two forecasting models indicated the superiority and reliability of the neural network model over the state-space model. The neural network model was modified to work in the Web and developed to be the basic model of the forecasting system for the flood runoff. The neural network model developed to be used in the Web was loaded into the server and was applied to the main stream of Geum river. For the main stage gauging stations mentioned above the applicability of the selected forecasting model, the Neural Network Model, was verified in the Web.

• Geomechanics and Engineering
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• v.15 no.2
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• pp.783-791
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• 2018

In consideration of the mesoscopic structure of soil-rock mixtures in which the rock aggregates are wrapped by soil at normal temperatures, a two-layer embedded model of single-inclusion composite material was built to calculate the shear modulus of soil-rock mixtures. At a freezing temperature, an interface ice interlayer was placed between the soil and rock interface in the mesoscopic structure of the soil-rock mixtures. Considering that, a three-layer embedded model of double-inclusion composite materials and a multi-step multiphase micromechanics model were then built to calculate the shear modulus of the frozen soil-rock mixtures. Given the effect of pore structure of soil-rock mixtures at normal temperatures, its shear modulus was also calculated by using of the three-layer embedded model. Experimental comparison showed that compared with the two-layer embedded model, the effect predicted by the three-layer embedded model of the soil-rock mixtures was better. The shear modulus of the soil-rock mixtures gradually increased with the increase in rock regardless of temperature, and the increment rate of the shear modulus increased rapidly particularly when the rock content ranged from 50% to 70%. The shear modulus of the frozen soil-rock mixtures was nearly 3.7 times higher than that of the soil-rock mixtures at a normal temperature.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.237-238
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• 2007

A new strain analysis model, so called the stress matched model, in an epitaxial multilayer system is proposed. The model makes it possible to know the strain, the stress, the elastic strain energy in each epitaxial layer. Analytical formulas of strain parameters in each epitaxial layer are derived under assumptions that the substrate thickness is finite and the in-plane lattice constant is the same for all epitaxial layers for dislocation free growth. As an example, the model is applied to a 405nm InGaN/InGaN multiple quantum well laser diode. Analysis result shows that AlxGa1-xN layer with Al mole fraction of 0.06 and the thickness of 6${\mu}m$ is one of good templates for a laser. In fact, this layer structure coincides with experimentally optimized one.