• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.157-162
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• 2005

Parallel implementation and performance assessment of the grid assembly in a structured chimera grid approach is studied. The grid assembly process, involving hole cutting and searching donor, is parallelized on the PC cluster. A message passing programming model based on the MPI library is implemented using the single program multiple data(SPMD) paradigm. The coarse-grained communication is optimized with the minimized memory allocation because that the parallel grid assembly can access the decomposed geometry data in other processors by only message passing in the distributed memory system such as a PC cluster. The grid assembly workload is based on the static load balancing tied to flow solver. A goal of this work is a development of parallelized grid assembly that is suited for handling multiple moving body problems with large grid size.

• Journal of Ship and Ocean Technology
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• v.10 no.3
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• pp.1-16
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• 2006

Despite the high cost of memory and CPU time required to resolve the boundary layer, a viscous unstructured grid solver has many advantages over a structured grid solver such as the convenience in automated grid generation and vortex capturing by solution adaption. In present study, an unstructured Cartesian grid solver is developed on the basis of the existing Euler solver, NASCART-GT. Instead of cut-cell approach, immersed boundary approach is applied with ghost cell boundary condition, which can be easily applied to a moving grid solver. The standard $k-{\varepsilon}$ model by Launder and Spalding is employed for the turbulence modeling, and a new wall function approach is devised for the unstructured Cartesian grid solver. Developed approach is validated and the efficiency of the developed boundary condition is tested in 2-D flow field around a flat plate, NACA0012 airfoil, and axisymmetric hemispheroid.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.1
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• pp.59-65
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• 2013

The signal broadcast from a GPS satellite experiences code delay and carrier phase advance while passing through the ionosphere, which causes a signal error. Many ionosphere models have been studied to correct this ionospheric delay error. In this paper, the ionosphere modeling for the Korean Peninsula was carried out using a spherical harmonics based model. In contrast to the previous studies, we considered a real-time ionospheric delay correction model using fewer number of basis functions. The modeling performance was evaluated by comparing with a grid model. Total number of basis functions was set to be identical to the number of grid points in the grid model. The performance test was conducted using the GPS measurements collected from 5 reference stations during 24 hours. In the test result, the modeling residual error was smaller than that of the existing grid model. However, when the number of measurements was small and the measurements were not evenly distributed, the overall trend was found to be problematic. For improving this problem, we implemented the modeling with additional virtual measurements.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.93-106
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• 2011

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.557-571
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• 2020

High-resolution flows around a steep mountainous island (Ulleungdo) in Korea were simulated by a computational fluid dynamics (CFD) model. To cover entire Ulleungdo and to resolve the topography around the Ulleungdo automatic synoptic observing system (ASOS) with high resolution, one-way nested grid system with large (60 m), and small (20 m) grid sizes was applied in the CFD model simulations. We conducted the numerical simulations for 16 inflow directions, and, for each inflow direction, we considered six different wind velocities(5, 10, 15, 20, 25, and 30 m s^-1) at the reference height (1,000 m). The effects of topography on surface wind observations were well reflected in the observed wind roses for the period of January 01, 2012 ~ December 31, 2016 at the Ulleungdo ASOS and marine buoy. Wind roses at the Ulleungdo ASOS was reproduced based on the CFD simulations. The changes in surface winds at the Ulleungdo ASOS caused by surrounding topography were relatively well simulated by the CFD model. The simulated wind-rose indicated that south-southwesterly and northeasterly were the dominant wind directions, which were also observed at the Ulleungdo ASOS. We investigated the flow characteristics around the Ulleungdo ASOS for northwesterly, south-southwesterly, and northeasterly winds in detail.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1621-1624
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• 2003

As the entities participating Grid become larger, performance requirement for the LDAP-based GIS(Grid Information Service) goes beyond that provided by a stand-alone single LDAP server. This entails the exploration of distributed LDAP systems. This paper presents the performance evaluation respectively for a distribution-based and a replication-based LDAP model. The analysis is based on an analytic performance model for each distributed system which is obtained by applying the M/M/1 queuing model. The performance evaluation made to these analytic models reveals that the distribution-based and the replication-based model show a significant tradeoff in their performance with respect to the system size as well as the amount of system load.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.3
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• pp.369-375
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• 2006

Large eddy simulation has been applied to simulate turbulent flow around a cubic obstacle mounted on a channel surface for a Reynolds number of 40000(based on the incoming bulk velocity and the obstacle height) using a Smagorinsky model and a Lagrangian dynamic model. In order to develop the LES to the practical engineering application, the effect of upwind scheme, turbulent sub-grid scale model were investigated. The computed velocities. turbulence quantifies, separation and reattachment length were evaluated by compared with the previous experimental results.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.363-370
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• 2003

This paper describes a rectification procedure that relies on a polynomial model derived from the imaging geometry without loss of accuracy. By using polynomial model, one can effectively eliminate the iterative process to find an image pixel corresponding to each output grid point. With the imaging geometry and ephemeris data, a geo-location polynomial can be constructed from grid points that are produced by solving three equations simultaneously. And, in order to correct the local distortions induced by the geometry and terrain height, a distortion model has been incorporated in the procedure, which is a function of incidence angle and height at each pixel position. With this function, it is straightforward to calculate the pixel displacement due to distortions and then pixels are assigned to the output grid by re-sampling the displaced pixels. Most of the necessary information for the construction of polynomial model is available in the leader file and some can be derived from others. For validation, sample images of ERS-l PRI and Radarsat-l SGF have been processed by the proposed method and evaluated against ground truth acquired from 1:25,000 topography maps.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.101-110
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• 2022

Histopathological analysis of biopsy specimens is still used for diagnosis and classifying the brain tumors today. The available procedures are intrusive, time consuming, and inclined to human error. To overcome these disadvantages, need of implementing a fully automated deep learning-based model to classify brain tumor into multiple classes. The proposed CNN model with an accuracy of 92.98 % for categorizing tumors into five classes such as normal tumor, glioma tumor, meningioma tumor, pituitary tumor, and metastatic tumor. Using the grid search optimization approach, all of the critical hyper parameters of suggested CNN framework were instantly assigned. Alex Net, Inception v3, Res Net -50, VGG -16, and Google - Net are all examples of cutting-edge CNN models that are compared to the suggested CNN model. Using huge, publicly available clinical datasets, satisfactory classification results were produced. Physicians and radiologists can use the suggested CNN model to confirm their first screening for brain tumor Multi-classification.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.