• Proceedings of the Korea Society for Simulation Conference
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• 1994.06a
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• pp.0.2-0
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• 1994

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.862-866
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• 2005

For urban watershed models, the ILLUDAS and SWMM are the popular rainfall-runoff models used in Korea. However, combined sewage systems in urban areas produced problems when a flood occured because of the surcharged precipitation amount which drained to the streams directly. Also, the lack of pipe line data and the difficulties of modeling yield inappropriate modeling results in urban runoff analysis. In addition, rainfall-runoff models in urban areas which use channel routing could have inaccurate and complicated processes. In this paper, the MIKE SWMM model has been applied for the stable runoff analysis of urban areas. Watershed and pipe line data were established by using past inundated records, DEM data, and the numerical pipe line data. For runoff modelings, the runoff block was adapted to a basin and the Extran block using dynamic equations was applied to the sewage system. After comparing to models that exist, it is concluded that the MIKE SWMM model produces reliable and consistence results without distorting the Parameters of the model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.3
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• pp.175-185
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• 2020

The six-DOF aerodynamic coefficients of a missile entail inherent physical gradient constraints originated from the geometric characteristics of a cylindrical fuselage. To effectively adopt the freely available gradient information in aerodynamic coefficients modeling, this research employed gradient-enhanced (GE) Gaussian process. To investigate the accuracy of aerodynamic coefficients predicted with gradients information, we compared two Gaussian-process-based models: ordinary and GE Gaussian process models with and without gradient information, respectively. As a result, we found that GE Gaussian process models were able to comply with imposed gradient information and more accurate than ordinary Gaussian process models. However, we also found that GE Gaussian process modeling cannot handle gradient information continuously and ends up with more samples due to additional gradient information.

• The Research Journal of the Costume Culture
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• v.25 no.3
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• pp.270-284
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• 2017

This study aimed to create 3D-printed insoles for flat-footed senior men using 3D systems. 3D systems are product-manufacturing systems that use 3-dimensional technologies like 3D scanning, 3D modeling, and 3D printing. This study used a 3D scanner (NexScan2), 3D CAD programs including Rapidform, AutoCAD, SolidWorks, Nauta+ compiling program, and a 3D printer. In order to create insoles for flat-footed senior men, we analyzed horizontal sections of 3D foot scans We selected 20 flat-footed and 20 normal-footed subjects. To make the 3D insole models, we sliced nine lines on the surface of the subjects' 3D foot scans, and plotted 144 points on the lines. We calculated the average of these 3D coordinates, then located this average within the 3D space of the AutoCAD program and created 3D sole models using the loft surface tools of the SolidWorks program. The sole models for flat feet differed from those of normal feet in the depth of the arch at the inner sideline and the big toe line. We placed the normal-footed sole model on a flat-footed sole model, and the combination of the two models resulted in the 3D insole for flat feet. We printed the 3D modeled insole using a 3D printer. The 3D printing material was an acrylic resin similar to rubber. This made the insole model flexible and wearable. This study utilized 3D systems to create 3D insoles for flat-footed seniors and this process can be applied to manufacture other items in the fashion industry as well.

• Steel and Composite Structures
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• v.43 no.3
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• pp.327-340
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• 2022

A vast amount of experimental and analytical research has been conducted related to the seismic behavior and performance of concrete filled steel tubular (CFT) columns. This research has resulted in a wealth of information on the component behavior. However, analytical and experimental data for structural systems with CFT columns is limited, and the well-known behavior of steel or concrete structures is assumed valid for designing these systems. This paper presents the development of an analytical model for nonlinear analysis of composite moment resisting frame (CFT-MRF) systems with CFT columns and steel wide-flange (WF) beams under seismic loading. The model integrates component models for steel WF beams, CFT columns, connections between CFT columns and WF beams, and CFT panel zones. These component models account for nonlinear behavior due to steel yielding and local buckling in the beams and columns, concrete cracking and crushing in the columns, and yielding of panel zones and connections. Component tests were used to validate the component models. The model for a CFT-MRF considers second order geometric effects from the gravity load bearing system using a lean-on column. The experimental results from the testing of a four-story CFT-MRF test structure are used as a benchmark to validate the modeling procedure. An analytical model of the test structure was created using the modeling procedure and imposed-displacement analyses were used to reproduce the tests with the analytical model of the test structure. Good agreement was found at the global and local level. The model reproduced reasonably well the story shear-story drift response as well as the column, beam and connection moment-rotation response, but overpredicted the inelastic deformation of the panel zone.

• Steel and Composite Structures
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• v.38 no.2
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• pp.223-239
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• 2021

This paper presents the analytical modeling and finite element (FE) analysis, using ABAQUS software, of the new types of steel reinforced lightweight aggregate concrete (SRLAC) columns with cross-shaped (+shaped and X-shaped) steel section, using proposed three analytical and two FE models in total. The stress-strain material models for different components in the columns, including the confined zones of the lightweight aggregate concrete (LWAC) using three and four concrete zones divisions approaches and with and without taking into account the stirrups reaction effect, are established first. The analytical models for determining the axial load-deformation behavior of the SRLAC columns are drawn based on the materials models. The analytical and FE models' results are compared with previously reported test results of the axially loaded SRLAC columns. The proposed analytical and FE models accurately predict the axial behavior and capacities of the new types of SRLAC columns with acceptable agreements for the load-displacement curves. The LWAC strength, steel section ratio, and steel section configuration affect the contact stress between the concrete and steel sections. The average ratios of the ultimate test load to the three analytical models and FEA model loads, Put /Pa1, Put /Pa2, Put /Pa3, and Put /PFE1, for the tested specimens are 0.96, 1.004, 1.016, and 1.019, respectively. Finally, the analytical parametric studies are also studied, in terms of the effects of confinement, LWAC strength, steel section ratio, and the reinforcement ratio on the axial capacity of the SRLAC column. When concrete strength, confinements, area of steel sections, or reinforcement bars ratio increased, the axial capacities increased.

• Journal of IKEEE
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• v.26 no.3
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• pp.349-354
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• 2022

In thermal power plants, boiler models have been used widely in evaluating logic configurations, performing system tuning and applying control theory, etc. Furthermore, proper plant models are needed to design the accurate controllers. Sometimes, mathematical models can not exactly describe a power plant due to time varying, nonlinearity, uncertainties and complexity of the thermal power plants. In this case, a neural network can be a useful method to estimate such systems. In this paper, the models of boiler steam system in a thermal power plant are developed by using a generalized regression neural network(GRNN). The models of the superheater, reheater, attemperator and drum are designed by using GRNN and the models are trained and validate with the real data obtained in 540[MW] power plant. The validation results showed that proposed models agree with actual outputs of the drum boiler well.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• The Journal of Society for e-Business Studies
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• v.1 no.2
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• pp.117-131
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• 1996

This paper presents the results of the systems analysis for the FCIM (Flexible Computer Integrated Manufacturing) system at the U.S. Tobyhanna Army Repair Depot, which is one of the RAMP (Rapid Acquisition of Manufactured Part) program sites for CALS implementation in the U.S. military. The FCIM system's acquisition and supply processes are represented by IDEFO function models and FCIM information systems are briefly decribed in this paper. The models presented here can be used at a reference for the development of CALS acquisition and supply systems. In addition. the distinction between input and control information on the IDEFO model it suggested from the practical modeling viewpoint.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.589-598
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• 2015

In longitudinal studies missing data are common and require a complicated analysis. There are two popular modeling frameworks, pattern mixture model (PMM) and selection models (SM) to analyze the missing data. We focus on the PMM and we also propose Bayesian pattern mixture models using generalized linear mixed models (GLMMs) for longitudinal binary data. Sensitivity analysis is used under the missing not at random assumption.