• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.13-18
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• 1998

The assessment of machined surface is difficult because the freeform surface must be evaluated by surface fairness as well as dimensional accuracy. In this paper, the methodology of freeform surface generation using measured data on the machine tool is presented. The reliability of measured points data is obtained by measuring error compensation. The compensated data are formulated through Non-uniform G-spline surface modeling. In order to improve the surface fairness, the generated model si smoothened by parameterization The validity and usefulness of the proposed method are examined through computer simulation and experiments on the machine tool.

• Korean Journal of Computational Design and Engineering
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• v.7 no.3
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• pp.148-156
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• 2002

Most Rapid Prototyping (RP) processes adopt a solid Computer Aided Design (CAD) model, which will be sliced into thin layers of constant thickness in the building direction. Each cross-sectional layer is successively deposited and, simultaneously, bonded onto the previous layer; and eventually the stacked layers from a physical part of the model. A new RP process, the transfer-type Variable Lamination Manufacturing process using expandable polystyrene foam sheet (VLM-ST), has been developed to reduce building time and to improve the surface finish of parts with the thick layers and a sloping surface. This paper describes the generation of Unit Shape Layer (USL), the cutting path data of the linen. hotwire cutter for the VLM-ST process. USL is a three-dimensional layer with a thickness of more than 1 mm and a side slope, and it is the basic unit of cutting and building in the VLM-ST process. USL includes data such as layer thickness, positional coordinates, side angles of each layer, hotwire cutting speed, the heat input to the hotwire, and reference shape. The procedure of generating USL is as follows: (1)Generation of the mid-slice from the CAD model, (2)Conversion of the mid-slice into a simply connected domain, (3)Generation to the reference shape for the mid-slice, (4)Calculation of the rotation angle of the hotwire of the cutting system.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.168-177
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• 2001

Reverse engineering has been widely used for the shape reconstruction of an object without CAD data and the measurement of clay or wood models fur the development of new products. To generate a surface from measured points by a laser scanner, typical steps include the scanning of a clay or wood model, the generation of compatible input curves, the generation of a surface and manufacturing data like G code or STL file. A laser scanner has a great potential to get geometrical data of a model for its frost measuring speed and higher precision. The data from a laser scanner are composed of many line stripes of points including small spikes and noise. A new approach using automated surface generating algorithm is introduced to deal with problems during reverse engineering process. And the input data and the generated surface are represented in IGES format, thus can be supplied to other CAD/CAM software without any data manipulation.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.8
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• pp.385-390
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• 2017

Because of the ever-increasing software complexity, model-based development techniques are becoming an essential technique in software development. However, even if model-based techniques are used, the test case generation for complex software is still a challenge to solve. In this paper, we propose a method to generate automatic test cases based on UML model using custom parser and SMT solver. By proposed technique, a test case can be generated even though the model is described in a platform independent language such as action language, or in a platform dependent language. In addition, a concolic execution technique is applied to efficiently generate test cases in the model. In this paper, we present a case study on the power window switch model of Hyundai Santa Fe through the proposed test case generation technique.

• Journal of Distribution Science
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• v.17 no.10
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• pp.61-71
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• 2019

Purpose - This study aims to explore the impact of factors on Korean consumer goods purchase decision of Vietnam's Generation Z. Research design, data, and methodology - A mixed research method was utilized in this study including focus group, in-depth interview, pilot study, and official study. The conceptual model and hypothesis were tested using data collected cross-sectional by questionnaire, from a sample of 439 respondents, by both electronic and paper surveys with non-probability and convenience sampling. The SPSS 20 and AMOS 20 software were employed to analyze the data. Results - Results showed that Vietnam's Generation Z was strongly impacted by social media, Hallyu, country of origin, social norms, and perceived usefulness. Besides, Korean consumer goods purchase decision of Vietnam's Generation Z also were impacted by intermediary factors such as trust, social norms, product involvement, perceived quality, perceived usefulness, attitude, and buying intention. There were differences in factors affecting the purchase decision of the boy and girl Generation Z group. Conclusions - The factors impacting on Korean consumer goods decision of Vietnam's Generation Z are very important for Korean firms and government. The findings provide Korean firms opportunity for appropriate to be carried out factors impacting Korean consumer goods to generation Z in Vietnam successful.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.241-246
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• 1996

An analytical model to calculate rate of vapor generation due to heterogeneous wall nucleation in flashing flow is developed. In the present model, an important parameter of the vapor generation term, i.e. nucleation site density is calculated by integrating its probability distribution function with respect to active cavity radius. The limits of integration are minimum and maximum active cavity radii, and these are formulated using an active cavity model for nucleate boiling. This formulation, therefore. can statistically account for the effect of surface specific thermo-physical and geometric conditions on the vapor generation rate and flashing inception. For verifying the adequacy of the present model, steady state two-fluid and the bubble transport equations are solved with applicable constitutive equations. The applicable region of the bubble transport equation is also extended to churn-turbulent flow regime to predict interfacial area concentration at high void fraction. Predicted results in terms of axial pressure and void fraction profiles along the channels are compared with experimental data of Super Moby Dick and BNL Reasonable agreements have been achieved and this shows the applicability of the present model to flashing flow analysis.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.103-112
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• 2012

This research introduces a trip generation model reflecting time-series effects derived from a panel analysis with the data collected from the national household trip surveys conducted in 1996, 2002 and 2006. The existing methods are unable to reflect time-series effects from the change of socioeconomic conditions because the parameters applied to the model were basically from the base year of study - the parameter values were unchanged. This study proposes a new trip generation model developed through a panel analysis performed with the data collected from the last three national household trip surveys. From the results, it was found that the number of school trips increases and that the number of shopping trips decreases as time passes. The results showed that there are time-series effects affecting in trip generation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.505-514
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• 2015

This paper proposes a probabilistic generation assessment model of renewable energy generators(REGs) considering uncertainty of resources, mainly focused on Wind Turbine Generator(WTG) and Solar Cell Generator(SCG) which are dispersed widely in South Korea The proposed numerical analysis method assesses the one day-ahead generation by combining equivalent generation characteristics function and probabilistic distribution function of wind speed(WS) and solar radiation(SR) resources. The equivalent generation functions(EGFs) of the wind and solar farms are established by grouping a lot of the farms appropriately centered on Weather Measurement Station(WMS). First, the EGFs are assessed by using regression analysis method based on typical least square method from the recorded actual generation data and historical resources(WS and SR). Second, the generation of the REGs is assessed by adding the one day-ahead resources forecast, announced by WMS, to the EGFs which are formulated as third order degree polynomials using the regression analysis. Third, a Renewable Energy Generation Assessment System(REGAS) including D/B of recorded actual generation data and historical resources is developed using the model and algorithm predicting one day-ahead power output of renewable energy generators.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.35-43
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• 2003

Currently, the government has been driving numerous projects to build the e-government which can enable limitless access and utilization of the information through the accomplishment of the real time based various administrative services. In water resource field, a project to generate digital river thematic maps has been undergoing as a part of the computerization projects. As a partial results, the RIMGIS project has been completed and generation of the various river thematic maps has been required to fully utilize the DB built from RIMGIS project. For the effective generation of the thematic maps, a data model needs to be developed. A data model has been developed in this study to provide more efficient method to generate the thematic maps utilizing existing DB. The data model proposed from this study has defined the relationships between core feature data and framework Data along with relationships among data elements to represent the rivers in the real world more accurately. The core feature data and framework layers have been defined based on the survey of the domestic and foreign case studies along with requirement analysis of the users in the water resource field. The proposed core feature data has been defined based on the minimum unit of 'class', and the relationship between classes has been established based on the ArcGIS Hydro Data Model for the integrated processing of the river information. The proposed spatial data model can be judged to contribute establishing more efficient generation methodology of the river thematic maps.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.