• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.15-20
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• 2009

The purpose of this study was to test the applicability of the HSPEXP model performance criteria for calibrating hydrologic parameters of HSPF. Baran watershed, located at Whasung city, was selected as a study watershed in this study. Input data for the HSPF model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1996 to 2000 was used for calibration and from 2002 to 2007 was for validation. Using the HSPEXP decision-support software, hydrology parameters were adjusted based on total volume, then low flows, storm flows, and finally seasonal flows. Suggested criteria for each model performance variables were referenced from the previous research. For the calibration period, all the HSPEXP model performance criteria were satisfied while two criteria were slightly violated for the validation period.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.6
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• pp.538-544
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• 2012

Analysis of thermal performance is required for the economic operation of turbine cycle of power plant. We developed corrective model of main feed water flow which is the most important parameter for the precise analysis of turbine cycle performance. Classification model for the identification of feed water flow measurement status was applied to increase the suitability of the corrective model. We used neural network and support vector machine to develop estimation model of main feed water flow with more generalization capability. The estimation model can be used practically to evaluate corrective performance of turbine cycle plant.

• Journal of Power Electronics
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• v.16 no.1
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• pp.374-387
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• 2016

This paper derives an improved analytical model to estimate switching loss and analyze the effects of parasitic elements on the switching performance of SiC MOSFETs. The proposed analytical model considers the parasitic inductances, the nonlinearity of the junction capacitances and the nonlinearity of the trans-conductance. The turn-on process and the turn-off process are illustrated in detail, and equivalent circuits are derived and solved for each switching transition. The proposed analytical model is more accurate and matches better with experimental results than other analytical models. Note that switching losses calculated based on experiments are imprecise, because the energy of the junction capacitances is not properly disposed. Finally, the proposed analytical model is utilized to account for the effects of parasitic elements on the switching performance of a SiC MOSFET, and the circuit design rules for high frequency circuits are given.

• Journal of KIBIM
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• v.8 no.4
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• pp.13-22
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• 2018

Future performance prediction of bridges is challenging task for structural engineers. Well-organized information from design, construction and operation stages is essential for the assessment of structures. Digital twin model is a new concept to realize more reliable data platform for management of infrastructures. Damage history including degradation of material, cracking, corrosion, etc. needs to be accumulated in the digital model. The digital model is linked to the analysis model for the assessment of structural performance considering changed mechanical properties of structural components. In this paper, initial definition digital twin model of a PSC-I girder bridge is proposed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• Fire Science and Engineering
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• v.28 no.2
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• pp.14-19
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• 2014

A current standard exist only on the surface tension in the current domestic wetting agent technology standards, so it is difficult to the performance evaluation of the wetting agent through the standard. So this study presents the optimized performance evaluation methods by scale model experimental equipment in order to present techniques for performance evaluation of wetting agents. The purpose of this study is to investigate validity of experimental results of the self-designed scale model experiment equipment by a comparative analysis of experimental results of the NFPA 18 experiment and the experiment using the self-designed scale model experiment equipment. As a result of a comparative analysis of experimental results of the NFPA 18 experiment that evaluate only the permeation performance on the contton and the experiment using the self-designed scale model experiment equipment that evaluate the permeation performance and fire extinguishing performance on wood flour, the discrimination of the permeation performance was confirmed in both the NFPA 18 experiment and the self-designed scale model experiment equipment. And a result of self-designed experiment equipment have clear discriminatory more than NFPA 18 by internal temperature measurement using the thermocouples.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.244-254
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• 2002

To enhance the acceleration performance and fuel consumption rate of a vehicle, the torque converter is modified or newly-developed with reliable analysis model. Up to recently, the one dimensional performance model has been used for the analysis and design of torque converter. The model is described with constant parameters based on the concept of mean flow path. When it is used in practice, some experiential correction factors are needed to minimize tole estimated error. These factors have poor physical meaning and cannot be applied confidently to the other specification of torque converter. In this study, the detail dynamic model of torque converter is presented to establish the physical meaning of correction factors. To verify the validity of model, performance test was carried out with various input speed and oil temperature. The effect of oil temperature on the performance is analysed, and it is applied to the dynamic model. And, to obtain the internal flow pattern of torque converter, CFD(Computational Fluid Dyanmics) analysis is carried out on three-dimensional turbulent flow. Correction factors are determined from the internal flow pattern, and their variation is presented with the speed ratio of torque converter. Finally, the sensitivity of correction factors to the speed ratio is studied for the case of changing capacity factor with maintaining torque ratio.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.103-109
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• 2011

The ODA(Official Development Assistance) of Korea is growing considerably, and the ODA projects in the technical and vocational education have the good performance to the recipient countries, because they have the direct and quick benefits. But there are no economic model of performance measurement for the ODA in the technical and vocational education. The purpose of this study is to develop the economic model of measuring the performance of the ODA in the technical and vocational education. This study use the ROI model using financial information and the BSC model using non-financial information, and link each model closely. The ROI model using financial information is more relevant, because the benefits of the technical and vocational education are distinct and quick to the recipient groups.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.267-276
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• 2022

Modelling the energy release performance of energetic material combustion in closed systems is of fundamental importance for aerospace and defense application. In particular, to compensate for the disadvantage of the combustion of single energetic material and maximize the benefits, a method of combusting the mixed energetic materials is used. However, since complicated heat transfer occurs when the energetic material is combusted, it is difficult to theoretically predict the combustion performance. Here, we suggest a theoretical model to estimate the energy release performance of mixed energetic material based on the model for the combustion performance of single energetic material. To confirm the effect of parameters on the model, and to gain insights into the combustion characteristics of the energetic material, we studied parameter analysis on the reaction temperature and the characteristic time scales of energy generation and loss. To validate the model, model predictions for mixed energetic materials are compared to experimental results depending on the amount and type of energetic material. The comparison showed little difference in maximum pressure and the reliability of the model was validated. Finally, we hope that the suggested model can predict the energy release performance of single or mixed energetic material for various types of materials, as well as the energetic materials used for validation.