• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.443-446
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• 2003

Conventional disturbance rejection methods have to derive the inverse model of a system. However, the inverse model of n nonholonomic system is not unique, because an inverse it changes depending on initial conditions and desired values. A kind of internal model control (IMC) using feedback error learning is discussed for the motion control of nonholonomic mobile robots in this paper, The present method is different from a conventional IMC whose control system consists of an inverse model, a direct model and a filter. The present disturbance rejection method need not use a direct model, where the remaining two elements are composed of the same inverse model based on neural networks.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.1
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• pp.83-88
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• 2018

Engineering is a sector with more than three times the industrial effectiveness of manufacturing. In the domestic engineering life cycle, the Operations & Maintenance (O&M) phase is a relatively high level of technology. Based on accumulated knowledge of O&M phase, it is necessary to advance operating technology and expand overseas O&M market expenditure. This study is the early stage of knowledge-based power plant O&M service framework reference model. In this study, we propose a conceptual model of architecture framework for power plant O&M. We survey the architecture framework and reference model and propose conceptual model of architecture framework for power plant O&M. The conceptual model of architecture framework for power plant O&M consists of stakeholder, O&M scenario, O&M technology. In particular, the O&M technology is defined as the fourth industrial revolution intelligence information technology. We defined a meta model from the conceptual model to define the power plant O&M architecture framework. In the future, we intend to development an architecture framework from the conceptual model and meta model.

• Journal of Ocean Engineering and Technology
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• v.27 no.4
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• pp.33-44
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• 2013

IIn this study, a wave-surge-tide coupling numerical model was developed to consider nonlinear interaction. Then, this model was applied and calculations were made for a storm surge on the southeast coast. The southeast coast was damaged by typhoon "Maemi" in 2003. In this study, we used a nearshore wind wave model called SWAN (Simulating WAves Nearshore). In addition, the Meyer model was used for the typhoon model, along with an ocean circulation model called POM (Princeton Ocean Model). The wave-surge-tide coupling numerical model could calculate exact parameters when each model was changed to consider the nonlinear interaction.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.5
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• pp.486-493
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• 2015

In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

• Applied Chemistry for Engineering
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• v.23 no.2
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• pp.204-209
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• 2012

In this study, kinetics data was obtained for steam reforming reaction of ethane over the commercial ruthenium catalyst. The variables of ethane steam reforming were the reaction temperature, partial pressure of ethane, and steam/ethane mole ratio. Parameters for the power rate law kinetic model and the Langmuir-Hinshelwood model were obtained from the kinetic data. Also, sizing of steam reforming reactor was performed by using PRO/II simulator. The reactor size calculated by the power rate law kinetic model was bigger than that of using the Langmuir-Hinshelwood model for the same conversion of ethane. Reactor size calculated by the Langmuir-Hinshelwood model seems to be more suitable for the reactor design because the Langmuir-Hinshelwood model was more consistent with the experimental results.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1069-1072
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• 1996

In modern control engineering, the model following system is a typical method. The model following system's performance is due to algorithm of control law, accuracy of modeling to the plant, and dynamics of the reference model. But the determination of the reference model depends on knowledge of an expert. Using an expert system, the determination method of the reference model was proposed in this paper. So, the reference model can be selected by user who has no Knowledge of dynamics and parameters.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.79-89
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• 2022

Soil moisture is significantly related to crop growth and plays an important role in irrigation management. To predict soil moisture, various process-based model has been developed and used in the world. Various models (Land surface model) may have different performance depending on the model parameters and structures that causes the different model output for the same modeling condition. In this study, the three land surface models (Noah Land Surface Model, Soil Water Atmosphere Plant, Community Land Model) were used to compare the model performance (soil moisture prediction) and develop the multi-model simulation. At first, the genetic algorithm was used to estimate the optimal soil parameters for each model, and the parameters were used to predict soil moisture in the study area. Then, we used the multi-model approach based on Bayesian model averaging (BMA). The results derived from this approach showed a better match to the measurements than the results from the original single land surface model. In addition, identifying the strengths and weaknesses of the single model and utilizing multi-model methods can help to increase the accuracy of soil moisture prediction.

• Earthquakes and Structures
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• v.17 no.5
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• pp.489-499
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• 2019

Elastic-plastic behavior of nuclear power plant elbow piping under seismic loads has been conducted in this study. Finite element analyses are performed using classical Bilinear kinematic hardening model (BKIN) and Multilinear kinematic hardening model (MKIN) as well as a nonlinear kinematic hardening model (Chaboche model). The influence of internal pressure and seismic loading on ratcheting strain of elbow pipe is studied by means of the three models. The results found that the predicted results of Chaboche model is maximum, closely followed by the predicted results of MKIN model, and the minimum is the predicted results of BKIN model. Moreover, comparisons of analysis results for each plasticity model against predicted results for a equivalent cyclic loading elbow component and for a simplified piping system seismic test are presented in the paper.