• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.70-73
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• 1996

Many researchers had considered biological systems as linear systems. In many cases of biological systems, the phenomena that show the regular and periodic dynamics are considered the normal state. However, some clinical experiments reported, in some cases, the periodic signals represented the abnormal state. We assume that signals from human body system are generated from deterministic, intrinsic mechanisms and can be represented a simple equation that show nonlinear dynamics dependent on control parameters. The objective of our study is to model a nonlinear dynamics correctly from the nonlinear time series using the genetic programming method; to find a simple equation of nonlinear dynamics using collected time series and its nonlinear characteristics. We applied genetic programming to model RR interval of ECG that shows chaotic phenomena. We used 4 statistic measures and 2 fractal measures to estimate fitness of each chromosome, and could obtain good solutions of which chaotic features are similar.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.05a
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• pp.121-123
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• 2001

• Proceedings of the Korean Magnestics Society Conference
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• 2012.05a
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• pp.8-8
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• 2012

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.1-11
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• 1998

In this work, we propose a modeling method based on an artifical intelligence technique for a stem generator in a nuclear power plant. Modeling the steam generator is known to be difficult due to several facts; especially, the dynamics of the steam generator is nonminimum phase which is mainly caused by the swell and shrink phenomena from thermal effects. In order to overcome this difficulty, we adopt so-called logic processor whose structure itself has a logical meaning to be easily established and also efficiently learned. Such a manner, we could derive an useful model simulating the dynamics of the steam generator in a nuclear power plant.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.10
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• pp.840-845
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• 2012

An ARX(Auto-Regressive eXogenous) modeling technique for vortex dynamics in the BFS(Backward Facing Step) flow field is proposed in this paper. In order for the modeling of the dynamics, the spatial and temporal modes are extracted through POD(Proper Orthogonal Decomposition) analysis. Determining the orders of the inputs and outputs for an ARX structure is carried out by the spectrum analysis and temporal mode analysis, respectively. The order of input delay terms is also determined by the flow velocity. Finally the coefficients of the ARX model are designed by using an artificial neural network.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.113-121
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• 2014

In this work, an integrated model including molecular dynamics and chemical rate theory was implemented to calculate the growth of point defect clusters(PDC) and copper-rich precipitates(CRP) which could change the mechanical properties of reactor pressure vessel(RPV) steels in a nuclear power plant. A number of time-dependent differential equations were established and numerically integrated to estimate the evolution of irradiation defects. The calculation showed that the concentration of the vacancies was higher than that of the self-interstitial atoms. The higher concentration of vacancies induced a formation of the CRPs in the later stage. The size of the CRPs was used to estimate the mechanical property changes in RPV steels, as is the same case with the PDCs. The calculation results were compared with the measured values of yield strength change and Charpy V-notch transition temperature shift, which were obtained from the surveillance test data of Korean light water reactors(LWRs). The estimated values were in fair agreement with the experimental results in spite of the uncertainty of the modeling parameters.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.5
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• pp.635-642
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• 2011

Hydraulic efficiency was a vital component in evaluating the disinfection capability of clearwell. Current practice evaluates these system based on the tracer test only. In this paper, CFD(Computational Fluid Dynamics) was applied on the clearwell for alternating or supplementing the tracer test. The baffle factor derived from the CFD modeling closely matched the values obtained from full scale tracer testing. And, for suggesting proper numerical model in clearwell; the turbulence model, discretization scheme, convergence criteria were investigated through separate simulation runs. The model validation was conducted by comparing the simulated data with experimental data. In the turbulence model, the realizable ${\kappa}-{\varepsilon}$ model and the standard ${\kappa}-{\varepsilon}$ model were found to be more appropriate than RNG ${\kappa}-{\varepsilon}$ model. The residuals of convergence criteria should be used as not $10^{-3}$ but $10^{-4}$ or $10^{-5}$. In discretization scheme, the difference of simulated values in 1st, 2nd, 3rd upwind scheme was found to be insignificant. Moreover, the result of this study suggest that CFD modeling can be a reliable alternative to tracer testing for evaluating the hydraulic efficiency.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.3
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• pp.206-221
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• 2015

Supercavitation is a modern technique which can be used to surround an underwater vehicle with a bubble in order to reduce the resistance of the vehicle. When the vehicle is at low speed in the deep sea, the cavitation number is relatively big and it is difficult to generate a cavity large enough to envelope the vehicle. In this condition, the artificial cavity, called ventilated cavity, can be used to solve this problem by supplying gas into the cavity and can maintain supercavitating condition. In this paper, a relationship between the ventilation gas supply rate and the cavity shape is determined. Based on the relationship a ventilation rate control is developed to maintain the supercavitating state. The performance of the ventilation control is verified with a depth change control. In addition, dynamics modeling for the supercavitating vehicle is performed by defining forces and moments acting on the vehicle body in contact with water. Simulation results show that the ventilation control can maintain the supercavity of an underwater vehicle at low speed in the deep sea.

• Journal of Ecology and Environment
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• v.29 no.4
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• pp.343-352
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• 2006

This study investigated the relationship between land cover and the water quality variables in the rivers, which are located in the Yamaguchi prefecture of West Japan. The study area included 12 catchments covering $5,809\;Km^2$. pH, dissolved oxygen, suspended solid, E. coli, total nitrogen and total phosphorus were considered as river water quality variables. Satellite data was applied to generate land cover map. For linking alterations in land cover (at whole catchment and buffer zone levels) and the river water quality variables, multiple regression modeling was applied. The results indicated that non-spatial attribute (%) of land cover types (at whole catchment level) consistently explained high amounts of variation in biological oxygen demand (72%), suspended solid (72%) and total nitrogen (87%). At buffer zone-scale, multiple regression models that were developed to represent the linkage between the alterations of land cover and the river water quality variables could also explain high level of total variations in suspended solid (86%) and total nitrogen (91%).

• Coupled systems mechanics
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• v.11 no.1
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• pp.79-91
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• 2022

Models for water treatment processes include simulation, i.e., modelling of water quality, flow hydraulics, process controls and design. Water treatment processes are inherently dynamic because of the large variations in the influent water flow rate, concentration and composition. Moreover, these variations are to a large extent not possible to control. Mathematical models and computer simulations are essential to describe, predict and control the complicated interactions of the water treatment processes. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. The main objective is to combine knowledge of the process dynamics with mathematical methods for processes estimation and identification. Good modelling practice is way to obtain this objective and to improve water treatment processes(its understanding, design, control and performance- efficiency). By synthesize of existing knowledge and experience on good modelling practices and principles the aim is to help address the critical strategic gaps and weaknessesin water treatment models application.