• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.421-428
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• 2014

For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.191-196
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• 2016

Recently, power dissipation is a very significant issue not only in embedded systems and mobile devices but also in high-end modern processors. Especially, by the prevalent use of smart phones and tablet PCs, low power consumption of microprocessors is requisite. In this paper, a fast power measurement tool for a high performance microprocessor based on the trace-driven simulator has been developed. The power model of the microprocessor consists of complex combinational circuits, array structures, and CAM structures. Using SPEC 2000 benchmarks as input, the trace-driven simulation has been performed to estimate the average power dissipation of each program.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1251-1256
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• 2014

The use of lubrication oil is of many purposes and one among them is to drive the engine mounted on a ship. Hence the supply of clean lubrication oil is important. And an oil purifier is one of key components in marine diesel engines. At present, the element type full-flow oil filter has been widely used for cleaning the engine oil. The self-driven centrifugal oil purifier is a device which is used to remove the impurities in lubrication oil using a jet flow. The flow characteristics and the physical behaviors of particles in this self-driven oil purifier were investigated numerically and the filtration efficiencies were evaluated. For calculations, a Computational Fluid Dynamics method is used and the Shear Stress Transport turbulence model has been adopted. The Multi Frames of Reference method is used to consider the rotating effect of the flows. The influence of centrifugal forcehas been numerically investigatedto improve filtration efficiency of tiny particles. As a result of this research, it was found that the particle filtration efficiency using the only center axis rotating and outer wall rotating system are higher than that of the fully rotating system in the self-driven oil purifier.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.201-210
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• 2010

In this study, new methodology to estimate the reliability of a water distribution system using HSPDA model is suggested. In general, the reliability of a water distribution system can be determined by estimating either the ratio of the required demand to the available demand or the ratio of the number of nodes with sufficient pressure head to the number of nodes with insufficient pressure head when the abnormal operating condition occurs. To perform this approach, hydraulic analysis under the abnormal operating condition is essential. However, if the Demand-Driven Analysis (DDA) which is dependant on the assumption that the required demand at a demand node is always satisfied regardless of actual nodal pressure head is used to estimate the reliability of a water distribution system, the reliability may be underestimated due to the defect of the DDA. Therefore, it is necessary to apply the Pressure-Driven Analysis (PDA) having a different assumption to the DDA's which is that available nodal demand is proportion to nodal pressure head. However, because previous study used a semi-PDA model and the PDA model which had limited applicability depending on the characteristics of a network, proper estimation of the reliability of a water distribution system was impossible. Thus, in this study, a new methodology is suggested by using HSPDA model which can overcome weak points of existing PDA model and Available Demand Fraction (ADF) index to estimate the reliability. The HSPDA can simulate the hydraulic condition of a water distribution system under abnormal operating condition and based on the hydraulic condition simulated, ADF index at each node is calculated to quantify the reliability of a water distribution system. The suggested model is applied to sample networks and the results are compared with those of existing method to demonstrate its applicability.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.533-541
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• 2005

In this paper, a wind turbine with power splitting transmission, which is realized through a novel three-shaft planetary, is presented. The input shaft of the transmission is driven by the rotor of the wind turbine, the output shaft is connected to the grid via the main generator (asynchronous generator), and the third shaft is driven by a control motor with variable speed. The dynamic models of the sub systems of this wind turbine, e.g. the rotor aerodynamics, the drive train dynamics and the power generation unit dynamics, were given and linearized at an operating point. These sub models were integrated in a multidisciplinary dynamic model, which is suitable for control syntheses to optimize the utilization of wind energy and to reduce the excessive dynamic loads. The important dynamic behaviours were investigated and a wind turbine with a soft main shaft was recommend.

• Annual Conference of KIPS
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• 2006.05a
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• pp.1325-1328
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• 2006

본 논문에서는 RTOS 기반 임베디드 소프트웨어 개발에 적합한 모델기반 방법론을 제안하고 이와 함께 개발된 자동코드생성 도구를 기술한다. 현재까지 알려진 대표적인 모델기반 방법론으로는 OMG (Object Management Group)의 MDA (Model-Driven Architecture)가 있으며, MDA 에서는 EJB, 웹서비스,.NET, 그리고 CORBA 와 같은 미들웨어 플랫폼을 대상으로 하는 응용 소프트웨어의 개발을 지원한다. 하지만, 통상적인 임베디드 시스템은 실시간성에 대한 요구조건은 물론 성능과 자원활용에 있어 많은 제약을 가짐에 따라 상당수의 임베디드 시스템은 미들웨어를 사용하지 않고 RTOS 상에서 직접 수행되도록 개발되고 있다. 이에 따라 본 연구에서는 MDA 방법론을 확장하여 플랫폼 의존적인 모델 (PSM, Platform Specific Model) 단계에서 추상화된 RTOS 행위를 표현할 수 있도록 추상 RTOS API (Generic RTOS API)를 정의하고, 아울러 추상화된 RTOS 행위를 자동으로 변환하여 C 코드를 생성해주는 도구인 TransPI 를 함께 제시한다.

• Journal of computational fluids engineering
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• v.8 no.2
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• pp.57-63
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• 2003

Two nonlinear κ-ε models with the wall function method are applied to the fully developed turbulent flow in a square duct. Typical predicted quantities such as axial and secondary velocities, turbulent kinetic energy and Reynolds stresses are compared in details both qualitatively and quantitatively with each other. A nonlinear κ-ε model with the wall function method capable of predicting accurately duct flows involving turbulence-driven secondary motion is presented in the present paper. The nonlinear κ-ε model of Shih et al.[1] adopted in a commercial code is found to be unable to predict accurately duct flows with the prediction level of secondary flows one order less than that of the experiment.

• Wind and Structures
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• v.9 no.2
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• pp.159-178
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• 2006

For the slender and flexible cable supported bridges, identification of all the flutter derivatives for the vertical, lateral and torsional motions is essential for its stability investigation. In all, eighteen flutter derivatives may have to be considered, the identification of which using a three degree-of-freedom elastic suspension system has been a challenging task. In this paper, a system identification technique, known as covariance-driven stochastic subspace identification (COV-SSI) technique, has been utilized to extract the flutter derivatives for a typical bridge deck. This method identifies the stochastic state-space model from the covariances of the output-only (stochastic) data. All the eighteen flutter derivatives have been simultaneously extracted from the output response data obtained from wind tunnel test on a 3-DOF elastically suspended bridge deck section-model. Simplicity in model suspension and measurements of only output responses are additional motivating factors for adopting COV-SSI technique. The identified discrete values of flutter derivatives have been approximated by rational functions.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.233-242
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• 2014

A magnetically levitated vehicle (Maglev) system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS) formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.