• Journal of Drive and Control
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• v.18 no.3
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• pp.1-7
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• 2021

In a hydraulic control system, since a hydraulic cylinder drives a relatively large mass of an object, an external load force acts as a disturbance on the control performance of the system. Additionally, as the hydraulic system is used for a long period, there are disturbances that occur gradually, such as a drop in supply pressure because of abrasion of the pump, oil leakage from a valve, and oil leakage from a cylinder. In this study, a state feedback controller based on a linearization technique is applied. To prevent the performance degradation of the controller from the load disturbance, an Extended Luenberger observer (ELO) is used for the Extended system. The case of using the proportional controller, which is a representative linear controller, and the result of using the controller designed in this study are compared and reviewed through simulation. Also, we propose an experimental gain-setting method for a state feedback controller that can be used at industrial sites, and examine how the stability and control performance of the system changes because of the disturbance inputs through the experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1335-1342
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• 2013

Subway is electrified railway system nowadays, in which liquid dielectric transformers have been widely used, though mold type transformers are replacing it. The transformers supplies large electric power and have innate hazards causing accidents under operation. A number of researcher have carried out on failures of it and have oriented to identify transformer's failure causes and how to maintain it healthy state. The transformer failures can cause serious accidents which can provoke economic loss and leads persons to kill. In this paper, we carried out a safety activity to reveal hazards and to estimate risk of subway liquid dielectric transformers using FMEA, HAZOP and What-if methods. In case of installing safety devices in oil immersed transformer, we tried to evaluate an effect on a subsystem's failure rate. We proposed how to design subsystem failure rate and safety device failure rates.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.72-80
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• 2013

For the proper cooling of in-wheel motor, the cooling channel should have the characteristics which are low pressure drop and adequate cooling oil supply to motor part. In this study, the flow performance of cooling channel for in-wheel motor was evaluated and the shape of the channel was optimized. First, the pressure drop and flow distribution characteristics of the initial channel model were evaluated using numerical analysis. Also, by the result of analysis and design modification, 4 design parameters of the channel were selected. Second, using the Taguchi optimal method, the cooling channel was optimized. In the method, nine models with different levels of the design parameters were generated and the flow characteristics of each models was estimated. Base on the result, the main effect of the design parameters was founded and optimized model was obtained. For the optimized model, the pressure drop and oil flow rate were about 0.196 bar and 0.207 L/min, respectively. The pressure drop decreased by about 0.3 bar and the oil flow rate to the motor part increased by about 0.2 L/min compared to the initial model.

• Steel and Composite Structures
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• v.49 no.6
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• pp.645-666
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• 2023

Due to the steadily declining supply of natural coarse aggregates, the concrete industry has shifted to substituting coarse aggregates generated from byproducts and industrial waste. Oil palm shell is a substantial waste product created during the production of palm oil (OPS). When considering the usage of OPSC, building engineers must consider its uniaxial compressive strength (UCS). Obtaining UCS is expensive and time-consuming, machine learning may help. This research established five innovative hybrid AI algorithms to predict UCS. Aquila optimizer (AO) is used with methods to discover optimum model parameters. Considered models are artificial neural network (AO - ANN), adaptive neuro-fuzzy inference system (AO - ANFIS), support vector regression (AO - SVR), random forest (AO - RF), and extreme gradient boosting (AO - XGB). To achieve this goal, a dataset of OPS-produced concrete specimens was compiled. The outputs depict that all five developed models have justifiable accuracy in UCS estimation process, showing the remarkable correlation between measured and estimated UCS and models' usefulness. All in all, findings depict that the proposed AO - XGB model performed more suitable than others in predicting UCS of OPSC (with R², RMSE, MAE, VAF and A_15-index at 0.9678, 1.4595, 1.1527, 97.6469, and 0.9077). The proposed model could be utilized in construction engineering to ensure enough mechanical workability of lightweight concrete and permit its safe usage for construction aims.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.1
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• pp.16-22
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• 2009

In order to investigate $CO_2$ heat transfer coefficient and pressure drop by PAG oil concentration during $CO_2$ evaporation, the experiment on evaporation heat transfer characteristics in a mini-channels were performed. The experimental apparatus consisted of a test section, a DC power supply, a heater, a chiller, a mass flow meter, a pump and a measurement system. Experiment was conducted for various mass fluxes($300{\sim}800kg/m^{2}s$), heat fluxes($10{\sim}40kW/m^2$) saturation temperatures($-5{\sim}5^{\circ}C$), and PAG oil concentration(0, 3, 5wt%). The variation of the heat transfer coefficient was different according to the oil concentration. With the increase of the oil concentration, the evaporation heat transfer coefficient decreased and the delay of dryout by oil addition was found. Pressure drop increased with the increase of the oil concentration and heat flux, and the decrease of saturation temperature.

• Proceedings of the KIEE Conference
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• 2008.10c
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• pp.218-220
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• 2008

Urban air quality, including carbon-dioxide emissions, and national energy security are related issues affecting the rail industry and transportation sector as a whole. They are related by the fact that (in the United States) 97-98% of the energy for the transport sector is based on oil, and more than 60% is imported. A fuelcell locomotive combines the environmental advantages of a catenary-electric locomotive with the higher overall energy efficiency and lower infrastructure costs of a diesel-electric. Catenaryelectric locomotives, when viewed as only one component of a distributed machine that includes an electricity-generating plant and transmission lines, are the least energy-efficient locomotive type. The natural fuel for a fuelcell is hydrogen, which can be produced from many renewable energies and nuclear energy, and thus a hydrogen-fuelcell locomotive will not depend on imported oil for its energy supply. This paper proposes a base models of Hybrid fuel cell/IPT railway vehicle power system, the necessary of this research.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.3
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• pp.107-111
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• 2011

This carbon nano heating system was consisted of power supply equipment, a carbon fiber and a stainless flexible hose. carbon nano heating system was manufactured by carbon fiber of a power capacity 30kw/h and light-oil hot air heater in control plot was the heating capacity 30,000kcal/h, As the result, Temperature difference due to carbon nano heating system and hot air heater in greenhouse showed that air temperature at experimental greenhouse, comparison greenhouse were $14.8^{\circ}C$, $13.4^{\circ}C$ respectively. It was found that carbon nano heating system and light-oil hot air heater heating cost were 1,095,740won, 2,683,628won. therefore as heating cost saving 60%. Yield of tomatoes cultured in greenhouse using carbon nano heating pipe was 4% inclease. Economic analysis comparison between the carbon nano heating pipe and the hot air heater in greenhouse were 41% respectively.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.27-33
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• 2004

Electro-theological fluid is recently used for the micro polishing of 3-dimensional micro-aspherical lens. It's also used for polishing small area defects on the wide flat wafer. Since ER fluid shows a behavior of viscosity changing under certain electric fields. micro polishing efficiency may be enhanced for certain cases. In this paper, a perfluorinated carbonyl fluoride oil based ER fluids was used to improve surface polishing rate and submicron-scale accuracy. As the polishing electrodes, micro size cylindrical tools had been used for maximizing the electric field. An experimental device, which was applied for micro polishing a number of wafers of 4inches in size and other workpiece. was made on a precision polishing system. It consisted of a steel electrode. a wafer fixture. l0㎃ current and DC 5㎸ power supply unit, and a controller unit. From the Experiments. the ER fluid is applicable for micro polishing of small parts.

• Tribology and Lubricants
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• v.14 no.3
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• pp.24-31
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• 1998

A new type squeeze film damper is proposed and its dynamic characteristics are investigated experimentally. The new one has a pulsating flow supply system which properly adds high pressure oil to the oil film of the damper so that the rotor vibration can be controlled actively. As the result, the amplitude of the rotor vibration can be reduced considerably. The algorithm which compensates the phase lag of servo valve as well as the high-performance servo valve are required in order that a new type squeeze film damper can be more effective device to attenuate the rotor vibration than typical one.