• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.835-842
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• 2003

A three dimensional numerical analysis has been conducted for a stoker type incinerator which has the capacity of 1.5 ton/hr. The objective of the present study is to predict the effects of swirl induced by secondary air and to find an optimal operating condition of the incinerator. In this study, combustion characteristics such as distributions of temperature, velocity and concentration of each species have been examined with various injection types of secondary air and with different flow rates of secondary air in the incinerator. It is found that the secondary air injection on the combustion process makes the path of fluid particle longer in the combustor and enhances the mixing between air and combustion gas by arousing a swirl. Therefore, the injection type of secondary air can be an important key in the design process of incinerator.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.34-41
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• 2020

Ready-mixed concrete is unconsolidated concrete typically transported to construction sites by using mixer trucks. A proper rotation of concrete is necessary to prevent its solidification in mixer trucks during transport: in accordance with the manufacturing method and quality inspection prescribed in KSF4009, this movement is maintained after the manufacturing of concrete in professional production plants and the addition of water, solid materials, and admixtures. Unfortunately, mixer truck parts wear out over long periods of time. In order to improve the wear resistance of the main part of mixer trucks, we used a steel plate with good wear resistance or partially added a reinforcement plate. In this study, we first tested the properties of concrete (as required for the DEM), and then carried out mixing and discharge simulations to define the actual operating conditions of mixer trucks. For each condition, we calculated the amount and location of wear. The reliability of our results was finally verified by comparing them with the measurement values. Overall, this study provided basic data for an optimal design of mixer trucks: one that would reduce the vehicles' weight and production costs.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.5
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• pp.258-263
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• 2004

The purpose of this experiment is to modify diagnosis criterion of isothermal relaxation current(IRC) measurement equipment which is using for distribution cable diagnosis. We're using this system for several years in the field instead of DC leakage current measurement and lots of cables were replaced. But we have to investigate on the reliability of this equipment for our cables because we didn't carried out condition assessment of extracted cables after field diagnosis by this equipment. It is important thing for cable maintenance. If the replacement criterion is improper we can not prevent failures or will waste budget on account of replacement of the sound cables. In this paper we selected field installed cables and injected silicone fluid to the cables for insulation rehabilitation. In order to prove reliability of the diagnosis equipment we compared diagnosis results and AC breakdown strength according to operating time after silicone treatment. This is the results of the field test for 1 year.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.26-28
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• 2009

This paper proposes maximum torque control of IPMSM drive using adaptive teaming mechanism-fuzzy neural network (ALM-FNN) controller, model reference adaptive fuzzy tonal(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using ALM-FNN, MFC and ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN, MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, MFC and ANN controller.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.155-157
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive learning mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.51-59
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• 2019

Flow forming is an eco-friendly and high-efficiency plastic deformation process with fewer chips during a process which is specifically used to manufacture seamless tubular products like tire wheels, rocket motor cases etc. On the development of mortar barrel using Inconel718 tube, some flow formed products had dimensional errors on their thickness. In this study, our purpose is to optimize the process conditions with the smallest dimensional error. In order to find an optimum process condition, 2D axisymmetric FEM simulation analyses with Taguchi method were conducted. Geometric variables (attack angle, flatting angle, roller nose radius) and operating parameters (depth of forming, feed rate) are considered as control factors. Forward flow forming with single roller was first analyzed to determine the effective factors using AFDEX software and attack angle of the roller was identified as the most influential factor. Also, the nose radius of the rollers was confirmed as a significant factor in multi-rollers flow forming system. The effect of rollers offset values are also studied and finally, we proposed optimal conditions to improve the accuracy of flow forming process with Inconel718 tube for mortar barrel manufacturing.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.219-220
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• 2008

The paper is proposed maximum torque control of SynRM drive using adaptive fuzzy neuro inference system(AFNIS) and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled AFNIS and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the AFNIS and ANN controller.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.367-372
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• 2018

The objective of this paper is to optimize the cross-section of aluminum decking units used in the bass boats under operating conditions, and to verify the optimized model from the results via by ANSYS software. Aluminum decking unit is needed to endure specific loading while leisure activity and sailing. For a stiffer and more cost-neutral aluminum decking unit, optimization is often considered in the naval and marine industries. This optimization of the aluminum decking unit is performed using the ANSYS program, which is based on the topology optimization method. The generation of finite element models and stress evaluations are conducted using the ANSYS Multiphysics module, which is based on the Finite Element Method (FEM). Through such a series of studies, it was possible to determine the most suitable case for satisfying the structural strength found among the phase-optimized aluminum deck units in bass boats. From these optimization results, CASE 1 shows the best solution in comparison with the other cases for this optimization. By linking the topology optimization with the structural strength analysis, the optimal solution can be found in a relatively short amount of time, and these procedures are expected to be applicable to many fields of engineering.