• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.147-150
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• 2004

In order to describe the mechanical behavior of highly anisotropic and asymmetric materials such as fiber­reinforced composites, the elastic-plastic constitutive equations were used here based on the recently developed yield criterion and hardening laws. As for the yield criterion, modified Drucker-Prager yield surface was used to represent the orthotropic and asymetric properties of composite materials, while the anisotropic evolution of back­stress was accounted for the hardening behavior. Experimental procedures to obtain the material parameters of the hardening laws and yield surface are presented for 3D Circular Braided Glass Fiber Reinforced Composites. For verification purpose, comparisons of finite element simulations using the elastic-plastic constitutive equations, anisotropic elastic constitutive equations and experiments were performed for the three point bending tests. The results of finite element simulations showed good agreements with experiments, especially for the elastic-plastic constitutive equations with yield criterion considering anisotropy as well as asymmetry and anisotropic back stress evolution rule.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.2127-2132
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• 2003

A computational study is performed to better understand the choke phenomenon of unsteady gas flow through a critical nozzle. The axisymmetric, unsteady, compressible, Navier-Stokes equations are solved using a finite volume method. In order to simulate the effects of back pressure fluctuations on the critical nozzle flow, a forced sinusoidal pressure wave is assumed downstream the exit of the critical nozzle. It's frequency is 20kHz and amplitude is varied below 15% of time-mean back pressure. The results obtained show that for low Reynolds numbers, the unsteady effects of the pressure fluctuations can propagate upstream of the throat of critical nozzle, and thereby giving rise to applicable fluctuations of mass flow through the critical nozzle. The effect of the amplitude of the excited pressure fluctuations on the choke phenomenon is discussed in details.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.4
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• pp.36-43
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• 2007

Dieless CNC forming is an innovative technology which can form various materials with complex shape by numerically controlled incremental forming process. In order to apply the technology to industrial parts, however, many problems such as spring-back, rising of material, and trimming difficulty must be solved. In this paper a new dieless CNC forming method to improve forming quality is proposed, which consists of how to modify its original shape in CAD and how to generate its CNC tool path in CAM. The effectiveness of the proposed procedures is tested with a brake dust shield of a vehicle. The results shows that the method proposed enhances the forming quality up to 48% compared to traditional method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• New & Renewable Energy
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• v.9 no.1
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• pp.44-50
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• 2013

In order to analyze the characteristics of tidal current power generation system, we measured the output power according to the stream velocity by a water tunnel system and a simulation in MATLAB/Simulink. The water tunnel system consisted of impeller tidal flow transducer and PMSG with rotor in the water. The simulation consisted of PMSG, the tidal current turbine, and back-to-back converter. Also, we simulated the characteristics of output power according to the change of blade length and angular velocity.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.28-33
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• 2000

The monitoring of the chatter vibration is necessarily required to do automatic manufacturing system. To this study, we constructed a sensing system using tool dynamometer in order to the chatter vibration on cutting process. And a approach to a neural network using the feature of principal cutting force signals is proposed. with the error back propagation training process, the neural network memorized and classified the feature of principal cutting force signals. As a result, it is shown by neural network that the chatter vibration can be monitored effectively.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.53-68
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• 2009

In this paper, we address a problem for minimizing the number of items inspected in a back-light-unit (BLU) inspection system, which includes a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective, we make a steady-state flow analysis between nodes (or shops), and derive the steady-state amount of flows between nodes and defective rates by solving a nonlinear balance equation. We provide an enumeration method for determining an optimal value of K which minimizes the number of items inspected. Our methodology could be applied and extended to similar situations with slight modification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1519-1525
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• 2014

This paper presents the shape design for reducing cogging torque and characteristic analysis in Brushless DC (BLDC) motor. In this BLDC motor, ${\Delta}$(delta)-winding is applied, and in order to obtain the $60^{\circ}$ trapezoidal phase back-EMF waveform, permanent magnet shape design is carried out. And then, a method on specifying design parameters to effectively reduce cogging torque is developed. back-EMF, input voltage and input current which are analyzed by the Finite Element Method (FEM) are validated by experimental results. Also, efficiency calculations based on analysis and experimental results are performed and analyzed.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.119-135
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• 2010

In this paper, we readdress the optimization problem for minimizing the inspection cost in a back-light unit inspection system, which forms a network including a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective function when the system is in a steady state, assuming that the number of nonconforming items in a lot follows a binomial distribution when a lot is formed for inspection, we make a steady-state network flow analysis between shops, and derive the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration method for determining an optimal value of K which minimizes our objective function. In addition, we compare our results numerically with previous ones.