• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.441-446
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• 2000

Although the net-shape molding of composites is generally recommended, molded composites frequently required cutting or grinding due to the dimensional inaccuracy for precision machine elements. During the composite machining operations such as cutting and grinding, the temperature at the grinding area may increase beyond the allowed limit due to the low thermal conductivity of composites, which might degrade the matrix of composite. Therefore, in this work, the temperature at the grinding point during surface grinding of carbon fiber epoxy composite was measured. The grinding temperature and surface roughness were also measured to investigate the surface grinding characteristics of the composited. The experiments were performed both under dry and wet grinding conditions with respect to cutting speed, feed speed, depth of cut and stacking angle. From the experimental investigation, the optimal conditions for the composite plain grinding were suggested.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.418-423
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• 2008

Among various sensitivity evaluation techniques, semi-analytical method is quite popular since this method is more advantageous than analytical method and global finite difference method. However, SAM reveals severe inaccuracy problem when relatively large rigid body motions are identified for individual elements. Such errors result from the numerical differentiation of the pseudo load vector calculated by the finite difference scheme. In the present study, the adjoint variable method combined with complex variable is proposed to obtain the shape and size sensitivity for structural optimization. The complex variable can present accurate results regardless of the perturbation size as well as easy to be implemented. Through a few numerical examples of the static problem for the structural sensitivity, the efficiency and reliability of the adjoint variable method combined with complex variable is demonstrated.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.66-73
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• 1996

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise control(ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.686-691
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• 2001

Structural optimization often require the evaluation of design sensitivities. The Semi Analytic method(SAM) is popular for shape optimization because this method has several advantages. But when relatively large rigid body motions are identified for individual elements, the SA method shows severe inaccuracy. In this paper, the improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes. Moreover, the error of the SA method caused by numerical difference scheme is alleviated by using a series approximation for the sensitivity derivatives and considering the higher order terms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.585-592
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• 2003

Among various sensitivity evaluation techniques, semi-analytical method(SAM) is quite popular since this method is more advantageous than analytical method(AM) and global finite difference method(FDM). However, SAM reveals severe inaccuracy problem when relatively large rigid body motions are identified fur individual elements. Such errors result from the numerical differentiation of the pseudo load vector calculated by the finite difference scheme. In the present study, an iterative method combined with mode decomposition technique is proposed to compute reliable semi-analytical design sensitivities. The improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes and the error of SAM caused by numerical difference scheme is alleviated by using a Von Neumann series approximation considering the higher order terms for the sensitivity derivatives.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.593-600
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• 2003

Structural optimization often requires the evaluation of design sensitivities. The Semi Analytic Method(SAM) fur computing sensitivity is popular in shape optimization because this method has several advantages. But when relatively large rigid body motions are identified for individual elements. the SAM shows severe inaccuracy. In this study, the improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes. Moreover. the error of the SAM caused by numerical difference scheme is alleviated by using a series approximation for the sensitivity derivatives and considering the higher order terms. Finally the present study shows that the refined SAM including the iterative method improves the results of sensitivity analysis in dynamic problems.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1870-1875
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• 2003

Optimization has been used in many engineering problems and must be one of the essential components during design process now. It is the process of maximizing the performance called an objective function of a system while satisfying some constraints, so finite element method is generally required in order to obtain these values during optimization. However, there are some difficulties to obtain them by means of FEM, where the changes of design variables cause the distortion and the regeneration of mesh that may result in inaccuracy and inefficiency. In order to overcome this problem, this paper proposed an alternative that the eXtended FEM introduced and developed by Ted Belytschko was applied to the optimization process because the key points of the X-FEM lie in that the discontinuity can be represented independently on the mesh by a function called in an enrichment function.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.6
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• pp.522-529
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• 2014

This study proposes an isolation amplifier circuit for the sensing and feedback of inverter DC-link voltage, which is inevitable for the precise control of inverter output voltage. The isolation amplifier consists of a pulse-width modulator and a pulse transformer with dual secondary windings. The accuracy of the proposed circuit depends on the precise matching of filter parameters in dual secondary circuits. The influences of parameter inaccuracy on the amplifier performances are analyzed. A modified circuit is proposed to reduce the dependency on filter parameters. The validity of the proposed method is verified through simulation and experiment.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1278-1287
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• 2017

Inverters are widely used in distributed power generation and other applications. However, their lack of inertia and variable impedance may cause system instability and power transfer inaccuracy. This paper proposes a control scheme for a single phase voltage-controlled inverter with some grid-friendly characteristics. The proposed control algorithm enables the inverter to function as a voltage source with an inner output impedance in both the islanded and grid-connected modes. Virtual inertia and rotor equations are embedded in the PLL part. Thus, the frequency stability can remain. The inner output impedance can be adjusted freely, which helps to accurately decouple and transmit the output active and reactive power. The proposed inverter operates like a traditional synchronous generator. Simulations and experiments are designed and carried out to verify the proposed control strategy.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1419-1425
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• 2000

When we predict of software reliability, we can't know the testing stopping time and how many faults be residues in software the (the maximum value of data) during these software testing process, therefore we assume the maximum value and the training result can be inaccuracy. In this paper, we present neural network approach for software reliability prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data.