• Journal of Hydrogen and New Energy
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• v.32 no.1
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• pp.86-91
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• 2021

In order to save the energy in vehicles using renewable energy, it is necessary to reduce the weight of parts with polymer matrix composites. Carbon nanotube (CNT) is the nano-scale reinforcement used to increase the interlaminar strength of fiber reinforced composites or enhance the fracture toughness of polymer. However, since the degree of improvement in mechanical properties varies according to the various experimental conditions such as shape of reinforcement, types of matrix and dispersion of reinforcement, research to find the optimal conditions is essentially needed. In this study, CNT/epoxy composites with different CNT concentration were fabricated under the same conditions, and the optimal CNT content (2 wt%) was found through Mode 1 fracture toughness test. Furthermore, through optical microscopy, it was confirmed that the fracture toughness was rather decreased due to the CNT aggregation when the CNT content exceeded 2 wt%.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.170-174
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• 2014

In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.533-536
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• 2014

In this paper, a near optimal decentralized observer-controller design method is proposed for ramp metering systems based on SDRE (State Dependent Riccati Equation) approach. The optimal nonlinear observer gain is parameterized in terms of the solution matrix of an SDRE. This paper gives a simple algorithm to compute the near optimal observer gain. The optimal control design problem is also considered. Finally, numerical simulation results are given to illuminate the effectiveness and practicality of the proposed design method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.234-239
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• 1993

Most of the control problem is for the redundant manipulators use the pseudo-inverse control, thit is, the redundancy is resolved by the pseudo-inverse of the Jacobian matrix and then the controller is designed based on this resolution. However, this pseudo-inverse control has some problems when the redundant robot repeats the cyclic tasks. This is because the pseudo-inverse resolution is a local solution that generates the different configurations of the robot arm for the same hand position. Therefore it is necessary to find the global solution that maintains the optimal configuration of the robot for the repetitive tasks. In this paper, we want to propose a redundancy resolution method by the optimal theory that uses the calculus of variation. The problem formulations are : first to convert the optimal resolution problem to an optimal control problem and then to resolve the redundancy using the necessary conditions of optimal control.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1240-1247
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• 2003

Water jet nozzle for LCD has been used as a wet cleaning process in many industries. It is necessary for the nozzle to consider cleaning effect and flux. In this paper, we applied the bubble dynamic theory(Rayleight-Plesset equation) to improve the cleaning efficiency. Generally, Rayleigh-Plesset equations for cavitation bubbles are used in analyzing computer simulation for caviting flows. Burst of bubbles causes potential energies and we can use these energies to remove organic and inorganic compounds on the LCD. Therefore, it is necessary to analyze the bubble generations and axiomatic design by computational fluid dynamics(CFD). By comparing the weight matrix of neural networks to the design matrix of axiomatic design, we propose methods to verify designs objectively. The optimal solution could be deduced by the regression analysis using the design parameters.

• Journal of the Korea Construction Safety Engineering Association
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• s.52
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• pp.58-66
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• 2011

This study presents an algorithm to select the best alternative plane among various bridge superstructure types (Steel box girder, Rational girder, PSC-I girder) using Value Engineering (VE). Economical efficiency, landscape, constructability, maintenance, stability, function of bridge superstructure were taken into consideration in the designing of bridge. Economical efficiency was evaluated for each alternative plan with optimal design considering Life Cycle Cost (LCC), Repair and rehabilitation histories and some factors were set to get reasonable results. In the application of Analytic Hierarchy Process (AHP), consistency of Pairwise Comparisons Matrix was evaluated and the best plan was determined.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.383-391
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• 2009

In this paper, blind equalization using a modified Fuzzy C-Means algorithm with Gaussian Weights (MFCM_GW) is attempted to the heavy noise-corrupted channels. The proposed algorithm can deal with both of linear and nonlinear channels, because it searches for the optimal channel output states of a channel instead of estimating the channel parameters in a direct manner. In contrast to the common Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in its search procedure. The selected channel states by MFCM_GW are always close to the optimal set of a channel even the additive white Gaussian noise (AWGN) is heavily corrupted in it. Simulation studies demonstrate that the performance of the proposed method is relatively superior to existing genetic algorithm (GA) and conventional FCM based methods in terms of accuracy and speed.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.5
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• pp.145-151
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• 2012

New design of catalytic converter is proposed by optimization of DFSS (Design For Six Sigma) and DOE (Design Of Experiment) method which is based on taguchi matrix. As a result of the optimization of design of catalytic converter, this paper classifies Exhaust-downpipe shapes with 3 parameters to increase flow velocity uniformity of front catalytic substrate face from CFD results. after finishing with L9 Taguchi test matrix, it can be found the main effect of each design parameter of concept model, and optimal design level. in conclusion, it can be increase flow uniformity from 0.60 upto 0.80 with optimal diffuser shape for Turbo-charger.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.101-108
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• 1988

In this paper the power spectrum of background EEG is estimated by the LMS PHD based on least mean square. At the power spectrum estimatiom, the stocastic process of background EEG is assumed to consist of the nonharmonic sinusoid and the white noise. In the LMS PHD the model parameters are obtained by the least mean square at optimal order which is obtained from the fact that the eigenvalue's fluctuation of autocorrelation matrix of the normal back-ground EEG is smaller at some order than at other order when the power spectrum of background EEG is esitmated by PHD. The optimal order of this model is the 6-th order when the eigenvalue's fluctuation of autocorrelation matrix of background EEG is considered. The estimation results are with compared the results from the Maximum Entropy Spectral Estimation and Pisarenko Harmonic Decomposition. From the comparison results. The LMS PHD is possible to estimate the power spectrum of background EEG.

• Journal of the Korean Society of Safety
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• v.24 no.6
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• pp.79-85
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• 2009

This study presents an algorithm to select the best alternative plane among various bridge superstructure types(Steel box girder, Rational girder, PSC-I girder) using Value Engineering(VE). Economical efficiency, landscape, constructability, maintenance, stability, function of bridge superstructure were taken into consideration in the designing of bridge. Economical efficiency was evaluated for each alternative plan with optimal design considering Life Cycle Cost(LCC). Repair and rehabilitation histories and some factors were set to get reasonable results. In the application of Analytic Hierarchy Process(AHP), consistency of Pairwise Comparisons Matrix was evaluated and the best plan was determined.