• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.41-46
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• 2003

The objective of this paper is to present a methodology for automatically balancing multi-cavity injection molds with the aid of flow simulation. After the runner and cavity layout has been designed, the methodology adjusts runner and gate sizes iteratively based on the outputs of flow analysis. This methodology also ensures that the runner sizes in the final design are machinable. To illustrate this methodology, an example is used wherein a 3-cavity mold is modeled and filling of all the cavities at the same time is achieved. Based on the proposed methodology, a multicavity mold with identical cavities is balanced to minimize overall unfilled volume among various cavities at discrete time steps of the molding cycle. The example indicates that the described methodology can be used effectively to balance runner systems for multi-cavity molds.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.592-596
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• 2004

Corrosion is never avoided in the use of materials with various environments. The underwater hull is normally protected against rusting by several coatings of anti-corrosive paint. The purpose of ICCP(Impressed Current Cathodic protection) system is to eliminate the rusting or corrosion, which occurs on metal immersed in seawater. The anode of ICCP system is controlled by an external DC source with converter. The function of anode is to conduct the protective current into seawater. The proposed algorithm includes the harmonic suppression control strategy and the optimum protection strategy and has tried to test the requirement current density for protection, the influence of voltage, the protection potential. This paper was studied the variation of potential and current density with environment factors, time and velocity, and the experimental results will be explained.

• Journal of the Korean Vacuum Society
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• v.4 no.S1
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• pp.190-195
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• 1995

The feature scale model for selective chemical vapor deopsition process was proposed and the simulation was performed to study the selectivity and uniformity of deposited thin film using Monte Carlo method and string algorithm. The effect of model parameters such as sticking coefficient, aspect ratio, and surface diffusion coefficient on the deposited thin film pattern was improved for lower sticking coefficient and higher aspect ratio. It was revealed that the selectivity loss ascrives to the surface diffusion. Different values of sticking coefficients on Si and on SiO2 surface greatly influenced the deopsited thin film profile. In addition, as the lateral wall angle decreased, the selectively deposited film had improved uniformity except the vicinity of trench wall. The optimum eondition for the most flat selective film deposition pattern is the case with low sticking coefficient and slightly increased surface diffusion coefficient.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2054-2061
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• 2010

This paper suggests an algorithm for optimal positioning individuals(or observations) with p-dimensional measurements into coordinates of a two dimensional space. A criterion for optimizing the rotation is taken as the consistency of the grouping result obtained by the cluster analysis. This paper introduces the criterion and a transformation matrix for the orthogonal rotation. The criterion of the optimal positioning is that standard groups are placed in each quadrant of the positioning. An optimal angle of the orthogonal rotation is investigated and found by this criterions.

• Journal of Communications and Networks
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• v.8 no.2
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• pp.205-211
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• 2006

This paper considers the maximum likelihood (ML) detection of 16-ary differential amplitude and phase shift keying (DAPSK) in Rayleigh fading channels. Based on the conditional likelihood function, two new receiver structures, namely ML symbol-by-symbol receiver and ML sequence receiver, are proposed. For the symbol-by-symbol detection, the conventional DAPSK detector is shown to be sub-optimum due to the complete separation in the phase and amplitude detection, but it results in very close performance to the ML detector provided that its circular amplitude decision thresholds are optimized. For the sequence detection, a simple Viterbi algorithm with only two states are adopted to provide an SNR gain around 1 dB on the amplitude bit detection compared with the conventional detector.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.1
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• pp.108-117
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• 1998

This study was performed to analyze the fluid flow characteristics and the temperature distribution of the aquarium for fish breeding. In this study, the finite volume method and turbulence k-$\varepsilon$ model with the SIMPLE computational algorithm are used to study the water flow in the aquarium. The calculation parameters are the circulating flow rate and the basin depth, and the experiments were carried out for the water flow visualization This numerical analysis gives reasonable velocity distributions in good agreement with the experimental data. As the results of the three dimmentional simulations, the sectional mean velocity increased as the sectional mean temperature increases for constant basin depth, and the mean velocity increased more rapidly for small basin depth than that of large basin depth, The mean velocity and temperature can be expressed as the function of the circulating flow rates and the basin depth.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.146-158
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• 1991

In this paper, we deal with the TSP (Traveling Salesperson Problem) which is well-known as NP-complete optimization problem. the TSP is applicable to network routing. task allocation or scheduling. and VLSI wiring. Well known numerical methods such as Newton's Metheod. Gradient Method, Simplex Method can not be applicable to find Global Solution but the just give Local Minimum. Exhaustive search over all cyclic paths requires 1/2 (n-1) ! paths, so there is no computer to solve more than 15-cities. Heuristic algorithm. Simulated Annealing, Artificial Neural Net method can be used to get reasonable near-optimum with polynomial execution time on problem size. Therefore, we are able to select the fittest one according to the environment of problem domain. Three methods are simulated about symmetric TSP with 30 and 50-city samples and are compared by means of the quality of solution and the running time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.42-52
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• 2006

In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.