• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.567-568
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• 2007

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2542-2547
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• 2005

In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

• Proceedings of the Korean Society For Composite Materials Conference
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• 1999.11a
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• pp.68-72
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• 1999

In an effort to construct a structure under the design principle of minimal use of materials for maximum performances, a discrete gradient structure has been introduced in laminate composite systems. Using a sequential linear programming method, the gradient structure of composites to maximize the buckling load was optimized in terms of fiber volume fraction and thickness of each layer. Theoretical optimization results were then verified with experimental ones. The buckling load of laminate composite showed maximum value with the outmost [$0^{\circ}$] layer concentrated by almost all the fibers when the ratio of length to width(aspect ratio) was less than 1.0. But when the aspect ratio was 2.0, the optimum was determined in a structure where the thickness and fiber volume fraction were well balanced in each layer. From the optimization of gradient structure, the optimal fiber volume fraction and thickness of each layer were proposed. Experimental results agreed well with the theoretical ones. Gradient structures have also shown an advantage in the weight reduction of composites compared with the conventional homogeneous structures.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.157-162
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• 2012

A structural modification of baseframe is an effective method to avoid resonance in marine diesel generator (D/G) set which consists of diesel engine, generator and baseframe. However the reinforcement with thick plates or additional parts to increase the natural frequency can be less effective because of increased weight. Especially fine control of target mode based on the experience is difficult because the weight and interference of system have to be considered. In this paper, the design optimization of baseframe was performed to reduce the resonant vibration using a gradient descent method. The design parameters such as thickness, shape and location of baseframe parts are optimized to increase the torsional natural frequency of D/G set. From the actual test, the new designed baseframe reduced the vibration level in resonance by 55% without any increase of weight and interference. interference.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.118-124
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• 2016

The shape and location of the cutoff shield in a projection-type headlight system were optimized by a ray-tracing technique. A shield based on a Petsval surface showed better cutoff characteristics than a flat or cylindrical shield, such as a sharp intensity gradient and less color separation at the cutoff line. Adjustment of the shield’s location between the reflector and the aspheric lens further improved its cutoff characteristics.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.33-35
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• 1993

A new low-power, high-order optimization scheme to design surface gradient coils (SGC) is proposed for magnetic resonance imaging (MRI). Although previous SGCs have been designed and constructed just to get strong linear gradients, this paper proposes more systematic ways of SGC design by minimizing electrical power consumption in the gradient coil and by removing unnecessary high-order field distortions in the imaging region. By assuming continuous current flow on the coil surface which may be or may not be planar, power consumption in the coil is minimized. According to the simulation results, the SGC designed by using the proposed scheme seems to produce much more uniform linear gradient field using less electrical power compared to the previously proposed SGCs.

• International Journal of Fluid Machinery and Systems
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• v.2 no.1
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• pp.1-12
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• 2009

Surrogate modeling is applied to a compressor blade shape optimization to modify its stacking line and thickness to enhance adiabatic efficiency and total pressure ratio. Six design variables are defined by parametric curves and three objectives; efficiency, total pressure and a combined objective of efficiency and total pressure are considered to enhance the performance of compressor blade. Latin hypercube sampling of design of experiments is used to generate 55 designs within design space constituted by the lower and upper limits of variables. Optimum designs are found by formulating a PRESS (predicted error sum of squares) based averaging (PBA) surrogate model with the help of a gradient based optimization algorithm. The optimum designs using the current variables show that, to optimize the performance of turbomachinery blade, the adiabatic efficiency objective is improved substantially while total pressure ratio objective is increased a very small amount. The multi-objective optimization shows that the efficiency can be increased with the less compensation of total pressure reduction or both objectives can be increased simultaneously.

• Journal of the Korea Society for Simulation
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• v.9 no.2
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• pp.89-102
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• 2000

In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this purpose, using the perturbation analysis, we apply a stochastic optimization algorithm to two types of queueing systems. Our simulation results indicate that the estimates obtained from a stochastic optimization algorithm for a two-tandem queuing network are very accurate, and those for closed loop manufacturing system are a little apart from the known optimal allocation. We find that as simulation time increases for obtaining a new gradient (performance measure with respect to decision variables) by perturbation algorithm, the estimates tend to be more stable. Thus, we consider that it would be more desirable to have more accurate sensitivity of performance measure by enlarging simulation time rather than more searching steps with less accurate sensitivity. We realize that more experiments on various types of systems are needed to identify such a relationship with regards to stopping rule, the size of moving step, and updating period for sensitivity.

• Composites Research
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• v.13 no.2
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• pp.40-50
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• 2000

In an effort to construct a structure under the design principle of minimal use of materials for maximum performances, a discrete gradient structure has been introduced in laminate composite systems. Using a sequential linear programming method, the gradient structure of composites to maximize the buckling load was optimized in terms of fiber volume fraction and thickness of each layer. The buckling load showed maximum value with the outmost [$0^{\circ}$] layer concentrated by almost all the fibers when the ratio of length to width(aspect ratio) was less than 1.0. But when the aspect ratio was 2.0, the optimum was determined in a structure where the thickness and fiber volume fraction were well-balanced in each layer. From the optimization of gradient structure, the optimal fiber volume fraction and thickness of each layer were proposed. Gradient structures have also shown an advantage in the weight reduction of composites compared with the conventional homogeneous structures.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.859-865
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• 2014

Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.