• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1998년도 추계 학술대회논문집
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• pp.121-126
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• 1998

A numerical optimization procedure is developed to find the inlet velocity profile that yields the most uniform epitaxial layer in a vertical MOCVD reactor. It involves the solution of fully elliptic equations of motion, temperature, and concentration; the finite volume method based on SIMPLE algorithm has been adopted to solve the Navier-Stokes equations. The overall optimization process is highly nonlinear and has been efficiently treated by the sequential linear programming technique that breaks the non-linear problem into a series of linear ones. The optimal profile approximated by a 6th-degree Chebyshev polynomial is very successful in reducing the spatial non-uniformity of the growth rate. The optimization is particularly effective to the high Reynolds number flow. It is also found that a properly constructed inlet velocity profile can suppress the buoyancy driven secondary flow and improve the growth-rate uniformity.

• 대한기계학회논문집A
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• 제27권6호
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• pp.1041-1049
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• 2003

In this paper, a new local two-point approximation method which is based on the exponential intervening variable is proposed. This new algorithm, called the Two-Point Convex Approximation(TPCA), use the function and design sensitivity information from the current and previous design points of the sequential approximate optimization to generate a sequence of convex, separable subproblems. This paper describes the derivation of the parameters associated with the approximation and the numerical solution procedure. In order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve several typical design problems. These optimization results are compared with those of other optimizers. Numerical results obtained from the test examples demonstrate the effectiveness of the proposed method.

• 소성∙가공
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• 제26권1호
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• pp.41-47
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• 2017

Cyclic behavior of advanced high strength steel sheets was measured using an inverse-optimization approach with pre-straining and bending. First, tensile specimens were pre-strained, and three-point bending was conducted for the pre-strained specimens. By using the inverse finite element optimization, the combined isotropic-kinematic hardening parameters that minimize the error between the measured and predicted bending force-displacement curves. The measured cyclic behavior agreed well with the cyclic behavior measured by sheet tension-compression test, which confirms the validity of the measuring procedure based on inverse optimization.

• 한국안전학회지
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• 제13권1호
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• pp.40-46
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• 1998

This paper is presented that theoretical optimization design method in order to consider mass reduction for the structural safety In this paper, it described methods for reducing vibration in structural safety by the determination of the optimum sizes and locations of tunning masses through formal mathematical optimization techniques. The optimization procedure which employs the tunning masses and corresponding locations is developed. Design variables are systematically changed to achieve low values of shear without a large mass penalty. Three optimization methods ire developed and tested. The first is based on minimizing the modal shaping parameter which indirectly reduce the modal shear amplitudes corresponding to each harmonic of airload. The second method reduces these amplitudes directly and the third method reduces the shear as a function of time during a revolution of the blade. The first method works well for reducing the shear for one mode responding to a single harmonic of the airload but has been found in some bases to be ineffective for more than one mode.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.695-700
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• 2008

Artificial neural network (ANN) has been extensively used in areas of nonlinear system modeling, analysis and design applications. Basically, ANN has its distinct capabilities of implementing system identification and/or function approximation using a number of input/output patterns that can be obtained via numerical and/or experimental manners. The paper describes a role of ANN, especially a back-propagation neural network (BPN) in the context of engineering analysis, design and optimization. Fundamental mechanism of BPN is briefly summarized in terms of training procedure and function approximation. The BPN based causality analysis (CA) is further discussed to realize the problem decomposition in the context of multidisciplinary design optimization. Such CA is also applied to quantitatively evaluate the uncoupled or decoupled design matrix in the context of axiomatic design with the independence axiom.

• 대한기계학회논문집B
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• 제27권9호
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• pp.1351-1359
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• 2003

This study presents a numerical procedure to optimize shape of streamwise periodic ribs mounted on both of the principal walls to enhance turbulent heat transfer in a rectangular channel flow. The response surface method is used as an optimization technique. The optimization is based on Navier-Stokes analysis of flow and heat transfer with $k-{\varepsilon}$ turbulence model. The width-to-height ratio of a rib, rib height-to-channel height ratio and rib pitch to rib height ratio are chosen as design variables. The object function is defined as a function of heat transfer coefficient and friction drag coefficient with weighting factor. Optimum shapes of the rib have been obtained for the range of 0.02 to 0.1 of weighting factor.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.170-177
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• 2014

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

• 말소리와 음성과학
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• 제8권2호
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• pp.23-30
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• 2016

This paper describes some implementation schemes of CNN in view of mini-batch DNN training for efficient second order optimization. This uses same procedure updating parameters of DNN to train parameters of CNN by simply arranging an input image as a sequence of local patches, which is actually equivalent with mini-batch DNN training. Through this conversion, second order optimization providing higher performance can be simply conducted to train the parameters of CNN. In both results of image recognition on MNIST DB and syllable automatic speech recognition, our proposed scheme for CNN implementation shows better performance than one based on DNN.

• 경영과학
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• 제26권1호
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• pp.65-76
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• 2009

The undirected Steiner tree problem in graphs is known to be NP-hard. The objective of this problem is to find a shortest tree containing a subset of nodes, called terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step. graph reduction rules eliminate useless nodes and edges which do not contribute to make an optimal solution. In the second step, a max-min ant colony optimization combined with Prim's algorithm is developed to solve the reduced problem. The proposed algorithm is tested in the sets of standard test problems. The results show that the algorithm efficiently presents very correct solutions to the benchmark problems.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.399-404
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• 2002

Analyzing acoustic-structural systems such as automobiles and aircraft the FRF-based substructuring method is one of the most powerful tools. In this paper, an optimization procedure far the engine mount system of passenger car has been presented using the design sensitivity analysis based on the multi-domain FRF-based substructuring formulation. The proposed method is applied to an optimization problem of the engine mount system, of which objective is to minimize the interior sound over the concerned rpm range. The design variables selected are the stiffnesses of the engine mounts and bushes. Plugging the gradient information calculated by the proposed method into nonlinear optimization software, we can obtain the optimal stiffnesses of the engine mounts and bushings through design iterations. The optimized interior noise in the passenger car shows that the proposed method is very useful in the realistic situation.