• Journal of Mechanical Science and Technology
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• 제15권9호
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• pp.1257-1267
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• 2001

For efficient mechanical system optimization, a new two-point approximation method is presented. Unlike the conventional two-point approximation methods such as TPEA, TANA, TANA-1, TANA-2 and TANA-3, this introduces the shifting level into each exponential intervening variable to avoid the lack of definition of the conventional exponential intervening variables due to zero-or negative-valued design variables. Then a new quadratic approximation whose Hessian matrix has only diagonal elements of different values is proposed in terms of these shifted exponential intervening variables. These diagonal elements are determined in a closed form that corrects the typical error in the approximate gradient of the TANA series due to the lack of definition of exponential type intervening variables and their incomplete second-order terms. Also, a correction coefficient is multiplied to the pre-determined quadratic term to match the value of approximate function with that of the previous point. Finally, in order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve six typical design problems. These optimization results are compared with those of TANA-3. These comparisons show that the proposed method gives more efficient and reliable results than TANA-3.

• 대한기계학회논문집A
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• 제25권9호
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• pp.1423-1431
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• 2001

Based on the exponential intervening variable, a new two-point approximation method is presented. This introduces the shifting level into each exponential intervening variable to avoid the lack of def inition of the conventional exponential intervening variables due to zero-or negative-valued design variables. Then a new quadratic approximation whose Hessian matrix has only diagonal elements of different values is proposed in terms of these intervening variables. These diagonal elements are determined in a closed form that corrects the typical error in the approximate gradient of the TANA series due to the lack of definition of exponential type intervening variables and their incomplete second-order terms. Also, a correction coefficient is multiplied to the pre-determined quadratic term to match the value of approximate function with that of the previous point. Finally, in order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve six typical design problems. These optimization results are compared with those of TANA-3. These comparisons show that the proposed method gives more efficient and reliable results than TANA-3.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.386-391
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• 2001

This paper presents a new two-point approximation method based on the exponential intervening variable. To avoid the lack of definition of the conventional exponential intervening variables due to zero- or negative-valued design variables the shifting level into each exponential intervening variable is introduced. Then a new quadratic approximation, whose Hessian matrix has only diagonal elements of different values, is proposed in terms of these intervening variables. These diagonal elements are computed in a closed form, which correct the typical error in the approximate gradient of the TANA series due to the lack of definition of exponential type intervening variables and their incomplete second-order terms. Also, a correction coefficient is multiplied to the pre-determined quadratic term to match the value of approximate function with that of the original function at the previous point. Finally, the authors developed a sequential approximate optimizer, solved several typical design problems used in the literature and compared these optimization results with those of TANA-3. These comparisons show that the proposed method gives more efficient and reliable results than TANA-3.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2242-2244
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• 2004

This paper deals with the design of a reduced-order stabilizing controller for the linear system. The coupled lineal matrix inequality (LMI) problem subject to a rank condition is solved by a sequential semidefinite programming (SDP) approach. The nonconvex rank constraint is incorporated into a strictly linear penalty function, and the computation of the gradient and Hessian function for the Newton method is not required. The penalty factor and related term are updated iteratively. Therefore the overall procedure leads to a successive LMI relaxation method. Extensive numerical experiments illustrate the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.714-716
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• 1996

This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.

• 한국전산구조공학회논문집
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• 제15권4호
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• pp.675-691
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• 2002

본 연구의 목적은 Navier-Stokes 유체와 같은 대용량 문제를 위한 최적화 기법의 개발에 있다. 이를 위해 본 연구에서는 reduced Hessian sequential quadratic programming을 개발하였다. 첫째, 유체의 해석을 위한 평형 방정식을 최적화 과정에서 제거하여 변수를 줄였고, 또한 평형방정식과 최적화 과정에서 연속기법을 사용하여 최적해를 보장하면서 더욱 해에 쉽게 접근하도록 하였다. 그리고 각 단계에서는 테일러 시리즈를 이용한 근사치를 이용하여 각 단계에서 대단히 좋은 초기치 값을 제공하여 최적해에 더욱 빠르게 접근하게 하고 아울러 유체의 평형방정식을 풀 때에도 해에 더욱 빠르고 쉽게 접근하도록 하였다. 이 기법을 항력을 줄이기 위한 유체의 최적 제어를 위한 문제에 적용하였다. 유체의 흐름을 제어하기 위하여 물체의 경계면에서 유체의 흡입(suction)과 방축(injection)이라는 기법을 사용하여 경계면에서 속도를 제어하였고, 목적함수로써 항력을 표현하기 위하여 에너지 소실의 변화율을 사용하였다. 예제를 통해 본 연구에서 개발한 최적화 기법의 효용성을 입증하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1263-1266
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• 1998

In this paper, we propose an optimal feature extraction method for normally distributed multiclass data. We search the whole feature space to find a set of features that give the smallest classification error for the Gaussian ML classifier. Initially, we start with an arbitrary feature vector. Assuming that the feature vector is used for classification, we compute the classification error. Then we move the feature vector slightly and compute the classification error with this vector. Finally we update the feature vector such that the classification error decreases most rapidly. This procedure is done by taking gradient. Alternatively, the initial vector can be those found by conventional feature extraction algorithms. We propose two search methods, sequential search and global search. Experiment results show that the proposed method compares favorably with the conventional feature extraction methods.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2004년도 춘계 학술대회논문집
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• pp.83-90
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• 2004

Substructuring methods are usually used in finite element structural analyses. In this study a multi-level substructuring algorithm is developed and proposed as a possible candidate for incompressible fluid solves. Finite element formulation for incompressible flow has been stabilized by a modified residual procedure proposed by Ilinca et.al.[5]. The present algorithm consists of four stages such as a gathering stage, a condensing stage, a solving stage and a scattering stage. At each level, a predetermined number of elements are gathered and condensed to form an element of higher level. At highest level, each subdomain consists of only one super-element. Thus, the inversion process of a stiffness matrix associated with internal degrees of freedom of each subdomain has been replaced by a sequential static condensation. The global algebraic system arising feom the assembly of each subdomains is solved using Conjugate Gradient Squared(CGS) method. In this case, pre-conditioning techniques usually accompanied by iterative solvers are not needed.

• 한국산학기술학회논문지
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• 제14권9호
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• pp.4156-4162
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• 2013

본 연구는 중형 크랭크샤프트 제작 과정에서 환봉을 가열하기 위한 최적의 유도가열조건을 결정하기 위한 것으로, 4가지 가열조건(가열코일 개수, 위치 등)에 대하여 수치해석적인 방법을 사용하여 전자기장 및 열전달해석을 순차적으로 수행하였다. 이러한 수치해석 결과로부터 일정시간 가열 후 크랭크샤프트 환봉 가열부에 발생하는 최고온도와 두께에 따른 내, 외부 최소 온도차를 평가하여 현장에 적용 가능한 가열코일의 위치 및 개수 등의 유도가열조건을 결정하였다.