• 한국정보과학회논문지:시스템및이론
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• 제31권10호
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• pp.543-552
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• 2004

이 논문은 지연 시간 및 화질 제약이 있는 비디오 응용을 위한 에너지 최적화 기법을 제안한다. 이는 두 가지 핵심 기법 - 프레임 생략 기법 및 버퍼링 기법 - 으로 구성되어있다. 버퍼링은 운영 체제 수준에서 유휴 시간 이용률을 증가시키고, 프레임 생략은 응용 수준에서 유휴 시간 자체를 증가시키며, 양쪽 모두 동적 전압 조절 기법의 효과를 향상시킨다. 이 논문에서는 제안한 기법을 적용하기 위해 H.263 부호기 응용을 사용한다. 실험에서는 제안한 기법이 주어진 지연 시간 및 화질 제약을 만족하면서 괄목할 만한 에너지 절감을 얻을 수 있음을 보인다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 춘계학술대회 논문집
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• pp.581-586
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• 2009

This paper presents an optimal design of magnetorheological(MR) damper based on analytical methodology and finite element analysis. The proposed MR damper consists of MR valve and gas chamber. The MR valve is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the pressure drop of the MR valve or damping force of the MR damper. In this work, the single-coil annular MR valve structure is considered. After describing the schematic configuration and operating principle of MR valve and damper, a quasi-static model is derived based on Bingham model of MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying the Kirchoff’s law and magnetic flux conservation rule. Based on the quasi-static modeling and the magnetic circuit analysis, the optimization problem of the MR valve and damper is built. The optimal solution of the optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution obtained from finite element method.

• 한국소음진동공학회논문집
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• 제19권11호
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• pp.1110-1118
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• 2009

This paper presents an optimal design of magnetorheological(MR) damper based on analytical methodology and finite element analysis. The proposed MR damper consists of MR valve and gas chamber. The MR valve is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the pressure drop of the MR valve or damping force of the MR damper. In this work, the single-coil annular MR valve structure is considered. After describing the schematic configuration and operating principle of MR valve and damper, a quasi-static model is derived based on Bingham model of MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying the Kirchoff' s law and magnetic flux conservation rule. Based on the quasi-static modeling and the magnetic circuit analysis, the optimization problem of the MR valve and damper is built. The optimal solution of the optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution obtained from finite element method.

• Elastomers and Composites
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• 제34권4호
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• pp.321-331
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• 1999

타이어 가황공정(curing process)은 타이어 제조를 위한 최종공정으로 여러 개의 고무배합물 층으로부터 성형된 그린타이어(green tire)를 가황기(mold)내에서 고압/고온 조건하에 유지시킴으로써 원하는 형상을 얻게 하고, 아울러 각 고무배합물이 고탄성을 갖도록 물성을 변화시키는 공정이다. 본 연구에서는 타이어 품질의 향상을 위해 가황공정을 수치적으로 최적화하는 기법을 개발하였다. 먼저, 가황공정 중 가황매체(cure media)의 최적공급 조건을 경정하기 위해 제약조건을 갖는 동적최적화문제(dynamic constrained optimization problem)로 정형화하였다. 즉, 가황기 내의 전열 및 가황 반응 현상을 묘사하는 공정모델로 표현되는 등위제약조건(equality constraint)과 가황매체가 갖는 온도의 한계를 표현하는 부등위제약조건(Inequality constraint) 아래 목적함수를 최적화 시켰다. 다음, 공급되는 가황매체의 최적조건을 결정하기 위해 구성된 최적화문제를 유한요소법(FEM)과 complex 알고리즘을 적용하여 풀었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.377-382
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• 2004

This paper presents a novel optimization method for the air- and gas-supplying network comprised of several air compression systems and air and gas streams in an industrial chemical plant. The optimization is based on the hybrid model developed by Han and $Han^1$ for predicting the power consumption of a compression system. A constrained optimization problem was formulated to minimize the total electric power consumption of all the compression systems in the air- and gas-supplying network under various operating constraints and was solved using a successive quadratic optimization algorithm. The optimization approach was applied to an industrial terephthalic acid manufacturing plant to achieve about 10% reduction in the total electric power consumption under varying ambient conditions.

• Architectural research
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• 제11권1호
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• pp.15-23
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• 2009

An application of the constrained adaptive topology optimization (CATO) algorithm is described for three-dimensional topology optimization of engineering structures. The enhanced assumed strain lower order solid finite element (FE) is used to evaluate the values of objective and constraint functions required in optimization process. The strain energy (SE) terms such as elastic and modal SEs are employed as the objective function to be minimized and the initial volume of structures is introduced as the constraint function. The SIMP model is adopted to facilitate the material redistribution and also to produce clearer and more distinct structural topologies. The linearly weighted objective function is introduced to consider both static and dynamic characteristics of structures. Several numerical tests are tackled and it is used to investigate the performance of the proposed three-dimensional topology optimization process. From numerical results, it is found to be that the CATO algorithm is easy to implement and extremely applicable to produce the reasonable optimum topologies for three dimensional optimization problems.

• 전기학회논문지P
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• 제58권2호
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• pp.164-171
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• 2009

This paper presents new learning algorithm of dynamic Bayesian networks (DBN) by means of constrained least square (LS) estimation algorithm and gradient descent method. First, we propose constrained LS based parameter estimation for a Markov chain (MC) model given observation data sets. Next, a gradient descent optimization is utilized for online estimation of a hidden Markov model (HMM), which is bi-linearly constructed by adding an observation variable to a MC model. We achieve numerical simulations to prove its reliability and superiority in which a series of non stationary random signal is applied for the DBN models respectively.

• 한국경영과학회지
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• 제28권4호
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• pp.191-198
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• 2003

The generalized knapsack problem or gknap is the combinatorial optimization problem of optimizing a nonnegative linear function over the integral hull of the intersection of a polynomially separable 0-1 polytope and a knapsack constraint. The knapsack, the restricted shortest path, and the constrained spanning tree problem are a partial list of gknap. More interesting1y, all the problem that are known to have a fully polynomial approximation scheme, or FPTAS are gknap. We establish some necessary and sufficient conditions for a gknap to admit an FPTAS. To do so, we recapture the standard scaling and approximate binary search techniques in the framework of gknap. This also enables us to find a weaker sufficient condition than the strong NP-hardness that a gknap does not have an FPTAS. Finally, we apply the conditions to explore the fully polynomial approximability of the constrained spanning problem whose fully polynomial approximability is still open.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.589-594
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.