• Journal of Mechanical Science and Technology
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• 제18권10호
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• pp.1722-1729
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• 2004

This paper presents a design methodology for determining configurations of slider air bearings considering the randomness of the air-bearing surface (ABS) geometry by using the iSIGHT. A reliability-based design optimization (RBDO) problem is formulated to minimize the variations in the mean values of the flying heights from a target value while satisfying the desired probabilistic constraints keeping the pitch and roll angles within a suitable range. The reliability analysis is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the reliability constraints affected by the random variables. Reliability constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the RBDO are listed in comparison with the values of the initial design and the results of the deterministic optimization, respectively. To show the effectiveness of the proposed approach, the reliability analyses are simply carried out by using the mean value first-order second-moment (MVFO) method. The Monte Carlo simulation of the RBDO's results is also performed to estimate the efficiency of the proposed approach. Those results are demonstrated to satisfy all the desired probabilistic constraints, where the target reliability level for constraints is defined as 0.8.

• 한국경영과학회지
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• 제40권3호
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• pp.49-61
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• 2015

We study the problem of multiple response optimization (MRO) and focus on the selection of input levels which will produce desirable output quality. We propose an interactive multiple objective optimization approach to the input design. The earlier interactive methods utilized for MRO communicate with the decision maker only using the response variable values, in order to improve the current response values, thereby resulting in the corresponding design solution automatically. In their interaction steps of preference articulation, no account is taken of any active changes in design variable values. On the contrary, our approach permits the decision maker to change the design variable values in its interaction stage, which makes possible the consideration of the preference or economics of the design variable side. Using some typical value functions, we also demonstrate that our method converges reasonably well to the known optimal solutions.

• Structural Engineering and Mechanics
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• 제52권4호
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• pp.739-753
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• 2014

There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.135-140
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• 2002

Studies on the optimization of machining process can be divided into two different approaches: off-line feedrate scheduling and adaptive control. Each approach possesses its respective strong and weak points compared to each other. That is, each system can be complementary to the other. In this regard, a combined system, which is a feedrate control system for cutting force optimization, was proposed in this paper to make the best of each approach. Experimental results show that the proposed system could overcome the weak points of two systems.

• International Journal of Aeronautical and Space Sciences
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• 제13권1호
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• pp.43-57
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• 2012

In a modern aircraft, there are many variations in its mass, stiffness, and aerodynamic characteristics. Recently, an analytical approach was proposed, and this approach uses the idea of uncertainty to find out the most critical flight flutter boundary due to the variations in such aerodynamic characteristics. An analytical method that has been suggested to predict robust stability is the mu method. We previously analyzed the robust flutter boundary by using the mu method, and in that study, aerodynamic variations in the Mach number, atmospheric density, and flight speed were taken into consideration. The authors' previous attempt and the results are currently quoted as varying Mach number mu analysis. In the author's previous method, when the initial flight conditions were located far from the nominal flutter boundary, conservative predictions were obtained. However, relationships among those aerodynamic parameters were not applied. Thus, the varying Mach number mu analysis results required validation. Using an optimization approach, the varying Mach number mu analysis was found out to be capable of capturing a reasonable robust flutter boundary, i.e., with a low percentage difference from boundaries that were obtained by optimization. Regarding the optimization approach, a discrete nominal flutter boundary is to be obtained in advance, and based on that boundary, an interpolated function was established. Thus, the optimization approach required more computational effort for a larger number of uncertainty variables. And, this produced results similar to those from the mu method which had lower computational complexity. Thus, during the estimation of robust aeroelastic stability, the mu method was regarded as more efficient than the optimization method was. The mu method predicts reasonable results when an initial condition is located near the nominal flutter boundary, but it does not consider the relationships that are among the aerodynamic parameters, and its predictions are not very accurate when the initial condition is located far from the nominal flutter boundary. In order to provide predictions that are more accurate, the relationships among the uncertainties should also be included in the mu method.

• Journal of Electrical Engineering and Technology
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• 제4권1호
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• pp.19-27
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• 2009

This paper presents a newly developed optimization algorithm, the Bee Optimization Algorithm (BeeOA), to solve the economic power dispatch (EPD) problem. The authors have developed a derivative free and global optimization technique based on the working of the honey bee. The economic power dispatch problem is a nonlinear constrained optimization problem. Classical optimization techniques fail to provide a global solution and evolutionary algorithms provide only a good enough solution. The proposed approach has been examined and tested on two test systems with different objectives. A simple power dispatch problem is tested first on 6 generators and then the algorithm is demonstrated on 13 thermal unit systems whose incremental fuel cost function takes into account the value point loading effect. The results are promising and show the effectiveness and robustness of the proposed approach over recently reported methods.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• 한국강구조학회 논문집
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• 제9권3호통권32호
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• pp.457-465
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• 1997

형상최적화는 단면최적화에 비하여 구조물의 중량과 경비를 줄일 수 있다. 많은 양의 애매한 정보가 최적설계 문제의 제약조건에 존재할 수도 있다. 상대적으로 중요한 퍼지정도를 포함한 여러개의 기준을 묘사하고 다루는 것은 매우 어렵고 때로는 애매하다. 본 논문에서는 ${\alpha}$-절단법에 의한 퍼지 구조계의 다목적 형상최적화에 대한 가중치방법을 제안한다. 본 연구의 알고리즘을 2부재 트러스 구조물에 적응하여 그 결과가 검토되었다. 그 결과는 ${\alpha}$-절단법과 체적과 변위에 관한 가중치에 따른 최적해를 얻음으로써 설계자는 실제에 적합한 하나의 해를 택할 수 있음을 보여준다.

• 한국전산구조공학회논문집
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• 제23권1호
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• pp.37-43
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• 2010

본 논문에서는 선형 구조물에 대해 성능함수법을 이용하여 신뢰성기반 위상 최적설계 기법을 개발하였다. 구조물을 라이즈너-민들린(Ressiner-Mindlin) 판 요소로 분할하였으며, 각 요소의 재료 물성치를 설계변수로 사용하였다. 설계변수와 임의변수의 효율적인 설계민감도를 구하기 위하여 연속체 역학에 기초한 해석기법 중 보조변수법(Adjont variable method)을 사용하였다. 또한 확률론적 제약조건을 평가하기 위해서 성능함수법(Performance measure approach)을 사용하였으며 변위 제약조건을 두어 위상 최적설계 문제를 구성하였다. 이 때 재료 물성치와 하중을 불확실 변수로 고려하였으며 수치적 예제를 통하여 본 논문에서 제안한 최적설계 방법론을 기존의 결정론적 방법, 안전계수법(Safety factor approach), 최악조건법(Worst case approach) 등과 비교하여 그 타당성을 검증하였다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2009년 춘계학술대회논문집
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• pp.57-65
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• 2009

An efficient and high-fidelity design approach for wing-body shape optimization is presented. Depending on the size of design space and the number of design of variable, aerodynamic shape optimization process is carried out via different optimization strategies at each design stage. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are used for wing surface design with a lot of design variables to maintain a sufficient design space with a high DOF (Degree of Freedom) geometric change. For global optimization, Kriging method in conjunction with Genetic Algorithm (GA) is used. Asearching algorithm of EI (Expected Improvement) points is introduced to enhance the quality of global optimization for the wing-planform design. For local optimization, a discrete adjoint method is adopted. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration while maintaining the baseline lift and the wing weight at the same time. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The performance of the proposed design framework including wing planform design variables can be efficiently evaluated by the drag decomposition method, which can examine the improvement of various drag components, such as induced drag, wave drag, viscous drag and profile drag.