• 대한기계학회논문집A
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• 제28권4호
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• pp.467-474
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• 2004

A numerical method and algorithms is proposed to perform optimization of non-linear response structures. An analytical and numerical method based finite element method is also proposed for the transformation of non-linear response into linear response. Loads transformed from this method are defined as the equivalent linear loads. With the loads and the transformed response, linear static optimization is performed for nonlinear response structure with geometric and/or material non-linearity. The results of the optimization are compared with them of typical non-linear response optimization using finite difference method. The proposed method is very efficient and derives good solution.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.999-1004
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• 2004

A numerical method and algorithms is proposed to perform optimization of non-linear response structures. An analytical and numerical method based finite element method is also proposed for the transformation of non-linear response into linear response. Loads transformed from this method are defined as the equivalent linear loads. With the loads and the transformed response, linear static optimization is performed for nonlinear response structure with geometric and/or material non-linearity. The results of the optimization are compared with them of typical non-linear response optimization using finite difference method. The proposed method is very efficient and derives good solution.

• 한국기계가공학회지
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• 제3권4호
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• pp.13-19
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• 2004

This paper deals with the analysis of geometric error and the optimization of process parameters in surface grinding. Taguchi method which is one of the design of experiments has been introduced in achieving the aims. The process parameters were the grain size, the wheel speed, the depth of cut and the table speed. The effect of the process parameters on the geometric error was examined and an optimal set of the parameters was selected to minimize the geometric error within the controllable range of the used grinding machine. The reliability of the results was evaluated by the ANOVA.

• Structural Engineering and Mechanics
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• 제86권3호
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• pp.337-348
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• 2023

The optimization of reinforced concrete (RC) cantilever retaining walls is a complex problem and requires the use of advanced techniques like metaheuristic algorithms. For this purpose, an optimization model must first be developed, which involves mathematical complications, multidisciplinary knowledge, and programming skills. This task has proven to be too arduous and has halted the mainstream acceptance of optimization. Therefore, it is necessary to unravel the complications of optimization into an easily applicable form. Currently, the most commonly used method for designing retaining walls is by following the proportioning limits provided by the ACI handbook. However, these limits, derived manually, are not verified by any optimization technique. There is a need to validate or modify these limits, using optimization algorithms to consider them as optimal limits. Therefore, this study aims to propose updated proportioning limits for the economical design of a RC cantilever retaining wall through a comprehensive parametric investigation using the genetic algorithm (GA). Multiple simulations are run to examine various design parameters, and trends are drawn to determine effective ranges. The optimal limits are derived for 5 geometric and 3 reinforcement variables and validated by comparison with their predecessor, ACI's preliminary proportioning limits. The results indicate close proximity between the optimized and code-provided ranges; however, the use of optimal limits can lead to additional cost optimization. Modifications to achieve further optimization are also discussed. Besides the geometric variables, other design parameters not covered by the ACI building code, like reinforcement ratios, bar diameters, and material strengths, and their effects on cost optimization, are also discussed. The findings of this investigation can be used by experienced engineers to refine their designs, without delving into the complexities of optimization.

• 응용통계연구
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• 제22권6호
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• pp.1277-1287
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• 2009

For stratifying skewed populations, the Lavall$\acute{e}$e-Hidiroglou(LH) algorithm is often considered to have a take-all stratum with the largest units and some take-some strata with the middle-size and small units. Related to its iterative nature have been reported some numerical difficulties such as the dependency of the ultimate stratum boundaries to a choice of initial boundaries and the slow convergence to locally-optimum boundaries. The geometric stratification has been recently proposed to provide initial boundaries that can avoid such numerical difficulties in implementing the LH algorithm. Since the geometric stratification does not pursuit the optimization but the equalization of the stratum CVs, the corresponding stratum boundaries may not be (near) optimal. This paper revisits these issues concerning convergence and near-optimality of optimal stratification algorithms using artificial numerical examples. We also discuss the formation of the strata and the sample allocation under the optimization process and some aspects related to discontinuity arisen from the finiteness of both population and sample as well.

• 대한기계학회논문집A
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• 제20권1호
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• pp.180-188
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• 1996

The stress singularity of a sharp wedge contacting a half plane can be avoided by changing the wedge shape. Shape optimization is accomplished with the geometric strain method (GSM), an optimality criterion method. Several numerical examples are provided for different materials in the wedge and half plane to avoid stress singularity neal the sharp corner of the wedge. Optimum wedge shapes are obtained and critical corner angles are compared with the angles from analytical contact mechanics. Numerical results are well matched to analytical and experimental results. It is shown that shape optimization by the geometric strain method is a useful tool to reshape the wedge and to avoid a stress singulatiry. The method applies to more general geometries where the singular behavior would be difficult to avoid by classical means.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.351-357
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• 2003

A method of design optimization for minimization of force ripple and maximization of thrust force in a linear brushless permanent magnet motor without finite element analysis is represented. The design optimization method calculated the driving force in the function of electric and geometric parameters of a linear brushless PM motor using the sequential quadratic programming method. Using electric and geometric parameters obtained by this method, the normalized force ripple is reduced 7.7% (9.7% to 2.0%) and the thrust force is increased 12.88N (111.55N to 124.43N) compared to those not using design optimization.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.559-564
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• 2001

The design of an automobile mirror actuator system needs a systematic optimization due to several variables, constraints, geometric limitations, moving angle, and so on. Therefore, this article provides the procedure of a genetic algorithm(GA) based optimization with finite element analysis for design of a mirror actuator considering design constraints, geometric limitations, moving angle. Local optimum problem in optimization design with sensitivity analysis is overcome by using zero-order overall searching method which is new optimization design method using a genetic algorithm.

• 한국항공우주학회지
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• 제31권8호
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• pp.27-35
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• 2003

쉘의 기하 모델링과 해석은 각각 다른 배경과 목적을 가지고 발전되어 왔다. 따라서 기하 모델링과 해석을 통합한 설계 도구를 만들기에 기존의 방법은 적절하지 않다. 본 연구에서는 기하 모델링과 해석, 최적 설계를 통합한 개념을 제시한다. 이것은 B-스플라인 곡면의 표현방법에 기초를 두고 있다. 기하학적으로 정확한 쉘 유한요소를 도입하였으며, 최적 설계 부분에서는 곡면의 조정점을 설계변수로 택하였다. 또한 설계 민감도를 계산하기 위해서 준해석적 방법을 사용했고, 이를 바탕으로 순차적 선형계획법을 이용해 곡면의 형상 최적화를 수행하였다. 이렇게 개발된 통합설계 개념은 곡면의 모델링과 해석에 적합한 도구로 이용될 수 있다.

• 한국정보통신학회논문지
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• 제5권4호
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• pp.756-765
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• 2001

An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.