• Advances in Computational Design
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• 제2권4호
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• 대한기계학회논문집A
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• 제35권2호
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• pp.183-190
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• 2011

최근 이동통신 가입자의 증가로 인해 기지국의 수요도 증가하게 되었다. 하지만 기지국 설치 장소의 부족으로 인해 이동통신모듈의 크기가 소형화 되어야 할 필요성이 생겼다. 이동통신모듈의 소형화를 위해서는 모듈 겉면에 부착된 히트싱크의 크기가 소형화 되어야 한다. 또한 모듈의 열적 안정성을 보장하기 위해 설치된 전자부품의 온도가 허용온도보다 낮아야 한다. 이를 위해 상용 PIDO(Process Integration and Design Optimization) 툴인 PIAnO와 전산유체역학 프로그램인 FLOTHERM을 사용하여 전자부품의 온도를 허용온도보다 낮게 유지시키면서 히트싱크의 부피를 최소화하였다. 그 결과, 이동통신 모듈에 설치된 전자부품의 허용온도를 만족하면서 모듈의 부피를 41.9% 감소시킬 수 있었다.

• 한국공간구조학회:학술대회논문집
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• 한국공간구조학회 2005년도 춘계학술발표회 및 정기총회 2권1호(통권2호)
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• pp.246-253
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algorithm are searching methods for optimum values. The object of this reserch is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic one, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm

• Advances in Computational Design
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• 제1권3호
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.145-146
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• 2010

• 한국CDE학회논문집
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• 제12권5호
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• pp.376-381
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• 2007

The geometric configuration in the weight-reduced structure is very required to be started from the conceptual design with low cost, high performance and quality. In this point, a structural-topological shape concerned with conceptual design of structure is important. The method used in this paper combines three optimization techniques, where the shape and physical dimensions of the structure and material distribution are hierachically optimized, with the maximum rigidity of structure and lightweight.

• International Journal of Automotive Technology
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• 제6권6호
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• pp.643-655
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• 2005

The frontal crash optimization of S-shaped closed-hat section member using the homogenization method, design of experiment (DOE) and response surface method (RSM) was studied. The optimization to effectively absorb more crash energy was studied to introduce the reinforcement design. The main focus of design was to decide the optimum size and thickness of reinforcement. In this study, the location of reinforcement was decided by homogenization method. Also, the effective size and thickness of reinforcements was studied by design of experiments and response surface method. The effects of various impact velocity for reinforcement design were researched. The high impact velocity reinforcement design showed to absorb the more crash energy than low velocities design. The effect of size and thickness of reinforcement was studied and the sensitivity of size and thickness was different according to base thickness of model. The optimum size and thickness of the reinforcement has shown a direct proportion to the thickness of base model. Also, the thicker the base model was, the effect of optimization using reinforcement was the bigger. The trend curve for effective size and thickness of reinforcement using response surface method was obtained. The predicted size and thickness of reinforcement by RSM were compared with results of DOE. The results of a specific dynamic mean crushing loads for the predicted design by RSM were shown the small difference with the predicted results by RSM and DOE. These trend curves can be used as a basic guideline to find the optimum reinforcement design for S-shaped member.

• Journal of Mechanical Science and Technology
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• 제16권5호
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• pp.609-618
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• 2002

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as collaborative optimization (CO) and individual discipline feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method.

• Journal of Mechanical Science and Technology
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• 제18권2호
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• pp.253-261
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• 2004

A simple and effective filtering method to control the member size of an optimized structure is proposed for topology optimization. In the present approach, the original objective sensitivities are replaced with their relative values evaluated within a filtering area. By adjusting the size of the filtering area, the member size of an optimized structure or the level of its topological complexity can be controlled even within a given finite element mesh. In contrast to the checkerboard-free filter, the present filter focuses on high-frequency components of the sensitivities. Since the present filtering method does not add a penalty term to the objective function nor require additional constraints, it is not only efficient but also simple to implement. Mean compliance minimization and eigenfrequency maximization problems are considered to verify the effectiveness of the present approach.

• 한국전산구조공학회논문집
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• 제14권3호
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• pp.277-286
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• 2001

자동차 경량화를 지향하는 초경량차체 기술 중에서 합체박판기술을 이용한 수 있는 일련의 최적설계 기법을 제안하고 기존의 자동차 도어 내판에 적용하여 경량화를 수행하였다. 먼저, 내판에 부착되는 보강재를 제거한 후 취약해진 강성을 보강하기 위한 파트 선정을 위해 위상 최적설계를 수행하여 대략적인 파트 분포를 결정하였다. 그 다음 상세설계 단계로서 각 파트의 두께는 치수 최적설계를 이용하여 정하고, 형상 최적설계로 최종 용접선을 결정하였다. 이러한 일련의 최적화를 위해 상용 소프트웨어인 GENESIS가 사용되었다.