• 대한기계학회논문집A
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• 제24권8호
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• pp.1940-1948
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• 2000

A design method for maximizing fatigue life of the deep groove ball bearing without enlarging mounting space is proposed by using a genetic algorithm. The use of gradient-based optimization methods for the design of the bearing is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. Constrains for manufacturing are applied in optimization scheme. Results obtained for several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increased about 9-34% compared with the standard ones.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2001년도 학술발표회 발표논문집
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• pp.129-135
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• 2001

The optimum design problems for the design of counterforted wall were formulated and computer programing to solve these problems were developed in this study. Both discrete optimization and continuous optimization method were applied to the design of counterforted wall and the results of these optimization methods were compared each other.

• 한국구조물진단유지관리공학회 논문집
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• 제9권1호
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• pp.259-269
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• 2005

본 연구에서는 철근콘크리트 연속보의 이산최적설계를 수행하기 위해서 유전알고리즘을 적용하였다. 콘크리트, 거푸집, 주철근 및 스터럽의 경비를 포함한 경비 최소화를 목적함수로 하였고, 제약조건으로는 휨강도와 전단강도, 처짐, 균열, 철근간격, 피복두께, 철근비 상 하한치 및 단면형상에 대한 기하학적 제약조건과 더불어 주철근의 정착을 고려하였다. 보의 폭과 유효깊이, 철근량을 설계변수로 취하였으며, 설계변수 값은 실무에서 사용되는 단면치수와 철근량을 데이터베이스화한 이산집합으로부터 선택되도록 하였다. GA의 신뢰성을 검증하기 위해서 이산변수로 철근콘크리트보에 대한 최적설계를 수행한 기존 문헌과 그 결과값을 비교 검토하였으며, GA의 적용성 및 효율성을 보이기 위하여 국내 구조설계기준을 만족하는 3경간 및 5경간 철근콘크리트보에 대해 이산최적설계를 수행하였다.

• 전산구조공학
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• 제10권2호
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• pp.255-263
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• 1997

실제로 구조시스템들의 최적설계는 설계변수가 연속값이 아닌 이산값을 요하는 경우가 대부분이다. 본 논문은 이산형 설계변수를 갖는 비대칭 복합 적층평판에 대해 선형 근사화방법을 이용한 이산최적설계를 수행하였으며, 이 방법이 매우 효율적임을 보였다. 대상 문제는 축력, 전단력, 그리고 휨과 비틀림 모멘트의 평면 내하중들(in-plane loads)의 다중하중조건을 받는 것으로 고려하였으며, 복합 적층평판을 구성하는 플라이들에 대한 최대변형률 규준을 설계 제약조건으로 부과하였다. 이산 최적화를 위한 초기 접근방법으로 단 한번의 연속변수 최적화 과정이 FDM(Feasible Direction Method)을 이용하여 수행되었으며, 차후 이산 및 연속변수를 포함하는 비선형 이산최적화문제를 SLDP(Sequential Linear Discrete Programming)방법에 의해 선형 근사화된 혼합정수계획문제로 형성하여 풀었다. 수치예에서 6개의 플라이로 구성된 비대칭 복합 적층평판을 대상으로 회전식 적층배열([(90-.theta.)/-(60+.theta.)/-.theta./-(45+.theta.)/(45-.theta.)]/sub s/)에 따른 이산최적해를 구하였다. 효율성 입증을 위해 똑같은 문제를 비선형 분기한계법을 이용하여 풀었으며, 그 결과를 비교 분석하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.786-792
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• 2006

The design of experiment(DOE) with orthogonal arrays is adopted when the engineering design is needed in a discrete design space. In this research, a design process with orthogonal array is peformed to obtain the optimum design which satisfy the frequency target of the steering system. The optimum design is determined from the analysis of means(ANOM) and sensitivity information about design variables is evaluated by the analysis of variance(ANOVA). Interactions between design variables are investigated to achieve additivity which should be valid in using orthogonal array. It is shown that when strong interactions exist, the DOE process with orthogonal array considering interaction is introduced to find out optimum design.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2001년도 제34회 추계학술대회 개최
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• pp.166-171
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design for the application-based exclusive rolling element bearings, this study propose design methodologies by using a genetic-based combinatorial optimization. By the presence of discrete variables such as the number of rolling element (standard component) and by the engineering point of views, the design problem of the rolling element bearing can be characterized by the combinatorial optimization problem as a fully discrete optimization. A genetic algorithm is used to efficiently find a set of the optimum discrete design values from the pre-defined variable sets. To effectively deal with the design constraints and the multi-objective problem, a ranking penalty method is suggested for constructing a fitness function in the genetic-based combinatorial optimization. To evaluate the proposed design method, a robust performance analyzer of ball bearing based on quasi-static analysis is developed and the computer program is applied to some design problems, 1) maximize fatigue life, 2) maximize stiffness, 3) maximize fatigue life and stiffness, of a angular contact ball bearing. Optimum design results are demonstrate the effectiveness of the design method suggested in this study. It believed that the proposed methodologies can be effectively applied to other multi-objective discrete optimization problems.

• 한국공간구조학회논문집
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• 제2권3호
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• pp.61-70
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• 2002

The objective of this study is the development of a size and shape discrete optimum design algorithms, which is based on the genetic algorithms and the fuzzy theory. This algorithms can perform both size and shape optimum designs of plane and space trusses. The developed fuzzy shape-GAs (FS-GAs) was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. This study solves the problem by introducing the FS-GAs operators into the genetic.

• 한국기계가공학회지
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• 제19권5호
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• pp.27-37
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• 2020

Structural optimization problems with discrete design variables require more function calculations (or finite element analyses) than those in the continuous design space. In this study, a method to find an optimal solution in the discrete design of the truss structure is presented, reducing the number of function calculations. Because a continuous optimal solution is the Karush-Kuhn-Tucker point that satisfies the optimality condition, it is assumed that the discrete optimal solution is around the continuous optimum. Then, response values such as weight, displacement, and stress are predicted using approximate models-referred to as hybrid metamodels-within specified design ranges. The discrete design method using the hybrid metamodels is used as a post-process of the continuous optimization process. Standard truss design problems of 10-bar, 25-bar, 15-bar, and 52-bar are solved to show the usefulness of this method. The results are compared with those of existing methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.408-413
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• 2001

The structural optimization is carried out in the continuous design space or discrete design space. Methods for discrete variables such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions for constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1995년도 가을 학술발표회 논문집
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• pp.9-16
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• 1995

This study presents the applicable possibility of numerical optimization and Genetic Algorithm in the design of truss structures using discrete variables and real constraints. The introduction of Genetic Algorithm in the design of truss structures enables us to do easier formulation and handle discrete variables. To investigate these applicable possibility, the design of 15 - bar truss structures has been studied using GT/STRUDL and Genetic Algorithm and the results of Genetic Algorithm are compared with GT/STRUDL's.