• 제목/요약/키워드: Method of Size Optimization

검색결과 662건 처리시간 0.042초

관 구조물 파괴에서의 크기효과 (Size Effect in Failure of Tube Structure)

  • Kim, Duk-Hyun;Kim, Doo-Hwan;Kwak, Jin-Sung
    • 한국복합재료학회:학술대회논문집
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    • 한국복합재료학회 2002년도 춘계학술발표대회 논문집
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    • pp.101-104
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    • 2002
  • Almost all buildings/infrastructures made of composite materials are fabricated without proper design. Unlike airplane or automobile parts, prototype test is impossible. One cannot destroy 10 story buildings or 100-meter long bridges. People try to build 100-story buildings or several thousand meter long bridges. In order to realize "composites in construction", the following subjects must be studied in detail, for his design. Concept optimization, Simple method of analysis, Folded plate theory, Size effects in failure, and Critical frequency. Unlike the design procedure with conventional materials, his design should include material design, selection of manufacturing methods, and quality control methods, in addition to the fabrication method. In this paper size/scale effects in failure criteria is briefly explained for practicing engineers.engineers.

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원공배열 결정에 최적기준법에 의한 전동차 크로스 빔의 위상최적화에 관한 연구( I ) (A Study on the Topology Optimization of Electric Vehicle Cross beam using an Optimality Criteria Method in Determination of Arranging Hole( I ))

  • 전형용
    • 한국정밀공학회지
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    • 제19권11호
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    • pp.137-145
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    • 2002
  • Electric vehicle body has to be subjected to uniform load and requires auxiliary equipment such as air pipe and electric wire pipe. Especially, the cross beam supports the weight of passenger and electrical equipments. a lightweight vehicle body is salutary to save operating costs and fuel consumption. Therefore this study is to perform the size and the shape optimization of crossbeam for electric vehicle using the method of topology optimization to introduce the concept of homogenization based on optimality criteria method which is efficient for the problem having the number of design variables and a few boundary condition. this provides the method to determine the optimum position and shape of circular hole in the cross beam and then can achieve the optimal design to reduce weight.

재료조각법을 이용한 위상최적설계 (Topology Optimization Through Material Cloud Method)

  • 장수영;윤성기
    • 대한기계학회논문집A
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    • 제29권1호
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    • pp.22-29
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    • 2005
  • A material cloud method, which is a new topology optimization method, is presented. In MCM, an optimal structure can be found out by manipulating sizes and positions of material clouds, which are lumps of material with specified properties. A numerical analysis for a specific distribution of material clouds is carried out using fixed background finite element mesh. Optimal material distribution can be element-wisely extracted from material clouds' distribution. In MCM, an expansion-reduction procedure of design domain for finding out better optimal solution can be naturally realized. Also the convergence of material distribution is faster and well-defined material distribution with fewer intermediate densities can be obtained. In addition, the control of minimum-member sizes in the material distribution can be realized to some extent. In this paper, basic concept of MCM is introduced, and formulation and optimization results of MCM are compared with those of the traditional density distribution method(DDM).

제약조건 처리기법에 따른 하모니써치 알고리즘의 효율성 평가 : 관로 최소비용설계 문제의 적용 (Efficiency Evaluation of Harmony Search Algorithm according to Constraint Handling Techniques : Application to Optimal Pipe Size Design Problem)

  • 유도근;이호민;이의훈;김중훈
    • 한국산학기술학회논문지
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    • 제16권7호
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    • pp.4999-5008
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    • 2015
  • 제약조건이 있는 공학 최적화 문제에서 보다 좋은 결과를 얻기 위해서는 효율적인 제약조건 처리기법의 적용은 필수적이다. 본 연구에서는 네 가지의 제약조건 처리기법을 적용하여 메타휴리스틱 최적화 기법으로 널리 사용되고 있는 Harmony Search 알고리즘의 최적화 효율성을 평가하였다. 평가를 위해 대표적인 이산형 최적화 문제 중 하나인 상수관로 최소비용설계 문제를 적용하였다. 적용결과 전통적인 제약조건 처리방법으로 사용되던 벌칙함수에 비해 제안된 제약조건 처리기법의 결과가 효율적임을 확인하였다. 특히, ${\varepsilon}$-Constrained Method의 경우 기존방법에 비하여 효율적이고 안정적인 결과를 도출하였다. 제안된 방법은 새로운 최적화 알고리즘의 개발 필요 없이 HS의 성능을 증가시킬 수 있다는 점에서 의의가 있다고 판단된다. 또한 400개 이상의 결정변수를 가지는 대규모 문제의 적용을 통하여, 제안된 방법이 대규모 공학 최적화 문제에서도 활용이 가능함을 확인하였다.

EQPS를 이용한 복합장갑의 해석 및 최적설계 (The analysis and optimization of dual armor plate considering EQPS)

  • 박명수;유정훈;정동택
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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    • pp.111-118
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    • 2004
  • For the precise analysis of high velocity impact problem though FEM with element erosive method, the adequate mesh size and critical equivalent plastic strain(EQPS) is chosen prior to the simulation. In this research, it is strongly required from a standpoint that critical EQPS is used to decide whether perforation occurs or not. The optimization of dual armor plate consisting of 4340 steel and 2024 aluminium against a die steel sphere with high-velocity has been suggested using Lagrangian explicit time-integration code, NET2D. The response surface method based on the design of experiment is utilized for the size optimization. The optimized thickness of each layer, in which perforation does not occur, the strength of multi-layer is maximized and total weight is minimized, is obtained at a constant velocity of a pellet with a designated total thickness.

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진화적 기법을 이용한 유체저장탱크의 슬로싱 저감 최적화 (Sloshing Reduction Optimization of Storage Tank Using Evolutionary Method)

  • 김현수;이영신;김승중;김영완
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 춘계학술대회논문집
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    • pp.410-415
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    • 2004
  • The oscillation of the fluid caused by external forces is call ed sloshing, which occurs in moving vehicles with contained liquid masses, such as trucks, railroad cars, aircraft, and liquid rocket. This sloshing effect could be a severe problem in vehicle stability and control. In this study, the optimization design technique for reduction of the sloshing using evolutionary method is suggested. Two evolutionary methods are employed, respectively the artificial neural network(ANN) and genetic algorithm. An artificial neural network is used for the analysis of sloshing and genetic algorithm is adopted as optimization algorithm. As a result of optimization design, the optimized size and location of the baffle is presented

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Kriging 기반 모델과 매개변수(Adjoint Variable)법을 이용한 항공기형상의 2단계 공력최적설계 (MULTI-STAGE AERODYNAMIC DESIGN OF AIRCRAFT GEOMETRIES BY KRIGING-BASED MODELS AND ADJOINT VARIABLE APPROACH)

  • 임진우;이병준;김종암
    • 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.

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유전자 알고리즘에 의한 평면 및 입체 트러스의 형상 및 위상최적설계 (Shape & Topology Optimum Design of Truss Structures Using Genetic Algorithms)

  • 여백유;박춘욱;강문명
    • 한국공간구조학회논문집
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    • 제2권3호
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    • pp.93-102
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    • 2002
  • The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

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Whale Optimization Algorithm and Blockchain Technology for Intelligent Networks

  • Sulthana, Shazia;Reddy, BN Manjunatha
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.157-164
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    • 2022
  • The proposed privacy preserving scheme has identified the drawbacks of existing schemes in Vehicular Networks. This prototype enhances the number of nodes by decreasing the cluster size. This algorithm is integrated with the whale optimization algorithm and Block Chain Technology. A set of results are done through the NS-2 simulator in the direction to check the effectiveness of proposed algorithm. The proposed method shows better results than with the existing techniques in terms of Delay, Drop, Delivery ratio, Overhead, throughout under the denial of attack.

Practical optimization of power transmission towers using the RBF-based ABC algorithm

  • Taheri, Faezeh;Ghasemi, Mohammad Reza;Dizangian, Babak
    • Structural Engineering and Mechanics
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    • 제73권4호
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    • pp.463-479
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    • 2020
  • This paper is aimed to address a simultaneous optimization of the size, shape, and topology of steel lattice towers through a combination of the radial basis function (RBF) neural networks and the artificial bee colony (ABC) metaheuristic algorithm to reduce the computational time because mere metaheuristic optimization algorithms require much time for calculations. To verify the results, use has been made of the CIGRE Tower and a 132 kV transmission towers as numerical examples both based on the design requirements of the ASCE10-97, and the size, shape, and topology have been optimized (in both cases) once by the RBF neural network and once by the MSTOWER analyzer. A comparison of the results shows that the neural network-based method has been able to yield acceptable results through much less computational time.