• Title/Summary/Keyword: design objective

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네트워크 특징에 따른 수질-수리 제약조건 기반 상수도관망 다목적 최적 설계 기술개발 (Development of multi-objective optimal design approach for water distribution systems based on water quality-hydraulic constraints according to network characteristic)

  • 고문진;최영환
    • 한국수자원학회논문집
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    • 제55권1호
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    • pp.59-70
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    • 2022
  • 상수도관망은 대표적인 사회기반시설로 수원에서 수용가에게 물을 공급하는 과정에서 병원성 미생물을 소독하기 위해 염소를 주입한다. 안전한 물의 공급을 위해 잔류염소 농도 기준(0.1-4.0 mg/L)을 유지하도록 규정하고 있으나, 사용자의 사용 패턴, 수령, 상수도관망의 형식 및 특징은 수리학적(i.e., 절점의 압력, 관로의 유속) 및 수질적(i.e., 잔류염소 농도) 특징에 영향을 미친다. 따라서, 본 연구에서는 Multi-objective Harmony Search (MOHS)를 사용하여 수질-수리 인자를 고려한 상수도관망 최적 설계 기법을 개발하였다. 설계인자로는 설계비용과 시스템 탄력성을 고려하였으며, 절점의 압력과 잔류염소 농도를 제약조건으로 적용하였다. 도출된 최적설계안은 상수도관망의 형식 및 특징에 따라 분석하였다. 이러한 최적설계안은 경제적인 측면과 수질 측면의 안전성을 충족할 수 있으며, 사용자의 사용성을 증가시킬 수 있다.

Design and optimization of steel trusses using genetic algorithms, parallel computing, and human-computer interaction

  • Agarwal, Pranab;Raich, Anne M.
    • Structural Engineering and Mechanics
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    • 제23권4호
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    • pp.325-337
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    • 2006
  • A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.

Optimal Shape Design of Dielectric Micro Lens Using FDTD and Topology Optimization

  • Chung, Young-Seek;Lee, Byung-Je;Kim, Sung-Chul
    • Journal of the Optical Society of Korea
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    • 제13권2호
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    • pp.286-293
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    • 2009
  • In this paper, we present an optimal shape design method for a dielectric microlens which is used to focus an incoming infrared plane wave in wideband, by exploiting the finite difference time domain (FDTD) technique and the topology optimization technique. Topology optimization is a scheme to search an optimal shape by adjusting the material properties, which are design variables, within the design space. And by introducing the adjoint variable method, we can effectively calculate a derivative of the objective function with respect to the design variable. To verify the proposed method, a shape design problem of a dielectric microlens is tested when illuminated by a transverse electric (TE)-polarized infrared plane wave. In this problem, the design variable is the dielectric constant within the design space of a dielectric microlens. The design objective is to maximally focus the incoming magnetic field at a specific point in wideband.

Reinforced concrete structures with damped seismic buckling-restrained bracing optimization using multi-objective evolutionary niching ChOA

  • Shouhua Liu;Jianfeng Li;Hamidreza Aghajanirefah;Mohammad Khishe;Abbas Khishe;Arsalan Mahmoodzadeh;Banar Fareed Ibrahim
    • Steel and Composite Structures
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    • 제47권2호
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    • pp.147-165
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    • 2023
  • The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

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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Shape & Topology GAs에 의한 트러스의 단면, 형상 및 위상최적설계 (Size, Shape and Topology Optimum Design of Trusses Using Shape & Topology Genetic Algorithms)

  • 박춘욱;여백유;김수원
    • 한국공간정보시스템학회:학술대회논문집
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    • 한국공간정보시스템학회 2004년도 춘계 학술발표회 논문집 제1권1호(통권1호)
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    • pp.43-52
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    • 2004
  • 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 algerian 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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Genetic Algorithm Based Design Optimization of a Six Phase Induction Motor

  • Fazlipour, Z.;Kianinezhad, R.;Razaz, M.
    • Journal of Electrical Engineering and Technology
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    • 제10권3호
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    • pp.1007-1014
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    • 2015
  • An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

Multi-Objective Design Exploration and its Applications

  • Obayashi, Shigeru;Jeong, Shin-Kyu;Shimoyama, Koji;Chiba, Kazuhisa;Morino, Hiroyuki
    • International Journal of Aeronautical and Space Sciences
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    • 제11권4호
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    • pp.247-265
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    • 2010
  • Multi-objective design exploration (MODE) and its applications are reviewed as an attempt to utilize numerical simulation in aerospace engineering design. MODE reveals the structure of the design space based on trade-off information. A self-organizing map (SOM) is incorporated into MODE as a visual data mining tool for the design space. SOM divides the design space into clusters with specific design features. This article reviews existing visual data mining techniques applied to engineering problems. Then, we discuss three applications of MODE: multidisciplinary design optimization for a regional-jet wing, silent supersonic technology demonstrator and centrifugal diffusers.

유전알고리즘을 이용한 로봇구동용 BLDC 형상최적화 (The Optimum Design of BLDC Motor driving a robot by using Genetic Algorithm)

  • 정춘길;이동엽;김규탁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 B
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    • pp.932-934
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    • 2004
  • BLDC Motor is used in robots requiring a precisive motion recently. This paper presents the optimal design reducing the rotor inertia in order to improve the driving characteristic of BLDC motor driving robots, The optimal design was performed by using a parallel Genetic Algorithm which is superior at searching objective functions for the comflicated models having several optimal points. Therefore, objective function for optimization is rotor inertia and efficiency.

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