• Title/Summary/Keyword: Structural design optimization

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Development and Application of Metropolis Genetic Algorithm for the Structural Design Optimization (구조물의 설계 최적화를 위한 메트로폴리스 유전알고리즘의 개발 및 적용)

  • 박균빈;류연선;김정태;조현만
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.10a
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    • pp.115-122
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    • 2003
  • A Metropolis genetic algorithm(MGA) is developed and applied for the structural design optimization. In MGA favorable features of Metropolis algorithm in simulated annealing(SA) are incorporated in simple genetic algorithm(SGA), so that the MGA alleviates the disadvantage of finding imprecise solution in SGA and time-consuming computation in SA. Performances of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro genetic algorithm(μGA), and Kirkpatrick's SA. Typical numerical examples are used to evaluate the favorable features and applicability of MGA From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA is a reliable and efficient tool for structural design optimization.

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Optimal design of pitched roof frames with tapered members using ECBO algorithm

  • Kaveh, Ali;Mahdavi, Vahid Reza;Kamalinejad, Mohammad
    • Smart Structures and Systems
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    • v.19 no.6
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    • pp.643-652
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    • 2017
  • Pitched roof frames are widely used in construction of the industrial buildings, gyms, schools and colleges, fire stations, storages, hangars and many other low rise structures. The weight and shape of the gable frames with tapered members, as a familiar group of the pitched roof frames, are highly dependent on the properties of the member cross-sectional. In this work Enhanced Colliding Bodies Optimization (ECBO) is utilized for optimal design of three gable frames with tapered members. In order to optimize the frames, the design is performed using the AISC specifications for stress, displacement and stability constraints. The design constraints and weight of the gable frames are computed from the cross-section of members. These optimum weights are obtained using aforementioned optimization algorithms considering the cross-sections of the members and design constraints as optimization variables and constraints, respectively. A comparative study of the PSO and CBO with ECBO is also performed to illustrate the importance of the enhancement of the utilized optimization algorithm.

Structural Design of a Front Lower Control Arm Considering Durability (내구성을 고려한 하부 컨트롤 암의 구조설계)

  • Park, Han-Seok;Kim, Jong-Kyu;Seo, Sun-Min;Lee, Kwon-Hee;Park, Young-Chul
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.8 no.4
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    • pp.69-75
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    • 2009
  • Recently developed automotive components are getting lighter providing a higher fuel efficiency and performance. Following the current trend, this study proposes a structural optimization method for the lower control arm installed at the front side of a Vehicle. Lightweight design of lower control arm can be achieved through design and material technology. In this research, the shape of lower control arm was determined by applying the optimization technology and aluminum was selected as a steel-substitute material. Strength performance is the most important design requirement in the structural design of a control arm. This study considers the static strength in the optimization process. For the optimum design, the durability analysis is performed to predict its fatigue life. In this study, the kriging interpolation method is adopted to obtain the minimum weight satisfying the strength constraint. Optimum designs are obtained by the in-house program, EXCEL-Kriging. Also, based on the optimum model obtained for the static strength, the optimization of Index of Fatigue Durability is carried out to get th optimum fatigue performance.

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An Improved Element Removal Method for Evolutionary Structural Optimization

  • Han, Seog-Young
    • Journal of Mechanical Science and Technology
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    • v.14 no.9
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    • pp.913-919
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    • 2000
  • The purpose of this study was to develop a new element removal method for ESO (Evolutionary Structural Optimization), which is one of the topology optimization methods. ESO starts with the maximum allowable design space and the optimal topology emerges by a process of removal of lowly stressed elements. The element removal ratio of ESO is fixed throughout topology optimization at 1 or 2%. BESO (bidirectional ESO) starts with either the least number of elements connecting the loads to the supports, or an initial design domain that fits within the maximum allowable domain, and the optimal topology evolves by adding or subtracting elements. But the convergence rate of BESO is also very slow. In this paper, a new element removal method for ESO was developed for improvement of the convergence rate. Then it was applied to the same problems as those in papers published previously. From the results, it was verified that the convergence rate was significantly improved compared with ESO as well as BESO.

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Structural Optimization using Reliability Analysis (신뢰성 해석을 이용한 구조최적화)

  • Park, Jae-Yong;Lim, Min-Kyu;Oh, Young-Kyu;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.2
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    • pp.224-229
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    • 2010
  • This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic topology optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. RBTO based on BESO starting from various design domains produces a similar optimal topology each other. Numerical examples are presented to compare the DTO with the RBTO.

A Study on the Multi-Objective Optimization of Impeller for High-Power Centrifugal Compressor

  • Kang, Hyun-Su;Kim, Youn-Jea
    • International Journal of Fluid Machinery and Systems
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    • v.9 no.2
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    • pp.143-149
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    • 2016
  • In this study, a method for the multi-objective optimization of an impeller for a centrifugal compressor using fluid-structure interaction (FSI) and response surface method (RSM) was proposed. Numerical simulation was conducted using ANSYS CFX and Mechanical with various configurations of impeller geometry. Each design parameter was divided into 3 levels. A total of 15 design points were planned using Box-Behnken design, which is one of the design of experiment (DOE) techniques. Response surfaces based on the results of the DOE were used to find the optimal shape of the impeller. Two objective functions, isentropic efficiency and equivalent stress were selected. Each objective function is an important factor of aerodynamic performance and structural safety. The entire process of optimization was conducted using the ANSYS Design Xplorer (DX). The trade-off between the two objectives was analyzed in the light of Pareto-optimal solutions. Through the optimization, the structural safety and aerodynamic performance of the centrifugal compressor were increased.

Structural optimization of stiffener layout for stiffened plate using hybrid GA

  • Putra, Gerry Liston;Kitamura, Mitsuru;Takezawa, Akihiro
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.11 no.2
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    • pp.809-818
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    • 2019
  • The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO2 emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.

Optimal design of reinforced concrete beams: A review

  • Rahmanian, Ima;Lucet, Yves;Tesfamariam, Solomon
    • Computers and Concrete
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    • v.13 no.4
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    • pp.457-482
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    • 2014
  • This paper summarizes available literature on the optimization of reinforced concrete (RC) beams. The objective of optimization (e.g. minimum cost or weight), the design variables and the constraints considered by different studies vary widely and therefore, different optimization methods have been employed to provide the optimal design of RC beams, whether as isolated structural components or as part of a structural frame. The review of literature suggests that nonlinear deterministic approaches can be efficiently employed to provide optimal design of RC beams, given the small number of variables. This paper also presents spreadsheet implementation of cost optimization of RC beams in the familiar MS Excel environment to illustrate the efficiency of the exhaustive enumeration method for such small discrete search spaces and to promote its use by engineers and researchers. Furthermore, a sensitivity analysis is performed on the contribution of various design parameters to the variability of the overall cost of RC beams.

Concurrent topology optimization of composite macrostructure and microstructure under uncertain dynamic loads

  • Cai, Jinhu;Yang, Zhijie;Wang, Chunjie;Ding, Jianzhong
    • Structural Engineering and Mechanics
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    • v.81 no.3
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    • pp.267-280
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    • 2022
  • Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm

  • Park, Joo-Shin;Kim, Yun-Young
    • Journal of Navigation and Port Research
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    • v.33 no.9
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    • pp.635-644
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    • 2009
  • The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.