• Title/Summary/Keyword: structure optimization

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Study on Design Optimization of Degasser Baffles using CFD (전산유체역학을 이용한 Degasser Baffle최적설계 연구)

  • Sur, Jong-Mu;Im, Hyonam;Lee, In-Su;Lee, Heesung;Choi, Jaewoong
    • Journal of Ocean Engineering and Technology
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    • v.29 no.5
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    • pp.331-341
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    • 2015
  • A degasser is a separation unit used in drilling to separate gas from the drilling mud. The degasser used in offshore drilling was developed at an early stage of drilling. Since its development, the design of the degasser’s internal structure has been optimized, with many limitations due to the restrictions of experimental and computational performance measurement methods. Despite the recent development of CFD technology for multiphase flow analysis, CFD has only been used in a limited way for degasser internal flow analysis and design optimization. In this study, a design optimization procedure for a degasser’s internal structure design was proposed, and CFD analyses of three types of internal structural designs were performed to evaluate the separation performance. The CFD result for each design type was used for the design optimization and, as the result, an optimized design is proposed.

Optimum parameterization in grillage design under a worst point load

  • Kim Yun-Young;Ko Jae-Yang
    • Journal of Navigation and Port Research
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    • v.30 no.2
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    • pp.137-143
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    • 2006
  • The optimum grillage design belongs to nonlinear constrained optimization problem. The determination of beam scantlings for the grillage structure is a very crucial matter out of whole structural design process. The performance of optimization methods, based on penalty functions, is highly problem-dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm ($R{\mu}GA$) is proposed to find the optimum beam scantlings of the grillage structure without handling any of penalty functions. $R{\mu}GA$ can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. Direct stiffness method is used as a numerical tool for the grillage analysis. In optimization study to find minimum weight, sensitivity study is carried out with varying beam configurations. From the simulation results, it has been concluded that the proposed $R{\mu}GA$ is an effective optimization tool for solving continuous and/or discrete nonlinear real-world optimization problems.

A Feasibility Study on the Application of the Topology Optimization Method for Structural Damage Identification (구조물의 결함 규명을 위한 위상최적설계 기법의 적용가능성 연구)

  • Lee, Joong-Seok;Kim, Jae-Eun;Kim, Yoon-Young
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.2 s.107
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    • pp.115-123
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    • 2006
  • A feasibility of using the topology optimization method for structural damage identification is investigated for the first time. The frequency response functions (FRFs) are assumed to be constructed by the finite element models of damaged and undamaged structures. In addition to commonly used resonances, antiresonances are employed as the damage identifying modal parameters. For the topology optimization formulation, the modal parameters of the undamaged structure are made to approach those of the damaged structure by means of the constraint equations, while the objective function is an explicit penalty function requiring clear black-and-white images. The developed formulation is especially suitable for damage identification problems dealing with many modal parameters. Although relatively simple numerical problems were considered in this investigation, the possibility of using the topology optimization method for structural damage identification is suggested through this research.

Structural optimal control based on explicit time-domain method

  • Taicong Chen;Houzuo Guo;Cheng Su
    • Structural Engineering and Mechanics
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    • v.85 no.5
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    • pp.607-620
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    • 2023
  • The classical optimal control (COC) method has been widely used for linear quadratic regulator (LQR) problems of structural control. However, the equation of motion of the structure is incorporated into the optimization model as the constraint condition for the LQR problem, which needs to be solved through the Riccati equation under certain assumptions. In this study, an explicit optimal control (EOC) method is proposed based on the explicit time-domain method (ETDM). By use of the explicit formulation of structural responses, the LQR problem with the constraint of equation of motion can be transformed into an unconstrained optimization problem, and therefore the control law can be derived directly without solving the Riccati equation. To further optimize the weighting parameters adopted in the control law using the gradient-based optimization algorithm, the sensitivities of structural responses and control forces with respect to the weighting parameters are derived analytically based on the explicit expressions of dynamic responses of the controlled structure. Two numerical examples are investigated to demonstrate the feasibility of the EOC method and the optimization scheme for weighting parameters involved in the control law.

A Network-based Optimization Model for Effective Target Selection (핵심 노드 선정을 위한 네트워크 기반 최적화 모델)

  • Jinho Lee;Kihyun Lee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.4
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    • pp.53-62
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    • 2023
  • Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

A Historical Review of Design Activities and a New-Concept Software System for Structural Optimization (설계활동의 역사적 흐름과 새로운 개념에 의한 구조최적설계 소프트웨어 소개)

  • Kwak, Byung-Man
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.17-21
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    • 2001
  • Theories for optimal design and optimization algorithms have long been well developed. In industries, however, they are not well practiced. To make them work for industry, a new philosophy is necessary and an integration of various software systems required. A review of the history in the aspect of optimal design software is made and a newly developed code DS-Structure is introduced.

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STUDY ON THE OPTIMAL PLANAR ARRAY STRUCTURE WITH TRIANGULAR LATTICE FOR SIDE-LOBE REDUCTION (삼각 격자구조를 갖는 평면배열 안테나의 부엽 레벨 감소를 위한 최적 평면배열 형상에 관한 연구)

  • 배지훈;성낙선;이태윤;김종면;표철식
    • Proceedings of the Korea Electromagnetic Engineering Society Conference
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    • 2002.11a
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    • pp.250-254
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    • 2002
  • In this paper, we design an optimized planar array structure with triangular lattice for side-lobe reduction using a genetic algorithm. A constraint optimization is implemented by optimally removing some outer array elements far from the array center. It is shown that only the proper array shape without optimizing the magnitudes and phases of each array antenna can give low side-lobe level with a slight main beam broadening.

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Study on the Optimization of LDD MOSFET (LDD MOSFET의 최적화에 관한 연구)

  • Dal Soo Kim
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.3
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    • pp.478-485
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    • 1987
  • Optimization of the sub-micron N-channel MOSFET with the LDD(Lightly Doped Drain)structure has been investigated. LDD devices with various length of n-region, n-dose and n-implantation species were fabricated for this purpose. It will be shown that LDD devices have lower substrate current by an order of magnitude and higher breakdown voltage than the conventional devices with comparable channel length. Optimized LDD structure has been found when the sidewall thickness is 2500\ulcorner and n-region is phosphorus implantd with the dose of 1.0E13/cm\ulcorner It has been found that transconductance degradation is less than 20%.

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Structural design using topology and shape optimization

  • Lee, Eun-Hyung;Park, Jaegyun
    • Structural Engineering and Mechanics
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    • v.38 no.4
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    • pp.517-527
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    • 2011
  • A topology optimization and shape optimization method are widely used in the design area of engineering field. In this paper, a unified procedure to combine both topology and shape optimization method is used. A material distribution method is used first to extract necessary design parameters of the structure and a shape optimization scheme using genetic algorithm and satisfying all the condition follows. As an example, a GFRP bridge deck is designed and compared with other commercial products. The performance of the designed deck shows that the used design procedure is very efficient and safe. This procedure can be generalized for using in other areas of engineering.

Optimization of Fuzzy Set Fuzzy Model by Means of Hierarchical Fair Competition-based Parallel Genetic Algorithms (계층적 경쟁기반 병렬 유전자 알고리즘을 이용한 퍼지집합 퍼지모델의 최적화)

  • Choi, Jeoung-Nae;Oh, Sung-Kwun;Hwang, Hyung-Soo
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.2097-2098
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    • 2006
  • In this study, we introduce the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA). HFCGA is a kind of multi-populations of Parallel Genetic Algorithms(PGA), and it is used for structure optimization and parameter identification of fuzzy set model. It concerns the fuzzy model-related parameters as the number of input variables, a collection of specific subset of input variables, the number of membership functions, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

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