• 제목/요약/키워드: optimization by direct search

검색결과 52건 처리시간 0.027초

Development of The New High Specific Speed Fixed Blade Turbine Runner

  • Skotak, Ales;Mikulasek, Josef;Obrovsky, Jiri
    • International Journal of Fluid Machinery and Systems
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    • 제2권4호
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    • pp.392-399
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    • 2009
  • The paper concerns the description of the step by step development process of the new fixed blade runner called "Mixer" suitable for the uprating of the Francis turbines units installed at the older low head hydropower plants. In the paper the details of hydraulic and mechanical design are presented. Since the rotational speed of the new runner is significantly higher then the rotational speed of the original Francis one, the direct coupling of the turbine to the generator can be applied. The maximum efficiency at prescribed operational point was reached by the geometry optimization of two most important components. In the first step the optimization of the draft tube geometry was carried out. The condition for the draft tube geometry optimization was to design the new geometry of the draft tube within the original bad draft tube shape without any extensive civil works. The runner blade geometry optimization was carried out on the runner coupled with the draft tube domain. The blade geometry of the runner was optimized using automatic direct search optimization procedure. The method used for the objective function minimum search is a kind of the Nelder-Mead simplex method. The objective function concerns efficiency, required net head and cavitation features. After successful hydraulic design the modal and stress analysis was carried out on the prototype scale runner. The static pressure distribution from flow simulation was used as a load condition. The modal analysis in air and in water was carried out and the results were compared. The final runner was manufactured in model scale and it is going to be tested in hydraulic laboratory. Since the turbine with the fixed blade runner does not allow double regulation like in case of full Kaplan turbine, it can be profitably used mainly at power plants with smaller changes of operational conditions or in case with more units installed. The advantages are simple manufacturing, installation and therefore lower expenses and short delivery time for turbine uprating.

유전자 알고리즘을 이용한 차량 승차감 개선에 관한 연구 (A Study on the Improvement of Vehicle Ride Comfort by Genetic Algorithms)

  • 백운태;성활경
    • 한국자동차공학회논문집
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    • 제6권4호
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    • pp.76-85
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    • 1998
  • Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

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구조최적설계시 직접법 및 근사법 알고리즘의 성능 비교에 관한 연구 (A Study on the Comparison of Performances Between Direct Method and Approximation Method in Structural Optimization)

  • 박영선;이상헌;박경진
    • 대한기계학회논문집
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    • 제18권2호
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    • pp.313-322
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    • 1994
  • Structural optimization has been developed by two methods. One is the direct method which applies the Nonlinear Programming (NLP) algorithm directly to the structural optimization problem. This method is known to be very excellent mathematically. However, it is very expensive for large-scale problems due to the one-dimensional line search. The other method is the approximation method which utilizes the engineering senses very well. The original problem is approximated to a simple problem and an NLP algorithm is adopted for solving the approximated problems. Practical solutions are obtained with low cost by this method. The two methods are compared through standard structural optimization problems. The Finite element method with truss and beam elements is used for the structural and sensitivity analyses. The results are analyzed based on the convergence performances, the number is function calculations, the quality of the cost functions, and etc. The applications of both methods are also discussed.

Reliability-based design optimization of structural systems using a hybrid genetic algorithm

  • Abbasnia, Reza;Shayanfar, Mohsenali;Khodam, Ali
    • Structural Engineering and Mechanics
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    • 제52권6호
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    • pp.1099-1120
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    • 2014
  • In this paper, reliability-based design optimization (RBDO) of structures is addressed. For this purpose, the global search and optimization capabilities of genetic algorithm (GA) are combined with the efficiency and reasonable accuracy of an advanced moment-based finite element reliability method. For performing RBDO, three variants of GA including a real-coded, a binary-coded and an improved binary-coded GA are developed. In these methods, GA performs (finite element) reliability analyses to evaluate reliability constraints. For truss structures which include finite element modeling, reliability constraints are evaluated using finite element reliability analysis. Response sensitivity required for finite element reliability analysis is obtained by direct differentiation method (DDM) rather than finite difference method (FDM). The proposed methods are examined within four standard test examples and real-world design problems. The results illustrate the superiority and efficiency of the improved binary-coded GA. Results also illustrate that DDM significantly reduces the computational cost and improves the efficiency of the optimization procedure.

U자형 리브의 최적설계에 의한 사출제품의 휨 최소화 (Minimization of Warpage in Injection-molded Parts By Optimal Design of U-type Ribs)

  • 박종천;김광호;김경모;구본흥
    • 한국기계가공학회지
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    • 제7권1호
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    • pp.53-61
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    • 2008
  • In this research, the layout and geometry of U-type ribs in the part, including significant process conditions, are automatically optimized to reduce part warpage with robustness in consideration. The optimization procedure are based on an iterative redesign methodology integrated with computer aided injection molding simulation, Taguchi's Design of Experiment(DOE), and a direct search-based optimization method. The robustness of a design alternative is efficiently measured by introducing composite noise factor and Taguchi's signal-to-noise ratio. As a solution search methodology, the modified design space reduction method based on orthogonal arrays is employed to exploit an optimal robust design alternative. To illustrate the proposed methodology, a case study is performed on simulation results, where an optimal robust design alternative is obtained with a moderate number of iterations.

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Locationing of telemanipulator based on task capability

  • Park, Young-Soo;Yoon, Jisup;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.392-395
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    • 1995
  • This paper presents a time efficient method for determining a sequence of locations of a mobile manipulator that facilitates tracking of continuous path in cluttered environment. Given the task trajectory in the form of octree data structure, the algorithm performs characterization of task space and subsequent multistage optimization process to determine task feasible locations of the robot. Firstly, the collision free portion of the trajectory is determined and classified according to uniqueness domains of the inverse kinematics solutions. Then by implementing the extent of task feasible subspace into an optimization criteria, a multistage optimization problem is formulated to determines the task feasible locations of the mobile manipulator. The effectiveness of the proposed method is shown through a simulation study performed for a 3-d.o.f. manipulator with generic kinematic structure.

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FEA based optimization of semi-submersible floater considering buckling and yield strength

  • Jang, Beom-Seon;Kim, Jae Dong;Park, Tae-Yoon;Jeon, Sang Bae
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제11권1호
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    • pp.82-96
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    • 2019
  • A semi-submersible structure has been widely used for offshore drilling and production of oil and gas. The small water plane area makes the structure very sensitive to weight increase in terms of payload and stability. Therefore, it is necessary to lighten the substructure from the early design stage. This study aims at an optimization of hull structure based on a sophisticated yield and buckling strength in accordance with classification rules. An in-house strength assessment system is developed to automate the procedure such as a generation of buckling panels, a collection of required panel information, automatic buckling and yield check and so on. The developed system enables an automatic yield and buckling strength check of all panels composing the hull structure at each iteration of the optimization. Design variables are plate thickness and stiffener section profiles. In order to overcome the difficulty of large number of design variables and the computational burden of FE analysis, various methods are proposed. The steepest descent method is selected as the optimization algorithm for an efficient search. For a reduction of the number of design variables and a direct application to practical design, the stiffener section variable is determined by selecting one from a pre-defined standard library. Plate thickness is also discretized at 0.5t interval. The number of FE analysis is reduced by using equations to analytically estimating the stress changes in gradient calculation and line search steps. As an endeavor to robust optimization, the number of design variables to be simultaneously optimized is divided by grouping the scantling variables by the plane. A sequential optimization is performed group by group. As a verification example, a central column of a semi-submersible structure is optimized and compared with a conventional optimization of all design variables at once.

Direct Search Methods for Nonlinear Optimization Problem used ART Theory

  • 손준혁;서보혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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    • pp.1830-1831
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    • 2006
  • In this paper, the search is conducted along each of the coordinate directions for finding the minimum. If $e_i$ is the unit vector along the coordinate direction i, we determine the value a, minimizing f(a)= $f(x+ae_i)$, where a is a real number. A move is made to the new point $x+a_ie_i$ at the end of the search along the direction i. In an n dimensional problem, we define the search along all the directions as one stage. The function value at the end of the stage is compared to the value at the beginning of the stage in establishing the convergence. The gradient appears to be zero at point. We can safeguard this by introducing an acceleration step of one additional step along the pattern direction developed by moves along the coordinate directions.

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Genetic Algorithm과 Expert System의 결합 알고리즘을 이용한 직구동형 풍력발전기 최적설계 (Optimal Design of Direct-Driven Wind Generator Using Genetic Algorithm Combined with Expert System)

  • 김상훈;정상용
    • 조명전기설비학회논문지
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    • 제24권10호
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    • pp.149-156
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    • 2010
  • In this paper, the optimal design of a wind generator, implemented with the hybridized GA(Genetic Algorithm) and ES(Expert System), has been performed to maximize the AEP(Annual Energy Production) over the whole wind speed characterized by the statistical model of wind speed distribution. In particular, to solve the problem of calculation iterate, ES finds the superior individual and apply to initial generation of GA and it makes reduction of search domain. Meanwhile, for effective searching in reduced search domain, it propose Intelligent GA algorithm. Also, it shows the results of optimized model 500[kW] wind generator using hybridized algorithm and benchmark result of compare with GA.

AI 기반 설계 탐색 기법을 통한 선박의 주요 치수 최적화 (A Study on the Optimization of Main Dimensions of a Ship by Design Search Techniques based on the AI)

  • 박동우;김인섭
    • 해양환경안전학회지
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    • 제28권7호
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    • pp.1231-1237
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    • 2022
  • 본 논문에서는 AI 기반 설계 탐색 기법을 활용하여 선박의 주요 치수 최적화를 수행하였다. 설계 탐색 기법은 최적화 프로그램 HEEDS의 SHERPA 알고리즘을 사용하였다. 유동 해석은 상용 CFD 코드인 STAR-CCM+를 사용하였고, 주요 치수 변환은 전처리 과정에서 JAVA Script와 Python을 사용하여 선박의 치수가 자동으로 변환되도록 설정하였다. 대상 선박은 소형 쌍동선형으로 주요 치수 최적화는 한쪽 선형의 길이, 폭, 흘수 그리고 단동선형 간의 간격에 대하여 수행되었다. 최적화 알고리즘에 사용된 목적함수는 총저항이며, 내부 의장 시스템의 크기 등을 고려한 배수 체적의 범위를 제한조건으로 선정하였다. 그 결과 최적 선형의 주요 치수는 기존 선형 대비 ±5% 내에서 변화가 있었고 총저항은 약 11% 개선된 결과를 보였다. 본 연구를 통해 선박의 형상을 직접 변경하지 않더라도 주요 치수 최적화를 통해 선박의 저항 성능이 향상됨을 확인하였고, 다양한 선박의 주요 치수 최적화를 통한 성능 향상에 활용이 될 것으로 기대한다.