• Title/Summary/Keyword: optimization procedure

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Shape Optimization of Axial Flow Fan Blade Using Surrogate Model (대리모델을 사용한 축류송풍기 블레이드의 형상 최적화)

  • Kim, Jin-Hyuk;Choi, Jae-Ho;Kim, Kwang-Yong
    • Proceedings of the KSME Conference
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    • 2008.11b
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    • pp.2440-2443
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    • 2008
  • This paper presents a three dimensional shape optimization procedure for a low-speed axial flow fan blade with a weighted average surrogate model. Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations. Six variables from airfoil profile and lean are selected as design variables. 3D RANS solver is used to evaluate the objective functions of total pressure efficiency. Surrogate approximation models for optimization have been employed to find the optimal design of fan blade. A search algorithm is used to find the optimal design in the design space from the constructed surrogate models for the objective function. The total pressure efficiency is increased by 0.31% with the weighted average surrogate model.

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A study on Reduction of Cogging Torque for BLDC Motor Using Response Surface Methodology Optimization (반응표면방법론을 이용한 BLDC전동기의 코깅토크 저감에 관한 연구)

  • Kim, Yeong-Gyun;Lee, Geun-Ho;Hong, Jeong-Pyo
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.51 no.2
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    • pp.55-60
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    • 2002
  • This paper presents an optimization procedure by using Response Surface Methodology(RSM) to determine design parameters for reducing cogging torque. RSM is achieved through using the experimental design method in combination with Finite Element Method and adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.

Topology Optimization Through Material Cloud Method (재료조각법을 이용한 위상최적설계)

  • Chang Su-Young;Youn Sung-Kie
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.1 s.232
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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).

OPTIMIZATION OF THE TEST INTERVALS OF A NUCLEAR SAFETY SYSTEM BY GENETIC ALGORITHMS, SOLUTION CLUSTERING AND FUZZY PREFERENCE ASSIGNMENT

  • Zio, E.;Bazzo, R.
    • Nuclear Engineering and Technology
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    • v.42 no.4
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    • pp.414-425
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    • 2010
  • In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

Design optimization of turning machine process

  • T. Jagan;S. Elizabeth Amudhini Stephen
    • Coupled systems mechanics
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    • v.13 no.3
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    • pp.219-229
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    • 2024
  • By introducing optimization algorithms into the machining process, product quality can be improved, time saved, and costs reduced. The cutting speed and feed can be handled by the turning machine. The approach of optimizing is used to manage pyrotechnics, Lawler's, greedy, bacterial colony, elephant herding, ant lion, spiral, auction, and pattern search for these ten odd ways. Ten artificial optimization methodologies were used to investigate the time and cost of a turning machine. It has been discovered how to create the optimal turning machine procedure. The best solution approach for the turning machine process problem is found, and the results are verified using ANSYS.

AN ACCELERATED DEFLATION TECHNIQUE FOR LARGE SYMMETRIC GENERALIZED EIGENPROBLEMS

  • HYON, YUN-KYONG;JANG, HO-JONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.3 no.1
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    • pp.99-106
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    • 1999
  • An accelerated optimization technique combined with a stepwise deflation procedure is presented for the efficient evaluation of a few of the smallest eigenvalues and their corresponding eigenvectors of the generalized eigenproblems. The optimization is performed on the Rayleigh quotient of the deflated matrices by the aid of a preconditioned conjugate gradient scheme with the incomplete Cholesky factorization.

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An Effective mesh smoothing technique for the mesh constructed by the mesh compression technique (격자압축을 이용해 구성된 격자의 효과적인 격자유연화 방법)

  • 홍진태;이석렬;양동열
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2003.05a
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    • pp.331-334
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    • 2003
  • In the finite element simulation of hot forging processes using hexahedron, remeshing of a flash is very difficult. The mesh compression method is a remeshing technique to construct an effective hexahedral mesh. However, because mesh is distorted during the compression procedure or the mesh compression method, mesh smoothing is necessary to improve the mesh Qualify. in this study, several geometric mesh smoothing techniques and a matrix norm optimization technique are applied and compared which is more adaptive to the mesh compression method.

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Analysis and Compression of Spun-yarn Density Profiles using Adaptive Wavelets

  • Kim, Joo-Yong
    • Textile Coloration and Finishing
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    • v.18 no.5 s.90
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    • pp.88-93
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    • 2006
  • A data compression system has been developed by combining adaptive wavelets and optimization technique. The adaptive wavelets were made by optimizing the coefficients of the wavelet matrix. The optimization procedure has been performed by criteria of minimizing the reconstruction error. The resulting adaptive basis outperformed such conventional basis as Daubechies-5 by 5-10%. It was also shown that the yarn density profiles could be compressed by over 95% without a significant loss of information.

Betterment of The Tractor Frame Design Applying Computation Mechanics Approach

  • Koike, Masayuki
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.1212-1221
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    • 1993
  • The shape optimization procedure applying finite element method was carried out for the specific purpose of analysis of a tractor chassis frame. Minimization of the mass as an objective function is executed under multiple constrained conditions of nodal displacements and stresses. The optimization process executions were succeeded in converging into single optimum solution. Although mass reduction and stress alleviation were attained by 40% and 26 to 24% respectively , the geometry of the shape is so complicated for fabrication that the refinement of the geometry is of necessity.

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Experimental Study on Temperature Profile Following Control (온도궤적 추종제어에 관한 실험적 연구)

  • Yoon, Seok-Young;Song, Tae-Seung;Yoon, Gun
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.239-239
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    • 2000
  • This paper present experimental results on temperature trajectory tracking. The benefits of precalculated feedforward input together with PID feedback control are demonstrated by experimental results. To find the feedforward input, the plant (autoregresiive) model is first identified and convex optimization procedure is applied. PID controller is then implemented based on Ziegler-Nickels tuning rule to reduce effects of disturbances and modeling errors. Experimental results show an improvement in slope tracking performance over the fully PID controller.

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