• Title/Summary/Keyword: Parameters optimization

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전산유체역학을 활용한 가전 제품용 원심팬 블레이드의 단계별 형상 최적화 (MULTI STAGE SHAPE OPTIMIZATION OF CENTRIFUGAL FAN FOR HOME APPLIANCE USING CFD)

  • 김종수;강태곤
    • 한국전산유체공학회지
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    • 제21권3호
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    • pp.39-47
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    • 2016
  • We conducted a multi-stage optimization to secure the desired performance of a centrifugal fan for home appliance in an early stage of product development. In optimization, the static pressure at the outlet of the fan is chosen as an objective function that is to be maximized, providing the required flow rate at the operating point of the fan. The optimization procedure begins with parameters for an initial baseline fan design. The baseline design is optimized by using a commercial optimization package. Accordingly, the corresponding blade models with a set of geometrical parameters are generated. Flow through a fan is simulated by solving the Reynolds-averaged Navier-Stokes equations. A multi-stage optimization scheme is employed to determine the family of optimum values for the parameters, leading to the pressure increase at the outlet of the fan. To validate the numerically obtained optimal design parameters, we fabricated the three types of fans using rapid prototyping and assessed the performance using a fan tester. Experimental results show that the design parameters at each stage satisfy the goal of optimization. The multi-stage optimization process turned out to be a useful tool in the development of a centrifugal fan.

OPTIMIZATION OF THE PARAMETERS OF FEEDWATER CONTROL SYSTEM FOR OPR1000 NUCLEAR POWER PLANTS

  • Kim, Ung-Soo;Song, In-Ho;Sohn, Jong-Joo;Kim, Eun-Kee
    • Nuclear Engineering and Technology
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    • 제42권4호
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    • pp.460-467
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    • 2010
  • In this study, the parameters of the feedwater control system (FWCS) of the OPR1000 type nuclear power plant (NPP) are optimized by response surface methodology (RSM) in order to acquire better level control performance from the FWCS. The objective of the optimization is to minimize the steam generator (SG) water level deviation from the reference level during transients. The objective functions for this optimization are relationships between the SG level deviation and the parameters of the FWCS. However, in this case of FWCS parameter optimization, the objective functions are not available in the form of analytic equations and the responses (the SG level at plant transients) to inputs (FWCS parameters) can be evaluated by computer simulations only. Classical optimization methods cannot be used because the objective function value cannot be calculated directely. Therefore, the simulation optimization methodology is used and the RSM is adopted as the simulation optimization algorithm. Objective functions are evaluated with several typical transients in NPPs using a system simulation computer code that has been utilized for the system performance analysis of actual NPPs. The results show that the optimized parameters have better SG level control performance. The degree of the SG level deviation from the reference level during transients is minimized and consequently the control performance of the FWCS is remarkably improved.

유전자 알고리즘을 이용한 서어보 밸브의 설계 파라미터 최적화 (Optimization of Design Parameters of a Servo Valve Using the Genetic Algorithm)

  • 엄태준
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 춘계학술대회논문집A
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    • pp.464-468
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    • 2000
  • This paper presents the optimization technique to select the design parameters of a hydraulic servo valve using the genetic algorithm. The dynamic performance is governed by the design parameters of the servo valve and they may be select by repeated number of simulations such that the desired performance is obtained. Using the genetic algorithm to optimize the design parameters, effective method is suggested. This method can be used for the design of the hydraulic systems as well as the servo valve.

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Numerical stability and parameters study of an improved bi-directional evolutionary structural optimization method

  • Huang, X.;Xie, Y.M.
    • Structural Engineering and Mechanics
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    • 제27권1호
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    • pp.49-61
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    • 2007
  • This paper presents a modified and improved bi-directional evolutionary structural optimization (BESO) method for topology optimization. A sensitivity filter which has been used in other optimization methods is introduced into BESO so that the design solutions become mesh-independent. To improve the convergence of the optimization process, the sensitivity number considers its historical information. Numerical examples show the effectiveness of the modified BESO method in obtaining convergent and mesh-independent solutions. A study of the effects of various BESO parameters on the solution is then conducted to determine the appropriate values for these parameters.

Optimal Design of a Planar-Type Antenna with a Reduced Number of Design Parameters Using Taguchi Method and Adaptive Particle Swarm Optimization

  • Lee, Jeong-Hyeok;Jang, Dong-Hyeok;Kim, Hyeong-Seok
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.2019-2024
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    • 2014
  • This paper presents a method to optimize the design of a planar-type antenna and reduce the number of design parameters for rapid computation. The electromagnetic characteristics of the structure are analyzed, and Taguchi method is used to identify critical design parameters. Adaptive particle swarm optimization, which has a faster convergence rate than particle swarm optimization, is used to achieve the design goal effectively. A compact dual-band USB dongle antenna is tested to verify the advantage of the proposed method. In this case, we can use only five selected geometrical parameters instead of eighteen to accelerate the optimization of the antenna design. The 10 dB bandwidth for return loss ranges from 2.3 GHz to 2.7 GHz and from 5.1 GHz to 5.9 GHz, covering all the WiBro, Bluetooth, WiMAX, and 802.11 b/g/n WLAN bands in both simulation and measurement. The optimization process enables the antenna design to achieve the required performance with fewer design parameters.

High Resistivity SOI RF CMOS 대칭형 인덕터 모델링을 위한 개선된 Optimization 방법 연구 (A Study on Improved Optimization Method for Modeling High Resistivity SOI RF CMOS Symmetric Inductor)

  • 안자현;이성현
    • 전자공학회논문지
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    • 제52권9호
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    • pp.21-27
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    • 2015
  • High resistivity(HR) silicon-on-insulator(SOI) RF CMOS 공정 인덕터의 모델 파라미터를 정확히 결정하기 위하여 직접추출과 simultaneous optimization을 사용한 개선된 방법을 개발하였다. 먼저, 대칭형 인덕터와 센터탭이 접지된 대칭형 인덕터 등가회로들의 Y 및 Z-파라미터 방정식 유도를 통해 일부 모델 파라미터들을 직접 추출하고, 병렬 저항과 전체 인덕턴스 방정식들로 미지 변수들을 줄여 모델링 정확도를 향상시켰다. 또한, 두 등가회로의 동일한 모델 파라미터들을 공통 변수로 두고 S-파라미터 데이터 세트를 동시에 optimization함으로써 optimization 정확도를 크게 향상시켰다.

Probabilistic optimization of nailing system for soil walls in uncertain condition

  • Mitra Jafarbeglou;Farzin Kalantary
    • Geomechanics and Engineering
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    • 제34권6호
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    • pp.597-609
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    • 2023
  • One of the applicable methods for the stabilization of soil walls is the nailing system which consists of tensile struts. The stability and safety of soil nail wall systems are influenced by the geometrical parameters of the nailing system. Generally, the determination of nailing parameters in order to achieve optimal performance of the nailing system for the safety of soil walls is defined in the framework of optimization problems. Also, according to the various uncertainty in the mechanical parameters of soil structures, it is necessary to evaluate the reliability of the system as a probabilistic problem. In this paper, the optimal design of the nailing system is carried out in deterministic and probabilistic cases using meta-heuristic and reliability-based design optimization methods. The colliding body optimization algorithm and first-order reliability method are used for optimization and reliability analysis problems, respectively. The objective function is defined based on the total cost of nails and safety factors and reliability index are selected as constraints. The mechanical properties of the nailing system are selected as design variables and the mechanical properties of the soil are selected as random variables. The results show that the reliability of the optimally designed soil nail system is very sensitive to uncertainty in soil mechanical parameters. Also, the design results are affected by uncertainties in soil mechanical parameters due to the values of safety factors. Reliability-based design optimization results show that a nailing system can be designed for the expected level of reliability and failure probability.

Collaborative optimization for ring-stiffened composite pressure hull of underwater vehicle based on lamination parameters

  • Li, Bin;Pang, Yong-jie;Cheng, Yan-xue;Zhu, Xiao-meng
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제9권4호
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    • pp.373-381
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    • 2017
  • A Collaborative Optimization (CO) methodology for ring-stiffened composite material pressure hull of underwater vehicle is proposed. Structural stability and material strength are both examined. Lamination parameters of laminated plates are introduced to improve the optimization efficiency. Approximation models are established based on the Ellipsoidal Basis Function (EBF) neural network to replace the finite element analysis in layout optimizers. On the basis of a two-level optimization, the simultaneous structure material collaborative optimization for the pressure vessel is implemented. The optimal configuration of metal liner and frames and composite material is obtained with the comprehensive consideration of structure and material performances. The weight of the composite pressure hull decreases by 30.3% after optimization and the validation is carried out. Collaborative optimization based on the lamination parameters can optimize the composite pressure hull effectively, as well as provide a solution for low efficiency and non-convergence of direct optimization with design variables.

볼록최적화에 의거한 구조계와 제어계의 동시최적화 - 근사적 어프로치 - (Simultaneous Optimization of Structure and Control Systems Based on Convex Optimization - An approximate Approach -)

  • 손회수
    • 대한기계학회논문집A
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    • 제27권8호
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    • pp.1353-1362
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    • 2003
  • This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

ROBUST RELIABILITY DESIGN OF VEHICLE COMPONENTS WITH ARBITRARY DISTRIBUTION PARAMETERS

  • Zhang, Y.;He, X.;Liu, Q.;Wen, B.
    • International Journal of Automotive Technology
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    • 제7권7호
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    • pp.859-866
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    • 2006
  • This study employed the perturbation method, the Edgeworth series, the reliability optimization, the reliability sensitivity technique and the robust design to present a practical and effective approach for the robust reliability design of vehicle components with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulae of the robust reliability design for vehicle components with arbitrary distribution parameters are obtained. The reliability sensitivity is added to the reliability optimization design model and the robust reliability design is described as a multi-objection optimization. On the condition of known first four moments of original random variables, the respective program can be used to obtain the robust reliability design parameters of vehicle components with arbitrary distribution parameters accurately and quickly.