• Title/Summary/Keyword: optimization scheme

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Design Optimization of A Multi-Blade Centrifugal Fan with Navier-Stokes Analysis (삼차원 Navier-Stokes 해석을 이용한 원심다익송풍기의 최적설계)

  • Seo, Seoung-Jin;Kim, Kwang-Yong
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.2157-2161
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    • 2003
  • In this paper, the response surface method using three-dimensional Navier-Stokes analysis to optimize the shape of a forward-curved blades centrifugal fan, is described. For numerical analysis, Reynolds-averaged Navier-Stokes equations with standard k-e turbulence model are transformed into non-orthogonal curvilinear coordinate system, and are discretized with finite volume approximations. Due to the large number of blades in forward-curved blades centrifugal fan, the flow inside of the fan is regarded as steady flow by introducing the impeller force models for economic calculations. Linear Upwind Differencing Scheme(LUDS) is used to approximate the convection terms in the governing equations. SIMPLEC algorithm is used as a velocity-pressure correction procedure. Design variables, location of cur off, radius of cut off, expansion angle of scroll and width of impeller were selected to optimize the shapes of scroll and blades. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, the efficiency was successfully improved. It was found that the optimization process provides reliable design of this kind of fans with reasonable computing time

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Design Optimization of Deep Groove Ball Bearing with Discrete Variables for High-Load Capacity (이산 설계변수를 포함하고 있는 깊은 홈 볼 베어링의 고부하용량 설계)

  • Yun, Gi-Chan;Jo, Yeong-Seok;Choe, Dong-Hun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.8 s.179
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    • pp.1940-1948
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    • 2000
  • A design method for maximizing fatigue life of the deep groove ball bearing without enlarging mounting space is proposed by using a genetic algorithm. The use of gradient-based optimization methods for the design of the bearing is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. Constrains for manufacturing are applied in optimization scheme. Results obtained for several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increased about 9-34% compared with the standard ones.

Level Set Based Shape Optimization of Linear Structures Using Topological Derivatives (Topological Derivative를 이용한 선형 구조물의 레벨셋 기반 형상 최적 설계)

  • Ha Seung-Hyun;Kim Min-Geun;Cho Seon-Ho
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2006.04a
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    • pp.299-306
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    • 2006
  • Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The 'Hamilton-Jacobi (H-J)' equation and computationally robust numerical technique of 'up-wind scheme' lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H -J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes is not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

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Multivariate Optimization of a Sulfated- β-Cyclodextrin-Modified Capillary Zone Electrophoretic Method for the Separation of Chiral Arylalcohols

  • Zhang, Yu-Ping;Noh, Hyun-Joo;Choi, Seong-Ho;Ryoo, Jae-Jeong;Lee, kwang-Pill;Ohta, Kazutoku;Fujimoto, Chuzo;Jin, Ji-Ye;Takeuchi, Toyohide
    • Bulletin of the Korean Chemical Society
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    • v.25 no.3
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    • pp.377-381
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    • 2004
  • Chiral separation of aryalcohols such as 1-phenyl-propanol, 1-phenyl-2-proanol, and 2-phenyl-1-propanol by capillary electrophoresis has been optimized using the overlapping resolution mapping (ORM) scheme. Three critical parameters of the electrophoretic media, i.e. phosphate concentration, sulfated ${\beta}$-cyclodextrin (CD) concentration and pH, were chosen for optimization. The working ranges were initially presumed by 7 preexperiments. Further optimization was carried out by another seven experiments within the narrow working ranges. From the final overlapping resolution mapping all peak pairs, the area of maximum separations were located. Using the conditions of a point in this area, we found that the target compounds were a baseline separated within 30 min. The maximum separation conditions of arylalcohols were a chiral selector concentration of 5.4%, a phosphate concentration of 28 mM, and a pH of 5.0.

Search space pruning technique for optimization of decision diagrams (결정 다이어그램의 최적화를 위한 탐색공간 축소 기법)

  • Song, Moon-Bae;Dong, Gyun-Tak;Chang, Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.8
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    • pp.2113-2119
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    • 1998
  • The optimization problem of BDDs plays an improtant role in the area of logic synthesis and formal verification. Since the variable ordering has great impacts on the size and form of BDD, finding a good variable order is very important problem. In this paper, a new variable ordering scheme called incremental optimization algorithm is presented. The proposed algorithm reduces search space more than a half of that of the conventional sifting algorithm, and computing time has been greatly reduced withoug depreciating the performance. Moreover, the incremental optimization algorithm is very simple than other variable reordering algorithms including the sifting algorithm. The proposed algorithm has been implemented and the efficiency has been show using may benchmark circuits.

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The SIMP-SRV Method for Stiffness Topology Optimization of Continuum Structures

  • Zhou, Xiangyang;Chen, Liping;Huang, Zhengdong
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.41-49
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    • 2007
  • In density-based topology optimization, 0/1 solutions are sought. Discrete topological problems are often relaxed with continuous design variables so that they can be solved using continuous mathematical programming. Although the relaxed methods are practical, grey areas appear in the optimum topologies. SIMP (Solid Isotropic Microstructures with Penalization) employs penalty schemes to suppress the intermediate densities. SRV (the Sum of the Reciprocal Variables) drives the solution to a 0/1 layout with the SRV constraint. However, both methods cannot effectively remove all the grey areas. SRV has some numerical aspects. In this work, a new scheme SIMP-SRV is proposed by combining SIMP and SRV approaches, where SIMP is employed to generate an intermediate solution to initialize the design variables and SRV is then adopted to produce the final design. The new method turned out to be very effective in conjunction with the method of moving asymptotes (MMA) when using for the stiffness topology optimization of continuum structures for minimum compliance. The numerical examples show that the hybrid technique can effectively remove all grey areas and generate stiffer optimal designs characterized with a sharper boundary in contrast to SIMP and SRV.

Optimization Technique for Parameter Estimation used in 2-Dimensional Modelling of Nonlinear Consolidation Analysis of Soft Deposits (2차원 모델화된 연약지반의 비선형 압밀해석시 이용되는 모델변수 추정을 위한 최적화기법)

  • 김윤태;이승래
    • Geotechnical Engineering
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    • v.13 no.1
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    • pp.47-58
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    • 1997
  • The predicted consolidation behavior of in-situ soft clay is quite different from the meas ureal one mainly due to the approximate numerical modelling techniques as well as the uncertainties involved in soil properties and geological configurations. In order to improve the prediction, this paper takes the following pinto consideration : an optimization technique should be adopted for characterizing the in-situ properties from measurements and also an equivalent and efficient model be considered to incorporate the actual 3-D effects. The soil parameters used be the modified Camflay model, which have an effect on the process of consolidation, were back-analyzed by BFGS scheme on the basis of settlements and pore pressures measured in real sites. The optimization technique was implemented in a general consolidation analysis program SPINED. By using the program, one may be able to appropriately analyze the timetependent consolidation behavior of soft deposits.

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Prototype-based Classifier with Feature Selection and Its Design with Particle Swarm Optimization: Analysis and Comparative Studies

  • Park, Byoung-Jun;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • v.7 no.2
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    • pp.245-254
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    • 2012
  • In this study, we introduce a prototype-based classifier with feature selection that dwells upon the usage of a biologically inspired optimization technique of Particle Swarm Optimization (PSO). The design comprises two main phases. In the first phase, PSO selects P % of patterns to be treated as prototypes of c classes. During the second phase, the PSO is instrumental in the formation of a core set of features that constitute a collection of the most meaningful and highly discriminative coordinates of the original feature space. The proposed scheme of feature selection is developed in the wrapper mode with the performance evaluated with the aid of the nearest prototype classifier. The study offers a complete algorithmic framework and demonstrates the effectiveness (quality of solution) and efficiency (computing cost) of the approach when applied to a collection of selected data sets. We also include a comparative study which involves the usage of genetic algorithms (GAs). Numerical experiments show that a suitable selection of prototypes and a substantial reduction of the feature space could be accomplished and the classifier formed in this manner becomes characterized by low classification error. In addition, the advantage of the PSO is quantified in detail by running a number of experiments using Machine Learning datasets.

Efficiency Optimization Control of SynRM with Hybrid Artificial Intelligent Controller (하이브리드 인공지능 제어기에 의한 SynRM의 효율 최적화 제어)

  • Choi, Jung-Sik;Ko, Jae-Sub;Lee, Jung-Ho;Chung, Dong-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2006.05a
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    • pp.321-326
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    • 2006
  • This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

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The Design of Rear Suspension Using Hydroforming (하이드로포밍을 이용한 후륜 현가장치 설계)

  • Oh, J.H.;Choi, H.H.;Lee, G.M.;Park, S.H.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2008.05a
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    • pp.205-208
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    • 2008
  • Generally, there are several types in rear suspension. The rear suspension of subframe type consisting of side member and front/rear cross member is widely used in a medium car and full car. In the small car case, the beam of tubular type without independent suspension system is used to reduce manufacturing cost. The optimized rear suspension of subframe type using hydroforming method has been developed in this study. In designing suspension, the driving stability and durability performance should be considered as an important factor. The stability is related to dynamic frequency and durability is connected with stress analysis of structure. We focus on increasing the stiffness of suspension and decreasing the maximum stress relating to durability cycle life. For making use of the merits of hydroforming which is possible to make the bead, tube expansion, and feeding in desiring position, several optimization design techniques such as shape, size, and topology optimization are proposed. This optimization scheme based on the sensitivity can provide distinguished performance improvement in using hydroforming. Through commercial software based on the finite element, the superiority of this design method is demonstrated.

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