• 제목/요약/키워드: response surface optimization

검색결과 1,449건 처리시간 0.027초

Response surface methodology based multi-objective optimization of tuned mass damper for jacket supported offshore wind turbine

  • Rahman, Mohammad S.;Islam, Mohammad S.;Do, Jeongyun;Kim, Dookie
    • Structural Engineering and Mechanics
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    • 제63권3호
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    • pp.303-315
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    • 2017
  • This paper presents a review on getting a Weighted Multi-Objective Optimization (WMO) of Tuned Mass Damper (TMD) parameters based on Response Surface Methodology (RSM) coupled central composite design and Weighted Desirability Function (WDF) to attenuate the earthquake vibration of a jacket supported Offshore Wind Turbine (OWT). To optimize the parameters (stiffness and damping coefficient) of damper, the frequency ratio and damping ratio were considered as a design variable and the top displacement and frequency response were considered as objective functions. The optimization has been carried out under only El Centro earthquake results and after obtained the optimal parameters, more two earthquakes (California and Northridge) has been performed to investigate the performance of optimal damper. The obtained results also compared with the different conventional TMD's designed by Den Hartog's, Sadek et al.'s and Warburton's method. From the results, it was found that the optimal TMD based on RSM shows better response than the conventional damper. It is concluded that the proposed response model offers an efficient approach regarding the TMD optimization.

반응면 기법을 이용한 천음속 축류압축기의 삼차원 형상 최적설계 (Design Optimization of An Axial-Flow Compressor Rotor Using Response Surface Method)

  • 안찬솔;김광용
    • 대한기계학회논문집B
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    • 제27권2호
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    • pp.155-162
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    • 2003
  • Design optimization of a transonic compressor rotor (NASA rotor 37) using response surface method and three-dimensional Navier-Stokes analysis has been carried out in this work. Baldwin-Lomax turbulence model was used in the flow analysis. Three design variables were selected to optimize the stacking line of the blade. 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, adiabatic efficiency was successfully improved. It is also found that the design process provides reliable design of a turbomachinery blade with reasonable computing time.

반응표면법의 향상된 최적화 알고리즘 구성에 관한 연구 (The Study for Construction of the Improved Optimization Algorithm by the Response Surface Method)

  • 박정선;이동주;임종빈
    • 한국항공운항학회지
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    • 제13권3호
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    • pp.22-33
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    • 2005
  • Response Surface Method (RSM) constructs approximate response surfaces using sample data from experiments or simulations and finds optimum levels of process variables within the fitted response surfaces of the interest region. It will be necessary to get the most suitable response surface for the accuracy of the optimization. The application of RSM plan experimental designs. The RSM is used in the sequential optimization process. The first goal of this study is to improve the plan of central composite designs of experiments with various locations of axial points. The second is to increase the optimal efficiency applying a modified method to update interest regions.

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Efficient Approximation Method for Constructing Quadratic Response Surface Model

  • Park, Dong-Hoon;Hong, Kyung-Jin;Kim, Min-Soo
    • Journal of Mechanical Science and Technology
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    • 제15권7호
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    • pp.876-888
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    • 2001
  • For a large scaled optimization based on response surface methods, an efficient quadratic approximation method is presented in the context of the trust region model management strategy. If the number of design variables is η, the proposed method requires only 2η+1 design points for one approximation, which are a center point and tow additional axial points within a systematically adjusted trust region. These design points are used to uniquely determine the main effect terms such as the linear and quadratic regression coefficients. A quasi-Newton formula then uses these linear and quadratic coefficients to progressively update the two-factor interaction effect terms as the sequential approximate optimization progresses. In order to show the numerical performance of the proposed method, a typical unconstrained optimization problem and two dynamic response optimization problems with multiple objective are solved. Finally, their optimization results compared with those of the central composite designs (CCD) or the over-determined D-optimality criterion show that the proposed method gives more efficient results than others.

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원심압축기의 공력소음 저감에 관한 설계연구 Part II : 저소음 최적설계 (A Design Study of Aerodynamic Noise Reduction In Centrifugal Compressor Part II . Low-noise Optimization Design)

  • 선효성;이수갑
    • 한국소음진동공학회논문집
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    • 제14권10호
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    • pp.939-944
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    • 2004
  • The numerical methods including the performance analysis and the noise prediction of the centrifugal compressor impeller are coupled with the optimization design skill, which consists of response surface method, statistical approach, and genetic algorithm. The flow-field Inside of a centrifugal compressor is obtained numerically by solving Wavier-Stokes equations. and then the propagating noise is estimated from the distributed surface pressure by using Ffowcs Williams-Hawkings formulation. The quadratic response surface model with D-optimal 3-level factorial experimental design points is constructed to optimize the impeller geometry for the advanced centrifugal compressor. The statistical analysis shows that the quadratic model exhibits a reasonable fitting quality resulting in the impeller blade design with high performance and low far-field noise level. The influences of selected design variables, objective functions, and constraints on the impeller performance and the impeller noise are also examined as a result of the optimization process.

차체 기본 진동 모드를 고려한 필러 단면의 신뢰성 최적설계 (Reliability-Based Optimal Design of Pillar Sections Considering Fundamental Vibration Modes of Vehicle Body Structure)

  • 이상범;임홍재
    • 한국공작기계학회논문집
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    • 제13권6호
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    • pp.107-113
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    • 2004
  • This paper presents the pillar section optimization technique considering the reliability of the vehicle body structure consisted of complicated thin-walled panels. The response surface method is utilized to obtain the response surface models that describe the approximate performance functions representing the system characteristics on the section properties of the pillar and on the mass and the natural frequencies of the vehicle B.I.W. The reliability-based design optimization on the pillar sections Is performed and compared with the conventional deterministic optimization. The FORM is applied for the reliability analysis of the vehicle body structure. The developed optimization system is applied to the pillar section design considering the fundamental natural frequencies of passenger car body structure. By applying the proposed RBDO technique, it can be possible to optimize the pillar sections considering the reliability that engineers require.

다목적 유전 알고리즘을 이용한 쌍대반응표면최적화 (Dual Response Surface Optimization using Multiple Objective Genetic Algorithms)

  • 이동희;김보라;양진경;오선혜
    • 대한산업공학회지
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    • 제43권3호
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    • pp.164-175
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    • 2017
  • Dual response surface optimization (DRSO) attempts to optimize mean and variability of a process response variable using a response surface methodology. In general, mean and variability of the response variable are often in conflict. In such a case, the process engineer need to understand the tradeoffs between the mean and variability in order to obtain a satisfactory solution. Recently, a Posterior preference articulation approach to DRSO (P-DRSO) has been proposed. P-DRSO generates a number of non-dominated solutions and allows the process engineer to select the most preferred solution. By observing the non-dominated solutions, the DM can explore and better understand the trade-offs between the mean and variability. However, the non-dominated solutions generated by the existing P-DRSO is often incomprehensive and unevenly distributed which limits the practicability of the method. In this regard, we propose a modified P-DRSO using multiple objective genetic algorithms. The proposed method has an advantage in that it generates comprehensive and evenly distributed non-dominated solutions.

Augmented D-Optimal Design for Effective Response Surface Modeling and Optimization

  • Kim, Min-Soo;Hong, Kyung-Jin;Park, Dong-Hoon
    • Journal of Mechanical Science and Technology
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    • 제16권2호
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    • pp.203-210
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    • 2002
  • For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

쌍대반응표면최적화를 위한 반복적 선호도사후제시법 (An Iterative Posterior Preference Articulation Approach to Dual Response Surface Optimization)

  • 정인준
    • 품질경영학회지
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    • 제40권4호
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    • pp.481-496
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    • 2012
  • Purpose: This paper aims at improving inefficiency of an existing posterior preference articulation method proposed for dual response surface optimization. The method generates a set of non-dominated solutions and then allows a decision maker (DM) to select the best solution among them through an interval selection strategy. Methods: This paper proposes an iterative posterior preference articulation method, which repeatedly generates the predetermined number of non-dominated solutions in an interval which becomes gradually narrower over rounds. Results: The existing method generates a good number of non-dominated solutions not used in the DM's selection process, while the proposed method generates the minimal number of non-dominated solutions necessitated in the selection process. Conclusion: The proposed method enables a satisfactory compromise solution to be achieved with minimal cognitive burden of the DM as well as with light computation load in generating non-dominated solutions.

쌍대반응표면최적화를 위한 사후선호도반영법: TOPSIS를 활용한 최고선호해 선택 (A Posterior Preference Articulation Method to Dual-Response Surface Optimization: Selection of the Most Preferred Solution Using TOPSIS)

  • 정인준
    • 지식경영연구
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    • 제19권2호
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    • pp.151-162
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    • 2018
  • Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)'s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the trade-off between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.