• Title, Summary, Keyword: response surface analysis

Search Result 1,572, Processing Time 0.051 seconds

Structural Optimization for Small Scale Vertical-Axis Wind Turbine Blade using Response Surface Method (반응표면법을 이용한 소형 수직축 풍력터빈 블레이드의 구조 최적화)

  • Choi, Chan-Woong;Jin, Ji-Won;Kang, Ki-Weon
    • The KSFM Journal of Fluid Machinery
    • /
    • v.16 no.4
    • /
    • pp.22-27
    • /
    • 2013
  • The purpose of this paper is to perform the structural design of the small scale vertical-axis wind turbine (VAWT) blade using a response surface method(RSM). First, the four design factors that have a strong influence on the structural response of blade were selected. Analysis conditions were calculated by using the central composite design(CCD), which is a typical design of experiment for the response surface method(RSM). Also, the significance of the central composite design(CCD) was verified using analysis of variance(ANOVA). The finite element analysis was performed for the selected analytical conditions for the application of response surface method(RSM). Finally, a optimization problem was solved with a objective function of blade weight and a constraint of allowable stress to achieve a optimal structural design of blade.

Improving the Quality of Response Surface Analysis of an Experiment for Coffee-Supplemented Milk Beverage: I. Data Screening at the Center Point and Maximum Possible R-Square

  • Rheem, Sungsue;Oh, Sejong
    • Food Science of Animal Resources
    • /
    • v.39 no.1
    • /
    • pp.114-120
    • /
    • 2019
  • Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. As a design for a response surface experiment, a central composite design (CCD) with multiple runs at the center point is frequently used. However, sometimes there exist situations where some among the responses at the center point are outliers and these outliers are overlooked. Since the responses from center runs are those from the same experimental conditions, there should be no outliers at the center point. Outliers at the center point ruin statistical analysis. Thus, the responses at the center point need to be looked at, and if outliers are observed, they have to be examined. If the reasons for the outliers are not errors in measuring or typing, such outliers need to be deleted. If the outliers are due to such errors, they have to be corrected. Through a re-analysis of a dataset published in the Korean Journal for Food Science of Animal Resources, we have shown that outlier elimination resulted in the increase of the maximum possible R-square that the modeling of the data can obtain, which enables us to improve the quality of response surface analysis.

Reliability Estimation for Crack Growth Life of Turbine Wheel Using Response Surface (반응표면을 사용한 터빈 휠의 균열성장 수명에 대한 신뢰성 평가)

  • Jang, Byung-Wook;Park, Jung-Sun
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.40 no.4
    • /
    • pp.336-345
    • /
    • 2012
  • In crack growth life, uncertainties are caused by variance of geometry, applied loads and material properties. Therefore, the reliability estimation for these uncertainties is required to keep the robustness of calculated life. The stress intensity factors are the most important variable in crack growth life calculation, but its equation is hard to know for complex geometry, therefore they are processed by the finite element analysis which takes long time. In this paper, the response surface is considered to increase efficiency of the reliability analysis for crack growth life of a turbine wheel. The approximation model of the stress intensity factors is obtained by the regression analysis for FEA data and the response surface of crack growth life is generated for selected factors. The reliability analysis is operated by the Monte Carlo Simulation for the response surface. The results indicate that the response surface could reduce computations that need for reliability analysis for the turbine wheel, which is hard to derive stress intensity factor equation, successfully.

Response Surface Analysis of Dietary n-3/n-6 and P/S Ratio on Reduction of Plasma Lipids in Rats (흰쥐현장지질 감소에 관한 n-3/n-6 와 P/S 섭취비율의 반응표면분석)

  • Park, Byung-Sung
    • Journal of the Korean Applied Science and Technology
    • /
    • v.21 no.2
    • /
    • pp.148-155
    • /
    • 2004
  • Response surface analysis was used to study dietary ratios of n-3/n-6 fatty acid and P/S to minimize plasma triglycerides, total cholesterol and LDL ${\cdot}$ VLDL-C levels and maximize plasma HDL ${\cdot}$ C levels of rats. Because the dietary components were not statistically independent, they were studied in combinations of two variables. The two-variable combinations were the most useful in locating the desired maximum or minimum plasma triglycerides, total cholesterol and LDL ${\cdot}$ VLDL-C response in terms of the proportions of the dietary components. Response surface contours and three dimensional plots were developed for each plasma lipid response. The contours and three dimensional plots were used to help determine those combinations of the dietary fatty acid ratios that would produce the desired minimum or maximum lpid responses. The statistical analyses indicated that the minimized plasma cholesterol response levels could be attained with a diet consisting of 2.26 n-3/n-6 fatty acid and 2.15 P/S ratios.

Structural reliability analysis using response surface method with improved genetic algorithm

  • Fang, Yongfeng;Tee, Kong Fah
    • Structural Engineering and Mechanics
    • /
    • v.62 no.2
    • /
    • pp.139-142
    • /
    • 2017
  • For the conventional computational methods for structural reliability analysis, the common limitations are long computational time, large number of iteration and low accuracy. Thus, a new novel method for structural reliability analysis has been proposed in this paper based on response surface method incorporated with an improved genetic algorithm. The genetic algorithm is first improved from the conventional genetic algorithm. Then, it is used to produce the response surface and the structural reliability is finally computed using the proposed method. The proposed method can be used to compute structural reliability easily whether the limit state function is explicit or implicit. It has been verified by two practical engineering cases that the algorithm is simple, robust, high accuracy and fast computation.

Reliability analysis of a mechanically stabilized earth wall using the surface response methodology optimized by a genetic algorithm

  • Hamrouni, Adam;Dias, Daniel;Sbartai, Badreddine
    • Geomechanics and Engineering
    • /
    • v.15 no.4
    • /
    • pp.937-945
    • /
    • 2018
  • A probabilistic study of a reinforced earth wall in a frictional soil using the surface response methodology (RSM) is presented. A deterministic model based on numerical simulations is used (Abdelouhab et al. 2011, 2012b) and the serviceability limit state (SLS) is considered in the analysis. The model computes the maximum horizontal displacement of the wall. The response surface methodology is utilized for the assessment of the Hasofer-Lind reliability index and is optimized by the use of a genetic algorithm. The soil friction angle and the unit weight are considered as random variables while studying the SLS. The assumption of non-normal distribution for the random variables has an important effect on the reliability index for the practical range of values of the wall horizontal displacement.

Multiresponse Optimization Using a Response Surface Approach to Taguchi′s Parameter Design (다구찌의 파라미터 설계에 대한 반응표면 접근방법을 이용한 다반응 최적화)

  • 이우선;이종협;임성수
    • Journal of the Korean Society for Quality Management
    • /
    • v.27 no.1
    • /
    • pp.165-194
    • /
    • 1999
  • Taguchi's parameter design seeks proper choice of levels of controllable factors (Parameters in Taguchi's terminology) that makes the qualify characteristic of a product optimal while making its variability small. This aim can be achieved by response surface techniques that allow flexibility in modeling and analysis. In this article, a collection of response surface modeling and analysis techniques is proposed to deal with the multiresponse optimization problem in experimentation with Taguchi's signal and noise factors.

  • PDF

Coupling relevance vector machine and response surface for geomechanical parameters identification

  • Zhao, Hongbo;Ru, Zhongliang;Li, Shaojun
    • Geomechanics and Engineering
    • /
    • v.15 no.6
    • /
    • pp.1207-1217
    • /
    • 2018
  • Geomechanics parameters are critical to numerical simulation, stability analysis, design and construction of geotechnical engineering. Due to the limitations of laboratory and in situ experiments, back analysis is widely used in geomechancis and geotechnical engineering. In this study, a hybrid back analysis method, that coupling numerical simulation, response surface (RS) and relevance vector machine (RVM), was proposed and applied to identify geomechanics parameters from hydraulic fracturing. RVM was adapted to approximate complex functional relationships between geomechanics parameters and borehole pressure through coupling with response surface method and numerical method. Artificial bee colony (ABC) algorithm was used to search the geomechanics parameters as optimal method in back analysis. The proposed method was verified by a numerical example. Based on the geomechanics parameters identified by hybrid back analysis, the computed borehole pressure agreed closely with the monitored borehole pressure. It showed that RVM presented well the relationship between geomechanics parameters and borehole pressure, and the proposed method can characterized the geomechanics parameters reasonably. Further, the parameters of hybrid back analysis were analyzed and discussed. It showed that the hybrid back analysis is feasible, effective, robust and has a good global searching performance. The proposed method provides a significant way to identify geomechanics parameters from hydraulic fracturing.