• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1314-1319
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• 2004

In this study, parameter optimization of micro-static mixer with a cantilever beam was accomplished for maximizing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

• Food Science of Animal Resources
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• v.39 no.2
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• pp.222-228
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• 2019

This research was motivated by our encounter with the situation where an optimization was done based on statistically non-significant models having poor fits. Such a situation took place in a research to optimize manufacturing conditions for improving storage stability of coffee-supplemented milk beverage by using response surface methodology, where two responses are $Y_1$=particle size and $Y_2$=zeta-potential, two factors are $F_1$=speed of primary homogenization (rpm) and $F_2$=concentration of emulsifier (%), and the optimization objective is to simultaneously minimize $Y_1$ and maximize $Y_2$. For response surface analysis, practically, the second-order polynomial model is almost solely used. But, there exists the cases in which the second-order model fails to provide a good fit, to which remedies are seldom known to researchers. Thus, as an alternative to a failed second-order model, we present the heterogeneous third-order model, which can be used when the experimental plan is a two-factor central composite design having -1, 0, and 1 as the coded levels of factors. And, for multi-response optimization, we suggest a modified desirability function technique. Using these two methods, we have obtained statistical models with improved fits and multi-response optimization results with the predictions better than those in the previous research. Our predicted optimum combination of conditions is ($F_1$, $F_2$)=(5,000, 0.295), which is different from the previous combination. This research is expected to help improve the quality of response surface analysis in experimental sciences including food science of animal resources.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.168-173
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• 2000

Design of experiments is utilized for exploring the design space and for building response surface models in order to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient means to rapidly model the trade-off among many conflicting goals. In robust design, it is important not only to achieve robust design objectives but also to maintain the robustness of design feasibility under the effects of variations, called uncertainties. However, the evaluation of feasibility robustness often needs a computationally intensive process. To reduce the computational burden associated with the probabilistic feasibility evaluation, the first-order Taylor series expansions are used to derive individual mean and variance of constraints. For robust design applications, these constraint response surface models are used efficiently and effectively to calculate variances of constraints due to uncertainties. Robust optimization of automotive seat is used to illustrate the approach.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.965-970
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• 2015

This paper uses response surface methodology as the optimization method of torque of multi-DOF deflection type PM motor. Firstly, the application of Taguchi algorithm selects structural parameters affecting the motor torque largely which simplifies the optimization process greatly. Then, based on the central composite design (CCD), response surface equation numerical model is constructed by the finite element method. With the aid of experiment design and analysis software, the effects of the interaction among factors on the index are analyzed. The results show that the analytical method is efficient and reliable and the experimental results can be predicted by response surface functions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.5 s.236
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• pp.625-632
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• 2005

This paper describes the shape optimization of a stator blade in a single-stage transonic axial compressor. The blade optimization has been performed using response surface method and three-dimensional Navier-Stokes analysis. Two shape variables of the stator blade, which are used to define a stacking line, are introduced to increase an adiabatic efficiency. Data points for response evaluations have been selected by D-optimal design, and linear programming method has been used for an optimization on a response surface. Throughout the shape optimization of a stator blade, the adiabatic efficiency is increased to 5.8 percent compared to that of the reference shape of the stator. The increase of the efficiency is mainly caused by the pressure enhancement in the stator blade. Flow separation on the blade suction surface of the stator is also improved by optimizing the stator blade. It is noted that the optimization of the stator blade is also useful method to increase the adiabatic efficiency in the axial compressor as well as the optimization of a rotor blade, which is widely used now.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.51-56
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• 2009

Optimization with metamodel is one of numerical optimization methods. Response surface method is performed for making metamodel. The Hcks-Henne function is used for designing 2D shape of the airfoil and spring analogy is used to change the grid according to the change in shape of the airfoil. Aerodynamic coefficient required for response surface method are obtained by using Navier-Stokes solver with $\kappa-\omega$ shear stress transport turbulence model. For the baseline airfoils, OA 312, OA 309, and OA 407 airfoils select and optimize to improve aerodynamic performance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.10
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• pp.1457-1463
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• 2003

In this paper, the response surface method using three-dimensional Navier-Stokes analysis to optimize the shape of a multi-blade centrifugal fan, is described. For numerical analysis, Reynolds-averaged Navier-Stokes equations with standard k - c 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 this 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.

• The KSFM Journal of Fluid Machinery
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• v.11 no.2
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• pp.38-45
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• 2008

This study presents a numerical procedure to optimize the compressor design to increase the surge margin of compressor with response surface method (RSM). The Box-Behnken design method is used to reduce the number of calculation for fitting the second-order response surface. In order to consider the increase of surge margin during numerical optimization without any calculation at the surge point, the slope of compressor characteristic curve at the design point is suggested as an objective function in the present optimization problem. Mean line performance analysis method is used to get the design and off-design characteristic curves of centrifugal compressor. The impeller exit angle, impeller exit height and impeller radius are chosen as design variables. The optimum shapes show the increase of surge margin for the surge margin optimization and increase of efficiency for the efficiency optimization in comparison with an initial shape.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.6 s.237
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• pp.842-851
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• 2005

In this paper, a new method for constrained optimization of noisy functions is proposed. In approximate optimization using response surface methods, if constraints have severe noise, the approximate feasible region defined by approximate constraints is apt to include some of the infeasible region defined by actual constraints. This can cause the approximate optimum to converge into the infeasible region. In the proposed method, the approximate optimization is performed with the approximate constraints shifted by their deviations, which are calculated using a diagonal quadratic response surface method. This can prevent the approximate optimum from converging into the infeasible region. To fit the objective and constraints into diagonal quadratic models, we select the center and 4 additional points along each axis of design variables as experimental points. The deviation of each function is calculated using the differences between the real and approximate function values at the experimental points. A sequential approximate optimization technique based on the trust region algorithm is adopted to manage approximate models. The proposed approach is validated by solving some design problems. The results of the problems show the effectiveness of the proposed method.

• Journal of Applied Reliability
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• v.4 no.1
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• pp.39-64
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• 2004

Taguchi's multi-characteristic experiments seek proper choice of levels of contollable factors which satisfy that all reponses of characteristics in a desirable range simultaneously. This aim can be achieved by response surface techniques that allow more flexible in modeling than traditional Taguchi's parameter design. In this article, a multi-response surface modeling and analysis techniques is proposed to deal with the multi-characteristic optimization problem in experimentation with Taguchi's controllable and noise factors.