• Knowledge Management Research
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• v.21 no.1
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.5
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• pp.223-232
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• 2021

The spatial variation characteristics of seismic motions at the nuclear power plant's site and structures were analyzed using earthquake records obtained at the Fukushima nuclear power plant during the Great East Japan Earthquake. The ground responses amplified as they approached the soil surface from the lower rock surface, and the amplification occurred intensively at about 50 m near the ground. Due to the soil layer's nonlinear characteristics caused by the strong seismic motion, the ground's natural frequency derived from the response spectrum ratio appeared to be smaller than that calculated from the shear wave velocity profile. The spatial variation of the peak ground acceleration at the ground surface of the power plant site showed a significant difference of about 0.6 g at the maximum. As a result of comparing the response spectrums at the basement of the structure with the design response spectrum, there was a large variability by each power plant unit. The difference was more significant in the Fukushima Daiichi site record, which showed larger peak ground acceleration at the surface. The earthquake motions input to the basement of the structure amplified according to the structure's height. The natural frequency obtained from the recorded results was lower than that indicated in the previous research. Also, the floor response spectrum change according to the location at the same height was investigated. The vertical response on the foundation surface showed a significant difference in spectral acceleration depending on the location. The amplified response in the structure showed a different variability depending on the type of structure and the target frequency.

• Computers and Concrete
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• v.19 no.6
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• pp.737-744
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• 2017

Geopolymer Concrete is typically proportioned with activator solution leading to moderately high material cost. Such cost can be enduring in high value added applications especially when cost savings can be recognized in terms of reduction in size of the members. Proper material selection and mix proportioning can diminish the material cost. In the present investigation, a total of 27 mixes were arrived considering the mix parameters as liquid-binder ratio, slag content and sodium hydroxide concentration to study the mechanical properties of geopolymer concrete (GPC) mixes such as compressive strength, split tensile strength and flexural strength. The derived statistical Response Surface Methodology is beleaguered to develop cost effective GPC mixes. The estimated responses are not likely to contrast in linear mode with selected variables; a plan was selected to enable the model of any response in a quadratic manner. The results reveals that a fair correlation between the experimental and the predicted strengths.

• Journal of the East Asian Society of Dietary Life
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• v.1 no.3
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• pp.305-311
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• 1991

The study was designed to investigate overall acceptability of rice extrudate with added ginseng flour extruded by single screw extruder. Graphic three dimension analysis on response surface regression was conducted for overall acceptability evaluated by balanced incomplete block design. Overall acceptability, which formed a saddle point, increased as moisture content increased at lower die temperature, and as moisture content decreased at higher die temperature. Critical values of each variable which indicated optimum response are 5.0% ginseng content, 17.8% moisture content and 104.6$^{\circ}C$ die temperature, and optimum inferred score of overall acceptability is 59.6 and 90. Key words: extrdate, overall acceptability, response surface regression analysis, balanced incomplete block method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.2
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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.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.510-515
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• 2004

A proton exchange membrane fuel cells(PEMFC) operate at low temperature, allowing for faster startups and immediate response to change in the demand for power, and also deliver high power density. To maximize economical efficiency in PEMPC, it is necessary to the optimization. Response surface method(RSM) has non-gradient and fast convergency characteristics. Sampling points are extracted by design of experiments using Central Composite Method. In this paper, it is shown that the optimization is required for the design study of the PEMFC.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.E2
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• pp.83-91
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• 2008

This work investigated the methodology to simultaneously optimize the ozone and relative humidity composition for the $NO_x$ degradation using soil biofilter. Experiments were made as a function of inlet ozone concentration ($0{\sim}1,770\;ppb$) and relative humidity ($38{\sim}81%$). Factorial design ($2^2+3$) and response surface methodology by central composite designs were used to examine the role of two factors and optimal response condition on $NO_x$ degradation. It was found that a second-order response surface model can properly interpret the experimental data with an $R^2$-value of 0.9730 and F-value of 71.83, based on which the maximum $NO_x$ degradation was predicted up to 92.8% within our experimental conditions.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.49-59
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• 2012

In computer simulation models the output from the computer code is often deterministic, i.e., running the code twice with the same values for the input variables would give the same output. It is discussed why the response surface method with polynomial approximation for the true response function is a good approximation to the computer experiments model. A sequential strategy to find the proper reduced quadratic polynomial model is illustrated with a case study in the military war game computer simulation model.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.92-99
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• 2007

In this paper, optimization of the vaned centrifugal compressor was carried out at a given mass flow rate condition. Firstly, impeller optimization was conducted using response surface method (RSM) which is one of optimization methods. After the optimization of the impeller was completed, diffuser optimization was performed with the optimized impeller. In these processes, Navier-Stokes solver was used to calculate the flow inside the centrifugal compressor. And the optimization is performed with Box-Behnken design method which is efficient for fitting second-order response surfaces to reduce the number of calculations required. As a result, compared with the reference model, the efficiency and the pressure ratio of the optimized impeller and diffuser are found to be increased. The performance at off-design conditions is presented.

• The KSFM Journal of Fluid Machinery
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• v.19 no.2
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• pp.16-20
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• 2016

Design optimization of a transonic compressor rotor(NASA rotor 37) was carried out using response surface method(RSM) which is one of the optimization methods. A numerical simulation was conducted using ANSYS CFX by solving three-dimensional Reynolds-averaged Navier Stokes(RANS) equations. Response surfaces that were based on the results of the design of experiment(DOE) techniques were used to find an optimal shape of blade which has the maximum aerodynamic performance. Two objective functions, viz., the adiabatic efficiency and the loss coefficient were selected with three design configurations to optimize the blade shape. As a result, the efficiency of the optimized blade is found to be increased.