• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.207-212
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• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• Food Science of Animal Resources
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• v.43 no.2
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.21-31
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• 2008

response surface method (RSM) is widely used to evaluate th e extremely smal probability of ocurence or toanalyze the reliability of very complicated structures. Althoug h Monte-Carlo Simulation (MCS) technique can evaluate any system, the procesing time of MCS dependson the reciprocal num ber of the probability of failure. The stochastic finite element method could solve thislimitation. However, it is limit ed to the specific program, in which the mean and coeficient o f random variables are programed by a perturbation or by a weigh ted integral method. Therefore, it is not aplicable when erequisite programing. In a few number of stage analyses, RSM can construct a regresion model from the response of the c omplicated structural system, thus, saving time and efort significantly. However, the acuracy of RSM depends on the dist ance of the axial points and on the linearity of the limit stat e functions. To improve the convergence in exact solution regardl es of the linearity limit of state functions, an improved adaptive response surface method is developed. The analyzed res ults have ben verified using linear and quadratic forms of response surface functions in two examples. As a result, the be st combination of the improved RSM techniques is determined and programed in a numerical code. The developed linear adapti ve weighted response surface method (LAW-RSM) shows the closest converged reliability indices, compared with quadratic form or non-adaptive or non-weighted RSMs.

• Transactions on Electrical and Electronic Materials
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• v.7 no.2
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• pp.81-86
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• 2006

In this paper, the response surface modeling of the control of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatment is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. After the design of experiments is performed, the process model is then explored using the response surface methodology. The analysis of variance is used to analyze the statistical significance and the effect plots are also investigated to examine the relationship between the process parameters and the response.

• Knowledge Management Research
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• v.20 no.3
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• pp.39-47
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• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.157-166
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• 2024

Generally, the rubble mound installed on the slope embankment of the open-type wharf is designed based on the impact of wave force, with no consideration for the impact of seismic force. Therefore, in this study, dynamic centrifuge model test results were analyzed to examine the acceleration amplification of embankment reinforced with rubble mound under seismic conditions. The experimental results show that when rubble mounds were installed on the ground surface of the embankment, acceleration response of embankment decreased by approximately 22%, and imbalance in ground settlement decreased significantly from eight to two times. Furthermore, based on the experimental results, one-dimensional site response (1DSR) analyses were conducted. The analysis results indicated that reinforcing the embankment with rubble mound can decrease the peak ground acceleration (PGA) and short period response (below 0.6 seconds) of the ground surface by approximately 28%. However, no significant impact on the long period response (above 0.6 seconds) was observed. Additionally, in ground with lower relative density, a significant decrease in response and wide range of reduced periods were observed. Considering that the reduced short period range corresponds to the critical periods in the design response spectrum, reinforcing the loose ground with rubble mound can effectively decrease the acceleration response of the ground surface.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.04b
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• pp.121-123
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• 2002

Fast response characteristics of twisted nematic liquid crystal display (TN-LCD) cell with different nematic liquid crystals (NLCs) and cell gap on a rubbed polyimide (PI) surface were studied. High transmittance and fast response time of the TN-LCD on the rubbed PI surface were achieved by using high birefringence ($\Delta$ n) and low cell gap. It is considered that the transmittance and response time of the TN-LCD on the rubbed PI surface decreased as $\Delta$ nd decrease.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.334-340
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• 2013

This paper deals with the optimization of blade stiffened composite panels. The main objective of the research is to make response surfaces for the constraints. The response surface for warping thermal deformation was previously made for a fixed dimension composite structure. In this study, the dimensions of the blade stiffener were treated as design variables. This meant that a new response surface technique was required for the constraints. For the response surfaces, the lamination parameters, linear thermal expansions and dimensions of the structures were used as variables. A genetic algorithm was adopted as an optimizer, and an optimal result, which satisfied two constraints, was obtained. As a result, a new response surface was obtained, for predicting warping thermal deformation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.4
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• pp.336-345
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• 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.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.491-499
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• 2009

The removal of turbidity from $TiO_2$ wastewater by an electrocoagulation/flotation process was studied in a batch reactor. The response surface methodology (RSM) was applied to evaluate the simple and combined effects of the three main independent parameters, current, NaCl dosage and initial pH of the $TiO_2$ solution on the turbidity removal efficiency, and to optimize the operating conditions of the treatment process. The reaction of electrocoagulation/flotation was modeled by use of the Box-Behnken method, which was used for the fitting of a 2nd order response surface model. The application of RSM yielded the following regression equation, which is an empirical relationship between the turbidity removal efficiency of $TiO_2$ wastewater and test variables in uncoded unit: Turbidity removal (%)=69.76+59.76Current+11.98NaCl+4.67pH+5.00Current${\times}$pH-160.11$Current^2-0.34pH^2$. The optimum current, NaCl dosage and pH of the $TiO_2$ solution to reach maximum removal rates were found to be 0.186 A, 0.161 g/l and 7.599, respectively. This study clearly showed that response surface methodology was one of the most suitable method to optimize the operating conditions for maximizing the turbidity removal. Graphical response surface and contour plots were used to locate the optimum point.