• Journal of the Korean Statistical Society
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• 제7권2호
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• pp.109-119
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• 1978

When a response surface by a seconde order polynomial regression model, the stationary point is obtained by solving simultaneous linear equations. But the point is a function of random variables. We can find a confidence region for this point as Box and Hunter provided. However, the confidence region is often too large to be useful for the experiments, and it is necessary to augment additional design points in order to obtain a satisfactory confidence region for the stationary point. In this note, the author suggests a method how to augment design points "eficiently", and shows the change of the confidence region of the estimated stationary point in a response surface.e surface.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.760-763
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• 2005

Optimum design of the tooth surface for the reduction of transmission error is very difficult to determine analytically due to nonlinearity of transmission error under the several load condition. The design of tooth surface that can give a low noise under the various load condition is very important. Therefore, this study proposes the method to determine the optimal lead curve and robust design of the tooth surface by using the response surface method. To do so, the design variables are selected by a screening experiment. Then the fitted regression model Is built with the check of the usefulness of the model. The model with constraints is solved to obtain the optimum values for the lead curve and the robust design fur the tooth surface.

• 한국축산식품학회지
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• 제37권1호
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• pp.139-146
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• 2017

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources.

• 한국유체기계학회 논문집
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• 제16권4호
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• pp.22-27
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• 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.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.557-564
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• 2006

Life-cycle performance and maintaining cost predictions are required for the effective management for bridges. In Korea, the importance of management of bridges has been recognized over the past two decades, resulting in the development of databases and various bridge management support tools by both government and private sectors. However, none of these tools has truly included the expected features of the bridge management system (EMS) for the next generation such as the quantification of the effects of maintenance interventions on bridge condition and safety. In this paper, a novel quantification process to simulate the life-cycle performance of steel box bridges has been developed. The process is based on the Response Surface method. Various performance-related variables aloe investigated to identify a set of significant design variables to construct the response surfaces.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.741-757
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• 2000

In may experimental situations, whenever a block design is used, the block effect is usually considered to be fixed. There are, however, experimental situations in which it should be treated as random. The choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of he prediction variance even if the experimental runs re the same. Therefore, care should be exercised in the selection of blocks. In this paper, in the presence of a random block effect, we propose a graphical method or evaluating the effect of blocking in response surface designs using cuboidal regions. This graphical method can be used to investigate how the blocking has influence on the prediction variance throughout all experimental regions of interest when this region is cuboidal, and compare the block effects in the cases of the orthogonal and non-orthogonal block designs, respectively.

• 한국항공우주학회지
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• 제36권5호
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• pp.438-447
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• 2008

본 논문에서는 이동최소자승법을 이용한 근사모델을 사용하여 신뢰성 최적설계를 수행하였다. 신뢰성 최적설계의 수행을 위한 반응표면 생성에는 RSM 과 Kriging이 사용될 수 있다. RSM은 계산시간은 빠르나 비선형성이 강한 문제에 약하며 Kriging은 비선형성이 강한 문제에 적용할 수 있으나 계산시간이 오래 걸리는 단점이 있다. 이 두 방법을 보완한 방법인 이동최소자승법(MLSM)을 이용하여 신뢰성 최적설계를 위한 반응표면을 생성하였다. 이동최소자승법을 이용한 신뢰성 최적설계기법은 Rosenbrock function 과 six-hump carmel back function으로 검증하였고 다른 기법과 비교하였다. 이동최소자승법을 이용하여 무인항공기 배기 덕트의 신뢰성 최적설계를 수행하였고 이는 항공우주구조물의 최적설계에 유용할 것으로 보여 진다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권4호
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• pp.750-769
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• 2015

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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• pp.182-183
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• 2019

In this study, the optimization of mixing proportion of press-forming board with blast furnace slag, pearlite and bottom ash was investigated using the response surface methodology. Ten Mixing proportions of specimens were designed by the response surface design, and then flexural failure load, moisture content and water absorption of specimens were measured. As a result of the reaction surface analysis based on the experimental results, it was possible to derive the optimal mixing proportion with the satisfaction of 93%.

• 한국환경과학회지
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• 제7권5호
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• pp.725-733
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• 1998

Three numerical experiments are done using IAP(Institute of Atmospheric Physics) global spectral model(T42L9) to investigate the influence of the surface temperatures on the 7-day simulation. Particularly, the response of the subtropical High in summer to the variation of soil temperature and sea surface temperature(SST) was emphasized through a series of experiments. Experiment 1 uses the June climate data as the earth surface conditions. Experiment 2 is similar to Experiment 1 except for the soil surface temperature. Experiment 3 is the same as Experiment 1 except for the modified SST, which is much warmer than the June climate SST on the sea around the Korean peninsula. The main finding in 7-day simulation is that the response of the subtropical high in summer to the variation of the sell surface temperature was much more than that to the variation of the SST. It is implied that the proper treatment of sell surface temperature is more important than that of the SST for the better 7-day simulation of the subtropical high in summer.