• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.621-626
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• 2021

A sequential design of experiments was used to optimize MOF-801 synthesis process. For the initial screening, a general 2^k factorial design was selected followed by the central composition design, one of the response surface methods. A 2³ factorial design based on the molar ratio of fumaric acid, dimethylformamide (DMF), and formic acid was performed to select the more suitable response variable for the design of experimental method among the crystallinity and BET specific surface area of MOF-801. After performing 8 synthesis experiments designed by MINITAB 19 software, the characteristic analysis was performed using XRD analysis and nitrogen adsorption method. The crystallinity with R² = 0.999 was found to be more suitable for the experimental method than that of BET specific surface area. Based on analysis of variance (ANOVA), it was confirmed that the molar ratio of fumaric acid and formic acid was a major factor in determining the crystallinity of MOF-801. Through the response optimization and contour plot of two factors, the optimal molar ratio of ZrOCl₂·8H₂O : fumaric acid : DMF : formic acid was 1 : 1 : 39 : 35. In order to optimize the synthesis process, the central composition design on synthesis time and temperature was performed under the identical molar ratio of precursors. The results derived through the designed 9 synthesis experiments were calculated using the quadratic model equation. Thus, the maximum crystallinity of MOF-801 predicted under the synthesis time and temperature of 7.8 h and 123 ℃, respectively.

• 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.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.852-857
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• 2004

A new and efficient method for estimating the statistical moments of a system performance function has been developed. The method consists of two steps: (1) An approximate response surface is generated by a quadratic regression model, and (2) the statistical moments of the regression model are then calculated by experimental design techniques proposed by Seo and $Kwak^{(4)}$. In this approach, the size of experimental region affects the accuracy of the statistical moments. Therefore, the region size should be selected suitably. The D-optimal design and the central composite design are adopted over the selected experimental region for the regression model. Finally, the Pearson system is adopted to decide the distribution type of the system performance function and to analyze structural reliability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1408-1418
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• 2000

Gradient-based optimization methods are inefficient in applications which require expensive function evaluations, and useless in applications where objective and/or constraint functions are 'noisy' due to modeling and cumulative numerical inaccuracy since gradient evaluation results cannot be reliable. Moreover, it is difficult to be integrated with commercial analysis software, and they cannot be employed when only experimental analysis results are available. In this research an optimization program based on a response surface method has been developed to overcome the aforementioned difficulties. Various methods for design of experiments and new proposed approximation models are implemented in the program. The effectiveness of the optimization program is tested on several test problems and results are discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1871-1877
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• 1999

An optimal design method using a response surface method for dynamic characteristics of a washer is presented. The proposed method uses the design of experiment and a computer model is used for the experiment. The value of the cost function is estimated using a computer model for each case of the design variable variation. An orthogonal array is used to obtain best cases to be considered with minimum number of experimentation. Using these experimental values, optimal design is performed using a response surface method. The method used in this paper can be applied to any complicated mechanical systems that can be modelled and analyzed by a computer program. The method is applied to the design of dynamic characteristics of a washer.

• The Korean Journal of Food And Nutrition
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• v.25 no.1
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• pp.17-25
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• 2012

이 연구는 블루베리 즙을 첨가하여 젤리의 제조조건을 최적화하고자 하였다. 16개의 블루베리 즙을 이용한 젤 시료는 Design Expert 프로그램을 이용하여 제조하였으며, 최적화를 위해 블루베리 즙(100~200 g), 설탕(40~160 g), 젤라틴(8~20 g)의 양을 독립변수로, 텍스처, pH, 관능평가 항목을 종속변수로 각각 선정하였다. 반응표면 분석법을 사용하기 위한 실험설계로 중심합성계획을 이용하였다. 각 항목별 최적조건은 Canonical 모형의 수치 최적화(numerical optimization)과 모형적 최적화(graphical optimization)를 통하여 선정하였으며, 그 중 가장 높은 desirability를 갖는 최적점을 선택하여 지점 예측(point prediction)을 통해 도출한 결과, 각 독립변수의 예측된 블루베리 즙을 첨가한 젤리의 최적값은 블루베리 주스 133.63 g, 설탕 160.0 g, 젤라틴은 12.78 g이었다.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.894-900
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• 2000

Optimization of chassis frame is performed according to the minimization of eleven responses representing one total frame weight, three natural frequencies and seven strength limits of chassis frame that are analyzed by using each response surface model from D-optimal design of experiments. After each response surface model is constructed form D-optimal design and random orthogonal array, the main effect and sensitivity analyses are successfully carried out by using this approximated regression model and the optimal solutions are obtained by using a nonlinear programming method. The response surface models and the optimization algorithms are used together to obtain the optimal design of chassis frame. The eleven-polynomial response surface models of the thirteen frame members (design factors) are constructed by using D-optimal Design and the multi-disciplinary design optimization is also performed by applying dual response analysis.

• Journal of Ocean Engineering and Technology
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• v.27 no.2
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• pp.27-32
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• 2013

A valve is a marine structure that is subjected to multiple seawater loads. Therefore, it is necessary to define the kind of loads applied to it to confirm whether the structure has sufficient strength. In this research, we aimed to find the optimal solution for the stress and deformation of valves under various loads. We first selected design variables and implement a finite element analysis according to changes in the thickness of each component of a valve based on a central composite design. Next we developed a regression model of the response surface. Using this model, we calculated the optimal objective value based on NSGA-II. Finally, to confirm the correspondence between the optimal objective value and the real FEM value, we compared the optimal result and structural analysis result to verify the performance of NSGA-II.

• Journal of Life Science
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• v.13 no.6
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• pp.794-798
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• 2003

Batch production of (S)-phenyl oxirane was investigated using epoxide hydrolase activity of Rhodosporidium toruloides SJ-4. Effect of reaction condition of asymmetric biohydrolysis of racemic phenyl oxirane was analyzed and optimized by response surface methodology. The optimal conditions of pH, temperature and DMSO cosolvent ratio were 7.4, $34^P\circ}C$, and 2.3%(v/v), respectively. The final yield was enhanced up to 67%, and reaction times required to reach 99% ee (enatiomeric excess) decreased down to 50% by response surface methodology Enantiopure (S)-phenyl oxirane with 100% enantiopurity and 24% yield (theoretical yield = 50%) was obtained from racemic substrate.