• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.2
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• pp.55-60
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• 2002

This paper presents an optimization procedure by using Response Surface Methodology(RSM) to determine design parameters for reducing cogging torque. RSM is achieved through using the experimental design method in combination with Finite Element Method and adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.

• 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.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.943-950
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• 2009

Cadmium (Cd) adsorption onto the activated carbon containing hydroxyapatite (HAP) was investigated in batch experiments and response surface methodology (RSM) using the Box-Behnken methods were applied to the experimental results. Cd adsorption with different HAP mass ratio of from 10% to 30%. With more HAP, Cd was more adsorbed. These results suggest that the higher HAP mass causes an increase of the ion exchange potential of the HAP sorbent. Equilibrium experimental results from Cd adsorption was fitted to Langmuir and Freundlich isotherm models. Cd adsorption on HAP sorbent were found to follow the Freundlich isotherm model well in the initial adsorbate concentration range. Also, Cd adsorption was a function of the HAP mass ratio ($x_1$), initial Cd concentration ($x_2$), and initial pH ($x_3$) from the application of the RSM. Statistical results showed the order of significance of the independent variables to be initial Cd concentration > HAP mass ratio > initial pH.

• Journal of Animal Science and Technology
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• v.53 no.3
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• pp.253-259
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• 2011

The aim of this work was to determine the method and predict the optimum conditions for egg quality stored for 7 days when combination treatments of irradiation and chitosan coating were applied using response surface methodology (RSM). A central composite design was chosen for the RSM in this study and the factors were irradiation dose (0~2 kGy) and concentration of chitosan coating material (0~2%). Performance of the irradiation and chitosan coating were evaluated by analyzing the egg quality and functional property factors. The predicted maximum level of Haugh units and foaming ability calculated by a developed model were 74.19 at 0 kGy of irradiation with coating by 0.96% chitosan solution and 50.83 mm at 2.0 kGy with 1.01%, respectively. The predicted minimum value of foam stability and 2-thiobarbituric acid reactive substances (TBARS) value were 2.97 mm at 0.39 kGy with 0.21% and 0.54 mg malonaldehyde/kg egg yolk at 0 kGy with 0.90% of chitosan solution, respectively. Results clearly showed that gamma irradiation negatively affected the Haugh unit and TBARS but positively affected the foaming capacity. The estimated value from the developed model by RSM was verified by no statistical difference with observed value. Therefore, RSM can be a good tool for optimization and prediction of egg quality when 2 or more treatments are combined. However, one should decide the target quality first to achieve a successful implementation of this technology.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.82-90
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• 2019

The Box-Benhken Design (BBD) model of response surface methodology (RSM) was used to optimize fluoride adsorption conditions in water using a 350℃ thermally treated cow bone. Water temperature, pH, contact time, and initial fluoride concentration were selected as variables to be optimized. A second order reaction equation was obtained from a Box-Behnken Design DoE experimental matrix of 29 runs. R² and p-value of the model were 0.9242 and <0.0001, respectively, indicating that the selected variables had a very substantial effect on the adsorption results. The optimized adsorption capacity of the thermally synthesized bone char was estimated to be 6.46 mgF/g at the water temperature of 39.68℃, pH 6.25, contact time of 88.81 minutes and an initial fluorine concentration of 14.64 mgF/L.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.582-588
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• 2010

This paper presents the Application of Response Surface Method for Optimal Transfer Conditions of MLCC Alignment System. his paper is composed of two parts: (1) Testing performance verification of MLCC alignment system, compared with manual operation; (2) Applying response surface method to figuring out the optimal transfer conditions of MLCC transfer system. Based on the successfully developed MLCC alignment system, the optimal transfer conditions have been explored by using RSM. The simulations using $ADAMS^{(R)}$ has been performed according to the cube model of CCD. By using $MiniTAB^{(R)}$, we have established the model of response surface based on the simulation results. The optimal conditions resulted from the response optimization tool of $MiniTAB^{(R)}$ has been verified by being assigned to the prototype of MLCC alignment system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.4
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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.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2609-2614
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• 2011

A proportional integral derivative (PID) controller is designed and applied to a magnetic levitation conveyor system to control the levitation gap length of the electromagnet constantly. The PID gain parameters are optimized by response surface methods (RSM). The controller is verified with the state-space model of electromagnetic suspension by MATLAB/SIMULINK program. And, the controller and the state-space model are also verified experimentally. Simulation and experimental results shows the effectiveness of the PID gain tuning by RSM as compared with the classical PID tuning.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.414-420
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• 2010

This paper presents a validation of the accuracy of a reduced order model(ROM) and the efficiency of the design optimization using a Proper Orthogonal Decomposition(POD) to transonic wing/fuselage system. Three dimensional Euler equations are solved to extrude snapshot data of the full order aerodynamic analysis, and then a set of POD basis vectors reproducing the behavior of flow around the wing/fuselage system is calculated from these snapshots. In this study, reduced order model constructed through this procedure is applied to several validation cases, and then it is confirmed that the ROM has the capability of the prediction of flow field in the space of interest. Additionally, after the design optimization of the wing/fuselage system with the ROM is performed, results of the ROM are compared with results of the design optimization using response surface model(RSM). From these, it can be confirmed that the design optimization with the ROM is more efficient than RSM.

• Food Science of Animal Resources
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• v.37 no.1
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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.