• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.557-564
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• 2019

The characteristics of the torque and torque ripple of Interior Permanent Magnet Synchronous Motor(IPMSM) are influenced by the size and position of the rotor magnet and the size of the stator slot. This paper deals with the optimal design method for improving torque and torque ripplerate for IPMSM using Response Surface Methodology(RSM). Two objective functions of torque output and torque ripple were derived from the sensitivity analysis by Plackett-Burmann(PB) for the characteristic variables affecting torque and torque ripple. Secondary characteristic variables were selected from the derived objective function and RSM secondary regression model function was estimated by the experiment schedule and analysis results according to the Central Composite Design (CCD). The reliability of the secondary regression model was verified using ANOVA table. The analysis according to the experimental schedule was verified by JMAG(Ver. 18.0) which is Finite Element Method(FEM) software. The torque output of IPMSM applied with final characteristic variables was increased torque output by 11.5 % and the torque ripplerate was reduced by 9.1 %.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.321-339
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• 2021

Response Surface Method (RSM) has been widely used for flammable cloud size prediction as it can reduce computational intensity for further Explosion Risk Analysis (ERA) especially during the early design phase of offshore platforms. However, RSM encounters the overfitting problem under very limited simulations. In order to overcome the disadvantage of RSM, Bayesian Regularization Artificial Neural (BRANN)-based model has been recently developed and its robustness and efficiency have been widely verified. However, for ERA during the early design phase, there seems to be room to further reduce the computational intensity while ensuring the model's acceptable accuracy. This study aims to develop an integrated method, namely the combination of Center Composite Design (CCD) method with Bayesian Regularization Artificial Neural Network (BRANN), for flammable cloud size prediction. A case study with constant and transient leakages is conducted to illustrate the feasibility and advantage of this hybrid method. Additionally, the performance of CCD-BRANN is compared with that of RSM. It is concluded that the newly developed hybrid method is more robust and computational efficient for ERAs during early design phase.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.35-43
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• 2001

As the demands for lightweight construction and precision grow, there is an increasing interest on hydroforming technology. This paper deals with designing automobile subframe for applying welded blanks hydroforming. In applying welded blanks hydroforming to automobile subframe, it is a serious problem that blanks wrinkle in deformed shape. To suppress wrinklings in blanks, the sections of the die where blanks wrinkled is modified. In addition to this, it is intended that the sum of thickness variation about wrinkling regions be minimized. For this purpose, parameters for influencing formability are selected and evaluated using orthogonal array. Among these parameters, parameters having a major effect on formability are selected again. Using CCD(central composite design) with the selected parameters, response surface is build up and optimal design is performed.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.299-306
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• 2023

In this study, the O/W emulsification processes with the natural surfactants that were extracted from Medicago sativa L. and Sapindus saponaria L. as emulsifiers were optimized using the central composite design-response surface methodology (CCD-RSM). Herein, independent parameters were the amounts of mixed emulsifiers, the mixing ratio of natural emulsifiers (soapberry saponin/alfalfa saponin), and the emulsification time, whereas the reaction parameters were the emulsion stability index (ESI), mean droplet size (MDS), and antioxidant activity (DPPH radical scanvenging activity). Through basic experiments, the ranges of operation variables for the amount of mixed emulsifiers, the mixing ratio of natural emulsifiers, and the emulsification time were 12~14 wt%, 30~70%, and 20~30 min, respectively. The optimum operation variables deduced from CCD-RSM for the amount of mixed emulsifiers, the mixing ratio of natural emulsifiers, and the emulsification time were 13.2 wt%, 44.2%, and 25.8 min, respectively. Under these optimal conditions, the expected values of the ESI, MDS, and antioxidant activity were 88.7%, 815.5 nm, and 38.7%, respectively. And, the measured values of the ESI, MDS, and antioxidant activity were 90.6%, 830.2 nm, and 39.6%, respectively, and the average experimental error for validating the accuracy was about 2.1%. Therefore, it was possible to design an optimization process for evaluating the O/W emulsion process using CCD-RSM.

• Applied Chemistry for Engineering
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• v.31 no.5
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• pp.532-538
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• 2020

In this study, emulsification process were conducted to manufacture the natural sunscreen from raw materials such as shea butter, olive emulsifier wax, and green tea extract. The emulsification was optimized by using the central composite design model-response surface methodology (CCD-RSM) where the response values were established as the mean droplet size (MDS) and emulsion stability index (ESI) after 7 days in addition to UV absorbance at 300nm. The amount of emulsifier and additives and emulsification time were established as operating variables and the optimal conditions of sunscreen emulsification were accepted as 3.70, 2.47 wt.%, and 15.42 min, respectively according to the result of CCD-RSM. On the other hand, the response values were estimated as 1173.80 nm and 99.56% for MDS and ESI, respectively, after 7 days, in addition to UV absorbance at 300 nm (2.47). The average error from actual experiments was a low level as about 3.0 ± 1.5%, which is mainly due to the fact that the optimization using CCD-RSM applied in this study was in the relatively high significant level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.535-541
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• 2015

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.359-368
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• 2014

The aim of our research was to apply experimental design methodology in the optimization of N, N-Dimethyl-4-nitrosoaniline (RNO, which is indictor of OH radical formation) degradation using gas mixing-circulation plasma process. The reaction was mathematically described as a function of four independent variables [voltage ($X_1$), gas flow rate ($X_2$), liquid flow rate ($X_3$) and time ($X_4$)] being modeled by the use of the central composite design (CCD). RNO removal efficiency was evaluated using a second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination ($R^2$) value of 0.9111, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the experimental data. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the RNO removal efficiency and independent variables in a coded unit: RNO removal efficiency (%) = $77.71+10.04X_1+10.72X_2+1.78X_3+17.66X_4+5.91X_1X_2+3.64X_2X_3-8.72X_2X_4-7.80X{_1}^2-6.49X{_2}^2-5.67X{_4}^2$. Maximum RNO removal efficiency was predicted and experimentally validated. The optimum voltage, air flow rate, liquid flow rate and time were obtained for the highest desirability at 117.99 V, 4.88 L/min, 6.27 L/min and 24.65 min, respectively. Under optimal value of process parameters, high removal(> 97 %) was obtained for RNO.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.661-666
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• 2000

Optimization of the elastic joint of train is performed according to the minimization of ten responses which represent driving safety and ride comfort of train and analyzed by using the each response se surface model from stochastic design of experiments. After the each response surface model is constructed, the main effect and sensitivity analyses are successfully performed by 2nd order approximated regression model as described in this paper. We can get the optimal solutions using by nonlinear programming method such as simplex or interval optimization algorithms. The response surface models and the optimization algorithms are used together to obtain the optimal design of the elastic joint of train. the ten 2nd order polynomial response surface models of the three translational stiffness of the elastic joint (design factors) are constructed by using CCD(Central Composite Design) and the multi-objective optimization is also performed by applying min-max and distance minimization techniques of relative target deviation.

• Journal of the Korean Magnetics Society
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• v.20 no.6
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• pp.239-243
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• 2010

This paper deals with the optimum design criteria for the premium efficiency of 250 kW traction induction motor, using response surface methodology (RSM) and finite element method (FEM). The focus of this paper is found firstly a design solution through the comparison of torque according to rotor bar shape, rotor dimensions variations. And secondly a mixed resolution with central composite design (CCD) is introduced and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model. The proposed procedure allows to be optimized the rotor copper bar shape, rotor slot, rotor dimensions starting from an existing motor or a preliminary design.