• Applied Chemistry for Engineering
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• v.32 no.5
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• pp.562-568
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• 2021

An O/W (oil in water) emulsion, wheat germ oil raw material, was produced by using natural wheat germ oil and composite sugar-ester. The effects of variables such as the hydrophile-lipophile balance (HLB) value, added emulsifier amount, and emulsification time on the average particle size, emulsification viscosity and ESI of O/W wheat germ oil emulsion were investigated. The parameters of the emulsification process produced by the central composite design model of the response surface methodology (CCD-RSM), which is a reaction surface analysis method, were simulated and optimized. The optimum process conditions obtained from this paper for the production of O/W wheat germ oil emulsion were 8.4, 6.4 wt%, 25.4 min for the HLB value, amount of emulsifier, and emulsion time, respectively. The predicted reaction values by CCD-RSM model under the optimum conditions were 206 nm, 8125 cP, and 98.2% for mean droplet size (MDS), viscosity, and ESI, respectively, based on the emulsion after 7 days. The MDS, viscosity and ESI of the emulsion obtained from actual experiments were 209 nm, 7974 cP and 98.7%, respectively. Therefore, it was possible to design an optimization process for evaluating the stability of the emulsion of wheat germ oil raw material by CCD-RSM.

• Journal of Microbiology and Biotechnology
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• v.22 no.1
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• pp.92-99
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• 2012

The optimal physical factors affecting enzyme production in an airlift fermenter have not been studied so far. Therefore, the physical parameters such as aeration rate, pH, and temperature affecting PLA-degrading enzyme production by Actinomadura keratinilytica strain T16-1 in a 3 l airlift fermenter were investigated. The response surface methodology (RSM) was used to optimize PLA-degrading enzyme production by implementing the central composite design. The optimal conditions for higher production of PLA-degrading enzyme were aeration rate of 0.43 vvm, pH of 6.85, and temperature at $46^{\circ}C$. Under these conditions, the model predicted a PLA-degrading activity of 254 U/ml. Verification of the optimization showed that PLA-degrading enzyme production of 257 U/ml was observed after 3 days cultivation under the optimal conditions in a 3 l airlift fermenter. The production under the optimized condition in the airlift fermenter was higher than un-optimized condition by 1.7 folds and 12 folds with un-optimized medium or condition in shake flasks. This is the first report on the optimization of environmental conditions for improvement of PLA-degrading enzyme production in a 3 l airlift fermenter by using a statistical analysis method. Moreover, the crude PLA-degrading enzyme could be adsorbed to the substrate and degraded PLA powder to produce lactic acid as degradation products. Therefore, this incident indicates that PLA-degrading enzyme produced by Actinomadura keratinilytica NBRC 104111 strain T16-1 has a potential to degrade PLA to lactic acid as a monomer and can be used for the recycle of PLA polymer.

• Journal of Welding and Joining
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• v.26 no.2
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• pp.85-91
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• 2008

In general, the quality of a welding process tends to vary with depending on the work environment or external disturbances. Hence, in order to achieve the desirable quality of welding, we should have the optimal welding condition that is not significantly affected by these changes in the environment or external disturbances. In this study, we used a dual response surface method in consideration of both the mean output variables and the standard deviation in order to optimize the V-groove arc welding process. The input variables for GMA welding process with the dual response surface are welding voltage, welding current and welding speed. The output variables are the welding quality function using the shape factor of bead geometry. First, we performed welding experiment on the interested area according to the central composite design. From the results obtained, we derived the regression model on the mean and standard deviation between the input and output variables of the welding process and then obtained the dual response surface. Finally, using the grid search method, we obtained the input variables that minimize the object function which led to the optimal V-groove arc welding process.

• Journal of Dairy Science and Biotechnology
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• v.26 no.2
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• pp.51-56
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• 2008

Using central composite design, we have designed optimization of the manufacturing of processed butter. And response surface analysis by least-square regression was used Statistical Analysis System(SAS). Central composite design can be achieved by response surface techniques that allow flexibility in modeling and analysis. Response surface methodology(RSM) was used to optimize hardness(%) using as independent variables; the content of butter($X_1$), ranging from 50 to 90(%), the content of soybean oil($X_2$), from 0 to 20(%), and the hydrogenated soybean oil($X_3$) from 0 to 4(%). The results on the regression coefficients calculated for overrun by response surface by least-square regression(RSREG) were followed. It was considered that the linear regression was significant(p<0.01). As for the processed butter, the regression model equation for the hardness(Y, %) to the change of an independent variable could be predicted as follow: $Y=60.88-8.92X_2-{29.3X_2}^2$. The optimal for the manufacturing of processed butter were determined at the content of butter of 88.22%, soybean oil of 6.71% and hydrogenated soybean oil of 2.36%, respectively. Optimum compositions were resulted in hardness of 65.78 N. Finally the reference sample(Butter in the morning, Seoul Dairy Co-op.) and processed butter manufacturing under the optimal conditions were compared with spreadability test. The spreadability scores result from reference sample and butter under optimal conditions was not found a significant difference.

• Korean Journal of Agricultural Science
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• v.45 no.2
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• pp.265-282
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• 2018

The purpose of this research was to produce symmetric (Saturated-Unsaturated-Saturated, SUS) triacylglycerol (TAG) using palm stearin fraction oil (PSFO) and high oleic sunflower oil (HOSO) as substrates to replace cocoa butter. PSFO was blended with HOSO (1 : 2 weight ratio), and $lipozyme^{(R)}$ TLIM (20 weight % of the substrate) was added. Interesterification was carried out in a shaking water bath at $55^{\circ}C$ at 220 rpm for 6 hours. The response surface methodology (RSM) through the central composite face design was employed to observe the optimized SUS-TAG. The independent factors were the reaction temperature ($X_1$: 65, 75 and $85^{\circ}C$), reaction time ($X_2$: 1, 3 and 5 hours) and ratio of TLIM ($X_3$: 10, 15 and 20 weight %). The dependent variables were $Y_1$ = Saturated-Unsaturated-Unsaturated (SUU, area %), $Y_2=SUS$ (area %), $Y_3$ = Saturated-Saturated-Unsaturated (SSU, area %), $Y_4$ = Unsaturated-Unsaturated-Unsaturated (UUU, area %), and $Y_5=sn-2$ unsaturated fatty acid (area %). The optimal conditions from the central composite face design minimized acyl migration while maximizing the presence of unsaturated fatty acid at the sn-2 position (73.43 area %). The optimal conditions were $X_1=65^{\circ}C$, $X_2=1hour$, and $X_3=20weight%$. As a result of the response surface analysis, the lack of fits was found as $Y_1=0.622$, $Y_2=0.438$, $Y_3=0.264$, $Y_4=0.526$, and $Y_5=0.215$, and their $R^2$ were 0.897, 0.944, 0.826, 0.857, and 0.867, respectively.

• Journal of Microbiology and Biotechnology
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• v.29 no.7
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• pp.1061-1070
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• 2019

In the present study, the optimization of poly(${\gamma}$-glutamic acid) (${\gamma}$-PGA) production by Bacillus sp. FBL-2 was studied using a statistical approach. One-factor-at-a-time method was used to investigate the effect of carbon sources and nitrogen sources on ${\gamma}$-PGA production and was utilized to select the most significant nutrients affecting the yield of ${\gamma}$-PGA. After identifying effective nutrients, response surface methodology with central composite design (CCD) was used to obtain a mathematical model to identify the optimum concentrations of the key nutrients (sucrose, $\text\tiny{L}$-glutamic acid, yeast extract, and citric acid) for improvement of ${\gamma}$-PGA production. The optimum amount of significant medium components appeared to be sucrose 51.73 g/l, $\text\tiny{L}$-glutamic acid 105.30 g/l, yeast extract 13.25 g/l, and citric acid 10.04 g/l. The optimized medium was validated experimentally, and ${\gamma}$-PGA production increased significantly from 3.59 g/l (0.33 g/l/h) to 44.04 g/l (3.67 g/l/h) when strain FBL-2 was cultivated under the optimal medium developed by the statistical approach, as compared to non-optimized medium.

• Steel and Composite Structures
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• v.19 no.1
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• pp.111-129
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• 2015

This paper first presents an experimental study of twelve specimens for their creep performance, including nine concrete-filled steel tubular (CFST) columns and three plain concrete columns, subjected to three levels of sustained axial loads for 1710 days. Then, the creep strain curves are predicted from the existing creep models including the ACI 209 model, the MC 78 model, and the MC 90 model, and further a fitted creep model is obtained by experimental data. Finally, the creep effects of a CFST arch bridge are analyzed to compare the accuracy of the existing creep models. The experimental results show that the creep strains in CFST specimens are far less than in the plain concrete specimens and still increase after two years. The ACI 209 model outperforms the MC 78 model and the MC 90 model when predicting the creep behavior of the CFST specimens. Analysis results indicate that the creep effects in the CFST arch bridge are significant. The deflections and stresses calculated by the ACI 209 model are the closest to the fitted model in the three existing models, demonstrating that the ACI 209 model can be used for creep analysis of CFST arch bridges and can meet the engineering accuracy requirement when lack of experimental data.

• Steel and Composite Structures
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• v.9 no.1
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• pp.1-17
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• 2009

This paper is focused on the buckling and post buckling behaviour of rectangular corrugated board panels simply supported and subjected to compression load. The aim of the work is to understand the failure mechanism of investigated structure in order to quantify the effect of design parameters on the strength of a panel of given geometry. Two numerical models were developed adopting the finite element method. In the first one the corrugated board is represented by means of shell elements adopting an equivalent material, in the second the local structure is described in full detail modelling both straight and corrugated layers by means of shell elements and representing the connection between layers by special interface elements. The model correctness was checked by the comparison between out of plane central displacement predicted by the models and the experimental values found in literature. For the same case the effect of panel planarity error was evaluated. Finally a parametric analysis to investigate the effect of design parameters was carried out.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.102-112
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• 1995

Estimation of each of mean response, difference between mean responses and derivatives of the response function is a possible objective of a response surface design. These objectives are to be achieved simultaneously when an experiment is designed to improve mean response. For the situations where departure from the assumed model is suspected, first and second order designs for improving mean response are obtained by combining minimum bias designs for the individual design objectives. D- and A-optimalities are used for selecting specific second order designs. The results are applied to central composite designs.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.43-50
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• 2009

Semi dry cutting known as MQL (Minimum Quantity Lubrication) machining is widely spreaded into the machining shops nowadays. The objective of this research is to suggest how to derive optimum cutting conditions for the milling process in MQL machining. To reach these goals, a bunch of finish milling experiments was carried out while varying cutting speed, feed rate, oil quantity, depth of cut and so on with MQL. Then, response surface analysis was introduced for the variance analysis and the regression model with the experimental data. Finally, desirability function based on regression model was used to obtain optimal cutting parameters and verification experiment was done.