• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.328-339
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• 2023

Methanol steam reforming (MSR) is a promising method for hydrogen supplying as a critical step in hydrogen fuel cell commercialization in mobile applications. Modelling and understanding of the reactor behavior is an attractive research field to develop an efficient reformer. Three-layer feed-forward artificial neural network (ANN) and Box-Behnken design (BBD) were used to modelling of MSR process using the Cu-SiO₂ aerogel catalyst. Furthermore, impacts of the basic operational variables and their mutual interactions were studied. The results showed that the most affecting parameters were the reaction temperature (56%) and its quadratic term (20.5%). In addition, it was also found that the interaction between temperature and Steam/Methanol ratio is important on the MSR performance. These models precisely predict MSR performance and have great agreement with experimental results. However, on the basis of statistical criteria the ANN technique showed the greater modelling ability as compared with statistical BBD approach.

• Journal of Electrochemical Science and Technology
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• v.14 no.2
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• pp.174-183
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• 2023

The dye wastewater discharge from the textile industries mainly affects the aquatic environment. Hence, the treatment of this wastewater is essential for a pollutant-free environment. The purpose of this research is to optimize the dye removal efficiency for process influencing independent variables such as pH, electrolysis time (ET), and current density (CD) by using Box-Behnken design (BBD) optimization and Genetic Algorithm (GA) modelling. The electrocoagulation treatment technique was used to treat the synthetically prepared Reactive Black dye solution under batch mode potentiometric operations. The percentage of error for the BBD optimization was significantly greater than for the GA modelling results. The optimum factors determined by GA modelling were CD-59.11 mA/cm², ET-24.17 minutes, and pH-8.4. At this moment, the experimental and predicted dye removal efficiencies were found to be 96.25% and 98.26%, respectively. The most and least predominant factors found by the beta coefficient were ET and pH respectively. The outcome of this research shows GA modeling is a better tool for predicting dye removal efficiencies as well as process influencing factors.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.37-42
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• 2012

This study investigated the use of Geobacter lovleyi with TBOS(Tetrabutoxysilane) for TCE(Trichloroethylene) dechlorination. The TCE dechlorination by Geobacter lovleiy was mathematically described as the independent variables such as initial concentration of TCE, protein mass of Geobacter lovleyi and initial concentration of TOBS, and these were modeled by the use of response surface methodology(RSM). These experiments were carried out as a Box-Behnken Design(BBD) consisting of 15 experiments. The application of RSM yielded the following equation, which is empirical relationship for the dechlorination efficiency($Y_1$, %) of TCE and first order kinetic constant of TCE($Y_2,\;d^{-1}$) by independent variables in coded unit : $Y_1=-11.50X_1$(initial concentration of TCE) + $4.25X_2$(protein mass as Geobacter lovleyi injected mass) - $4.75X_3$(initial concentration of TBOS) - ${6.58X_1}^2$ - ${8.58X_2}^2$ + 93.67, $Y_2=-10.92X_1+5.06X_2-4.89X_3-{4.93X_3}^2-2.19X_1X_2+2.54X_1X_3-2.19X_2X_3+16.71$. In this case, the value of the adjusted determination coefficient(adjusted $R^2$= 0.975 and 0.934) were closed to 1, showing a high significance of the model. Statistical results showed the order of TCE dechlorination at experimental factors to be initial TCE concentration > initial TBOS concentration > protein mass, but the interaction effects were non-significant.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.408-414
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• 2019

In this study, an antioxidant was extracted from dandelion leaves using traditional hot water and ultrasonic extraction methods. In order to optimize the extraction yield and total flavonoid, an antioxidant, Box-Behnken design (BBD) model among response surface analysis methods was used. In the case of hot water extraction, the extraction temperature and time as well as the ratio of alcohol/ultrapure water were set as variables, and for the ultrasonic extraction, the ultrasonic survey century and irradiation time and the ratio of alcohol/ultrapure water were variables. Optimum extraction conditions in the hot water extraction method were the extraction temperature and time of $45.76^{\circ}C$ and 1.75 h and the ratio of alcohol/ultrapure water of 41.92 vol.%. While for the ultrasonic extraction method the survey century of 512.63 W, the ratio of alcohol/ultrapure water of 56.97 vol.% and the extraction time of 20.79 min were optimum conditions. Expected reaction yield and flavonoid content values under the optimized condition were calculated as 22.09 wt.% and 28.98 mg QE/mL dw, respectively. In addition, the error value of less than 3% was obtained validating our optimization process.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.4
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• pp.349-360
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• 2020

Bio-conversion manufacturing technology has been developed to produce ginsenoside Rd which is increasingly in demand as a cosmetic material due to various possibilities related to improving skin function. In order to convert ginsenoside Rb1 which is contained in red ginseng saponin (RGS) into Rd, several commercial enzymes were tested. Viscoflow MG was found to be the most efficient. In order to optimize the conversion of RGS to ginsenoside Rd by enzymatic transition was carried out using response surface methodology (RSM) based on Box-Behnken design (BBD). The main independent variables were RGS concentration, enzyme concentration, and reaction time. Conversion of ginsenoside Rd was performed under 17 conditions selected according to BBD model and optimization conditions were analyzed. The concentration of the converted ginsenoside Rd ranged from 0.3113 g/L to 0.5277 g/L, and the highest production volume was obtained under condition of reacting 2% RGS and 1.25% enzyme for 13.5 hours. Consequently, RGS concentration, enzyme concentration which is 0.05 less than p-value and among the interactions between the independent variables, the interaction between enzyme concentration and reaction time was confirmed to be the most influential.

• Honam Mathematical Journal
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• v.35 no.1
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• pp.1-15
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• 2013

In this paper, we study a sheaf-theoretic analysis of the convolution algebra on quiver varieties. As by-products, we reinterpret the results of H. Nakajima. We also produce a refined form of the BBD decomposition theorem for quiver varieties. Finally, we study a construction of highest weight modules through constructible functions.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.2
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• pp.183-192
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• 2015

Response surface methodology (RSM) based on a Box-Behnken Design (BBD) was applied to optimize the thermal-alkaline pre-treatment operating conditions for anaerobic digestion of flotation scum in food waste leachate. Three independent variables such as thermal temperature, NaOH concentration and reaction time were evaluated. The maximum methane production of 369.2 mL $CH_4/g$ VS was estimated under the optimum conditions at $62.0^{\circ}C$, 10.1% NaOH and 35.4 min reaction time. A confirmation test of the predicted optimum conditions verified the validity of the BBD with RSM. The analysis of variance indicated that methane production was more sensitive to both NaOH concentration and thermal temperature than reaction time. Thermal-alkaline pretreatment enhanced the improvement of 40% in methane production compared to the control experiment due to the effective hydrolysis and/or solubilization of organic matters. The fractions with molecular weight cut-off of scum in food waste leachate were conducted before and after pre-treatment to estimate the behaviors of organic matters. The experiment results found that thermal-alkaline pre-treatment could reduce the organic matters more than 10kD with increase the organic matters less than 1kD.

• Resources Recycling
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• v.28 no.2
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• pp.23-30
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• 2019

An color sorting technique was introduced to recycle End-of-life automobile shredded bumpers. The color sorting is a innovate method of separating the differences in the color of materials which are difficult to separate in gravity and size classification by using a camera and an image process technique. Experiments were planned and optimal conditions were derived by applying BBD (Box-Behnken Design) in the reaction surface method. The effects of color sensitivity, feed rate and sample size were analyzed, and a second-order reaction model was obtained based on the analysis of regression and statistical methods and $R^2$ and p-value were 99.56% and < 0.001. Optimum recovery was 94.1% under the conditions of color sensitivity, feed rate and particle size of 32%, 200 kg/h, and 33 mm respectively. The recovery of actual experiment was 93.8%. The experimental data agreed well with the predicted value and confirmed that the model was appropriate.

• Applied Chemistry for Engineering
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• v.30 no.1
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• pp.29-33
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• 2019

Carbon nanotubes, nanofibers and powders were used for acetylene adsorption experiments. A total of 15 different experiments were designed by 3-level of Box-Behnken Design (BBD) with 3 factors including the Pd concentration of 0 to 5%, adsorption temperature of 30 to $80^{\circ}C$ and $C_2H_2/CO_2$ of 3 to 10. Based on those data, a second order polynomial regression analysis was used to derive the adsorption amount prediction equation according to operating conditions. The adsorption temperature showed the greatest influence index while the $C_2H_2/CO_2$ ratio showed the smallest according to the F-value measurement of the ANOVA analysis. However, there was little interaction between major factors. In the adsorption optimization analysis, a 22.0 mmol/g was adsorbed under the conditions of Pd concentration of 3.0%, adsorption temperature of $47^{\circ}C$ and $C_2H_2/CO_2$ of 10 with 95.9% accuracy.

• 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.