• Journal of Environmental Science International
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• v.19 no.7
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• pp.889-900
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• 2010

The experimental design and response surface methodology (RSM) have been applied to the investigation of the electro-UV complex process for the disinfection of E. coli in the water. The disinfection reactions of electro-UV process were mathematically described as a function of parameters power ($X_1$), NaCl dosage ($X_2$), initial pH ($X_3$) and disinfection time ($X_4$) being modeled by use of the Box-Behnken technique. The application of RSM using the Box-Behnken technique yielded the following regression equation, which is an empirical relationship between the residual E. coli number and test variables in actual variables: Ln (CFU) = 23.57 - 0.87 power - 1.87 NaCl dosage - 2.13 pH - 2.84 time - 0.09 power time - 0.07 NaCl dosage pH + 0.14 pH time + 0.03 $power^2$ + 0.47 NaCl $dosage^2$ + 0.20 $pH^2$+ 0.33 $time^2$. The model predictions agreed well with the experimentally observed result ($R^2$ = 0.9987). Graphical response surface and contour plots were used to locate the optimum point. The estimated ridge of maximum response and optimal conditions for the E. coli disinfection using canonical analysis was Ln 1.06 CFU (power, 15.40 W; NaCl dosage, 1.95 g/L, pH, 5.94 and time, 4.67 min). To confirm this optimum condition, the obtained number of the residual E. coli after three additional experiments were Ln 1.05, 1.10 and Ln 1.12. These values were within range of 0.62 (95% PI low)~1.50 (95% PI high), which indicated that conforming the reproducibility of the model.

• Advances in environmental research
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• v.6 no.3
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• pp.217-227
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• 2017

In this study, the elimination of $Ni^{2+}$ using 13X sorbent due to an electrostatic interaction was reported. The significant factors including pH, time and 13X sorbent amount were investigated using Box-Behnken design (BBD). In the optimum experimental conditions, the linear rang and limit of detection of the proposed method were 0.1-20 and $0.102mg\;L^{-1}$, respectively. The precision as RSD% was 1.3% for concentration of $2mg\;L^{-1}$. Concerning the excellent recoveries in a short time with highly efficient sample clean-up and removal, this method may be a very powerful and innovative future sample removal technique. To the best of our knowledge, this is the first report on using BBD for optimizing the parameters affected the removal of $Ni^{2+}$ by 13X zeolite sorbent.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.3
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• pp.149-156
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• 2011

This experimental design and response surface methodology (RSM) have been applied to the investigation of the electro-UV-ultrasonic complex process for the disinfection of E. coli in the water. The disinfection reactions of electro-UV-ultrasonic process were mathematically described as a function of parameters power of electrolysis ($X_1$), UV ($X_2$), and ultrasonic process ($X_3$) being modeled by use of the Box-Behnken technique, which was used for fitting 2nd order response surface model. The application of RSM yielded the following regression equation, which is empirical relationship between the residual E. coli number (Ln CFU) in water and test variables in coded unit: residual E. coli number (Ln CFU) = 23.69 - 3.75 Electrolysis - 0.67 UV - 0.26 Ultrasonic - 0.16 Electrolysis UV + 0.05 Electrolysis Ultrasonic + 0.27 $Electrolysis^2$ + 0.14 $UV^2$ - 0.01 $Ultrasonic^2$). The model predictions agreed well with the experimentally observed result ($R^2$ = 0.983). Graphical 2D contour and 3D response surface plots were used to locate the optimum range. The estimated ridge of maximum response and optimal conditions for residual E. coli number (Ln CFU) using 'numerical optimization' of Design-Expert software were 1.47 Ln CFU/L and 6.94 W of electrolysis, 6.72 W of UV and 14.23 W of ultrasonic process. This study clearly showed that response surface methodology was one of the suitable methods to optimize the operating conditions and minimize the residual E. coli number of the complex disinfection.

• Environmental Engineering Research
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• v.25 no.4
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• pp.488-497
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• 2020

The present study investigates the feasibility of nitrogenous heterocyclic compounds (NHCs) (Pyridine-Quinoline) degradation by catalytic wet peroxidation (CWPO) in the presence of nanoscale zerovalent iron supported on granular activated carbon (nFe⁰/GAC) using statistical optimization technique. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the process parameters of CWPO process such as initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of pyridine (Py) and quinolone (Qn) were chosen as the main variables, and total organic carbon (TOC) removal and total Fe leaching were selected as the investigated response. The optimization of process parameters by desirability function showed the ~85% of TOC removal with process condition of initial solution pH 3.5, catalyst dose of 0.55 g/L, hydrogen peroxide concentration of 0.34 mmol, initial concentration of Py 200 mg/L and initial concentration of Qn 200 mg/L. Further, for TOC removal the analysis of variance results of the RSM revealed that all parameter i.e. initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of Py and initial concentration of Qn were highly significant according to the p values (p < 0.05). The quadratic model was found to be the best fit for experimental data. The present study revealed that BBD was reliable and effective for the determination of the optimum conditions for CWPO of NHCs (Py-Qn).

• Journal of the Korean Chemical Society
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• v.58 no.2
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• pp.198-204
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• 2014

In this present study, bagasse based pulp and paper industry wastewater was treated under different operating conditions such as initial pH (6-8), temperature ($25-35^{\circ}C$) and contact time (3-7 days) by using Bacillus subtilis. Response surface methodology (RSM) coupled with Box-Behnken response surface design (BBD) was employed to investigate the effect of process variables on the responses such as turbidity, biological oxygen demand (BOD) and chemical oxygen demand (COD) removal. The experimental data were analyzed by Pareto analysis of variance (ANOVA) and the second order polynomial models were developed. Interactive effects of the process variables on the responses were studied using plotting 3D response surface contour graph and the optimum process conditions were found to be: initial pH of 7, temperature of $30^{\circ}C$ and contact time of 5 days. Under these conditions, removal efficiencies of turbidity, BOD and COD were found to be 85%, 93% and 80% respectively which are close agreement with real experiments. These results indicate that the treatment of bagasse based pulp and paper industry wastewater using Bacillus subtilis is an effective and novel technique.

• Journal of Microbiology and Biotechnology
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• v.18 no.12
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• pp.1903-1907
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• 2008

Prodigiosin is a natural red pigment with algicidal activity against Cochlodinium polykrikoides, a major harmful red-tide microalga. To increase the yield of prodigiosin production by Hahella chejuensis KCTC 2396, significant medium components were determined using a two-level Plackett-Burman statistical design technique. Among 12 components included in basal medium, $NaHCO_3$, ${Na}_{2}{SiO}_{3}$, ${NH_4}{NO_3}$, ${Na}_{2}{SO}_{4}$ and $CaCl_2$ were determined to be important for prodigiosin production. The medium formulation was finally optimized using a Box-Behnken design as follows: 1% sucrose; 0.4% peptone; 0.1 % yeast extract; and (g/l): NaCl, 20.0; ${Na}_{2}{SO}_{4}$, 9.0; $CaCl_2$, 1.71; KCl, 0.4; and (mg/l): ${H_3}{BO_3}$, 10.0; KBr, 50.0; NaF, 2.0; $NaHCO_3$, 45.0; ${Na}_{2}{SiO}_{3}$, 4.5; ${NH_4}{NO_3}$, 4.5. The predicted maximum yield of prodigiosin in the optimized medium was 1.198 g/l by the Box-Behnken design, whereas the practical production was 1.495 g/l, which was three times higher than the basal medium (0.492 g/l).

• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.761-768
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• 2013

Removal of COD and TSS from rice mill wastewater was investigated using continuous electrocoagulation method (CEC). The electrical energy consumption (EEC) of the process was also examined in order to evaluate the economic viability. The Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM) were used to investigate the effects of major operating variables. Initial pH, current density, electrode distance and flow rate were selected as independent variables in BBD while COD removal, TSS removal and EEC were considered as the response functions. The predicted values of responses obtained using the response function was in good agreement with the experimental data. Optimum operating conditions were found to be pH of 7, current density of 15 mA $cm^{-2}$, electrode distance of 5 cm and flow rate of 70 ml/min. Under these conditions, greater than 89% removal of COD and TSS were obtained with EEC value of 7 KWh.

• Environmental Engineering Research
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• v.24 no.3
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• pp.484-494
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• 2019

This paper presents a preliminary investigation of the optimum nutrients combination required for bioremediation of spent-engine oil contaminated soil using Box-Behnken-Design. Three levels of cow-manure, poultry-manure and inorganic nitrogen-phosphorus-potassium (NPK) fertilizer were used as independent biostimulants variables; while reduction in total petroleum hydrocarbon (TPH) and total soil porosity (TSP) response as dependent variables were monitored under 6-week incubation. Ex-situ data generated in assessing the degree of biodegradation in the soil were used to develop second-order quadratic regression models for both TPH and TSP. The two models were found to be highly significant and good predictors of the response fate of TPH-removal and TSP-improvement, as indicated by their coefficients of determination: $R^2=0.9982$ and $R^2=1.000$ at $p{\leq}0.05$, respectively. Validation of the models showed that there was no significant difference between the predicted and observed values of TPH-removal and TSP-improvement. Using numerical technique, the optimum values of the biostimulants required to achieve a predicted maximum TPH-removal and TSP-improvement of 67.20 and 53.42%-dry-weight per kg of the contaminated soil were as follows: cow-manure - 125.0 g, poultry-manure - 100.0 g and NPK-fertilizer - 10.5 g. The observed values at this optimum point were 66.92 and 52.65%-dry-weight as TPH-removal and TSP-improvement, respectively.

• 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.