scholarly journals Using response surface methodology (RSM) for optimizing turbidity removal by electrocoagulation/electro-flotation in an internal loop airlift reactor

2019 ◽  
Vol 19 (8) ◽  
pp. 2476-2484 ◽  
Author(s):  
T. Ntambwe Kambuyi ◽  
F. Eddaqaq ◽  
A. Driouich ◽  
B. Bejjany ◽  
B. Lekhlif ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Energy Consumption ◽  
Response Surface ◽  
Removal Rate ◽  
Desirability Function ◽  
Airlift Reactor ◽  
Optimal Conditions ◽  
Turbidity Removal ◽  
Linear Interaction ◽  
Internal Loop

Abstract Response surface methodology (RSM) is used to optimize the electrocoagulation/electro-flotation process applied for the removal of turbidity from surface water in an internal loop airlift reactor. Two flat aluminium electrodes are used in monopolar arrangement for the production of coagulants. The central composite design is used as a second-order mathematical model. The model describes the change of the measured responses of turbidity removal efficiency and energy consumption according to the initial conductivity (X1), applied voltage (X2), treatment time (X3) and inter-electrode distance (X4). The evaluation of the model fit quality is done by analysis of variance (ANOVA). Fisher's F-test is used to provide information about the linear, interaction and quadratic effects of factors. Multicriteria methodology, mainly the desirability function (D), is used to determine optimal conditions. The results show that, for a maximal desirability function D = 0.79, optimal conditions estimated are X1 = 1,487 μS/cm, X2 = 5 V, X3 = 6.5 min, X4 = 14 mm. The corresponding turbidity removal rate and energy consumption are 84.15% and 0.215 kWh/m3 respectively. A confirmation study is then carried out at laboratory scale using the optimal conditions estimated. The results show a turbidity removal rate of 72.05% and an energy consumption of 0.210 kWh/m3.

Bioremediation Condition Optimization of Hydrocarbon in Soil Using Response Surface Methodology by Microbial Consortium KL9-1

2012 ◽  
Vol 518-523 ◽  
pp. 2073-2078 ◽  
Author(s):  
Qi You Liu ◽  
Yun Bo Zhang ◽  
Dong Feng Zhao ◽  
Chao Cheng Zhao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Microbial Consortium ◽  
Ph Value ◽  
Removal Rate ◽  
Desirability Function ◽  
Nitrogen And Phosphorus ◽  
Predictive Values ◽  
Independent Variables ◽  
Condition Optimization

A response surface methodology was applied to optimize the bioremediation condition of hydrocarbon in soil by microbial consortium KL9-1. A four-level Box-Behnken factorial design was employed to study the relationship of independent variables and dependent variable by applying pH value, inoculation amount of microbial consortium KL9-1, ratio of nitrogen and phosphorus (N/P ) and surfactant (SDBS) concentration as independent variables (factors) and crude oil removal rate as dependent variable (response). Then the statistically significant model was obtained and numerical optimization based on desirability function was carried out for pH 7.0, inoculation amount 50.0 mL, N/P 2: 1 and SDBS concentration 4.0 g, and the hydrocarbon removal rate reached as high as 52.58%. The predictive values showed good agreement with the experimental values under the optimization conditions, by standard variance <1.3%. It showed that the optimal result was reliable.

scholarly journals Multi-response optimization of magnetic field assisted EDM through desirability function using response surface methodology

2020 ◽  
Vol 29 (1) ◽  
pp. 19-35
Author(s):  
Anish Kumar ◽  
Renu Sharma
Keyword(s):  
Magnetic Field ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Performance Measures ◽  
Process Parameters ◽  
Removal Rate ◽  
Desirability Function ◽  
Surface Model ◽  
Electrode Wear ◽  
En 31

AbstractMagnetic field assisted electrical discharge machining (MFAEDM) is the modification of in conventional EDM process by use of magnetic field on EN-31. This article explain the application of response surface methodology to analyzes the effect of various process parameters such as Ton, Toff and Ip on performance measures such as material removal rate (MRR), electrode wear rate (EWR) and overcut (OC). Analysis of variance was used to check the adequacy of response surface model and significance of process parameters on performance measures. Multi-objective desirability function has been applied to obtain the optimal process parameter settings. Thereafter, machined surface of EN-31 characterized through SEM and EDX. The novelty of this paper is to improve the strategies for flushing the debris which remain clogged in standard EDM in-between machining gap that will interrupts the regular discharge conditions and reduces cutting rate as well as deteriorate the surface characteristics.

Chemical Demulsification-Ultrasonic Recycle Oil from Oil-Based Drilling Fluid Using Response Surface Methodology

2014 ◽  
Vol 955-959 ◽  
pp. 2653-2657 ◽  
Author(s):  
Mi Jia Zhu ◽  
Hai Jun Liu ◽  
Jun Yao ◽  
Qing Hua Luo
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Oil Content ◽  
Heating Temperature ◽  
Removal Rate ◽  
Drilling Fluid ◽  
Oil Removal ◽  
Optimal Conditions ◽  
Box Behnken Design ◽  
Ultrasonic Time

The abandoned oil-based drilling fluid is a kind of water-in-oil system with high oil content, which has a significant recovery value. The effects of demulsifier dosage, heating temperature, ultrasonic time and centrifuge speed on the oil recycle were investigated in the chemical demulsification-ultrasonic treatment of oil-based drilling fluid. From the results of the experiment, BSF-L62 was a suitable reagent with the highest oil removal rate among the selected demulsifiers. The main influencing factors were optimized using the Response Surface Methodology based on Box-Behnken design. The oil removal rate was up to 76.9% under the optimal conditions of demulsifier dosage of 250 mg/L, heating temperature of 70 °C, ultrasonic time of 12.5 min and centrifuge speed of 7000 r/min.

scholarly journals Optimization of biochar preparation from the stem of Eichhornia crassipes using response surface methodology on adsorption of Cd2+

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Runjuan Zhou ◽  
Ming Zhang ◽  
Jinhong Zhou ◽  
Jinpeng Wang
Keyword(s):  
Response Surface Methodology ◽  
Adsorption Capacity ◽  
Response Surface ◽  
Heating Rate ◽  
Eichhornia Crassipes ◽  
Heating Temperature ◽  
Removal Rate ◽  
Heating Time ◽  
Optimal Conditions ◽  
Preparation Conditions

AbstractIn this study, preparation of Eichhornia crassipes stem biochar (ECSBC) was optimized and applied for the removal of Cd2+ from aqueous solution. To obtain the best adsorption capacity of ECSBC, the response surface methodology (RSM) was used to optimize the preparation conditions of ECSBC (OECSBC). The interactions among heating time (X1), heating temperature (X2) and heating rate (X3) were designed by Box-Behnken Design (BBD) experiments. The software gave seventeen runs experiment within the optimal conditions towards two response variables (removal rate and adsorption capacity for Cd2+). The results showed that the mathematical model could fit the experimental data very well and the significance of the influence factors followed the order as heating temperature (X2) > heating rate (X3) > heating time (X1), and the influence of interaction term is: X1 and X2 (heating time and heating temperature) > X2 and X3 (heating temperature and heating rate) > X1 and X3 (heating time and heating rate). Based on the analysis of variance and the method of numerical expected function, the optimal conditions were heating time of 2.42 h, heating temperature of 393 °C, and heating rate of 15.56 °C/min. Under the optimum conditions, the predicted the maximum removal rate and adsorption capacity were 85.2724% and 21.168 mg/g, respectively, and the experimental value of removal rate and adsorption capacity for Cd2+ were 80.70% and 20.175 mg/g, respectively, the deviation from the predicted value were 5.36% and 4.69%. The results confirmed that the RSM can optimize the preparation conditions of ECSBC, and the adsorption capacity of OECSB was improved.

Optimization of Kaolin Wastewater Treatment Processes Research via Response Surface Methodology

2011 ◽  
Vol 366 ◽  
pp. 361-365
Author(s):  
Li Ping Wu ◽  
Dian Mo Zheng ◽  
Sheng Gan Zhu
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Ph Value ◽  
Removal Rate ◽  
Average Particle Size ◽  
Average Particle ◽  
Good Prediction ◽  
Turbidity Removal ◽  
Treatment Processes

The CCD mathematical model of response surface methodology (RSM) has been used to optimize the process parameters of treating kaolin wastewater, the interaction of the factors on removal rate of turbidity and average particle size of floc such as the flocculation temperature ,the pH value, the dosage of PAC, the dosage of St-PAM were studied. The optimum condition of the effluent disposal via the experiment was as follows: the flocculation temperature was 25°C,the pH value was 6.5, the dosage of PAC was 21.5/mg/L, the dosage of St-PAM was 5/mg/L.In these conditions,the turbidity removal rate of the kaolin wastewater was 97.56%,and the average particle size of flocculation body was 0.994mm. Under the optimum conditions, the removal rate of turbidity and the average particle size of flocculation body was respectively 98.05% and 1.09mm.The model had good prediction effect.

scholarly journals Optimization of Preparation Conditions of Novel Adsorbent from Sugar Scum Using Response Surface Methodology for Removal of Methylene Blue

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Y. El maguana ◽  
N. Elhadiri ◽  
M. Bouchdoug ◽  
M. Benchanaa ◽  
A. Boussetta
Keyword(s):  
Methylene Blue ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Calcination Temperature ◽  
Desirability Function ◽  
Organic Pollutant ◽  
Optimal Conditions ◽  
Methylene Blue Adsorption ◽  
Preparation Conditions ◽  
Kinetic Test

A novel and inexpensive adsorbent was prepared from sugar scum for the removal of methylene blue as an organic pollutant from aqueous solutions. The response surface methodology was used to study the effects of the calcination temperature and time on the yield and the methylene blue adsorption. In order to determine the optimal conditions of the preparation, the Doehlert design and desirability function were applied. The increase in calcination temperature increases the methylene blue adsorption and induces a reduction in yield. The optimal conditions have been identified to be a calcination temperature of 986°C and calcination time of 61 min. The characteristics of the obtained adsorbent were determined using SEM/EDX, and surface functions were obtained based on FTIR and pHpzc. The produced adsorbent had a porous structure and a pHpzc of 12.5. The results showed that the yield was 49.74% and the adsorption of methylene blue was 24.52 mg·g−1 with a contact time of 10 h determined by kinetic test. The sugar scum was found to be an effective material for the preparation of appropriate adsorbent for dye removal from wastewater.

scholarly journals Comparative Prediction of Red Alga Biosorbent Performance in Dye Removal using Multivariate Models of Response Surface Methodology (RSM) and Artificial Neural Network (ANN)

2018 ◽  
Vol 7 (4.35) ◽  
pp. 551
Author(s):  
Nadiah Mokhtar ◽  
Edriyana A.Aziz ◽  
Azmi Aris ◽  
W.FW. Ishak ◽  
Anwar P.P. Abdul Majeed ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Dye Removal ◽  
Removal Rate ◽  
Desirability Function ◽  
Quadratic Model ◽  
Ann Model ◽  
Biosorption Process ◽  
Rsm Model ◽  
High Removal Rate

Red algae species, Euchema Spinosum (ES) in Malaysia possesses excellent biosorbent properties in removing dyes from aqueous solutions. In the present study, the experimental design for the biosorption process was carried out via response surface methodology (RSM-CCD). A total of 20 runs were carried out to generate a quadratic model and further analysed for optimisation. Prior to the evaluation, the characterisation study of the ES was performed. It was observed that the maximum uptake capacity of 399 mg/g (>95%) is obtained at equilibrium time of 60 min, pH solution of 6.9-7.1, dosage of 0.72 g/L and initial dye concentration of 300 g/L through statistical optimisation (CCD-RSM) based on the desirability function. It is demonstrated in the present study that the ANN model (R2=0.9994, adj-R2=0.9916, MSE=0.19, RMSE=0.4391, MAPE=0.087 and AARE=0.001) is able to provide a slightly better prediction in comparison to the RSM model (R2= 0.9992, adj-R2= 0.9841, MSE=1.95, RMSE=1.395, MAPE=0.08 and AARE=0.001). Moreover, the SEM-EDX analysis indicates the development of a considerable number of pore size ranging between 132 to 175 mm. From the experimental observations, it is evident that the ES can achieve high removal rate (>95%), indeed become a promising eco-friendly biosorptive material for MB dye removal.

Multiobjective Optimization of an Electroxidation Process of Biologically Pre-Treated Landifill Leachate by Response Surface Methodology and Desirability Function Approach

2012 ◽  
Vol 15 (2) ◽  
Author(s):  
G. Del Moro ◽  
E. Barca ◽  
C. Di Iaconi ◽  
F. Palmisano ◽  
G. Mascolo
Keyword(s):  
Response Surface Methodology ◽  
Energy Consumption ◽  
Response Surface ◽  
Desirability Function ◽  
Specific Energy Consumption ◽  
Coefficient Of Determination ◽  
Residual Chlorine ◽  
Leachate Treatment ◽  
Two Stages ◽  
Desirability Function Approach

AbstractThe optimization of the electrochemical step in a combined (biological and electro-oxidative) landfill leachate treatment was performed using a two stages approach, response surface methodology coupled with the desirability function. Four constraints were imposed, namely the discharge limit for COD (i.e. 160 mg / L), the maximization of color removal, the minimization of both residual chlorine and specific energy consumption. Each variable was modeled employing a second-order regression model. Analysis of variance (ANOVA) showed coefficient of determination (R

scholarly journals Determination of the Optimal Neural Network Transfer Function for Response Surface Methodology and Robust Design

2021 ◽  
Vol 11 (15) ◽  
pp. 6768
Author(s):  
Tuan-Ho Le ◽  
Hyeonae Jang ◽  
Sangmun Shin
Keyword(s):  
Response Surface Methodology ◽  
Transfer Function ◽  
Response Surface ◽  
Robust Design ◽  
Transfer Functions ◽  
Desirability Function ◽  
Likelihood Estimation ◽  
Statistical Simulation ◽  
Screening Procedure ◽  
Function Estimation

Response surface methodology (RSM) has been widely recognized as an essential estimation tool in many robust design studies investigating the second-order polynomial functional relationship between the responses of interest and their associated input variables. However, there is scope for improvement in the flexibility of estimation models and the accuracy of their results. Although many NN-based estimations and optimization approaches have been reported in the literature, a closed functional form is not readily available. To address this limitation, a maximum-likelihood estimation approach for an NN-based response function estimation (NRFE) is used to obtain the functional forms of the process mean and standard deviation. While the estimation results of most existing NN-based approaches depend primarily on their transfer functions, this approach often requires a screening procedure for various transfer functions. In this study, the proposed NRFE identifies a new screening procedure to obtain the best transfer function in an NN structure using a desirability function family while determining its associated weight parameters. A statistical simulation was performed to evaluate the efficiency of the proposed NRFE method. In this particular simulation, the proposed NRFE method provided significantly better results than conventional RSM. Finally, a numerical example is used for validating the proposed method.

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