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.

scholarly journals Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Jasir Jawad ◽  
Alaa H. Hawari ◽  
Syed Javaid Zaidi
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Forward Osmosis ◽  
Feed Solution ◽  
Operating Conditions ◽  
Ann Model ◽  
Membrane Flux ◽  
Input Variables ◽  
Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

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 Effect of Terminalia catappa Leaves Extract on Corrosion of Mild Steel using Response Surface Methodology

2020 ◽  
Vol 27 (2) ◽  
pp. 47-56
Author(s):  
A.O. Okewale ◽  
O.A. Adesina ◽  
B.H. Akpeji
Keyword(s):  
Response Surface Methodology ◽  
Mild Steel ◽  
Response Surface ◽  
Inhibition Efficiency ◽  
Desirability Function ◽  
Inhibitory Effect ◽  
Quadratic Model ◽  
Box Behnken Design ◽  
Terminalia Catappa ◽  
Maximum Inhibition

Effect of Terminalia catappa leaves (TCL) extract in inhibiting corrosion of mild steel was investigated. In order to obtain the maximum inhibition efficiency, optimization of the process variables affecting corrosion of mild steel was carried out using the Box – Behnken Design plan and desirability function of Response Surface Methodology (RSM). The three parameters - varied include; TCL concentration (inhibitor), immersion time, and temperature and there effects in corrosion inhibition were established. The optimum conditions predicted from the quadratic model were inhibitor’s concentratrion (0.39 g/l), exposure time (8.68 hours), and temperature (36.06 oC) with the inhibition efficiency of 91.95 %. The data fitted well to the quadratic model which was validated. Adsorption of the extract’s component on the mild steel was responsible for the inhibitory effect of the TCL extract.The results showed that 97.92% of the total variation in the inhibition efficiency of TCL can be connected to the variables studied. Keywords: Mild steel, acid, Terminalia catappa, Corrosion, Response surface methodology (RSM).

Study of the Parameters in Electro-Discharge Diamond Face Grinding through Response Surface Methodology Approach

2011 ◽  
Vol 110-116 ◽  
pp. 847-855
Author(s):  
Gyanendra Kumar Singh ◽  
Vinod Yadava ◽  
Raghuvir Kumar
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Removal Rate ◽  
Experimental Models ◽  
Duty Factor ◽  
Predicted Values ◽  
Rsm Model ◽  
Pulse On Time ◽  
Face Grinding

The present study investigates the relationship of process parameters in electro-discharge diamond face grinding (EDDFG) of tungsten carbide and cobalt composite (WC-Co). The central composite rotatable design had been utilized to plan the experiments and response surface methodology (RSM) was employed for developing experimental models. Analysis on machining characteristics of EDDFG was made based on the developed models. In this study, wheel RPM, current, pulse on-time, and duty factor are considered as input process parameters. The process performances such as material removal rate (MRR) and average surface roughness (Ra) were evaluated. Analysis of variance test had also been carried out to check the adequacy of the developed regression models. The observed optimal process parameter settings are wheel RPM of 1500, current of 6.9029 A, pulse on-time of 137. 8208 µs, and duty factor of 0.79 for achieving maximum MRR and minimum Ra; finally, the results were experimentally verified. A good agreement is observed between the results based on the RSM model and the actual experimental observations. The error between experimental and predicted values at the optimal combination of parameter settings for MRR and Ra lie within 6.18% and 12.33%, respectively.

scholarly journals The Influence of Pluronic F-127 Modification on Nano Zero-Valent Iron (NZVI): Sedimentation and Reactivity with 2,4-Dichlorophenol in Water Using Response Surface Methodology

Catalysts ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 412 ◽  
Author(s):  
Yajun Li ◽  
Yongxiang Zhang ◽  
Qi Jing ◽  
Yuhui Lin
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Colloidal Stability ◽  
Removal Rate ◽  
Zero Valent Iron ◽  
Quadratic Model ◽  
Biphasic Model ◽  
Sedimentation Behavior ◽  
Nano Zero Valent Iron ◽  
The Stability

Nano zero-valent iron (NZVI) is widely used for reducing chlorinated organic pollutants in water. However, the stability of the particles will affect the removal rate of the contaminant. In order to enhance the stability of nano zero-valent iron (NZVI), the particles were modified with F-127 as an environmentally friendly organic stabilizer. The study investigated the effect of the F-127 mass ratio on the colloidal stability of NZVI. Results show that the sedimentation behavior of F-NZVI varied at different mass ratios. A biphasic model was used to describe the two time-dependent settling processes (rapid sedimentation followed by slower settling), and the settling rates were calculated. The surface morphology of the synthesized F-NZVI was observed with a scanning electron microscope (SEM), and the functional groups of the samples were analyzed with Fourier Transform Infrared Spectroscopy (FTIR). Results show that the F-127 was successfully coated on the surface of the NZVI, and that significantly improved the stability of NZVI. Finally, in order to optimize the removal rate of 2,4-dichlorophenol (2,4-DCP) by F-NZVI, three variables were tested: the initial concentration 2,4-DCP, the pH, and the F-NZVI dosage. These were evaluated with a Box-Behnken Design (BBD) of response surface methodology (RSM). The experiments were designed by Design Expert software, and the regression model of fitting quadratic model was established. The following optimum removal conditions were determined: pH = 5, 3.5 g·L−1 F-NZVI for 22.5 mg·L−1 of 2,4-DCP.

Optimization of process parameters in magnetic field assisted powder mixed EDM of aluminium 6061 alloy

2020 ◽  
pp. 095440622095910
Author(s):  
Arun Kumar Rouniyar ◽  
Pragya Shandilya
Keyword(s):  
Magnetic Field ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Discharge Current ◽  
Electrical Discharge Machining ◽  
Desirability Function ◽  
Fine Powder ◽  
Quadratic Model ◽  
Electrode Wear

Magnetic field assisted powder mixed electrical discharge machining (MFAPM-EDM) is a variant of EDM process where magnetic field coupled with electric field is used with addition of fine powder in dielectric to improve the surface quality, machining rate and stability of the process. Aluminium 6061 alloy as workpiece was selected due to growing use in aviation, automotive, naval industries. In this present work, parametric study and optimization was carried out on MFAPM-EDM machined Aluminium 6061 alloy. In this study, process parameters such as discharge current (IP), spark duration (PON), pause duration (POFF), concentration of powder (CP) and magnetic field (MF) were considered to analyze the effect on material erosion rate (MER) and electrode wear rate (EWR). Box Behnken design approach based on response surface methodology (RSM) was utilized for performing the experiments. Quadratic model to predict the MER and EWR were developed using response surface methodology. Discharge current has most significant effect of 50.176% and 36.36% on MER and EWR, respectively among all others process parameters. Teacher-learning-based optimization (TLBO) was employed for determining the optimal process parameters for maximum MER and minimal EWR. The results obtained with TLBO was compared with well-known optimization methods such as genetic algorithm (GA) and desirability function of RSM. Minimum EWR (0.1021 mm3/min) and maximum MER (30.4687 mm3/min) obtained using TLBO algorithm for optimized process parameters was found to better as compared to GA and desirability function.

scholarly journals Intensification of Azo Dye Removal Rate in the Presence of Immobilized Nanoparticles and Inorganic Anions under UV-C Irradiation: Optimization by Response Surface Methodology

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad A. Behnajady ◽  
Mahsa Hajiahmadi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Azo Dye ◽  
Dye Removal ◽  
Removal Rate ◽  
Organic Pollutant ◽  
Inorganic Anions ◽  
Coefficient Of Determination ◽  
Synergy Effect ◽  
Uv C

Wastewaters contain inorganic anions that affect the removal rate of organic pollutants. The present study aims to optimize the effects of inorganic anions such as , Cl−, , and on the removal rate of an organic pollutant in the presence of immobilized TiO2nanoparticles using response surface methodology (RSM). C.I. Acid Red 17 (AR17) was used as a model organic pollutant. Thirty experiments were required to study the effects of anions in various concentrations. The results indicate that the addition of and ions intensifies the removal rate of AR17. The results of the analysis of variance (ANOVA) showed a high coefficient of determination value ( and ). The results indicate that RSM is a suitable method for modeling and optimizing the process. The results prove that in the presence of and and ions especially in the combination situation the removal rate of AR17 is enhanced considerably. An important synergy effect was observed in the combination of and ions, so that AR17 removal percent under the optimized RSM conditions was considerably more than the sum of removal percent when these ions are used individually.

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.

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.

scholarly journals Biosorption Processof Synthetic Textile Waste-water using Bjerkandera Agustavia Response Surface Methodology (RSM)

2018 ◽  
Vol 68 ◽  
pp. 04020
Author(s):  
Ariani Dwi Astuti ◽  
Khalida Muda
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Textile Industry ◽  
Contact Time ◽  
Textile Wastewater ◽  
Quadratic Model ◽  
Biosorption Process ◽  
Physico Chemical ◽  
Inorganic Species ◽  
Effects Of Ph

Textile industry generates large quantities of wastewater. Discharging effluent of textile industry without treatment is led to the degradation of the quality of receiving water bodies.A high color, high BOD/COD and salt (Total Dissolved Solids, TDS) load are founded in the textile wastewater. Several alternative of methods,including physico-chemical methods such as filtration, carbon activated, coagulation and chemical flocculation have been used to treat textile industry wastewater. Although these methods are effective, but they are expensive and result concentrated sludge that creates a secondary disposal problem. The passive uptake of organic and inorganic species including metals and dyes from aqueous solutions by the use of non-growing/living microbial mass or their derivatives is namely biosorption.The effects of pH, weight of biosorbent, contact time and size of biosorbent in biosorption process using Bjerkandera adusta in synthetic textile wastewater were investigated and optimized using response surface methodology (RSM). The optimum removal conditions were determined at pH 4, contact time 90 minutes, weight of biosorbent 3000 mg/L, and size of biosorbent 0.4 mm. Color removal of 53.55% was demonstrated, the experimental data and model predictions agreed well. In the optimization, R2 and 2correlation coefficients for the quadratic model was estimated quite satisfactorily as 0.988 and 0.977, respectively.

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