scholarly journals Effective Chromium Adsorption From Aqueous Solutions and Tannery Wastewater Using Bimetallic Fe/Cu Nanoparticles: Response Surface Methodology and Artificial Neural Network

2021 ◽  
Vol 14 ◽  
pp. 117862212110281
Author(s):  
Ahmed S. Mahmoud ◽  
Nouran Y. Mohamed ◽  
Mohamed K. Mostafa ◽  
Mohamed S. Mahmoud
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Industrial Effluent ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Tannery Wastewater ◽  
P Value ◽  
Cu Nanoparticles ◽  
Artificial Neural ◽  
Cr Removal

Tannery industrial effluent is one of the most difficult wastewater types since it contains a huge concentration of organic, oil, and chrome (Cr). This study successfully prepared and applied bimetallic Fe/Cu nanoparticles (Fe/Cu NPs) for chrome removal. In the beginning, the Fe/Cu NPs was equilibrated by pure aqueous chrome solution at different operating conditions (lab scale), then the nanomaterial was applied in semi full scale. The operating conditions indicated that Fe/Cu NPs was able to adsorb 68% and 33% of Cr for initial concentrations of 1 and 9 mg/L, respectively. The removal occurred at pH 3 using 0.6 g/L Fe/Cu dose, stirring rate 200 r/min, contact time 20 min, and constant temperature 20 ± 2ºC. Adsorption isotherm proved that the Khan model is the most appropriate model for Cr removal using Fe/Cu NPs with the minimum error sum of 0.199. According to khan, the maximum uptakes was 20.5 mg/g Cr. Kinetic results proved that Pseudo Second Order mechanism with the least possible error of 0.098 indicated that the adsorption mechanism is chemisorption. Response surface methodology (RSM) equation was developed with a significant p-value = 0 to label the relations between Cr removal and different experimental parameters. Artificial neural networks (ANNs) were performed with a structure of 5-4-1 and the achieved results indicated that the effect of the dose is the most dominated variable for Cr removal. Application of Fe/Cu NPs in real tannery wastewater showed its ability to degrade and disinfect organic and biological contaminants in addition to chrome adsorption. The reduction in chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), Cr, hydrogen sulfide (H2S), and oil reached 61.5%, 49.5%, 44.8%, 100%, 38.9%, 96.3%, 88.7%, and 29.4%, respectively.

scholarly journals Taguchi Method and Response Surface Methodology in the Treatment of Highly Contaminated Tannery Wastewater Using Commercial Potassium Ferrate

Materials ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 3784 ◽  
Author(s):  
Violetta Kozik ◽  
Krzysztof Barbusinski ◽  
Maciej Thomas ◽  
Agnieszka Sroda ◽  
Josef Jampilek ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Organic Carbon ◽  
Taguchi Method ◽  
Chemical Oxygen Demand ◽  
Total Organic Carbon ◽  
Response Surface ◽  
Suspended Solids ◽  
Oxygen Demand ◽  
Tannery Wastewater ◽  
Potassium Ferrate

The potential implementation of Envifer®, a commercial product containing potassium ferrate (40.1% K2FeO4), for the purification of highly contaminated tannery wastewater from leather dyeing processes was proposed. The employment of the Taguchi method for optimization of experiments allowed the discoloration (98.4%), chemical oxygen demand (77.2%), total organic carbon (75.7%), and suspended solids (96.9%) values to be lowered using 1.200 g/L K2FeO4 at pH 3 within 9 min. The application of the central composite design (CCD) and the response surface methodology (RSM) with the use of 1.400 g/L K2FeO4 at pH 4.5 diminished the discoloration, the chemical oxygen demand, the total organic carbon, and suspended solids within 9 min. The Taguchi method is suitable for the initial implementation, while the RSM is superior for the extended optimization of wastewater treatment processes.

scholarly journals Fixed bed utilization for the isolation of xylene vapor: Kinetics and optimization using response surface methodology and artificial neural network

2020 ◽  
Vol 26 (2) ◽  
pp. 200105-0
Author(s):  
Kaushal Naresh Gupta ◽  
Rahul Kumar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Operating Parameters ◽  
Bed Height ◽  
Artificial Neural

This paper discusses the isolation of xylene vapor through adsorption using granular activated carbon as an adsorbent. The operating parameters investigated were bed height, inlet xylene concentration and flow rate, their influence on the percentage utilization of the adsorbent bed up to the breakthrough was found out. Mathematical modeling of experimental data was then performed by employing a response surface methodology (RSM) technique to obtain a set of optimum operating conditions to achieve maximum percentage utilization of bed till breakthrough. A fairly high value of R2 (0.993) asserted the proposed polynomial equation’s validity. ANOVA results indicated the model to be highly significant with respect to operating parameters studied. A maximum of 76.1% utilization of adsorbent bed was found out at a bed height of 0.025 m, inlet xylene concentration of 6,200 ppm and a gas flow rate of 25 mL.min-1. Furthermore, the artificial neural network (ANN) was also employed to compute the percentage utilization of the adsorbent bed. A comparison between RSM and ANN divulged the performance of the latter (R2 = 0.99907) to be slightly better. Out of various kinetic models studied, the Yoon-Nelson model established its appropriateness in anticipating the breakthrough curves.

scholarly journals Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models

2021 ◽  
Vol 83 (5) ◽  
pp. 1250-1264
Author(s):  
B. L. Dinesha ◽  
Sharanagouda Hiregoudar ◽  
Udaykumar Nidoni ◽  
K. T. Ramappa ◽  
Anilkumar Dandekar ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Wastewater Treatment ◽  
Response Surface ◽  
Dairy Industry ◽  
Oxygen Demand ◽  
Ann Models ◽  
Artificial Neural ◽  
Industry Wastewater

Abstract The present investigation was focused to compare chitosan based nano-adsorbents (CZnO and CTiO2) for efficient treatment of dairy industry wastewater using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models. The nano-adsorbents were synthesized using chemical precipitation method and characterized by using scanning electron microscope with elemental detection sensor (SEM-EDS) and atomic force microscope (AFM). Maximum %RBOD (96.71 and 87.56%) and %RCOD (90.48 and 82.10%) for CZnO and CTiO2 nano-adsorbents were obtained at adsorbent dosage of 1.25 mg/L, initial biological oxygen demand (BOD) and chemical oxygen demand (COD) concentration of 100 and 200 mg/L, pH of 7.0 and 2.00, contact time of 100 and 60 min, respectively. The results obtained for both the nano-adsorbents were subject to RSM and ANN models for determination of goodness of fit in terms of sum of square errors (SSE), root mean square error (RMSE), R2 and Adj. R2, respectively. The well trained ANN model was found superior over RSM in prediction of the treatment effect. Hence, the developed CZnO and CTiO2 nano-adsorbents could be effectively used for dairy industry wastewater treatment.

Optimization of photo-Fenton process of RO concentrated coking wastewater using response surface methodology

2012 ◽  
Vol 66 (4) ◽  
pp. 816-823 ◽  
Author(s):  
Zhang Huiqing ◽  
Ye Chunsong ◽  
Zhang Xian ◽  
Yang Fan ◽  
Yang Jun ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ph Value ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Quadratic Model ◽  
Coking Wastewater ◽  
Fenton Process ◽  
Predicted Values ◽  
Optimized Conditions

The objective of this study was aimed at investigating the removal of chemical oxygen demand (COD) from reverse osmosis (RO) concentrated coking wastewater by the photo-Fenton process. The optimum extraction conditions for the photo-Fenton process by Box–Behnken design (BBD) and response surface methodology (RSM) to establish a predictive polynomial quadratic model were discussed based on a single factor test. Optimized parameters validated by the analysis of variances (ANOVA) were found to be H2O2 concentration of 345.2 mg/L, pH value of 4.1 and reaction time of 103.5 minutes under ultraviolet irradiation. The experimental results of the COD removal under the optimized conditions presented better agreement with the predicted values with deviation error of 3.2%. The results confirmed that RSM based on BBD was a suitable method to optimize the operating conditions of RO concentrated coking wastewater.

scholarly journals Modelling of cutting forces and surface roughness evolutions during straight turning of Stellite 6 material based on response surface methodology, artificial neural networks and support vector machine approaches

2021 ◽  
Vol 15 (4) ◽  
pp. 8540-8554
Author(s):  
Brahim Ben Fathallah ◽  
R. Saidi ◽  
S. Belhadi ◽  
M.A. Yallese ◽  
T. Mabrouki
Keyword(s):  
Support Vector Machine ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface ◽  
Feed Rate ◽  
Research Work ◽  
Operating Conditions ◽  
Support Vector ◽  
Stellite 6 ◽  
Artificial Neural

The present research work proposes an experimental investigation helping to comprehend fundamental impacts of operating conditions during the cutting of cobalt alloys (Stellite 6). Thus, an experimental design was adopted to allow to build predicted mathematical models for the outputs, which are the average peak-to-valley profile roughness (Rz) and the tangential cutting force (Ft). Artificial neural network (ANN), support vector machine (SVM) and response surface methodology (RSM) were exploited to model the pre-cited outputs according to operation parameters. As a result, it has been highlighted that both feed rate and cutting depth, considerably, affect tangential cutting force evolution. Moreover, results show that both the insert feed rate and nose radius, are higher. This means the average peak-to-valley profile roughness is higher. In order to put out the effect of operating parameters on cutting outputs, Analysis of variance (ANOVA) method has been employed. This has allowed the detection of significant cutting conditions affecting average peak-to-valley profile roughness and tangential cutting force. In fact, to highlight the performance of adopted mathematical approaches, a comparison between RSM, ANN, and SVM has been also established in this study.

scholarly journals Optimization of Coagulation-flocculation Process for Pre-treatment of Artisanal Tannery Wastewater Using Response Surface Methodology

2021 ◽  
Author(s):  
Miriam Appiah-Brempong ◽  
Helen Michelle Korkor Essandoh ◽  
Nana Yaw Asiedu ◽  
Samuel Kwame Dadzie ◽  
Francis Yao Momade
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Oxygen Demand ◽  
Tannery Wastewater ◽  
Volume Index ◽  
Aluminium Sulphate ◽  
Plant Materials ◽  
Initial Ph ◽  
Pre Treatment ◽  
Flocculation Process

Abstract There is a dearth in knowledge on artisanal tannery wastewater treatment as most studies are focused on treatment of wastewater generated from modern-day leather manufacturing industries. The extensive use of plant materials in artisanal tanneries introduces high loads of polyphenolic compounds in the wastewater rendering biological treatment of the wastewater ineffective. This study, therefore, employed coagulation-flocculation process to pre-treat artisanal tannery wastewater with the aim of applying the central composite design, a statistical approach in Response Surface Methodology (RSM) to model and optimize the removal of Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and turbidity and to minimize Sludge Volume Index (SVI). Optimization process focused on the two most important influencing parameters: dosage of aluminium sulphate and initial pH of wastewater. Results revealed that optimal pH and aluminium sulphate dosage of 6.09 and 11.6g/L respectively could yield maximum removal efficiencies of 38.51% of COD, 76.05% of TSS and 79.64% of turbidity from the wastewater with a minimum SVI of 29.57mL/g. Further experiments conducted to validate these results showed a good agreement between the experimental and predicted results signifying the suitability of RSM for optimization of the coagulation treatment process. This is the first reported study on optimization of coagulation-flocculation treatment of artisanal tannery wastewater. Results of this study can be used practically for efficient pre-treatment of artisanal tannery wastewater.

scholarly journals RESPONSE SURFACE METHODOLOGY AND DESIRABILITY FUNCTION AS STATISTICAL TOOLS IN THE OPTIMIZATION OF ELECTROCOAGULATION PROCESS IN SURFACE WATER

2020 ◽  
Vol 6 (2) ◽  
pp. 0152-0163
Author(s):  
Efraim Lázaro Reis ◽  
Maria Paulina Mendonza Combatt ◽  
Karina Esther Vasquez Sanjuan ◽  
Antônio Augusto Neves ◽  
Regina Célia Santos Mendonça
Keyword(s):  
Response Surface Methodology ◽  
Surface Water ◽  
Response Surface ◽  
Desirability Function ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Safe Work ◽  
Apparent Color ◽  
Initial Ph ◽  
Electrocoagulation Process

The electrocoagulation for water clarification for purification have been studied as alternative to the processes of the water treatment. This study aimed to model and to optimize this process for types of water with different turbidity conditions; considering the current intensity, electrolysis time and initial pH on apparent color removal, chemical oxygen demand and surface water turbidity. Electrocoagulation tests were make aluminum electrodes. The optimal operating conditions and models based on the response surface methodology were obtained with central composite design. In order to comply with the esthetic / organoleptic standard stipulated for this stage of the process, the characterization of the three types of water studied must have color < 15 uH, COD < 18 mg L-1 O2 and turbidity < 5 NTU). The correlation between the analyzed answers allows finding specific conditions of the parameters, assisting in the determination of safe work points in the operation of clarification.

Employment of Quality by Design approach via Response Surface Methodology to Optimize and Develop Modified Release formulation of Hydrochlorothiazide

2020 ◽  
Vol 16 ◽  
Author(s):  
Vikas D Singhai ◽  
Rahul Maheshwari ◽  
Swapnil Sharma ◽  
Sarvesh Paliwal
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quality By Design ◽  
Management Tool ◽  
Contour Plot ◽  
P Value ◽  
Average Weight ◽  
Content Uniformity ◽  
Modified Release ◽  
Release Formulation

Background: Heart attack predominantly occurs during the last phase of sleep and early morning hours, causing millions of death worldwide. Hydrochlorothiazide (HCTZ) is recommended drug for the prevention of heart disease but its long action (>4 h) dosage form is lacking in the commercial market and development of extended-release formulation may have industrial significance. Regulatory agencies emphasize Quality by Design based approach for product development to entrust quality in the product. Objective: Aim of the current research was to develop a quality product profile of HCTZ modified-release tablets (MRT; ~14 h) by applying Response Surface Methodology using computational QbD approach. Methods: Three independent factors were identified by qualitative and quantitative risk assessment. Statistical terms like p-value, lack of fit, sum of square, R-squared value, model F value and linear equations were determined. Graphical tools like normal plot of residual, residual vs predicted plot and box cox plot were used to verify model selection. Graphical relationship among the critical, independent variables was represented using the Contour plot and 3-D surface plot. Design space was identified by designing overlay plot using response surface design. Results: Excellent correlation was observed between actual and predicted values. Similarity Factor (F2) of reproducible trials was 78 and 79 and content uniformity was 100.9% and 100.4%. Average weight, hardness, thickness, diameter and friability were within acceptable limits. Conclusions: QbD approach along with quality risk management tool provided an efficient and effective paradigm to build quality MRT of HCTZ.

scholarly journals A Response Surface Methodology (RSM) Approach for Optimizing the Attenuation of Human IgE-Reactivity to β-Lactoglobulin (β-Lg) by Hydrostatic High Pressure Processing

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1741
Author(s):  
Xin Sun ◽  
Jialing Vivien Chua ◽  
Quynh Anh Le ◽  
Francisco Trujillo ◽  
Mi-Hwa Oh ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Optimal Condition ◽  
Response Surface ◽  
High Pressure Processing ◽  
Molecular Structures ◽  
Holding Time ◽  
P Value ◽  
Molecular Change ◽  
Ige Reactivity ◽  
Β Lactoglobulin

The response surface methodology (RSM) and central composite design (CCD) technique were used to optimize the three key process parameters (i.e., pressure, temperature and holding time) of the high-hydrostatic-pressure (HHP) processing either standalone or combined with moderate thermal processing to modulate molecular structures of β-lactoglobulin (β-Lg) and α-lactalbumin (α-La) with reduced human IgE-reactivity. The RSM model derived for HHP-induced molecular changes of β-Lg determined immunochemically showed that temperature (temp), pressure (p2) and the interaction between temperature and time (t) had statistically significant effects (p < 0.05). The optimal condition defined as minimum (β-Lg specific) IgG-binding derived from the model was 505 MPa at 56 °C with a holding time of 102 min (R2 of 0.81 and p-value of 0.01). The validation carried at the optimal condition and its surrounding region showed that the model to be underestimating the β-Lg structure modification. The molecular change of β-Lg was directly correlated with HHP-induced dimerization in this study, which followed a quadratic equation. The β-Lg dimers also resulted in the undetectable human IgE-binding.

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