scholarly journals Optimization of a High-Performance Poly(diallyl dimethylammonium chloride)-alumina-perfluorooctanoate Intercalated Ultrafiltration Membrane for Treating Emulsified Oily Wastewater via Response Surface Methodology Approach

Membranes ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 956
Author(s):  
Yusuf Olabode Raji ◽  
Mohd Hafiz Dzarfan Othman ◽  
Nik Abdul Hadi Sapiaa Md Nordin ◽  
Mohd Ridhwan Adam ◽  
Khairul Anwar Mohamad Said ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ceramic Membrane ◽  
Separation Efficiency ◽  
Water Flux ◽  
Operating Conditions ◽  
Interactive Effects ◽  
Oily Wastewater ◽  
Feed Concentration ◽  
Cross Flow Filtration

This research aimed to investigate the ultrafiltration of water from emulsified oily wastewater through the application of surface-functionalized ceramic membrane to enhance its water permeability based on optimized parameters using a cross-flow filtration system. The interactive effects of feed concentration (10–1000 ppm), pH (4–10), and pressure (0–3 bar) on the water flux and oil rejection were investigated. Central composite design (CCD) from response surface methodology (RSM) was employed for statistical analysis, modeling, and optimization of operating conditions. The analysis of variance (ANOVA) results showed that the oil rejection and water flux models were significant with p-values of 0.0001 and 0.0075, respectively. In addition, good correlation coefficients of 0.997 and 0.863 were obtained for the oil rejection and water flux models, respectively. The optimum conditions for pressure, pH, and feed concentration were found to be 1.5 bar, pH 8.97, and 10 ppm, respectively with water flux and oil rejection maintained at 152 L/m2·h and 98.72%, respectively. Hence, the functionalized ultrafiltration ceramic membrane enables the separation efficiency of the emulsified oil in water to be achieved.

Demulsification of a Water-in-crude Oil Emulsion with a Corn Oil BasedDemulsifier using the Response Surface Methodology: Modelling and Optimization

2021 ◽  
Vol 14 ◽  
Author(s):  
Abed Saad ◽  
Nour Abdurahman ◽  
Rosli Mohd Yunus
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Water Content ◽  
Response Surface ◽  
Separation Efficiency ◽  
Corn Oil ◽  
Oil Emulsion ◽  
Optimal Values ◽  
Input Variables ◽  
Oil Emulsions

: In this study, the Sany-glass test was used to evaluate the performance of a new surfactant prepared from corn oil as a demulsifier for crude oil emulsions. Central composite design (CCD), based on the response surface methodology (RSM), was used to investigate the effect of four variables, including demulsifier dosage, water content, temperature, and pH, on the efficiency of water removal from the emulsion. As well, analysis of variance was applied to examine the precision of the CCD mathematical model. The results indicate that demulsifier dose and emulsion pH are two significant parameters determining demulsification. The maximum separation efficiency of 96% was attained at an alkaline pH and with 3500 ppm demulsifier. According to the RSM analysis, the optimal values for the input variables are 40% water content, 3500 ppm demulsifier, 60 °C, and pH 8.

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 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.

Fabrication, performance evaluation, and optimisation of adsorptive ammonia removal using hollow fibre ceramic membrane: Response surface methodology approach

2021 ◽  
Vol 316 ◽  
pp. 110932
Author(s):  
Mohd Ridhwan Adam ◽  
Mohd Hafiz Dzarfan Othman ◽  
Siti Hamimah Sheikh Abdul Kadir ◽  
Mohd Hafiz Puteh ◽  
Mohd Riduan Jamalludin ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Performance Evaluation ◽  
Response Surface ◽  
Ceramic Membrane ◽  
Hollow Fibre ◽  
Ammonia Removal

Optimization of biodiesel synthesis under simultaneous ultrasound-microwave irradiation using response surface methodology (RSM)

2015 ◽  
Vol 4 (4) ◽  
Author(s):  
Seyed Mohammad Safieddin Ardebili ◽  
Teymor Tavakoli Hashjin ◽  
Barat Ghobadian ◽  
Gholamhasan Najafi ◽  
Stefano Mantegna ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Microwave Irradiation ◽  
Response Surface ◽  
Palm Oil ◽  
Catalyst Concentration ◽  
Irradiation Time ◽  
Operating Conditions ◽  
Molar Ratio ◽  
Reaction Conditions ◽  
Biodiesel Synthesis

AbstractThis work investigates the effect of simultaneous ultrasound-microwave irradiation on palm oil transesterification and uncovers optimal operating conditions. Response surface methodology (RSM) has been used to analyze the influence of reaction conditions, including methanol/palm oil molar ratio, catalyst concentration, reaction temperature and irradiation time on biodiesel yield. RSM analyses indicate 136 s and 129 s as the optimal sonication and microwave irradiation times, respectively. Optimized parameters for full conversion (97.53%) are 1.09% catalyst concentration and a 7:3.1 methanol/oil molar ratio at 58.4°C. Simultaneous ultrasound-microwave irradiation dramatically accelerates the palm oil transesterification reaction. Pure biodiesel was obtained after only 2.2 min while the conventional method requires about 1 h.

scholarly journals Development, Characterization, and Optimization of Protein Level in Date Bars Using Response Surface Methodology

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Nadeem ◽  
Salim-ur-Rehman ◽  
Faqir Muhammad Anjum ◽  
Mian Anjum Murtaza ◽  
Ghulam Mueen-ud-Din
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Whey Protein ◽  
Protein Level ◽  
Protein Supplementation ◽  
Interactive Effects ◽  
Whey Protein Concentrate ◽  
Protein Concentrate ◽  
Protein Isolates ◽  
Nutritional Profile

This project was designed to produce a nourishing date bar with commercial value especially for school going children to meet their body development requirements. Protein level of date bars was optimized using response surface methodology (RSM). Economical and underutilized sources, that is, whey protein concentrate and vetch protein isolates, were explored for protein supplementation. Fourteen date bar treatments were produced using a central composite design (CCD) with 2 variables and 3 levels for each variable. Date bars were then analyzed for nutritional profile. Proximate composition revealed that addition of whey protein concentrate and vetch protein isolates improved the nutritional profile of date bars. Protein level, texture, and taste were considerably improved by incorporating 6.05% whey protein concentrate and 4.35% vetch protein isolates in date bar without affecting any sensory characteristics during storage. Response surface methodology was observed as an economical and effective tool to optimize the ingredient level and to discriminate the interactive effects of independent variables.

scholarly journals Investigation of soil properties influence on the heavy metals sorption by plants and possibilities for prediction of their bioaccumulation by response surface methodology

2016 ◽  
Vol 81 (8) ◽  
pp. 947-958 ◽  
Author(s):  
Zlate Velickovic ◽  
Negovan Ivankovic ◽  
Vanja Strikovic ◽  
Radovan Karkalic ◽  
Dalibor Jovanovic ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Response Surface Methodology ◽  
Soil Properties ◽  
Response Surface ◽  
Interactive Effects ◽  
Npk Fertilizers ◽  
Limit Value ◽  
Safety Regulations ◽  
Icp Ms ◽  
The Individual

The aim of this study was to determine soil properties influence on the heavy metals sorption by vegetables which are used in the diet and possibilities for prediction of their bioaccumulation by response surface methodology (RSM). Lettuce was used as biosorbent, and cadmium (Cd) and lead (Pb) were used as contaminants. Lettuce is grown on compost (previously contaminated with different concentrations of Cd and Pb) which pH was adjusted with different amounts of NPK fertilizers. The content of heavy metals was determined by ICP-MS. Results showed that Cd content in lettuce was below the toxic values, but Pb concentration was above allowable, which indicates that limit value for Pb is not set in accordance with the food safety regulations. It was found that the heavy metals accumulation in plants depends not only on its content in the soil, but also on the plant affinity to the specific metal, and the individual or the interactive effects of different soil properties. Through the transfer factor it was found that lettuce has a much higher affinity to Cd in relation to Pb. RSM has proved to be very good for the examination of a large number of variables with a small number of experiments.

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