scholarly journals Optimization the Process of Chemically Modified Carbon Nanofiber Coated Monolith via Response Surface Methodology for CO2 Capture

Materials ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1775 ◽  
Author(s):  
Mohamad Rasool Malekbala ◽  
Soroush Soltani ◽  
Suraya Abdul Rashid ◽  
Luqman Chuah Abdullah ◽  
Umer Rashid ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Reaction Temperature ◽  
Flow Rate ◽  
Co2 Capture ◽  
Carbon Nanofiber ◽  
Co2 Adsorption ◽  
Operating Conditions ◽  
Co2 Uptake ◽  
Operating Pressure

In the present study, a sequence of experiments was performed to assess the influence of the key process parameters on the formation of a carbon nanofiber-coated monolith (CNFCM), using a four-level factorial design in response surface methodology (RSM). The effect of reaction temperature, hydrocarbon flow rate, catalyst and catalyst promoter were examined using RSM to enhance the formation yield of CNFs on a monolith substrate. To calculate carbon yield, a quadratic polynomial model was modified through multiple regression analysis and the best possible reaction conditions were found as follows: a reaction temperature of 800 °C, furfuryl alcohol flow of 0.08525 mL/min, ferrocene catalyst concentration of 2.21 g. According to the characterization study, the synthesized CNFs showed a high graphitization which were uniformly distributed on a monolith substrate. Besides this, the feasibility of carbon dioxide (CO2) adsorption from the gaseous mixture (N2/CO2) under a range of experimental conditions was investigated at monolithic column. To get the most out of the CO2 capture, an as-prepared sample was post-modified using ammonia. Furthermore, a deactivation model (DM) was introduced for the purpose of studying the breakthrough curves. The CO2 adsorption onto CNFCM was experimentally examined under following operating conditions: a temperature of 30–50 °C, pressure of 1–2 bar, flow rate of 50–90 mL/min, and CO2 feed amount of 10–40 vol.%. A lower adsorption capacity and shorter breakthrough time were detected by escalating the temperature. On the other hand, the capacity for CO2 adsorption increased by raising the CO2 feed amount, feed flow rate, and operating pressure. The comparative evaluation of CO2 uptake over unmodified and modified CNFCM adsorbents confirmed that the introduced modification procedure caused a substantial improvement in CO2 adsorption.

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 Optimization of Ostrich Eggshell Catalyst in Transesterification Using Waste Cooking Oil via Response Surface Methodology

2018 ◽  
Vol 5 (2) ◽  
pp. 277-285 ◽  
Author(s):  
Yie Hua Yie Tan ◽  
Mohammad Omar Abdullah ◽  
Jibrail Kansedo ◽  
Agus Saptoro ◽  
Cirilo Nolasco Hipolito
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Reaction Temperature ◽  
Catalyst Concentration ◽  
Waste Cooking Oil ◽  
Operating Conditions ◽  
Transesterification Reaction ◽  
Biodiesel Production ◽  
Cooking Oil ◽  
Ostrich Eggshell

In this research work, waste cooking oil biodiesel production was optimized using a design of experiment (DOE) approach: response surface methodology (RSM), based on a five level, three variables central composite design (CCD) to investigate the interaction effects of the different combination of transesterification reaction variables such as catalyst concentration, reaction temperature and time, using ostrich eggshell CaO base catalyst. A quadratic polynomial equation of the response, biodiesel yield was attained via multiple regression analysis to predict the relation between yield and the chosen variables. The results showed that the temperature and time are the most important process parameters on the biodiesel production. The optimal operating conditions for the transesterification reaction have been found to be: reaction temperature of 67 °C, alcohol/oil molar ratio of 10:1 (fixed parameter), catalyst concentration of 1.97 % w/w and reaction time of 1.77 h. The predicted biodiesel yield was about 99.67% under the optimal conditions through the ANOVA numerical method.

scholarly journals Natural organic matter and sulphate elimination from rainwater with nanofiltration technology and process optimisation using response surface methodology

2020 ◽  
Author(s):  
Börte Köse-Mutlu
Keyword(s):  
Response Surface Methodology ◽  
Organic Matter ◽  
Response Surface ◽  
Natural Organic Matter ◽  
Applied Pressure ◽  
Operating Conditions ◽  
Model Parameters ◽  
Operating Pressure ◽  
Nanofiltration Membranes ◽  
Drinking Water Production

Abstract In the current study, the effect of operating conditions including membrane characteristics and applied pressure on natural organic matter and sulphate removal of nanofiltration membranes for drinking water production was investigated. Water stress has been increasing all over the world due to population growth, climate change, and pollution; rainwater management stands out as one of the key solutions to this problem. Nanofiltration to treat rainwater stored in a cistern was studied. The objectives were sufficient treatment performance to overcome the taste problem and lower energy consumption. In this regard, three commercial nanofiltration membranes (NP010, NP030, and NF90) were used for the experiments carried out at 6–12 bar operating pressure regarding the response surface methodology. The correlation among the results of experiments and the model parameters were also calculated for all steps. According to the results, the effect of membrane characteristics was more abundant than the effect of the operating pressure. Finally, over 99% of natural organic matter and sulphate were eliminated in the optimum conditions. The results showed that it is possible to obtain treated rainwater with desired qualities, in a non-continuous NF plant operated at the pressure of 6 bar to reuse the rainwater and achieve water sustainability.

scholarly journals Prediction of maximum permeate flux (%) of disc membrane using response surface methodology (RSM)

2019 ◽  
Vol 46 (4) ◽  
pp. 299-307 ◽  
Author(s):  
Anirban Banik ◽  
Suman Dutta ◽  
Tarun Kanti Bandyopadhyay ◽  
Sushant Kumar Biswal
Keyword(s):  
Response Surface Methodology ◽  
Pore Size ◽  
Response Surface ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Operating Pressure ◽  
Permeate Flux ◽  
Feed Velocity ◽  
Disc Membrane ◽  
Influencing Parameters

The paper investigates increasing permeate flux (%) of the disc membrane which can improve the quality of rubber industrial effluent of Tripura. Response surface methodology was used to optimize the independent influencing parameters to improve the permeate flux. The effect of different influencing parameters like operating pressure, membrane pore size, and inlet feed velocity on membrane permeate flux were studied to determine the optimum operating conditions within the predefined boundary. The experiments were pre-planned and designed according to central composite rotatable design, and second-order polynomial regression model was developed for regression and analysis of variance study. Results show the membrane has maximum permeate flux (%) when the operating pressure is 14.50 Pa, pore size is 0.20 μm, and inlet feed velocity is 2.10 m/s. The Pareto analysis in the study established that the inlet velocity was the most influential parameter in the model equation.

scholarly journals Optimasi Adsorpsi Ion Mg2+ pada Fixed Bed Column dengan Menggunakan Response Surface Methodology

REAKTOR ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 126
Author(s):  
Novi Sylvia ◽  
Meriatna Meriatna ◽  
Fikri Hasfita ◽  
Lukman Hakim
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Adsorption Process ◽  
Fixed Bed ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Process Variables ◽  
Fixed Bed Column ◽  
Box Behnken Design

Abstract OPTIMIZATION ADSORPTION OF Mg2+ ION ON FIXED BED COLUMN USING RESPONSE SURFACE METHODOLOGY. Modeling of the adsorption process is used to establish the mathematical relationship between the interacting process variables and process optimization. This is important to determine the factor values that produce a maximum response. Adsorption of Mg from groundwater was optimized using response surface methodology based on Box-Behnken design was used to analyze adsorption data. The process was investigated by continuous experiments. Variables included in the process were: bed depths (7.5, 10, and 12.5 cm), time (20, 40, and 60 min), and flow rate (6, 10, and 14 L/min). Regression analysis was used to analyze the developed models. The outcome of this research showed that 72.784% of the variability in removal efficiency is attributed to the three process variables considered, that is, bed depths, time, and flow rate. Optimization tests showed that the optimum operating conditions for the adsorption process occurred at a bed depth of 11.37 cm, time of 55.53 min and flow rate of 6 L/min. Keywords: adsorption; Box-Behnken design; magnesium (Mg2+); optimization  AbstrakPemodelan dari proses adsorpsi digunakan untuk menentukan hubungan matematis antara variabel proses interaksi dan proses optimasi. Hal ini penting untuk menentukan nilai faktor yang menghasilkan respon maksimum. Adsorpsi magnesium (Mg2+) dari air tanah dioptimalkan menggunakan metodologi respon permukaan model Desain Box-Behnken yang digunakan untuk menganalisis data adsorpsi. Percobaan dilakukan secara kontinyu. Variabel yang termasuk dalam proses tersebut adalah: tinggi unggun (7,5, 10 dan 12,5 cm), waktu kontak (20, 40, dan 60 menit), dan laju alir (6, 10, dan 14 L/menit). Analisis regresi digunakan untuk menganalisis model yang dikembangkan. Hasil penelitian menunjukkan bahwa 72,784% efisiensi penyisihan Mg2+ ditentukan oleh tiga variabel proses, yaitu tinggi unggun, waktu kontak, dan laju alir. Hasil optimasi menunjukkan bahwa kondisi operasi optimum untuk proses adsorpsi terjadi pada tinggi unggun 11,37 cm, waktu kontak 55,53 menit dan laju alir 6 L/menit. Kata kunci: adsorpsi; Box-Behnken desain; magnesium (Mg2+); optimasi

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.

Optimization of Magnesium Separation and Extraction from Boron Slurry Using Response Surface Methodology

2011 ◽  
Vol 366 ◽  
pp. 366-369
Author(s):  
Feng Gao ◽  
Rong Fu ◽  
Ming Yang Qian ◽  
Zhu Min Wang ◽  
Xiang Zhang
Keyword(s):  
Response Surface Methodology ◽  
Reaction Time ◽  
Factorial Design ◽  
Response Surface ◽  
Reaction Temperature ◽  
Fractional Factorial Design ◽  
Design Criterion ◽  
Fractional Factorial ◽  
Effective Factors

Response surface methodology was used to optimize the soaking Mg leaching ratio from the boron slurry screened by 25 fractional factorial design. Five effective factors such as H2SO4 concentrations, reaction time, reaction temperature and stir velocity were tested by using 25 fractional factorial design criterion and three effective factors H2SO4 concentrations, reaction time and reaction temperature showed significant effect(P2SO4 concentrations of 0.29mol/l, reaction time of 90 min and reaction temperature of 50°C. Three runs of additional confirmation experiments were conducted. The mixture magnesium leaching value was 58.20%.

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.

Sign in / Sign up

Export Citation Format

Share Document