Mullite ceramic membranes for industrial oily wastewater treatment: experimental and neural network modeling

In this paper, results of an experimental and modeling of separation of oil from industrial oily wastewaters (desalter unit effluent of Seraje, Ghom gas wells, Iran) with mullite ceramic membranes are presented. Mullite microfiltration symmetric membranes were synthesized from kaolin clay and α-alumina powder. The results show that the mullite ceramic membrane has a high total organic carbon and chemical oxygen demand rejection (94 and 89%, respectively), a low fouling resistance (30%) and a high final permeation flux (75 L/m2 h). Also, an artificial neural network, a predictive tool for tracking the inputs and outputs of a non-linear problem, is used to model the permeation flux decline during microfiltration of oily wastewater. The aim was to predict the permeation flux as a function of feed temperature, trans-membrane pressure, cross-flow velocity, oil concentration and filtration time, using a feed-forward neural network. Finally the structure of hidden layers and nodes in each layer with minimum error were reported leading to a 4–15 structure which demonstrated good agreement with the experimental measurements with an average error of less than 2%.

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Neural network modeling for separation of bentonite in tubular ceramic membranes

Desalination ◽

10.1016/j.desal.2007.10.006 ◽

2008 ◽

Vol 228 (1-3) ◽

pp. 175-182 ◽

Cited By ~ 21

Author(s):

Nidal Hilal ◽

Oluwaseun O. Ogunbiyi ◽

Mohammed Al-Abri

Keyword(s):

Neural Network ◽

Network Modeling ◽

Ceramic Membranes ◽

Neural Network Modeling

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Separation Performance of Nanostructured Ceramic Membranes: Analytical Model Development

Journal of Non-Equilibrium Thermodynamics ◽

10.1515/jnet-2018-0013 ◽

2018 ◽

Vol 43 (3) ◽

pp. 245-253 ◽

Cited By ~ 1

Author(s):

Mashallah Rezakazemi ◽

Saeed Shirazian

Keyword(s):

Analytical Model ◽

Ceramic Membrane ◽

Porous Ceramic ◽

Model Development ◽

Ceramic Membranes ◽

Hydrogen Gas ◽

Separation Performance ◽

Diffusivity Coefficient ◽

Predictive Tool ◽

Nanostructured Ceramic

AbstractNanostructured ceramic membranes have shown considerable separation performance. In this work, an analytical model is developed to evaluate the separation performance of porous ceramic membranes in gas separation applications. The model takes into account three layers, i. e., (1) active layer, (2) interlayer, and (3) support layer. For estimation of sorption at the interface of feed stream and membrane, the partition coefficient model was used and the unsteady-state conservation of mass equation coupled to molecular models of the diffusivity coefficient was used to predict the permeation of penetrant hydrogen gas through a ceramic membrane. It was observed that the model can be readily applied to other systems of interest as a predictive tool.

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Treatment of oily wastewater using low cost ceramic membrane: Comparative assessment of pore blocking and artificial neural network models

Chemical Engineering Research and Design ◽

10.1016/j.cherd.2009.12.005 ◽

2010 ◽

Vol 88 (7) ◽

pp. 881-892 ◽

Cited By ~ 89

Author(s):

B.K. Nandi ◽

A. Moparthi ◽

R. Uppaluri ◽

M.K. Purkait

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Ceramic Membrane ◽

Low Cost ◽

Network Models ◽

Comparative Assessment ◽

Oily Wastewater ◽

Neural Network Models ◽

Pore Blocking ◽

Artificial Neural Network Models

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Oily wastewater treatment using mullite ceramic membrane

Desalination and Water Treatment ◽

10.1080/19443994.2012.661249 ◽

2012 ◽

Vol 37 (1-3) ◽

pp. 21-30 ◽

Cited By ~ 31

Author(s):

Mohsen Abbasi ◽

Abdolhamid Salahi ◽

Mojtaba Mirfendereski ◽

Toraj Mohammadi ◽

Fatemeh Rekabdar ◽

...

Keyword(s):

Wastewater Treatment ◽

Ceramic Membrane ◽

Oily Wastewater ◽

Mullite Ceramic ◽

Oily Wastewater Treatment

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Dimensional analysis of permeation flux for microfiltration of oily wastewaters using mullite ceramic membranes

Desalination ◽

10.1016/j.desal.2009.10.015 ◽

2010 ◽

Vol 252 (1-3) ◽

pp. 113-119 ◽

Cited By ~ 59

Author(s):

Mohsen Abbasi ◽

Abdolhamid Salahi ◽

Mojtaba Mirfendereski ◽

Toraj Mohammadi ◽

Afshin Pak

Keyword(s):

Dimensional Analysis ◽

Ceramic Membranes ◽

Permeation Flux ◽

Mullite Ceramic

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State-of-the-Art Ceramic Membranes for Oily Wastewater Treatment: Modification and Application

Membranes ◽

10.3390/membranes11110888 ◽

2021 ◽

Vol 11 (11) ◽

pp. 888

Author(s):

Mingliang Chen ◽

Sebastiaan G. J. Heijman ◽

Luuk C. Rietveld

Keyword(s):

Wastewater Treatment ◽

Membrane Fouling ◽

Membrane Filtration ◽

Ceramic Membrane ◽

Sol Gel ◽

Ceramic Membranes ◽

Oily Wastewater ◽

Membrane Modification ◽

Flux Enhancement ◽

Oily Wastewater Treatment

Membrane filtration is considered to be one of the most promising methods for oily wastewater treatment. Because of their hydrophilic surface, ceramic membranes show less fouling compared with their polymeric counterparts. Membrane fouling, however, is an inevitable phenomenon in the filtration process, leading to higher energy consumption and a shorter lifetime of the membrane. It is therefore important to improve the fouling resistance of the ceramic membranes in oily wastewater treatment. In this review, we first focus on the various methods used for ceramic membrane modification, aiming for application in oily wastewater. Then, the performance of the modified ceramic membranes is discussed and compared. We found that, besides the traditional sol-gel and dip-coating methods, atomic layer deposition is promising for ceramic membrane modification in terms of the control of layer thickness, and pore size tuning. Enhanced surface hydrophilicity and surface charge are two of the most used strategies to improve the performance of ceramic membranes for oily wastewater treatment. Nano-sized metal oxides such as TiO2, ZrO2 and Fe2O3 and graphene oxide are considered to be the potential candidates for ceramic membrane modification for flux enhancement and fouling alleviation. The passive antifouling ceramic membranes, e.g., photocatalytic and electrified ceramic membranes, have shown some potential in fouling control, oil rejection and flux enhancement, but have their limitations.

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A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

Matériaux & Techniques ◽

10.1051/mattech/2019002 ◽

2018 ◽

Vol 106 (6) ◽

pp. 603 ◽

Cited By ~ 2

Author(s):

Bendaoud Mebarek ◽

Mourad Keddam

Keyword(s):

Neural Network ◽

Experimental Data ◽

Fuzzy Neural Network ◽

Treatment Time ◽

Calculation Model ◽

Average Error ◽

Network Approach ◽

Neural Network Approach ◽

Fuzzy Neural ◽

Kinetics Of

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.

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