Ceramic membrane performance in microfiltration of oily wastewater

Membrane separation technique has a beneficial effect when applied to remove dispersed oil,emulsified oil and dissolved oil,the removal rate is more than 95%,meanwhile there is no secondary pollution, and separation process is without phase transformation, at the same time the membrane module structure is simple,and it has a short process,meanwhile the equipment also consumes low energy[1]. We use flat ceramic membrane filtering device adding coagulant to dispose oily wastewater.To choosing coagulant,we do an experiment in motionless beaker with FeCl3,PAC,PAM and two combinations of them to investigate the effect of oily wastewater treatment.Meanwhile,to provide a scientific basis for oily wastewater,we perform univariate analysis on optimal pharmacy to gain the most suitable technological parameters of oily wastewater treatment.

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

Water Science & Technology ◽

10.2166/wst.2011.655 ◽

2011 ◽

Vol 64 (3) ◽

pp. 670-676 ◽

Cited By ~ 7

Author(s):

H. Shokrkar ◽

A. Salahi ◽

N. Kasiri ◽

T. Mohammadi

Keyword(s):

Neural Network ◽

Ceramic Membrane ◽

Ceramic Membranes ◽

Average Error ◽

Neural Network Modeling ◽

Alumina Powder ◽

Permeation Flux ◽

Oily Wastewater ◽

Predictive Tool ◽

Mullite Ceramic

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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Performance of BaCo0.7Fe0.2Nb0.1O3-δ Membrane under CO2-Containing Atmosphere for CCS Application

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.239-242.21 ◽

2011 ◽

Vol 239-242 ◽

pp. 21-26 ◽

Cited By ~ 3

Author(s):

Pei Jun Shen ◽

Wei Zhong Ding ◽

Hai Hai Wang ◽

Zhen Geng ◽

Xu Liu ◽

...

Keyword(s):

Oxygen Vacancy ◽

Ceramic Membrane ◽

Membrane Material ◽

Membrane Performance ◽

The Stability

Mixed ionic-electronic conducting BaCo0.7Fe0.2Nb0.1O3-δ perovskite is a newly developed promising ceramic membrane material. In this work, the stability and permeability of BaCo0.7Fe0.2Nb0.1O3-δ regarding the special requirements for CCS application are investigated. CO2 would deteriorate the membrane performance by decreasing gradient of oxygen vacancy across bulk and surface carbonatation.

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