Flux and antifouling performance of poly(vinylidnene fluoride) (PVDF) (15wt%.) nanocomposite ultrafiltration membrane with different functional carbon nanotubes (–COOH, –OH, –NH2) are considered. Membranes are prepared with phase‐inversion method using n‐methylpyrrolidone as solvent. This is the first time that hydrophilicity of different nanocomposite membranes are changing gradually, as performance of nanocomposite membrane are considered. Gradually changing of hydrophilicity explains behavior and performance of nanocomposite membrane. Scanning electron microscopy analysis of PVDF membrane with different functional multiwall carbon nanotube (FMWCNT) showed that all prepared membranes are asymmetric structure with a compact top layer and a bottom layer with large pore channels. All modified nanocomposite membranes show better hydrophilicity surface in compared with pristine PVDF membrane (87°). Results of pure water flux are approved by the result of contact angle and porosity. Measurement flux membranes with optimized percent FMWCNT is increased more than twofold compared to pristine membrane (146 L·m−2·hr−1). Atomic force microscopic also revealed that modified membranes have smaller roughness in compared with neat membrane (Sa = 270 nm). Flux recovery ratio analysis for all membranes is increased more than pure membrane (39%) because of better hydrophobicity and decrease of roughness. This subject is shown that FMWCNTs have no detrimental effect on mechanical resistance in modified membranes.
Abstract:In this paper, a new and more accurate correlation to predict bubble point pressure (P b ) for Middle East crudes by using the genetic alorithm (GA) is attempted. For this purpose, a total of 286 data sets of different crude oils from Middle East reservoirs were used as training data for constructing the correlation. The general form of the correlation was found by several regressive examinations. To improve the correlation, the genetic algorithm was applied. To validate the correlation, 143 data sets of different crudes from Middle East reservoirs which were different from the training data were used as test data for calculating mean absolute relative error (MARE) and correlation coefficient (R 2 ) between the predicted values from the proposed correlation and the experimental values. In addition, the MARE and R 2 were calculated for previous correlation in the test data. The results show that the proposed correlation is more accurate than all of the previous correlations exclusively for Middle East crudes.
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