Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II

Optimization of spinning conditions plays a key role in the development of high performance asymmetric hollow fiber membranes. However, from previous studies, in solving these spinning condition optimization problems, they were handled mostly by using an experimentation that varied one of the indepe...

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Main Author:	Shakir, Noor Adila Aluwi
Format:	Thesis
Language:	English
Published:	2016
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/78824/1/NoorAdilaAluwiPFKM2016.pdf
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spelling	my-utm-ep.788242018-09-17T04:20:54Z Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II 2016-06 Shakir, Noor Adila Aluwi TJ Mechanical engineering and machinery Optimization of spinning conditions plays a key role in the development of high performance asymmetric hollow fiber membranes. However, from previous studies, in solving these spinning condition optimization problems, they were handled mostly by using an experimentation that varied one of the independent spinning conditions and fixed the others. The common problem is the preparation of hollow fiber membranes that cannot be performed effectively due to inappropriate settings of the spinning conditions. Moreover, complexities in the spinning process have increased where the interaction effects between the spinning conditions with the presence of multiple objectives also affect the optimal spinning conditions. This is one of the main reasons why very little work has been carried out to vary spinning conditions simultaneously. Hence, in order to address these issues, this study focused on a non-dominated sorting genetic algorithm-II (NSGA-II) methodology to optimize the spinning conditions during the fabrication of polyethersulfone (PES) ultrafiltration hollow fiber membranes for oily wastewater treatment to maximize flux and rejection. Spinning conditions that were investigated were dope extrusion rate (DER), air gap length (AGL), coagulation bath temperature (CBT), bore fluid ratio (BFR), and post-treatment time (PT). First, the work was focused on predicting the performance of hollow fiber membranes by considering the design of experiments (DOE) and statistical regression technique as an important approach for modeling flux and rejection. In terms of experiments, a response surface methodology (RSM) and a central composite design (CCD) were used, whereby the factorial part was a fractional factorial design with resolution V and overall, it consisted of a combination of high levels and low levels, center points, as well as axial points. Furthermore, the regression models were generated by employing the Design Expert 6.0.5 software and they were found to be significant and valid. Then, the regression models obtained were proposed as the objective functions of NSGA-II to determine the optimal spinning conditions. The MATLAB software was used to code and execute the NSGA-II. With that, a non-dominated solution set was obtained and reported. It was discovered that the optimal spinning conditions occurred at a DER of 2.20 cm3/min, AGL of 0 cm, CBT of 30 °C, BFR (NMP/H2O) of 0/100 wt.%, and PT of 6 hour. In addition, the membrane morphology under the influence of different spinning conditions was investigated via a scanning electron microscope (SEM). The proposed optimization method based on NSGA-II offered an effective way to attain simple but robust solutions, thus providing an efficient production of PES ultrafiltration hollow fiber membranes to be used in oily wastewater treatment. Therefore, the optimization results contributed by NSGA-II can assist engineers and researchers to make better spinning optimization decisions for the membrane fabrication process. 2016-06 Thesis http://eprints.utm.my/id/eprint/78824/ http://eprints.utm.my/id/eprint/78824/1/NoorAdilaAluwiPFKM2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106017 phd doctoral Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Shakir, Noor Adila Aluwi Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
description	Optimization of spinning conditions plays a key role in the development of high performance asymmetric hollow fiber membranes. However, from previous studies, in solving these spinning condition optimization problems, they were handled mostly by using an experimentation that varied one of the independent spinning conditions and fixed the others. The common problem is the preparation of hollow fiber membranes that cannot be performed effectively due to inappropriate settings of the spinning conditions. Moreover, complexities in the spinning process have increased where the interaction effects between the spinning conditions with the presence of multiple objectives also affect the optimal spinning conditions. This is one of the main reasons why very little work has been carried out to vary spinning conditions simultaneously. Hence, in order to address these issues, this study focused on a non-dominated sorting genetic algorithm-II (NSGA-II) methodology to optimize the spinning conditions during the fabrication of polyethersulfone (PES) ultrafiltration hollow fiber membranes for oily wastewater treatment to maximize flux and rejection. Spinning conditions that were investigated were dope extrusion rate (DER), air gap length (AGL), coagulation bath temperature (CBT), bore fluid ratio (BFR), and post-treatment time (PT). First, the work was focused on predicting the performance of hollow fiber membranes by considering the design of experiments (DOE) and statistical regression technique as an important approach for modeling flux and rejection. In terms of experiments, a response surface methodology (RSM) and a central composite design (CCD) were used, whereby the factorial part was a fractional factorial design with resolution V and overall, it consisted of a combination of high levels and low levels, center points, as well as axial points. Furthermore, the regression models were generated by employing the Design Expert 6.0.5 software and they were found to be significant and valid. Then, the regression models obtained were proposed as the objective functions of NSGA-II to determine the optimal spinning conditions. The MATLAB software was used to code and execute the NSGA-II. With that, a non-dominated solution set was obtained and reported. It was discovered that the optimal spinning conditions occurred at a DER of 2.20 cm3/min, AGL of 0 cm, CBT of 30 °C, BFR (NMP/H2O) of 0/100 wt.%, and PT of 6 hour. In addition, the membrane morphology under the influence of different spinning conditions was investigated via a scanning electron microscope (SEM). The proposed optimization method based on NSGA-II offered an effective way to attain simple but robust solutions, thus providing an efficient production of PES ultrafiltration hollow fiber membranes to be used in oily wastewater treatment. Therefore, the optimization results contributed by NSGA-II can assist engineers and researchers to make better spinning optimization decisions for the membrane fabrication process.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Shakir, Noor Adila Aluwi
author_facet	Shakir, Noor Adila Aluwi
author_sort	Shakir, Noor Adila Aluwi
title	Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
title_short	Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
title_full	Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
title_fullStr	Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
title_full_unstemmed	Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II
title_sort	modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-ii
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2016
url	http://eprints.utm.my/id/eprint/78824/1/NoorAdilaAluwiPFKM2016.pdf
_version_	1747818080264781824

Modeling and optimization of spinning conditions for polyethersulfone hollow fiber membrance fabrication using non-dominated sorting genetic algorithm-II

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