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 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

Development of a High Performance PES Ultrafiltration Hollow Fiber Membrane for Oily Wastewater Treatment Using Response Surface Methodology

This study attempts to optimize the spinning process used for fabricating hollow fiber membranes using the response surface methodology (RSM). The spinning factors considered for the experimental design are the dope extrusion rate (DER), air gap length (AGL), coagulation bath temperature (CBT), bore fluid ratio (BFR), and post-treatment time (PT) whilst the response investigated is rejection. The optimal spinning conditions promising the high rejection performance of polyethersulfone (PES) ultrafiltration hollow fiber membranes for oily wastewater treatment are at the dope extrusion rate of 2.13 cm3/min, air gap length of 0 cm, coagulation bath temperature of 30 °C, and bore fluid ratio (NMP/H2O) of 0.01/99.99 wt %. This study will ultimately enable the membrane fabricators to produce high-performance membranes that contribute towards the availability of a more sustainable water supply system

Effect of high temperature chemical etching on surface roughness of tungsten carbide substrate

High hardness, lower thermal expansion and friction coefficient, chemical inertness and strength are the most important characteristics of cutting tools, which can be enhanced by coating the tool surface with a thin layer of diamond. A variety of surface pretreatment methods have been developed to enhance diamond nucleation rate density and adhesion strength between diamond films and substrates which include scratching, seeding, electrical biasing, pulsed laser irradiation, interlayer, ion implantation, carburization and chemical pretreatment. Among them, chemical pretreatment is the simplest and cheapest. In this paper, a single step chemical pretreatment using mixture of sulfuric acid and hydrogen peroxide solutions were carried out on tungsten carbide with 6% cobalt (WC-6% Co). Three independent variables such as concentration of sulfuric acid, etching temperature and time were varied to investigate the best combination of these parameters for roughening the WC-6% Co surface. It was found that the highest surface roughness (Ra=1.3μm) was obtained when using 95% concentration of sulfuric acid, and lower etching temperature of 40oC in duration of two minutes etching time

Linear programming model for optimizing of noise and vibration in passenger car cabin

Link to publisher's homepage at http://ieeexplore.ieee.org/Car cabin acoustical comfort is one of the factors which attract the buyer prospective buyer on purchasing a new vehicle. Basically the amount of discomfort depends to magnitude, frequency, direction and also the duration of exposed vibration in the cabin. The comfort of the driving influences driving performance. Generally the vibration is caused by two main sources: engine transmission and interaction between tyre and road surface. In this study the effects of vibration to noise in passenger car cabin were investigated. Vehicle acoustical comfort index (VACI) was used to evaluate the noise annoyance level and vibration dose value (VDV) was used to evaluate the vibration level. By using the changes trend of noise and vibration level depending to engine speeds, LP model was used to optimise the vibration level in the passenger car cabin