Optimisation of reverse osmosis based wastewater treatment system for the removal of chlorophenol using genetic algorithms

Abstract

Citation: Al-Obaidi MA, Li J-P, Kara-Zaitri C et al (2017) Optimisation of reverse osmosis based wastewater treatment system for the removal of chlorophenol using genetic algorithms. Chemical Engineering Journal. 316: 91-100. AbstractReverse Osmosis (RO) has found extensive applications in industry as an efficient separation process in comparison with thermal process. In this study, a one-dimensional distributed model based on a wastewater treatment spiral-wound RO system is developed to simulate the transport phenomena of solute and water through the membrane and describe the variation of operating parameters along the x-axis of membrane. The distributed model is tested against experimental data available in the literature derived from a chlorophenol rejection system implemented on a pilot-scale cross-flow RO filtration system with an individual spiral-wound membrane at different operating conditions. The proposed model is then used to carry out an optimisation study using a Genetic Algorithm (GA). The GA is developed to solve a formulated optimisation problem involving two objective functions of RO wastewater system performance. The model code is written in MATLAB, and the optimisation problem is solved using an optimisation platform written in C++. The objective function is to maximize the solute rejection at different cases of feed concentration and minimize the operating pressure to improve economic aspects. The operating feed flow rate, pressure and temperature are considered as decision variables. The optimisation problem is subjected to a number of upper and lower limits of decision variables, as recommended by the module's manufacturer, and the constraint of the pressure loss along the membrane length to be within the allowable 2 value. The algorithm developed has yielded a low optimisation execution time and resulted in improved unit performance based on a set of optimal operating conditions.

Methanol steam reforming performance optimisation of cylindrical microreactor for hydrogen production utilising error backpropagation and genetic algorithm

“…Variables bh the thresholds of the hidden-layer neuron in the mathematical model, namely undetermined coefficients in the mathematical model bo the thresholds of the output-layer neuron in the mathematical model, namely undetermined coefficients in the mathematical model Neural networks have strong feature extraction and abstraction capabilities, and they can integrate multisource information, process heterogeneous data, and capture change dynamics, thus playing an important role in parameter optimisation [19][20]. To date, some foreign scholars have used neural networks to optimise the reaction performance of microreactors.…”

Performance evaluation of multi-stage reverse osmosis process with permeate and retentate recycling strategy for the removal of chlorophenol from wastewater

“…Several successful mathematical models were developed to describe the removal of phenol and phenolic compounds from wastewater using a single spiral wound RO process and focused on the impact of operating parameters on the whole performance and optimising the removal of chlorophenol using genetic algorithm (Srinivasan et al, 2009;Sundaramoorthy et al, 2011b;Srinivasan et al, 2010;Srinivasan et al, 2011;Al-Obaidi and Mujtaba, 2016;Al-Obaidi et al, 2017a;Al-Obaidi et al, 2017b;Al-Obaidi et al, 2017c). However, multi-stage RO wastewater system considering the permeate and retentate recycling scheme for the removal of phenol and phenolic compounds from wastewater has not been investigated yet.…”

Sustainable Production Methods in Textile Industry

“…Application of metaheuristic optimization methods to textile processes is a novel subject, and there are different perspectives on it. In some of the studies, the lot size and scheduling [12] are tried to optimize, while some of them try to model the end-of-pipe treatments [13][14][15][16][17][18][19]. However, only a few studies are meant to reduce the amount of wastewater and improve the process for clean production [4,[20][21][22][23].…”