yes / Reverse osmosis (RO)is one of the most important technologies used in wastewater treatment plants due to high contaminant rejection and low utilization of energy in comparison to other treatment procedures. For single-component spiral-wound reverse osmosis membrane process, one dimensional steady state and dynamic mathematical models have been developed based on the solution-diffusion model coupled with the concentration polarization mechanism. The model has been validated against reported data for wastewater treatment from literature at steady state conditions. Detailed simulation using the dynamic model has been carried out in order to gain deeper insight of the process. The effect of feed flow rate, pressure, temperature and concentration of pollutants on the performance of the process measured in terms of salt rejection, recovery ratio and permeate flux has been investigated. / The full text will be available at the end of the publisher's embargo

Yes / Reverse osmosis (RO) has long been recognised as an efficient separation method for treating and removing harmful pollutants, such as dimethylphenol in wastewater treatment. This research aims to study the effects of RO network configuration of three modules of a wastewater treatment system using a spiral-wound RO membrane for the removal of dimethylphenol from its aqueous solution at different feed concentrations. The methodologies used for this research are based on simulation and optimisation studies carried out using a new simplified model. This takes into account the solution-diffusion model and film theory to express the transport phenomena of both solvent and solute through the membrane and estimate the concentration polarization impact respectively. This model is validated by direct comparison with experimental data derived from the literature and which includes dimethylphenol rejection method performed on a small-scale commercial single spiral-wound RO membrane system at different operating conditions. The new model is finally implemented to identify the optimal module configuration and operating conditions that achieve higher rejection after testing the impact of RO configuration. The optimisation model has been formulated to maximize the rejection parameters under optimal operating conditions of inlet feed flow rate, pressure and temperature for a given set of inlet feed concentration. Also, the optimisation model has been subjected to a number of upper and lower limits of decision variables, which include the inlet pressure, flow rate and temperature. In addition, the model takes into account the pressure loss constraint along the membrane length commensurate with the manufacturer’s specifications. The research clearly shows that the parallel configuration yields optimal dimethylphenol rejection with lower pressure loss.

Yes / Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCGA) based optimisation framework to optimise the design and operational parameters of the process. To provide a deeper insight of the process to the readers, the influences of membrane design parameters on dimethylphenol rejection, water recovery rate and the level of specific energy consumption of the process for two different sets of operating conditions are presented first which were achieved via simulation. The membrane parameters taken into consideration include membrane length, width and feed channel height. Finally, a multi-objective function is presented to optimise the membrane design parameters, dimethylphenol rejection and required energy consumption. Simulation results affirmed insignificant and significant impacts of membrane length and width on dimethylphenol rejection and specific energy consumption, respectively. However, these performance indicators are negatively influenced due to increasing the feed channel height. On the other hand, optimisation results generated an optimum removal of dimethylphenol at reduced specific energy consumption for a wide sets of inlet conditions. More importantly, the dimethylphenol rejection increased by around 2.51% to 98.72% compared to ordinary RO module measurements with a saving of around 20.6% of specific energy consumption.

Yes / Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCGA) based optimisation framework to optimise the design and operational parameters of the process. To provide a deeper insight of the process to the readers, the influences of membrane design parameters on dimethylphenol rejection, water recovery rate and the level of specific energy consumption of the process for two different sets of operating conditions are presented first which were achieved via simulation. The membrane parameters taken into consideration include membrane length, width and feed channel height. Finally, a multi-objective function is presented to optimise the membrane design parameters, dimethylphenol rejection and required energy consumption. Simulation results affirmed insignificant and significant impacts of membrane length and width on dimethylphenol rejection and specific energy consumption, respectively. However, these performance indicators are negatively influenced due to increasing the feed channel height. On the other hand, optimisation results generated an optimum removal of dimethylphenol at reduced specific energy consumption for a wide sets of inlet conditions. More importantly, the dimethylphenol rejection increased by around 2.51% to 98.72% compared to ordinary RO module measurements with a saving of around 20.6% of specific energy consumption.

Yes / The use of Reverse Osmosis (RO) membrane processes for the clarification and the concentration of apple juice is proposed as an alternative to the conventional concentration technique, which is based on evaporation and freezing. Several models have been published on RO process models relying on different assumptions that predict the permeate flux and aroma compounds rejections for aqueous solutions apple juice. The solution-diffusion model (Lumped model) has been applied for the previous models. The main instrument of this study is the use of the gPROMS software to develop a new distributed steady state model that will relax a number of earlier assumptions. The model has been validated with an observational data of apple juice filtration derived from the literature by analysing the permeate flux and the performance of membrane rejection at different concentrations, temperatures and pressures for a laboratory scale of spiral-wound RO module. Simulated results corroborate with experimental and model predictions.

yes / In this paper, a one-dimensional mathematical model based on coupled differential and algebraic equations has been developed for analysing the separation mechanism of a N-nitrosamine in a spiral-wound reverse osmosis process. The model is based on Spiegler and Kedem’s work on mass transport and Darcy’s law and concentration polarization to analyse the pressure drop and mass transfer coefficient in the module feed channel respectively. The model is built using the gPROMS software suite and validated using N-nitrosamine rejection experimental data from the literature, obtained by using a pilot-scale cross-flow reverse osmosis filtration system. Analysis results derived from the model corroborate experimental data.

Yes / Reverse 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 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.

Yes / The removal of the ubiquitous phenol and phenolic compounds in industrial wastes is a critical environmental issue due to their harmful threats to wildlife and potential adverse human health effects. The removal of such compounds is therefore of significant importance in water treatment and reuse. In recent years, reverse osmosis (RO) has been successfully utilised in several industrial processes and wastewater treatment including phenol removal. In this paper, a new model based on a spiral-wound RO process is developed for the removal of phenol from wastewater. A simplified mathematical algorithm using an irreversible thermodynamic approach is developed. This results in a set of non-linear Differential and Algebraic Equations (DAEs), which are solved based on a number of optimised model parameters using a combined methodology of parameter estimation and experimental phenol-water data derived from the literature. The effects of several operational parameters on the performance (in terms of removal of phenol) of the process are explored using the model.

Yes / Reverse Osmosis (RO) membrane process has been commonly used for clarification and concentration of apple juice processes, due to significant advance in membrane technology, requirements for low energy and cost, and effective retention of aroma components. In this paper, a multi-stage RO industrial full-scale plant based on the MSCB 2521 RE99 spiral-wound membrane module has been used to simulate the process of concentrating apple juice and to identify an optimal multi-stage RO process for a specified apple juice product of high concentration measured in Brix. The optimisation problem is formulated as a Nonlinear Programming (NLP) problem with five different RO superstructures to maximise the apple juice concentration as well as the operating parameters such as feed pressure, flow rate and temperature are optimised. A simple lumped parameter model based on the solution-diffusion model and the contribution of all sugar species (sucrose, glucose, malic acid, fructose and sorbitol) to the osmotic pressure is assumed to represent the process. The study revealed that the multi-stage series RO process can optimise the product concentration of apple juice better than other configurations. It has been concluded that the series configuration of twelve elements of 1.03 m2 area improves the product apple juice concentration by about 142% compared to one element. Furthermore, the feed pressure and flow rate were found to have a significant impact on the concentration of the apple juice.