The purpose of this work is to develop and evaluate electroding methods for a reverse osmosis (RO) membrane that results in an in situ sensor able to detect RO membrane protein fouling. Four electroding techniques were explored: i) gold exchange-reduction, ii) encapsulated carbon grease, iii) "direct assembly process" (DAP), and iv) platinized polymer graft. The novel platinized polymer graft method involves chemically modifying the RO membrane surface to facilitate platinization based on the hypothesis that deposition of foulant on the platinized surface will affect platinum/foulant/solution interfacial regions, thus sensor impedance. Platinized polymer graft sensors were shown to be sensitive to protein fouling. Electrodes were characterized by their electrical properties, SEM and XPS. Assembled sensors were evaluated for sensitivity to electrolyte concentration and protein fouling. Micrographs showed coating layers and pre-soak solution influence gold exchange-reduction electrode formation. High surface resistance makes gold exchange-reduction an unsuitable method. Concentration sensitivity experiments showed carbon grease and DAP electroding methods produce unusable sensors. Carbon grease sensors have time-dependent impedance response due to electrolyte diffusion within the micro-porous polysulfone support. DAP electroded sensors proved quite fragile upon hydration; their impedance response is transient and lacks predictable trends with changes in concentration. A parametric study of the platinized polymer graft method shows amount of grafted monomer correlates to grafting time, and deposited platinum is a function of exchange-reduction repetitions and amount of grafted monomer. Platinized polymer graft sensors were fouled in both dead-end and cross-flow RO systems, and their impedance trends, while varying between sensors, indicate protein-fouling sensitivity. / Master of Science

Yes / The water permeability constant, (Kw) is one of many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g.within the RO process model, estimation of Kw is therefore important. There are only two available literature correlations for calculating the dynamic Kw values. However, each of them are only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict Kw in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the Kw values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict Kw values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. While developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated.

Yes / The implementation of Reverse Osmosis (RO) technology is noticeably increased to produce freshwater from brackish and seawater resources. In this work, performance analysis of a multistage multi pass medium-sized spiral wound brackish water RO (BWRO) desalination plant (1200 m³/day) of Arab Potash Company (APC) located in Jordan is evaluated using modelling and simulation. For this purpose, a mathematical model for the spiral wound RO process based on the principles of solution diffusion model is developed. The model is then used to simulate the operating conditions of low-salinity brackish water RO (BWRO) desalination plant. The results obtained are then compared against the real industrial data of BWRO desalination plant of APC which shows a high-level of consistency. Finally, the model is used to analysis the impact of the operating parameters such as salinity, pressure, temperature, and flow rate on the plant performance. The sensitivity analysis confirms that both feed flow rate and operating pressure as the critical parameters that positively affect the product salinity.

Yes / Reverse Osmosis (RO) is one of the most widely used technologies for wastewater treatment for the removal of toxic impurities, such as phenol and phenolic compounds from industrial effluents. In this research, performance of multi-stage RO wastewater treatment system is evaluated for the removal of chlorophenol from wastewater using model-based techniques. A number of alternative configurations with recycling of permeate, retentate, and permeate-retentate streams are considered. The performance is measured in terms of total recovery rate, permeate product concentration, overall chlorophenol rejection and energy consumption and the effect of a number of operating parameters on the overall performance of the alternative configurations are evaluated. The results clearly show that the permeate recycling scheme at fixed plant feed flow rate can remarkably improve the final chlorophenol concentration of the product despite a reduction in the total recovery rate.

Yes / Reverse osmosis (RO) has become a significant method for removing salts and organic compounds from seawater and wastewater in recent decades. Spiral-wound module has been widely used due to a number of special features such as high packing density, premium separation and low operating cost. In this paper, a two-dimensional mathematical model is developed for the transport of dilute aqueous solutions through a spiral-wound RO module and the operational characteristics of the process under steady state conditions are analysed. The model is based on the solution-diffusion model coupled with the concentration polarization mechanism. This model yields a set of Differential and Algebraic Equations (DAEs), which are solved using the gPROMS software. The model is validated using experimental data from the literature for the rejection of dimethylphenol as solute in aqueous solutions. The model is then used to simulate the process under steady state conditions to gain deeper insight of the process.

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.

Yes / Reverse osmosis (RO) is becoming one of the most promising technologies used in wastewater treatment because it offers high rate of contaminant rejection and lower energy consumption in comparison with other thermal treatment processes. Earlier research by the same authors in respect of a distributed one-dimensional mathematical model for a single spiral-wound RO membrane module based on the solution-diffusion model has been used in this paper to simulate the rejection of NDMA (N-nitrosodimethylamine) from wastewater in a series of seven RO elements full-scale treatment plant. Firstly, the applicability of this model has been evaluated using a simulation study and the results have been compared against experimental data gathered from the literature for a given plant. Secondly, further simulation and analysis studies are carried out to assess the performance of the plant for NDMA rejection and recovery rate under different operating conditions of feed pressure, flow rate, and concentration. For the studied RO configuration, it is concluded that a maximum of 55.1% NDMA rejection can be achieved, which confirms the remaining issue of lower NDMA rejection.

Yes / The removal of pollutants such as N-nitrosamine present in drinking and reuse water resources is of significant interest for health and safety professionals. Reverse osmosis (RO) is one of the most promising and efficient methodologies for removing such harmful organic compounds from wastewater. Having said this, the literature confirms that the multi-stage RO process with retentate reprocessing design has not yet achieved an effective removal of N-nitrosodimethylamine-D6 (NDMA) from wastewater. This research emphasizes on this particular challenge and aims to explore several conceptual designs of multi-stage RO processes for NDMA rejection considering model-based techniques and compute the total recovery rate and energy consumption for different configurations of retentate reprocessing techniques. In this research, the permeate reprocessing design methodology is proposed to increase the process efficiency. An extensive simulation analysis is carried out using high NDMA concentration to evaluate the performance of each configuration under similar operational conditions, thus providing a deep insight on the performance of the multi-stage RO permeate reprocessing predictive design. Furthermore, an optimisation analysis is carried out on the final design to optimise the process with a high NDMA rejection performance and the practical recovery rate by manipulating the operating conditions of the plant within specified constraints bounds. The results show a superior removal of NDMA from wastewater.