Optimal Reverse Osmosis Network Configuration for the Rejection of Dimethylphenol from Wastewater
Publication: Journal of Environmental Engineering
Volume 144, Issue 1
Abstract
Reverse osmosis (RO) has long been recognized as an efficient separation method for treating and removing harmful pollutants such as dimethylphenol in wastewater treatment. This paper studies the effects of a 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 optimization studies carried out using a new simplified model which takes into account the solution-diffusion model and film theory to express the transport phenomena of both solvent and solute through the membrane and to estimate the concentration polarization impact, respectively. This model is validated by direct comparison with experimental data derived from the literature and which includes a dimethylphenol rejection method performed on a small-scale commercial single spiral-wound RO membrane system at different operating conditions. The new model is implemented to identify the optimal module configuration and operating conditions that achieve higher rejection after testing the impact of RO configuration. The optimization model is 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. In addition, the optimization model is subjected to a number of upper and lower limits of decision variables, including the inlet pressure, flow rate, and temperature. The model also 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.
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Published In
Journal of Environmental Engineering
Volume 144 • Issue 1 • January 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Mar 21, 2017
Accepted: Jun 7, 2017
Published online: Oct 25, 2017
Published in print: Jan 1, 2018
Discussion open until: Mar 25, 2018
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