META-SYNTHESIS AND MATHEMATICAL MODELING OF REVERSE OSMOSIS SYSTEM PERFORMANCE DURING SURFACE WATER TREATMENT: A DATA MINING APPROACH

A new testable mathematical model of normalized permeability and normalized system salt passage was developed to predict both the quantity and quality of the product water that was observed during the pilot study on RO systems A and D. The model constructed from data collected from RO system A accurately predicts the quantitative dependence of normalized permeability on temperature, feed flow, system recovery, net driving pressure, and water flux of the system. The model constructed from data collected from RO system D accurately predicts the quantitative dependence of normalized system salt passage on temperature, feed flow, post-recycle feed conductivity, system recovery, permeate TDS, manufacturer’s rated membrane salt passage, and water flux of the system. This analysis explains the manner in which fouling is caused by both physical and chemical interactions between the membrane and the fouling agents. The strong interdependence of these fundamental operating conditions and correlation between permeability and system salt passage were confirmed when the models were tested on data collected from RO systems A, B, C, and D. Although a reasonable agreement between the results was obtained when the model was tested in these four RO systems, the models slightly overestimated the permeability values and underestimated the system salt passage values recorded in RO system B. This discrepancy is possibly attributed to fouling, concentration polarization, structure and surface morphology of the RO membrane, system recovery (RO B ran at 75%, RO systems A and D ran at 82%), and increase in RO systems A and D membrane water flux from 11 gallons/ft²/day (gfd) to 12 gfd.