A generic reverse osmosis model for full-scale operation

Mathematical models can be a powerful tool in the operation of reverse osmosis (RO) facilities which is often challenged by a varying feed water quality. Most models, however, do not consider both full-scale and good modelling practice, which makes them less suited in practice. In this paper, a generic steady state model for RO was set-up and applied to a unique three-year data set from a full-scale RO process according to state-of-the-art good modelling practice. It was found that the model outputs are most sensitive towards the water and the solute permeability, and the feed spacer channel height, and therefore, only these parameters were calibrated. Furthermore, manufacturer's tests do not always reflect the full-scale situation, which highlights the importance of calibration. The model was validated with online conductivity data as input taking into account the uncertainty originating from online sensors, and compared to the commercial software Winflows. Despite the lack of long-term predictive power since fouling was not included, the model with online conductivity data as input showed satisfactory results, i.e. an average deviation from the data of 2.7%, 12.7%, 34.1% and 18.7% for respectively the recovery, the concentrate pressure, the permeate and concentrate solute concentration. [Display omitted] •A generic RO model is applied to a unique 3-year data set from a full-scale process.•Water and solute permeability, and feed spacer channel height are calibrated.•Manufacturer's tests do not always reflect full-scale situation: value of calibration.•The model with online data as input can predict the performance of an RO process.