Exploring the Pressure Change of Reverse Osmosis Filtration: Time-Course Pressure Curves and a Novel Model for Mechanism Study and Newater Application

Medientyp: E-Book

Titel: Exploring the Pressure Change of Reverse Osmosis Filtration : Time-Course Pressure Curves and a Novel Model for Mechanism Study and Newater Application

Beteiligte: Xu, Yu-Qing [VerfasserIn]; Wu, Yin-Hu [VerfasserIn]; Tong, Xin [VerfasserIn]; Song, Ke-Ying [VerfasserIn]; Chen, Gen-Qiang [VerfasserIn]; Bai, Yuan [VerfasserIn]; Luo, Li-Wei [VerfasserIn]; Wang, Hao-Bin [VerfasserIn]; Zhang, Zi-Wei [VerfasserIn]; Ikuno, Nozomu [VerfasserIn]; Hu, Hong-Ying [VerfasserIn]

Erschienen: [S.l.]: SSRN, [2022]

Umfang: 1 Online-Ressource (44 p)

Sprache: Englisch

DOI: 10.2139/ssrn.4038146

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Beschreibung: Reverse osmosis membranes have been producing high quality reclaimed water for portable and industrial use, but face inevitable fouling problems. In the constant flux RO membrane operation, fouling is manifested as increase in operational pressure. However, the pressure-time curves have no consistent form, and there’s a lack of pressure-time models that is capable of fitting various shapes of curves. In this study, the pressure-time curves of RO membranes were summarized into 3 types according to their change in pressure increasing rate. Each type of curve was speculated to be caused by a specific density change pattern of the fouling layer. An Integrated Spherical Diffusion Cell (SDC) Model was developed for the pressure-time relationships of Type I curves (pressure increasing rate increases with time) and Type III curves (pressure increasing rate decreases with time). Time-course pressure data of Type I and III curves were collected from literature, and the Integrated SDC model fitted these data better than other models derived from literature. Over 70% of R 2 exceeded 0.90 for Type I curves and over 85% of R 2 exceeded 0.88 for Type III curves. Furthermore, the Integrated SDC Model also showed superior fitting performance to the operational data of the full-scale RO system in the Changi Newater plant. The model could characterize the fouling tendency by the model parameters, and predict subsequent pressure growth with the pressure data within 20% increase compared to the original pressure. For 10 out of 14 sets of data, the relative error of the predicted final pressure to the actual final pressure was below 10%. The findings are well-applied to industrial practice and may enable further research in the pressure growth pattern of constant flux RO filtration, assuring stable operation of full-scale RO systems

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