(378s) A Predictive Model for Seawater Reverse Osmosis Module

A Predictive Model for Seawater
Reverse Osmosis Module

Mingheng
Li<sup>1

1</sup>Califorina State Polytechnic University, Pomona, CA 91768, United States,
minghengli@cpp.edu

Optimal design and operation of membrane
processes are important engineering problems arising at the water-energy nexus
[1, 2]. To enhance process efficiency, it is essential to develop system-level
models that can accurately predict of process behaviors including water flux,
salt flux and pressure drops [3, 4]. While high-fidelity CFD models are available
to explore local transport phenomena [5], enormous computational time is
required for a whole membrane module. This presentation will focus on an
efficient two-dimensional model that is capable of predicting the performance
of commercial reverse osmosis modules with reasonable accuracy. The model
explicitly accounts for longitudinal pressure drop in the brine channels and
spiral pressure drop in the permeate channels as well as the effect of
temperature on membrane permeability. Figure 1 shows
that the model predictions of module performance from various feed conditions match
fairly well with experimental data from a commercial Dow Filmtec^TM
module [6].  Model-based optimization of process
design and operation will be also discussed.

    

Fig. 1. Comparison of model predicted permeate outlet
pressure (left), permeate flow rate (middle) and salt amount in permeate (right)
and measured data.

References

[1]  Li,
M. Chem. Eng. Res. Des., 2018, 137, 1-9.

[2]  Li,
M. AIChE J., 2018, 64, 144-152.

[3]  Li,
M. Desalination, 2012, 293, 61-68.

[4]  Li,
M.; Noh, B. Desalination, 2012, 304,
20-24.

[5]  Li,
M.; Bui, T.; Chao, S. Desalination, 2016, 81, 191-208.

[6]  Avlomtis, S.; Hanbury, W.T.; Ben Boudmar M. Desalination, 1991, 397, 194-204.

Acknowledgements

This
work was supported by American Chemical Society Petroleum Research Fund.