Computational framework for modeling membrane processes without process and solution property simplifications
Abstract
Accurately modeling membrane processes is critical to evaluating novel process configurations, designing scalable membrane systems, informing process cost estimates, and directing future research. Most membrane process models trade accuracy for computational efficiency by employing simplified approximations of the process (i.e. no salt flux, no pressure drop) and solution properties (i.e. ideal solution, and constant density, viscosity, and diffusivity). Our report introduces a detailed one-dimensional finite difference model for evaluating membrane processes that avoids these common simplifications. We apply this model to quantify the error introduced by these simplifications for case studies of reverse osmosis, osmotically assisted reverse osmosis, forward osmosis, and pressure retarded osmosis. While the magnitude of error introduced by these simplifications is reliant on the case study parameters and specifications, we find that existing model formulations can underestimate or overestimate average water flux by nearly 50% for some membrane processes operating under standard conditions. Lastly we investigate the error introduced by simplified inlet-outlet models that do not solve the governing system of differential equations, and we assess the accuracy of novel inlet-outlet formulations that use a log and geometric mean, instead of the typical arithmetic mean, to represent non-linear water flux profiles.
- Authors:
-
- Carnegie Mellon Univ., Pittsburgh, PA (United States); National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)
- Publication Date:
- Research Org.:
- National Energy Technology Lab. (NETL), Morgantown, WV (United States)
- Sponsoring Org.:
- USDOE Office of Fossil Energy (FE)
- OSTI Identifier:
- 1532667
- Alternate Identifier(s):
- OSTI ID: 1636552
- Grant/Contract Number:
- FE0004000; CBET-1554117
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Membrane Science
- Additional Journal Information:
- Journal Volume: 573; Journal Issue: C; Journal ID: ISSN 0376-7388
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING; Reverse osmosis; Osmotically assisted reverse osmosis; Forward osmosis; Pressure retarded osmosis; Module scale model
Citation Formats
Bartholomew, Timothy V., and Mauter, Meagan S. Computational framework for modeling membrane processes without process and solution property simplifications. United States: N. p., 2018.
Web. doi:10.1016/j.memsci.2018.11.067.
Bartholomew, Timothy V., & Mauter, Meagan S. Computational framework for modeling membrane processes without process and solution property simplifications. United States. https://doi.org/10.1016/j.memsci.2018.11.067
Bartholomew, Timothy V., and Mauter, Meagan S. Thu .
"Computational framework for modeling membrane processes without process and solution property simplifications". United States. https://doi.org/10.1016/j.memsci.2018.11.067. https://www.osti.gov/servlets/purl/1532667.
@article{osti_1532667,
title = {Computational framework for modeling membrane processes without process and solution property simplifications},
author = {Bartholomew, Timothy V. and Mauter, Meagan S.},
abstractNote = {Accurately modeling membrane processes is critical to evaluating novel process configurations, designing scalable membrane systems, informing process cost estimates, and directing future research. Most membrane process models trade accuracy for computational efficiency by employing simplified approximations of the process (i.e. no salt flux, no pressure drop) and solution properties (i.e. ideal solution, and constant density, viscosity, and diffusivity). Our report introduces a detailed one-dimensional finite difference model for evaluating membrane processes that avoids these common simplifications. We apply this model to quantify the error introduced by these simplifications for case studies of reverse osmosis, osmotically assisted reverse osmosis, forward osmosis, and pressure retarded osmosis. While the magnitude of error introduced by these simplifications is reliant on the case study parameters and specifications, we find that existing model formulations can underestimate or overestimate average water flux by nearly 50% for some membrane processes operating under standard conditions. Lastly we investigate the error introduced by simplified inlet-outlet models that do not solve the governing system of differential equations, and we assess the accuracy of novel inlet-outlet formulations that use a log and geometric mean, instead of the typical arithmetic mean, to represent non-linear water flux profiles.},
doi = {10.1016/j.memsci.2018.11.067},
journal = {Journal of Membrane Science},
number = C,
volume = 573,
place = {United States},
year = {2018},
month = {11}
}
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