MemPy v1.0 - Simulation Software for Gas Separation Using Spiral-Wound Membrane Modules

A simulation software tool to evaluate performance of spiral-wound membrane modules. Applications: Spiral-wound membrane modules, Gas or chemical separation

 A variety of mathematical models have been presented for gas separations with spiral-wound membrane modules. The models, found to be in agreement with experiments performed on N2/O2 mixtures, were implemented into a computer program that can be downloaded at https://z.umn.edu/MemPy.

Link to Project: https://rapid.aiche.org/projects/energy-efficient-separations-olefins-and-paraffins-through-membrane

Primary Category

Associated Content

Modeling and simulation of gas separations with spiral-wound membranes

About

Researchers at the University of Minnesota have developed a simulation software tool based on a new mathematical model to accurately describe the mass and momentum balances for gas separations in a spiral-wound membrane module.

 

Licensing Info

This technology is now available for license! The University is excited to partner with industry to see this innovation reach its potential. Please contact us to share your business’ needs and your licensing interests in this technology. The license is for the sale, manufacture or use of products claimed by the patents.

Acknowledgment for Software

The research leading to the development of MemPy was primarily supported by the Department of Energy's (DOE) Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE000788, and also by the DOE's Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award Number DE-FG02-17ER16362.

Corresponding Author(s)

Robert F. DeJaco, University of Minnesota, dejac001@umn.edu

IIJa Siepmann, University of Minnesota, siepmann@umn.edu

Michael Tsapatsis, Johns Hopkins University/University of Minnesota, TSAPATSIS@JHU.EDU

 

 

 

Licensing

These materials are subject to licensing terms agreed by the developers in accordance to the RAPID Members Agreement. The referenced published material is subject to the appropriate copyright and publisher restrictions.

 

Acknowledgment

This material is primarily supported by the U.S. Department of Energy's (DOE) Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE000788, and also by the U.S. Department of Energy's Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award Number DE-FG02-17ER16362. The authors acknowledge the Minnesota Supercomputing Institute at the University of Minnesota (UMN) for providing computational resources that contributed to this work. R. F. D. thanks P. Constantino, C. Parrish, and M. Palys (UMN) for helpful conversations on finite-difference techniques, T. Yang for discussions on P-R EOS, and the reviewers for their helpful comments.