Evan Cyganowski Colin Fitzsimonds Lydia Krahn Rachel Martineau
Computational Fluid Dynamics Analysis and Symbolic Regression of Multiphase Separation
NEL Hydrogen is a global company, delivering hydrogen production technologies such as water electrolysers. This process splits water molecules to produce hydrogen, which can then be used for energy production. Within NEL’s hydrogen production process, a downstream, multi-phase separator tank separates oxygen from water and returns a high purity water stream to the production cycle. Our goal was to improve the efficiency of NEL’s phase separator using computational fluid dynamics. We used ANSYS Fluent to simulate oxygenated water flow and study the effect of varying separator geometries on separation efficiency. Using the simulation results and Alamo’s symbolic regression software, our group created an algebraic model to correlate the phase separator geometry with separation efficiency. The application of this model would provide NEL Hydrogen with a tool for designing efficient phase separation units for their water electrolysis processes.