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The purge bin has been widely applied in industry, e.g., solvent removal for polyolefins and food products, moisture reducing for biomass or plastics, etc. ExxonMobil also applied the purge bin for their polyolefin technology. After being generated in a reactor, these polyolefin materials are known to have high levels of dissolved hydrocarbon content, and adequate purging is required for safe operations and regulatory compliance. On the other hand, excessive purge gas flow rate could introduce unwanted N₂, and increase flaring. This work focuses on understanding the multiscale, fundamentals of a purge bin.

The scale-down strategy focuses on a, first of kind, multiscale model to enable predictive capability in a moving bed purge bin. The phenomenological components of the model are developed based on “scaling down” the commercial unit (e.g. understanding the key technical issues). These components are modeled in a transient manner (not just simulated at steady state) in the gPROMS software platform. After comparing with the literature data, a sensitivity study will be presented to understand the effects of operating parameters such as purging dimensions, temperature, pressure, purge gas flow rate and composition, purging gas injection locations, on the purging performance. As the model is transient, it can use non-steady state experiments, which are ideal for determining mass transfer rates. Hydrodynamic effects were shown to have a large effect on purging performance. Analysis of various fluid solids interactions as well as the gas/solids residence time distributions will also be discussed.