Dynamics and long-time behavior of gas–solid flows on recurrent-transient backgrounds

• Published in: Chemical engineering journal (Lausanne, Switzerland : 1996) Vol. 364; pp. 562 - 577
• Main Authors: Lichtenegger, T., Kieckhefen, P., Heinrich, S., Pirker, S.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.05.2019
• Subjects: Data exchange schemes; Fluidized bed; Recurrence CFD; Time-extrapolation; Transient-recurrent motion; Transient-recurrent motion; Data exchange schemes; Recurrence CFD; Time-extrapolation; Fluidized bed
• ISSN: 1385-8947; 1873-3212
• DOI: 10.1016/j.cej.2019.01.161

[Display omitted] •We interpolate between time-series of weakly and more strongly excited flow fields.•A directed relaxation model avoids unphysical configurations efficiently.•Different implementations and data exchange strategies are compared.•We predict particle temperatures for recurrent-transient conditions accurately.•Simulations are sped up by more than two orders of magnitude compared to CFD-DEM. Gas–solid fluidized beds exhibit characteristic, reappearing patterns. External parameter variations or coupling between internal processes superpose a transient behavior on top of these recurrences. We demonstrate how recurrence CFD (rCFD) can cope with such scenarios by interpolating between multiple, pre-generated databases corresponding to short (2.5 s) time series in different flow regimes. The methodology is applied to a fluidized bed of approximately 80 000 solid particles subject to internal heat production and fluidization with cool gas for a duration of 800 s. The fluid’s thermal expansion due to heat transfer ([290 K; 430 K]) and the varying inlet velocities ([0.4 m/s; 0.9 m/s]) cause the desired transiency. We find excellent agreement for particle mean temperatures over time and qualitative similarity for their standard deviation between detailed, established simulation techniques and rCFD with speed-ups of more than two orders of magnitude. Furthermore, we present implementation advancements concerning parallel data exchange and compare all-to-all with one-to-one communication schemes. Analysis of the code’s performance points the way for future optimization measures.