Two-Zone Fluidized Bed Reactors for Butadiene Production: A Multiphysical Approach with Solver Coupling for Supercomputing Application
The application of multiphysical modelling is steadily increasing in the last decade, which also leads to a corresponding increase of the complexity and of the diversity of software packages used. To deal with this complexity, users of supercomputing clusters are often challenged to couple two or more software systems of different software vendors together. However, the combined use of complex software systems usually raises additional limitations, thus reducing considerably the efficiency of the parallel simulations. In the present work, an example of such complex software utilization has been shown and the particular limitations are identified. The most severe limitation for the current supercomputing simulations has been the relatively high RAM requirement per computing core. At this stage of the numerical investigation, in order to overcome the limitations, the software packages have been ported to a different, more suitable hardware architecture with increased RAM per node. This way, the efficient use of the parallel computational resources has been guaranteed which was confirmed by means of strong scaling tests.
KeywordsCFD-DEM Eulerian-Lagrangian approach Strong scaling Two-zone fluidized bed reactor TZFBR
The simulations for the present work were partly supported by the bwHPC initiative and the bwHPC-C5 project [A1] provided through associated compute services of the JUSTUS HPC facility at the University of Ulm. The grant of supercomputing resources on the ForHLR-I supercomputer at the Steinbuch Centre for Computing of the Karlsruhe Institute of Technology for the project with acronym “butadiene” is highly appreciated.
The authors would like to thank Jürgen Salk from the Communication and Information Center of the University of Ulm (Competence Center for Computational chemistry), Alexandru Saramet from the University of Applied Sciences Esslingen (Competence Center for Engineering sciences) and Dr. Stefan Radl from the Graz University of Technology for their valuable help and advices during the software installation and the software adjustment processes. The authors would like to thank also to their colleagues Dr. Holger Obermaier and Richard Walter from SCC/SCS for the fruitful discussions.
The support of the Helmholtz programme “Supercomputing and Big Data” [A2] is also highly appreciated.
[A1] bwHPC and bwHPC-C5 (http://www.bwhpc-c5.de) funded by the Ministry of Science, Research and the Arts Baden-Württemberg (MWK) and the German Research Foundation (DFG).
[A2] The Programme “‘Supercomputing & Big Data” https://www.helmholtz.de/en/research/key\_technologies/supercomputing\_big\_data/
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