Contribution to a conference proceedings/Contribution to a book FZJ-2020-01507

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Sub-Grid Scale Modelling at Scale with Deep Learning and up to 60 Billion Degrees of Freedom

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2020
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich

NIC Symposium 2020
NIC Symposium 2020, JülichJülich, Germany, 27 Feb 2020 - 28 Feb 20202020-02-272020-02-28
Jülich : Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series 50, 379 - 388 ()

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Abstract: This work presents fully resolved direct numerical simulations (DNSs) of a turbulent reactive planar temporally non-premixed jet configuration with up to 60 billion degrees of freedom. As scalar mixing is of utmost importance for this kind of configuration, a novel deep learning (DL) approach in the context of large-eddy simulation is presented which results in predictive mixing statistics on underresolved grids. The usability of the mixing model is approved by applying it to the DNS data. Furthermore, node performance measurements for the training of the DL networks are shown for different computing clusters.


Contributing Institute(s):
  1. John von Neumann - Institut für Computing (NIC)
  2. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 512 - Data-Intensive Science and Federated Computing (POF3-512) (POF3-512)

Appears in the scientific report 2020
Database coverage:
Creative Commons Attribution CC BY 4.0 ; OpenAccess
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NIC Symposium 2020: proceedings
NIC Symposium, JülichJülich, Germany, 27 Feb 2020 - 28 Feb 20202020-02-272020-02-28 Jülich : Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, NIC Series 50, v, 424 S. () OpenAccess  Download fulltext Files  Download fulltextFulltext by OpenAccess repository BibTeX | EndNote: XML, Text | RIS


 Record created 2020-03-16, last modified 2021-01-30