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| 001 | 874553 | ||
| 005 | 20210130004725.0 | ||
| 024 | 7 | _ | |a 2128/24572 |2 Handle |
| 037 | _ | _ | |a FZJ-2020-01507 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Bode, Mathis |0 P:(DE-HGF)0 |b 0 |
| 111 | 2 | _ | |a NIC Symposium 2020 |c Jülich |d 2020-02-27 - 2020-02-28 |w Germany |
| 245 | _ | _ | |a Sub-Grid Scale Modelling at Scale with Deep Learning and up to 60 Billion Degrees of Freedom |
| 260 | _ | _ | |a Jülich |c 2020 |b Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag |
| 295 | 1 | 0 | |a NIC Symposium 2020 |
| 300 | _ | _ | |a 379 - 388 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
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| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1584451491_22058 |2 PUB:(DE-HGF) |
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| 490 | 0 | _ | |a Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series |v 50 |
| 520 | _ | _ | |a 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. |
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| 700 | 1 | _ | |a Denker, Dominik |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Jitsev, Jenia |0 P:(DE-Juel1)158080 |b 2 |e Corresponding author |
| 700 | 1 | _ | |a Pitsch, Heinz |0 P:(DE-HGF)0 |b 3 |
| 787 | 0 | _ | |i IsPartOf |0 FZJ-2020-01353 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/874553/files/NIC_2020_Pitsch.pdf |
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| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
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