Gast ::
| 001 | 986276 | ||
| 005 | 20251006144119.0 | ||
| 024 | 7 | _ | |2 ISBN |a 978-3-96144-263-8 |
| 024 | 7 | _ | |2 ISBN |a 978-3-96144-264-5 |
| 024 | 7 | _ | |2 ISBN |a 978-3-96144-265-2 |
| 037 | _ | _ | |a RWTH-2024-05122 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |0 P:(DE-82)IDM02462 |a Bobzin, Kirsten |b 0 |u rwth |
| 111 | 2 | _ | |a International Thermal Spray Conference |c Milan |d 2024-04-29 - 2024-05-01 |g ITSC 2024 |w Italy |
| 245 | _ | _ | |a Physics-Informed Neural Networks for Predicting Particle Properties in Plasma Spraying |h media combination |
| 260 | _ | _ | |a Düsseldorf |b DVS Media GmbH |c 2024 |
| 295 | 1 | 0 | |a ITSC 2024 : international thermal spray conference and exhibition : conference proceedings and poster sessions of the conference in Milan/Italy on April 29-May 1, 2024 / organizers: DVS - German Welding Society, ASM International - Thermal Spray Society (TSS), DVS Media GmbH |
| 300 | _ | _ | |a 452-458 |
| 336 | 7 | _ | |0 33 |2 EndNote |a Conference Paper |
| 336 | 7 | _ | |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |a Contribution to a book |m contb |
| 336 | 7 | _ | |0 PUB:(DE-HGF)8 |2 PUB:(DE-HGF) |a Contribution to a conference proceedings |b contrib |m contrib |
| 336 | 7 | _ | |2 BibTeX |a INPROCEEDINGS |
| 336 | 7 | _ | |2 DRIVER |a conferenceObject |
| 336 | 7 | _ | |2 DataCite |a Output Types/Conference Paper |
| 336 | 7 | _ | |2 ORCID |a CONFERENCE_PAPER |
| 490 | 0 | _ | |a DVS-Berichte |v 393 |
| 500 | _ | _ | |a Buch: Conference abstracts (including proceedings on USB stick) |
| 536 | _ | _ | |0 G:(DE-82)X080067-WS-B2.II |a WS-B2.II - Discontinuous Production (X080067-WS-B2.II) |c X080067-WS-B2.II |x 0 |
| 536 | _ | _ | |0 G:(GEPRIS)390621612 |a DFG project 390621612 - EXC 2023: Internet of Production (IoP) (390621612) |c 390621612 |x 1 |
| 591 | _ | _ | |a Germany |
| 653 | _ | 7 | |a Atmospheric plasma spraying (APS) |
| 653 | _ | 7 | |a artificial neural networks (ANNs) |
| 653 | _ | 7 | |a computational fluid dynamics (CFD) |
| 653 | _ | 7 | |a grey box model |
| 653 | _ | 7 | |a machine learning (ML) |
| 653 | _ | 7 | |a physics-informed neural networks (PINNs) |
| 700 | 1 | _ | |0 P:(DE-82)IDM03140 |a Heinemann, Hendrik |b 1 |u rwth |
| 700 | 1 | _ | |0 P:(DE-82)IDM03312 |a Dokhanchi, Ali |b 2 |e Corresponding author |u rwth |
| 856 | 4 | _ | |u https://publications.rwth-aachen.de/record/986276/files/986276.pdf |y Restricted |
| 909 | C | O | |o oai:publications.rwth-aachen.de:986276 |p VDB |
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| 914 | 1 | _ | |y 2024 |
| 915 | 1 | _ | |0 StatID:(DE-HGF)0021 |2 StatID |a No peer reviewed article |x 0 |
| 920 | 1 | _ | |0 I:(DE-82)419010_20140620 |k 419010 |l Lehrstuhl und Institut für Oberflächentechnik im Maschinenbau |x 0 |
| 920 | 1 | _ | |0 I:(DE-82)080067_20181221 |k 080067 |l Internet of Production |x 1 |
| 980 | _ | _ | |a I:(DE-82)080067_20181221 |
| 980 | _ | _ | |a I:(DE-82)419010_20140620 |
| 980 | _ | _ | |a UNRESTRICTED |
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| 980 | _ | _ | |a contb |
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