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Parallelized Machine Learning for the Analysis of Hybrid Rocket Combustion Data

Rüttgers, Alexander and Petrarolo, Anna and Kobald, Mario and Siggel, Martin and Debus, Charlotte (2021) Parallelized Machine Learning for the Analysis of Hybrid Rocket Combustion Data. In: WCCM-ECCOMAS CONGRESS. 14th World Congress on Computational Mechanics (WCCM), 11.-15. Januar 2021, virtuelle Konferenz.

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Item URL in elib:https://elib.dlr.de/141719/
Document Type:Conference or Workshop Item (Speech)
Additional Information:Vortragsvideo: https://slideslive.com/38944037
Title:Parallelized Machine Learning for the Analysis of Hybrid Rocket Combustion Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Rüttgers, AlexanderAlexander.Ruettgers (at) dlr.dehttps://orcid.org/0000-0001-6347-9272
Petrarolo, AnnaAnna.Petrarolo (at) dlr.dehttps://orcid.org/0000-0002-2291-2874
Kobald, MarioMario.Kobald (at) dlr.dehttps://orcid.org/0000-0002-1708-3944
Siggel, Martinmartin.siggel (at) dlr.dehttps://orcid.org/0000-0002-3952-4659
Debus, CharlotteCharlotte.Debus (at) dlr.deUNSPECIFIED
Journal or Publication Title:WCCM-ECCOMAS CONGRESS
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:HPDA, HPC, Machine Learning, Data Mining, Anomaly Detection
Event Title:14th World Congress on Computational Mechanics (WCCM)
Event Location:virtuelle Konferenz
Event Type:international Conference
Event Dates:11.-15. Januar 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Vorhaben SISTEC (old)
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology
Institute for Software Technology > High-Performance Computing
Institute of Space Propulsion > Spacecraft and Orbital Propulsion
Deposited By: Rüttgers, Dr. Alexander
Deposited On:13 Apr 2021 09:34
Last Modified:13 Apr 2021 09:34

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