Dresia, Kai and Waxenegger-Wilfing, Günther and Riccius, Jörg and Deeken, Jan C. and Oschwald, Michael (2019) Numerically Efficient Fatigue Life Prediction of Rocket Combustion Chambers using Artificial Neural Networks. In: Proceedings of the 8th European Conference for Aeronautics and Space Sciences. 8th European Conference for Aeronautics and Space Sciences EUCASS, 2019-07-01 - 2019-07-04, Madrid, Spain. doi: 10.13009/EUCASS2019-264.
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Abstract
Fatigue life prediction is an essential part of multidisciplinary design studies and optimization loops, but state of the art finite element based methods are numerically inefficient. We overcome this challenge by training an artificial neural network to predict the number of cycles to failure, based on combustion chamber geometry and operational point. To accomplish this, a 2-d finite element analysis generates 250 000 training data samples. The trained network then predicts previously unseen data with a mean absolute percentage error of 6:8 % in less than 0:1 ms per sample compared to up to 5 min with finite element based methods. To the best of our knowledge, this publication is the first to successfully apply machine learning to fatigue life prediction.
Item URL in elib: | https://elib.dlr.de/130206/ | ||||||||||||||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||||||
Title: | Numerically Efficient Fatigue Life Prediction of Rocket Combustion Chambers using Artificial Neural Networks | ||||||||||||||||||||||||
Authors: |
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Date: | 2019 | ||||||||||||||||||||||||
Journal or Publication Title: | Proceedings of the 8th European Conference for Aeronautics and Space Sciences | ||||||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||||||
Open Access: | Yes | ||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||
In SCOPUS: | No | ||||||||||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||||||||||
DOI: | 10.13009/EUCASS2019-264 | ||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||
Keywords: | machine learning, artificial neural network, liquid rocket engines, fatigue life prediction, surrogate models | ||||||||||||||||||||||||
Event Title: | 8th European Conference for Aeronautics and Space Sciences EUCASS | ||||||||||||||||||||||||
Event Location: | Madrid, Spain | ||||||||||||||||||||||||
Event Type: | international Conference | ||||||||||||||||||||||||
Event Start Date: | 1 July 2019 | ||||||||||||||||||||||||
Event End Date: | 4 July 2019 | ||||||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||||||
HGF - Program Themes: | Space Transportation | ||||||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||
DLR - Program: | R RP - Space Transportation | ||||||||||||||||||||||||
DLR - Research theme (Project): | R - Project LUMEN (Liquid Upper Stage Demonstrator Engine) | ||||||||||||||||||||||||
Location: | Lampoldshausen | ||||||||||||||||||||||||
Institutes and Institutions: | Institute of Space Propulsion > Rocket Propulsion | ||||||||||||||||||||||||
Deposited By: | Hanke, Michaela | ||||||||||||||||||||||||
Deposited On: | 18 Nov 2019 09:14 | ||||||||||||||||||||||||
Last Modified: | 24 Apr 2024 20:33 |
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