Machine Learning Methods for the Design and Operation of Liquid Rocket Engines -- Research Activities at the DLR Institute of Space Propulsion

• URL: http://arxiv.org/abs/2102.07109v1
• Date: Sun, 14 Feb 2021 09:09:37 GMT
• Title: Machine Learning Methods for the Design and Operation of Liquid Rocket Engines -- Research Activities at the DLR Institute of Space Propulsion
• Authors: G\"unther Waxenegger-Wilfing, Kai Dresia, Jan Deeken, Michael Oschwald
• Abstract summary: The paper describes current machine learning applications at the DLR Institute of Space Propulsion. The advantages and disadvantages of the presented methods as well as current and future research directions are discussed.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The last years have witnessed an enormous interest in the use of artificial intelligence methods, especially machine learning algorithms. This also has a major impact on aerospace engineering in general, and the design and operation of liquid rocket engines in particular, and research in this area is growing rapidly. The paper describes current machine learning applications at the DLR Institute of Space Propulsion. Not only applications in the field of modeling are presented, but also convincing results that prove the capabilities of machine learning methods for control and condition monitoring are described in detail. Furthermore, the advantages and disadvantages of the presented methods as well as current and future research directions are discussed.

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