Machine Learning Methods for the Design and Operation of Liquid Rocket Engines -- Research Activities at the DLR Institute of Space Propulsion
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 4 of its 25 references that are in the map. First posted on arXiv 14 Feb 2021.
Builds on
4 of 25 references.
References · 4
- 2020A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challengescited by 819
- 2020A Reinforcement Learning Approach for Transient Control of Liquid Rocket Enginescited by 4
- 2019Heat Transfer Prediction for Methane in Regenerative Cooling Channels with Neural Networkscited by 2
- 2020Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learningcited by 2
Built on by
Citing papers per year: 2024: 1; 2025: 0; 2026: 2.
3 papers.
- 2026Reducing Experimental Testing in Space Propulsion Film Cooling Analyses by Pixelwise Generative Image Interpolationcited by 1
- 2024Interactive Design-of-Experiments: Optimizing a Cooling Systemcited by 0
- 2026Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Datasetcited by 0
- 2026Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset25 Sep 2026
- 2026Reducing Experimental Testing in Space Propulsion Film Cooling Analyses by Pixelwise Generative Image Interpolation28 May 2026
- 2024Interactive Design-of-Experiments: Optimizing a Cooling System8 Aug 2024