A neural network based approach for thrust prediction in cold gas propulsion systems
Abstract In this paper, we present a machine learning method to accurately predict thrust in a cold gas thruster using a feedforward neural network (FFNN). The model leverages critical operational parameters, such as storage pressure, mass flow rate, nozzle length, exit pressure, and propellant mass...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-12705-0 |
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