A neural network based approach for thrust prediction in cold gas propulsion systems

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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Bibliographic Details
Main Authors: Morteza Farhid, Mohammad Reza Ghavidel Aghdam, Moharram Shameli
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Thrust prediction
Cold gas thruster
Neural network
GUI
Online Access:https://doi.org/10.1038/s41598-025-12705-0
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https://doi.org/10.1038/s41598-025-12705-0

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