Prediction of the transient coolant jet released from the nose cone at supersonic flow via machine learning

Prediction of the transient coolant jet released from the nose cone at supersonic flow via machine learning

Abstract In this paper, the usage of a predictive surrogate model for the estimate of flow variables in the transient phase of coolant injection from the nose cone by combining the Long Short-Term Memory (LSTM) and Proper Orthogonal Decomposition (POD) technique. The velocity, pressure, and mass fra...

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Bibliographic Details
Main Authors: Ali Basem, M. Yasiri, Pooya Ghodratallah, Kamal Sharma, Nimesh Raj, S. Abdul Ameer, Mohammed Yaseen Abdullah, Abbas Hameed Abdul Hussein, Mohammed Y. Al-Khuzaie, M. Ahmedi
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Supersonic flow
Coolant jet
Machine learning
POD
LSTM
Nose cone
Online Access:https://doi.org/10.1038/s41598-025-87926-4
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https://doi.org/10.1038/s41598-025-87926-4

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