Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks
In this study, a transfer learning-based neural network approach to predict ignition delays for a variety of fuels is proposed to meet the demand for accurate combustion analysis. A comprehensive dataset of ignition delays was generated using a random sampling technique across different temperatures...
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Main Authors: | Mo Yang, Dezhi Zhou |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
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Series: | Energy and AI |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546824001332 |
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