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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Bibliographic Details
Main Authors: Mo Yang, Dezhi Zhou
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Energy and AI
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546824001332
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