Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation
This article establishes a data-driven modeling framework for lean hydrogen ( $ {\mathrm{H}}_2 $ )-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particularly challenging since $ {\mathrm{H}}_2 $ molecules diffuse much faster than heat, leading to l...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Data-Centric Engineering |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2632673625000012/type/journal_article |
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