Machine Learning and Its Application to Reacting Flows ML and Combustion /
| 企业作者: | |
|---|---|
| 其他作者: | , |
| 总结: | XI, 346 p. 127 illus., 98 illus. in color. text |
| 语言: | 英语 |
| 出版: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
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| 版: | 1st ed. 2023. |
| 丛编: | Lecture Notes in Energy,
44 |
| 主题: | |
| 在线阅读: | https://doi.org/10.1007/978-3-031-16248-0 |
| 格式: | 电子 图书 |
书本目录:
- Introduction
- ML Algorithms, Techniques and their Application to Reactive Molecular Dynamics Simulations
- Big Data Analysis, Analytics & ML role
- ML for SGS Turbulence (including scalar flux) Closures
- ML for Combustion Chemistry
- Applying CNNs to model SGS flame wrinkling in thickened flame LES (TFLES)
- Machine Learning Strategy for Subgrid Modelling of Turbulent Combustion using Linear Eddy Mixing based Tabulation
- MILD Combustion–Joint SGS FDF
- Machine Learning for Principal Component Analysis & Transport
- Super Resolution Neural Network for Turbulent non-premixed Combustion
- ML in Thermoacoustics
- Concluding Remarks & Outlook.