Data-driven subgrid scale modelling with neural networks
An exploratory study is performed to assess the proficiency of the neural networks in prediction of the non-linear mapping of the closure terms of LES and the coarse grid components in the flow, with \textit{a priori} assumptions. Two distinct frameworks of convolutional neural networks are built to...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/137038 |