Parametric Study of Convolution Autoencoder for Reduced-Order Modeling of Turbulent Flow
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials,Computational Mechanics
Link
https://link.springer.com/content/pdf/10.1007/s40997-023-00632-2.pdf
Reference32 articles.
1. Brackbill JU, Kothe DB, Zemach C (1992) A continuum method for modeling surface tension. J Comput Phys 100(2):335–354
2. Brunton SL, Noack BR, Koumoutsakos P (2020) Machine learning for fluid mechanics. Annu Rev Fluid Mech 52:477–508
3. Cho K, Van Merriënboer B, Bahdanau D, Bengio Y (2014) On the properties of neural machine translation: Encoder-decoder approaches. arXiv preprint arXiv:1409.1259
4. Deng Z, Chen Y, Liu Y, Kim KC (2019) Time-resolved turbulent velocity field reconstruction using a long short-term memory (LSTM)-based artificial intelligence framework. Phys Fluids 31(7):075108
5. Deng Z, He C, Liu Y, Kim KC (2019) Super-resolution reconstruction of turbulent velocity fields using a generative adversarial network-based artificial intelligence framework. Phys Fluids 31(12):125111
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