Funder
Scientific research project of Department of Education of Hunan Province
Publisher
Springer Science and Business Media LLC
Reference44 articles.
1. Brenner MP, Eldredge JD, Freund JB (2019) Perspective on machine learning for advancing fluid mechanics. Phys Rev Fluids 4(10):100501. https://doi.org/10.1103/PhysRevFluids.4.100501
2. Haixin C, Kaiwen D, Runze L (2019) Utilization of machine learning technology in aerodynamic optimization. Acta Aeronauticaet Astronautica Sinica 40(01):52–68. https://doi.org/10.7527/S1000-6893.2018.22480
3. Wiewel S, Kim B, Azevedo VC et al (2020) Latent space subdivision: stable and controllable time predictions for fluid flow. Comput Graph Forum 39(8):15–25. https://doi.org/10.1111/cgf.14097
4. Yazdani A, Raissi M, Karniadakis G (2018) Hidden fluid mechanics: Navier–Stokes informed deep learning from the passive scalar transport. In: 71st Annual Meeting of the APS Division of Fluid Dynamics. American Physical Society
5. Rabault J, Ren F, Zhang W et al (2020) Deep reinforcement learning in fluid mechanics: a promising method for both active flow control and shape optimization. J Hydrodyn 32(4–5):234–246. https://doi.org/10.1007/s42241-020-0028-y