AI techniques in CFD: leveraging physical priors with deep learning to improve on numerical solvers
Computational fluid dynamics (CFD) simulation is an irreplaceable modelling step in many engineering designs, but it is often computationally expensive to execute numerically. Data-driven methods such as using neural networks to simulate the solving of partial differential equations such as Navier-S...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2025
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| Online Access: | https://hdl.handle.net/10356/182523 |