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Physics-informed neural networks for viscoelastic fluid flows around a cylinder in a two-dimensional channel
Grid-based fluid dynamics solvers routinely struggle with exhaustive meshing demands and ill-posed inverse problems. A practical mesh-free alternative is given by Physics-informed neural networks (PINNs) but, applying them to highly elastic Oldroyd-B fluids results in many training failures. The Hig
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