C(NN)FD -- a deep learning framework for turbomachinery CFD analysis

arXiv:2306.05889v2 Announce Type: replace
Abstract: Deep Learning methods have seen a wide range of successful applications across different industries. Up until now, applications to physical simulations such as CFD (Computational Fluid Dynamics), have been limited to simple test-cases of minor industrial relevance. This paper demonstrates the development of a novel deep learning framework for real-time predictions of the impact of manufacturing and build variations on the overall performance of axial compressors in gas turbines, with a focus on tip clearance …

abstract analysis applications arxiv cases cfd computational cs.ce cs.lg deep learning deep learning framework development dynamics fluid dynamics framework industrial industries novel paper physics.flu-dyn replace simple simulations test type