Researchers introduced TurtLES, a 14 TB dataset of 3D turbulent cylinder wakes in the shear-layer transition regime, as a large-scale benchmark for machine-learning surrogates of turbulent 3D neural PDEs. The benchmark targets a gap in computational fluid dynamics, where progress on ML surrogates is limited by the absence of benchmarks capturing realistic, time-dependent turbulent flows.
Machine-learning surrogates are increasingly used to accelerate computational fluid dynamics, yet progress is limited by the lack of benchmarks capturing realistic, time-dependent turbulent flows. We introduce TurtLES, a 14 TB dataset of 3D turbulent cylinder wakes in the shear-layer transition regi
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