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• W2889969125 abstract "Abstract The utility of flow simulations relies on the robustness of computational fluid dynamics (CFD) solvers and reproducibility of results. The aim of this study was to validate the Oasis CFD solver against in vitro experimental measurements of jet breakdown location from the FDA nozzle benchmark at Reynolds number 3500, which is in the particularly challenging transitional regime. Simulations were performed on meshes consisting of 5, 10, 17, and 28 million (M) tetrahedra, with Δ t = 10 −5 seconds. The 5M and 10M simulation jets broke down in reasonable agreement with the experiments. However, the 17M and 28M simulation jets broke down further downstream. But which of our simulations are “correct”? From a theoretical point of view, they are all wrong because the jet should not break down in the absence of disturbances. The geometry is axisymmetric with no geometrical features that can generate angular velocities. A stable flow was supported by linear stability analysis. From a physical point of view, a finite amount of “noise” will always be present in experiments, which lowers transition point. To replicate noise numerically, we prescribed minor random angular velocities (approximately 0.31 % ), much smaller than the reported flow asymmetry (approximately 3 % ) and model accuracy (approximately 1 % ), at the inlet of the 17M simulation, which shifted the jet breakdown location closer to the measurements. Hence, the high‐resolution simulations and “noise” experiment can potentially explain discrepancies in transition between sometimes “sterile” CFD and inherently noisy “ground truth” experiments. Thus, we have shown that numerical simulations can agree with experiments, but for the wrong reasons." @default.
• W2889969125 created "2018-09-27" @default.
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• W2889969125 date "2018-10-22" @default.
• W2889969125 modified "2023-09-30" @default.
• W2889969125 title "The FDA nozzle benchmark: “In theory there is no difference between theory and practice, but in practice there is”" @default.
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• W2889969125 doi "https://doi.org/10.1002/cnm.3150" @default.
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• W2889969125 hasPublicationYear "2018" @default.
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