Fast 3D flow reconstructions from 2D cross-plane observations

Abstract

A computationally efficient flow reconstruction technique is proposed, exploiting homogeneity in a given direction, to recreate three-dimensional instantaneous turbulent velocity fields from snapshots of two dimension planar fields. This methodology, termed as ’snapshot optimisation’ or SO, can help to provide 3D data sets for studies which are currently restricted by the limitations of experimental measurement techniques. The SO method aims at optimising the error between an inlet plane with a homogeneous direction and snapshots, obtained over a sufficient period of time, on the observation plane. The observations are carried out on a plane perpendicular to the inlet plane with a shared edge normal to the homogeneity direction. The method is applicable to all flows which display a direction of homogeneity such as cylinder wake flows, channel flow, mixing layer, and jet (axisymmetric). The ability of the method is assessed with two synthetic data sets, and three experimental PIV data sets. A good reconstruction of the large-scale structures is observed for all cases. The small-scale reconstruction ability is partially limited especially for higher dimensional observation systems. POD-based SO method and averaging SO variations of the method are shown to reduce discontinuities created due to temporal mismatch in the homogenous direction providing a smooth velocity reconstruction. The volumetric reconstruction is seen to capture large-scale structures for synthetic and experimental case studies. The algorithm run time is found to be in the order of a minute providing results comparable with the reference. Such a reconstruction methodology can provide important information for data assimilation in the form of initial condition, background condition, and 3D observations.

Graphical abstract

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Acknowledgements

The authors would like to thank Anthony Guibert for providing the experimental data sets (cases 3 and 5), and Sylvain Laizet for the channel flow DNS data set.

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Correspondence to Pranav Chandramouli.

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Chandramouli, P., Memin, E., Heitz, D. et al. Fast 3D flow reconstructions from 2D cross-plane observations. Exp Fluids 60, 30 (2019). https://doi.org/10.1007/s00348-018-2674-1

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