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Flow Enhancement of Tomographic Particle Image Velocimetry Measurements Using Sequential Data Assimilation

He, C.X.; Wang, P.; Liu, Y.Z.; Gan, L.

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Authors

C.X. He

P. Wang

Y.Z. Liu



Abstract

Sequential data assimilation (DA) was performed on three-dimensional flow fields of a circular jet measured by tomography particle image velocimetry (tomo-PIV). The work focused on the in-depth analysis of the flow enhancement and the pressure determination from volumetric flow measurement data. The jet was issued from a circular nozzle with an inner diameter of 𝐷 = 20 mm. A split-screen configuration including two high-speed cameras was used to capture the particle images from four different views for the tomography reconstruction of the voxels in the tomo-PIV measurement. Planar PIV was also performed to obtain the benchmark two-dimensional velocity fields for validation. The adjoint-based sequential DA scheme was used with the measurement uncertainty implanted using a threshold function to recover the flow fields with high fidelity and fewer measurement errors. Pressure was determined by either the direct mode, with implementation directly in the DA solver, or by the separate mode, which included solving the Poisson equation on the DA-recovered flow fields. Sequential DA recovered high signal-to-noise flow fields that had piecewise-smooth temporal variations due to the intermittent constraints of the observations, while only the temporal sequence of the fields at the observational instances was selected as the DA output. Errors were significantly reduced, and DA improved the divergence condition of the threedimensional flow fields. DA also enhanced the dynamical features of the vortical structures, and the pressure determined by both modes successfully captured the downstream convection signatures of the vortex rings.

Citation

He, C., Wang, P., Liu, Y., & Gan, L. (2022). Flow Enhancement of Tomographic Particle Image Velocimetry Measurements Using Sequential Data Assimilation. Physics of Fluids, 34(3), Article 035101. https://doi.org/10.1063/5.0082460

Journal Article Type Article
Acceptance Date Feb 8, 2022
Online Publication Date Mar 1, 2022
Publication Date 2022-03
Deposit Date Feb 8, 2022
Publicly Available Date Mar 29, 2024
Journal Physics of Fluids
Print ISSN 1070-6631
Electronic ISSN 1089-7666
Publisher American Institute of Physics
Peer Reviewed Peer Reviewed
Volume 34
Issue 3
Article Number 035101
DOI https://doi.org/10.1063/5.0082460

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