Baker, JL and Einav, I (2021) Deep velocimetry: Extracting full velocity distributions from projected images of flowing media. Experiments in Fluids, 62 (5). ISSN 0723-4864

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Abstract

Abstract: Particle image velocimetry (PIV) is a powerful image correlation method for measuring bulk velocity fields of flowing media. It typically uses optical images, representing quasi-two-dimensional experimental slices, to measure a single velocity value at each in-plane position. However, projection-based imaging methods, such as x-ray radiography or shadowgraph imaging, encode additional out-of-plane information that regular PIV is unable to capture. Here, we introduce a new image analysis method, named deep velocimetry, that goes beyond established PIV methods and is capable of extracting full velocity distributions from projected images. The method involves solving a deconvolution inverse problem to recover the distribution at each in-plane position, and is validated using artificial data as well as controlled laboratory x-ray experiments. The additional velocity information delivered by deep velocimetry could provide new insight into a range of fluid and granular flows where out-of-plane variation is significant. Graphic abstract: [Figure not available: see fulltext.]

Item Type:	Article
Uncontrolled Keywords:	0901 Aerospace Engineering; 0913 Mechanical Engineering; 0915 Interdisciplinary Engineering; Fluids & Plasmas
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions:	Computer Science & Mathematics
Publisher:	Springer Science and Business Media LLC
SWORD Depositor:	A Symplectic
Date Deposited:	17 Oct 2022 10:49
Last Modified:	17 Oct 2022 10:49
DOI or ID number:	10.1007/s00348-021-03203-w
URI:	https://researchonline.ljmu.ac.uk/id/eprint/17852

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