Processing of three-dimensional particle tracking velocimetry data

Liburdy, James A.; Young, Edward F.

doi:10.1016/0143-8166(92)90037-8

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…There are different approaches in imposing the continuity equation. Su et al utilized the concept of minimization of errors for the interpolation of 3D velocity data on the basis of the continuity constraint (Su and Dahm 1996;Liburdy and Young 1992). They inserted the continuity constraint into the local minimization functional of the interpolation procedure-a functional composed of several terms including the local measurements and smoothness requirement.…”

Section: Constraint Of Incompressibilitymentioning

confidence: 99%

Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

2014

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Section: Constraint Of Incompressibilitymentioning

confidence: 99%

Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

2014

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“…By integrating the previous equation and assuming a lift coefficient of 0.5, a relationship for the relative velocity can be obtained. The associated time constant, t, for this situation (1) as shown by Liburdy and Young 1 =1Iç 111…”

Section: Particle Dynamicsmentioning

confidence: 98%

<title>Experimental design considerations for pulsed holographic particle-tracking velocimetry</title>

Barker¹,

Liburdy²

1993

SPIE Proceedings

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Holographic imaging represents one method for particle imaging velocimetry, and has the advantage of tracking particles in three dimensions without the use of stereoscopic methods. Far-field holographic imaging has been applied to the study of particle sizing in sprays and other two-phase flows. There have also been attempts to use this imaging method to determine velocity fields, but there has been little systematic development of the method to understand its limitations relative to velocity dynamic range and other three-dimensional flow analysis issues.This study examines some of the advantages and disadvantages of using far-field holographic recording to study velocity fields. Several important experimental design features are discussed and resolution and inherent signal-to-noise ratio problems are presented. Seeding requirements for determining velocity scales down to the Kolmogorov range are presented based on a Poisson distribution of seed particles. The source density, a measure of the seeding density, is restricted to values much less than one to achieve adequate holographic imaging. The limitations of particle motion during exposure required 1or adequate imaging are also assessed. The seeding density is limited by the desired measurable velocity range, according to particle tracking requirements. Experimental measurements of a velocity and vorticity field are presented, and the effects of seed density, particle motion, and tracking sequence on the velocity range are included.

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“…Distributed flow measurements provide valuable information about simple and complex flows, but they are typically contaminated by measurement errors which limit their usability in practice to some extent. In order to make the flow measurements more suitable for further analysis, e.g., for model discrimination or for the assessment of derived quantities like pressure drop or wall shear stress, some sort of data post-processing is required [25].…”

Section: Introductionmentioning

confidence: 99%

Enhancement of flow measurements using fluid-dynamic constraints

Egger

Seitz

Tropea

2017

Journal of Computational Physics

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Novel experimental modalities acquire spatially resolved velocity measurements for steady state and transient flows which are of interest for engineering and biological applications. One of the drawbacks of such high resolution velocity data is their susceptibility to measurement errors. In this paper, we propose a novel filtering strategy that allows enhancement of noisy measurements to obtain reconstruction of smooth divergence free velocity and corresponding pressure fields, which together approximately comply to a prescribed flow model. The main step in our approach consists of the appropriate use of the velocity measurements in the design of a linearized flow model which can be shown to be well-posed and consistent with the true velocity and pressure fields up to measurement and modeling errors. The reconstruction procedure is formulated as a linear quadratic optimal control problem and the resulting filter has analyzable smoothing and approximation properties. We also discuss briefly the discretization of our approach by finite element methods and comment on the efficient solution of the linear optimality system by iterative solvers. The capability of the proposed method to significantly reduce data noise is demonstrated by numerical tests in which we also compare to other methods like smoothing and solenoidal filtering.

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Processing of three-dimensional particle tracking velocimetry data

Cited by 7 publications

References 18 publications

Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

<title>Experimental design considerations for pulsed holographic particle-tracking velocimetry</title>

Enhancement of flow measurements using fluid-dynamic constraints

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