scholarly journals Deep velocimetry: Extracting full velocity distributions from projected images of flowing media

2021 ◽  
Vol 62 (5) ◽  
Author(s):  
James Lindsay Baker ◽  
Itai Einav
Keyword(s):  
Particle Image ◽  
Correlation Method ◽  
Image Correlation ◽  
Analysis Method ◽  
X Ray ◽  
Optical Images ◽  
Image Velocimetry ◽  
Out Of Plane ◽  
Velocity Information ◽  
Insight Into

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

Multi-Cross-Correlation Method in Particle Image Velocimetry

2011 ◽  
Vol 27 (3) ◽  
pp. 365-377
Author(s):  
T.-W. Hsu ◽  
C.-Y. Shin ◽  
S.-H. Ou ◽  
Y.-T. Li
Keyword(s):  
Particle Image Velocimetry ◽  
Cross Correlation ◽  
Particle Image ◽  
Processing System ◽  
Correlation Method ◽  
Seeding Density ◽  
Image Velocimetry ◽  
Accuracy Of Measurements ◽  
Out Of Plane ◽  
Particle Images

ABSTRACTA multi-cross-correlation method (MCCM) was developed in a particle image velocimetry (PIV) auto-processing system to reduce spurious vectors and improve accuracy of measurements. This technique is an improvement based on conventional cross-correlation method (CCM). Four typical neighboring interrogation windows were specified to be overlapped and calculated by MCCM. A high cross-correlation value is obtained in which many particle images match up with their corresponding spatially shifted partners, and small cross-correlation peaks due to interference of noises during experiments are reduced. Several parameters such as out-of-plane motions, particle size, and seeding density are considered for checking both MCCM and conventional PIV algorithms. The examination gives authenticity to the merits of MCCM for avoiding particles loss or mistaken velocity vectors.

Out-of-Plane Motion Effects in Microscopic Particle Image Velocimetry

2003 ◽  
Vol 125 (5) ◽  
pp. 895-901 ◽  
Author(s):  
Michael G. Olsen ◽  
Chris J. Bourdon
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Laser Sheet ◽  
Plane Motion ◽  
Entire Volume ◽  
Measurement Volume ◽  
Microscopic Particle ◽  
Image Velocimetry ◽  
Out Of Plane ◽  
Signal Peak

In microscopic particle image velocimetry (microPIV) experiments, the entire volume of a flowfield is illuminated, resulting in all of the particles in the field of view contributing to the image. Unlike in light-sheet PIV, where the depth of the measurement volume is simply the thickness of the laser sheet, in microPIV, the measurement volume depth is a function of the image forming optics of the microscope. In a flowfield with out-of-plane motion, the measurement volume (called the depth of correlation) is also a function of the magnitude of the out-of-plane motion within the measurement volume. Equations are presented describing the depth of correlation and its dependence on out-of-plane motion. The consequences of this dependence and suggestions for limiting its significance are also presented. Another result of the out-of-plane motion is that the height of the PIV signal peak in the correlation plane will decrease. Because the height of the noise peaks will not be affected by the out-of-plane motion, this could lead to erroneous velocity measurements. An equation is introduced that describes the effect of the out-of-plane motion on the signal peak height, and its implications are discussed. Finally, the derived analytical equations are compared to results calculated using synthetic PIV images, and the agreement between the two is seen to be excellent.

Using the Simplified 3D DIC Method to Measure the Deformation of 3D Surface

2011 ◽  
Vol 121-126 ◽  
pp. 3945-3949 ◽  
Author(s):  
Shih Heng Tung ◽  
Jui Chao Kuo ◽  
Ming Hsiang Shih ◽  
Wen Pei Sung
Keyword(s):  
Measurement Accuracy ◽  
Good Accuracy ◽  
Correlation Method ◽  
Image Correlation ◽  
2D Digital Image Correlation ◽  
Plate Specimen ◽  
Before And After ◽  
Out Of Plane ◽  
Plane Displacement ◽  
2D And 3D

In recent years, 2D digital image correlation method (DIC) has been widely used in the measurement of plane strain. However, out-of-plane displacement could be induced during the loading and it would affect the measurement accuracy. Thus, a 3D measurement is necessary. This study utilizes a simplified 3D DIC to measure the geometry of an object before and after deformation. Then the finite element concept is involved to determine the strain after deformation. A flat plate specimen with in-plane and out-of-plane displacement is observed. Both 2D and 3D DIC are used to analyze the strain. The results show that using 3D DIC to measure strain is feasible and with a very good accuracy.

Cinema PIV and Its Application to Impinging Vortex Systems

1999 ◽  
Vol 121 (4) ◽  
pp. 720-724 ◽  
Author(s):  
J.-C. Lin ◽  
D. Rockwell
Keyword(s):  
Particle Image ◽  
Turbulent Shear ◽  
Turbulent Shear Layer ◽  
Image Velocimetry ◽  
Framing Rate ◽  
Image Density ◽  
First Time ◽  
Vortex Systems ◽  
Insight Into ◽  
Pressure Measurement System

An integrated cinema PIV-pressure measurement system allows detailed insight into impinging vortex systems. It employs a high framing rate camera in conjunction with a scanning-laser version of high-image-density particle image velocimetry, thereby generating space-time representations of the flow. Simultaneously, instantaneous surface pressures are acquired. This approach allows the instantaneous velocity and vorticity fields to be related to the induced loading. The instantaneous structure of vortex systems arising from an initially turbulent jet impinging upon an edge and an initially turbulent shear layer past a cavity are quantitatively characterized for the first time. In addition, distinctive mechanisms of vortex-wedge and vortex-corner interactions are related to the occurrence of peak values of instantaneous surface pressure.

Self-correction method of out-of-plane motions in two-dimensional digital image correlation

2016 ◽  
Vol 232 (9) ◽  
pp. 1672-1676 ◽  
Author(s):  
Wentao Yan ◽  
Feng Lin
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Correlation Method ◽  
Correction Method ◽  
Image Correlation ◽  
Two Dimensional ◽  
Monitoring Method ◽  
Strain Monitoring ◽  
Out Of Plane ◽  
Relationship Of

Strain monitoring is very important in the manufacturing, assembling, installation and servicing processes in both mechanical and civil engineering fields. Two-dimensional digital image correlation is a simple, efficient strain monitoring method, but one major bottleneck is the unacceptable error due to the unavoidable out-of-plane motions of the object in practice. We propose a “self-correction” method: employing the originally extracted strain values in different directions to correct the errors due to out-of-plane motions. It is applicable to many engineering applications with known relationship of strains in different directions. A uniaxial tension test was conducted to demonstrate the effectiveness and practicality of this self-correction method. Compared with other correction methods, this method is not only simpler but also more efficient in correcting errors due to the lens distortion caused by self-heating. Both the experiment and theoretical analyses demonstrate that this self-correction method maintains the high accuracy of the digital image correlation method.

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