In-Vitro Investigation of three-dimensional Carotid Artery Haemodynamics by Tomographic Particle Image Velocimetry

2009 ◽  
pp. 1665-1668
Author(s):  
N. A. Buchmann ◽  
C. H. Atkinson ◽  
M. C. Jermy ◽  
J. Soria
Keyword(s):  
Particle Image Velocimetry ◽  
Carotid Artery ◽  
Particle Image ◽  
Three Dimensional ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
In Vitro Investigation

scholarly journals Tomographic particle image velocimetry of desert locust wakes: instantaneous volumes combine to reveal hidden vortex elements and rapid wake deformation

2012 ◽  
Vol 9 (77) ◽  
pp. 3378-3386 ◽  
Author(s):  
Richard J. Bomphrey ◽  
Per Henningsson ◽  
Dirk Michaelis ◽  
David Hollis
Keyword(s):  
Particle Image Velocimetry ◽  
High Speed ◽  
Particle Image ◽  
Aerodynamic Force ◽  
Three Dimensional ◽  
Flow Fields ◽  
Diagnostic Methods ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
Spatio Temporal

Aerodynamic structures generated by animals in flight are unstable and complex. Recent progress in quantitative flow visualization has advanced our understanding of animal aerodynamics, but measurements have hitherto been limited to flow velocities at a plane through the wake. We applied an emergent, high-speed, volumetric fluid imaging technique (tomographic particle image velocimetry) to examine segments of the wake of desert locusts, capturing fully three-dimensional instantaneous flow fields. We used those flow fields to characterize the aerodynamic footprint in unprecedented detail and revealed previously unseen wake elements that would have gone undetected by two-dimensional or stereo-imaging technology. Vortex iso-surface topographies show the spatio-temporal signature of aerodynamic force generation manifest in the wake of locusts, and expose the extent to which animal wakes can deform, potentially leading to unreliable calculations of lift and thrust when using conventional diagnostic methods. We discuss implications for experimental design and analysis as volumetric flow imaging becomes more widespread.

A Simplified 3D Reconstruction Technique for Tomographic Particle Image Velocimetry

2013 ◽  
Vol 718-720 ◽  
pp. 2184-2190
Author(s):  
Bao Quan ◽  
Jiang Nan
Keyword(s):  
Particle Image Velocimetry ◽  
3D Reconstruction ◽  
Particle Image ◽  
Tomographic Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
3D Volume ◽  
Reconstruction Model

Tomographic particle image velocimetry (Tomo-PIV) is a newly developed technique for three-component three-dimensional (3C-3D) velocity measurement based on the tomographic reconstruction of a 3D volume light intensity field from multiple two-dimensional projections. A simplification of 3D tomographic reconstruction model, which reduced from a 3D volume with 2D images to a 2D slice with 1D lines, simplify this 3D reconstruction into a problem of 2D plane reconstruction by means of optical tomography, is applied in this paper . The principles and details of the tomographic algorithm are discussed, as well as the study of ART and MART reconstruction algorithm is carried out by means of computer-simulated image reconstruction procedure. The three-dimensional volume particle field is reconstructed by MART reconstruction algorithm base on the simplified 3D reconstruction model which made a high reconstruction quality Q=81.37% prove that the way of simplification by MART reconstruction is feasible, so it could be applied in reconstruction of 3D particle field in tomographic particle image velocimetry system.

Three-dimensional illumination system for tomographic particle image velocimetry

2016 ◽  
Author(s):  
Fen Zhang ◽  
Yang Song ◽  
Xiangju Qu ◽  
Yunjing Ji ◽  
Zhenhua Li ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Three Dimensional ◽  
Tomographic Particle Image Velocimetry ◽  
Illumination System ◽  
Image Velocimetry

Experimental study on dominant vortex structures in near-wall region of turbulent boundary layer based on tomographic particle image velocimetry

2019 ◽  
Vol 874 ◽  
pp. 426-454 ◽  
Author(s):  
Chengyue Wang ◽  
Qi Gao ◽  
Jinjun Wang ◽  
Biao Wang ◽  
Chong Pan
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Three Dimensional ◽  
Vortex Structures ◽  
Wall Region ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
Inclination Angles ◽  
The Difference ◽  
Near Wall

Vortex structures are very popular research objects in turbulent boundary layers (TBLs) because of their prime importance in turbulence modelling. This work performs a tomographic particle image velocimetry measurement on the near-wall region ($y<0.1\unicode[STIX]{x1D6FF}$) of TBLs at three Reynolds numbers $Re_{\unicode[STIX]{x1D70F}}=1238$, 2286 and 3081. The main attention is paid to the wall-normal evolution of the vortex geometries and topologies. The vortex is identified with swirl strength ($\unicode[STIX]{x1D706}_{ci}$), and its orientation is recognized by using the real eigenvector of the velocity gradient tensor. The vortex inclination angles in the streamwise–wall-normal plane and in the streamwise–spanwise plane as functions of wall-normal positions are investigated, which provide useful information to speculate on the three-dimensional shape of the vortex tubes in a TBL. The difference between the orientations of vorticity and swirl is discussed and their inherent relationship is revealed based on the governing equation of vorticity. Linear stochastic estimation (LSE) is further deployed to directly extract three-dimensional vortex models. The LSE velocity fields for ejection events happening at different wall-normal positions shed light on the evolution of the topologies for the vortices dominating ejection events. LSE based on a centred prograde spanwise vortex provides a typical packet model, which indicates that the population density of the packets in a TBL is large enough to leave footprints in conditionally averaged flow fields. This work should help to settle the severe debate on the existence of packet structures and also lays some foundation for the TBL model theory.

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