scholarly journals QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Marc Pereyra ◽  
Armin Drusko ◽  
Franziska Krämer ◽  
Frederic Strobl ◽  
Ernst H. K. Stelzer ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Image Data ◽  
Biological Data ◽  
Cellular Migration ◽  
Data Sets ◽  
Squared Error ◽  
Image Velocimetry ◽  
2D And 3D

Abstract Background The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language—quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data. Results QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data. Conclusions The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

Particle Image Velocimetry Experiment and Computational Fluid Dynamics Simulation of Flow Around Rigid Cylinder

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Guangyao Wang ◽  
Ye Tian ◽  
Spyros A. Kinnas
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Cfd Simulation ◽  
Dynamics Simulation ◽  
Reynolds Stresses ◽  
Rigid Cylinder ◽  
Image Velocimetry

This work focuses on the study of the flow around a rigid cylinder with both particle image velocimetry (PIV) experiment and computational fluid dynamics (CFD) simulation. PIV measurements of the flow field downstream of the cylinder are first presented. The boundary conditions for CFD simulations are measured in the PIV experiment. Then the PIV flow is compared with both Reynolds-averaged Navier–Stokes (RANS) two-dimensional (2D) and large eddy simulation (LES) three-dimensional (3D) simulations performed with ANSYS fluent. The velocity vector fields and time histories of velocity are analyzed. In addition, the time-averaged velocity profiles and Reynolds stresses are analyzed. It is found that, in general, LES (3D) gives a better prediction of flow characteristics than RANS (2D).

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

2020 ◽  
Author(s):  
Daniel Inman ◽  
David Gonzalez Cuadrado ◽  
Valeria Andreoli ◽  
Jordan Fisher ◽  
Guillermo Paniagua ◽  
...  
Keyword(s):  
High Pressure ◽  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Flow Direction ◽  
Operating Conditions ◽  
Velocity Magnitude ◽  
Resultant Velocity ◽  
Image Velocimetry ◽  
Annular Cascade

Abstract Particle Image Velocimetry (PIV) is a well-established technique for determining the flow direction and velocity magnitude of complex flows. This paper presents a methodology for executing this non-intrusive measurement technique to study a scaled-up turbine vane geometry within an annular cascade at engine-relevant conditions. Custom optical tools such as laser delivery probes and imaging inserts were manufactured to mitigate the difficult optical access of the test section and perform planar PIV. With the use of a burst-mode Nd: YAG laser and Photron FASTCAM camera, the frame straddling technique is implemented to enable short time intervals for the collection of image pairs and velocity fields at 10 kHz. Furthermore, custom image processing tools were developed to optimize the contrast and intensity balance of each image pair to maximize particle number and uniformity, while removing scattering and background noise. The pre-processing strategies significantly improve the vector yield under challenging alignment, seeding, and illumination conditions. With the optical and software tools developed, planar PIV was conducted in the passage of a high-pressure stator row, at mid-span, in an annular cascade. Different Mach and Reynolds number operating conditions were achieved by modifying the temperature and mass flow. With careful spatial calibration, the resultant velocity vector fields are compared with Reynolds Averaged Navier Stokes (RANS) simulations of the vane passage with the same geometry and flow conditions. Uncertainty analysis of the experimental results is also presented and discussed, along with prospects for further improvements.

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

2020 ◽  
Author(s):  
Daniel Inman ◽  
David G. Cuadrado ◽  
Valeria Andreoli ◽  
Jordan Fisher ◽  
Guillermo Paniagua ◽  
...  
Keyword(s):  
High Pressure ◽  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Flow Direction ◽  
Operating Conditions ◽  
Velocity Magnitude ◽  
Resultant Velocity ◽  
Image Velocimetry ◽  
Annular Cascade

Abstract Particle Image Velocimetry (PIV) is a well-established technique for determining the flow direction and velocity magnitude of complex flows. This paper presents a methodology for executing this non-intrusive measurement technique to study a scaled-up turbine vane geometry within an annular cascade at engine-relevant conditions. Custom optical tools such as laser delivery probes and imaging inserts were manufactured to mitigate the difficult optical access of the test section and perform planar PIV. With the use of a burst-mode Nd: YAG laser and Photron FASTCAM camera, the frame straddling technique is implemented to enable short time intervals for the collection of image pairs and velocity fields at 10 kHz. Furthermore, custom image processing tools were developed to optimize the contrast and intensity balance of each image pair to maximize particle number and uniformity, while removing scattering and background noise. The pre-processing strategies significantly improve the vector yield under challenging alignment, seeding, and illumination conditions. With the optical and software tools developed, planar PIV was conducted in the passage of a high-pressure stator row, at mid-span, in an annular cascade. Different Mach and Reynolds number operating conditions were achieved by modifying the temperature and mass flow. With careful spatial calibration, the resultant velocity vector fields are compared with Reynolds Averaged Navier Stokes (RANS) simulations of the vane passage with the same geometry and flow conditions. Uncertainty analysis of the experimental results is also presented and discussed, along with prospects for further improvements.

scholarly journals Investigations of flow alteration of commissural misalignment of TAVR using Particle Image Velocimetry

2020 ◽  
Vol 6 (3) ◽  
pp. 159-163
Author(s):  
Finja Borowski ◽  
Jan Oldenburg ◽  
Sylvia Pfensig ◽  
Sebastian Kaule ◽  
Stefan Siewert ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Vector Fields ◽  
Particle Image ◽  
Clinical Performance ◽  
Circulation Model ◽  
Measuring Method ◽  
Flow Fields ◽  
Native Valve ◽  
Image Velocimetry

AbstractDue to the raising number of TAVR implantations (transcatheter aortic valve replacement), tests for durability and prevention of associated diseases are becoming increasingly important. Not only the anatomy but also the positioning of the TAVR is decisive for its clinical performance. A misalignment in the circumferential direction can influence the flow in the sinus and thus inhibit the blood supply of the coronary arteries and influence the thrombosis potential. Therefore, the modification of the flow field is investigated in this study. For the characterization of the flow fields the measuring method of digital particle image velocimetry is used. A hydraulic circulation model is used to generate physiological flow and pressure conditions. Additionally, an aortic root model with Sinus Valsalvae, which represents the implantation environment, was developed. A prototype of a TAVR was implanted aligned to the commissure lines of the native valve leaflets on the one hand, and misaligned by 60 degree to the commissure of the native valves on the other hand. By determining the velocity vector fields, it could be shown that implantation of the TAVR with a commissureal misalignment influences the flow around the leaflets. A comparison of the flow fields shows that different recirculation areas occur. This is also indicated by a comparison of the mean velocities in the sinus and the observed shear rates. The influence of the altered flow field on the thrombosis and hemolysis potential should be investigated in future studies.

scholarly journals BeePIV: A Method to Measure Apis Mellifera Traffic with Particle Image Velocimetry in Videos

2021 ◽  
Vol 11 (5) ◽  
pp. 2276
Author(s):  
Vladimir Kulyukin ◽  
Sarbajit Mukherjee ◽  
Angela Minichiello ◽  
Tadd Truscott
Keyword(s):  
Particle Image Velocimetry ◽  
Apis Mellifera ◽  
Vector Fields ◽  
Particle Image ◽  
Displacement Vector ◽  
Ground Truth ◽  
Raspberry Pi ◽  
Displacement Vectors ◽  
Image Velocimetry ◽  
Uniform Background

Accurate measurement of honeybee (Apis mellifera) traffic in the vicinity of the hive is critical in systems that continuously monitor honeybee colonies to detect deviations from the norm. BeePIV, the algorithm we describe and evaluate in this article, is a new significant result in our longitudinal investigation of honeybee flight and traffic in electronic beehive monitoring. BeePIV converts frames from bee traffic videos to particle motion frames with uniform background, applies particle image velocimetry to these motion frames to compute particle displacement vector fields, classifies individual displacement vectors as incoming, outgoing, and lateral, and uses the respective vector counts to measure incoming, outgoing, and lateral bee traffic. We evaluate BeePIV on twelve 30-s color videos with a total frame count of 8928 frames for which we obtained the ground truth by manually counting every full bee motion in each frame. The bee motion counts obtained from these videos with BeePIV come closer to the human bee motion counts than the bee motion counts obtained with our previous video-based bee counting methods. We use BeePIV to compute incoming and outgoing bee traffic curves for two different hives over a period of seven months and observe that these curves closely follow each other. Our observations indicate that bee traffic curves obtained by BeePIV may be used to predict colony failures. Our experiments suggest that BeePIV can be used in situ on the raspberry pi platform to process bee traffic videos.

scholarly journals MEASUREMENTS OF PARTICLE VELOCITIES AND TRAJECTORIES IN A WAVE-CURRENT MOTION USING PARTICLE IMAGE VELOCIMETRY

2011 ◽  
Vol 1 (32) ◽  
pp. 2 ◽  
Author(s):  
Motohiko Umeyama ◽  
Tetsuya Shintani ◽  
Shinya Watanabe
Keyword(s):  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Surface Displacement ◽  
Taylor Series Expansion ◽  
Finite Amplitude ◽  
Angular Frequency ◽  
Water Particle ◽  
Piv Measurement ◽  
Image Velocimetry

This article deals with some physical aspects of a water particle under surface waves, which propagate with or without a current in a constant water depth, using an imaging technique. The use of particle image velocimetry (PIV) made it possible to investigate the velocity and trajectory of each individual water particle. The velocity vector fields and its vertical distributions were estimated at several phases in one wave cycle. The theory of progressive waves based on finite-amplitude approximation was adapted to express the velocity potential, surface displacement and angular frequency. The PIV result showed suitable agreement with a solution solved to the third order by a perturbation method. In addition, the distributions of horizontal and vertical velocity components by the PIV measurement were compared with those by an EC meter. These attempts proved the ability of the PIV technique to accurately measure both temporal and spatial variations of the velocity. This technique was applied to the prediction of particle trajectory in a Eulerian scheme. In the method, the surrounding grid velocities were used to identify a Lagrangian velocity. The measured particle path was compared with the positions found theoretically by integrating the Eulerian velocity to the second order of a Taylor series expansion.

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