Particle Tracking Velocimetry / Dana Dabiri and Charles Pecora.

Format:

Book

Author/Creator:

Dabiri, Dana, author.

Pecora, Charles, author.

Series:

IOP Ebooks Series

Language:

English

Subjects (All):

Particle image velocimetry.

Particle tracking velocimetry.

Physical Description:

1 online resource (211 pages)

Edition:

First edition.

Place of Publication:

Bristol, England : IOP Publishing Ltd, [2020]

Summary:

Particle tracking velocimetry (PTV) is one of the latest and most powerful flow visualization techniques, using numerous cameras to track flow tracers in two or three dimensions. This book provides a review of both experimental and computational aspects of PTV for academic and industrial researchers and engineers.

Contents:

Intro

Author biographies

Dana Dabiri

Charles Pecora

Chapter 1 Introduction

References

Chapter 2 Experimental set-up

2.1 Tracer particles

2.1.1 Tracers in liquid flows

2.1.2 Tracers in subsonic gas flows

2.1.3 Tracers in supersonic flows

2.2 Illumination

2.3 Area/volume illumination optics

2.4 Camera

Chapter 3 Particle image identification

3.1 Non-overlapped particles

3.1.1 Threshold binarization

3.1.2 Centroid estimation

3.1.3 Gaussian estimation

3.2 Overlapped particles

3.2.1 Threshold binarization

3.2.2 Neural network particle identification

3.2.3 Particle mask correlation

3.2.4 Optical flow feature extraction

3.2.5 Linear model inversion

3.3 Particle identification comparison

3.3.1 Non-overlapped particle identification comparison

3.3.2 Overlapped particle identification comparison

Chapter 4 Identification of particles' spatial locations

4.1 Spatial location in 2D

4.2 Spatial localization in 3D

4.2.1 Photogrammetric PTV

4.2.2 Tomographic PTV

4.2.3 Synthetic aperture PTV

4.2.4 Plenoptic imaging

4.2.5 Holographic PTV

4.3 Optical distortions and calibration in PTV systems

4.3.1 2D calibration

4.3.2 Stereoscopic calibration

4.3.3 3D calibration

Chapter 5 Particle tracking techniques

5.1 Multi-frame approach

5.2 Cross correlation

5.3 Relaxation methods

5.4 Neural networks

5.5 Velocity gradient tensor

5.6 Polar-coordinate similarity

5.7 Optimization methods

5.7.1 Deterministic annealing

5.7.2 Variational approach

5.7.3 Genetic algorithms

5.7.4 Ant colony optimization

5.7.5 Fuzzy logic PTV

5.8 Delaunay tessellation methods

5.9 Voronoi diagram methods

5.10 Vision-based PTV

5.11 Statistical approach

5.12 Outlier detection

References.

Chapter 6 Combined tracking and localization for 3D PTV

6.1 Shake-the-box

Chapter 7 3D-PTV comparison

Chapter 8 Post-processing

8.1 Interpolation

8.2 Pressure calculation

Chapter 9 Conclusions

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references.

ISBN:

0-7503-4178-5