1 Introduction

2 Experimental Set Up

3 Particle Image Identification

4 Identification of Particles' Spatial Locations

5 Particle Tracking Techniques

6 Combined Tracking and Localization For 3D PTV

7 3D PTV Comparison

8 Post-Processing

9 Conclusions

Turbulent flow affects all aspects of our lives, in nature and within our engineered society. It affects the atmosphere, the oceans, seas, rivers and therefore our natural environment. Flow visualization has been the primary technique for analyzing turbulence. As early as the 1400s, Leonardo da Vinci used fine particles to trace turbulent flows in the aortic heart valve. Despite this long pedigree, it is only since the early twentieth century that flow visualisation has been systematically and quantitatively employed in research and engineering, empowered by developments in fast photography and the laser.

In parallel with the improvement of imaging technology, numeric and computational techniques have also been developed significantly over this time. Using numerous cameras, flow tracers can now also be tracked in three dimensions, allowing for obtaining velocity fields, vorticity and strain rate fields, and pressure fields in 3D. It is among the few techniques that can measure fluid motion in almost any complexity, three-dimensionality and unsteadiness. This book provides a review of the development and improvements in both the experimental and computational aspects of particle tracking velocimetry for both academic or industrial researchers and engineers.

Dana Dabiri is an associate professor at the William E Boeing Department of Aeronautics and Astronautics at the University of Washington, in Seattle. He received a BS in mechanical engineering at the University of California, San Diego, in 1985; an MS in mechanical engineering at the University of California, Berkeley, in 1987; and a PhD in aerospace engineering at the University of California, San Diego, in 1992.

Charles Pecora studied mechanical engineering at the University of Miami, where he was introduced to fluid dynamics during a project focused on testing and optimizing a novel vertical axis wind turbine design. After graduating in 2016, he pursued a master's degree in aeronautics and astronautics at the University of Washington under the mentorship of Dabiri. Since his graduation in 2019, he became a systems engineer for APiJET.