Particle tracking velocimetry / Dana Dabiri and Charles Pecora.

Format:

Book

Author/Creator:

Dabiri, Dana, 1963- author.

Pecora, Charles, author.

Contributor:

Institute of Physics (Great Britain), publisher.

Series:

IOP ebooks. 2020 collection.

IOP ebooks. [2020 collection]

Language:

English

Subjects (All):

Particle tracking velocimetry.

Particle image velocimetry.

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2020]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

text file

Biography/History:

Dana Dabiri is Associate Professor at the William E. Boeing Department of Aeronautics and Astronautics at the University of Washington, in Seattle. He received his B.S. in Mechanical Engineering at the University of California, San Diego in 1985; his M.S. in Mechanical Engineering at the University of California, Berkeley in 1987; and his PhD in Aerospace Engineering at the University of California, San Diego in 1992. He was a Post-doc at Caltech from 1992-1993, and continued at Caltech as a research scientist until the end of 2001. In 2002, he joined the faculty at the William E. Boeing Department of Aeronautics and Astronautics as an Assistant Professor, and was promoted as an Associate Professor in 2009. His work pursues developing novel ways for quantitatively visualizing and revealing flow physics that otherwise could not be determined. At present, Professor Dabiri's research activities are focused on developing novel implementations of 2D and 3D digital particle tracking velocimetry (2DPTV and 3DPTV) , global wall shear stress measurements and global non-intrusive pressure and/or temperature measurements within flows with applications in bio-flows, aero-acoustics, heat transfer, combustion, and computational fluid dynamics modelling. 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 then pursued a Master's degree in Aeronautics and Astronautics at the University of Washington under the mentorship of Professor Dabiri, where he developed post-processing algorithms for particle tracking velocimetry. Since his graduation in 2019, he became a systems engineer for APiJET, a small company that integrates and analyzes real-time aircraft data to improve airline operations.

Summary:

Particle velocimetry is a non-intrusive optical measurement method whereby global velocity fields can be obtained in either two- or three-dimensions through time by inferring fluid motion through the displacement of particle tracers which seed the flow. While particle image velocimetry (PIV), which obtains each velocity vector by tracking groups of particles within an interrogation window through a cross-correlation algorithm, has thrived generously since its development, particle tracking velocimetry (PTV), which obtains each of the velocity vector by tracking individual particle, has received less attention. The goal of this book is to therefore provide a review of PTV, with a focus on methods and techniques that have been implemented towards its development and improvement, rather than on its applications.

Contents:

1. Introduction

2. Experimental set-up

2.1. Tracer particles

2.2. Illumination

2.3. Area/volume illumination optics

2.4. Camera

3. Particle image identification

3.1. Non-overlapped particles

3.2. Overlapped particles

3.3. Particle identification comparison

4. Identification of particles' spatial locations

4.1. Spatial location in 2D

4.2. Spatial localization in 3D

4.3. Optical distortions and calibration in PTV systems

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

5.8. Delaunay tessellation methods

5.9. Voronoi diagram methods

5.10. Vision-based PTV

5.11. Statistical approach

5.12. Outlier detection

6. Combined tracking and localization for 3D PTV

6.1. Shake-the-box

7. 3D-PTV comparison

8. Post-processing

8.1. Interpolation

8.2. Pressure calculation

9. Conclusions.

Notes:

"Version: 20191101"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on December 9, 2019).

Other Format:

Print version:

ISBN:

9780750322034

9780750322027

OCLC:

1130295079

Access Restriction:

Restricted for use by site license.