PTVlab (Particle Tracking Velocimetry - lab) is a Matlab software featuring state of the art mathematical algorithms and a Graphical User Interface (GUI) adapted from the open source project PIVlab.
This software aims at the analysis of experimental Image Velocimetry measurements using a Lagrangian frame of reference, which can offer several benefits compared to the standard Particle Image Velocimetry (PIV) technique. Several institutions have been involved in the development of PTVlab. Dr Wernher Brevis mainly developed the underlying mathematical algorithms and their implementation during his PhD studies at the University of Chile, Chile and Karlsruhe Institute of Technology, Germany (Brevis et al, 2011). Dr Brevis’s research groups at the University of Sheffield, United Kingdom, have developed new algorithms and bug fix. The adaptation of the graphical user interface of PIVlab and the development of new functionalities have been contributed by Antoine Patalano, as part of his PhD studies at the National University of Cordoba, Argentina. Our intention is to contribute with an open source, state of the art and easy to use tool for the analysis of experimental fluid mechanics images, thus we are releasing a Beta version of the software for testing. There are still several bugs that need attention but the main functionalities have been tested and validated.
Feel free to ask any questions regarding the implemented functionalities. Any feedback, including improvement, the request of new features and bugs report are especially important to keep improving the project.
This project would like to thank Dipl. Biol. William Thielicke and Prof. Dr. Eize J. Stamhuis for sharing the codes and GUI of PIVlab.
References:
Brevis W, Niño Y and Jirka GH (2011) Integrating cross-correlation and relaxation algorithms for particle tracking velocimetry. Experiments in Fluids, 50 (1), pp 135-147. ISSN 0723-4864. DOI 10.1007/s00348-010-0907-z
Antoine Patalano is a member of the Center for Water Studies and Technology (CETA) of the National University of Córdoba in Argentina.
Example:
In the video below the particle density is high for “standard” PTV analysis. The results show the performance of the algorithms, which are able to detect individual particles and calculate their associated velocity.
