Flow Visualization Software
This page includes a compilation of free fluid visualization software generated by academics in the field, including particle image velocimetry and particle tracking velocimetry.
|Software:||Qi - Quantitative Imaging (PIV and more)|
|PI:||Pavlos Vlachos (Purdue Univ.)|
|Description:||Qi is a collection of MATLAB tools for the quantitative analysis of flow field images. Our Particle Image Velocimetry (PIV) tool, prana, implements a Robust Phase Correlation kernel for PIV analysis, and now includes Particle Tracking Velocimetry and sizing tools. Tools for pressure calculation, proper orthogonal decomposition (POD), and 3d imaging are under development.|
|Software:||queen 2.0 & LCS MATLAB|
|PI:||John O. Dabiri (California Inst. of Tech.)|
|Description:||queen 2.0: This MATLAB software package takes as input one or more text files with 2D or 3D velocity field data and, optionally, files with coordinates of a solid object in the flow, and computes the corresponding pressure field. queen 2.0 eliminates the quasi-steady approximations used in version 1.0, so it can compute fully unsteady pressure due to accelerating flows, added mass/acceleration reaction in flow-structure interactions with moving and deformable bodies, etc.
LCS MATLAB: This MATLAB software package enables the user to input a time-series of velocity field data (e.g., DPIV measurements or CFD calculations) and compute the corresponding finite-time Lyapunov exponent (FTLE) fields, from which Lagrangian Coherent Structures (LCS) such as vortices and fluid transport barriers can be identified.
|Software:||Droplet Morphometry and Velocimetry (DMV)|
|PI:||Amar Basu (Wayne State Univ.)|
|Webpage:||http://ece.eng.wayne.edu/~abasu/ (go to Research > DMV)|
|Description:||When performing biochemical assays in droplets, a great deal of relevant information is encoded into a droplet's physical characteristics, such its size, shape, velocity, trajectory, and pixel intensity. Indeed, many recent reports utilize such characteristics as quantitative measurements for label-free assays. The challenge for researchers in droplet microfluidics is that much of the analysis must be done manually. DMV is a machine vision software which uses image processing techniques to identify and track droplets in digital videos, providing quantitative, time-resolved, label-free measurements. DMV tracks 20 different parameters, including size, shape, trajectory, velocity, pixel statistics, and nearest neighbor spacing. Our Lab on a Chip paper provides details on DMV and how it can be used to analyze common droplet operations and systems reported by industry and academic labs, including: droplet generators, splitting and merging devices, cell encapsulation, serial dilutions, emulsion packing, size distributions and sorting efficiency. DMV provides throughputs of 2-30 frames per second.|
|Software:||OpenPIV - open source Particle Image Velocimetry|
|Description:||OpenPIV is an initiative of scientists to develop a software, algorithms and methods for the state-of-the-art experimental tool of Particle Image Velocimetry (PIV) which are free, open source, and easy to operate. Open PIV is provided in three versions: Matlab, Python, and C++ with Qt. OpenPIV is not only the PIV image analysis software. It is a fully integrated solution from an experiment to a publication. We provide an integrated Matlab toolbox for Spatial and Temporal PIV data analysis that provides time and spatial analysis, e.g. velocity profiles, spatial correlations, FFT, contours of vorticity, etc.|
|Software:||OpenPTV - open source Particle Image Velocimetry|
OpenPTV foundation is a collaborative effort of several research groups to join in order to develop a better software for three-dimensional Lagrangian particle tracking velocimetry. OpenPTV is standing on the shoulders of giants. The origins are from the 3D-PTV software, developed for years at ETH Zurich. Since then few additional branches of the software have been developed independently by TU/e group of Turbulence and Vortex Dynamics (C++ version with Tcl/Tk and few new algorithms of general coordinate transformation) and by the Turbulence Structure Laboratory at Tel Aviv University (Python version, PyPTV).
|PI:||William Thielicke and Eize J. Stamhuis|
|Description:||Time-resolved digital particle image velocimetry tool for MATLAB.
|PI:||Frederic Moisy (Univ. Paris-Sud)|
The PIVMat Toolbox for Matlab contains a set of command-line functions to import, post-process and analyse 2- and 3-components vector fields from PIV (particle image velocimetry), stereo-PIV, DIC (digital image correlation) SS (synthetic schlieren) or BOS (background-oriented schlieren) applications. It is compatible with several data formats, including DaVis (LaVision) (FlowMaster/StrainMaster packages). The PIVMat Toolbox enables to handle and perform complex operations over large amount of velocity fields, and to produce high-quality vector/scalar outputs. This toolbox in itself does not perform any PIV computations. New: Stereo-PIV fields now supported
|PI:||Antoine Patalano (Univ. Nacional de Cordoba)
Brevis Wernher (Univ. of Sheffield)
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.
|Software:||Particle Tracking (various *.m files)|
|PI:||Nick Ouellette (Yale Univ.)
As described in our research pages, much of our work depends on constructing the trajectories of tracer particles moving in fluids from videos of their motion. While particle tracking has become a widely used research tool, not all tracking algorithms are suitable for all situations. We tend to focus on systems where the particles move deterministically, and have developed predictive tracking algorithms that take advantage of this determinism to allow even difficult tracking problems to be solved. Click on the links below to download MATLAB routines that implement this algorithm. We also have parallelized versions of the algorithm written in C++ that are much faster; contact us if you need the extra speed.
|Software:||Tracker: Video Analysis and Modeling Tool|
|PI:||Douglas Brown (Cabrillo College, retired)
Tracker is a free video analysis and modeling tool built on the Open Source Physics(OSP) Java framework. It is designed to be used in physics education.