[SciPy-user] Use of Scipy in a students final year mechanical engineering project

Alex Liberzon alex.liberzon at gmail.com
Mon Aug 7 07:13:47 CDT 2006

I'm from mechanical engineering field myself, from the fluid
mechanical part of it and I'm working on a project that might be
useful for you to see as a 'test case'. The project is about one of
the experimental techniques in fluid mechanics, called Particle Image
Velocimetry and it is the state-of-the-art method to measure spatial
and temporal distribution of the flow velocity fields. You may find
thousands of references about the method all around the web. The 'test
case' I'm talking about is an algorithm used for analysing the images
of particles in the flow. The original project, called URAPIV
http://urapiv.wordpress.com was developed (proudly to say among the
first) in Matlab, to allow various users to test their commercial
software, to compare or to develop further different algorithms for
this digital image correlation method. Recently we decided that
Mathworks's licensing is too strict and we would like to let the users
not only open source, but also a real open source project, one they
can use without paying for 'beer'. So, we develop PyPIV, a clone of
URAPIV in Python with Scipy/Numpy. We already have one more developer
from outside the group, from Australia, a Master student for
Aeronautics, and we'd like to have more developers. You can download
both packages and demo images and start playing with it. The further
development which is necessary:
1) develop drivers and image acquisition to allow this project be
complete package, allowing open source and free educational tool for
high schools, universities, etc.
2) develop GUI in Python for easy installation, use and analysis
3) develop new algorithms, e.g. iterative, multi-resolution, window
shifting, pattern matching, optical flow, etc.
4) develop it into a new package, for strain measurements, using the
basic ability to do 2D correlation and followed by a gradients
(strain, stress) measurements of tenciles, etc.
5) develop other techniques of the similar kind, e.g. particle
tracking velocimetry in three dimensions and similar.

The list is actually very long and I'll skip the rest. If you're
interested, you can contact us offline (urapiv at gmail dot com)

Best regards and good luck with Python/Numpy/Scipy. It does not need
the justification, it's great.

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