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. Alex