Something to read :-)

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URAPIV grows and grows and grows

URAPIV – is our Matlab toolbox for PIV analysis

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Recommended reading: Notebooks of Shalizi

http://www.cscs.umich.edu/~crshalizi/notebooks/

I enjoyed the ’superstatistics’ the ‘information theory’ example and many others. There are even some regarding the turbulent problems. For example this: “Why do physicists care about power laws so much?”

whenever we see power law correlations, we assume
there must be something complex and interesting going on to produce them. (If
this sounds like the fallacy of affirming the consequent, that’s because it
is.) By a kind of transitivity, this makes power laws interesting in
themselves.

or this:

So
badly are we infatuated that there is now a huge, rapidly growing literature
devoted to “Tsallis statistics” or “non-extensive
thermodynamics”, which is a recipe for modifying normal statistical
mechanics so that it produces power law distributions; and this, so far as I
can see, is its only good feature.

and this I sign (not tenured )

I will not attempt, here, to
support that sweeping negative verdict on the work of many people who have more
credentials and experience than I do.

Enjoy.

http://www.cscs.umich.edu/~crshalizi/notebooks/information-theory.html

Imagine that someone hands you a sealed envelope, containing, say, a
telegram. You want to know what the message is, but you can’t just open it up
and read it. Instead you have to play a game with the messenger: you get to
ask yes-or-no questions about the contents of the envelope, to which he’ll
respond truthfully. Question: assuming this rather contrived and boring
exercise is repeated many times over, and you get as clever at choosing your
questions as possible, what’s the smallest number of questions needed, on
average, to get the contents of the message nailed down?

This question actually has an answer. Suppose there are only a finite
number of messages (“Yes”; “No”; “Marry me?”; “In Reno, divorce final”; “All is
known stop fly at once stop”; or just that there’s a limit on the length of the
messages, say a thousand characters). Then we can number the messages from 1
to N. Call the message we get on this trial S. Since the game is
repeated many times, it makes sense to say that there’s a probability

of getting message number i on any given
trial, i.e. Prob(S=i) =

. Now, the number of yes-no questions needed to pick out any
given message is, at most,

, taking the logarithm to base two. (If you were allowed to
ask questions with three possible answers, it’d be log to the base three.
Natural logarithms would seem to imply the idea of their being 2.718… answers
per question, but nonetheless make sense mathematically.) But one can do
better than that: if message i is more frequent than
message j (if

), it makes sense to ask whether the message is i
before considering the possibility that it’s j; you’ll save time. One
can in fact show, with a bit of algebra, that the smallest average number of
yes-no questions is

. This gives us

when all the

are equal, which makes sense:
then there are no prefered messages, and the order of asking doesn’t make any
difference. The sum is called, variously, the information, the information
content, the self-information, the entropy or the Shannon entropy of the
message, conventionally written H[S].

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Rayleigh-Benard convection and more… site of J. Pallares

J. Pallares’ research website has several very nice flow animations. Some of them are nice and some are very useful …
for example: convection in a cubic cavity

 

Just to remind you that on the right side you can find some results of our Rayleigh-Benard convection research in a cubic cavity – but with 3D flow measurements and discussion of a negative energy production >>

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Smoking for photography? or flow visualization?

Photocritic.org published an article on the way of making smoke photos. For us, it’s simply astonishing fluid mechanics – low Reynolds number, unstable, mixing, folding, stretching and all this from smoke. Please, don’t smoke

and if you look at my page – Fascinating flows you find a link to the Flickr group called Artsmoke – http://www.flickr.com/groups/artsmoke/pool/

Light forces the liquid in micro-channels

This is a cross-post from Optics.org: Light modulates electro-osmotic flow – but there is Particle Tracking Velocimetry

FE simulation

Particle tracking

Not sure why the channel is inclined to the optical view, and why
particles are just marked, not tracked. Probably it’s solved. If not,
the ETH software could readily be applied to such particle images.

Website of Multi-Media Fluid Mechanics

Archive of classical papers by G. Vallis

Look at these papers, including Coriolis, Ekman, Lord Kelvin and so on. Extremely nice to see it online and publicly available. For our students.
Thanks.

[Link]

Dr Sean Oughton has a page with “Turbulence in Art, Nature, Space, etc.”

http://www.math.waikato.ac.nz/~seano/index.html