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Friday, January 29, 2016

Problem resolved?

I think I have figured out my flaky wheel results.  I was comparing experimental data which I took using an old wheel against the model.  It was a different wheel than the wheel I had used for my main test cases.  The wheel did not seem that different so I expected things would be similar, but the results were really bizarre.  In the end, I found a couple of programming errors and I learned something about the model.   The errors were things that were perfectly obvious on inspection, but if your results look good it is hard to make yourself inspect carefully.  It takes something really strange to focus the attention on the programming and really see anything wrong.

The thing I learned about is the effect of exceeding the buckling load in the model.  Buckling limit is one of the things I wanted to be able to calculate with the model.  I know that the spokes increase the buckling load compared to the bare rim but I did not know how to calculate from the model.  I am on the track of a tidying up the theory.  Just by chance, the stiffness data (Izz, Irr, and J) and spoke tension I picked for this wheel were right on the limit for buckling.  The matrices are singular at the buckling point so the inverse of the matrix near it is unreliable.  That accounts for the flaky results.

The good news is that putting stiffness parameters from my first case (a good bit stiffer to both bending and torsion) pushes the buckling limit out to higher value.  With that set of parameters, the model gives excellent displacement results in comparison to the experiment.  In playing with the parameters, the predictions of displacement and spoke tension are very sensitive to stiffness parameters near buckling but not so sensitive away from it.  The stiffness parameters I first estimated for the second wheel are not particularly accurate.  I do think this wheel is close to the buckling limit.

I am working on getting some help to calculate stiffness parameters accurately for a given rim profile.


1 comment:

  1. Love your out-loud thinking style -- a pretty good mirror of how my own derivations and programming proceed. I am glad that I am getting to know you via email.

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