> The only "new" thing was noting the (theoretical) adverse effect of wheel > mass. >Has anyone real experience with very heavy wheels? Or tried trying 3 lb scuba >weights to their wheels? The 30lb front wheel build has gone horribly bad with multiple alignment issues, so not sure when I will get back to it. There should be other workout ideas. How about a python cargo bike, larger than the Pythoon, 200-lb capacity, with front/back load balancing? > http://www.rjs.org/recumbents/images//SWB/side.jpg Nice build, I have only managed rear suspension on my RWD. Skip the suspension if you want to go fast (light & stiff). > The problem, as Jürgen noted, is that there isn't any good correlation > between >self-stability and ride-ability. As an extreme example, a programmatic method >cannot analyze a unicycle because ride-ability is almost entirely a human >control problem, height and wheel diameter are small issues. Self-balancing unicycle (electric, gyro controlled) with rider has been demonstrated http://www.youtube.com/watch?v=tdhw-MnbbHA , so we should be able to do similar with a python . The data collected from such a setup would help us understand at least half of the python mystery (non-metaphysical). > i already mentioned the 4-bar-linkage-design to Vi ;-) > The virtual pivot idea has severe design/use issues My excuse for not pursuing 4-bar linkage is because it costs 4 pivots (4 bikes). Plus it's too remote/distant for my taste. I prefer closer integration with the machine or extension of the body, for example that training stick & handlebar integration (see attached), which has been a really good tool for training. The sticks also enable more freedom with higher seat / bigger wheels, which seems more stable / maneuverable as mentioned here before. >What is actually the seat rise effect on Vi's double pivot design compared to >the normal python? About the same, since both pivots only see have the turn? I had concerns about the reduction in seat rise but am relieved that the rear pivot only rotates at large turning angle / pedal force, not in the range where self-centering occurs, say due to road bumps. Last, after a brief disappointment with the car wheel alignment issues, I felt much better after riding the bipolar and teaching kids to ride with sticks. There may be some design work left in usability, but much to do in python adoption... Cheers, Vi ________________________________ From: "mtb@xxxxxxx" <mtb@xxxxxxx> To: python@xxxxxxxxxxxxx Sent: Mon, April 18, 2011 7:26:42 AM Subject: [python] Re: A Bicycle Can Be Self-Stable Without Gyroscopic or Caster Effects At 11:24 AM 4/17/2011, you wrote: Help me - I am trapped in a time loop ... Exactly. I've never written anything for that though... On 17.04.2011 20:04, Vi Vuong wrote: > >Hi Ray, >>Thanks for sharing the program. Is there a way to automatically grind >>through >>the 18 parameter space, and save the output? not at this point I think we need to find stable speed between 4-8mph to run along with the experimental bike. Not necessarily - unstable low speeds can easily be controlled with technique; it is also very difficult to get good low speed self-stability except in the classic safety design. It is at higher speed that this type of stability feels better, my SWB bent suffers from this, but it is also due to wiggle in the full suspension design, http://www.rjs.org/recumbents/images//SWB/side.jpg a parameter nearly impossible to model. The console output >>velo A B C D E #6 #7 >>m/k 10**8 10**9 10**9 10**9 10**10 10**20 10**26 >>suggests that when colunm #6 and #7 both go positive then we have stability, >>and >>can be used to search the parameter space. correct, that it the basis for the colored bar on the right The problem, as Jürgen noted, is that there isn't any good correlation between self-stability and ride-ability. As an extreme example, a programmatic method cannot analyze a unicycle because ride-ability is almost entirely a human control problem, height and wheel diameter are small issues. The virtual pivot idea has severe design/use issues, and a mechanical device to create -K would be extremely complicated as it must change with lean angle as well. Our legs can do it easily with practice, however. With the specific python design, the only thing I can see being of some use to the group is to use some -K in the GUI, and test each design in Jürgen's database with the other dimensional factors and seeing if there is any correlation with ride reports at all... Ray ============================================================ This is the Python Mailinglist //www.freelists.org/list/python Listmaster: Jürgen Mages jmages@xxxxxx To unsubscribe send an empty mail to python-request@xxxxxxxxxxxxx with 'unsubscribe' in the subject field. ============================================================
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