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25mm vs 32mm tires, unscientific testing

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25mm vs 32mm tires, unscientific testing

Old 06-04-20, 10:26 AM
  #76  
ZHVelo
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Originally Posted by wgscott
Sorry, where did I (or anyone) make such a claim?

It is completely disingenuous to attribute to me something I never said or even implied, and then get whiny about me being too invested.
I was reading comment after comment where you were pretending the data that are there are enough and people pointing out a powermeter was missing were wrong. That literally implies you think a powermeter is not needed and would not have provided significantly more insight. It is not disingenuous at all. You are just digging in. Good luck with that, I am not getting involved any further.
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Old 06-04-20, 10:36 AM
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Originally Posted by tomato coupe
That pretty much is the definition of bad science.
Sure, if your definition of "bad science" is it disagrees with your expectation bias.
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Old 06-04-20, 10:39 AM
  #78  
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Originally Posted by ZHVelo
I was reading comment after comment where you were pretending the data that are there are enough and people pointing out a powermeter was missing were wrong. That literally implies you think a powermeter is not needed and would not have provided significantly more insight. It is not disingenuous at all. You are just digging in. Good luck with that, I am not getting involved any further.
Was any bike science ever done before power meters were invented? Are wind tunnels unscientific?
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Old 06-04-20, 10:45 AM
  #79  
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Originally Posted by tomato coupe
What is the single biggest factor that determines the speed of a bicycle (on flat ground)?
Wind. It is the largest single variable and a 2mph diff will change everything.
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Old 06-04-20, 10:46 AM
  #80  
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Originally Posted by wgscott
Sure, if your definition of "bad science" is it disagrees with your expectation bias.
The "experiment" has fatal flaws, so no conclusion can be drawn from the results. That is not expectation bias.

Bad science is when you lend credence to the results of a bad experiment because they agree with another experiment. The results of a bad experiment should be ignored, regardless of whether they agree or disagree with other experiments.
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Old 06-04-20, 10:56 AM
  #81  
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Recalling my years in engineering school a million years ago, even with "accurate" equipment and testing, test results were typically nothing more than an average of values. There wasn't any "one true answer" to anything. The more data I had, the more sure I was of my results (i.e., smaller variances) and lots of data helped to spot trends and discard bad data. If the OP cares to repeat this experiment ~3 billion times, I think we'll be able to come to a reasonable conclusion w/o the power meter.
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Old 06-04-20, 11:23 AM
  #82  
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Originally Posted by Seattle Forrest
Was any bike science ever done before power meters were invented? Are wind tunnels unscientific?
1. You can't measure rolling resistance in a wind tunnel.
2. There are ways to measure rolling resistance without a power meter but they all require, at a minimum, known force.
3. I've presented data and a method here to estimate Crr (and CdA) without a power meter but with a known force.
4. There are ways to estimate Crr (but not CdA) without a power meter or even a speed sensor but with a known force.
5. Rides4Beer's ride was nice but he doesn't measure force.
6. I'm not sure what wgscott's null hypothesis is but it appears to be related to rolling resistance. He's claiming that Ride4Beer's data is "pretty close to ideal" for testing whatever his null is, although it lacks any measurement of force. He also claims that replicating the rides 10 times without measurement of force will make the experiment "more robust." I think it will make Rides4Beer more robust.

[Edited to add] Just as not every ride has to be a race, not every ride has to be an experiment. Rides4Beer had a nice ride.

Last edited by RChung; 06-04-20 at 11:35 AM.
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Old 06-04-20, 12:10 PM
  #83  
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Originally Posted by Seattle Forrest
Was any bike science ever done before power meters were invented? Are wind tunnels unscientific?
Sure there was. But i can guarantee you - a test with a sample size of n=1 would have been laughed at even then if declared "near ideal".

If you were to do this in an era without a power meter and have results which would be a little more valid and wouldnt make you the butt of jokes on peer review, you would at the very least:
- repeat the experiment multiple times to average out random error (eg, one run being slightly faster than the other)
- you would use a larger sample size
- you would perhaps control for wind by picking days with consistent weather/temperature
- you would do some runs with thicker wheels first and others with thinner wheels first
etc etc

And even then, you would lack the precision that you can get with a power meter nowadays. Going for a less precise method when a better method exists isnt really scientific either.

If you want to argue whether this level of precision is needed - that's a different story. For the purposes of getting a ballpark estimate of how different the two wheels roll, field tests can often be good enough - and this was a pretty good field test. But a near-ideal scientific test it wasnt, as some people are arguing.

Last edited by guadzilla; 06-04-20 at 12:13 PM.
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Old 06-04-20, 12:52 PM
  #84  
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Originally Posted by wgscott
Sure, if your definition of "bad science" is it disagrees with your expectation bias.
I think people are talking around each other.

If it's assumed to be suspected that small differences in tire width produce differences in paved performance so large that they're casually-obvious, then what rides4beer is doing may be an adequate demonstration otherwise.

Insofar as the experiment hopes to determine the actual magnitude (or even polarity) of the difference in performance between the two tire setups, it's woefully inadequate.
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Old 06-04-20, 02:34 PM
  #85  
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Originally Posted by RChung
1. You can't measure rolling resistance in a wind tunnel.
2. There are ways to measure rolling resistance without a power meter but they all require, at a minimum, known force.
3. I've presented data and a method here to estimate Crr (and CdA) without a power meter but with a known force.
4. There are ways to estimate Crr (but not CdA) without a power meter or even a speed sensor but with a known force.
5. Rides4Beer's ride was nice but he doesn't measure force.
6. I'm not sure what wgscott's null hypothesis is but it appears to be related to rolling resistance. He's claiming that Ride4Beer's data is "pretty close to ideal" for testing whatever his null is, although it lacks any measurement of force. He also claims that replicating the rides 10 times without measurement of force will make the experiment "more robust." I think it will make Rides4Beer more robust.

[Edited to add] Just as not every ride has to be a race, not every ride has to be an experiment. Rides4Beer had a nice ride.
Could you back into the data with a calculator like Silca's?
Attached Files
File Type: pdf
Power Calc - SILCA.pdf (160.8 KB, 11 views)
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Old 06-04-20, 02:49 PM
  #86  
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Originally Posted by HTupolev
I think people are talking around each other. If it's assumed to be suspected that small differences in tire width produce differences in paved performance so large that they're casually-obvious, then what rides4beer is doing may be an adequate demonstration otherwise. Insofar as the experiment hopes to determine the actual magnitude (or even polarity) of the difference in performance between the two tire setups, it's woefully inadequate.
​​​​​​​Why are you trying to bring people together? This is the 41, the only reason other people don't like everything I like is they're inbred!
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Old 06-04-20, 03:04 PM
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Originally Posted by Sy Reene
Could you back into the data with a calculator like Silca's?
I just saw that, and sent a note to Josh about it. He should have an altitude field in the air density section.

Calculators like this are handy for steady-state approximation if given CdA, Crr, rho, mu, slope, etc. I think I did a calculator like that back for my old bike club back in the last millenium, based on the equations in Whitt&Wilson.

The issue here is the inverse problem: given average speed (but not power, wind, air density, slope, etc.) can you derive what CdA and Crr were? Or, even more dauntingly, can you estimate *the difference in Crr between two tires* given average speed but not power, wind, air density, etc. That's a lot harder. That's sort of like asking, can you estimate the difference in black and white mortality from COVID-19 from two different measurements of population average death rates? (This turns out to be related to a real problem I'm working on right now, which is why it's on my mind).
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Old 06-04-20, 03:08 PM
  #88  
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Originally Posted by RChung
I just saw that, and sent a note to Josh about it. He should have an altitude field in the air density section.

Calculators like this are handy for steady-state approximation if given CdA, Crr, rho, mu, slope, etc. I think I did a calculator like that back for my old bike club back in the last millenium, based on the equations in Whitt&Wilson.

The issue here is the inverse problem: given average speed (but not power, wind, air density, slope, etc.) can you derive what CdA and Crr were? Or, even more dauntingly, can you estimate *the difference in Crr between two tires* given average speed but not power, wind, air density, etc. That's a lot harder. That's sort of like asking, can you estimate the difference in black and white mortality from COVID-19 from two different measurements of population average death rates? (This turns out to be related to a real problem I'm working on right now, which is why it's on my mind).
Aww.. and here I thought I was special receiving a beta preview
Yeah, that would be perhaps more interesting.. have all of the variables, including power be able to be entered in, except for just one data field (user choice), and the calculator could figure out the missing value. Eg. you could tell the temperature outside by filling everything else in.
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Old 07-02-20, 03:56 PM
  #89  
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https://www.bicyclerollingresistance...000-comparison

This guy does some good work.

And.. the 32's are fastest.
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Old 07-02-20, 05:48 PM
  #90  
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Originally Posted by RChung
I just saw that, and sent a note to Josh about it. He should have an altitude field in the air density section.

Calculators like this are handy for steady-state approximation if given CdA, Crr, rho, mu, slope, etc. I think I did a calculator like that back for my old bike club back in the last millenium, based on the equations in Whitt&Wilson.

The issue here is the inverse problem: given average speed (but not power, wind, air density, slope, etc.) can you derive what CdA and Crr were? Or, even more dauntingly, can you estimate *the difference in Crr between two tires* given average speed but not power, wind, air density, etc. That's a lot harder. That's sort of like asking, can you estimate the difference in black and white mortality from COVID-19 from two different measurements of population average death rates? (This turns out to be related to a real problem I'm working on right now, which is why it's on my mind).
Hi RChung,
seems like you're the most knowledgable guy in this thread. So let me just ask you this.

I think all these "tire rolling comparisons" are not a bit obsessive by the layman. Unless one is doing a flat and steady state TT, tire rolling resistance means VERY little in real world races. Why? And here's my question to you. Have you or your collegues tested ACCELERATION of a tire? and come away with some quantifcation of the cost of acceleration of using different tire sizes? I ask because, in a race, or even in a spirited club ride, NOBODY is cruising stead-state, people are attacking out of the saddle... and if the tires are squishy.. then the rider is losing major wattage... and losing ground... and we all know that to make up even a few lost positions will cost the rider dearly over the course of a race or ride. I, personally, have found that the larger the volume of the tire, the harder it is to accerlerate the bike to speed,.. it does me NO GOOD if I can be "efficient and comfortable" at cruising speed but lost everything when the attacks come because I cannot keep up... and once you've lost the draft.. it's game over,.. you may resume rolling steady state by all by yourself.
So, I ask, what is your take on this matter of prioritizing acceleration over steady-state rolling efficiency.
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Old 07-02-20, 06:25 PM
  #91  
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Originally Posted by Aladin
https://www.bicyclerollingresistance...000-comparison

This guy does some good work.

And.. the 32's are fastest.
The 32mm tires are only faster if you inflate them to ridiculously high pressures. At normal pressures, they are the slowest.
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Old 07-02-20, 06:32 PM
  #92  
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Originally Posted by tomato coupe
The 32mm tires are only faster if you inflate them to ridiculously high pressures. At normal pressures, they are the slowest.
Read.. that data closer. MUCH closer..........

On a junk tire I'd agree. NOT.. on quality rubber.

All junk rubber is slllllloooowwww.
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Old 07-02-20, 06:39 PM
  #93  
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Originally Posted by Aladin
Read.. that data closer. MUCH closer..........

On a junk tire I'd agree. NOT.. on quality rubber.

All junk rubber is slllllloooowwww.
The page you linked specifically compares Continental GP5000 tires at 23, 25, 28, and 32mm widths. GP5000 are hardly "junk" tires.
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Old 07-02-20, 06:44 PM
  #94  
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Originally Posted by Aladin
https://www.bicyclerollingresistance...000-comparison

This guy does some good work.

And.. the 32's are fastest.
I don’t see where he includes the impedance contribution to RR so the best I would say he does good but limited work and wouldn’t use his results to draw any conclusions across tire sizes.
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Old 07-02-20, 07:10 PM
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Originally Posted by aclinjury
And here's my question to you. Have you or your collegues tested ACCELERATION of a tire? and come away with some quantifcation of the cost of acceleration of using different tire sizes? I ask because, in a race, or even in a spirited club ride, NOBODY is cruising stead-state, people are attacking out of the saddle... and if the tires are squishy.. then the rider is losing major wattage... and losing ground... and we all know that to make up even a few lost positions will cost the rider dearly over the course of a race or ride. I, personally, have found that the larger the volume of the tire, the harder it is to accerlerate the bike to speed,.. it does me NO GOOD if I can be "efficient and comfortable" at cruising speed but lost everything when the attacks come because I cannot keep up... and once you've lost the draft.. it's game over,.. you may resume rolling steady state by all by yourself.
So, I ask, what is your take on this matter of prioritizing acceleration over steady-state rolling efficiency.
So, I've done tests at varying speeds including accelerations (and decelerations) to see how Crr varies. I haven't done 1000+ watt sprints (mostly because I'd need to get out of the saddle to do that which would change my aero drag which in turn makes the rolling resistance drag harder to nail down) but I've done seated accelerations where I went from 150 up to 450 watts over a few seconds. I haven't been able to detect a major change in rolling resistance during these seated accelerations; if there are changes they must be beneath my ability to detect. On the other hand, I can detect pretty small changes in rolling resistance from, say, 3 psi in pressure. So my sense is, if there is an acceleration effect, it's smaller than that.
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Old 07-02-20, 10:00 PM
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Originally Posted by RChung
I just saw that, and sent a note to Josh about it. He should have an altitude field in the air density section.

Calculators like this are handy for steady-state approximation if given CdA, Crr, rho, mu, slope, etc. I think I did a calculator like that back for my old bike club back in the last millenium, based on the equations in Whitt&Wilson.

The issue here is the inverse problem: given average speed (but not power, wind, air density, slope, etc.) can you derive what CdA and Crr were? Or, even more dauntingly, can you estimate *the difference in Crr between two tires* given average speed but not power, wind, air density, etc. That's a lot harder. That's sort of like asking, can you estimate the difference in black and white mortality from COVID-19 from two different measurements of population average death rates? (This turns out to be related to a real problem I'm working on right now, which is why it's on my mind).
Any info on where to read about the problem currently on your mind? I've been thinking about this problem from a very different angle than you have (ie clinical vs statistical ). While the two are no doubt related, I love reading modeling research.

Kudos.
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Old 07-03-20, 12:51 AM
  #97  
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Originally Posted by Aladin
https://www.bicyclerollingresistance...000-comparison

This guy does some good work.

And.. the 32's are fastest.
When over-inflated, yes. This is a sort of apples to oranges comparison.

A larger tire at the same pressure is a harder spring. Just try riding a 40mm tire at 80 psi; it's going to be a total boneshaker. A 23mm tire at 80 psi is going to offer a hell of a lot of cushioning (unless you are fat, in which case it will pinch flat and you should ride fatter tires).

We know overinflated tires have the least rolling resistance on a smooth drum test, but in reality on the road it doesn't quite pan out. When the tires are inflated so that they offer a similar amount of suspension, the rolling resistance evens out. What's left is tire aerodynamics, which doesn't matter that much in the pack but you're not going to see triathletes or timetrialists on 28 or 32mm rubber; 23/25 F/R mix is the norm.

If tire width was such a rolling resistance win, you wouldn't expect Continental to make their GP5000 more narrow than GP4000s at the same nominal width
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Old 07-03-20, 01:33 AM
  #98  
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Originally Posted by Branko D
A larger tire at the same pressure is a harder spring.
This is true, but with respect to surface irregularities, I wonder if it doesn't get overstated. At a given pressure, the vertical spring rate of a tire appears to change much less with respect to tire width for small deflectors than for pressing a wheel against a flat surface, at least in the static case. So the method that BRR uses to equalize tire pressure for comfort - seeing how far a tire drops against a flat surface - potentially overestimates how much lower the tire pressure needs to be in the wider tire to satisfy the suspension needs of a given use case.

It would be interesting to see real-world measurements characterizing how the suspension breakpoint on various surfaces changes with respect to tire width.
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Old 07-03-20, 09:30 AM
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Originally Posted by ridethecliche
Any info on where to read about the problem currently on your mind? I've been thinking about this problem from a very different angle than you have (ie clinical vs statistical ). While the two are no doubt related, I love reading modeling research.
Actually, at the time I wrote that a month ago, we were lacking a great deal of detail on racial and ethnic disparities in mortality reports: the initial data showed some info on age and sex, but with a long reporting lag that depended in part on whether the death occurred in a hospital setting or a nursing home or somewhere else. Since then, we've been starting to get more detailed data, which means that the modeling I was doing probably won't be necessary. Basically, we have a pretty good idea about age, sex, and race/ethnicity for all 3100 counties in the US, so we could do a Bayesian analysis to indirectly estimate differentials based on county-level compositional characteristics. We know that's too simple, but this might've been a way to identify unusual outliers, potential hotspots, and would give us a way to think about reliabilitiy of hotspots. At the same time, compositional effects aren't just a number on a spreadsheet; those compositions are the result of a long string of constraints over time, and that's always thought-provoking.


The connection to cycling is that we have large aggregative measures of speed and power and we're trying to indirectly back-out plausible values for rolling and aerodynamic resistance. The speed-power model is pretty well understood, so there are parts of that model that constrain what those plausible values are. Cycling data, no matter how lousy, are cleaner than the data I normally work with, so applying analytic methods developed for crappy data to relatively clean data turns out to work pretty well.
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Old 07-21-20, 05:29 AM
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Originally Posted by asgelle
I don’t see where he includes the impedance contribution to RR so the best I would say he does good but limited work and wouldn’t use his results to draw any conclusions across tire sizes.

Yes.. true. Yet suggest that specific test w same flavor rubber significant. I can tend to agree drum data not real world in many respects.

Any way rolling data is sliced.. from whose perspective.. the needle is going to tilt. I test rolling off a minor hill... was very surprised when the 32mm
Ultra ll's 48/60psi set up tubeless where near the S Pro Ones 25mm. Yet my test is very limited view... S Ones on long rides hot days give much higher average speeds. But IMO that is just a 'weather report'.
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