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Showing posts from February, 2010

Dynamic pressure and barometric altimetry: simulation results

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In my last post on the subject of barometric altimetry, it was discussed that a moving altimeter may report a lower altitude than a stationary one, due to the dynamic pressure of the air piling up in front of the moving cyclist. The amount of this altitude increase is determined by a coefficient between zero and one relating the effective wind speed to the cyclist speed. Before that, I described how I'd combine a barometric altitude signal with a GPS signal to get the best of both: the short-term responsiveness and reliability of the barometric altimeter with the general accuracy of the GPS (at least when there's a signal). I'd applied this to randomly generated data , which were derived using a simple pacing model with the bike power-speed equations. The effect of dynamic pressure on measured altitude is simply derived from Bernoulli's equation : Δz = ‒½ ( k dp v )² / g, where Δz is the error in altitude, v is the speed relative to the wind, k dp is the coeffici

Powertap torque test: more wheels

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My torque test I described in my previous post indicated something was wrong: obviously the powertap was reporting substantially less torque than I was applying. So something was up. Of course, it could be one of three things: with my hub, with the rest of the drivetrain, or with my test protocol. An example of a test protocol problem would be error in determining the weight I'd loaded on the pedal, or a problem orienting the frame, or things flexing in a way which modified the actual torque applied by hanging the weight from the spindle. Lots of possibilities. So when doing experiments, you always want a "control case". It's better to compare the results of two similar experiments than to compare the result of one experiment with theory. So I borrowed a wheel, one I suspect works well, and tested that. Here's the result: It's nice having access to a second PowerTap: these things aren't cheap. You can see from the results that this one tests better i

Powertap torque test

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I've been depressed at my inability to produce the same power up Old La Honda as I used to. Times were fine, just power was off. A lot can affect times, but power is rock-solid reliable, right? So I finally tested my Powertap, using the following procedure: I filled a bucket, first part way, then later further, with water, in each case measuring the mass (actually, the weight) with my Ultimate hanging scale before and after the test, and averaging. Mass values: first fill line = 9.765 kg, filled further = 12.56 kg, further still = 13.955 kg. I hung my bike from my Park stand. I shimmed the stand so the frame measured vertical with a plumb bob which hung vertical from the top tube. I wanted the string to just brush the down tube. My bike (Ritchey Breakway) has round steel tubes so this works. For each gear combination tested: shift into gear of interest, spinning the rear wheel bring rear wheel to a stop zero torque (hold right button on PT) hang bucket from pedal while holdi

Summerson's Guide to Climbing, California Edition

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John Summerson's book, The Complete Guide to Climbing by Bike , is a wonderful reference to some of the best cycling climbs in the United States. But the US is obviously vast, and a national guide, while useful for planning trips, may be less useful than guides with a more regional focus. So he's started producing a regional series, as well. First was a book on the Southwest . This is really good, but is mostly a subset of the national guide, with a few more climbs added in. Still recommended. Far closer to home for me is the newly released California edition . Wow! What a resourse! If you ride in California, this is a must-buy. Even if you find one, just one climb here you weren't aware of, one gem of a climb to add to your "done that" list, the cost of the book is more than justified. And I can't imagine any rider not finding some inspiration here. Okay, now to some details. First, the route profiles... at first I was taken aback at the rela

Coastal Trail Runs: Rodeo Beach 18 miles: FAIL

Today was the Rodeo Beach 18 mile trail race . Unfortunately, I previewed the course map and I thought I knew where I was going. Sure, the map's crude, but that's no excuse. I have a better map I could have compared it to. Or I could have, err, read the course description . But I thought I knew the route. But after descending Coastal Trail onto Bunker Road I didn't see any ribbons, which served as course markers. Weird. I ran up the road, where I was fairly sure the course went, and still didn't see any. I scanned to the right, where there was a dirt road paralleling Bunker Road. Nobody there, and no ribbons there either. Finally I saw a ribbon ahead on the left -- cool. As I approached, though, a runner appeared almost out of nowhere. When I got there I saw he'd come off a side-trail onto Bunker Road. How did he get there? I thought back to the Coastal Trail descent and didn't recall seeing any junctions. Maybe there'd been a frontage trail

Caltrain weekend service: a proposed schedule

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SportVelo held its winter training camp Thursday through Friday. Each of the first two days, I boarded a Caltrain Limited from Sam Francisco with my bike, stopped off in either Starbucks or Peets, and easily made it well in advance of the 9:15 am start time for the training rides. Caltrain does fairly well for commuters on traditional workdays. Honestly I don't understand why so many persist in driving. Indeed, as I type this, I'm on the train back to San Francisco from my office in Palo Alto. It's the weekends that're the killer. For various reasons I wasn't able to make the weekend rides, but I would have liked to have the option. This is especially true for Sunday's "Queen Stage". Except Caltrain's earliest train on weekends leaves the City at 8:15. And not only does it leave late, it's slower than any weekday train, stopping not only at all the weekday stops, but additionally at Broadway in Burlingame and Atherton, stops which have

Weight Weenie $/gram record?

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Cervelo has announced a new special project frame, Project California , a frame much like the R3 and R3-SL except with a claimed mass at a super-impressive 700 grams in size 54. Announced price for the California (which I'll call the "R-CA"), presumably for stock sizes, is $9000 US. Damon Rinard shows the Cervelo Test Team the new Project California frame Now, 700 grams is impressive and all. But I judge mass savings based on the marginal cost of attaining them. Usually mass is confounded with functionality, but on the Cervelo R-series, with identical geometry and similar ride characteristics, I think it's safe to say the upgrade progression is mostly a weight weenie play. So I'll resist the temptation to compare it with the Guru Photon, a fully custom frame of comparable mass at half the price. Maybe the Cervelo is simply better. But comparing to the other Cervelos in the R-series, to which Thor Hoshovd himself claims the ride is similar: frame list price g

MegaMonster Enduro 2008-2010 Pacing Analysis

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Saturday was the 2010 MegaMonster Enduro , a fun 102 mile time trial which is the invention of Kevin Winterfield, with course assistance from Bill Bushnell. It really is a unique event for the greater San Francisco Bay area: ride 51 miles out on a road (Highway 25), turn around and ride back. Not that there haven't been wrong turns... Low-Key Volunteers @ the MegaMonster ( Cara Coburn ) This year we were sponsored by Hammer Nutrition , who sent us some great gel and Enduralytes and Heed. We supplemented this with an additional order of Gel and Perpeteum "liquid food". We were ready! Unfortunately in a bit of a snafu the stuff didn't make it to the checkpoints, which thus featured cookies, pretzels, and water, similar to previous versions of the MegaMonster. Since it looks like the MegaMonster will be back for 2011, I figured it would be fun to analyze how people did on the incoming versus the outgoing leg, so next year we can see the effect of Hammer Product.

Old La Honda repeats with Sport Velo

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At the first day of the SportVelo training camp, Dan Smith had us do four Old La Honda repeats. The goal was to start slow and get faster each time. I was able to accomplish half of this, anyway: I started slow. My approach was progressive gearing. 34/26, 34/23, 34/21, 34/19. I'd set my PR in July in 36/18. At the same cadence as my PR, this last gear would have gotten me to the top in 18:48. That's a typical good Noon Ride time for me, well at least it was last summer, on my Ritchey Breakaway, which has been my training bike of choice. Instead my legs were already feeling the 34/26 effort, the 34/23 felt harder, the 34/21 a struggle, and despite a caffeinated Gu to fuel my motivation, I basically collapsed on the final rep. I hate making excuses for myself, so I won't. But if I cloned myself and had to give myself advice, I'd probably tell my alternate self that the 6 running repeats up Potrero Hill I'd done 1.5 days earlier had blunted my legs. I've

Bernoulli, stagnation pressure, and barometric altimeters

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I never could wrap my head around this stuff. Bernoulli's_principle basically says that when an incompressible fluid is moving more rapidly, the pressure drops. Air is obviously included in the list of incompressible fluids, leading to all the activity at SFO not so far south of where I live. In some physics class in my distant pass, the professor justified this by launching into a set of differential equations . You stare at the equations, one after another, and sure enough it's hard to dispute any one of the steps, but that doesn't mean the result actually makes any sense . Differential equations, after all, are just a model. There's no physics in differential equations. The physics is in particles bouncing around: scattering elastically and inelastically, transferring momentum, transferring energy. Scattering, if anything, is the heart of physics. So I envision gas molecules bouncing around, energy scattering between various degrees of freedom, minding their

combining GPS and barometric altimetry: correcting the barometric data

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Okay, back to altimetry. After painstakingly constructing simulated altitude data consisting of the following: true altitude GPS altitude signal: tends to fluctuate and drop out for periods, never deviates too far from the true altitude, at least in my model barometric altitude: smoother than the GPS and never drops out, but has a slowly varying offset from the true altitude So the approach I take is to first identify points at which the GPS signal is good. At those points, I calculate a difference between the GPS and barometic altitudes. I then locally average these distances using my favorite smoothing function, cosine squared: The key is to pick the time constant. Too short a time constant, and you don't suppress the GPS fluctuations. Too long a time constant and the barometric error may change sufficiently that the correction is no longer accurate. So I picked: τ = 100 seconds. When the GPS signal drops out, I don't do the averaging to calculate the correction amplitud

DSE Runners Club Waterfront 10-miler: results comparison

I finally checked out the results of the Dolphin South End Runners Club Waterfront 10-miler I ran a week ago. In fall 2008 I'd done a 10 km race from them on a subset of the same course. Since some runners find 10 milers longer than their preference, this time they also offered a 5 km run. The runs proceeed along the Embarcadero, southward, towards AT&T Park (the San Francisco Giants home turf). The 5 km route turns around less than half-way to the stadium, the 10 km route turns within sight of the stadium, while the 10-miler continues past the stadium, crosses the bridge on 3rd, continues to hug the water on Terry Francois, then goes left, up a hill, on Illinois. Then it's back the way you came. So in addition to being longer, the 10-miler includes a hill. I figured it would be interesting to compare paces at the different distances. Here's the result, plotted semi-logarithmically. On the x-axis, the placing normalized from 0 to 1. On the y-axis, the log o

combining GPS and barometric altimetry: generating random altitude data

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I'll now describe the model I used for the various altitude signals. This is probably a bit more elaborate than it needed to be, I admit. But I like realism. First, the altitude versus time, as this was the most complicated. I started with Fourier coefficients generated using normal random magnitudes each chosen with an rms value proportional to a Lorentzian factor 1 / [1 + (s / λ)²], where λ is a reference distance of 10 km, describing the approximate length of a typical climb. This distribution is nice because it keeps enough of the high-frequency component for things to be interesting, but while allowing the low-frequency components to generate nice continuous climbs. The phase for each component was then randomized from 0 to 360 degrees. But this doesn't represent a realistic profile, since the random Fourier components yield peaks and valleys of the same shape. So I transformed the altitude using the following: z → (50 meters) ln [ 1 + exp(z / 50 meters) ], which you