On Bicycles, and.... what else is there?

Moving backwards through the four copies of Bicycle Quarterly I recently received, I came across a very interesting article in the Spring 2010 edition. It addressed a topic I'd been puzzled about before: the relationship between trail and cross-wind stability. It's well established that trail contributes to bicycle stability. For example, this reference describes trail as a generally positive thing for stabiltiy: more trail = more stable. So if I'm riding in a cross-wind with deep-dish wheels, I should want a lot of trail, obviously. Yet of my two bikes, a Ritchey Breakaway (somewhat slack 72.5° head tube angle) and my Fuji SL/1 (super-slack 71° head tube angle), the Ritchey seems to do better in cross-winds. What's up with that? Everything I'd read says trail is what makes bikes move in a straight line. That should apply to cross-winds as well as to other conditions, right? Well, not quite. What trail does is cause the bike to steer when it leans.

After reading Cozy Beehive's review of a recent article, and having read editor/primary contributor Jan Heine's absolutely excellent The Competition Bicycle , I knew I had to subscribe to Bicycle Quarterly . So I jumped straight in: I ordered the past year's worth of back-issues and committed to a 2-year subscription. After having become acclimated to the usual commercial touchy-feely stuff which is the staple of most cycling publications, the analytic approach taken by Bicycle Quarterly is refreshing. Sure, any sort of analysis is going to be flawed in some way, but at least there's something with substance there to bite into. Plenty of stuff for blog posts. First I checked out the Summer 2010 copy, since this is where the article analyzed by Cozy Beehive was printed. But there's a lot more there than just the analysis of Tour de France speeds. A real gem was a translation of an article from a 1939 Vélo , by Jean Leulliot: How to Become a Bicycle Racer

Another quick one today. I shifted the distribution of results in the Mt Tam Double by assuming the slowest 35% of riders who would have completed the ride were either deterred by the time limit or failed to make the time limit. In reality, only 35 riders DNF'ed, some of them for mechanical reasons or for crashes, so the time limit wasn't necessarily an issue with all of them. But if I do make that assumption, that without a limit more slower riders would have participated, each at the long end of the Gaussian tail, then the rankings line up nicely with the Mt Hamilton Hillclimb. So the argument about the relative speed versus power of the double century versus the hillclimb does not necessarily apply: there's a viable alternate explanation for the difference in distributions.

I've been a bit busy, but I got curious about the statistical spread of the times in the recent Mount Tam Double compared to other events. The Mount Tam double isn't a race, more a ride where the goal is to finish. But it has a deadline so riders at least must make an effort to hurry to some extent. Anyway, without further delay, here's a quick plot: The result? The times are tighter in the Mt Tam Double than they are either for the 2008 Dolphin Running Club Embarcadero 10 km running race or for the 2009 Mount Hamilton Low-Key Hillclimb . A simple explanation is in both the hillclimb and in the running race speed is somewhat proportional to power. On the other hand, the double century includes time descending and riding on the flats, at times with considerable wind, in which a proportionate difference in power results in a considerably lesser difference in speed. So the result's not a surprise. Of course the cut-off time has an effect, as well. You

I did some quick analysis on the relationship between the net time and the start time in the 2010 Mt Tam Double results . Unfortunately the start times of DNF's weren't provided, so all I can work with are numbers for ride finishers. Riders were started potentially every 5 minutes. One rider, Harish Narayanaswamy, started at 6:15, 15 minutes after the official cut-off (but he still finished with daylight to spare); all others started within the official 4 am to 6 am start window. So I binned the riders by start time then did a weighted linear regression of the average net times. The result is plotted here: Not surprisingly, faster riders tended to start later. Or perhaps riders who started later tended to be faster due to less riding in pre-dawn darkness, although I suspect more of the former. Obviously it takes a special motivation to get out there for a 4 am start, foregoing the advantage of the 5 am mass-start, and a nice source of such motivation is fear of ridin

The result of unfortunate experiment today: Make sure auto-pause (bike settings) and auto-power-down (system settings) are both set. This is the default. Start riding towards ride meeting place. Hit "start/stop" to start recording data. Reach your meeting point. Wait. Chat. First the system "auto-pauses", then finally the system auto-power-downs, but you don't notice because you're chatting. Start riding again. Notice system is off, so you turn it back on, figuring everything should be okay now. Begin your critical climbing interval (which for purposes of this work we'll refer to as "OLH"), you hit "lap". The system reports a lap time and everything seems fine. Finish your critical climbing interval, you hit "lap". However, no lap data have been saved. Indeed no data at all are being saved.... RoadBikeAction photo It's a bit of a shock to get to the end of your ride only to find that you have data on

results are posted for the Mt Tam Double, and consistent with the "not a race" philosophy of the event, net time, let alone a ranking by net time, is not provided. But of course I wanted to know in the end how I ended up: I'd been told eighth when I'd checked in, but with riders starting at various times, that had been impossible to determine. So the numbers were there: a bit of Perl hacking and I reformatted them into ranking by net time. Three guys who finished before me had started sufficiently earlier that their net time was greater. Bruno and Max Mehech, each starting at 4 am dark-and-early, may well have cost themselves several places with their early start: losing the benefit of a faster pack leaving at 5 am, of the control of traffic signals out to Lucas Valley Road, and of an hour extra daylight. Randy Moschetti started at 4:15 and also finished before me but with more net time. On the other hand, Peter Burnett and Steven Smead each decided to forego

Still recovering, obviously, from Mt. Tam on Saturday, I rode yesterday to Bike Nüt to try on some Bont A-1 Shoes they'd ordered for me: undrilled to allow custom drilling of a 4-hole Speedplay pattern, with straps, not buckles, to save weight. Issue is Bont sent the rounded-sole shoes rather than the flat-soled required for Speedplay pedals. But at least I wanted to try them on before having Bont sent the proper shoes. BTW, they were 217 grams each, quite impressive, and the fit is what I'd expect for the shoes pre-heat-molding, so I'm excited about those even if a bit dissappointed the delays mean I don't have them for key rides this season. Bike Nüt is right off Fillmore Street on Filbert, only a block from Union, where the famous climb which had been featured in the late-great San Francisco Grand Prix. Despite my tired legs, I couldn't resist having a run at Dan Vigil's Strava record for the climb. This was more timely because I was on my Fuji SL/1

Mount Tamalpais Without a hint yet of the coming dawn, the lead police car led the main pack out of the Vallecito Elementary School parking lot, and we were off. The pack was considerably smaller than the 300 rider limit, but given the 10:30 pm finish deadline and the desire to minimize time spent on Marshal-Petaluma road after sunset, a large number of riders had already left. This is a sanctioned option, with riders allowed to check out at any time from 4 am to 6 am, but those starting at 5 am have the advantage police control through the traffic signals early on, not to mention the draft advantage of the pack. Soon enough we were on Lucas Valley Road, the first climb of the day. In 2005 I'd done this ride without a light, figuring I'd simply utilize the illumination of proximate riders. But that had been an uncomfortable experiment, one which led me to go out too hard on the opening climb as I put too much value staying with the lead group and the lights of the pace ve

Yesterday: Edge 500 with current firmware: Hit start Ride 195 miles (Mt Tam Double); 8th finisher Severely depleted, didn't think to hit stop, or anything other than checking in and then recovering. 2 hours later, notice Edge is on, so I shut it off. Hooked up with car pool buddy, I drive home. Go to upload ride to Strava, but no data has been stored. User error? Maybe. But obviously at the end of challenging almost-200 mile course the synapses aren't going to be firing with razor-like sharpness. User interface design 101: Never, ever delete or otherwise discard data which has been recorded without warning the user. Here's what I propose, just in case Garmin engineers are reading this (or my post on Garmin forums): Create a Trash directory under Activities When data is about to be discarded, dump it into a FIT file in the Trash folder, warning the user When a FIT file in Trash becomes a week old, check with the user if he wants to clean it up. Needless to

Someone pointed this blog post out to me. Climb by Bike Interesting experiment: the rider (Luke, who went on to finish 26th in the Tour of L'Avenir ) did L'Alpe d'Huez four times, each at close to 275 watts average power (measured with Powertap), trying different "treatments". In sequence, in the same day: Normal bike + 1.8L extra water in tires : Yes, you read that correctly: water was put in the tires. The goal was to determine the difference between the effects of rotating mass and translational mass on climbing times. Now the theory is simple enough: rotating mass makes it harder to change speed. In other words, harder to speed up, harder to slow down. Typically during a climb you speed up and slow down a lot: a bit each pedal stroke, in fact. So the magnitude of these speed changes is fractionally less with more mass in the tires relative to on the frame. But one speed increase is not canceled by an offsetting speed increase: the net speed ch

Last time I described in principle what I want to do in fitting critical power (CP) model parameters to maximal power data. Recall the idea is to derive a model which envelops the existing data: no data values should fall above the curve, but subject to that restriction, the curve should be as low as possible, touching at least two of the measured data values. The fit to the curve is most easily done using work versus time, rather than power versus time, where for each time duration work equals the product of average power over the interval and the duration of the interval. Typically units used are watts for power and seconds for time. Multiplying these gives work in joules, typically reported in units of 1000 called kilojoules (kJ). So the first step is to derive the maximal work for each interval. One point which some codes miss is that work done can never decrease with increasing time. Obviously if someone did a certain number of kilojoules in a certain time, even if he got

The critical power model is a very simple approach to estimating the amount of power one can produce in a given activity for different durations. For example in my experience it is most often applied to cycling. What I describe here I implemented in GoldenCheetah , an open source power data management program written in C++. The model's assumption is there are two components to power: an anaerobic work component: The body has a certain amount of anaerbic fuel which it can use to produce power. Spending that fuel in a short time results in more average power, spending it over more time results in less average power. For steady anaerobic power, the product of the power and the duration it can be sustained equals the anaeronic work capacity (AWC) for the given individual at the given time. aerobic power: In addition to anaerobic power, there is a certain amount of "aerobic" power which can be sustained indefinitely. Obviously this model breaks down at both short an

A lot of fuss was made in the Tour about the Berner SRAM derailleur upgrades used by Alberto Contador and Andy Schleck. By going from 11 teeth to 15 teeth on the lower rear pulley, the chain bends less upon entry and exit to the pulley while the pulley additionally turns more slowly. Each of these effects reduces drivetrain losses, and that means more of the power to the pedals goes to the road instead of to heating up the bike and air. Berner mod to a Red rear derailleur on a Team Saxo Bank SL/3 ( BikeRadar ) SRAM has evaluated this and claims the results are inconclusive. So much for experimental data: what's a model show? I spent several posts looking at a drivetrain model. I ended up with the following: P loss = (K / L) P (1 / N f + 1 / N r ) + C T 0 K (1 + N f /N r + N f [ 1 / N dt + 1 / N db ] ) + K d C N f [ 1 / N dt + 1 / N db ] / 2 where I define: P loss = power lost to drivetrain, N f = chainring teeth, N r = cog teeth, N db = bottom pu